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1. Figure 3 30 General Parameters In the Technology for Slash Firewood and Technology for Industrial Firewood tabs the users needs to set up the efficiency heating value and GHG emission factors of the fuel amp technology to be substituted in general a fossil fuel based technology but could also be an old biomass system to be replaced for the purposes of carbon mitigation and for the alternative fuel amp technology Figure 3 31 In this case the user can either enter the values one by one using their own data sources or rather choose a default fuel technology from a built in database Figures 3 32 and 3 33 by using the Select button in each fuel technology section These values are loaded from a text file called bioenergy_data txt which can be edited using a text editor Alterra rapport 1068 doc 61 Bioenergy Parameters za aora Improved Cookstove Figure 3 31 Technology tor Slash Firewood 62 Alterra rapport 1068 doc Fuel amp Technology to be substituted Figure 3 33 Selecting alternative fuel amp technology All the parameters associated to the Technology for Slash Firewood and Technology for Industrial Firewood can be set up on a scenario basis just like other modules 3 7 4 Parameters validation When the total emissions from the chosen alternative technology are higher than those from the substituted technology the result will be negative carbon mitigation In such
2. Cancel Apply Help Figure 3 13 General Parameters screen in main menu General Parameters with in this case management mortality as a function of the total volume harvested If management related mortality is depending on the volume harvested per cohort the annual mortality in the whole stand all cohorts equally that is caused by logging in the cohort chosen in the top of the window should be quantified The mortality is parameterised as an annual fraction of the standing biomass and for a certain impact time If management mortality is dependent on the total volume harvested the cohort box is not visible and mortality will be applied irrespective of the cohort harvested 46 Alterra rapport 1068 doc Stems Foliage Branches Roots Mortality Competition Management mortality Thinning Harvest Scenario Scenario 1 y MANAGEMENT MORTALITY Volume m3 Starting mort Impact time yr Figure 3 14 Parameterisation of management mortality where management mortality is only dependent on the total volume harvested 3 4 6 Interaction between cohorts competition Tree growth is affected by interactions with neighbouring trees Interaction effects can range from decreased growth competition via no effect to increased growth synergic effects The most important type of interaction is competition For a cohort the interaction can be caused by other individuals in the same cohort or by individuals of
3. in Mg gas Mg fuel The equivalent emission of fossil fuels or the technology to be replaced is calculated according to E FI EC EC n n Mg gas yt 27 Alterra rapport 1068 doc 29 where EC is energy content of the alternative bioenergy fuel EC is energy content of the fuel to be substituted Na is energy efficiency of the alternative technology UN is energy efficiency of the technology to be substituted is emission factor of the fuel technology to be substituted for each GHG In order to get the compound effect of all greenhouse gases emissions of each gas have to be weighed by their respective global warming potential Therefore the total mitigation of GHG emissions will be TOTGHGmit GHGmit GWP in Mg C equiv 28 where GHGmit is the mitigation associated to each GHG 4 and GWP is the global warming potential of each GHG In the CO2FIX model CO emissions from bioenergy technologies should always be kept at zero The reason for this is that in case of a sustainable harvesting cycle net emissions are zero In case of a non sustainable harvest not followed by re growth the net emissions will show up as a reduction of carbon stocks at the forest level The substitution of fossil fuels by biomass leads to a permanent GHG mitigation Therefore we can regard the cumulative mitigated GHG as an increasing carbon stock in the forests 2 6 Forest financial module Financial
4. 1 2 S S 1 he 08 Foliage 2 06 Branch g Roots o 0 4 2 w 0 2 c 0 5 30 50 70 100 Age years Figure 3 8 Example of the growth of biomass of foliage branches and roots relative to stem biomass growth biomass allocation coefficient as a function of age Turnover is the annual rate of mortality of the biomass component in question foliage branches roots A turnover rate of 0 3 means that 30 of the total biomass of the component is converted to litter every year The stems compartment has no separate turnover rate Turnover of stems is parameterised by the mortality process see next section For each of the three compartments Foliage Branches and Roots a separate tab is present in the Biomass menu For each cohort in each scenario the allocation to these compartments needs to be given relative to the stems dry matter growth rate Figure 3 9 gives an example for the Branches compartment with the growth rate depending on age Again data entered in the table will be visualised in the graph The curve in Figure 3 9 has a typical shape Very often in young trees most of the NPP is allocated to foliage branches and roots When the annual volume increment increases the relative allocation to other compartments decreases When the trees mature and the annual increment decreases relative allocation to other compartments increases again in order to keep the absolute production of for instance foliage constant Toget
5. Climatic change can have several impacts on the forest via different mechanisms such as higher increments due to CO fertilisation higher temperatures and a longer growing season and lower increments due to decreased precipitation and increased evapotranspiration Also the soil compartment may be affected by changes in temperature and water availability In CO2FIX the resulting changes can be simulated but not its underlying processes In our example climatic change co2 we show how climatic change could affect the Finnish Scots pine case The process based model FINNFOR was applied to a Scots pine stand in Southern Finland Kramer and Mohren 2001 for current climate and climate change conditions The ratio between increment under current climate and climate change per age class is used in CO2FIX to express the effect of a changing climate on the increment Figure 5 9 We assumed that allocation and turnover patterns are not affected Changes in temperature precipitation and potential evapotranspiration were derived from the GCM runs that were used as input for the FINNFOR model rn gt E AA Increment m ha yr Current climate M Climate change 0 20 40 60 80 100 120 Age year o Figure 5 9 Increment under current climate and under climatic change in the CO2FIX example for Scots pine in Southern Finland Kramer and Mobren 2001 94 Alterra ra
6. Koivisto 1959 and dry wood density values were derived from the CO2FIX V 2 0 manual Nabuurs et al 2002 0 490 for Scots pine and 0 440 for Norway spruce Carbon content was assumed to be 50 for all biomass The growth of other biomass compartments i e foliage branches and roots needs to be parameterised as relative to growth of the stem We determined these relative growth values by first calculating the biomass of each compartment on the basis of biomass equations Marklund 1988 and yield tables Koivisto 1959 then calculating the periodic growth and comparing that to the periodic growth of the stem Turnover rates of different biomass compartments are needed in model to calculate the litter production We derived these turnover coefficients for foliage 0 25 for Scots pine and 0 16 for Norway spruce from Kellomaki et al 1992 and for branches 0 027 for both tree species and roots 0 027 for both tree species from Liski et al 2002 Thinning regimes were taken from national guidelines for forest management Metsatalouden kehitt miskeskus Tapio 2001 and no natural mortality competition or management mortality was assumed in these examples 4 3 3 Soil parameters General parameters for conifers were used in the soil module Liski et al 2003b Karjalainen et al 2002 Climate data precipitation during the growing season mm and potential evapotranspiration during the growing season mm were derived from a global climate
7. 2003 Decisi n 19 CP 9 Modalities and procedures for afforestation and reforestation project activities under the clean development mechanism in the first commitment period of the Kyoto Protocol http unfecc int FCCC CP 2003 6 Add 2 DTF CINSJP 1998 Plan de Manejo Forestal 1998 2007 Direcci n T cnica Forestal Comunidad Ind gena de Nuevo San Juan Parangaricutiro Unpubl Doc Eggers T 2002 The Impacts of Manufacturing and Utilisation of Wood Products on the European Carbon Budget European Forest Institute Internal Report 9 ENCOFOR 2004 Should one trade tCERs or ICERs http www joanneum at encofor publication propublications html Fassbender H W 1993 Modelos edafol gicos de sistemas agroforestales CATIE Serie de Materiales de Ense anza No 29 471 p Finnish Forest Research Institute FFRI 2002 The Finnish Statistical Yearbook of Forestry 2001 Helsinki Finland 98 Alterra rapport 1068 doc Gabus A 2003 L Economie mondiale face au climat Collection Economie et Innovation L Harmattan Paris 276 p Gill R A Jackson R B 2000 Global patterns of root turnover for terrestrial ecosystems New Phytol 147 13 31 Groen T A G J Nabuurs in prep Carbon Accounting and Cost Estimation in Forestry Projects using CO2FIX V 3 1 Submitted to Climatic Change Hakkila P amp Fredriksson T 1996 Metsamme bioenergian l hteen Forests as a source of bioenergy Mets ntutkimuslaitoksen ti
8. Carbon is released to the atmosphere through decomposition at the millsite dump at the landfill or via the bioenergy module This module is based on a model developed and used before by Karjalainen et al 1994 for modelling the carbon budget for the Finnish forest sector A more detailed version has been applied for the European forest sector Karjalainen et al 2002 Eggers 2002 Two default parameters sets are delivered with the model a set with high processing and recycling efficiency and a set with low processing and recycling efficiency All parameters concerning the products module can be found under the Products main menu New is the option Exclude products in General Parameters see Figure 3 25 This option should be used when simulating real world carbon crediting projects since products are to be excluded according to the Marrakech accords General Parameters x Comments Scenario General Parameters Cohorts Simulation length yr 200 Maximum biomass in the stand Mg ha 400 M Growth as a function of r Competition relative to Age The total biomass in the stand Above ground biomass Each cohort r Management mortality Depends on which cohort is harvested PRA on the total volume harvest M Optional modules I Exclude Products Figure 3 25 General Parameters screen in main menu General Parameters with the options to exclude the products module a
9. landfill 145 years long term products 30 years medium term products 15 years ERRER short term products 1 year mill site dump 5 years Figure 2 4 Discarding curves of carbon in end use products mill site dump and landfill for their default half lives When end products are discarded they can be recycled deposited in a landfill or they can be used for bioenergy The latter is taken care of in the bioenergy module A product can only be recycled to the same life span category or lower From the landfill and the mill site dump carbon is released directly to the atmosphere Two default parameter sets are delivered with the model a set with high processing and recycling efficiency and a set with low processing and recycling efficiency Their values are included in Annex 5 Alterra rapport 1068 doc 27 2 5 Bioenergy module 2 5 1 Background Bioenergy is energy derived from biomass Biomass may be produced from the so called energy crops such as sugarcane or forests or as a byproduct of forestry sawmilling and agriculture Biomass can be utilized directly for heat energy or can be converted into gas electricity or liquid fuels Energy production from fossil fuels has very different implications than energy production from biomass regarding CO emissions Burning fossil fuels releases CO that has been locked up for millions of years By contrast burning biomass simply returns t
10. 1068 doc logging is carried out but 4 follow up thinnings of 15 of standing biomass follow until the year 200 The beech cohort is also thinned at year 140 with 20 and at year 200 with 30 Products ate excluded from the carbon calculations Because it is a regular forest management project no baseline is needed Previous land use was assumed to be Norway spruce as well thus the soil was initialised with 90 Mg C ha of which 10 Mg C coarse woody litter from logging slash For soil weather data site Freiburg was used from http www worldclimate com 4 6 Reduced impact logging RIL The file Central America CDM_RIL co2 contains a CDM case for a lowland wet tropical rainforest in Central America The baseline situation is conventional heavy logging followed by further degradation This type of management is not eligible under the CDM yet but may be accepted in the future Four cohorts are distinguished 1 Traditionally commercial species 2 Potentially commercial species 3 Other species 4 Pioneers Cohorts 1 2 and 3 used to be harvested at a 20 year cutting cycle Growth in this forest is not specified in relation to age but in relation to standing biomass Masera et al 2003 Competition is important and has a profound impact on the pioneer species in the forest Masera et al 2003 On average a higher roadside price for wood from the RIL project can be expected 200 vs 160 m3 because less wood is damaged However in case
11. August 2004 Liski J Nissinen A Erhard M amp Taskinen O 2003b Climatic effects on litter decomposition from arctic tundra to tropical rainforest Global Change Biology 9 575 584 Liski J Perruchoud D Karjalainen T 2002 Increasing carbon stocks in the forest soils of western Europe Forest Ecology and Management 169 163 179 Marklund L G 1988 Biomassafunktioner f r tall gran och bj rk I Sverige Sveriges lantbruksuniversitetet Rappoter Skog 45 1 73 Masera O R Garza Caligaris J F Kanninen M Karjalainen T Liski J Nabuurs G J Pussinen A de Jong B H J Mohren G M J 2003 Modeling carbon sequestration in afforestation agroforestry and forest management projects the CO2FIX V 2 approach Ecological Modelling 164 2 3 177 199 McClaugherty C A Pastor J Aber J D and Melillo J M 1985 Forest litter decomposition in relation to soil nitrogen dynamics and litter quality Ecology 66 266 275 Mets talouden kehitt miskeskus Tapio 2001 Hyv n mets nhoidon suositukset 95 p Mohren G M J and C G M Klein Goldewijk 1990 CO2FIX A dynamic model of the CO2 fixation in forest stands De Dorschkamp Research Institute for Forestry and Urban Ecology Report no 624 35 Mohten G M J Garza Caligaris J F Masera O Kanninen M Karjalainen T Pussinen A and Nabuurs G J 1999 CO2FIX For Windows a dynamic model of the CO fixation in forests Version 1 2 IBN Rese
12. IPCC Special Report Land Use Land Use Change and Forestry Cambridge University Press New York pp 53 126 Palosuo T Liski J Trofymow J A and Titus B In prep Testing the soil carbon model Yasso against litterbag data from the Canadian Intersite Decomposition Experiment Manuscript submitted to Biogeochemistry Parton W J Scurlock J M O Ojima D S Schimel D S Hall D O 1995 Impact of climate change on grassland production and soil carbon worldwide Global Change Biology 1 13 22 Paul K L Polglase P J amp Richards G P 2003 Predicted change in soil carbon following afforestation or reforestation and analysis of controlling factors by linking a C account model CAMFor to models of forest growth 3PG litter decomposition GENDEC and soil C turnover RothC Forest Ecology and Management 177 485 501 Philips P D amp Gardingen P R van 2000 Ecological Species Grouping for Forest Management in East Kalimantan Pinard M A amp Putz F E 1996 Retaining forest biomass by reducing logging damage Biotropica 28 3 278 295 Pinard M and Putz F 1997 Monitoring carbon sequestration benefits associated with a reduced impact logging in Malaysia Mitigat Adapt Strategies Global Change 2 pp 203 215 Puolakka P 2003 Profitability of teak in Costa Rica MSc Thesis University of Helsinki 78 pp 102 Alterra rapport 1068 doc Rasse D P B Longdoz et al 2001 TRAP a modell
13. aboveground biomass and products is concerned this method will work well However if a thinning is carried out in CO2FIX the root compartment will loose the same fraction of roots as the fraction of trees that is removed So in this case all roots will die when all aboveground biomass is harvested while in reality the root system will stay alive In the model this causes extra input to the litter with repercussions on the simulated carbon stocks in the soil A way to solve this problem is to make separate simulations one for the aboveground biomass and products as described above and separate ones for each rotation to simulate the belowground catbon and soil dynamics The starting point for the simulation is the aboveground run At the moment of harvest the user can check the carbon amounts in the roots and all soil compartments These amounts are then entered into a new simulation see scenario below and soil 1 so the root system is in place but there is no initial aboveground biomass The allocation pattern to the roots probably needs to be adjusted because the root system is still intact The annual increment for the second rotation may have to be adjusted as well since the increment in the second rotation is often higher At each harvest the amounts of carbon in roots and soil should be used as initial values for a new simulation Combined with the aboveground and products simulation from the first simulation this will yield a full c
14. be defined for each cohort separately A thinning is described by the following parameters 50 Alterra rapport 1068 doc a Age at which the intervention takes place b Intensity of the intervention fraction of cohort biomass removed c Allocation of the biomass removed to different raw material classes as slash logwood and pulpwood A final felling can be simulated in the model by a thinning where 100 of the biomass is removed In case of a management intervention all biomass compartments are reduced according to the specified intensity Stemwood and branches can be allocated to logwood pulpwood or slash Foliage is always regarded as slash and roots are always regarded as litter It is possible to re allocate the slash partly or totally to the firewood raw material class to simulate fuelwood collection See also the products module description for more information Parameters concerning the management can be found in the Biomass main menu tab Thinning Harvest Figure 3 19 For each thinning to be carried out in the cohort chosen in the top of the window a tow should be inserted in the table At each row the age should be inserted first column and the fraction of trees biomass to be removed Furthermore the initial allocation of harvested stems and branches over logwood pulpwood and slash should be defined The column 5 ash is always updated automatically grey fields where Slash 1 logwood pulpwood Foliag
15. carbon sequestration estimates in a tropical and temperate forest Koivisto P 1959 Growth and yield tables Communications Instituti Forestalis Fenniae 51 1 44 Finnish Forest Research Insitute Helsinki Finland compilation of Norway spruce Scots pine white birch and common birch treated in different ways Kramer K and G M J Mohren 2001 Long term effects of climate change on carbon budgets of forests in Europe Wageningen Alterra Alterra report 194 Lettens S Muys B Ceulemans R Moons E Garcia J Coppin P 2003 Energy budget and greenhouse gas balance evaluation of sustainable coppice systems for electricity production Biomass amp Bioenergy 24 179 197 Liski J Ilvesniemi H M kel A and Starr M 1998 Model analysis of the effects of soil age fires and harvesting on the carbon storage of boreal forest soils Eur J Soil Sci 49 407 416 Liski J Ilvesniemi H M kel A and Westman C J 1999 CO2 emissions from soil in response to climatic warming are overestimated the decomposition of old soil organic matter is tolerant of temperature Ambio 28 171 174 100 Alterra rapport 1068 doc Liski J Nissinen A Erhard M and Taskinen O 2003a Climatic effects on litter decomposition from arctic tundra to tropical rainforest Global Chance Biology 9 1 10 Liski J Palosuo T Peltoniemi M amp Sievanen R In prep Carbon and decomposition model Yasso for forest soils Submitted
16. dataset www worldclimate com using the climate data of Tampere Finland Degree days above zero C were calculated from the mean monthly 78 Alterra rapport 1068 doc temperatures using the method described by Liski et al 2003b Initial soil carbon stocks were calculated and added to the soil module on the basis of preparatoty simulations which were done to determine the mean annual carbon input to forest soil with each rotation length 4 3 4 Wood product parameters Harvested wood is divided into logwood pulpwood and harvest residues We assumed that there is no logwood before the mean diameter exceeds 20 cm in the yield table and if harvested roundwood has not yet met the requirements for logwood 85 of the harvested wood goes to pulpwood and the rest to the soil as harvest residues When the mean diameter has exceeded 20 cm 30 of the harvested roundwood is allocated to logwood 60 to pulpwood and the rest to soil as harvest residues in thinnings and in final fellings 60 is allocated to logwood and 30 to pulpwood Product module parameters were defined separately for each tree species by slightly modifying the figures given in Karjalainen et al 1994 Because of the large uncertainties related to landfill it was excluded from our examinations 4 3 5 Bioenergy parameters Input sources of fuelwood are harvest residues from the biomass module and raw material and process losses from products module In our simulations
17. estimate of discounted costs and benefits made per carbon credit earned Furthermore a wider variety of example cases is released with V 3 1 including non forested ecosystems Chapter 2 describes the concepts of the model How to download and operate V 3 1 can be found in Chapter 3 Chapter 4 contains a description of the examples that are delivered with the model Chapter 5 shows how to parameterise some special cases such as disturbances and coppice systems Chapter 6 discusses some aspects on accuracy of the model For a quick start a separate manual is delivered with the model as pdf file based on the Chapters 2 3 and 4 from this description Since Chapter 3 is basically written for the manual some overlap exists between Chapter 2 and 3 mainly in the modelling principles Within the CAFOR II project a new model will be developed that interacts with CO2FIX V 3 1 to be able to simulate whole landscapes instead of forest stands only This model version called CO2Land is to be released in end of 2004 and will be available via the project website 14 Alterra rapport 1068 doc 2 Conceptual description 2 1 Model structure The CO2FIX V 3 1 is an ecosystem level simulation model that quantifies the C stocks and fluxes in the forest using the so called full carbon accounting approach i e calculating changes in carbon stocks in all carbon pools over time Noble et al 2000 It has been programmed in C using an object oriented programmi
18. forest 4 11 4 Secondary forest 5 Special parameterisations 5 1 Introduction 5 2 Non forest systems 5 3 Coppice 5 4 Fire 5 5 Storm damage 5 6 Pests and diseases 5 7 Climatic change 6 Accuracy of the carbon balances as simulated by CO2FIX V 3 1 References Annexes Overview of units and conversions Acronyms FAQs Troubleshooting Default parameters for products module Default parameters bioenergy module Kyoto decision tree NAO BWN PR 83 83 83 84 84 85 85 87 88 91 92 94 95 97 105 107 109 113 115 117 119 Summary The CO2FIX stand level simulation model is a tool which quantifies the C stocks and fluxes in the forest biomass the soil organic matter and the wood products chain The model calculates the carbon balance with a time step of one year Basic input is stem volume growth and allocation pattern to the other tree compartments foliage branches and roots Carbon stocks in living biomass are calculated as the balance between growth on the one hand and turnover mortality and harvest on the other hand Litter from turnover and mortality processes and logging slash form the input for the soil module The organic matter decomposes and transforms into soil organic matter The harvested stemwood is tracked through processing lines via product classes with different lifespans to its final fate decomposition in landfills or dumps or used as a source for bioenergy The bioenergy module calculates the
19. grassland systems are the high turnover rates in foliage and roots in this case set at 0 8 and 0 9 respectively To avoid a large build up of biomass in the stem a high mortality rate 0 9 is parameterised as well If the grassland is managed harvest can be inserted as well However the user should be careful here An annual harvest of 60 means that 60 of the stem biomass is removed but foliage will be regarded as slash Therefore the Slash Fire Wood box should be set at 1 to indicate that all slash is removed This is shown in the scenario Grassland managed As a guideline Table 5 1 shows some production estimates of grassland and pasture systems around the world Alterra rapport 1068 doc 85 xi Stems Foliage Branches Roots Mortality Competition Management mortality Thinning Harvest Scenario grass gt Cohort re CAI m3fhajyr a 01 STBuiS GROWTH TABLE 0012 001 0 0 0 00 a 0 oo 10 xi Stems Foliage Branches Roots Mortality Competition Management mortality Thinning Harvest Carbon content MaC MagDM a7 Wood density MgDM m3 fi Initial carbon MgC ha fo 01 FOLIAGE GROWTH TABLE Initial carbon MgC ha Growth correction factor Tumover rate 1 yr E i o 19 o RELATIVE TO STEM GROWTH Figure 5 1 Suggested parameterisation for grassland showing the stem and foliage compartment Roots compartment is similar to foliage 86 A
20. growth 3 4 3 Biomass growth and turnover of foliage branches and roots 3 4 4 Mortality 3 4 5 Management related mortality 3 4 6 Interaction between cohorts competition 3 4 7 Management interventions harvesting 3 5 Soil module 3 5 1 Applicability 3 5 2 Structure 3 6 Products module 3 6 1 General 3 6 2 Production line 3 6 3 End products 3 6 4 Life span for products in use and recycling 3 6 5 Default parameters 3 7 Bioenergy module 3 7 1 General 3 7 2 Input sources 3 7 3 Parameters dialog 3 7 4 Parameters validation 3 7 5 Enabling disabling the Bioenergy Module 3 8 Forest financial module 3 9 Carbon accounting module 3 10 Output Example parameterisations 4 1 Introduction 4 2 Scots pine monocultures in The Netherlands 4 2 1 General 4 2 2 Biomass 4 2 3 Soil 4 2 4 Products 4 2 5 Financial module 4 3 Managed Scots pine and Norway spruce stands in Southern Finland 4 3 1 General 4 3 2 Biomass parameters 4 3 3 Soil parameters 4 3 4 Wood product parameters 4 3 5 Bioenergy parameters 4 3 6 Finance parameters 4 4 Afforestation in Romania 4 5 Forest Management in Central Europe 4 6 Reduced impact logging RIL 4 7 Afforestation under the Clean Development Mechanism CDM afforestation 4 8 Pine Oak Central Mexico 4 9 Teak plantation Costa Rica 4 10 Agroforestry Costa Rica 81 82 82 82 4 11 Lowland dipterocarp forests at Kalimantan Indonesia 4 11 1 General 4 11 2 Protected primary forest 4 11 3 Logged primary
21. is a constant to convert volume yields into dry biomass basic wood density in Mg dry biomass per m of fresh stemwood volume for each cohort 1 Ys is the volume yield of stem wood for each cohort 4 m ha yr Es is the biomass allocation coefficient of each living biomass component p foliage branches and roots relative to stems for each cohort i at time t Mg per Mg stemwood and Mg is the growth modifier due to interactions among and within cohorts dimensionless The model provides two alternative ways to define stem growth of each cohort a as function of tree or stand age conventional yield tables and b as a function of the cohort total and maximum aboveground biomass The latter input option has been added because in tropical forests often diameter dependent instead of age dependent growth of trees is used In order to be able to model the carbon stored and accumulated in multi cohort stands CO2FIX modifies the growth of each cohort due to tree interactions This is because tree growth in a cohort is influenced by the presence of other trees Alterra rapport 1068 doc 17 Interaction effects can range from decreased growth competition via no effect to increased growth synergic effects The major type of interaction is competition For a cohort the interaction can be caused by other individuals in the same cohort or by individuals of other cohorts There are various ways of modeling com
22. maximum parameter values for the amount of primary product and process losses in different standard production system for high processing efficiency PRODUCTION LOSSES DURING MANUFACTURING To Sawn wood To Boards To Paper To Fitewood To Mill site dump Production Default Min default Min default Min default Min default Min Line max max max max max Sawnwood 0 4 0 2 0 6 0 1 0 0 3 0 3 0 1 0 5 0 2 0 0 3 0 0 0 6 Boards 0 0 0 0 6 0 4 0 9 0 3 0 0 5 0 1 0 0 0 6 0 0 0 6 Paper 0 0 0 0 1 0 0 2 0 6 0 3 0 9 0 3 0 0 4 0 0 0 4 Firewood 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 Table 4 Default minimum and maximum parameter values for the amount of primary product and process losses in different standard production system for low processing efficiency PRODUCTION LOSSES DURING MANUFACTURING To Sawn wood To Boards To Paper To Fitewood To Mill site dump Production default Min default Min default Min default Min default Min max Line max max max max Sawnwood 0 3 0 2 0 5 0 0 0 0 0 0 0 0 0 0 7 0 0 9 Boards 0 0 0 0 3 0 1 0 8 0 0 0 0 1 0 0 7 0 6 0 0 7 Paper 0 0 0 0 0 0 25 0 2 0 5 0 25 0 0 8 0 5 0 0 8 Firewood 0 0 0 0 0 0 0 0 0 0 9 0 5 1 0 0 0 0 Alterra rapport 1068 doc 115 Table 5 Default minimum and maximum parameter values for allocation of products to lifespan categories Fraction allocated to Long term Medium term Short term Product Default Min Default Min Default Min max max max Sawnwood 0 5 0 3 0 8 0 25 0 1 0 5
23. of RIL there is a loss due to missed logging revenues We work with rather high harvesting costs here because roadside prices are used No other costs or returns are expected The soil carbon was initialised with a stock of 111 Mg C ha For soil weather data the site San Jose Costa Rica was used from http www worldclimate com 4 7 Afforestation under the Clean Development Mechanism CDM afforestation The file Central _America_CDM_afforestation co2 deals with the afforestation of an area in Central America that is currently used as a pasture Initial grass NPP is 10 Mg dry matter ha yr The site is degrading due to overgrazing reduced litter input to the soil and subsequent loss of soil organic matter The soil is initialised with 58 Mg C ha The project scenario assumes an active reforestation with native species in four functional groups 1 Traditionally commercial species 2 Potentially commercial species 3 Other species and 4 Pioneers Growth data are from Camacho and Finegan 1997 and provide an NPP of around 4 to 5 5 Mg C NPP at its maximum No harvesting is carried out the forest is left to its natural dynamics with some 2 to 3 natural mortality per year The same growth rates are applied as in the CDM RIL case Costs data are from Boer 2001 and are estimated at 400 for initial establishment in a landscape level scheme and at 44 recurring annually Alterra rapport 1068 doc 81 4 8 Pine Oak Central
24. of different landuses Three of those ate included with the CO2FIX V 3 1 installation showing three cases of lowland dipterocarp forests at Kalimantan Indonesia protected primary forest Ind_dipt_primaty forest_protected co2 logged primary forest Ind_dipt_primary forest_logged co2 and secondary forest Ind_dipt_secondary forest co2 Data were obtained from the Malinau Research Forest supplemented with literature data The generally 150 250 tree species per hectare of undisturbed forest were categorised in 6 cohorts according to common growth characteristics Philips et al 2000 Soerianegara et al 1993 Sosej et al 1998 and common use of the different tree species 4 11 2 Protected primary forest For the initial situation dry weight biomass of the stems was estimated from sample plot recordings using an empirical equation by Brown et al 1989 Data from Yamakura et al 1986 were used to estimate initial biomass of branches and leaves Initial root biomass was taken as 17 of total stand biomass Pinard amp Putz 1996 Stemwood densities were derived from http www worldagroforestrycentre org sea Products AFDbases WD carbon content for all biomass components was assumed to be 0 5 In the sample files stem increment is depending on the total biomass of the stand Increment was estimated from re measurements of the permanent sample plots Maximum increment was derived from plots with low biomass densities Competition wa
25. possibilities of management to influence it Also international emission reduction policies continue to center around the role of the biosphere Main agreement was reached at COP VIb in Bonn and elaborated at COP VII in Marrakesh in 2001 Since then the Intergovernmental Panel on Climate Change IPCC has been asked to prepare Good Practice Guidance GPG on reporting greenhouse gases of the Land Use Land Use Change and Forestry Sector an elaboration of the 1996 Revised IPCC Guidelines This GPG was adopted in October 2003 Furthermore the policy arena has set up a draft document how to deal with permanence leakage and accounting of projects falling under the Clean Development Mechanism Pending these decisions and real life projects taking shape now e g under the Prototype BioCarbonFund of the World Bank there is a great need for harmonised tools to quantify the carbon balance of forested ecosystems To address these issues and provide insight in the temporal dynamics of carbon sequestration CO2FIX V 1 0 was designed for even aged monospecies stands Mohren and KleinGoldewijk 1990 Nabuurs and Mohren 1995 Under the first CASFOR project this version was further developed into a windows based user friendly programme and released through the world wide web in June 1999 V 1 2 Mohten et al 1999 Since then more than 1000 users from over 75 countries have downloaded the first version and applied it in several studies see for examp
26. produced takes place This activity is not eligble for Carbon crediting Carbon sequestration by grazing land management is optionally and has to be elected by countries in order to be creditable Is the activity a direct human induced activity to increase Carbon stocks on sites through the establishment of vegetation that covers a minimum area of 0 05 and that does not meet the definition of Afforestation Reforestation Forest Management Cropland Management or Grassland Managem ent Did your country elect revegetation as a Kyoto protocol option for the area where the activity takes place This activity is not eligible for Carbon crediting The activity falls under the Land Use Land Use Change and F orestry options Art 3 4 of the Kyoto protocol For the first commitm ent period accountable anthropogenic greenhouse gas emissions by sources and removals by sinks resulting from cropland m anagement grazing land managem ent or revegetation under Article 3 4 shall be equal to anthropogenic greenhouse gas emissions by sources and removals by sinksin the commitment period less five times the anthropogenic greenhouse gas emissions by sources and removals by sinks resulting from these eligible activities in the base year of that Party while avoiding double accounting This activity is not eligible for C arbon crediting C arbon sequestration by revegetation is optionally and hasto be elected by countriesi
27. produced in the biomass module through biomass turnover natural mortality management mortality and logging slash see section 2 2 for a description of these processes For the soil carbon module the litter is grouped as non woody litter foliage and fine roots fine woody litter branches and coarse roots and coarse woody litter stems and stumps Since the biomass module makes no distinction between fine and coarse roots root litter is separated into fine and coarse roots according to the proportion of branches and foliage litter Each of the litter compartments has a fractionation rate determining the proportion of its contents released to the decomposition compartments in a time step For the compartment of non woody litter this rate is equal to 1 which means that all of its contents is released in one time step whereas for the woody litter compartments this rate is smaller than 1 Litter is distributed over the decomposition compartments of extractives celluloses and lignin like compounds according to its chemical composition Each decomposition compartment has a specific decom position rate determining the proportional loss of its contents in a time step Fractions of the losses from the decomposition compartments are transferred into the subsequent decomposition compartments having slower decomposition rates while the rest is removed from the system The fractionation rates of woody litter and the decomposition rates are controlled by te
28. separated into logwood and pulpwood Slash can optionally be used to produce bioenergy see for details section 2 5 In the first step logwood is allocated to the commodities sawn wood boards amp panels and pulp amp paper and pulpwood is allocated to boards amp panels and pulp amp paper Processing losses are transferred to the bioenergy module The products module distinguishes three categories of end products long term medium term and short term products Each of the commodities sawn wood boards amp panels and pulp amp paper is distributed over these end product categories Process losses can either be re used in lower grade production lines can be used as bioenergy or can be dumped at the mill site For each end product category for the mill site dump and for the landfill an a half live is defined In CO2FIX V 3 1 exponential discard or decay functions are used 26 Alterra rapport 1068 doc Prag Py FU InQ L 24 where lie is the amount of carbon in product category k at time t and L is the half live for category k When this function is applied the average carbon stock remaining in a certain end product compartment amounts to 50 of the original amount after a period equal to the half live This is illustrated for different half lives in Figure 2 4 100 Carbon remaining ol o 40 30 20 10 0 J 0 10 20 30 40 50 60 70 80 90 100 Time
29. terms of carbon stocks and fluxes Is there readily available input data for some tree species Yes when you download a version of CO2FIX you automatically receive a number of input forest types with it In addition you find a list of forest types on the Casfor web pages under case studies Furthermore you ate welcome to send us your input forest types and with your permission we will put them on the web What are the features of and options in each version of CO2FIX CO2FIX V 1 2 is the windows version of V1 which was originally developed by Frits Mohten V1 2 has the possibility to simulate only one cohort functional group of trees i e an evenaged monospecious stand of one ha It has a simple soil module simple management module and a simple products module lt does give a full ecosystem carbon balance If you are new in using models we advise you to use this version first CO2FIX V 2 0 has a couple of main advances main thing is the possibility to work with multiple cohort stands still of one ha These cohorts can influence each other through competition V 2 0 has more advanced options to simulate mortality management and its related mortality Furthermore it has a more detailed products module and an improved soil module CO2FIX V 3 1 contains three new modules a financial module a bioenergy module and a carbon accounting module Furthermore there are some minor changes in the soil and products module Can I si
30. three tabs Management Costs Management Returns and Other Returns and Costs Figure 3 34 In the Management Costs tab you can specify per scenario and cohort the costs directly related to the management In the left side of the window costs related to thinnings and final harvest can be specified The age at which a thinning will take place is specified already in the Biomass module Note these ages cannot be changed here nor can these rows be deleted here That should be done in the biomass module At the right side of the window other age related costs can be specified These are separated in fixed costs such as costs of re planting and recurring costs Note that these costs are related to the age of the cohort In the Management Returns tab you can specify the revenues of the management For revenues of timber harvest the stwmpage price of pulp logs saw logs and firewood must be specified This is in the model combined with the amount of wood that will be harvested to calculate the total revenue In the right side of the window fixed and recurring revenues that are related to the age of the cohort can be specified In the Other Returns and Costs tab costs and revenues related to the simulation year can be specified per scenario both divided in faxed and recurring issues Recurring costs can be for instance property taxes on the forest These are not related to the actual age of the cohort s standing on it Furthermore the discount rate can b
31. through improved or changing management are not eligible Therefore the carbon stored in the forest can not be credited Was the land use in the area where the activity takes place forest before the activity was implemented Was the land use in the area for 50 years or more different to that of forest Was the area without forest clear cut the 31st Did you Was the activity officially establish a forest submitted for registration that will meet before the 31st of December the forest 2005 definition ena The activity falls under the Clean Developm ent Mechanism Art 12 of the Kyoto protocol Under this mechanism reforestation and afforestation activities can be credited by Annex I countries up to 1 of their assigned amount Because the activity was not submitted for registration before the 31 st of December 2005 only Carbon that is sequestered after the The activity falls under the Clean Development Mechanism Art 12 of the Kyoto protocol Under this mechanism reforestation and afforestation activities can be credited by Annex I countries up to 1 of their assigned am ount Because the activity was submitted for registration before the 31 st of December 2005 Carbon that is sequestered prior to the date ofitsregistration but not before the 1st of January 2000 can be credited of December 19897 registration date can be credited The activity do
32. to different bioenergy technologies For example all the biomass produced in the forest may be directed to slash firewood in a bioenergy plantation directed to electricity generation On the other hand the residues produced at a sawmill by a forest managed for timber production may end up as input of a residential heating facility For these reasons the carbon mitigation is executed separately for each of the two main input sources 3 7 3 Parameters dialog The bioenergy parameters can be found under the Bioenergy main menu Within this menu three tabs ate available e General parameters tab to set up the parameters involved in both slash fuelwood and industrial residues fuelwood calculations and in all scenarios Figure 3 30 e Technology for slash firewood tab to enter parameters for each scenario s catbon mitigation calculations for slash firewood based alternative technologies and e Technology for industrial residues firewood tab to enter parameters for each scenario s carbon mitigation calculations for industrial firewood based alternative technologies The General Parameters tab has default values for the global warming potential GWP associated to the different GHG under consideration and default values for the heating value associated to slash firewood and industrial firewood Figure 3 30 If needed these default values can be replaced by other values by the user 60 Alterra rapport 1068 doc Bioenergy Parameters
33. we assumed that 60 of harvest residues from stem branches and needles from the final harvests of Norway spruce stands were utilised as energy Harvest residues from thinnings and Scots pine stands were not utilised in these simulations Industrial residues from both Norway spruce and Scots pine were assumed to be utilised as energy In Finland the process waste of forest industries is actually the biggest domestic source of energy Process losses were determined based on VTT Energy 1999 and Hakkila amp Fredriksson 1996 16 of raw material in sawn wood was allocated to boards 20 to paper and 15 to energy 30 of raw material in boards was allocated to papers and 19 to energy and 40 of papers were allocated to energy Default values of general parameters heating values of fuelwood and global warming potentials of gases and emissions of different fuels and technologies were used Slash fuelwood meaning harvest residues of the final harvests of Norway spruce were assumed to be burned in combustion plant smaller than 50 MW and substitute coal burned in power plant Industrial residues from all the processes from both Norway spruce and Scots pine were assumed to be burned in combustion plant bigger than 50 MW and substitute coal burned in power plant Applicability of the default emission values to Finnish energy production systems was not evaluated Alterra rapport 1068 doc 79 4 3 6 Finance parameters Cost and revenues of the for
34. while during the rest of the year 75 is allocated to fine roots and 25 to coarse roots If we assume a three month period for the leaf expansion phase on average 80 is allocated to fine roots In a simple worksheet calculation we can allocate the total annual root assimilates to fine and coarse roots and determine the annual absolute turnover with the abovementioned turnover rates Then we can calculate a weighed average of turnover relative to the carbon stock in the roots over the full 100 year period realising that this turnover will be too small in the beginning of the simulation and too large towards the end leading to inaccuracies in the simulated stock in the root system and correspondingly in the litter input to the soil see also De Bruijn 2004 Mortality Management mortality and Competion are not parametrised since this should be covered already in the yield tables Thinning Harvest According to the yield table thinnings are carried out every five years However in practice the first thinnings are left out because they yield only unmarketable wood Instead a first thinning without yield of 1 000 trees per ha was assuemd to take place at an age of 20 tot 35 years depending on the site conditions The thinning intensity fraction removed is calculated as the fraction of volume removed in a thinning relative to the sum of remaining volume and the removed volume The minimum diameter for pulp and paperwood is 8 cm Heidemij
35. 0 25 0 1 0 4 Boards 0 3 0 1 0 7 0 5 0 2 0 7 0 2 0 1 0 4 Paper 0 01 0 0 05 0 1 0 0 2 0 89 0 8 1 0 Table 6 Default minimum and maximum parameter values for shares of recycling burning and landfill at disposal Fraction disposed to Recycling Energy Landfill Life span Default Min Default Min Default Min max max max Long term 0 3 0 1 0 4 0 1 0 0 3 0 6 0 4 0 8 Medium 0 1 0 0 4 0 1 0 0 4 0 8 0 6 1 0 term Short term 0 4 0 2 0 6 0 5 0 25 0 1 0 0 3 0 8 Table 7 Default minimum and maximum parameter values for recycling to life spans for each original life span category Original Recycled to life span Long term Medium term Short term Default Min max Default Min max Default Min max Long term 0 1 0 0 2 0 3 0 0 6 0 6 0 4 0 8 Medium 0 0 0 0 1 0 0 4 0 9 0 6 1 0 term Short term 0 0 0 0 0 0 1 1 0 1 0 Table 8 Default life spans Category Half life yr Long term products 30 Medium term products 15 Short term products 1 Mill site dump 5 Landfill 145 116 Alterra rapport 1068 doc Annex 6 Default parameters bioenergy module Table 1 Default parameter values for heating content of different fuels Fuel Heating value MJ kg Biomass Slash Fuelwood Biomass Industrial Residues Fuelwood Coal Gas oil Kerosene LPG Natural gas Oil 15 15 28 43 33 44 75 47 31 42 62 40 19 Table 2 Default parameter values for the Global Warming Potential of GHG val
36. 10 Figure 5 6 Parameterisation of a foliage feeding insect at year 41 and 42 Biomass Stems Foliage Branches Roots Mortality Competition Management mortality Thinning Harvest Scenario Foliage feeder y Cohort Scots pine y STES GROWTH TABLE Carbon content MgC MgDM 5 Wood density MgDM m3 43 Initial carbon MgC ha o CAI m3 ha yr Figure 5 7 Reduced increment between 41 and 45 years caused by defoliation Cancel Apply Help Insect pests causing direct mortality to the trees such as bark beetles can be simulated by a thinning in the same way as storm damage In the example scenario Bark beetles a five year outbreak of bark beetles is simulated Figure 5 8 This leads to a decreased increment during and after the outbreak not shown Specific costs for chemical or biological measures against the pest or disease can be specified in the financial module Alterra rapport 1068 doc 93 Biomass xi Stems Foliage Branches Roots Mortality Competition Management mortality Thinning Harvest Scenario Bark beetle y Cohort Scots pind y Rotation length yr fioo Age Fraction Stems Branches Branches Branches Foliage Slash yr Removed LogWood PulpPap LogWood PulpPap Firewood Cancel Apply Help Figure 5 8 Bark beetle outbreak causing mortality in years 51 55 5 7 Climatic change
37. 1980 van Wijk 1999 so we made sure to have 50 of the trees allocated to pulpwood at the age where the average diameter of the thinned trees exceeded 8 cm in the yield table The minimum diameter for sawnwood is 20 cm at the smallest end van Wijk 1999 We assume here that a small portion 10 of the stems will be suitable for sawnwood at the age where the average diameter exceeds 20 cm Further allocation over Logwood and Pulpwood is more or less linearly interpolated between these points and an increasing fraction is allocated to Logwood after this last point Losses stemwood remaining in the forest are assumed to be at least 10 76 Alterra rapport 1068 doc 4 2 3 Soil Mean monthly temperature and precipitation are obtained from the website www wotldclimate com location De Bilt for the period 1971 2000 The annual degree days are calculated to be 3439 C and potential evapotranspiration 468 mm Total precipitation in the months April October is 460 mm From the flux output table we calculated the average carbon input to the soil for branches foliage and fine roots For the stems we need to consider only the part that is not harvested which can be calculated from the parametrisation in the products tab see later We used these averages as input for the option Calculate initial catbon to initialise the soil carbon However this will in this case probably lead to an overestimation of soil carbon since a large part of the Sc
38. 25 6 52 29 57 30 46 72 17 55 P 60 15 73 p Q 31 38 Soil Soil humus 1 humus 2 carbon carbon MgC ha mgC ha 36 80 60 47 37 01 60 46 Calculate initial carbo Non woody litter Soluble compounds Humus stock 1 Fine woody litter Holocellulose Coarse woody litter 30 Lignin like compounds 30 46 Humus stock 2 60 46 Figure 5 3 Initialisation of the soil module after the fire assuming that 30 of coarse litter has burned as well as all fine and non woody litter Due to damage to the trees increased mortality may occur in the years after a fire event To simulate this we can use the mortality tab of the biomass module see for an example Figure 5 4 As a consequence of the reduced stocking and damage to the trees in the example the increment is reduced in the period after the fire Also the management has changed all regular thinnings have been cancelled and the final felling is carried out already at year 90 90 Alterra rapport 1068 doc x Stems Foliage Branches Roots Mortality Competition Management mortality Thinning Harvest Scenario Fire soil y Cohort MORTALITY TABLE Figure 5 4 Parameterisation of increased mortality after the fire in year 72 In the fire example we now have two simulations one with the right output for the biomass and the products over the whole simulation and one that simulat
39. 3 10 If growth is dependent on the ratio of actual biomass over maximum biomass natural mortality should be parameterised according to this ratio as well 80 70 60 50 40 30 20 10 0 1 30 60 100 200 Age years Mortality of trees Figure 3 10 Mortality due to senescence of three cohorts parameterised as a function of stand age Note that these are hypothetical curves displaying very high mortality rates up to 70 The parameterisation of natural mortality as a fraction of the standing biomass is done in the Biomass main menu tab Mortality Figure 3 11 shows an example of the parameterisation of age dependent natural mortality For several ages the fraction of the standing biomass that dies every year is defined Data on natural mortality can generally be found from measurements of permanent forest inventory plots specialised studies and sometimes it is included in growth and yield tables Generally natural mortality is strongly dependent on management intensity Biomass Douglas r MORTALITY TABLE Figure 3 11 Mortality parameterisation screen in main menu Biomass 44 Alterra rapport 1068 doc 3 4 5 Management related mortality Forest logging operations can damage the remaining trees in the stand causing mortality even several years after the operation Pinard and Putz 1996 Traditional logging methods in tropical primary forests can cause mortality of the remaining trees
40. Art 3 3 option of the Kyoto protocol Under this option Deforestation activities have to be included in the national Carbon inventories Carbon credit transfer to an other Annex I country by the Joint Implem entation mechanism seem sirrelevant here The activity does not meet the requirements of the Is the area used for other purposes Kyoto protocol Did your se elect Forest eae ent as a Kyoto protonai that forest alone like crop production This type of project option for the area where the activity takes place or grazing land is only eligible Y under the Kyoto y protocol when the The activity is forest management Art 3 4 under under the Joint Implementation Art 6 provision F or the hosting country has first com mitm ent period 2003 2012 the amount of credits that can be obtained by Annex I countries from elected this type as Please proceed with the Joint Implementation I decision tree forest managem ent activities under Joint Implementation projects together with forest management activities inside the country is bound to a maximum value CAP that is specified per Annex I country Annex Z Carbon sequestration for these activities can only be transferred to an other Annex I Country when the eligible No credits or debits can be gained by this project quantified emission limitation or reduction commitment is already realised by the hosting country Is the activity related to a
41. CO2FIX V 3 1 A modelling framework for quantifying carbon sequestration in forest ecosystems Dedication We dedicate this document to the memory of Jos Garza Caligaris better known as Pepe Pepe was a member of the CASFOR project since its inception in 1998 As part of the UNAM team he was in charge of programming the first two versions of the CO2FIX model He also set up the basic software structure for the new versions of the program Pepe was energetic imaginative incredibly hard working and insightful He had a critical mind always looking to the most efficient path to solving complex issues Pepe was full of joy and had a strong social commitment Above all he was a wonderful friend and a great companion We will always miss him Acknowledgements The CO2FIX model V 3 1 was developed in the CASFOR II project CASFOR II was financed through the European Commission INCO2 programme ICA4 2001 10100 Additional funding was recetved from the North South programme of the Dutch Ministry of Agriculture Nature Management and Food Quality and by the Mexican National Council of Science and Technology CONACYT under project No 32715 N 2 Alterra rapport 1068 doc CO2FIX V 3 1 A modelling framework for quantifying carbon sequestration in forest ecosystems M J Schelhaas P W van Esch T A Groen B H J de Jong M Kanninen J Liski O Masera G M J Mohren G J Nabuurs T Palosuo L Pedroni A Vallejo T Vil n Al
42. DM ha y at the beginning declining to 5 9 Mg DM ha y at the end of the simulation after 200 years 60 of the grass is harvested every year by grazing and turnover rates are 0 8 for foliage and 0 9 for roots Costs and benefits are based on original project literature but may deviate from the real life case due to interpolation from project scale costs to hectare scale costs and possible omissions of costs Brown et al 2002 Because wood is sold as stumpage no harvesting costs are calculated For soil weather data the site Bucharest was used from http www worldclimate com 4 5 Forest Management in Central Europe The file Central Europe_FM co2 is based on a case presented earlier by Nabuurs and Mohten 1993 and Masera et al 2003 that dealt with an even aged monoculture of Norway spruce Picea abies L Karst on a fertile site in the middle mountain regions in Central Europe This case is now extended with forest management Le it is assumed that through management the increment has increased and that instead of a clearcut after 95 years regeneration of beech Fagus sylvatica is stimulated when Norway spruce has reached an age of 45 years resulting in a mixed stand of Norway spruce and beech Selective logging is applied in this stand The harvesting regime of the spruce cohort is adjusted The initial non commercial thinning of 20 and the 3 follow up thinnings of 20 remain However no final 80 Alterra rapport
43. End products The second tab End products contains parameters for the end products allocation process and the end of life process Figure 3 27 The top part of the window allows the user to define for each commodity sawnwood board paper which fraction is used for long medium and short term products These allocations will sum to 1 because short term 1 long term medium term The bottom part of the window in Figure 3 27 describes the fate of the products at the end of its life The user should define which fraction of the discarded products is recycled and which fraction is burned used for bioenergy The rest of the products are assumed to be dumped in a landfill Alterra rapport 1068 doc 57 Production line End products Recycling life span Default parameters Scenario Scenario 1 y m Products allocation PRODUC FRACTION ALLOCATED TO TION LINE Long term Medium term Short term Sawnwood ner fo 25 o 250000 Boards fo 30 fo 50 fo 200000 Paper 0 01 0 10 0 890000 m End of life PRODUCT FRACTION DISPOSED TO RTE Recycling Energy Landfill Long term fox 08 o 100000 fot fo 8 Medium term Short term fo 2 fo 75 0 050000 Figure 3 27 Parameterising the products module life span allocation and end of life disposal 3 6 4 Life span for products in use and recycling The third tab Recycling life span contains the life spans of the three product groups the landfill and millsite dump and
44. For the users that want a quick start we refer to the separate manual delivered with the model as pdf file 3 2 How to obtain the model The software can be found on the World Wide Web on the site http www efi fi projects casfor Go to CO2FIX model V 3 1 and after reading the disclaimer and completely filling out the registration form including your email address click I agree A response email is automatically sent to you instantly It gives the URL where you can download the software Go to that URL and start the download CO2FIX V 3 1 installer exe to a local directory e g C temp The purpose of the registration is to have insight to the user group of CO2FIX The information you have provided will be used only for internal use and will not be given to any third party With your e mail address which is obligatory in order to receive CO2FIX it is possible for us to keep you informed on major changes and or additions to CO2FIX We will use that only in seldom cases through a mailing list address Your personal email address is thereby secured Execute the CO2FIX V 3 1 installer exe and follow instructions in the install shield Successful installation will result amongst others in a CO2FIX executable a subdirectory called Samples with the case studies and a subdirectory called Special cases with examples for some special cases 3 3 Main menu and General parameters To start double click the CO2FIX ic
45. In that case the ICERs can either be reversed ICERs with reversal or the project owner can choose not to sell these credits CERs without reversal In case of ICERs with reversal the ICERs are calculated as following t 5 ICER 1CER Y ICERf 36 i c0 In case of ICERs without reversal expected future carbon losses are taken into account already beforehand In order to do this we must check if the net sequestered carbon at any verification point in future will be lower than the current amount t 5 If NPG gt min nPG _ gt ICER min nPG _ ICER 37 i c0 t 5 ICER 1CER ICER 38 i c0 If NPG lt min nPG cp t For a visualisation of these approaches see Section 3 10 2 7 5 Kyoto assist tree Under the Kyoto Protocol several types of projects are eligible each with its specific requirements In order to help the user to determine the type of project a decision tree has been constructed By answering the questions the user will be guided through the tree leading to the type of his project The outline of this decision tree is shown in Annex 7 34 Alterra rapport 1068 doc 3 How to use the model 3 1 Introduction This chapter shows the model implementation in C with a user friendly interface We explain how the model can be obtained and operated The text in this chapter was originally written for the manual and therefore the text overlaps with the text in Chapter 2
46. Interactions competition of a cohort as a function of total stand biomass total biomass of all cohorts in a stand i e the interactions of this cohort are with all the cohorts combined including the cohort in question default b Interactions competition of a cohort as a function of biomass of each other cohort i e the interactions of this cohort are defined with each other cohort separately The choice between these methods has to be made in the General Parameters main menu tab General parameters Figure 3 16 The other parameters can be found in the Biomass main menu tab Competition Figure 3 17 and 3 18 General Parameters Ea Comments Scenario General Parameters Cohorts Simulation length yr jan Maximum biomass in the stand Maha 1400 M Growth as a function of Competition relative to Age C Above ground biomass The total biomass in the stand C Each cohort r Management mortality Depends on which cohort is harvested Depends only on the total volume harvest r Optional modules FF Exclude Products I Exclude Bioenergy Cancel Apply Help Figure 3 16 General Parameters screen in main menu General Parameters with in this case competition as a function of the total biomass in the stand 48 Alterra rapport 1068 doc In case of option a for each cohort to be chosen in the top of the window the user should inse
47. M AR project and baseline the difference between the two and the calculation of the amount of credits according to the stock change approach 2 7 3 Temporary crediting approach A temporary CER or tCER is a certified emission reduction CER 1 Mg of CO e issued for an afforestation or reforestation project activity under the CDM which expires at the end of the commitment period following the one during which it was issued The amount of credits that can be earned during a verification is equal to the Alterra rapport 1068 doc 33 amount of sequestered carbon at that moment taking into account the baseline scenario nPG MnC BnC 44 12 34 tCER nAG 35 where nPGt is the net Project greenhouse gas removal by sinks at time t in CO e but without taking into account non CO2 greenhouse gasses and leakage MnCt is the Mitigation net CO removal by sinks at time t carbon stock of the mitigation scenario BnCt is the Baseline net CO removal by sinks at time t carbon stock of the baseline scenario 2 7 4 Long term crediting approach A long term CER or ICER is a certified emission reduction CER issued for an afforestation or reforestation project activity under the CDM which expires at the end of the crediting period of the afforestation or reforestation project activity under the CDM for which it was issued Since ICERs are valid for a long period there is a risk that the sequestered carbon will be lost later in time
48. Mexico The file Central Mexico_pine_oak co2 is an example of an unevenaged mixed stand of Pine Pinus spp and Oak Quercus spp characteristic of the highlands of Central Mexico A more extensive description can be found in de Jong et al In prep The region has volcanic soils of varying depth and fertility Increment data are derived from yield tables obtained from the forest inventory of Nuevo San Juan Parangaricutiro DTF CINSJP 1998 The baseline scenario named conventional scenario shows the typical management regime of mixed pine oak forests as been recommended by the Mexican government The management is based on a 50 yr rotation cycle with thinnings every 10 years Pine trees are subject to logging with 80 of the volume removed at the end of the 50 year cycle About 30 40 trees per ha will remain for 10 years in order to propagate natural regeneration Competing oaks are removed every 10 years about 30 of standing volume and completely removed at the end of the rotation cycle Competition is simulated based on total standing biomass A mid to low efficient processing and low recycling of wood products has been assumed Soil carbon simulation is still preliminary and has been simulated using precipitation and evapotranspiration of the dry season In the Oak conservation scenario all parameters are the same as in the baseline scenario except that the oak removal is reduced Only 20 of the highly competing oaks are remove
49. OC Combustion plant Boilers 33 3206 42 0 065 0 08666 1 2999 0 065 Table 6 Default emission factors for technologies fuelled by kerosene g kg of fuel Emission factors Technology Efficiency CO2 CH4 N20 CO TNMOC Cookstove a 45 6958 63 1 25524 0 18706 0 0 Cookstove b 45 6175 5 1 47675 0 0358 85 025 35 5763 Table 7 Default emission factors for technologies fuelled by LPG g kg of fuel Emission factors Technology Efficiency CO CH N20 CO TNMOC Cookstove a 60 5057 439 0 99871 0 08894 0 0 Cookstove b 55 3075 15 0 04731 0 09462 1 1828 0 0946 Table 8 Default emission factors for technologies fuelled by natural gas g kg of fuel Emission factors Technology Efficiency CO2 CH N20 CO TNMOC Cookstove 55 3852 9332 0 8801 0 07842 0 0 Combustion plant lt 50MW Boilers 30 2439 995 0 6393 0 04262 1 1934 0 0852 Combustion plant gt 50 and lt 300MW Boilers 30 2439 995 0 25572 0 04262 1 1934 0 0852 Table 9 Default emission factors for technologies fuelled by oil 2 kg of fuel Emission factors Technology Efficiency CO2 CH4 N20 CO TNMOC Combustion plant Boilers 33 3134 82 0 12057 0 08038 0 6029 0 1206 118 Alterra rapport 1068 doc Annex 7 Kyoto decision tree CO2FIX Decision tree Tool to asses the type and eligibility of Land Use Land Use Change and Forestry Activities under the Kyoto protocol Legend Question This shape contains a question that can be answered with a Yes or a N
50. OR 2004 tCERs amp ICERs Cumulative Net COze Cumulative Net COze 2012 2017 2022 2027 2032 End of subsequent End of crediting period commitment period Figure 3 35 TCERs and ICERs in case of monotonically increasing carbon stocks ENCOFOR 2004 Cumulative Net COze Cumulative Net COze 2012 2017 2022 2027 2032 Figure 3 36 TCERs and ICERs in case of fluctuating carbon stocks with reversal ENCOFOR 2004 66 Alterra rapport 1068 doc Retired ICERs Cumulative Net COze Cumulative Net COze 2012 201 7 2022 2027 2032 Figure 3 37 TCERs and ICERs in case of fluctuating carbon stocks without reversal ENCOFOR 2004 A requirement for certain types of projects under the Kyoto Protocol is a baseline scenario This baseline scenario defines what would have happened if the project was not initiated Therefore in CO2FIX V 3 1 different scenarios can be specified for example a baseline scenario and one or two mitigation scenarios The definition of these scenarios is done in the main menu General Parameters tab Scenario Figure 3 38 General Parameters x Comments Scenario General Parameters Cohorts Scenario name _ Description A Grass Grassland Afforestation Afforestation with poplar Create new scenario Copy scenario Remove scenario Cancel Amy Hep Figure 3 38 The definition of different scenarios The other parameters concerning the carbon accounting module
51. Pussinen A amp de Jong B J 2003 Modelling carbon sequestration in afforestation agroforestry and forest management projects the CO2FIX V 2 approach Ecological Modelling 164 177 199 Please send information about publications in which you have used CO2FIX to the developers of the software G J Nabuurs ALTERRA PO Box 47 NL 6700 AA Wageningen The Netherlands Except for the enclosed case study forest types the user of CO2FIX is solely responsible for the quality of parameterisation data Neither the authors of the model nor those of the Windows version assume responsibility for damages caused directly or indirectly from the use of the program or by the application of results derived from it CASFOR Team Wageningen Patzcuaro Turrialba Joensuu October 2004 Prof G M J Mohren Wageningen University and Research Centre Forest Ecology and Forest Management Group The Netherlands frits mohren wur nl Dr G J Nabuurs Mr M J Schelhaas amp Mr T A Groen Wageningen University and Research Centre Alterra The Netherlands gert jan nabuurs wur nl Dr O Masera amp B H J de Jong Laboratorio de Bioenerg a Centro de Investigaciones en Ecosistemas CIECO National Autonomous University of M xico UNAM M xico omasera Moikos unam mx Dr L Pedroni Mr A Vallejo amp dr M Kanninen Centro Agron mico Tropical de Investigaci n y Ense anza CATIE Costa Rica lpedroni catie ac cr Dr M Lind
52. al Change Biology 8 519 530 VTT Energy 1999 Energia Suomessa Energy in Finland Edita Helsinki In Finnish Yamakura T Hagihara A Sukardjo S Ogawa H 1986 Aboveground biomass of tropical rain forest stands in Indonesian Borneo Department of Biology Faculty of Science Osaka City University Osaka 558 Japan 68 71 82 104 Alterra rapport 1068 doc Annex 1 Overview of units and conversions 1 ton C 1 Mg C 44 12 ton C 1 ton CO Alterra rapport 1068 doc 105 Annex 2 C CAI CASFOR CATIE CDM CER CIECO DM EFI GWP IPCC JI ICER LULUCF PET tCER UNAM UNFCCC Alterra rapport 1068 doc Acronyms catbon Current Annual Increment Carbon Sequestration in Forested Landscapes Centro Agron mico Tropical de Investigaci n y Ense anza Clean Development Mechanism Certified Emission Reduction Laboratorio de Bioenerg a Ecosistemas Dry matter European Forest Institute Global Warming Potential International Panel on Climate Change Joint Implementation long term CER Land use land use change and forestry Potential EvapoTranspiration temporary CER National Autonomous University of M xico United Nations Framework Convention on Climate Change Centro de Investigaciones en 107 Annex 3 FAQs What is CO2FIX CO2FIX is a modelling frame where a user builds in his own forest data in order to simulate the long term carbon balance of a forest ecosystem It provides annual output in
53. arbon cycle 5 4 Fire The following example deals with the case of forest fire The example is illustrated in the file fire co2 in the Special Cases directory Basis for this example is the Scots pine case in The Netherlands yield class 8 as explained in Chapter 4 It is included in the scenario Regular as comparison to the fire parameterisation Fire can be simulated in CO2FIX as a kind of thinning using the thinning harvest tab in the biomass module The intensity of the fire can be expressed as the fraction of trees that is removed i e killed If the fire is not too severe part of the trees ate killed but still usable This can be simulated by allocating a fraction of the trees killed to LogWood and or PulpPap Usually the wood is of lower quality which can be expressed by a relatively high fraction of pulpwood In our example at year 72 a fire occurs that kills half of the trees Of those trees 20 is harvested and used as pulp ot paper wood Figure 5 2 88 Alterra rapport 1068 doc Biomass Stems Foliage Branches Roots Mortality Competition Management mortality Thinning Harvest Scenario Fire biomass products hd Cohort Scots pine y Rotation length yr so Stems Branches Branches Branches Foliage Slash PulpPap LogWood PulpPap Firewood Figure 5 2 Parameterisation of fire in year 72 that kills 50 of the trees The rest of the affected trees and all other sla
54. arch Report 99 3 33 p Monserud R A and Sterba H 1996 A basal area increment model for individual trees growing in even and uneven aged forest stands in Austria For Ecol Manage 80 pp 57 80 Mori T 1999 Rehabilitation of degraded forests in lowland Kutai East Kalimantan Indonesia In Kobayashi S Turnbull J W Toma T Mori T Majid N M N A 2001 Rehabilitation of degraded tropical forest ecosystems Workshop proceedings 2 4 November 1999 Bogor Indonesia Alterra rapport 1068 doc 101 Nabuurs G J and G M J Mohren 1995 Modelling analysis of potential carbon sequestration in selected forest types Canadian Journal of Forest Research 25 1157 1172 Nabuurs G J and G M J Mohren 1993 Carbon in Dutch forest ecosystems Neth J Agr Sci 41 309 326 Nabuurs G J and M J Schelhaas 2002 Carbon profiles of forest types across Europe assessed with CO2FIX Ecological Indicators 1 213 223 Nabuurs G J Garza Caligaris J F Kanninen M Karjalainen T Lapvetelainen T Liski J Masera O Mohren G M J Pussinen A Schelhaas M J 2002 CO2FIX V2 0 manual of a model for quantifying carbon sequestration in forest ecosystems and wood products Wageningen ALTERRA report 445 45 p Noble I Apps M Houghton R Lashof D Makundi W Murdiyarso D Murray B Sombroek W Valentini R 2000 Implications of different definitions and generic issues In Watson R et al Eds
55. ary forest If logging impact is low and does not change the forest structure and composition too much forests can still be regarded as primary forest To simulate this the primary forest example is harvested in a 35 year cycle followed by management mortality From the sample plots an average harvested volume of 40 m ha was estimated Management mortality was implemented using the figures suggested by Bertauld amp Kadir 1989 who suggest tree mortality increases after harvest from 1 5 yt to 2 5 yr lasting for 15 years 4 11 4 Secondary forest If the forest structure and species composition have changed significantly from the primary situation a forest will be classified as secondary The causes can be diverse such as logging fire and re growth after cultivation This example simulates a forest which is degraded due to heavy logging For the simulation the same cohorts as in the primary forest were used Total initial biomass is set at 50 of the untouched situation with a 15 share for the pioneer species after the suggestion by Mort 1999 Because of the lack of commercial species this forest is not logged anymore 84 Alterra rapport 1068 doc 5 Special parameterisations 5 1 Introduction Although CO2FIX was originally developed for forest ecosystems questions arose if it could be applied to other systems as well With the development of CO2Land this question became even more important Moreover there was inter
56. benefits for greenhouse gas emissions of the use of biomass instead of fossil fuels Fuel sources for bioenergy can be either logging slash or industrial residues processing losses or discarded products In the financial module costs and revenues can be specified to get an indication of the profitability of the project In the carbon accounting module the user will get an indication of the amount of credits that can be generated with the project according to different types of crediting systems tCERs and ICERs for CDM AR projects and the stock change method for other projects The model produces output in tabular and graphic forms It allows estimating the time evolution at the stand level of the carbon stored in different pools of the system The CO2FIX model V 3 1 is applicable to many different situations afforestation projects agroforestry systems and selective logging systems The model is freely available from the web together with numerous examples The model has many users The two earlier versions of the model have been downloaded already almost 2000 times Alterra rapport 1068 doc 11 1 Introduction The terrestrial biosphere plays an important role in the global carbon cycle On average in the 1990 s it absorbed 2 3 billion tonnes C y which is 36 of annual fossil fuel emissions IPCC 2001 This notion continues to drive scientific research on the temporal evolution of the sink the location of the sink across biomes and the im
57. bes x t the weight of organic carbon in each decomposition compartment j at time t extractives ext celluloses cel lignin like compounds lig simple humus hum1 or complicated humus hum2 cij the concentration of compound group j in litter type 1 kj the decomposition rate of compartment j and p the proportion of mass decomposed in compartment i transferred to a subsequent compartment The invasion rates of litter by microbes ai and the decomposition rates kj depend on effective temperature sum T effective temperature sum 0 C threshold and summer drought D precipitation minus potential evapotranspiration from May to September as follows k T D kio 1 5 0 000387 T 1903 0 00325 D 32 22 a T D a 1 s 0 000387 T 1903 0 00325 D 32 23 where ai and ko denote microbial invasion and decomposition rates in chosen standard conditions T 1903 C days D 32 mm For the humus compart ments parameter s may have a value lower than one to reduce the temperature sensitivity of humus decomposition for the other decomposition rates s is equal to one The decreasing effect of summer drought on decomposition was included in the model to account for slow decomposition observed in Mediterranean like climate where summers are dry Liski et al 2003a In similar conditions in the southern hemisphere the months from May to September should be replaced by another per
58. biomes of the world Watson et al 2000 Biome Current average dry matter content tropical forests 241 temperate forests 113 boreal forests 128 tropical savannas 59 temperate grasslands 14 deserts 4 tundra 13 wetlands 86 croplands 4 The parameterisation of the stem compartment is done in the Biomass main menu tab Stems Figure 3 7 gives an example of the parameterisation of the Stems compartment in case of the age related growth method In this case stem volume increment is given with 5 year intervals In addition to the volume increment the catbon content of dry matter the basic wood density dry matter per fresh volume and any carbon initially present on the site need to be given The latter is mainly the case when simulations do not start at age zero These data need to be filled in for each cohort in each scenario Information on biomass of many forests around the world can be found for example in Cannell et al 1982 The maximum aboveground biomass of the stand or of each of the cohorts can be estimated from inventory data coming from undisturbed or lightly disturbed forests in or around the site area Locally developed or published regression equations that convert inventory data to standing biomass should be used for this purpose Brown 1997 If only commercial volume data ate available for the whole forest or the cohorts standardized biomass expansion factors can be applied to these data If no inventory or v
59. c 69 3 10 Output The output of CO2FIX can be viewed as graphs or as tables In the main menu six buttons are available View stocks table icon to generate a table that shows all kinds of stocks View flow table icon to generate a table that shows all kinds of fluxes View financial output to generate a table that shows all discounted costs and revenues and NPVs View carbon credits to generate a table that shows carbon credits and costs per credit for the different methods View chart output icon to view simple ready made charts of the output View options icon to select alternatives for the ready made charts and tables All tables can be exported to a flat text file that can be imported in e g Excel with the Excel button the fourth button from the left The ready made charts Figure 3 41 can easily be altered through the view options icon A screen with the different options will appear Figure 3 42 This allows viewing stocks of carbon dry weight volume or current annual increment for total biomass by scenario and cohort or for the soil or products compartment Also a comparison between scenarios is possible as well as a chart with the development of carbon credits under the different methods over time With the introduction of scenarios and the bioenergy module it is possible to produce negative values if the mitigation scenario or technology is less than the baseline However the
60. can be found under the Carbon Accounting main menu The Carbon Accounting module consists of two tabs Carbon Accounting and Kyoto Protocol The Carbon Accounting tab contains all parameters concerning the carbon accounting the Kyoto Protocol tab provides the user with some help concerning the Kyoto Protocol and different types of projects Alterra rapport 1068 doc 67 Under the Kyoto Protocol tab the type of project you are investigating must be selected Figure 3 39 At the bottom of the window a short description of the type of project and some of its requirements will be visible To determine the type of your project you can click the Assist button By answering the questions you will be guided through a decision tree and so find out what type of project you have Carbon Accounting x Carbon Accounting Kyoto Protocol For assistance or testing if the project complies TER to the Kyoto protocol click the assist button ssis Project Type Afforestation or Reforestation C Forest Management C Forest Management under JI C Cropland Grazingland management or Revegetation Cropland Grazingland management or Revegetation under JI C Not elligible under Kyoto Guidelines for this type of project For the clean development mechanism a maximum 1 of the assigned amount is specified in the first commitment period 2008 201 2 In the case of a hectare scale project this is not of importance For CDM projects a baseline ha
61. cases a warning will appear indicating for which situation scenario number and slash fuelwood or industrial residues firewood the carbon mitigation shows a negative result 3 7 5 Enabling disabling the Bioenergy Module The Bioenergy Module can be enabled disabled at the general parameters dialog The basic input to the model fuelwood coming from both slash and industrial sources is taken from the products module so the Bioenergy Module depends on Alterra rapport 1068 doc 63 the Products Module to be enabled Disabling the Bioenergy Module prevents all mitigation calculation and carbon mitigation increment to the scenario total carbon stock in the scenario The bioenergy output columns can be hidden from the carbon stocks table by using the carbon stocks table view options but this does not prevent the bioenergy mitigation carbon from being added to the total scenario carbon stock 3 8 Forest financial module Costs and benefits are assessed in CO2Fix V 3 1 with a simple module Different types of cost and benefit inputs have to be specified by the user The model will calculate the costs and benefits the discounted costs and benefits and the Net Present Value NPV Note that the financial module only takes into account the direct revenues from the forest and not any added value from end products farther away in the wood products chain Parameters for the financial module can be found under the Finance main menu This menu contains
62. costs and benefits are assessed in CO2FIX V 3 1 with a simple module Different types of cost and benefit inputs have to be specified by the user CO2FIX calculates the discounted costs and income as well as the Net Present Value NPV per carbon credit since income from carbon credits is not asked as an input If the result of the case is a negative NPV this can be seen as the costs per credit The calculation of the net costs and income balance in a year is the sum of all costs made and benefits earned in that year The discounted balance B of a year is the balance multiplied with a financial discount factor D CB discounted CB 7 Dpr 29 where Dp is calculated with 1 1 1 Dry a T Se 30 fe teas Eder bare ge 30 Alterra rapport 1068 doc in which rp is the financial discount rate specified for year t The discount rate r is not considered constant but can be specified for several years allowing a trend in discounting the costs The net present value NPV of a forest in a given year t is obtained through summing the total amount of discounted costs and benefits from the beginning of the project up to that year 31 t discounted NPV y CB tb 2 7 Carbon accounting module 2 7 1 Introduction In the past many methods have been developed and proposed to calculate carbon credits At the CoP9 meeting in December 2003 the exact carbon crediting methods for CDM afforestation or reforestation CDM AR project
63. d b Interactions of the cohort in question as a function of the relative biomass of each other cohort separately Mathematically we can express Mg either as B Mg f os L dimensionless or 6 Me MS dimensionless 7 where Mg i is the dimensionless growth modifier function of each cohort 1 relative to each of the other cohorts k and Mg u f Pics dimensionless 8 1max where B and Bmx ate the aboveground biomass of each cohort 1 and the maximum aboveground cohort biomass respectively Thus if two cohorts are present we have to include four possible growth modifiers if three cohorts are present then potentially nine growth modifiers might be defined and so on 18 Alterra rapport 1068 doc 2 2 3 Tree mortality due to senescence Mortality due to senescence can be estimated as a function of tree age or as a function of the relative biomass standing biomass divided by the maximum stand biomass B Ms flage or Ms f dimensionless 9 imax where Ms is the cohort mortality due to senescence of cohort 1 at time t In the first case it is assumed that all trees have a maximum age and that the mortality i e the probability of dying increases when the age of the stand approaches the maximum age In some situations there may also be high initial mortality for instance of pioneer species in a natural succession Vanclay 1989 If data of mortality related to age
64. d at each thinning or harvesting activity The Oak conservation Bioenergy scenario is similar to the Oak Conservation scenario except that a large fraction of the harvested product and slash is used to generate bio energy to substitute fossil fuels 4 9 Teak plantation Costa Rica The file CR_teak_plantation co2 contains an example of a Teak Tectona grandis plantation in Costa Rica on a degraded soil The mean annual increment MAI is 15 m ha yr over the rotation of 40 years Thinning takes place at ages 3 10 20 and 30 years Financial information is derived from Puolakka 2003 4 10 Agroforestry Costa Rica The file CR_coffee_agroforestry co2 contains an example of an agroforestry system in Costa Rica The system contains three cohorts The canopy layer consists of shade trees of the species Cordia alliodora 100 trees per ha with a rotation of 20 years The wood is used for furniture The intermediate layer consists of Erythrina poeppigiana which is a service tree It is managed in a 10 year rotation and each year leaves and branches are pruned and left to decompose The understory consists of 82 Alterra rapport 1068 doc Coffea species which are renewed every 20 years Most data are obtained from Fassbender 1993 4 11 Lowland dipterocarp forests at Kalimantan Indonesia 4 11 1 General For an application of the landscape level model CO2Land in Kalimantan de Bruijn In prep set up a series of files covering a range
65. e inserted in this tab 64 Alterra rapport 1068 doc Finance Management Costs Management Retums Other Retums and Costs Scenario Fem Cohort Pine y Thinning Harvesting costs Age related costs Recurring RECURRING COSTS Costs Figure 3 34 The parameterisation of the Financial module 3 9 Carbon accounting module In the past many methods have been developed and proposed to calculate carbon credits At the CoP9 meeting in December 2003 the exact carbon crediting methods were settled as well as the eligible carbon pools Decision 19 CP 9 see for the exact text http unfecc int resource docs cop9 06a02 pdf Carbon pools eligible for carbon credit issuance for afforestation or reforestation project activities under the CDM are above ground biomass below ground biomass litter dead wood and soil organic matter Temporary CER or tCER is a certified emission reduction CER 1 Mg of CO e issued for an afforestation or reforestation project activity under the CDM which expires at the end of the commitment period following the one during which it was issued A tCER can be used only in the commitment period for which it was issued When it expires its buyer must replace it in full Long term CER or ICER is a certified emission reduction CER issued for an afforestation or reforestation project activity under the CDM which expires at the end of the crediting period 20 or 30 years of the afforestatio
66. e is automatically added to slash The last two columns define the allocation of slash between firewood and input to the soi litter The last row entered in the table is regarded as the end of the rotation If this is a final harvest a 1 under fraction removed should be entered to remove all stems and biomass However this fraction can be lower than 1 to simulate some living trees left at the site In this way it is also possible to simulate regular interventions in unevenaged forests where for example every 25 years 10 of the commercial trees is harvested If growth is driven by age the cohort will start growing according to age zero after the end of the rotation even if not all trees were harvested The rotation length that will be applied is shown in the upper right box Stems Foliage Branches Roots Mortality Competition Management mortality Thinning Harvest Scenario Scenario 1 y Cohort Ping y Rotation length yr 50 Age Fraction Stems Branches Branches Branches Foliage Removed Logwo PulpPap Slash Firewood Soil Cancel Apply Help Figure 3 19 Thinning and final harvesting table Alterra rapport 1068 doc 51 3 5 Soil module 3 5 1 Applicability In CO2Fix the dynamic soil carbon model Yasso Liski et al in prep http www efi fi projects yasso is used The model describes decomposition and dynamics of soil carbon in well drained soils soils in which poo
67. edonantoja 613 Vantaa In Finnish Hakkila P 1989 Utilization of residual forest biomass Springer Verlag Berlin Heidemij 1980 Regionaal hout een onderzoek naar de huidige en toekomstige beschikbaarheid van rondhout en houtafval afkomstig uit Nederland en aangrenzende gebieden 183 FAO 2001 Global Forest Resources Assessment 2000 FAO Forestry Paper 140 IEA Bioenergy 2001 Greenhouse Balances of Biomass and Bioenergy Systems IEA Bioenergy Task 38 In www ieabioenergy com Intergovernmental Panel on Climate Change IPCC 2001 IPCC Third Assessment Report Cambridge University Press New York IPCC 2003 Good Practice Guidance for Land Use Land Use Change and Forestry IPCC NGGIP Japan ITTO 2002 ITTO Technical report Phase I 1997 2001 ITTO project PD 12 97 REV 1 F Forest science and sustainability The Malinau Model Forest Jansen J J J Sevenster et al Eds 1996 Opbrengsttabellen voor belangrijke boomsoorten in Nederland Yield tables for important tree species in the Netherlands IBN Rapport 221 Hinkeloord Report No 17 Jansen P A G 1999 De Nederlandse rondhoutverwerkende industrie in 1998 Wageningen Stichting Bos en Hout SBH Janssens I A D A Sampson et al 1999 Above and belowground phytomass and carbon storage in a Belgian Scots pine stand Ann For Sci 56 81 90 Jong B H J de O Masera M Olgu n R Mart nez In prep Greenhouse gas mitigation potential of combining
68. er compartments this rate is smaller than 1 Litter is distributed over the decomposition compartments of extractives celluloses and lignin like compounds according to its chemical composition Each decomposition compartment has a specific decomposition rate determining the proportional loss of its contents in a time step Fractions of the losses from the decomposition compartments are transferred into the subsequent decomposition compartments having slower decomposition rates while the rest is removed from the system The fractionation rates of woody litter and the decomposition rates ate controlled by temperature and water availability The parameters for the soil module can be found under the Soil main menu The soil module consists of two tabs General Parameters and Cohort Parameters In the General Parameters tab the user needs to provide climate parameters for the site Figure 3 20 These are effective temperature sum degree days above zero over the year C d precipitation in growing season mm and Potential evapotranspiration in growing season PET mm Temperature and precipitation data may be found at for example http www worldclimate com CO2FIX can calculate degree days above zero and potential evapotranspiration from mean monthly temperatures This can be done by 52 Alterra rapport 1068 doc activating the Cakulate button In the Calculate climate window Figure 3 21 monthly temperatures can be specified as well as whic
69. er of fine roots is higher total root turnover should be higher under short rotations than under long rotations Some literature data on root allocation and turnover can be found in Cairns et al 1997 Gill and Jackson 2000 and Rasse et al 2001 The parameterisation of the foliage branches and roots compartments can be evaluated by checking simulated stocks against e g measured biomass data at different ages 3 4 4 Mortality Tree mortality within each cohort is separated into two causes natural mortality mortality due to senescence and competition and mortality due to management activities This section deals with the natural mortality only for management mortality see the next section In CO2FIX the natural mortality is incorporated as a fraction of the standing biomass This fraction can vary with age or with the ratio between actual and maximum attainable biomass depending on the growth method chosen see Figure 3 6 If growth and thus mortality is dependent on age mortality may be high at low ages simulating severe competition during early and dense stages e g cohort 3 in Figure 3 10 When the initial planting density is low initial mortality may be low as well e g like cohort 2 and 3 in Figure 3 10 At middle ages mortality may be low especially in the case of managed stands When the trees approach their maximum Alterra rapport 1068 doc 43 attainable age mortality will increase again cohort 1 and 2 in Figure
70. es the soil compartment after the fire In order to obtain a full carbon balance the user should combine the results of these two simulations The results of the biomass compartment should be the same but we need to continue the first simulation to keep track of the carbon in the products since the product pools cannot be initialised in the model 5 5 Storm damage The following example deals with the case of storm damage The example is illustrated in the file storm co2 in the Special Cases directory Basis for this example is again the Scots pine case in The Netherlands yield class 8 as explained in Chapter 4 It is included in the scenario Regular as comparison to the storm damage parameterisation Storm damage can be simulated in a similar way as a fire expressing the intensity of damage via the Harvest tab The example shows a storm damage in year 81 which uprooted or broke 30 of the trees Figure 5 5 The amount of wood salvaged can be simulated by specifying fractions of stems extracted for sawnwood or pulpwood If the wood is damaged a higher fraction of wood will be left in the forest or a higher fraction of pulpwood may be specified than in case of regular thinnings In the example only 10 of the downed wood is still usable as logwood 50 is used for pulp or paper and 40 is left in the forest to decompose Also after a storm increased mortality can occur for example due to new windfalls at newly created edges or su
71. esnot meet the requirements of the Kyoto protocol to fall under Afforestation or Reforestation options and is therefore not eligible to credit sequestered Carbon for a Clean Developm ent Mechanism CDM like project 122 Alterra rapport 1068 doc
72. est in the simulation of coppice systems e g Lettens et al 2003 disturbance events and climate change In this chapter we will show some examples of the use of CO2FIX for other purposes These examples ate provided with the model and can be found in the directory Special Cases 5 2 Non forest systems The CO2FIX model is in the first place meant to be used for assessment of forest ecosystem carbon balances However it is possible to parameterise CO2FIX in such a way that it represents grassland or cropland systems However when doing this the user should keep in mind that the model was never really designed to be used for grass or cropland ecosystems An example of a simulation of a grass ecosystem is shown in the file grass co2 in the directory Special Cases In order to simulate a grass or crop the grass can be seen as a tree with a very small stem volume no branches and a lot of foliage and roots The stem part is needed since allocation to foliage and roots is driven by stem increment In order to keep the influence of the stem compartment as small as possible a very small increment has to be specified for example 0 01 Figure 5 1 The foliage and root compartment receive a very high relative increment 500 and 400 respectively Figure 5 1 Since the wood density has been set at 1 the aboveground production is 500 1 0 01 5 Mg DM ha Similarly belowground production is 4 Mg DM ha Characteristic for
73. est management were derived from Finnish Statistical Yearbook of Forestry 2001 FFRI 2002 Costs were as follows soil preparation harrowing and scarification 144 14 ha Planting 737 83 ha and tending of seedlings 221 12 ha Stumpage of pulp logs was parameterised to be 25 13 m and stumpage of saw logs 48 32 m 4 4 Afforestation in Romania The file Rom_Robinia_afforestation co2 contains a monoculture of Robinia Robinia pseudoaccacia on degraded soils in Romania that were formerly used for agriculture This case is based on a small part of a larger real life afforestation project that is currently carried out in Romania Brown et al 2002 Figures and practices in this parameterisation were followed as good as possible However the real life case has a project duration of 30 years but here a total project life of 60 years is assumed This was done to facilitate the comparison with the next three cases as described in Groen et al In prep A mortality of 2 per year is assumed for the first 10 years which decreases after 10 years to 1 No logging related mortality was assumed Products are excluded from the carbon calculations An initial soil carbon content of 54 Mg C ha was assumed Brown et al 2002 Because this is a JI project carbon credits are purchased by the prototype carbon fund a base line is required Degrading grassland is simulated in the CO2FIX program serving as a base line with an NPP of 9 Mg
74. ever with some additional work it is possible to simulate such systems This example is illustrated in the file coppice co2 in the Special Cases directory The simulated system is a coppice system of Eucalyptus globulus in Galicia Spain Data for the first rotation are based on the work of Valero and Picos Valero and Picos 2002 Valero and Picos in prep In a coppice system all aboveground biomass is removed with a certain interval depending on the tree species and the aim of the product after which the trunks will re sprout This interval can range from a few years to several decennia in this case 16 years The fraction of removed trees must be 1 to simulate the harvest of all aboveground biomass The allocation of the removed trees to logwood or pulpwood depends on the purpose of the coppice system In the case of coppice most branches are harvested as well which is taken into account by entering a fraction in the Branches to Logwood or Branches to Pulpwood cells If the aim of the coppice system is to generate energy all stems and branches can be allocated to Slash and a 1 can be put in the SlashFireWood cell indicating that all Alterra rapport 1068 doc 87 slash stems plus branches plus foliage is used as firewood The parameterisation of the stem increment and allocation to other biomass compartments will be different for coppice than for high forest especially after coppicing and thus needs special attention As far as the
75. forest management and bioenergy substitution A case study from Central Highlands of Michoacan Mexico Submitted to Forest Ecology and Management Alterra rapport 1068 doc 99 Kaipainen T Liski J Pussinen A amp Karjalainen T 2004 Managing carbon sinks by changing rotation length in European forests Environmental Science amp Policy 7 205 219 Kangas A S 1997 On the prediction of bias and variance in long term growth projections Forest Ecology and Management 96 207 216 Karjalainen T Kellomaki S amp Pussinen A 1994 Role of wood based products in absorbing atmospheric carbon Silva Fennica 28 2 67 80 Karjalainen T Pussinen A Liski J Nabuurs G J Erhard M Eggers T Sonntag M Mohren F 2002 An approach towards an estimate of the impact of forest management and climate change on the European forest sector budget Germany as a case study Forest Ecology and Management 162 1 87 103 Kellom ki S V is nen H H nninen H Kolstr m T Lauhanen R Mattila U Pajari B 1992 SIMA a model for forest succession based on the carbon and nitrogen cycles with application to silvicultural management of the forest ecosystem Silva Carelica 22 91 p Kira T amp Shidei T 1967 Primary production and turnover of organic matter in different forest ecosystems of the western Pacific Jap J Ecol 17 2 70 87 Knippers T and P W van Esch B van Putten In prep Uncertainty in
76. g and storing planting material 1575 per ha for planting material and 1322 for planting The costs for the first uncommercial thinning are 333 per ha Selection of quality trees takes place once every rotation and cost 98 per ha The costs for marking trees depend on the number of trees per ha to be marked and amount up to 165 per ha The costs for thinnings with yield and final cutting are based on cost standards for harvesters and forwarders The cost for harvester operations depend on the tree Alterra rapport 1068 doc 77 diameter and vary from 5 to 18 per m The costs for timber extraction using a forwarder are set to 6 per m where as the cost for transportation of timber to the factory are set to 5 50 per m The returns at the factory delivery value for pulp logs are set to 35 per m whereas the returns for saw logs are set to 50 per m 4 3 Managed Scots pine and Norway spruce stands in Southern Finland 4 3 1 General The examples of Scots pine Pinus sylvestris at Vaccinium site type Fin_Scots pine co2 and Norway spruce Picea abies at Myrtillus site type Fin_Norway spruce co2 stands in Southern Finland are based on the study of Kaipainen et al 2004 Both stands contain only one cohort The simulation length is 450 years with a rotation length of 90 years 4 3 2 Biomass parameters Current annual increment CAI was taken from local growth and yield table
77. g rotations However for representing the soil dynamics in greater detail this one root compartment is distinguished in coarse roots and fine roots at the time of turnover The fractions of these two are assumed the same as the ratio between branches and foliage litter at that time Alterra rapport 1068 doc 19 2 2 5 Harvesting If the particular forest ecosystem under analysis is managed part or all of the tree biomass is removed through thinnings selective logging or clear cutting This harvested biomass is subtracted from the existing biomass and is allocated to the products and soil modules see the chapters on soil organic matter and wood products below Harvest in year t in cohort is defined as a fraction of the existing biomass in that cohort fH This fraction is applied to all components 4 foliage stems branches roots Total harvested biomass H is then calculated as H By fA Mg C ha 11 2 2 6 Mortality due to logging harvesting damage Forest logging operations can increase the mortality of the remaining trees This damage depends very much on the type of forest and the type of technology and methods used in logging Mortality due to logging is directly related to the intensity of logging which can be expressed as the number of trees basal area volume or biomass logged Also the logging may cause mortality several years after the operation Pinard and Putz 1997 In many cases the in
78. g sections each of these examples is discussed For the first example a more extensive description is included to show the parameterisation process step by step Table 4 1 Overview of the examples included 3 Pale E 5 EHE gt 2 H y g es 60 MS o Y g 3 y oO D a g Elz E lle e f 5 2 8 8 8 s8 8 File name co2 Countty region Tree species ZAlolol slilalalels NL_Scots pine X Netherlands Pinus sylvestris 1 A E X X E Southern Fin_Scots pine Finland Pinus sylvestris 1 A X X X Southern Fin_Norway spruce Finland Picea abies 1 X X X Robinia Rom_Robinia_affor Romania pseudoacacia 1 A 3 T X X X Picea abies Central Europe_FM Central Europe Fagus sylvatica 2 A C X X Central America CDM_RIL Central America Tropical species B G X X Central America CDM_affor Central America Tropical species 4 B T X X Pinus spp Central Mexico_pine_oak Central Mexico Quercus spp 2 A T E X X CR_coffee_agroforestry Costa Rica Trees coffee 3 A C E X CR_teak_plantation Costa Rica Tectona grandis 1 A T X Ind_dipt_primary Kalimantan forest_protected Indonesia Tropical species 6 B T T Kalimantan Ind_dipt_primary forest_logged Indonesia Tropical species 6 B T T Ind_dipt_secondary forest Kalimantan Indonesia Tropical species 6 B T T Growth A as a function of Age B as a function of Biomass Co
79. gging The management mortality in the model is linearly interpolated between the given mortality functions depending on the intensity of logging In case the logging intensity is higher than the highest parameterised intensity the function for the highest logging intensity is used The user has two options for modelling the mortality due to logging damage a Mortality as a function of total biomass removed i e the mortality of the remaining trees in all cohorts is uniform and proportional to the remaining biomass of each cohort default Alterra rapport 1068 doc 45 b Mortality as a function of biomass removed from each cohott i e the mortality of all the remaining trees in all the remaining cohorts depends on the degree of logging of the cohort logged The choice between these methods has to be made in the General Parameters main menu tab General parameters Figure 3 13 The other parameters can be found in the Biomass main menu tab Management mortality Figure 3 14 General Parameters Ea Comments Scenario General Parameters Cohorts Simulation length yr pi Maximum biomass in the stand Ma ha 400 M Growth as a function of Age Competition relative to The total biomass in the stand Each cohort Management mortality Depends on which cohort is harvested Depends only on the total volume harvest m Optional modue T Exclude Products I Exclude Bioenergy
80. h months are considered as growing season It is important to note that CO2FIX V 3 1 uses effective temperature sum as the temperature variable not annual mean temperature like V 2 0 did General Parameters Cohort Parameters Degree days above zero C Calculate Precipitation in growing season mm 390 Potential evapotranspiration in hoo growing season mm 1000 Figure 3 20 Main window for the Soil module Calculate climate xi Please fill in the mean temperature degree Celcius for each month and set the check box for true if the month is in the growing season January D July JV 120 6 El fs August v 20 1 cin September v 16 9 Apil 103 October f 123 Iv 14 9 November 6 1 June Jv 17 8 December E i Cancel Figure 3 21 Calculate climate window with in this case a growing season from May till September February March iii May v For each cohort in each scenario the carbon stocks in each soil compartment i e the boxes in Figure 2 2 must be initialised This can be done through manually inserting available data in the Cohort parameters tab Figure 3 22 or initial stocks can be calculated by providing litterfall rates of the vegetation on the site before the current case study This latter option can be activated by the Calculate initial carbon button In Alterra rapport 1068 doc 53 the Equilibrium window Figure 3 23 the litterfall rate
81. he Leningrad Region Ecological Bulletins 49 137 147 Tomppo E 1996 Multi source national forest inventory of Finland In R Paivinen J Vanclay amp S Miina eds New thrusts in Forest Inventory EFI proceedings No 7 p 27 41 Trofymow J A Preston C M and Prescott C E 1995 Litter quality and its potential effect on decay rates of materials from Canadian forests Water Air Soil Pollut 82 215 226 Vaessen O 2001 Literatuurstudie naar de biomassa aanwasverdeling van de Groveden Hogeschool Larenstein 37 Wijk M N van M J Schelhaas et al 1999 Effecten van een veranderend bosbeheer op de houtkwaliteit een methode om de invloed van veranderingen in het beheer op de houtkwaliteit te bekijken toegepast op douglas Wageningen IBN DLO Instituut voor Bos en Natuuronderzoek Alterra rapport 1068 doc 103 Valero E and Picos J 2002 Estudio de la Influencia de la Selvicultura en la Fijaci n de CO2 de un Eucaliptal tipo en Galicia mediante el modelo CO2fix Catedra Ence University of Vigo Valero E and Picos J in prep Biomass and carbon storage of Galician Eucalyptus plantations Field results vs CO2Fix model output Submitted to Forest Ecology and Management Vanclay J K 1989 A growth model for North Queensland rainforests Forest Ecology and Management 27 245 271 Vleeshouwers L M Verhagen A 2002 Carbon emission and sequestration by agricultural land use a model study for Europe Glob
82. he tree will make foliage which is then eaten by the insects However in CO2FIX it is not possible to remove the foliage directly at least not in one simulation However it is possible to decrease the allocation to foliage to simulate a reduced amount of biomass in a certain period In the example scenario Foliage feeder a foliage feeding insect occurs at year 41 and 42 simulated by a zero allocation to foliage Figure 5 6 Some mortality occurs during and afterwards of the defoliation analogue to the fire case see Figure 5 4 Also the increment is affected Figure 5 7 Pests affecting branches or roots could be simulated in a similar way by adapting their respective allocation figures A more realistic way to simulate defoliation would be to initialise a new simulation at the moment of defoliation and reducing the amount of foliage biomass as needed The fine litter component should then be increased to simulate increased litter fall and excrements of the insects However this will have only minor effects on the total simulated carbon stocks in the soil 92 Alterra rapport 1068 doc Biomass Stems Foliage Branches Roots Mortality Competition Management mortality ThinningHarvest Scenario Foliage feeder w Cohort FOLIAGE GROWTH TABLE Carbon content MgC MgDM 5 Initial carbon MgC ha o Growth correction factor fi Tumover rate 1 yr 5 0 20 30 wo D 70 80 0 100 1
83. her with turnover rates of these compartments the stocks of carbon in the foliage branches and roots are simulated Note that when you click Apply or OK the simulation is immediately updated The growth correction factor makes it possible to apply a defined case study to a site of different fertility where allocation to roots and foliage may be higher In that case it is avoided that the parameterisation of the complete case study needs to be done again 42 Alterra rapport 1068 doc Stems Foliage Branches Roots Mortality Competition Management mortality ThinningHarvest Scenario Scenario 1 Cohort Pine y Carbon content MaC MaDM 0 5 Relative growth BRANCHES GROWTH TABLE 1 Initial carbon MaC ha fe Growth correction factor fi 0 o Turmover rate 12yr 0 02 14 0 15 D 18 0 15 o 22 0 2 O 2D 40 wD BD 100 120 140 160 120 200 za gt jp z Cancel Apply Help Figure 3 9 Branches parameterisation screen in main menu biomass Note also that there is no separate compartment for coarse roots and fine roots This has implications for the turnover rate of the root compartment Generally the turnover of fine roots is much higher than coarse roots but the biomass of coarse roots increases during a rotation whereas the biomass in fine roots shows less variation In case of short rotations there will be relatively more fine roots than in case of long rotations Since turnov
84. iled a dataset with Scots pine biomass data from all over Europe and derived regressions of foliage branches stem and root biomass on breast height diameter of individual trees We applied the resulting relationships to the yield table data to obtain individual tree biomass of these compartments Multiplication with the stem number yielded estimates of total biomass in these compartments for 5 year intervals Figure 4 1 Subsequently the allocation parameters for foliage and branches at various ages were set to 1 and changed by trial error to match as good as possible to the biomass curves Figure 4 1 In order to do this we first need the initial biomass carbon content and the turnover coefficients Initial biomass is set again as zero and carbon content at 0 5 For branch turnover we took a coefficient of 0 03 rather arbitrarily For foliage we know that in general two needle classes are present for Scots pine Janssens et al 1999 own observations this year s needles and last year s needles If we assume hypothetically that the same amount of foliage is produced each year the total amount of foliage should be twice as much Therefore we take a turnover coefficient of 0 5 for the foliage since s x lim 970 5 2 The growth correction factor is set at 1 since we derive specific allocation curves for each growth class Later on these allocation curves could perhaps be combined to one general curve for Scots pine which can be adjusted by
85. ing approach to below ground carbon allocation in temperate forests Plant and Soil 229 2 281 293 Reed K L 1980 An ecological approach to modeling the growth of forest trees Forest Science 26 33 50 Richards G 2001 The FULLCAM carbon accounting model development calibration and implementation for the national carbon accounting system Technical report 28 Australian Greenhouse Office Richards G and D Evans 2000 Carbon accounting model for forests CAMFOR user manual version 3 35 Canberra Australia Australian greenhouse Office 56 p Soerianegara Lemmens R H M J 1993 Plant Resources of South East Asia No 5 1 timber trees major commercial timbers PROSEA Project Pudoc Scientific Publishers Wageningen Netherlands 610 p Sosej M S M Hing L T Prawirohatmodjo S 1998 Plant resources of South East Asia No 5 3 timber trees lesser known timbers PROSEA project Backhuys Publishers Leiden The Netherlands 859 p Staatsbosbeheer 2000 Normenboek Staatsbosbeheer 2000 2001 normen voor uitvoering van werkzaamheden in bosbouw natuurbeheer en landschapsverzorging Driebergen Staatsbosbeheer 138 p Sykes M T Prentice 1 C Cramer W 1996 A bioclimatic model for the potential distributions of North European tree species under present and future climates Journal of Biogeography 23 203 233 Tarasov M E and R A Birdsey 2001 Decay rate and potential storage of coearse woody debris in t
86. interface of the model is not yet able to show these negative values since the x axis is fixed at the bottom of the graph CO2Fix pine_oak co2 BEE d Fie Edit View Data Window Help 18 x Dd 301242 tft Ae E x BIOMASS COMPONENTS Scenario 1 carbon MgC ha 1257 1004 1 o 20 4 60 20 100 120 140 160 180 200 220 Scenario 1 stems Scenario 1 foliage Scenario l branches Scenario 1 roots For Help press F1 NUM Figure 3 41 Example of a ready made view option showing carbon stocks in each of the main carbon pools 70 Alterra rapport 1068 doc Options for Chart output fo SSC o EUNE f CAI gt 2 9 2 o 2 o 2 Figure 3 42 Options to change the content of the ready made charts Alterra rapport 1068 doc Scenario SS 71 4 1 Introduction Example parameterisations Together with the CO2FIX V 3 1 model a couple of example files are provided These cases are parameterised by the CASFOR team and can serve the user as a basis for his own parameterisations and as an example how the different modules and options can be used We have tried to include a range of examples that covers all aspects of the CO2FIX V 3 1 model and a range of different countries and regions as well Table 4 1 gives a summary of the examples indicating their location tree species and modules and approaches used In the followin
87. iod of five months during which drought is experienced In the wet tropics this term is not important because decomposition is fast in any case because of high Alterra rapport 1068 doc 23 temperatures If the user assumes no drought effects on decomposition he she should use a precipitation deficit value equal to 0 mm in the model The model has so far been validated in the northern hemisphere only Summer drought D is calculated as summer precipitation minus potential evapotranspiration PET The soil carbon module was calibrated using PET values calculated using the Priestley Taylor equation and the algorithms of the BIOM model Sykes et al 1996 For the CO2FIX users a simple spreadsheet program was made that calculates the PET according to the Thorthwaite method According to tests carried out this will only cause minor differences in the results 2 3 3 Parameter values Parameter values have been determined for the chosen standard conditions prevailing in southern Finland and middle Sweden T 1903 C days D 32 mm Table 2 1 Equation 21 and 22 are used to modify these values to the parameter values for other conditions Different kind of data have been used to determine the parameter values The decomposition rates of the extractives the celluloses and the lignin like compounds and the transfer fractions of decomposed matter between the compartments ate based on data from litter bag experiments Berg et al 1991 Decom
88. is not available a typical situation for tropical natural forests the mortality can be modelled as a function of relative cohort biomass The mortality fraction is applied equally to all living biomass compartments stems foliage branches and roots 2 2 4 Turnover In addition to tree mortality an accurate estimation of carbon dynamics in the other biomass compartments needs to account for the turnover of foliage branches and roots of the remaining trees This turnover is also very important to adequately model the carbon dynamics of soil organic matter We model the turnover for each cohort T as the sum of the turnovers of each component 4 which in turn is simply the existing biomass of the particular component multiplied by a decay or turnover constant Kt Mathematically T Bat Ke Mg C ha 10 where Kt ranges between 1 i e all the component biomass is lost during the year to 0 There is no separate compartment for coarse roots and fine roots This has implications for the turnover rate of the root compartment Generally the turnover of fine roots is much higher than coarse roots but the biomass of coarse roots increases during a rotation whereas the biomass in fine roots shows less variation In case of short rotations there will be relatively more fine roots than in case of long rotations Since turnover of fine roots is higher total root turnover should be higher under short rotations than under lon
89. it contains the parameters for the recycling process Figure 3 28 The top part of the window allows parameterisation of the recycling between groups of life spans A product can only be recycled to the same life span category or lower The rows should sum to one since the fraction that is recycled is defined earlier these parameters concern only the allocation over the different life spans The bottom part of the window provides the parameterisation of life spans of the three product groups the landfill and millsite dump An exponential discard decay over time is used in CO2FIX V 3 1 Figure 2 4 The life span parameter defines the half life so a life span of 15 years means that after 15 years 50 of the original amount of carbon is left On average the life span will then also be 15 years For the product groups the end of life can result in recycling using the wood as fire wood bioenergy or dumping the wood in a landfill For the millsite dump and for the landfill end of life will result in the actual release of carbon 58 Alterra rapport 1068 doc Figure 3 28 Parameterising the products module way of recycling and life spans 3 6 5 Default parameters Under the Default parameters tab two sets of default parameters can be loaded Figure 3 29 These ate a high and a low processing efficiency parameter set Further own parameter sets can be saved here for use in other scenarios and case studies With the Load button
90. itial mortality is high during the first years after the logging and the mortality decreases gradually reaching zero in 10 20 years depending on the forest type and technology used Pinard and Putz 1997 In the CO2FIX model we use a logging damage mortality coefficient Kl as a linear function of time years after logging p with three parameters a initial mortality Mo b duration of the damage r and c intensity of the initial logging Io Mathematically MI B Kl Mg C ha 12 whete KI f Up Mois p Mg C ha 13 2 3 Soil module 2 3 1 Applicability The dynamic soil carbon model Yasso Liski et al in prep http www efi fi projects yasso is used as the soil module of CO2FIX The model describes decomposition and dynamics of soil carbon in well drained soils soils in which poor drainage does not slow down decomposition The current version is calibrated to describe the total stock of soil carbon without distinction between soil layers The model can be applied for both coniferous and deciduous forests It has 20 Alterra rapport 1068 doc been tested to describe appropriately the effects of climate on decomposition rates of several litter types in a wide range of ecosystems from arctic tundra to tropical rainforest Liski et al 2003a Palosuo et al in prep 2 3 2 Structure The soil module consists of three litter compartments and five decomposition compartments Figure 2 2 Litter is
91. k 2 This can be explained by the fact that this is a large stock with very long residence times Results Carbon content te stems 120 us 1 0 behaved sin y CERCAR RA 80 S on o Q Std Dev 15 45 PR 9 Mean 186 4 peepee an n 100000 5 LM gel gt a tg tg ty Ox tag AA 7 EA Ta Ta P Tx Fe TA A amp af Sr Sy Br Dy Ea A Es 5 ke D a E 7 NA AS A A A A A __ _ EZA zs Total carbon stock t c ha Figure 6 1 Results of the sensitivity analysis for carbon content in the stems Input for stem carbon content was drawn from a normal distribution with a standard deviation of 20 10 and 5 respectively 96 Alterra rapport 1068 doc References Alder D and J N M Silva 2000 An empirical cohort model for management of Terra Firme forests in the Brazilian Amazon Forest Ecology and Management 130 141 157 Beer J A Bonneman W Ch vez H W Fassbender A C Imbach and I Martel 1990 Modelling agroforestry systems of cacao Theobroma cacao with laurel Cordia alliodora or por Erythrina poeppigiana in Costa Rica Agroforestry Systems 12 229 249 Berg B H Booltink A Breymeyer A Ewertsson A Gallardo B Holm M B Johansson S Koivuoja V Meentemeyer P Nyman J Olofsson A S Pettersson A Reurslag H Staaf I Staaf and L Uba 1991 Data on needle litter decomposition and soil climate as well as site characteristics for some coniferous forest sites Part II Deco
92. l and in case of a managed forest the wood products as well as the financial costs and revenues and the carbon Alterra rapport 1068 doc 15 credits that can be earned under different accounting systems Stocks fluxes costs revenues and carbon credits are simulated at the hectare scale with time steps of one year Each of these modules is described separately in the following sections decomposition decompgqsition Figure 2 1 The modules of CO2FIX V 3 1 2 2 Biomass module 2 2 1 The cohort approach The carbon stocks and flows in the forests living biomass above and belowground are estimated using a cohort model approach Reed 1980 Each cohort is defined as a group of individual trees or species which are assumed to exhibit similar growth and which may be treated as single entities within the model Vanclay 1989 Alder and Silva 2000 These cohorts may be for example a successional groups in a natural forest e g pioneers intermediate and climax b species in a mixed forests e g mixed pine oak forests and c strata in a multi strata agroforestry system e g understory middle layer upper layer The carbon stored in living biomass Cb of the whole forest stand can then be expressed as the sum of the biomasses of each cohort i e Cb 2 Cb Mg C ha 3 where Cb is the carbon stored in the living biomass of cohort i at time Mg C ha 16 Alterra rap
93. land use change between cropland grassland wetland and or settlements or any other category The activity does not meet the requirem ents of the Kyoto protocol to fall under the Land U se Change options andis therefore not eligible to credit sequestered Carbon The activity doesnot meet the requirem ents of the Kyoto protocol to fall under the Land U se Change options and is The activity falls under therefore not eligible to credit sequestered Carbon the Land Use Land Use Change and Forestry Did your country elect options Art 3 4 of the Is the activity part of a system on which agricultural cropland management as Kyotopr tocol For the first commitment period accountable anthropogenic greenhouse gas emissions a Kyoto protocol option for the area where the activity takes place crops are grown and on land that is set aside or temporarily not being used for crop production Did your country by sources and removals lect ing land by sinks resulting from SHER RETAZVAS AAA This activity is not eligible for Carbon crediting Carbon cropland managem ent Is the activity part ofa management asa sequestration by cropland management is optionally and grazing land system of practices on land Kyoto protocol has to be elected by countries in order to be creditable management or used for livestock option for the area revegetation under where the activity takes place Article 3 4 shall be equal to anthropogenic greenh
94. le Nabuurs and Schelhaas 2002 Lettens et al 2003 Paul et al 2003 Gabus 2003 or further developed it Richards and Evans 2000 Richards 2001 In the meanwhile the model was developed further by the CASFOR team on the following points e The ability to simulate multi species and unevenaged stands in multiple cohorts e The ability to parameterise the growth also by stand density e The ability to deal with inter cohort competition e Allocation processing lines and end of life disposal of harvested wood e Soil dynamics e The ability to deal with a wider variety of forest types including agro forestry systems selective logging systems and post harvesting mortality e Output viewing charts This resulted in the release of version 2 0 in October 2001 Until November 2004 almost 2000 users from over 75 countries have downloaded it A description of the version 2 0 model can be found in Nabuurs et al 2002 and Masera et al 2003 Within the CASFOR II project the current V 3 1 has been developed The major points of improvement with regards to V 2 0 are e Inclusion of a financial module to calculate costs and revenues Alterra rapport 1068 doc 13 e Inclusion of a carbon accounting module to calculate carbon credits e Bio energy module The new version should give developers of LULUCF projects a user friendly tool to asses the amount of credits that can be earned under the different crediting schemes and to provide an
95. ll be part of the nations national Carbon 120 emission inventory Nf Didthe activity involve the permanent rem oval of trees beyond the definition criteria of forest and did it change the land use in the area from forest to one other than forest The activity falls under the Deforestation Art 3 3 options of the Kyoto protocol Under this option Deforestation activities have to be included in the national Carbon inventories Did your country elect Forest Management as a Kyoto protocol option for the area where the activity takes place Vv The activity falls under the Land Use Land U se Change and Forestry options Art 3 4 of the Kyoto protocol For the first commitment period 2008 2012 the amount of credits that can be obtained by Annex I countries from forest managem ent activities together with forest management activities under Joint Implem entation projects is bound to a maximum value CAP that is specified per Annex I country Annex Z This CAP does not apply if the sequestered Carbon compensates for possible Carbon emissionsin Afforestation Reforestation or Deforestation Art 3 3 activities up to a maximum of 9 0 Mt times5 Is the area used for other purposes or grazing land with the National IT decision tree that forest alone like crop production Please proceed The activity doesnot meet the requirements of the Kyoto protocol to fall under deforestatio
96. logies e g by replacing an old technology by a newer more efficient one The specific mitigation to be attained by a given bioenergy option per unit area depends on the following parameters e Amount of biofuels produced annually e Energy content of the biofuels and fossil fuels e Efficiency of the bioenergy and fossil fuel technology e Emission factors of the current and alternative fuel technology The production of energy from biomass releases greenhouse gases GHG other than CO which are not absorbed with plant re growth Such gases are methane CH nitrous oxide NO carbon monoxide CO and non methanogenic organic compounds INMOC A proper mitigation analysis needs to account for the difference in emissions of non CO GHG between the proposed biomass technology and the fossil fuel to be substituted For each GHG we estimate the difference between the emissions from the old and the new technology for producing the same amount of energy GHGmit Ej Ej Mg gas yr 25 where GHGmit is greenhouse gas mitigation of greenhouse gas E is emissions of greenhouse gas 4 of the fuel technology to be substituted E is emissions of greenhouse gas j of the alternative technology The emissions of the alternative technology can be calculated according to 1 Ey FI Mg gas ye 26 where FI is fuel input Mg DM yr Ea is emission factor for the alternative technology for each greenhouse gas
97. lterra rapport 1068 doc Table 5 1 Production of grassland and pastures in different regions of the world Production Mg DM ha yr Type Region Source Aboveground Belowground Cold desert steppe Parton et al 1995 0 6 0 92 Temperate steppe Parton et al 1995 0 36 0 59 central great Short grass steppe plain USA Campbell et al 2000 0 5 3 Dry savanna Parton et al 1995 0 55 0 85 Semi arid savanna Sahel Campbell et al 2000 0 5 2 5 Savanna Parton et al 1995 1 91 2 22 Tropical savanna woodland Australia Campbell et al 2000 2 Subtropical savanna Australia Campbell et al 2000 2 5 Humid savanna Parton et al 1995 3 4 3 44 Mediterranean grassland Parton et al 1995 0 79 1 03 Semi arid grassland inner Mongolia Campbell et al 2000 1 2 2 6 Savanna grassland N Australia Campbell et al 2000 0 5 3 Temperate grassland Australia Campbell et al 2000 0 5 4 Tall grass prairie Kansas USA Campbell et al 2000 3 95 Grassland Switzerland Campbell et al 2000 6 5 12 Mediterranean Vleeshouwers and Pasture Europe Verhagen 2002 3 5 8 Vleeshouwers and Pasture Central Europe Verhagen 2002 4 9 Temperate pasture Australia Campbell et al 2000 5 10 Pasture New Zealand Campbell et al 2000 6 8 Northern Vleeshouwers and Pasture Europe Verhagen 2002 6 11 Western Vleeshouwers and Pasture Europe Verhagen 2002 8 14 5 3 Coppice The CO2FIX model was originally not designed for simulating coppice systems How
98. matic representation of processes and flows in the biomass module for one cohort CO2FIX V 3 1 allows two basic approaches for modelling growth of the cohorts tree growth as a function of tree or stand age and tree growth as a function of biomass Re 1 In a situation where the age of the forest and or trees is known the growth of tree biomass is often expressed as a function of time In case of stemwood volume this is called current annual increment CAI Figure 3 5a When natural mortality is taken into account separately this should be gross annual increment Stemwood increment data are most commonly available usually in the form of yield tables Re 2 In a situation where the tree forest age is not known e g the case of tropical primary or secondary forests another approach is needed A common method in such a situation is to express growth as a function of the ratio between actual biomass and maximum attainable biomass Figure 3 5b 38 Alterra rapport 1068 doc am 3 Cohort 2 Cohort 5 20 1 Ss 1 E 1s Cohort z Cohort 2 10 2 lt 10 lt E y Cohort E 5 S N Cohort E 34 N 3 20 40 60 80 5 30 50 70 100 Age years Cohort biomass of maximum Figure 3 5a Current annual volume increment CAI of three cohorts in a forest stand as a function of cohort age Exemplary only growth will normally not decline to 0 Figure 3 5b Current annual increment CAI n ha yr of three cohorts in a forest stand as a functi
99. mperature and water availability Alterra rapport 1068 doc 21 CO2 By eo Extractives Fine roots litter A X co2 Branches Fine woody jitter y Cellulose Coarse roots NA A CO2 Stem Coarse woody SL ignin like litter compounds CO2 CO2 Figure 2 2 Flow chart of the soil model The boxes represent carbon compartments and the arrows represent carbon fluxes The dynamics of carbon in the litter Equation 13 to 15 and the decomposition compartments Equation 16 to 20 can be described as follows dx nwl _ dt U nwi a nwi X nfl 1 4 dx fol A FU py T O yi fit gt 15 dx cwl _ dt Uy T Aew A yt 1 6 dx ext __ dt gt Cawl ext A yl X awl C fl 2 ext py X iwl Cowl Ss ext Fowl X owl K ox X oxt gt 1 7 Pia k 18 dt z Cowl _cel d awi X nwl C fol W cel A fwl X fil Cowl _cel Al X owl cel Xcel gt 22 Alterra rapport 1068 doc AX ig dt Chyl _lig a nwl Xnwi C fol _lig A fol x fwl Cowl _lig Dewi X ew 1 9 PextKextXext PeelKcelXcel E Kiig Xlig dx hum _ dt PrieKiig Nig K pumi X humi gt and 20 dx hum2 _ nat dt P rum K rumi X humi K pum2X hum 21 where u t the input of litter type i to the system i non woody litter nwl fine woody litter fwl or coarse woody litter cwl xi t the weight of organic carbon in woody litter compartment i at time t i fine ot coarse woody litter ai the rate of invasion of litter i by micro
100. mpetition C relative to each Cohort T relative to Total biomass Management mortality C depends on which Cohort is harvest T depends on the Total volume harvested 73 Alterra rapport 1068 doc 4 2 Scots pine monocultures in The Netherlands 4 2 1 General This example shows a range of regularly managed Scots pine stands of different growth classes in The Netherlands files NL_Scots pine X co2 Increment data are derived from yield tables Jansen et al 1996 Five growth classes are distinguished based on the maximum mean annual increment MAJ reached during a rotation The growth classes range from 4 lowest growth class to 12 with intervals of 2 For each site class a separate CO2FIX file is set up containing one cohort of type conifers The simulation length is chosen as 100 years analogue to the yield table Growth is driven by age and no mortality and competition ate included since this is supposed to be captured in the yield table 4 2 2 Biomass Stems Firstly the current annual increment as a function of age is entered into the Stems tab from the appropriate yield table Carbon content is assumed to be 50 0 5 a value commonly used but this may be subject to variations However no detailed better information source was available Wood density is set to 0 49 Mg per m of wood Initial carbon in living biomass is set to zero since we simulate the stand from scratch Foliage branches Vaessen 2001 comp
101. mposition data 42 Sveriges Lantbruksuniversitet Institutionen for ekologi ach milj v rd Uppsala Berg B M P Berg P Bottner E Box A Breymeyer R C De Anta M Couteaux E M lk nen C McClaugherty V Meentemeyer F Mu oz P Piussi J Remacle and A V De Santo 1993 Litter mass loss in pine forests of Europe and Eastern United States some relationships with climate and litter quality Biogeochemistry 20 127 159 Berger E P J Luijt and M J Voskuilen 2003 Bedrijfsuitkomsten in de Nederlandse bosbouw over 2001 Den Haag LEI Rapport 1 03 02 74 p Bertault J G amp Kadir K 1998 Silvicultural research in a lowland mixed dipterocarp forest of East Kalimantan the contribution of STREK project CIRAD for t Montpellier France 250 p Boer R 2001 Economic Assessment of mitigation options for enhancing and maintaining carbon sink capacity in Indonesia Mit Adap Stra Gl Ch 6 257 290 Botkin D B Janak J F and Wallis J R 1972 Some ecological consequences of a computer model of forest growth J Ecol 60 pp 849 872 Brown S Gillespie A J R Lugo A E 1989 Biomass estimation methods for tropical forests with applications to forest inventory data Brown S 1997 Estimating Biomass and Biomass Change of Tropical Forests a Primer FAO Forestry Paper 134 http www fao ore docrep w4095e w4095e00 htm Contents Alterra rapport 1068 doc 97 Brown S Phillips H Voicu M Ab
102. mulate short rotation bioenergy plantations With some limitations yes These and other special applications like application to degrading grassland are explained in the new manual for V 3 1 Where can I find growth data for my simulations There is a list of yield table references at the http www efi fi projects forsce yield_tables html Is there any CO2FIX related publications available You can download the publications of the CASFOR II research team from the Results There ate also references to other publications where CO2FIX is used at the Links Alterra rapport 1068 doc 109 Is it possible that you would check my simulations This is not possible Even though another user of CO2FIX may be working on the same problem we cannot give out names of registrants either Who are the contact persons in different institutions related to project See Research team Where can I find references about biomass equations biomass turnover rates carbon content and basic wood densities Some general refs DeAngelis D L R H Gardner et al 1981 Productivity of forest ecosystems studied during the IBP the woodlands data set In Reichle D E ed Dynamic properties of forest ecosystems International Biological Programme 23 Cambridge University Press Cambridge etc pp 567 672 Cannell M G R e Ed 1982 World forest biomass and primary production data Natural Environment Research Council Institute of Terrest
103. n The activity does not meet the requirements of the Kyoto protocol This type of project is only eligible under the Kyoto protocol when the hosting country has elected this type as eligible No credits or debits can be gained by this project National II Is the activity related to a land use change The activity does not meet the requirements of the Kyoto between cropland grassland wetland and or protocol to fall under the Land Use Change options andis settlements or any other category therefore not el e to credit sequestered Carbon The activity doesnot meet the requirements of the Kyoto protocol to fall under the Land U se Change options and is therefore not eligible to credit sequestered C arbon Did your country elect cropland management as a Kyoto protocol option for the area where the activity takes place Is the activity part of a system on which agricultural crops are grown and on land that is set aside or temporarily not being used for crop production Did your country elect grazing land management as a Kyoto protocol This activity is not eligble for Carbon crediting Carbon sequestration by cropland management is optionally and has to be elected by countries in order to be creditable Is the activity part of a system of practices on land option for the area where the activity used for livestock production aimed at manipulating the amount and type of vegetation and livestock
104. n they work with a much shorter timestep depending on the timestep of available weather data With these formulas we can calculate at any age the fractions of above and belowground allocation as well as their ratio From the earlier derived parametrisation of foliage and branches relative growth of foliage F branches F and stems F 1 is known The relative growth of roots F can then be expressed as BG frac F U4 F F 7 frac Alterra rapport 1068 doc 75 Carbon content is again set at 0 5 and initial carbon at 0 The turnover coefficients is more difficult to determine Rasse 2001 give a fine root turnover of 1 and a coarse root turnover of 0 02 However CO2FIX does not distinguish between fine and coatse roots Therefore we try to calculate an average turnover However young stands have a high proportion of fine roots and therefore a high turnover whereas old stands have relatively much coarse roots and a correspondingly low turnover so overall root turnover should decrease with time From the output of CO2FIX we can determine how much carbon in absolute quantity is allocated to the stem and from our own calculations we know the relative growth rate of the roots at various ages When we combine these we can calculate for each year the absolute quantity of catbon allocated to the roots According to Rasse 2001 during the leaf expansion phases in spring all below ground assimiliates are allocated to the fine roots
105. n or reforestation project activity under the CDM for which it was issued An ICER can be used in the commitment period for which it was issued It cannot be carried over to subsequent commitment periods When expired it must be replaced in full If an ICER is reversed then it must be replaced in the current commitment period The crediting period can be 20 or 30 years and can be extended once in the case of a period of 30 years and extended twice in case of a period of 20 years leading to a maximum crediting period of 60 years Alterra rapport 1068 doc 65 The difference between tCERs and ICERs is that tCERs are valid only until the end of the next commitment period whereas ICERs are valid until the end of the crediting period If the net sequestration is monotonically increasing then there ate always credits being generated Figure 3 35 If there is a period of net loss of carbon during the crediting period e g due to harvesting then there is the potential for reversal of ICERs Figure 3 36 and 3 37 The project proponent may decide to sell all ICERs issued but may have to offer a discount for ICERs that will be reversed before the end of the crediting period Figure 3 36 Alternatively the project proponent may choose to retire or not sell the ICERs that would be reversed in the next period Figure 3 37 This would mean that they would not need to be replaced All tCERs can be sold regardless of the potential loss of carbon ENCOF
106. n order to be creditable Alterra rapport 1068 doc Joint Implementation I The activity does not meet N the requirements of the Kyoto protocol to fall under Afforestation or Reforestation options and is therefore not eligible to credit sequestered Carbon Is the activity that you employ related to forest management or to land use change to or from forest Please proceed with the Joint Implementation IT decision tree Was the area without forest clear cut the 31st of December 19897 Was the land use in the area for 50 years or more different to that of forest Was the land use in the area where the activity takes place forest before the activity was implemented The activity is an Afforestation or Reforestation Art 3 3 option of the Kyoto protocol under the Joint Implem entation art 6 provision Sequestered C arbon can be credited by Annex I countries Emission reduction units for these activities can only be transferred to an other Annex I country when the quantified emission limitation or reduction commitment is already realised by the hosting country Did the activity involve the permanent removal of trees beyond the definition criteria of forest and didit change the land use in the area from forest to one other than forest The activity doesnot meet the requirements of the Kyoto protocol The activity falls under the Deforestation
107. nburn of newly exposed trees These can be simulated in the same way as mortality after a fire see for example Figure 5 4 Effects on the increment can be simulated similarly to the fire case In the storm example no effects on the increment Alterra rapport 1068 doc 91 are assumed The thinning at year 85 is cancelled but further no effects on the regular management are assumed Fire or storm damage might also be connected with higher costs for example higher harvesting costs due to dangerous situations or costs for fire fighting These can be specified in the financial module Biomass x Stems Foliage Branches Roots Mortality Competition Management mortality Thinning Harvest Rotation length yr fi 00 Scenario Storm X Age Fraction Stems Branches Branches Branches Foliage Slash yr Removed LogWood PulpPap LogWood PulpPap Firewood Cancel Apply Help Figure 5 5 Parameterisation of storm damage in year 81 that uprooted or broke 30 of the stems 5 6 Pests and diseases Pests and diseases can cause damage to leaves branches and roots or can even cause mortality In this example we discuss two cases an outbreak of insects that feed on the foliage and an outbreak of bark beetles The example file is called pests co2 Again we take the Scots pine 8 as a basis In CO2FIX a pest affecting the foliage can be simulated by adjusting the foliage allocation In reality t
108. nd or the bioenergy module 3 6 2 Production line The first tab Production l ne contains the parameters for the processes of raw material allocation and process losses Figure 3 26 The top part of the window 56 Alterra rapport 1068 doc concerns the raw material allocation Pulpwood and logwood ate distributed to the commodities sawnwood boards amp panels pulp amp paper and bioenergy The firewood bioenergy value is automatically updated in such a way that the sum of the fractions is 1 In the bottom part of the window the user can specify what happens with the process losses within the production line of each commodity Process losses can be re used in lower grade production lines can be used as firewood bioenerey or can be dumped at the mill site The total of the fractions in each line is the total process loss so 1 minus this total is the processing efficiency Production line End products Recycling ife span Default parameters Scenario Scenario 1 y m Raw material allocation Raw FRACTION TO PRODUCTION LINE MATERIAL Sawnwood Boards Paper Firewood Lowood ff fo p Momm Pulpwood po p Mo m Process losses PRODUC FRACTION LOST IN PROCESS REALLOCATED TO TION LINE Boards Paper Firewood Mill site dump Sawnwood fo foio 0 20 b2 Boards 0 05 b2 for Paper for foo Firewood fo o0 Figure 3 26 Parameterising the products module raw material allocation and processing losses 3 6 3
109. ner Mr T Eggers Ms T Vil n Ms T Palosuo amp Dr J Liski European Forest Institute EFT Finland jari liski efi fi 1 Current address Wageningen University and Research Centre Tropical Nature Conservation and Vertebrate Ecology Group The Netherlands 2El Colegio de la Frontera Sur Unidad Villahermosa M xico bjong vhs ecosur mx 3 Current address Center for International Forestry Research CIFOR Indonesia m kanninen cgiar org 4 Current address Finnish Environment Institute Finland jariliski ymparisto fi Contents Dedication Acknowledgements Disclaimer Summaty 1 2 Introduction Conceptual description 2 1 22 2 3 2 4 2 5 2 6 2 7 Model structure Biomass module 2 2 1 The cohort approach 2 2 2 Biomass growth 2 2 3 Tree mortality due to senescence 2 2 4 Turnover 2 2 5 Harvesting 2 2 6 Mortality due to logging harvesting damage Soil module 2 3 1 Applicability 2 3 2 Structure 2 3 3 Parameter values Products module Bioenergy module 2 5 1 Background 2 5 2 Calculation of GHG mitigation Forest financial module Carbon accounting module 2 7 1 Introduction 2 7 2 Stock change approach 2 7 3 Temporary crediting approach 2 7 4 Long term crediting approach 2 7 5 Kyoto assist tree How to use the model 3 1 3 2 3 3 3 4 Introduction How to obtain the model Main menu and General parameters Biomass module 3 4 1 The cohort approach 3 4 2 Stemwood
110. ng environment The model is divided in six main modules Figure 2 1 e biomass module e soil module e products module e bioenergy module e financial module e carbon accounting module The total carbon physically stored in the system at any time CT is considered to be CT Cb Cs Cp Mg C ha 1 where Cb is the total carbon stored in living above plus belowground biomass at any time Mg C ha Cs is the carbon stored in soil organic matter Mg C ha and Cp is the carbon stored in wood products Mg C ha The bioenergy module does not represent a carbon stock but calculates the effect of using wood or wood waste for the generation of energy In that case fossil fuels are replaced by CO neutral fuels and can thus be regarded as an avoided emission These avoided emissions can be expressed in carbon equivalents and added to the total stock in the system to calculate the total effect of the simulation on the atmosphere A CTt Cbio MgC ha 2 where A is total atmospheric effect and Cbio is avoided emissions due to bioenergy use The carbon accounting module keeps track of all fluxes to and from the atmosphere and determines the effects of the chosen scenarios using different carbon accounting approaches The financial module uses costs and revenues of management interventions to determine the financial profitably of the different scenarios The model simulates stocks and fluxes of carbon in trees soi
111. o The answer then leads to another question or to a result Positive result This shape contains a positive result based on the answers to the previous questions The shape will also contain an explanation of the modalities and regulations of the Kyoto protocol that apply to the activity that is assessed Negative result This shape contains a negative result based on the answers to the previous questions The shape will also contain an explanation of the reason why the assessed activity is not eligible under the Kyoto protocol L Alterra rapport 1068 doc 119 Is the activity that you employ related to forest management or to land use change to or from forest Please proceed with the National I decision tree National I The activity doesnot meet the requirements of the A Was th Was the land use in the area Anac ana Was the land use in the area where the activity fon5Uyearsionm ore without forest clear pa ey ores takes place forest before the activity was different to that of forest cut the 31st of Reforestation options and implemented December 1989 is therefore not eligible to credit sequestered Carbon The activity falls under the Afforestation Reforestation and Deforestation Art 3 3 options of the Kyoto protocol Under this option Reforestation and Afforestation activities can be credited completely by Annex I countries The C arbon that is sequestered through this activity wi
112. o the atmosphere the CO that was absorbed as the plants grew and there is no net release of CO if the cycle of growth and harvest is sustained see Figure 2 5 In other words sustainably produced biomass is CO neutral However if a forest area is harvested and not replanted or is permanently lost due to natural events like fire or disease then the CO emitted by bio energy is not captured again and the CO emissions associated to the bioenergy option should be accounted for Figure 2 5 Carbon cycle of a bioenergy power plant Source IEA Bioenergy 2001 Substituting sustainably produced bioenergy for fossil fuels is a way of mitigating greenhouse gas emissions to the atmosphere In contrast with carbon storage within the forest the carbon benefits provided by bioenergy substituting for fossil fuels are irreversible even if the bioenergy scheme only operates for a fixed period Within the CO2FIX model two types of biomass fuel are considered one resulting from industrial residues such as discarded products losses during processing and one from slash that is removed from the forest site For both processes different baseline and substituting technologies and fuels can be specified 28 Alterra rapport 1068 doc 2 5 2 Calculation of GHG mitigation There are two general ways of mitigating carbon emissions by using bioenergy a Substituting fossil fuels by biomass and b Improving the characteristics of the existing biomass techno
113. olume data are available published data of forests under similar ecological conditions should be consulted Brown 1997 gives an overview on biomass estimation in the tropics including many tables with biomass data It also includes a long annex with wood densities for tropical species Further the Global Forest Resource Assessment FAO 2001 is a valuable source of information on biomass parameters Age dependent increment can be found in yield tables Yield tables are usually available for most species that are planted in commercial plantations An overview of European yield tables can be found at http www efi fi projects forsce yield_tables html 40 Alterra rapport 1068 doc Biomass Figure 3 7 Stems parameterisation screen in main menu Biomass 3 4 3 Biomass growth and turnover of foliage branches and roots The biomass growth of foliage branches and roots are expressed as fractions relative to the growth rate of the stem biomass These fractions are additional to the stem biomass production Relative fractions can change with age or with the ratio actual biomass over maximum biomass depending on the growth method in question Figure 3 8 B F B where F is relative biomass allocation coefficient F for foliage F for branches F for roots B is growth of biomass B for foliage B for branches B for roots B is growth of stem biomass Alterra rapport 1068 doc 41
114. on The first step consists of the creation of a new case study or of opening an already existing one When a case study is opened all menu options and icons will be active Figure 3 1 YY CO2Fix Central Mexico_Pine Dak co2 43 File Edit view Data Window Help Figure 3 1 Main menu options and icons Alterra rapport 1068 doc 35 From left to right the icons show alternatively the drop down menus File Edit etc can be used as well Six standard windows icons Seven icons for the seven main menus for parameterisation general parameters biomass module soil module products module carbon accounting module and financial module New window icon that allows you to open multiple case studies at the same time Six icons to view output in different ways About icon Within this manual we will mostly follow the Pine Oak case study to illustrate the various in and output options This is an example of an unevenaged mixed stand of Pine Pinus spp and Oak Quercus spp characteristic of the highlands of Central Mexico When you click on the General parameters icon a dialogue screen will appear containing four tabs Comments Scenario General Parameters and Cohorts In the Comments tab any written information can be specified such as origin of data location of case study etcetera The Scenario tab is a new feature in V 3 1 and allows the definition of different scenarios for the same ca
115. on of cohort biomass Exemplary only growth will normally not decline to 0 The growth method to be applied in the simulation can be chosen in the General Parameters main menu tab General Parameters Figure 3 6 The growth method chosen will be applied to all cohorts and all scenarios within the simulation If growth as a function of aboveground biomass is chosen the box Maximum biomass in the stand should be filled in as well As a guidance to maximum biomass data Table 3 1 is provided Other options in this tab are the choice of competition method the way management mortality is included and how long the simulation should run The options on competition and management mortality are explained later on in this chapter General Parameters x Comments Scenario General Parameters Cohorts Simulation length yr jan Maximum biomass in the stand Mg ha 400 rowth as a function of Age C Above ground biomass Competition relative to The total biomass in the stand C Each cohort Depends on which cohort is harvested Depends only on the total volume harvest m Optional modules TF Exclude Products FT Exclude Bioenergy Cancel Ape Hep Figure 3 6 General Parameters screen in main menu General Parameters with in this case growth as a Junction of age Alterra rapport 1068 doc 39 Table 3 1 Current average standing biomass tonnes dry matter per ha in different
116. other cohorts In CO2FIX interaction is expressed as a parameter that modifies the current annual increment as it is given in the stem compartment This growth modifier describes the influence of other individuals in the same cohort or the influence of other cohorts on the growth of the cohort in question In Figure 3 15 we have three cases of interaction Case 1 shows no competition i e no growth reduction occurs at any stand density This is the model default In that case any kind of competition is assumed to be included already in the yield table data Case 2 shows no competition as long as the actual biomass is less than 50 of the maximum attainable biomass At higher densities competition increases and the growth modifier decreases from 1 to 0 4 This is a typical situation for many forest stands Case 3 shows an increase of the growth modifier up to 1 2 at low densities but decreases at higher densities Here we have synergy there is a certain range of stand density e g a mixture of two cohorts where the growth is higher in the mixture than in the case of each cohort separately This may be relevant in multi species and multi strata situations e g Beer et al 1990 Alterra rapport 1068 doc 47 Growth modifier 20 40 80 100 Stand biomass of maximum Figure 3 15 Growth modifier as a function of total stand biomass Mg ha in three cases Within CO2FIX there are two options to define the growth modifier a
117. ots pine stands in The Netherlands are planted on former driftsands and heathlands about 100 years ago so they will still be accumulating carbon nowadays 4 2 4 Products For the products compartment we took the high processing and recycling efficiency default as basis with some changes Overall the quality of Dutch Scots pine is not very good Jansen 1999 so we lowered the proportion of Logwood allocated to sawnwood to 35 and increased the fraction of boards to 45 According to Heidemij 1980 half of the pulpwood production in 1976 was for paper so we assume 45 for boards and 45 for paper with 10 loss to firewood Further we lowered the amount of products ending up in landfills to 5 since landfilling is not so common in The Netherlands Most of the discarded products are being burned so the fraction used for energy is increased accordingly 4 2 5 Financial module Recurring costs are derived from statistical data as derived from forest enterprises by Berger et al 2003 and consist out of 28 ha yr for levies taxes and contributions 19 ha yr for infrastructure and 43 ha yr for management and supervision Costs for silvicultural measures are derived from cost standards from the Dutch State Forestry Service Staatsbosbeheer 2000 The costs for stand establishment 4500 transplants per ha ate in total 3593 per ha consisting of 502 per ha for ground preparation 194 per ha for unloadin
118. ouse gas emissions by sources production aimed at manipulating the amount and type of vegetation and livestock produced This activity is not eligble for Carbon crediting Carbon and removals by sinks in sequestration by grazing land management is optionally and the commitment period has to be elected by countries in order to be creditable less five tim es the anthropogenic Is the activity a direct human induced activity to increase Carbon stocks on sites through the establishment of vegetation that covers a minimum area of 0 05 and that does not meet the definition of Afforestation Reforestation Forest Management Cropland Management or Grassland Management greenhouse gas emissions by sources and removals by sinks resulting from these eligible activitiesin the base year of that Party while avoiding double accounting Did your country elect revegetation as a Kyoto protocol option for the area where the activity takes place This activity is not eligible for Carbon crediting Carbon sequestration by revegetation is optionally and has to be elected by countriesin order to be creditable This activity is not eligible for Carbon crediting Alterra rapport 1068 doc 121 Clean Development Mechanism CDM The activity isnot eligible under theKyoto protocol Under Art 12 CDM activities aiming at the prevention of deforestation or activities that aim at improving C arbon sequestration in forests
119. petition In gap models growth modifiers are used for this purpose Botkin et al 1972 It is assumed that trees grow at a maximum rate under optimal conditions but that this growth can be affected by biotic and abiotic conditions of the environment In growth and yield models the growth modifier is usually defined as a function of stand basal area or as a function of other variables indicating stocking density of the stand Peng 2000 Monserud and Sterba 1996 The modifier values range from 0 no growth at all via 1 1 e growth is not reduced to more than 1 when there are synergic effects i e where growth is higher in the mixture than in the case of each cohort alone This is relevant for multi species and multi strata situations e g Beer et al 1990 In this model a single parameter Mg is used to simulate the influence of the same cohort or the influence of other cohorts on the growth of the cohort in question Mg is defined as a function of total biomass of the stand The model provides two basic options for modelling the interactions between and within the cohorts a Competition of a cohort as a function of total stand biomass 1 e total aboveground biomass of all cohorts in a stand at any time B Mg DM ha relative to the maximum total stand biomass of all cohorts Bax in Mg DM ha In this case the interactions of this cohort with all the cohorts combined including the cohort in question is modelle
120. port 1068 doc For each new time step Cb is calculated as the balance between the original biomass plus biomass growth Gb minus the turnover of branches foliage and roots T minus tree mortality due to senescence Ms minus harvest H minus mortality due to logging Ml Le Cb gt Cb Kc Gb Ms gt Ti H z MI MgC ha 4 where Kc is a constant to convert biomass to carbon content Mg C per Mg biomass dry weight 2 2 2 Biomass growth CO2FIX distinguishes four tree biomass compartments stem including bark foliage branches and roots In order to simulate Gb the model uses as input the growth rate of stem volumes gross annual increment which can be derived from yield tables From this growth rate of stem volumes growth rates for foliage branches and roots are calculated using time dependent allocation coefficients Hence the model uses stem volume growth in m ha yr as the main input and uses an allometric approach to derive biomass increment of the main biomass components from stem volume growth These growth rates are later modified by the interactions of the cohort within itself and with other cohorts To adjust for differences in site quality yield tables dertved for good medium and poor site conditions may be used and other growth related parameters modified accordingly Nabuurs and Mohren 1995 Mathematically Gb Kv Ys 1 2 F Mg Mg ha yr 5 where Ky
121. position rates of humus ate based on data on soil carbon accumulation on a 5500 year soil chronosequence Liski et al 1998 The invasion rates of woody litter by microbes ate based on data on decay of logs Tarasov and Birdsey 2001 The climatic dependencies Equation 21 and 22 were determined based on data from Berg et al 1993 The tolerance of humus decomposition on temperature is based on soil carbon measurements along a temperature gradient Liski et al 1999 24 Alterra rapport 1068 doc Table 2 1 Parameter values of the model and their estimated uncertainties under chosen standard conditions annual mean temperature 3 3 C effective temperature sum 0 C threshold 1903 C days and precipitation minus potential evapotranspiration from May to September 32 mm Parameter Value Notes Invasion rates of woody litter by microbes year Non woody litter Am 1 Fine woody litter ag 0 54 Coarse woody litter acy 0 030 or Smaller value for larger logs 20 0 077 60 cm larger value for smaller logs 5 20 cm Decomposition rates year Extractives kext 0 48 or Smaller value for conifers larger 0 82 value for deciduous plants Celluloses Kee 0 30 Lignin like compounds hig 0 22 Faster humus Khum1 0 012 Slower humus khum2 0 0012 Formation of more complex compounds in decomposition proportion of decomposed mass Extractives to lignin like 0 2 compounds Pex Celluloses to lignin like com
122. pounds 0 2 Peel Lignin like compounds to faster 0 2 humus piig Faster humus to slower humus 0 2 Phum1 The initial contents of the compartments of the soil module can be determined in two ways 1 manually just like any other input information or 2 allowing CO2FIX to calculate equilibrium contents based on litter input Among the cohort parameters the user needs to give information on chemical litter quality The concentrations of the three fractions can be measured using common laboratory methods McClaugherty et al 1985 and for many species reference values are available in literature Hakkila 1989 McClaugherty et al 1985 Trofymow et al 1995 The standard value of the temperature sensitivity for humus decomposition s is 0 6 The initial decomposition rate for soluble compounds kOsol is equal to 0 5 year for the litter of conifers and equal to 0 8 year for the litter of deciduous trees 2 4 Products module The products module tracks the carbon after harvesting In the same year as the harvest takes place several intermediate processing and allocation steps are done until the carbon resides in the end products the millsite dump or is transferred to the bioenergy module Figure 2 3 When end products are discarded at the end of their lifespan they can be recycled deposited in a landfill or they can be used for bioenergy which is taken care of in the bioenergy module Carbon is released to the atmosphe
123. pport 1068 doc 6 Accuracy of the carbon balances as simulated by CO2FIX V 3 1 Errors in forest resource projections and thus C balances have two main sources Kangas 1997 a the stochastic character of the estimated model coefficients b measurement errors in the data or lack of data used for model construction Re a In nature an enormous variability occurs This variability still exists within one clearly defined forest type and is the result of e g growth variation between years caused by weather circumstances intra species genetic differences and site quality variation This natural variability is not captured by CO2FIX because it very much relies on fixed input data from yield tables that can be seen as some sort of complete and perfectly managed forests Other stochastic events are management irregularity and risks caused by e g storm and fire These events are not captured either but can be paramettised as special cases see Chapter 5 Furthermore natural variability occurs in carbon content of dry matter basic wood density litter and humus decomposition rates When parametrising CO2FIX this variability is usually dealt with by trying to find the average or median value of a parameter Only when multiple runs are carried out in which the natural variability in e g growth rates carbon content and humus decomposition is captured then CO2FIX provides insight in this type of uncertainty Re b CO2FIX relies heavily on net ann
124. r drainage does not slow down decomposition The current version is calibrated to describe the total stock of soil carbon without distinction between soil layers The model can be applied for both coniferous and deciduous forests It has been tested to describe appropriately the effects of climate on decomposition rates of several litter types in a wide range of ecosystems from arctic tundra to tropical rainforest Liski et al 2003a Palosuo et al In prep 3 5 2 Structure The soil module consists of three litter compartments and five decomposition compartments Figure 2 2 Litter is produced in the biomass module through biomass turnover natural mortality management mortality and logging slash see biomass module for a description of these processes For the soil carbon module the litter is grouped as non woody litter foliage and fine roots fine woody litter branches and coarse roots and coarse woody litter stems and stumps Since the biomass module makes no distinction between fine and coarse roots root litter is separated into fine and coarse roots according to the proportion between branch litter and foliage litter Each of these litter compartments has a fractionation rate determining the proportion of its contents released to the decomposition compartments in a time step For the compartment of non woody litter this rate is equal to 1 which means that all of its contents are released in one time step whereas for the woody litt
125. re converted to CO2 equivalents by multiplying them with a factor 44 12 their respective molecular weights However the user must be aware that within the CO2FIX carbon accounting module leakage and greenhouse gas emissions other than CO are not taken into account Alterra rapport 1068 doc 31 2 7 2 Stock change approach The stock change method is a simple and clear way of calculating the amount of sequestered carbon In its most simple way it calculates the difference between the amount of carbon stored in year t minus the amount stored in yeat t 1 In formula Cri E CE seg t t t l 32 where C is the sequestered amount of carbon at year t and C is the amount of catbon stored at year t In real life projects credits will be issued within a certain crediting period The amount of credits that can be obtained then becomes the difference between the starting year of that period or base year tb and the last year of that period or crediting year tc In formula C Co Cy 3 3 seq tc In case a baseline is applied the amount of carbon sequestered according to this baseline has to be subtracted as well Figure 2 6 32 Alterra rapport 1068 doc Stored Carbon oD mi p a i E al 0 5 y Time n ou oD gt D 5 3 to B 5 D E TA O aa ES a a a ar mn Stock Change 0 t0 tb te Time Figure 2 6 A visual example of carbon stocks in a CD
126. re through decomposition at the millsite dump at the landfill or via the bioenergy module The products module is based on a model developed and used before by Karjalainen et al 1994 for modelling the carbon budget for the Finnish Alterra rapport 1068 doc 25 forest sector A more detailed version has been applied for the European forest sector Karjalainen et al 2002 Eggers 2002 Atmosphere A Logwood Pulpwood Removed slash Pulp amp Boards amp Sawnwood panels Paper ASIOUDOTg Millsite dump End produc O AAA AE gt long medium short term oe A e e 1 a a i gt raw material allocation ERE gt process losses K end products allocation 7 nf tet eeeeeeee gt dof life pS gt EA gt f recycling Landfill Recycling decomposition Figure 2 3 Outline of the wood products module Boxes are stocks of carbon the arrows show transfers of carbon between different phases of the chain from harvest to final allocation The distinction between logwood pulpwood and slash is done in the biomass module Stem and harvested branch biomass are the inputs to the products module Within the products module only carbon is tracked that has its origin in the biomass part so carbon added in the processing stages for instance glue are not taken into account Harvested biomass of stems and branches is
127. reproduced or published in any form or by any means or stored in a database or retrieval system without the written permission of Alterra Alterra assumes no liability for any losses resulting from the use of the research results ot recommendations in this report Alterra rapport 1068 11 2004 Disclaimer By having clicked on the I agree button when you registered for CO2FIX you have agreed to the license conditions mentioned below CO2FIX V 3 1 software can be downloaded free of charge and used exclusively for the purpose of research education or real life application in carbon sequestration projects CO2FIX V 3 1 may not be distributed to third parties in any other way than by downloading the original software from this web site CO2FIX V 3 1 software may only be used in the downloaded form Any modifications or further developments of the software can only be done after having consulted the developers Use of the model should be acknowledged in publications by making reference to both of the following publications e Schelhaas M J P W van Esch T A Groen B H J de Jong M Kanninen J Liski O Masera G M J Mohren G J Nabuurs T Palosuo L Pedroni A Vallejo T Vil n 2004 CO2FIX V 3 1 A modelling framework for quantifying carbon sequestration in forest ecosystems ALTERRA Report 1068 Wageningen The Netherlands e Masera O Garza Caligaris J F Kanninen M Karjalainen T Liski J Nabuurs G J
128. rial Ecology Academic Press London New York 391 p Attempts to bring together biomass equations and biomass expansion factors to simulate foliage branches roots ate undertaken in the COST E21 Contribution of Forests and Forestry to Mitigate Greenhouse Effects http www bib fsagx ac be coste21 Lehtonen A Sievanen R Makela A Makipaa R Korhonen K T Hokkanen T 2004 Potential litterfall of Scots pine branches in southern Finland Ecological Modelling 180 305 315 Matthews G 1993 The carbon content of trees Forestry Commission Technical paper 4 21 Forest Products Laboratory Handbook of wood and wood based materials Hemisphere Publishing Corporation New York London Rijsdijk J F Laming P B 1994 Physical and related properties of 145 timbers Kluwer Academic Publishers Dordrecht Boston London Nadelhoffer K J and Raich J W 1992 Fine root production estimates and belowground carbon allocation in forest ecosystems Ecology 73 4 1139 1147 Brown S 1997 Estimating Biomass and Biomass Change of Tropical Forests a Primer FAO Forestry Paper 134 http www fao org docrep w4095e w4095e00 htm Contents includes an appendix with wood densities for many tropical species Global Forest Resources Assessment 2000 110 Alterra rapport 1068 doc http www fao ore docrep 004 v1997e v1997e00 htm Contents Good Practice Guidance for Land Use Land Use Change and Forestry ht
129. rio instead In the Carbon stock box the compartments that will be included in the carbon crediting scheme can be specified If soil and biomass should be evaluated together here Toral should be used and in the General Parameters screen the option Exclude products should be activated Figure 3 25 In the output of the carbon accounting module the amount of sequestered carbon in the project is shown for the selected carbon stocks only and taking into account the selected baseline and mitigation scenario Since the credits are expressed in CO2 equivalents also the CO2 equivalents are shown The carbon accounting module does not take into account leakage outside the project and does not consider other greenhouse gasses than CO Results of the bioenergy module are not taken into account Within the crediting period tCERs and ICERs with and without reversal are shown as well as their respective lifespans If costs and revenues have been specified in the financial module the net present value NPV per credit will be shown as well However tCERs and ICERs can be issued for CDM afforestation or reforestation projects only For other project types the stock change approach is shown This is simply the difference between the carbon stock at a certain point in time and the start year of the crediting period Carbon Accounting Oak consery bioenergy Figure 3 40 The parameters for carbon accounting Alterra rapport 1068 do
130. rom where to download the software Downloading took too long and your connection failed Just try again on a more quiet time of the day Clicking the URL in the instant reply email that you got after registering gave the response that the page cannot be found The URL in the instant reply email that you got after registering may have truncated the URL address Make the message box wide enough so that the whole URL is on one line Alterra rapport 1068 doc 113 Annex5 Default parameters for products module Table 1 Default minimum and maximum parameter values for raw material allocation to different production lines for high processing and recycling efficiency system The sum of each row must be one Production line Sawn wood Boards Paper Firewood Raw Default Min max Default Min max Default Min max Default Min max material Logwood 0 8 0 5 1 0 0 15 0 2 1 0 0 05 0 0 1 0 0 0 Pulpwood 0 0 0 0 05 0 0 4 0 9 0 8 1 0 0 0 0 Slash 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 Table 2 Default minimum and maximum parameter values for raw material allocation to different production lines for low processing and recycling efficiency system The sum of each row must be one Production line Sawn wood Boards Paper Firewood Raw material Default Min Default Min Default Min default Min max max max max Logwood 1 1 1 0 0 0 0 0 0 0 0 0 Pulpwood 0 0 0 0 0 0 0 0 0 0 0 0 2 Slash 0 0 0 0 0 0 0 0 0 0 0 0 1 Table 3 Default minimum and
131. rs in the biomass soil and products modules a standard deviation could be specified When running the model random values were taken for these input parameters assuming a normal distribution For the Alterra rapport 1068 doc 95 sensitivity analysis all parameters were changed separately to analyse the effects on the outcomes For the uncertainty analysis all parameters were randomly drawn to determine the overall effect on the outcome As an illustration of the sensitivity analysis Figure 6 1 shows the results for the carbon content of the stems with an assumed standard deviation of 5 10 and 20 of the average For the 20 standard deviation the average total carbon stock was 186 4 Mg C ha with a 95 confidence interval of 155 5 217 3 Mg C ha So a 20 standard deviation in the input of carbon content of stems results in a 10 standard deviation in the total carbon stock per hectare Generally the outcomes of the model were most sensitive to all parameters related to the stem compartment This can be explained by two reasons Firstly the stem compartment represents one of the largest stocks in the whole system Secondly growth of the other biomass compartments is derived from stem increment and all other compartments are depending on the outcomes of the biomass module So a change in one of the stem parameters influences the results of all other calculations Further the model proved to be sensitive to the parameters concerning Humus stoc
132. rt how the density of the whole stand actual biomass over maximum biomass influences the growth of that cohort An example of option a is given in Figure 3 17 In case of option b the user can define for the cohort in the top of the window how all cohorts separately influence its growth This is also done as a function of actual biomass over maximum biomass but then for each cohort separately An example of option b is given in Figure 3 18 In the example file CR_coffee_agroforestry co2 an example of competition between cohorts for light can be found Some mote explanation about this case is given in Box 3 1 In practice there is very little information and data on interactions especially in case of natural forests In practical forestry situations these effects are already embedded in other variables such as the growth and mortality Therefore the default is no competition Figure 3 17 Competition relative to total biomass in the stand Alterra rapport 1068 doc 49 Stems Foliage Branches Roots Mortality Competition l Management mortality Thinning Harvest A Maximum above ground biomass Scenario Scenario 1 understory in the whole stand MgDM hal fo COMPETITION TABLE DN OD 04 02 03 O OS OS OF 03 05 10 14 canopy Iemedte Bio Max intermediate Figure 3 18 Competition relative to each cohort In this case is displayed how the understorey cohort is affected b
133. rudan I Blujdea V Pahontu C Vasiliy K 2002 Romania Afforestation of Degraded Agricultural Land Project Baseline Study Emission Reductions Projection and Monitoring Plans Prototype Carbon Fund Wotld Bank Washington 147 p Bruijn A de 2004 The importance of a double root compartment in CO2FIX MsC Thesis Dept Terrestrial Ecology and Nature Management Univ Wageningen 20 p Bruijn A de In prep Carbon dynamics in simulation in Malinau Research Forest Borneo Indonesia using CO2Land Wageningen University MSc thesis Cairns M A Brown S Helmer E H Baumgardner G A 1997 Root biomass allocation in the world s upland forests Oecologia 111 1 11 Camacho and Finegan 1997 Efectos del aprovechamiento forestal y el tratamiento silvicultural en un bosque humedo del noreste de Costa Rica CATIE Serie T cnica Informe t cnico No 295 38 p Campbell B D Stafford Smith D M Ash A J Fuhrer J Gifford R M Hiernaux P Howden S M Jones M B Ludwig J A Manderscheid R Morgan J A Newton P C D Nosberger J Owensby C E Soussana J F Tuba Z and ZuoZhong C 2000 A synthesis of recent global change research on pasture and rangeland production reduced uncertainties and their management implications Agriculture Ecosystems and Environment 82 39 55 Cannell M G R 1982 World Forest Biomass and Primary Production Data Academic Press London 391 p Conference of the Parties
134. s can be specified Those litterfall rates can among others be derived by parameterising and running the previous vegetation land use in CO2FIX 0 500299 12 482393 3 837766 25 797206 Figure 3 22 Soil initial stocks per compartment in the soil module Equilibrium Figure 3 23 Window to initialise soil carbon stocks through litterfall rates of the previous land use On the Cohort parameters tab is a button Yasso model parameters Under this button the user can give specific parameter values of chemical litter quality the temperature sensitivity parameter and the znitial decomposition parameter Figure 3 24 Two default sets of parameters are available one for conifers and one for broadleaves Usually these defaults are used unless site specific data are available 54 Alterra rapport 1068 doc Yasso model parameters Figure 3 24 Soil module internal parameters Alterra rapport 1068 doc 55 3 6 Products module 3 6 1 General The products module tracks the carbon after harvesting In the same year as the harvest takes place several intermediate processing and allocation steps are done until the carbon resides in the end products the millsite dump or is transferred to the bioenergy module Figure 2 3 When end products are discarded at the end of their lifespan they can be recycled deposited in a landfill or they can be used for bioenergy which is taken care of in the bioenergy module
135. s set by trial and error to suppress the increment at higher biomass densities Relative increment rates of other biomass components were balanced against the turnover and matched with data from Yamakura et al 1996 Natural tree mortality was set at 1 according to Bertauld amp Kadir 1998 Turnover rates for the tree components are frequently fairly unknown or unspecific In this study foliage turnover was set at 1 yr according to Kira amp Shidei 1967 They suggest even higher foliage turnover for tropical moist forests 1 3 1 5 yt but CO2FIX V 3 1 does not allow foliage turnover values over 1 yr Branches turnover was set at 0 10 yt according to Kira Shidei 1967 and root turnover was set at 0 10 yr according to Gill and Jackson 2000 Degree days for the soil module was obtained by multiplication of the average temperature estimated at 26 C Bertault amp Kadir 1998 with a 365 days growing Alterra rapport 1068 doc 83 season Precipitation in the growing season was set at 3789 mm according to ITTO 2002 Potential evapotranspiration in the growing season was estimated at 1500 mm Default Yasso model parameters are used The initial carbon quantities for the different tree components were estimated assuming a constant input of the different biomass components which were estimated by multiplication of the turnover coefficient with the estimations of initial carbon in the different tree components 4 11 3 Logged prim
136. s to be specified Cancel Apply Help Figure 3 39 The Kyoto Protocol ab showing the choice between different kinds of projects The first parameter in the Carbon Accounting tab is the start year for crediting period Figure 3 40 This refers to the simulation year as displayed in the output So if you start your simulation in 1985 and you want to start the crediting in 1990 year 5 should be entered here The first verification has to be within 5 years of the start of the crediting period Therefore the year of first verification is limited to a few values depending on your starting year CO2FIX will give you a warning if this requirement is not fulfilled The duration of crediting period is limited to 20 30 40 or 60 years as explained above In the next boxes the user can define which scenario to take as baseline and which as mitigation scenario A baseline scenario is not always required but depends on the type of project The user can check this under the Kyoto Protocol tab In case a baseline is required but no baseline is specified a baseline of 0 is assumed which is reported in a warning In case a baseline is not required but still selected the baseline 68 Alterra rapport 1068 doc is incorporated in the calculations but a warning will appear In case a certain scenario is selected as baseline or mitigation but is deleted in the General Parameters window Figure 3 38 the user will be forced to choose a new scena
137. s were settled as well as the eligible carbon pools Decision 19 CP 9 on Modalities and procedures for afforestation and reforestation project activities under the clean development mechanism in the first commitment period of the Kyoto Protocol FCCC CP 2003 6 Add 2 see for the exact text http unfccc int resource docs cop9 06a02 pdf The official methods are temporary credits tCERs and long term credits ICERs For projects other than CDM AR projects no official credits can be obtained yet For such projects the stock change method is recommended However there are no official accounting rules for this type of method yet The user project owner can specify during which period credits can be sold This period does not necessarily have to start at the same time as the project starts The first verification has to be carried out within five years after the start of the crediting period next verifications will take place every 5 years The crediting period can be 20 or 30 years and can be extended once in the case of a period of 30 years and extended twice in case of a period of 20 years leading to a maximum crediting period of 60 years Within CO2FIX the stock change method temporary credits and long term credits with and without reversal can be calculated Since carbon credits need to be compatible with avoided emissions they are expressed in CO2 equivalents CO For this purpose all carbon pools that are taken into account a
138. se study This is explained further in the chapter on carbon accounting The General Parameters tab allows for inserting main input data to describe the case study and the simulation methods chosen see also the chapter on the biomass module In the Cohorts tab the name and type of the cohorts to be simulated can be specified see also the chapter on the biomass module In many input screens data is entered in the form of a table Usually the data entered in these tables will be visualised in a graph next to the table During simulations CO2FIX will make linear interpolations in between the data points If the maximum value is exceeded the value of the last data point will be used 3 4 Biomass module 3 4 1 The cohort approach The biomass module of the CO2FIX model is a flexible tool that can be applied to a wide variety of forest types Besides the regular monospecies plantations it is possible to model multi species and uneven aged stands The model used here is a cohort model Reed 1980 where each cohort is defined as a group of individual trees or as a group of species which are assumed to exhibit similar growth and which may be treated as single entities within the model Vanclay 1989 Alder and Silva 2000 Each cohort has growth mortality and turnover and can be harvested Further interaction between cohorts can be defined Figure 3 2 36 Alterra rapport 1068 doc 4 4 Figure 3 2 Processes within and interac
139. sh will be added to the litter pools which is of course not according to reality In order to simulate this properly we can make a new simulation starting at the moment of the fire cohort age at start of 72 years As initial situation we take the biomass values from the first simulation just after the fire We also take the carbon amounts in all soil compartments but here we can adjust for the litter that is burned In the example we assume that all non woody litter and fine litter is burned and around 30 of the coarse litter i e 30 Mg C initially in the coarse litter compartment opposed to 45 61 in the simulation just after the fire The other compartments are not affected See Figure 5 3 The soil module does not take into account any other effects of fire that may occur like the formation of charcoal with very long lifetimes emissions of CH and volatile organic carbons or other changes that might affect decomposition Alterra rapport 1068 doc 89 MT CO2Fix fire co2 E File Edit Yiew Data Window Help OS RH SAS mh BIGHI ABE EEuw nass products nass products nass products nass products nass products nass products nass products nass products Soil Soil Soil Soil Soil Soil non w litter Fine litter coarse litter soluble holocell lignine year carbon carbon carbon carbon carbon carbon yr Macha Macha Macha Macha Macha MgC ha 70 4 40 6 55 18 44 6 43 29 51 30 56 ql 3 58 5 97 18
140. terra rapport 1068 Alterra Wageningen 2004 ABSTRACT Schelhaas M J P W van Esch T A Groen B H J de Jong M Kanninen J Liski O Masera G M Mohren G J Nabuurs T Palosuo L Pedroni A Vallejo amp T Vil n 2004 CO2FIX V 3 1 A modelling framework for quantifying carbon sequestration in forest ecosystems Wageningen Alterra Alterra rapport 1068 120 blz 60 figs 4 tables 95 refs This report describes the conceptual approach of the CO2FIX V 3 1 model as well as its implementation and numerous examples This stand level simulation model is a tool which quantifies the C stocks and fluxes in the forest biomass the soil organic matter and the wood products chain Included are also a bioenergy module a financial module and a carbon accounting module The model is applicable to many different situations afforestation projects agroforestry systems and selective logging systems The model is freely available from the web together with numerous examples The model has many users The two earlier versions of the model have been downloaded already almost 2000 times Keywords afforestation agroforestry bioenergy carbon accounting Carbon sequestration CDM forest management forest simulation model Kyoto protocol ISSN 1566 7197 2004 Alterra P O Box 47 6700 AA Wageningen The Netherlands Phone 31 317 474700 fax 31 317 419000 e mail Hinfo alterra wur nlH No part of this publication may be
141. the growth correction factor to correct for the specific growth class 74 Alterra rapport 1068 doc 14 12 10 g e E 8 x Vaessen 6 CO2FIX E gt 4 APTA a 2 0 T T T T T 1 0 20 40 60 80 100 120 Age Figure 4 1 Total biomass per hectare in branches upper line and foliage lower line as derived from yield table data combined with the functions of Vaessen 2001 compared to CO2FIX simulation results for the same biomass compartments for yield class 4 Roots In principle for the root compartment the same approach as for branches and foliage could be followed but we used a more detailed approach since more information was available Rasse 2001 developed a general model for below ground carbon allocation in temperate forests based on root shoot ratios found in literature According to their results the fraction of assimilates allocated to aboveground parts AG ia as depending on age of the stand in years is as following AG 0 47 x 1 0 GRADO fra frac The fraction of assimilates allocated to belowground parts BG as BG is then calculated fra 1 0 AG STA frac frac frac where STA is the starch fraction used to restart leaf growth of deciduous trees in the spring STAfrac for Scots pine is therefore set to 0 0 while for beech they suggest a value of 0 0 during the leaf shooting phase and 0 1 during the rest of the growing seaso
142. the specified parameter set can be loaded The Save button provides the possibility to save the current set of parameters under a new name The Update button will update the specified default set with the current parameters The Delete button will delete the selected default set Products low processing and recycling efficieny Figure 3 29 Parameterising the products module choosing sets of parameters Alterra rapport 1068 doc 59 3 7 Bioenergy module 3 7 1 General The bioenergy module calculates the carbon mitigation due to substituting biomass for fossil fuels and improving the efficiency of biomass combustion The bioenergy carbon mitigation depends on the following general parameters i Amount of biomass fuel fuelwood produced annually 1 e the input source ii Energy content of fossil and bioenergy fuel slash and industrial fuel wood iii Efficiencies and Emission factors of the current and alternative technologies 3 7 2 Input sources The annual input fuelwood for the mitigation calculation is taken from the biomass module and from the products module It is categorized as follows e Slash fuelwood the slash firewood coming from the Thinning Harvest tab from the Biomass module e Industrial residues fuelwood the raw material and process losses disposed to bioenergy at the product s Production line tab and products at their end of life disposed to Energy The two input sources may be associated
143. tion between cohorts Cohorts can be defined in the General Parameters main menu tab Cohorts The Cohorts screen allows defining per scenario the number of cohorts that form the stand the starting age of each cohort and whether it is a coniferous or broadleaved species Figure 3 3 This latter information is used to characterise the quality of the litter input to the soil module General Parameters i al Pine a conifers ha Oak 0 broadleaves Figure 3 3 Cohorts screen in main menu General Parametets 3 4 2 Stemwood growth The driving factor of each cohort in the biomass module is the stemwood production in volume per ha Figure 3 4 as this is the information that is usually readily available for most forest types Multiplication with the stemwood density and the carbon content yields carbon flux into the stemwood compartment Fluxes into the other biomass compartments roots branches foliage are determined by their growth relative to the stemwood production and their respective carbon contents Turnover of all biomass compartments is added to the soil as well as any slash that will arise due to management activities Harvested stemwood is tracked further in the products module Alterra rapport 1068 doc 37 relative growth carbon content production m carbon content wood density Products relative growth Roots carbon content Figure 3 4 Sche
144. tp www ipcc nggip iges or jp public gpglulucf gpglulucf_contents htm On the CARBODATA website references can be found to relevant soutces of information for carbon modelling http carbodat eijrc it Where can I find meteo data for the soil module http www worldclimate com Why should I register to use CO2FIX The purpose of the registration is to have insight to the user group of CO2FIX The information you have provided will be used only for internal use and will not be given to any third party With your e mail address which is obligatory in order to receive CO2FIX it is possible for us to keep you informed on major changes and or additions to CO2FIX We will do that only in seldom cases through a mailing list address Your personal email address is thereby secured What are the minimum requirements for CO2FIX to run on my computer The minimum requirements for installing the program on your personal computer are Intel 80386 processor 4 MB RAM memoty 4 MB free space on the hard disk and any Win32 operating system previously installed Alterra rapport 1068 doc 111 Annex 4 Troubleshooting Problems 1 Clicking the URL in the instant reply email that you got after registering gave the response that the page cannot be found You may have waited longer than 24 hours with downloading since the registration you did In this case just register again The instant reply email that you will get will give you the new URL f
145. ual increment data from yield tables These tables are based on long term measurement series in permanent plots and or forest inventories In these measurement series errors and or bias can occur However these errors are usually very small Both forest inventories and yield tables ate generally seen as very reliable Tomppo 1996 gives standard errors of some characteristics of the National Forest Inventory in Finland forest land area 0 4 growing stock 0 7 and increment 1 1 However where input data for CO2FIX rely on few measurements or a single series uncertainty in the predictions will increase very much This type of uncertainty especially exists in the soil pools Van der Voet in Nabuurs amp Mohren 1993 carried out an uncertainty analysis of CO2FIX V 1 0 He specified input uncertainties in the form of simultaneous input distributions for an even aged forest type The 100 simulations with randomly chosen values of input gave an average total carbon stock of 316 Mg C ha The standard deviation was 12 and the 95 confidence interval was 254 403 Mg C ha He concluded that it was mainly the litter and humus coefficients and the carbon content that determined this uncertainty but in general it was mainly the natural variability rather than a lack of data that determined the overall uncertainty Knippers et al In prep carried out a sensitivity and uncertainty analysis of an early version of CO2FIX V 3 0 For 37 input paramete
146. ues taken for a 100 yr time horizon Source IPCC 2001 Greenhouse gas Global warming potential CO2 CH4 N20 CO TNMOC 1 23 270 2 12 Table 3 Default emission factors for technologies fuelled by biomass g kg of fuel Emission factors Efficiency Technology CO CH N20 CO TNMOC Traditional Stove 13 0 9 4 0 08 64 7 9 65 Improved Cookstove 25 0 7 92 0 06 69 5 6 84 Charcoal Stove 29 0 7 8 0 08 250 10 5 Incineration high efficiency 24 0 0 4275 0 057 6 6 0 Stoker Boiler 24 0 0 225 0 8 85 0 Combustion plant lt 50MW Boilers 24 0 0 48 0 06 3 6 0 72 Combustion plant gt 50 and lt 300MW Boilers 24 0 0 48 0 06 3 6 0 72 Stationary engine 24 0 0 48 0 06 3 6 0 72 Table 4 Default emission factors for technologies fuelled by coal g kg of fuel Emission factors Technology Efficiency CO CH4 N20 CO TNMOC Cookstove 24 2550 7 98 0 0372 66 2 0 02 Stove 25 2540 75 7 98 0 0372 100 8 0 Furnace 25 2540 75 7 98 0 0372 13 44 0 Water Heater 25 2540 75 7 98 0 0372 0 504 0 Anthracite Space Heaters 25 2540 7518 6 45 0 0355 0 0 Power Plant 33 2425 15 0 0186 0 0426 0 239 0 Alterra rapport 1068 doc 117 Table 5 Default emission factors for technologies fuelled by gas oil g kg of fuel Emission factors Technology Efficiency CO CH N20 CO TNM
147. up to 40 of the remaining stand as measured in basal area Alder and Silva 2000 In many cases mortality is high during the first years after the logging and decreases gradually over a period of 10 20 years depending on the forest type the technology used and the intensity of the logging operation Pinard and Putz 1996 In CO2FIX the mortality after logging depends on the intensity of the logging operation expressed as the volume harvested per hectare The user can define the initial mortality as a fraction of standing biomass and the impact time at various logging intensities Mortality decreases linearly over time reaching zero at the end of the impact time In Figure 3 12 cases one and two the mortality due to logging damage affects the remaining stand in a similar way through time but depending on logging intensity case one 50 m case two 20 m In case three low intensity logging causes low initial mortality but the damage lasts long In case four the initial mortality is low and the impact of damage is of short duration For all cases the cumulative percentage of mortality gives an idea of the total damage to the stand In case two this amounts to about 55 D 15 Case 1 50 m3 E Case 2 20 m3 v 18 Case 3 15 m3 o e 5 Case 4 15 m3 D E 0 0 2 4 6 8 10 12 14 16 18 20 Years after logging Figure 3 12 Mortality caused by damage from logging in four hypothetical cases depending on the intensity of lo
148. y all three cohorts Box 3 1 Competition for light Canopy Intermediate i Understory 1 0 8 0 6 0 4 0 2 0 25 0 5 0 75 1 1 25 0 25 0 5 0 75 1 1 25 0 0 25 0 5 0 75 al 1 25 Ratio biomass max biomass Ratio biomass max biomass Ratio biomass max biomass Growth modifier Growth modifier Growth modifier Competition for light demonstrated for the case CR_coffee_agroforestry Three cohorts are present a canopy blue an intermediate layer green and an understory red The figures illustrate how each cohort is influenced by the presence of other cohorts The growth of the canopy left figure is only influenced by itself The presence of other layers does not affect the growth of the canopy layer The growth of the intermediate layer middle figure is influenced by itself and by the presence of a canopy layer The presence of an understory has no influence The growth of the understory is affected by all three layers The presence of a light canopy even enhances the growth of the understory 3 4 7 Management interventions harvesting Within CO2FIX two types of management interventions are possible thinning and final felling Other management activities like drainage and fertilization cannot be parameterised but their effects can be inserted by changing the current annual increment data see also special parameterisations Thinning and final felling can

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