Scenario analysis of the impacts of forest management and climate change on the European forest sector carbon budget

Forest Policy and Economics 5 (2003) 141–155

Scenario analysis of the impacts of forest management and climate change on the European forest sector carbon budget Timo Karjalainena,b,*, Ari Pussinenc, Jari Liskic,d, Gert-Jan Nabuursc,e, Thies Eggersc, f ¨ Tuija Lapvetelainen , Terhi Kaipainenc a

Finnish Forest Research Institute, Joensuu Research Centre, Yliopistokatu 7, FIN-80100 Joensuu, Finland b Faculty of Forestry, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland c European Forest Institute, Torikatu 34, FIN-80100 Joensuu, Finland d Department of Forest Ecology, University of Helsinki, P.O. Box 24, FIN-00014 Helsinki, Finland e ALTERRA, P.O. Box 47, NL-6700 AA Wageningen, The Netherlands f Ministry of Agriculture and Forestry, P.O. Box 30, FIN-00023 Government, Helsinki, Finland

Abstract Analysis of the impacts of forest management and climate change on the European forest sector carbon budget between 1990 and 2050 are presented in this article. Forest inventory based carbon budgeting with large scale scenario modelling was used. Altogether 27 countries and 128.5 million hectare of forests are included in the analysis. Two forest management and climate scenarios were applied. In Business as Usual (BaU) scenario national fellings remained at the 1990 level while in Multifunctional (MultiF) scenario fellings increased 0.5–1% per year until 2020, 4 million hectare afforestation program took place between 1990 and 2020 and forest management paid more attention to current trends towards more nature oriented management. Mean annual temperature increased 2.5 8C and annual precipitation 5–15% between 1990 and 2050 in changing climate scenario. Total amount of carbon in 1990 was 12 869 Tg, of which 94% in tree biomass and forest soil, and 6% in wood products in use. In 1995–2000, when BaU scenario was applied under current climatic conditions, net primary production was 409 Tg C yeary1, net ecosystem production 164 Tg C yeary1, net biome production 84.5 Tg C yeary1 , and net sequestration of the whole system 87.4 Tg C yeary1 which was equal to 7–8% of carbon emissions from fossil fuel combustion in 1990. Carbon stocks in tree biomass, soil and wood products increased in all applied management and climate scenarios, but slower after 2010–2020 than that before. This was due to ageing of forests and higher carbon densities per unit of forest land. Differences in carbon sequestration were very small between applied management scenarios, implying that forest management should be changed more than in this study if aim is to influence carbon sequestration. Applied climate scenarios increased carbon stocks and net carbon sequestration compared to current climatic conditions. 䊚 2003 Elsevier Science B.V. All rights reserved.

Keywords: Carbon cycle; Carbon sequestration; Forest inventory; Greenhouse effect; Scenario modelling

*Corresponding author. E-mail address: [email protected] (T. Karjalainen). 1389-9341/03/$ - see front matter 䊚 2003 Elsevier Science B.V. All rights reserved. doi:10.1016/S1389-9341(03)00021-2

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1. Introduction Carbon cycle connects forests and climate change. Forests contain large quantities of carbon, as approximately 77% of the global vegetation carbon is in tree biomass and approximately 42% of the global 1 m top soil carbon is in the forest soil (Bolin et al., 2000). Forests also exchange large quantities of carbon in photosynthesis and respiration. When forests are disturbed they become sources of carbon, and sinks of carbon when recovering and regrowing after disturbances, and thus contributing to the global carbon cycle. Over the past two decades many methods have been developed and applied to quantify terrestrial carbon sources and sinks. These methods include inversions based on atmospheric chemistry (Bousquet et al., 1999a), biogeochemical models (Schimel et al., 2000), land-use book-keeping models (Houghton et al., 1999), eddy flux tower measurements (Martin et al., 1998; Valentini et al., 2000) and forest inventories (Dixon et al., 1994; Liski and Kauppi, 2000; Nabuurs et al., 1997). Each of these methods has its strengths and weaknesses. While atmospheric inversions constrain the magnitude of terrestrial carbon sinks, they have limited ability to discern the responsible mechanisms or exact location of the observed sink. Global biogeochemical models can explore the importance of ecosystem physiological responses to climate variability or increasing CO2, but they do not yet consider natural or human-induced disturbances. In contrast, methods that focus on the effects of human-induced land-use changes are insensitive to changes in ecosystem physiology (Houghton et al., 1999). Measurements from eddy flux towers reflect one signal from all of the mechanisms affecting net ecosystem production (NEP) of a footprint area, but these local measurements at few sites do not capture the variability of carbon flux across the landscape or nation. Neither do they capture the human influence as harvesting, because measurements are carried out over a short time period only (Valentini et al., 2000). In forest inventory based carbon budgeting method stem wood volumes, increment and harvest from forest inventories and wood consumption statistics are converted to whole tree biomass carbon by multi-

plying stem wood volumes with dry wood density, biomass expansion factors and carbon content. Sometimes, this method is expanded to include also carbon in the forest soil and wood products. One advantage of forest inventory based carbon budgeting is that it provides estimates not only of the carbon stock changes but also of the size of the stocks. Furthermore, it is representative for large areas, and is based on widely accepted and established forest inventories. All of these different methods have thus produced a variety of estimates on the location and timing of the terrestrial carbon sink. Estimates for the European terrestrial biosphere net sink, based on inversion for forest and agricultural lands vary from 300 to 700 Tg C yeary1 with large uncertainties (Ciais et al., 1995; Bousquet et al., 1999a,b). In the same order of magnitude, 710"220 Tg C yeary1, is the estimate based on biogeochemical measurements and upscaling for NEP of European forests (Schulze et al., 2000). Estimates based on forest inventories suggests much smaller net sink for European forests, between 100 and 110 Tg C yeary1 (Nabuurs et al., 1997; Liski and Kauppi, 2000). Increasing concentrations of greenhouse gases in the atmosphere have already changed earth’s climate system (IPCC, 2001). Climate model projections suggest for Europe a general increase in temperature, being greatest in the northerly latitudes (Houghton et al., 2001). Changes in precipitation are considerably more uncertain, but generally wetter conditions in the north and drier conditions in the south, and increasingly drier conditions from west to east have been projected. Projected changes in climate are likely to have impact on structure and functioning of forest ecosystems and carbon sequestration in Europe and depending on the impacts it can mitigate or further accelerate climate change. 2. Aim This article provides insight how changes in forest management and climate could influence European forest sector carbon budget. Forest inventory based carbon budgeting has been applied in this study and has been expanded to include

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carbon in the forest soil and in wood products. Forest inventory data from late 1980s and early 1990s has been used as input data, i.e. approximately 1990, which is important milestone for reporting to the United Nations Framework Convention on Climate Change and also for reporting under the Kyoto Protocol. Potential impacts of changes in forest management and climate on the future development of forest resources and carbon budget are based on two forest management and climate scenarios, on a large scale scenario modelling framework developed at the European Forest Institute. Scenario analysis can be used to investigate how certain changes in forest management and forest growth can influence future development of forest resources, availability of wood raw material, and carbon sequestration in forestry. Underlying assumptions, however, in the input data, methods and scenarios should be kept in mind when interpreting the results.

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soil carbon and wood product submodels, as well as carbon book-keeping has been included in order to calculate carbon budgets of forests and wood products (Karjalainen et al., 2002). Changes in climate also influence decomposition in the soil (Liski et al., 2003). The projection of the forest growth in the model is based on growth functions that are calibrated based on the forest inventory data. Forest growth under changing climate is incorporated by scaling current forest growth with growth changes in process based model outputs. Process based models COCAyFEF (Hari, 1999; ¨ et al., Hari et al., 1999), FINNFOR (Kellomaki 1993), FORGRO (Mohren, 1987; Kramer, 1996), GOTILWA (Gracia et al., 1999), HYDRALL (Magnani et al., 2000a; Magnani, 2000b), and TREEDYN (Sonntag, 1998) were run for selected representative sites and tree species under current and changing climatic conditions. Description of the process based models and site level impact studies are provided in Kramer et al. (2002) and Kramer and Mohren (2001).

3. Method 4. Initial situation Forest inventory data and a large scale forestry model European Forest Information Scenario Model (EFISCEN) have been applied in this carbon budgeting method. EFISCEN is a forest resource model, especially suitable for large scale ()10 000 ha) and long term (20–70 years) analysis of the future state of forests under assumptions of future felling levels. The projections carried out with EFISCEN provide insight in increment, growing stock, age class distribution and actual felling per tree species. EFISCEN is an area-based forest matrix model and is based on earlier work of ¨ (1990) and Nilsson et al. (1992). This Sallnas model has been further improved, and the version used in this study, EFISCEN 2.0, is described in Pussinen et al. (2001). Analyses of the future development of forest resources in Europe and Russia have been carried out with this model (see ¨ for e.g. Nabuurs and Paivinen, 1996; Nabuurs et ¨ al., 1998; Paivinen et al., 1999). Possibility to include transient changes in forest growth has been incorporated in EFISCEN, as well as conversion of stem wood volumes to whole tree biomass and carbon, litter production, dynamic

Altogether 27 countries and 128.5 million hectare of forest land are included in this study. In 1990, average standing volume was 140 m3 hay1, ranging between 43 m3 hay1 in Spain and 393 m3 hay1 in Switzerland (Table 1). Growing stock was highest in Central European countries and lowest in Northern and Southern Europe. Growing stock in 1990 were as the initial values in the forest inventory database (Schelhaas et al., 1999), numbers for consecutive years are based on modelling with EFISCEN. Average net annual increment was 5.1 m3 hay1 yeary1, highest in Central European countries and lower in Northern and Southern Europe. Felling levels varied between countries from 0.5 m3 hay1 yeary1 in Albania to 6.3 m3 hay1 yeary1 in Belgium. In 1990, average stock of carbon in tree biomass varied from 19 to 105 Mg C hay1, average for all countries was 47 Mg C hay1 (Fig. 1) which is in good agreement with the estimate of 46 Mg C hay1 in the recent UN-ECEyFAO report (Liski and Kauppi, 2000). Total carbon stock in the 128.5 million hectare area was 6079 Tg and carbon stock change in the

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Table 1 Area of forest, average growing stem wood stock, net annual increment, fellings, and carbon stock in tree biomass for the 27 countries included in the assessment based on forest inventory data and EFISCEN Country

Albania Austria Belgium Bulgaria Croatia Czech Republic Denmark Finland France Germany Hungary Ireland Italy Luxembourg Macedonia Netherlands Norway Poland Portugal Romania Slovak Republic Slovenia Spain Sweden Switzerland United Kingdom Yugoslavia Totalyaverage

Area of Growing Net annual Fellings, forest, stock increment, m3 hay1 yeary1 1000 ha 1990, m3 hay1 yeary1 (90–95) m3 hay1 (90–95) 899 2942 531 3202 1443 2446 442 19 919 13 300 9905 1609 344 5757 71 805 304 7070 6309 1508 6211 1823 1072 13 980 22 219 1043 1898 1512

Carbon stock in trees 1990, Mg C hay1

Carbon stock in trees 1995, Mg C hay1

Total carbon stock in trees in 1990, Tg C

Carbon stock change (90–95), Tg C yeary1

68 310 220 117 117 265 144 93 143 266 192 108 141 321 56 172 86 201 76 203 228 262 43 120 393 139 85

2.0 9.8 9.0 3.2 3.1 6.7 9.6 3.8 5.8 9.0 6.9 12.2 4.2 11.2 1.9 7.8 3.2 6.5 7.3 7.2 6.2 5.4 2.2 4.5 10.3 8.4 2.9

0.5 5.3 5.9 1.4 1.3 5.7 4.9 2.7 3.9 4.1 3.3 4.3 2.3 5.1 2.2 4.1 2.1 3.3 5.2 2.6 3.2 2.7 2.2 2.8 4.8 3.6 2.1

21.4 82.1 65.1 36.3 37.2 68.3 41.1 29.7 55.2 71.9 61.8 29.1 53.9 92.0 18.6 49.5 28.5 54.1 20.8 64.4 64.6 73.3 45.2 40.7 105.1 39.9 28.2

24.4 88.7 68.0 39.2 39.8 69.7 45.3 31.7 57.6 78.4 67.4 36.7 56.5 100.9 18.0 54.7 30.4 58.1 25.3 72.1 69.2 76.2 45.4 44.0 112.5 46.4 29.3

19 242 35 116 54 167 18 592 734 712 99 10 310 7 15 15 202 341 31 400 118 79 632 904 110 76 43

0.55 3.84 0.31 1.84 0.76 0.68 0.37 8.00 6.56 12.85 1.80 0.52 2.96 0.13 y0.10 0.31 2.67 5.03 1.35 9.55 1.69 0.63 0.63 14.61 1.54 2.47 0.35

128 564 140

5.1

3.0

47.3

50.5

6079

81.9

tree biomass (net sink) was 82 Tg C yeary1, 0.6 Mg C hay1 yeary1 as an average. Carbon stocks in the soil were initialised in this study by setting the soil compartments to steady state with the input of the first 5 years (1990– 1995). This was due to the fact that there is lack of empirical data to estimate the carbon stock in the soil and in particular, the age of carbon in the soil. Situation was very similar for the wood products stock, too, since it was initialised by running the model with harvesting data from 1961 until 1990 in the wood product model. In order to have long enough time series for initialising the wood product stock, input of 1961 was used also for years 1931–1960. It should be noted that

estimates for soil carbon include carbon that originates from trees only, and therefore, underestimates total carbon in the soil. It should also be noted that carbon in wood products include carbon from homegrown wood, i.e. export and import of wood and wood products are not included in the analysis. Average carbon stock in the soil for 1990 was 47 Mg C hay1 and for wood products 6 Mg C hay1 (Table 2). If the initial stock estimates are too low, they will increase substantially with the current input and if too high, they would decrease substantially with the current input. Total amount of carbon in 1990 in those 27 countries was 12 869 Tg, of which 6079 Tg C in tree biomass (47% of the total), 6005 Tg in the

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Fig. 1. Carbon stock in tree biomass in 1990.

soil (47% of the total) and 786 Tg in wood products in use (6% of the total). Approximately 88% of the carbon stock in wood products was in long and medium long lifespan products, such as buildings and furniture, and 12% in short lifespan products, such as paper and packing materials. During the period 1990–1995, carbon stock of tree biomass was increasing by a rate of 82 Tg C yeary1, that of soil was assumed to be in equilibrium (soil was initialised with that assump-

tion), i.e. not increasing or decreasing, and carbon stock of wood products was increasing by a rate of 4.1 Tg C yeary1. 5. Forest management and climate scenarios and production of wood products To analyse the impact of climate change on forest growth and carbon budget, the output of the Hadley Centre’s Climate model 2 (HadCM2) run

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based on emission scenario IS92a (Mitchell et al., 1995) was used. This climate change scenario predicted 2.5 8C increase in mean annual temperature between 1990 and 2050 and q5 to q15% increase in annual precipitation (Erhard et al., 2001). Two scenarios for forest management were run, both under current climatic conditions and under changing climatic conditions. The scenarios were called ‘BaU’ and ‘MultiF’ management. In the BaU scenario the total national felling levels remained at the 1990 level throughout the simulation period (Fig. 2). Felling levels were specified for coniferous and deciduous tree species groups per country, separately for thinnings and final cut. Management regimes were applied as they are today and no changes in the tree species composition or in the total forest area were assumed.

Fig. 2. Simulated fellings (m3 hay1 yeary1 ) in the two scenarios. BaU is Business as Usual scenario assuming fellings to stay at level of 1990. MultiF is Multifunctional forest management scenario assuming fellings to increase 0.5–1% per year till 2020, but also biodiversity value getting more attention in forest management.

Table 2 Average carbon stock in tree biomass, soil and wood products in 1990

Albania Austria Belgium Bulgaria Croatia Czech Republic Denmark Finland France Germany Hungary Ireland Italy Luxembourg Macedonia Netherlands Norway Poland Portugal Romania Slovak Republic Slovenia Spain Sweden Switzerland United Kingdom Yugoslavia Europe

Trees, (Mg C hay1)

Soil, (Mg C hay1)

Products, (Mg C hay1)

Total, (Mg C hay1)

21.4 82.1 65.1 36.3 37.2 68.3 41.1 29.7 55.2 71.9 61.8 29.1 53.9 92.0 18.6 49.5 28.5 54.1 20.8 64.4 64.6 73.3 45.2 40.7 105.1 39.9 28.2

17.0 112.9 59.5 33.0 21.0 50.7 44.5 37.5 45.6 59.3 49.7 47.6 41.6 62.9 21.8 58.5 29.3 47.2 42.1 45.5 42.5 40.1 61.3 46.0 68.8 35.6 28.1

7.1 13.5 8.1 3.0 9.4 11.8 16.2 2.9 7.9 12.6 7.2 4.4 3.7 11.2 3.6 9.3 3.1 9.8 11.0 12.1 4.7 8.8 2.7 3.4 11.9 5.9 11.7

45.5 208.6 132.8 72.3 67.5 130.7 101.8 70.0 108.7 143.7 118.7 81.1 99.2 166.0 44.0 117.4 61.0 111.0 74.0 122.1 111.8 122.2 109.2 90.1 185.9 81.3 68.0

47.3

46.7

6.1

100.1

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This scenario addresses the question, what will happen to the European forest carbon budget if current management continues also in the future. In the MultiF scenario fellings increased with 0.3% per year during the first 30 years and stabilised then (Fig. 2). This assumption of a gradual increase in fellings reflects a combination of developments that influence demand for wood: firstly, a reduced interest of forest owners in wood production because many do not depend on the forest for their income anymore; secondly, a higher interest of forest owners in nature values of the forest; thirdly, large imports of roundwood from Russia; fourthly, continuous increase in demand for wood products, especially paper (Trømborg et al., 2000); and fifthly, a higher demand for wood because of large scale application for bioenergy. All together it was assumed that this leads to increased demand as mentioned above. Furthermore, new management regimes were adopted in this scenario in order to pay more attention to current trends in forest management towards more nature oriented management, i.e. all forests of usually more than 150 years old (depending on the country) were taken out of production. This meant initially an area of 4 million hectare, but during the simulated period, this area increased because the forest got older. Also the rotation length of all species was elongated by 20 years and the proportion of thinning out of total fellings was increased from current 30 to 45%. Tree species distribution was kept as it was in 1990. Moreover, a forest area expansion of 4 million hectare, i.e. afforestation between 1990 and 2020 was incorporated in this scenario because of marginal agricultural land being available. This scenario relates to possible forest management regimes based on the changed perception of forestry in general. Optimisation of carbon sequestration, however, was not emphasised in this scenario, although applied changes in forest management should also result in changes in carbon sequestration. Compared to BaU scenario MultiF scenario provided 3223 million m3 more fellings during the 60 year period, or as an average 54 million m3 yeary1. Total felling in 1990 was 372 million m3, of

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which the main part, equal to 77.9 Tg C, went to forest industries. In addition, forest industries is using recycled material, and total amount of carbon in the used raw material was 104 Tg. Approximately 20% of the carbon in the raw material, or 20.7 Tg, was released when raw material was processed into final products, and approximately 83.2 Tg went into final products in 1990. At the same time, approximately 80.4 Tg C was removed from use, i.e. recycled, burned to generate energy, and disposed to landfills. All in all, carbon stock of wood products in use was estimated to increase by 2.8 Tg in 1990. 6. Impact of forest management and climate change on carbon stocks Impact of applied forest management and climate change scenarios on increment, fellings and growing stock have been described in Nabuurs et al. (2002), showing higher increments than in 1990 until 2020–2030, when increments in all scenarios started to decline as a result of ageing of the forests and high growing stocks being reached. During the 60 year simulation period average carbon stock in the tree biomass in the studied 27 countries increased by 63% when BaU scenario was applied (Fig. 3). When MultiF scenario was applied, average carbon stock of the tree biomass was slightly smaller, and at the end 3% smaller than in the BaU scenario. Climate change increased average carbon stocks of the tree biomass in both scenarios and the difference between BaU and MultiF scenario remained approximately the same as under current climate, i.e. 3%. Average carbon stocks of the tree biomass were approximately 10% higher under changing climate than under current climate by 2050. Average carbon stock of the soil increased by 8% during the 60 years simulation period when BaU scenario was applied under current climate. MultiF scenario had very small impact on the average carbon stocks of the soil. Under changing climatic conditions average carbon stock of the soil was slightly smaller than under current climatic conditions due to faster decomposition of litter and soil organic matter under warmer climate.

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Fig. 3. Development of carbon stocks in trees, soil, products and total carbon stock when different scenarios were applied. BaU is Business as Usual scenario, and MultiF is multifunctional scenario.

Average carbon stock of the products increased by 16% during the 60 years simulation period when BaU scenario was applied. Since more timber was harvested in MultiF scenario during the 60 year period (3 223 million m3 more than in BaU), also carbon stock of the products was higher in the MultiF scenario, 12% higher than in the BaU scenario at the end of the simulation period. Average total carbon stock was 35% higher after 60 years simulation in the BaU scenario. In the MultiF scenario, average total carbon stock was slightly smaller (2%) than in BaU scenario. Average total carbon stocks were approximately 5% higher under changing climatic conditions than under current climatic conditions. Forest area was approximately 4 million hectare larger in the MultiF scenario by 2050 than in the BaU. Under current climatic conditions total carbon stock was 1% larger in the MultiF scenario than in the BaU scenario by 2050 (Table 3). Under changing climatic conditions all the stocks were

also 1% larger in the MultiF scenario than in the BaU scenario by 2050. 7. Impact of forest management and climate change on carbon fluxes All carbon fluxes of the forests and wood products, i.e. carbon budget for the period 1995– 2000 when BaU under current climatic conditions was applied can be seen in Fig. 4. Estimated net primary production (NPP) was 409 Tg C yeary1. Approximately 18% of the NPP was bound in the tree biomass, 20% was removed from the forest and 62% transferred into the soil as litter, natural losses, unrecovered fellings and felling residues. NEP was 164 Tg C yeary1, which is the difference between NPP and heterotrophic respiration (245 Tg C yeary1). When biomass removed from forest is subtracted from NEP, result is net biome production (NBP), 84.5 Tg C yeary1, which was 21% of the NPP. Total net sequestration of the system,

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Table 3 Total carbon stocks in trees, soil and products in 1990 and 2050 Forest area Mha

C stock in trees Tg C

1990

128.5

6079

6005

786

12 869

2050, BaU, Current climate

128.5

9955

6517

900

17 372

2050, MultiF, Current climate

132.4

9949

6558

1042

17 549

2050, BaU, Changing climate

128.5

10 946

6473

902

18 321

2050, MultiF, Changing climate

132.4

10 989

6497

1050

18 536

net sector exchange (NSE), requires that the amount that is sequestered in wood products is also taken into account (net product exchange, NPE), which was 2.8 Tg C yeary1 higher than NBP, i.e. 87.4 Tg C yeary1. Approximately 87% of the net sequestration was into the tree biomass, 10% into the soil and 3% into the products. This demonstrates that consideration of part of the system or only gross fluxes (e.g. NPP or NEP or tree biomass) provides biased estimates for carbon sequestration. For comparison, carbon emissions from fossil fuel combustion in 1990 were 1163 Tg

C stock in soil Tg C

C stock in products Tg C

Total C stock Tg C

C for 23 of the 27 countries included in this study (data for Albania, Croatia, Macedonia and Yugoslavia not available) (FCCCySBIy2000y11), i.e. forests and wood products were able to sequester 7–8% of the carbon emissions from fossil fuel combustion. As an average NPP was 3.18 Mg C hay1 yeary1, NEP 1.29 Mg C hay1 yeary1, NPE 0.02 Mg C hay1 yeary1, NBP, 0.66 Mg C hay1 yeary1 and NSE 0.69 Mg C hay1 yeary1 (Table 4). NPP values per unit of forest area were highest in Central Europe, smaller in Southern and

Fig. 4. Carbon budget of the included 27 countries, covering forest area of 128.5 million hectare, for the period 1995–2000 when BaU scenario was applied under current climatic conditions. Size of the carbon stock in tree biomass was 6879 Tg, in the soil 6067 Tg and in wood products in use 814 Tg. Other numbers in the graph represent carbon fluxes, Tg C yeary1.

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Table 4 Area average NPP, NEP, NPE, NBP and NSE (Mg C hay1 yeary1) for the 27 countries included in the study for the period 1995–2000 when BaU scenario was applied under current climatic conditions Country

NPP

NEP

NPE

NBP

NSE

Albania Austria Belgium Bulgaria Croatia Czech Republic Denmark Finland France Germany Hungary Ireland Italy Luxembourg Macedonia Netherlands Norway Poland Portugal Romania Slovak Republic Slovenia Spain Sweden Switzerland United Kingdom Yugoslavia

1.40 8.00 5.25 2.39 1.87 4.00 4.31 2.05 3.22 5.04 4.44 5.30 3.10 5.98 1.24 4.53 1.70 3.80 3.72 4.60 3.79 3.04 2.85 2.58 7.51 4.48 1.95

0.60 2.27 1.87 0.83 0.85 1.38 2.36 0.93 1.25 2.20 1.93 2.74 1.39 3.04 0.35 1.90 0.78 1.60 1.78 2.28 1.61 1.25 0.53 1.20 2.61 2.31 0.69

y0.12 0.11 0.16 0.00 y0.09 0.08 0.04 0.02 0.06 y0.01 0.00 0.11 0.03 0.08 y0.03 0.03 0.04 0.03 y0.05 y0.03 0.04 y0.02 0.05 0.02 0.08 0.06 y0.06

0.49 1.27 0.66 0.54 0.56 0.23 1.19 0.43 0.43 1.34 1.11 1.92 0.67 1.88 y0.16 1.11 0.40 0.87 0.92 1.66 0.91 0.65 0.00 0.68 1.63 1.65 0.23

0.37 1.38 0.82 0.53 0.47 0.31 1.24 0.45 0.50 1.32 1.12 2.04 0.69 1.96 y0.19 1.14 0.44 0.91 0.87 1.63 0.95 0.63 0.05 0.70 1.71 1.71 0.16

Europe

3.18

1.29

0.02

0.66

0.69

Northern Europe. Map of the average NBP, show that it was highest in UK, Central and Eastern Europe (Fig. 5). NPE was negative in some countries, implying that more products were removed from use than manufactured. NSE was negative in one country, implying that forest and wood product sector was loosing carbon into the atmosphere and thereby enhancing greenhouse effect, while in other countries it was the contrary. NPP increased slightly under current climatic conditions until 2030 when it started to decline slightly due to larger proportion of higher age classes (Fig. 6). Under changing climatic conditions, NPP continued to increase until 2050, when it was approximately 20% higher than at the beginning and approximately 15% higher than

under current climatic conditions. NPP was slightly higher in the MultiF scenario than in the BaU scenario. NEP decreased under current climatic conditions over time. This was due to the fact that heterotrophic respiration increased more than NPP over time. Under changing climatic conditions, NEP increased until 2010–2015, then it started to decline slightly. Also NEP was slightly higher in the MultiF scenario than in the BaU scenario. NBP also decreased under current climatic conditions, while under changing climatic conditions it increased until 2010. NBP was higher in the BaU scenario than in the MultiF scenario, since in the MultiF scenario more biomass was removed from the forest than in the BaU scenario. Also NSE decreased over time under current climatic conditions. Under changing climatic conditions NSE increased until 2015 when it started to decline. NSE was slightly higher in the BaU scenario than in the MultiF scenario. 8. Discussion and conclusions Analysis showed that most of the carbon in the forest sector is in forest, in 1990 approximately 94% was in tree biomass and in forest soil. Net carbon sequestration in forests and wood products, i.e. net carbon sink, was 87.5 Tg C yeary1 in 1995–2000. By comparison, carbon emissions from fossil fuel combustion were 1163 Tg in 1990, i.e. net forest and wood product sink was 7–8% of the emissions. Estimates for net carbon sequestration in this study are much smaller than those with other methods, such as inversions based on atmospheric chemistry (Ciais et al., 1995; Bousquet et al., 1999a,b), or eddy flux tower measurements (Martin et al., 1998; Valentini et al., 2000) or upscaling of biogeochemical measurements (Schulze et al., 2000). These results are, however, in the same order of magnitude with other estimates based on forest inventories. An annual buildup of 50 Tg C yeary1 in tree biomass in Europe between 1971 and 1990 has been estimated (Kauppi et al., 1992). Dixon et al. (1994) have estimated that forests in Europe would have been a sink of 90–120 Tg C yeary1 in the late 1980s. Liski and Kauppi (2000) have estimated 110 Tg C yeary1 sink for tree biomass in Europe. One

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151

Fig. 5. NBP during the period 1990 and 1995.

estimate for carbon sink in the EU forests is 63 Tg C yeary1 (Liski et al., 2000). Carbon stocks in tree biomass, soil and wood products increased in all applied management and climate scenarios, but slower after 2010–2020 than that before. This is due to ageing of forests and higher carbon densities per unit of forest land. Differences in carbon sequestration were very

small between applied management scenarios, implying that on European level management should be changed more than in this study if aim is to have larger influence on carbon sequestration. Applied climate change scenario increased carbon stocks and net carbon sequestration compared to current climatic conditions. It should be noted that other climate change scenarios could provide dif-

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Fig. 6. Development of the area average NPP, NEP, NPE, NBP and NSE (Mg C hay1 yeary1 ) of the 27 countries included in the study until 2050 under current and changing climatic conditions when BaU and MultiF scenarios were applied.

ferent results. For example, scenarios that project drier but warmer conditions could result in larger reductions in forest growth in the long-run and also in larger reductions in carbon sequestration. Results also demonstrate that the whole system should be considered when assessing carbon sequestration in forestry. Substitution possibilities,

i.e. possibilities to use wood based energy and materials instead of fossil fuel based energy and materials were not considered in this analysis. ¨ Such possibilities are large in forestry (Borjesson and Gustavsson, 2000). Scenario analysis can be used to investigate how certain changes in forest management and forest

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growth can influence future development of forest resources, availability of wood raw material and carbon sequestration in forestry. Underlying assumptions, however, in the input data, methods and scenarios should be kept in mind when interpreting the result. Therefore, even though this kind of scenario analysis provides absolute numbers and differences between applied scenarios, more attention should be given to relative differences between the outputs than to absolute differences. This is due to the fact that uncertainties can be large and are from various sources, from input data, method itself and from projections (management and climate scenarios), and larger they are longer are the projections. Uncertainties have been studied preliminary and analysis show that uncertainties could be reduced substantially by better biomass expansion factors (Kaipainen et al., manuscript in preparation). One of the strengths and advantages of the applied method is that the starting point for analysis is in existing forests, based on measurements and results from representative forest inventories. Strength is also that forest management, which is key determinant for the European forest carbon budget has been taken into account. Most of the European forests are managed and classified as available for wood supply and approximately 60% of the annual stem wood increment is harvested (FAO, 1997). Also comparisons between countries are feasible as same method has been applied across the countries included in the analysis. Forest inventory based carbon budgeting with EFISCEN is under further development and more comprehensive analysis of the European forestry carbon budget are coming in several ongoing projects. For example, in the SilviStrat project (contract EVK2-CT-2000-00073) which aims at studying adaptive strategies for the sustainable management of European forests under changing climatic conditions, EFISCEN is further improved to take directly into account, impacts of changes in temperature and precipitation into the forest growth and thus forest structure, carbon budget and fellings. In the MEFYQUE project (contract QLRT-2000-00345) which aims to increase knowledge of the relationships between site conditions and growth, yield and timber quality for current

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and future scenarios of atmospheric change, EFISCEN is further developed to include timber quality and energy submodules. In the ATEAM project (contract EVK2-2000-00075), EFISCEN is improved and used to study vulnerability of timber production and carbon sequestration in European forests under changing climatic conditions. In the CarboInvent project (contract EVK2-2002-00157), calculation of tree biomass and soil carbon stocks and fluxes in the EFISCEN will be improved based on more reliable set of biomass expansion factors for most important tree species in Europe as well as based on improvement of the calculation of initial soil carbon stocks using soil survey data and soil carbon data as input data. Acknowledgments We have presented in this article, results that are based on large development work of the EFISCEN model, to include calculation of forest sector carbon budgets and incorporation of transient changes in forest growth in the modelling framework. Major part of the work was in an EU funded project Long term regional effects of climate change on European forests: impact assessment and consequences of carbon budgets (LTEEF II, ENV4-CT97-0577). We want to thank those who worked with the process based models in the LTEEF II project: Pepe Hari and Ari Nissinen with ¨ and Heli Peltola COCAyFEF; Seppo Kellomaki with FINNFOR; Frits Mohren, Koen Kramer, Wilma Jans and Raymond van der Wijngaart with FORGRO; Carlos Gracia, Santi Sabate´ and Annabel Sanchez with GOTILWA; Federico Magnani and Marco Borghetti with HYDRALL; Michael Sonntag and Michael Hauhs with TREEDYN; Michael Freeman, Emil Cienciala and Sune Linder with BIOMASS. References Bousquet, P., Ciais, P., Peylin, P., Ramonet, M., Monfray, P., 1999. Inverse modeling of annual atmospheric CO2 sources and sinks. 1. Method and control inversion. Journal of Geophysical Research—Atmospheres 104 (D21), 26169–26178. Bousquet, P., Ciais, P., Peylin, P., Ramonet, M., Monfray, P., 1999. Inverse modeling of annual atmospheric CO2 sources

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