IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability New findings since TAR

Confirmation of TAR: Modelling studies predict increased global timber production.

Simulations with yield models show that climate change can increase global timber production through location changes of forests and higher growth rates, especially when positive effects of elevated CO2 concentration are taken into consideration (Irland et al., 2001; Sohngen et al., 2001; Alig et al., 2002; Solberg et al., 2003; Sohngen and Sedjo, 2005). For example, Sohngen et al. (2001) and Sohngen and Sedjo (2005) projected a moderate increase of timber yield due to both rising NPP and a poleward shift of the most productive species due to climate change. Changing timber supply will affect the market and could impact supply for other uses, e.g., for biomass energy. Global economic impact assessments predict overall demand for timber production to increase only modestly (see Section with a moderate increase or decrease of wood prices in the future in the order of up to ±20% (Irland et al., 2001; Sohngen et al., 2001; Nabuurs et al., 2002; Perez-Garcia et al., 2002; Solberg et al., 2003; Sohngen and Sedjo, 2005), with benefits of higher production mainly going to consumers. For the U.S., Alig et al. (2002) computed that the net impact of climate change on the forestry sector may be small. Similarly, Shugart et al. (2003) concluded that the U.S. timber markets have low susceptibility to climate change, because of the large stock of existing forests, technological change in the timber industry and the ability to adapt. These and other simulation studies are summarised in Table 5.4.

Table 5.4. Examples of simulated climate change impacts on forestry.

Reference; location Scenario and GCM Production impact Economic impact 

Sohngen et al., 2001; Sohngen and

Sedjo, 2005.



UIUC and

Hamburg T-106 for CO2 topping 550 ppm in 2060

  • 2045: production up by 29-38%; reductions in N. America, Russia; increases in S. America and Oceania.
  • 2145: production up by 30%, increases in N. America, S. America, and Russia.
  • 2045: prices reduced, high-latitude loss, low-latitudes gain.
  • 2145: prices increase up to 80% (no climate change), 50% (with climate change), high-latitude gain, low-latitude loss. Benefits go to consumers.

Solberg et al., 2003.



Baseline, 20-40%, increase in forest growth by 2020

  • Increased production in W. Europe,
  • Decreased production in E. Europe.

Price drop with an increase in welfare to producers and consumers. Increased profits of forest industry and forest owners.


Perez-Garcia et al., 2002.




MIT GCM, MIT EPPA emissions

  • Harvest increase in the US West (+2 to +11%), New Zealand (+10 to +12%), and S. America (+10 to +13%).
  • Harvest decrease in Canada.

Demand satisfied; prices drop with an increase in welfare to producers and consumers.


Lee and Lyon, 2004.



ECHAM-3 (2 * CO2 in 2060),

TSM 2000,


Hamburg model

  • 2080s, no climate change: increase of the industrial timber harvest by 65% (normal demand) or 150% (high demand); emerging regions triple their production.
  • With climate change: increase of the industrial timber harvest by 25% (normal demand) or 56% (high demand), E. Siberia & US South dominate production.

No climate change:

  • Pulpwood price increases 44%
  • Solid wood increase 21%.

With climate change:

  • Pulpwood price decrease 25%
  • Solid wood decrease 34%
  • Global welfare 4.8% higher than in no climate change scenario.

Nabuurs et al., 2002.



HadCM2 under IS92a


18% extra increase in annual stemwood increment by 2030, slowing down on a longer term. 

Both decreases or increases in prices are possible.


Schroeter, 2004.



IPCC A1FI, A2, B1, B2 up to 2100.

Few management scenarios

  • Increased forest growth (especially in N. Europe) and stocks, except for A1FI.
  • 60-80% of stock change is due to management, climate explains 10-30% and the rest is due to land use change.

In the A1FI and A2 scenarios, wood demand exceeds potential felling, particularly in the second half of the 21st century, while in the B1 and B2 scenarios future wood demand can be satisfied.


Alig et al., 2002;

Joyce et al., 2001.






  • Increase in timber inventory by 12% (mid-term); 24% (long-term) and small increase in harvest. Major shift in species and an increase in burnt area by 25-50%.
  • Generally, high elevation and northern forests decline, southern forests expand.
  • Reduction in log prices
  • Producer welfare reduced compared to no climate change scenario
  • Lower prices; consumers will gain and forest owners will lose

New Knowledge: Increased regional variability; change in non-timber forest products.

Although models suggest that global timber productivity will likely increase with climate change, regional production will exhibit large variability, similar to that discussed for crops. Mendelsohn (2003), analysing production in California, projected that, at first (2020s), climate change increases harvests by stimulating growth in the standing forest. In the long run, up to 2100, these productivity gains were offset by reductions in productive area for softwoods growth. Climate change will also substantially impact other services, such as seeds, nuts, hunting, resins, plants used in pharmaceutical and botanical medicine, and in the cosmetics industry; these impacts will also be highly diverse and regionalised.

New Knowledge: CO2 enrichment effects may be overestimated in models; models need improvement.

New studies suggest that direct CO2 effects on tree growth may be revised to lower values than previously assumed in forest growth models. A number of FACE studies in 550 ppm CO2 showed average NPP increase of 23% in young tree stands (Norby et al., 2005). However, in a 100-year old tree stand, Korner et al. (2005) found little overall stimulation in stem growth over a period of four years. Additionally, the initial increase in growth increments may be limited by competition, disturbance, air pollutants, nutrient limitations and other factors (Karnosky, 2003), and the response is site- and species-specific. By contrast, models often presume larger fertilisation effects: Sohngen et al. (2001) assumed a 35% NPP increase under a 2 * CO2 scenario. Boisvenue and Running (2006) suggest increasing forest-growth rate due to increasing CO2 since the middle of the 20th century; however, some of this increase may result from other effects, such as land-use change (Caspersen et al., 2000).

In spite of improvements in forest modelling, model limitations persist. Most of the major forestry models don’t include key ecological processes. Development of Dynamic Global Vegetation Models (DGVMs), which are spatially explicit and dynamic, will allow better predictions of climate-induced vegetative changes (Peng, 2000; Bachelet et al., 2001; Cramer et al., 2001; Brovkin, 2002; Moorcroft, 2003; Sitch et al., 2003) by simulating the composition of deciduous and evergreen trees, forest biomass, production, and water and nutrient cycling, as well as fire effects. DGVMs are also able to provide GCMs with feedbacks from changing vegetation, e.g., Cox et al. (2004) found that DGVM feedbacks raise HadCM3LC GCM temperature and decrease precipitation forecasts for Amazonia, leading to eventual loss of rainforests. There are still inconsistencies, however, between the models used by ecologists to estimate the effects of climate change on forest production and composition and those used to predict forest yield. Future development of the models that integrate both the NPP and forestry yield approaches (Nabuurs et al., 2002; Peng et al., 2002) will significantly improve the predictions.