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 x 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.

5.45.2 Additional factors not included in the models contribute uncertainty

Fire, insects and extreme events are not well modelled. Both forest composition and production are shaped by fire frequency, size, intensity and seasonality. There is evidence of both regional increase and decrease in fire activity (Goldammer and Mutch, 2001; Podur et al., 2002; Bergeron et al., 2004; Girardin et al., 2004; Mouillot and Field, 2005), with some of the changes linked to climate change (Gillett et al., 2004; Westerling et al., 2006). Climate change will interact with fuel type, ignition source and topography in determining future damage risks to the forest industry, especially for paper and pulp operations; fire hazards will also pose health threats (see Chapter 8, Section 8.2) and affect landscape recreational value. There is an uncertainty associated with many studies of climate change and forest fires (Shugart et al., 2003; Lemmen and Warren, 2004); however, current modelling studies suggest that increased temperatures and longer growing seasons will elevate fire risk in connection with increased aridity (Williams et al., 2001; Flannigan et al., 2005; Schlyter et al., 2006). For example, Crozier and Dwyer (2006) indicated the possibility of a 10% increase in the seasonal severity of fire hazard over much of the United States under changed climate, while Flannigan et al. (2005) projected as much as 74-118% increase of the area burned in Canada by the end of the 21st century under a 3 x CO2 scenario. However, much of this fire increase is expected in inaccessible boreal forest regions, so the effects of climate-induced wildfires on timber production may be more modest.

For many forest types, forest health questions are of great concern, with pest and disease outbreaks as major sources of natural disturbance. The effects vary from defoliation and growth loss to timber damage to massive forest die backs; it is very likely that these natural disturbances will be altered by climate change and will have an impact on forestry (Alig et al., 2004). Warmer temperatures have already enhanced the opportunities for insect spread across the landscape (Carroll et al., 2004; Crozier and Dwyer, 2006). Climate change can shift the current boundaries of insects and pathogens and modify tree physiology and tree defence. Modelling of climate change impacts on insect and pathogen outbreaks remains limited.

The effects of climate extremes on commercial forestry are region-specific and include reduced access to forestland, increased costs for road and facility maintenance, direct damage to trees by wind, snow, frost or ice; indirect damage from higher risks of wildfires and insect outbreaks, effects of wetter winters and early thaws on logging, etc. For example, in January 2005 Hurricane Gudrun, with maximum gusts of 43 m/s, damaged more than 60 million m3 of timber in Sweden, reducing the country's log trade deficit by 30% (UNECE, 2006). Higher direct and indirect risks could affect timber supplies, market prices and cost of insurance (DeWalle et al., 2003). Globally, model predictions mentioned in the SAR suggested extensive forest die back and composition change; however, some of these effects may be mitigated (Shugart et al., 2003) and changes in forest composition will likely occur gradually (Hanson and Weltzin, 2000).

Interaction between multiple disturbances is very important for understanding climate change impacts on forestry. Wind events can damage trees through branch breaking, crown loss, trunk breakage or complete stand destruction. The damage might increase for faster-growing forests. This damage can be further aggravated by increased damage from insect outbreaks and wildfires (Fleming et al., 2002; Nabuurs et al., 2002). Severe drought increases mortality and is often combined with insect and pathogen damage and wildfires. For example, a positive feedback between deforestation, forest fragmentation, wildfire and increased frequency of droughts appears to exist in the Amazon basin, so that a warmer and drier regional climate may trigger massive deforestation (Laurance and Williamson, 2001; Laurance et al., 2004; Nepstad et al., 2004). Few, if any, models can simulate these effects.

5.4.53 Social and economic impacts

Climate change impacts on forestry and a shift in production preferences (e.g., towards biofuels) will translate into social and economic impacts through the relocation of forest economic activity. Distributional effects would involve businesses, landowners, workers, consumers, governments and tourism, with some groups and regions benefiting while others experience losses. Net benefits will accrue to regions that experience increased forest production, while regions with declining activity will likely face net losses. If wood prices decline, as most models predict, consumers will experience net benefits, while producers experience net losses. Even though the overall economic benefits are likely to exceed losses, the loss of forest resources may directly affect 90% of the 1.2 billion forest-dependent people who live in extreme poverty (FAO, 2004a). Although forest-based communities in developing countries are likely to have modest impact on global wood production, they may be especially vulnerable because of the limited ability of rural, resource-dependent communities to respond to risk in a proactive manner (Davidson et al., 2003; Lawrence, 2003). Non-timber forest products (NTFP) such as fuel, forest foods or medicinal plants, are equally important for the livelihood of the rural communities. In many rural Sub-Saharan Africa communities, NTFP may supply over 50% of a farmer's cash income and provide the health needs for over 80% of the population (FAO, 2004a). Yet little is known about the possible impacts on NFTP.

5.4.6 Capture fisheries and aquaculture: marine and inland waters

World capture production of fish, crustaceans and molluscs in 2004 was more than twice that of aquaculture (Table 5.5), but since 1997 capture production decreased by 1%, whereas aquaculture increased by 59%. By 2030, capture production and aquaculture are projected to be closer to equality (93 Mt and 83 Mt, respectively) (FAO, 2002). Aquaculture resembles terrestrial animal husbandry more than it does capture fisheries and therefore shares many of the vulnerabilities and adaptations to climate change with that sector. Similarities between aquaculture and terrestrial animal husbandry include ownership, control of inputs, diseases and predators, and use of land and water.

Some aquaculture, particularly of plants and molluscs, depends on naturally occurring nutrients and production, but the rearing of fish and Crustacea usually requires the addition of suitable food, obtained mainly from capture fisheries. Capture fisheries depend on the productivity of the natural ecosystems on which

Table 5.5. World fisheries production in 2004 (source: FAO, Yearbook of Fisheries Statistics

World production in Mt




Capture production

Fish, crustaceans, molluscs, etc.

0 0

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