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Wind is the major abiotic disturbance in New Zealand's planted forests, but little is known about how the risk of wind damage may be affected by future climate change. We linked a mechanistic wind damage model (Forest GALES) to an empirical growth model for radiata pine ( Pinus radiata D. Don) and a process-based growth model ( cenw) to predict the risk of wind damage under different future emissions scenarios and assumptions about the future wind climate. The cenw model was used to estimate site productivity for constant CO2 concentration at 1990 values and for assumed increases in CO2 concentration from current values to those expected during 2040 and 2090 under the B1 (low), A1B (mid-range) and A2 (high) emission scenarios. Stand development was modelled for different levels of site productivity, contrasting silvicultural regimes and sites across New Zealand. The risk of wind damage was predicted for each regime and emission scenario combination using the Forest GALES model. The sensitivity to changes in the intensity of the future wind climate was also examined. Results showed that increased tree growth rates under the different emissions scenarios had the greatest impact on the risk of wind damage. The increase in risk was greatest for stands growing at high stand density under the A2 emissions scenario with increased CO2 concentration. The increased productivity under this scenario resulted in increased tree height, without a corresponding increase in diameter, leading to more slender trees that were predicted to be at greater risk from wind damage. The risk of wind damage was further increased by the modest increases in the extreme wind climate that are predicted to occur. These results have implications for the development of silvicultural regimes that are resilient to climate change and also indicate that future productivity gains may be offset by greater losses from disturbances. [ABSTRACT FROM AUTHOR]

Many studies have been conducted to quantify the possible ecosystem/landscape response to the anticipated global warming. However, there is a large amount of uncertainty in the future climate predictions used for these studies. Specifically, the climate predictions can be very different based on a variety of global climate models and alternative greenhouse emission scenarios. In this study, we coupled a forest landscape model, LANDIS-II, and a forest process model, PnET-II, to examine the uncertainty (that results from the uncertainty in the future climate predictions) in the forest-type composition prediction for a transitional forest landscape [the Boundary Water Canoe Area]. Using an improved global-sensitivity analysis technique [Fourier amplitude sensitivity test], we also quantified the amount of uncertainty in the forest-type composition prediction contributed by different climate variables including temperature, CO2, precipitation and photosynthetic active radiation (PAR). The forest landscape response was simulated for the period 2000–2400ad based on the differential responses of 13 tree species under an ensemble of 27 possible climate prediction profiles (monthly time series of climate variables). Our simulations indicate that the uncertainty in the forest-type composition becomes very high after 2200ad, which is close to the time when the current forests are largely removed by windthrow disturbances and natural mortality. The most important source of uncertainty in the forest-type composition prediction is from the uncertainty in temperature predictions. The second most important source is PAR, the third is CO2 and the least important is precipitation. Our results also show that if the optimum photosynthetic temperature rises due to CO2 enrichment, the forest landscape response to climatic change measured by forest-type composition may be substantially reduced. [ABSTRACT FROM AUTHOR]

In the coming century, forecast climate changes caused by increasing greenhouse gases may produce dramatic shifts in tree species distributions and the rates at which individual tree species sequester carbon or release carbon back to the atmosphere. The species composition and carbon storage capacity of northern Wisconsin (USA) forests are expected to change significantly as a result. Projected temperature changes are relatively large (up to a 5.8°C increase in mean annual temperature) and these forests encompass a broad ecotone that may be particularly sensitive to climate change. Our objective was to estimate the combined effects of climate change, common disturbances, and species migrations on regional forests using spatially interactive simulations. Multiple scenarios were simulated for 200 years to estimate aboveground live biomass and tree species composition. We used a spatially interactive forest landscape model (LANDIS-II) that includes individual tree species, biomass accumulation and decomposition, windthrow, harvesting, and seed dispersal. We used data from two global circulation models, the Hadley Climate Centre (version 2) and the Canadian Climate Center (version 1) to generate transient growth and decomposition parameters for 23 species. The two climate change scenarios were compared with a control scenario of continuing current climate conditions. The results demonstrate how important spatially interactive processes will affect the aboveground live biomass and species composition of northern Wisconsin forests. Forest composition, including species richness, is strongly affected by harvesting, windthrow, and climate change, although five northern species (Abies balsamea,Betula papyrifera,Picea glauca,Pinus banksiana,P. resinosa) are lost in both climate scenarios regardless of disturbance scenario. Changes in aboveground live biomass over time are nonlinear and vary among ecoregions. Aboveground live biomass will be significantly reduced because of species dispersal and migration limitations. The expected shift towards southern oaks and hickory is delayed because of seed dispersal limitations. [ABSTRACT FROM AUTHOR]