A Climate Change Database for Biological Assessments in the Southeastern United States: Development and Case Study

A regional database containing historical time series and climate change scenarios for the Southeastern United States was developed for the U.S.D.A. Forest Service Southern Global Change Program (SGCP). Daily historical values of maximum temperature, minimum temperature and precipitation and empirically derived estimates of vapor pressure deficit and solar radiation across a uniform 1° latitude × 1° longitude grid were obtained. Climate change scenarios of temperature, precipitation, vapor pressure deficit and solar radiation were generated using semi-empirical techniques which combined historical time series and simulation field summaries from GISS, GFDL, OSU and UKMO General Circulation Model (GCM) experiments. An internally consistent 1° latitude × 1° longitude climate change scenario database was produced in which vapor pressure deficit and solar radiation conditions were driven by the GCM temperature projections, but were not constrained to agree with GCM calculated radiation and humidity fields. Some of the unique characteristics of the database were illustrated through a case study featuring growing season and annual potential evapotranspiration (ET_p) estimates. Overall, the unconstrained scenarios produced smaller median ET_p changes from historical baseline conditions, with a smaller range of outcomes than those driven by GCM-directed scenarios. Collectively, the range of annual and growing season ET changes from baseline estimates in response to the unconstrained climate scenarios was +10% to +40%. No outlier responses were identified. ET_p changes driven by GCM-directed (constrained) UKMO radiation and humidity scenarios were on the order of +100%, resulting in the identification of some ET_p responses as statistical outliers. These response differences were attributed to differences between the constrained and unconstrained humidity scenarios.     

Climate trends of the North American prairie pothole region 1906–2000

The Prairie Pothole Region (PPR) is unique to North America. Its millions of wetlands and abundant ecosystem goods and services are highly sensitive to wide variations of temperature and precipitation in time and space characteristic of a strongly continental climate. Precipitation and temperature gradients across the PPR are orthogonal to each other. Precipitation nearly triples from west to east from approximately 300 mm/year to 900 mm/year, while mean annual temperature ranges from approximately 1°C in the north to nearly 10°C in the south. Twentieth-century weather records for 18 PPR weather stations representing 6 ecoregions revealed several trends. The climate generally has been getting warmer and wetter and the diurnal temperature range has decreased. Minimum daily temperatures warmed by 1.0°C, while maximum daily temperatures cooled by 0.15°C. Minimum temperature warmed more in winter than in summer, while maximum temperature cooled in summer and warmed in winter. Average annual precipitation increased by 49 mm or 9%. Palmer Drought Severity Index (PDSI) trends reflected increasing moisture availability for most weather stations; however, several stations in the western Canadian Prairies recorded effectively drier conditions. The east-west moisture gradient steepened during the twentieth century with stations in the west becoming drier and stations in the east becoming wetter. If the moisture gradient continues to steepen, the area of productive wetland ecosystems will shrink. Consequences for wetlands would be especially severe if the future climate does not provide supplemental moisture to offset higher evaporative demand.     

Global warming and 21st century drying

Global warming is expected to increase the frequency and intensity of droughts in the twenty-first century, but the relative contributions from changes in moisture supply (precipitation) versus evaporative demand (potential evapotranspiration; PET) have not been comprehensively assessed. Using output from a suite of general circulation model (GCM) simulations from phase 5 of the Coupled Model Intercomparison Project, projected twenty-first century drying and wetting trends are investigated using two offline indices of surface moisture balance: the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Evapotranspiration Index (SPEI). PDSI and SPEI projections using precipitation and Penman-Monteith based PET changes from the GCMs generally agree, showing robust cross-model drying in western North America, Central America, the Mediterranean, southern Africa, and the Amazon and robust wetting occurring in the Northern Hemisphere high latitudes and east Africa (PDSI only). The SPEI is more sensitive to PET changes than the PDSI, especially in arid regions such as the Sahara and Middle East. Regional drying and wetting patterns largely mirror the spatially heterogeneous response of precipitation in the models, although drying in the PDSI and SPEI calculations extends beyond the regions of reduced precipitation. This expansion of drying areas is attributed to globally widespread increases in PET, caused by increases in surface net radiation and the vapor pressure deficit. Increased PET not only intensifies drying in areas where precipitation is already reduced, it also drives areas into drought that would otherwise experience little drying or even wetting from precipitation trends alone. This PET amplification effect is largest in the Northern Hemisphere mid-latitudes, and is especially pronounced in western North America, Europe, and southeast China. Compared to PDSI projections using precipitation changes only, the projections incorporating both precipitation and PET changes increase the percentage of global land area projected to experience at least moderate drying (PDSI standard deviation of ≤?1) by the end of the twenty-first century from 12 to 30 %. PET induced moderate drying is even more severe in the SPEI projections (SPEI standard deviation of ≤?1; 11 to 44 %), although this is likely less meaningful because much of the PET induced drying in the SPEI occurs in the aforementioned arid regions. Integrated accounting of both the supply and demand sides of the surface moisture balance is therefore critical for characterizing the full range of projected drought risks tied to increasing greenhouse gases and associated warming of the climate system.     

Optimal water depth management on river-fed National Wildlife Refuges in a changing climate

The prairie pothole region (PPR) in the north-central United States and south-central Canada constitutes the most important waterfowl breeding area in North America. Projected long-term changes in precipitation and temperature may alter the drivers of waterfowl abundance: wetland availability and emergent vegetation cover. Previous studies have focused on isolated wetland dynamics, but the implications of changing precipitation on managed, river-fed wetlands have not been addressed. Using a structured decision making (SDM) approach, we derived optimal water management actions for 20 years at four river-fed National Wildlife Refuges (NWRs) in North and South Dakota under contrasting increasing/decreasing (+/?0.4 %/year) inflow scenarios derived from empirical trends. Refuge pool depth is manipulated by control structures. Optimal management involves setting control structure heights that have the highest probability of providing a desired mix of waterfowl habitat, given refuge capacities and inflows. We found optimal seasonal control structure heights for each refuge were essentially the same under increasing and decreasing inflow trends of 0.4 %/year over the next 20 years. Results suggest managed pools in the NWRs receive large inflows relative to their capacities. Hence, water availability does not constrain management; pool bathymetry and management tactics can be greater constraints on attaining management objectives than climate-mediated inflow. We present time-dependent optimal seasonal control structure heights for each refuge, which are resilient to the non-stationary precipitation scenarios we examined. Managers can use this information to provide a desired mixture of wildlife habitats, and to re-assess management objectives in reserves where pool bathymetry prevents attaining the currently stated objectives.     

Potential effects of climate change on a semi-permanent prairie wetland

We assessed the potential effects of a greenhouse gas-induced global climate change on the hydrology and vegetation of a semi-permanent prairie wetland using a spatially-defined, rule-based simulation model. An 11-yr simulation was run using current versus enhanced greenhouse gas climates. Projections of climatic change were from the Goddard Institute for Space Studies (GISS) general circulation model. Simulations were also run using a range of temperature (+2 and +4 °C) and precipitation change values (–20, –10, 0, +10, +20%) to determine the responsiveness of wetland vegetation and hydrology to a variety of climate scenarios.Maximum water depths were significantly less under the enhanced greenhouse gas scenario than under the current climate. The wetland dried in most years with increased temperature and changes in precipitation. Simulations also revealed a significant change in the vegetation, from a nearly balanced emergent cover to open water ratio to a completely closed basin with no open water areas. Simulations over a range of climate change scenarios showed that precipitation changes (particularly increases) had a greater impact on water levels and cover ratios when the temperature increase was moderate (+2 °C).These potential changes in wetland hydrology and vegetation could result in a dramatic decline in the quality of habitat for breeding birds, particularly waterfowl. Continued research on climate and wetland modeling is needed.     

Application of relative drought indices in assessing climate-change impacts on drought conditions in Czechia

The common versions (referred to as self-calibrated here) of the Standardized Precipitation Index (SPI) and the Palmer Drought Severity Index (PDSI) are calibrated and then applied to the same weather series. Therefore, the distribution of the index values is about the same for any weather series. We introduce here the relative SPI and PDSI, abbreviated as rSPI and rPDSI. These are calibrated using a reference weather series as a first step, which is then applied to the tested series. The reference series may result from either a different station to allow for the inter-station comparison or from a different period to allow for climate-change impact assessments. The PDSI and 1–24 month aggregations of the SPI are used here. In the first part, the relationships between the self-calibrated and relative indices are studied. The relative drought indices are then used to assess drought conditions for 45 Czech stations under present (1961–2000) and future (2060–2099) climates. In the present climate experiment, the drought indices are calibrated by using the reference station weather series. Of all drought indices, the PDSI exhibits the widest spectrum of drought conditions across Czechia, in part because it depends not only on precipitation (as does the SPI) but also on temperature. In our climate-change impact experiments, the future climate is represented by modifying the observed series according to scenarios based on five Global Climate Models (GCMs). Changes in the SPI-based drought risk closely follow the modeled changes in precipitation, which is predicted to decrease in summer and increase in both winter and spring. Changes in the PDSI indicate an increased drought risk at all stations under all climate-change scenarios, which relates to temperature increases predicted by all of the GCMs throughout the whole year. As drought depends on both precipitation and temperature, we conclude that the PDSI is more appropriate (when compared to the SPI) for use in assessing the potential impact of climate change on future droughts.     

VULNERABILITY OF AGRONOMIC SYSTEMS IN BULGARIA

In recent years the problem of climate and its variations under the influence of natural processes and factors of anthropogenetic origin has come to the forefront of scientific and practical problems on a world-wide scale. Climate change vulnerability assessments of agronomic systems in Bulgaria have been initiated. In this paper preliminary results of this study are presented. Different climate change scenarios were defined. Global circulation model (GCM) scenarios and incremental scenarios for Bulgaria were created and applied. The influence of climate change on potential crop growing season above a base of 5° and 10 °C in Bulgaria was investigated. Increases in temperature can be expected to lengthen the potential growing season, resulting in a shift of thermal limits of agriculture in Bulgaria. The Decision Support System for Agrotechnology Transfer (DSSAT) Version 2.1 was used to assess the influence of climate change on grain yield of maize and winter wheat. Maize and winter wheat yields decreased with increasing temperatures and decreasing precipitation.     

Tropical disturbances in a GCM

We have analyzed the tropical disturbances in a 11-layer atmospheric general circulation model (GCM) on a 2.5° × 3.75° horizontal grid coupled to a 50 m-mixed layer ocean. Due to the coarse resolution, the GCM is unable to resolve adequately tropical cyclones. The tropical disturbances simulated by the GCM are much weaker and have a much larger horizontal extent. However, they still display much of the essential physics of tropical cyclones, including low-level convergence of mass and moisture, upper tropospheric outflow and a warm core. For most ocean basins the spatial and temporal distribution of the simulated tropical disturbances compares well with the observed tropical cyclones. On doubling the CO₂ concentration, the number of simulated tropical disturbances increases by about 50%. There is a relative increase in the number of more intense tropical disturbances, whose maximum windspeed increases by about 20%. This agrees with the theoretical estimate of Emanuel. However, because the low-resolution of the GCM severely restricts their maximum possible intensity, simulated changes in tropical disturbance intensity should be interpreted cautiously.     

USE OF A STOCHASTIC WEATHER GENERATOR IN THE DEVELOPMENT OF CLIMATE CHANGE SCENARIOS

Climate change scenarios with a high spatial and temporal resolution are required in the evaluation of the effects of climate change on agricultural potential and agricultural risk. Such scenarios should reproduce changes in mean weather characteristics as well as incorporate the changes in climate variability indicated by the global climate model (GCM) used. Recent work on the sensitivity of crop models and climatic extremes has clearly demonstrated that changes in variability can have more profound effects on crop yield and on the probability of extreme weather events than simple changes in the mean values. The construction of climate change scenarios based on spatial regression downscaling and on the use of a local stochastic weather generator is described. Regression downscaling translated the coarse resolution GCM grid-box predictions of climate change to site-specific values. These values were then used to perturb the parameters of the stochastic weather generator in order to simulate site-specific daily weather data. This approach permits the incorporation of changes in the mean and variability of climate in a consistent and computationally inexpensive way. The stochastic weather generator used in this study, LARS-WG, has been validated across Europe and has been shown to perform well in the simulation of different weather statistics, including those climatic extremes relevant to agriculture. The importance of downscaling and the incorporation of climate variability are demonstrated at two European sites where climate change scenarios were constructed using the UK Met. Office high resolution GCM equilibrium and transient experiments.     

Climate Scenarios for the Southeastern U.S. Based on GCM and Regional Model Simulations

We analyze the control runs and 2 × CO₂ projections (5-yearlengths) of the CSIRO Mk 2 GCM and the RegCM2 regional climate model, which was nested in the CSIRO GCM, over the Southeastern U.S.; and we present the development of climate scenarios for use in an integrated assessment of agriculture. The RegCM exhibits smaller biases in both maximum and minimum temperature compared to the CSIRO. Domain average precipitation biases are generally negative and relatively small in winter, spring, and fall, but both models produce large positive biases in summer, that of the RegCM being the larger. Spatial pattern correlations of the model control runs and observations show that the RegCM reproduces better than the CSIRO the spatial patterns of precipitation, minimum and maximum temperature in all seasons. Under climate change conditions, the most salient feature from the point of view of scenarios for agriculture is the large decreases in summer precipitation, about 20% in the CSIRO and 30% in the RegCM. Increases in springprecipitation are found in both models, about 35% in the CSIRO and 25% in theRegCM. Precipitation decreases of about 20% dominate in winter in the CSIRO,while a more complex pattern of increases and decreases is exhibited by the regional model. Temperature increases by 3 to 5 °C in the CSIRO, the higher values dominating in winter and spring. In the RegCM, temperature increases are much more spatially and temporally variable, ranging from 1 to 7 °C acrossall months and grids. In summer large increases (up to 7 °C) in maximum temperature are found in the northeastern part of the domain where maximum drying occurs.     

Vulnerability and adaptation assessments of agriculturalcrops under climate change in the Southeastern USA

Summary  It is expected that a change in climatic conditions due to global warming will directly impact agricultural production. Most climate change studies have been applied at very large scales, in which regions were represented by only one or two weather stations, which were mainly located at airports of major cities. The objective of this study was to determine the potential impact of climate change at a local level, taking into account weather data recorded at remote locations. Daily weather data for a 30-year period were obtained for more than 500 sites, representing the southeastern region of the USA. Climate change scenarios, using transient and equilibrium global circulation models (GCM), were defined, created and applied to the daily historical weather data. The modified temperature, precipitation and solar radiation databases corresponding to each of the climate change scenarios were used to run the CERES v.3.5 simulation model for maize and winter wheat and the CROPGRO v.3.5 model for soybean and peanut. The GCM scenarios projected a shorter duration of the crop-growing season. Under the current level of CO₂, the GCM scenarios projected a decrease of crop yields in the 2020s. When the direct effects of CO₂ were assumed in the study, the scenarios resulted in an increase in soybean and peanut yield. Under equilibrium , the GCM climate change scenarios projected a decrease of maize and winter wheat yield. The indirect effects of climate change also tended to decrease soybean and peanut yield. However, when the direct effects of CO₂ were included, most of the scenarios resulted in an increase in legume yields. Possible changes in sowing data, hybrids and cultivar selection, and fertilization were considered as adaptation options to mitigate the potential negative impact of potential warming. Received July 20, 1999/Revised April 18, 2000     

Use of general circulation model output in the creation of climate change scenarios for impact analysis

Many scientific studies warn of a rapid global climate change during the next century. These changes are understood with much less certainty on a regional scale than on a global scale, but effects on ecosystems and society will occur at local and regional scales. Consequently, in order to study the true impacts of climate change, regional scenarios of future climate are needed. One of the most important sources of information for creating scenarios is the output from general circulation models (GCMs) of the climate system. However, current state-of-the-art GCMs are unable to simulate accurately even the current seasonal cycle of climate on a regional basis. Thus the simple technique of adding the difference between 2 × CO₂ and 1 × CO₂ GCM simulations to current climatic time series cannot produce scenarios with appropriate spatial and temporal details without corrections for model deficiencies. In this study a technique is developed to allow the information from GCM simulations to be used, while accommodating for the deficiencies. GCM output is combined with knowledge of the regional climate to produce scenarios of the equilibrium climate response to a doubling of the atmospheric CO₂ concentration for three case study regions, China, Sub-Saharan Africa and Venezuela, for use in biological effects models. By combining the general climate change calculated with several GCMs with the observed patterns of interannual climate variability, reasonable scenarios of temperature and precipitation variations can be created. Generalizations of this procedure to other regions of the world are discussed.     

Origin of July Antarctic precipitation and its influence on deuterium content: a GCM analysis

The NASA/GISS GCM is used to estimate the evaporative contributions of several oceanic regions (defined by temperature) to Antarctica's July precipitation. Tracer diagnostics in the GCM suggest that the weighted average evaporative source temperature for Antarctic precipitation as a whole is about 12°C. The average source temperature for local precipitation there varies from 9° C to 14° C. To examine the effect of evaporative source on water isotope concentration, the GCM also follows a global deuterium (HDO) tracer and deuterium tracers evaporating from each oceanic region. The results suggest that although evaporative source temperature does affect the concentrations of the individual HDO tracers, differences in evaporative source do not explain the scatter in the roughly linear relationship between condensation temperature and isotope concentration. Offprint requests to: R Koster     

Simulated Climate Change Effects on Year-Round Water Temperatures in Temperate Zone Lakes

A deterministic, one-dimensional model is presented to simulate daily water temperature profiles and associated ice and snow covers for dimictic and polymictic lakes of the temperate zone. The lake parameters required as model input are surface area (A_s), maximum depth (H_MAX), and Secchi depth (z_s), the latter, used as a measure of light attenuation and trophic state. The model is driven by daily weather data and operates year-round over multiple years. The model has been tested with extensive data (over 5,000 temperature points). Standard error between simulated and measured water temperatures is 1.4°C in the open water season and 0.5°C in the ice cover season. The model is applied to simulate the sensitivity of Minnesota lake water temperature characteristics to climate change. The projected climate changes due to a doubling of atmospheric CO₂ are obtained from the output of the Canadian Climate Center General Circulation Model (CCC GCM) and the Goddard Institute of Space Studies General Circulation Model (GISS GCM). Simulated lake temperature characteristics have been plotted in a coordinate system with a lake geometry ratio (A _s ^0.25 /H_MAX) on one axis and Secchi depth on the other. The lake geometry ratio expresses a lake's susceptibility to stratification. By interpolation, the sensitivity of lake temperature characteristics to changes of water depth and Secchi depth under the projected climate scenarios can therefore be obtained. Selected lake temperature characteristics simulated with past climate conditions (1961–1979) and with a projected 2 × CO₂ climate scenario as input are presented herein in graphical form. The simulation results show that under the 2 × CO₂ climate scenario ice formation is delayed and ice cover period is shortened. These changes cause water temperature modifications throughout the year.     

The Vulnerability of the Australian Beef Industry to Impacts of the Cattle Tick (Boophilus microplus) under Climate Change

An integrated assessment is presented of the potential impacts of the cattle tick (Boophilus microplus Canestrini) on the Australian beefindustry under climate change. The project was carried out as a case study to test an impact assessment approach that was designed to integrate biological, production and socio-economic impacts on managed and natural systems. A climate-driven, tick population model was run for European, zebu and crossbred cattle breeds having different levels of resistance to cattle ticks. A geographical information system (GIS) was used to organise spatial data on climate scenarios and industry statistics and to undertake regional analyses.A comparison was made of the two available approaches to conducting impact assessments, namely a bottom-up approach using sensitivity analysis and a top-down approach using climate change scenarios from a global circulation model (GCM) (CSIRO, 1996). The output, in terms of the abundance of tick populations and reductions in cattle productivity for each breed showed significant expansions in potential geographical impacts. In the absence of any adaptation measures, the results indicated changes in the losses in live weight gain of cattle tick ranging from 7780 tonnes per year by 2030 to 21637 tonnes per year by 2100, in comparison with estimates for current losses of 6594 tonnes per year.The principal adaptation options available to the beef industry are to switch to breeds that are more resistant to cattle ticks, or to increase the frequency of treatments with various tick control products. In this paper we focus on switching breeds as an adaptive measure when appropriate damage thresholds are triggered under the climate change scenarios. When adaptation measures were put in place, the losses ranged from 4962 tonnes in 2030 to 5619 tonnes in 2100 compared with 2636 tonnes at present if all producers adopted the optimal breed structure. Optimal breed structure was defined as one that would prevent tick numbers per animal exceeding 100 ticks per animal for European and 700 ticks per animal for crossbred breeds of cattle in any week of the year under a tick control strategy that was suitable for present climatic conditions. The lower threshold for European breeds reflects their vulnerability to explosive increases in numbers because of their low resistance to ticks. The results of the analyses using the GCM scenarios were used in an economic model to calculate costs of lost live-weight gain for 2030, 2070 and 2100. The greatest increases in costs were incurred in the southern parts of the current distribution in Queensland and potentially in northern New South Wales if the present quarantine barrier failed.Given the great uncertainty of the nature of possible regional changes in climate, analyses of the sensitivity of losses in live weight gain to changes in climatic variables were also undertaken. The analyses included a measure of likely impacts of cattle tick on the beef cattle industry, in the absence of adaptation measures, as a baseline measure of sensitivity. The likely impacts on crossbred cattle were insensitive to the climatic variables.When adaptive breed changes were allowed, the economic impacts on the industry were insensitive to the GCM scenarios. This suggests that, at least in this instance, reducing the uncertainties in climate change scenarios is not a priority if the adaptation strategies can be implemented in a cost-effective manner. Finally we made a qualitative assessment of the sustainability and robustness of alternative approaches to adaptation and assessed regional vulnerability to cattle tick under climate change. The conclusions were so strongly dependent on assumptions about the future of other global changes, in particular the ability to maintain quarantine barriers and to retain effective acaricides at comparable costs to the present, that we strongly recommend that risk assessments of climate change extend to all relevant variables in involved in global change where possible.     

A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

Climate simulation of the twenty-first century with interactive land-use changes

To include land-use dynamics in a general circulation model (GCM), the physical system has to be linked to a system that represents socio-economy. This issue is addressed by coupling an integrated assessment model, IMAGE2.2, to an ocean–atmosphere GCM, CNRM-CM3. In the new system, IMAGE2.2 provides CNRM-CM3 with all the external forcings that are scenario dependent: greenhouse gas (GHGs) concentrations, sulfate aerosols charge and land cover. Conversely, the GCM gives IMAGE changes in mean temperature and precipitation. With this new system, we have run an adapted scenario of the IPCC SRES scenario family. We have chosen a single scenario with maximum land-use changes (SRES A2), to illustrate some important feedback issues. Even in this two-way coupled model set-up, land use in this scenario is mainly driven by demographic and agricultural practices, which overpowers a potential influence of climate feedbacks on land-use patterns. This suggests that for scenarios in which socio-economically driven land-use change is very large, land-use changes can be incorporated in GCM simulations as a one-way driving force, without taking into account climate feedbacks. The dynamics of natural vegetation is more closely linked to climate but the time-scale of changes is of the order of a century. Thus, the coupling between natural vegetation and climate could generate important feedbacks but these effects are relevant mainly for multi-centennial simulations.     

The heat and water budgets of a beaver pond

Small water bodies create their own characteristic local meteorological environments. The heat and water budgets will generally vary with surface area and water depth. If a small pond gradually becomes covered by vegetation, its meteorological conditions will change. On occasion, a vegetated area may change into a pond, complete with vegetation established in the water and extending above the surface. Such are beaver ponds and other flooded areas.

The paper discusses the main features of the development of beaver ponds and their heat and water budgets at different stages. The energy budget programme used was previously developed by the authors, but it has been modified to account for the different phases of the pond development. The effects of the various physical changes are evaluated by comparing the individual heat and water budget terms for different stages between an open lake surface and a forest cover.

The local heat budget will only be affected on a small scale by the establishment of a beaver pond, but the influence on the water budget has far‐reaching consequences.     

Boreal forest responses to climate-change scenarios along an ecoclimatic transect in central Canada

The FORSKA2 patch model was used to simulate responses of forest biomass and species composition to four GCM projections of climate change at 11 locations along a transect oriented northeast-southwest across the boreal zone of central Canada. In agreement with earlier results, FORSKA2 produced estimates of present-day biomass accumulation and functional types very consistent with local inventory data. Simulated responses to the four GCM scenarios of climate change produced different results. The GFDL scenario consistently reduced total biomass accumulation compared to present-day conditions, whereas the other three GCMs produced overall increases. In the north, where ecosystem productivity is thought to be limited by low temperature, changes in steady-state biomass accumulation and species composition were relatively minor. In the south, where productivity is probably limited by summer water deficits, the GCM scenarios resulted in larger absolute changes, with generally large increases under GISS, and OSU and generally smaller increases under UKMO. Pronounced changes in species composition were not evident in most simulations, with the exception that warmer winter temperatures evidently allowed invasion by species currently excluded through intolerance to winter minima.     

Potential climate change impacts on the probability of wind damage in a south Swedish forest

We estimated how the possible changes in wind climate and state of the forest due to climate change may affect the probability of exceeding critical wind speeds expected to cause wind damage within a forest management unit located in Southern Sweden. The topography of the management unit was relatively gentle and the forests were dominated by Norway spruce (Picea abies (L.) Karst.). We incorporated a model relating the site index (SI) to the site productivity into the forest projection model FTM. Using estimated changes in the net primary production (NPP) due to climate change and assuming a relative change in NPP equal to a relative change in the site productivity, we simulated possible future states of the forest under gradual adjustment of SI in response to climate change. We estimated changes in NPP by combining the boreal-adapted BIOMASS model with four regional climate change scenarios calculated using the RCAO model for the period 2071–2100 and two control period scenarios for the period 1961–1990. The modified WINDA model was used to calculate the probability of wind damage for individual forest stands in simulated future states of the forest. The climate change scenarios used represent non-extreme projections on a 100-year time scale in terms of global mean warming. A 15–40% increase in NPP was estimated to result from climate change until the period 2071–2100. Increasing sensitivity of the forest to wind was indicated when the management rules of today were applied. A greater proportion of the calculated change in probability of wind damage was due to changes in wind climate than to changes in the sensitivity of the forest to wind. While regional climate scenarios based on the HadAM3H general circulation model (GCM) indicated no change (SRES A2 emission scenario) or a slightly reduced (SRES B2 emission scenario) probability of wind damage, scenarios based on the ECHAM4/OPYC3 GCM indicated increased probability of wind damage. The assessment should, however, be reviewed as the simulation of forest growth under climate change as well as climate change scenarios are refined.