Will climate change be beneficial or detrimental to the invasive swede midge in North America? Contrasting predictions using climate projections from different general circulation models

Climate change may dramatically affect the distribution and abundance of organisms. With the world's population size expected to increase significantly during the next 100 years, we need to know how climate change might impact our food production systems. In particular, we need estimates of how future climate might alter the distribution of agricultural pests. We used the climate projections from two general circulation models (GCMs) of global climate, the Canadian Centre for Climate Modelling and Analysis GCM (CGCM2) and the Hadley Centre model (HadCM3), for the A2 and B2 scenarios from the Special Report on Emissions Scenarios in conjunction with a previously published bioclimatic envelope model (BEM) to predict the potential changes in distribution and abundance of the swede midge, Contarinia nasturtii, in North America. The BEM in conjunction with either GCM predicted that C. nasturtii would spread from its current initial invasion in southern Ontario and northwestern New York State into the Canadian prairies, northern Canada, and midwestern United States, but the magnitude of risk depended strongly on the GCM and the scenario used. When the CGCM2 projections were used, the BEM predicted an extensive shift in the location of the midges' climatic envelope through most of Ontario, Quebec, and the maritime and prairie provinces by the 2080s. In the United States, C. nasturtii was predicted to spread to all the Great Lake states, into midwestern states as far south as Colorado, and west into Washington State. When the HadCM3 was applied, southern Ontario, Saskatchewan, and Washington State were not as favourable for C. nasturtii by the 2080s. Indeed, when used with the HadCM3 climate projections, the BEM predicted the virtual disappearance of ‘very favourable’ regions for C. nasturtii. The CGCM2 projections generally caused the BEM to predict a small increase in the mean number of midge generations throughout the course of the century, whereas, the HadCM3 projections resulted in roughly the same mean number of generations but decreased variance. Predictions of the likely potential of C. nasturtii spatial spread are thus strongly dependent on the source of climate projections. This study illustrates the importance of using multiple GCMs in combination with multiple scenarios when studying the potential for spatial spread of an organism in response to climate change.     

Climate change and the fate of cereal aphids in Southern Britain

Climate change will drive dramatic changes in the abundance and distribution of species. Assessing the impacts of climate change on our agricultural systems is essential for mitigation planning. Here, I combine projections from the UK Hadley Centre's HadRM03 climate change model for Southern Britain with a general mechanistic model of the interaction between climate, temperate grass physiology and cereal aphid population dynamics. Aphids are one of the largest and most important groups of crop pests and disease vectors worldwide but particularly in temperate regions. The model predicts an increasingly dramatic decline in cereal aphid abundance from the 1961 to 1990 baseline with increasing CO₂ emissions: low emissions=?5%, medium low=?12%, medium high=?61%, and high=?92%. Of the six climate variables used in the model, changes in temperature and rainfall were the most important across all emissions scenarios and, counter‐intuitively, the direct impact of elevated CO₂ actually declines as emissions increase. The results suggest that the pest status of cereal aphids in Southern Britain will significantly decline by the end of this century.     

Climate change scenarios and models yield conflicting predictions about the future risk of an invasive species in North America

• 1 The pea leafminer Liriomyza huidobrensis (Blanchard) (Diptera: Agromyzidae) is an invasive species in North America and a serious economic pest on a wide variety of crops. We developed a bioclimatic envelope model (BEM) for this species and examined the envelope's potential location in North America under various future climates.
• 2 We compared the future bioclimatic envelopes for L. huidobrensis using either simple scenarios comprising uniform changes in temperature/precipitation or climate projections from general circulation models (GCMs). Our simple scenarios were: (i) an increase of 0.1°C per degree in latitude with a 20% increase in summer precipitation and a 20% decrease in winter precipitation and (ii) an overall increase of 3°C everywhere, also with the same changes in precipitation. For GCM‐modelled climate change, we used the Canadian Centre for Climate Modelling and Analysis GCM (CGCM2) and the Hadley Centre climate model (HadCM3), each in combination with two scenarios from the Special Report on Emissions Scenarios (A2 and B2).
• 3 The BEM results using the simple scenarios were more similar to each other than to the results obtained using GCM projections. The results were also qualitatively different (i.e. spatially different and divergent) depending on which GCM‐scenario combination was used.
• 4 This modelling exercise illustrates that: (i) results using first approximation simple climate change scenarios can give predictions very different from those that use GCM‐modelled climate projections (comprising a result that has worrying implications for empirical impact research) and that (ii) different GCM‐models using the same scenario can give very different results (implying strong model dependency in projected biological impacts).

     

Climate change and the potential for range expansion of the Lyme disease vector Ixodes scapularis in Canada

We used an Ixodes scapularis population model to investigate potential northward spread of the tick associated with climate change. Annual degree-days >0 degrees C limits for I. scapularis establishment, obtained from tick population model simulations, were mapped using temperatures projected for the 2020s, 2050s and 2080s by two Global Climate Models (the Canadian CGCM2 and the UK HadCM3) for two greenhouse gas emission scenario enforcings 'A2'and 'B2' of the Intergovernmental Panel on Climate Change. Under scenario 'A2' using either climate model, the theoretical range for I. scapularis establishment moved northwards by approximately 200 km by the 2020s and 1000 km by the 2080s. Reductions in emissions (scenario 'B2') had little effect on projected range expansion up to the 2050s, but the range expansion projected to occur between the 2050s and 2080s was less than that under scenario 'A2'. When the tick population model was driven by projected annual temperature cycles (obtained using CGCM2 under scenario 'A2'), tick abundance almost doubled by the 2020s at the current northern limit of I. scapularis, suggesting that the threshold numbers of immigrating ticks needed to establish new populations will fall during the coming decades. The projected degrees of theoretical range expansion and increased tick survival by the 2020s, suggest that actual range expansion of I. scapularis may be detectable within the next two decades. Seasonal tick activity under climate change scenarios was consistent with maintenance of endemic cycles of the Lyme disease agent in newly established tick populations. The geographic range of I. scapularis-borne zoonoses may, therefore, expand significantly northwards as a consequence of climate change this century.     

Shifting global invasive potential of European plants with climate change

Global climate change and invasions by nonnative species rank among the top concerns for agents of biological loss in coming decades. Although each of these themes has seen considerable attention in the modeling and forecasting communities, their joint effects remain little explored and poorly understood. We developed ecological niche models for 1804 species from the European flora, which we projected globally to identify areas of potential distribution, both at present and across 4 scenarios of future (2055) climates. As expected from previous studies, projections based on the CGCM1 climate model were more extreme than those based on the HadCM3 model, and projections based on the a2 emissions scenario were more extreme than those based on the b2 emissions scenario. However, less expected were the highly nonlinear and contrasting projected changes in distributional areas among continents: increases in distributional potential in Europe often corresponded with decreases on other continents, and species seeing expanding potential on one continent often saw contracting potential on others. In conclusion, global climate change will have complex effects on invasive potential of plant species. The shifts and changes identified in this study suggest strongly that biological communities will see dramatic reorganizations in coming decades owing to shifting invasive potential by nonnative species.     

Comparing growth patterns among field populations of cereal aphids reveals factors limiting their maximum abundance

Cereal stands in central Europe are commonly infested with three species of aphids that may become serious pests. With increasing abundance, the proportion of a particular species in the total aphid population may remain constant, suggesting a density-independent exponential growth, or the proportion can change, suggesting density-dependent constraints on growth. The constraints that affect particular species, and thus their relative abundance, were studied. The proportionality between maximum abundances of the cereal aphids was studied using a 10-year census of the numbers of aphids infesting 268 winter wheat plots. For two species their abundance on leaves and ears was compared. With increasing aphid density the maximum abundance of Rhopalosiphum padi (Linnaeus) remained proportional, but not that of Sitobion avenae (Fabricius), which was constrained by the smaller surface area of ears compared to leaves. There was no evidence of inter-specific competition. Maximum abundance of R. padi and Metopolophium dirhodum (Walker) on leaves did not change proportionally as the proportion of M. dirhodum decreased with increasing overall aphid density. This decrease was probably caused by the restricted distribution of M. dirhodum, which is confined to leaves, where space is limiting. No change in proportion between populations was detected when the average densities were below 0.54 aphids per leaf or ear. Non-proportional relationships between aphid populations appeared to be due to spatial constraints, acting upon the more abundant population. Detecting the limitation of population growth can help with the assessment of when density-independent exponential growth is limited by density-dependent factors. This information may help in the development of models of cereal aphid population dynamics.     

Projection of climate variables by general circulation and deep learning model for Lahore,Pakistan

Climate change significantly impacts the hydrological cycle and environment. The key parameters driving climate change for densely populated city of Lahore in Pakistan were studied. The projections of these parameters were evaluated using General Circulation Model (GCM) named Community Climate System Model (CCSM4) under two Representative Concentration Pathways (RCP 4.5 and 8.5) scenarios. The outputs of CCSM4 model were bias corrected using quantile mapping using historical data. Additionally, a deep learning model named long short-term memory (LSTM) was developed applying machine learning applications to forecast the climate parameters for the future. LSTM model with two LSTM layers including one fully connected layer was modeled for the projection of climate variables in the region. Total number of parameters were 9888, and the input and forecasted output length was kept as 24 sequential months without overlapping. The conventional projection methods of GCM were compared with LSTM outputs for bridging the gap. The LSTM model was found to be more effective and dependable in forecasting the climate with significant improvement in the statistical parameters for the region. The LSTM model can be applied for projections of climate in comparison to GCM with sufficient precision.     

Projecting the future of an alpine ungulate under climate change scenarios

Climate change represents a primary threat to species persistence and biodiversity at a global scale. Cold adapted alpine species are especially sensitive to climate change and can offer key “early warning signs” about deleterious effects of predicted change. Among mountain ungulates, survival, a key determinant of demographic performance, may be influenced by future climate in complex, and possibly opposing ways. Demographic data collected from 447 mountain goats in 10 coastal Alaska, USA, populations over a 37‐year time span indicated that survival is highest during low snowfall winters and cool summers. However, general circulation models (GCMs) predict future increase in summer temperature and decline in winter snowfall. To disentangle how these opposing climate‐driven effects influence mountain goat populations, we developed an age‐structured population model to project mountain goat population trajectories for 10 different GCM/emissions scenarios relevant for coastal Alaska. Projected increases in summer temperature had stronger negative effects on population trajectories than the positive demographic effects of reduced winter snowfall. In 5 of the 10 GCM/representative concentration pathway (RCP) scenarios, the net effect of projected climate change was extinction over a 70‐year time window (2015–2085); smaller initial populations were more likely to go extinct faster than larger populations. Using a resource selection modeling approach, we determined that distributional shifts to higher elevation (i.e., “thermoneutral”) summer range was unlikely to be a viable behavioral adaptation strategy; due to the conical shape of mountains, summer range was expected to decline by 17%–86% for 7 of the 10 GCM/RCP scenarios. Projected declines of mountain goat populations are driven by climate‐linked bottom‐up mechanisms and may have wide ranging implications for alpine ecosystems. These analyses elucidate how projected climate change can negatively alter population dynamics of a sentinel alpine species and provide insight into how demographic modeling can be used to assess risk to species persistence.     

Relative importance of long‐term changes in climate and land‐use on the phenology and abundance of legume crop specialist and generalist aphids

Abstract Insect populations are prone to respond to global changes through shifts in phenology, distribution and abundance. However, global changes cover several factors such as climate and land-use, the relative importance of these being largely unknown. Here, we aim at disentangling the effects of climate, land-use, and geographical drivers on aphid abundance and phenology in France, at a regional scale and over the last 40 years. We used aerial data obtained from suction traps between 1978 and 2015 on five aphid species varying in their degree of specialization to legumes, along with climate, legume crop area and geographical data. Effects of environmental and geographical variables on aphid annual abundance and spring migration dates were analyzed using generalized linear mixed models. We found that within the last four decades, aphids have advanced their spring migration by a month, mostly due to the increase in temperature early in the year, and their abundance decreased by half on average, presumably in response to a combination of factors. The influence of legume crop area decreased with the degree of specialization of the aphid species to such crops. The effect of geographical variation was high even when controlling for environmental variables, suggesting that many other spatially structured processes act on aphid population characteristics. Multifactorial analyses helped to partition the effects of different global change drivers. Climate and land-use changes have strong effects on aphid populations, with important implications for future agriculture. Additionally, trait-based response variation could have major consequences at the community scale.     

Climate and host plant availability impact the future distribution of the bean leaf beetle (Cerotoma trifurcata)

The bean leaf beetle, Cerotoma trifurcata, has become a major pest of soybean throughout its North American range. With a changing climate, there is the potential for this pest to further expand its distribution and become an increasingly severe pest in certain regions. To examine this possibility, we developed bioclimatic envelope models for both the bean leaf beetle, and its most important agronomic host plant, soybean (Glycine max). These two models were combined to examine the potential future pest status of the beetle using climate change projections from multiple general circulation models (GCMs) and climate change scenarios. Despite the broad tolerances of soybean, incorporation of host plant availability substantially decreased the suitable and favourable areas for the bean leaf beetle as compared to an evaluation based solely on the climate envelope of the beetle, demonstrating the importance of incorporating biotic interactions in these predictions. The use of multiple GCM–scenario combinations also revealed differences in predictions depending on the choice of GCM, with scenario choice having less of an impact. While the Norwegian model predicted little northward expansion of the beetle from its current northern range limit of southern Ontario and overall decreases in suitable and favourable areas over time, the Canadian and Russian models predict that much of Ontario and Quebec will become suitable for the beetle in the future, as well as Manitoba under the Russian model. The Russian model also predicts expansion of the suitable and favourable areas for the beetle over time. Two predictions that do not depend on our choice of GCM include a decrease in suitability of the Mississippi Delta region and continued favourability of the southeastern United States.     

Designing ecological climate change impact assessments to reflect key climatic drivers

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.     

Statistical downscaling of general-circulation-model- simulated average monthly air temperature to the beginning of flowering of the dandelion (Taraxacum officinale) in Slovenia

Phenological observations are a valuable source of information for investigating the relationship between climate variation and plant development. Potential climate change in the future will shift the occurrence of phenological phases. Information about future climate conditions is needed in order to estimate this shift. General circulation models (GCM) provide the best information about future climate change. They are able to simulate reliably the most important mean features on a large scale, but they fail on a regional scale because of their low spatial resolution. A common approach to bridging the scale gap is statistical downscaling, which was used to relate the beginning of flowering of Taraxacum officinale in Slovenia with the monthly mean near-surface air temperature for January, February and March in Central Europe. Statistical models were developed and tested with NCAR/NCEP Reanalysis predictor data and EARS predict and data for the period 1960-1999. Prior to developing statistical models, empirical orthogonal function (EOF) analysis was employed on the predictor data. Multiple linear regression was used to relate the beginning of flowering with expansion coefficients of the first three EOF for the Janauary, Febrauary and March air temperatures, and a strong correlation was found between them. Developed statistical models were employed on the results of two GCM (HadCM3 and ECHAM4/OPYC3) to estimate the potential shifts in the beginning of flowering for the periods 1990-2019 and 2020-2049 in comparison with the period 1960-1989. The HadCM3 model predicts, on average, 4 days earlier occurrence and ECHAM4/OPYC3 5 days earlier occurrence of flowering in the period 1990-2019. The analogous results for the period 2020-2049 are a 10- and 11-day earlier occurrence.     

Geographical distribution and phenotypic differentiation in populations of Dactylis glomerata L. in Japan

Although the perennial grass Dactylis glomerata L. has established dominant populations in Japan since its introduction in the 1870s, there have been marked reductions in its abundance in southern and northeastern regions. In order to examine the effects of climatic factors on distribution and differentiation of the naturalized populations of D. glomerata, abundance of 26 populations over a distance of 1500 km along a latitudinal gradient was recorded at each site, and life-history traits of each population were measured in a common garden. It was found that the reduction in abundance was related to the mean summer temperature in southern regions and to the lowest temperature before snow cover in northeastern regions. Recent climatic records in Japan show an increase in the mean summer temperature but no apparent changes in the lowest temperature before snow cover. These data suggest that, assuming the recent trend in climatic changes continues, the population abundance will decrease in southern regions and will change little in the northeastern regions. Germination speed, leaf width and reproductive allocations showed clinal variation over a geographical range, and the southern populations had more rapid germination, narrower leaves and lower reproductive allocation than did the northern populations. On the other hand, seed size and germination date showed margin-center differentiation. Marginal populations in both distributional borders had smaller seeds and lower germination rates than did the central populations. This revised version was published online in June 2006 with corrections to the Cover Date.     

Prevalences of fungal pathogens and othernatural enemies of cereal aphids (Homoptera:Aphididae) in wheat under dryland and irrigatedconditions in South Africa

Surveys were conducted in the summer andwinter rainfall wheat producing regions of SouthAfrica in a first attempt to investigate theidentity and impact of entomopathogenic fungi withinthe cereal aphid complex. Wheat produced underdryland and irrigated conditions was surveyed duringthe 1996 and 1997 seasons. Six cereal aphid specieswere recorded of which the Russian wheat aphid, Diuraphis noxia, was the most abundantunder dryland conditions in the summer rainfallregion as opposed to the oat aphid, Rhopalosiphum padi, in the winter rainfallregion. Rose grain aphid, Metopolophiumdirhodum, was most prevalent underirrigated conditions in the summer rainfall region.Five species of entomopathogenic fungi were recordedincluding four entomophthorales and the hyphomycete,Beauveria bassiana. TheEntomophthorales included Pandora neoaphidis, Conidiobolus obscurus, C.thromboides, and Entomophthoraplanchoniana. Pandora neoaphidis wasthe most important etiological agent recorded fromD. noxia, with up to 50% mycosis recordedunder dryland conditions in the Bethlehem summerrainfall region. Similarly, P. neoaphidis wasthe most prevalent species within populations ofM. dirhodum. under irrigated conditions in theBergville/Winterton summer rainfall region (up to77% mycosis). However, mycoses of R. padi didnot exceed 1.7% in samples from these areas,suggesting that R. padi may be lesssusceptible to P. neoaphidis than M.dirhodum. Epizootics in populations of D.noxia under dryland conditions in both the winterand summer rainfall regions indicated a high levelof susceptibility to P. neoaphidis.Occurrences of hymenopterous parasitoids andpredators in populations of D. noxia were low,although a parasitism level of 25% was recorded inone small sample of R. padi collected from anirrigated field in the summer rainfall region.     

Climate change affects winter chill for temperate fruit and nut trees

Background

Temperate fruit and nut trees require adequate winter chill to produce economically viable yields. Global warming has the potential to reduce available winter chill and greatly impact crop yields.

Methodology/Principal Findings

We estimated winter chill for two past (1975 and 2000) and 18 future scenarios (mid and end 21st century; 3 Global Climate Models [GCMs]; 3 greenhouse gas emissions [GHG] scenarios). For 4,293 weather stations around the world and GCM projections, Safe Winter Chill (SWC), the amount of winter chill that is exceeded in 90% of all years, was estimated for all scenarios using the “Dynamic Model” and interpolated globally. We found that SWC ranged between 0 and about 170 Chill Portions (CP) for all climate scenarios, but that the global distribution varied across scenarios. Warm regions are likely to experience severe reductions in available winter chill, potentially threatening production there. In contrast, SWC in most temperate growing regions is likely to remain relatively unchanged, and cold regions may even see an increase in SWC. Climate change impacts on SWC differed quantitatively among GCMs and GHG scenarios, with the highest GHG leading to losses up to 40 CP in warm regions, compared to 20 CP for the lowest GHG.

Conclusions/Significance

The extent of projected changes in winter chill in many major growing regions of fruits and nuts indicates that growers of these commodities will likely experience problems in the future. Mitigation of climate change through reductions in greenhouse gas emissions can help reduce the impacts, however, adaption to changes will have to occur. To better prepare for likely impacts of climate change, efforts should be undertaken to breed tree cultivars for lower chilling requirements, to develop tools to cope with insufficient winter chill, and to better understand the temperature responses of tree crops.     

Modelling changes in species’ abundance in response to projected climate change

Aim Existing climate envelope models give an indication of broad scale shifts in distribution, but do not specifically provide information on likely future population changes useful for conservation prioritization and planning. We demonstrate how these techniques can be developed to model likely future changes in absolute density and population size as a result of climate change. Location Great Britain. Methods Generalized linear models were used to model breeding densities of two northerly‐ and two southerly‐distributed bird species as a function of climate and land use. Models were built using count data from extensive national bird monitoring data and incorporated detectability to estimate absolute abundance. Projections of likely future changes in the distribution and abundance of these species were made by applying these models to projections of future climate change under two emissions scenarios. Results Models described current spatial variation in abundance for three of the four species and produced modelled current estimates of national populations that were similar to previously published estimates for all species. Climate change was projected to result in national population declines in the two northerly‐distributed species, with declines for Eurasian curlew Numenius arquata projected to be particularly severe. Conversely, the abundances of the two southerly distributed species were projected to increase nationally. Projected maps of future abundance may be used to identify priority areas for the future conservation of each species. Main conclusions The analytical methods provide a framework to make projections of impacts of climate change on species abundance, rather than simply projected range changes. Outputs may be summarized at any spatial scale, providing information to inform future conservation planning at national, regional and local scales. Results suggest that as a consequence of climate change, northerly distributed bird species in Great Britain are likely to become an increasingly high conservation priority within the UK.     

Predicting the wetland distributions under climate warming in the Great Xing’an Mountains,northeastern China

The wetland ecosystem is particularly vulnerable to hydrological and climate changes. The Great Xing’an Mountain is such a region in China that has a large area of wetlands with rare human disturbance. The predictions of the global circulation model CGCM3 (the third-generation coupled global climate model from the Canadian Centre for Climate Modeling and Analysis) indicated that the temperature in The Great Xing’an Mountain will rise by 2–4°C over the next 100 years. This paper predicts the potential distributions of wetlands in this area under the current and warming climate conditions. This predication was performed by the Random Forests model, with 18 environmental variables, which will reflect the climate and topography conditions. The model has been proven to have a great prediction ability. The wetland distributions are primarily topography-driven in the Great Xing’an Mountains. Mean annual temperature, warmness index, and potential evapotranspiration ratio are the most important climatic factors in wetland distributions. The model predictions for three future climate scenarios show that the wetland area tends to decrease, and higher emission will also cause more drastic shrinkage of wetland distributions. About 30% of the wetland area will disappear by 2050. The area will decrease 62.47, 76.90, and 85.83%, respectively, under CGCM3-B1, CGCM3-A1B, and CGCM3-A2 by 2100. As for spatial allocation, wetlands may begin to disappear from the sides to the center and south to north under a warming climate. Under CGCM3-B1, the loss of wetlands may mainly occur in the south hills with flatter terrain, and some may occur in the north hills and intermontane plains. Under CGCM3-A1B, severe vanish of wetlands is predicted. Under CGCM3-A2, only a small area of wetlands may remain in the north of the high mountains.     

Impact of twenty-first century climate change on diadromous fish spread over Europe, North Africa and the Middle East

Climate change is expected to drive species ranges towards the poles and to have a strong influence on species distributions. In this study, we focused on diadromous species that are of economical and ecological importance in the whole of Europe. We investigated the potential distribution of all diadromous fish regularly encountered in Europe, North Africa and the Middle East (28 species) under conditions predicted for twenty‐first century climate change. To do so, we investigated the 1900 distribution of each species in 196 basins spread across all of Europe, North Africa and the Middle East. Four levels were used to semiquantitatively describe the abundance of species, that is missing, rare, common and abundant. We then selected five variables describing the prevailing climate in the basins, the physical nature of the basins and reflecting historical events known to have affected freshwater fish distribution. Logistic regressions with a four‐level ordinal response variable were used to develop species‐specific models. These predictive models related the observed distribution of these species in 1900 to the most explanatory combination of variables. Finally, we selected the A2 SRES scenario and the HadCM3 (Hadley Centre Coupled Model version 3) global climate model (GCM) to obtain climate variables (temperature and precipitation) at the end of this century. We used these 2100 variables in our models and obtained maps of climatically suitable and unsuitable basins, percentages of contraction or expansion for each species. Twenty‐two models were successfully built, that is there were five species for which no model could be established because their distribution range was too narrow and the Acipenser sturio model failed during calibration. All the models selected temperature or/and precipitation as explanatory variables. Responses to climate change were species‐specific but could be classified into three categories: little or no change in the distribution (five species), expansion of the distribution range (three species gaining suitable basins mainly northward) and contraction of the distribution (14 species losing suitable basins). Shifting ranges were in accordance with those found in other studies and underlined the high sensitivity of diadromous fish to modifications in their environment.     

Hydrological Response to Climate Change for Gilgel Abay River,in the Lake Tana Basin - Upper Blue Nile Basin of Ethiopia

Climate change is likely to have severe effects on water availability in Ethiopia. The aim of the present study was to assess the impact of climate change on the Gilgel Abay River, Upper Blue Nile Basin. The Statistical Downscaling Tool (SDSM) was used to downscale the HadCM3 (Hadley centre Climate Model 3) Global Circulation Model (GCM) scenario data into finer scale resolution. The Soil and Water Assessment Tool (SWAT) was set up, calibrated, and validated. SDSM downscaled climate outputs were used as an input to the SWAT model. The climate projection analysis was done by dividing the period 2010-2100 into three time windows with each 30 years of data. The period 1990-2001 was taken as the baseline period against which comparison was made. Results showed that annual mean precipitation may decrease in the first 30-year period but increase in the following two 30-year periods. The decrease in mean monthly precipitation may be as much as about -30% during 2010-2040 but the increase may be more than +30% in 2070-2100. The impact of climate change may cause a decrease in mean monthly flow volume between -40% to -50% during 2010-2040 but may increase by more than the double during 2070-2100. Climate change appears to have negligible effect on low flow conditions of the river. Seasonal mean flow volume, however, may increase by more than the double and +30% to +40% for the Belg (small rainy season) and Kiremit (main rainy season) periods, respectively. Overall, it appears that climate change will result in an annual increase in flow volume for the Gilgel Abay River. The increase in flow is likely to have considerable importance for local small scale irrigation activities. Moreover, it will help harnessing a significant amount of water for ongoing dam projects in the Gilgel Abay River Basin.     

Climate change and broadacre livestock production across southern Australia. 1. Impacts of climate change on pasture and livestock productivity,and on sustainable levels of profitability

Broadacre livestock production is a major but highly diverse component of agriculture in Australia that will be significantly exposed to predicted changes in climate over coming decades. We used the GRAZPLAN simulation models to assess the impacts of climate change under the SRES A2 scenario across southern Australia. Climate change impacts were examined across space (25 representative locations) and time (1970–99, 2030, 2050 and 2070 climate) for each of five livestock enterprises. Climate projection uncertainty was considered by analysing projections from four global circulation models (GCMs). Livestock production scenarios were compared at their profit‐maximizing stocking rate, constrained to ensure that risks of soil erosion were acceptable. Impacts on net primary productivity (ANPP) varied widely between GCM projections; the average declines from historical climate were 9% in 2030, 7% in 2050 and 14% in 2070. Declines in ANPP were larger at lower‐rainfall locations. Sensitivity of ANPP to changes in rainfall ranged from 0.4 to 1.7, to temperature increase from ?0.15 to +0.07 °C^?1 and to CO₂ increase from 0.11 to 0.32. At most locations the dry summer period lengthened, exacerbating the greater erosion risk due to lower ANPP. Transpiration efficiency of pastures increased by 6–25%, but the proportion of ANPP that could safely be consumed by livestock fell sharply so that operating profit (at constant prices) fell by an average of 27% in 2030, 32% in 2050 and 48% in 2070. This amplification of ANPP reductions into larger profitability declines is likely to generalize to other extensive livestock systems. Profit declines were most marked at drier locations, with operating losses expected at 9 of the 25 locations by 2070. Differences between livestock enterprises were smaller than differences between locations and dates. Future research into climate change impacts on Australian livestock production needs to emphasise the dry margin of the cereal‐livestock zone.