Modeling climate change impacts on overwintering bald eagles

Bald eagles (Haliaeetus leucocephalus) are recovering from severe population declines, and are exerting pressure on food resources in some areas. Thousands of bald eagles overwinter near Puget Sound, primarily to feed on chum salmon (Oncorhynchus keta) carcasses. We used modeling techniques to examine how anticipated climate changes will affect energetic demands of overwintering bald eagles. We applied a regional downscaling method to two global climate change models to obtain hourly temperature, precipitation, wind, and longwave radiation estimates at the mouths of three Puget Sound tributaries (the Skagit, Hamma Hamma, and Nisqually rivers) in two decades, the 1970s and the 2050s. Climate data were used to drive bald eagle bioenergetics models from December to February for each river, year, and decade. Bald eagle bioenergetics were insensitive to climate change: despite warmer winters in the 2050s, particularly near the Nisqually River, bald eagle food requirements declined only slightly (<1%). However, the warming climate caused salmon carcasses to decompose more rapidly, resulting in 11% to 14% less annual carcass biomass available to eagles in the 2050s. That estimate is likely conservative, as it does not account for decreased availability of carcasses due to anticipated increases in winter stream flow. Future climate-driven declines in winter food availability, coupled with a growing bald eagle population, may force eagles to seek alternate prey in the Puget Sound area or in more remote ecosystems.     

Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?

Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species’ bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate envelope models and discusses the implications of these criticisms for the different modelling strategies employed. It is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity. However, it is stressed that the spatial scale at which these models are applied is of fundamental importance, and that model results should not be interpreted without due consideration of the limitations involved. A hierarchical modelling framework is proposed through which some of these limitations can be addressed within a broader, scale‐dependent context.     

Validation of species–climate impact models under climate change

Increasing concern over the implications of climate change for biodiversity has led to the use of species–climate envelope models to project species extinction risk under climate‐change scenarios. However, recent studies have demonstrated significant variability in model predictions and there remains a pressing need to validate models and to reduce uncertainties. Model validation is problematic as predictions are made for events that have not yet occurred. Resubstituition and data partitioning of present‐day data sets are, therefore, commonly used to test the predictive performance of models. However, these approaches suffer from the problems of spatial and temporal autocorrelation in the calibration and validation sets. Using observed distribution shifts among 116 British breeding‐bird species over the past ～20 years, we are able to provide a first independent validation of four envelope modelling techniques under climate change. Results showed good to fair predictive performance on independent validation, although rules used to assess model performance are difficult to interpret in a decision‐planning context. We also showed that measures of performance on nonindependent data provided optimistic estimates of models' predictive ability on independent data. Artificial neural networks and generalized additive models provided generally more accurate predictions of species range shifts than generalized linear models or classification tree analysis. Data for independent model validation and replication of this study are rare and we argue that perfect validation may not in fact be conceptually possible. We also note that usefulness of models is contingent on both the questions being asked and the techniques used. Implementations of species–climate envelope models for testing hypotheses and predicting future events may prove wrong, while being potentially useful if put into appropriate context.     

Projected climate impacts to South African maize and wheat production in 2055: a comparison of empirical and mechanistic modeling approaches

Crop model‐specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs’ median‐projected maize and wheat yield changes were ?3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water‐use efficiency gains simulated by the MMs under elevated CO₂ accounted for much of the EM?MM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EM?MM comparisons to provide a fuller picture of crop–climate response uncertainties.     

Where will species go? Incorporating new advances in climate modelling into projections of species distributions

Bioclimatic models are the primary tools for simulating the impact of climate change on species distributions. Part of the uncertainty in the output of these models results from uncertainty in projections of future climates. To account for this, studies often simulate species responses to climates predicted by more than one climate model and/or emission scenario. One area of uncertainty, however, has remained unexplored: internal climate model variability. By running a single climate model multiple times, but each time perturbing the initial state of the model slightly, different but equally valid realizations of climate will be produced. In this paper, we identify how ongoing improvements in climate models can be used to provide guidance for impacts studies. In doing so we provide the first assessment of the extent to which this internal climate model variability generates uncertainty in projections of future species distributions, compared with variability between climate models. We obtained data on 13 realizations from three climate models (three from CSIRO Mark2 v3.0, four from GISS AOM, and six from MIROC v3.2) for two time periods: current (1985–1995) and future (2025–2035). Initially, we compared the simulated values for each climate variable (P, T_max, T_min, and T_mean) for the current period to observed climate data. This showed that climates simulated by realizations from the same climate model were more similar to each other than to realizations from other models. However, when projected into the future, these realizations followed different trajectories and the values of climate variables differed considerably within and among climate models. These had pronounced effects on the projected distributions of nine Australian butterfly species when modelled using the BIOCLIM component of DIVA-GIS. Our results show that internal climate model variability can lead to substantial differences in the extent to which the future distributions of species are projected to change. These can be greater than differences resulting from between-climate model variability. Further, different conclusions regarding the vulnerability of species to climate change can be reached due to internal model variability. Clearly, several climate models, each represented by multiple realizations, are required if we are to adequately capture the range of uncertainty associated with projecting species distributions in the future.     

The impacts of climate change on the annual cycles of birds

Organisms living today are descended from ancestors that experienced considerable climate change in the past. However, they are currently presented with many new, man-made challenges, including rapid climate change. Migration and reproduction of many avian species are controlled by endogenous mechanisms that have been under intense selection over time to ensure that arrival to and departure from breeding grounds is synchronized with moderate temperatures, peak food availability and availability of nesting sites. The timing of egg laying is determined, usually by both endogenous clocks and local factors, so that food availability is near optimal for raising young. Climate change is causing mismatches in food supplies, snow cover and other factors that could severely impact successful migration and reproduction of avian populations unless they are able to adjust to new conditions. Resident (non-migratory) birds also face challenges if precipitation and/or temperature patterns vary in ways that result in mismatches of food and breeding. Predictions that many existing climates will disappear and novel climates will appear in the future suggest that communities will be dramatically restructured by extinctions and changes in range distributions. Species that persist into future climates may be able to do so in part owing to the genetic heritage passed down from ancestors who survived climate changes in the past.     

Investigating the potential impacts of climate change on a marine turtle population

Recent increases in global temperatures have affected the phenology and survival of many species of plants and animals. We investigated a case study of the effects of potential climate change on a thermally sensitive species, the loggerhead sea turtle, at a breeding location at the northerly extent of the range of regular nesting in the United States. In addition to the physical limits imposed by temperature on this ectothermic species, sea turtle primary sex ratio is determined by the temperature experienced by eggs during the middle third of incubation. We recorded sand temperatures and used historical air temperatures (ATs) at Bald Head Island, NC, to examine past and predict future sex ratios under scenarios of warming. There were no significant temporal trends in primary sex ratio evident in recent years and estimated mean annual sex ratio was 58% female. Similarly, there were no temporal trends in phenology but earlier nesting and longer nesting seasons were correlated with warmer sea surface temperature. We modelled the effects of incremental increases in mean AT of up to 7.5°C, the maximum predicted increase under modelled scenarios, which would lead to 100% female hatchling production and lethally high incubation temperatures, causing reduction in hatchling production. Populations of turtles in more southern parts of the United States are currently highly female biased and are likely to become ultra‐biased with as little as 1°C of warming and experience extreme levels of mortality if warming exceeds 3°C. The lack of a demonstrable increase in AT in North Carolina in recent decades coupled with primary sex ratios that are not highly biased means that the male offspring from North Carolina could play an increasingly important role in the future viability of the loggerhead turtle in the Western Atlantic.     

Potential impacts of climate change on the winter distribution of Afro-Palaearctic migrant passerines

We modelled the present and future sub-Saharan winter distributions of 64 trans-Saharan migrant passerines to predict the potential impacts of climate change. These predictions used the recent ensemble modelling developments and the latest IPCC climatic simulations to account for possible methodological uncertainties. Results suggest that 37 species would face a range reduction by 2100 (16 of these by more than 50%); however, the median range size variation is −13 per cent (from −97 to +980%) under a full dispersal hypothesis. Range centroids were predicted to shift by 500±373 km. Predicted changes in range size and location were spatially structured, with species that winter in southern and eastern Africa facing larger range contractions and shifts. Predicted changes in regional species richness for these long-distance migrants are increases just south of the Sahara and on the Arabian Peninsula and major decreases in southern and eastern Africa.     

The potential impacts of global climate change on marine protected areas

The potential effects of global climate changeon marine protected areas do not appear to havebeen addressed in the literature. This paperexamines the literature on protected areas,conservation biology, marine ecology,oceanography, and climate change, and reviewssome of the relevant differences between marineand terrestrial environments. Frameworks andclassifications systems used in protected areadesign are discussed. Finally, a frameworkthat summarizes some of the importantoceanographic processes and their links to thefood chain are reviewed. Species abundance anddistribution are expected to change as a resultof global climate change, potentiallycompromising the efficacy of marine protectedareas as biodiversity conservation tools. Thisreview suggests the need for: furtherinterdisciplinary research and the use oflinked models; an increase in marine protectedareas for biodiversity conservation and asresearch sites for teasing apart fishingeffects from climate effects; a temporallyresponsive approach to siting new marineprotected areas, shifting their locations ifnecessary; and large-scale ecosystem/integratedmanagement approaches to address the competinguses of the oceans and boundary-less threatssuch as global climate change and pollution.     

Possible impacts of climate change on natural vegetation in Saxony (Germany)

Recent climate changes have had distinct impacts on plant development in many parts of the world. Higher air temperatures, mainly since the end of the 1980s, have led to advanced timing of phenological phases and consequently to an extension of the general growing season. For this reason it is interesting to know how plants will respond to future climate change. In this study simple phenological models have been developed to estimate the impact of climate change on the natural vegetation in Saxony. The estimations are based on a regional climate scenario for the state of Saxony. The results indicate that changes in the timing of phenophases could continue in the future. Due to distinct temperature changes in winter and in summer, mainly the spring and summer phases will be advanced. Spring phenophases, such as leafing or flowering, show the strongest trends. Depending on the species, the average timing of these phenophases could be advanced by 3–27 days by 2050. Phenophases in autumn show relatively small changes. Thus, the annual growth period of individual trees will be further extended, mainly because of the shift of spring phases. Frequent droughts in summer and in autumn can compensate for the earlier leafing of trees, because in this case leaf colouring and leaf fall would start some weeks earlier. In such cases, the growing period would not be really extended, but shifted to the beginning of the year.     

Disentangling effects of uncertainties on population projections: climate change impact on an epixylic bryophyte

Assessment of future ecosystem risks should account for the relevant uncertainty sources. This means accounting for the joint effects of climate variables and using modelling techniques that allow proper treatment of uncertainties. We investigate the influence of three of the IPCC's scenarios of greenhouse gas emissions (special report on emission scenarios (SRES)) on projections of the future abundance of a bryophyte model species. We also compare the relative importance of uncertainty sources on the population projections. The whole chain global climate model (GCM)-regional climate model-population dynamics model is addressed. The uncertainty depends on both natural- and model-related sources, in particular on GCM uncertainty. Ignoring the uncertainties gives an unwarranted impression of confidence in the results. The most likely population development of the bryophyte Buxbaumia viridis towards the end of this century is negative: even with a low-emission scenario, there is more than a 65 per cent risk for the population to be halved. The conclusion of a population decline is valid for all SRES scenarios investigated. Uncertainties are no longer an obstacle, but a mandatory aspect to include in the viability analysis of populations.     

Disparities between observed and predicted impacts of climate change on winter bird assemblages

Understanding how climate change affects the structure and function of communities is critical for gauging its full impact on biodiversity. To date, community-level changes have been poorly documented, owing, in part, to the paucity of long-term datasets. To circumvent this, the use of ‘space-for-time’ substitution—the forecasting of temporal trends from spatial climatic gradients—has increasingly been adopted, often with little empirical support. Here we examine changes from 1975 to 2001 in three community attributes (species richness, body mass and occupancy) for 404 assemblages of terrestrial winter avifauna in North America containing a total of 227 species. We examine the accuracy of space-for-time substitution and assess causal associations between community attributes and observed changes in annual temperature using a longitudinal study design. Annual temperature and all three community attributes increased over time. The trends for the three community attributes differed significantly from the spatially derived predictions, although richness showed broad congruence. Correlations with trends in temperature were found with richness and body mass. In the face of rapid climate change, applying space-for-time substitution as a predictive tool could be problematic with communities developing patterns not reflected by spatial ecological associations.     

Impacts of climate change on the seasonal distribution of migratory caribou

Arctic ecosystems are especially vulnerable to global climate change as temperature and precipitation regimes are altered. An ecologically and socially highly important northern terrestrial species that may be impacted by climate change is the caribou, Rangifer tarandus . We predicted the current and potential future occurrence of two migratory herds of caribou [Rivière George herd (RG) and Rivière-aux-Feuilles (RAF) herd] under a Canadian General Circulation Model climate change scenario, across all seasons in the Québec–Labrador peninsula, using climatic and habitat predictor variables. Argos satellite-tracking collars have been deployed on 213 caribou between 1988 and 2003 with locations recorded every 4–5 days. In addition, we assembled a database of climate (temperature, precipitation, snowfall, timing and length of growing season) and habitat data obtained from the SPOT VEGETATION satellite sensor. Logistic regression models indicated that both climatic and physical habitat variables were significant predictors of current migratory caribou occurrence. Migratory caribou appeared to prefer regions with higher snowfall and lichen availability in the fall and winter. In the summer, caribou preferred cooler areas likely corresponding to a lower prevalence of insects, and they avoided disturbed and recently burnt areas. Climate change projections using climate data predicted an increased range for the RAF herd and decreased range for the RG herd during 2040–2069, limiting the herds to northeastern regions of the Québec–Labrador peninsula. Direct and indirect consequences of climate change on these migratory caribou herds possibly include alteration in habitat use, migration patterns, foraging behaviour, and demography, in addition to social and economic stress to arctic and subarctic native human populations.     

Spatial and temporal variation of phenological growing season and climate change impacts in temperate eastern China

Using phenological and normalized difference vegetation index (NDVI) data from 1982 to 1993 at seven sample stations in temperate eastern China, we calculated the cumulative frequency of leaf unfolding and leaf coloration dates for deciduous species every 5 days throughout the study period. Then, we determined the growing season beginning and end dates by computing times when 50% of the species had undergone leaf unfolding and leaf coloration for each station year. Next, we used these beginning and end dates of the growing season as time markers to determine corresponding threshold NDVI values on NDVI curves for the pixels overlaying phenological stations. Based on a cluster analysis, we determined extrapolation areas for each phenological station in every year, and then implemented the spatial extrapolation of growing season parameters from the seven sample stations to all possible meteorological stations in the study area. Results show that spatial patterns of growing season beginning and end dates correlate significantly with spatial patterns of mean air temperatures in spring and autumn, respectively. Contrasting with results from similar studies in Europe and North America, our study suggests that there is a significant delay in leaf coloration dates, along with a less pronounced advance of leaf unfolding dates in different latitudinal zones and the whole area from 1982 to 1993. The growing season has been extended by 1.4–3.6 days per year in the northern zones and by 1.4 days per year across the entire study area on average. The apparent delay in growing season end dates is associated with regional cooling from late spring to summer, while the insignificant advancement in beginning dates corresponds to inconsistent temperature trend changes from late winter to spring. On an interannual basis, growing season beginning and end dates correlate negatively with mean air temperatures from February to April and from May to June, respectively.     

Potential impacts of climate change on the distributions and diversity patterns of European mammals

The Intergovernmental Panel on Climate Change (IPCC) predicts an increase in global temperatures of between 1.4°C and 5.8°C during the 21st century, as a result of elevated CO₂ levels. Using bioclimatic envelope models, we evaluate the potential impact of climate change on the distributions and species richness of 120 native terrestrial non-volant European mammals under two of IPCC’s future climatic scenarios. Assuming unlimited and no migration, respectively, our model predicts that 1% or 5–9% of European mammals risk extinction, while 32–46% or 70–78% may be severely threatened (lose > 30% of their current distribution) under the two scenarios. Under the no migration assumption endemic species were predicted to be strongly negatively affected by future climatic changes, while widely distributed species would be more mildly affected. Finally, potential mammalian species richness is predicted to become dramatically reduced in the Mediterranean region but increase towards the northeast and for higher elevations. Bioclimatic envelope models do not account for non-climatic factors such as land-use, biotic interactions, human interference, dispersal or history, and our results should therefore be seen as first approximations of the potential magnitude of future climatic changes.     

The ability of climate envelope models to predict the effect of climate change on species distributions

Climate envelope models (CEMs) have been used to predict the distribution of species under current, past, and future climatic conditions by inferring a species' environmental requirements from localities where it is currently known to occur. CEMs can be evaluated for their ability to predict current species distributions but it is unclear whether models that are successful in predicting current distributions are equally successful in predicting distributions under different climates (i.e. different regions or time periods). We evaluated the ability of CEMs to predict species distributions under different climates by comparing their predictions with those obtained with a mechanistic model (MM). In an MM the distribution of a species is modeled based on knowledge of a species' physiology. The potential distributions of 100 plant species were modeled with an MM for current conditions, a past climate reconstruction (21 000 years before present) and a future climate projection (double preindustrial CO₂ conditions). Point localities extracted from the currently suitable area according to the MM were used to predict current, future, and past distributions with four CEMs covering a broad range of statistical approaches: Bioclim (percentile distributions), Domain (distance metric), GAM (general additive modeling), and Maxent (maximum entropy). Domain performed very poorly, strongly underestimating range sizes for past or future conditions. Maxent and GAM performed as well under current climates as under past and future climates. Bioclim slightly underestimated range sizes but the predicted ranges overlapped more with the ranges predicted with the MM than those predicted with GAM did. Ranges predicted with Maxent overlapped most with those produced with the MMs, but compared with the ranges predicted with GAM they were more variable and sometimes much too large. Our results suggest that some CEMs can indeed be used to predict species distributions under climate change, but individual modeling approaches should be validated for this purpose, and model choice could be made dependent on the purpose of a particular study.     

Modelling adaptive management strategies for coping with the impacts of climate variability and change on riverine algal blooms

The impact of climate change on hydrology and water resources is one of the most critical issues facing the world in the next few decades. In particular, there is a need to quantify the risks associated with maintaining the security of resource quantity and quality, and to assess the effectiveness of potential management strategies. In this paper, we assess the impacts of climate variability and change on one aspect of river health. A simple model of Anabaena algal bloom occurrence at a weir pool in the lower Murrumbidgee River, Australia, has been coupled to a catchment model that is used to simulate streamflow, irrigation demand and diversions, dam water storage and releases, and decision-making by both irrigators and managers. Long-term climate data are obtained from a statistical downscaling algorithm, which, when applied to global climate model predictions can provide climate data suitable for driving the coupled model under a variety of climatic scenarios. The coupled model is then used to assess the impact of climate variability and projected climate change on the frequency, duration and magnitude of Anabaena blooms. The impact of two management strategies for bloom control are also assessed and it is shown that even a single, quite simple, resource-neutral, adaptive management strategy has the potential to substantially reduce the occurrence and impact of algal blooms and to more than compensate for the deleterious impacts of climate change. This result supports the notion that planning for the future can lead to positive outcomes in the present.     

Assessing effects of forecasted climate change on the diversity and distribution of European higher plants for 2050

The rapidly increasing atmospheric concentrations of greenhouse gases may lead to significant changes in regional and seasonal climate patterns. Such changes can strongly influence the diversity and distribution of species and, therefore, affect ecosystems and biodiversity. To assess these changes we developed a model, called euromove. The model uses climate data from 1990 to 2050 as compiled from the image 2 model, and determines climate envelopes for about 1400 plant species by multiple logistic regression analysis. The climate envelopes were applied to the projected climate to obtain predictions about plant diversity and distributions by 2050. For each European grid cell, euromove calculates which species would still occur in forecasted future climate conditions and which not. The results show major changes in biodiversity by 2050. On average, 32% of the European plant species that were present in a cell in 1990 would disappear from that cell. The area, in which 32% or more of the 1990 species will disappear, takes up 44% of the modelled European area. Individual responses of the plant species to the forecasted climate change were diverse. In reviewing possible future trends, we found that plant species, in general, would find their current climate envelopes further northeast by 2050, shifting ranges that were comparable with those ranges in other studies.     

Influence of simulated climate change and eutrophication on three‐spined stickleback populations: a large scale mesocosm experiment

1. Shallow lakes and their ectothermic inhabitants are particularly vulnerable to the effects of climatic warming. These impacts are likely to depend on nutrient loading, especially if the combination of warming and eutrophication leads to severe hypoxia. 2. To investigate effects of realistic warming and nutrient loading on a fish species with high tolerance of warming and hypoxia, we observed population changes and timing of reproduction of three‐spined sticklebacks in 24 outdoor shallow freshwater ecosystems with combinations of temperature (ambient and ambient +4 °C) and three nutrient treatments over 16 months. 3. Warming reduced stickleback population biomass by 60% (population size by 76%) and nutrient‐addition reduced biomass by about 80% (population size 95%). Nutrients and warming together resulted in extinction of the stickleback populations. These losses were mainly attributed to the increased likelihood of severe hypoxia in heated and nutrient‐addition mesocosms. 4. Warming of nutrient‐rich waters can thus have dire consequences for freshwater ectotherm populations. The loss even of a hardy fish suggests a precarious future for many less tolerant species in such eutrophic systems under current climate change predictions.