Using a climatic niche model to predict the direct and indirect impacts of climate change on the distribution of Douglas‐fir in New Zealand

Climate change is likely to have major impacts on the distribution of planted and natural forests. Herein, we demonstrate how a process‐based niche model (CLIMEX) can be extended to globally project the potential habitat suitable for Douglas‐fir. Within this distribution, we use CLIMEX to predict abundance of the pathogen P haeocryptopus gaeumannii and severity of its associated foliage disease, Swiss needle cast. The distribution and severity of the disease, which can strongly reduce growth rate of Douglas‐fir, is closely correlated with seasonal temperatures and precipitation. This model is used to project how climate change during the 2080s may alter the area suitable for Douglas‐fir plantations within New Zealand. The climate change scenarios used indicate that the land area suitable for Douglas‐fir production in the North Island will be reduced markedly from near 100% under current climate to 36–64% of the total land area by 2080s. Within areas shown to be suitable for the host in the North Island, four of the six climate change scenarios predict substantial increases in disease severity that will make these regions at best marginal for Douglas‐fir by the 2080s. In contrast, most regions in the South Island are projected to sustain relatively low levels of disease, and remain suitable for Douglas‐fir under climate change over the course of this century.     

Identifying climate refugia and its potential impact on Tibetan brown bear (Ursus arctos pruinosus) in Sanjiangyuan National Park,China

Climate change has direct impacts on wildlife and future biodiversity protection efforts. Vulnerability assessment and habitat connectivity analyses are necessary for drafting effective conservation strategies for threatened species such as the Tibetan brown bear (Ursus arctos pruinosus). We used the maximum entropy (MaxEnt) model to assess the current (1950–2000) and future (2041–2060) habitat suitability by combining bioclimatic and environmental variables, and identified potential climate refugia for Tibetan brown bears in Sanjiangyuan National Park, China. Next, we selected Circuit model to simulate potential migration paths based on current and future climatically suitable habitat. Results indicate a total area of potential suitable habitat under the current climate scenario of approximately 31,649.46 km², of which 28,778.29 km² would be unsuitable by the 2050s. Potentially suitable habitat under the future climate scenario was projected to cover an area of 23,738.6 km². Climate refugia occupied 2,871.17 km², primarily in the midwestern and northeastern regions of Yangtze River Zone, as well as the northern region of Yellow River Zone. The altitude of climate refugia ranged from 4,307 to 5,524 m, with 52.93% lying at altitudes between 4,300 and 4,600 m. Refugia were mainly distributed on bare rock, alpine steppe, and alpine meadow. Corridors linking areas of potentially suitable brown bear habitat and a substantial portion of paths with low‐resistance value were distributed in climate refugia. We recommend various actions to ameliorate the impact of climate change on brown bears, such as protecting climatically suitable habitat, establishing habitat corridors, restructuring conservation areas, and strengthening monitoring efforts.     

Trends and uncertainties in budburst projections of Norway spruce in Northern Europe

Budburst is regulated by temperature conditions, and a warming climate is associated with earlier budburst. A range of phenology models has been developed to assess climate change effects, and they tend to produce different results. This is mainly caused by different model representations of tree physiology processes, selection of observational data for model parameterization, and selection of climate model data to generate future projections. In this study, we applied (i) Bayesian inference to estimate model parameter values to address uncertainties associated with selection of observational data, (ii) selection of climate model data representative of a larger dataset, and (iii) ensembles modeling over multiple initial conditions, model classes, model parameterizations, and boundary conditions to generate future projections and uncertainty estimates. The ensemble projection indicated that the budburst of Norway spruce in northern Europe will on average take place 10.2 ± 3.7 days earlier in 2051–2080 than in 1971–2000, given climate conditions corresponding to RCP 8.5. Three provenances were assessed separately (one early and two late), and the projections indicated that the relationship among provenance will remain also in a warmer climate. Structurally complex models were more likely to fail predicting budburst for some combinations of site and year than simple models. However, they contributed to the overall picture of current understanding of climate impacts on tree phenology by capturing additional aspects of temperature response, for example, chilling. Model parameterizations based on single sites were more likely to result in model failure than parameterizations based on multiple sites, highlighting that the model parameterization is sensitive to initial conditions and may not perform well under other climate conditions, whether the change is due to a shift in space or over time. By addressing a range of uncertainties, this study showed that ensemble modeling provides a more robust impact assessment than would a single phenology model run.     

Anticipated climate and land‐cover changes reveal refuge areas for Borneo's orang‐utans

Habitat loss and climate change pose a double jeopardy for many threatened taxa, making the identification of optimal habitat for the future a conservation priority. Using a case study of the endangered Bornean orang‐utan, we identify environmental refuges by integrating bioclimatic models with projected deforestation and oil‐palm agriculture suitability from the 1950s to 2080s. We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s. We then projected to the 2020s, 2050s and 2080s in models incorporating only land‐cover change, climate change or both processes combined. For future climate, we incorporated projections from four model and emission scenario combinations. For future land cover, we developed spatial deforestation predictions from 10 years of satellite data. Refuges were delineated as suitable forested habitats identified by all models that were also unsuitable for oil palm – a major threat to tropical biodiversity. Our analyses indicate that in 2010 up to 260 000 km² of Borneo was suitable habitat within the core orang‐utan range; an 18–24% reduction since the 1950s. Land‐cover models predicted further decline of 15–30% by the 2080s. Although habitat extent under future climate conditions varied among projections, there was majority consensus, particularly in north‐eastern and western regions. Across projections habitat loss due to climate change alone averaged 63% by 2080, but 74% when also considering land‐cover change. Refuge areas amounted to 2000–42 000 km² depending on thresholds used, with 900–17 000 km² outside the current species range. We demonstrate that efforts to halt deforestation could mediate some orang‐utan habitat loss, but further decline of the most suitable areas is to be expected given projected changes to climate. Protected refuge areas could therefore become increasingly important for ongoing translocation efforts. We present an approach to help identify such areas for highly threatened species given environmental changes expected this century.     

气候变化对东北濒危动物驼鹿潜在生境的影响

气候变化是造成生物多样性下降和物种灭绝的主要因素之一。研究气候变化对物种生境,尤其是濒危物种生境影响对未来保护物种多样性和保持生态系统功能完整性具有重要意义。以驼鹿乌苏里亚种(Alces alces cameloides)为研究对象,选取了对驼鹿分布可能存在影响的22个环境因子,利用最大熵(Maxent)模型模拟了驼鹿基准气候条件下在我国东北的潜在生境分布,并预测了RCP4.5和RCP8.5两种气候变化情景下2041—2060年(2050s)、2061—2080年(2070s)驼鹿潜在分布,采用接收工作曲线下面积(AUC)对模型预测能力进行评估。研究结果表明:最大熵模型预测驼鹿潜在生境分布的精度较高(平均AUC值为0.845),22个环境因子中,年均温、最暖季均温、年降水、平均日较差是影响驼鹿生境分布的主要因子。基准气候条件下,驼鹿的潜在生境面积占研究区域总面积的36.4%,潜在生境分布区主要在大、小兴安岭。随着时间的推移,研究区内驼鹿当前潜在生境面积明显减少,而新增潜在生境面积较少,总面积呈现急剧减少的趋势,其中RCP8.5情景减少程度大于RCP4.5情景。至2050s阶段,当前潜在生境面积平均将减少62.3%,新增潜在分布面积平均仅为3.6%,总潜在生境面积最高将减少65.6%,平均将减少58.8%;至2070s阶段,当前潜在生境面积平均将减少75.8%,新增潜在分布面积平均仅为1.9%,总潜在生境面积最高将减少93.1%,平均减少73.9%。空间分布上,驼鹿的潜在生境的几何中心将先向西北移动,然后再向高纬度地区西南方向迁移,至2050s阶段,潜在分布生境的几何中心在RCP4.5和RCP8.5情景下的迁移距离分别为183.5 km和210.8 km;至2070s阶段,相应情景下的迁移距离将缩短至28.7 km和33.8 km。潜在生境分布整体呈现向高海拔、高纬度迁移的趋势。     

Effects of Climate Change on Habitat Availability and Configuration for an Endemic Coastal Alpine Bird

North America’s coastal mountains are particularly vulnerable to climate change, yet harbour a number of endemic species. With little room “at the top” to track shifting climate envelopes, alpine species may be especially negatively affected by climate-induced habitat fragmentation. We ask how climate change will affect the total amount, mean patch size, and number of patches of suitable habitat for Vancouver Island White-tailed Ptarmigan (Lagopus leucura saxatilis; VIWTP), a threatened, endemic alpine bird. Using a Random Forest model and a unique dataset consisting of citizen science observations combined with field surveys, we predict the distribution and configuration of potential suitable summer habitat for VIWTP under baseline and future (2020s, 2050s, and 2080s) climates using three general circulation models and two greenhouse gas scenarios. VIWTP summer habitat is predicted to decline by an average of 25%, 44%, and 56% by the 2020s, 2050s, and 2080s, respectively, under the low greenhouse gas scenario and 27%, 59%, and 74% under the high scenario. Habitat patches are predicted to become fragmented, with a 52–79% reduction in mean patch size. The average elevation of suitable habitat patches is expected to increase, reflecting a loss of patches at lower elevations. Thus ptarmigan are in danger of being “squeezed off the mountain”, as their remaining suitable habitat will be increasingly confined to mountaintops in the center of the island. The extent to which ptarmigan will be able to persist in increasingly fragmented habitat is unclear. Much will depend on their ability to move throughout a more heterogeneous landscape, utilize smaller breeding areas, and survive increasingly variable climate extremes. Our results emphasize the importance of continued monitoring and protection for high elevation specialist species, and suggest that White-tailed Ptarmigan should be considered an indicator species for alpine ecosystems in the face of climate change.     

Balancing bioenergy and biosecurity policies: estimating current and future climate suitability patterns for a bioenergy crop

In an apparent paradox, bioenergy crops offer potential benefits to a world adjusting to the challenges of climate change and declining fossil fuel stocks, as well as potential ecological and economic threats resulting from biological invasions. In considering this paradox it is important to understand that benefits and threats may not always be apparent in equal measure throughout the potential range of each candidate biofuel species. In some environments, a species could potentially produce valuable biological materials without posing a significant invasion threat. In this study, we develop a bioclimatic niche model for a candidate biofuel crop, Millettia pinnata, and apply the model to different climatic and irrigation scenarios to estimate the current and future patterns of climate suitability for its growth and naturalization. We use Australia as a case study for interpreting the niche model in terms that may be informative for both biofuels proponents and biosecurity regulators to plan management programmes that reflect the invasive potential in different areas. The model suggests that suitable growing conditions for M. pinnata in Australia are naturally restricted to the moist and semimoist tropics. Irrigation can extend the suitable growing conditions more widely throughout the tropics, and into more arid regions. Under future climate scenarios, suitable growing conditions for M. pinnata under natural rainfall contract towards the east coast, and extend southward into the subtropics. With irrigation, M. pinnata appears to have the potential in the future to naturalize across much of Australia. The bioclimatic modelling method demonstrated here is comparatively quick and easy, and can produce a rich array of data products to inform the interests of both bioenergy proponents and biosecurity regulators. We show how this modelling can support the development of spatially explicit biosecurity policies designed to manage invasion risks in a manner that balances bioenergy and biosecurity concerns.     

Current and future distribution of the deciduous shrub Hydrangea macrophylla in China estimated by MaxEnt

Climate change has a significant impact on the growth and distribution of vegetation worldwide. Hydrangea macrophylla is widely distributed and considered a model species for studying the distribution and responses of shrub plants under climate change. These results can inform decision‐making regarding shrub plant protection, management, and introduction of germplasm resources, and are of great importance for formulating ecological countermeasures to climate change in the future. We used the maximum entropy model to predict the change, scope expansion/reduction, centroid movement, and dominant climate factors that restrict the growth and distribution of H. macrophylla in China under current and future climate change scenarios. It was found that both precipitation and temperature affect the distribution of suitable habitat for H. macrophylla. Akaike information criterion (AICc) was used to select the feature combination (FC) and the regularization multiplier (RM). After the establishment of the optimal model (FC = QP, RM = 0.5), the complexity and over‐fitting degree of the model were low (delta AICc = 0, omission rate = 0.026, difference between training and testing area under the curve values = 0.0009), indicating that it had high accuracy in predicting the potential geographical distribution of H. macrophylla (area under the curve = 0.979). Overall, from the current period to future, the potential suitable habitat of this species in China expanded to the north. The greenhouse effect caused by an increase in CO₂ emissions would not only increase the area of high‐suitability habitat in Central China, but also expand the area of total suitable habitat in the north. Under the maximum greenhouse gas emission scenario (RCP8.5), the migration distance of the centroid was the longest (e.g., By 2070s, the centroids of total and highly suitable areas have shifted 186.15 km and 89.84 km, respectively).     

Early response of the platypus to climate warming

Combining a climatic envelope modelling technique with more than two centuries (1800–2009) of distribution records has revealed the effects of a changing climate on the egg‐laying monotreme, the platypus, Ornithorhynchus anatinus. We show that the main factor associated with platypus occurrence switched from aquatic habitat availability (estimated by rainfall) to thermal tolerances (estimated by annual maximum temperature) in the 1960s. This correlates directly with the change in the annual maximum temperature anomaly from cooler to warmer conditions in southeastern Australia. Modelling of platypus habitat under emission scenarios (A1B, A2, B1 and B2) revealed large decreases (>30%) in thermally suitable habitat by 2070. This reduction, compounded by increasing demands for water for agriculture and potable use, suggests that there is real cause for concern over the future status of this species, and highlights the need for restoration of thermal refugia within the platypus’ modelled range.     

Modelling distribution in European stream macroinvertebrates under future climates

Climate change is predicted to have profound effects on freshwater organisms due to rising temperatures and altered precipitation regimes. Using an ensemble of bioclimatic envelope models (BEMs), we modelled the climatic suitability of 191 stream macroinvertebrate species from 12 orders across Europe under two climate change scenarios for 2080 on a spatial resolution of 5 arc minutes. Analyses included assessments of relative changes in species’ climatically suitable areas as well as their potential shifts in latitude and longitude with respect to species’ thermal preferences. Climate‐change effects were also analysed regarding species’ ecological and biological groupings, namely (1) endemicity and (2) rarity within European ecoregions, (3) life cycle, (4) stream zonation preference and (5) current preference. The BEMs projected that suitable climate conditions would persist in Europe in the year 2080 for nearly 99% of the modelled species regardless of the climate scenario. Nevertheless, a decrease in the amount of climatically suitable areas was projected for 57–59% of the species. Depending on the scenario, losses could be of 38–44% on average. The suitable areas for species were projected to shift, on average, 4.7–6.6° north and 3.9–5.4° east. Cold‐adapted species were projected to lose climatically suitable areas, while gains were expected for warm‐adapted species. When projections were analysed for different species groupings, only endemics stood out as a particular group. That is, endemics were projected to lose significantly larger amounts of suitable climatic areas than nonendemic species. Despite the uncertainties involved in modelling exercises such as this, the extent of projected distributional changes reveals further the vulnerability of freshwater organisms to climate change and implies a need to understand the consequences for ecological function and biodiversity conservation.     

Integrating mechanistic and empirical model projections to assess climate impacts on tree species distributions in northwestern North America

Empirical and mechanistic models have both been used to assess the potential impacts of climate change on species distributions, and each modeling approach has its strengths and weaknesses. Here, we demonstrate an approach to projecting climate‐driven changes in species distributions that draws on both empirical and mechanistic models. We combined projections from a dynamic global vegetation model (DGVM) that simulates the distributions of biomes based on basic plant functional types with projections from empirical climatic niche models for six tree species in northwestern North America. These integrated model outputs incorporate important biological processes, such as competition, physiological responses of plants to changes in atmospheric CO₂ concentrations, and fire, as well as what are likely to be species‐specific climatic constraints. We compared the integrated projections to projections from the empirical climatic niche models alone. Overall, our integrated model outputs projected a greater climate‐driven loss of potentially suitable environmental space than did the empirical climatic niche model outputs alone for the majority of modeled species. Our results also show that refining species distributions with DGVM outputs had large effects on the geographic locations of suitable habitat. We demonstrate one approach to integrating the outputs of mechanistic and empirical niche models to produce bioclimatic projections. But perhaps more importantly, our study reveals the potential for empirical climatic niche models to over‐predict suitable environmental space under future climatic conditions.     

Upward elevation and northwest range shifts for alpine Meconopsis species in the Himalaya–Hengduan Mountains region

Climate change may impact the distribution of species by shifting their ranges to higher elevations or higher latitudes. The impacts on alpine plant species may be particularly profound due to a potential lack of availability of future suitable habitat. To identify how alpine species have responded to climate change during the past century as well as to predict how they may react to possible global climate change scenarios in the future, we investigate the climatic responses of seven species of Meconopsis, a representative genus endemic in the alpine meadow and subnival region of the Himalaya–Hengduan Mountains. We analyzed past elevational shifts, as well as projected shifts in longitude, latitude, elevation, and range size using historical specimen records and species distribution modeling under optimistic (RCP 4.5) and pessimistic (RCP 8.5) scenarios across three general circulation models for 2070. Our results indicate that across all seven species, there has been an upward shift in mean elevation of 302.3 m between the pre‐1970s (1922–1969) and the post‐1970s (1970–2016). The model predictions suggest that the future suitable climate space will continue to shift upwards in elevation (as well as northwards and westwards) by 2070. While for most of the analyzed species, the area of suitable climate space is predicted to expand under the optimistic emission scenario, the area contracts, or, at best, shows little change under the pessimistic scenario. Species such as M. punicea, which already occupy high latitudes, are consistently predicted to experience a contraction of suitable climate space across all the models by 2070 and may consequently deserve particular attention by conservation strategies. Collectively, our results suggest that the alpine high‐latitude species analyzed here have already been significantly impacted by climate change and that these trends may continue over the coming decades.     

The Predicted Influence of Climate Change on Lesser Prairie-Chicken Reproductive Parameters

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001–2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter’s linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.     

Potential impacts of a future persistent El Niño or La Niña on three subspecies of Australian butterflies

One of the major uncertainties of 21st century climate change is the potential for shifts to the intensity and frequency of the El Niño Southern Oscillation (ENSO) cycle. Although this phenomenon is known to have dramatic impacts on ecosystems regionally and globally, the biological consequences of climate change‐driven shifts in future ENSO events have been unexplored. Here, we investigate the potential impacts that a persistent El Niño, La Niña, or ‘Neutral' phase may have on species distributions. Using MaxEnt, we model the distribution of climatically suitable habitat for three northeast Australian butterfly subspecies (Doleschallia bisaltide australis, Hypolimnas alimena lamina, and Mycalesis terminus terminus) across the three ENSO phases. We find that the spatial extent and quality of habitat are lowest under conditions that would characterize a persistent El Niño (hot/dry). In contrast, suitable habitat is broadest under the warm/wet conditions associated with La Niña. Statistical analyses of the difference between pair‐wise combinations of suitability maps using Hellinger distance showed that projections for each subspecies and ENSO phase combination were significantly different from other combinations. The resilience of these, and other, butterfly (sub)species to changes in ENSO will be influenced by fluctuations in the strength of these events, availability of refugia, and life‐history characteristics. However, the population dynamics of wet‐ and dry‐season phenotypes of M. t. terminus and physiological limitations to high temperatures suggest that this subspecies, in particular, may have limited resilience should the strength and frequency of El Niño events increase.     

Influence of climate change and postdelisting management on long‐term population viability of the conservation‐reliant Kirtland's Warbler

Rapid global climate change is resulting in novel abiotic and biotic conditions and interactions. Identifying management strategies that maximize probability of long‐term persistence requires an understanding of the vulnerability of species to environmental changes. We sought to quantify the vulnerability of Kirtland's Warbler (Setophaga kirtlandii), a rare Neotropical migratory songbird that breeds almost exclusively in the Lower Peninsula of Michigan and winters in the Bahamian Archipelago, to projected environmental changes on the breeding and wintering grounds. We developed a population‐level simulation model that incorporates the influence of annual environmental conditions on the breeding and wintering grounds, and parameterized the model using empirical relationships. We simulated independent and additive effects of reduced breeding grounds habitat quantity and quality, and wintering grounds habitat quality, on population viability. Our results indicated the Kirtland's Warbler population is stable under current environmental and management conditions. Reduced breeding grounds habitat quantity resulted in reductions of the stable population size, but did not cause extinction under the scenarios we examined. In contrast, projected large reductions in wintering grounds precipitation caused the population to decline, with risk of extinction magnified when breeding habitat quantity or quality also decreased. Our study indicates that probability of long‐term persistence for Kirtland's Warbler will depend on climate change impacts to wintering grounds habitat quality and contributes to the growing literature documenting the importance of considering the full annual cycle for understanding population dynamics of migratory species.     

Genetic diversity is related to climatic variation and vulnerability in threatened bull trout

Understanding how climatic variation influences ecological and evolutionary processes is crucial for informed conservation decision‐making. Nevertheless, few studies have measured how climatic variation influences genetic diversity within populations or how genetic diversity is distributed across space relative to future climatic stress. Here, we tested whether patterns of genetic diversity (allelic richness) were related to climatic variation and habitat features in 130 bull trout (Salvelinus confluentus) populations from 24 watersheds (i.e., ~4–7th order river subbasins) across the Columbia River Basin, USA. We then determined whether bull trout genetic diversity was related to climate vulnerability at the watershed scale, which we quantified on the basis of exposure to future climatic conditions (projected scenarios for the 2040s) and existing habitat complexity. We found a strong gradient in genetic diversity in bull trout populations across the Columbia River Basin, where populations located in the most upstream headwater areas had the greatest genetic diversity. After accounting for spatial patterns with linear mixed models, allelic richness in bull trout populations was positively related to habitat patch size and complexity, and negatively related to maximum summer temperature and the frequency of winter flooding. These relationships strongly suggest that climatic variation influences evolutionary processes in this threatened species and that genetic diversity will likely decrease due to future climate change. Vulnerability at a watershed scale was negatively correlated with average genetic diversity (r = ?0.77; P < 0.001); watersheds containing populations with lower average genetic diversity generally had the lowest habitat complexity, warmest stream temperatures, and greatest frequency of winter flooding. Together, these findings have important conservation implications for bull trout and other imperiled species. Genetic diversity is already depressed where climatic vulnerability is highest; it will likely erode further in the very places where diversity may be most needed for future persistence.     

Multiple stressors facilitate the spread of a non‐indigenous bivalve in the Mediterranean Sea

Aim

The introduction of non‐indigenous species (NIS) via man‐made corridors connecting previously disparate oceanic regions is increasing globally. However, the environmental and anthropogenic factors facilitating invasion dynamics and their interactions are still largely unknown. This study compiles and inputs available data for the NIS bivalve Brachidontes pharaonis across the invaded biogeographic range in the Mediterranean basin into a species distribution model to predict future spread under a range of marine scenarios.

Location

Mediterranean Sea.

Methods

A systematic review produced the largest presence database ever assembled to inform the selection of biological, chemical and physical factors linked to the spread of B. pharaonis through the Suez Canal. We carried out a sensitivity analysis to simulate current and future trophic and salinity scenarios. A species distribution model was run to determine key drivers of invasion, quantify interactive impacts arising from a range of trophic states, salinity conditions and climatic scenarios and forecast future trajectories for the spread of NIS into new regions under multiple‐parameter scenarios (based on the main factors identified from the systematic review).

Results

Impacts on invasion trajectory arising from climate change and interactions with increasing salinity from the new opening of the canal were the primary drivers of expansion across the basin, the effects of which were further enhanced by eutrophication. Predictions of the current distribution were most accurate when multiple stressors were used to drive the model. A habitat suitability index developed at a subcontinental scale from model outputs identified novel favourable conditions for future colonization at specific locations under 2030 and 2050 climatic scenarios.

Main conclusions

Future expansion of B. pharaonis will be enhanced by climate‐facilitated increased sea temperature, interacting with increasing pressures from salinity and eutrophication. The spatially explicit risk output maps of invasions represent a powerful visual product for use in communication of the spread of NIS and decision‐support tools for scientists and policymakers. The suggested approach, the observed distribution pattern and driving processes can be applied to other NIS species and regions by providing novel forecasts of species occurrences under future multiple stressor scenarios and the location of suitable recipient habitats with respect to anthropogenic and environmental parameters.     

An ecological genetic delineation of local seed‐source provenance for ecological restoration

An increasingly important practical application of the analysis of spatial genetic structure within plant species is to help define the extent of local provenance seed collection zones that minimize negative impacts in ecological restoration programs. Here, we derive seed sourcing guidelines from a novel range‐wide assessment of spatial genetic structure of 24 populations of Banksia menziesii (Proteaceae), a widely distributed Western Australian tree of significance in local ecological restoration programs. An analysis of molecular variance (AMOVA) of 100 amplified fragment length polymorphism (AFLP) markers revealed significant genetic differentiation among populations (Φ_PT = 0.18). Pairwise population genetic dissimilarity was correlated with geographic distance, but not environmental distance derived from 15 climate variables, suggesting overall neutrality of these markers with regard to these climate variables. Nevertheless, Bayesian outlier analysis identified four markers potentially under selection, although these were not correlated with the climate variables. We calculated a global R‐statistic using analysis of similarities (ANOSIM) to test the statistical significance of population differentiation and to infer a threshold seed collection zone distance of ~60 km (all markers) and 100 km (outlier markers) when genetic distance was regressed against geographic distance. Population pairs separated by >60 km were, on average, twice as likely to be significantly genetically differentiated than population pairs separated by <60 km, suggesting that habitat‐matched sites within a 30‐km radius around a restoration site genetically defines a local provenance seed collection zone for B. menziesii. Our approach is a novel probability‐based practical solution for the delineation of a local seed collection zone to minimize negative genetic impacts in ecological restoration.     

Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models

Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage‐structured, seasonal, nonlinear, two‐sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture‐mark‐recapture analysis, we find that seasonal sea ice concentration anomalies (SIC_a) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SIC_a, because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SIC_a. We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SIC_a, which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor penguin. Our analytical approach, in which demographic models are linked to IPCC climate models, is powerful and generally applicable to other species and systems.     

A process‐based approach to modelling impacts of climate change on the damage niche of an agricultural weed

Predicting the impact of climate change on the damage niche of an agricultural weed at a local scale requires a process‐based modelling approach that integrates local environmental conditions and the differential responses of the crop and weed to change. A simulation model of the growth and population dynamics of winter wheat and a competing weed, Sirius 2010, was calibrated and validated for the most economically damaging weed in UK cereals, Alopecurus myosuroides. The model was run using local‐scale climatic scenarios generated by the LARS‐WG weather generator and based on the HadCM3 projections for the periods 2046–2065 and 2080–2099 to predict the impact of climate change on the population dynamics of the weed and its effect on wheat yields. Owing to rising CO₂ concentration and its effect on radiation use efficiency of wheat, weed‐free wheat yields were predicted to increase. The distribution of the weed was predicted to remain broadly similar with a possible northward shift in range. Local‐scale variation in the impact of climate change was apparent owing to variation in soil type and water holding capacity. The competitive balance was shifted in favour of the deeper rooted crop under climate change, particularly on sites with lighter soils, owing to more frequent and severe drought stress events. Although the damage niche of A. myosuroides was predicted to reduce under climate change, it is likely that weeds with contrasting physiology, such as C4 species, will be better adapted to future conditions and pose a more serious threat.