Incorporating anthropogenic variables into a species distribution model to map gypsy moth risk

This paper presents a novel methodology for multi-scale and multi-type spatial data integration in support of insect pest risk/vulnerability assessment in the contiguous United States. Probability of gypsy moth (Lymantria dispar L.) establishment is used as a case study. A neural network facilitates the integration of variables representing dynamic anthropogenic interaction and ecological characteristics. Neural network model (back-propagation network [BPN]) results are compared to logistic regression and multi-criteria evaluation via weighted linear combination, using the receiver operating characteristic area under the curve (AUC) and a simple threshold assessment. The BPN provided the most accurate infestation-forecast predictions producing an AUC of 0.93, followed by multi-criteria evaluation (AUC = 0.92) and logistic regression (AUC = 0.86) when independently validating using post model infestation data. Results suggest that BPN can provide valuable insight into factors contributing to introduction for invasive species whose propagation and establishment requirements are not fully understood. The integration of anthropogenic and ecological variables allowed production of an accurate risk model and provided insight into the impact of human activities.     

Increase in Quantity and Quality of Suitable Areas for Invasive Species as Climate Changes

As climatically suitable range projections become increasingly used to assess distributions of species, we recommend systematic assessments of the quality of habitat in addition to the classical binary classification of habitat. We devised a method to assess occurrence probability, captured by a climatic suitability index, through which we could determine variations in the quality of potential habitat. This relative risk assessment circumvents the use of an arbitrary suitability threshold. We illustrated our method with 2 case studies on invasive ant species. We estimated invasion potential of the destroyer ant (Monomorium destructor) and the European fire ant (Myrmica rubra) on a global scale currently and by 2080 with climate change. We found that 21.1% of the world's landmass currently has a suitable climate for the destroyer ant and 16% has a suitable climate for European fire ant. Our climatic suitability index showed that both ant species would benefit from climate change, but in different ways. The size of the potential distribution increased by 35.8% for the destroyer ant. Meanwhile, the total area of potential distribution remained the same for the European fire ant (>0.05%), but the level of climatic suitability within this range increased greatly and led to an improvement in habitat quality (i.e., of invasive species’ establishment likelihood). Either through quantity or quality of suitable areas, both invasive ant species are likely to increase the extent of their invasion in the future, following global climate change. Our results show that species may increase their range if either more areas become suitable or if the available areas present improved suitability. Studies in which an arbitrary suitability threshold was used may overlook changes in area quality within climatically suitable areas and as a result reach incorrect predictions. Incremento de la Cantidad y Calidad de Áreas Idóneas para Especies Invasoras a Medida que Cambia el Clima     

A state-dependent model for the optimal management of an invasive metapopulation.

Management of invasive species involves choosing between different management strategy options, but often the best strategy for a particular scenario is not obvious. We illustrate the use of optimization methods to determine the most efficient management strategy using one of the most devastating invasive forest pests in North America, the gypsy moth (Lymantria dispar), as a case study. The optimization approach involves the application of stochastic dynamic programming (SDP) to a metapopulation framework with different infestation patch sizes, with the goal of minimizing infestation spread. We use a novel "moving window" approach as a way to address a spatially explicit problem without being explicitly spatial. We examine results for two cases in order to develop general rules of thumb for management. We explore a model with limited parameter information and then assess how strategies change with specific parameterization for the gypsy moth. The model results in a complex but stable, state-dependent management strategy for a multiyear management program that is robust even under situations of uncertainty. The general rule of thumb for the basic model consists of three strategies: eradicating medium-density infestations, reducing large-density infestations, and reducing the colonization rate from the main infestation, depending on the state of the system. With specific gypsy moth parameterization, reducing colonization decreases in importance relative to the other two strategies. The application of this model to gypsy moth management emphasizes the importance of managing based on the state of the system, and if applied to a specific geographic area, has the potential to substantially improve the efficiency and cost-effectiveness of current gypsy moth eradication programs, helping to slow the spread of this pest. Additionally, the approach used for this particular invasive species can be extended to the optimization of management programs for the spread of other invasive and problem species exhibiting metapopulation dynamics.     

Egg protein insolubility inLymantria dispar versus other forest Lepidoptera

Summary A standard buffer (5 mM phosphate at pH 7) which is used to extract protein from insect eggs provided complete protein solubility for eggs from three of four tree-feeding lepidopteran species: obliquebanded leaf roller (Choristoneura rosaceana), forest tent caterpillar (Malacosoma disstria), and the eastern tent caterpillar (Malacosoma americanum). Under the same extraction protocol, egg proteins from the gypsy moth (Lymantria dispar), remained nearly insoluble. An array of methods typically used to solubilize insect egg proteins were tried and all but the most denaturing (2% SDS) were ineffective. Extraction buffers with typically high pH values were then evaluated. The results indicated that 1) solubility of gypsy moth egg proteins was pH dependent, and full solubility of most egg proteins required the extraction buffer to have a pH of 12 or more prior to the addition of eggs. We also determined that 2) the gypsy moth egg has a buffering capacity which must be surpassed for complete protein extraction, 3) low salt/high pH buffers gave slightly higher total protein values than did high salt/high pH buffers, 4) parental nutritional history (host species utilized) and egg developmental state (pre-embryonatedvs postembryonated/pre-hatch) were unrelated to the requirements for complete egg protein solubilization, and 5) the presence of soluble phenolics, compounds that have the potential to bind to protein and cause insolubility, was confirmed for the gypsy moth egg with 2-D paper chromatography and several other tests. Based on these results, we present a hypothesis about the cause of egg protein insolubility in the gypsy moth.     

A tree and climate assessment tool for modelling ecosystem response to climate change

Understanding how vulnerable forest ecosystems are to climate change is a key requirement if sustainable forest management is to be achieved. Modelling the response of species in their regeneration niche to phenological and biophysical processes that are directly influenced by climate is one method for achieving this understanding. A model was developed to investigate species resilience and vulnerability to climate change within its fundamental-regeneration niche. The utility of the developed model, tree and climate assessment (TACA), was tested within the interior Douglas-fir ecosystem in south-central British Columbia. TACA modelled the current potential tree species composition of the ecosystem with high accuracy and modelled significant responses amongst tree species to climate change. The response of individual species suggests that the studied ecosystem could transition to a new ecosystem over the next 100 years. TACA showed that it can be an effective tool for identifying species resilience and vulnerability to changes in climate within the most sensitive stage of development, the regeneration phase. The TACA model was able to identify the degree of change in phenological and biophysical variables that control tree establishment, growth and persistence. The response to changes in one or more of these variables resulted in changes in the climatic suitability of the ecosystem for species and enabled a measure of vulnerability to be quantified. TACA could be useful to forest managers as a decision support tool for adaptation actions and by researchers interested in modelling stand dynamics under climate change.     

Invasive prey impacts the abundance and distribution of native predators

While an extensive literature exists on the negative effects of invasive species, little is known about their facilitative effects on native species, particularly the role of invasives as trophic subsidies to native predators. The invasive gypsy moth (Lymantria dispar) undergoes periodic outbreaks during which it represents a super-abundant food source for predators capable of consuming it, particularly native cuckoos (Coccyzus erythropthalmus and C. americanus). We examined how gypsy moth outbreaks affect the abundance and distribution of cuckoos using the North American Breeding Bird Survey and 29 years of U.S. Forest Service gypsy moth defoliation records. Abundances of both Black-billed and Yellow-billed Cuckoos were significantly above average during outbreaks, but populations were average or below average in preceding and subsequent years, suggesting that cuckoos are immigrating to defoliations during outbreak years. Spatial analyses showed that cuckoo abundances approximately 40-150 km outside of defoliation areas were significantly below average, and these under-occupied breeding areas extended in all four compass directions around outbreaks. This result supports the idea that cuckoos locate gypsy moth outbreaks during a post-migratory nomadic phase. By shifting the annual distribution of cuckoos, gypsy moths may be shifting the trophic impact of cuckoos across large distances, which could affect native insect herbivores and plants.     

Scenarios of large mammal loss in Europe for the 21st century

Distributions and populations of large mammals are declining globally, leading to an increase in their extinction risk. We forecasted the distribution of extant European large mammals (17 carnivores and 10 ungulates) based on 2 Rio+20 scenarios of socioeconomic development: business as usual and reduced impact through changes in human consumption of natural resources. These scenarios are linked to scenarios of land‐use change and climate change through the spatial allocation of land conversion up to 2050. We used a hierarchical framework to forecast the extent and distribution of mammal habitat based on species’ habitat preferences (as described in the International Union for Conservation of Nature Red List database) within a suitable climatic space fitted to the species’ current geographic range. We analyzed the geographic and taxonomic variation of habitat loss for large mammals and the potential effect of the reduced impact policy on loss mitigation. Averaging across scenarios, European large mammals were predicted to lose 10% of their habitat by 2050 (25% in the worst‐case scenario). Predicted loss was much higher for species in northwestern Europe, where habitat is expected to be lost due to climate and land‐use change. Change in human consumption patterns was predicted to substantially improve the conservation of habitat for European large mammals, but not enough to reduce extinction risk if species cannot adapt locally to climate change or disperse.     

Choice of threshold alters projections of species range shifts under climate change

One of the least explored sources of algorithmic uncertainty in bioclimatic envelope models (BEM) is the selection of thresholds to transform modelled probabilities of occurrence (or indices of suitability) into binary predictions of species presence and absence. We investigate the impacts of such thresholds in the specific context of climate change. BEM for European tree species were fitted combining 9 climatic models and emissions scenarios, 7 modelling techniques, and 14 threshold-setting techniques. We quantified sources of uncertainty in projections of turnover, and found that the choice of the modelling technique explained most of the variability (39%), while threshold choice explained 25% of the variability in the results, and their interaction an additional 19%. Choice of future climates explained 9% of total variability among projections. Estimated species range shifts obtained by applying different thresholds and models were grouped by IUCN-based categories of threat. Thresholds had a large impact on the inferred risks of extinction, producing 1.7- to 9.9-fold differences in the proportions of species projected to become threatened by climate change. Results demonstrate that threshold selection has large - albeit often unappreciated - consequences for estimating species range shifts under climate change.     

Predicting species distributions: use of climatic parameters in BIOCLIM and its impact on predictions of species’ current and future distributions

Bioclimatic models are widely used tools for assessing potential responses of species to climate change. One commonly used model is BIOCLIM, which summarises up to 35 climatic parameters throughout a species’ known range, and assesses the climatic suitability of habitat under current and future climate scenarios. A criticism of BIOCLIM is that the use of all 35 parameters may lead to over-fitting of the model, which in turn may result in misrepresentations of species’ potential ranges and to the loss of biological reality. In this study, we investigated how different methods of combining climatic parameters in BIOCLIM influenced predictions of the current distributions of 25 Australian butterflies species. Distributions were modeled using three previously used methods of selecting climatic parameters: (i) the full set of 35 parameters, (ii) a customised selection of the most relevant parameters for individual species based on analysing histograms produced by BIOCLIM, which show the values for each parameter at all of the focal species known locations, and (iii) a subset of 8 parameters that may generally influence the distributions of butterflies. We also modeled distributions based on random selections of parameters. Further, we assessed the extent to which parameter choice influenced predictions of the magnitude and direction of range changes under two climate change scenarios for 2020. We found that the size of predicted distributions was negatively correlated with the number of parameters incorporated in the model, with progressive addition of parameters resulting in progressively narrower potential distributions. There was also redundancy amongst some parameters; distributions produced using all 35 parameters were on average half the size of distributions produced using only 6 parameters. The selection of parameters via histogram analysis was influenced, to an extent, by the number of location records for the focal species. Further, species inhabiting different biogeographical zones may have different sets of climatic parameters limiting their distributions; hence, the appropriateness of applying the same subset of parameters to all species may be reduced under these situations. Under future climates, most species were predicted to suffer range reductions regardless of the scenario used and the method of parameter selection. Although the size of predicted distributions varied considerably depending on the method of selecting parameters, there were no significant differences in the proportional change in range size between the three methods: under the worst-case scenario, species’ distributions decrease by an average of 12.6, 11.4, and 15.7%, using all parameters, the ‘customised set’, and the ‘general set’ of parameters, respectively. However, depending on which method of selecting parameters was used, the direction of change was reversed for two species under the worst-case climate change scenario, and for six species under the best-case scenario (out of a total of 25 species). These results suggest that when averaged over multiple species, the proportional loss or gain of climatically suitable habitat is relatively insensitive to the number of parameters used to predict distributions with BIOCLIM. However, when measuring the response of specific species or the actual size of distributions, the number of parameters is likely to be critical.     

Modelling phytoclimatic versatility as a large scale indicator of adaptive capacity to climate change in forest ecosystems

CLIMPAIR is a new phytoclimatic model, correlative and niche-based, which simultaneously assesses non-linear, non-statistical and dual measurements of proximity/potentiality of a site with respect to a number of climatic ranges of species, defined by convex hulls, within a suitability space. This set of phytoclimatic distances makes it possible to evaluate the degree to which each species is suitable for that site. Considering not only the number of species compatible (expected species richness), but also all those compatible covers presenting a high level of suitability evenness and finally applying an indicator derived from Shannon's classic entropy index to the set of standardized phytoclimatic coordinates in the suitability hyperspace, we can evaluate the phytoclimatic entropy which may be considered as a means of estimating the phytoclimatic versatility of the site. A site with high phytoclimatic entropy would promise versatile future behaviour, characterized by a wide range of possibilities of adaptation to climate change, and hence versatility can be used as an index of resilience and ability of a forest ecosystem to adapt to climate change. The model has been applied to peninsular Spain for 18 forest tree species and 12 climatic variables between the current mean climate (period 1951-1999) and a future climatic scenario (period 2040-2069). The results generally point to a significant decrease in the versatility of forest tree formations in the area studied, which is not homogeneous owing to a dual altitudinal/latitudinal decoupling. The decrease in versatility is greater in Mediterranean biogeographical areas than in Euro-Siberian ones, where in some cases it actually increases. In altitudinal terms, areas at elevations of less than 1500 m tend to become less versatile than areas situated at higher elevations, where versatility increases partly as a result of enrichment of alpine conifer forests with broadleaf species.     

Effects of Elevated Atmospheric Carbon Dioxide on Insect-Plant Interactions

Abstract: In the enriched carbon dioxide atmosphere expected in the next century, many species of herbivorous insects will confront less nutritious host plants that will induce both lengthened larval developmental times and greater mortality. The limited data currently available suggest that the effect of increased atmospheric CO₂ on herbivory will be not only highly species-specific but also specific to each insect-plant system. Several scenarios can be predicted, however: (1) local extinctions will occur; (2) the endangered species status as well as the pest status of some insect species will change; (3) geographic distributions for some insect species will shift with host-plant ranges; and (4) changes in the population dynamics of affected insect species will influence their interactions with other insects and plants. For insect conservation purposes, it is critical to begin long-term studies on the effects of enhanced CO₂ levels on insect populations. An analysis of the available literature indicates that many orders containing insect species important for ecosystem conservation, and even those important as agricultural or medical pests, have not been examined. Without a major increase in research on this topic, we will be unprepared for the species changes that will occur, we will lose the opportunity to document just how some insects adapt to elevated CO₂ levels, and we will lack the information necessary for effective conservation efforts.     

A concept model to estimate the potential distribution of the Asiatic citrus psyllid (Diaphorina citri Kuwayama) in Australia under climate change—A means for assessing biosecurity risk

Increasing global temperatures as a result of climate change are widely considered inevitable for Australia. Despite this, the specific effects of climate change on Australian agriculture are little studied and the effects on agricultural pests and diseases are virtually unknown. In this paper we consider the impact of climate change on the Asiatic citrus psyllid (Diaphorina citri Kuwayama [Hemiptera: Psyllidae]); one of two known vectors of huanglongbing (citrus greening); a debilitating disease which is caused in Asia by a phloem-limited bacterium ‘Candidatus Liberibacter asiaticus’ (α-Proteobacteria). D. citri does not occur in Australia, but if introduced would pose a major threat to the viability of the Australian citrus industry and to native Citrus species. This paper presents an approach developed to understand how climate change may influence the behaviour, distribution and breeding potential of D. citri. Here we developed and describe an initial dynamic point model of D. citri biology in relation to its citrus host and applied it to a scenario of increasing temperatures, as indicators of climate change, on a continental scale. A comparison between model outputs for the three time frames considered (1990, 2030 and 2070) confirms that increasing temperatures projected under climate change will affect the timing and duration of new citrus growth (flush) necessary for psyllid development throughout Australia. Flushing will start progressively earlier as the temperature increases and be of shorter duration. There will also be a gradual southward expansion of shorter durations of the occurrence of flush. Increasing temperatures will impact on D. citri both directly through alteration of its temperature dependant development cycle and indirectly through the impact on the host flushing cycle. For the whole of Australia, a comparison between model outputs for the three scenarios considered indicates the seasonality of D. citri development will change to match changes in citrus flush initiation. Results indicate that the risk of establishment by D. citri is projected to decrease under increasing temperatures, mainly due to shortened intervals when it can feed on new leaf flushes of the host. However, the spatially heterogeneous results also suggest that regions located on the southern coastline of Australia could become more suitable for D. citri than projected under current temperatures. These results confirm the value of a linked host-pest approach as based on D. citri climatic requirements alone the model would have accounted only for shorter development periods and predicted an increased risk of potential distribution.     

Climate Change, Elevational Range Shifts, and Bird Extinctions

Abstract:  Limitations imposed on species ranges by the climatic, ecological, and physiological effects of elevation are important determinants of extinction risk. We modeled the effects of elevational limits on the extinction risk of landbirds, 87% of all bird species. Elevational limitation of range size explained 97% of the variation in the probability of being in a World Conservation Union category of extinction risk. Our model that combined elevational ranges, four Millennium Assessment habitat-loss scenarios, and an intermediate estimate of surface warming of 2.8° C, projected a best guess of 400–550 landbird extinctions, and that approximately 2150 additional species would be at risk of extinction by 2100. For Western Hemisphere landbirds, intermediate extinction estimates based on climate-induced changes in actual distributions ranged from 1.3% (1.1° C warming) to 30.0% (6.4° C warming) of these species. Worldwide, every degree of warming projected a nonlinear increase in bird extinctions of about 100–500 species. Only 21% of the species predicted to become extinct in our scenarios are currently considered threatened with extinction. Different habitat-loss and surface-warming scenarios predicted substantially different futures for landbird species. To improve the precision of climate-induced extinction estimates, there is an urgent need for high-resolution measurements of shifts in the elevational ranges of species. Given the accelerating influence of climate change on species distributions and conservation, using elevational limits in a tested, standardized, and robust manner can improve conservation assessments of terrestrial species and will help identify species that are most vulnerable to global climate change. Our climate-induced extinction estimates are broadly similar to those of bird species at risk from other factors, but these estimates largely involve different sets of species.     

Assessing species reintroduction sites based on future climate suitability for food resources

The reintroduction of a species that is extinct in the wild demands caution because reintroduction locations may be associated with threats, such as hunting, poor-quality habitat, and climate change. This is the case for Cyanopsitta spixii (Spix's Macaw), which has been extinct in the wild since 2000. The few living individuals were created in captivity and will be used in a reintroduction project within the species’ original distribution area, the Caatinga domain (Brazil). Because the occurrence records for this bird are old and inaccurate, we investigated the current and future environmental suitability of the 14 plant species used by C. spixii as resource. These plants are key elements for the long-term reestablishment of the species in the wild, so the use of models helps in the assessment of the effects of climate change on the availability of these resources for the species and informs selection of the best places for reintroduction. We based our models of environmental suitability on 19 bioclimatic variables and nine physical soil and topography variables. Climate projections were created for the present and for the year 2070 with an optimistic (SSP2-4.5) and a pessimistic (SSP5-8.5) climate scenario. Both future climate scenarios lead to a reduction in area of environmental suitability that overlapped for all the plant species: 33% reduction for SSP2-4.5 and 63% reduction for SSP5-8.5. If our projections materialize, climate change could thus affect the distribution of key resources, and the maintenance of C. spixii would depend on restoration of degraded areas, especially riparian forests, and the preservation of already existing natural areas. The Caatinga domain is very threatened by habitat loss and, for the success of this reintroduction project, the parties involved must act to protect the species and the resources it uses.     

Choosing and Using Climate‐Change Scenarios for Ecological‐Impact Assessments and Conservation Decisions

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate‐change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate‐change scenarios for ecological impact assessment. Selección y Uso de Escenarios de Cambio Climático para Estudios de Impacto Ecológico y Decisiones de Conservación     

Scenarios of change in the realized climatic niche of mountain carnivores and ungulates

Mountains are among the natural systems most affected by climate change, and mountain mammals are considered particularly imperiled, given their high degree of specialization to narrow tolerance bands of environmental conditions. Climate change mitigation policies, such as the Paris Agreement, are essential to stem climate change impacts on natural systems. But how significant is the Paris Agreement to the survival of mountain mammals? We investigated how alternative emission scenarios may determine change in the realized climatic niche of mountain carnivores and ungulates in 2050. We based our predictions of future change in species niches based on how species have responded to past environmental changes, focusing on the probabilities of niche shrink and niche stability. We found that achieving the Paris Agreement's commitments would substantially reduce climate instability for mountain species. Specifically, limiting global warming to below 1.5°C would reduce the probability of niche shrinkage by 4% compared with a high-emission scenario. Globally, carnivores showed greater niche shrinkage than ungulates, whereas ungulates were more likely to shift their niches (i.e., face a level of climate change that allows adaptation). Twenty-three species threatened by climate change according to the IUCN Red List had greater niche contraction than other species we analyzed (3% higher on average). We therefore argue that climate mitigation policies must be coupled with rapid species-specific conservation intervention and sustainable land-use policies to avoid high risk of loss of already vulnerable species.     

河北省夏玉米气候适宜度及其变化特征分析

采用逐日气象要素和统计方法,建立了河北省夏玉米（Zea Mays）各生育期气候适宜度评价模型,计算了河北省1981—2010年逐年夏玉米各生育期气温、降水、日照、气候适宜度值,并对夏玉米各生育期气候适宜度特征及变化趋势进行了分析。结果表明：夏玉米生长期间气温适宜度最高,日照次之,降水最低且变异系数最大。气温适宜度以夏玉米灌浆期最低,变异系数最大;日照和降水适宜度均以抽雄期最低且变异系数最大。多年适宜度变化趋势为：全生育期日照适宜度明显下降（下降速率为0.047/10a）;气温适宜度基本持平;降水适宜度波动较大,无明显变化规律。幼苗和灌浆期气候适宜度呈下降趋势（下降速率分别为0.015/10a,0.024/10a）,其中幼苗期气候适宜度下降由期间气温和日照适宜度下降引起;灌浆期气候适宜度下降由日照和降水适宜度下降引起。     

外来有害生物风险评估技术

概述了有害生物风险分析的概念、必要性、生物学基础和一般程序 ;论述了生态气候图、农业气候相似距库、生态气候评价的分析模型、地理信息系统、专家系统、基于定性分析与定量估算相结合的数学模型等有害生物风险分析技术的原理和特点 ;认为应用网络技术 ,建立基于分布式计算的全球入侵物种风险评价数据体系 ,可有效提高风险评价的速度和准确性。     

Accounting for adaptive capacity and uncertainty in assessments of species’ climate‐change vulnerability

Climate‐change vulnerability assessments (CCVAs) are valuable tools for assessing species’ vulnerability to climatic changes, yet failure to include measures of adaptive capacity and to account for sources of uncertainty may limit their effectiveness. We took a more comprehensive approach that incorporates exposure, sensitivity, and capacity to adapt to climate change. We applied our approach to anadromous steelhead trout (Oncorhynchus mykiss) and nonanadromous bull trout (Salvelinus confluentus), threatened salmonids within the Columbia River Basin (U.S.A.). We quantified exposure on the basis of scenarios of future stream temperature and flow, and we represented sensitivity and capacity to adapt to climate change with metrics of habitat quality, demographic condition, and genetic diversity. Both species were found to be highly vulnerable to climate change at low elevations and in their southernmost habitats. However, vulnerability rankings varied widely depending on the factors (climate, habitat, demographic, and genetic) included in the CCVA and often differed for the 2 species at locations where they were sympatric. Our findings illustrate that CCVA results are highly sensitive to data inputs and that spatial differences can complicate multispecies conservation. Based on our results, we suggest that CCVAs be considered within a broader conceptual and computational framework and be used to refine hypotheses, guide research, and compare plausible scenarios of species’ vulnerability to climate change.     

Identifying robust strategies for assisted migration in a competitive stochastic metacommunity

Assisted migration (AM) is the translocation of species beyond their historical range to locations that are expected to be more suitable under future climate change. However, a relocated population may fail to establish in its donor community if there is high uncertainty in decision-making, climate, and interactions with the recipient ecological community. To quantify the benefit to persistence and risk of establishment failure of AM under different management scenarios (e.g., choosing target species, proportion of population to relocate, and optimal location to relocate), we built a stochastic metacommunity model to simulate several species reproducing, dispersing, and competing on a temperature gradient as temperature increases over time. Without AM, the species were vulnerable to climate change when they had low population sizes, short dispersal, and strong poleward competition. When relocating species that exemplified these traits, AM increased the long-term persistence of the species most when relocating a fraction of the donor population, even if the remaining population was very small or rapidly declining. This suggests that leaving behind a fraction of the population could be a robust approach, allowing managers to repeat AM in case they move the species to the wrong place and at the wrong time, especially when it is difficult to identify a species’ optimal climate. We found that AM most benefitted species with low dispersal ability and least benefited species with narrow thermal tolerances, for which AM increased extinction risk on average. Although relocation did not affect the persistence of nontarget species in our simple competitive model, researchers will need to consider a more complete set of community interactions to comprehensively understand invasion potential.