Uncertainties in coupled species distribution-metapopulation dynamics models for risk assessments under climate change

Recommendations for quantitative uncertainty consideration in ecology and evolution

Ecological and evolutionary studies are currently failing to achieve complete and consistent reporting of model-related uncertainty. We identify three key barriers - a focus on parameter-related uncertainty, obscure uncertainty metrics, and limited recognition of uncertainty propagation - which have led to gaps in uncertainty consideration. However, these gaps can be closed. We propose that uncertainty reporting in ecology and evolution can be improved through wider application of existing statistical solutions and by adopting good practice from other scientific fields. Our recommendations include greater consideration of input data and model structure uncertainties, field-specific uncertainty standards for methods and reporting, and increased uncertainty propagation through the use of hierarchical models.

Global Warming and Long-Distance Spread of Invasive Discoglossus pictus (Amphibia, Alytidae): Conservation Implications for Protected Amphibians in the Iberian Peninsula

Discoglossus pictus is a North African amphibian that was introduced in southern France early the 20th century and has spread south and north along the Mediterranean coastal plains up to 170 km. In order to disentangle the conservation implications of the spread of D. pictus for sensitive native species, we examined the impact of long-term climate warming on the basis of niche overlap analysis, taking into account abiotic factors. The study area covered the distribution ranges of all genus Discoglossus species in northwestern Africa (659,784 km²), Sicily (27,711 km²), the Iberian Peninsula, and southern France (699,546 km²). Niche overlap was measured from species environmental spaces extracted via PCA, including climate and relief environmental variables. Current and future climatic suitability for each species was assessed in an ensemble-forecasting framework of species distribution models, built using contemporary species data and climate predictors and projected to 2070's climatic conditions. Our results show a strong climatic niche overlap between D. pictus and native and endemic species in the Iberian Peninsula. In this context, all species will experience an increase in climatic suitability over the next decades, with the only exception being Pelodytes punctatus, which could be negatively affected by synergies between global warming and cohabitation with D. pictus.

Large-scale PVA modeling of insects in cultivated grasslands: The role of dispersal in mitigating the effects of management schedules under climate change

In many species, dispersal is decisive for survival in a changing climate. Simulation models for population dynamics under climate change thus need to account for this factor. Moreover, large numbers of species inhabiting agricultural landscapes are subject to disturbances induced by human land use. We included dispersal in the HiLEG model that we previously developed to study the interaction between climate change and agricultural land use in single populations. Here, the model was parameterized for the large marsh grasshopper (LMG) in cultivated grasslands of North Germany to analyze (1) the species development and dispersal success depending on the severity of climate change in subregions, (2) the additional effect of grassland cover on dispersal success, and (3) the role of dispersal in compensating for detrimental grassland mowing. Our model simulated population dynamics in 60-year periods (2020-2079) on a fine temporal (daily) and high spatial (250 × 250 m2) scale in 107 subregions, altogether encompassing a range of different grassland cover, climate change projections, and mowing schedules. We show that climate change alone would allow the LMG to thrive and expand, while grassland cover played a minor role. Some mowing schedules that were harmful to the LMG nevertheless allowed the species to moderately expand its range. Especially under minor climate change, in many subregions dispersal allowed for mowing early in the year, which is economically beneficial for farmers. More severe climate change could facilitate LMG expansion to uninhabited regions but would require suitable mowing schedules along the path. These insights can be transferred to other species, given that the LMG is considered a representative of grassland communities. For more specific predictions on the dynamics of other species affected by climate change and land use, the publicly available HiLEG model can be easily adapted to the characteristics of their life cycle.

Feature extraction and classification of climate change risks: a bibliometric analysis

Risks brought by climate change are inevitable obstacles to global development. Clarifying the features of climate change risks helps us to further understand and cope with climate change. There lacks a systematic review of climate change risks in terms of feature extraction and classification. The bibliometric analysis can be used to analyze and extract climate change risk features. The literature in the field of climate change was searched in the Web of Science database. Coauthors, citations, bibliographic coupling, co-citations, and keyword co-occurrence were analyzed. From five dimensions including nature, politics, economy, society, and culture, the risk features of climate change were extracted and summarized. Through text mining and cluster analysis, the climate change risk feature system was established, which is embodied in five different aspects: ecosystem and sustainability; uncertainty, vulnerability, and efficiency; behavior and decision-making; governance and management; and adaptation and mitigation. The feature system reflects that the current climate change risk presents strong variability and that the risk boundary is gradually blurred. The areas affected by risk are expanding and deepening. The strategies and governance for addressing risks are gradually diversified. This research contributes to the domain of climate change risk identification and assessment. The features of climate change indicate that we need to adjust policymaking and managerial practices for climate change in the future. Interdisciplinary cooperation, human cognition and preferences, public participation in global governance, and other unnatural factors related to climate change should be strengthened with a more positive attitude.

Evaluating multiple historical climate products in ecological models under current and projected temperatures

Gridded historical climate products (GHCPs) are employed with increasing frequency when modeling ecological phenomena across large scales and predicting ecological responses to projected climate changes. Concurrently, there is an increasing acknowledgement of the need to account for uncertainty when employing climate projections from ensembles of global circulation models (GCMs) and emissions scenarios. Despite the growing usage and documented differences among GHCPs, uncertainty characterization has primarily focused on GCM and emissions scenario choice, while the consequences of using a single GHCP to make predictions over space and time have received less attention. Here we employ average July temperature data from observations and seven GHCPs to model plant canopy cover and tree basal area across central Alaska, USA. We first compare the fit of, and support for, models employing observed temperatures, GHCP temperatures, and GHCP temperatures with an elevation adjustment, finding (1) greater support for, and better fit using, elevation-adjusted vs. raw temperature models and (2) overall similar fits of elevation-adjusted models employing temperatures from observations or GHCPs. Focusing on basal area, we next compare predictions generated by elevation-adjusted models employing GHCP data under current conditions and a warming scenario of current temperatures plus 2°C, finding good agreement among GHCPs though with between-GHCP differences and variation primarily at middle elevations (~1,000 m). These differences were amplified under the warming scenario. Finally, using pooled indices of prediction variation and difference across GHCP models, we identify characteristics of areas most likely to exhibit prediction uncertainty under current and warming conditions. Despite (1) overall good performance of GHCP data relative to observations in models and (2) positive correlation among model predictions, variation in predictions across models, particularly in mid-elevation areas where the position of treeline may be changing, suggests researchers should exercise caution if selecting a single GHCP for use in models. We recommend the use of multiple GHCPs to provide additional uncertainty information beyond standard estimated prediction intervals, particularly when model predictions are employed in conservation planning.

Can we project changes in fish abundance and distribution in response to climate?

Large-scale and long-term changes in fish abundance and distribution in response to climate change have been simulated using both statistical and process-based models. However, national and regional fisheries management requires also shorter term projections on smaller spatial scales, and these need to be validated against fisheries data. A 26-year time series of fish surveys with high spatial resolution in the North-East Atlantic provides a unique opportunity to assess the ability of models to correctly simulate the changes in fish distribution and abundance that occurred in response to climate variability and change. We use a dynamic bioclimate envelope model forced by physical-biogeochemical output from eight ocean models to simulate changes in fish abundance and distribution at scales down to a spatial resolution of 0.5°. When comparing with these simulations with annual fish survey data, we found the largest differences at the 0.5° scale. Differences between fishery model runs driven by different biogeochemical models decrease dramatically when results are aggregated to larger scales (e.g. the whole North Sea), to total catches rather than individual species or when the ensemble mean instead of individual simulations are used. Recent improvements in the fidelity of biogeochemical models translate into lower error rates in the fisheries simulations. However, predictions based on different biogeochemical models are often more similar to each other than they are to the survey data, except for some pelagic species. We conclude that model results can be used to guide fisheries management at larger spatial scales, but more caution is needed at smaller scales.

Potential changes in the distribution of Carnegiea gigantea under future scenarios

Over the last decades several studies have identified that the directional changes in climate induced by anthropogenic emissions of greenhouse gases are affecting the ecology of desert ecosystems. In the Southwest United States, the impacts of climate change to plant abundance and distribution have already been reported, including in the Sonoran Desert ecosystem, home of the iconic Saguaro (Carnegiea gigantea). Hence, there is an urgent need to assess the potential impacts of climate change on the saguaro. The goals of this study are to provide a map of actual habitat suitability (1), describe the relationships between abiotic predictors and the saguaro distribution at regional extents (2), and describe the potential effect of climate change on the spatial distribution of the saguaro (3). Species Distribution Modeling (SDM) was used to investigate the relationships between abiotic variables and the Saguaro distribution. SDMs were calibrated using presence records, 2,000 randomly-generated pseudo absences, and ten abiotic variables. Of these, annual precipitation and max temperature of the warmest month was found to have the greatest relative influence on saguaro distribution. SDMs indicated that 6.9% and 8.1% of the current suitable habitat is predicted to be lost by 2050 and 2070, respectively. Therefore, predicted changes in climate may result in a substantial contraction of the suitable habitat for saguaro over the next century. By identifying the drivers of saguaro distribution and assessing potential changes in habitat suitability due to climate change, this study will help practitioners to design more comprehensive strategies to conserve the saguaro in the face of climate change.

Urban hubs of connectivity: contrasting patterns of gene flow within and among cities in the western black widow spider

As urbanization drastically alters the natural landscape and generates novel habitats within cities, the potential for changes to gene flow for urban-dwelling species increases. The western black widow spider (Latrodectus hesperus) is a medically relevant urban adapter pest species, for which we have previously identified population genetic signatures consistent with urbanization facilitating gene flow, likely due to human-mediated transport. Here, in an analysis of 1.9 million genome-wide SNPs, we contrast broad-scale geographical analyses of 10 urban and 11 non-urban locales with fine-scale within-city analyses including 30 urban locales across the western USA. These hierarchical datasets enable us to test hypotheses of how urbanization impacts multiple urban cities and their genetic connectivity at different spatial scales. Coupled fine-scale and broad-scale analyses reveal contrasting patterns of high and low genetic differentiation among locales within cities as a result of low and high genetic connectivity, respectively, of these cities to the overall population network. We discuss these results as they challenge the use of cities as replicates of urban eco-evolution, and have implications for conservation and human health in a rapidly growing urban habitat.

Binational climate change vulnerability assessment of migratory birds in the Great Lakes Basins: Tools and impediments

Climate change is a global concern, requiring international strategies to reduce emissions, however, climate change vulnerability assessments are often local in scope with assessment areas restricted to jurisdictional boundaries. In our study we explored tools and impediments to understanding and responding to the effects of climate change on vulnerability of migratory birds from a binational perspective. We apply and assess the utility of a Climate Change Vulnerability Index on 3 focal species using distribution or niche modeling frameworks. We use the distributional forecasts to explore possible changes to jurisdictional conservation responsibilities resulting from shifting distributions for: eastern meadowlark (Sturnella magna), wood thrush (Hylocichla mustelina), and hooded warbler (Setophaga citrina). We found the Climate Change Vulnerability Index to be a well-organized approach to integrating numerous lines of evidence concerning effects of climate change, and provided transparency to the final assessment of vulnerability. Under this framework, we identified that eastern meadowlark and wood thrush are highly vulnerable to climate change, but hooded warbler is less vulnerable. Our study revealed impediments to assessing and modeling vulnerability to climate change from a binational perspective, including gaps in data or modeling for climate exposure parameters. We recommend increased cross-border collaboration to enhance the availability and resources needed to improve vulnerability assessments and development of conservation strategies. We did not find evidence to suggest major shifts in jurisdictional responsibility for the 3 focal species, but results do indicate increasing responsibility for these birds in the Canadian Provinces. These Provinces should consider conservation planning to help ensure a future supply of necessary habitat for these species.

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options.

Uncertainties in the projection of species distributions related to general circulation models

Ecological Niche Models (ENMs) are increasingly used by ecologists to project species potential future distribution. However, the application of such models may be challenging, and some caveats have already been identified. While studies have generally shown that projections may be sensitive to the ENM applied or the emission scenario, to name just a few, the sensitivity of ENM-based scenarios to General Circulation Models (GCMs) has been often underappreciated. Here, using a multi-GCM and multi-emission scenario approach, we evaluated the variability in projected distributions under future climate conditions. We modeled the ecological realized niche (sensu Hutchinson) and predicted the baseline distribution of species with contrasting spatial patterns and representative of two major functional groups of European trees: the dwarf birch and the sweet chestnut. Their future distributions were then projected onto future climatic conditions derived from seven GCMs and four emissions scenarios using the new Representative Concentration Pathways (RCPs) developed for the Intergovernmental Panel on Climate Change (IPCC) AR5 report. Uncertainties arising from GCMs and those resulting from emissions scenarios were quantified and compared. Our study reveals that scenarios of future species distribution exhibit broad differences, depending not only on emissions scenarios but also on GCMs. We found that the between-GCM variability was greater than the between-RCP variability for the next decades and both types of variability reached a similar level at the end of this century. Our result highlights that a combined multi-GCM and multi-RCP approach is needed to better consider potential trajectories and uncertainties in future species distributions. In all cases, between-GCM variability increases with the level of warming, and if nothing is done to alleviate global warming, future species spatial distribution may become more and more difficult to anticipate. When future species spatial distributions are examined, we propose to use a large number of GCMs and RCPs to better anticipate potential trajectories and quantify uncertainties.

The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be "suitable" for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges.