Evaluating The Impact Of Species Specialisation On Ecological Network Robustness Using Analytic Methods

Ecological networks describe the interactions between different species, informing us of how they rely on one another for food, pollination and survival. If a species in an ecosystem is under threat of extinction, it can affect other species in the system and possibly result in their secondary extinction as well. Understanding how (primary) extinctions cause secondary extinctions on ecological networks has been considered previously using computational methods. However, these methods do not provide an explanation for the properties which make ecological networks robust, and can be computationally expensive. We develop a new analytic model for predicting secondary extinctions which requires no non-deterministic computational simulation. Our model can predict secondary extinctions when primary extinctions occur at random or due to some targeting based on the number of links per species or risk of extinction, and can be applied to an ecological network of any number of layers. Using our model, we consider how false positives and negatives in network data affect predictions for network robustness. We have also extended the model to predict scenarios in which secondary extinctions occur once species lose a certain percentage of interaction strength, and to model the loss of interactions as opposed to just species extinction. From our model, it is possible to derive new analytic results such as how ecological networks are most robust when secondary species degree variance is minimised. Additionally, we show that both specialisation and generalisation in distribution of interaction strength can be advantageous for network robustness, depending upon the extinction scenario being considered.Comment: 22 pages, 12 figures, 2 table

Large carnivore range expansion in Iberia in relation to different scenarios of permeability of human‐dominated landscapes

Aim Large carnivores are currently recolonizing parts of their historical ranges in Europe after centuries of persecution and habitat loss. Understanding the mechanisms driving these recolonizations is important for proactive conservation planning. Using the brown bear (Ursus arctos) and the Iberian lynx (Lynx pardinus) as examples, we explore where and when large carnivores are likely to expand into human-dominated landscapes and how varying levels of resistance due to human pressure might impact this recolonization process. Location Iberian Peninsula. Methods We used ensembles of species distribution models to relate species occurrence data to climate, topography and satellite-based land-cover predictors at a 10 km spatial resolution. Resulting predictions of suitable habitat areas were fed into a dispersal model to simulate range expansion over the 10 time-steps for different human pressure scenarios. Finally, we overlaid predictions with protected areas to highlight areas that are likely key for future connectivity, but where human pressures might hamper dispersal. Results We found widespread suitable habitat for both species (bear: 30,000 km2, lynx: 170,000 km2), yet human pressure limits potential range expansions. For brown bears, core habitats between the Cantabrian and Pyrenean populations remained unconnected despite suitable habitat in between. For lynx, we predicted higher range expansion potential, although high human pressures in southern coastal Spain negatively affected expansion potential. Main conclusions Our results highlight that the recolonization potential of brown bears and lynx in the Iberian Peninsula is likely more constrained by lower permeability of landscapes due to human pressure than by habitat availability, a situation likely emblematic for large carnivores in many parts of the world. More generally, our approach provides a simple tool for conservation planners and managers to identify where range expansion is likely to occur and where proactively managing to allow large carnivores to safely disperse through human-dominated landscapes can contribute to viable large carnivore populations.Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Peer Reviewe

Standardised empirical dispersal kernels emphasise the pervasiveness of long‐distance dispersal in European birds

1. Dispersal is a key life-history trait for most species and is essential to ensure connectivity and gene flow between populations and facilitate population viability in variable environments. Despite the increasing importance of range shifts due to global change, dispersal has proved difficult to quantify, limiting empirical understanding of this phenotypic trait and wider synthesis. 2. Here, we introduce a statistical framework to estimate standardised dispersal kernels from biased data. Based on this, we compare empirical dispersal kernels for European breeding birds considering age (average dispersal; natal, before first breeding; and breeding dispersal, between subsequent breeding attempts) and sex (females and males) and test whether different dispersal properties are phylogenetically conserved. 3. We standardised and analysed data from an extensive volunteer-based bird ring-recoveries database in Europe (EURING) by accounting for biases related to different censoring thresholds in reporting between countries and to migratory movements. Then, we fitted four widely used probability density functions in a Bayesian framework to compare and provide the best statistical descriptions of the different age and sex-specific dispersal kernels for each bird species. 4. The dispersal movements of the 234 European bird species analysed were statistically best explained by heavy-tailed kernels, meaning that while most individuals disperse over short distances, long-distance dispersal is a prevalent phenomenon in almost all bird species. The phylogenetic signal in both median and long dispersal distances estimated from the best-fitted kernel was low (Pagel's λ 0.7) when comparing dispersal distance estimates for fat-tailed dispersal kernels. As expected in birds, natal dispersal was on average 5 km greater than breeding dispersal, but sex-biased dispersal was not detected. 5. Our robust analytical framework allows sound use of widely available mark-recapture data in standardised dispersal estimates. We found strong evidence that long-distance dispersal is common among European breeding bird species and across life stages. The dispersal estimates offer a first guide to selecting appropriate dispersal kernels in range expansion studies and provide new avenues to improve our understanding of the mechanisms and rules underlying dispersal events.Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Peer Reviewe

RangeShifter 2.0 : An extended and enhanced platform for modelling spatial eco-evolutionary dynamics and species’ responses to environmental changes

Acknowledgements We thank R. L. Allgayer, A. Ponchon and N. W. Synes for their help and contribution to the RangeShifter development and application. We also thank the many users of RangeShifter and participants to workshops for their invaluable feedback. Funding Development of RangeShifter 2.0 was supported by the project PROBIS funded by the BiodivERsA European Joint Call 2012–2013. GB was supported by a Royal Society University Research Fellowship (UF160614). AKM and DZ were supported by Deutsche Forschungsgemeinschaft (DFG) under grant agreement no. ZU 361/1-1.Peer reviewedPublisher PD

Spatially explicit models for decision-making in animal conservation and restoration

DZ, CK, AKM and GF were supported by the German Science Foundation (DFG) under grant agreement no. ZU 361/1-1. GB was supported by a Royal Society University Research Fellowship (UF160614). We acknowledge the support of the Deutsche Forschungsgemeinschaft and Open Access Publishing Fund of University of Potsdam.Peer reviewedPublisher PD

RangeShiftR : an R package for individual-based simulation of spatial eco-evolutionary dynamics and species' responses to environmental changes

Acknowledgements – We are grateful for valuable feedback from many users who tested previous versions of the package. The Figures 1 and 2 were created using the draw.io app. We acknowledge the support of the Open Access Publishing Fund of the Univ. of Potsdam. Funding – AM and DZ were supported by Deutsche Forschungsgemeinschaft (DFG) under grant agreement No. ZU 361/1-1. GB was supported by a Royal Society University Research Fellowship (UF160614).Peer reviewedPublisher PD

Seasonal niche tracking of climate emerges at the population level in a migratory bird.

Seasonal animal migration is a widespread phenomenon. At the species level, it has been shown that many migratory animal species track similar climatic conditions throughout the year. However, it remains unclear whether such a niche tracking pattern is a direct consequence of individual behaviour or emerges at the population or species level through behavioural variability. Here, we estimated seasonal niche overlap and seasonal niche tracking at the individual and population level of central European white storks (Ciconia ciconia). We quantified niche tracking for both weather and climate conditions to control for the different spatio-temporal scales over which ecological processes may operate. Our results indicate that niche tracking is a bottom-up process. Individuals mainly track weather conditions while climatic niche tracking mainly emerges at the population level. This result may be partially explained by a high degree of intra- and inter-individual variation in niche overlap between seasons. Understanding how migratory individuals, populations and species respond to seasonal environments is key for anticipating the impacts of global environmental changes

Dispersal and extrapolation on the accuracy of temporal predictions from distribution models for the Darwin's frog

Indexación: Web of Science; Scopus.Climate change is a major threat to biodiversity; the development of models that reliably predict its effects on species distributions is a priority for conservation biogeography. Two of the main issues for accurate temporal predictions from Species Distribution Models (SDM) are model extrapolation and unrealistic dispersal scenarios. We assessed the consequences of these issues on the accuracy of climate-driven SDM predictions for the dispersal-limited Darwin's frog Rhinoderma darwinii in South America. We calibrated models using historical data (1950-1975) and projected them across 40 yr to predict distribution under current climatic conditions, assessing predictive accuracy through the area under the ROC curve (AUC) and True Skill Statistics (TSS), contrasting binary model predictions against temporal-independent validation data set (i.e., current presences/absences). To assess the effects of incorporating dispersal processes we compared the predictive accuracy of dispersal constrained models with no dispersal limited SDMs; and to assess the effects of model extrapolation on the predictive accuracy of SDMs, we compared this between extrapolated and no extrapolated areas. The incorporation of dispersal processes enhanced predictive accuracy, mainly due to a decrease in the false presence rate of model predictions, which is consistent with discrimination of suitable but inaccessible habitat. This also had consequences on range size changes over time, which is the most used proxy for extinction risk from climate change. The area of current climatic conditions that was absent in the baseline conditions (i.e., extrapolated areas) represents 39% of the study area, leading to a significant decrease in predictive accuracy of model predictions for those areas. Our results highlight (1) incorporating dispersal processes can improve predictive accuracy of temporal transference of SDMs and reduce uncertainties of extinction risk assessments from global change; (2) as geographical areas subjected to novel climates are expected to arise, they must be reported as they show less accurate predictions under future climate scenarios. Consequently, environmental extrapolation and dispersal processes should be explicitly incorporated to report and reduce uncertainties in temporal predictions of SDMs, respectively. Doing so, we expect to improve the reliability of the information we provide for conservation decision makers under future climate change scenarios.http://onlinelibrary.wiley.com/doi/10.1002/eap.1556/abstract;jsessionid=1E2084FF99600D0EEC9FA358A3DBC2A3.f02t0

Predicting extinctions with species distribution models

Predictions of species-level extinction risk from climate change are mostly based on species distribution models (SDMs). Reviewing the literature, we summarise why the translation of SDM results to extinction risk is conceptually and methodologically challenged and why critical SDM assumptions are unlikely to be met under climate change. Published SDM-derived extinction estimates are based on a positive relationship between range size decline and extinction risk, which empirically is not well understood. Importantly, the classification criteria used by the IUCN Red List of Threatened Species were not meant for this purpose and are often misused. Future predictive studies would profit considerably from a better understanding of the extinction risk–range decline relationship, particularly regarding the persistence and non-random distribution of the few last individuals in dwindling populations. Nevertheless, in the face of the ongoing climate and biodiversity crises, there is a high demand for predictions of future extinction risks. Despite prevailing challenges, we agree that SDMs currently provide the most accessible method to assess climate-related extinction risk across multiple species. We summarise current good practice in how SDMs can serve to classify species into IUCN extinction risk categories and predict whether a species is likely to become threatened under future climate. However, the uncertainties associated with translating predicted range declines into quantitative extinction risk need to be adequately communicated and extinction predictions should only be attempted with carefully conducted SDMs that openly communicate the limitations and uncertainty

Estimating nest-switching in free-ranging wild birds: an assessment of the most common methodologies, illustrated in the White Stork (Ciconia ciconia)

Reliable estimates of nest-switching are required to study avian mating systems and manage wild populations, yet different estimation methods have rarely been integrated or assessed. Through a literature review and case study, we reveal that three common methods for assessing nest-switching blend different components, producing a wide range of estimates. Careful component definition and reporting are essential to properly estimate this behaviour