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Aim: Optimum shifts in species–environment relationships are intensively studied in a wide range of ecological topics, including climate change and species invasion. Numerous statistical methods are used to study optimum shifts, but, to our knowledge, none explicitly estimate it. We extended an existing model to explicitly estimate optimum shifts for multiple species having symmetrical response curves. We called this new Bayesian hierarchical model the Explicit Hierarchical Model of Optimum Shifts (EHMOS). Location: All locations. Taxon: All taxa. Methods: In a simulation study, we compared the accuracy of EHMOS to a mean comparison method and a Bayesian generalized linear mixed model (GLMM). Specifically, we tested if the accuracy of the methods was sensitive to (1) sampling design, (2) species optimum position and (3) species ecological specialization. In addition, we compared the three methods using a real dataset of investigated optimum shifts in 24 Orthopteran species between two time periods along an elevation gradient. Results: Of all the simulated scenarios, EHMOS was the most accurate method. GLMM was the most sensitive method to species optimum position, providing unreliable estimates in the presence of marginal species, that is, species with an optimum close to a sampling boundary. The mean comparison method was also sensitive to species optimum position and ecological specialization, especially in an unbalanced sampling design, with high negative bias and low interval coverage compared to EHMOS. The case study results obtained with EHMOS were consistent with what is expected considering ongoing climate change, with mostly upward shifts, which further improved confidence in the accuracy of the EHMOS method. Main Conclusions: Explicit Hierarchical Model of Optimum Shifts could be used for a wide range of topics and extended to produce new insights, especially in climate change studies. Explicit estimation of optimum shifts notably allows investigation of ecological assumptions that could explain interspecific variability of these shifts. [ABSTRACT FROM AUTHOR]

Entomological studies often aim to estimate species distribution, community composition, or species‐richness patterns. False absences can, however, bias these estimates and should consequently not be overlooked in insect studies. Multi‐species occupancy models (MSOMs) afford a flexible solution to cover the main topics in ecological entomology while dealing with detectability issues.We sampled Orthoptera communities at 81 mountain grasslands sites in France, using three sampling techniques: sighting, listening, and sweep netting. Five plots were sampled per site. This sampling design allowed MSOMs to be used to estimate richness, occupancy, and detection probabilities while accounting for the effect of covariates. We also used MSOMs to evaluate the efficiency of the survey design and to assess the effects of sampling optimisation.The estimates obtained for altitudinal distribution were reliable, with known species distributions confirming the relevance of MSOMs to model the effects of covariates on Orthoptera communities. The species‐specific detection probability was often less than one and varied with the detection technique used and the grass height, confirming the need to deal with detection issues in orthopteran studies.We estimated an inventory completeness superior to 0.80 for 93% of the sites, and an overall detection probability superior to 0.95 for 52% of the species, suggesting the sampling design was suitable for studying occupancy in Orthoptera communities. We also found that the sweep netting step may be omitted or the number of plots reduced without affecting species detectability or inventory completeness. Those recommendations may help to optimise future sampling strategies. [ABSTRACT FROM AUTHOR]

Sampling efficiency is crucial to overcome the data crisis in biodiversity and to understand what drives the distribution of rare species.Adaptive niche‐based sampling (ANBS) is an iterative sampling strategy that relies on the predictions of species distribution models (SDMs). By predicting highly suitable areas to guide prospection, ANBS could improve the efficiency of sampling effort in terms of finding new locations for rare species. Its iterative quality could potentially mitigate the effect of small and initially biased samples on SDMs.In this study, we compared ANBS with random sampling by assessing the gain in terms of new locations found per unit of effort. The comparison was based on both simulations and two field surveys of mountain birds.We found an increasing probability of contacting the species through iterations if the focal species showed specialization in the environmental gradients used for modelling. We also identified a gain when using pseudo‐absences during first iterations, and a general tendency of ANBS to increase the omission rate in the spatial prediction of the species' niche or habitat.Overall, ANBS is an effective and flexible strategy that can contribute to a better understanding of distribution drivers in rare species. [ABSTRACT FROM AUTHOR]

Investigating how and why the life history and demographic traits of a species vary across its range is fundamental to understand its evolution and population ecology and then develop sustainable management recommendations. At the margins of a species' distribution range, populations are expected to exhibit a slower pace of life than in core areas, making them less able to withstand pressures that impact survival. To explore these questions, we estimated age and sex-dependent seasonal survival probabilities using 305 radio-tagged birds monitored over a 18-year period in two alpine rock ptarmigan populations at the southern limit of their distribution, one in the Alps and one in the Pyrenees. We also estimated fecundity of both populations and then conducted sensitivity analysis as well as population viability analyses using deterministic and stochastic population models. Annual survival probability was high in both populations (0.65 for adults and 0.60 for juveniles), but reproductive success was much lower in the Alps (0.55 chicks per hen in the Alps vs 1.19 in the Pyrenees). The results showed that adult survival was the most sensitive demographic parameter. While population in the Pyrenees was stable (λ=1.01; 0.87--1.16), the other in the Alps appeared to be strongly declining (λ=0.81; 0.72--0.91) and this difference was clearly driven by differences of fecundity. While our findings confirm that our peripheral populations are associated with a slower pace of life, they present the particularity to be situated both at the edge and at high altitude. A more systematic study of peripheral population at higher latitude or on island may provide new insight on inter-pop variations of pace of life that would be useful for manager of these cold-adapted species. [ABSTRACT FROM AUTHOR]

Connectivity in pond ecosystems is essential for amphibian population persistence. To test the role of connectivity, a diversity of scales accounting for the different processes underlying species distribution needs to be considered. Several approaches exist for accounting for the potential connectivity, mainly based on structural versus functional methods. Based on occupancy data, our aim was to assess the relative power of connectivity metrics in explaining amphibian distribution when accounting for cross‐scale effects from pond to network scales, and to identify network features relevant to amphibian conservation in agricultural landscapes in the Seine‐et‐Marne department (east of Paris, France).We propose an original analytical framework that allows examining different spatial scales of influence, with a focus on connectivity. We analyse the distribution of three amphibian species (Bufo bufo, Rana dalmatina, and Lissotriton vulgaris) in relation to various pond conditions (fish presence, water quality, and nearby woodland habitat) as well as connectivity using three connectivity approaches: (1) structural, (2) area‐functional based on potential migration areas, and (3) path‐functional based on the least accumulated cost paths. Values of landscape resistance were assigned according to a biological risk‐based approach that is proposed as an enhanced, transparent expert‐based approach. We further investigated cross‐scale effects in amphibian responses to the environment by assessing the relative importance of pond and network characteristics as well as their interactions.Despite some species‐specific characteristics, the area‐functional approach of connectivity was generally the most effective in explaining species distribution by emphasising the relevance of potential migration areas as conservation units. Although pond conditions usually had a greater influence than network connectivity, we highlighted important cross‐scale and threshold effects in species' response to local conditions, to pond connectivity, and to the availability of potentially suitable terrestrial habitats in the networks.Our cross‐scale approach accounts for scale‐dependent processes that potentially underlie amphibian distribution such as habitat selection and metapopulation dynamics. Both structural and functional connectivity should be considered as complementary features of pond connectivity when dispersal traits are likely to be less limiting. From a management perspective, our results encourage conservation plans to combine functional network‐centred strategies with the preservation of local conditions. We give guidelines as to the features of such networks to help maintain amphibian populations in agricultural landscapes. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms that regulate the dynamics of spatially structured populations (SSP) is a critical challenge for ecologists and conservation managers. Internal population processes such as births and deaths occur at a local level, while external processes such as dispersal take place at an inter‐population level. At both levels, density dependence is expected to play a critical role. At a patch scale, demographic traits (e.g., survival, breeding success) and the population growth rate can be influenced by density either negatively (e.g., competition effect) or positively (e.g., Allee effects). At the scale of an SSP, although positive density‐dependent dispersal has been widely reported, an increasing number of studies have highlighted negative density‐dependent dispersal.While many studies have investigated the effects of density on population growth or on dispersal, few have simultaneously examined density‐dependent effects at the scale of both the local population and the entire SSP. In this study, we examine how density is related to demographic processes at both the pond level (survival and population growth) and the SSP level (between‐pond dispersal) in a pond‐breeding amphibian, the great crested newt (Triturus cristatus). The study was based on 20 years of individual capture–recapture (CR) data (from 1996 to 2015) gathered from an SSP made up of 12 experimental ponds ("patches").We first used a CR multievent model to estimate both survival and dispersal rates in specific ponds as a function of distance between ponds. Then, using a second CR multievent model, we examined whether survival and recapture rates were influenced by population density in a pond. Lastly, we used state‐space time series models to investigate whether density affected population growth in each pond.Our results found a positive density‐dependent effect on survival and a negative density‐dependent effect on departure. In addition, the findings indicate that population growth was negatively related to density in all 12 ponds.These results support the hypothesis that in SSPs, density may have multiple and contrasting effects on demographic parameters and growth rates within local populations as well as on dispersal. This study underlines the need to better understand how density dependence may influence potential trade‐offs between life‐history strategies and life‐history stages. This paper is the first measure of density effects in a large spatially structured population of an amphibian. The relationship between density and both survival and emigration leads to local crowding effects. However, a negative relationship with local population growth rate suggests regulatory processes probably due to competition among larvae. [ABSTRACT FROM AUTHOR]

Abstract: Aim: Species distribution modelling, a family of statistical methods that predicts species distributions from a set of occurrences and environmental predictors, is now routinely applied in many macroecological studies. However, the reliability of evaluation metrics usually employed to validate these models remains questioned. Moreover, the emergence of online databases of environmental variables with global coverage, especially climatic, has favoured the use of the same set of standard predictors. Unfortunately, the selection of variables is too rarely based on a careful examination of the species' ecology. In this context, our aim was to highlight the importance of selecting ad hoc variables in species distribution models, and to assess the ability of classical evaluation statistics to identify models with no biological realism. Innovation: First, we reviewed the current practices in the field of species distribution modelling in terms of variable selection and model evaluation. Then, we computed distribution models of 509 European species using pseudo‐predictors derived from paintings or using a real set of climatic and topographic predictors. We calculated model performance based on the area under the receiver operating curve (AUC) and true skill statistics (TSS), partitioning occurrences into training and test data with different levels of spatial independence. Most models computed from pseudo‐predictors were classified as good and sometimes were even better evaluated than models computed using real environmental variables. However, on average they were better discriminated when the partitioning of occurrences allowed testing for model transferability. Main conclusions: These findings confirm the crucial importance of variable selection and the inability of current evaluation metrics to assess the biological significance of distribution models. We recommend that researchers carefully select variables according to the species' ecology and evaluate models only according to their capacity to be transfered in distant areas. Nevertheless, statistics of model evaluations must still be interpreted with great caution. [ABSTRACT FROM AUTHOR]

The environment of most species is heterogeneous at different spatial and temporal scales; this heterogeneity can have a direct effect on various components of fitness. As a consequence, individual space-use and movement strategies are central issues in ecology and conservation and receive considerable attention from researchers., In the last 30 years, this issue has led to the development of capture-recapture models that allow movement between sites to be quantified, while handling imperfect detection. For studies involving numerous recapture sites in which the emphasis is on dispersal or migration rather than movement between particular sites, Lagrange et al. recently proposed a parsimonious CR multi-event model that contrasts individuals that move and individuals that stay in place, irrespective of the sites involved., In this study, we developed a generalized version of this model to allow survival probability and movement probability to differ for different types of habitat to which the individual sites may be assigned. We investigated the potential of this new parameterization by studying the movements of an amphibian, the yellow-bellied toad ( Bombina variegata), in a set of breeding and resting/foraging ponds., Our capture-recapture multi-event model provides a highly flexible tool allowing users to model movements within and between several habitats. This approach can be potentially used to study movement behaviour and space-use strategies of a wide range of taxa. [ABSTRACT FROM AUTHOR]

Aim To determine the performance of different pseudo-absence selection strategies on the prediction of species-distribution models after 30 years of regional climatic and land use changes. Location Continental France and the Iberian Peninsula. Methods In this study, we used a large database of Coprophagous Scarabaeidae beetle records collected between 1970 and 1980 in continental France and the Iberian Peninsula to assess the relative performance of different modelling methods in predicting species distributions using current climate and land use information. We used maxent with standard settings and boosted regression trees with three different approaches to generate pseudo-absences. We used historical data to model species distribution and then projected the models into the present. Each method's performance was then assessed by specific field sampling conducted at 20 different sites. Results Field validation demonstrated that model predictions were more accurate when pseudo-absence data were selected from a sampling bias grid and that model evaluations based on test datasets can lead to false conclusions if not correctly calibrated. The study also demonstrated that the method in which pseudo-absences are dealt with has a major impact on ecological conclusions. Main conclusion Correcting for spatial bias in collections datasets is of great importance for predicting future trends in species distributions. Uncorrected models showed a strong bias in their predicted species richness patterns. [ABSTRACT FROM AUTHOR]

Occupancy estimates can inform biodiversity managers about the distribution of elusive species, such as the Pyrenean desman Galemys pyrenaicus, a small semi-aquatic mammal that lives along streams. Occupancy models rely on replication within a sampling site and provide estimates of the probability of detection. However, we still do not know how occupancy and detection estimates obtained from spatial vs. temporal replications differ or the appropriateness of using one or the other when cost and logistics make one approach prohibitive. Recently, the Markovian occupancy model has been developed to analyse adjacent spatial replicates and to test for spatial dependence between them. This model has already been applied to large and highly mobile mammals using trails, but never tested for any species with linear home ranges., We compared detection and occupancy estimates obtained from both temporal and spatial sampling designs that were subsequently organized into four data configurations (sites with both spatial and temporal replicates, adjacent spatial replicates only, temporal replicates only at the segment and site scales). From that, five occupancy models with different assumptions (the standard occupancy model, the standard multiscale model, the multiscale model with Markovian process for detection, the Markovian detection model and the Markovian occupancy model) were used. We also assessed which occupancy model was the most appropriate for each data configuration to determine whether it is necessary to incorporate correlation into models., We found that the estimated detection probabilities were relatively high (≥0·58) and similar when the same model was applied to each data configuration., Spatial replication weakly underestimated occupancy. But when using this design, the Markovian occupancy model was the most supported and minimized the underestimation of occupancy, highlighting a spatial dependence between adjacent replicates., Synthesis and applications. We show that a survey based on adjacent spatial replicates for a mammal living along linear features of the landscape is a good compromise between cost and occupancy estimates, while using the Markovian occupancy model to estimate detection and occupancy. Our finding may have wider applications for the monitoring of species especially when temporal replicates are difficult or unrealistic. Spatial design, for surveys based on sign detection, could thus be applied for species with linear home ranges or when surveys are constrained by linear habitats. [ABSTRACT FROM AUTHOR]

The invasion of the giant Madagascar day gecko Phelsuma grandis has increased the threats to the four endemic Mauritian day geckos (Phelsuma spp.) that have survived on mainland Mauritius. We had two main aims: (i) to predict the spatial distribution and overlap of P. grandis and the endemic geckos at a landscape level; and (ii) to investigate the effects of P. grandis on the abundance and risks of extinction of the endemic geckos at a local scale. An ensemble forecasting approach was used to predict the spatial distribution and overlap of P. grandis and the endemic geckos. We used hierarchical binomial mixture models and repeated visual estimate surveys to calculate the abundance of the endemic geckos in sites with and without P. grandis. The predicted range of each species varied from 85 km2 to 376 km2. Sixty percent of the predicted range of P. grandis overlapped with the combined predicted ranges of the four endemic geckos; 15% of the combined predicted ranges of the four endemic geckos overlapped with P. grandis. Levin's niche breadth varied from 0.140 to 0.652 between P. grandis and the four endemic geckos. The abundance of endemic geckos was 89% lower in sites with P. grandis compared to sites without P. grandis, and the endemic geckos had been extirpated at four of ten sites we surveyed with P. grandis. Species Distribution Modelling, together with the breadth metrics, predicted that P. grandis can partly share the equivalent niche with endemic species and survive in a range of environmental conditions. We provide strong evidence that smaller endemic geckos are unlikely to survive in sympatry with P. grandis. This is a cause of concern in both Mauritius and other countries with endemic species of Phelsuma. [ABSTRACT FROM AUTHOR]

Highlights: [•] We compared IUCN expert-based map of corncrake range and modelled distribution. [•] A sampling bias correction was applied to build an accurate distribution model. [•] The modelled distribution was surprisingly close to the expert-based assessment. [•] Model predictions are significantly correlated with species abundance per country. [Copyright &y& Elsevier]

Environmental DNA (eDNA) analysis allows efficient surveys of freshwater species and is being increasingly used. However, because different authors use different methods, eDNA data cannot easily be summarised for a global overview. One promising approach is to standardise methods for long-term monitoring. Standardised eDNA metabarcoding methods have been implemented in France for an elusive group: freshwater bivalves. All French bivalve species can be detected and identified at each sampling site. Here, we analyse this comprehensive dataset (280 sites across all France; 40 species) to investigate detection probabilities, infer species distributions and reassess conservation status, and finally examine community patterns (richness) and their determinants. Our method gave over 95 % probability of detection for most species. Species distributions inferred from eDNA sampling were compared with currently known distributions. Four invasive species and one species of conservation concern were found outside their known range. Others were found in a surprisingly small number of localities, although they are currently thought to be widespread and not of conservation concern. Indeed, the databases currently used to determine conservation status are biased by the inclusion of old data, mainly based on shell records only, and may include misidentified species. The main drivers of species richness were latitude and distance from the spring. Co-occurrence of species was investigated for the first time. The results highlight the valuable data that eDNA analysis can provide when used on a large scale, for monitoring and ecological studies, as well as providing improved species distributions, which are essential for conservation policymaking. [Display omitted] • An extensive eDNA survey (260 sites) of freshwater bivalves has been undertaken • We study detection probabilities, current distributions and drivers of biodiversity patterns • The conservation status of some species is reassessed • The use of large-scale eDNA monitoring provides important guidelines for conservation policy [ABSTRACT FROM AUTHOR]

As freshwater habitats are among the most endangered, there is an urgent need to identify critical areas for conservation, especially those that are home to endangered species. The Pyrenean desman ( Galemys pyrenaicus ) is a semi-aquatic mammal whose basic ecological requirements are largely unknown, hindering adequate conservation planning even though it is considered as a threatened species. Species distribution modelling is challenging for freshwater species. Indeed, the complexity of aquatic ecosystems (e.g., linear and hierarchical ordering) must be taken into account as well as imperfect sampling. High-quality and relevant hydrological descriptors should also be used. To understand the influence of environmental covariates on the occupancy and detection of the Pyrenean desman, we combine both a robust sign-survey data set (i.e. with genetic validation ensuring true presence information) and a hydrological model to simulate the flow regime across a whole catchment. Markovian site-occupancy analysis, taking into account sign detection and based on spatially adjacent replicates, indicated a positive influence of heterogeneity of substrate and shelters, and a negative influence of flow variability on Pyrenean desman detection. This valuable information should help to improve monitoring programs for this endangered species. Our results also highlighted a spatially clustered distribution and a positive influence of stream flow and number of tributaries on occupancy. Hence, modifications of flow regime (e.g. hydropower production, irrigation, climate change) and habitat fragmentation appear to be major threats for this species, altering the connectivity between tributaries and the mainstream river as well as between adjacent sub-catchments. [ABSTRACT FROM AUTHOR]