Projected northward shifts in eastern red-backed salamanders due to changing climate.

Many species' distributions are being impacted by the acceleration of climate change. Amphibians in particular serve numerous ecosystem functions and are useful indicators of environmental change. Understanding how their distributions have been impacted by climate change and will continue to be impacted is thus important to overall ecosystem health. Plethodon cinereus (Eastern Red-Backed Salamander) is a widespread species of lungless salamander (Plethodontidae) that ranges across northeastern North America. To better understand future potential lungless salamander range shifts, we quantify environmental favorability, the likelihood of membership in a set of sites where environmental conditions are favorable for a species, for P. cinereus in multiple time periods, and examine shifts in the species' distribution. First, utilizing a large data set of georeferenced records, we assessed which bioclimatic variables were associated with environmental favorability in P. cinereus. We then used species distribution modeling for two time periods (1961-1980 and 2001-2020) to determine whether there was a regional shift in environmental favorability in the past 60 years. Models were then used to project future distributions under eight climate change scenarios to quantify potential range shifts. Shifts were assessed using fuzzy logic, avoiding thresholds that oversimplify model predictions into artificial binary outputs. We found that P. cinereus presence is strongly associated with environmental stability. There has been a substantial northward shift in environmental favorability for P. cinereus between 1961-1980 and 2001-2020. This shift is predicted to continue by 2070, with larger shifts under higher greenhouse gas emission scenarios. As climate change accelerates, it is differentially impacting species but has especially strong impacts on dispersal-limited species. Our results show substantial northward shifts in climatic favorability in the last 60 years for P. cinereus, which are likely to be exacerbated by ongoing climate change. Since P. cinereus is dispersal-limited, these models may imply local extirpations along the southern modern range with limited northward dispersal. Continued monitoring of amphibians in the field will reveal microclimatic effects associated with climate change and the accuracy of the model predictions presented here.

Mechanistic models project bird invasions with accuracy.

Invasive species pose a major threat to biodiversity and inflict massive economic costs. Effective management of bio-invasions depends on reliable predictions of areas at risk of invasion, as they allow early invader detection and rapid responses. Yet, considerable uncertainty remains as to how to predict best potential invasive distribution ranges. Using a set of mainly (sub)tropical birds introduced to Europe, we show that the true extent of the geographical area at risk of invasion can accurately be determined by using ecophysiological mechanistic models that quantify species' fundamental thermal niches. Potential invasive ranges are primarily constrained by functional traits related to body allometry and body temperature, metabolic rates, and feather insulation. Given their capacity to identify tolerable climates outside of contemporary realized species niches, mechanistic predictions are well suited for informing effective policy and management aimed at preventing the escalating impacts of invasive species.

MAMMALS IN PORTUGAL: A data set of terrestrial, volant, and marine mammal occurrences in Portugal.

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications.

Spatiotemporal persistence of bat roadkill hotspots in response to dynamics of habitat suitability and activity patterns.

Wildlife roadkill hotspots are frequently used to identify priority locations for implementing mitigation measures. However, understanding the landscape-context and the spatial and temporal dynamics of these hotspots is challenging. Here, we investigate the factors that drive the spatiotemporal variation of bat mortality hotspots on roads along three years. We hypothesize that hotspot locations occur where bat activity is higher and that this activity is related to vegetation density and productivity, probably because this is associated with food availability. Statistically significant clusters of bat-vehicle collisions for each year were identified using the Kernel Density Estimation (KDE) approach. Additionally, we used a spatiotemporal analysis and generalized linear mixed models to evaluate the effect of local spatiotemporal variation of environmental indices and bat activity to predict the variation on roadkill hotspot locations and to asses hotspot strength over time. Between 2009 and 2011 we conducted daily surveys of bat casualties along a 51-km-long transect that incorporates different types of roads in southern Portugal. We found 509 casualties and we identified 86 statistically significant roadkill hotspots, which comprised 12% of the road network length and contained 61% of the casualties. Hotspots tended to be located in areas with higher accumulation of vegetation productivity along the three-year period, high bat activity and low temperature. Furthermore, we found that only 17% of the road network length was consistently classified as hotspots across all years; while 43% of hotspots vanished in consecutive years and 40% of new road segments were classified as hotspots. Thus, non-persistent hotspots were the most frequent category. Spatiotemporal changes in hotspot location are associated with decreasing vegetation production and increasing water stress on road surroundings. This supports our hypothesis that a decline on overall vegetation productivity and increase of roadside water deficit, and the presumed lower abundance of prey, have a significant effect on the decrease of bat roadkills. To our knowledge, this is the first study demonstrating that freely available remote sensing data can be a powerful tool to quantify bat roadkill risk and assess its spatiotemporal dynamics.

Rattlesnake (Crotalus spp.) distribution and diversity in Zacatecas, Mexico.

Mexico is home to a large number of reptile species and has one of the greatest diversities of venomous snakes, among which the rattlesnakes pertaining to the Crotalus genus stand out. Out of more than 40 species in the country, nine are found in Zacatecas: C. aquilus, C. atrox, C. basiliscus, C. lepidus, C. molossus, C. polystictus, C. pricei, C. scutulatus and C. willardi. Although these reptiles are important, due to their relevance in terms of ecology, cultural use and public health, their conservation is impacted by multiple factors, such as habitat fragmentation and indiscriminate killing. Thus, most species within this genus are found in some type of risk category at both the national and international level. The purpose of this study was to determine the potential distribution and diversity of rattlesnakes at the municipal level in the understudied state of Zacatecas. To do this, we analyzed and described the global distribution of nine rattlesnake species by building species distribution models, which determined their potential distribution based on a set of ecological variables and presence records. The resulting models were used to assess the diversity of rattlesnake species potentially present in each municipality within the state. Thirty-nine (67.24 %) out of fifty-eight municipalities registered at least one rattlesnake species. Fresnillo, Sombrerete and Valparaíso were some of the municipalities showing greatest diversity. Moreover, C. atrox, C. lepidus, C. molossus and C. scutulatus were the most widely found species in the state. On the other hand, C. basiliscus, C. polystictus, C. pricei and C. willardi were rarely spotted and so, information on their distribution patterns within Zacatecas is limited. Finally, the areas having the largest potential for the distribution of these species were defined. These findings should make field work much more time- and cost-effective, facilitating the collection of in situ data that are useful for management and conservation plans of these species in Zacatecas.

Accounting for Connectivity Uncertainties in Predicting Roadkills: a Comparative Approach between Path Selection Functions and Habitat Suitability Models.

Functional connectivity modeling is increasingly used to predict the best spatial location for over- or underpasses, to mitigate road barrier effects and wildlife roadkills. This tool requires estimation of resistance surfaces, ideally modeled with movement data, which are costly to obtain. An alternative is to use occurrence data within species distribution models to infer movement resistance, although this remains a controversial issue. This study aimed both to compare the performance of resistance surfaces derived from path versus occurrence data in identifying road-crossing locations of a forest carnivore and assess the influence of movement type (daily vs. dispersal) on this performance. Resistance surfaces were built for genet (Genetta genetta) in southern Portugal using path selection functions with telemetry data, and species distribution models with occurrence data. An independent roadkill dataset was used to evaluate the performance of each connectivity model in predicting roadkill locations. The results show that resistance surfaces derived from occurrence data are as suitable in predicting roadkills as path data for daily movements. When dispersal was simulated, the performance of both resistance surfaces was equally good at predicting roadkills. Moreover, contrary to our expectations, we found no significant differences in locations of roadkill predictions between models based on daily movements and models based on dispersal. Our results suggest that species distribution models are a cost-effective tool to build functional connectivity models for road mitigation plans when movement data are not available.

Changes in potential mammal diversity in national parks and their implications for conservation.

Observed species richness (OSR) is a widely used and well-studied biodiversity metric. However, non-observed species in favorable ecosystems are also relevant. Two metrics that include observed and potential species were recently defined: potential biodiversity (hereafter potential species richness-PSR) and geometric mean of favorabilities (GMF). We used these metrics to evaluate the national park network of mainland Spain at two time periods (2002 and 2015), using terrestrial mammals on a UTM 100-km2 grid. PSR and GMF are based on the favorability function, a species distribution model that assesses how favorable an area is for the presence of a species, over and above its prevalence in the study area. For each park and for the whole network, we calculated the mean and sum of OSR, PSR, and GMF in each time period, as well as changes between periods. OSR and PSR were higher inside than outside the park network in both time periods. Thus, although the network covers a very small proportion of the country, it performs well for the representation of mammal species and their favorable areas. However, mean PSR was lower in 2015 than in 2002 inside the national park network, whereas the opposite was the case outside the network. Mountainous Parks generally not only concentrated highly favorable areas for mammals, but they also showed less favorable areas in 2015 compared to 2002, although the reduction was moderate to low. This is a result to consider for future analyses because if the tendency increases, it may have consequences for the conservation of mammals and for the adequacy of the national park network.

Research trends and geographical distribution of mammalian carnivores in Portugal (SW Europe).

Information regarding species' status at a regional scale is instrumental for effective conservation planning. Some regions of southwestern Europe, such as Portugal, albeit included in the Mediterranean biodiversity hotspot, lack a detailed assessment of the distribution patterns of several taxonomic groups, such as carnivores. Moreover, information is scattered, often unreliable and biased towards some species or regions. This study aimed at reviewing the existing knowledge on mammalian terrestrial carnivores in Portugal, to analyse research trends, update the species checklist and assess their historical and current distribution patterns. We conducted a comprehensive review of 755 scientific studies to analyse several publication metrics and compiled 20,189 presence records of all mammalian terrestrial carnivores occurring in Portugal since historical times to evaluate their distribution patterns. Carnivore research in Portugal began in the 18th century, with a recent boost in the mid-1990s, and has been biased towards certain research topics and regionally threatened species. There are 15 extant species in Portugal, with nine occurring across the country, six showing a more limited range, as well as one additional species currently locally extinct (Ursus arctos). Over the last decades, the distribution ranges of seven species apparently remained stable, two expanded, two contracted, and three showed unclear trends. The presence of a new invasive carnivore, the raccoon (Procyon lotor), is also documented here. This study illustrates the relevance of a comprehensive analysis of non-systematic data to assess the historic and current status of mammalian terrestrial carnivores at a national level, and to identify knowledge gaps and research priorities.

Outstanding Challenges in the Transferability of Ecological Models.

Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their 'transferability') undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models. Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions.

Integrative inference of population history in the Ibero-Maghrebian endemic Pleurodeles waltl (Salamandridae).

Inference of population histories from the molecular signatures of past demographic processes is challenging, but recent methodological advances in species distribution models and their integration in time-calibrated phylogeographic studies allow detailed reconstruction of complex biogeographic scenarios. We apply an integrative approach to infer the evolutionary history of the Iberian ribbed newt (Pleurodeles waltl), an Ibero-Maghrebian endemic with populations north and south of the Strait of Gibraltar. We analyzed an extensive multilocus dataset (mitochondrial and nuclear DNA sequences and ten polymorphic microsatellite loci) and found a deep east-west phylogeographic break in Iberian populations dating back to the Plio-Pleistocene. This break is inferred to result from vicariance associated with the formation of the Guadalquivir river basin. In contrast with previous studies, North African populations showed exclusive mtDNA haplotypes, and formed a monophyletic clade within the Eastern Iberian lineage in the mtDNA genealogy. On the other hand, microsatellites failed to recover Moroccan populations as a differentiated genetic cluster. This is interpreted to result from post-divergence gene flow based on the results of IMA2 and Migrate analyses. Thus, Moroccan populations would have originated after overseas dispersal from the Iberian Peninsula in the Pleistocene, with subsequent gene flow in more recent times, implying at least two trans-marine dispersal events. We modeled the distribution of the species and of each lineage, and projected these models back in time to infer climatically favourable areas during the mid-Holocene, the last glacial maximum (LGM) and the last interglacial (LIG), to reconstruct more recent population dynamics. We found minor differences in climatic favourability across lineages, suggesting intraspecific niche conservatism. Genetic diversity was significantly correlated with the intersection of environmental favourability in the LIG and LGM, indicating that populations of P. waltl are genetically more diverse in regions that have remained environmentally favourable through the last glacial cycle, particularly southern Iberia and northern Morocco. This study provides novel insights into the relative roles of geology and climate on the biogeography of a biodiversity hotspot.

Species Distributions, Quantum Theory, and the Enhancement of Biodiversity Measures.

Species distributions are typically represented by records of their observed occurrence at a given spatial and temporal scale. Such records are inevitably incomplete and contingent on the spatial-temporal circumstances under which the observations were made. Moreover, organisms may respond differently to similar environmental conditions at different places or moments, so their distribution is, in principle, not completely predictable. We argue that this uncertainty exists, and warrants considering species distributions as analogous to coherent quantum objects, whose distributions are better described by a wavefunction rather than by a set of locations. We use this to extend the existing concept of "dark diversity", which incorporates into biodiversity metrics those species that could, but which have not yet been observed to, inhabit a region-thereby developing the idea of "potential biodiversity". We show how conceptualizing species' distributions in this way could help overcome important weaknesses in current biodiversity metrics, both in theory and by using a worked case study of mammal distributions in Spain over the last decade. We propose that considerable theoretical advances could eventually be gained through interdisciplinary collaboration between biogeographers and quantum physicists. [Biogeography; favorability; physics; predictability; probability; species occurrence; uncertainty; wavefunction.

Sampling effects on the identification of roadkill hotspots: Implications for survey design.

Although locating wildlife roadkill hotspots is essential to mitigate road impacts, the influence of study design on hotspot identification remains uncertain. We evaluated how sampling frequency affects the accuracy of hotspot identification, using a dataset of vertebrate roadkills (n = 4427) recorded over a year of daily surveys along 37 km of roads. "True" hotspots were identified using this baseline dataset, as the 500-m segments where the number of road-killed vertebrates exceeded the upper 95% confidence limit of the mean, assuming a Poisson distribution of road-kills per segment. "Estimated" hotspots were identified likewise, using datasets representing progressively lower sampling frequencies, which were produced by extracting data from the baseline dataset at appropriate time intervals (1-30 days). Overall, 24.3% of segments were "true" hotspots, concentrating 40.4% of roadkills. For different groups, "true" hotspots accounted from 6.8% (bats) to 29.7% (small birds) of road segments, concentrating from <40% (frogs and toads, snakes) to >60% (lizards, lagomorphs, carnivores) of roadkills. Spatial congruence between "true" and "estimated" hotspots declined rapidly with increasing time interval between surveys, due primarily to increasing false negatives (i.e., missing "true" hotspots). There were also false positives (i.e., wrong "estimated" hotspots), particularly at low sampling frequencies. Spatial accuracy decay with increasing time interval between surveys was higher for smaller-bodied (amphibians, reptiles, small birds, small mammals) than for larger-bodied species (birds of prey, hedgehogs, lagomorphs, carnivores). Results suggest that widely used surveys at weekly or longer intervals may produce poor estimates of roadkill hotspots, particularly for small-bodied species. Surveying daily or at two-day intervals may be required to achieve high accuracy in hotspot identification for multiple species.

Phylogeographic triangulation: using predator-prey-parasite interactions to infer population history from partial genetic information.

Phylogeographic studies, which infer population history and dispersal movements from intra-specific spatial genetic variation, require expensive and time-consuming analyses that are not always feasible, especially in the case of rare or endangered species. On the other hand, comparative phylogeography of species involved in close biotic interactions may show congruent patterns depending on the specificity of the relationship. Consequently, the phylogeography of a parasite that needs two hosts to complete its life cycle should reflect population history traits of both hosts. Population movements evidenced by the parasite's phylogeography that are not reflected in the phylogeography of one of these hosts may thus be attributed to the other host. Using the wild rabbit (Oryctolagus cuniculus) and a parasitic tapeworm (Taenia pisiformis) as an example, we propose comparing the phylogeography of easily available organisms such as game species and their specific heteroxenous parasites to infer population movements of definitive host/predator species, independently of performing genetic analyses on the latter. This may be an interesting approach for indirectly studying the history of species whose phylogeography is difficult to analyse directly.

Geographical gradients in Argentinean terrestrial mammal species richness and their environmental correlates.

We analysed the main geographical trends of terrestrial mammal species richness (SR) in Argentina, assessing how broad-scale environmental variation (defined by climatic and topographic variables) and the spatial form of the country (defined by spatial filters based on spatial eigenvector mapping (SEVM)) influence the kinds and the numbers of mammal species along these geographical trends. We also evaluated if there are pure geographical trends not accounted for by the environmental or spatial factors. The environmental variables and spatial filters that simultaneously correlated with the geographical variables and SR were considered potential causes of the geographic trends. We performed partial correlations between SR and the geographical variables, maintaining the selected explanatory variables statistically constant, to determine if SR was fully explained by them or if a significant residual geographic pattern remained. All groups and subgroups presented a latitudinal gradient not attributable to the spatial form of the country. Most of these trends were not explained by climate. We used a variation partitioning procedure to quantify the pure geographic trend (PGT) that remained unaccounted for. The PGT was larger for latitudinal than for longitudinal gradients. This suggests that historical or purely geographical causes may also be relevant drivers of these geographical gradients in mammal diversity.

Applying fuzzy logic to comparative distribution modelling: a case study with two sympatric amphibians.

We modelled the distributions of two toads (Bufo bufo and Epidalea calamita) in the Iberian Peninsula using the favourability function, which makes predictions directly comparable for different species and allows fuzzy logic operations to relate different models. The fuzzy intersection between individual models, representing favourability for the presence of both species simultaneously, was compared with another favourability model built on the presences shared by both species. The fuzzy union between individual models, representing favourability for the presence of any of the two species, was compared with another favourability model based on the presences of either or both of them. The fuzzy intersections between favourability for each species and the complementary of favourability for the other (corresponding to the logical operation "A and not B") were compared with models of exclusive presence of one species versus the exclusive presence of the other. The results of modelling combined species data were highly similar to those of fuzzy logic operations between individual models, proving fuzzy logic and the favourability function valuable for comparative distribution modelling. We highlight several advantages of fuzzy logic over other forms of combining distribution models, including the possibility to combine multiple species models for management and conservation planning.

Use of coarse-resolution models of species' distributions to guide local conservation inferences.

Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter (Lutra lutra), in the Iberian Peninsula. The models, built from presence-absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measures.