Painting maps with bats: Species distribution modelling in bat research and conservation

Species distribution models (SDMs) offer an effective tool for identifying species conservation requirements and forecasting how global environmental changes will affect species diversity and distribution. This approach is particularly relevant for bats because their nocturnal behaviour hinders detectability and identification in flight. Despite their important contribution to global biodiversity and wide geographical ranges, bats have been under-represented in early SDM studies, and only in the last few years has this approach become more widely used in bat research. We carried out a meta-analysis of the published literature to review the history of the use of SDMs in bat research and their application in conservation, climate change assessments and genetic studies. We focus on the geographical coverage, theme and modelling algorithm of published studies, and compare studies that are uniquely dedicated to bats to multi-taxa studies that include bats. We provide recommendations for good modelling practices through considering spatial scale and spatial biases, selecting ecologically relevant variables, following rigorous modelling protocols, and recognising the limitations of extrapolation across temporal scales. We suggest future developments that will further favour the use of SDMs to study bat ecology and biogeography, as well as inform conservation management. We conclude that despite an increase in bat SDM studies, their scope and application can be further enhanced through incorporating dispersal, landscape connectivity and biotic interactions between bats, their prey and their pathogens

how many hippopotamid species roamed Sicily? The case study of Amoroso Cave

Funding Information: R.M. is funded by the Fundação para a Ciência e a Tecnologia (FCT) (2021.08458.BD, https://doi.org/10.54499/2021), an Erasmus + grant [29191(532)105/2022/SMT], and SYNTHESYS + [DE-TAF-TA4-063 2022]. This research was also supported by the FCT, I.P through the Research Unit UIDB/04035/2020 (Geobiotec, DOI: 10.54499/UIDB/04035/2020). This work is part of the project P2022RZ4PL funded by the European Union—Next Generation EU, call PRIN 2022 PNRR (granted to L.P.). M.R. thanks the Stimulus of Scientific Employment, Individual Support – 2018 Call grant by the Fundação para a Ciência e a Tecnologia (Portugal, CEECIND/02199/2018) and GeoBioTec. Publisher Copyright: © 2025 The Linnean Society of London.Hippopotamus pentlandi, although lacking a comprehensive description, is regarded as one of the best known dwarfed hippopotamid species within the Mediterranean region. This study provides a detailed analysis of a hippopotamus mandible from Amoroso Cave (Palermo, Sicily). Morphological and morphometric comparisons with insular and continental species reveal a significant similarity between the Amoroso mandible and some specimens from San Ciro Cave (Palermo, Sicily), as well as with Hippopotamus amphibius. Conversely, material from Cannita Cave (Palermo, Sicily) attributed to H. pentlandi is less robust, more elongated and smaller. 3D geometric morphometric analysis performed on the symphyseal sagittal cross-section further support a closer morphological affinity of the Amoroso mandible to San Ciro Cave specimens and H. amphibius, suggesting an attribution to the latter. Our research reveals the presence of at least two different, potentially coeval, taxa in the Pleistocene of Sicily: the dwarfed Hippopotamus pentlandi primarily known from Cannita Cave, and H. amphibius. While Cannita Cave material has been thoroughly studied over the years, abundant remains from other localities, e.g. San Ciro Cave, require re-evaluation. A thorough analysis of Sicilian hippopotamids is crucial to improve our understanding of their systematics and to provide new insights into the palaeobiogeography, palaeobiology, and palaeoenvironment of Sicily during the Pleistocene.publishersversionpublishe

Too much of a good thing? Supplementing current species observations with fossil data to assess climate change vulnerability via ecological niche models

Ecological niche models (ENMs) are a powerful tool in ecological research and conservation planning. Since ENMs provide probability maps of suitable areas under environmental change, they may assist in designing conservation actions and addressing conservation priorities. However, ENMs are usually implemented by learning the species climatic preferences from their current geographic distribution, which leaves them vulnerable to the issue of niche truncation, as it comes with non-climatic limits to the current species distribution as posed by anthropic activities and settlements, and competition avoidance. These problems might be alleviated by the inclusion of fossil occurrences, which refer to moments during species existence when such limits were absent or distributed differently. By stacking species occurrences from different time moments is conceivable that a larger fraction of the species fundamental niche is thence explored. Here, we combined current and fossil occurrence data for 38 medium-large mammal species of conservation concern in order to assess the influence of the fossil record inclusion on ENM predictions under future climate change scenarios. We found that ignoring or including fossil data yields consistent trends in terms of predicted range increase/decrease. Yet, although adding fossil data invariably results in increased niche width, estimates of range change improved for almost a half only of the species pool. These results suggest that most species might currently be in non-equilibrium with their environment, and that the inclusion of fossil data may be crucial to the better understanding of species climatic requirements, hence for designing more effective conservation strategies

Potential distribution of Xylella fastidiosa in Italy: a maximum entropy model

Species distribution models may provide realistic scenarios to explain the influence of bioclimatic variables in the context of emerging plant pathogens. Xylella fastidiosa is a xylem-limited Gram-negative bacterium causing severe diseases in many plant species. We developed a maximum entropy model for X. fastidiosa in Italy. Our objectives were to carry out a preliminary analysis of the species’ potential geographical distribution and determine which eco-geographical variables may favour its presence in other Italian regions besides Apulia. The analysis of single variable contribution showed that precipitation of the driest (40.3%) and wettest (30.4%) months were the main factors influencing model performance. Altitude, precipitation of warmest quarter, mean temperature of coldest quarter, and land cover provided a total contribution of 19.5%. Based on the model predictions, X. fastidiosa has a high probability (> 0.8) of colonizing areas characterized by: i) low altitude (0–150 m a.s.l.); ii) precipitations in the driest month < 10 mm, in the wettest month ranging between 80–110 mm and during the warmest quarter < 60 mm; iii) mean temperature of coldest quarter ≥ 8°C; iv) agricultural areas comprising intensive agriculture, complex cultivation patterns, olive groves, annual crops associated with permanent crops, orchards and vineyards; forest (essentially oak woodland); and Mediterranean shrubland. Species distribution models showed a high probability of X. fastidiosa occurrence in the regions of Apulia, Calabria, Basilicata, Sicily, Sardinia and coastal areas of Campania, Lazio and south Tuscany. Maxent models achieved excellent levels of predictive performance according to area under curve (AUC), true skill statistic (TSS) and minimum difference between training and testing AUC data (AUCdiff). Our study indicated that X. fastidiosa has the potential to overcome the current boundaries of distribution and affect areas of Italy outside Apulia

Testing for changes in rate of evolution and position of the climatic niche of clades

1. There is solid recognition that phylogenetic effects must be acknowledged to appreciate climatic niche variability among species clades properly. Yet, most currently available methods either work at the intra- specific level (hence they ignore phylogeny) or rely on the Brownian motion model of evolution to estimate phylogenetic effects on climatic niche variation. The Brownian mo-tion model may be inappropriate to describe niche evolution in several cases, and even a significant phylogenetic signal in climatic variables does not in-dicate that the effect of shared ancestry was relevant to niche evolution.2. We introduce a new phylogenetic comparative method which describes sig-nificant changes in the width and position of the climatic niche at the inter-specific (clade) level, while making no a priori assumption about how niche evolution took place.3. We devised the R function phylo.niche.shift to estimate whether the climatic niches of individual clades in the tree are either wider or narrower than expected, and whether the niche occupies unexpected climates. We tested phylo.niche.shift on realistic virtual species’ distribution patterns applied to a phylogeny of 365 extant primate species.4. We demonstrate via simulations that the new method is fast and accurate under widely different climatic niche evolution scenarios. phylo.niche.shift showed that the capuchin monkeys and langurs occupy much wider, and prosimian much narrower, climatic niche space than expected by their phylogenetic positions.5. phylo.niche.shift may help to improve research on niche evolution by allow-ing researchers to test specific hypotheses on the factors affecting clades’ realised niche width and position, and the potential effects of climate change on species’ distribution

Modelling reveals the effect of climate and land use change on Madagascar’s chameleons fauna

The global biodiversity crisis is generated by the combined effects of human-induced climate change and land conversion. Madagascar is one of the World’s most renewed hotspots of biodiversity. Yet, its rich variety of plant and animal species is threatened by deforestation and climate change. Predicting the future of Madagascar’s chameleons, in particular, is complicated by their ecological rarity, making it hard to tell which factor is the most menacing to their survival. By applying an extension of the ENphylo species distribution model algorithm to work with extremely rare species, we find that Madagascar chameleons will face intense species loss in the north-western sector of the island. Land conversion by humans will drive most of the loss, and will intersect in a complex, nonlinear manner with climate change. We find that some 30% of the Madagascar’s chameleons may lose in the future nearly all their habitats, critically jeopardizing their chance for survival

RRphylogeography: A new method to find the area of origin of species and the history of past contacts between species

Abstract One of the main goals of historical biogeography is understanding where species originated, and how climate change and ecological interactions shaped their distribution. The task is complicated by both active and passive mechanisms, including habitat tracking, the separation of species into metapopulations of variably interconnected demes, and long-distance dispersal, which may all obscure the geographic signature of species origin. Current historical biogeography tools use phylogenies to infer the area of origin (AOO). They work by discretizing the geographic range occupied by the species into distinct areas and then applying ancestral character estimation to identify the area occupied at speciation. These methods are powerful and can account for different modes of speciation. Yet, they are bound to assume that the discrete areas currently occupied by the species are faithful representation of their climatic and historic affiliation and ignore metapopulation structures. Still, most methods cannot take advantage of fossil information or work with phylogenies including extinct species. Although explicit bioclimatic modelling is now possible under some implementations, these limitations are partly unresolved, which burdens the accuracy of the AOO estimation process. We present a new tool written in R, named RRphylogeography, meant to find the AOO of species, and to locate feasible zones of contact between species throughout their history. RRphylogeography starts from the bioclimatic modelling of the species, identifies potential habitat patches occupied during speciation and finds the habitat patches most likely to represent the AOO or contact. By using virtual species simulations, we compared RRphylogeography to common historical biogeography tools. We found RRphylogeography statistically outcompetes these alternatives under all study conditions, reaching especially accurate predictions. We additionally used RRphylogeography to investigate the complex phylogeographic history of the polar bear Ursus maritimus. The method placed the origin of the species in Northern Beringia. Intriguingly, it further shows possible contact zones between polar and brown bear in northwestern Europe during the late Pleistocene and in Beringia during the Pleistocene to Holocene transition, which is in perfect agreement with the known hybridization history between the two species

A new, fast method to search for morphological convergence with shape data

Morphological convergence is an intensely studied macroevolutionary phenomenon. It refers to the morphological resemblance between phylogenetically distant taxa. Currently available methods to explore evolutionary convergence either: rely on the analysis of the phenotypic resemblance between sister clades as compared to their ancestor, fit different evolutionary regimes to different parts of the tree to see whether the same regime explains phenotypic evolution in phylogenetically distant clades, or assess deviations from the congruence between phylogenetic and phenotypic distances. We introduce a new test for morphological convergence working directly with non-ultrametric (i.e. paleontological) as well as ultrametric phylogenies and multivariate data. The method (developed as the function search.conv within the R package RRphylo) tests whether unrelated clades are morphologically more similar to each other than expected by their phylogenetic distance. It additionally permits using known phenotypes as the most recent common ancestors of clades, taking full advantage of fossil information. We assessed the power of search.conv and the incidence of false positives by means of simulations, and then applied it to three well-known and long-discussed cases of (purported) morphological convergence: the evolution of grazing adaptation in the mandible of ungulates with high-crowned molars, the evolution of mandibular shape in sabertooth cats, and the evolution of discrete ecomorphs among anoles of Caribbean islands. The search.conv method was found to be powerful, correctly identifying simulated cases of convergent morphological evolution in 95% of the cases. Type I error rate is as low as 4-6%. We found search.conv is some three orders of magnitude faster than a competing method for testing convergence