Regional climate contributes more than geographic distance to beta diversity of copepods (Crustacea Copepoda) between caves of Italy.

Despite the study of subterranean biodiversity facing harsh sampling and mapping challenges, the huge diversity of taxa, ecological adaptations and evolutionary trajectories in subterranean environments is gaining increasing attention. Yet, the spatial and environmental factors driving the composition of groundwater communities are still poorly understood. To partially fill this knowledge gap, we collected copepod crustaceans from 12 caves along the Italian peninsula between 2019 and 2022, sampling each cave twice. The resulting presence-absence data were analysed to assess: (i) between-cave taxonomic beta diversity, also partitioning between turnover and nestedness-resultant dissimilarity; (ii) the relative weight of geographic distance and climatic differences in shaping observed beta diversity. Seventy-one species of copepods were collected overall. Pairwise beta diversity was high for most pairs of caves, with turnover being the major component. Geographic distance-decay models partially explained total beta diversity and turnover patterns. However, in Generalized Dissimilarity Models (GDM), including surface climatic conditions as predictors, the contribution of seasonal temperature averages was generally higher than that of geographic distance. Further, the explanatory and predictive performance of the GDMs notably increased, along with temperature contribution, when widening the spatial extent from which climate data were gathered. Our results confirmed a high spatial turnover in groundwater copepods' assemblages and strengthened the link between regional climate and subterranean biodiversity.

Some like it hot: Thermal preference of the groundwater amphipod Niphargus longicaudatus (Costa, 1851) and climate change implications.

Groundwater is a crucial resource for humans and the environment, but its global human demand currently exceeds available volumes by 3.5 times. Climate change is expected to exacerbate this situation by increasing the frequency of droughts along with human impacts on groundwater ecosystems. Despite prior research on the quantitative effects of climate change on groundwater, the direct impacts on groundwater biodiversity, especially obligate groundwater species, remain largely unexplored. Therefore, investigating the potential impacts of climate change, including groundwater temperature changes, is crucial for the survival of obligate groundwater species. This study aimed to determine the thermal niche breadth of the crustacean amphipod species Niphargus longicaudatus by using the chronic method. We found that N. longicaudatus has a wide thermal niche with a natural performance range of 7-9 °C, which corresponds to the thermal regime this species experiences within its distribution range in Italy. The observed range of preferred temperature (PT) was different from the mean annual temperature of the sites from which the species has been collected, challenging the idea that groundwater species are only adapted to narrow temperature ranges. Considering the significant threats of climate change to groundwater ecosystems, these findings provide crucial information for the conservation of obligate groundwater species, suggesting that some of them may be more resilient to temperature changes than previously thought. Understanding the fundamental thermal niche of these species can inform conservation efforts and management strategies to protect groundwater ecosystems and their communities.

Assessing future shifts in habitat suitability and connectivity to old-growth forests to support the conservation of the endangered giant noctule.

Background: Suitable climate and availability of habitats for roosting, foraging, and dispersing are critical for the long-term persistence of bat species. The giant noctule (Nyctalus lasiopterus) represents one of the lesser-known European bats, especially regarding the environmental factors which shape its distribution. Methodology: We integrated climate-based ecological niche models with information about topography and rivers' network to model weighted suitability for N. lasiopterus in the western Palearctic. The weighted suitability map was then used to estimate connectivity among the distinct occurrence localities of N. lasiopterus, as well as from these latter towards European old-growth forests, under current conditions and different combinations of future timeframes (2030, 2050, 2070) and shared socioeconomic pathways (SSPs 3.70 and 5.85). Results: Current weighted suitability is highest in Andalusia, northern Iberia, southwestern France, peninsular Italy, coastal Balkans and Anatolia, with dispersed suitable patches elsewhere. A north-eastward shift of weighted suitability emerges in the considered future scenarios, especially under SSP 5.85. The major current ecological corridors for N. lasiopterus are predicted within a 'belt' connecting northern Spain and southwestern France, as well as in the Italian Alps. However, following changes in weighted suitability, connectivity would increase in central-eastern Europe in the future. The bioclimatic niche of the western N. lasiopterus populations does not overlap with those of the central and eastern ones, and it only overlaps with climatic conditions characterizing old-growth forests in western Europe. Conclusions: The outcomes of our analyses would help in designing specific conservation measures for the distinct groups of giant noctule populations, favoring the possibility of range expansion and movement towards forested habitats.

Determination of hair cortisol in horses: comparison of immunoassay vs LC-HRMS/MS.

The measure of hair cortisol concentration (HCC) is becoming an emerging approach to monitor mid-/long-term stress in animals, so it is more and more important to develop accurate and reliable methods. In the light of this, the aim of the present study was to compare mane HCCs of 47 horses with different managements, by means of an immunoassay (ELISA) and liquid chromatography coupled to hybrid high-resolution mass spectrometry (LC-HRMS/MS). After the washing step, the ground hair was extracted with methanol. The extract was evaporated and redissolved in two different aqueous solutions, depending on the detection technique. The methods were validated according to EMA guideline for bioanalytical method validation, in the range 2-50 pg mg-1 (ELISA) and 1-100 pg mg-1 (LC-HRMS/MS). Satisfactory quantitative performances were obtained for both of the approaches, but this latter demonstrated better precision. The detected concentrations in real samples were encompassing the range 1.3-8.8 pg mg-1 and 2.0-17.9 pg mg-1 by means of LC-HRMS/MS and ELISA, respectively. Overall, HCCs measured with ELISA technique were 1.6 times higher. The overestimation of immunoassay results might be caused by cross-reactivity phenomena of laboratory reagents and other structurally similar hormones present in the mane.

Taxonomy, Habitat Preference, and Niche Overlap of Two Arrow-Poison Flea Beetle Species of the Genus Polyclada in Sub-Saharan Africa (Coleoptera, Chrysomelidae).

Coupling the geographic distribution and the ecological requirements of species often supports taxonomy and biogeography. In this contribution, we update the distribution of two flea beetle species of ethno-entomological interest, Polyclada bohemani and P. pectinicornis, by analyzing original data. In addition, we supply their main morphological diagnostic characters, describing their aedeagal and spermathecal shapes for the first time. We also assess their niche differences in terms of climatic and vegetation needs, by means of ecological niche modelling and remote sensing techniques. Several new localities were identified to improve knowledge of the geographical distribution of both species. Moreover, we located a wide climatic suitability overlap in East Africa for these two flea beetle species, while in other areas they show a clear separation. Our analysis also reports that P. bohemani is associated with areas of denser tree cover than P. pectinicornis. Finally, the lectotypes of Diamphidia bohemani Baly, 1861, Clytra pectinicornis Olivier, 1791, and Diamphidia compacta Fairmaire, 1887 are here designated and the new synonymy Clytra pectinicornis Olivier = Diamphidia compacta Fairmaire syn.nov. is proposed.

Assessment of Welfare in Groups of Horses with Different Management, Environments and Activities by Measuring Cortisol in Horsehair, Using Liquid Chromatography Coupled to Hybrid Orbitrap High-Resolution Mass Spectrometry.

Horses have always been animals used for companionship, work, transportation, and performance purposes over the history of humanity; there are different ways of managing horses, but studies on how horse welfare is influenced by different activities and managements are scanty. Understanding how the management, the environment, and the different uses of horses can affect the level of stress and well-being is important not only for people associated with horses. Three groups of horses with different management, environments, and activities were selected: (1) stabled horses ridden frequently, (2) horses that perform public order service under the Italian state police, and (3) free-ranging horses. Cortisol analysis was carried out on horsehair samples using liquid chromatography coupled to hybrid orbitrap high-resolution mass spectrometry (LC-HRMS/MS), a laboratory technique used for the first time to quantify horsehair cortisol. The selection of horses to be included in the three groups was carried out by including only subjects with positive welfare assessment in accordance with the horse welfare assessment protocol (AWIN). These analyses demonstrated that the cortisol levels detected in the horsehair of free-ranging animals were significantly higher compared to those detected in stabled and working horses. These results may have been a consequence of complex environmental, managerial, and behavioral factors, which should be worth further investigation.

Worldclim 2.1 versus Worldclim 1.4: Climatic niche and grid resolution affect between-version mismatches in Habitat Suitability Models predictions across Europe.

The influence of climate on the distribution of taxa has been extensively investigated in the last two decades through Habitat Suitability Models (HSMs). In this context, the Worldclim database represents an invaluable data source as it provides worldwide climate surfaces for both historical and future time horizons. Thousands of HSMs-based papers have been published taking advantage of Worldclim 1.4, the first online version of this repository. In 2017, Worldclim 2.1 was released. Here, we evaluated spatially explicit prediction mismatch at continental scale, focusing on Europe, between HSMs fitted using climate surfaces from the two Worldclim versions (between-version differences). To this aim, we simulated occurrence probability and presence-absence across Europe of four virtual species (VS) with differing climate-occurrence relationships. For each VS, we fitted HSMs upon uncorrelated bioclimatic variables derived from each Worldclim version at three grid resolutions. For each factor combination, HSMs attaining sufficient discrimination performance on spatially independent test data were projected across Europe under current conditions and various future scenarios, and importance scores of the single variables were computed. HSMs failed in accurately retrieving the simulated climate-occurrence relationships for the climate-tolerant VS and the one occurring under a narrow combination of climatic conditions. Under current climate, noticeable between-version prediction mismatch emerged across most of Europe for these two VSs, whose simulated suitability mainly depended upon diurnal or yearly variability in temperature; differently, between-version differences were more clustered toward areas showing extreme values, like mountainous massifs or southern regions, for VSs responding to average temperature and precipitation trends. Under future climate, the chosen emission scenarios and Global Climate Models did not evidently influence between-version prediction discrepancies, while grid resolution synergistically interacted with VSs' niche characteristics in determining extent of such differences. Our findings could help in re-evaluating previous biodiversity-related works relying on geographical predictions from Worldclim-based HSMs.

Determinants of habitat suitability models transferability across geographically disjunct populations: Insights from Vipera ursinii urs inii.

Transferability of habitat suitability models (HSMs), essential to accurately predict outside calibration conditions, has been seldom investigated at intraspecific level. We targeted Vipera ursinii ursinii, a meadow viper from southeastern France and central Italy, to assess determinants of transferability among geographically disjunct populations. We fitted HSMs upon occurrences of the Italian and French populations separately, as well as on the combined occurrence dataset. Internal transferability of HSMs, on spatially independent test data drawn from the calibration region, and their external transferability on the geographically disjunct populations were evaluated according to (a) use of full or spatially rarefied presence datasets; (b) ecology-driven or statistics-driven filtering of predictors; (c) modeling algorithm, testing generalized additive models and gradient boosting models; and (d) multivariate environmental novelty within test data. Niche overlap between French and Italian populations was also tested. Niche overlap was low, but niche divergence between the two populations' clusters was not corroborated. Nonetheless, wider niche breadth and heterogeneity of background environmental conditions characterizing the French populations led to low intercluster transferability. Although models fitted on the combined datasets did not attain consistently higher internal transferability than those separately fitted for the French and Italian populations, ensemble projection from the HSMs fitted on the joint occurrences produced more consistent suitability predictions across the full range of V. u. ursinii. Spatial thinning of occurrences ameliorated internal transferability but did not affect external transferability. The two approaches to predictors filtering did not differ in transferability of the respective HSMs but led to discrepant estimated environment-occurrence relationships and spatial predictions, while the two algorithms attained different relative rankings depending on the considered prediction task. Multivariate novelty of projection sites was negatively correlated to both internal transferability and external transferability. Our findings clarify issues researchers should keep in mind when using HSMs to get predictions across geographically disjunct populations.

Coupling GIS spatial analysis and Ensemble Niche Modelling to investigate climate change-related threats to the Sicilian pond turtle Emys trinacris, an endangered species from the Mediterranean.

The pond turtle Emys trinacris is an endangered endemic species of Sicily showing a fragmented distribution throughout the main island. In this study, we applied "Ensemble Niche Modelling", combining more classical statistical techniques as Generalized Linear Models and Multivariate Adaptive Regression Splines with machine-learning approaches as Boosted Regression Trees and Maxent, to model the potential distribution of the species under current and future climatic conditions. Moreover, a "gap analysis" performed on both the species' presence sites and the predictions from the Ensemble Models is proposed to integrate outputs from these models, in order to assess the conservation status of this threatened species in the context of biodiversity management. For this aim, four "Representative Concentration Pathways", corresponding to different greenhouse gases emissions trajectories were considered to project the obtained models to both 2050 and 2070. Areas lost, gained or remaining stable for the target species in the projected models were calculated. E. trinacris' potential distribution resulted to be significantly dependent upon precipitation-linked variables, mainly precipitation of wettest and coldest quarter. Future negative effects for the conservation of this species, because of more unstable precipitation patterns and extreme meteorological events, emerged from our analyses. Further, the sites currently inhabited by E. trinacris are, for more than a half, out of the Protected Areas network, highlighting an inadequate management of the species by the authorities responsible for its protection. Our results, therefore, suggest that in the next future the Sicilian pond turtle will need the utmost attention by the scientific community to avoid the imminent risk of extinction. Finally, the gap analysis performed in GIS environment resulted to be a very informative post-modeling technique, potentially applicable to the management of species at risk and to Protected Areas' planning in many contexts.

Unraveling climate influences on the distribution of the parapatric newts Lissotriton vulgaris meridionalis and L. italicus.

BACKGROUND: Climate is often considered as a key ecological factor limiting the capability of expansion of most species and the extent of suitable habitats. In this contribution, we implement Species Distribution Models (SDMs) to study two parapatric amphibians, Lissotriton vulgaris meridionalis and L. italicus, investigating if and how climate has influenced their present and past (Last Glacial Maximum and Holocene) distributions. A database of 901 GPS presence records was generated for the two newts. SDMs were built through Boosted Regression Trees and Maxent, using the Worldclim bioclimatic variables as predictors. RESULTS: Precipitation-linked variables and the temperature annual range strongly influence the current occurrence patterns of the two Lissotriton species analyzed. The two newts show opposite responses to the most contributing variables, such as BIO7 (temperature annual range), BIO12 (annual precipitation), BIO17 (precipitation of the driest quarter) and BIO19 (precipitation of the coldest quarter). The hypothesis of climate influencing the distributions of these species is also supported by the fact that the co-occurrences within the sympatric area fall in localities characterized by intermediate values of these predictors. Projections to the Last Glacial Maximum and Holocene scenarios provided a coherent representation of climate influences on the past distributions of the target species. Computation of pairwise variables interactions and the discriminant analysis allowed a deeper interpretation of SDMs' outputs. Further, we propose a multivariate environmental dissimilarity index (MEDI), derived through a transformation of the multivariate environmental similarity surface (MESS), to deal with extrapolation-linked uncertainties in model projections to past climate. Finally, the niche equivalency and niche similarity tests confirmed the link between SDMs outputs and actual differences in the ecological niches of the two species. CONCLUSIONS: The different responses of the two species to climatic factors have significantly contributed to shape their current distribution, through contractions, expansions and shifts over time, allowing to maintain two wide allopatric areas with an area of sympatry in Central Italy. Moreover, our SDMs hindcasting shows many concordances with previous phylogeographic studies carried out on the same species, thus corroborating the scenarios of potential distribution during the Last Glacial Maximum and the Holocene emerging from the models obtained.

Comparing pseudo-absences generation techniques in Boosted Regression Trees models for conservation purposes: A case study on amphibians in a protected area.

Boosted Regression Trees (BRT) is one of the modelling techniques most recently applied to biodiversity conservation and it can be implemented with presence-only data through the generation of artificial absences (pseudo-absences). In this paper, three pseudo-absences generation techniques are compared, namely the generation of pseudo-absences within target-group background (TGB), testing both the weighted (WTGB) and unweighted (UTGB) scheme, and the generation at random (RDM), evaluating their performance and applicability in distribution modelling and species conservation. The choice of the target group fell on amphibians, because of their rapid decline worldwide and the frequent lack of guidelines for conservation strategies and regional-scale planning, which instead could be provided through an appropriate implementation of SDMs. Bufo bufo, Salamandrina perspicillata and Triturus carnifex were considered as target species, in order to perform our analysis with species having different ecological and distributional characteristics. The study area is the "Gran Sasso-Monti della Laga" National Park, which hosts 15 Natura 2000 sites and represents one of the most important biodiversity hotspots in Europe. Our results show that the model calibration ameliorates when using the target-group based pseudo-absences compared to the random ones, especially when applying the WTGB. Contrarily, model discrimination did not significantly vary in a consistent way among the three approaches with respect to the tree target species. Both WTGB and RDM clearly isolate the highly contributing variables, supplying many relevant indications for species conservation actions. Moreover, the assessment of pairwise variable interactions and their three-dimensional visualization further increase the amount of useful information for protected areas' managers. Finally, we suggest the use of RDM as an admissible alternative when it is not possible to individuate a suitable set of species as a representative target-group from which the pseudo-absences can be generated.