Intraspecific variation in metabolic responses to diverse environmental conditions in the Malagasy bat Triaenops menamena

Widespread species often display traits of generalists, yet local adaptations may limit their ability to cope with diverse environmental conditions. With climate change being a pressing issue, distinguishing between the general ecological and physiological capacities of a species and those of individual populations is vital for assessing the capability to adapt rapidly to changing habitats. Despite its importance, physiological variation across broad range distributions, particularly among free-ranging bats in natural environments, has rarely been assessed. Studies focusing on physiological variation among different populations across seasons are even more limited. We investigated physiological variation in the Malagasy Trident Bat Triaenops menamena across three different roost types in Madagascar during the wet and dry season, examining aspects such as energy regimes, body temperature, and roost microclimates. We focused on patterns of torpor in relation to roosting conditions. We hypothesized that torpor occurrence would be higher during the colder, more demanding dry season. We predicted that populations roosting in more variable microclimates would expend less energy than those in mores stable ones due to more frequent use of torpor and greater metabolic rate reductions. Our findings highlight complex thermoregulatory strategies, with varying torpor expression across seasons and roosts. We observed an overall higher energy expenditure during the wet season but also greater energy savings during torpor in that season, regardless of roost type. We found that reductions in metabolic rate were positively correlated with greater fluctuations in ambient conditions, demonstrating these bats' adaptability to dynamic environments. Notably, we observed diverse torpor patterns, indicating the species' ability to use prolonged torpor under extreme conditions. This individual-level variation is crucial for adaptation to changing environmental conditions. Moreover, the flexibility in body temperature during torpor suggests caution in relying solely on it as an indicator for torpor use. Our study emphasizes the necessity to investigate thermoregulatory responses across different populations in their respective habitats to fully understand a species' adaptive potential.

Testing spatial transferability of species distribution models reveals differing habitat preferences for an endangered delphinid (Cephalorhynchus hectori) in Aotearoa, New Zealand

Species distribution models (SDMs) can be used to predict distributions in novel times or space (termed transferability) and fill knowledge gaps for areas that are data poor. In conservation, this can be used to determine the extent of spatial protection required. To understand how well a model transfers spatially, it needs to be independently tested, using data from novel habitats. Here, we test the transferability of SDMs for Hector's dolphin (Cephalorhynchus hectori), a culturally important (taonga) and endangered, coastal delphinid, endemic to Aotearoa New Zealand. We collected summer distribution data from three populations from 2021 to 2023. Using Generalised Additive Models, we built presence/absence SDMs for each population and validated the predictive ability of the top models (with TSS and AUC). Then, we tested the transferability of each top model by predicting the distribution of the remaining two populations. SDMs for two populations showed useful performance within their respective areas (Banks Peninsula and Otago), but when used to predict the two areas outside the models' source data, performance declined markedly. SDMs from the third area (Timaru) performed poorly, both for prediction within the source area and when transferred spatially. When data for model building were combined from two areas, results were mixed. Model interpolation was better when presence/absence data from Otago, an area of low density, were combined with data from areas of higher density, but was otherwise poor. The overall poor transferability of SDMs suggests that habitat preferences of Hector's dolphins vary between areas. For these dolphins, population-specific distribution data should be used for conservation planning. More generally, we demonstrate that a one model fits all approach is not always suitable. When SDMs are used to predict distribution in data-poor areas an assessment of performance in the new habitat is required, and results should be interpreted with caution.

Spatio-temporal shifts in British wild bees in response to changing climate

Climate plays a major role in determining where species occur, and when they are active throughout the year. In the face of a changing climate, many species are shifting their ranges poleward. Many species are also shifting their emergence phenology. Wild bees in Great Britain are susceptible to changes in climatic conditions but little is known about historic or potential future spatio-temporal trends of many species. This study utilized a sliding window approach to assess the impacts of climate on bee emergence dates, estimating the best temperature window for predicting emergence dates for 88 species of wild bees. Using a 'middle-of-the-road' (RCP 4.5) and 'worst-case' (RCP 8.5) climate scenario for the period 2070-2079, predictions of future emergence dates were made. In general, the best predicting climate window occurred in the 0-3 months preceding emergence. Across the 40 species that showed a shift in emergence dates in response to a climate window, the mean advance was 13.4 days under RCP 4.5 and 24.9 days under RCP 8.5. Species distribution models (SDMs) were used to predict suitable climate envelopes under historic (1980-1989), current (2010-2019) and future (2070-2079 under RCP 4.5 and RCP 8.5 scenarios) climate conditions. These models predict that the climate envelope for 92% of studied species has increased since the 1980s, and for 97% and 93% of species under RCP 4.5 and RCP 8.5 respectively, this is predicted to continue, due to extension of the northern range boundary. While any range changes will be moderated by habitat availability, it highlights that Great Britain will likely experience northward shifts of bee populations in the future. By combining spatial and temporal trends, this work provides an important step towards informing conservation measures suitable for future climates, directing how interventions can be provided in the right place at the right time.

A quixotic view of spatial bias in modelling the distribution of species and their diversity

Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling.

The establishment of ecological conservation for herpetofauna species in hotspot areas of South Korea

Understanding the geographic distribution of species is crucial for establishing protected areas. This study aimed to identify the preferred habitat environment of South Korean herpetofauna using distribution point information, providing the information necessary to protect their habitat by establishing a species distribution model. We found that climate variables in the region where 19 amphibians and 20 reptiles were distributed correlated with the altitude, suggesting that altitude had a major influence on their distribution. The species distribution modeling indicated that 10–12 amphibian and 13–16 reptile species inhabit the Gangwon-do region, forming hotspot areas in the eastern and western regions around the Taebaek Mountains. Some of these hotspot areas occurred in the Demilitarized Zone and national parks, which are government-managed ecological conservation areas. However, some hotspot areas are vulnerable to habitat destruction due to development and deforestation as they are not designated conservation areas. Therefore, it is necessary to establish new conservation areas with a focus on herpetofauna after confirming the actual inhabitation of species through precise monitoring in predicted hotspot areas and designating them as protected areas. Our results can serve as important basic data for establishing protection measures and designating protected areas for herpetofauna species.

The impact of climate change on the distribution of rare and endangered tree Firmiana kwangsiensis using the Maxent modeling

The upsurge in anthropogenic climate change has accelerated the habitat loss and fragmentation of wild animals and plants. The rare and endangered plants are important biodiversity elements. However, the lack of comprehensive and reliable information on the spatial distribution of these organisms has hampered holistic and efficient conservation management measures. We explored the consequences of climate change on the geographical distribution of Firmiana kwangsiensis (Malvaceae), an endangered species, to provide a reference for conservation, introduction, and cultivation of this species in new ecological zones. Modeling of the potential distribution of F. kwangsiensis under the current and two future climate scenarios in maximum entropy was performed based on 30 occurrence records and 27 environmental variables of the plant. We found that precipitation-associated and temperature-associated variables limited the potentially suitable habitats for F. kwangsiensis. Our model predicted 259,504 km2 of F. kwangsiensis habitat based on 25 percentile thresholds. However, the high suitable habitat for F. kwangsiensis is only about 41,027 km2. F. kwangsiensis is most distributed in Guangxi's protected areas. However, the existing reserves are only 2.7% of the total suitable habitat and 4.2% of the high suitable habitat for the plant, lower than the average protection area in Guangxi (7.2%). This means the current protected areas network is insufficient, underlining the need for alternative conservation mechanisms to protect the plant habitat. Our findings will help identify additional F. kwangsiensis localities and potential habitats and inform the development and implementation of conservation, management, and cultivation practices of such rare tree species.