Climate change could fuel urinary schistosomiasis transmission in Africa and Europe.

The freshwater snail Bulinus truncatus is an important intermediate host for trematode parasites causing urogenital schistosomiasis, a tropical disease affecting over 150 million people. Despite its medical importance, uncertainty remains about its global distribution and the potential impacts of climate change on its future spread. Here, we investigate the distribution of B. truncatus, combining the outputs of correlative and mechanistic modelling methods to fully capitalize on both experimental and occurrence data of the species and to create a more reliable distribution forecast than ever constructed. We constructed ensemble correlative species distribution models using 273 occurrence points collected from different sources and a combination of climatic and (bio)physical environmental variables. Additionally, a mechanistic thermal suitability model was constructed, parameterized by recent life-history data obtained through extensive lab-based snail-temperature experiments and supplemented with an extensive literature review. Our findings reveal that the current suitable habitat for B. truncatus encompasses the Sahel region, the Middle East, and the Mediterranean segment of Africa, stretching from Southern Europe to Mozambique. Regions identified as suitable by both methods generally coincide with areas exhibiting high urogenital schistosomiasis prevalence. Model projections into the future suggest an overall net increase in suitable area of up to 17%. New suitable habitat is in Southern Europe, the Middle East, and large parts of Central Africa, while suitable habitat will be lost in the Sahel region. The change in snail habitat suitability may substantially increase the risk of urogenital schistosomiasis transmission in parts of Africa and Southern Europe while reducing it in the Sahel region.

Climate correlates of bluetongue incidence in southern Portugal.

Model forecasts of the spatiotemporal occurrence dynamics of diseases are necessary and can help understand and thus manage future disease outbreaks. In our study, we used ecological niche modelling to assess the impact of climate on the vector suitability for bluetongue disease, a disease affecting livestock production with important economic consequences. Specifically, we investigated the relationship between the occurrence of bluetongue outbreaks and the environmental suitability of each of the four vector species studied. We found that the main vector for bluetongue disease, Culicoides imicola, a typically tropical and subtropical species, was a strong predictor for disease outbreak occurrence in a region of southern Portugal from 2004 to 2021. The results highlight the importance of understanding the climatic factors that might influence vector presence to help manage infectious disease impacts. When diseases impact economically relevant species, the impacts go beyond mortality and have important economic consequences.

An Assessment of the Climate Change Impacts on the Distribution of the Glacial Relict Woodpecker Three-Toed Woodpecker Picoides tridactylus.

The Three-Toed Woodpecker Picoides tridactylus is a rare and endangered woodpecker on the Balkan Peninsula. Despite being widely distributed in Northern Europe, its distribution on the Balkan Peninsula is limited to high-altitude forest habitats, where it represents a glacial relict. Assessing the climate change impacts on its distribution can be crucial for improving the conservation and future survival of this specialist species on the Balkan Peninsula. We used species distribution modelling (SDM) to identify its potential distribution in the past (last interglacial and last glacial maximum), present, and future (2050 and 2070). Our results indicate that this species had the greatest distribution during the last glacial maximum, after which its distribution contracted to areas where suitable environment persisted (high altitudes). The largest territory of the Balkan Peninsula has an unsuitable environment for the species to inhabit, while highly suitable habitats have the smallest share in the total area of suitable habitats. All future models show a decrease in the area of suitable habitats compared with the current period, indicating that global warming has a negative effect on the distribution of the species. We recommend that conservation activities must be of greater extent to ensure the species' survival in the Balkans.

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.

Distribution Model Reveals Rapid Decline in Habitat Extent for Endangered Hispid Hare: Implications for Wildlife Management and Conservation Planning in Future Climate Change Scenarios.

The hispid hare, Caprolagus hispidus, belonging to the family Leporidae is a small grassland mammal found in the southern foothills of the Himalayas, in India, Nepal, and Bhutan. Despite having an endangered status according to the IUCN Red List, it lacks studies on its distribution and is threatened by habitat loss and land cover changes. Thus, the present study attempted to assess the habitat suitability using the species distribution model approach for the first time and projected its future in response to climate change, habitat, and urbanization factors. The results revealed that out of the total geographical extent of 188,316 km2, only 11,374 km2 (6.03%) were identified as suitable habitat for this species. The results also revealed that habitat significantly declined across its range (>60%) under certain climate change scenarios. Moreover, in the present climate scenario protected areas such as Shuklaphanta National Park (0.837) in Nepal exhibited the highest mean extent of habitat whereas, in India, Dibru-Saikhowa National Park (0.631) is found to be the most suitable habitat. Notably, two protected areas in Uttarakhand, India, specifically Corbett National Park (0.530) and Sonanandi Wildlife Sanctuary (0.423), have also demonstrated suitable habitats for C. hispidus. Given that protected areas showing a future rise in habitat suitability might also be regarded as potential sites for species translocation, this study underscores the importance of implementing proactive conservation strategies to mitigate the adverse impacts of climate change on this species. It is essential to prioritize habitat restoration, focused protection measures, and further species-level ecological exploration to address these challenges effectively. Furthermore, fostering transboundary collaboration and coordinated conservation actions between nations is crucial to safeguarding the long-term survival of the species throughout its distribution range.

Tracing histoplasmosis genomic epidemiology and species occurrence across the USA.

ABSTRACTHistoplasmosis is an endemic mycosis in North America frequently reported along the Ohio and Mississippi River Valleys, although autochthonous cases occur in non-endemic areas. In the United States, the disease is provoked by two genetically distinct clades of Histoplasma capsulatum sensu lato, Histoplasma mississippiense (Nam1) and H. ohiense (Nam2). To bridge the molecular epidemiological gap, we genotyped 93 Histoplasma isolates (62 novel genomes) including clinical, environmental, and veterinarian samples from a broader geographical range by whole-genome sequencing, followed by evolutionary and species niche modelling analyses. We show that histoplasmosis is caused by two major lineages, H. ohiense and H. mississippiense; with sporadic cases caused by H. suramericanum in California and Texas. While H. ohiense is prevalent in eastern states, H. mississipiense was found to be prevalent in the central and western portions of the United States, but also geographically overlapping in some areas suggesting that these species might co-occur. Species Niche Modelling revealed that H. ohiense thrives in places with warmer and drier conditions, while H. mississippiense is endemic to areas with cooler temperatures and more precipitation. In addition, we predicted multiple areas of secondary contact zones where the two species co-occur, potentially facilitating gene exchange and hybridization. This study provides the most comprehensive understanding of the genomic epidemiology of histoplasmosis in the USA and lays a blueprint for the study of invasive fungal diseases.

Predicting the responses of European grassland communities to climate and land cover change.

European grasslands are among the most species-rich ecosystems on small spatial scales. However, human-induced activities like land use and climate change pose significant threats to this diversity. To explore how climate and land cover change will affect biodiversity and community composition in grassland ecosystems, we conducted joint species distribution models (SDMs) on the extensive vegetation-plot database sPlotOpen to project distributions of 1178 grassland species across Europe under current conditions and three future scenarios. We further compared model accuracy and computational efficiency between joint SDMs (JSDMs) and stacked SDMs, especially for rare species. Our results show that: (i) grassland communities in the mountain ranges are expected to suffer high rates of species loss, while those in western, northern and eastern Europe will experience substantial turnover; (ii) scaling anomalies were observed in the predicted species richness, reflecting regional differences in the dominant drivers of assembly processes; (iii) JSDMs did not outperform stacked SDMs in predictive power but demonstrated superior efficiency in model fitting and predicting; and (iv) incorporating co-occurrence datasets improved the model performance in predicting the distribution of rare species. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Establishing the distribution of Carpophilus truncatus in Australia using an integrative approach for an emerging global pest.

The nitidulid beetle Carpophilus truncatus is rapidly becoming a major pest of nut crops around the world. This insect first infested Australian almonds in 2013 and has since escalated to be the preeminent insect pest for the industry. Data pertaining to C. truncatus distribution are scant, but without awareness of its origin, distribution, and ecological factors that influence distribution, efforts to understand and manage the insect as a pest are stymied. Here, we employ an integrative approach to gain a multifaceted understanding of the distribution of C. truncatus in Australia. Methods employed were (1) reviewing historical records in insect collections to establish the presence of C. truncatus prior to commercial almond horticulture, (2) field trapping of insects to establish presence in regions of interest, (3) laboratory trials to determine the thermal limits of the organism, and (4) correlative species distribution modelling to describe its current distribution. We find that C. truncatus is more widespread across Australia than was previously known, with historical records preceding commercial almond production in Australia by a century. The methods developed in this study can be applied elsewhere in the world where C. truncatus is an emerging pest, or to novel pest species as they arise with increasing frequency in a globalised and warming world.

Molecular phylogenetics of the Ophiocordyceps sinensis-species complex lineage (Ascomycota, Hypocreales), with the discovery of new species and predictions of species distribution.

Ophiocordyceps sinensis is a famous traditional Chinese medicine adapted to the alpine environment of the Qinghai-Tibet Plateau and adjacent regions. Clarification of the species diversity of Ophiocordyceps sinensis and its relatives could expand the traditional medicinal resources and provide insights into the speciation and adaptation. The study is prompted by the discovery of a new species, O. megala, described here from a biodiversity hotspot in the Hengduan Mountains, China. Combined morphological, ecological, and phylogenetic evidence supports its distinctiveness from O. sinensis, O. xuefengensis, and O. macroacicularis. Additionally, based on the phylogenetic construction of Ophiocordyceps, a special clade was focused phylogenetically on the more closely related O. sinensis complex, which was defined as the O. sinensis- species complex lineage. A total of 10 species were currently confirmed in this lineage. We made a comprehensive comparison of the sexual/asexual morphological structures among this species complex, distinguishing their common and distinctive features. Furthermore, using the method of species distribution modelling, we studied the species ocurrences in relation to climatic, edaphic, and altitudinal variables for the eight species in the O. sinensis-species complex, and determined that their potential distribution could extend from the southeastern Qinghai-Tibet Plateau to the Xuefeng Mountains without isolating barrier. Thus, the biodiversity corridor hypothesis was proposed around the O. sinensis-species complex. Our study highlights the phylogeny, species diversity, and suitable distribution of the O. sinensis-species complex lineage, which should have a positive implication for the resource discovery and adaptive evolution of this unique and valuable group.

Ecologically and medically important black flies of the genus Simulium: Identification of biogeographical groups according to similar larval niches.

The black fly genus Simulium includes medically and ecologically important species, characterized by a wide variation of ecological niches largely determining their distributional patterns. In a rapidly changing environment, species-specific niche characteristics determine whether a species benefits or not. With aquatic egg, larval and pupal stages followed by a terrestrial adult phase, their spatial arrangements depend upon the interplay of aquatic conditions and climatic-landscape parameters in the terrestrial realm. The aim of this study was to enhance the understanding of the distributional patterns among Simulium species and their ecological drivers. In an ecological niche modelling approach, we focused on 12 common black fly species with different ecological requirements. Our modelling was based on available distribution data along with five stream variables describing the climatic, land-cover, and topographic conditions of river catchments. The modelled freshwater habitat suitability was spatially interpolated to derive an estimate of the adult black flies' probability of occurrence. Based on similarities in the spatial patterns of modelled habitat suitability we were able to identify three biogeographical groups, which allows us to confirm old assessments with current occurrence data: (A) montane species, (B) broad range species and (C) lowland species. The five veterinary and human medical relevant species Simulium equinum, S. erythrocephalum, S. lineatum, S. ornatum and S. reptans are mainly classified in the lowland species group. In the course of climatic changes, it is expected that biocoenosis will slightly shift towards upstream regions, so that the lowland group will presumably emerge as the winner. This is mainly explained by wider ecological niches, including a higher temperature tolerance and tolerance to various pollutants. In conclusion, these findings have significant implications for human and animal health. As exposure to relevant Simulium species increases, it becomes imperative to remain vigilant, particularly in investigating the potential transmission of pathogens.

Modelling the spatial risk of malaria through probability distribution of Anopheles maculipennis s.l. and imported cases.

Malaria remains one of the most important infectious diseases globally due to its high incidence and mortality rates. The influx of infected cases from endemic to non-endemic malaria regions like Europe has resulted in a public health concern over sporadic local outbreaks. This is facilitated by the continued presence of competent Anopheles vectors in non-endemic countries.We modelled the potential distribution of the main malaria vector across Spain using the ensemble of eight modelling techniques based on environmental parameters and the Anopheles maculipennis s.l. presence/absence data collected from 2000 to 2020. We then combined this map with the number of imported malaria cases in each municipality to detect the geographic hot spots with a higher risk of local malaria transmission.The malaria vector occurred preferentially in irrigated lands characterized by warm climate conditions and moderate annual precipitation. Some areas surrounding irrigated lands in northern Spain (e.g. Zaragoza, Logroño), mainland areas (e.g. Madrid, Toledo) and in the South (e.g. Huelva), presented a significant likelihood of A. maculipennis s.l. occurrence, with a large overlap with the presence of imported cases of malaria.While the risk of malaria re-emergence in Spain is low, it is not evenly distributed throughout the country. The four recorded local cases of mosquito-borne transmission occurred in areas with a high overlap of imported cases and mosquito presence. Integrating mosquito distribution with human incidence cases provides an effective tool for the quantification of large-scale geographic variation in transmission risk and pinpointing priority areas for targeted surveillance and prevention.

Phylogenetics and phylogeography of Euphorbia canariensis reveal an extreme Canarian-Asian disjunction but limited inter-island colonization.

Euphorbia canariensis is an iconic endemic species representative of the lowland xerophytic communities of the Canary Islands. It is widely distributed in the archipelago despite having diasporas unspecialized for long-distance dispersal. Here, we reconstructed the evolutionary history of E. canariensis at two levels: a time-calibrated phylogenetic analysis aimed at clarifying interspecific relationships and large-scale biogeographic patterns; and a phylogeographic study focused on the history of colonization across the Canary Islands. For the phylogenetic study, we sequenced the ITS region for E. canariensis and related species of Euphorbia sect. Euphorbia. For the phylogeographic study, we sequenced two cpDNA regions for 28 populations representing the distribution range of E. canariensis. The number of inter-island colonization events was explored using PAICE, a recently developed method that includes a sample size correction. Additionally, we used species distribution modelling (SDM) to evaluate environmental suitability for E. canariensis through time. Phylogenetic results supported a close relationship between E. canariensis and certain Southeast Asian species (E. epiphylloides, E. lacei, E. sessiliflora). In the Canaries, E. canariensis displayed a west-to-east colonization pattern, not conforming to the "progression rule", i.e. the concordance between phylogeographic patterns and island emergence times. We estimated between 20 and 50 inter-island colonization events, all of them in the Quaternary, and SDM suggested a late Quaternary increase in environmental suitability for E. canariensis. The extreme biogeographic disjunction between Macaronesia and Southeast Asia (ca. 11,000 km) parallels that found in a few other genera (Pinus, Dracaena). We hypothesize that these disjunctions are better explained by extinction across north Africa and southwest Asia rather than long-distance dispersal. The relatively low number of inter-island colonization events across the Canaries is congruent with the low dispersal capabilities of E. canariensis.

Predicting Climate Change Impact on the Habitat Suitability of the Schistosoma Intermediate Host Oncomelania hupensis in the Yangtze River Economic Belt of China.

Oncomelania hupensis is the exclusive intermediary host of Schistosoma japonicum in China. The alteration of O. hupensis habitat and population distribution directly affects the safety of millions of individuals residing in the Yangtze River Economic Belt (YREB) and the ecological stability of Yangtze River Basin. Therefore, it is crucial to analyze the influence of climate change on the distribution of O. hupensis in order to achieve accurate control over its population. This study utilized the MaxEnt model to forecast possible snail habitats by utilizing snail distribution data obtained from historical literature. The following outcomes were achieved: The primary ecological factors influencing the distribution of O. hupensis are elevation, minimum temperature of the coldest month, and precipitation of wettest month. Furthermore, future climate scenarios indicate a decrease in the distribution area and a northward shift of the distribution center for O. hupensis; specifically, those in the upstream will move northeast, while those in the midstream and downstream will move northwest. These changes in suitable habitat area, the average migration distance of distribution centers across different climate scenarios, time periods, and sub-basins within the YREB, result in uncertainty. This study offers theoretical justification for the prevention and control of O. hupensis along the YREB.

Ecological associations distribution modelling of marine plankton at a global scale.

Marine plankton communities form intricate networks of interacting organisms at the base of the food chain, and play a central role in regulating ocean biogeochemical cycles and climate. However, predicting plankton community shifts in response to climate change remains challenging. While species distribution models are valuable tools for predicting changes in species biogeography under climate change scenarios, they generally overlook the key role of biotic interactions, which can significantly shape ecological processes and ecosystem responses. Here, we introduce a novel statistical framework, association distribution modelling (ADM), designed to model and predict ecological associations distribution in space and time. Applied on a Tara Oceans genome-resolved metagenomics dataset, the present-day biogeography of ADM-inferred marine plankton associations revealed four major biogeographic biomes organized along a latitudinal gradient. We predicted the evolution of these biome-specific communities in response to a climate change scenario, highlighting differential responses to environmental change. Finally, we explored the functional potential of impacted plankton communities, focusing on carbon fixation, outlining the predicted evolution of its geographical distribution and implications for ecosystem function.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Unravelling the impact of climate change on honey bees: An ensemble modelling approach to predict shifts in habitat suitability in Queensland, Australia.

Honey bees play a vital role in providing essential ecosystem services and contributing to global agriculture. However, the potential effect of climate change on honey bee distribution is still not well understood. This study aims to identify the most influential bioclimatic and environmental variables, assess their impact on honey bee distribution, and predict future distribution. An ensemble modelling approach using the biomod2 package in R was employed to develop three models: a climate-only model, an environment-only model, and a combined climate and environment model. By utilising bioclimatic data (radiation of the wettest and driest quarters and temperature seasonality) from 1990 to 2009, combined with observed honey bee presence and pseudo absence data, this model predicted suitable locations for honey bee apiaries for two future time spans: 2020-2039 and 2060-2079. The climate-only model exhibited a true skill statistic (TSS) value of 0.85, underscoring the pivotal role of radiation and temperature seasonality in shaping honey bee distribution. The environment-only model, incorporating proximity to floral resources, foliage projective cover, and elevation, demonstrated strong predictive performance, with a TSS of 0.88, emphasising the significance of environmental variables in determining habitat suitability for honey bees. The combined model had a higher TSS of 0.96, indicating that the combination of climate and environmental variables enhances the model's performance. By the 2020-2039 period, approximately 88% of highly suitable habitats for honey bees are projected to transition from their current state to become moderate (14.84%) to marginally suitable (13.46%) areas. Predictions for the 2060-2079 period reveal a concerning trend: 100% of highly suitable land transitions into moderately (0.54%), marginally (17.56%), or not suitable areas (81.9%) for honey bees. These results emphasise the critical need for targeted conservation efforts and the implementation of policies aimed at safeguarding honey bees and the vital apiary industry.

Importance of Habitat Context in Modelling Risk Maps for Two Established Invasive Alien Plant Species: The Case of Ailanthus altissima and Phytolacca americana in Slovenia (Europe).

Forests are important ecosystems that face threats from climate change and global environmental shifts, with invasive alien plant species being a significant concern. Some of these invasive species have already become established, while others are in the process of naturalisation. Although forests are a relatively stable ecosystem, extreme weather events increase their vulnerability to change, and clearings left after natural disturbances are particularly susceptible to invasion by alien plant species (IAPS). We created risk maps of two species that have spread rapidly in the last decade: American pokeweed (Phytolacca americana) and the tree of heaven (Ailanthus altissima). We prepared a generalised linear model based on the occurrence data collected within the LIFE ARTEMIS project. Eleven environmental variables were used to determine habitat characteristics. We constructed two models for each species: one covering the entirety of Slovenia and the other specifically for the forested areas in Slovenia, with the latter incorporating forest-specific variables (such as forest sanitation felling and monocultures). We observed the presence of both species at lower altitudes and in close proximity to water sources. American pokeweed tends to occur nearer to railways, while the presence of the tree of heaven is associated with areas lacking carbonate parent material and influenced by land use patterns. In forested areas, the occurrence of American pokeweed is influenced by forest habitat characteristics, such as disturbances caused by extreme weather events or the prevalence of Norway spruce monocultures. In contrast, the occurrence of the tree of heaven is influenced by more general environmental variables, such as altitude and proximity to railways. Consequently, we have generated risk maps for the entirety of Slovenia and separately for forested areas, both of which indicate similar levels of risk, particularly for the tree of heaven. The risk map for American pokeweed highlights numerous vulnerable areas, especially forest edges, which are highly susceptible to invasion. Furthermore, there is a higher likelihood of this species occurring in areas that have undergone sanitation felling. This study suggests that the production of risk maps of IAPS could be improved by focussing on habitat types and taking into account habitat-specific variables. This approach could enhance the early detection and management of these invasive species.

Spatial prioritization of dugong habitats in India can contribute towards achieving the 30 × 30 global biodiversity target.

Indian coastal waters are critical for dugong populations in the western Indian Ocean. Systematic spatial planning of dugong habitats can help to achieve biodiversity conservation and area-based protection targets in the region. In this study, we employed environmental niche modelling to predict suitable dugong habitats and identify influencing factors along its entire distribution range in Indian waters. We examined data on fishing pressures collected through systematic interview surveys, citizen-science data, and field surveys to demarcate dugong habitats with varying risks. Seagrass presence was the primary factor in determining dugong habitat suitability across the study sites. Other variables such as depth, bathymetric slope, and Euclidean distance from the shore were significant factors, particularly in predicting seasonal suitability. Predicted suitable habitats showed a remarkable shift from pre-monsoon in Palk Bay to post-monsoon in the Gulf of Mannar, indicating the potential of seasonal dugong movement. The entire coastline along the Palk Bay-Gulf of Mannar region was observed to be at high to moderate risk, including the Gulf of Mannar Marine National Park, a high-risk area. The Andaman Islands exhibited high suitability during pre- and post-monsoon season, whereas the Nicobar Islands were highly suitable for monsoon season. Risk assessment of modelled suitable areas revealed that < 15% of high-risk areas across Andaman and Nicobar Islands and Palk Bay and Gulf of Mannar, Tamil Nadu, fall within the existing protected areas. A few offshore reef islands are identified under high-risk zones in the Gulf of Kutch, Gujarat. We highlight the utility of citizen science and secondary data in performing large-scale spatial ecological analysis. Overall, identifying synoptic scale 'Critical Dugong Habitats' has positive implications for the country's progress towards achieving the global 30 × 30 target through systematic conservation planning.

Range map data of marine ecosystem structuring species under global climate change.

Data on contemporary and future geographical distributions of marine species are crucial for guiding conservation and management policies in face of climate change. However, available distributional patterns have overlooked key ecosystem structuring species, despite their numerous ecological and socioeconomic services. Future range estimates are mostly available for few species at regional scales, and often rely on the outdated Representative Concentration Pathway scenarios of climate change, hindering global biodiversity estimates within the framework of current international climate policies. Here, we provide range maps for 980 marine structuring species of seagrasses, kelps, fucoids, and cold-water corals under present-day conditions (from 2010 to 2020) and future scenarios (from 2090 to 2100) spanning from low carbon emission scenarios aligned with the goals of the Paris Agreement (Shared Socioeconomic Pathway 1-1.9), to higher emissions under reduced mitigation strategies (SSP3-7.0 and SSP5-8.5). These models were developed using state-of-the-art and advanced machine learning algorithms linking the most comprehensive and quality-controlled datasets of occurrence records with high-resolution, biologically relevant predictor variables. By integrating the best aspects of species distribution modelling over key ecosystem structuring species, our datasets hold the potential to enhance the ability to inform strategic and effective conservation policy, ultimately supporting the resilience of ocean ecosystems.

The future of plant diversity within a Mediterranean endemism centre: Modelling the synergistic effects of climate and land-use change in Peloponnese, Greece.

Climate- and land-use change stand as primary threats to terrestrial biodiversity. Yet, their synergistic impacts on species distributions remain poorly understood. To address this knowledge gap, we conducted the first-ever comprehensive species distribution analysis on an entire regional endemism centre within an eastern Mediterranean country, incorporating dynamic land-use/land-cover change data together with climate change scenarios. Specifically, we apply species distribution modelling and spatial data analysis techniques to compare the individual and synergistic effects of these environmental drivers on the endemic vascular flora of Peloponnese, focusing on potential range contractions, altitudinal shifts, and habitat fragmentation levels. Moreover, we identify fine-scale present and potential future endemism hotspots within our study area, incorporating taxonomic and phylogenetic information. Overall, we aim to enhance our current understanding of endemism patterns and contribute to the development of future-proof conservation strategies for safeguarding Greece's endangered endemic flora. The integration of land-use change projections with climate change yielded less severe impacts compared to the effects anticipated when considering climatic variables alone. Most taxa are expected to undergo significant range declines and nearly half might experience increased habitat fragmentation, due to the synergistic effects of climate- and land-use change. We identified endemism hotspots, which are concentrated in or along the main Peloponnesian mountain massifs. However, our predictions indicate that areas presently recognized as endemism hotspots will undergo a concerning area decline, across all future scenarios considered in this study. Our findings highlight the importance of including dynamic land-use variables alongside climatic predictors when projecting species distributions under global change. Moreover, we showed that endemism hotspots are not static and considering their potential geographic shifts is paramount to delineate effective forward-looking conservation strategies.

Predicting suitable habitats for foraging and migration in Eastern Indian Ocean pygmy blue whales from satellite tracking data.

BACKGROUND: Accurate predictions of animal occurrence in time and space are crucial for informing and implementing science-based management strategies for threatened species. METHODS: We compiled known, available satellite tracking data for pygmy blue whales in the Eastern Indian Ocean (n = 38), applied movement models to define low (foraging and reproduction) and high (migratory) move persistence underlying location estimates and matched these with environmental data. We then used machine learning models to identify the relationship between whale occurrence and environment, and predict foraging and migration habitat suitability in Australia and Southeast Asia. RESULTS: Our model predictions were validated by producing spatially varying accuracy metrics. We identified the shelf off the Bonney Coast, Great Australian Bight, and southern Western Australia as well as the slope off the Western Australian coast as suitable habitat for migration, with predicted foraging/reproduction suitable habitat in Southeast Asia region occurring on slope and in deep ocean waters. Suitable foraging habitat occurred primarily on slope and shelf break throughout most of Australia, with use of the continental shelf also occurring, predominanly in South West and Southern Australia. Depth of the water column (bathymetry) was consistently a top predictor of suitable habitat for most regions, however, dynamic environmental variables (sea surface temperature, surface height anomaly) influenced the probability of whale occurrence. CONCLUSIONS: Our results indicate suitable habitat is related to dynamic, localised oceanic processes that may occur at fine temporal scales or seasonally. An increase in the sample size of tagged whales is required to move towards developing more dynamic distribution models at seasonal and monthly temporal scales. Our validation metrics also indicated areas where further data collection is needed to improve model accuracy. This is of particular importance for pygmy blue whale management, since threats (e.g., shipping, underwater noise and artificial structures) from the offshore energy and shipping industries will persist or may increase with the onset of an offshore renewable energy sector in Australia.