Michelia lacei W.W. Smith, a magnolia species categorized as Endangered on the IUCN Red List, is subject to severe disturbance. We carried out field surveys and a review of literature records to present a detailed description of the current status of M. lacei. We then predicted the potential distribution of M. lacei under different climatic scenarios based on 60 occurrence records (53 recorded during our field surveys and 7 earlier records) and 19 bioclimatic variables from the WorldClim database. We selected 18 locations and four bioclimatic variables for model training. Temperature seasonality and annual temperature range were the most influential variables for predicting the potential distribution of the species. We used MaxEnt to model distribution under current climate conditions and four Shared Socioeconomic Pathway scenarios in four future time periods to determine the effects of future climate change on the habitat suitable for the species. We predict areas of moderately and highly suitable habitat will gradually decrease over time. We recommend increased in situ and ex situ conservation efforts to mitigate this habitat decline and protect populations of M. lacei.

Evidence-based conservation can be hindered by limited field data, but historical archives have the potential to provide unique insights into conservation-relevant parameters, such as identification of suitable habitat for threatened species. The Manumea or Tooth-billed Pigeon Didunculus strigirostris has declined on Samoa and only a tiny remnant population still persists, and a key first step for conservation is to locate surviving birds. Numerous Manumea records are available from the nineteenth century onwards, and we used historical and modern records to generate a series of species distribution models to predict the distribution of suitable habitat across Samoa to guide new field searches. Manumea distribution is closely associated with forest cover or its proxies. Preferred Manumea food plants are suggested to be low-elevation trees, but elevation provides relatively low percentage contribution in most models, thus not excluding the possibility that Manumea might occur at high elevations. There is also little evidence for elevational change in records over the past century. Models based on visual versus acoustic records exhibit differences in predicted habitat suitability, suggesting that some purported acoustic records might not actually represent Manumea calls. Field searches should target areas representing high habitat suitability across all models, notably the forested central axis of Upolu.

The Argentine ant (Linepithema humile) and the little fire ant (Wasmannia auropunctata) are among the top 100 invasive alien species globally, causing significant ecological and economic harm. Therefore, it is crucial to study their potential geographic distribution worldwide. This study aimed to predict their global distribution under current and future climate conditions. We used distribution data from various sources, including CABI, GBIF, and PIAKey, and key climate variables selected from 19 environmental factors to model their potential geographic distribution using MaxEnt. The AUC values were 0.925 and 0.937 for L. humile and W. auropunctata, respectively, indicating good predictive performance. Suitable areas for L. humile were mainly in southern North America, northern South America, Europe, central Asia, southern Oceania, and parts of Africa, while W. auropunctata suitable areas were mostly in southern North America, most of South America, a small part of Europe, southern Asia, central Africa, and some parts of Oceania. Under climate change scenario, suitable areas for L. humile increased, while highly suitable areas for W. auropunctata decreased. The top four countries with the largest areas of overlapping suitable habitat under current climate were Brazil, China, Australia, and Argentina, while under future SSP585 climate scenario, the top four countries were Brazil, China, Indonesia, and Argentina. Some countries, such as Estonia and Finland, will see an overlapping adaptation area under climate change. In conclusion, this study provides insight into controlling the spread and harm of L. humile and W. auropunctata.

The rare Himalayan wolf Canis lupus chanco is categorized as Vulnerable on the IUCN Red List, and there is limited knowledge of its ecology and distribution. In Bhutan, the Himalayan wolf is one of the least known carnivores. Our aims in this study were to map the current distribution of the wolf in Bhutan and to identify potential habitats within the country. We compiled 32 records of wolf presence from camera-trap surveys and, using a maximum entropy approach, we estimated a potential habitat of 2,431 km2, comprising c. 6.3% of Bhutan. However, wolf presence was localized and non-continuous. We recommend a detailed fine-scale habitat analysis in areas of potential habitat and genetic studies to investigate population structure. Knowledge of these matters will provide insights regarding connectivity and facilitate the development of conservation strategies for this threatened wolf.

Yushania anceps is a temperate woody bamboo taxon of high socio-economic importance occurring in the sub-alpine zone of the western Himalayas. This study was carried out to delineate the potential distribution of Y. anceps in the western Himalayas through species distribution modelling (SDM), and genetic characterization using sequence-tagged microsatellite (STMS) markers. The present study revealed an endemic distribution of this species in the Uttarakhand Himalayas, with an estimated area of 211.59 km2. The maximum probability of occurrence was recorded in the moderately dense forests between the altitudinal ranges of 2500 and 2700 m. The model output was well supported with high values of different statistical measures, such as the AUC (0.911) and Kappa coefficient (K = 0.513). Environmental variables related to precipitation, temperature and topography were identified as the most contributory in current SDM. In addition, diversity measures, namely allelic richness (Ar), expected heterozygosity (He), and fixation index (FST), were calculated in five sampled populations with eight STMS markers, which indicated high genetic diversity (Ar = 4.24; He = 0.689) and little differentiation (FST = 0.062). The diversity maps displayed that the populations located in the Kumaon region captured relatively more genetic diversity than the Garhwal region. Further, genetic clustering and STRUCTURE analysis revealed a substantial level of genetic admixing across the analysed populations, and as a result, no sub-structuring was detected. Due to the rare and endemic distribution of Y. anceps, it requires immediate conservation measures, and the knowledge base generated here will be of paramount importance to forest managers, researchers and policymakers.

Hyalomma marginatum is an important tick species which is the main vector of Crimean–Congo haemorrhagic fever and spotted fever. The species is predominantly distributed in parts of southern Europe, North Africa and West Asia. However, due to ongoing climate change and increasing reports of H. marginatum in central and northern Europe, the expansion of this range poses a potential future risk. In this study, an ecological niche modelling approach to model the current and future climatic suitability of H. marginatum was followed. Using high-resolution climatic variables from the Chelsa dataset and an updated list of locations for H. marginatum, ecological niche models were constructed under current environmental conditions using MaxEnt for both current conditions and future projections under the ssp370 and ssp585 scenarios. Models show that the climatically suitable region for H. marginatum matches the current distributional area in the Mediterranean basin and West Asia. When applied to future projections, the models suggest a considerable expansion of H. marginatum's range in the north in Europe as a result of rising temperatures. However, a decline in central Anatolia is also predicted, potentially due to the exacerbation of drought conditions in that region.

The Critically Endangered African wild ass Equus africanus is one of the most threatened equids, with fewer than 400 individuals persisting in the Danakil Desert (Eritrea), and fewer than 600 globally. To effectively conserve the species, it is essential to determine the extent of available suitable habitats and understand the environmental factors that most influence its current distribution. During 2016–2019 we observed African wild asses, recorded their locations during both the wet and dry seasons and analysed the bioclimatic data and topography using the maximum entropy species distribution model. Distance from water sources and precipitation of the driest month were the top predictors of suitable habitat for the dry season, whereas seasonal temperature variability and precipitation during the warmest quarter were the top predictors for the wet season. Model performances were high, with area under the curve values of 0.97 and 0.98 for the dry and wet seasons, respectively. In the Danakil Desert of Eritrea, the extent of optimal habitat for African wild asses is estimated to be 130 km2 in the dry season and 739 km2 in the wet season, with a potential range of 11,000 km2 for both seasons. Our model results also indicate that in the dry season 89 km2 of the Messir Plateau is optimal habitat, and the entire plateau area of 124 km2 provides optimal habitat during the wet season. These findings provide wildlife management authorities with substantive information and rationale for the establishment of a protected area on the Messir Plateau for African wild asses in Eritrea.

The Western Tragopan Tragopan melanocephalus is endemic to the Western Himalayas and currently listed as ‘Vulnerable’ on the IUCN Red List which also emphasizes a data deficiency regarding its distribution and population size. With this study we provide new data from the Palas Valley, northern Pakistan and deliver a range wide estimate of the species current, past, and future potential distribution as derived from environmental niche models. In the Palas Valley, Western Tragopans occupied different summer habitats on north-facing slopes and winter habitats on south-facing slopes. A quantitative estimate of local populations in six side valleys was inferred from individual call-count surveys during two breeding seasons (April and May 2017, 2018) and disturbance factors were evaluated from information of local people provided in questionnaires. Generalized-linear models (GLMs) showed a significant effect of disturbance factors on Western Tragopans, i.e. local abundances decreased with increasing disturbance from livestock, collectors and hunters visiting the area. This effect was visible across survey years and at both, south- as well as north-facing slopes. While the known distributional range of the Western Tragopan is small and fragmented, our niche models inferred climatically suitable space between Himachal Pradesh and northwestern Pakistan to be more continuous. Given the species sensitivity to disturbance, these findings indicate that the observed fragmentation of the current range might also be attributed to habitat transformation or anthropogenic disturbance rather than climatic suitability. During the Last Glacial Maximum (LGM) T. melanocephalus was probably restricted to small forest refugia, whereas projections onto eleven future climate simulations were inconclusive with the majority suggesting that climatically suitable space for T. melanocephalus will likely expand in response to anthropogenic climate change. In conclusion, we recommend that future conservation measures should be planned with regard to the species’ sensitivity to anthropogenic disturbances.

The distribution of regeneration makes it possible to assess whether populations of tree species will maintain or change their distributions. For Neotropical dry forests there is little information on the potential changes in the distribution of tree species. Here, we evaluate the potential distributions of adults and seedlings of eight timber tree species of the Piedmont Forest of north-western Argentina by recording the presence of seedlings and adults in plots and modelling with MaxEnt software using three bioclimatic variables. The potential distribution areas of seedlings and adults and the percentage of overlap of seedlings with respect to adults were calculated. The potential distribution for adults was 694 457 ± 62 535 ha, and this figure was 656 564 ± 194 769 ha for seedlings. The potential distribution of seedlings of Calycophyllum multiflorum covered the smallest area (184 496 ha) and had the least overlap with the adults (18%). The difference in the overlap of the potential distribution areas between adults and seedlings suggests that there could be changes in the future distribution of this tree species and C. multiflorum should therefore be the focus of conservation strategies so that the species can follow its bioclimatic niche as the climate changes.

As natural and anthropogenic forcings impel anticipated climate change, their effects on biodiversity and environmental sustainability are evident. A fundamental question that is often overlooked is: which changes in climate will cause the redistribution or extinction of threatened species? Here, we mapped and modelled the current and future geographical distributions of the four threatened medicinal plants – Aconitum heterophyllum Wall. ex Royle, Fritillaria cirrhosa D.Don, Meconopsis aculeata Royle and Rheum webbianum Royle – in Kashmir Himalaya using maximum entropy (MaxEnt) modelling. Species occurrence records were collated from detailed field studies carried out between the years 2010 and 2020. Four general circulation models for Representative Concentration Pathway (RCP) 4.5 and RCP8.5 climate change scenarios were chosen for future range changes over periods around 2050 (average for 2041–2060) and 2070 (average of 2061–2080). Notable differences existed between species in their responses to predictive environmental variables of temperature and precipitation. Increase in the most suitable habitat, except for A. heterophyllum and R. webbianum, were evident across Himalayan Mountain regions, while the Pir Panjal mountain region exhibited a decrease for all four species under future climate change scenarios. This study exemplifies the idiosyncratic response of narrow-range plants to expected future climate change and highlights conservation implications.

Tropical montane systems are characterized by a high plant species diversity and complex environmental gradients. Climate warming may force species to track suitable climatic conditions and shift their distribution upward, which may be particularly problematic for species with narrow elevational ranges. To better understand the fate of montane plant species in the face of climate change, we evaluated a) which environmental factors best predict the distribution of 277 plant species along the Himalayan elevational gradient in Nepal, and b) whether species elevational ranges increase with increasing elevation. To this end, we developed ecological niche models using MaxEnt by combining species survey and presence data with 19 environmental predictors. Key environmental factors that best predicted the distribution of Himalayan plant species were mean annual temperature (for 54.5% of the species) followed by soil clay content (10.2%) and slope (9.4%). Although temperature is the best predictor, it is associated with many other covariates that may explain species distribution, such as irradiance and potential evapotranspiration. Species at both ends of the Himalayan elevational gradient had narrower elevational ranges than species in the middle. Our results suggest that with further global warming, most Himalayan plant species have to migrate upward, which is especially critical for upland species with narrow distribution ranges.

Climate change is causing the geographical ranges of some species to track suitable conditions. Habitat specialists, range-restricted species and species with limited dispersal abilities may be unable to track changing conditions, increasing their extinction risk. In response to changing conditions and species movement patterns, there is a need to account for the effects of climate change when designing protected areas and identifying potential climate refugia. We used ecological niche models projected into future climates to identify potential impacts of climate change on the distribution of 11 rupicolous reptile species in the Soutpansberg Mountains, South Africa. Lygodactylus incognitus, Lygodactylus soutpansbergensis, Platysaurus relictus and Vhembelacerta rupicola were identified as being vulnerable to climate change due to substantial reductions in suitable habitat and low spatial overlap between current and future niche envelopes. We identified areas of high conservation importance for the persistence of these species under present-day and projected future conditions. The western Soutpansberg was identified as an area of high conservation priority as it is a potential refuge under future projections. Projecting distributions of vulnerable species into future climate predictions can guide future research and identify potential refugia that will best conserve species with restricted ranges in a world with climate change.

The prevention of tropical forest deforestation is essential for mitigating climate change. We tested the machine learning algorithm Maxent to predict deforestation across the Peruvian Amazon. We used official annual 2001–2019 deforestation data to develop a predictive model and to test the model’s accuracy using near-real-time forest loss data for 2020. Distance from agricultural land and distance from roads were the predictor variables that contributed most to the final model, indicating that a narrower set of variables contribute nearly 80% of the information necessary for prediction at scale. The permutation importance indicating variable information not present in the other variables was also highest for distance from agricultural land and distance from roads, at 40.5% and 14.3%, respectively. The predictive model registered 73.2% of the 2020 early alerts in a high or very high risk category; less than 1% of forest cover in national protected areas were registered as very high risk, but buffer zones were far more vulnerable, with 15% of forest cover being in this category. To our knowledge, this is the first study to use 19 years of annual data for deforestation risk. The open-source machine learning method could be applied to other forest regions, at scale, to improve strategies for reducing future deforestation.

Species of Agonoscena (Hemiptera: Aphalaridae) are key pests of pistachio in all of the most important pistachio producing countries in the Old World. The efficiency and accuracy of DNA barcoding for the identification of Agonoscena species were tested using mitochondrial cytochrome c oxidase subunit 1 (mtCO1) and cytochrome b (cytb) gene sequences. Moreover, morphometric sexual dimorphism was studied. Finally, the potential geographical distribution of Agonoscena pistaciae, the most important pistachio pest, was calculated using the MaxEnt model. Similar relationships of clustering were found in the morphometric analysis and the molecular analyses with mtCO1 and cytb genes, with A. bimaculata and A. pistaciae being closely related, and A. pegani constituting their sister group. Although the results showed that the cytb gene is a better marker for barcoding in this group, the mtCO1 gene clearly separates the three psyllid species making mtCO1 suitable for diagnostic purposes. A geometric morphometric analysis showed that the distance between landmark number 7 (bifurcation of vein M) to the fore margin of the forewing, and the distance between landmarks number 6 (apex of vein Cu1b) and 11 (wing base), are the most important geometric characters for diagnosing the studied species. Moreover, the forewing shape of males vs females is similar in A. pistaciae and A. bimaculata but differs significantly in A. pegani. In the ecological niche modeling of the distribution of A. pistaciae, the most important contribution was made by the variable ‘minimum temperature of coldest period’. The most suitable areas for A. pistaciae are restricted to Eastern, Southern and some parts of Central Iran.

Invasive populations of Dalmation toadflax [Linaria dalmatica (L.) Mill.] and yellow toadflax (Linaria vulgaris Mill.) are widespread throughout the Intermountain West, where gene flow between these nonnative species is producing vigorous and fertile hybrids. These hybrid toadflax populations are less responsive to herbicides than either parent species, and biocontrol agents routinely released on L. dalmatica and L. vulgaris often fail to establish on hybrid hosts. Early detection of hybrid Linaria populations is therefore essential for effective management, but resources are limited for scouting large expanses of range and wildland. We used species distribution modeling to identify environmentally suitable areas for these invasive Linaria taxa in Montana, Wyoming, and Colorado. Areas suitable for hybrid Linaria establishment were estimated using two different modeling approaches: first, based on known hybrid occurrence and associated environmental conditions, and second, based on zones environmentally suitable for co-occurrence of the parent species. This also allowed comparison of different model outputs, especially relevant when modeling emerging invasives, such as novel hybrids, with minimal occurrence data. Combining the two model outputs identified areas at greatest risk of hybrid Linaria invasion, including parts of north-central Montana, where model estimates indicate the hybrid may spread without prior co-invasion of the parents. Potential hybrid hot spots were also identified in western Montana; northwestern, northeastern, and southeastern Wyoming; and the Western Slope and Front Range of Colorado. Despite relatively few confirmed occurrences of hybrid populations to date, our results indicate that extensive spread of hybrid populations is possible within the studied area. Model-based maps of potential Linaria distributions will allow area weed managers to direct limited resources more effectively for locating and controlling these invaders.

The jaguar Panthera onca, a threatened species in Brazil, is losing suitable habitat as a result of agricultural expansion and other forms of land conversion, especially in the Cerrado biome. In the current context of habitat loss and fragmentation, a network of protected areas is paramount for the conservation of this species. We aimed to identify jaguar conservation units in the Cerrado, and propose a ranking of priority areas for the species in this region. We used the maximum entropy algorithm to model habitat suitability for the jaguar in the Cerrado, with nine uncorrelated environmental variables and 106 non-autocorrelated presence-only records. We prioritized regions, using Zonation, and ranked jaguar conservation units according to their area, proximity to strictly protected areas, jaguar presence, and potential for connectivity. Circa 30% of the Cerrado is suitable for the jaguar. The most important variables affecting jaguar distribution are mean rainfall and land cover, with a high probability of jaguar presence in forest and savannah. We selected 31 high-priority jaguar conservation units, covering c. 174,825 km2 (8.5%) of the Cerrado. We emphasize the need for new protected areas and the promotion of sustainable development, as only 0.4% of the Cerrado (8,345 km2) has high environmental suitability for jaguars and < 1% of the area covered by jaguar conservation units falls within protected areas. Most jaguar conservation units identified here are relevant for habitat connectivity in Brazil, given their proximity to other critical areas for jaguar conservation in the Caatinga and the Amazon.

The Caatinga of north-eastern Brazil is the largest and most diverse seasonally dry tropical forest in the Americas and is home to numerous endemic species. However, only 1.2% of the area is under full protection, and given the ongoing decline of this biome there is an urgent need to expand the protected area network. The Endangered Caatinga howler monkey Alouatta ululata is almost endemic to the Caatinga, and is a potential umbrella species for the protection of its biodiversity. Using all available distribution data and our own surveys we applied Maxent and Zonation spatial modelling to identify the range of A. ululata, and priority conservation areas for the species, maximizing habitat quality and connectivity, and minimizing conservation constraints. The top 10% priority areas cover 34,400 km2 and mostly coincide with good remnants of Caatinga. Only priority areas in the northern part of the species’ range are protected, so it is essential to create new protected areas in the centre and south of the range. Maxent modelling indicates that the species depends on good tree cover, but even inside protected areas we observed recent deforestation, illustrating the urgency to improve management. Maxent also indicated that aridity limits the species' range, and therefore the ongoing aridification of the Caatinga is a threat to its future. The protection of A. ululata requires establishing new protected areas in priority locations and improving management of existing protected areas. Preservation of priority areas for the Caatinga howler monkey also represents an opportunity for the conservation of other important biodiversity in the region.

Asian tropical forests are among the most affected by overhunting of wildlife species. Bushmeat is not just a source of food, but is also often seen as an income source due to the increasing regional demand for wildlife products. In this study, we assess for the first time the medium- and large-size vertebrate species present in Lampi Marine National Park (Myanmar) using camera traps and opportunistic sightings, and we use data from law enforcement patrolling to identify areas where poaching activities occur. Nineteen different terrestrial vertebrate species were observed in the Park, five of which are listed as globally threatened, while illegal activities were recorded at 107 locations. We estimated wildlife and human distributions using the maximum-entropy (i.e., MaxEnt) algorithm. Human activities were widely distributed in the Park, and areas selected by people were those at lower elevations and mainly in evergreen or semi-evergreen forests where most of the species occur. These models could improve knowledge of species presence and of the potential risk to wildlife associated with human activities. The modelling of wildlife and human presence proved to be useful for identifying areas that would receive special attention during patrolling, management and conservation actions.

The rate of deforestation in the Amazon is increasing. Predictive models estimate that as a result of agricultural expansion 40% of these forests will be lost by 2050. As a consequence the habitat of forest-dwelling species such as the Endangered black-faced black spider monkey Ateles chamek is being lost, particularly along the arc of deforestation in the Brazilian Amazon. We used species distribution modelling to (1) define the distribution of this spider monkey, using environmental predictors, (2) calculate the area of this distribution covered by the protected area network, and (3) calculate the expected loss of the species’ habitat under future scenarios of deforestation. We found that the species occupies only c. 28% of its extent of occurrence. Only 32% of the species’ area of occupancy is legally protected, and the modelling suggests that 31–40% of the species’ habitat will be lost by 2050. We highlight three unprotected regions with extensive forest cover that are predicted to become severely deforested by 2050 as priority regions for expanding the protected area network. We also propose landscape management and restoration in three human-modified regions. Our study provides an example of how species distribution modelling can be applied to assess threats to species and support decision makers in implementing conservation actions.