Habitat Suitability For Species Research Articles

Filling gaps in global myrmecology: ants of the Kingdom of Bahrain (Hymenoptera: Formicidae)

ABSTRACT We present the first faunal analysis of the ants (Formicidae) of the Kingdom of Bahrain (Bahrain), an island nation in the Arabian Gulf. We document a total of 35 ant species based on published, unpublished and new specimen records, including 26 presumed native species and nine non-native tramp species. The native fauna was predominantly of Palaearctic origin, with a few Afrotropical species. A new species of the genus Lepisiota Santschi, 1926, L. bahrainensis sp. n., is described and illustrated based on the worker caste. Habitat suitability modelling of the ant fauna of Bahrain was generated using a total of 157 recorded points against the panel of 19 bioclimatic factors. We used Maxent software to generate the final map which indicates a significantly high and excellent habitat suitability of species on the northern part of the country and high suitability on the eastern coasts. Our results show that the mean temperature of the driest season is the most effective parameter in modelling the distribution, and we present interpretations of the very low habitat suitability in the extremely arid desert in the southern regions of the main island. Finally, we present ecological and biological remarks and distribution maps for each species. http://www.zoobank.org/urn:lsid:zoobank.org:pub:18D05DD2-4B64-4A87-8389-582D5714411C http://www.zoobank.org/urn:lsid:zoobank.org:act:DA93B16A-C23B-45F8-8C6A-867B8734D587

Species habitat suitability increased during COVID-19 lockdowns

COVID-19 lockdowns had strong positive and negative effects on the environment and biodiversity. The most evident effects were the occurrence of wildlife in the middle of urban settlements, the reduction of noise, and the improvement in air quality. However, other effects on species are less well known. Our main question is: did species habitat suitability increase during lockdowns? Here, we analysed trends in species habitat suitability over time by modelling the species distributions with a time series of environmental variables obtained from satellite remote sensing. We modelled the habitat suitability of 381 species of vascular plants, amphibians, reptiles, birds, and mammals, before, during, and after the lockdowns in the Iberian Peninsula (Portugal and Spain), from July 2017 to August 2022 with the Maxent presence-background algorithm and five MODIS variables (Albedo, Evapotranspiration, LST, NDVI, and Surface reflectance) with a periodicity of 8 days, and analysed their trends with the Mann-Kendall test. We compared our results with air quality data (PM10, CO, and NO2) from ground stations and Sentinel 5 P and with mobility data from Google mobility reports. Habitat suitability increased during both lockdowns when considering all species together. The peak in species' habitat suitability trends during the first lockdown was coincident with air quality and mobility trends: air pollution decreased when people stayed at home. Reduction in human mobility during COVID-19 lockdowns revealed positive effects on species’ habitat quality, highlighting the importance of reducing human activities as the only solution for nature conservation.

On the elephant trails: habitat suitability and connectivity for Asian elephants in eastern Indian landscape.

Identifying suitable habitats and conserving corridors are crucial to the long-term conservation of large and conflict-prone animals. Being a flagship species, survival of Asian elephants is threatened by human-induced mortality and habitat modification. We aimed to assess the habitat suitability and connectivity of the Asian elephant Elephas maximus Linnaeus, 1758 habitat in the state of Odisha in eastern India. We followed the ensemble of spatial prediction models using species presence data and five environmental variables. We used least-cost path and circuit theory approaches to identify the spatial connectivity between core habitats for Asian elephants. The results revealed that normalized difference vegetation index (NDVI; variable importance 42%) and terrain ruggedness (19%) are the most influential variables for predicting habitat suitability of species within the study area. Our habitat suitability map estimated 14.6% of Odisha's geographical area (c. 22,442 km2) as highly suitable and 13.3% (c. 20,464 km2) as moderate highly suitable. We identified 58 potential linkages to maintain the habitat connectivity across study area. Furthermore, we identified pinch points, bottlenecks, and high centrality links between core habitats. Our study offers management implications for long-term landscape conservation for Asian elephants in Odisha and highlights priority zones that can help maintain spatial links between elephant habitats.

Species distribution modeling of two poorly known populations of Spalerosophis diadema (Reptilia: Colubridae): are the Zagros Mountains a true barrier for fragmentation in this species?

ABSTRACT Predictive models of species distribution can be beneficial for identifying the most important and influential environmental factors in species distribution and understanding the current and future habitat suitability of species. In this study, we used species distribution modeling to find out the potential distribution and habitat suitability of two spatially separated populations of Spalerosophis diadema and show the most important environmental factors that affect their habitat separation. The findings of SDM analyses demonstrated that the most important factors for the two populations are annual mean temperature, precipitation of coldest quarter, NDVI in May, and elevation, as these factors contributing about 80–85% of the environmental factors to the whole model. Two populations react similarly to these environmental predictors and there is no significant difference between the important, and influential environmental factors of their habitats. Although our results show some overlap of the potential distributions of populations among Mesopotamian plain and Afghanistan, there is no confirmed report or voucher specimen proving the overlap distribution in these regions. Our results support the hypothesis that the Zagros Mountains acted as a barrier to the east–west fragmentation of these two populations.

Climate Change Impacts on the Availability of Anti-malarial Plants in Kenya

In many rural East African areas, anti-malarial plants are commonly used as first-line treatment against malaria. However, spatially explicit information about the future availability of anti-malarial plant species and its relation to future suitable habitat for malaria vectors is limited. In this study we 1) model the distribution of anti-malarial plant and malaria vector species and assess the drivers of their distributions taking the example of the Samburu dryland in Kenya, 2) map the modeled overlap in this area, 3) assess the impact of future climate change on anti-malarial plant and malaria vector species and 4) report their future overlaps. Our results show that mean temperature of warmest quarter, precipitation of wettest quarter and mean temperature of coldest quarter were the most important environmental variables that affected the distribution of anti-malarial species. The effects of climate change will be detrimental, since most areas will witness huge losses in anti-malarial species habitat while only a few gained or remained stable under both SSP2-4.5 and SSP5-8.5 climate change scenarios by 2050s and 2070s. According to most of our scenarios, more than half of the anti-malarial species will become threatened by 2050s and 2070s. A comparison between distribution patterns of future anti-malarial species richness and malaria vector species suitable habitat suggests that the former will decrease considerably while the later will increase. Because the availability of anti-malarial species will decrease in the areas affected by malaria vectors, geographically targeted conservation strategies and further control measures against malaria vectors are all the more important.

MaxEnt brings comparable results when the input data are being completed; Model parameterization of four species distribution models.

Species distribution models (SDMs) are practical tools to assess the habitat suitability of species with numerous applications in environmental management and conservation planning. The manipulation of the input data to deal with their spatial bias is one of the advantageous methods to enhance the performance of SDMs. However, the development of a model parameterization approach covering different SDMs to achieve well-performing models has rarely been implemented. We integrated input data manipulation and model tuning for four commonly-used SDMs: generalized linear model (GLM), gradient boosted model (GBM), random forest (RF), and maximum entropy (MaxEnt), and compared their predictive performance to model geographically imbalanced-biased data of a rare species complex of mountain vipers. Models were tuned up based on a range of model-specific parameters considering two background selection methods: random and background weighting schemes. The performance of the fine-tuned models was assessed based on recently identified localities of the species. The results indicated that although the fine-tuned version of all models shows great performance in predicting training data (AUC > 0.9 and TSS > 0.5), they produce different results in classifying out-of-bag data. The GBM and RF with higher sensitivity of training data showed more different performances. The GLM, despite having high predictive performance for test data, showed lower specificity. It was only the MaxEnt model that showed high predictive performance and comparable results for identifying test data in both random and background weighting procedures. Our results highlight that while GBM and RF are prone to overfitting training data and GLM over-predict nonsampled areas MaxEnt is capable of producing results that are both predictable (extrapolative) and complex (interpolative). We discuss the assumptions of each model and conclude that MaxEnt could be considered as a practical method to cope with imbalanced-biased data in species distribution modeling approaches.

Landscape features affect caiman body condition in the middle Araguaia River floodplain

AbstractLandscape modifications often undermine habitat suitability for species’ persistence, with initial effects observed through the physiological responses of individuals and populations. However, some landscape features can allow tolerant wildlife species to persist in human‐modified landscapes, but they are still overlooked. Across distinct agricultural landscapes, we assessed landscape features affecting the body condition (estimate through scaled mass index ‐ SMI) of Caiman crocodilus (Crocodylia, Alligatoridae) in human‐modified landscapes of the Araguaia floodplain, central Brazil. We used a spatial Bayesian model averaging approach to determine the effects of landscape attributes, ectoparasites, tail damage and severe body injuries on caiman body condition. We found that caimans had higher SMI in anthropogenic (ditches and artificial ponds) than natural habitats (lakes or rivers). Overall, caiman SMI was negatively associated with wetland cohesion (an aggregation and connectivity metric). Otherwise, landscape composition did not influence caiman SMI. Further, ectoparasites and body injuries did not affect SMI, whereas tail damage negatively affected SMI. Our findings underscore that caiman populations can adapt to artificial wetlands and irrigated rice fields, provided they incorporate natural and semi‐natural habitat patches that enhance environmental heterogeneity, prey availability, and waterbody availability and connectivity.

The hydroclimate niche: A tool for predicting and managing riparian plant community responses to streamflow seasonality

AbstractHabitat suitability is a consequence of interacting environmental factors. In riparian ecosystems, suitable plant habitat is influenced by interactions between stream hydrology and climate, hereafter referred to as “hydroclimate”. We tested the hypothesis that hydroclimate variables would improve the fit of ecological niche models for a suite of riparian species using occurrence data from the western United States. We focus on the climate conditions (temperature, precipitation and vapor pressure deficit) during the months of lowest and highest streamflow as integrative hydroclimate metrics of resource and stress levels. We found that the inclusion of hydroclimate variables improved model fit for all species in the western USA dataset. We then tested the utility of the improved habitat suitability models by projecting them onto a regulated segment of the Colorado River to assess potential impacts of streamflow seasonality on vegetation metrics of management concern. Species frequency derived from independent survey data in the Colorado River segment was significantly higher for species with predicted suitable habitat than for species without predicted suitable habitat. Under different simulated hydrographs for the Colorado River, overall species richness was predicted to be greatest with peak streamflows during summer, and native‐to‐non‐native species ratios were predicted to be greatest with lowest streamflows in winter. Summer high flows were particularly associated with higher predicted habitat suitability for species that have increased in cover over recent decades (e.g., Pluchea sericea, Baccharis species). We conclude that hydroclimate covariates can be useful tools for predicting how riparian vegetation communities respond to changes in the seasonal timing of low and high streamflows.

Predicting the habitat suitability for populations of Pacific cod under different climate change scenarios considering intraspecific genetic variation

Several studies have demonstrated the importance of integrating intraspecific genetic variation in forecasting the habitat suitability of species under climate change scenarios. The Pacific cod (Gadus macrocephalus) is an economically important fish species in the North Pacific that can be classified into western and eastern populations based on molecular phylogeographic data. Herein, we first quantified the realized niche of the two Pacific cod populations using n-dimensional hypervolumes and estimated the niche differentiation between the populations. We then projected the habitat suitability based on the georeferenced occurrence records and environmental predictors using species distribution models (SDMs) at the population and species levels. The low niche overlap demonstrated the marked niche differentiation between the two populations. The distinct responses of the populations to climate predictors implied that the population-level SDM produced more reliable projections than the corresponding species-level SDM. The model indicated that the eastern population expanded its suitable area northward, while maintaining most of its current habitat and exhibited resilience to climate impacts. However, the western population lost much of its current suitable area, while colonizing a new habitat in a small section of the offshore waters of the Japanese Sea, implying the vulnerability of this population to climate change. This study highlights the necessity of incorporating intraspecific genetic variation into SDMs to predict the habitat suitability of Pacific cod on the global scale. The spatiotemporal predictive maps of habitat suitability provide crucial information for designing climate-adaptive conservation and management strategies based on more precise taxonomic units for the sustainability of Pacific cod.

Potential global distribution of a temperate marine coastal predator: The role of barriers and dispersal corridors on subpopulation connectivity

AbstractPredicting the potential distribution of species and possible dispersal corridors at a global scale can contribute to better understanding the availability of suitable habitat to move between, and the potential connectivity between regional distributions. Such information increases knowledge of ecological and biogeographic processes, but also has management applications at a global scale, for example, for estimating the restocking ability of exploited regional subpopulations. As a case study, we tested the utility of environmental niche modeling to investigate the potential global distribution of a highly mobile temperate marine coastal species, the broadnose sevengill shark (Notorynchus cepedianus). First, we characterized and compared three model variants using global data and regional data from two geographically distant and genetically diverging subpopulations in the Southwest Atlantic and southern Australia. The best performing model was then transferred to the rest of the world to obtain a final global prediction for the species. Predictions revealed broad suitable areas across temperate regions of the Northern and Southern Hemispheres. As a final step, we overlaid underwater seamount data on suitability maps to simulate possible dispersal corridors and regional connectivity. Global subpopulation connectivity and dispersal are discussed in the light of recent genetic evidence, to help explain why unoccupied suitable areas are not currently accessed by the species. This study highlights the potential use of global and regional data for the assessment of habitat suitability of species at a global scale, and provides considerations when applying these models to other highly mobile species.

Predicting the suitable habitats of parasitic desert species based on a niche model with Haloxylon ammodendron and Cistanche deserticola as examples.

Haloxylon ammodendron, an excellent tree species for sand fixation and afforestation in the desert areas of western China, is threatened by climate change and anthropogenic activities. The suitable habitat of this species is shrinking at a remarkable rate, although conservation measures have been implemented. Cistanche deserticola is an entirely parasitic herb that occurs in deserts, is a source of “desert ginseng” worldwide, and has extremely high medicinal value. Little is known about using niche models to simulate habitat suitability and evaluate important environmental variables related to parasitic species. In this study, we modeled the current suitable habitat of H. ammodendron and C. deserticola by MaxEnt based on occurrence record data of the distributions of these two species in China. We grouped H. ammodendron and C. deserticola into three groups according to the characteristics of parasitic species and modeled them with environmental factors. The results showed that bioclimate was the most important environmental parameter affecting the H. ammodendron and C. deserticola distribution. Precipitations, such as annual precipitation, precipitation seasonality, and precipitation in the driest quarter, were identified as the most critical parameters. The slope, diurnal temperature range, water vapor pressure, ground‐frost frequency, and solar radiation also substantially contributed to the distribution of the two species. The proportions of the most suitable areas for Groups 1, 2, and 3 were 1.2%, 1.3%, and 1.7%, respectively, in China. When combined with cultural geography, five hot spot conservation areas were determined within the distribution of H. ammodendron and C. deserticola. The comprehensive analysis indicated that by using MaxEnt to model the suitable habitat of parasitic species, we further improved the accuracy of the prediction and coupled the error of the distribution of a single species. This study provides a useful reference for the protection of H. ammodendron forests and the management of C. deserticola plantations.

Climate change impact on the distribution of Tossa jute using maximum entropy and educational global climate modelling

AbstractTossa (Corchorus olitorius L.) is a significant cash crop, cultivated commercially in the lower flood plain of Bangladesh. The climatic regimes in Bangladesh are changing as well as the world does. However, this species is threatened by climate change. Occurrences of data on threatened and endangered species are frequently sparse which makes it difficult to analyse the species suitable habitat distribution using various modelling approaches. The current paper used maximum entropy (Maxent) and educational global climate model (EdGCM) modelling to predict and conserve the suitable habitat distributions for Tossa species in Bangladesh to the year 2100. Nine environmental variables, 239 occurrence data and two Representative Concentration Pathway scenarios (RCP4.5 and RCP8.5) were used for the Maxent modelling to project the impact of climate change on the Tossa distributions. Furthermore, the EdGCM was used to study the climatic space suitability for the Tossa species in the context of Bangladesh. Both of the climatic scenarios were used for the prediction to the year 2100. The Maxent model performed better than random for the Tossa species with a high AUC value of 0.86. Under the RCP scenarios, the Maxent model predicted habitat reduction for RCP4.5 is 2%, RCP8.5 is 9% and EdGCM is 10.2% from the current localities. The predictive modelling approach presented here is promising and can be applied to other important species for conservation planning, monitoring and management, especially those under the threat of extinction due to climate change.

Modeling habitat suitability of the Red-backed Shrike (Lanius collurio) in the Irano-Anatolian biodiversity hotspot

Identifying suitable habitats of species is essential knowledge to conserve them successfully. Human activities causes the reduction of population size and habitat suitability of many species. Red-backed Shrike is a widespread in western Palearctic. However, the population of this specie has declined in its geographical range due to the loss of suitable habitats. Therefore, it is necessary to identify its suitable habitats and factors affecting species habitat suitability and to protect its reduction population size. The aim of the present study was to identify the suitable habitat of the Red-backed Shrike and determine the most important predictors of its suitable habitat in Irano-Anatolian biodiversity hotspot. To achieve this goal, species presence points were first collected and seven environmental variables related to climate, topography and anthropogenic activities, were used to construct the species habitat suitable model. Models were built using five distribution modeling methods: Maxent, GAP, GLM, RF and GBM in sdm package. Then the models were Ensemble from 5 different models and the final model was constructed. The results of this study showed that the most suitable habitats of this species are in the western and northern parts of the area of study. The mean annual temperature with 41% contribution was the most important variable in constructing the habitat suitability model for this specie. In addition, climate variables with 75% contribution were identified as the most important habitat suitability factor for this specie. Also in relation to conservation of the Red-backed Shrike species in the Irano-Anatolian region, it can be stated that the extent of distribution and presence of this specie has been extended to the northern latitudes due to climate change. As a result, the temperature and climate factor should be given special attention in the management of bird habitats in this area.

Modeling the distribution and movement intensity of the Arabian Leopard Panthera pardus nimr (Mammalia: Felidae)

This study attempts to link the distribution and movement rate of the critically endangered Arabian Leopard (Panthera pardus nimr) to environmental and anthropogenic features, and to identify environmental constraints and priority areas for the recovery of leopard in Arabian Peninsula. Generalized linear and additive models were used to fit leopard presence/absence locations to environmental and anthropogenic variables. Movement rates between the polygons of modeled leopard presence were inferred and mapped using the isolation-by-resistance model, where probability values of the species distribution model were treated as those of conductance. Our results suggest that currently the Arabian Leopard prefers to live and move in terrain that has high values of normalized difference vegetation index (NDVI) and is difficult for humans to reach. The current network of protected areas largely under-represents the species suitable habitat only covering its 11%, and most of the survey effort to detect and ensure the survival of the leopard in the peninsula has taken place outside the polygons identified by our models as core areas for the species. Our models coupled with existing data suggest the following scenario of the species biogeography: The Arabian Leopard accumulated genetic and phenotypic differences from its conspecifics at a series of glacial maxima during the last glacial period in the Yemeni refugium, from where it expanded elsewhere in the Holocene warming following the expansion of suitable landscape types. Humans expanded too, eventually restricting the source populations of the leopard to an area intersecting eastern Yemen and western Oman today. Our models may serve as a tool for planning future research and conservation for Arabian Leopard.

Embracing Ensemble Species Distribution Models to Inform At-Risk Species Status Assessments

AbstractConservation planning depends on reliable information regarding the geographic distribution of species. However, our knowledge of species' distributions is often incomplete, especially when species are cryptic, difficult to survey, or rare. The use of species distribution models has increased in recent years and proven a valuable tool to evaluate habitat suitability for species. However, practitioners have yet to fully adopt the potential of species distribution models to inform conservation efforts for information-limited species. Here, we describe a species distribution modeling approach for at-risk species that could better inform U.S. Fish and Wildlife Service's species status assessments and help facilitate conservation decisions. We applied four modeling techniques (generalized additive, maximum entropy, generalized boosted, and weighted ensemble) to occurrence data for four at-risk species proposed for listing under the U.S. Endangered Species Act (Papaipema eryngii, Macbridea caroliniana, Scutellaria ocmulgee, and Balduina atropurpurea) in the Southeastern United States. The use of ensemble models reduced uncertainty caused by differences among modeling techniques, with a consequent improvement of predictive accuracy of fitted models. Incorporating an ensemble modeling approach into species status assessments and similar frameworks is likely to benefit survey efforts, inform recovery activities, and provide more robust status assessments for at-risk species. We emphasize that co-producing species distribution models in close collaboration with species experts has the potential to provide better calibration data and model refinements, which could ultimately improve reliance and use of model outputs.

Future habitat suitability for species under climate change – Lessons learned from the strawberry tree case study

Climate change is already a reality, and habitat loss is affecting relentlessly tree species distributions. The strawberry tree (Arbutus unedo L., Ericaceae) is a Mediterranean evergreen tree used in this article as a case study to evince its expected threatening situation in the upcoming age. This research work seeks to identify the bioclimatic and physiographic variables that have the most impact on the strawberry tree’s spatial distribution in Portugal, acquiring vital knowledge for the design of accurate conservation and afforestation plans for the use and conservation of strawberry tree, working as a guide under a climate change scenario. For that, twenty-one bioclimatic variables, two physiographic attributes (altitude and slope), and the Emberger Index (EI) were used together with 318 observations of strawberry trees, to build a scalable Bayesian procedure, based on machine learning techniques, aimed to assess the species’ future habitat evolution through three temporal scenarios: (i) Control Run (1960–1990); (ii) 2050 and (iii) 2070. The results indicate for 2050 a 30% loss of the humid sub-region and a 35% increase in the semi-arid sub-region towards the north. In 2070, it is expected a 2% recuperation for the sub-humid area, but an 8% loss of the humid sub-area. Under these extreme climate change conditions, it is anticipated an almost complete loss of habitat for the strawberry tree in the south of Portugal. The expected ecological evolvability may trigger future migration paths and new refuges’ settlement in the northern sub-region for the succeeding decades and suggesting after 2070 the possibility of habitat switch and species drifting.

Research on a Biodiversity Conservation Value Assessment Method Based on Habitat Suitability of Species: A Case Study in Gansu Province, China

Quantitative assessment and evaluation of ecological parameters and biodiversity conservation are prime concerns for long-term conservation of rare and endangered species and their associated habitats in any ecological region. In this study, Gansu Province, a biodiversity hotspot, was chosen as the research area. We predicted the distribution patterns of suitable habitats for rare and endangered species. The replacement cost method was adopted to calculate the conservation value of rare and endangered species. The suitable habitat distribution area of rare and endangered wild animals reached 351,607.76 km2 (without overlapping area), while that of plants reached 72,988.12 km2 (without overlapping area). The conservation value of rare and endangered wildlife is US $1670.00 million. The high-value areas are mostly concentrated in the south and north of Gansu Province. The conservation value of rare and endangered wild plants is US $56,920.00 million. The high-value areas are mostly concentrated south of Gansu Province. The conservation value is US $58,590.00 million a year, and its distribution trend is gradually decreasing from northeast to southwest, with the highest in the forest area south of Gansu Province, followed by the Qilian Mountain area in the north. These results are of great significance for future improvement of the evaluation index system of ecosystem services and the development of ecosystem services and management strategies.

Cetacean habitat modelling to inform conservation management, marine spatial planning, and as a basis for anthropogenic threat mitigation in Indonesia

Indonesia harbours a high diversity of cetaceans, yet effective conservation is hampered by a lack of knowledge about cetacean spatial distribution and habitat preferences. This study aimed to address this knowledge gap at an adequate resolution to support national cetacean conservation and management planning. Maximum Entropy (Maxent) modelling was used to map the distribution of 15 selected cetacean species in seven areas within Indonesian waters using recent cetacean presence datasets as well as environmental predictors (topographic and oceanographic variables). We then combined the individual species suitable habitat maps and overlaid them with provincial marine spatial planning (MSP) jurisdictions, marine protected areas (MPAs), oil and gas contract areas, and marine traffic density. Our results reflect a great heterogeneity in distribution among species and within species among different locations. This heterogeneity reflects an interrelated influence of topographic variables and oceanographic processes on the distribution of cetacean species. Bathymetry, distance to- coast and the −200m isobaths, and chlorophyll-a concentration and sea surface temperature were important variables influencing distribution of most species in many regions. Areas rich in species were mainly related to coastal areas or insular-reef complexity, representing high productivity and upwelling-modified waters. Although some important suitable habitats currently fall within MPAs, other areas are not and overlap with oil and gas exploration activities and marine traffic, indicating potentially high risk areas for cetaceans. The results of this study can support national cetacean conservation and management planning, and be used to reduce or avoid adverse anthropogenic threats. We advise to consider currently unprotected suitable cetacean habitats in MPA and MSP development.

Support for a relationship between demography and modeled habitat suitability is scale dependent for the purple martin Progne subis.

Species distribution models (SDMs) estimate habitat suitability for species in geographic space. They are extensively used in conservation under the assumption that there is a positive relationship between habitat suitability and species success and stability. Given the difficulties in obtaining demographic data across a species' range, this assumption is rarely tested. Here we provide a range-wide test of this relationship for the eastern subspecies of purple martin Progne subis subis. We build a well-supported SDM for the breeding range of the purple martin, and pair it with an unparalleled demographic dataset of nest success and local and regional abundance data for the species to test the proposed link between habitat suitability and fecundity and demography. We find a positive relationship between regional abundance and habitat suitability but no relationship between local abundance or fecundity and habitat suitability. Our data suggest that local success is driven largely by biotic and stochastic factors and raise the possibility that purple martins are experiencing a time lag in their distribution. More broadly our results call for caution in how we interpret SDMs and do not support the assumption that areas of high habitat suitability are the best areas for species persistence.

Evolutionary history and eco‐climatic diversification in southern African dung beetle Sisyphus

AbstractAimThe high diversity of species in southern Africa has been attributed to geological and palaeoclimatic factors. The timing of radiations in some groups is held to be linked to these geoclimatic trends. Using the Scarabaeinae dung beetle genus, Sisyphus, as a model system, we investigate how geological uplift and climatic changes in the late Cenozoic affected its diversification patterns in southern Africa.LocationSouthern Africa.TaxonThe dung beetle genus, Sisyphus Latreille, 1807 (Coleoptera: Scarabaeidae: Scarabaeinae).MethodsA dated molecular phylogeny of southern African Sisyphus was compared with a factor analysis of species distribution data that statistically defined groups of species according to current climatic distribution. We used these climatic clusters to estimate ancestral ranges using the “BioGeoBEARS” R package. A lineage through time plot was calculated using the R package ‘APE’. We used Bayesian diversification models (compound Poisson process on mass extinction times) to test hypotheses on how late Cenozoic uplift and climatic changes affected speciation and extinction of Sisyphus. Furthermore, we implemented ecological niche modelling in MaxEnt to predict the habitat suitability of species under present climatic conditions.ResultsFour species groups defined from factor analysis of current climatic distribution data are primarily restricted to the moist summer rainfall region in the northeast. Species diversification occurred from the mid‐Miocene until the Pleistocene, during which the central southern African plateau was uplifted in tandem with the advent of winter rainfall and arid climatic zones to the southwest. The ancestor of Sisyphus was centred in eastern low to mid‐altitude areas. Speciation rates were higher in the Miocene to Pliocene, followed by a dramatic drop during the transition to the Pleistocene.Main conclusionsThe taxonomic and eco‐climatic diversification of sisyphines is coincident with geological uplift and changes in climate in east‐central southern Africa. However, phylogenetic relationships of southern African Sisyphus species are not homogenously distributed with respect to geography and climate.