Ecological niche modelling of the distribution of cold-water coral habitat using underwater remote sensing data

Despite a growing appreciation of the need to protect sensitive deep sea ecosystems such as cold-water corals, efforts to map the extent of their distribution are limited by their remoteness. Here we develop ecological niche models to predict the likely distributions of cold-water corals based on occurrence records and data describing environmental parameters (e.g. seafloor terrain attributes and oceanographic conditions). This study has used bathymetric data derived from ship-borne multibeam swath systems, species occurrence data from remotely operated vehicle video surveys and oceanographic parameters from hydrodynamic models to predict coral locations in regions where there is a paucity of direct observations. Predictions of the locations of the scleractinian coral, Lophelia pertusa are based primarily upon ecological niche modelling using a genetic algorithm. Its accuracy has been quantified at local (~ 25 km²) and regional scales (~ 4000 km²) along the Irish continental slope using a variety of error assessment techniques and a comparison with another ecological niche modelling technique. With appropriate choices of parameters and scales of analyses, ecological niche modelling has been effective in predicting the distributions of species at local and regional scales. Refinements of this approach have the potential to be particularly useful for ocean management given the need to manage areas of sensitive habitat where survey data are often limited.     

Using Landscape and Bioclimatic Features to Predict the Distribution of Lions,Leopards and Spotted Hyaenas in Tanzania's Ruaha Landscape

Tanzania''s Ruaha landscape is an international priority area for large carnivores, supporting over 10% of the world''s lions and important populations of leopards and spotted hyaenas. However, lack of ecological data on large carnivore distribution and habitat use hinders the development of effective carnivore conservation strategies in this critical landscape. Therefore, the study aimed to (i) identify the most significant ecogeographical variables influencing the potential distribution of lions, leopards and spotted hyaenas across the Ruaha landscape; (ii) identify zones with highest suitability for harbouring those species; and (iii) use species distribution modelling algorithms (SDMs) to define important areas for conservation of large carnivores. Habitat suitability was calculated based on environmental features from georeferenced presence-only carnivore location data. Potential distribution of large carnivores appeared to be strongly influenced by water availability; highly suitable areas were situated close to rivers and experienced above average annual precipitation. Net primary productivity and tree cover also exerted some influence on habitat suitability. All three species showed relatively narrow niche breadth and low tolerance to changes in habitat characteristics. From 21,050 km² assessed, 8.1% (1,702 km²) emerged as highly suitable for all three large carnivores collectively. Of that area, 95.4% (1,624 km²) was located within 30 km of the Park-village border, raising concerns about human-carnivore conflict. This was of particular concern for spotted hyaenas, as they were located significantly closer to the Park boundary than lions and leopards. This study provides the first map of potential carnivore distribution across the globally important Ruaha landscape, and demonstrates that SDMs can be effective for understanding large carnivore habitat requirements in poorly sampled areas. This approach could have relevance for many other important wildlife areas that only have limited, haphazard presence-only data, but which urgently require strategic conservation planning.     

Unveiling the Conservation Biogeography of a Data-Deficient Endangered Bird Species under Climate Change

It remains a challenge to identify the geographical patterns and underlying environmental associations of species with unique ecological niches and distinct behaviors. This in turn hinders our understanding of the ecology as well as effective conservation management of threatened species. The white-eared night heron (Gorsachius magnificus) is a non-migratory nocturnal bird species that has a patchy distribution in the mountainous forests of East Asia. It is currently categorized as “Endangered” on the IUCN Red List, primarily due to its restricted range and fragmented habitat. To improve our knowledge of the biogeography and conservation of this species, we modeled the geographical pattern of its suitable habitat and evaluated the potential impacts of climate change using ecological niche modeling with a maximum entropy approach implemented in Maxent. Our results indicated that the amount of suitable habitat in all of East Asia was about 130 000 km², which can be spatially subdivided into several mountain ranges in southern and southwestern China and northern Vietnam. The extent of suitable habitat range may shrink by more than 35% under a predicted changing climate when assuming the most pessimistic condition of dispersal, while some more suitable habitat would be available if the heron could disperse unrestrainedly. The significant future changes in habitat suitability suggested for Gorsachius magnificus urge caution in any downgrading of Red List status that may be considered. Our results also discern potentially suitable areas for future survey efforts on new populations. Overall, this study demonstrates that ecological niche modeling offers an important tool for evaluating the habitat suitability and potential impacts of climate change on an enigmatic and endangered species based on limited presence data.     

大型野生食草动物生境资源利用竞争关系

生物多样性维持是三江源区的重要生态功能,野生动物保护的科学规划需要掌握区内野生动物的栖息地分布状况与资源竞争关系。利用无人机遥感的新技术,在三江源玛多县开展藏野驴、藏原羚和岩羊的适宜栖息地识别与划定以及生境资源利用竞争关系研究。结果显示,2017年玛多县藏野驴适宜生境面积3559.43 km²,距水源距离是限制适宜生境面积的主要因子;藏原羚的适宜生境面积为283.76 km²,岩羊的适宜生境面积为29.97 km²,坡度、距水源距离以及植被类型是制约适宜栖息地面积的主要因素。由于在栖息地坡度选择中的生态位差异,三种大型野生食草动物的生境重叠面积均较小,生境竞争关系较弱。研究为生物多样性保护提供了全新的思路,可为相似区域的野生动物保护与恢复综合规划提供支撑。     

Identifying the habitat suitability and built-in corridors for Asiatic black bear (Ursus thibetanus) movement in the northern highlands of Pakistan

Identifying habitat suitability and potential corridors are important tools for biodiversity conservation in the face of climate change. We modeled habitat suitability and simulated possible corridors for movement and gene flow among the Asiatic black bear (Ursus thibetanus) population in the Northern Highlands of Pakistan (NHP). Results indicated that the areas of 13,923 km² and 21,931 km² suitable for the Asiatic black bear under current and future scenarios respectively. Under the future scenario, we found an area of 12,657 km² (57.21%) as increase in suitable habitat (ISH_f) and 4649 km² (33.39%) area as a decrease in current suitable habitat (DSH_c). Our model predicted that about >65% (9274 km²) of the current suitable habitat as a climate refugia which is projected from the center to southeast east and northwest of the NHP primarily in the Khyber Pakhtunkhwa (KPK) and Pakistan Administered Kashmir (PAK). The attitudinal range of refugia was projected from 688 m to 4483 m with >56% at the elevations between 2001 m to 3000 m. A very small portion of suitable habitats (current suitable habitat = 2.75%, future suitable habitat = 5.11%) were projected under the protected areas. Maps connecting suitable habitats identified different regions delineated as important for the dispersal of Asiatic black bears, which mainly distributed in the PAK and KPK. Our results help informs conservation strategies and management plans for mitigating the impacts of climate change on Asiatic black bears in the NHP.     

Integrating aspects of ecology and predictive modelling: implications for the conservation of the leopard cat (Prionailurus bengalensis) in the Eastern Himalaya

An understanding of species ecology is vital for effective conservation, particularly if the species forms an important constituent of the lesser mammal guild and regulates small mammal and bird populations. As the ecological role of the leopard cat (Prionailurus bengalensis) in the intricate eastern Himalayan habitats is not known, we assessed the site occupancy, detection probability and activity pattern of leopard cats in Khangchendzonga Biosphere Reserve, India, based on sign surveys and camera trapping. The estimated site occupancy was 0.352?±?0.061 and detection probability was 0.143?±?0.0484. Occupancy modelling indicated low elevation, high rodent abundance and tree cover as best predictors for the occupancy of leopard cat. Diet based on analysed scats revealed murids as the most dominant prey (89.2 %). Information based on photographic captures indicated that the leopard cat exhibited a nocturnal activity pattern (peak activity between 0200–0300 hours), which coincided with its principal prey (revealed through diet analysis), but mainly contradicted with other sympatric competitors, hence indicating a temporal partitioning of resources among them. Ecological niche factor analysis indicated that the leopard cat exhibits high global marginality (1.32) and low global tolerance (0.275). The habitat suitability map for leopard cats showed majority of the habitat as unsuitable (1,959.44 km²) and predicted only 164.54 km² areas of lower temperate forests as moderate to highly suitable. As highly suitable habitats of the leopard cat are in close proximity to villages, conflict issues are a major threat and therefore need to be addressed in conservation program for this felid.     

Identifying climate refugia and its potential impact on Tibetan brown bear (Ursus arctos pruinosus) in Sanjiangyuan National Park,China

Climate change has direct impacts on wildlife and future biodiversity protection efforts. Vulnerability assessment and habitat connectivity analyses are necessary for drafting effective conservation strategies for threatened species such as the Tibetan brown bear (Ursus arctos pruinosus). We used the maximum entropy (MaxEnt) model to assess the current (1950–2000) and future (2041–2060) habitat suitability by combining bioclimatic and environmental variables, and identified potential climate refugia for Tibetan brown bears in Sanjiangyuan National Park, China. Next, we selected Circuit model to simulate potential migration paths based on current and future climatically suitable habitat. Results indicate a total area of potential suitable habitat under the current climate scenario of approximately 31,649.46 km², of which 28,778.29 km² would be unsuitable by the 2050s. Potentially suitable habitat under the future climate scenario was projected to cover an area of 23,738.6 km². Climate refugia occupied 2,871.17 km², primarily in the midwestern and northeastern regions of Yangtze River Zone, as well as the northern region of Yellow River Zone. The altitude of climate refugia ranged from 4,307 to 5,524 m, with 52.93% lying at altitudes between 4,300 and 4,600 m. Refugia were mainly distributed on bare rock, alpine steppe, and alpine meadow. Corridors linking areas of potentially suitable brown bear habitat and a substantial portion of paths with low‐resistance value were distributed in climate refugia. We recommend various actions to ameliorate the impact of climate change on brown bears, such as protecting climatically suitable habitat, establishing habitat corridors, restructuring conservation areas, and strengthening monitoring efforts.     

Unravelling the response of diurnal raptors to land use change in a highly dynamic landscape in northwestern Spain: an approach based on satellite earth observation data

Land use and land cover change (LULCC) is one of the main components of current anthropogenic global change. Unravelling the ecological response of biodiversity to the combined effect of land use change and other stressors is essential for effective conservation. For this purpose, we used co-inertia analysis to combine LULCC analysis of earth observation satellite data-derived maps and raptor data obtained from road censuses conducted in 2001 and 2014 at sampling unit level (10 km² spatial resolution), in northwestern Spain (province of Ourense, c. 7281 km²). In addition, habitat suitability models were also computed using ten widely used single-modelling techniques providing an ensemble of predictions at landscape level (four spatial resolutions: 500-m, 1-km, 2-km and 5-km radius around each sighting) for each year and raptor species to analyse the habitat suitability changes in the whole study area through three niche overlap indices. The models revealed an increase in occurrence and habitat suitability of forest raptor species coupled with a strong decrease in species associated with open habitats, mainly heaths and shrub formations. Open-habitat specialist species were negatively affected by the concomitant effects of intensive forest management and a long-lasting trend of rural abandonment coupled with an unusually high frequency of wildfires. Sustainable forest management and agricultural practices should be encouraged by both public and private sectors, through, e.g. policies related to European funds for rural and regional development (FEDER and FEADER programs) to effectively protect threatened habitats and species, and to comply with current environmental legislation. The combined use of satellite imagery and ground-level biodiversity data proved to be a cost-effective and systematic method for monitoring priority habitats and their species in highly dynamic landscapes.     

Global Habitat Suitability and Ecological Niche Separation in the Phylum Placozoa

The enigmatic placozoans, which hold a key position in the metazoan Tree of Life, have attracted substantial attention in many areas of biological and biomedical research. While placozoans have become an emerging model system, their ecology and particularly biogeography remain widely unknown. In this study, we use modelling approaches to explore habitat preferences, and distribution pattern of the placozoans phylum. We provide hypotheses for discrete ecological niche separation between genetic placozoan lineages, which may also help to understand biogeography patterns in other small marine invertebrates. We, here, used maximum entropy modelling to predict placozoan distribution using 20 environmental grids of 9.2 km² resolution. In addition, we used recently developed metrics of niche overlap to compare habitat suitability models of three genetic clades. The predicted distributions range from 55°N to 44°S and are restricted to regions of intermediate to warm sea surface temperatures. High concentrations of salinity and low nutrient concentrations appear as secondary factors. Tests of niche equivalency reveal the largest differences between placozoan clades I and III. Interestingly, the genetically well-separated clades I and V appear to be ecologically very similar. Our habitat suitability models predict a wider latitudinal distribution for placozoans, than currently described, especially in the northern hemisphere. With respect to biogeography modelling, placozoans show patterns somewhere between higher metazoan taxa and marine microorganisms, with the first group usually showing complex biogeographies and the second usually showing “no biogeography.”     

Predicting potential distribution and identifying priority areas for conservation of the lowland tapir (Tapirus terrestris) in Peruvian Amazon

A key conservation biology tool is the information on the geographic distribution of species as well as the variables driving those patterns. Here, we used maximum entropy modeling, MaxEnt, to model the total potential distribution of Tapirus terrestris, classified as “Vulnerable” on the IUCN Red List of Threatened Species. In this study, we recorded 117 occurrence records and considered 18 environmental variables. The total potential distribution area covers 96,055.6 km², meaning 12.3 % of the territory of the Peruvian Amazon, with “high potential” habitat covering 3,891.36 km², “moderate potential” habitat covering 22,849.5 km², and “low potential” habitat covering 69,314.7 km². Natural Protected Areas (NPAs) shelter 32.2 % (30,966.2 km²) of the total potential distribution area of the species, being the Bahuaja Sonene and Manu National Parks, the NPAs with the largest total potential distribution, 8,220.2 km² and 7,619.7 km² respectively. Eventually, 67.8 % (65,089.4 km²) of the total potential distribution were identified without any type of protection category by SINANPE and its complementary categories; therefore, we consider this area as a priority for the conservation of T. terrestris in Peru.     

Density and Spatial Distribution of Buffy-tufted-ear Marmosets (<Emphasis Type="Italic">Callithrix aurita</Emphasis>) in a Continuous Atlantic Forest

The continued degradation of forest habitats and isolation of fragmented populations means that the conservation of endemic marmosets in the Brazilian Atlantic forest depends on human interventions including legal protection. Population monitoring is required to ensure effective management and appropriate allocation of conservation resources; however, deriving estimates of population metrics such as density within heterogeneous environments is challenging. We aimed to quantify the population density and spatial distribution of buffy-tufted-ear marmosets (Callithrix aurita) in the northern region of Serra-do-Mar State Park. We incorporated habitat suitability as quantified by a niche modeling algorithm (MAXENT) to refine density estimates obtained via distance methods. We used 6 environmental predictors to model the distribution of Callithrix aurita and used the resulting MAXENT niche model to identify environmental conditions that represent suitable habitat for this species. We used 877.7 km of line transect surveys and distance methods to derive estimates of 2.19 groups or 7.55 individuals/km² from direct observations (n = 40), providing an overall population estimate of 1892 (95% CI = 1155–3068) individuals in 250.7 km² of Atlantic forest. Our refined density estimate, obtained by combining distance methods and a niche model, yielded a result of 1386 individuals. Suitable habitat was not uniformly distributed across the study area and was most strongly associated with altitude and the type of vegetation cover. We provide a review of previous surveys and find this is the largest known population of Callithrix aurita. Our refinement of density estimates provides a simple and informative addition to the primatologist’s toolbox.     

Potential distribution of Notopterygium incisum Ting ex H. T. Chang and its predicted responses to climate change based on a comprehensive habitat suitability model

Notopterygium incisum Ting ex H. T. Chang is a rare and endangered traditional Chinese medicinal plant. In this research, we built a comprehensive habitat suitability (CHS) model to analyze the potential suitable habitat distribution of this species in the present and future in China. First, using nine different algorithms, we built an ensemble model to explore the possible impacts of climate change on the habitat distribution of this species. Then, based on this model, we built a CHS model to further identify the distribution characteristics of N. incisum‐suitable habitats in three time periods (current, 2050s, and 2070s) while considering the effects of soil and vegetation conditions. The results indicated that the current suitable habitat for N. incisum covers approximately 83.76 × 10³ km², and these locations were concentrated in the Tibet Autonomous Region, Gansu Province, Qinghai Province, and Sichuan Province. In the future, the areas of suitable habitat for N. incisum would significantly decrease and would be 69.53 × 10³ km² and 60.21 × 10³ km² in the 2050s and 2070s, respectively. However, the area of marginally suitable habitat would remain relatively stable. This study provides a more reliable and comprehensive method for modelling the current and future distributions of N. incisum, and it provides valuable insights for highlighting priority areas for medicinal plant conservation and resource utilization.     

Integrating individual habitat choices and regional distribution of a biodiversity indicator and top predator

Aim Habitat selection studies have mainly focused on behavioural choices of individuals or on the habitat‐related regional distribution of a population, with little integration of the two approaches. This is despite the fact that traditional biogeography theory sees the geographical distribution of a species as the collective outcome of the adaptive habitat choices of individuals. Here, we integrate individual habitat choices with regional distribution through a bottom‐up Geographical Information System (GIS)‐based approach, by using a 9‐year data set on a large avian predator, the eagle owl (Bubo bubo L.). We further examine the potential population level and biodiversity consequences of this approach. Location The study was conducted in the Trento Region (central‐eastern Italian Alps) and in six other areas of the nearby Lombardia Region in the central Alps. Methods We used stepwise logistic regression to build a habitat suitability model discriminating between eagle owl territories and an equal number of random locations. The model was applied to the whole Trento region by means of a GIS so as to predict suitable habitat patches. The predicted regional distribution (presence–absence in 10‐km grid quadrats) was then compared with the observed one. Furthermore, we compared estimates of biodiversity in quadrats with and without eagle owls, so as to test whether the presence of this top predator may signal macro‐areas of high biodiversity. Results The logistic habitat suitability model showed that, compared with a random distribution, eagle owls selected low‐elevation breeding sites with high availability of prey‐rich habitats in their surroundings. Breeding performance increased with the availability of prey‐rich habitats, confirming the adaptiveness of the detected habitat choices. We applied the habitat suitability model to the 6200 km² study region by means of a GIS and found a close fit between the observed and predicted regional distribution. Furthermore, population abundance was positively related to the availability of habitat defined as suitable by the above analyses. Finally, high biodiversity levels were associated with owl presence and with the amount of suitable owl habitat, demonstrating that modelling habitat suitability of a properly chosen indicator species may provide key conservation information at the wider ecosystem level. Main conclusions Our bottom‐up modelling approach may increase the conservation‐value of habitat selection models, by (1) predicting local and regional distribution, (2) estimating regional population size, (3) stimulating further hypothesis testing, (4) forecasting the population effects of future habitat loss and degradation and (5) aiding in the identification and prioritization of high‐biodiversity areas.     

Modelling benthic habitats and biotopes off the coast of Norway to support spatial management

Habitat conservation, and hence conservation of biodiversity hinges on knowledge of the spatial distribution of habitats, not least those that are particularly valuable or vulnerable. In offshore Norway, benthic habitats are systematically surveyed and described by the national programme MAREANO (Marine AREAl database for NOrwegian waters). Benthic habitats and biotopes are defined in terms of the species composition of their epibenthic megafauna. Some habitats are of special conservation interest on account of their intrinsic value and/or vulnerability (e.g., long-lived species, rareness, to comply with international regulations such as OSPAR). In Norway, off Nordland and Troms, the following habitats of special interest can be found: Umbellula encrinus Stands, Radicipes sp. Meadows, Deep Sea Sponge Aggregations, Seapen and Burrowing Megafauna Communities, Hard Bottom Coral Gardens. In this paper, we used underwater video data collected within the MAREANO programme to define and describe benthic habitats and biotopes of special interest, and to map the geographic distribution thereof by means of habitat modelling.We first evaluated the community structure of each habitat in the list using a SIMPROF test. We determined that the class Deep Sea Sponge Aggregations, as defined by OSPAR, had to be split into at least three classes. We then re-defined seven new types of ecological features, including habitats and biotopes that were sufficiently homogeneous. Then we modelled the spatial distributions of these habitats and biotopes using Conditional Inference Forests. Since the purpose of the distribution maps is to support spatial planning we classified the heat maps using density thresholds.The accuracy of models ranged from fair to excellent. Hard Bottom Coral Gardens were the most rare habitat in terms of total area predicted (224 km², 0.3% of the area modelled), closely followed by Radicipes Meadows (391 km², 0.6%). Soft Bottom Demosponges (Geodid sponges and other taxa) represent the largest habitat, with a predicted area of 9288 km² (14%). Distribution maps of classes defined by habitat-forming species (Hard Bottom Coral Gardens) were more reliable than those defined by a host of species, or where no single species was a clear habitat provider (e.g. Seapen and Burrowing Megafauna Communities). We also put forward that a scale of patchiness larger than the scale of observation, and homogeneity of the community both play a role in model performance, and hence in map usefulness. These along with density threshold values based on observed data should all be taken into account in marine classifications and habitat definitions.     

Population status and distribution modelling of the critically endangered riverine rabbit (Bunolagus monticularis)

The riverine rabbit (Bunolagus monticularis) is one of the most endangered mammals in the world due to fragmentation of its habitat in the semi‐arid Karoo region of South Africa, to which it is endemic. It is an umbrella conservation species for the riparian shrubland associated with the seasonal drainage system of the Karoo, where its presence is an indicator of ecosystem health. In this study, we analysed historical survey data to derive an improved assessment of the current B. monticularis population status and distribution. Geospatial analysis was conducted using geographical information systems, and distribution modelling was performed using Maxent. Extent of occurrence for the species is 54,227 km², and area of occupancy is 2943 km². Estimates of 157–207 mature individuals confirm an alarmingly small species population size, and it appears that no subpopulation has >50 mature individuals. Our findings thus support the continued classification of this species as ‘critically endangered’ under IUCN Red List criteria. However, with most remaining habitat occurring outside of protected areas, and with habitat loss being exacerbated by climate change, a viable conservation plan remains elusive.     

Predictive mapping of two endemic oak tree species under climate change scenarios in a semiarid region: Range overlap and implications for conservation

Quercus infectoria and Quercus libani are two important species distributed across most of the Kurdistan Region of Iraq's mountain ranges (KRI). They have significant ecological, medicinal, and socioeconomic values. Recent studies have documented how plant distributions have been impacted by climate change. This study's goal is to establish the existing distributions of both species, measure the consequences of prospective environmental conditions on their distributions, predict possible habitat distributions, map the overlapped habitat ranges for the species in the KRI, and identify the key factors influencing their distributions. For these aims, distribution data points of the species, different environmental factors, including the existing climate, three emission predictions for the 2050s, 2070s, and 2090s of two general circulation models (GCMs), a machine learning approach, and geospatial techniques were used. Modeling revealed that the total magnitude of the habitat increase for the species would be less than the overall magnitude of the habitat contraction. The yearly mean temperature, yearly precipitation, and minimum temperature during the coldest period mostly alter the target species' geographic dispersion. Across the three emission scenarios of the both models, Q. infectoria habitat would contract by 2760.9–2856.9 km² (5.36–5.55%), 2856.9–3357.2 km² (5.55–6.52%) and 2822.1–3400.2 km² (5.48–6.60%), whereas it would expand by 1153.3–1638.9 km² (2.24–3.18%), 761.0–1556.8 km² (1.48–3.02%), and 721.5–1547.1 km² (1.40–3.00%) for the 2050s, 2070s, and 2090s, respectively. A similar pattern was also noted for Q. libani. The two species' habitat ranges in KRI would be considerably reduced due to climate change. The species' estimated area would extend mostly to the east and southeast of the KRI at high altitudes. The mountain areas, notably those where the species overlap by 1767.2–1807.5 km² (3.43–3.51%) for the two GCMs, must be the primary objective of conservation efforts. This research presents new baseline data for future research on mountain forest ecosystems and the techniques of biodiversity conservation to reduce climate change's effects in Iraq.     

How do Snow Partridge (Lerwa lerwa) and Tibetan Snowcock (Tetraogallus tibetanus) coexist in sympatry under high‐elevation conditions on the Qinghai–Tibetan Plateau?

The Qinghai–Tibetan Plateau (QTP) has the highest elevations of all biodiversity hotspots. Difficulties involved in fieldwork at high elevations cause challenges in researching mechanisms facilitating species coexistence. Herein, we investigated Snow Partridge (Lerwa lerwa) and Tibetan Snowcock (Tetraogallus tibetanus), the only two endemic Galliformes on the QTP, to understand species coexistence patterns and determine how they live in sympatry for the first time. We assembled occurrence data, estimated habitat suitability differences and the underlying factors between two species at different scales using ecological niche models. Niche overlap tests were used to investigate whether niche differences between these species allow for their coexistence. We found that elevation was the most important factor determining habitat suitability for both species. At the meso‐scale, two species have similar ecological niches with their suitable habitats lying predominantly along ridge crests. However, ridge crests were more influential for habitat suitability by L. lerwa than for that of T. tibetanus because the latter species ranges further afield than ridge crests. Thus, differences in habitat suitability between these species lead to habitat partitioning, which allows stable coexistence. At the macro‐scale, temperature and precipitation were major factors influencing habitat suitability differences between these species. Tetraogallus tibetanus extended into the hinterland of the QTP and occurred at higher elevations, where colder and drier alpine conditions are commonplace. Conversely, L. lerwa occurred along the southeastern margin of the QTP with a lower snow line, an area prone to rainy and humid habitats. Niche overlap analysis showed that habitat suitability differences between these species are not driven by niche differentiation. We concluded that the coexistence of these two pheasants under high‐elevation conditions could be an adaption to different alpine conditions.     

Combining Occurrence and Habitat Suitability Data Improve Conservation Guidance for the Giant Kangaroo Rat

Identifying high-quality habitat (i.e., areas with resources and conditions suitable to support long-term species persistence) is a priority for conservation, but estimating habitat quality is expensive and time consuming. Instead managers often rely on occurrence data or models of habitat suitability, but these data are only proximally related to individual and population persistence on the landscape. In most habitat suitability modeling studies, researchers treat the model as a hypothesis and the occurrence data as the truth. But occurrence does not always correlate with habitat as expected; therefore, occurrence data may be unreliable. We propose that suitability models and occurrence data be given equal weight to highlight areas of disagreement for future demographic study. To highlight this approach, we used the giant kangaroo rat (Dipodomys ingens) as a case study because their distinct burrow mounds allow for remote monitoring of short-term presence and long-term persistence. We conducted trapping, manned aerial surveys, and aerial imagery surveys in the San Joaquin Desert in California, USA, between 2001 and 2017 and compared the results to an existing habitat suitability model to provide estimates of long-term persistence based on the presence of burrow mounds made by giant kangaroo rats. We treated areas of positive agreement as priorities for habitat conservation and areas of negative agreement as areas managers could ignore. Remaining areas should be prioritized for additional occupancy and demographic studies. From an initial area of 17,385 km², we identified 668 km² of currently occupied high-quality habitat. Of this, just 135 km² was on private land and therefore requiring protection. We classified 1,498 km² (8.6%) for additional research. Of that area, 744 km² was flagged for additional occupancy surveys. Our 3 data sets disagreed over 754 km², suggesting a need for further demographic studies to reveal important population-habitat relationships for the species in those areas. This approach can be useful as part of any habitat conservation exercise for prioritizing protection or targeting future demographic studies. © 2021 The Wildlife Society.     

Habitat assessment of Marco Polo sheep (Ovis ammon polii) in Eastern Tajikistan: Modeling the effects of climate change

Identifying the factors predicting the high‐elevation suitable habitats of Central Asian argali wild sheep and how these suitable habitats are affected by the changing climate regimes could help address conservation and management efforts and identify future critical habitat for the species in eastern Tajikistan. This study used environmental niche models (ENMs) to map and compare potential present and future distributions of suitable environmental conditions for Marco Polo argali. Argali occurrence points were collected during field surveys conducted from 2009 to 2016. Our models showed that terrain ruggedness and annual mean temperature had strong correlations on argali distribution. We then used two greenhouse gas concentration trajectories (RCP 4.5 and RCP 8.5) for two future time periods (2050 and 2070) to model the impacts of climate change on Marco Polo argali habitat. Results indicated a decline of suitable habitat with majority of losses observed at lower elevations (3,300–4,300 m). Models that considered all variables (climatic and nonclimatic) predicted losses of present suitable areas of 60.6% (6,928 km²) and 63.2% (7,219 km²) by 2050 and 2070, respectively. Results also showed averaged habitat gains of 46.2% (6,106 km²) at much higher elevations (4,500–6,900 m) and that elevational shifts of habitat use could occur in the future. Our results could provide information for conservation planning for this near threatened species in the region.     

Silvicolous on a Small Scale: Possibilities and Limitations of Habitat Suitability Models for Small,Elusive Mammals in Conservation Management and Landscape Planning

Species distribution and endangerment can be assessed by habitat-suitability modelling. This study addresses methodical aspects of habitat suitability modelling and includes an application example in actual species conservation and landscape planning. Models using species presence-absence data are preferable to presence-only models. In contrast to species presence data, absences are rarely recorded. Therefore, many studies generate pseudo-absence data for modelling. However, in this study model quality was higher with null samples collected in the field. Next to species data the choice of landscape data is crucial for suitability modelling. Landscape data with high resolution and ecological relevance for the study species improve model reliability and quality for small elusive mammals like Muscardinus avellanarius. For large scale assessment of species distribution, models with low-detailed data are sufficient. For regional site-specific conservation issues like a conflict-free site for new wind turbines, high-detailed regional models are needed. Even though the overlap with optimally suitable habitat for M. avellanarius was low, the installation of wind plants can pose a threat due to habitat loss and fragmentation. To conclude, modellers should clearly state the purpose of their models and choose the according level of detail for species and environmental data.