Anticipating Knowledge to Inform Species Management: Predicting Spatially Explicit Habitat Suitability of a Colonial Vulture Spreading Its Range

Background

The knowledge of both potential distribution and habitat suitability is fundamental in spreading species to inform in advance management and conservation planning. After a severe decline in the past decades, the griffon vulture (Gyps fulvus) is now spreading its breeding range towards the northwest in Spain and Europe. Because of its key ecological function, anticipated spatial knowledge is required to inform appropriately both vulture and ecosystem management.

Methodology/Findings

Here we used maximum entropy (Maxent) models to determine the habitat suitability of potential and current breeding distribution of the griffon vulture using presence-only data (N = 124 colonies) in north-western Spain. The most relevant ecological factors shaping this habitat suitability were also identified. The resulting model had a high predictive performance and was able to predict species'' historical distribution. 7.5% (∼1,850 km²) of the study area resulted to be suitable breeding habitat, most of which (∼70%) is already occupied by the species. Cliff availability and livestock density, especially of sheep and goats, around 10 km of the colonies were the fundamental factors determining breeding habitat suitability for this species.

Conclusions/Significance

Griffon vultures could still spread 50–60 km towards the west, increasing their breeding range in 1,782 km². According to our results, 7.22% of the area suitable for griffon vulture will be affected by wind farms, so our results could help to better plan wind farm locations. The approach here developed could be useful to inform management of reintroductions and recovery programmes currently being implemented for both the griffon vulture and other threatened vulture species.     

From topography to hydrology—The modifiable area unit problem impacts freshwater species distribution models

Species distribution models (SDMs) are statistical tools to identify potentially suitable habitats for species. For SDMs in river ecosystems, species occurrences and predictor data are often aggregated across subcatchments that serve as modeling units. The level of aggregation (i.e., model resolution) influences the statistical relationships between species occurrences and environmental predictors—a phenomenon known as the modifiable area unit problem (MAUP), making model outputs directly contingent on the model resolution. Here, we test how model performance, predictor importance, and the spatial congruence of species predictions depend on the model resolution (i.e., average subcatchment size) of SDMs. We modeled the potential habitat suitability of 50 native fish species in the upper Danube catchment at 10 different model resolutions. Model resolutions were derived using a 90‐m digital‐elevation model by using the GRASS‐GIS module r.watershed. Here, we decreased the average subcatchment size gradually from 632 to 2 km². We then ran ensemble SDMs based on five algorithms using topographical, climatic, hydrological, and land‐use predictors for each species and resolution. Model evaluation scores were consistently high, as sensitivity and True Skill Statistic values ranged from 86.1–93.2 and 0.61–0.73, respectively. The most contributing predictor changed from topography at coarse, to hydrology at fine resolutions. Climate predictors played an intermediate role for all resolutions, while land use was of little importance. Regarding the predicted habitat suitability, we identified a spatial filtering from coarse to intermediate resolutions. The predicted habitat suitability within a coarse resolution was not ported to all smaller, nested subcatchments, but only to a fraction that held the suitable environmental conditions. Across finer resolutions, the mapped predictions were spatially congruent without such filter effect. We show that freshwater SDM predictions can have consistently high evaluation scores while mapped predictions differ significantly and are highly contingent on the underlying subcatchment size. We encourage building freshwater SDMs across multiple catchment sizes, to assess model variability and uncertainties in model outcomes emerging from the MAUP.     

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.     

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.     

Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence‐only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km²) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest.     

Exploring the spatiotemporal dynamics of habitat suitability to improve conservation management of a vulnerable plant species

Ongoing declines in biodiversity caused by global environmental changes call for adaptive conservation management, including the assessment of habitat suitability spatiotemporal dynamics potentially affecting species persistence. Remote sensing (RS) provides a wide-range of satellite-based environmental variables that can be fed into species distribution models (SDMs) to investigate species-environment relations and forecast responses to change. We address the spatiotemporal dynamics of species’ habitat suitability at the landscape level by combining multi-temporal RS data with SDMs for analysing inter-annual habitat suitability dynamics. We implemented this framework with a vulnerable plant species (Veronica micrantha), by combining SDMs with a time-series of RS-based metrics of vegetation functioning related to primary productivity, seasonality, phenology and actual evapotranspiration. Besides RS variables, predictors related to landscape structure, soils and wildfires were ranked and combined through multi-model inference (MMI). To assess recent dynamics, a habitat suitability time-series was generated through model hindcasting. MMI highlighted the strong predictive ability of RS variables related to primary productivity and water availability for explaining the test-species distribution, along with soil, wildfire regime and landscape composition. The habitat suitability time-series revealed the effects of short-term land cover changes and inter-annual variability in climatic conditions. Multi-temporal SDMs further improved predictions, benefiting from RS time-series. Overall, results emphasize the integration of landscape attributes related to function, composition and spatial configuration for improving the explanation of ecological patterns. Moreover, coupling SDMs with RS functional metrics may provide early-warnings of future environmental changes potentially impacting habitat suitability. Applications discussed include the improvement of biodiversity monitoring and conservation strategies.     

Maxent modeling for predicting the spatial distribution of three raptors in the Sanjiangyuan National Park,China

Upland buzzard (Buteo hemilasius), Saker falcon (Falco cherrug), and Himalayan vulture (Gyps himalayensis) are three common large raptors in the Sanjiangyuan National Park (SNP), China's first national park. Among them, Upland buzzard and Saker falcon play a significant role in controlling plateau rodent populations and reducing the transmission of pathogens carried by rodents. The Himalayan vulture can provide services for the redistribution and recycling of nutrients in the ecosystem, and play an irreplaceable role in the celestial burial culture of Tibetans in China. Exploring their habitat suitability is important for the protection of the three raptors. Our research was based on the current distribution of Upland buzzard, Saker falcon, and Himalayan vulture that we had extensively surveyed in the Sanjiangyuan National Park from 2016 to 2017. Combined with the correlation analysis of environmental variables, we utilized maximum entropy model (MaxEnt) to evaluate and compare the habitat suitability of the three species in the Sanjiangyuan National Park. Elevation, climate, and human disturbance factors, which had direct or indirect effects on species survival and reproduction, were all included in the model. Among them, elevation was the most important environmental variables affecting the suitability of habitats of three species. Temperature‐related factor was another important predictor. The high (>60%) suitable habitat areas for Upland buzzard, Saker falcon, and Himalayan vulture were 73,017.63, 40,732.78, and 61,654.33 km², respectively, accounted for 59.32%, 33.09%, and 50.08% of the Sanjiangyuan National Park and their total suitable area (i.e., the sum area of high and moderate habitats) reached 96.07%, 60.59%, and 93.70%, respectively. Besides, the three species have overlapping areas for the suitable habitats, which means that overlapping areas should be highly valued and protected. Therefore, understanding the distribution of suitable habitats of the three raptors can provide useful information and reasonable reference for us to put forward suggestions for their protection and regional management.     

Species Distribution Modelling predicts habitat suitability and reduction of suitable habitat under future climatic scenario for Sclerophrys perreti: A critically endangered Nigerian endemic toad

Sclerophrys perreti is a critically endangered Nigerian native frog currently imperilled by human activities. A better understanding of its potential distribution and habitat suitability will aid in conservation; however, such knowledge is limited for S. perreti. Herein, we used a species distribution model (SDM) approach with all known occurrence data (n = 22) from our field surveys and primary literature, and environmental variable predictors (19 bioclimatic variables, elevation and land cover) to elucidate habitat suitability and impact of climate change on this species. The SDM showed that temperature and precipitation were the predictors of habitat suitability for S. perreti with precipitation seasonality as the strongest predictor of habitat suitability. The following variable also had a significant effect on habitat suitability: temperature seasonality, temperature annual range, precipitation of driest month, mean temperature of wettest quarter and isothermality. The model predicted current suitable habitat for S. perreti covering an area of 1,115 km². However, this habitat is predicted to experience 60% reduction by 2050 owing to changes in temperature and precipitation. SDM also showed that suitable habitat exists in south-eastern range of the inselberg with predicted low impact of climate change compared to other ranges. Therefore, this study recommends improved conservation measures through collaborations and stakeholder's meeting with local farmers for the management and protection of S. perreti.     

Forecasting the Effects of Land Use Scenarios on Farmland Birds Reveal a Potential Mitigation of Climate Change Impacts

Climate and land use changes are key drivers of current biodiversity trends, but interactions between these drivers are poorly modeled, even though they could amplify or mitigate negative impacts of climate change. Here, we attempt to predict the impacts of different agricultural change scenarios on common breeding birds within farmland included in the potential future climatic suitable areas for these species. We used the Special Report on Emissions Scenarios (SRES) to integrate likely changes in species climatic suitability, based on species distribution models, and changes in area of farmland, based on the IMAGE model, inside future climatic suitable areas. We also developed six farmland cover scenarios, based on expert opinion, which cover a wide spectrum of potential changes in livestock farming and cropping patterns by 2050. We ran generalized linear mixed models to calibrate the effects of farmland cover and climate change on bird specific abundance within 386 small agricultural regions. We used model outputs to predict potential changes in bird populations on the basis of predicted changes in regional farmland cover, in area of farmland and in species climatic suitability. We then examined the species sensitivity according to their habitat requirements. A scenario based on extensification of agricultural systems (i.e., low-intensity agriculture) showed the greatest potential to reduce reverse current declines in breeding birds. To meet ecological requirements of a larger number of species, agricultural policies accounting for regional disparities and landscape structure appear more efficient than global policies uniformly implemented at national scale. Interestingly, we also found evidence that farmland cover changes can mitigate the negative effect of climate change. Here, we confirm that there is a potential for countering negative effects of climate change by adaptive management of landscape. We argue that such studies will help inform sustainable agricultural policies for the future.     

新疆塔什库尔干野生动物自然保护区马可波罗盘羊生境适宜性评价

马可波罗盘羊是帕米尔高原的代表性物种,开展生境适宜性评价对于该物种的保护与管理具有重要意义。综合考虑植被、地形等影响马可波罗盘羊生境选择的关键因子,以及道路和牧场等人为干扰因子,借助ArcGIS,构建生境适宜性指数模型,在不同尺度上评价分析马可波罗盘羊的生境适宜性及其季节变化特征。结果表明:15836 km~2保护区内马可波罗盘羊夏季潜在适宜生境面积为2127.19 km~2,冬季为1915.70 km~2。保护区西北部面积3767.73 km~2的马可波罗盘羊实际分布区内,夏季潜在适宜生境面积为1095.48 km~2,冬季为1072.82 km~2,马可波罗盘羊适宜生境集中分布于保护区内该物种实际分布区。受人为干扰,保护区内马可波罗盘羊夏季和冬季实际适宜生境丧失率分别为18.43%和17.78%,实际分布区内适宜生境丧失率分别为33.65%和29.73%,表明实际分布区马可波罗盘羊适宜生境受人类活动影响较大,应予以重点保护。总体而言,影响马可波罗盘羊生境适宜性的关键因素是国道314和放牧。基于上述研究结果,作者提出了4点关于马可波罗盘羊生境保护,以及保护区管理与规划的建议与思考。     

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.     

Anticipated climate and land‐cover changes reveal refuge areas for Borneo's orang‐utans

Habitat loss and climate change pose a double jeopardy for many threatened taxa, making the identification of optimal habitat for the future a conservation priority. Using a case study of the endangered Bornean orang‐utan, we identify environmental refuges by integrating bioclimatic models with projected deforestation and oil‐palm agriculture suitability from the 1950s to 2080s. We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s. We then projected to the 2020s, 2050s and 2080s in models incorporating only land‐cover change, climate change or both processes combined. For future climate, we incorporated projections from four model and emission scenario combinations. For future land cover, we developed spatial deforestation predictions from 10 years of satellite data. Refuges were delineated as suitable forested habitats identified by all models that were also unsuitable for oil palm – a major threat to tropical biodiversity. Our analyses indicate that in 2010 up to 260 000 km² of Borneo was suitable habitat within the core orang‐utan range; an 18–24% reduction since the 1950s. Land‐cover models predicted further decline of 15–30% by the 2080s. Although habitat extent under future climate conditions varied among projections, there was majority consensus, particularly in north‐eastern and western regions. Across projections habitat loss due to climate change alone averaged 63% by 2080, but 74% when also considering land‐cover change. Refuge areas amounted to 2000–42 000 km² depending on thresholds used, with 900–17 000 km² outside the current species range. We demonstrate that efforts to halt deforestation could mediate some orang‐utan habitat loss, but further decline of the most suitable areas is to be expected given projected changes to climate. Protected refuge areas could therefore become increasingly important for ongoing translocation efforts. We present an approach to help identify such areas for highly threatened species given environmental changes expected this century.     

Vulnerability of Domestic Sheep to Lynx Depredation in Relation to Roe Deer Density

Abstract The Eurasian lynx (Lynx lynx) causes large loss of free-ranging domestic sheep in Norway. We tested whether the observed higher kill rates by male lynx than female lynx were related to an association between the availability of the main natural prey, as measured by roe deer (Capreolus capreolus) habitat suitability, presence of sheep, and habitat selection of male and female lynx. We found that lynx selected areas with high roe deer suitability during summer and winter. Moreover, during summer, compared to male lynx, females had greater selection for roe deer areas and a stronger avoidance for sheep grazing areas, which suggests that previously observed differences in kill rates between male and female lynx can be attributed to sex-specific habitat use during summer. The connection between lynx habitat use and roe deer also was reflected in a positive relationship between the roe deer suitability of a sheep grazing area and the total loss of lambs, which suggests that livestock, rather than being actively selected, are mainly killed by lynx incidentally when encountered during other lynx activities (e.g., searching for natural prey species). Therefore, any management practice that separates lynx and sheep, such as concentrating livestock into small patches or less preferred habitats, may reduce depredation.     

Microclimate species distribution models estimate lower levels of climate-related habitat loss for salamanders

Species distribution models (SDMs) largely rely on free-air temperatures at coarse spatial resolutions to predict habitat suitability, potentially overlooking important microhabitat. Integrating microclimate data into SDMs may improve predictions of organismal responses to climate change and support targeting of conservation assets at biologically relevant scales, especially for small, dispersal-limited species vulnerable to climate-change-induced range loss. We integrated microclimate data that account for the buffering effects of forest vegetation into SDMs at a very high spatial resolution (3 m²) for three plethodontid salamander species in Great Smoky Mountains National Park (North Carolina and Tennessee). Microclimate SDMs were used to characterize potential changes to future plethodontid habitat, including habitat suitability and habitat spatial patterns. Additionally, we evaluated spatial discrepancies between predictions of habitat suitability developed with microclimate and coarse-resolution, free-air climate data. Microclimate SDMs indicated substantial losses to plethodontid ranges and highly suitable habitat by mid-century, but at much more conservative levels than coarse-resolution models. Coarse-resolution SDMs generally estimated higher mid-century losses to plethodontid habitat compared to microclimate models and consistently undervalued areas containing highly suitable microhabitat. Furthermore, microclimate SDMs revealed potential areas of future gain in highly suitable habitat within current species’ ranges, which may serve as climatic microrefugia. Taken together, this study highlights the need to develop microclimate SDMs that account for vegetation and its biophysical effects on near-surface temperatures. As microclimate datasets become increasingly available across the world, their integration into correlative and mechanistic SDMs will be imperative for accurately estimating organismal responses to climate change and helping environmental managers tasked with spatially prioritizing conservation assets.     

Estimating the influence of land management change on weed invasion potential using expert knowledge

Aim To develop and test a general framework for estimating weed invasion potential (suitability and susceptibility) that utilized expert knowledge of dispersal, establishment and persistence and considered the influence of land management. Location The semi‐arid Desert Channels Region of Queensland, Australia (476,000 km²). Methods We developed a general framework that integrated knowledge and empirical data of the environmental and land management variables influencing the dispersal, establishment and persistence of the invasive shrub parkinsonia (Parkinsonia aculeata) using a Bayesian network linked to a Geographic Information System (GIS). We evaluated the influence of different land management scenarios on landscape suitability for parkinsonia. Model performance was assessed by comparing predicted landscape suitability with mapped parkinsonia locations and estimated parkinsonia density. Results Our predictions of moderate to high suitability corresponded reasonably well with mapped parkinsonia locations (71% match) and areas of common to abundant estimated density (92% match). They also suggested that parkinsonia has not reached its potential distribution within the study region. Under current land management conditions, 77,000 km² of land was found to be highly or moderately suitable for parkinsonia. Scenario analysis indicated that maintaining moderate herbaceous ground cover levels, and using sheep to browse juvenile parkinsonia, reduced the predicted moderate to high suitability area to 27,000 km², offering a potential management strategy for limiting parkinsonia invasion. Main conclusions Weed invasion potential can be reasonably estimated using expert knowledge of dispersal, establishment and persistence, integrated using a Bayesian network linked to a GIS. This modelling approach can be an alternative to process‐based and phenomenological modelling, which can be problematic for modelling new and emerging weed invasions, particularly where data are patchy. The modelling approach also allows the influence of land management change on invasion potential to be investigated through scenario analysis.     

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.     

Scenario-Led Habitat Modelling of Land Use Change Impacts on Key Species

Accurate predictions of the impacts of future land use change on species of conservation concern can help to inform policy-makers and improve conservation measures. If predictions are spatially explicit, predicted consequences of likely land use changes could be accessible to land managers at a scale relevant to their working landscape. We introduce a method, based on open source software, which integrates habitat suitability modelling with scenario-building, and illustrate its use by investigating the effects of alternative land use change scenarios on landscape suitability for black grouse Tetrao tetrix. Expert opinion was used to construct five near-future (twenty years) scenarios for the 800 km² study site in upland Scotland. For each scenario, the cover of different land use types was altered by 5–30% from 20 random starting locations and changes in habitat suitability assessed by projecting a MaxEnt suitability model onto each simulated landscape. A scenario converting grazed land to moorland and open forestry was the most beneficial for black grouse, and ‘increased grazing’ (the opposite conversion) the most detrimental. Positioning of new landscape blocks was shown to be important in some situations. Increasing the area of open-canopy forestry caused a proportional decrease in suitability, but suitability gains for the ‘reduced grazing’ scenario were nonlinear. ‘Scenario-led’ landscape simulation models can be applied in assessments of the impacts of land use change both on individual species and also on diversity and community measures, or ecosystem services. A next step would be to include landscape configuration more explicitly in the simulation models, both to make them more realistic, and to examine the effects of habitat placement more thoroughly. In this example, the recommended policy would be incentives on grazing reduction to benefit black grouse.     

Habitat shift and time budget of the Tibetan argali: the influence of livestock grazing

Livestock production is the primary source of livelihood and income in most of the high steppe and alpine regions of the Indian Trans-Himalaya. In some areas, especially those established or proposed for biodiversity conservation, recent increases in populations of domestic livestock, primarily sheep and goats, have raised concern about domestic animals competitively excluding wild herbivores from the rangelands. We evaluated the influence of domestic sheep and goat grazing on the habitat use and time budget of the endangered Tibetan argali Ovis ammon hodgsoni in the proposed Gya-Miru Wildlife Sanctuary, Ladakh, India. We asked if the domestic sheep and goat grazing and collateral human activities relegate the argali to sub-optimal habitats, and alter their foraging time budgets. Data were collected on habitat use and time budget of a population of c. 50 argalis before and after c. 2,000 sheep and goats moved onto their winter pasture in the Tsabra catchment of the aforementioned reserve. Following the introduction of domestic sheep and goats, argalis continued to use the same catchment but shifted to steeper habitats, closer to cliffs, with lower vegetation cover, thus abandoning previously used plant communities with denser cover. Argalis’ active time spent foraging also decreased by 10% in response to the presence of livestock. These results suggest a clear disturbance effect of livestock on argalis, and indicate a potential for competition, conceivably a significant disadvantage for argalis in winter when forage availability is minimal.     

Changes in heathland vegetation under goat grazing: effects of breed and stocking rate

Questions: How are heathland vegetation dynamics affected by different goat grazing management? Location: Cantabrian heathlands in Illano, Asturias, northern Spain. Methods: During 4 years, vegetation dynamics (structural composition, canopy height and floristic diversity) were studied under three goat grazing treatments with three replicates: high stocking rate (11.7 goats ha^?1) with a local Celtiberic breed, and high (15 goats ha^?1) and low (6.7 goats ha^?1) stocking rates with a commercial Cashmere breed. Results: The relative cover of woody plants, particularly heather species, decreased more while herbaceous cover increased more under local Celtiberic than under Cashmere breed grazing. Within Cashmere treatments, the cover and height of live shrubs decreased more and the herbaceous cover increased more under high than under low stocking rate. Redundancy analysis showed a significant effect of treatment × year interaction on floristic composition. Greater species richness was recorded under local goat grazing, but Shannon diversity index fell in the fourth year on these plots because of dominance by two grass species. Conclusions: Local Celtiberic goat grazing at such a high stocking rate (11.7 goats ha^?1) hinders the development of sustainable systems on these heathlands, both in environmental and productive terms, owing to the limitations in soil fertility. Nevertheless, Celtiberic goats could be useful for controlling excessive shrub encroachment and reducing fire hazard. Cashmere goat grazing at high stocking rate promoted the highest Shannon diversity by generating a better balance between woody and herbaceous plants, while shrub dominance was not altered under the low stocking rate.     

Spatio-temporal habitat assessment of the Gangetic floodplain in the Hastinapur wildlife sanctuary

Remote sensing provides multi-dimensional and multi-temporal information about habitat, insights into the significant drivers of change, and the key factors affecting landscape dynamics. Such information is crucial to provide perspective and a more profound understanding of ecological surveys. This study utilizes Google Earth Engine's capability to assess a riverine wetland grassland floodplain in Hastinapur Wildlife Sanctuary (HWS) along the Ganga River, which is a critical habitat for wintering migratory birds, the critically endangered gharial, turtles, aquatic mammals such as otters and dolphins, and cervid species such as swamp deer. We have developed a framework for regular monitoring through rapid habitat assessment, which visualizes the spatio-temporal change in land cover, the seasonal dynamics in water and vegetation, changes due to anthropogenic influences on the landscape, and finally, how these factors affect the habitat availability of species of concern in the HWS. The results show a dynamic river system with high seasonal variations. The vegetation trend shows increasing greenness, indicative of the conversion of grassland, scrubland, and herbaceous cover to more permanent vegetation, which will adversely affect the riparian habitat structure. A habitat suitability index generated through geospatial analysis using the weighted overlay method suggests that 40.07% of the HWS, nearly 767.12 km², comprising mainly the riverscape, wetland, and riparian grasslands, is suitable habitat for aquatic and semi-aquatic species. However, only 9.93% of the sanctuary comprising 197.27 km², is available as a core habitat. Further, the area is threatened by encroachment evident from the rapidly increasing land-use intensity and night light pollution, which puts the grasslands sheltered to swamp deer and other wildlife at higher risk leaving almost 27.9% of the area comprising 533.63 km² unsuitable for wildlife. Urban and agricultural land use has taken over 67% of the sanctuary. An increase in minimum radiance value representing ALAN, from 0.41 to 0.73 W/m²-sr in just six years from 2015 to 2021, shows a reduction in nocturnal darkness, reducing safe niches for wildlife. The study results provide critical baseline information for ecological surveys and a rapid assessment platform for future sanctuary management. Constant monitoring of anthropogenic activities such as farming, settlements, and transport routes threatening the habitat is essential for informed conservation management decisions.