Multi-scale habitat modelling and predicting change in the distribution of tiger and leopard using random forest algorithm

Examining the rationality of Giant Panda National Park's zoning designations and management measures for habitat conservation: Insights from interpretable machine learning methods

Examining the rationality of zoning designations and management measures in the initial establishment of national parks in China is of great significance for supporting decision-making regarding habitat conservation. There exists a research gap in exploring the threshold effects of both environmental and human-related factors on habitat distribution in the context of national parks. However, it may be a challenge because of the limited species distribution data. Our study aims to put forward an analytical framework that integrates species distribution models (SDMs) with interpretable machine learning methods. A case study was performed in the Sichuan region of the Giant Panda National Park (GPNP). We constructed a SDM based on the Random Forest algorithm and made use of accessible remote sensing and big data to predict the distribution of giant panda habitat (GPH) in 2020. Interpretable machine learning methods, namely Partial dependence plots (PDPs) and SHapley Additive exPlanations (SHAP), were utilized to uncover the underlying mechanisms of environmental and anthropogenic variables influencing the GPH distribution. Through GIS overlay analysis, areas where conflicts between human settlements, transportation infrastructure, and GPH exist were identified. Our findings indicated a potential 28.44 % decrease in GPH from 2014 to 2020. Environmental factors such as temperature, topography, and vegetation type, as well as anthropogenic factors including distance to built-up areas and transportation infrastructure, notably distance to national roads, provincial roads and city arterial roads, influenced the GPH distribution with threshold effects significantly. The overlay analysis revealed escalated conflicts between human settlements, transportation infrastructure, and GPH in 2020 compared to 2014. Currently, the Sichuan region of the GPNP implements two zones: a core protection zone and a general control zone, covering 63.71 % of the GPH, while 36.29 % remains outside the management scope. Drawing from the analysis above, this study provided suggestions for the adjustment of zoning designations and management measures in the GPNP.

Landscape predictors influencing livestock depredation by leopards in and around Annapurna Conservation Area, Nepal

Livestock depredation by leopards is a pervasive issue across many Asian and African range countries, particularly in and around protected areas. Developing effective conflict mitigation strategies requires understanding the landscape features influencing livestock depredation. In this study, we investigated predictors associated with livestock depredation by leopards using 274 cases of leopard attacks on livestock that occurred between 2017 and 2020 in the Annapurna Conservation Area, Nepal. We also examined how livestock predation by leopards varied depending on the species, season, and time. A generalized linear model with binary logistic regression was used to test the statistical significance of variables associated with the presence and absence of conflict sites. The results revealed that the area of forest, agricultural land, length of rivers, slope, proximity to settlements and protected areas, and elevation significantly predicted the probability of leopard attacks on livestock. We also observed a significant increase in the incidence of leopard predation on livestock with decreasing slopes and rising elevations. The areas near human settlements and the protected areas faced a higher risk of leopard predation. The incidence of leopard predation on livestock varied significantly depending on the livestock species, season, and time. Goats were the most highly predated livestock, followed by sheep, cow/ox, and buffalo. A total of 289.11 km2 (or around 5% of the research area) was deemed to be at high risk for leopard predation on livestock. This study's comprehensive understanding of human-leopard conflicts provides valuable insights for planning and implementing measures to reduce damage caused by leopard populations throughout their range.

Modelling the current and future distribution potential areas of Peperomia abyssinica Miq., and Helichrysum citrispinum Steud. ex A. Rich. in Ethiopia

BACKGROUND

The aim of this study is to investigate how climate change influences the distribution of economically and environmentally important species of P. abyssinica and H. citrispinum in Ethiopia. The species distribution modeling intends to forecast species' ecological niche ranges and habitat suitability by employing a variety of environmental parameters as predictors, which is vital for conservation planning and restoration success. Six representative concentration pathways (RCP 2.6, 4.5, and 8.5 for the years 2050 and 2070) with the same resolution of 2.5 min that shows the emission scenarios were used for the prediction. To predict the current and future distributions of H. citrispinum and P. abyssinica 56 and 45 occurrence records from National Herbarium, Addis Ababa University, GBIF, and available literatures were used respectively.

RESULTS

The MaxEnt model predicted habitat suitability for H. citrispinum species with an Area Under Curve (AUC) value of 0.961 ± 0.027, and 0.809 ± 0.045 for P. abyssinica, indicating excellent discriminatory ability or accuracy under the current climate scenario. The Future distribution of suitable habitat for both H. citrispinum and P. abyssinica plant species was accurately predicted with AUC values of 0.960 ± 0.017 and 0.780 ± 0.35, respectively under future climatic scenarios. The jackknife test result indicates that environmental variables such as topographic position index (92.5%), precipitation of the driest quarter (3%) and precipitation in the coldest quarter (1.8%) are associated with the distributions of H. citrispinum, while topographic position index (36.6%), precipitation of driest quarter (21.4%), precipitation of warmest quarter (16.2%) and precipitation seasonality (13.9%) were found to be limiting environmental variables for P. abyssinica under current and future climatic conditions in Ethiopia. The prediction map and interception calculation for both present and projected (in the 2050s and again in the 2070s) climate change scenarios indicate significant habitat loss, decreased, and fragmentation under all RCPs (2.6, 4.5, and 8.5) scenarios for P. abyssinica while habitat gain, and increasing for H. citrispinum in Ethiopia.

CONCLUSIONS

Topographic position index (TPI) is the most impactful predictor variable on the distribution of the two species. Consequently, potentially habitable areas (with diverse aspects and slopes) are increasing for H. citrispinum while decreasing for P. abyssinica.

Assessing the suitability and dynamics of three medicinal Sambucus species in China under current and future climate scenarios

Climate change exerts profound influences on the ecological environments on a global scale, leading to habitat destruction and altering distribution patterns for numerous plant species. Traditional Chinese medicinal plants, such as those belonging to the Sambucus genus, have been extensively utilized for several centuries to treat fractures, rheumatism, and inflammation. However, our understanding of their geographic distribution and climatic adaptation within China still needs to be improved. In this study, we screened the optimal predictive model (random forest model) to predict the potential suitable distribution of three Sambucus species (Sambucus adnata, Sambucus javanica, and Sambucus williamsii) across China under both current and future climate scenarios. Moreover, we identified key climate factors that influence their potential distributions. Our findings revealed that S. adnata and S. javanica are predominantly shaped by temperature seasonality and mean diurnal range, respectively, whereas S. williamsii is significantly affected by the precipitation of the wettest month. Currently, S. williamsii is primarily distributed in north and central south China (covering 9.57 × 105 km2), S. javanica is prevalent in the south and east regions (covering 6.41×105 km2), and S. adnata predominantly thrives in the southwest China (covering 1.99×105 km2). Under future climate change scenarios, it is anticipated that S. adnata may migrate to higher latitudes while S. javanica may shift to lower latitudes. However, potentially suitable areas for S. williamsii may contract under certain scenarios for the years 2050 and 2090, with an expansion trend under the SSP585 scenario for the year 2090. Our study emphasizes the importance of climatic variables in influencing the potential geographic distribution of Sambucus species. These findings provide valuable theoretical insights for the preservation, cultivation, and utilization of Sambucus medicinal plant resources in the context of ongoing climate change.

Habitat suitability of four threatened Himalayan species: Asiatic black bear, common leopard, musk deer, and snow leopard

Background

Biodiversity conservation is becoming challenging day by day. For this, it is essential to understand the distribution, habitat, and impact of anthropogenic activities on animals at risk. We assessed the suitable habitats and anthropogenic impacts on Asiatic black bears, common leopards, musk deer, and snow leopards in and outside the protected areas of Gandaki Province, Nepal.

Methods

We collected the presence locations of Asiatic black bears, common leopards, musk deer, and snow leopards based on scats and other signs. We employed the Maximum Entropy (MaxEnt) tool to identify suitable habitats of our studied species and their anthropogenic impacts on them.

Results

The total suitable habitat of the common leopard was found to be 6,052 km2, followed by the Asiatic black bear (5,819 km2), snow leopard (4,447 km2), and musk deer (1,690 km2) in Gandaki Province. Most of the areas of suitable habitat for common leopards and Asiatic black bears were outside the protected areas, and for musk deer and snow leopards were inside the protected areas. Elevation was the most important variable determining habitat suitability of Asiatic black bear, common leopard, and musk deer, whereas the distance to water was the most important variable determining habitat suitability of snow leopard. Asiatic black bears, common leopards, and musk deer face significant anthropogenic impacts, but snow leopards face some anthropogenic impacts.

Conclusion

Managing these animals' habitats inside and outside protected areas is essential. Hence, biodiversity conservation and livelihood opportunities should be balanced in the Himalayas on a win-win basis.

Can Bengal Tiger (Panthera tigris tigris) endure the future climate and land use change scenario in the East Himalayan Region? Perspective from a multiple model framework

Large mammals are susceptible to land use and climate change, unless they are safeguarded within large, protected areas. It is crucial to comprehend the effects of these changes on mammals to develop a conservation plan. We identified ecological hotspots that can sustain an ecosystem for the endangered Bengal tiger (Panthera tigris tigris), an umbrella species. We developed three distinct ensemble species distribution models (SDMs) for the Bengal tiger in the Indian East Himalayan Region (IEHR). The first model served as the baseline and considered habitat type, climate, land cover, and anthropogenic threats. The second model focused on climate, land use, and anthropogenic threats, the third model focused on climate variables. We projected the second and third models onto two future climate scenarios: RCP 4.5 and RCP 8.5. We evaluated the threats possess to protected areas within eco-sensitive zone based on the potential tiger habitat. Finally, we compared the potential habitat with the IUCN tiger range. Our study revealed that the Brahmaputra valley will serve as the primary habitat for tigers in the future. However, considering the projected severe climate scenarios, it is anticipated that tigers will undergo a range shift towards the north and east, especially in high-altitude regions. Very high conservation priority areas, which make up 3.4% of the total area, are predominantly located in the riverine corridor of Assam. High conservation priority areas, which make up 5.5% of total area are located in Assam and Arunachal Pradesh. It is important to note that conservation priority areas outside of protected areas pose a greater threat to tigers. We recommend reassessing the IUCN Red List's assigned range map for tigers in the IEHR, as it is over-predicted. Our study has led us to conclude both land use and climate change possess threats to the future habitat of tigers. The outcomes of our study will provide crucial information on identifying habitat hotspots and facilitate appropriate conservation planning efforts.

Influence of land use changes on landscape connectivity for North China leopard (Panthera pardus japonensis)

North China leopard (Panthera pardus japonensis) is the most widespread subspecies of leopard and one of the rare and endangered species in China. It is currently confined to several isolated natural reserves, and little is known about its habitat network connectivity with land use changes. This study was conducted to assess the impacts of land use changes on landscape connectivity for North China leopard in the Great Taihang Region. Circuit theory‐based connectivity models and least‐cost path analyses were used to delineate pathways suitable for species movement, and evaluate the impacts of land use changes on landscape connectivity. The results revealed that there were 37 least‐cost paths in 1990 and 38 in 2020. The area of forest land increased from 57,142.74 km² to 74,836.64 km², with the percentage increasing from 26.61% to 34.85%. In general, the increase in forest land area promoted the landscape connectivity for North China leopard at broad spatial scales. The improvement of landscape connectivity was not always consistent with the land use changes, and there was a slightly decreasing trend on connectivity in some key movement barrier areas with high intensity of human activities. Improving landscape connectivity at broad spatial scales is as important as protecting the habitats (natural reserves) where the species lives. Our study can serve as an example of exploring the relationships between land use changes and landscape connectivity for species conservation at broad spatial scales with limited movement pattern data. This information is proved to be critical for enhancing landscape connectivity for the conservation concern of North China leopard and planning of natural reserves network.

Spatial-temporal dynamics and evolution of ecological security in a rapid urbanization city, Southwest China

The main goal of constructing ecological security patterns (ESPs) is to identify ecological sources, corridors and nodes that play significant roles in sustainable development on a regional scale. Although there are many studies on the construction of ESPs, there is no consensus in terms of research methodology and systematic frameworks for integrated landscape management. Based on land use data from 2000, 2010, and 2020 of Chongqing Municipality in southwest China, we evaluated the spatial-temporal variation of ESPs by integrating InVEST and Circuit Theory. Results showed that: (a) Habitat quality varied through space, with habitat quality being lower in the western and central regions and higher in the southeastern and northeastern regions. (b) The area of lower quality habitat across different time periods was more than 46%, and habitat quality over the last two decades has generally been low with no significant improvement. (c) From 2000 to 2020, ecological sources were primarily distributed in the mountainous areas with high habitat quality and fractional vegetation coverage in the northeast and southeast. The regions identified ecological sources in 2000, 2010, and 2020 accounted for 31.37, 33.53, and 32.7% of Chongqing Municipality, respectively. (d) The ESPs were composed of ecological sources dominated by forests, connected by continuous ecological corridors. The current ESPs of Chongqing Municipality included 20 ecological nodes, 17 continuous ecological corridors and 23 ecological sources. We strongly suggest the local governments strengthen the protection of the identified ecological nodes, ecological corridors, ecological sources, and protection gaps, and focus on strengthening the construction and management of the ecological corridor network system to promote species diffusion and gene exchange. Our findings are helpful for policy makers to introduce appropriate measures to objectively guide urban expansion via rational and sustainable development of land resources and improve the level of ecological security for Chongqing Municipality.

Identifying connectivity for two sympatric carnivores in human-dominated landscapes in central Iran

Central Iran supports a diversity of carnivores, most of which are threatened by habitat loss and fragmentation. Carnivore conservation requires the identification and preservation of core habitats and ensuring connectivity between them. In the present study, we used species distribution modeling to predict habitat suitability and connectivity modeling to predict linkage (resistant kernel and factorial least-cost path analyses) for grey wolf and golden jackal in central Iran. For grey wolf, elevation, topographic ruggedness, and distance to Conservation Areas (CAs) were the strongest predictors; for golden jackal, distance to human settlements, dump sites and topographic ruggedness were the most influential variables in predicting the occurrence of this species. Our results also indicated a high potential for large parts of the landscape to support the occurrence of these two canid species. The largest and the most crucial core habitats and corridor paths for the conservation of both species are located in the southern part of the study landscape. We found a small overlap between golden jackal corridor paths and core habitats with CAs, which has important implications for conservation and future viability of the golden jackal populations. Some sections of core areas are bisected by roads, where most vehicle collisions with grey wolf and golden jackal occurred. To minimize mortality risk, we propose that successful conservation of both species will necessitate integrated landscape-level management, as well as conservation of core areas and corridors and development of mitigation strategies to reduce vehicle collisions.

Land use/land cover changes in the central part of the Chitwan Annapurna Landscape, Nepal

Background

Land use/land cover assessment and monitoring of the land cover dynamics are essential to know the ecological, physical and anthropogenic processes in the landscape. Previous studies have indicated changes in the landscape of mid-hills of Nepal in the past few decades. But there is a lack of study in the Chitwan Annapurna Landscape; hence, this study was carried out to fill in study gap that existed in the area.

Methods

This study evaluates land use/land cover dynamics between 2000 to 2020 in the central part of the Chitwan Annapurna Landscape, Nepal by using Landsat images. The Landsat images were classified into eight different classes using remote sensing and geographic information system (GIS). The accuracy assessment of classified images was evaluated by calculating actual accuracy, producer's accuracy, user's accuracy and kappa coefficient based on the ground-truthing points for 2020 and Google Earth and topographic maps for images of 2010 and 2000.

Results

The results of land use/land cover analysis of Landsat image 2020 showed that the study area was composed of grassland (1.73%), barren area (1.76%), riverine forest (1.93%), water body (1.97%), developed area (4.13%), Sal dominated forest (15.4%), cropland (28.13%) and mixed forest (44.95%). The results of land cover change between 2000 to 2020 indicated an overall increase in Sal dominated forest (7.6%), developed area (31.34%), mixed forest (37.46%) and decrease in riverine forest (11.29%), barren area (20.03%), croplands (29.87%) and grasslands (49.71%). The classification of the images of 2000, 2010 and 2020 had 81%, 81.6% and 84.77% overall accuracy, respectively. This finding can be used as a baseline information for the development of a proper management plan to protect wildlife habitats and forecasting possible future changes, if needed.

A 3D transcriptomics atlas of the mouse nose sheds light on the anatomical logic of smell

The sense of smell helps us navigate the environment, but its molecular architecture and underlying logic remain understudied. The spatial location of odorant receptor genes (Olfrs) in the nose is thought to be independent of the structural diversity of the odorants they detect. Using spatial transcriptomics, we create a genome-wide 3D atlas of the mouse olfactory mucosa (OM). Topographic maps of genes differentially expressed in space reveal that both Olfrs and non-Olfrs are distributed in a continuous and overlapping fashion over at least five broad zones in the OM. The spatial locations of Olfrs correlate with the mucus solubility of the odorants they recognize, providing direct evidence for the chromatographic theory of olfaction. This resource resolves the molecular architecture of the mouse OM and will inform future studies on mechanisms underlying Olfr gene choice, axonal pathfinding, patterning of the nervous system, and basic logic for the peripheral representation of smell.

New Evidence on the Linkage of Population Trends and Species Traits to Long-Term Niche Changes

Despite the assessment of long-term niche dynamics could provide crucial information for investigating species responses to environmental changes, it is a poorly investigated topic in ecology. Here, we present a case study of multi-species niche analysis for 71 common breeding birds in Northern Italy, exploring long-term niche changes from 1992 to 2017 and their relationship with both population trends and species traits. We (i) quantified the realized Grinnellian niche in the environmental space, (ii) compared variations in niche breadth and centroid, (iii) tested niche divergence and conservatism through equivalency and similarity tests, (iv) calculated niche temporal overlap, expansion and unfilling indices, and (v) investigated their association with both population changes and species traits. Results supported niche divergence (equivalency test) for 32% of species, although two-thirds were not supported by the similarity test. We detected a general tendency to adjust the niche centroids towards warmer thermal conditions. Increasing populations were positively correlated with niche expansion, while negatively correlated with niche overlap, albeit at the limit of the significance threshold. We found moderate evidence for a non-random association between niche changes and species traits, especially for body size, clutch size, number of broods per year, inhabited landscape type, and migration strategy. We encourage studies correlating long-term population trends and niche changes with species traits’ information and a specific focus on cause-effect relationship at both the single and multiple-species level.

Driving Mechanism of Habitat Quality at Different Grid-Scales in a Metropolitan City

Urban ecosystem dysfunction, habitat fragmentation, and biodiversity loss caused by rapid urbanization have threatened sustainable urban development. Urban habitat quality is one of the important indicators for assessing the urban ecological environment. Therefore, it is of great practical significance to carry out a study on the driving mechanism of urban habitat quality and integrate the results into urban planning. In this study, taking Zhengzhou, China, as an example, the InVEST model was used to analyze the spatial differentiation characteristics of urban habitat quality and Geodetector software was adopted to explore the driving mechanism of habitat quality at different grid-scales. The results show the following: (1) LUCC, altitude, slope, surface roughness, relief amplitude, population, nighttime light, and NDVI are the dominant factors affecting the spatial differentiation of habitat quality. Among them, the impacts of slope, surface roughness, population, nighttime light, and NDVI on habitat quality are highly sensitive to varying grid-scales. At the grid-scale of 1000 to 1250 m, the impacts of the dominant factors on habitat quality is closer to the mean level of multiple scales. (2) The impact of each factor on the spatial distribution of habitat quality is different, and the difference between most factors has always been significant regardless of the variation of grid-scales. The superimposed impact of two factors on the spatial distribution of habitat quality is greater than the impact of the single factor. (3) Combined with the research results and the local conditions of Zhengzhou, we put forward some directions of habitat protection around adjusting urban land use structure, applying nature-based solutions and establishing a systematic thinking model for multi-level urban habitat sustainability.

Identifying core habitats and corridors for giant pandas by combining multiscale random forest and connectivity analysis

Habitat loss and fragmentation are widely acknowledged as the main driver of the decline of giant panda populations. The Chinese government has made great efforts to protect this charming species and has made remarkable achievements, such as population growth and habitat expansion. However, habitat fragmentation has not been reversed. Protecting giant pandas in a large spatial extent needs to identify core habitat patches and corridors connecting them. This study used an equal-sampling multiscale random forest habitat model to predict a habitat suitability map for the giant panda. Then, we applied the resistant kernel method and factorial least-cost path analysis to identify core habitats connected by panda dispersal and corridors among panda occurrences, respectively. Finally, we evaluated the effectiveness of current protected areas in representing core habitats and corridors. Our results showed high scale dependence of giant panda habitat selection. Giant pandas strongly respond to bamboo percentage and elevation at a relatively fine scale (1 km), whereas they respond to anthropogenic factors at a coarse scale (≥2 km). Dispersal ability has significant effects on core habitats extent and population fragmentation evaluation. Under medium and high dispersal ability scenarios (12,000 and 20,000 cost units), most giant panda habitats in the Qionglai mountain are predicted to be well connected by dispersal. The proportion of core habitats covered by protected areas varied between 38% and 43% under different dispersal ability scenarios, highlighting significant gaps in the protected area network. Similarly, only 43% of corridors that connect giant panda occurrences were protected. Our results can provide crucial information for conservation managers to develop wise strategies to safeguard the long-term viability of the giant panda population.

Potential Range Shift of Snow Leopard in Future Climate Change Scenarios

The snow leopard (Panthera uncia) lives in alpine ecosystems in Central Asia, where it could face intensive climate change and is thus a major conservation concern. We compiled a dataset of 406 GPS-located occurrences based on field surveys, literature, and the GBIF database. We used Random Forest to build different species distribution models with a maximum of 27 explanatory variables, including climatic, topographical, and human impact variables, to predict potential distribution for the snow leopard and make climate change projections. We estimated the potential range shifts of the snow leopard under two global climate models for different representative concentration pathways for 2050 and 2070. We found the distribution center of the snow leopard may move northwest by about 200 km and may move upward in elevation by about 100 m by 2070. Unlike previous studies on the range shifts of the snow leopard, we highlighted that upward rather than northward range shifts are the main pathways for the snow leopard in the changing climate, since the landform of their habitat allows an upward shift, whereas mountains and valleys would block northward movement. Conservation of the snow leopard should therefore prioritize protecting its current habitat over making movement corridors.

Evaluating the importance of wolverine habitat predictors using a machine learning method

In the conterminous United States, wolverines (Gulo gulo) occupy semi-isolated patches of subalpine habitats at naturally low densities. Determining how to model wolverine habitat, particularly across multiple scales, can contribute greatly to wolverine conservation efforts. We used the machine-learning algorithm random forest to determine how a novel analysis approach compared to the existing literature for future wolverine conservation efforts. We also determined how well a small suite of variables explained wolverine habitat use patterns at the second- and third-order selection scale by sex. We found that the importance of habitat covariates differed slightly by sex and selection scales. Snow water equivalent, distance to high-elevation talus, and latitude-adjusted elevation were the driving selective forces for wolverines across the Greater Yellowstone Ecosystem at both selection orders but performed better at the second order. Overall, our results indicate that wolverine habitat selection is, in large part, broadly explained by high-elevation structural features, and this confirms existing data. Our results suggest that for third-order analyses, additional fine-scale habitat data are necessary.

Density estimation of tiger and leopard using spatially explicit capture-recapture framework

The conservation of large carnivores often requires precise and accurate estimates of their populations. Being cryptic and occurring at low population densities, obtaining an unbiased population estimate is difficult in large carnivores. To overcome the uncertainties in the conventional capture–recapture (CR) methods used to estimate large carnivore densities, more robust methods such as spatially explicit capture-recapture (SECR) framework are now widely used. We modeled the CR data of tiger (Panthera tigris tigris) and leopard (Panthera pardus fusca) in the SECR framework with biotic and abiotic covariates likely believed to influence their densities. An effort of 2,211 trap nights resulted in the capture of 33 and 38 individual tigers and leopards. A total of 95 and 74 detections of tigers and leopards were achieved using 35 pairs of camera traps. Tiger and leopard density were estimated at 4.71 ± 1.20 (3.05–5.11) and 3.03 ± 0.78 (1.85–4.99) per 100 km². Our results show that leopard density increased with high road density, high terrain ruggedness and habitats with high percentage of cropland and natural vegetation. The tiger density was positively influenced by the mosaic of cropland and natural vegetation. This study provides the first robust density estimates of tiger and leopard within the study area. Our results support the notion that large carnivores can attain moderate densities within human-dominated regions around protected areas relying on domestic livestock. Broader management strategies aimed at maintaining wild prey in the human-dominated areas around protected areas are necessary for large and endangered carnivores’ sustenance in the buffer zones around protected areas.