Sex-Specific Habitat Suitability Modeling for Panthera tigris in Chitwan National Park, Nepal: Broader Conservation Implications

Although research on wildlife species across taxa has shown that males and females may differentially select habitat, sex-specific habitat suitability models for endangered species are uncommon. We developed sex-specific models for Bengal tigers (Panthera tigris) based on camera trapping data collected from 20 January to 22 March 2010 within Chitwan National Park, Nepal, and its buffer zone. We compared these to a sex-indiscriminate habitat suitability model to assess the benefits of a sex-specific approach to habitat suitability modeling. Our sex-specific models produced more informative and detailed habitat suitability maps and highlighted vital differences in the spatial distribution of suitable habitats for males and females, specific associations with different vegetation types, and habitat use near human settlements. Improving and refining habitat models for this and other critically endangered species provides the necessary information to meet established conservation goals and population recovery targets.

Habitat Suitability modeling of Urial (Ovis orientalis arkal) in the Samelghan plain by using Maximum Entropy Method

Habitat suitability models are useful tools for a variety of wildlife management objectives. Distributions of wildlife species can be predicted for geographical areas that have not been extensively surveyed. The basis of these models' work is to minimize the relationship between species distribution and biotic and abiotic environments. For some species, there is information about presence and absence that allows the use of a variety of standard statistical methods, however, the absence data is not available for most species. Nowadays, the methods that need presence-only data are expanded. One of these methods is the Maximum Entropy (MaxEnt) modeling. The purpose of this study is to model the habitat of Urial ( Ovis orientalis arkal ) in the Samelghan plain in the North East of Iran with the MaxEnt method. This algorithm uses the Jackknife plot and percent contribution values to determine the significance of the variables. The results showed that variables such as southern aspects, Juniperus-Acer, Artemisia-Perennial plants, slope 0-5%, and asphalt road were the most important factors affecting the species’ habitat selection. The area under curve (AUC) Receiver Operating Characteristic (ROC) showed an excellent model performance. Suitable habitat was classified based on the threshold value (0.0513) and the ROC, which based on the results 28% of the area was a suitable habitat for Urial.

Comparison of Catasetum bicolor and C. ochraceum (Catasetinae: Orchidaceae) habitat preferences: implications for their conservation

Family Orchidaceae is widely recognized for its mutualistic relationship with their pollinators, however, the knowledge about the most diverse monocotyledonous group on the planet it is still limited. Here, we recognized the ecological requirements and modeled the habitat preferences for Catasetum bicolor and C. ochraceum (Subfamily: Epidendroideae). We used climatic and bioclimatic data along with species’ occurrences records in a) Principal Components Analysis (PCA) to screen for the most influential variables; and, b) a maximum entropy algorithm (Maxent) for habitat suitability modeling. Also, preliminary conservation status and probable priority areas for monitoring and conservation were identified. Both species differed in their habitat preferences as shown by the altitudinal range. Factors screened by PCA were associated to temperature (average, minimum, seasonality), solar radiation, and precipitation of the driest and warmest months. The variables that influenced the most in the modeling process for C. bicolor were solar radiation, temperature seasonality, and its annual range; while for C. ochraceum were the precipitation of the driest month and solar radiation. Areas with habitat suitable conditions were identified in countries (Brazil, Colombia, Costa Rica, Ecuador, Nicaragua, Panama, and Venezuela) and biomes (humid and dry tropical, and subtropical forests) with highly dynamic land cover changes. The studied species were found to be in an endangered status based on their area of occupancy (< 76 km2). However, considering their extent of occurrence (> 20000 km2), they are in a status of less concern. These findings may be relevant for future monitoring plans and planning for ex-situ and in-situ conservation strategies.

Habitat Suitability Modeling to Inform Seascape Connectivity Conservation and Management

Coastal habitats have experienced significant degradation and fragmentation in recent decades under the strain of interacting ecosystem stressors. To maintain biodiversity and ecosystem functioning, coastal managers and restoration practitioners face the urgent tasks of identifying priority areas for protection and developing innovative, scalable approaches to habitat restoration. Facilitating these efforts are models of seascape connectivity, which represent ecological linkages across heterogeneous marine environments by predicting species-specific dispersal between suitable habitat patches. However, defining the suitable habitat patches and migratory pathways required to construct ecologically realistic connectivity models remains challenging. Focusing on two reef-associated fish species of the Florida Keys, United States of America (USA), we compared two methods for constructing species- and life stage-specific spatial models of habitat suitability—penalized logistic regression and maximum entropy (MaxEnt). The goal of the model comparison was to identify the modeling algorithm that produced the most realistic and detailed products for use in subsequent connectivity assessments. Regardless of species, MaxEnt’s ability to distinguish between suitable and unsuitable locations exceeded that of the penalized regressions. Furthermore, MaxEnt’s habitat suitability predictions more closely aligned with the known ecology of the study species, revealing the environmental conditions and spatial patterns that best support each species across the seascape, with implications for predicting connectivity pathways and the distribution of key ecological processes. Our research demonstrates MaxEnt’s promise as a scalable, species-specific, and spatially explicit tool for informing models of seascape connectivity and guiding coastal conservation efforts.

Mapping habitat suitability for Asiatic black bear and red panda in Makalu Barun National Park of Nepal from Maxent and GARP models

Habitat evaluation is essential for managing wildlife populations and formulating conservation policies. With the rise of innovative powerful statistical techniques in partnership with Remote Sensing, GIS and GPS techniques, spatially explicit species distribution modeling (SDM) has rapidly grown in conservation biology. These models can help us to study habitat suitability at the scale of the species range, and are particularly useful for examining the overlapping habitat between sympatric species. Species presence points collected through field GPS observations, in conjunction with 13 different topographic, vegetation related, anthropogenic, and bioclimatic variables, as well as a land cover map with seven classification categories created by support vector machine (SVM) were used to implement Maxent and GARP ecological niche models. With the resulting ecological niche models, the suitable habitat for asiatic black bear (Ursus thibetanus) and red panda (Ailurus fulgens) in Nepal Makalu Barun National Park (MBNP) was predicted. All of the predictor variables were extracted from freely available remote sensing and publicly shared government data resources. The modeled results were validated by using an independent dataset. Analysis of the regularized training gain showed that the three most important environmental variables for habitat suitability were distance to settlement, elevation, and mean annual temperature. The habitat suitability modeling accuracy, characterized by the mean area under curve, was moderate for both species when GARP was used (0.791 for black bear and 0.786 for red panda), but was moderate for black bear (0.857), and high for red panda (0.920) when Maxent was used. The suitable habitat estimated by Maxent for black bear and red panda was 716 km2 and 343 km2 respectively, while the suitable area determined by GARP was 1074 km2 and 714 km2 respectively. Maxent predicted that the overlapping area was 83% of the red panda habitat and 40% of the black bear habitat, while GARP estimated 88% of the red panda habitat and 58% of the black bear habitat overlapped. The results of land cover exhibited that barren land covered the highest percentage of area in MBNP (36.0%) followed by forest (32.6%). Of the suitable habitat, both models indicated forest as the most preferred land cover for both species (63.7% for black bear and 61.6% for red panda from Maxent; 59.9% black bear and 58.8% for red panda from GARP). Maxent outperformed GARP in terms of habitat suitability modeling. The black bear showed higher habitat selectivity than red panda. We suggest that proper management should be given to the overlapping habitats in the buffer zone. For remote and inaccessible regions, the proposed methods are promising tools for wildlife management and conservation, deserving further popularization.

Habitat Suitability Modeling for the Feeding Ground of Immature Albacore in the Southern Indian Ocean Using Satellite-Derived Sea Surface Temperature and Chlorophyll Data

In the current study, remotely sensed sea surface ocean temperature (SST) and sea surface chlorophyll (SSC), an indicator of tuna abundance, were used to determine the optimal feeding habitat zone of the southern Indian Ocean (SIO) albacore using a habitat suitability model applied to the 2000–2016 Taiwanese longline fishery data. The analysis showed a stronger correlation between the 2-month lag SSC and standardized catch per unit effort (CPUE) than 0-, 1-, 3-, and 4-month lag SSC. SST also exhibited a stronger correlation with standardized CPUE. Therefore, SST and SSC_2 were selected as final variables for model construction. An arithmetic mean model with SST and SSC_2 was deemed suitable to predict the albacore feeding habitat zone in the SIO. The preferred ranges of SSC_2 and SST for the feeding habitat of immature albacore were 0.07–0.09 mgm−3 and 16.5–18.5 °C, respectively, and mainly centralized at 17.5 °C SST and 0.08 mgm−3 SSC_2. The selected habitat suitability index model displayed a high correlation (R2 = 0.8276) with standardized CPUE. Overall, temperature and ocean chlorophyll were found to be essential for albacore habitat formation in the SIO, consistent with previous studies. The results of this study can contribute to ecosystem-based fisheries management in the SIO by providing insights into the habitat preference of immature albacore tuna in the SIO.

Conservation of endangered Tipton kangaroo rats (Dipodomys nitratoides nitratoides): status surveys, habitat suitability, and conservation recommendations

The Tipton kangaroo rat (Dipodomys nitratoides nitratoides; TKR) is listed as endangered both Federally and by the state of California due to profound habitat loss throughout its range in the southern San Joaquin Valley of California. Habitat loss is still occurring and critical needs for TKR include identifying occupied sites, quantifying optimal habitat conditions, and conserving habitat. Our objectives were to (1) conduct surveys to identify sites where TKR were extant, (2) assess habitat attributes on all survey sites, (3) generate a GIS-based model of TKR habitat suitability, (4) use the model to determine the quantity and quality of remaining TKR habitat, and (5) use these results to develop conservation recommendations. We surveyed for TKR on 44 sites by live-trapping and detected TKR on 15 sites. Sites with TKR tended to have larger alkali scalds and no obvious sign of past tilling compared to sites without TKR. Also, sites with TKR usually had relatively sparse ground cover and seepweed (Suaeda nigra) was present. The non-protected Heermann’s kangaroo rat (Dipodomys heermanni), a larger competitor, was either absent or present in relatively low numbers at sites with TKR, and when present its abundance was inversely related to that of TKR. Based on our habitat suitability modeling, an estimated 30,000 ha of moderately high or high quality TKR habitat and 60,000 ha of lower or medium quality habitat remain. However, habitat is still being lost and conversion of at least one survey site with TKR occurred during this project. Recommendations for TKR conservation are to (1) conduct additional TKR surveys on unsurveyed but suitable sites, (2) conserve suitable habitat on unprotected lands, (3) manage vegetation on occupied sites if necessary, (4) restore disturbed lands to increase suitability for TKR, and (5) research methods and conduct translocations of TKR to unoccupied sites with suitable habitat.

Prediction of leopard habitat suitability in Taman Negara main forest complex, Malaysia

Aim: This research assessed the distribution of leopard to predict the habitat suitability in Taman Negara National Park and adjacent forest area. Methodology: Environmental factors for habitat suitability were derived from geographical information system (GIS) data such as elevation, slope, land-use, distance from urban and distance from river. Leopard presence data from 1993 to 2008 were integrated with the environmental parameters using maximum entropy (MaxEnt) modeling to assess habitat suitability across the study area. Results: The results showed that distance from river contributed the most (39.3%) in the habitat suitability modeling followed by distance from urban (31.4%), elevation (12.3%), land use types (10.1%), and slope (6.9%). Distance from river and urban showed highest contribution that influenced leopard distribution in which most suitable habitat occurred in proximity with river and further from urban. Habitat suitability of leopard were distributed among 48% over 2,218,389 ha of the study area. Interpretation: The findings of this study provides knowledge on how the species move and exploit different habitat niches for more effective conservation management. It provide models for future wildlife conservation and urban planning.

Cyathea Sm. (Cyatheaceae) on Trindade Island (Brazil): An integrative approach

Trindade is a Brazilian oceanic island approximately 1,100 km from the American mainland. The Cyathea Sm. plants from Trindade were originally considered an endemic species, Cyathea copelandii Kuhn & Luerssen, but later included in Cyathea delgadii Sternb. Based on molecular data (trnL-trnF, trnG-trnR and rbcL-accD), morphometric analysis of leaf characters, scanning electron microscopy of indusia and spores, and habitat suitability modeling, the present study confirms the status of C. copelandii as a synonym of C. delgadii. Intraspecific molecular variation suggests phylogeographic structuring in C. delgadii and differentiation between the coastal Atlantic Forest domain and the Cerrado domain (savanna) in the interior of Brazil. The Trindade populations are more closely related to the Atlantic Forest populations, indicating a colonization of the island from the latter area.