Habitat suitability of Proboscis monkey (Nasalis larvatus) in Berau Delta, East Kalimantan, Indonesia

The proboscis monkey (Nasalis larvatus) is an endemic species to Borneos’ island and is largely confined to mangrove, riverine, and swamp forest. Most of their habitat is outside the conservation due to degraded and habitat converted. Habitat loss is a significant threat to a decreased in the monkey's population. Berau Delta is an unprotected habitat of proboscis monkey, lacking in attention and experiencing a lot of disturbances. This study was conducted on April – August 2019; with aims of the study is to determine Species Distribution Modeling (SDM) for identifying proboscis monkey habitat suitability in Delta Berau, East Kalimantan. The MaxEnt algorithm was used to produce a habitat suitability map based on this species’ occurrence records and environmental predictors. We built the models using 208 points of proboscis monkey presence and 12 environment variables within the study area. Model performance was assessed by examining the area under the curve. The variables most influencing the habitat suitability model were the riverine habitat (60.9%), distance from the pond (16.0%), and distance from the coastline (5.2%). The proboscis monkey suitable habitat is only 9.32% (8,726.58 ha) from 93,631.41 ha total area. The appropriate habitat areas are Sapinang Island, Bungkung Island, Sambuayan Island, Saodang Kecil Island, Besing Island, Lati River, Bebanir Lama, Batu-Batu, and Semanting Bay. We provide some suggestions for the proboscis monkey conservation, which are local protection of uninhabited islands, participatory ecotourism management, and company involvement in protection and management efforts.

Identifying Priority Landscapes for Conservation of Snow Leopards in Pakistan

Pakistan’s total estimated snow leopard habitat is about 80,000 km2 of which about half is considered prime. However, this preliminary demarcation was not always in close agreement with the actual distribution—the discrepancy may be huge at the local and regional level. Recent technological developments like camera trapping and molecular genetics allow for collecting reliable presence records that could be used to construct realistic species distribution based on empirical data and advanced mathematical approaches like MaxEnt. Current study followed this approach to construct accurate distribution of the species in Pakistan. Moreover, movement corridors, among different landscapes, were also identified through the circuit theory. The habitat suitability map, generated from 384 presence points and 28 environmental variables, scored the snow leopard’s assumed range in Pakistan, from 0 to 0.97. A large shear of previously known range represented low-quality habitat, including areas in lower Chitral, Swat, Astore and Kashmir. Conversely, Khunjerab, Misgar, Chapursan, Qurumber, Broghil, and Central Karakoram represented high-quality habitats. Variables with higher contribution in the MaxEnt model were precipitation of driest month (34%), annual mean temperature (19.5%), mean diurnal range of temperature (9.8%), annual precipitation (9.4%) and river density (9.2). The validation texts suggest a good model fit, and strong prediction power.The connectivity analysis revealed that the population in the Hindukush landscape appears to be more connected with the population in Afghanistan as compared to other populations in Pakistan. Similarly, the Pamir-Karakoram population is better connected with China and Tajikistan, while the Himalayan population was with the population in India.Current study allows for proposing three model landscapes to be considered under GSLEP agenda as regional priority areas, to safeguard safeguard future of the species in the long run. These landsacpes fall in mountain ranges of the Himalaya, Hindu Kush and Karakoram-Pamir, respectively. We also identified gaps in existing protected areas network, and suggest new protected areas in Chitral and Gilgit-Baltistan to protect critical habitats of snow leopard in Pakistan.

SEAGRASS HABITAT SUITABILITY MAP AT MERAMBONG SHOAL, JOHOR: A PRELIMINARY STUDY USING MULTIBEAM ECHOSOUNDER AND MAXENT MODELLING

In recent years, there has been an increasing interest to use high-resolution multibeam dataset and Species Distribution Modelling (SDM) for seagrass habitat suitability model. This requires a specific variable derived from multibeam data and in-situ seagrass occurrence samples. The purpose of this study was (1) to derive variables from multibeam bathymetry data to be used in seagrass habitat suitability model, (2) to produce seagrass habitat suitability model using Maximum Entropy (MaxEnt), and (3) to quantify the contribution of each variable for predicting seagrass habitat suitability map. The study area was located at Merambong Shoal, covering an area of 0.04 km2, situated along Johor Strait. First, twelve (12) variables were derived from bathymetry data collected from multibeam echosounder using Benthic Terrain Modeller (BTM) tool. Secondly, all variables and seagrass occurrence samples were integrated in MaxEnt to produce seagrass habitat suitability map. The results showed that the Area Under Curve (AUC) values based on training and test data were 0.88 and 0.65, respectively. The northwest region of survey area indicated higher habitat suitability of seagrass, while the southeast region of survey area indicated lower suitability. Bathymetry mean found to be the most contributed variables among others. The spatial distribution of seagrass from modelling technique agreed with the previous studies and they are found to be distributed at depths ranging from 2.2 to 3.4 meters whilst less suitable with increasing of water depth. This study concludes that seagrass habitat suitability map with high-resolution pixel size (0.5 meter) can be produced at Merambong Shoal using acoustic data from multibeam echosounder coupled with MaxEnt and underwater video observations.

Application of Least-Cost Movement Modeling in Planning Wildlife Mitigation Measures along Transport Corridors: Case Study of Forests and Moose in Lithuania

The present work presents the development of a moose movement model to explore the value of wildlife mitigation structures and examine how hypothetical changes in land use patterns could alter wildlife habitats at landscape scales. Collisions between vehicles and animals pose a threat to humans and wildlife populations, the most dangerous collisions being with moose. Migrations of moose are generally predictable and habitat-dependent. Here, we use GIS-based simulations of moose movements to examine road-related habitat fragmentation around the main highways A1 and A2 in Lithuania. From forest data, we develop a moose habitat suitability map. Then, by running multiple simulation iterations, we generate potential moose pathways and statistically describe the most efficient potential long-range movement routes that are based on the principles of habitat utilization. Reflecting the probabilities of cross-highway moose movement, ranks are assigned to all 1 km highway segments, characterizing them in terms of their likelihood of moose movement, and thus identifying discrete migration corridors and highway crossing zones. Bottlenecks are identified through simulation, such as where sections of wildlife fencing end without highway crossing structures, thereby creating a ‘spillover’ effect, i.e., moose moving parallel to the highway, then crossing. The tested model has proven the prognostic capacity of the tool to foresee locations of moose-vehicle collisions with high accuracy, thus allowing it to be a valuable addition to the toolbox of highway planners.

Maxent Data Mining Technique and Its Comparison with a Bivariate Statistical Model for Predicting the Potential Distribution of Astragalus Fasciculifolius Boiss. in Fars, Iran

The identification of geographical distribution of a plant species is crucial for understanding the importance of environmental variables affecting plant habitat. In the present study, the spatial potential distribution of Astragalus fasciculifolius Boiss. as a key specie was mapped using maximum entropy (Maxent) as data mining technique and bivariate statistical model (FR: frequency ratio) in marl soils of southern Zagros, Iran. The A. fasciculifolius locations were identified and recorded by intensive field campaigns. Then, localities points were randomly split into a 70% training dataset and 30% for validation. Two climatic, four topographic, and eight edaphic variables were used to model the A. fasciculifolius distribution and its habitat potential. Maps of environmental variables were generated using Geographic Information System (GIS). Next, the habitat suitability index (HSI) maps were produced and classified by means of Maxent and FR approaches. Finally, the area under the receiver operating characteristic (AUC-ROC) curve was used to compare the performance of maps produced by Maxent and FR models. The interpretation of environmental variables revealed that the climatic and topographic parameters had less impact compared to edaphic variables in habitat distribution of A. fasciculifolius. The results showed that bulk density, nitrogen, acidity (pH), sand, and electrical conductivity (EC) of soil are the most significant variables that affect distribution of A. fasciculifolius. The validation of results showed that AUC values of Maxent and FR models are 0.83 and 0.76, respectively. The habitat suitability map by the better model (Maxent) showed that areas with high and very high suitable classes cover approximately 22% of the study area. Generally, the habitat suitability map produced using Maxent model could provide important information for conservation planning and a reclamation project of the degraded habitat of intended plant species. The distribution of the plants identifies the water, soil, and nutrient resources and affects the fauna distribution, and this is why it is relevant to research and to understand the plant distribution to properly improve the management and to achieve a sustainable management.

Preferencia de hábitat del murciélago hortelano meridional Eptesicus isabellinus (Temminck, 1840) en ambientes mediterráneos semiáridos

Several molecular studies have recently reported the presence of a second species of the genus Eptesicus in the Iberian peninsula, the meridional serotine bat, E. isabellinus. This species is present in the south of Iberia and it seems to have an allopatric distribution with its twin species, E. serotinus. Ecological studies are now needed to understand the biology of E. isabellinus in southeast Spain. In this study, we used presence–only data for E. isabellinus to perform an ecological niche factor analysis (ENFA) and to create a habitat suitability map (HSM). Our results show that the species has a low marginality index, suggesting it is well adapted to the semiarid conditions of the study area. The main habitats used by E. isabellinus are water courses, scrublands, and zones with high primary productivity. The species avoids non–irrigated cropland and shows no preference for human settlements or irrigated cropland. This study provides information about the ecology of E. isabellinus in southeast Spain and allows us to discuss relevant aspects for its conservation.

Identifying Potential Habitat for the Endangered Aleutian Shield Fern Using Topographical Characteristics

The Aleutian shield fern Polystichum aleuticum is endemic to the Aleutian archipelago of Alaska and is listed as endangered pursuant to the U.S. Endangered Species Act. Despite numerous efforts to discover new populations of this species, only four known populations are documented to date, and information is needed to prioritize locations for future surveys. Therefore, we incorporated topographical habitat characteristics (elevation, slope, aspect, distance from coastline, and anthropogenic footprint) found at known Aleutian shield fern locations into a Geographical Information System (GIS) model to create a habitat suitability map for the entirety of the Andreaonof Islands. A total of 18 islands contained 489.26 km2 of highly suitable and moderately suitable habitat when weighting each factor equally. This study reports a habitat suitability map for the endangered Aleutian shield fern using topographical characteristics, which can be used to assist current and future recovery efforts for the species.

Climate change threatens the survival of highly endangered Sardinian populations of the snake Hemorrhois hippocrepis

Sardinian populations of the snake Hemorrhois (= Coluber) hippocrepis are likely the most endangered populations of snakes in Italy. Major threats to survivorship are the anthropogenic habitat alteration and the extremely low population density, while nothing is known about the potential effects that climate change could exert on this species. The main goal of this paper is to provide helpful instruments for the short- and long-term conservation of H. hippocrepis in Sardinia. By means of an ecological modeling approach, we derived the Sardinian whip snake habitat suitability map, and we compared the potential range extent under present condition and future climatic scenarios. Results clearly show an alarming trend for H. hippocrepis conservation: changing climate conditions will cause a dramatic reduction on suitable surface since 2020, with a further collapse by 2050 (down to 11 km2). We also identified areas of species potential persistence up till 2050, where prospective management initiatives could have the greatest probability of success in this region. In particular, only one existing protected area will likely still keep suitable habitats for H. hippocrepis. Therefore, we suggest that very careful management of this relictual area should be implemented by now if we really want to save these exceedingly threatened snake populations.