Bismay Tripathy – email@example.com
Already an endangered species, the Asian Elephants (Elephas maximus) continue to be increasingly threatened by habitat degradation, poaching for ivory and conflicts with people (Sukumar 2003; Menon et al., 2017). India harbours 60% of the current Asian elephant population, but only 23% of its elephant habitats reside within protected zones while the rest are perpetually disturbed by escalating anthropogenic pressures (such as expansion of human settlements and agriculture, livestock grazing and fuelwood gathering) and economic activities (mining, construction of road-railway networks etc.). Habitat degradation contributes to increasing elephant encounters with people and triggering human-elephant conflict (HEC). The conflict scenario in India escalates day by day gaining in severity and frequency. In the four-year period between 2015 and 2018 alone, it had caused deaths of around 2,400 people and 490 elephants and annually, 0.5 million households suffered due to crop loss by elephant raiding from 2000 through 2010 (MOEF 2012; MoEF & CC, 2018). Elephants have the capacity to adapt to a mosaic of natural and modified habitats and their preference of habitat selection is often determined by the landscape composition as well as space and resource availability (such as vegetation and water). Thus, comprehension of elephants’ space-use with respect to their distribution is crucial for managing human-wildlife coexistence. We conducted our study on the space-use of elephants in the Keonjhar forest division in eastern India, where several hundreds of elephants have been killed as a result of electrocution, road-train mishaps, poaching and HEC.
Figure. 1: Pattern of estimated elephant occupancy, which was evaluated using the top model for occupancy probability. Keonjhar forest division has seven forest ranges (Barbil, Bhuiyan-Juang Pihra (BJP), Champua, Ghatgaon, Keonjhar, Patna and Telkoi). Five elephant habitat cores (light blue color polygon) were identified and named as CFR, KFR, BFR, GFR and TFR
We used a popular species distribution technique called occupancy modeling, which analyzed the histories of elephant presence or absence on the survey sites (MacKenzie et al. 2017) to estimate the probability of elephant presence and underlying driving factors. For occupancy modeling, we used elephant GPS location at different sites along with anthropogenic and environmental variables, including climate variables such as precipitation data derived from monthly rain gauge data and mean annual temperature from MODIS-MOD11A1. Sentinel-2A satellite images were very helpful for extracting variables such as forests, cropland and settlements.
We observed elephant occupancy in 43% of the study region (about 2710 km2) (Figure 1) and occupancy was found to be higher in the regions with over 40% open forest cover (Figure 2B). It is easy to believe that a mega herbivore species like the elephants would prefer dense forests with minimum anthropogenic disturbances. However, we were surprised to find that elephants were actually drawn towards forests in human dominated landscapes with multiple land-use activities, over relatively intact forests (Sitompul et al., 2013; Huang et al. 2019). Scrubs and grasses, which are a primary forage of elephants, can grow easily in open forests as they receive better space and light conditions. Thus, open forests are the strongest variable influencing elephant occupancy, which specifically plays an important role in providing food and shelter for elephants as well as in their thermoregulation.
Figure. 2: Relationships between elephant detectability and the influential covariates
Furthermore, train-vehicle collisions have been one of the major causes of elephant mortality through the years (Jha et al., 2014; Dasgupta & Ghosh, 2015), so we evidenced a lower elephant occupancy in the regions with denser transportation networks (Figure. 2F). Even though crops are not natural forage for elephants, they preferred crops over grazing on natural forage, due to higher accessibility, palatability and nutrition (Sukumar, 1990; Campos-Arceiz et al., 2008). Thus, elephant detectability near croplands was relatively high.
When it comes to climate variables, we found a positive influence of precipitation on elephant detection, which was contrary to a study conducted in an extremely wet landscape of Southern India, that found how precipitation was the least influential covariate. However, we believe that favourable rainfall conditions improved water availability, while also increasing the productivity of deciduous forests with an abundance of palatable trees (Kumar et al., 2010; Jathanna et al., 2015), which attracted more elephants to these regions in the study area. Therefore, it is reasonable that variations in precipitation will be immediately reflected in the elephants’ space-use as rain-driven vegetation can prompt highly opportunistic elephant movement patterns.
It is very challenging to demarcate exclusive regions for people and elephants within the varying landscapes of India where both human and elephant populations are high. However, owing to the presence of areas which are more frequently used by elephants such as the five habitat cores that we identified in our study (Figure 1), we can conclude that this region still has the potential to support a significant elephant population (Tripathy et al., 2021). Hence, for efficient landscape management and planning it is critical to understand the spatial factors that potentially influence the preference of space-use by elephants in this region which will in turn ensure peaceful coexistence between elephants and people while also facilitating elephant conservation strategies.