Saurabh Shanu

Bio: Saurabh Shanu is an academic researcher from University of Petroleum and Energy Studies. The author has contributed to research in topics: Wildlife corridor & Habitat fragmentation. The author has an hindex of 2, co-authored 10 publications receiving 13 citations.

A Computational Approach for Designing Tiger Corridors in India

Abstract: Wildlife corridors are components of landscapes, which facilitate the movement of organisms and processes between intact habitat areas, and thus provide connectivity between the habitats within the landscapes. Corridors are thus regions within a given landscape that connect fragmented habitat patches within the landscape. The major concern of designing corridors as a conservation strategy is primarily to counter, and to the extent possible, mitigate the effects of habitat fragmentation and loss on the biodiversity of the landscape, as well as support continuance of land use for essential local and global economic activities in the region of reference.

A Computational Approach for Designing Tiger Corridors in India

Abstract: Wildlife corridors are components of landscapes, which facilitate the movement of organisms and processes between intact habitat areas, and thus provide connectivity between the habitats within the landscapes. Corridors are thus regions within a given landscape that connect fragmented habitat patches within the landscape. The major concern of designing corridors as a conservation strategy is primarily to counter, and to the extent possible, mitigate the effects of habitat fragmentation and loss on the biodiversity of the landscape, as well as support continuance of land use for essential local and global economic activities in the region of reference. In this paper, we use game theory, graph theory, membership functions and chain code algorithm to model and design a set of wildlife corridors with tiger (Panthera tigris tigris) as the focal species. We identify the parameters which would affect the tiger population in a landscape complex and using the presence of these identified parameters construct a graph using the habitat patches supporting tiger presence in the landscape complex as vertices and the possible paths between them as edges. The passage of tigers through the possible paths have been modelled as an Assurance game, with tigers as an individual player. The game is played recursively as the tiger passes through each grid considered for the model. The iteration causes the tiger to choose the most suitable path signifying the emergence of adaptability. As a formal explanation of the game, we model this interaction of tiger with the parameters as deterministic finite automata, whose transition function is obtained by the game payoff.

An Automated Animal Classification System: A Transfer Learning Approach

Abstract: Animal classification from images obtained by various techniques in forest become an important task to carry out focused distribution and abundance estimation. In the following paper a frame work based on Transfer Learning (TL) in a Convolutional Neural Network is proposed for the construction of an automated animal identification system. The framework is used to analyze & identify focal species in the images. A dataset of 6,203 camera trap images of 11 species including Wild pig, Barking deer, Chital, Elephant, Gaur, Hare, Jackal, Jungle cat, Porcupine, Sambhar, Sloth bear was obtained. Superior performance can be achieved by using Transfer learning in Deep Convolutions Neural Network (DCNN) for species classification. The accuracy achieved by the proposed model on the test dataset is 96% in 18 epochs by using batch-size of 32. This, in turn, can speed up research findings, construct more efficient and reliable animal monitoring systems, and consequently, save the time and effort of the Indian scientists. Therefore, having the potential to make significant impacts in the classification and analysis of camera trap images of the site under observation.

A graph theoretic approach for modelling wildlife corridors

Abstract: Wildlife corridors are components of landscapes, which facilitate the movement of organisms and processes between areas of intact habitat, and thus provide landscape corridor. Corridors are thus regions within a given landscape that generally comprise native vegetation, and connect otherwise fragmented, disconnected, non-contiguous wildlife habitat patches in the landscape. The purpose of designing corridors as a conservation strategy is primarily to counter, and to the extent possible, mitigate the impacts of habitat fragmentation and loss on the biodiversity of the landscape, as well as support continuance of land use for essential local and global economic activities in the region of reference. In this paper, we use game theory and graph theory to model and design a wildlife corridor network in the Central India Eastern Ghats landscape complex, with tiger (Panthera tigris tigris) as the focal species. We construct a graph using the habitat patches supporting wild tiger populations in the landscape complex as vertices and the possible paths between these vertices as edges. A cost matrix is constructed to indicate the cost incurred by the tiger for passage between the habitat patches in the landscape, by modelling a two-person Prisoners Dilemma game. A minimum spanning tree is then obtained by employing Kruskals algorithm, which would suggest a feasible tiger corridor network for the tiger population within the landscape complex. Additionally, analysis of the graph is done using various centrality measures, in order to identify and focus on potentially important habitat patches, and their potential community structure. Correlation analysis is performed on the centrality indices to draw out interesting trends in the network.

Data from: Prioritizing tiger conservation through landscape genetics and habitat linkages

Abstract: Even with global support for tiger (Panthera tigris) conservation their survival is threatened by poaching, habitat loss and isolation. Currently about 3,000 wild tigers persist in small fragmented populations within seven percent of their historic range. Identifying and securing habitat linkages that connect source populations for maintaining landscape-level gene flow is an important long-term conservation strategy for endangered carnivores. However, habitat corridors that link regional tiger populations are often lost to development projects due to lack of objective evidence on their importance. Here, we use individual based genetic analysis in combination with landscape permeability models to identify and prioritize movement corridors across seven tiger populations within the Central Indian Landscape. By using a panel of 11 microsatellites we identified 169 individual tigers from 587 scat and 17 tissue samples. We detected four genetic clusters within Central India with limited gene flow among three of them. Bayesian and likelihood analyses identified 17 tigers as having recent immigrant ancestry. Spatially explicit tiger occupancy obtained from extensive landscape-scale surveys across 76,913 km2 of forest habitat was found to be only 21,290 km2. After accounting for detection bias, the covariates that best explained tiger occupancy were large, remote, dense forest patches; large ungulate abundance, and low human footprint. We used tiger occupancy probability to parameterize habitat permeability for modeling habitat linkages using least-cost and circuit theory pathway analyses. Pairwise genetic differences (F ST) between populations were better explained by modeled linkage costs (r>0.5, p<0.05) compared to Euclidean distances, which was in consonance with observed habitat fragmentation. The results of our study highlight that many corridors may still be functional as there is evidence of contemporary migration. Conservation efforts should provide legal status to corridors, use smart green infrastructure to mitigate development impacts, and restore habitats where connectivity has been lost.

Perceived-Value-driven Optimization of Energy Consumption in Smart Homes

Abstract: Residential energy consumption has been rising rapidly during the last few decades. Several research efforts have been made to reduce residential energy consumption, including demand response and smart residential environments. However, recent research has shown that these approaches may actually cause an increase in the overall consumption, due to the complex psychological processes that occur when human users interact with these energy management systems. In this article, using an interdisciplinary approach, we introduce a perceived-value driven framework for energy management in smart residential environments that considers how users perceive values of different appliances and how the use of some appliances are contingent on the use of others. We define a perceived-value user utility used as an Integer Linear Programming (ILP) problem. We show that the problem is NP-Hard and provide a heuristic method called COndensed DependencY (CODY). We validate our results using synthetic and real datasets, large-scale online experiments, and a real-field experiment at the Missouri University of Science and Technology Solar Village. Simulation results show that our approach achieves near optimal performance and significantly outperforms previously proposed solutions. Results from our online and real-field experiments also show that users largely prefer our solution compared to a previous approach.

Trends in Wildlife Connectivity Science from the Biodiverse and Human-Dominated South Asia

Abstract: The threat of habitat fragmentation and population isolation looms large over much of biodiversity in this human-dominated epoch. Species-rich South Asia is made particularly vulnerable by its high human density and anthropogenic habitat modification. Therefore, reliably estimating wildlife connectivity and the factors underpinning it become crucial in mitigating extinction risk due to isolation. We analysed peer-reviewed literature on connectivity and corridors for terrestrial mammals in South Asia to identify trends in connectivity research. We identify key research gaps and highlight future directions that may aid efforts to robustly study connectivity. We found a significant bias towards charismatic megafauna and their habitats. Methodologically, although we observed a range of approaches reflecting some of the advances and innovations in the field, several studies lacked data on animal movement/behaviour, leading to potentially biased inferences of how species disperse through human-modified landscapes. New avenues for connectivity research, though currently under-explored in South Asia, offer alternatives to the heavily used but less-reliable habitat suitability models. We highlight the advantages of landscape genetic methods that reflect effective dispersal and are made feasible through non-invasive and increasingly more cost-effective sampling methods. We also identify important gaps or areas of focus that need to be addressed going forward, including accounting for animal movement/behaviour, human impacts and landscape change for dynamic and adaptive connectivity planning for the future.

The Review of Ecological Network Indicators in Graph Theory Context: 2014–2021

Abstract: Graph theory (GT) is extensively applied in the ecological network analysis. This review study aimed to examine GT in the field of ecological network analysis based on the following questions: In what areas are the articles focused?, what indexes or graph-based indicators have been thus far utilized in ecological network analysis?, and what aspects of ecological network analysis have been less considered in terms of the use of the GT indicators? To address these questions, a systematic literature review was conducted and the results showed that most of the articles in this field had been fulfilled in China, the United States, and France. This theory could have implications for more research on plants and mammals. In addition, 118 indicators were identified in the field of GT in the ecological network analysis. Among these indicators, the probability of connectivity (PC) and an integral index of connectivity (IIC) had been consistently exploited in most articles. Moreover, the results revealed the increasing trend of introducing the new indicators of GT to ecological network analysis, suggesting the applicability of GT in this context. Despite the importance of ecological network resilience, it has been less reflected from the GT perspective while it can be useful and efficient in analyzing the sustainability of ecological networks within this framework. The current trend of exploiting the GT indicators delineates three future lines of development, viz. (1) the GT use more widely in ecological network analysis, (2) emerging new and more precise indexes, and (3) new concerns mainly examining ecological network resilience.