Monitoring the Chilla–Motichur wildlife corridor using geospatial tools

Land Use/Cover Change Reduces Elephant Habitat Suitability in the Wami Mbiki–Saadani Wildlife Corridor, Tanzania

Wildlife corridors are critical for maintaining the viability of isolated wildlife populations and conserving ecosystem functionality. Anthropogenic pressure has negatively impacted wildlife habitats, particularly in corridors between protected areas, but few studies have yet quantitatively assessed habitat changes and corresponding wildlife presence. We quantified land use/land cover and human–elephant conflict trends over the past two decades in the Wami Mbiki–Saadani (WMS) wildlife corridor, Tanzania, using RS and GIS combined with human–wildlife conflict reports. We designed landscape metrics and habitat suitability models for the African savanna elephant (Loxodonta africana) as a large mammal key species in the WMS ecosystem. Our results showed that forest cover, a highly suitable habitat for elephants, decreased by 3.0% between 1998 and 2008 and 20.3% between 2008 and 2018. Overall, the highly suitable habitat for elephants decreased by 22.4% from 1998 to 2018, when it was scarcely available and when small fragmented patches dominated the unprotected parts of the corridor. Our findings revealed that large mammalian habitat conservation requires approaches beyond habitat-loss detection and must consider other facets of landscape patterns. We suggest strengthening elephant habitat conservation through community conservation awareness, wildlife corridor mapping, and restoration practices to ensure a sustainable pathway to human–wildlife coexistence.

Monitoring and predicting regional land use and land cover changes in an estuarine landscape of India

Deciphering land use and land cover (LULC) change patterns, identifying the variables that act as the major driving forces of change, and predicting possible changes are necessary tools of decision support for policymakers. Estuarine landscapes world over are under extreme pressure of developmental activities because of their resources. The developmental activities lead to unforeseen changes in the traditional land use practices, making it necessary for investigation of the possible outcomes. The present study aims to study the changing pattern of LULC in the East Godavari River Estuarine Ecosystem (EGREE) landscape during 1977-2015 using temporal satellite data and to predict the possible LULC changes by 2029. Cellular Automata-Markov model (CAMM) with and without the multi-criteria evaluator (MCE) and the multi-layer perceptron (MLP) models were used for future LULC prediction. Between 1977 and 2015, mangroves were converted to aquaculture (5.81 km²) on the landward side and were also lost to submergence at the seaward side (15 km²). All of the coastal scrub (69 km²) was lost to beach clearing. Over this period, the aquaculture area rose to 177 km². The CAMM with MCE was found to yield better predictions. A further rise was predicted in aquaculture (16%), built-up (30%), and Casuarina plantations (28%) by 2029. The study highlighted the LULC change patterns in EGREE, an important estuarine landscape of India. The information generated in this study can act as baseline information for the stakeholders and policy makers in decision-making of developmental projects, land acquisition, and diversion of agricultural land to non-agricultural purposes.

Predicting the deforestation probability using the binary logistic regression, random forest, ensemble rotational forest, REPTree: A case study at the Gumani River Basin, India

Rapid population growth and its corresponding effects like the expansion of human settlement, increasing agricultural land, and industry lead to the loss of forest area in most parts of the world especially in such highly populated nations like India. Forest canopy density (FCD) is a useful measure to assess the forest cover change in its own as numerous works of forest change have been done using only FCD with the help of remote sensing and GIS. The coupling of binary logistic regression (BLR), random forest (RF), ensemble of rotational forest and reduced error pruning trees (RTF-REPTree) with FCD makes it more convenient to find out the deforestation probability. Advanced vegetation index (AVI), bare soil index (BSI), shadow index (SI), and scaled vegetation density (VD) derived from Landsat imageries are the main input parameters to identify the FCD. After preparing the FCDs of 1990, 2000, 2010 and 2017 the deforestation map of the study area was prepared and considered as dependent parameter for deforestation probability modelling. On the other hand, twelve deforestation determining factors were used to delineate the deforestation probability with the help of BLR, RF and RTF-REPTree models. These deforestation probability models were validated through area under curve (AUC), receiver operating characteristics (ROC), efficiency, true skill statistics (TSS) and Kappa co-efficient. The validation result shows that all the models like BLR (AUC = 0.874), RF (AUC = 0.886) and RTF-REPTree (AUC = 0.919) have good capability of assessing the deforestation probability but among them, RTF-REPTree has the highest accuracy level. The result also shows that low canopy density area i.e. not under the dense forest cover has increased by 9.26% from 1990 to 2017. Besides, nearly 30% of the forested land is under high to very high deforestation probable zone, which needs to be protected with immediate measures.

Assessment of historical forest cover loss and fragmentation in Asian elephant ranges in India

India is home of the largest remaining population of the Asian elephant (Elephas maximus L.) in the South and Southeast Asia. The forest loss and fragmentation is the main threat to the long-term survival of Asian elephants. In the present study, we assessed forest loss and fragmentation in the major elephant ranging provinces in India, viz., north-eastern, north-western, central, and southern since the 1930s. We quantified forest cover changes by generating and analyzing forest cover maps of 1930, 1975, and 2013, whereas fragmentation of contiguous forest areas was quantified by applying landscape metrics on the temporal forest cover maps. A total of 21.49% of the original forest cover was lost from 1930 to 1975, while another 3.19% forest cover was lost from 1975 to 2013 in the elephant ranges in India. The maximum forest loss occurred in the southern range (13,084 km²) followed by north-eastern (10,188 km²), central (5614 km²), and north-western (4030 km²) elephant ranges in the past eight decades. The forests in the central range were the most fragmented followed by southern, north-eastern, and north-western elephant ranges. The forest fragmentation in the southern range occurred at the fastest rate than central, north-eastern, and north-western ranges. The core forest areas shrunk by 39.6% from 1930 to 2013. The causative factors of forest change and situation of elephant-human conflict have been discussed. Study outcomes would be helpful in planning effective conservation strategies for Asian elephants in India.

Losing time for the tiger Panthera tigris: delayed action puts a globally threatened species at risk of local extinction

Meeting global and regional environmental targets is challenging, given the multiplicity of stakeholders and their diverse and often competing policy agendas and objectives. Relatively few studies have sought to systematically analyse the progress, or lack thereof, of institutionally complex and diffuse projects. Here we analyse one such project, which aims to protect and restore a critical landscape corridor for tigers Panthera tigris in north-western India, using a temporal–analytic framework that integrates ecological information on species population status and spatial connectivity modelling with a systematic examination of the decision-making process. We find that even with adequate ecological knowledge the tiger population is on the verge of local extinction because of weak institutional support, poor adaptive planning and ineffective leadership in a complex political arena, which has led to delays in conservation action. From the outset the conservation agencies and NGOs that were the primary drivers of the project lacked awareness of the political idiosyncrasies of coordinating the actions of disparate agencies within the decision-making process. To secure better future environmental outcomes we recommend the adoption of an improved project appraisal methodology that explicitly encompasses an evaluation of organizational incentives, to determine political buy-in, including alignment with organizational objectives and funding availability.

Identification of swamp deer (Cervus duvauceli duvauceli Cuvier) potential habitat in Jhilmil Jheel Conservation Reserve, Uttarakhand, India using multi-criteria analysis

The present study aims to identify the potential habitat for swamp deer (Cervus duvauceli duvauceli Cuvier) in Jhilmil Jheel Conservation Reserve in the Uttarakhand province of India using multi-criteria analysis. The study area represents one of the last remnant habitats of the flagship species, the swamp deer in Uttarakhand, which is considered as vulnerable. The study showed that only 6.08% of the study area (225 km(2)) was highly suitable to suitable for the swamp deer. An area of 135.52 km(2) (60.23%) turned out to be moderately suitable. Within the officially designated Conservation Reserve (area 37.84 km(2)), 10.91% (4.13 km(2)) area was found highly suitable to suitable, while 74.19% (28.07 km(2)) happens to be moderately suitable. Only 14 km(2) area, which was found as suitable habitat for swamp deer falls short of the space required by a population of 134 animals. The problem could be mitigated if the agricultural land (2.47 km(2)) adjacent to the Jhilmil Jheel is brought under the Reserve management. This would provide additional area to meet the fodder requirement. The study brings out a particularly grim situation with limited options for conservation and management of the swamp deer in the Indo-Gangetic plains. It also emphasizes the role of geospatial techniques in quick appraisal of habitat attributes and identification of potential sites for protected areas.