Habitat suitability assessment for the endangered Nilgiri Laughingthrush: A multiple logistic regression approach
ABSTRACT Application of remote sensing and Geographic Informa-tion System (GIS) tools has assumed an increasingly important role in conservation biology and wildlife management by providing means for modelling poten-tial distributions of species and their habitats, unlike the conventional ground surveys. We present here a predic-tive model of habitat suitability for the Nilgiri Laugh-ingthrush, Garrulax cachinnans based on a synergistic use of field surveys and digitally processed satellite im-agery combined with features mapped using GIS data layers. Collateral data were created in a GIS framework based on ground surveys comprising layers such as land-use, measures of proximity to likely features of distur-bance and a digital terrain model. Multiple binomial logistic regression approach was used for modelling, and the model performance was assessed by the area under the receiver operating characteristics (ROC) curve. About 320 km 2 , 25.12% of the area of the Nilgiris considered for modelling was predicted to be suitable for the Nilgiri Laughingthrush. The area under the ROC curve was found to be 0.984 ± 0.003 (R 2 : 0.93 at P < 0.0001), implying a highly effective model. The as-sessed suitable habitat was highly fragmented and comprised of 1352 patches (natural as well as man-made) distributed all over the study area. The smallest suitable patch identified by the model was 400 m 2 and the largest patch 17.65 km 2 . Also, ca. 92% of all patches were smaller than 0.5 km 2 . We presume that some suit-able habitat patches may be unoccupied due to strong fidelity of the species to shola (montane wet temperate forest) patches, low colonization rates, or large inter-fragment distances. Also, larger fragments might serve as source or 'exporters' of surplus individuals to main-tain sink populations throughout the rest of the range. We discuss the implication of habitat fragmentation and narrow geographical range and anthropogenic pressure for the conservation of the Nilgiri Laughing-thrush.
Full-textDOI: · Available from: Aditya Singh, Aug 13, 2015
- SourceAvailable from: Satya Kushwaha
- "RS and GIS also help in monitoring areas of land for 35 their suitability to endangered species, through integration of various habitat variables of both spatial and non-spatial nature (Davis et al. 1990). The outputs of such models are usually simple, easily understandable and can be used for the assessment of 40 environmental impacts or prioritisation of conservation efforts in a timely and cost-effective manner (Kushwaha et al. 2004; Zarri et al. 2008). Indian gaur (Bos gaurus) belongs to the Bovidae family and is one among the nine species of wild oxen 45 found in the world. "
Dataset: Ekwal+Kushwaha JAAR
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- "If the value of the index is high on a particular location, then the chance of species occurrence is greater. HSI models use geo-statistics (Kushwaha and others 2004; Habib and others 2010), logistic regression (Zarri and others 2008; Imam and others 2009), refined logistic regression (Singh and Kushwaha 2011), multi-criteria analysis using analytical hierarchy process (AHP) (Nekhaya and others 2009; Goswami 2010) and other data integration techniques to calculate an index of species occurrence (Clark and others 1999; Brown and others 2000) and provide an efficient and inexpensive method for determining habitat quality (Schamberger and Krohn 1982). "
ABSTRACT: 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.Environmental Management 03/2012; 49(4):902-14. DOI:10.1007/s00267-012-9826-5 · 1.65 Impact Factor
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- "Thus quantifying the amount of potential habitat available. In India recently, Kushwaha et al. (2004), Aditya (2004), Quadri (2004), Braunisch et al. (2008) and Zarri et al. (2008) have used " binomial multiple logistic regression " to analyze habitat suitability for Cervus unicolor and Muntiacus muntjac at Ranikhet, muntjac in Binsor Wildlife Sanctuary, tiger in Corbett Tiger Reserve, edge effect on two population of capercaillie (Tetrao urogallus) and Nilgiri laughingthrush (Garrulax cachinnans) in Western Ghats respec- tively. "
ABSTRACT: Application of remote sensing and Geographic Information System (GIS) as a tool has assumed an immense significance in habitat suitability modelling for various wildlife species and now a days these are widely used in conservation biology and wildlife management.This paper evaluates habitat suitability for tigers (Panthera tigris tigris) in Chandoli National Park, India. This research provides information about potential areas that can be declared as Tiger Reserve, a federal designation of protection. Habitat evaluation was completed in the Chandoli National Park (17° 04′ 00″ N to 17° 19′ 54″ N and 73° 40′ 43″ E to 73° 53′ 09″ E) using habitat suitability index (HSI). Remotely sensed data of satellite IRS-P6, LISS-III of 25th February 2005 was procured from National Remote Sensing Agency, India. The satellite imagery data was digitally processed and collateral data were generated from topographic maps in a GIS framework. Various layers of different variables such as landuse land cover, forest density, measures of proximity to disturbances and water resources and a digital terrain model were created based on ground truthing. These layers, GPS location of animal's presence and “binomial multiple logistic regression (BMLR)” techniques were integrated in a GIS environment for the HSI modelling.Results indicate that approximately 160.48 km2 (55%) of the forest of Chandoli National Park is highly suitable for herbivores population, and 176.52 km2 (50%) of the Park is suitable for tigers. Therefore, this study concludes that forest areas within the Chandoli National Park are appropriate for consideration as Tiger Reserve.Furthermore, the identification and mapping of wildlife corridors and other forest patches lying in between neighboring protected area like Koyana sanctuary, suggests that these region of Sahyadri range of Western Ghats should be included into the proposed Tiger Reserve. This will be a benefit for tigers, as tigers require larger and least disturbed forest habitats for establishing and maintaining their high-density population. Fortunately, in May 2008 the Government of India declared Chandoli NP as tiger reserve. Thus declaration of Chandoli National Park as a Tiger Reserve reflects that the habitat suitability model developed by us for tiger was not only statistically sound but also has potential to be considered while taking any decision regarding wildlife habitat management.Ecological Modelling 12/2009; 220(24):3621–3629. DOI:10.1016/j.ecolmodel.2009.06.044 · 2.07 Impact Factor