Disturbances to wildlife populations and their habitats is an inescapable outcome for a finite earth system which is home to a human population necessitating evermore resources to sustain its wants and needs. Inherently, an EIA serves to enhance the conservation and management of wildlife through careful screening, scoping, prediction, mitigation and monitoring of project activities. To maximize an EIA’s efficacy, valuable tools for collecting and processing data need to be at the disposition of scientists and practitioners. In recent years, models predicting species spatial distribution and habitat requirements have become prominent tools in wildlife management (Syartinilia and Tsuyuki 2008). The Habitat Suitability (HS) model is a perfect example of such a tool. HS models essentially predict the suitability of habitat for a target species based on its known affinities with environmental variables, consequently enabling the prediction of species spatial distribution (Hirzel et al 2006). From such a model can be produced HS maps, like the one seen below which predicts the spatial distribution of the black capped vireo based on vegetation.
Black-capped vireo presence data and predicted probability of vireo presence from a vegetation composition map (VEG, 10-m resolution), LiDAR-derived measures of vegetation structure (LiDAR, 25-m resolution), and a map of soil depth (SOIL DEPTH, 10-m resolution).. (Wilsey et al. 2012)
EIA’s can greatly benefit from such a tool at several steps of its process. During the scoping stage, HS maps can help determine key areas where baseline conditions on wildlife population and their habitats can be gathered. In Sub-Saharan Africa, project alternatives presented for road development used HS maps to account for the habitat preferences of International Union for Conservation of Nature(IUCN) red listed species (Traill and Bigalke 2006). During the prediction and mitigation stage of the EIA, HS models could be used to predict how species will respond to habitat fragmentation (Schadt et al 2006). Habitat models can also be used identify and protect probable corridors between source populations, which is vital to ensure “species survival through maintaining genetic variability and providing a source of individuals to offset losses caused by poaching, predation and accidents (Gavashelishvili and Lukarevskiy 2008). The relocation or repopulation of a disturbed wildlife species into a new suitable environment is another mitigation measure which can be achieved effectively with thorough data pertaining to species-habitat associations. Finally, HS maps can be useful for identifying areas where monitoring of wildlife viability should occur after the project has been implemented.
The use of HS models have been used for impact assessment for many decades, an example being its employment in 1983 by the U.S fish and wildlife service for Coho Salmon (McMahon 1983). Considering that the increased availability of remote sensing data, GIS, and advances in statistical computation capabilities over the decades have permitted the development of more powerful techniques in habitat modeling (Syartinilia and Tsuyuki 2008), HS models should be given considerable attention for EIAs where wildlife viability is at stake.
Gavashelishvili. Alexander and Victor Lukarevskiy (2008) Modelling the habitat requirements of leopard Panthera pardus in west and central Asia. Journal of Applied Ecology. 45: 579-588
Hirzel.H.A, Gwenaelle Le Lay, Veronique Helfera,Christophe Randina, and Antoine Guisana (2006) Evaluating the ability of habitat suitability models to predict species presences. Ecological Modelling. 199: 142-152
Lochran W. Traill and Rudi C. Bigalke (2006) A presence-only habitat suitability model for large grazing African ungulates and its utility for wildlife management. African Journal of Ecology. 45: 347–354
McMahon. T. E. (1983) Habitat suitability index models: Coho salmon. U.S. Dept. Int., Fish Wildl. Servo FWS/OBS-82/10.49 pp:1-29
Stephanie Schadt, Eloy Revilla, Thorsten Wiegand, Felix Knauer, Petra Kaczensky, Urs Breitenmoser, Ludek Bufka, Jaroslav Cerveny , Petr Koubek, Thomas Huber, Cvetko Stanisa and Ludwig Trepl (2002) Assessing the suitability of central European landscapes for the reintroduction of Eurasian lynx. Journal of Applied Ecology. 39: 189-203
Syartinilia and Satoshi Tsuyuki (2008) GIS-based modeling of Javan Hawk-Eagle distribution using logistic and autologistic regression models. Biological conservation 141: 756-769.
Wilsey. B Chad, Joshua J.Lawler, and David A.Cimprich (2012) Performance of habitat suitability models for the endangered black-capped vireo built with remotely-sensed data. Remote Sensing of Environment. 119:35-42