“Spatial Prediction of Rufous Bristlebird Habitat in a Coastal Heathland: a GIS-Based Approach” Gibson, L. A., B. A. Wilson, D. M. Cahill, J. Hill.  2004. Journal of Applied Ecology 41:  pp. 213-223.

The article focused on the rufous bristlebird, which is a threatened species of ground dwelling bird in southwest Australia.  In order to conserve the remaining population, the authors created a predictive model using a logistical regression coupled with habitat requirements of the bird with GIS to generate a spatial configuration of suitable habitat.  The researchers surveyed the study area to determine the location and abundance of rufous bristlebird to establish a baseline in order to check the their model.  Terrain attributes used to determine suitable habitat include a 20m resolution DEM, hydrology information, and vegetative information.  The authors then used a statistical regression model based on the five dependent variables used in a GIS analysis with the independent variable of bird presence or absences.  Taking the weighted terrain attribute information and applying the output to an inverse logistic transformation, the authors were able to create a probability scale for suitable habitat.  Results of the model were then checked with field surveys and a strong correlation between model and the field results were found.  The goal of the researchers was to use this model in order to identify corridors of habitat in order to prevent rufous bristlebird populations from becoming isolated.

“Predictive mapping of powerful owl (Ninox Strenua) breeding sites using Geographical Information Systems (GIS) in urban Melbourne, Australia” Isaac, B., R. Cooke, D. Simmons, F. Hogan.  2008. Landscape and Urban Planning 84: pp. 212-218.

The focus of the article is the use of GIS to predict suitable of breeding habitat in urban and urban fringe areas for the powerful owl in Melbourne.  The authors contend that with the continued growth of urban landscapes it will be necessary to examine how species are adapting to this new environment and therefore wanted to discern if a predictive habitat suitability model could be constructed.  From successful powerful owl breeding sites in the wild, the researchers examined and compiled the physical elements of the sites in order to create a predictive GIS model then applied those attributes to the urban landscape of Melbourne.  After creating a predictive map of the urban and urban fringe area, the authors then validated the model using historical records and field observations and found that 76% of all of historical powerful owl breeding sites were within the predictive model areas.  The paper concluded with the discussion that powerful owls have a chance to thrive in an urban environment with the next step being an examination of breeding success in artificial nest boxes placed in areas of identified as highly suitable habitat.

“The State of Lemur Conservation in South-eastern Madagascar:  Population and Habitat Assessments for Diurnal and Cathmeral Lemurs Using Surveys, Satellite Imagery and GIS” Irwin, M. T., S. E. Johnson, P. C. Wright.  2005.  Oryx 39 (2): pp204-218

The island of Madagascar has a unique and diverse population of Lemurs, but continued habitat destruction threatens the ecosystem on which these animals depend.  The focus of the paper is to provide an assessment of lemur populations through the use of census data and vegetation characterization of habitat in a GIS to estimate lemur populations and identify suitable remaining areas for conservation.  The researchers conducted transects in the study area in order to estimate lemur population densities.  For habitat assessment, the authors analyzed six satellite images taken of the area and performed a vegetation classification to indentify forested areas.  The six maps were joined to produce an available habitat layer for different lemur populations.  In addition, the researchers also added a digital elevation component in order to help classify the type of forest that needed to be protected.  From the analysis, the authors concluded habitat loss, fragmentation, habitat disturbance, and hunting will continue to threaten lemur populations.  The habitat analysis of south-eastern Madagascar will provide data to help conservation programs identify key areas that need to be protected in order to ensure the survival of lemur populations in the study area.

“GIS Habitat Analysis for Lesser Prairie-Chickens in Southwestern New Mexico” Johnson, K., T. B. Neville, P. Neville. 2006.  BMC Ecology 6 (18): pp. 1-17.

Through the use of GIS analysis, researchers were able to identify habitat that would be suitable for lesser prairie-chicken (LPCH) conservation planning. Using existing research, the authors were able to discern LPCH preferred shin-oak sand sagebrush areas.  For the GIS habitat analysis two types of imagery were used, Landsat Enhanced Thematic Mapper+ satellite imagery at 30m x 30m resolution and digital aerial photos at 1-m spatial resolution.  After applying the attributes that defined LPCH habitat, the researchers then removed areas that were used for agriculture, suitable for oil and gas exploration or large population areas.  The paper concluded that currently 16% of land was quality habitat for LPCH, but habitat patches were identified for possible restoration that could increase the current habitat for the LPCH in New Mexico.

“A spatial Model to Prioritize Sagebrush Landscapes in the Intermountain West (U.S.A.) for Restoration” Meinke, C. W., S. T. Knick, D. A. Pyke.  2008. Restoration Ecology

The intent of the authors was to identify sagebrush habitat throughout the intermountain west that would be suitable for habitat restoration. Identification of suitable areas for restoration using GIS is one of the best methods for maximizing limited resources available to restoration projects.   The researchers used a spatial model that helped reduce environmental uncertainty and then based other model factors on management objectives in order to find the best-suited areas for restoration.  The datasets used included region wide raster grid of sagebrush distribution, extensive field surveys throughout the sagebrush biome and other environmental variables, including elevation, rainfall.  The goal was to identify areas, through restoration, that would increase the connectivity of existing habitat.  In the end, the authors were able to identify areas to be restored using a GIS model to estimate the probability of sagebrush restoration success through meeting certain environmental specifications.

“The use of Geographic Information Systems, Remote Sensing, and Suitability Modeling to Indentify Conifer Restoration Sites with High Biological Potential for Anadromous Fish at the Cedar River Municipal Watershed in Western Washington, U.S.A.”  Mollot, L. A., R. E. Bilby.  2008. Restoration Ecology 16 (2):  pp. 336-347.

The authors set out to create a methodology using several types of remote sensed data in a GIS model to create an output that would help identify the areas that would be the most suitable for salmonid habitat restoration.  Stream gradient, stream confinement, and riparian cover were used to quantify suitable habitat in the Cedar River Municipal Watershed.  Previous attempts to accurately assess stream gradient and stream confinement had been hampered by the use of 30-m and 10-m DEM.  In this study a 4-m LIDAR DEM for the entire watershed was used to discern the channel gradient and confinement. This higher resolution scale allowed for ranking and suitability for salomind spawning to be assigned.  The riparian forest cover was determined using a MASTER digital dataset, which provided 5-m pixel resolution of vegetative cover.  The high-resolution dataset caused an issue by showing to much of the riparian diversity, which made it difficult to identify target stands for restoration.  In order to overcome this issue the authors used a focal majority technique to generate a more uniform stand structure and again assign values that ranked the habitat suitability for salmonids.  The final step was to take the quantified data and create a new raster dataset, through the use of a GIS model, that showed the most suitable areas for habitat restoration in watershed.  The researchers concluded that this methodology had been the most accurate used to date due to the nature of high spatial and high spectral resolution data.

“Spatial Analysis of the Suitability of Olive Plantations for Wildlife Habitat Restoration” Nekhay, O., M. Arriaza, J.R. Guzman-Alvarez.  2009. Computers and Electronics in Agriculture 65: pp. 49-64.

The focus of the paper was to use a two-step methodology to determine the most suitable habitat for restoration in olive plantations and areas that border national parks in southern Spain.  The first part of the two-step approach involves using an Analytic Hierarchy Process (AHP).  This process involves taking experts opinion of specific factors and averages them together in order to create a matrix showing the aggregate importance of different factors.  In this case the experts addressed what would are the most important natural elements for a parcel of land for restoration for large mammals.  Furthermore, the experts also ranked the magnitude of negative effects various man-made structures.  Second, the researchers created a map that reflected land use and also applied the negative and positive zones of influence attribute to objects on the map and used these different layers in a raster calculation.  Once that was completed authors then applied the ranking factors to land use attributes and reclassified the data to get the final overlay of positive and negative attributes in the area of study.  The result of the model was found to be quite accurate when groundtruthed and the authors felt the model was robust.  The final product of AHP and GIS analysis identified areas in the study area that would be best suited to extend current protected areas and provide a methodology that could be applied to other restoration identification projects.

“GIS-Based Niche Modeling For Mapping Species’ Habitat.”  Rotenberry, J., K. L. Preston, S. T. Knick.  2006. Ecology 87 (6): pp. 1458-1464.

In general, habitat models are based on species presence and abundance in a particular region but these models tend to break down when looking at potential habitat for colonization.  Current models have a difficult time making predications on habitat suitability when there is an absence of a species.  The authors attempted to create a model that predicted habitat suitability for a species in the absence of that species using a principal-components analysis on a correlation matrix of environmental variables.  Instead of looking at the characteristics of the most suitable habitat, the authors choose to use the limiting factor approach and used GIS to apply eighenvectors as related to habitat suitability. The use of limiting factors allowed for predications of habitat that was suitable, but not optimal.  The model was applied to the field examining California Gnatchatcer.  The authors concluded a single variable factor could be used to determine the suitability of habitat and there exists a large potential of the coupling of habitat modeling and GIS.

“The Role of GIS in Selecting Sites for Riparian Restoration Based on Hydrology and Land Use.”  Russel, G., C. P. Hawkins, M. P. O’Neil.  1997. Restoration Ecology 5 (4s): pp.  56-68.

The authors of the paper approach the problem of identifying appropriate habitat for preservation and restoration and attempt to create an effective methodology.  By using a 30-meter DEM to create a wetness index and remote sensing data to qualify vegetation, the researchers hope to identify wetlands to preserve and potential areas for restoration activity.   In the end, the scientists found the remote sensing data had issues accurately discerning different vegetation types, which made it difficult to determine the difference between riparian areas and upland areas.  To overcome this problem the researchers relied on the slope model to help qualify likely riparian areas.  The scientists acknowledged the fact that their methodology could prove effective in providing a guide for exploring potential sites for preservation and restoration with limited resources.

“Restoration of Bighorn Sheep Metapopulations in the Near Western National Parks” Singer, F. J., V. C. Bleich, M. A. Guorf.  2000. Restoration Ecology 8 (4s): pp 14-24.

Bighorn sheep are habitat specialists and because of their narrow habit range have been declining due to anthropogenic factors.  The dispersal of bighorn sheep into new habitats is rare and only occurs when suitable habitats are contiguous.  The authors of the paper define a process to identify suitable habitat in or near national parks that historically had bighorn sheep populations and depending on the results form the analysis planned to re-introduce the species in those areas.  After surveying existing populations, the authors used GIS to evaluate large land areas in order to determine suitability for big horn sheep.  Some criteria use to make the evaluation were escape terrain, which used a DEM, distance to perennial water, human developments, and horizontal visibility.  Following the habitat assessment with GIS, the information was given in to an expert panel on bighorn sheep in order to evaluate the results and receive recommendations.  It was found that 36 of the 73 areas surveyed were suitable for bighorn sheep with another 27 patches recommended for restoration. Once suitable habitat was identified a metapopulation restoration plan and translocation of sheep into the new habitat was completed.  The restoration process, which occurs from 1991-1998, resulted in a 25% increase in bighorn sheep populations.