A rapid approach to modeling species–habitat relationships

Abstract

A growing number of species require conservation or management efforts. Success of these activities requires knowledge of the species' occurrence pattern. Species-habitat models developed from GIS data sources are commonly used to predict species occurrence but commonly used data sources are often developed for purposes other than predicting species occurrence and are of inappropriate scale and the techniques used to extract predictor variables are often time consuming and cannot be repeated easily and thus cannot efficiently reflect changing conditions. We used digital orthophotographs and a grid cell classification https://ntrs.nasa.gov/search.jsp?R=20110024058 2018-05-13T02:08:21+00:00Z scheme to develop an efficient technique to extract predictor variables. We combined our classification scheme with a priori hypothesis development using expert knowledge and a previously published habitat suitability index and used an objective model selection procedure to choose candidate models. We were able to classify a large area (57,000 ha) in a fraction of the time that would be required to map vegetation and were able to test models at varying scales using a windowing process. Interpretation of the selected models confirmed existing knowledge of factors important to Florida scrub-jay habitat occupancy. The potential uses and advantages of using a grid cell classification scheme in conjunction with expert knowledge or an HSI and an objective model selection procedure are discussed.

Conservation of Mediterranean otters: the influence of map scale resolution

“…Coarse resolution data overestimated the role of climate in the invasion process and this influenced subsequent invasive species management programs. Attempts have been made to use multiple regression to quantify the explanatory power of a set of variables at several different scale resolutions (Turner et al Table 1 Eurasian otter (Lutra lutra) distribution in the Sado River basin (Portugal) at three scale resolutions and over two seasons, using a Universal Transverse Mercator (UTM) grid sampling system Wet season Dry season 10 9 10 km 5 9 5 km 2.5 9 2.5 km 10 9 10 km 5 9 5 km 2.5 9 2.5 km Pearson and Turner 1995), and to downscale species distributions to finer resolutions by combining remotely sensed data and expert opinion (Carter et al 2006), or by modeling techniques that explore the correlation between species occurrence and environmental predictor variables (Bombi et al 2011), but these approaches are usually limited to a few, well known species (Araújo et al 2005). An extrapolation model of otter distribution in Iberian Peninsula from a 10 9 10 km squares to a 1 9 1 km squares map, based on the Spanish otter survey (Ruiz-Olmo and Delibes 1998) and having as explanatory variables environmental data (air humidity, temperature, precipitation, soil permeability, etc.…”

“…These concerns commonly address whether correlates of species distribution vary with the scale resolution of measurement. Typically resource selection functions are used to map suitable habitat based on predicted probability of use but the spatial resolution selected to obtain data to enter the models influences the accuracy of predictions (Meyer and Thuiller 2006;Baker et al 2007) and does not affect models equally across regions, techniques, or species types (Carter et al 2006;Guisan et al 2007). Consequently, failure to consider and select the most appropriate scale or suite of scales (domain) may lead to incorrect interpretations of data and consequently the mismanagement of critical natural resources (Bowyer and Kie 2006;Bombi et al 2011).…”

Identifying conservation priority ponds of an endangered minnow, Pseudorasbora pumila, in the area invaded by Pseudorasbora parva

“…One of the key constraints to conservation progress is priority setting that can support adequate conservation efforts (Saunders et al 2002;Filipe et al 2004). Constructing predictive models of habitat distribution for prioritizing management or restoration efforts (Guisan and Zimmermann 2000;Ricciardi 2003) is very useful to estimate the habitat quality of endangered species (Carter et al 2006) and reduce the occurrence and impact of invasive species on the resident species Lodge 2001, 2002).…”

Post-Fledging Habitat Selection by the Slender-billed Parakeet (Enicognathus leptorhynchus) in a Fragmented Agricultural Landscape of Southern Chile

“…Although multitudes of animal populations are declining worldwide because of anthropogenic destruction and alteration of their habitats (Petit et al 1999, Virkkala et al 2004, Carter et al 2006, for many such species there is a lack of basic ecological information on which conservation measures might be based. For example, the Slender-billed Parakeet (Enicognathus leptorhynchus) is a medium-sized (~300 g) psittacine endemic to southern Chile for which existing ecological information is both scant and anecdotal.…”