INVESTIGADORES
MARTELLA Monica Beatriz
artículos
Título:
Modeling habitat suitability for Greater Rheas based on satellite image texture
Autor/es:
BELLIS L.M.; PIDGEON A.M.; RADELOFF V.C.; ST-LOUIS V.; NAVARRO J.L.; MARTELLA M.B.
Revista:
ECOLOGICAL APPLICATIONS
Editorial:
ECOLOGICAL SOC AMER
Referencias:
Año: 2008 vol. 18 p. 1956 - 1966
ISSN:
1051-0761
Resumen:
Many wild species are affected by human activities occurring at broad spatialscales. For instance, in South America, habitat loss threatens Greater Rhea (Rhea americana)populations, making it important to model and map their habitat to better target conservationefforts. Spatially explicit habitat modeling is a powerful approach to understand and predictspecies occurrence and abundance. One problem with this approach is that commonly usedland cover classifications do not capture the variability within a given land cover class thatmight constitute important habitat attribute information. Texture measures derived fromremote sensing images quantify the variability in habitat features among and within habitattypes; hence they are potentially a powerful tool to assess species–habitat relationships. Ourgoal was to explore the utility of texture measures for habitat modeling and to develop ahabitat suitability map for Greater Rheas at the home range level in grasslands of Argentina.Greater Rhea group size obtained from aerial surveys was regressed against distance to roads,houses, and water, and land cover class abundance (dicotyledons, crops, grassland, forest, andbare soil), normalized difference vegetation index (NDVI), and selected first- and second-ordertexture measures derived from Landsat Thematic Mapper (TM) imagery. Among univariatemodels, Rhea group size was most strongly positively correlated with texture variables derivedfrom near infrared reflectance measurement (TM band 4). The best multiple regression modelsexplained 78% of the variability in Greater Rhea group size. Our results suggest that texturevariables captured habitat heterogeneity that the conventional land cover classification did notdetect. We used Greater Rhea group size as an indicator of habitat suitability; we categorizedmodel output into different habitat quality classes. Only 16% of the study area representedhigh-quality habitat for Greater Rheas (group size 15). Our results stress the potential ofimage texture to capture within-habitat variability in habitat assessments, and the necessity topreserve the remaining natural habitat for Greater Rheas.