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Using GIS, remote sensing and modern statistics to study steppe birds at large spatial scales: a short review essay

Proceedings article published in 2006 by Patrick E. Osborne ORCID
This paper was not found in any repository; the policy of its publisher is unknown or unclear.
This paper was not found in any repository; the policy of its publisher is unknown or unclear.

Full text: Unavailable

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Preprint: policy unknown
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Postprint: policy unknown
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Abstract

Advances in technology during the last 15 years have led to new ways both to acquire environmental data via satellites and to process it using geographical information systems (GIS), and to new statistical techniques. Satellite imagery and related products are available at a wide range of spatial resolutions and provide the researcher with quality data and uniform coverage over large geographic extents. Advances in computer processing speed have freed statistics from unrealistic assumptions about data structure and permit us to explore the complex patterns that occur in environmental data without over-simplification. This paper examines the state of the art in using GIS, remote sensing and modern statistics to help us understand the ecological factors influencing steppe birds and to identify problems requiring conservation action. Steppe birds in Europe are concentrated on agricultural land, the habitat with the highest proportion of bird species with unfavourable conservation status. Agricultural land is extensive in range, often intensive in use and influenced by policies that respect neither political boundaries nor biogeographic zones. The appropriate scale for analysis of steppe bird-habitat interactions is equally large and far beyond the scale most field studies can manage. It is therefore appropriate to consider complementary approaches using GIS and remote sensing. By reviewing both published and unpublished work, this paper examines the following themes: · Static distribution models – data sources, quality and scale effects; extrapolation versus interpolation approaches; GLM, GAM and emerging techniques such as MART. · IBBMs versus static distribution models. · Extensions into the time domain – prediction of impacts; temporal suitability analysis. · Hypothesis testing versus hypothesis generation – habitat suitability indices and what they mean; testing hypotheses using residuals. · Geographic variation in habitat selection – does it occur and does it matter? Future directions for research: Emphasis is placed on what can be gained from these approaches (including non-steppe examples where no appropriate studies were found), what the limitations are to the techniques, and where we go from here. It is concluded that large-scale analysis of steppe bird distributions is essential to conservation efforts to save these species. Furthermore, spatial analytical approaches can provide researchers with new ways to test hypotheses at scales far beyond those possible through fieldwork alone.