Ruth Sonnenschein

Bringing an ecological view of change to Landsat-based remote sensing

When characterizing the processes that shape ecosystems, ecologists increasingly use the unique perspective offered by repeat observations of remotely sensed imagery. However, the concept of change embodied in much of the traditional remote-sensing literature was primarily limited to capturing large or extreme changes occurring in natural systems, omitting many more subtle processes of interest to ecologists. Recent technical advances have led to a fundamental shift toward an ecological view of change. Although this conceptual shift began with coarser-scale global imagery, it has now reached users of Landsat imagery, since these datasets have temporal and spatial characteristics appropriate to many ecological questions. We argue that this ecologically relevant perspective of change allows the novel characterization of important dynamic processes, including disturbances, longterm trends, cyclical functions, and feedbacks, and that these improvements are already facilitating our understanding of critical driving forces, such as climate change, ecological interactions, and economic pressures.

Livestock subsidies and rangeland degradation in central Crete.

Marginal and unstable environmental conditions force stockbreeders in drylands to develop adaptive strategies to ensure stability of production. In intensive market-oriented pastoral systems, the partial substitution of rangeland forage production by external feed increases the influence of commodity prices in stockbreeders’ decisions, which become increasingly decoupled from environmental constraints. In Mediterranean countries of the European Union (EU), Common Agricultural Policy (CAP) subsidies also influence agricultural practices, potentially increasing environmental impacts. By modeling subsidy allocation to sheep and goat breeders in Crete, we showed that livestock subsidies for Less Favoured Areas (LFA) stimulated flock growth up to a point. By linking interviews of farmers to remote-sensing data in four village communities in central Crete, we tested statistically alternative hypotheses explaining the links between CAP subsidies, livestock-husbandry practices, and land degradation at the farm level. The flock growth stimulated by livestock subsidies was accompanied by the intensification of herd management, and decreasing yields and profits, with no statistical association to vegetation degradation. Farms with larger flocks became more sensitive to market fluctuations.

Modelling avian biodiversity using raw, unclassified satellite imagery

Applications of remote sensing for biodiversity conservation typically rely on image classifications that do not capture variability within coarse land cover classes. Here, we compare two measures derived from unclassified remotely sensed data, a measure of habitat heterogeneity and a measure of habitat composition, for explaining bird species richness and the spatial distribution of 10 species in a semi-arid landscape of New Mexico. We surveyed bird abundance from 1996 to 1998 at 42 plots located in the McGregor Range of Fort Bliss Army Reserve. Normalized Difference Vegetation Index values of two May 1997 Landsat scenes were the basis for among-pixel habitat heterogeneity (image texture), and we used the raw imagery to decompose each pixel into different habitat components (spectral mixture analysis). We used model averaging to relate measures of avian biodiversity to measures of image texture and spectral mixture analysis fractions. Measures of habitat heterogeneity, particularly angular second moment and standard deviation, provide higher explanatory power for bird species richness and the abundance of most species than measures of habitat composition. Using image texture, alone or in combination with other classified imagery-based approaches, for monitoring statuses and trends in biological diversity can greatly improve conservation efforts and habitat management.