Disturbance patterns of socio-ecological systems at multiple scales.
Zurlini, Giovanni*,1, Riitters, Kurt2, Zaccarelli, Nicola1, Petrosillo, Irene 1, 1 Landscape Ecology Laboratory, Lecce, Lecce, Italy2 Forest Health Monitoring, US Forest Service, Research Triangle Park NC 27709, NC, USA
ABSTRACT- Ecological system properties such as hierarchical organization and non-equilibrium dynamics demand multiple-scale analysis to comprehend how a system is structured and to formulate hypotheses about regulatory mechanisms. Characteristic scales in real landscapes are determined by, or at least reflect, the spatial patterns and scales of human interactions with the biophysical environment. If the patterns or scales of human actions change, then the structure and dynamics of the entire socio-ecological system (SES) can change accordingly. To understand biodiversity, it is necessary to know how the actions of humans as a keystone species shape the environment across a range of scales in a region. We address the problem of characterizing the spatial patterns of human disturbances at multiple scales in a SES in southern Italy. We describe an operational framework to identify multi-scale profiles of short-term anthropogenic disturbance patterns using a moving window algorithm to measure the amount and spatial configuration of disturbance as detected by satellite imagery. The resulting profiles at multiple scales were then interpreted with respect to defining critical support regions and scale-dependent models for the assessment and management of disturbances, and for indicating system fragility and resilience of socio-ecological systems. Prevailing land uses contribute in different ways to disturbance gradients at multiple scales, as land uses resulted from other types of biophysical and social controls shaping the region. The results are also discussed in terms of the potential for predicting ecological effects from planning and management of landscape disturbance mosaics.
Key words: Multiple scale disturbance, socio-ecological systems, retrospective resilience
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