Browsing by Subject "scale"

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    Protected areas as social-ecological systems: perspectives from resilience and social-ecological systems theory
    (2017) Cumming, Graeme S; Allen, Craig R
    Conservation biology and applied ecology increasingly recognize that natural resource management is both an outcome and a driver of social, economic, and ecological dynamics. Protected areas offer a fundamental approach to conserving ecosystems, but they are also social-ecological systems whose ecological management and sustainability are heavily influenced by people. This editorial, and the papers in the invited feature that it introduces, discuss three emerging themes in social-ecological systems approaches to understanding protected areas: (1) the resilience and sustainability of protected areas, including analyses of their internal dynamics, their effectiveness, and the resilience of the landscapes within which they occur; (2) the relevance of spatial context and scale for protected areas, including such factors as geographic connectivity, context, exchanges between protected areas and their surrounding landscapes, and scale dependency in the provision of ecosystem services; and (3) efforts to reframe what protected areas are and how they both define and are defined by the relationships of people and nature. These emerging themes have the potential to transform management and policy approaches for protected areas and have important implications for conservation, in both theory and practice.
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    Understanding pathogen transmission dynamics in waterbird communities: At what scale should interactions be studied?
    (Academy of Science of South Africa, 2011) MacGregor, Lindy H; Cumming, Graeme S; Hockey, Philip A
    Pathogen transmission in animal populations is contingent on interactions between and within species. Often standard ornithological data (e.g. total counts at a wetland) are the only data available for assessing the risks of avian pathogen transmission. In this paper we ask whether these data can be used to infer fine-scale transmission patterns. We tested for non-randomness in waterbird assemblages and explored waterbird interactions using social network analysis. Certain network parameter values were then compared to a data set on avian influenza prevalence in southern Africa. Our results showed that species associations were strongly non-random, implying that most standard ornithological data sets would not provide adequate information on which to base models of pathogen spread. In both aquatic and terrestrial networks, all species regularly associated closely with other network members. The spread of pathogens through the community could thus be rapid. Network analysis together with detailed, fine-scale observations offers a promising avenue for further research and management-oriented applications.