Wetlands, salination and biodiversity: modelling the response of biodiversity to changes in salinity to provide a management tool for biodiversity preservation in wetlands subject to salination.
Jin, Changhao1, Turnbull, Derek*,1, Schreiber, Sabine1, 1 Arthur Rylah Institute for Environmental Research, Heidelberg, Victoria, Australia
ABSTRACT- Salination affects various landscapes in Victoria, Australia, including wetland ecosystems, which has implications for land use management and natural resource conservation. We are undertaking a multi-disciplinary project to improve wetland management, through an enhanced understanding of the ecological impact of salination and the interaction between wetland ecology and management actions, by predictive modelling, wetland surveys, testing model predictions in whole wetlands and testing specific management actions within an adaptive management framework. We will discuss the utility of an initial, quantitative, conceptual framework to explicitly describe relationships between secondary salination, biodiversity and wetland ecology, namely the development of a theoretical model of the relationship between biodiversity and secondary salination across a range of temporal scales. The basic model predicts that wetland ecosystems subject to salination will exhibit mono or multi-stable states based upon the initial quality of the wetland. Low quality wetlands display a graded response to changes in salinity, whereas high quality wetlands have multiple stable states (high and low biodiversity) and the change between stable states depends on maximum and minimum salinity thresholds. Incorporating seasonal variation of water level into the model indicates that biodiversity and the existence of multiple stable states are affected by the magnitude of seasonal variation. A large change promotes biodiversity in wetlands with either: low salinity (regardless of quality); or high initial quality (regardless of salinity). Hence, large seasonal variation can alter the salinity thresholds for transition between stable states in high quality wetlands. We will detail the model development and predictions with relevance to field survey data, which indicates potential threshold levels, and management tools to preserve biodiversity. The modelling framework can be used to generate testable hypotheses of the response of wetlands to management measures and changed chemical, physical and biological conditions. We suggest that rigorous hypothesis generation is necessary to test the efficacy of specific management actions in mitigating the effects of salination on wetland ecology.
Key words: adaptive management, wetland ecology, salinity, modelling
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