Identifying the spatial scale of land use that most strongly influences overall river ecosystem health score

• Published in: Ecological applications 2012-12, Vol.22 (8), p.2188-2203
• Main Authors: Sheldon, Fran, Peterson, Erin E, Boone, Ed L, Sippel, Suzanne, Bunn, Stuart E, Harch, Bronwyn D
• Format: Article
• Language: English
• Subjects: Animals; Catchments; Climate; Conservation of Natural Resources; data collection; Ecosystem; ecosystem health; Ecosystem models; Ecosystems; environmental health; fish; Fishes - physiology; Forest ecosystems; Forests; Freshwater; Freshwater ecosystems; Geographic Information Systems; Health; Human Activities; hydrology; indicators; Land use; Lotic systems; Macroinvertebrates; Mathematical models; monitoring; nutrients; Queensland; Rain; Restoration; riparian buffers; Riparian forests; Rivers; Seasons; spatial scale; Streams; surveys; Trees; urbanization; water quality; Watersheds
• ISSN: 1051-0761; 1939-5582
• DOI: 10.1890/11-1792.1

Catchment and riparian degradation has resulted in declining ecosystem health of streams worldwide. With restoration a priority in many regions, there is an increasing interest in the scale at which land use influences stream ecosystem health. Our goal was to use a substantial data set collected as part of a monitoring program (the Southeast Queensland, Australia, Ecological Health Monitoring Program data set, collected at 116 sites over six years) to identify the spatial scale of land use, or the combination of spatial scales, that most strongly influences overall ecosystem health. In addition, we aimed to determine whether the most influential scale differed for different aspects of ecosystem health. We used linear-mixed models and a Bayesian model-averaging approach to generate models for the overall aggregated ecosystem health score and for each of the five component indicators (fish, macroinvertebrates, water quality, nutrients, and ecosystem processes) that make up the score. Dense forest close to the survey site, mid-dense forest in the hydrologically active near-stream areas of the catchment, urbanization in the riparian buffer, and tree cover at the reach scale were all significant in explaining ecosystem health, suggesting an overriding influence of forest cover, particularly close to the stream. Season and antecedent rainfall were also important explanatory variables, with some land-use variables showing significant seasonal interactions. There were also differential influences of land use for each of the component indicators. Our approach is useful given that restoring general ecosystem health is the focus of many stream restoration projects; it allowed us to predict the scale and catchment position of restoration that would result in the greatest improvement of ecosystem health in the regions streams and rivers. The models we generated suggested that good ecosystem health can be maintained in catchments where 80% of hydrologically active areas in close proximity to the stream have mid-dense forest cover and moderate health can be obtained with 60% cover.