Context Landscape-scale research quantifying ecological connectivity is required to maintain the viability of populations in dynamic environments increasingly impacted by anthropogenic modification and environmental change.Objective To evaluate how surface water network structure, landscape resistance to movement, and flooding affect the connectivity of amphibian habitats within the Murray-Darling Basin (MDB), a highly modified but ecologically significant region of southeastern Australia. Methods We evaluated potential connectivity network graphs based on circuit theory, Euclidean and least-cost path distances for two amphibian species with different dispersal abilities, and used graph theory metrics to compare regional-and patch-scale connectivity across a range of flooding scenarios. Results Circuit theory graphs were more connected than Euclidean and least-cost equivalents in floodplain environments, and less connected in highly modified or semi-arid regions. Habitat networks were highly fragmented for both species, with flooding playing a crucial role in facilitating landscape-scale connectivity. Both formally and informally protected habitats were more likely to form important connectivity ''hubs'' or ''stepping stones'' compared to nonprotected habitats, and increased in importance with flooding. Conclusions Surface water network structure and the quality of the intervening landscape matrix combine to affect the connectivity of MDB amphibian habitats in ways which vary spatially and in response to flooding. Our findings highlight the importance of utilising organism-relevant connectivity models which incorporate landscape resistance to movement, and accounting for dynamic landscape-scale processes such as flooding when quantifying connectivity to inform the conservation of dynamic and highly modified environments.

No abstract

No abstract

No abstract

Accurately mapping the boundary between land and water (the 'waterline') is critical for tracking change in vulnerable coastal zones, and managing increasingly threatened water resources. Previous studies have largely relied on mapping waterlines at the pixel scale, or employed computationally intensive sub-pixel waterline extraction methods that are impractical to implement at scale. There is a pressing need for operational methods for extracting information from freely available medium resolution satellite imagery at spatial scales relevant to coastal and environmental management. In this study, we present a comprehensive evaluation of a promising method for mapping waterlines at sub-pixel accuracy from satellite remote sensing data. By combining a synthetic landscape approach with high resolution WorldView-2 satellite imagery, it was possible to rapidly assess the performance of the method across multiple coastal environments with contrasting spectral characteristics (sandy beaches, artificial shorelines, rocky shorelines, wetland vegetation and tidal mudflats), and under a range of water indices (Normalised Difference Water Index, Modified Normalised Difference Water Index, and the Automated Water Extraction Index) and thresholding approaches (optimal, zero and automated Otsu's method). The sub-pixel extraction method shows a strong ability to reproduce both absolute waterline positions and relative shape at a resolution that far exceeds that of traditional whole-pixel methods, particularly in environments without extreme contrast between the water and land (e.g., accuracies of up to 1.50-3.28 m at 30 m Landsat resolution using optimal water index thresholds). We discuss key challenges and limitations associated with selecting appropriate water indices and thresholds for sub-pixel waterline extraction, and suggest future directions for improving the accuracy and reliability of extracted waterlines. The sub-pixel waterline extraction method has a low computational overhead and is made available as an open-source tool, making it suitable for operational continental-scale or full time-depth analyses aimed at accurately mapping and monitoring dynamic waterlines through time and space.