Muddy waters: Modifying reserve design algorithms for riverine landscapes

The objective of systematic conservation planning is to select areas to protect or rehabilitate ecological assets in the most efficient way. After setting targets for ecological assets, heuristic algorithms or optimization techniques are employed to meet these targets. This technique - traditionally only used in terrestrial and marine settings - has recently been adapted to river management, acknowledging spatial constraints arising from the connected nature of rivers. However, terrestrial heuristics and optimization techniques employed to solve the minimum-set or maximum-coverage problem in conservation planning scenarios have been designed to deal with non-connected systems. Therefore, different algorithms will perform better or worse in a riverine setting. In this study, we compare the performance of two different techniques to identify important cells for meeting ecological targets in terms of efficiency, congruence and computational effort.