Complementarity-based conservation prioritization using a community classification, and its application to riverine ecosystems

We demonstrate a novel method for spatial conservation prioritization at a community-level that takes account of: (i) an environmentally-based classification of the landscape into community classes; (ii) similarities between community classes to allow for community complementarity-based selection; (iii) variation in species richness; (iv) variation in human impacts on ecological integrity; and (v) requirements for maintenance of upstream–downstream connectivity in riverine systems. While this technique has generic application, we demonstrate its application using a biologically-trained environmental classification of New Zealand’s river network. Our analysis produces a priority ranking of planning units (here 4th order catchments or sub-catchments) and performance estimates in terms of expected biodiversity returns given varying degrees of geographic protection. Accounting for community similarity ensures high protection for distinct habitat classes with low similarity to other classes; our results indicate a 28% loss in conservation efficiency of the highest-ranked 10% of the landscape if it is ignored. Accounting for human pressures and connectivity also had clear influences on spatial priority rankings, indicating the need to consider these factors in the conservation planning process.