Regional-scale conservation planning considering ecosystems as a whole is important in allowing us to capture emergent system properties, such as complementarity, connectivity, and large-scale ecological processes and threats. Consequently, there has been an increase in the number of regional-scale prioritisation assessments in the conservation planning literature. However, conservation planning cannot stop at regional scales. Planning at such broad extents results in a planning-implementation gap, where there is a mismatch in the scale of planning (regional) and that of implementation (local), impeding the transition from conservation designs to actions. Regional-scale plans are less relevant to actual actions on the ground and should therefore be a starting guide to subsequent finer-scale plans.

We now also understand the importance of integrating accurate and representative socioeconomic costs into conservation prioritisations. Doing so increases cost effectiveness and stakeholder buy-in, both of which are necessary for successful implementation and continuation of conservation plans. However, detailed and representative cost data rarely (if ever) exists across entire regions. My recent investigation into these issues, using Fiji and Micronesia as case studies, has revealed that the socioeconomic cost data used in prioritisations has a strong influence on the location of determined priorities. I have found that carrying out coarse-resolution prioritisations with spatially variable cost data, can reduce the likelihood of selected priority areas to incidentally represent finer-scale conservation objectives, derived from higher-resolution habitat data. Leading to a useful recommendation for future regional prioritisations: if good quality, high-resolution data is unavailable when using habitat data as a surrogate for biodiversity, it is better to prioritise the whole region with spatially uniform costs to increase the likelihood of representing finer-resolution conservation objectives.


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