Costs in conservation: Common costly mistakes and how to avoid them.

There has been an increasingly prevalent message that data regarding costs must be included in conservation planning activities to make cost-efficient decisions. Despite the growing acceptance that socioeconomic context is critical to conservation success, the approaches to embedded economic and financial considerations into planning have not significantly evolved. Inappropriate cost data is frequently included in decisions, with the potential of compromising biodiversity and social outcomes. For each conservation planning step, this essay details common mistakes made when considering costs, proposing solutions to enable conservation managers to know when and how to include costs. Appropriate use of high-quality cost data obtained at the right scale will improve decision-making and ultimately avoid costly mistakes.

Integrated social-ecological data for regional natural resource management.

Natural resource managers need information about both human and natural systems and interactions between those systems. Much data is available, but mostly from disparate sources and data have often been collected at different time steps and at different geographic scales. We used insights from the literature to select 270 relevant variables, available at national scale, from 33 unique (Australian) data sources. There were numerous with repeat measures, so in total we have 425 variables: 143 specific to 2016, 148 specific to 2021, and 134 available for both periods. We used GIS to summarize the variables spatially based on two geographic boundaries: one describes 63 Natural Resource Management Regions; the other describes 419 (sub) bioregions (formally, IBRA - Interim Biogeographic Regionalisation for Australia). Data deficiencies prevented us from being able to report on all variables for all regions. In the NRM dataset many regions are offshore islands, about which data are not generally available. Moreover, many IBRA regions are small and household level data are not always available at that scale. For analyses requiring a complete dataset at a single time step, our 2021 dataset for NRM regions includes 270 unique variables that describe 56 regions. Our IBRA data includes 214 variables describing 409 regions. To help managers select appropriate data for specific problems/contexts, the metadata file also categorises variables according to (a) whether they pertain to the social or ecological system, or interactions; (b) the segment of society described (where relevant); and (c) the frequency with which data are updated.