The impact of data realities on conservation planning

Conservation planning decisions are typically made on the basis of species distribution or occurrence data, which ideally would have complete spatial and taxonomic coverage. Agencies are constrained in the data they can collect, often pragmatically prioritising certain groups such as threatened species, or methods, such as volunteer surveys. This mismatch between goals and realities inevitably leads to bias and uncertainty in conservation planning outputs, yet few studies have assessed how data realities affect planning outputs. We conducted a sensitivity analysis on the Protection Index, a method for assessing conservation progress and priorities, using an extensive dataset on species occurrences and distributions derived from the Florida Natural Areas Inventory. Analyses revealed a high proportion of occurrence records for threatened species and certain taxonomic groups, reflecting the agencies' priorities. We performed a sensitivity analysis on conservation planning outputs, simulating a 'data poor' scenario typical of many real situations; we deleted increasing amounts of data in both a biased (exaggerating patterns observed) and unbiased (random) manner. We assessed the effects of data paucity and bias on the value of potential conservation sites, and planning priorities. Certain high value sites with only a few important species occurrences were more sensitive to data depletion than those with many occurrences. Data bias based on taxonomic bias was more influential to site value than threat rank. To maximise benefit from surveys from a planning perspective, it would be better to focus on poorly surveyed areas rather than adding occurrences in already well represented sites. This study demonstrates the importance of sensitivity analysis in conservation planning, and that the effects of uncertainty and data quality on planning decisions should not be ignored. © 2011 Elsevier Ltd.