ReviewDensity-impact functions for terrestrial vertebrate pests and indigenous biota: Guidelines for conservation managers

•We review relationships between pest density and impacts on indigenous species.•Linear functions comprised less than one fifth of relationships reviewed.•Non-linear functions comprised half - benefits accrued only with low pest numbers.•Our guidelines will help conservation managers maximise the value of these functions.

The relationship between the density of a pest and its impact on a valued resource is critical for cost-effective management. Despite their simplistic representation of dynamic and often complex systems, density-impact functions (DIFs) are appealing because they provide managers with tangible goals for pest control. Historically, these relationships have focused on agricultural resources: relatively few have been quantified for conservation assets. We provide empirical evidence for six theoretical forms of DIF. Linear functions are the default condition based on the notion that some conservation benefit will result from any level of pest control, but they comprised less than one fifth of DIFs reviewed. More than half were strongly non-linear, with substantial benefits for indigenous species when pests were suppressed to low levels. Recovery of species, however, is usually a function of multiple processes, not just removal of pests, and recovery tends to be place- and time-specific. Thus, guidelines to help conservation managers derive and use DIFs in ways that maximise their value without overextending their utility are: 1) minimise influences of factors other than pests; 2) where necessary, undertake site-specific experiments, rather than generalising from other studies; 3) use time scales that recognise delays for biota to adjust to pest control; 4) measure instantaneous responses (e.g. demographic rates) as early indicators; and 5) use DIFs to guide short-term pest management, and trophic-interactive modelling for longer-term management. DIFs derived and used in this way are a significant improvement over unguided biodiversity management, and provide managers with an evidence base for decision-making.