Applying a versatile, comprehensive, attribute-based waterhole classification scheme to ecosystem-based management challenges

Abstract

Context Understanding habitat suitability for feral animals across a landscape is important for conservation planning because the spatial and temporal availability of water provides critical limits to native biodiversity and the processes that threaten it. Previous attempts to support management actions on feral pig populations through predictions of population abundance, distribution and seasonal resource constraints have been confounded by a lack of knowledge, classification and mapping of waterholes – which are critical to their survival. Aims In this paper, we aimed to apply a waterhole classification scheme for feral pig management to address gaps in our understanding of water and food availability through space and time, at scales relevant to feral animal movement and resource use. Methods We utilise an attribute-based waterhole classification scheme for ecosystem-based management by defining a waterhole typology of feral pig habitat suitability and applying it spatially. Key results Five attributes (water permanence, predictability of inundation, oceanic influence, dominant vegetation and shading) reflect many of the critical requirements for feral pig habitat in northern Australia. The attributes directly relate to the environmental constraints that exert population and behavioural pressure on feral pigs. These attributes were applied spatially in a specific hierarchy to group waterholes into 21 types. Conclusions A waterhole typology that characterises within the context of their suitability for feral pig populations is foundational for systematic adaptive management and monitoring programs that aim to reduce the impact of threatening processes on freshwater ecosystems. Implications Refining the mapping of important feral pig habitat variables (water and food) will greatly improve modelling approaches that aim to support data-driven management approaches, such as connectivity analysis and estimating population dynamics to inform culling programs. Here we demonstrate a significant increase in overlap with known feral pig distributions using a much smaller mapped effective management area when compared with previous best available spatial products.