Science based approaches for conservation prioritisation and target setting

Abstract

Globally we are beginning to realise the need for policies built on evidence, and for environmental policy that entails science-based policy. Yet, any analysis is only as good as the data used to conduct it, thus understanding the limitations and assumptions in environmental data is crucial to ensuring it’s sensible and effective use. The digital revolution has seemingly changed the problem for many ecologists trying to understand the natural world from having insufficient data to approach many ecological questions, to one of how to usefully analyse ever growing volumes of data. Yet despite this huge volume of data, natural biases within the data require caution to ensure their sensible use, as those biases shape the outcomes of our analysis and may misrepresent true ecological patterns as a consequence. We also explore how different modes of data collection and the impact of citizen science in shaping our understanding of species patterns and how it may actually exacerbate rather than ameliorate existing biases. However guiding sensible use and providing more robust solutions is key, thus building from this we provide recommendations to help guide sensible and effective use and interpretation of data, frameworks to enable more effective use of data within its sensible limits, and better approaches for the generation of further data to aid the development of effective conservation, policy and management. We also demonstrate how data can be sensitively analysed and applied to help create better and more sensitive environmental targets, and can also help align, such as ecological conservation redline policy and to maximise the synergies between climate and biodiversity targets.