Dr Andrew Hoskins

Research Scientist

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I am a quantitative biologist experienced in developing and applying novel statistical and technical solutions to questions of ecological significance. My expertise lies in integrating multiple disparate data streams, through the use of smart modelling techniques, to produce spatially explicit estimates of biodiversity change, species behaviour and anthropogenic influence. I apply this expertise across local to global scales, within both marine and terrestrial environments.

My research aims to bridge the gap between large-area (e.g. continental and global) ecological assessments and the underlying fine-grained ecological processes that they describe. In general, many large-area assessments of biodiversity are constrained in spatial and temporal scale by the available methods and data being used to derive them, rendering them inconsistent with the ecological processes that they describe. My goal is to bring the scale of understanding down within broad-area ecological models, increasing their relevance at local and sub-regional scales. I am also interested in how different pressures (anthropogenic, biotic and abiotic) influence and change not just ecological systems, but also species behaviour.

At the global level, my work has focused on developing inputs and methods for large-area biodiversity modelling. This has been deployed into a new biodiversity modelling infrastructure (BILBI) which, for the first time, enables the prediction of species turnover for plants, invertebrates and vertebrates (approx. 400,000 species) at 1 km resolution across the entire terrestrial surface of the planet. This work is the foundation of two new CSIRO led global biodiversity indicators developed for reporting progress against CBD Aichi Targets – The Protected Area Representativeness Index for reporting progress towards Aichi Target 11 and the Biodiversity Habitat Index for reporting progress towards Aichi Target 5.

At the local level, I am interested in ways that individual animal behaviours (usually interpreted through animal-borne behavioural logging equipment) can influence population level responses and, in turn, how these population effects regulate the structure and function of ecological assemblages. My work has investigated the intrinsic and extrinsic factors that drive individual foraging decisions and survival in a number of species across marine and terrestrial systems. Currently, I am working on integrating next-generation sensor networks into predictive models of animal movement and behaviour using the large feral mammals (pigs, cattle and buffalo) of Northern Australia as a test case. This work aims to optimise control methods for these species by providing dynamic predictions of encounter probabilities to on ground partners – enabling enhanced targeting of control activities throughout the year – and scenario analysis of the impacts of different resource targeting control techniques.

Academic Qualifications

  • 2014

    Doctor of Philosophy
    Deakin Univeristy