NESP MaC Project 1.29 b – NESP Marine and Coastal Hub scoping study: New approaches to monitoring (2022) (CSIRO)

本记录概述了NESP海洋和沿海中心小规模研究- NESP海洋和沿海中心范围研究：监测的新方法。< br / >

This record provides an overview of the NESP Marine and Coastal Hub small-scale study - NESP Marine and Coastal Hub scoping study: New approaches to monitoring. <br /> <br /> Observations of marine species have rapidly diversified over the last decade with increasing numbers of observations collected either through citizen science programs or opportunistically by citizens and then submitted into public databases. The expectation of citizens contributing those data is that the data is incorporated into formal analyses and utilised either for scientific or management purposes, with outcomes that improve current understanding and conservation of marine species. Further, there is increasing reliance on more informal and publicly driven approaches to the collection of observations given the costs of conducting formal surveys particularly if accessing remote regions, or if repetition of collection (across seasons or years) is needed.<br /> <br /> Integrating opportunistic observations with more formally collected observations (e.g. those collected through robust survey designs), however, is not straightforward. Traditional approaches to estimating population abundance, changes in species assemblages, abundances and distributions through time require some understanding of the effort associated with those observations and how that effort is also distributed through time; information that is missing from opportunistic observations, given the nature of those observations. Further, many opportunistically collected datasets do not meet the statistical assumptions of many analytical approaches that might be applied to scientific datasets. As a result, opportunistic observations are underutilised at present and are largely only used qualitatively within research applications. <br /> <br /> To take full advantage of this rapidly expanding resource and ensure that efforts associated with the collection of these observations are not wasted, methods that can integrate opportunistically collected data with scientific datasets are needed.<br /> <br /> This project represents the first stage in developing integrative methods. It will bring together data holders, quantitative ecologists and statisticians to explore potential approaches that might be applied to facilitate the integration of opportunistic datasets with scientific datasets. In doing so, it will identify what datasets might be best suited to the development of integrative approaches (and what might not) and outline a pathway for developing those methods that could be implemented through a future project<br /> <br /> Planned Outputs<br /> • Workshop<br /> • Final technical report with analysed data and a short summary of recommendations for policy makers of key findings [written]