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

本记录概述了国家海洋和沿海中心小规模研究--国家海洋和沿海中心范围确定研究：监测的新方法。<br/> <br/> 在过去的十年里，对海洋物种的观察迅速多样化，越来越多的观察结果要么是通过公民科学计划收集的，要么是由公民机会主义地收集的，然后提交到公共数据库。提供这些数据的公民的期望是，这些数据被纳入正式分析，并用于科学或管理目的，其结果将改善目前对海洋物种的了解和保护。此外，鉴于进行正式调查的费用，特别是在访问偏远地区或需要重复收集(跨越季节或年份)的情况下，对收集观测数据的更非正式和公共驱动的方法的依赖程度越来越高。<br/> <br/> 然而，将机会主义观察与更正式收集的观察(例如，通过稳健的调查设计收集的观察)结合起来并不是一帆风顺的。估计种群丰度、物种组合、丰度和分布随时间的变化的传统方法需要对与这些观测有关的努力以及这种努力如何随时间分布有所了解；鉴于这些观测的性质，机会性观测中缺少的信息。此外，许多机会主义收集的数据集不符合可能应用于科学数据集的许多分析方法的统计假设。因此，机会主义的观察目前没有得到充分利用，而且在很大程度上只在研究应用中定性地使用。<br/> <br/> 为了充分利用这一快速增长的资源，并确保与收集这些观测数据相关的努力不被浪费，需要能够将机会性收集的数据与科学数据集相结合的方法。<br/> <br/> 该项目是开发综合方法的第一阶段。它将把数据持有者、定量生态学家和统计学家聚集在一起，探索可能适用于促进机会主义数据集与科学数据集整合的潜在方法。在这样做时，它将确定哪些数据集可能最适合开发综合方法(以及哪些可能不适合)，并勾勒出开发这些方法的途径，这些方法可以通过未来的项目实施<br/> <br/> 计划产量<br/> ·研讨会<br/> ·最后一份技术报告，包括分析的数据和对关键发现向政策制定者提出的建议的简短摘要[书面]

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]