Integrating Presence-Only Data Into Spatio-Temporal Models to Support Fisheries Assessments and Management in Freshwater and Marine Environments

IF 6.1 1区 农林科学 Q1 FISHERIES
Anthony R. Charsley, Arnaud Grüss, Nokuthaba Sibanda, Shannan K. Crow, Owen F. Anderson, Ashley A. Rowden, Simon D. Hoyle, David D. Bowden
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Abstract

Spatio-temporal species distribution models can support fisheries assessments and management in marine and freshwater environments. However, the high costs of structured surveys often limit the spatio-temporal coverage of the data available for modelling. To address this issue, we present a spatio-temporal modelling approach integrating structured survey data with unstructured presence-only data, which have greater spatio-temporal coverage than structured data, but are often disregarded in fisheries research. Data integration is achieved by generating pseudo-absences for the presence-only data and estimating spatially varying catchability for all data sources relative to the structured dataset. We consider a freshwater application, building longfin eel (Anguilla dieffenbachii, Anguillidae) spatio-temporal distribution models for the Taranaki region, New Zealand, and a marine application, building spatial density models for the vulnerable marine ecosystem indicator taxon Demospongiae in the South Pacific Ocean. We also conduct a simulation experiment to investigate the impacts of using pseudo-absences that do not reflect true absence patterns in our modelling framework. By integrating unstructured presence-only data, our approach improves the spatio-temporal coverage of the data available for modelling. Our applications provide results consistent with previous modelling studies but also offer new insights into the distribution and density patterns of longfin eel and Demospongiae. The simulation experiment found greater error and poorer uncertainty characterisation in models that mis-specified true absence patterns. We recommend assessing spatial structure in presence-only data and generating spatially structured pseudo-absences that match this structure. Our approach has many potential applications, such as providing enhanced information to assist fisheries in assessments and management.

Abstract Image

将仅存在数据整合到时空模型中,以支持淡水和海洋环境中的渔业评估和管理
物种时空分布模型可为海洋和淡水环境的渔业评估和管理提供支持。然而,结构化调查的高成本往往限制了可用于建模的数据的时空覆盖范围。为了解决这一问题,我们提出了一种时空建模方法,将结构化调查数据与非结构化存在数据相结合,后者比结构化数据具有更大的时空覆盖范围,但在渔业研究中经常被忽视。数据集成是通过为仅存在的数据生成伪缺席,并相对于结构化数据集估计所有数据源的空间变化可捕获性来实现的。我们考虑在淡水应用中建立新西兰Taranaki地区长鳍鳗(Anguilla dieffenbachii, Anguillidae)的时空分布模型,以及在海洋应用中建立南太平洋脆弱海洋生态系统指示分类群Demospongiae的空间密度模型。我们还进行了模拟实验,以研究在我们的建模框架中使用不反映真实缺失模式的伪缺失的影响。通过整合非结构化的仅存在数据,我们的方法提高了可用于建模的数据的时空覆盖范围。我们的应用程序提供了与以前的建模研究一致的结果,但也为长鳍鳗和Demospongiae的分布和密度模式提供了新的见解。模拟实验发现,在错误指定真实缺失模式的模型中,误差更大,不确定性更差。我们建议评估仅存在数据中的空间结构,并生成与该结构匹配的空间结构化伪缺失。我们的方法有许多潜在的应用,例如提供增强的信息,以协助渔业进行评估和管理。
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来源期刊
Fish and Fisheries
Fish and Fisheries 农林科学-渔业
CiteScore
12.80
自引率
6.00%
发文量
83
期刊介绍: Fish and Fisheries adopts a broad, interdisciplinary approach to the subject of fish biology and fisheries. It draws contributions in the form of major synoptic papers and syntheses or meta-analyses that lay out new approaches, re-examine existing findings, methods or theory, and discuss papers and commentaries from diverse areas. Focal areas include fish palaeontology, molecular biology and ecology, genetics, biochemistry, physiology, ecology, behaviour, evolutionary studies, conservation, assessment, population dynamics, mathematical modelling, ecosystem analysis and the social, economic and policy aspects of fisheries where they are grounded in a scientific approach. A paper in Fish and Fisheries must draw upon all key elements of the existing literature on a topic, normally have a broad geographic and/or taxonomic scope, and provide general points which make it compelling to a wide range of readers whatever their geographical location. So, in short, we aim to publish articles that make syntheses of old or synoptic, long-term or spatially widespread data, introduce or consolidate fresh concepts or theory, or, in the Ghoti section, briefly justify preliminary, new synoptic ideas. Please note that authors of submissions not meeting this mandate will be directed to the appropriate primary literature.
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