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Integrating freshwater biodiversity data sources: key challenges and opportunities

Jarvis, Susan G. ORCID: https://orcid.org/0000-0001-5382-5135; Mackay, Eleanor B. ORCID: https://orcid.org/0000-0001-5697-7062; Risser, Hannah A. ORCID: https://orcid.org/0000-0001-9819-1092; Feuchtmayr, Heidrun; Fry, Matthew ORCID: https://orcid.org/0000-0003-1142-4039; Isaac, Nick J.B. ORCID: https://orcid.org/0000-0002-4869-8052; Thackeray, Stephen J. ORCID: https://orcid.org/0000-0003-3274-2706; Henrys, Peter A. ORCID: https://orcid.org/0000-0003-4758-1482. 2023 Integrating freshwater biodiversity data sources: key challenges and opportunities. Freshwater Biology, 68 (9). 1479-1488. 10.1111/fwb.14143

Abstract
1. In order to better quantify spatial and temporal patterns in freshwater biodiversity, and potential underlying drivers of change, we must utilise the increasingly broad range of data available on freshwater ecosystems. Statistical advances in the field of integrated modelling provide new opportunities to further our understanding through the combined and simultaneous analysis of these diverse datasets. 2. We briefly introduce integrated modelling in the context of freshwater biodiversity and outline the key steps involved in its implementation, from data collection to analysis. We highlight both opportunities and challenges for the application of integrated approaches. 3. To illustrate the potential for integrated models to improve our understanding of freshwater biodiversity compared to standard approaches, we combine two datasets collected using different methods to model the distribution of Agabus water beetles in England. The integrated model had greater power to detect covariate effects on Agabus distribution, and reduced parameter uncertainty compared with analysis using only a single dataset. 4. We show that integrated methods have the potential to increase our understanding of freshwater systems and enable us to make full use of the diversity of freshwater data available.
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