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| Format: | Artículo científico |
| Sprache: | en |
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Journal of environmental management
2025
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| Schlagworte: | |
| Online-Zugang: | https://pubmed.ncbi.nlm.nih.gov/39612785/ |
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| author | Luhede, Amelie Freund, Jan A Dajka, Jan-Claas Upmann, Thorsten |
| author_facet | Luhede, Amelie Freund, Jan A Dajka, Jan-Claas Upmann, Thorsten Luhede, Amelie Freund, Jan A Dajka, Jan-Claas Upmann, Thorsten |
| collection | PubMed - marine biology |
| contents | The value of information in predicting harmful algal blooms. Luhede, Amelie Freund, Jan A Dajka, Jan-Claas Upmann, Thorsten Harmful Algal Bloom Water Pollution Environmental Monitoring Decision Making Germany Seawater Decision Support Techniques Probability Fisheries Environmental decision-making is inherently subject to uncertainty. However, decisions are often urgent, and whether to take direct action or invest in collecting additional data beforehand is pervasive. To make this trade-off explicit, the value of information (VoI) theory offers a powerful decision analytic tool to quantify the expected benefit of resolving uncertainty in a decision context. Although it is mainly used in economic contexts, it can be applied to biodiversity conservation and management. In our approach, we evaluate the expected surplus in resolving uncertainty about the occurrence of harmful algal blooms (HABs) in the German North Sea coastal waters and the effect on decision-making. We use an established dynamic foodweb model (NPPZ) with two competing phytoplankton consortia (harmful, non-harmful) and regional monitoring data to analyse the prediction accuracy of different indicators. Our analysis revealed a prediction accuracy of a HAB occurrence of 0.65 % if additional information on zooplankton is included. We then evaluate the effect of reducing uncertainty about these indicators (e.g., through extended monitoring) on management decisions employing a VoI analysis. We find that additional information may lead to an expected welfare gain of up to 2.67 million Euro in our decision context. Our results highlight the significant potential for VoI analysis to enhance decision-making in fishery and ecosystem management and provide insights for future monitoring strategies to mitigate the adverse effects of HABs. This approach contributes valuable methodological insights for optimising management strategies and further emphasises the importance of considering uncertainty in decision-making processes. |
| format | Artículo científico |
| id | pubmed_39612785 |
| institution | PubMed |
| language | en |
| publishDate | 2025 |
| publisher | Journal of environmental management |
| record_format | pubmed |
| spellingShingle | The value of information in predicting harmful algal blooms. Luhede, Amelie Freund, Jan A Dajka, Jan-Claas Upmann, Thorsten Harmful Algal Bloom Water Pollution Environmental Monitoring Decision Making Germany Seawater Decision Support Techniques Probability Fisheries The value of information in predicting harmful algal blooms. Luhede, Amelie Freund, Jan A Dajka, Jan-Claas Upmann, Thorsten Harmful Algal Bloom Water Pollution Environmental Monitoring Decision Making Germany Seawater Decision Support Techniques Probability Fisheries Environmental decision-making is inherently subject to uncertainty. However, decisions are often urgent, and whether to take direct action or invest in collecting additional data beforehand is pervasive. To make this trade-off explicit, the value of information (VoI) theory offers a powerful decision analytic tool to quantify the expected benefit of resolving uncertainty in a decision context. Although it is mainly used in economic contexts, it can be applied to biodiversity conservation and management. In our approach, we evaluate the expected surplus in resolving uncertainty about the occurrence of harmful algal blooms (HABs) in the German North Sea coastal waters and the effect on decision-making. We use an established dynamic foodweb model (NPPZ) with two competing phytoplankton consortia (harmful, non-harmful) and regional monitoring data to analyse the prediction accuracy of different indicators. Our analysis revealed a prediction accuracy of a HAB occurrence of 0.65 % if additional information on zooplankton is included. We then evaluate the effect of reducing uncertainty about these indicators (e.g., through extended monitoring) on management decisions employing a VoI analysis. We find that additional information may lead to an expected welfare gain of up to 2.67 million Euro in our decision context. Our results highlight the significant potential for VoI analysis to enhance decision-making in fishery and ecosystem management and provide insights for future monitoring strategies to mitigate the adverse effects of HABs. This approach contributes valuable methodological insights for optimising management strategies and further emphasises the importance of considering uncertainty in decision-making processes. |
| title | The value of information in predicting harmful algal blooms. |
| topic | Harmful Algal Bloom Water Pollution Environmental Monitoring Decision Making Germany Seawater Decision Support Techniques Probability Fisheries |
| url | https://pubmed.ncbi.nlm.nih.gov/39612785/ |