A Fish-Based Tool for the Quality Assessment of Portuguese Large Rivers
Résumé fourni par la source
Multimetric indices play a pivotal role in assessing river ecological quality, aligning with the European Water Framework Directive (EU WFD) requirements. However, indices developed specifically for large rivers are uncommon. Our objective was to develop a fish-based tool specifically tailored to assess the ecological quality in Portuguese large rivers. Data were collected from seven sites in each of three Portuguese large rivers (Minho, Guadiana, and Tagus). Each site was classified using an environmental disturbance score, combining different pressure types, such as water chemistry, land use, and hydromorphological alterations. The Fish-based Multimetric Index for Portuguese Large Rivers (F-MMIP-LR) comprises four metrics: % native lithophilic individuals; % alien individuals; % migrant individuals; and % freshwater native individuals, representing compositional, reproductive, and migratory guilds. The index showed good performance in separating least- and most-disturbed sites. Least-disturbed sites were rated ‘high’ or ‘good’ by F-MMIP-LR, contrasting with no such classification for most-disturbed sites, highlighting index robustness. The three rivers presented a wide range of F-MMIP-LR values across the gradient of ‘bad’ to ‘high’, indicating that, on a large spatial extent, the biological condition was substantially altered. The F-MMIP-LR provides vital information for managers and decision-makers, guiding restoration efforts and strengthening conservation initiatives in line with the WFD.
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Contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- A Fish-Based Tool for the Quality Assessment of Portuguese Large Rivers
- Date Crossref
- 23/04/2024
- Éditeur
- MDPI AG
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.
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