Mapping the world’s free-flowing rivers using the Connectivity Status Index (CSI)
Notice bibliographique
Résumé
Free-flowing rivers (FFRs) are the freshwater equivalent of wilderness areas and they support many of the most diverse, complex and dynamic ecosystems globally, providing important societal and economic services. We define FFRs as rivers where ecosystem functions and services are largely unaffected by changes to the fluvial connectivity, allowing unobstructed movement and exchange of water, energy, material and species within the river system and with surrounding landscapes. However, there is immense anthropogenic pressure on natural connectivity in rivers: river connectivity can be compromised by physical infrastructure in the river channel, along riparian zones or in adjacent floodplains; hydrological alterations of river flow due to water abstractions or regulation; and changes to water quality that lead to ecological barrier effects caused by pollution or alterations in water temperature. We developed the Connectivity Status Index (CSI), a novel methodology to measure of the current state of connectivity at a river reach scale (river segment of ~2.5 km length). The CSI considers five ‘pressure factors’ that represent the main human interferences within the four dimensions of river connectivity: a) river fragmentation (longitudinal); b) flow regulation (lateral and temporal); c) sediment trapping (longitudinal, lateral, and vertical); d) water consumption (lateral, vertical, and temporal); and e) infrastructure development in riparian areas and floodplains (lateral and longitudinal). We developed proxy indicators for these components informed by available global data and numerical model outputs and combined these layers into the CSI using a weighted overlay model. We assessed the connectivity status of 12 million kilometres of rivers globally and identified rivers that remain free-flowing in their entire length. We found that only a third of rivers longer than 1,000 kilometres remain free-flowing over their entire length and less than a quarter flow uninterrupted to the ocean. Very long FFRs are largely restricted to remote regions of the Arctic and of the Amazon and Congo basins. In densely populated areas only few very long rivers remain free-flowing, such as the Irrawaddy and Salween. Dams and reservoirs and their up- and downstream propagation of fragmentation and flow regulation are the leading contributors to the loss of river connectivity. Plans to rapidly develop new infrastructure in basins around the world threaten the loss of extensive kilometers of free-flowing rivers, including status changes of several iconic long free-flowing rivers in tropical regions, such as the Amazon, Salween, Irrawaddy and Karnali rivers. Given the current status and future perspective of free-flowing rivers, we will discuss a range of opportunities for application of the Connectivity Status Index, including a) as a component in studies of ecosystem health; b) to play a role in prioritizing rivers with high conservation value for protection; c) in optimizing the informed selection of low-impact infrastructure developments; and d) as a tool for national and global monitoring.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».