Projecting exceedance of juvenile salmonid thermal maxima in streams under climate change: A crosswalk from lab experiments to riparian restoration
Notice bibliographique
Résumé
Abstract Concern over rising water temperatures for freshwater ectotherms has led to application of experimentally derived thermal thresholds to stream temperature models for estimation of streams at high risk of exceeding thermal thresholds under current and future climate conditions. We optimised an approach that links field‐relevant thermal maxima experiments to corresponding stream temperature models and identifies opportunities to reduce stream temperatures through riparian tree growth. We conducted a thermal maxima experiment on cold‐water adapted juvenile Chinook ( Oncorhynchus tshawytscha ) and coho salmon ( Oncorhynchus kisutch ) that reflected natural temperatures by using incremental temperature ramping with diel fluctuations (IT‐D max ) and refit a regionally specific stream temperature model for British Columbia, Canada to directly relate to lab‐derived thresholds. Salmon‐bearing streams across British Columbia were categorised by threshold exceedance risk (i.e., low, moderate, high, severe) based on risk tolerance scenarios for management decision making (i.e., considering a range of prediction intervals [PIs] and stream thermal sensitivities to air temperature). We linked these results directly to riparian management and restoration actions by estimating the potential for riparian tree growth to reduce threshold exceedance risk. Lab‐derived IT‐D max endpoints were consistently 24°C (based on the median value between the 7‐day average of the daily maximum and the mean weekly average temperature) across acclimation treatments for both species. Under current conditions, most stream reaches (99.6% using an intermediate risk tolerance scenario) were below the thermal threshold; streams with moderate to high risk of threshold exceedance were projected to increase from 0.4% to 1.5% (total linear stream length of 6,929 km) by end of century. The risk‐averse (high sensitivity, 75% PI) and risk‐tolerant (low sensitivity, 95% PI) scenarios differed by 1,107 km of streams predicted to have a moderate to severe risk of exceeding thresholds by end of century. Maximal riparian tree growth was predicted to shift 670 km of streams from moderate to low exceedance risk under end‐of‐century conditions and intermediate risk tolerance, showing the potential for mitigation from thermal impacts. Our integrative approach tackled several key considerations in identifying streams at high temperature risk for freshwater ectotherms that to date have not been addressed. Furthermore, we showcased the delineation of spatially comprehensive estimates that identify where management mitigation and a specific restoration activity may be most needed to reduce impacts of rising temperatures on rearing salmonids across an extensive region.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».