Can dispersal buffer against salinity‐driven zooplankton community change in Great Plains' lakes?
Notice bibliographique
Résumé
Abstract The North American Great Plains contains thousands of lakes that vary in salinity from freshwater to hypersaline. Paleolimnological studies show that salinity levels in these lakes are tightly linked with climate, and current projections point to a more arid future in the region due to natural and anthropogenic climate change, potentially influencing lake salinity. Many zooplankton species are sensitive to changes in salinity, and their position near the base of the aquatic food web makes it important to understand how they might respond to increasing salinity levels. Zooplankton communities in lakes with rising salinity levels may exhibit changes in structure, including a shift toward more salinity‐tolerant species and a reduction in abundance, species richness, and diversity. However, it is possible that dispersal of zooplankton among lakes could mitigate such community changes when migrant populations replace sensitive zooplankton with those that are locally adapted to higher salinities. To test if dispersal could reduce salinity‐induced changes in zooplankton communities, we ran a field enclosure experiment at a freshwater lake in southern Saskatchewan where we manipulated salinity levels and zooplankton dispersal. We evaluated how salinity and dispersal influenced species identities and relative abundances (community structure) using multivariate statistics and comparing taxonomic and functional compositions among the different treatments (richness, diversity, and evenness). We found that increasing salinity levels in our enclosures above that in our study lake resulted in lower zooplankton abundances and species richness levels, primarily due to the loss of cladoceran species. However, patterns in our multivariate analyses suggested that cladocerans were maintained in enclosures with salinity levels of 2.5 and 5.0 g/L when those enclosures received immigration from nearby lakes. In contrast, our univariate analyses failed to find evidence that immigration affected community structure (richness, diversity, evenness). The lack of significant statistical differences could suggest that dispersal does not have an effect, or it may have been a problem with statistical power, as a power analysis suggested that fairly large effect sizes would have been required to achieve statistical significance. Based on our results, we were unable to reach a definitive conclusion on the role that dispersal might play in buffering zooplankton communities against salinity‐driven changes. However, our study provides two important insights for planning future work. First, our power analyses indicated that more replication may be needed given the variability among our experimental enclosures. Second, the patterns in our multivariate analyses suggested that cladocerans could be maintained in lakes undergoing salinity increases if they receive immigration from surrounding lakes with higher salinities. Future work examining how inter‐ and intraspecific salinity tolerance varies across lakes with a gradient of salinities would be helpful for understanding the role that dispersal might play in buffering against salinity‐driven losses of cladoceran zooplankton.
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 | 0,001 |
| 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 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».