Does dispersal limitation impact the recovery of zooplankton communities damaged by a regional stressor?
Notice bibliographique
Résumé
The acidification and ongoing pH recovery of lakes in Killarney Provincial Park, Canada, provide a unique opportunity to increase our understanding of the role of dispersal as communities respond to environmental change. Time lags in community recovery following pH increases in acidified lakes have typically been attributed to local factors; however, no studies have been conducted to determine if colonist availability could also play a role. Moreover, the rates and mechanisms of dispersal to recovering lakes are poorly understood. In this study, we sought to determine if dispersal limitation could impede the recovery of zooplankton communities affected by a regional stressor. To achieve this objective, we used a combination of empirical data collection along with spatial modeling and variation partitioning techniques. Data were collected by measuring dispersal to four recovering lakes in Killarney Park. Dispersal traps were placed next to lakes to measure immigration overland, drift nets were used to measure immigration via streams, and in situ emergence traps were used to quantify immigration from historically deposited resting eggs. Documented dispersal levels were then compared with the theoretical critical density required for reproduction (N(c)) to determine if adequate numbers were dispersing to establish populations of acid-sensitive species in recovering lakes. Spatial modeling and variation partitioning were conducted using community and physical/chemical data for 45 park lakes that were collected in 1972-1973, 1990, and 2005. Field data demonstrated that a variety of zooplankton species were dispersing to recovering lakes through streams and the egg bank, but few individuals were collected dispersing overland. Although we identified 24 species of zooplankton dispersing, only six species absent from the communities of our study lakes were identified from our traps, and two of these species did not disperse in high enough numbers to surpass N(c). Local environmental variables explained the largest proportion of the variation in zooplankton communities (18-37%); however, spatial variables were also important (7-18%). The significant spatial patterns we found in the park's zooplankton communities, combined with the low overland dispersal levels we documented, suggest that dispersal limitation may be a more important impediment to recovery than was previously thought.
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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 | 0,001 |
| 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) | 0,008 | 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 ».