Spatiotemporal stability of two beetle populations in non‐farmed habitats in an agricultural landscape
Notice bibliographique
Résumé
Summary Understanding the spatiotemporal ecology of invertebrates in agricultural ecosystems is important for developing management strategies to enhance biodiversity and reduce pesticide use. There is increasing recognition that studies need to be undertaken at scales larger than the field but the ability to do this is often resource limited. Pheromone traps, developed for pest management, can provide a relatively cheap means of collecting data across wide geographical scales. In this study we used such traps to examine the spatial stability of two species of agrioted beetles in non‐farmed habitats over a period of 3 years. The spatial distributions of adult male Agriotes lineatus and Agriotes obscurus were sampled from April until July at a number of sites across 950 ha on Westham Island, British Columbia, Canada. Data were assembled as spatially referenced cumulative trap counts by species and year, and analysed for evidence of aggregation and clustering using spatial analysis by distance indices (SADIE) methodology. Both intraspecific and interspecific association analyses were then carried out. A further set of analyses considered the spatial associations between different sampling dates in 2004. Agriotes lineatus was clustered into patches and gaps at the landscape scale in all 3 years, and A. obscurus showed similar spatial structure in 2002 and 2003. For both species, spatiotemporal stability at the landscape scale was evident. There was also a positive association between the two species in 2 out of the 3 years, suggesting that they were responding in a similar manner to the landscape environment. Synthesis and applications . This study showed that there was substantial temporal stability in the spatial structures of A. lineatus and A. obscurus in non‐farmed habitats, and that the two species respond in a broadly similar way to a heterogeneous agricultural landscape. This suggests that models to predict distributions within a landscape could be developed to guide decisions about where to grow vulnerable crops. Identification of the environmental factors that differentiate between clusters and gaps in their spatial distributions may also make it possible to manipulate populations and reduce their impact as pests without recourse to insecticides. Moreover, our results extend the spatial scales over which SADIE statistics have been used, and demonstrate the usefulness of pheromone trapping as a sampling method in addressing ecological questions at a landscape scale.
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 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) | 0,000 | 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 ».