Spatio-Temporal Dynamics of Snowshoe Hare Density and Relationships to Canada Lynx Occurrence in Northern Maine
Notice bibliographique
Résumé
I compared snowshoe hare densities between two locations in northern Maine, 2001-2009, to determine if fluctuations occurred in geographic synchrony, and to compare the magnitude of population change to amplitudes documented for cyclic hare populations within the boreal forest. Changes in winter density occurred synchronously between locations. Hares exhibited a 6-year period of higher density from 2001-2006, followed by a 3-year period of lower density from 2007-2009. Average density during the high period was lower than most peak levels observed in boreal populations, and average density during the low period was higher than the lowest densities observed in cyclic boreal populations. The 2.1-fold change in density was dampened compared to amplitudes of change documented for boreal populations. While hare populations fluctuated synchronously between two locations, they did not exhibit the extreme cyclic dynamics documented in the boreal forest. I investigated whether forest development can explain the observed hare decline in regenerating conifer stands in northern Maine. I evaluated the strength of relationship between the decline in hare fecal pellet density and a suite of stand development indices, including stand age, site quality, and relative density from a density management diagram. Additionally, I predicted hare pellet density using a model based on measures of vegetation structure and compared observed pellet density during the low hare density period to predicted density based on vegetation structure. Observed pellet density was lower than predicted for all stands. All relationships between the decline in pellet density and stand development indices were non-significant except one, which indicated a negative relationship between the decline in pellet density and relative density. This result was inconsistent with the hypotheses that the hare decline was driven by stand development. Alternatively, broad-scale processes (e.g. community interactions with mobile predators, or spatially-correlated environmental perturbations) may be driving factors behind declines in hare density. Finally, I evaluated the influence of declines in hares from the period of high density (2001-2006) to the period of low density (2007-2009) on predicted probability of occurrence of Canada lynx across a 1.6 million acre landscape of northern Maine. I estimated the change in landscape-scale densities of hares from the high to low period, and applied an occurrence model to project changes in predicted probability of occurrence of lynx. With habitat composition held static at the 2004 condition, 14.7% of potential lynx home ranges were predicted to have hare density exceeding 0.75 hares/ha during the high period; however, none of the ranges were predicted to have hare density exceeding 0.75 hares/ha during the low period, and 95.1% of the landscape had a predicted density of < 0.50 hares/ha. During the high period, 22.1% of forestland had a probability of lynx occurrence > 80%, but during the low period, only 0.2% had probability > 80%, and 98% had a probability < 50%. On average, lynx would have had to increase their home-range size by 1.9-times during the period of low hare density to have access to an equivalent number of hares as during the period of high density.
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 | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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 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 ».