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Dendroecological reconstructions of forest disturbance history using time-series analysis with intervention detection

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Abstract:

The detection of release events in the annual growth increments of trees has become a central and widely applied method for reconstructing the disturbance history of forests. While numerous approaches have been developed for identifying release events, the preponderance of these methods relies on running means that compare the percent change in growth rates. These methods do not explicitly account for the autocorrelation present within tree-ring width measurements and may introduce spurious events. This paper utilizes autoregressive integrated moving-average (ARIMA) processes to model tree-ring time series and incorporates intervention detection to identify pulse and step outliers as well as changes in trends indicative of a deterministic exogenous influence on past growth. This approach is evaluated by applying it to three chronologies from the Forest Responses to Anthropogenic Stress (FORAST) project that were impacted by prior disturbance events. The examples include a hemlock (Tsuga canadensis (L.) Carrière) chronology from New Hampshire, a white pine (Pinus strobus L.) chronology from Pennsylvania, and an American beech (Fagus grandifolia Ehrh.) chronology from Virginia. All three chronologies exhibit a clustering of step, pulse, and trend interventions subsequent to a known or likely disturbance event. Time-series analysis offers an alternative approach for identifying prior forest disturbances via tree rings based on statistical methods applicable across species and disturbance regimes.

La détection des épisodes de dégagement dans les accroissements annuels des arbres est devenue une méthode essentielle et largement appliquée pour reconstituer l'historique des perturbations dans les forêts. Alors que plusieurs approches ont été développées pour identifier les épisodes de dégagement, la prépondérance de ces méthodes repose sur des moyennes mobiles qui comparent le pourcentage de variation dans le taux de croissance. Ces méthodes ne tiennent pas explicitement compte de l'autocorrélation présente dans les mesures de largeur de cernes. Cet article utilise un processus autorégressif de moyennes mobiles intégrées pour modéliser les chronoséquences et incorpore (ARIMA) la détection des interventions pour identifier les impulsions et les observations aberrantes ainsi que les variations de tendance qui indiquent une influence déterministe exogène sur la croissance passée. Cette approche est évaluée pour trois courbes dendrochronologiques du projet « Forest Responses to Anthropogenic Stress » (FORAST) qui ont été affectées par des perturbations antérieures. Les exemples incluent des courbes dendrochronologiques de la pruche occidentale (Tsuga canadensis (L.) Carrière) provenant du New Hampshire, du pin blanc (Pinus strobus L.) provenant de la Pennsylvanie et du hêtre à grandes feuilles (Fagus grandifolia Ehrh.) provenant de la Virginie. Ces trois courbes montrent un regroupement de marches, d'impulsions et d'interventions subséquemment à un épisode connu ou probable de perturbation. L'analyse des courbes dendrochronologiques offre une approche alternative pour identifier les perturbations passées en forêt via les cernes annuels basée sur des méthodes statistiques applicables peu importe l'espèce et le régime de perturbation.[Traduit par la Rédaction]

Document Type: Research Article

Publication date: April 1, 2005

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  • Published since 1971, this monthly journal features articles, reviews, notes and commentaries on all aspects of forest science, including biometrics and mensuration, conservation, disturbance, ecology, economics, entomology, fire, genetics, management, operations, pathology, physiology, policy, remote sensing, social science, soil, silviculture, wildlife and wood science, contributed by internationally respected scientists. It also publishes special issues dedicated to a topic of current interest.
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