Modeling cold tolerance in the mountain pine beetle, Dendroctonus ponderosae

Régnière, Jacques; Bentz, Barbara

doi:10.1016/j.jinsphys.2007.02.007

Cited by 163 publications

(160 citation statements)

References 58 publications

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“…Alterations in established climatic limitations to mountain pine beetle survival (Réginière and Bentz 2007 and an abundance of suitable hosts (typically Pinus contorta) have contributed to this current population increase and the associated spread of the beetle into geographic regions not conventionally host to large populations of mountain pine beetle (Taylor et al 2006). Typical mountain pine beetle monitoring and mitigation scenarios are informed by airborne platforms that identify foliar discoloration indicative of successful attack (red attack) and guide ground surveys to locate currently attacked trees (green attack) in a systematic manner (Wulder et al 2006b).…”

Section: Introductionmentioning

confidence: 99%

Challenges for the operational detection of mountain pine beetle green attack with remote sensing

Wulder¹,

White²,

Carroll³

et al. 2009

The Forestry Chronicle

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Mountain pine beetle infestations are spatially correlated; current (green) attack is often located near previous (red) attack. This spatial correlation between the green and red attack stages enables operational survey methods, as detection of red attack trees-typically from an airborne survey such as a helicopter GPS survey or aerial photography-guides the location of subsequent ground surveys for green attack trees. Forest managers, in an attempt to understand beetle movement and infestation patterns, hope to utilize remotely sensed data to detect and map green attack trees, with the expectation that the spatial extent, accuracy, and timeliness afforded by remotely sensed data will greatly improve the efficacy of beetle treatment and control. In this communication, we present the biological, logistical, and technological factors that limit the operational utility of remotely sensed data for green attack detection and mapping. To provide context for these limitations, we identify the operational information needs associated with green attack and discuss how these requirements dictate the characteristics of any potential remotely sensed data source (e.g., spatial, spectral, and temporal characteristics). Based upon our assessment, we conclude that the remote detection of green attack is not operationally viable, and is unlikely to become so unless the limiting factors we have identified are altered substantially or removed.Key words: green attack, remote sensing, operational, insect survey, high spatial resolution, high spectral resolution RÉSUMÉ Les infestations de dendroctones du pin ponderosa démontrent une corrélation spatiale : l'attaque courante (verte) est souvent localisée à proximité de l'attaque précédente (rouge). Cette corrélation spatiale entre les périodes vertes et rouges permet l'utilisation de méthodes de relevé opérationnelles, compte tenu que la détection d'arbres rouges attaqués-habituellement à partir d'un relevé par voie aérienne par exemple effectué au moyen d'un GPS monté à bord d'un hélicoptère ou par photos aériennes-indique la localisation des relevés terrestres à venir des arbres verts attaqués. Les aménagistes forestiers, cherchant à comprendre le déplacement des dendroctones et les patrons d'infestation, souhaitent utiliser les données obtenues par télédétection afin d'identifier et de cartographier les arbres verts attaqués, avec l' espoir que la distribution et la précision dans le temps et l' espace permises par les données de télédétection permettront de grandement améliorer l' efficacité du traitement et du contrôle du dendroctone. Nous présentons dans ce texte les facteurs biologiques, logistiques et technologiques qui limitent l'utilité opérationnelle des données de télédétection dans le cas de la détection et la cartographie des attaques vertes. Afin d'illustrer le contexte de ces limites, nous identifions les besoins requis en matière d'information opérationnelle associée à une attaque verte et nous discutons comment ces besoins dictent les caractéristiques de tout...

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Section: Introductionmentioning

confidence: 99%

Challenges for the operational detection of mountain pine beetle green attack with remote sensing

Wulder¹,

White²,

Carroll³

et al. 2009

The Forestry Chronicle

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“…Examples were presented by Wilder (1999), predicting the timing and magnitude of L. dispar outbreaks based on egg and larval performance, and Régnière and Bentz (2007), mechanistically modelling the regulation of population dynamics by density independent winter mortality and stage specific cold-tolerance. An important aspect in modelling population dynamics are the regulatory effects of predators and parasitoids (e.g., Mills and Getz, 1996;Abbott and Dwyer, 2007;Berggren et al, 2009).…”

Section: Occurrencementioning

confidence: 99%

Modelling natural disturbances in forest ecosystems: a review

Seidl

Fernandes

Fonseca

et al. 2011

Ecological Modelling

336

218

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“…Empirically driven, statistical approaches have been proposed (Safranyik et al 1975;Aukema et al 2008;Preisler et al 2012;Reyes et al 2012), and mechanistic models have also been developed (Bentz et al 1991;Gilbert et al 2004;Régnière and Bentz 2007;Powell and Bentz 2009), to analyze the role of temperature in MPB population outbreaks using historic and future climate data (Logan and Bentz 1999;Logan and Powell 2001;Hicke et al 2006;Safranyik et al 2010). While empirical models have good descriptive power for the range of conditions for which they were derived, they need to be used with caution under unobserved multivariate contexts such as encountered when crossing ecoregional boundaries.…”

Section: The Modelmentioning

confidence: 99%

“…Previous mechanistic model development, however, has used frameworks that don't allow inclusion of processes other than the influence of temperature on insect development time. For example, Powell and Bentz (2009) were successful in linking phenology, temperature, and population growth rates; although their approach is based on cohorts, it is unsuited to linking with other aspects of MPB life history such as cold tolerance (Régnière and Bentz 2007). MPB has no obligate diapause stage.…”

Section: The Modelmentioning

confidence: 99%