The “sun-effect”: microclimatic alterations predispose forest edges to bark beetle infestations

Kautz, Markus; Schopf, R.; Ohser, Joachim

doi:10.1007/s10342-013-0685-2

Cited by 96 publications

(74 citation statements)

References 55 publications

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“…The spatial distribution of a butterfly, Lopinga achine Scopoli (Lepidoptera: Nymphalidae), showed distinct edge-biased distribution, which was explained by specific microclimatic conditions leading to the ground cover of Carex montana L. (Cyperaceae) having the highest abundance near forest edges (Bergman 1999). In a study of bark beetle [Ips typographus L. (Coleoptera: Curculionidae)] infestations, Kautz et al (2013) investigated the risk of infestation in three types of forest edges and compared the results of trees from the interior of the same forests. They concluded that the risk of bark beetle infestation was highest in forest patches cleared by sanitary logging measures, in particular along south-facing edges.…”

Section: Microclimatementioning

confidence: 99%

Edge-biased distributions of insects. A review

Nguyen

Nansen

2018

Agron. Sustain. Dev.

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Spatial ecology includes research into factors responsible for observed distribution patterns of organisms. Moreover, the spatial distribution of an animal at a given spatial scale and in a given landscape may provide valuable insight into its host preference, fitness, evolutionary adaptation potential, and response to resource limitations. In agro-ecology, in-depth understanding of spatial distributions of insects is of particular importance when the goals are to (1) promote establishment and persistence of certain food webs, (2) maximize performance of pollinators and natural enemies, and (3) develop precision-targeted monitoring and detection of emerging outbreaks of herbivorous pests. In this article, we review and discuss a spatial phenomenon that is widespread among insect species across agricultural systems and across spatial scales-they tend to show "edge-biased distributions" (spatial distribution patterns show distinct "edge effects"). In the conservation and biodiversity literature, this phenomenon has been studied and reviewed intensively in the context of how landscape fragmentation affects species diversity. However, possible explanations of, and also implications of, edge-biased distributions of insects in agricultural systems have not received the same attention. Our review suggests that (1) mathematical modeling approaches can partially explain edge-biased distributions and (2) abiotic factors, crop vegetation traits, and environmental parameters are factors that are likely responsible for this phenomenon. However, we argue that more research, especially experimental research, is needed to increase the current understanding of how and why edge-biased distributions of insects are so widespread. We argue that the fact that many insect pests show edge-biased distribution patterns may be used to optimize both pest monitoring practices and precision targeting of pesticide applications and releases of natural enemies.

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Section: Microclimatementioning

confidence: 99%

Edge-biased distributions of insects. A review

Nguyen

Nansen

2018

Agron. Sustain. Dev.

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“…Grodzki et al, 2006;Hilszczań ski et al, 2006). During the progradation stage of the outbreak, defined as the period of initial beetle population increase during an outbreak, which is thought to be governed by a combination of topographic, stand structure, and environmental factors (Kautz et al, 2013;Mezei et al, 2014b), bark beetles spread rapidly at large spatial scales, flying distances well beyond 500 m, in search of large, weakened host trees (Wichmann and Ravn, 2001;Wermelinger, 2004). By the outbreak's culmination, marked by epidemic beetle population levels and high tree mortality rates, attacks become more proximal to previously infested host trees and selection is dictated less by topographic and environmental factors (Mezei et al, 2014b).…”

Section: Introductionmentioning

confidence: 99%

Tree and stand-level patterns and predictors of Norway spruce mortality caused by bark beetle infestation in the Tatra Mountains

Sproull

Adamus

Bukowski

et al. 2015

Forest Ecology and Management

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“…Damage was simulated based on Schroeder and Lindelow (2002), Kärvemo et al (2014), Kautz et al (2013), and from TFDI data from the study area (S. Wulff, pers. comm.…”

Section: Simulation Of Study Populationsmentioning

confidence: 99%

Improving the precision of sample-based forest damage inventories through two-phase sampling and post-stratification using remotely sensed auxiliary information

Roberge

Wulff

Reese

et al. 2016

Environ Monit Assess

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Many countries have a national forest inventory (NFI) designed to produce statistically sound estimates of forest parameters. However, this type of inventory may not provide reliable results for forest damage which usually affects only small parts of the forest in a country. For this reason, specially designed forest damage inventories are performed in many countries, sometimes in coordination with the NFIs. In this study, we evaluated a new approach for damage inventory where existing NFI data form the basis for two-phase sampling for stratification and remotely sensed auxiliary data are applied for further improvement of precision through post-stratification. We applied Monte Carlo sampling simulation to evaluate different sampling strategies linked to different damage scenarios. The use of existing NFI data in a two-phase sampling for stratification design resulted in a relative efficiency of 50 % or lower, i.e., the variance was at least halved compared to a simple random sample of the same size. With post-stratification based on simulated remotely sensed auxiliary data, there was additional improvement, which depended on the accuracy of the auxiliary data and the properties of the forest damage. In many cases, the relative efficiency was further reduced by as much as one-half. In conclusion, the results show that substantial gains in precision can be obtained by utilizing auxiliary information in forest damage surveys, through two-phase sampling, through post-stratification, and through the combination of these two approaches, i.e., post-stratified two-phase sampling for stratification.

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The “sun-effect”: microclimatic alterations predispose forest edges to bark beetle infestations

Cited by 96 publications

References 55 publications

Edge-biased distributions of insects. A review

Edge-biased distributions of insects. A review

Tree and stand-level patterns and predictors of Norway spruce mortality caused by bark beetle infestation in the Tatra Mountains

Improving the precision of sample-based forest damage inventories through two-phase sampling and post-stratification using remotely sensed auxiliary information

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