Temperatures experienced by wood-boring beetles in the under-bark microclimate

Vermunt, Bradley; Cuddington, Kim; Sobek-Swant, Stephanie; Crosthwaite, Jill C.; Lyons, D. Barry; Sinclair, Brent J.

doi:10.1016/j.foreco.2011.12.019

Cited by 40 publications

(26 citation statements)

References 27 publications

(60 reference statements)

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“…Bark foragers have a food source that is available throughout the annual cycle (Vermunt et al. ), and all of these species are permanent residents. For waterbird invertivores and water‐foraging species, in particular, it is likely that their primary food sources are less affected by either short‐term climate variability or long‐term climate averages than by the condition and quality of the water bodies they depend on.…”

Section: Discussionmentioning

confidence: 99%

“…During the breeding season, occurrences of floral hover species may be less tied to nectar resources influenced by weather and more to local habitat characteristics and presence of conspecifics (Feldman and McGill 2013). Bark foragers have a food source that is available throughout the annual cycle (Vermunt et al 2012), and all of these species are permanent residents. For waterbird invertivores and water-foraging species, in particular, it is likely that their primary food sources are less affected by either short-term climate variability or long-term climate averages than by the condition and quality of the water bodies they depend on.…”

Section: Discussionmentioning

confidence: 99%

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Potential breeding distributions of U.S. birds predicted with both short‐term variability and long‐term average climate data

Bateman

Pidgeon

Radeloff

et al. 2016

Ecological Applications

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Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate variability is low, and assess how species' potential distributions may have already shifted due recent climate change. However, long-term climate averages require less data and processing time and may be more readily available for some areas of interest. Where data on short-term climate variability are not available, long-term climate information is a sufficient predictor of species distributions in many cases. However, short-term climate variability data may provide information not captured with long-term climate data for use in SDMs.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Potential breeding distributions of U.S. birds predicted with both short‐term variability and long‐term average climate data

Bateman

Pidgeon

Radeloff

et al. 2016

Ecological Applications

View full text Add to dashboard Cite

show abstract

“…Mainly minimum and maximum temperatures were analysed in similar studies. While the results on the buffering effect of wood against minimum winter temperatures are unequivocal (Bolstad et al 1997;Tran et al 2007;Vermunt et al 2012), maximum temperature values were found to be higher inside (Bolstad et al 1997;Vermunt et al 2012), or higher outside the trees (Tran et al 2007). Apart from examining the extreme and mean values, we also took into account the general thermal variability pattern inside and outside stumps.…”

Section: Discussionmentioning

confidence: 86%

“…Therefore, most existing studies examined living pine trees, and temperature data were recorded under the bark of trees. The results are contradictory; some studies showed that the buffering effect of wood can be small (<1 °C difference for an annual study; Bolstad et al 1997), or considerable (up to 12 °C difference for a period of sub-zero temperatures; Beal 1934, after Tran et al 2007; that it may have a constant effect (Bolstad et al 1997), or may depend on other environmental factors, as in a two-year study on 60 ash trees by Vermunt et al (2012). Potter and Andresen (2002) designed a theoretical model of heat flow throughout the tree.…”

Section: Introductionmentioning

confidence: 97%

Microclimate buffering of winter temperatures by pine stumps in a temperate forest

Walczyńska

Kapusta

2016

Clim Dyn

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“…averaged ~2 °C warmer than winter air temperatures; however, buffering capacity is also dependent on several other factors (e.g. orientation of bole exposure, time of day, tree species and diam, wood and tissue moisture, depth of overwintering site) (Derby & Gates 1966;Bolstad et al 1997;Vermunt et al 2012). Additionally, during winter months, X. glabratus may be in direct contact with ice crystals from moisture stored within the wood or from that of R. lauricola.…”

Section: Resultsmentioning

confidence: 99%