Selection of roosting habitat by forest bats in a diverse forested landscape

Perry, Roger W.; Thill, Ronald E.; Leslie, David M.

doi:10.1016/j.foreco.2006.10.008

Cited by 53 publications

(48 citation statements)

References 44 publications

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“…Forest habitat classes (Perry et al, 2007) were derived from ONF forest stand maps of the study area, which were updated and corrected using a 10-m digital color orthoquad (DOQ) and ground truthing. Because single-tree selection stands and pine-woodland restoration areas were in the early stages of development and were treated initially with similar partial harvesting, midstory removal, and burning in 2000, those two treatments were grouped into a single ''partially harvested/thinned'' class.…”

Section: Roost and Site Data Collectioncontrasting

confidence: 99%

“…National forest lands in the basin were divided into six 513-1791-ha management units where different silvicultural treatments were implemented in 2000 (Perry et al, 2007). A 1232-ha pine-grassland restoration unit was initially thinned in 2000; goal of this restoration is to create open woodland conditions maintained by periodic prescribed burning.…”

Section: Study Areamentioning

confidence: 78%

“…Although Hutchinson and Lacki (2000) found no red bat roosts <50 m from any edge, we found red bats frequently roosted in greenbelts that were generally <30-m wide. We also found red bats preferred to roost in close proximity to partially harvested stands (Perry et al, 2007). Thus, our data do not support suggestions that red bats avoid edges.…”

Section: Discussionmentioning

confidence: 99%

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Sex-specific roost selection by adult red bats in a diverse forested landscape

Perry

Thill

Carter

2007

Forest Ecology and Management

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Section: Roost and Site Data Collectioncontrasting

confidence: 99%

Section: Study Areamentioning

confidence: 78%

Section: Discussionmentioning

confidence: 99%

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Sex-specific roost selection by adult red bats in a diverse forested landscape

Perry

Thill

Carter

2007

Forest Ecology and Management

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“…Traditionally, habitat polygons are based on a landscape concept of spatial area using x and y coordinate axes that represent distribution of species across the landscape (e.g., Krummel et al 1987, Perry et al 2007). Often, ecologically relevant comparisons among species are difficult when polygons are overlaid and there is no information concerning important environmental drivers.…”

Section: Introductionmentioning

confidence: 87%

Landscape position and habitat polygons in a dynamic coastal environment

et al. 2011

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Abstract. In contrast to stable inland systems, coastal landscape positions are dynamic, changing as shorelines migrate and storms alter topography. We define landscape position by distance to ocean shoreline and elevation above sea level, two metrics that integrate a suite of environmental and biotic factors. As shoreline and elevation change, suitability of a geo-referenced position for a given plant species may also change. The objectives of our study were to use two methods for measuring landscape position (GPS and hyperspectral/light detection and ranging or LIDAR) to develop habitat polygons, compare habitat polygons for five species representing several adaptive strategies, and illustrate change in landscape position due to migrating shoreline for a Virginia, USA barrier island. Habitat polygons for each species were distinct, represented several growth forms or functional groups, and were indicative of tolerances to biotic and abiotic stresses. The habitat polygon for Cakile edentula (annual forb) was relatively small, indicating narrow habitat requirements for the strand environment. Cirsium horridulum (biennial forb), with succulent shoots and roots, occurred on dunes where water is most limiting. For the dunebuilding grass, Ammophila breviligulata, as distance from shoreline increased, minimum elevation also increased. Two woody species occurred across the entire island; however, Morella cerifera (N-fixing shrub), was limited to mesic swales whereas Juniperus virginiana (evergreen tree), with the largest habitat polygon, occurred on both dunes and swales. For a geo-referenced point on the north end of Hog Island, distance to shoreline increased from the shoreline to 1100 m inland over 139 years. In contrast, the geo-referenced point on the eroding portion of the island decreased from 1700 m to 120 m from the ocean shoreline over the same time period. Where sea level rise and storms are expected to alter shorelines and island topography, generation of habitat polygons from hyperspectral and LIDAR imagery provide rapid assessment of potential effects on species distribution patterns at local and regional scales. Habitat polygons have broad applicability beyond coastal systems and may contribute to a rapid assessment or identification of vulnerability for species as climate patterns shift through time.

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“…National Forest lands within the basin were divided into four areas where different silvicultural treatments were implemented in 2000 (Perry et al, 2007). These included: (1) partial harvesting and midstory removal (2096 ha) with overstory basal areas (BA) of 13.8 m 2 /ha pine and 1.1-2.3 m 2 /ha hardwood; (2) group selection (1044 ha) where groups or trees were removed in openings of 0.40-4.05 ha and pines in the forest surrounding these openings were thinned; (3) mix of treatments (1791 ha) including single-tree selection, group selection, seed-tree cuts, and unharvested areas in stands of approximately 18 ha; and (4) unharvested forest (836 ha) consisting mostly of mature, second-growth pine-hardwood forest.…”

Section: Study Areamentioning

confidence: 99%