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coin (version 1.4-3)

treepipit: Tree Pipits in Franconian Oak Forests

Description

Data on the population density of tree pipits, Anthus trivialis, in Franconian oak forests including variables describing the forest ecosystem.

Usage

treepipit

Arguments

Format

A data frame with 86 observations on 10 variables.

counts

the number of tree pipits observed.

age

age of the overstorey oaks taken from forest data.

coverstorey

cover of canopy overstorey (%). The crown cover is described relative to a fully stocked stand. Very dense overstorey with multiple crown cover could reach values greater than 100%.

coverregen

cover of regeneration and shrubs (%).

meanregen

mean height of regeneration and shrubs.

coniferous

coniferous trees (% per hectare).

deadtree

number of dead trees (per hectare).

cbpiles

number of crowns and branch piles (per hectare). All laying crowns and branch piles were counted. These were induced by logging and the creation of wind breaks.

ivytree

number of ivied trees (per hectare).

fdist

distance to the forest edge. The closest distance to the forest edge was measured from the centre of each grid.

Details

This study is based on fieldwork conducted in three lowland oak forests in the Franconian region of northern Bavaria close to Uffenheim, Germany. Diurnal breeding birds were sampled five times, from March to June 2002, using a quantitative grid mapping. Each grid was a one-hectare square. In total, 86 sample sites were established in 9 stands. All individuals were counted in time intervals of 7 min/grid during slow walks along the middle of the grid with a stop in the centre. Environmental factors were measured for each grid.

References

Müller, J. and Hothorn, T. (2004). Maximally selected two-sample statistics as a new tool for the identification and assessment of habitat factors with an application to breeding bird communities in oak forests. European Journal of Forest Research 123(3), 219--228. tools:::Rd_expr_doi("10.1007/s10342-004-0035-5")

Examples

Run this code
## Asymptotic maximally selected statistics
maxstat_test(counts ~ age + coverstorey + coverregen + meanregen +
                      coniferous + deadtree + cbpiles + ivytree,
             data = treepipit)

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