Point counts of birds in bottomland hardwood forests of the Mississippi Alluvial Valley: Duration, minimal sample size, and points versus visits

W.P. Smith; D.J. Twedt; D.A. Wiedenfeld; P.B. Hamel; R.P. Ford; R.J. Cooper

Home/Archive/USGS

USGS · 5230239

Point counts of birds in bottomland hardwood forests of the Mississippi Alluvial Valley: Duration, minimal sample size, and points versus visits

W.P. Smith·D.J. Twedt·D.A. Wiedenfeld·P.B. Hamel·R.P. Ford·R.J. Cooper

View original source ↗Read source document ↗Export metadata ↓

Abstract

The purpose of the research was to evaluate the efficacy of point count surveys in bottomland hardwood forests. The specific objectives were to determine: (1) whether the recommended distance measures for point count circular plots are useful in bottomland hardwood forests, (2) the optimum duration for each point count, (3) the optimum number of points to sample at each locality, (4) the optimum number of counts at each point during a season, and (5) the minimum sample size to accommodate the variation in bird species distribution and relative abundance throughout the lower MAV.

Explore related subjects

Research Paper Report

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

W.P. Smith, D.J. Twedt, D.A. Wiedenfeld, P.B. Hamel, R.P. Ford, R.J. Cooper. 1993. Point counts of birds in bottomland hardwood forests of the Mississippi Alluvial Valley: Duration, minimal sample size, and points versus visits. https://pubs.usgs.gov/publication/5230239

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2021

Simulating the effort necessary to detect changes in northern spotted owl (Strix occidentalis caurina) populations using passive acoustic monitoring

Passive acoustic monitoring is a promising method for monitoring rare and nocturnal species, and for tracking changes in forest wildlife biodiversity. We conducted simulations to compare and evaluate various passive acoustic sampling designs effectiveness for monitoring spotted owl ( Strix occidentalis caurina ) population trends. We found that each design was effective for detecting a decline (or stability) in spotted own populations within 10 years with even a moderate amount of sampling. There are however, important considerations and tradeoffs among the various design options. Often, estimated changes in use of the landscape were biased with a consistently lower magnitude of change compared to simulated changes in the population. Although this method has challenges, passive acoustic monitoring can be used to effectively monitor northern spotted owls in the Pacific Northwest.

California, Oregon, Washington↗

USGS2016

Relation of initial spacing and relative stand density indices to stand characteristics in a Douglas-fir plantation spacing trial

This report presents updated information on a 1981 Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco var. menziesii ) plantation spacing trial at 33 years from planting. Stand statistics at the most recent measurement were compared for initial spacing of 1 through 6 meters and associated relative densities. There was no clear relationship of spacing to top height. Diameter, live crown ratio, and percent survival increased with spacing; basal area and relative density decreased with increase in spacing. Volume in trees ≥ 4 cm diameter was greatest at 2 m spacing, while utilizable volume (trees ≥20 cm dbh) was greatest at 4 m spacing. Live crown ratio decreased and total crown projectional area increased with increasing relative density indices. Total crown projectional area was more closely related to relative density than to basal area.

Washington↗

USGS2000

Statistical considerations in monitoring birds over large areas

The proper design of a monitoring effort depends primarily on the objectives desired, constrained by the resources available to conduct the work. Typically, managers have numerous objectives, such as determining abundance of the species, detecting changes in population size, evaluating responses to management activities, and assessing habitat associations. A design that is optimal for one objective will likely not be optimal for others. Careful consideration of the importance of the competing objectives may lead to a design that adequately addresses the priority concerns, although it may not be optimal for any individual objective. Poor design or inadequate sample sizes may result in such weak conclusions that the effort is wasted. Statistical expertise can be used at several stages, such as estimating power of certain hypothesis tests, but is perhaps most useful in fundamental considerations of describing objectives and designing sampling plans.

Research Paper↗