@article{simons_shriner_farnsworth_2006, title={Comparison of breeding bird and vegetation communities in primary and secondary forests of Great Smoky Mountains National Park}, volume={129}, ISSN={["1873-2917"]}, DOI={10.1016/j.biocon.2005.10.044}, abstractNote={We compared breeding bird communities and vegetation characteristics at paired point locations in primary (undisturbed) and mature secondary forest (70–100 years old) sites in Great Smoky Mountains National Park, USA to understand how sites logged prior to creation of the park compare to undisturbed sites following 70 years of protection from human disturbance. We found that bird and vegetation communities are currently similar, but retain some differences in species composition. Rank abundance curves for primary and secondary forest bird communities showed very similar patterns of species dominance. Species composition was also similar on the two sites which shared 24 of the 25 most frequently recorded species. Nonetheless, comparisons of density estimates derived from distance sampling showed three bird species were more abundant on primary forest sites and that one bird species was significantly more abundant on secondary forest sites. Notably, comparisons based on raw counts (unadjusted for potential differences in detectability) produced somewhat different results. Analyses of vegetation samples for the paired sites also showed relative similarity, but with some differences between primary and secondary forests. Primary forest sites had more large trees (trees greater than 50 cm diameter at breast height) and late successional species. Primary forest sites had a denser tall shrub layer while secondary forest sites had a denser canopy layer. Nonetheless, tree species richness, basal area of live trees and number of standing snags did not differ between primary and secondary forest sites. Results indicate that breeding bird communities on sites within the park that were logged commercially 70 years ago are currently quite similar to bird communities on sites with no history of human disturbance. Similarities between the bird communities on previously disturbed and undisturbed sites in Great Smoky Mountains National Park may exceed those on more fragmented landscapes because large patches of primary forest, adjacent to commercially logged sites, remained in the park when it was established in 1935. These patches of primary forest may have served as source areas for commercially logged sites.}, number={3}, journal={BIOLOGICAL CONSERVATION}, author={Simons, TR and Shriner, SA and Farnsworth, GL}, year={2006}, month={May}, pages={302–311} }
 @article{farnsworth_pollock_nichols_simons_hines_sauer_2002, title={A removal model for estimating detection probabilities from point-count surveys}, volume={119}, ISSN={["1938-4254"]}, DOI={10.1642/0004-8038(2002)119[0414:ARMFED]2.0.CO;2}, abstractNote={Use of point-count surveys is a popular method for collecting data on abundance and distribution of birds. However, analyses of such data often ignore potential differences in detection probability. We adapted a removal model to directly estimate detection probability during point-count surveys. The model assumes that singing frequency is a major factor influencing probability of detection when birds are surveyed using point counts. This may be appropriate for surveys in which most detections are by sound. The model requires counts to be divided into several time intervals. Point counts are often conducted for 10 min, where the number of birds recorded is divided into those first observed in the first 3 min, the subsequent 2 min, and the last 5 min. We developed a maximum-likelihood estimator for the detectability of birds recorded during counts divided into those intervals. This technique can easily be adapted to point counts divided into intervals of any length. We applied this method to unlimited-radius counts conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. We found differences in detection probability among species. Species that sing frequently such as Winter Wren (Troglodytes troglodytes) and Acadian Flycatcher (Empidonax virescens) had high detection probabilities (∼90%) and species that call infrequently such as Pileated Woodpecker (Dryocopus pileatus) had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. We used the same approach to estimate detection probability and density for a subset of the observations with limited-radius point counts.}, number={2}, journal={AUK}, author={Farnsworth, GL and Pollock, KH and Nichols, JD and Simons, TR and Hines, JE and Sauer, JR}, year={2002}, month={Apr}, pages={414–425} }
 @article{pollock_nichols_simons_farnsworth_bailey_sauer_2002, title={Large scale wildlife monitoring studies: statistical methods for design and analysis}, volume={13}, ISSN={["1099-095X"]}, DOI={10.1002/env.514}, abstractNote={Techniques for estimation of absolute abundance of wildlife populations have received a lot of attention in recent years. The statistical research has been focused on intensive small-scale studies. Recently, however, wildlife biologists have desired to study populations of animals at very large scales for monitoring purposes. Population indices are widely used in these extensive monitoring programs because they are inexpensive compared to estimates of absolute abundance. A crucial underlying assumption is that the population index (C) is directly proportional to the population density (D). The proportionality constant, β, is simply the probability of ‘detection’ for animals in the survey. As spatial and temporal comparisons of indices are crucial, it is necessary to also assume that the probability of detection is constant over space and time. Biologists intuitively recognize this when they design rigid protocols for the studies where the indices are collected. Unfortunately, however, in many field studies the assumption is clearly invalid. We believe that the estimation of detection probability should be built into the monitoring design through a double sampling approach. A large sample of points provides an abundance index, and a smaller sub-sample of the same points is used to estimate detection probability. There is an important need for statistical research on the design and analysis of these complex studies. Some basic concepts based on actual avian, amphibian, and fish monitoring studies are presented in this article. Copyright © 2002 John Wiley & Sons, Ltd.}, number={2}, journal={ENVIRONMETRICS}, author={Pollock, KH and Nichols, JD and Simons, TR and Farnsworth, GL and Bailey, LL and Sauer, JR}, year={2002}, month={Mar}, pages={105–119} }