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Geology topics

J.R. Sauer

Publications and source records attributed to J.R. Sauer.

At least 55 records · Page 3Linked to original sources
USGS2003

Hierarchical models and the analysis of bird survey information

Management of birds often requires analysis of collections of estimates. We describe a hierarchical modeling approach to the analysis of these data, in which parameters associated with the individual species estimates are treated as random variables, and probability statements are made about the species parameters conditioned on the data. A Markov-Chain Monte Carlo (MCMC) procedure is used to fit the hierarchical model. This approach is computer intensive, and is based upon simulation. MCMC allows for estimation both of parameters and of derived statistics. To illustrate the application of this method, we use the case in which we are interested in attributes of a collection of estimates of population change. Using data for 28 species of grassland-breeding birds from the North American Breeding Bird Survey, we estimate the number of species with increasing populations, provide precision-adjusted rankings of species trends, and describe a measure of population stability as the probability that the trend for a species is within a certain interval. Hierarchical models can be applied to a variety of bird survey applications, and we are investigating their use in estimation of population change from survey data.

Ornis Hungarica↗
USGS2003

Developing a general conceptual framework for avian conservation science

Avian conservation science in North America has produced a variety of monitoring programs designed to provide information on population status of birds. Waterfowl surveys provide population estimates for breeding ducks over most of the continent, the North American Breeding Bird Survey (BBS) provides indexes to population change for >400 breeding bird species, and many other surveys exist that index bird populations at a variety of scales and seasons. However, many fundamental questions about bird population change remain unanswered. I suggest that analyses of monitoring data provide limited understanding of causes of population change, and that the declining species paradigm (Caughley 1994) is sometimes an inefficient approach to increasing our understanding of causes of population change. In North America, the North American Bird Conservation Initiative (NABCI) provides an opportunity to implement alternative approaches that use management, modeling of population responses to management, and monitoring in combination to increase our understanding of bird populations. In adaptive resources management, modeling provides predictions about consequences of management, and monitoring data allow us to assess the population consequences of management. In this framework, alternative hypotheses about response of populations to management can be evaluated by formulating a series of models with differing structure, and management and monitoring provide information about which model best predicts population response.

Ornis Hungarica↗
USGS2002

On the estimation of species richness based on the accumulation of previously unrecorded species

Estimation of species richness of local communities has become an important topic in community ecology and monitoring. Investigators can seldom enumerate all the species present in the area of interest during sampling sessions. If the location of interest is sampled repeatedly within a short time period, the number of new species recorded is typically largest in the initial sample and decreases as sampling proceeds, but new species may be detected if sampling sessions are added. The question is how to estimate the total number of species. The data collected by sampling the area of interest repeatedly can be used to build species-accumulation curves: the cumulative number of species recorded as a function of the number of sampling sessions (which we refer to as ?species-accumulation data?). A classic approach used to compute total species richness is to fit curves to the data on species accumulation with sampling effort. This approach does not rest on direct estimation of the probability of detecting species during sampling sessions and has no underlying basis regarding the sampling process that gave rise to the data. Here we recommend a probabilistic, nonparametric estimator for species richness for use with species-accumulation data. We use estimators of population size that were developed for capture-recapture data, but that can be used to estimate the size of species assemblages using species-accumulation data. Models of detection probability account for the underlying sampling process. They permit variation in detection probability among species. We illustrate this approach using data from the North American Breeding Bird Survey (BBS). We describe other situations where species accumulation data are collected under different designs (e.g., over longer periods of time, or over spatial replicates) and that lend themselves to use of capture-recapture models for estimating the size of the community of interest. We discuss the assumptions and interpretations corresponding to each situation.

Alabama, Louisiana, Maine, Maryland, New Hampshire↗
USGS2002

Large scale wildlife monitoring studies: Statistical methods for design and analysis

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 studios 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.

Environmetrics↗
USGS2002

Evaluating causes of population change in North American insectivorous songbirds

Although the North American Breeding Bird Survey (BBS) is a principal source of information regarding populations of most North American bird species, many features of the survey complicate analysis of population change. Correlation studies based on BBS data cannot be used to unambiguously define cause and effect relationships. Recently, Bohning-Gaese et al. (1993) presented an analysis of population trends in insectivorous songbirds using data from the BBS. They concluded that predation has played an important role in influencing population trends. We review aspects of the analysis methods for estimating population trends (e.g., observer effects, data subset) and for associating mean trends with species attributes (e.g., confounding of attributes). Using alternative analyses of the same BBS data, we demonstrate that the evidence that predation is associated with population declines is weaker than they suggested. Based on our analyses the only factor among those tested that is consistently associated with population trends is migration status (i.e., short-distance migrant/resident vs. long-distance migrant) during the period 1978-1987. Also, we present evidence that the harsh winters of the mid-1970's severely depressed populations of short-distance migrant species, and may be responsible for the observed associations between migration status and population trends.

Conservation Biology↗
USGS2002

A removal model for estimating detection probabilities from point-count surveys

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.

The Auk↗
USGS2002

Disentangling sampling and ecological explanations underlying species-area relationships

We used a probabilistic approach to address the influence of sampling artifacts on the form of species-area relationships (SARs). We developed a model in which the increase in observed species richness is a function of sampling effort exclusively. We assumed that effort depends on area sampled, and we generated species-area curves under that model. These curves can be realistic looking. We then generated SARs from avian data, comparing SARs based on counts with those based on richness estimates. We used an approach to estimation of species richness that accounts for species detection probability and, hence, for variation in sampling effort. The slopes of SARs based on counts are steeper than those of curves based on estimates of richness, indicating that the former partly reflect failure to account for species detection probability. SARs based on estimates reflect ecological processes exclusively, not sampling processes. This approach permits investigation of ecologically relevant hypotheses. The slope of SARs is not influenced by the slope of the relationship between habitat diversity and area. In situations in which not all of the species are detected during sampling sessions, approaches to estimation of species richness integrating species detection probability should be used to investigate the rate of increase in species richness with area.

Maryland↗
USGS2002

Hierarchical modeling of population stability and species group attributes from survey data

Many ecological studies require analysis of collections of estimates. For example, population change is routinely estimated for many species from surveys such as the North American Breeding Bird Survey (BBS), and the species are grouped and used in comparative analyses. We developed a hierarchical model for estimation of group attributes from a collection of estimates of population trend. The model uses information from predefined groups of species to provide a context and to supplement data for individual species; summaries of group attributes are improved by statistical methods that simultaneously analyze collections of trend estimates. The model is Bayesian; trends are treated as random variables rather than fixed parameters. We use Markov Chain Monte Carlo (MCMC) methods to fit the model. Standard assessments of population stability cannot distinguish magnitude of trend and statistical significance of trend estimates, but the hierarchical model allows us to legitimately describe the probability that a trend is within given bounds. Thus we define population stability in terms of the probability that the magnitude of population change for a species is less than or equal to a predefined threshold. We applied the model to estimates of trend for 399 species from the BBS to estimate the proportion of species with increasing populations and to identify species with unstable populations. Analyses are presented for the collection of all species and for 12 species groups commonly used in BBS summaries. Overall, we estimated that 49% of species in the BBS have positive trends and 33 species have unstable populations. However, the proportion of species with increasing trends differs among habitat groups, with grassland birds having only 19% of species with positive trend estimates and wetland birds having 68% of species with positive trend estimates.

Ecology↗
USGS2002

A hierarchical analysis of population change with application to Cerulean Warblers

Estimation of population change from count surveys is complicated by variation in quality of information among sample units, by the need for covariates to accommodate factors that influence detectability of animals, and by multiple geographic scales of interest. We present a hierarchical model for estimation of population change from the North American Breeding Bird Survey. Hierarchical models, in which population parameters at different geographic scales are viewed as random variables, provide a convenient framework for summary of population change among regions, accommodating regional variation in survey quality and a variety of distributional assumptions about observer effects and other nuisance parameters. Markov chain Monte Carlo methods provide a convenient means for fitting these models and also allow for construction of estimates of derived variables such as weighted regional trends and composite yearly population indices. We construct an overdispersed Poisson regression model for estimation of trend and year effects for Cerulean Warblers (Dendroica cerulea), accommodating nuisance covariates for observer and start-up effects, and estimating abundance- and area-weighted annual indices at regional and continent-wide geographic scales. A goodness-of-fit test is also presented for the model. Cerulean Warblers declined at a rate of 3.04% per year over the interval 1966-2000.

Ecology↗
USGS2002

Using Christmas Bird Count data in analysis of population change

The scientific credibility of Christmas Bird Count (CBC) results depend on the development and implementation of appropriate methods of statistical analysis. The key to any successful analysis of CBC data is to begin with a careful review of how the limitations of the data are likely to influence the results of the analysis, then to choose methods of analysis that accommodate as much as possible the limitations of the survey. For our analyses of CBC data, we develop a flexible model for effort adjustment and use information from the data to guide the selection of the best model. We include geographic structuring to accommodate the regional variation in number of samples, use a model that allows for overdispersed poisson data appropriate for counts, and employ empirical Bayes procedures to accommodate differences in quality of information in regional summaries. This generalized linear model approach is very flexible, and can be applied to a variety of studies focused on factors influencing wintering bird populations. In particular, the model can be easily modified to contain covariates, allowing for assessment of associations between CBC counts and winter weather, disturbance, and a variety of other environmental factors. These new survey analysis methods have added value in that they provide insights into changes in survey design that can enhance the value of the information. The CBC has been extremely successful as a tool for increasing public interest in birding and bird conservation. Use of the information for bird conservation creates new demands on quality of information, and it is important to maintain a dialogue between users of the information, information needs for the analyses, and survey coordinators and participants. Our work as survey analysts emphasizes the value and limitations of existing data, and provides some indications of what features of the survey could be modified to make the survey a more reliable source of bird population data. Surveys only remain useful if they adapt to current needs, while still maintaining consistency with historical goals.

American Birds↗
USGS2001

Effects of landscape composition and wetland fragmentation on frog and toad abundance and species richness in Iowa and Wisconsin, USA

Management of amphibian populations to reverse recent declines will require defining high-quality habitat for individual species or groups of species, followed by efforts to retain or restore these habitats on the landscape. We examined landscape-level habitat relationships for frogs and toads by measuring associations between relative abundance and species richness based on survey data derived from anuran calls and features of land-cover maps for Iowa and Wisconsin. The most consistent result across all anuran guilds was a negative association with the presence of urban land. Upland and wetland forests and emergent wetlands tended to be positively associated with anurans. Landscape metrics that represent edges and patch diversity also had generally positive associations, indicating that anurans benefit from a complex of habitats that include wetlands. In Iowa the most significant associations with relative abundance were the length of the edge between wetland and forest ( positive) and the presence of urban land (negative). In Wisconsin the two most significant associations with relative abundance were forest area and agricultural area ( both positive). Anurans had positive associations with agriculture in Wisconsin but not in Iowa. Remnant forest patches in agricultural landscapes may be providing refuges for some anuran species. Differences in anuran associations with deep water and permanent wetlands between the two states suggest opportunities for management action. Large-scale maps can contribute to predictive models of amphibian habitat use, but water quality and vegetation information collected from individual wetlands will likely be needed to strengthen those predictions. Landscape habitat analyses provide a framework for future experimental and intensive research on specific factors affecting the health of anurans.

Iowa, Wisconsin↗
USGS2001

Forest fragmentation and bird community dynamics: Inference at regional scales

With increasing fragmentation of natural areas and a dramatic reduction of forest cover in several parts of the world, quantifying the impact of such changes on species richness and community dynamics has been a subject of much concern. Here, we tested whether in more fragmented landscapes there was a lower number of area-sensitive species and higher local extinction and turnover rates, which could explain higher temporal variability in species richness. To investigate such potential landscape effects at a regional scale, we merged two independent, large-scale monitoring efforts: the North American Breeding Bird Survey (BBS) and the Land Use and Land Cover Classification data from the U.S. Geological Survey. We used methods that accounted for heterogeneity in the probability of detecting species to estimate species richness and temporal changes in the bird communities for BBS routes in three mid-Atlantic U.S. states. Forest breeding bird species were grouped prior to the analyses into area-sensitive and non-area-sensitive species according to previous studies. We tested predictions relating measures of forest structure at one point in time (1974) to species richness at that time and to parameters of forest bird community change over the following 22-yr-period (1975–1996). We used the mean size of forest patches to characterize landscape structure, as high correlations among landscape variables did not allow us to disentangle the relative roles of habitat fragmentation per se and habitat loss. As predicted, together with lower species richness for area-sensitive species on routes surrounded by landscapes with lower mean forest-patch size, we found higher mean year-to-year rates of local extinction. Moreover, the mean year-to-year rates of local turnover (proportion of locally new species) for area-sensitive species were also higher in landscapes with lower mean forest-patch size. These associations were not observed for the non-area-sensitive species group. These results suggest that landscape structure may influence forest bird communities at regional scales through its effects on the total number of species but also on the temporal rates of change in community composition. Evidence for higher rates of local extinction and turnover in more fragmented landscapes suggests that bird communities function as metapopulations at a regional scale, and points out the importance of colonizations and recolonizations from surrounding landscapes to local community dynamics. Further, our results illustrate that the methods used to estimate the community parameters can be a powerful statistical tool in addressing questions relative to the dynamics of communities.

Ecology↗
USGS2001

Estimation of species richness and parameters reflecting community dynamics using data from ecological monitoring programs

Although many ecological monitoring programs are now in place, the use of resulting data to draw inferences about changes in biodiversity is problematic. The difficulty arises because of the inability to count all animals present in any sampled area. This inability results not only in underestimation of species richness but also in potentially misleading comparisons of species richness over time and space. We recommend the use of probabilistic estimators for estimating species richness and related parameters (e.g., rate of change in species richness, local extinction probability, local turnover, local colonization) when animal detection probabilities are <1. We illustrate these methods using data from the North American Breeding Bird Survey obtained along survey routes in Maryland. We also introduce software to implement these estimation methods.

Book chapter↗
USGS2001

Regional patterns in proportion of bird species detected in the North American Breeding Bird Survey

Counts from the North American Breeding Bird Survey (BBS) underestimate species richness. We use capture-recapture methods to estimate species richness from BBS count data collected in 1996 and show that detection probabilities demonstrate clear regional patterns. Capture-recapture methods should be used to estimate species richness from count data, and failure to use estimation procedures for species richness could result in biased estimates of spatial change in species richness.

Book chapter↗
USGS2000

Evaluation of terrestrial and streamside salamander monitoring techniques at Shenandoah National Park

In response to concerns about amphibian declines, a study evaluating and validating amphibian monitoring techniques was initiated in Shenandoah and Big Bend National Parks in the spring of 1998. We evaluate precision, bias, and efficiency of several sampling methods for terrestrial and streamside salamanders in Shenandoah National Park and assess salamander abundance in relation to environmental variables, notably soil and water pH. Terrestrial salamanders, primarily redback salamanders ( Plethodon cinereus ), were sampled by searching under cover objects during the day in square plots (10 to 35 m 2 ). We compared population indices (mean daily and total counts) with adjusted population estimates from capture-recapture. Analyses suggested that the proportion of salamanders detected ( p ) during sampling varied among plots, necessitating the use of adjusted population estimates. However, adjusted population estimates were less precise than population indices, and may not be efficient in relating salamander populations to environmental variables. In future sampling, strategic use of capture-recapture to verify consistency of p 's among sites may be a reasonable compromise between the possibility of bias in estimation of population size and deficiencies due to inefficiency associated with the estimation of p . The streamside two-lined salamander ( Eurycea bislineata ) was surveyed using four methods: leaf litter refugia bags, 1 m 2 quadrats, 50 × 1 m visual encounter transects, and electric shocking. Comparison of survey methods at nine streams revealed congruent patterns of abundance among sites, suggesting that relative bias among the methods is similar, and that choice of survey method should be based on precision and logistical efficiency. Redback and two-lined salamander abundance were not significantly related to soil or water pH, respectively.

Texas, Virginia↗
USGS2000

A double-observer approach for estimating detection probability and abundance from point counts

Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated 'primary' observer indicates to another ('secondary') observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.

The Auk↗
USGS2000

Relative species richness and community completeness: avian communities and urbanization in the mid-Atlantic states

The idea that local factors govern local richness has been dominant for years, but recent theoretical and empirical studies have stressed the influence of regional factors on local richness. Fewer species at a site could reflect not only the influence of local factors, but also a smaller regional pool. The possible dependency of local richness on the regional pool should be taken into account when addressing the influence of local factors on local richness. It is possible to account for this potential dependency by comparing relative species richness among sites, rather than species richness per se. We consider estimation of a metric permitting assessment of relative species richness in a typical situation in which not all species are detected during sampling sessions. In this situation, estimates of absolute or relative species richness need to account for variation in species detection probability if they are to be unbiased. We present a method to estimate relative species richness based on capture-recapture models. This approach involves definition of a species list from regional data, and estimation of the number of species in that list that are present at a site-year of interest. We use this approach to address the influence of urbanization on relative richness of avian communities in the Mid-Atlantic region of the United States. There is a negative relationship between relative richness and landscape variables describing the level of urban development. We believe that this metric should prove very useful for conservation and management purposes because it is based on an estimator of species richness that both accounts for potential variation in species detection probability and allows flexibility in the specification of a 'reference community.' This metric can be used to assess ecological integrity, the richness of the community of interest relative to that of the 'original' community, or to assess change since some previous time in a community.

Delaware, Maryland, New Jersey, New York, Pennsylv↗