Sea ducks in the Atlantic Flyway: population status and a review of special hunting seasons
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Book↗
Geology topics
J.R. Sauer
Publications and source records attributed to J.R. Sauer.
DC birdscape: a program for monitoring neotropical migrant birds in Washington, DC
Urban and suburban habitats often contain a variety of Neotropical migratory birds, but are poorly sampled by programs such as the North American Breeding Bird Survey. DC Birdscape was developed to inventory and monitor birds in Washington, D.C. Birds were surveyed using a systematic sample of point counts during 1993-1995. Results indicate that species richness of Neotropical migratory birds varied among land-use categories, and that maximum species richness occurred in parkland habitats. Although DC Birdscape has provided relevant information on bird distribution and species richness, it is unclear whether the information is of sufficient management interest to support its continuation as a long-term monitoring program.
Book chapter↗
Combining information from monitoring programs: Complications associated with indices and geographic scale
To adequately monitor Neotropical migratory birds, information must be collected to assess population change at local, regional, and continent-wide scales. I suggest that large-scale survey results (such as those derived from the North American Breeding Bird Survey) should not be used to predict population attributes on parks, refuges, and other protected areas. These areas are often managed, and generally contain habitats that can be poorly sampled in large scale surveys, hence local bird populations might be quite different from those sampled in the large-scale surveys. Furthermore, we are limited in our capabilities to combine information from local surveys with large-scale survey data. Most surveys of bird populations collect indices of abundance which are often not comparable among surveys due to habitat and region specific differences in probabilities of detecting birds. In assessing the effects of management, it is important to understand the limitations of monitoring at different geographic scales and to design programs to monitor at the scale at which management is conducted.
Book chapter↗
Population and habitat assessment: Monitoring bird populations over large areas: Introduction
Monitoring provides essential information about status and change in bird populations. For Neotropical Migrant Birds (NTMBs), the North American Breeding Bird Survey (BBS) has been particularly influential in documenting regional population change and often is cited as justification for management actions. However, as with most bird surveys, the design of the BBS, and the geographic scale of the information, often limits its use either in evaluating the response of bird populations to management, or in identifying causes of population change.
Book chapter↗
Temporal and geographic patterns in population trends of brown-headed cowbirds
The temporal and geographic patterns in the population trends of Brown-headed Cowbirds are summarized from the North American Breeding Bird Survey. During 1966-1992, the survey-wide population declined significantly, a result of declining populations in the Eastern BBS Region, southern Great Plains, and the Pacific coast states. Increasing populations were most evident in the northern Great Plains. Cowbird populations were generally stable or increasing during 1966-1976, but their trends became more negative after 1976. The trends in cowbird populations were generally directly correlated with the trends of both host and nonhost species, suggesting that large-scale factors such as changing weather patterns, land use practices, or habitat availability were responsible for the observed temporal and geographic patterns in the trends of cowbirds and their hosts.
Book chapter↗
Landscape associations of frog and toad species in Iowa and Wisconsin, U.S.A
Landscape habitat associations of frogs and toads in Iowa and Wisconsin were tested to determine whether they support or refute previous general habitat classifications. We examined which Midwestern species shared similar habitats to see if these associations were consistent across large geographic areas (states). Rana sylvatica (wood frog), Hyla versicolor (eastern gray treefrog), Pseudacris crucifer (spring peeper), and Acris crepitans (cricket frog) were identified as forest species, P. triseriata (chorus frog), H. chrysoscelis (Cope's gray treefrog), R. pipiens (leopard frog), and Bufo americanus (American toad) as grassland species, and R. catesbeiana (bullfrog), R. clamitans (green frog), R. palustris (pickerel frog), and R. septentrionalis (mink frog) as lake or stream species. The best candidates to serve as bioindicators of habitat quality were the forest species R. sylvatica, H. versicolor, and P. crucifer, the grassland species R. pipiens and P. triseriata, and a cold water wetland species, R. palustris. Declines of P. crucifer, R. pipiens, and R. palustris populations in one or both states may reflect changes in habitat quality. Habitat and community associations of some species differed between states, indicating that these relationships may change across the range of a species. Acris crepitans may have shifted its habitat affinities from open habitats, recorded historically, to the more forested habitat associations we recorded. We suggest contaminants deserve more investigation regarding the abrupt and widespread declines of this species. Interspersion of different habitat types was positively associated with several species. A larger number of wetland patches may increase breeding opportunities and increase the probability of at least one site being suitable. We noted consistently negative associations between anuran species and urban development. Given the current trend of urban growth and increasing density of the human population, declines of amphibian populations are likely to continue.
Book chapter↗
Roadside versus remote: Is the habitat sampled by the Breeding Bird Survey in Maryland representative of statewide conditions?
The North American Breeding Bird Survey (BBS) has received criticism that the bird habitat sampled along the 24.5 mile long roadside transects may not be proportional to regional totals. If true, trends in bird populations recorded by the BBS may not be sensitive predictors of regional or continental change in songbird abundance. To test whether the approximately 60 BBS routes in Maryland representatively sample the state's habitat, a geographic information system (GIS) database was compiled of significant bird habitat identified from remotely sensed landcover and land-use information (e.g., Multi-Resolution Land Characteristics Consortiumclassified Landsat Thematic Mapper imagery, etc.). These GIS data layers were analyzed to determine the statewide acreage of identified habitats as well as the acreage in each of the major physiographic regions of Maryland. Regional and statewide totals were also extracted for the subsample of habitat within 30 m of the BBS transects. The results of the comparison of regional and statewide habitat totals with the BBS sample showed very low proportional difference for nearly all of the identified habitat parameters. For Maryland and perhaps other urbanizing states, the BBS provides an accurate sample of available songbird habitats.
Book chapter↗
A removal model for estimating detection probabilities from point-count surveys
We adapted a removal model to estimate detection probability during point count surveys. The model assumes one factor influencing detection during point counts is the singing frequency of birds. This may be true for surveys recording forest songbirds when most detections are by sound. The model requires counts to be divided into several time intervals. We used time intervals of 2, 5, and 10 min to develop a maximum-likelihood estimator for the detectability of birds during such surveys. We applied this technique to data from bird surveys 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. The overall detection probability for all birds was 75%. We found differences in detection probability among species. Species that sing frequently such as Winter Wren and Acadian Flycatcher had high detection probabilities (about 90%) and species that call infrequently such as Pileated Woodpecker 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. This method of estimating detectability during point count surveys offers a promising new approach to using count data to address questions of the bird abundance, density, and population trends.
Book chapter↗
The northeastern states' waterfowl breeding population survey
Efforts to tailor waterfowl hunting regulations to conditions in the Atlantic Flyway have been hampered by lack of information on local breeding populations. The Atlantic Flyway Council's technical section voted at its 1987 winter meeting (Atlantic Flyway Council Technical Section, Toronto, Canada) to establish a regional waterfowl breeding survey. Consequently, an annual survey was started in 1989 and further refined in 1993 using results from 1989 to 1992. During 1993-1997, annual spring surveys of more than 1,450 randomly selected 1-km2 plots, stratified by physiographic strata, were conducted in the Atlantic Flyway from New Hampshire to Virginia to estimate breeding populations of mallards (Arias platyrhynchos), American black ducks (A. rubripes), wood ducks (Aix sponsa), and Canada geese (Branta canadensis). Ground crews systematically surveyed all potential waterfowl habitat for these species in each plot. The adjusted mean mallard pair estimate over the 5-year period was 375,962 (range 310,299-415,182, mean SE 25,761) for the region surveyed. The estimate for black duck pairs was 31,1 54 (range 27,164'37,521, mean SE 4,978), and for wood duck pairs it was 240,473 (range 218,959-281,916, mean SE 25,408). Total number of Canada geese increased from 526,663 in 1993 to 892,278 in 1997. Population estimates for other species had unacceptably large standard errors.
Wildlife Society Bulletin↗
Why monitoring matters
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Bird Conservation↗
The 1995-1999 Summary of the North American Breeding Bird Survey
Data from the North American Breeding Bird Survey were used to estimate continental and regional changes in bird populations for the 5-yr period 1995-1999 and the 2-yr period 1998-1999. These short-term changes were placed in the context of population trends estimated over the 1966-1999 interval. During 1995-1999, 44% of all species exhibited positive trends over the entire survey area, while 44% of all species exhibited positive trends during 1998-1999; neither of these percentages differed significantly from 50%. The continental and regional percentages of species with positive trends were also analyzed for 12 species groups having shared life-history traits. Survey-wide for the entire survey period, grassland birds exhibited the lowest percentage of increasing species (19%). However, during 1995-1999 the declines were less extreme in the Central and Western BBS regions, with 49% and 36% of species increasing in these regions. Neotropical migrants continued to fare better than grassland birds in all regions, although in the Eastern BBS region only 30% of neotropical species had increasing trends during 1995-1999.
Bird Populations↗
Controlling for varying effort in count surveys: An analysis of Christmas Bird Count data
The Christmas Bird Count (CBC) is a valuable source of information about midwinter populations of birds in the continental U.S. and Canada. Analysis of CBC data is complicated by substantial variation among sites and years in effort expended in counting; this feature of the CBC is common to many other wildlife surveys. Specification of a method for adjusting counts for effort is a matter of some controversy. Here, we present models for longitudinal count surveys with varying effort; these describe the effect of effort as proportional to exp(B effortp), where B and p are parameters. For any fixed p, our models are loglinear in the transformed explanatory variable (effort)p and other covariables. Hence, we fit a collection of loglinear models corresponding to a range of values of p and select the best effort adjustment from among these on the basis of fit statistics. We apply this procedure to data for six bird species in five regions, for the period 1959-1988.
Journal of Agricultural, Biological, and Environme↗
Factors influencing counts in an annual survey of Snail Kites in Florida
Snail Kites ( Rostrhamus sociabilis ) in Florida were monitored between 1969 and 1994 using a quasi-systematic annual survey. We analyzed data from the annual Snail Kite survey using a generalized linear model where counts were regarded as overdispersed Poisson random variables. This approach allowed us to investigate covariates that might have obscured temporal patterns of population change or induced spurious patterns in count data by influencing detection rates. We selected a model that distinguished effects related to these covariates from other temporal effects, allowing us to identify patterns of population change in count data. Snail Kite counts were influenced by observer differences, site effects, effort, and water levels. Because there was no temporal overlap of the primary observers who collected count data, patterns of change could be estimated within time intervals covered by an observer, but not for the intervals among observers. Modeled population change was quite different from the change in counts, suggesting that analyses based on unadjusted counts do not accurately model Snail Kite population change. Results from this analysis were consistent with previous reports of an association between water levels and counts, although further work is needed to determine whether water levels affect actual population size as well as detection rates of Snail Kites. Although the effects of variation in detection rates can sometimes be mitigated by including controls for factors related to detection rates, it is often difficult to distinguish factors wholly related to detection rates from factors related to population size. For factors related to both, count survey data cannot be adequately analyzed without explicit estimation of detection rates, using procedures such as capture-recapture.
The Auk↗
On the importance of controlling for effort in analysis of count survey data: Modeling population change from Christmas Bird Count data
Count survey data are commonly used for estimating temporal and spatial patterns of population change. Since count surveys are not censuses, counts can be influenced by 'nuisance factors' related to the probability of detecting animals but unrelated to the actual population size. The effects of systematic changes in these factors can be confounded with patterns of population change. Thus, valid analysis of count survey data requires the identification of nuisance factors and flexible models for their effects. We illustrate using data from the Christmas Bird Count (CBC), a midwinter survey of bird populations in North America. CBC survey effort has substantially increased in recent years, suggesting that unadjusted counts may overstate population growth (or understate declines). We describe a flexible family of models for the effect of effort, that includes models in which increasing effort leads to diminishing returns in terms of the number of birds counted.
Book chapter↗
Regional analysis of population trajectories from the North American Breeding Bird Survey
The North American Breeding Bird Survey (BBS) was started in 1966, and provides information on population change and distribution for most of the birds in North America. The geographic extent of the survey, and the logistical compromises needed to survey such a large area, present many challenges for estimation from BBS data. In this paper, we describe the survey and discuss some of the limitations of the survey design and implementation. Analysis of the survey has evolved over time as new statistical methods and insights into the analysis of count data are developed. Survey results and analysis tools for the BBS are now available over intemet; we present new methods that use generalized linear models for estimation of population change and empirical Bayes procedures for regional summaries.
Book chapter↗
Population status of North American grassland birds from the North American Breeding Bird Survey
We summarize population trends for grassland birds from 1966 to 1996 using data from the North American Breeding Bird Survey. Collectively, grassland birds showed the smallest percentage of species that increased of any Breeding Bird Survey bird group, and population declines prevailed throughout most of North America. Although 3 grassland bird species experienced significant population increases between 1966 and 1996, 13 species declined significantly and 9 exhibited non-significant trend estimates. We summarize the temporal and geographic patterns of the trends for grassland bird species and discuss factors that have contributed to these trends.
Book chapter↗
Marsh birds and the North American Breeding Bird Survey: judging the value of a landscape level survey for habitat specialist species with low detection rates
The North American Breeding Bird Survey was started in 1966, and provides information on population change for >400 species of birds. it covers the continental United States, Canada, and Alaska, and is conducted once each year, in June, by volunteer observers. A 39.4 kIn roadside survey route is driven starting 30 min before sunrise, and a 3 min point count is conducted at each of 50 stops spaced every 0.8 kIn. Existing analyses of the data are internet-based (http://www.mbr-pwrc.usgs.govlbbslbbs.html), and include maps of relative abundance, estimates of population change including trends (%/yr), composite annual indices (pattern in time), and maps of population trend (pattern in space). At least 36 species of marsh birds are encountered on the BBS, and the survey provides estimates with greatly varying levels of efficiency for the species. It is often difficult to understand how well the BBS surveys a species. Often, efficiency is judged by estimating trend and its variance for a species, then by calculating power and needed samples to detect a prespecified trend over some time period (e.g., a 2%/yr trend over 31 yr). Unfortunately, this approach is not always valid, as estimated trends and variances can be of little use if the population is poorly sampled. Lurking concerns with BBS data include (1) incomplete coverage of species range; (2) undersampling of habitats; and (3) low and variable visibility of birds during point counts. It is difficult to evaluate these concerns, because known populations do not exist for comparison with counts, and detection rates are time-consuming and costly to estimate. I evaluated the efficiency of the BBS for selected rails (Rallidae) and snipes (Scolopacidae), presenting estimates of population trend over 1966-1996 (T), power to detect 2%/yr trend over 31 yr, needed samples to achieve power of 0.75 with alpha= 0.1, number of survey routes with data for the species (N), average abundance on survey routes (RA), and maps of relative abundance. Examples include Yellow Rail (Coturnicops noveboracensis) (T=12 %/yr; P= 0.0085; N =28; routes; RA=0.05; Power=0.37; Needed samples=85), Black Rail (Laterallus jamaicensis) (No trend data or power information available, N =8), Clapper Rail (Rallus longirostris) (T=1.9%/yr; P=0.55; N =64; RA=0.31; Power=0.35; Needed samples=590), King Rail (Rallus elegans) (T=-4.2 %/yr; P= 0.03; N =76; Power=0.41; Needed samples=159), Sora (Porzana carolina) (T=0.98 %/yr; P= 0.24; N =720; RA= 0.92; Power=0.69; Needed samples= 377), and Common Snipe (Gallinago gallinago) (T=-0.24 %/yr; P= 0.54; N =1412; RA= 2.19; Power=0.98; Needed samples=205). With regard to quality of BBS data, marsh birds fall into 3 categories: (1) almost never encountered on BBS routes; (2) encountered at extremely low abundances on BBS routes; and (3) probably fairly well sampled by BBS roadside counts. BBS data can provide useful information for many marsh bird species, but users should be aware of the limitations of the BBS sample for monitoring species that have low visibility from point counts and prefer habitats not often encountered on roadsides.
Book chapter↗
Estimating rates of local species extinction, colonization and turnover in animal communities
Species richness has been identified as a useful state variable for conservation and management purposes. Changes in richness over time provide a basis for predicting and evaluating community responses to management, to natural disturbance, and to changes in factors such as community composition (e.g., the removal of a keystone species). Probabilistic capture-recapture models have been used recently to estimate species richness from species count and presence-absence data. These models do not require the common assumption that all species are detected in sampling efforts. We extend this approach to the development of estimators useful for studying the vital rates responsible for changes in animal communities over time; rates of local species extinction, turnover, and colonization. Our approach to estimation is based on capture-recapture models for closed animal populations that permit heterogeneity in detection probabilities among the different species in the sampled community. We have developed a computer program, COMDYN, to compute many of these estimators and associated bootstrap variances. Analyses using data from the North American Breeding Bird Survey (BBS) suggested that the estimators performed reasonably well. We recommend estimators based on probabilistic modeling for future work on community responses to management efforts as well as on basic questions about community dynamics.
Ecological Applications↗