Observer Differences in the North American Breeding Bird Survey

Sauer, John R.; Peterjohn, Bruce G.; Link, William A.

doi:10.2307/4088504

Cited by 403 publications

(349 citation statements)

References 8 publications

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“…Differences in detection error imposed by multiple observers could diminish the congruence of trends based on presence and count data. Error imposed by multiple observers is problematic for many long-term monitoring schemes, although methods exist to account for error and determine observer-specific detection probabilities (Sauer et al 1994;Nichols et al 2000).…”

Section: Discussionmentioning

confidence: 99%

The utility of repeated presence data as a surrogate for counts: a case study using butterflies

et al. 2013

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Section: Discussionmentioning

confidence: 99%

The utility of repeated presence data as a surrogate for counts: a case study using butterflies

et al. 2013

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“…Even comparisons over time in counts made at the same locations are compromised if habitat succession affects detectability, or if an observer's hearing ability changes over time, or if observers change or, in the case of surveys near roads, if traffic noise increases over time.' Observer variation in detectability has been well demonstrated for the NA BBS (Sauer et al 1994;Kendall et al 1996;Link & Sauer 1998a,b). Detectability can be safely ignored only if detection is certain (or nearly so) within the sampled plots.…”

Section: Survey Designmentioning

confidence: 99%

Monitoring change in biodiversity through composite indices

Buckland

Magurran

Green

et al. 2005

Phil. Trans. R. Soc. B

330

306

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The need to monitor trends in biodiversity raises many technical issues. What are the features of a good biodiversity index? How should trends in abundance of individual species be estimated? How should composite indices, possibly spanning very diverse taxa, be formed? At what spatial scale should composite indices be applied? How might change-points-points at which the underlying trend changes-be identified? We address some of the technical issues underlying composite indices, including survey design, weighting of the constituent indices, identification of change-points and estimation of spatially varying time trends. We suggest some criteria that biodiversity measures for use in monitoring surveys should satisfy, and we discuss the problems of implementing rigorous methods. We illustrate the properties of different composite indices using UK farmland bird data. We conclude that no single index can capture all aspects of biodiversity change, but that a modified Shannon index and the geometric mean of relative abundance have useful properties.

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“…In particular, in the MHB there are four important components that affect detection of a species in a quadrat; route length, duration of survey, season of survey and observer identity. All were previously shown to have considerable effects on counts of species or individuals in avian surveys such as the North American BBS or the Swiss MHB (Sauer et al 1994;Link and Sauer 1998;Kéry et al 2005;Royle et al 2005;Kéry and Schmid 2006;Royle et al 2007b). In our analysis, we account for all of them except the last one; we note that it would be entirely possible to include a random observer effect if the same observer surveys different quadrats.…”

Section: The Applicationmentioning

confidence: 99%

Inference About Species Richness and Community Structure Using Species-Specific Occupancy Models in the National Swiss Breeding Bird Survey MHB

Kéry

Royle²

2009

Modeling Demographic Processes in Marked Populations

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Species richness is the most widely used biodiversity measure. Virtually always, it cannot be observed but needs to be estimated because some species may be present but remain undetected. This fact is commonly ignored in ecology and management, although it will bias estimates of species richness and related parameters such as occupancy, turnover or extinction rates. We describe a species community modeling strategy based on species-specific models of occurrence, from which estimates of important summaries of community structure, e.g., species richness, occupancy, or measures of similarity among species or sites, are derived by aggregating indicators of occurrence for all species observed in the sample, and for the estimated complement of unobserved species. We use data augmentation for an efficient Bayesian approach to estimation and prediction under this model based on MCMC in WinBUGS. For illustration, we use the Swiss breeding bird survey (MHB) that conducts 2-3 territory-mapping surveys in a systematic sample of 267 1 km 2 units on quadrat-specific routes averaging 5.1 km to obtain species-specific estimates of occupancy, and estimates of species richness of all diurnal species free of distorting effects of imperfect detectability. We introduce into our model speciesspecific covariates relevant to occupancy (elevation, forest cover, route length) and sampling (season, effort). From 1995 to 2004, 185 diurnal breeding bird species were known in Switzerland, and an additional 13 bred 1-3 times since 1900. 134 species were observed during MHB surveys in 254 quadrats surveyed in 2001, and our estimate of 169.9 (95% CI 151-195) therefore appeared sensible. The observed number of species ranged from 4 to 58 (mean 32.8), but with an estimated 0.7-11.2 (mean 2.6) further, unobserved species, the estimated proportion of detected species was 0.48-0.98 (mean 0.91). As is well known, species richness declined at higher elevation and fell above the timberline, and most species showed some preferred elevation. Route length had clear effects on occupancy, suggesting it is a proxy for the size of the effectively sampled area. Detection probability of most species showed clear seasonal patterns and increased with greater survey effort; these are important results for the planning of focused surveys. The main benefit of our model, and its implementation in WinBUGS for which we provide code, is its conceptual simplicity. Species richness is naturally expressed as the sum of occurrences of individual species. Information about species is combined across sites, which yields greater efficiency or may even enable estimation for sites with very few observed species in the first place. At the same time, species detections are clearly segregated into a true state process (occupancy) and an observation process (detection, given occupancy), and covariates can be readily introduced, which provides for efficient introduction of such additional information as well as sharp testing of such relationships.

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Observer Differences in the North American Breeding Bird Survey

Cited by 403 publications

References 8 publications

The utility of repeated presence data as a surrogate for counts: a case study using butterflies

The utility of repeated presence data as a surrogate for counts: a case study using butterflies

Monitoring change in biodiversity through composite indices

Inference About Species Richness and Community Structure Using Species-Specific Occupancy Models in the National Swiss Breeding Bird Survey MHB

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