Bias in estimated breeding-bird abundance from closure-assumption violations

The closure assumption of many abundance models, that individual animals are present throughout the survey season, often is inconsistent with field data. The effects of closure-assumption violations on estimators of abundance and associations between abundance and covariates are not fully understood...

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Bibliographic Details
Main Authors: Fleishman, E. (Author), Fogarty, F.A (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2021
Subjects:
Online Access:View Fulltext in Publisher
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001 10.1016-j.ecolind.2021.108170
008 220427s2021 CNT 000 0 und d
020 |a 1470160X (ISSN) 
245 1 0 |a Bias in estimated breeding-bird abundance from closure-assumption violations 
260 0 |b Elsevier B.V.  |c 2021 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1016/j.ecolind.2021.108170 
520 3 |a The closure assumption of many abundance models, that individual animals are present throughout the survey season, often is inconsistent with field data. The effects of closure-assumption violations on estimators of abundance and associations between abundance and covariates are not fully understood. Furthermore, one's definition of abundance affects these estimates. We used simulated data on breeding birds to explore how permanent, non-random immigration and emigration that violate the closure assumption affect estimates from N-mixture abundance models and naïve models (models that do not account for imperfect detection). This is the first work to evaluate the effect of permanent immigration and emigration on estimates from N-mixture models, and to compare these effects among definitions of abundance (initial, season-long, and superpopulation). We also collected and analyzed point-count data on breeding bird species in the Great Basin (USA) to evaluate the frequency of within-season movement. When detection probability was high (ρ ≥ 0.65), estimators of superpopulation abundance from N-mixture and naïve models were relatively unbiased. By comparison, in many cases, even relatively small violations of the closure assumption biased estimates of initial and season-long abundance by > 20%. Naïve abundance models generally were less biased than N-mixture models when ρ ≥ 0.65, but highly biased when ρ ≤ 0.4. In both model types, estimators of the association between abundance and an environmental covariate were minimally biased. The magnitudes of assumption violations tested in our simulations were consistent with those in our field data. Movement of individuals (availability) strongly affected detection probability of nearly all species and, in 7 of 34 species-region combinations, was temporally heterogeneous, suggesting that closure-assumption violations are common in our study system. Our results highlight that permanent movement of individuals within a season may be a substantial source of bias in studies of breeding birds that are based on count data, and that the definition of abundance affects the magnitude of these biases. © 2021 The Authors 
650 0 4 |a abundance estimation 
650 0 4 |a bird 
650 0 4 |a Birds 
650 0 4 |a breeding population 
650 0 4 |a closure 
650 0 4 |a Closure assumptions 
650 0 4 |a Covariates 
650 0 4 |a emigration 
650 0 4 |a Emigration 
650 0 4 |a Emigration 
650 0 4 |a Field data 
650 0 4 |a Great Basin 
650 0 4 |a Great Basin 
650 0 4 |a Great Basin 
650 0 4 |a immigration 
650 0 4 |a Immigration 
650 0 4 |a Immigration 
650 0 4 |a Mixture modeling 
650 0 4 |a Mixtures 
650 0 4 |a Movement 
650 0 4 |a Movement 
650 0 4 |a N-mixture model 
650 0 4 |a N-mixture model 
650 0 4 |a numerical model 
650 0 4 |a Point count 
650 0 4 |a Point count 
650 0 4 |a probability 
650 0 4 |a United States 
700 1 |a Fleishman, E.  |e author 
700 1 |a Fogarty, F.A.  |e author 
773 |t Ecological Indicators