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DETERMINANTS OF WOOD THRUSH NEST SUCCESS: A MULTI‐SCALE, MODEL SELECTION APPROACH
Author(s) -
DRISCOLL MELANIE J. L.,
DONOVAN THERESE,
MICKEY RUTH,
HOWARD ALAN,
FLEMING KATHLEEN K.
Publication year - 2005
Publication title -
the journal of wildlife management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.94
H-Index - 111
eISSN - 1937-2817
pISSN - 0022-541X
DOI - 10.2193/0022-541x(2005)069[0699:dowtns]2.0.co;2
Subject(s) - nest (protein structural motif) , habitat , vegetation (pathology) , fledge , ecology , geography , biology , medicine , biochemistry , pathology , predation
We collected data on 212 wood thrush ( Hylocichla mustelina ) nests in central New York from 1998 to 2000 to determine the factors that most strongly influence nest success. We used an information–theoretic approach to assess and rank 9 models that examined the relationship between nest success (i.e., the probability that a nest would successfully fledge at least 1 wood thrush offspring) and habitat conditions at different spatial scales. We found that 4 variables were significant predictors of nesting success for wood thrushes: (1) total core habitat within 5 km of a study site, (2) distance to forest–field edge, (3) total forest cover within 5 km of the study site, and (4) density and variation in diameter of trees and shrubs surrounding the nest. The coefficients of these predictors were all positive. Of the 9 models evaluated, amount of core habitat in the 5‐km landscape was the best‐fit model, but the vegetation structure model (i.e., the density of trees and stems surrounding a nest) was also supported by the data. Based on AIC weights, enhancement of core area is likely to be a more effective management option than any other habitat‐management options explored in this study. Bootstrap analysis generally confirmed these results; core and vegetation structure models were ranked 1, 2, or 3 in over 50% of 1,000 bootstrap trials. However, bootstrap results did not point to a decisive model, which suggests that multiple habitat factors are influencing wood thrush nesting success. Due to model uncertainty, we used a model averaging approach to predict the success or failure of each nest in our dataset. This averaged model was able to correctly predict 61.1% of nest outcomes.