44 research outputs found
LaydateCS_12Mar13.xlsx
Excel file with data on changing phenology and population size of birds (N= 196 studies). Variables are explained and sources given in the sheet titled "Variables & Sources
LaydateYr_23Jan13.txt
Data file for mcmcGLMM in R. Note that slightly different data files were used for different analyses. This file was used for the analyses of laying date change per year in Table 4 of the paper
Appendix S1
Body mass (g), brain mass (g), eumelanic and pheomelanic plumage colour score, mean breeding latitude (ÂşN) and sexual dichromatism in melanin-based color (0: monochromatic, 1: dichromatic) for the 323 species of birds used in the study
Temporal Variation in Population Size of European Bird Species: Effects of Latitude and Marginality of Distribution
<div><p>In the Northern Hemisphere, global warming has been shown to affect animal populations in different ways, with southern populations in general suffering more from increased temperatures than northern populations of the same species. However, southern populations are also often marginal populations relative to the entire breeding range, and marginality may also have negative effects on populations. To disentangle the effects of latitude (possibly due to global warming) and marginality on temporal variation in population size, we investigated European breeding bird species across a latitudinal gradient. Population size estimates were regressed on years, and from these regressions we obtained the slope (a proxy for population trend) and the standard error of the estimate (SEE) (a proxy for population fluctuations). The possible relationships between marginality or latitude on one hand and slopes or SEE on the other were tested among populations within species. Potentially confounding factors such as census method, sampling effort, density-dependence, habitat fragmentation and number of sampling years were controlled statistically. Population latitude was positively related to regression slopes independent of marginality, with more positive slopes (i.e., trends) in northern than in southern populations. The degree of marginality was positively related to SEE independent of latitude, with marginal populations showing larger SEE (i.e., fluctuations) than central ones. Regression slopes were also significantly related to our estimate of density-dependence and SEE was significantly affected by the census method. These results are consistent with a scenario in which southern and northern populations of European bird species are negatively affected by marginality, with southern populations benefitting less from global warming than northern populations, thus potentially making southern populations more vulnerable to extinction.</p> </div
Fig 2 Pop models_16Sep13.xls
Excel worksheets with population models shown in Fig. 2 of the paper. Details of each model are given in the individual worksheets
Tree29Dec12g.nex
Nexus tree file for mcmcGLMM analyses in R. This tree was used with the data file "LaydateYr_23Jan13.txt" to conduct the analyses shown in Table 4 of the paper. Note that slightly different trees were used for some other analyses. The g in the file name indicates that we used Grafen's method to construct branch lengths. There are 172 studies in the file; multiple studies of the same species were coded as A, B, C, etc. in the phylogen
Relationships between abundance (response variable) and a number of ecological, demographic, life history and genetic parameters of European breeding bird species according to phylogenetic generalized least square regression models.
<p>Relationships between abundance (response variable) and a number of ecological, demographic, life history and genetic parameters of European breeding bird species according to phylogenetic generalized least square regression models.</p
Relationships between the estimates of population fluctuations and (A) relative abundance, (B) relative breeding range, and (C) relative coloniality in European breeding bird species.
<p>Relative abundance was estimated as the residuals from a model with abundance as the response variable and total breeding range, coloniality and population trend as predictors. Relative breeding range was estimated as the residuals from a model with total breeding range as the response variable and abundance, coloniality and population trend as predictors. Relative coloniality was estimated as the residuals from a model with coloniality as the response variable and abundance, total breeding range and population trend as predictors. All variables except coloniality and population fluctuations were transformed before the analyses (see Statistical analysis). Lines are best-fit regressions (a: y = 1.032–0.071 x; b: y = 1.025 + 0.011 x; c: y = 1.026 + 0.060 x). All models and regressions took into account the number of countries used to calculate population trends and fluctuations (bubble size indicates this number; range = 1–12) and similarities among species due to common ancestry (see Statistical analysis for details).</p
Frequency distribution of population parameters in 767 populations of 74 European breeding bird species.
<p>(a) Coefficient of variation (CV) of population size estimates (population indices) corrected for sample size (see text); (b) slope and (c) standard error of the estimate (SEE) after regressing population indices on year. Outliers are included (see text). Mean (SE) for the three parameters is CV: 21.95 (0.51); slope: 0.008 (0.003); SEE: 0.202 (0.008).</p