Ecography DOI: 10.1111/ecog.01798 Michel, N.L., A.C. Smith, R.G. Clark, C.A. Morrissey, K.A. Hobson. 2015. Differences in spatial synchrony and interspecific concordance inform guild-level population trends for aerial insectivorous birds Raw data Raw Breeding Bird Survey data are publicly available from the United States Geological Survey Patuxent Wildlife Research Center’s (USGS PWRC) website at: https://www.pwrc.usgs.gov/bbs/RawData/. Bird Conservation Regions Shapefile delineating Bird Conservation Region boundaries are publicly available from the USGS PWRC website at: http://www.pwrc.usgs.gov/bba/index.cfm?fa=bba.getdata. WinBUGS spatial CAR model code Code for the WinBUGS spatial CAR model is publicly available as Supporting Information (Supplementary Text S1) for Smith et al. 2015, available at: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130768#sec016. Annual indices from the spatial CAR model Annual indices of abundance estimated from the spatial CAR model for the five focal species are publicly as Supporting Information (Supplementary Table S2) for Smith et al. 2015, available at: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130768#sec016. Appendix 4: Dynamic factor analysis code In this script, annual indices from the spatial CAR model are transformed and analyzed using dynamic factor analysis (DFA). DFA models are run with three different covariance structures (diagonal and equal, diagonal and unequal, and unconstrained). For each covariance structure, DFA models with an increasing number of underlying common trends are fit until the AICc increases between models. DFA model objects are output to the hard drive as *.rda files, and a summary AICc model table is output as an *.html file. Appendix 5: Bayesian linear model code In this script, common trends from the top DFA model are converted to log-linear models and long-term trends (defined here as slopes of the regression line), probability of decreasing trend, and probability of increasing trend are estimated. A model summary table is output as a *.csv file. Appendix 6: Cross-correlation (concordance) code In this script, common trends from the top DFA model are first detrended (linear trend removed using a linear model). Spearman’s cross-correlations (rs) are then calculated following Kirchner (2001) using an effective sample size (Neff) that corrects for the loss of degrees of freedom due to temporal autocorrelation. A summary table is output as a *.csv file. Additional questions can be addressed to Nicole Michel (Nicole.L.Michel1@gmail.com).