Data from: Quantifying the importance of geographic replication and representativeness when estimating demographic rates, using a coastal species as a case study
Field, Christopher R., University of Connecticut
Ruskin, Katharine J., University of Maine
Benvenuti, Bri, University of New Hampshire
Borowske, Alyssa C., University of Connecticut
Cohen, Jonathan B., Queens College, CUNY
Garey, Laura, University of Maine
Hodgman, Thomas P., University of Connecticut
Kern, Rebecca A., University of New Hampshire
King, Erin, University of Connecticut
Kocek, Alison R., Queens College, CUNY
Kovach, Adrienne I., University of New Hampshire
O'Brien, Kathleen M., United States Fish and Wildlife Service
Olsen, Brian J., University of Maine
Pau, Nancy, United States Fish and Wildlife Service
Roberts, Samuel G., University of Delaware
Shelly, Emma, University of Connecticut
Shriver, W. Gregory, University of Delaware
Walsh, Jennifer, University of New Hampshire
Elphick, Chris S., University of Connecticut
Longenecker, Rebecca A., United States Fish and Wildlife Service
Published Jul 14, 2017 on Dryad.
Cite this dataset
Field, Christopher R. et al. (2017). Data from: Quantifying the importance of geographic replication and representativeness when estimating demographic rates, using a coastal species as a case study [Dataset]. Dryad. https://doi.org/10.5061/dryad.f5c50
Demographic rates are rarely estimated over an entire species range, limiting empirical tests of ecological patterns and theories, and raising questions about the representativeness of studies that use data from a small part of a range. The uncertainty that results from using demographic rates from just a few sites is especially pervasive in population projections, which are critical for a wide range of questions in ecology and conservation. We developed a simple simulation to quantify how this lack of geographic representativeness can affect inferences about the global mean and variance of growth rates, which has implications for the robust design of a wide range of population studies. Using a coastal songbird, saltmarsh sparrow (Ammodramus caudacutus), as a case study, we first estimated survival, fecundity, and population growth rates at 21 sites distributed across much of their breeding range. We then subsampled this large, representative dataset according to five sampling scenarios in order to simulate a variety of geographic biases in study design. We found spatial variation in demographic rates, but no large systematic patterns. Estimating the global mean and variance of growth rates using subsets of the data suggested that at least 10-15 sites were required for reasonably unbiased estimates, highlighting how relying on demographic data from just a few sites can lead to biased results when extrapolating across a species range. Sampling at the full 21 sites, however, offered diminishing returns, raising the possibility that for some species accepting some geographical bias in sampling can still allow for robust range-wide inferences. The sub-sampling approach presented here, while conceptually simple, could be used with both new and existing data to encourage efficiency in the design of long-term or large-scale ecological studies.
"Mark_recapture_matrix.csv": A file containing capture records for each individual (by row) for each year of the study (1 is captured in a given year; 0 is not captured). Covariates used in the analysis of annual survival are also provided: Species ID (1 for Ammodramus caudacutus, 0 for Ammodramus nelsoni, NA for unknown species identity), Sex (1 is male), First capture (the date of first capture; 1 is 2010, 2 is 2011, etc.), Site (1-21), and Plot size (standardized by subtracting the mean and dividing by two standard deviations).
"brood_size_MCMC.csv": A file containing the posterior estimates of the parameters from a regression of brood size (at fledging) by clutch size. Rows are 1000 draws from the posterior distributions for the regression intercept (intercept) and the effect of clutch size (clutch).
"nest_failure_MCMC.csv": A file containing the posterior estimates of the parameters from a regression of daily nest failure probability by site and date. Rows are 1000 draws from the posterior distributions for each site effect (site through site) and site-specific coefficient for the date effect (one coefficient for each site; date through date).
"renest_prob_MCMC.csv": A file containing the posterior estimates of the parameters from a regression of re-nesting probability by latitude and date. Rows are 1000 draws from the posterior distributions for each coefficient: intercept (intercept of the regression equation), latitude (the effect of latitude on renesting probability), and date (the effect of date on renesting probability).
"annual_survival_MCMC.csv": A file containing posterior estimates of adult annual survival, by site (columns). Rows are 1000 draws from the posterior distributions for the log-odds of survival (survival estimates are back-transformed using the inverse logit in the model code in order to take a value between 0 and 1). Sites are identified by a two-letter code and are provided from low to high latitude.