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Alternative spatial sampling in studies of plant demography: consequences for estimates of population growth rate

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Ecologists commonly use matrix models to study the population dynamics of plants. Most studies of plant demography use plot-based methods to collect data, in part, because mapped individuals are easier to relocate in subsequent surveys and survey methods can be standardized among sites. However, there is tremendous variation among studies, both in terms of plot arrangement and the total area sampled. In addition, there has been little discussion of how alternative sampling arrangements influence estimates of population growth rates (λ) calculated with matrix models. We surveyed the literature to determine what sampling designs are most used in studies of plant demography using matrix models. We then used simulations of three common sampling techniques—using a single randomly placed plot, multiple randomly placed plots, and systematically distributed plots—to evaluate how these alternative strategies influenced the precision of estimates of λ. These simulations were based on long-term demographic data collected on 13 populations of the Amazonian understory herb Heliconia acuminate (Heliconiaceae). We found that the method used to collect data did not affect the bias or precision of estimates in our system—a surprising result, since the advantage in efficiency that is gained from systematic sampling is a well-known result from sampling theory. Because the statistical advantage of systematic sampling is most evident when there is spatial structure in demographic vital rates, we attribute this result to the lack of spatially structured vital rates in our focal populations. Given the likelihood of spatial autocorrelation in most ecological systems, we advocate sampling with a systematic grid of plots in each study site, as well as that researchers ensure that enough area is sampled—both within and across sites—to encompass the range of spatial variation in plant survival, growth, and reproduction.

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Acknowledgments

We thank M. Oli, B. Bolker, and three anonymous reviewers for helpful discussions and comments on the manuscript. We would also like to thank the many technicians and students who helped conduct the censuses and the logistical support of the BDFFP and its staff. Financial support was provided by the US National Science Foundation (award numbers DEB-0614149 and DEB-0614339) and the University of Florida. This is publication number 547 in the BDFFP Technical Series. Code used to conduct simulations is available from IJF upon request.

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Author notes

  1. Ian J. Fiske

    Present address: Department of Statistics, North Carolina State University, Box 8203, Raleigh, NC, 27695-8203, USA

Authors and Affiliations

  1. Department of Wildlife Ecology and Conservation, University of Florida, PO Box 110430, Gainesville, FL, 32611-0430, USA

    Ian J. Fiske & Emilio M. Bruna

  2. Center for Latin American Studies, University of Florida, PO Box 115530, Gainesville, FL, 32611-5530, USA

    Emilio M. Bruna

  3. Biological Dynamics of Forest Fragments Project, Instituto Nacional de Pesquisas da Amazonia and Smithsonian Tropical Research Institute, C.P. 478, Manaus, AM, 69011-970, Brazil

    Emilio M. Bruna

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  1. Ian J. Fiske
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Corresponding author

Correspondence to Emilio M. Bruna.

Appendix: studies of plant demography using matrix models reviewed to determine the sample sizes used to parameterize models

Appendix: studies of plant demography using matrix models reviewed to determine the sample sizes used to parameterize models

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Fiske, I.J., Bruna, E.M. Alternative spatial sampling in studies of plant demography: consequences for estimates of population growth rate. Plant Ecol 207, 213–225 (2010). https://doi.org/10.1007/s11258-009-9666-4

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