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Ability of matrix models to explain the past and predict the future of plant populations.

Publication ,  Journal Article
Crone, EE; Ellis, MM; Morris, WF; Stanley, A; Bell, T; Bierzychudek, P; Ehrlén, J; Kaye, TN; Knight, TM; Lesica, P; Oostermeijer, G; Doak, DF ...
Published in: Conservation biology : the journal of the Society for Conservation Biology
October 2013

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models.

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Published In

Conservation biology : the journal of the Society for Conservation Biology

DOI

EISSN

1523-1739

ISSN

0888-8892

Publication Date

October 2013

Volume

27

Issue

5

Start / End Page

968 / 978

Related Subject Headings

  • Population Dynamics
  • Population Density
  • Plant Physiological Phenomena
  • Models, Theoretical
  • Forecasting
  • Ecology
  • Conservation of Natural Resources
  • 4104 Environmental management
  • 3109 Zoology
  • 3103 Ecology
 

Citation

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Crone, E. E., Ellis, M. M., Morris, W. F., Stanley, A., Bell, T., Bierzychudek, P., … Menges, E. S. (2013). Ability of matrix models to explain the past and predict the future of plant populations. Conservation Biology : The Journal of the Society for Conservation Biology, 27(5), 968–978. https://doi.org/10.1111/cobi.12049
Crone, Elizabeth E., Martha M. Ellis, William F. Morris, Amanda Stanley, Timothy Bell, Paulette Bierzychudek, Johan Ehrlén, et al. “Ability of matrix models to explain the past and predict the future of plant populations.Conservation Biology : The Journal of the Society for Conservation Biology 27, no. 5 (October 2013): 968–78. https://doi.org/10.1111/cobi.12049.
Crone EE, Ellis MM, Morris WF, Stanley A, Bell T, Bierzychudek P, et al. Ability of matrix models to explain the past and predict the future of plant populations. Conservation biology : the journal of the Society for Conservation Biology. 2013 Oct;27(5):968–78.
Crone, Elizabeth E., et al. “Ability of matrix models to explain the past and predict the future of plant populations.Conservation Biology : The Journal of the Society for Conservation Biology, vol. 27, no. 5, Oct. 2013, pp. 968–78. Epmc, doi:10.1111/cobi.12049.
Crone EE, Ellis MM, Morris WF, Stanley A, Bell T, Bierzychudek P, Ehrlén J, Kaye TN, Knight TM, Lesica P, Oostermeijer G, Quintana-Ascencio PF, Ticktin T, Valverde T, Williams JL, Doak DF, Ganesan R, McEachern K, Thorpe AS, Menges ES. Ability of matrix models to explain the past and predict the future of plant populations. Conservation biology : the journal of the Society for Conservation Biology. 2013 Oct;27(5):968–978.
Journal cover image

Published In

Conservation biology : the journal of the Society for Conservation Biology

DOI

EISSN

1523-1739

ISSN

0888-8892

Publication Date

October 2013

Volume

27

Issue

5

Start / End Page

968 / 978

Related Subject Headings

  • Population Dynamics
  • Population Density
  • Plant Physiological Phenomena
  • Models, Theoretical
  • Forecasting
  • Ecology
  • Conservation of Natural Resources
  • 4104 Environmental management
  • 3109 Zoology
  • 3103 Ecology