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Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations

CRONE, ELIZABETH E ; ELLIS, MARTHA M ; MORRIS, WILLIAM F ; STANLEY, AMANDA ; BELL, TIMOTHY ; BIERZYCHUDEK, PAULETTE ; EHRLÉN, JOHAN ; KAYE, THOMAS N ; KNIGHT, TIFFANY M ; LESICA, PETER ; OOSTERMEIJER, GERARD ; QUINTANA‐ASCENCIO, PEDRO F ; TICKTIN, TAMARA ; VALVERDE, TERESA ; WILLIAMS, JENNIFER L ; DOAK, DANIEL F ; GANESAN, RENGAIAN ; MCEACHERN, KATHYRN ; THORPE, ANDREA S ; MENGES, ERIC S

Conservation biology, 2013-10, Vol.27 (5), p.968-978 [Periódico revisado por pares]

Hoboken, NJ: Blackwell Scientific Publications

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Título:
Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations
Autor: CRONE, ELIZABETH E ; ELLIS, MARTHA M ; MORRIS, WILLIAM F ; STANLEY, AMANDA ; BELL, TIMOTHY ; BIERZYCHUDEK, PAULETTE ; EHRLÉN, JOHAN ; KAYE, THOMAS N ; KNIGHT, TIFFANY M ; LESICA, PETER ; OOSTERMEIJER, GERARD ; QUINTANA‐ASCENCIO, PEDRO F ; TICKTIN, TAMARA ; VALVERDE, TERESA ; WILLIAMS, JENNIFER L ; DOAK, DANIEL F ; GANESAN, RENGAIAN ; MCEACHERN, KATHYRN ; THORPE, ANDREA S ; MENGES, ERIC S
Assuntos: analisis de viabilidad poblacional ; Animal and plant ecology ; Animal, plant and microbial ecology ; análisis de viabilidad poblacional ; Applied ecology ; Biological and medical sciences ; Conservation of Natural Resources ; Conservation, protection and management of environment and wildlife ; correlation ; data collection ; Demecology ; density dependence ; dependencia de la densidad ; dinamica poblacional de plantas ; dinámica poblacional de plantas ; ecological forecasting ; Ecology ; environmental change ; Forecasting ; Fundamental and applied biological sciences. Psychology ; General aspects ; General aspects. Techniques ; Matrix ; matrix projection models ; Methods and techniques (sampling, tagging, trapping, modelling...) ; modelos de proyeccion matricial ; modelos de proyección matricial ; Models, Theoretical ; Parks, reserves, wildlife conservation. Endangered species: population survey and restocking ; Plant Physiological Phenomena ; plant population dynamics ; Plant populations ; Population Density ; Population Dynamics - trends ; population growth ; population size ; population viability analysis ; precipitacion ; precipitación ; precipitation ; pronostico ecologico ; pronóstico ecológico ; temperatura ; temperature ; uncertainty ; Weather forecasting
É parte de: Conservation biology, 2013-10, Vol.27 (5), p.968-978
Notas: http://dx.doi.org/10.1111/cobi.12049
ArticleID:COBI12049
istex:99D35521CF439CE6DE3675546127610D18A3D5E3
National Science Foundation - No. EF-0553768
National Center for Ecological Analysis and Synthesis
ark:/67375/WNG-31ZR2BKQ-C
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Descrição: 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. Habilidad de los Modelos Matriciales para Explicar el Pasado y Predecir el Futuro de las Poblaciones de Plantas
Editor: Hoboken, NJ: Blackwell Scientific Publications
Idioma: Inglês

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Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations

Hoboken, NJ: Blackwell Scientific Publications

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