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Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations
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2013 (English)In: Conservation Biology, ISSN 0888-8892, E-ISSN 1523-1739, Vol. 27, no 5, 968-978 p.Article in journal (Refereed) Published
Abstract [en]

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 Resumen La incertidumbre asociada con el pronostico ecologico ha sido reconocida durante un largo tiempo pero rara vez se cuantifica su seguridad. Evaluamos que tan bien la informacion de 82 poblaciones de 20 especies de plantas a lo largo de 3 continentes explica y predice la dinamica de poblacion de las plantas. Realizamos parametros con modelos matriciales con base en estadios con datos demograficos a partir de plantas marcadas individualmente y determinamos que tan bien estos modelos pronostican el tamano de las poblaciones al menos 5 anos en el futuro. Los modelos demograficos simples pronosticaron pobremente las dinamicas de poblacion; solamente el 40% de las poblaciones observadas cayo dentro de los limites de confianza de 85% de nuestros pronosticos. Estos modelos sin embargo explicaron la dinamica de poblacion a lo largo de los anos en los que se colectaron datos; los cambios observados en el tamano de la poblacion durante el periodo de colecta de datos estuvieron positivamente correlacionados con la tasa de crecimiento de la poblacion. Asi, estos modelos son por lo menos una manera segura de cuantificar el estado de la poblacion. Los pronosticos debiles no estuvieron asociados con el numero de plantas individuales o con los anos de datos. Probamos si las tasas vitales dependian de la densidad y encontramos que existe dependencia hacia la densidad tanto positiva como negativa, sin embargo la dependencia de densidad no se asocio con el error de pronostico. El error de pronostico estuvo significativamente asociado con diferencias ambientales entre la recoleccion de datos y los periodos de pronostico. Para predecir el destino de las poblaciones se necesitan modelos mas detallados, como aquellos que proyectan los cambios probables en el ambiente y como estos cambios afectaran a la dinamica de las poblaciones. Tales modelos tan detallados no siempre son factibles. Por ello puede ser mejor tomar decisiones aversas a riesgos que esperar pronosticos precisos de los modelos.

Place, publisher, year, edition, pages
2013. Vol. 27, no 5, 968-978 p.
Keyword [en]
density dependence, ecological forecasting, environmental change, matrix projection models, plant population dynamics, population viability analysis, precipitation, temperature, analisis de viabilidad poblacional, dependencia de la densidad, dinamica poblacional de plantas, modelos de proyeccion matricial, precipitacion, pronostico ecologico, temperatura
National Category
Environmental Sciences Ecology
URN: urn:nbn:se:su:diva-95751DOI: 10.1111/cobi.12049ISI: 000324931700011OAI: diva2:662260


Available from: 2013-11-06 Created: 2013-11-04 Last updated: 2013-11-06Bibliographically approved

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Ehrlén, Johan
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Department of Botany
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