Evaluando métodos para la comparación de diversidad de especies de diferentes fuentes de datos: El cao de bosques urbanos y periurbanos

Christina L. Staudhammer, Francisco Javier Escobedo, Amy Blood

Resultado de la investigación: Contribución a RevistaArtículo

Resumen

Inventarios forestales a gran escala y los datos de monitoreo se utilizan cada vez más en estudios que evalúan la diversidad, estructura, perturbación y dinámica del carbono de los bosques. Además, los inventarios de bosques urbanos a nivel local están proporcionando datos de parcelas y protocolos para estudiar la diversidad de árboles y los servicios ecosistémicos en los bosques urbanos de todo el mundo. Sin embargo, las diferencias en los métodos de muestreo que subyacen a estos protocolos dispares y fuentes de datos no constituyen una preocupación trivial en la formulación de análisis comparativos. Evaluamos métodos comúnmente utilizados para comparar la diversidad de árboles en bosques periurbanos y urbanos cuando los datos disponibles tienen diferentes tamaños de muestra, tamaño de parcela e intensidades de muestreo. Presentamos métodos para evaluar adecuadamente la riqueza de especies, así como métodos para comparar las distribuciones de especies a través de matrices de datos de la comunidad. Usando datos de parcelas permanentes del sureste de los Estados Unidos, presentamos un estudio de caso que compara bosques urbanos y periurbanos a lo largo de un gradiente norte-sur, y evalúa la riqueza de especies y la hipótesis de homogeneización ecológica. Resultados indican que las comparaciones de la riqueza de especies de árboles entre comunidades, o tipos de bosques, a menudo no son concluyentes, ya que los tamaños de muestra utilizados comúnmente no proporcionan estimaciones precisas del número de especies presentes. Si bien las hipótesis de homogeneización ecológica se pueden probar en condiciones de esfuerzo de muestreo desigual, sugerimos métodos sólidos como PERMANOVA y el índice de disimilitud de Raup-Crick. También se discute un marco para seleccionar los métodos apropiados. Como los impulsores antropogénicos están modificando cada vez más los bosques, los estudios futuros que utilizan fuentes de datos dispares deben tener en cuenta las diferencias en las mediciones y los protocolos de muestreo para producir resultados que sean estadísticamente defendibles y útiles para el manejo basado en la ciencia.
Título traducido de la contribuciónEvaluando métodos para la comparación de diversidad de especies de diferentes fuentes de datos: El cao de bosques urbanos y periurbanos
IdiomaEnglish (US)
Número de artículoe02450
PublicaciónEcosphere
Volumen9
Número de edición10
EstadoPublished - sep 1 2018

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title = "Assessing methods for comparing species diversity from disparate data sources: the case of urban and peri‐urban forests",
abstract = "Multi‐scale forest inventory and monitoring data are increasingly being used in studies assessing forest diversity, structure, disturbance, and carbon dynamics. Also, local‐level urban forest inventories are providing plot data and protocols to study tree diversity and ecosystem services in urban forests worldwide. But, differences in the sampling methods underlying these disparate protocols and data sources is a non‐trivial concern in formulating comparative analyses. We assess commonly used methods for comparing tree diversity in peri‐urban and urban forests when available data have different sample sizes, plot sizes, and sampling intensities. We present methods for appropriately evaluating species richness, as well as methods for comparing species distributions via community data matrices. Using permanent plot data from the southeastern United States, we present a case study comparing urban and peri‐urban forests along a north–south gradient, and assessing species richness and the ecological homogenization hypothesis. Our findings indicate that comparisons of tree species richness among communities, or forest types, are often inconclusive since commonly used sample sizes do not provide precise estimates of the number of species present. While the ecological homogenization hypotheses can be tested under conditions of unequal sampling effort, we suggest robust methods such as PERMANOVA and the Raup‐Crick dissimilarity index. A framework for selecting appropriate methods is also discussed. As forests are increasingly being altered by anthropogenic drivers, future studies using disparate data sources must account for differences in measurements and sampling protocols in order to produce results that are both statistically defensible and useful for science‐based management.",
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Assessing methods for comparing species diversity from disparate data sources: the case of urban and peri‐urban forests. / Staudhammer, Christina L.; Escobedo, Francisco Javier; Blood, Amy.

En: Ecosphere, Vol. 9, N.º 10, e02450, 01.09.2018.

Resultado de la investigación: Contribución a RevistaArtículo

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N2 - Multi‐scale forest inventory and monitoring data are increasingly being used in studies assessing forest diversity, structure, disturbance, and carbon dynamics. Also, local‐level urban forest inventories are providing plot data and protocols to study tree diversity and ecosystem services in urban forests worldwide. But, differences in the sampling methods underlying these disparate protocols and data sources is a non‐trivial concern in formulating comparative analyses. We assess commonly used methods for comparing tree diversity in peri‐urban and urban forests when available data have different sample sizes, plot sizes, and sampling intensities. We present methods for appropriately evaluating species richness, as well as methods for comparing species distributions via community data matrices. Using permanent plot data from the southeastern United States, we present a case study comparing urban and peri‐urban forests along a north–south gradient, and assessing species richness and the ecological homogenization hypothesis. Our findings indicate that comparisons of tree species richness among communities, or forest types, are often inconclusive since commonly used sample sizes do not provide precise estimates of the number of species present. While the ecological homogenization hypotheses can be tested under conditions of unequal sampling effort, we suggest robust methods such as PERMANOVA and the Raup‐Crick dissimilarity index. A framework for selecting appropriate methods is also discussed. As forests are increasingly being altered by anthropogenic drivers, future studies using disparate data sources must account for differences in measurements and sampling protocols in order to produce results that are both statistically defensible and useful for science‐based management.

AB - Multi‐scale forest inventory and monitoring data are increasingly being used in studies assessing forest diversity, structure, disturbance, and carbon dynamics. Also, local‐level urban forest inventories are providing plot data and protocols to study tree diversity and ecosystem services in urban forests worldwide. But, differences in the sampling methods underlying these disparate protocols and data sources is a non‐trivial concern in formulating comparative analyses. We assess commonly used methods for comparing tree diversity in peri‐urban and urban forests when available data have different sample sizes, plot sizes, and sampling intensities. We present methods for appropriately evaluating species richness, as well as methods for comparing species distributions via community data matrices. Using permanent plot data from the southeastern United States, we present a case study comparing urban and peri‐urban forests along a north–south gradient, and assessing species richness and the ecological homogenization hypothesis. Our findings indicate that comparisons of tree species richness among communities, or forest types, are often inconclusive since commonly used sample sizes do not provide precise estimates of the number of species present. While the ecological homogenization hypotheses can be tested under conditions of unequal sampling effort, we suggest robust methods such as PERMANOVA and the Raup‐Crick dissimilarity index. A framework for selecting appropriate methods is also discussed. As forests are increasingly being altered by anthropogenic drivers, future studies using disparate data sources must account for differences in measurements and sampling protocols in order to produce results that are both statistically defensible and useful for science‐based management.

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