Climatic and edaphic-based predictors of normalized difference vegetation index in tropical dry landscapes: A pantropical analysis


Por: de la Peña-Domene M., Tapia, Gerardo Rodriguez, Mesa-Sierra, Natalia, Rivero-Villar, Anaitzi, Giardina, Christian P., Johnson, Nels G., Campo, Julio

Publicada: 1 sep 2022
Resumen:
Aim Spatial patterns in resource supply drive variability in vegetation structure and function, yet quantification of this variability for tropical dry forests (TDFs) remains rudimentary. Several climate-driven indices have been developed to classify and delineate TDFs globally, but there has not been a climo-edaphic synthesis of these indices to assess and delineate the extent of TDFs. A statistical climo-edaphic synthesis of these indices is therefore required. Location Pantropical. Time period Modern. Major taxa studied Vascular plants. Methods We assembled most known prior descriptions of TDFs into a single data layer and assessed statistically how the TDF biome, which we call tropical dry landscapes (TDLs) composed of forest and non-forest vegetation, varied with respect to the normalized difference vegetation index (NDVI) sensed by MODIS (250 m pixel resolution). We examined how the NDVI varied with respect to mean annual temperature (MAT) and rainfall (MAR), precipitation regime, evapotranspiration and the physical, chemical and biological properties of TDL soils. Results Overall, the NDVI varied widely across TDLs, and we were able to identify five principal NDVI categories. A regression tree model captured 90% of NDVI variation across TDLs, with 14 climate and soil metrics as predictors. The model was then pruned to use only the three strongest metrics. These included the Lang aridity index, total evapotranspiration (ET) and MAT, which aligned with identified NDVI thresholds and accounted for 70% of the variation in NDVI. We found that across a global TDL distribution, ET was the strongest positive predictor and MAT the strongest negative predictor of the NDVI. Main conclusions The remote sensing-based approach described here provides a comprehensive and quantitative biogeographical characterization of global TDL occurrence and the climatic and edaphic drivers of these landscapes.

Filiaciones:
de la Peña-Domene M.:
 Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico

 Centro Interdisciplinario para la Formación y Vinculación Social, Instituto Tecnológico y de Estudios Superiores de Occidente, Tlaquepaque, Mexico

Tapia, Gerardo Rodriguez:
 Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico

 Univ Nacl Autonoma Mexico, Inst Ecol, Mexico City 04510, DF, Mexico

Mesa-Sierra, Natalia:
 Instituto Tecnológico y de Estudios Superiores de Occidente, Centro Interdisciplinario para la Formación y Vinculación Social, Tlaquepaque, Mexico

 Inst Tecnol & Estudios Super Occidente, Ctr Interdisciplinario Formac & Vinculac Social, Tlaquepaque, Mexico

Rivero-Villar, Anaitzi:
 Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico

 Univ Nacl Autonoma Mexico, Inst Ecol, Mexico City 04510, DF, Mexico

Giardina, Christian P.:
 Institute of Pacific Islands Forestry, Pacific Southwest Research Station, USDA Forest Service, Hilo, HI, United States

 US Forest Serv, Inst Pacific Isl Forestry, Pacific Southwest Res Stn, USDA, Hilo, HI USA

Johnson, Nels G.:
 USDA Forest Service, Pacific Southwest Research Station, Albany, CA, United States

 US Forest Serv, USDA, Pacific Southwest Res Stn, Albany, CA USA

Campo, Julio:
 Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico

 Univ Nacl Autonoma Mexico, Inst Ecol, Mexico City 04510, DF, Mexico
ISSN: 1466822X





GLOBAL ECOLOGY AND BIOGEOGRAPHY
Editorial
Blackwell Publishing Ltd, COMMERCE PLACE, 350 MAIN ST, MALDEN 02148, MA USA, Estados Unidos America
Tipo de documento: Article
Volumen: 31 Número: 9
Páginas: 1850-1863
WOS Id: 000829192000001

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