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
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