Carbon stocks, species diversity and their spatial relationships in the yucatán peninsula, mexico

José Luis Hernández-Stefanoni, Miguel Ángel Castillo-Santiago, Juan Andres-Mauricio, Carlos A. Portillo-Quintero, Fernando Tun-Dzul, Juan Manuel Dupuy

Research output: Contribution to journalArticlepeer-review

Abstract

Integrating information about the spatial distribution of carbon stocks and species diversity in tropical forests over large areas is fundamental for climate change mitigation and biodiversity conservation. In this study, spatial models showing the distribution of carbon stocks and the number of species were produced in order to identify areas that maximize carbon storage and biodiversity in the tropical forests of the Yucatan Peninsula, Mexico. We mapped carbon density and species richness of trees using L-band radar backscatter data as well as radar texture metrics, climatic and field data with the random forest regression algorithm. We reduced sources of errors in plot data of the national forest inventory by using correction factors to account for carbon stocks of small trees (<7.5 cm DBH) and for the temporal difference between field data collection and imagery acquisition. We created bivariate maps to assess the spatial relationship between carbon stocks and diversity. Model validation of the regional maps obtained herein using an independent data set of plots resulted in a coefficient of determination (R2) of 0.28 and 0.31 and a relative mean square error of 38.5% and 33.0% for aboveground biomass and species richness, respectively, at pixel level. Estimates of carbon density were influenced mostly by radar backscatter and climatic data, while those of species richness were influenced mostly by radar texture and climatic variables. Correlation between carbon density and species richness was positive in 79.3% of the peninsula, while bivariate maps showed that 39.6% of the area in the peninsula had high carbon stocks and species richness. Our results highlight the importance of combining carbon and diversity maps to identify areas that are critical—both for maintaining carbon stocks and for conserving biodiversity.

Original languageEnglish
Article number3179
JournalRemote Sensing
Volume13
Issue number16
DOIs
StatePublished - Aug 2 2021

Keywords

  • Aboveground biomass
  • Biodiversity
  • L-band SAR
  • National forest inventory
  • Texture analysis
  • Tropical dry forests

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