Spatially-explicit models of global tree density

Sci Data. 2016 Aug 16;3:160069. doi: 10.1038/sdata.2016.69.

Abstract

Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services.

Publication types

  • Research Support, Non-U.S. Gov't
  • Comment

MeSH terms

  • Biodiversity
  • Ecosystem*
  • Forests
  • Models, Theoretical
  • Trees*

Associated data

  • figshare/10.6084/M9.FIGSHARE.3179986