Data from: Anthropogenic ecosystem disturbance and the recovery debt

  • David Moreno-Mateos (Contributor)
  • Edward Barbier (Contributor)
  • Peter Jones (Contributor)
  • Holly Jones (Contributor)
  • James Aronson (Contributor)
  • Jose A Lopez-Lopez (Contributor)
  • Michelle McCrackin (Contributor)
  • Paula Meli (Contributor)
  • Daniel Montoya (Contributor)
  • Jose M Rey Benayas (Contributor)

Dataset

Description

Ecosystem recovery from anthropogenic disturbances, either without human intervention or assisted by ecological restoration, is increasingly occurring worldwide. As ecosystems progress through recovery, it is important to estimate any resulting deficit in biodiversity and functions. Here we use data from 3,035 sampling plots worldwide, to quantify the interim reduction of biodiversity and functions occurring during the recovery process (that is, the ‘recovery debt’). Compared with reference levels, recovering ecosystems run annual deficits of 46–51% for organism abundance, 27–33% for species diversity, 32–42% for carbon cycling and 31–41% for nitrogen cycling. Our results are consistent across biomes but not across degrading factors. Our results suggest that recovering and restored ecosystems have less abundance, diversity and cycling of carbon and nitrogen than ‘undisturbed’ ecosystems, and that even if complete recovery is reached, an interim recovery debt will accumulate. Under such circumstances, increasing the quantity of less-functional ecosystems through ecological restoration and offsetting are inadequate alternatives to ecosystem protection.,Ecosystem recovery databaseThis meta-analytical database includes data from 354 studies of ecosystems undergoing recovery worldwide. We include ecosystem recovering from agriculture, logging, eutrophication, mining, hydrological disruption, overfishing, oil spills, and one natural disturbance, hurricanes. We include studies reporting three measures, two in the recovering ecosystem and one in a reference site.Moreno, Jones database.xlsxEcosytem recovery R scriptsR scripts used to calculate the recovery debt values with the meta-analytical database. Includes generalized mixed models, heterogeneity tests, and variance adjustments to meet meta-analytical criteria.Rdebt models.R,
Date made available10 Nov 2017
PublisherDryad

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