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Timing recovery of ecosystems in sequential remotely sensed and simulated data
van Belzen, J.; van de Koppel, J.; van der Wal, D.; Herman, P.M.J.; Dakos, V.; Kéfi, S.; Scheffer, M.; Bouma, T.J. (2017). Timing recovery of ecosystems in sequential remotely sensed and simulated data . Protocol Exchange June 2017. https://dx.doi.org/10.1038/protex.2017.038
In: Protocol Exchange. Nature Publishing Group: London. ISSN 2043-0116; e-ISSN 2043-0116, more

Available in  Authors 

Author keywords
    disturbance; ecosystem dynamics; recovery; resilience; stability; tipping points

Authors  Top 
  • van Belzen, J., more
  • van de Koppel, J., more
  • van der Wal, D., more
  • Herman, P.M.J., more
  • Dakos, V.
  • Kéfi, S.
  • Scheffer, M.
  • Bouma, T.J., more

Abstract
    The time needed for ecosystems to recover from a disturbance has been proposed as a generic indicator of ecosystem resilience. The lengthening of the recovery time with increasing stress is referred to as “Critical Slowing Down” and has been proposed as an early warning of a nearing tipping point. Hence, methodologies for measuring recovery rates and critical slowing down in remotely sensed data might provide a powerful way to synoptically asses ecosystem resilience. Here, we present a protocol using an algorithm to measure the recovery time after a disturbance from sequential spatial data. The algorithm can be applied to both empirical, e.g. remotely sensed, and simulated spatial data.

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