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Ecological Disturbance and Impact on Species Diversity
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Harnessing tipping points in complex ecological networks.

Junjie Jiang1, Alan Hastings2,3, Ying-Cheng Lai1,4

  • 1School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA.

Journal of the Royal Society, Interface
|September 12, 2019
PubMed
Summary
This summary is machine-generated.

Maintaining pollinator abundance prevents ecological tipping points and extinction cascades. This strategy also enables ecosystem recovery after critical transitions by removing hysteresis.

Keywords:
complex networksecosystem managementmutualistic networksnonlinear dynamicsspecies recoverytipping point

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Area of Science:

  • Ecology
  • Network Theory
  • Conservation Biology

Background:

  • Complex ecological networks, such as those involving pollinators and plants, are susceptible to tipping points leading to global extinction.
  • These tipping points are often characterized by hysteresis, making recovery difficult once a critical threshold is crossed.

Purpose of the Study:

  • To develop an ecologically feasible strategy for managing tipping points in mutualistic networks.
  • To investigate the role of hysteresis in ecosystem transitions and recovery.

Main Methods:

  • Utilized real-world mutualistic networks of pollinators and plants.
  • Developed a management strategy focused on maintaining constant abundance of a key pollinator species.
  • Employed a universal, two-dimensional reduced model to predict recovery points.

Main Results:

  • Maintaining constant pollinator abundance effectively removes hysteresis, preventing abrupt shifts to extinction states.
  • This management strategy can prevent sudden drastic changes when approaching a tipping point.
  • Active management of abundance is crucial for full ecosystem recovery after a tipping point has been passed.

Conclusions:

  • Constant abundance management of key species is a viable strategy to control ecological tipping points.
  • The removal of hysteresis is key to both preventing and recovering from critical transitions in ecological networks.
  • A reduced two-dimensional model can predict the recovery point in post-tipping point ecosystems.