4.8 Article

Predicting the effect of habitat modification on networks of interacting species

Journal

NATURE COMMUNICATIONS
Volume 8, Issue -, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-017-00913-w

Keywords

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Funding

  1. National Socio-Environmental Synthesis Center (SESYNC) - National Science Foundation [DBI-1052875]
  2. NERC [NE/N010221/1]
  3. European commission [QLRT-2001-01495]
  4. Swiss Federal Office for Science and Technology [01.0524-2]
  5. British Ecological Society [4785/5824]
  6. German Science Foundation [DFG: KL 1849/5-2]
  7. James Martin 21st Century Foundation [LC1213-006]
  8. Rutherford Discovery Fellowship
  9. NERC [NE/N010221/1] Funding Source: UKRI
  10. Natural Environment Research Council [NE/N010221/1] Funding Source: researchfish
  11. Direct For Biological Sciences
  12. Div Of Biological Infrastructure [1052875] Funding Source: National Science Foundation

Ask authors/readers for more resources

A pressing challenge for ecologists is predicting how human-driven environmental changes will affect the complex pattern of interactions among species in a community. Weighted networks are an important tool for studying changes in interspecific interactions because they record interaction frequencies in addition to presence or absence at a field site. Here we show that changes in weighted network structure following habitat modification are, in principle, predictable. Our approach combines field data with mathematical models: the models separate changes in relative species abundance from changes in interaction preferences (which describe how interaction frequencies deviate from random encounters). The models with the best predictive ability compared to data requirement are those that capture systematic changes in interaction preferences between different habitat types. Our results suggest a viable approach for predicting the consequences of rapid environmental change for the structure of complex ecological networks, even in the absence of detailed, system-specific empirical data.

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