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Predicting the effect of habitat modification on networks of interacting species.
Staniczenko, Phillip P A; Lewis, Owen T; Tylianakis, Jason M; Albrecht, Matthias; Coudrain, Valérie; Klein, Alexandra-Maria; Reed-Tsochas, Felix.
Affiliation
  • Staniczenko PPA; National Socio-Environmental Synthesis Center (SESYNC), Annapolis, MD, 21401, USA. pstaniczenko@sesync.org.
  • Lewis OT; Department of Biology, University of Maryland College Park, Maryland, MD, 20742, USA. pstaniczenko@sesync.org.
  • Tylianakis JM; CABDyN Complexity Centre, Saïd Business School, University of Oxford, Oxford, OX1 1HP, UK. pstaniczenko@sesync.org.
  • Albrecht M; Department of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS, UK.
  • Coudrain V; Centre for Integrative Ecology, School of Biological Sciences, University of Canterbury, Christchurch, 8140, New Zealand.
  • Klein AM; Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 7PY, UK.
  • Reed-Tsochas F; Institute for Sustainability Sciences, Agroscope, Zurich, 8046, Switzerland.
Nat Commun ; 8(1): 792, 2017 10 06.
Article in En | MEDLINE | ID: mdl-28986532
ABSTRACT
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.In a changing world, the ability to predict the impact of environmental change on ecological communities is essential. Here, the authors show that by separating species abundances from interaction preferences, they can predict the effects of habitat modification on the structure of weighted species interaction networks, even with limited data.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Ecosystem / Food Chain / Ecology / Host-Parasite Interactions Type of study: Prognostic_studies / Risk_factors_studies Limits: Animals Country/Region as subject: America do sul / Asia / Ecuador / Europa Language: En Journal: Nat Commun Journal subject: BIOLOGIA / CIENCIA Year: 2017 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Ecosystem / Food Chain / Ecology / Host-Parasite Interactions Type of study: Prognostic_studies / Risk_factors_studies Limits: Animals Country/Region as subject: America do sul / Asia / Ecuador / Europa Language: En Journal: Nat Commun Journal subject: BIOLOGIA / CIENCIA Year: 2017 Type: Article Affiliation country: United States