Abstract
Original language | English |
---|---|
Pages (from-to) | 10794-10804 |
Number of pages | 11 |
Journal | Ecology & Evolution |
Volume | 8 |
Issue number | 22 |
Early online date | 31 Oct 2018 |
DOIs | |
Publication status | Published - 1 Nov 2018 |
Keywords
- coextinction
- ecological interactions
- extinction models
- mutualistic network
- network
- plant–pollinator communities
- pollinators
- robustness
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Ecology
- Nature and Landscape Conservation
Cite this
Effects of model choice, network structure and interaction strengths on knockout extinction models of ecological robustness. / Bane, Miranda; Pocock, Michael; James, Richard.
In: Ecology & Evolution, Vol. 8, No. 22, 01.11.2018, p. 10794-10804.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Effects of model choice, network structure and interaction strengths on knockout extinction models of ecological robustness
AU - Bane, Miranda
AU - Pocock, Michael
AU - James, Richard
PY - 2018/11/1
Y1 - 2018/11/1
N2 - Analysis of ecological networks is a valuable approach to understanding the vulnerability of systems to disturbance. The tolerance of ecological networks to coextinctions, resulting from sequences of primary extinctions (here termed “knockout extinction models”, in contrast with other dynamic approaches), is a widely used tool for modeling network “robustness”. Currently, there is an emphasis to increase biological realism in these models, but less attention has been given to the effect of model choices and network structure on robustness measures. Here, we present a suite of knockout extinction models for bipartite ecological networks (specifically plant–pollinator networks) that can all be analyzed on the same terms, enabling us to test the effects of extinction rules, interaction weights, and network structure on robustness. We include two simple ecologically plausible models of propagating extinctions, one new and one adapted from existing models. All models can be used with weighted or binary interaction data. We found that the choice of extinction rules impacts robustness; our two propagating models produce opposing effects in all tests on observed plant–pollinator networks. Adding weights to the interactions tends to amplify the opposing effects and increase the variation in robustness. Variation in robustness is a key feature of these extinction models and is driven by the structural heterogeneity of nodes (specifically, the skewness of the plant degree distribution) in the network. Our analysis therefore reveals the mechanisms and fundamental network properties that drive observed trends in robustness.
AB - Analysis of ecological networks is a valuable approach to understanding the vulnerability of systems to disturbance. The tolerance of ecological networks to coextinctions, resulting from sequences of primary extinctions (here termed “knockout extinction models”, in contrast with other dynamic approaches), is a widely used tool for modeling network “robustness”. Currently, there is an emphasis to increase biological realism in these models, but less attention has been given to the effect of model choices and network structure on robustness measures. Here, we present a suite of knockout extinction models for bipartite ecological networks (specifically plant–pollinator networks) that can all be analyzed on the same terms, enabling us to test the effects of extinction rules, interaction weights, and network structure on robustness. We include two simple ecologically plausible models of propagating extinctions, one new and one adapted from existing models. All models can be used with weighted or binary interaction data. We found that the choice of extinction rules impacts robustness; our two propagating models produce opposing effects in all tests on observed plant–pollinator networks. Adding weights to the interactions tends to amplify the opposing effects and increase the variation in robustness. Variation in robustness is a key feature of these extinction models and is driven by the structural heterogeneity of nodes (specifically, the skewness of the plant degree distribution) in the network. Our analysis therefore reveals the mechanisms and fundamental network properties that drive observed trends in robustness.
KW - coextinction
KW - ecological interactions
KW - extinction models
KW - mutualistic network
KW - network
KW - plant–pollinator communities
KW - pollinators
KW - robustness
UR - http://www.scopus.com/inward/record.url?scp=85055875131&partnerID=8YFLogxK
U2 - 10.1002/ece3.4529
DO - 10.1002/ece3.4529
M3 - Article
VL - 8
SP - 10794
EP - 10804
JO - Ecology & Evolution
JF - Ecology & Evolution
SN - 2045-7758
IS - 22
ER -