Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Dec 7;12(12):e0189086.
doi: 10.1371/journal.pone.0189086. eCollection 2017.

Robustness of rigid and adaptive networks to species loss

Savannah Nuwagaba  1 , Feng Zhang  2 , Cang Hui  1   3
Affiliations

Robustness of rigid and adaptive networks to species loss

Savannah Nuwagaba et al. PLoS One. .

Abstract

Controversies in the complexity-stability debate have been attributed to the methodologies used such as topological vs. dynamical approaches or rigid vs. adaptive foraging behaviour of species. Here, we use a bipartite network model that incorporates both topological and population dynamics to investigate the robustness of 60 real ecological networks to the loss of generalist and specialist species. We compare the response in both adaptive and rigid networks. Our results show that the removal of generalists leads to the most secondary extinctions, implying that conservation strategies should aim to protect generalist species in the ecosystem. We also show that adaptive behaviour renders networks vulnerable to species loss at initial stages but enhances long term stability of the system. However, whether adaptive networks are more robust to species loss than rigid ones depends on the structure of the network. Specifically, adaptive networks with modularity < 0.3 are more robust than rigid networks of the same modularity. Interestingly, the more modular a network is, the less robust it is to external perturbations.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Predicted vs. observed network architecture.
For each network, simulations were run to equilibrium and its architecture (modularity, nestedness, and connectance) recorded. Predictions are the averages of the last 200 time units after the dynamics stabilize.
Fig 2
Fig 2. Robustness vs. network structure.
For each simulation, the model was ran up t = 150, after which its structure was recorded. The generalist species were sequentially removed and the level of robustness recorded. Panels show the relationship between robustness and connectance, link density, nestedness, resource-consumer ratio, skewness of the degree distribution and modularity in both adaptive and rigid networks. R50 was used as the measure of robustness. Cyan lines indicate regressions for adaptive networks (cyan dots) while red lines for rigid networks (red dots). Spearman’s rank correlation coefficients are summarised in Table 1.
Fig 3
Fig 3. Robustness to the removal of species in adaptive and rigid networks.
Panels (a) and (c) correspond to the real network, N41 while (b) and (d) correspond to N43 in S1 Table in the supporting information. For panels (a) and (b), generalist species were sequentially removed while for (c) and (d), specialists were sequentially removed. Points show the percentage of consumer extinctions that resulted from the removal of a certain percentage of generalist (a and b) or specialist (c and d) resource species from an adaptive or rigid network.
Fig 4
Fig 4. Robustness to the removal of generalists and specialists in two networks (N41 and N43 in S1 Table).
Points show the percentage of consumer extinctions that result from the removal of a certain percentage of resource generalists and specialists. Panels (a) and (b) correspond to adaptive networks while (c) and (d) correspond to rigid networks.
Fig 5
Fig 5. Genaralised additive model lines of fit of robustness with different threshold percentages on modularity and nestedness.
R10—R70 correspond to the percentage of resources that need to be removed before at least 10–70% of consumer species go extinct in an adaptive network while R50ns corresponds to the percentage of resources that need to be removed before at least 50% of consumer species go extinct in a rigid network. Panels (a) and (b) indicate the removal of generalists while (c) and (d) indicate the removal of specialists.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Baskaran N, Anbarasan U, Agoramoorthy G. India’s biodiversity hotspot under anthropogenic pressure: A case study of Nilgiri Biosphere Reserve. J. Nat. Conserv. 2012; 20: 56–61.
    1. Brook BW, Sodhi NS, Ng PKL. Catastrophic extinctions follow deforestation in Singapore. Nature 2003; 424: 420–423. doi: 10.1038/nature01795 - DOI - PubMed
    1. Brose U. Extinctions in complex, size-structured communities. Basic Appl. Ecol. 2011; 12: 557–561.
    1. de Visser SN, Freymann BP, Olff H. The Serengeti food web: empirical quantification and analysis of topological changes under increasing human impact. J. Anim. Ecol. 2011; 80: 484–494. doi: 10.1111/j.1365-2656.2010.01787.x - DOI - PubMed
    1. Kiers ET, Palmer TM, Ives AR, Bruno JF, Bronstein JL. Mutualisms in a changing world: an evolutionary perspective. Ecol. Lett. 2010; 13: 1459–1474 doi: 10.1111/j.1461-0248.2010.01538.x - DOI - PubMed

Grants and funding

This project is supported by National Natural Science Foundation of China (No. 31360104), South African Research Chair Initiative (SARChI), National Research Foundation of South Africa (grants 81825 and 76912), DST-NRF Centre of Excellence for Invasion Biology (C∙I∙B), African Institute for Mathematical Sciences (AIMS). SN receives a PhD Scholarship from the German Academic Exchange Service (DAAD). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

LinkOut - more resources