Food Web Topology and Nested Keystone Species Complexes

Important species may be in critically central network positions in ecological interaction networks. Beyond quantifying which one is the most central species in a food web, a multinode approach can identify the key sets of the most central species as well. However, for sets of different size , these structural keystone species complexes may differ in their composition. If larger sets contain smaller sets, higher nestedness may be a proxy for predictive ecology and efficient management of ecosystems. On the contrary, lower nestedness makes the identification of keystones more complicated. Our question here is how the topology of a network can influence nestedness as an architectural constraint. Here, we study the role of keystone species complexes in 27 real food webs and quantify their nestedness. After quantifying their topology properties, we determine their keystone species complexes, calculate their nestedness, and statistically analyze the relationship between topological indices and nestedness. A better understanding of the cores of ecosystems is crucial for efficient conservation efforts, and to know which networks will have more nested keystone species complexes would be a great help for prioritizing species that could preserve the ecosystem’s structural integrity.

[1]  R. Levins,et al.  Identifying keystone trophic groups in benthic ecosystems: Implications for fisheries management , 2013 .

[2]  Dénes Schmera,et al.  A new conceptual and methodological framework for exploring and explaining pattern in presence – absence data , 2011 .

[3]  Werner Ulrich,et al.  A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement , 2008 .

[4]  R. Paine.  A Note on Trophic Complexity and Community Stability , 1969, The American Naturalist.

[5]  J. Castilla,et al.  Challenges in the Quest for Keystones , 1996 .

[6]  Dénes Schmera,et al.  A general framework for analyzing beta diversity, nestedness and related community-level phenomena based on abundance data , 2013 .

[7]  B. Menge,et al.  Indirect Effects in Marine Rocky Intertidal Interaction Webs: Patterns and Importance , 1995 .

[8]  Ferenc Jordán,et al.  Identifying important species: Linking structure and function in ecological networks , 2008 .

[9]  Albert-László Barabási,et al.  Error and attack tolerance of complex networks , 2000, Nature.

[10]  Robert E. Ulanowicz,et al.  Assessment of long-term changes of ecosystem indexes in Tongoy Bay (SE Pacific coast): Based on trophic network analysis , 2016 .

[11]  William,et al.  Challenges in the Quest for Keystones Identifying keystone species is difficult-but essential to understanding bow loss of species will affect ecosystems , 2003 .

[12]  G. Daily,et al.  Double keystone bird in a keystone species complex. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Neo D. Martinez,et al.  Simple rules yield complex food webs , 2000, Nature.

[14]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.

[15]  Ernesto Estrada,et al.  Characterization of topological keystone species: Local, global and “meso-scale” centralities in food webs , 2007 .

[16]  Colin W. Clark,et al.  Management of Multispecies Fisheries , 1979, Science.

[17]  F. Jordán.  Keystone species and food webs , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.

[18]  Ferenc Jordán,et al.  Topological keystone species complexes in ecological interaction networks , 2007 .

[19]  Santiago Saura,et al.  Connectivity conservation priorities for individual patches evaluated in the present landscape: how durable and effective are they in the long term? , 2015 .

[20]  Ferenc Jordán,et al.  A Reliability Theoretical Quest for Keystones , 1999 .

[21]  F. Jordán,et al.  Quantifying keystone species complexes: Ecosystem-based conservation management in the King George Island (Antarctic Peninsula) , 2017 .

[22]  Ferenc Jordán,et al.  A new approach to exploring architecture of bipartite (interaction) ecological networks , 2014, J. Complex Networks.

[23]  Paola Lecca,et al.  Identifying key species in ecosystems with stochastic sensitivity analysis , 2011 .

[24]  Ferenc Jordán,et al.  Single‐node vs. multi‐node centrality in landscape graph analysis: key habitat patches and their protection for 20 bird species in NE Spain , 2017 .

[25]  Stefano Allesina,et al.  Who dominates whom in the ecosystem? Energy flow bottlenecks and cascading extinctions. , 2004, Journal of theoretical biology.

[26]  Ferenc Jordán,et al.  Multi-node selection of patches for protecting habitat connectivity: Fragmentation versus reachability , 2017 .

[27]  Ferenc Jord,et al.  Network ecology: topological constraints on ecosystem dynamics , 2004 .

[28]  Daniel B. Stouffer,et al.  Nestedness versus modularity in ecological networks: two sides of the same coin? , 2010, The Journal of animal ecology.

[29]  Stephen P. Borgatti,et al.  Identifying sets of key players in a social network , 2006, Comput. Math. Organ. Theory.

[30]  Neo D. Martinez,et al.  Network structure and biodiversity loss in food webs: robustness increases with connectance , 2002, Ecology Letters.

[31]  Neo D. Martinez,et al.  Scaling up keystone effects from simple to complex ecological networks , 2005 .

[32]  Ferenc Jordán,et al.  Control Strategy Scenarios for the Alien Lionfish Pterois volitans in Chinchorro Bank (Mexican Caribbean): Based on Semi-Quantitative Loop Analysis , 2015, PloS one.

[33]  D. Doak,et al.  The Keystone-Species Concept in Ecology and ConservationManagement and policy must explicitly consider the complexity of interactions in natural systems , 1993 .

[34]  Jeremy W. Fox.  Current food web models cannot explain the overall topological structure of observed food webs , 2006 .