Predicting The Sign of Trophic Effects: Individual-Based Simulation Versus Loop Analysis

Food web research needs to be predictive in order to support decisions system-based conservation. In order to increase predictability and applicability, complexity needs to be reduced to simple and clear results. One question emerging frequently is whether certain perturbations (environmental effects or human impact) have positive or negative effects on natural ecosystems or their particular components. Yet, most of food web studies do not consider the sign of effects.Here, we study 6 versions of the Kelian River (Borneo) food web, representing six study sites along the river. For each network, we study the sign of the effect of a perturbed trophic group i on each other j groups. We compare the outcome of the relatively complicated dynamical simulation model and the relatively simple loop analysis model. We compare these results for the 6 sites and also the 14 trophic groups. Finally, we see if sign-agreement and sign-determinacy depend on certain structural features (node centrality, interaction strength).We found major differences between different modelling scenarios, with herbivore-detritivore fish behaving in the most consistent, while algae and particulate organic matter behaving in the least consistent way.

[1]  Interactions Between Physical Template and Self-organization Shape Plant Dynamics in a Stream Ecosystem , 2019, Ecosystems.

[2]  Jeffrey M Dambacher,et al.  UNDERSTANDING AND PREDICTING EFFECTS OF MODIFIED INTERACTIONS THROUGH A QUALITATIVE ANALYSIS OF COMMUNITY STRUCTURE , 2007, The Quarterly Review of Biology.

[3]  F. Jordán,et al.  Combining centrality indices: Maximizing the predictability of keystone species in food webs , 2021, Ecological Indicators.

[4]  Jeffrey M. Dambacher,et al.  Qualitative predictions in model ecosystems , 2003 .

[5]  F. Jordán,et al.  Quantifying the importance of species and their interactions in a host-parasitoid community , 2003 .

[6]  P. Kareiva,et al.  Re‐examining the Role of Positive Interactions in Communities1 , 1997 .

[7]  A Mutualism Between Unattached Coralline Algae and Seagrasses Prevents Overgrazing by Sea Turtles , 2020, Ecosystems.

[8]  J. Bruno,et al.  Inclusion of facilitation into ecological theory , 2003 .

[9]  Jeffrey M. Dambacher,et al.  RELEVANCE OF COMMUNITY STRUCTURE IN ASSESSING INDETERMINACY OF ECOLOGICAL PREDICTIONS , 2002 .

[10]  Ferenc Jordán,et al.  Weighting, scale dependence and indirect effects in ecological networks: A comparative study , 2007 .

[11]  L. Boyero,et al.  Effects of sediment pollution on food webs in a tropical river (Borneo, Indonesia) , 2010 .

[12]  Ferenc Jordán,et al.  Food-Web Simulations: Stochastic Variability and Systems-Based Conservation , 2017 .

[13]  Corrado Priami,et al.  Algorithmic systems biology , 2009, CACM.

[14]  D. Gillespie.  Exact Stochastic Simulation of Coupled Chemical Reactions , 1977 .

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

[16]  Corrado Priami,et al.  Modelling the dynamics of biosystems , 2004, Briefings Bioinform..

[17]  A. Bodini,et al.  Vegetation, herbivores and fires in savanna ecosystems: A network perspective , 2016 .

[18]  R. Ulanowicz,et al.  Unexpected Effects of Predators Upon Their Prey: The Case of the American Alligator , 1999, Ecosystems.

[19]  Wei-Chung Liu,et al.  A simple approach for quantifying node centrality in signed and directed social networks , 2020, Applied Network Science.

[20]  Chester W. J. Liu,et al.  Quantifying the interaction structure and the topological importance of species in food webs: a signed digraph approach. , 2010, Journal of theoretical biology.

[21]  N. Stenseth,et al.  Population regulation in snowshoe hare and Canadian lynx: asymmetric food web configurations between hare and lynx. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

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

[23]  R. Gilabert,et al.  Body size and mobility explain species centralities in the Gulf of California food web , 2019, Community Ecology.

[24]  F. Jordán,et al.  Children in time: community organization in social and ecological systems , 2009 .

[25]  Frank Harary,et al.  Status and Contrastatus , 1959 .

[26]  F. Jordán,et al.  Simulating Food Web Dynamics along a Gradient: Quantifying Human Influence , 2012, PloS one.

[27]  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.

[28]  Robert E. Ulanowicz,et al.  Utricularia's secret: the advantage of positive feedback in oligotrophic environments , 1995 .

[29]  Corrado Priami,et al.  Evolving BlenX programs to simulate the evolution of biological networks , 2008, Theor. Comput. Sci..

[30]  M. Bertness,et al.  Competition and Facilitation in Marsh Plants , 1993, The American Naturalist.

[31]  Antonio Bodini,et al.  Reconstructing trophic interactions as a tool for understanding and managing ecosystems: application to a shallow eutrophic lake , 2000 .

[32]  Charles J. Puccia,et al.  Qualitative Modeling of Complex Systems: An Introduction to Loop Analysis and Time Averaging , 1986 .