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Analysis of indirect effects within ecosystem models using pathway-based methodology

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  • Ma, Q.
  • Kazanci, C.

Abstract

The role of indirect relations within an ecosystem is crucial to its function. Emergent properties such as adaptability, plasticity, and robustness are hard to explain without understanding the system-wide effects of direct and indirect interactions. In this paper, we take advantage of a different representation of ecosystem models to provide a better understanding of indirect effects. We focus on pathways of individual particles that flow through systems. Particles represent small units of flow material, such as a single carbon atom, 1g of biomass, or 1cal of energy. The view of an entire system from an individual particle perspective provides a more practical and intuitive basis to study indirect relations than earlier input–output based algebraic methods. Our findings show that the current two algebraic formulations for indirect and direct effect ratio (I/D) do not exactly compute their intended meaning. We come up with a new throughflow based I/D ratio, which revises the current definition, and accurately compares direct and indirect flows. The two different perspectives (algebraic and pathway-based) enable an insightful analysis and conceptual clarification as to what exactly each formulation measures. We compare all three measures on twenty real-life ecosystem models. Finally, we rescale the I/D ratio to I/(I+D) and define the later one as indirect effect index (IEI), which is better suited to compare indirect effects among different models.

Suggested Citation

  • Ma, Q. & Kazanci, C., 2013. "Analysis of indirect effects within ecosystem models using pathway-based methodology," Ecological Modelling, Elsevier, vol. 252(C), pages 238-245.
    • Handle: RePEc:eee:ecomod:v:252:y:2013:i:c:p:238-245
    DOI: 10.1016/j.ecolmodel.2012.05.002
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    References listed on IDEAS

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    1. Tollner, E.W. & Schramski, J.R. & Kazanci, C. & Patten, B.C., 2009. "Implications of network particle tracking (NPT) for ecological model interpretation," Ecological Modelling, Elsevier, vol. 220(16), pages 1904-1912.
    2. Kazanci, C. & Ma, Q., 2012. "Extending ecological network analysis measures to dynamic ecosystem models," Ecological Modelling, Elsevier, vol. 242(C), pages 180-188.
    3. Matamba, L. & Kazanci, C. & Schramski, J.R. & Blessing, M. & Alexander, P. & Patten, B.C., 2009. "Throughflow analysis: A stochastic approach," Ecological Modelling, Elsevier, vol. 220(22), pages 3174-3181.
    4. Borrett, S.R. & Freeze, M.A. & Salas, A.K., 2011. "Equivalence of the realized input and output oriented indirect effects metrics in Ecological Network Analysis," Ecological Modelling, Elsevier, vol. 222(13), pages 2142-2148.
    5. Ray, Santanu, 2008. "Comparative study of virgin and reclaimed islands of Sundarban mangrove ecosystem through network analysis," Ecological Modelling, Elsevier, vol. 215(1), pages 207-216.
    6. Salas, Andria K. & Borrett, Stuart R., 2011. "Evidence for the dominance of indirect effects in 50 trophic ecosystem networks," Ecological Modelling, Elsevier, vol. 222(5), pages 1192-1204.
    7. Kazanci, C. & Matamba, L. & Tollner, E.W., 2009. "Cycling in ecosystems: An individual based approach," Ecological Modelling, Elsevier, vol. 220(21), pages 2908-2914.
    8. Kazancı, Caner, 2007. "EcoNet: A new software for ecological modeling, simulation and network analysis," Ecological Modelling, Elsevier, vol. 208(1), pages 3-8.
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    Cited by:

    1. Coskun, Huseyin, 2018. "Dynamic Ecological System Analysis," OSF Preprints 35xkb, Center for Open Science.
    2. Kazanci, Caner & Ma, Qianqian & Basheer, Aladeen Al & Azizi, Asma, 2023. "Resilience, indirect effects and cycling in ecological networks," Ecological Modelling, Elsevier, vol. 481(C).
    3. Borrett, Stuart R. & Sheble, Laura & Moody, James & Anway, Evan C., 2018. "Bibliometric review of ecological network analysis: 2010–2016," Ecological Modelling, Elsevier, vol. 382(C), pages 63-82.
    4. Coskun, Huseyin, 2018. "Static Ecological System Analysis," OSF Preprints zqxc5, Center for Open Science.
    5. Coskun, Huseyin, 2018. "Static Ecological System Measures," OSF Preprints g4xzt, Center for Open Science.
    6. Burns, Thomas P. & Rose, Kenneth A. & Brenkert, Antoinette L., 2014. "Quantifying direct and indirect effects of perturbations using model ecosystems," Ecological Modelling, Elsevier, vol. 293(C), pages 69-80.
    7. Coskun, Huseyin, 2018. "Dynamic Ecological System Measures," OSF Preprints j2pd3, Center for Open Science.
    8. Patten, Bernard C., 2016. "The cardinal hypotheses of Holoecology," Ecological Modelling, Elsevier, vol. 319(C), pages 63-111.

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