Assessment of robustness indicators for ecological networks

Introduction

Human activity is causing different hazards to natural ecosystems which could compromise their continued functioning. To be sustainable, an ecosystem must be robust, which means it should have the ability to maintain its metabolic activity and also internal structure or organization. A robust system is categorized by there being balance among activity, organization, and resilience. Thus, “a ‘healthy’ system is one that can develop an efficient diversity of components and exchange pathways (high organization) while maintaining some overhead (redundancy) or resilience as insurance against stress, and substantial vigor to quickly recover or utilize stress in a positive manner" [1] From the different views of robustness and the importance of robustness in ecological systems, the present study corroborates the views of [1]. 

Methods

Ecological network analysis (ENA), is used to explore whole system interactions. Ecosystem networks of one South African estuary, the Mdloti on the KwaZulu-Natal North Coast of South Africa, in two different seasons are used for analyses. Networks of carbon exchanges of the Mdloti estuary as described in [2] were transferred to the Ecopath software [3]. Using the network as a case study, the impact of perturbations on the food web network is investigated; specifically information theory-based indices are assessed. Three scenarios are considered. Biomass of the autotrophic compartments are increased and decreased from 10% up to 99% step by step in 10% intervals (scenario 1); fish yield is increased from 10% up to 99% step by step in 10% intervals (scenario 2); import of all the three detritus compartments are increased and decreased from 10% up to 99% step by step in 10% intervals (scenario 3). The changes in network indices are observed and robustness [4] is measured.

Results

Among all the network indices (TST, AMI, H, A/C, R, FCI), all indices are good indicators of  some scenarios but not consistent in all scenarios in both networks. Robustness measure and redundancy are quite consistent in all the three scenarios in both networks and show some good information about the system health. These are able to reflect the information about the system even when the system faces small scale perturbations. Increase or decrease in the values and the pattern of change of these two indices with robustness are quite consistent with different perturbations. Therefore, these are sensitive enough to be considered as indicators. They reveal the change in robustness of the system in different scenarios and can portray the pattern of changes in the flow structure or magnitude which brings about the actual change in the condition of the system. The change in behavior of the indices might help us to understand the type of food chain (grazing or detritus) which is more important for the system.

Please note these Proceedings have received limited or no review from supervisors and IIASA program directors, and the views and results expressed therein do not necessarily represent IIASA, its National Member Organizations, or other organizations supporting the work.

Last edited: 23 March 2015