Bioaccumulation modelling and sensitivity analysis for discovering key players in contaminated food webs: The case study of PCBs in the Adriatic Sea

Abstract

Modelling bioaccumulation processes at the food web level is the main step to analyse the effects of pollutants at the global ecosystem level. A crucial question is understanding which species play a key role in the trophic transfer of contaminants to disclose the contribution of feeding linkages and the importance of trophic dependencies in bioaccumulation dynamics. In this work we present a computational framework to model the bioaccumulation of organic chemicals in aquatic food webs, and to discover key species in polluted ecosystems. As a result, we reconstruct the first PCBs bioaccumulation model of the Adriatic food web, estimated after an extensive review of published concentration data. We define a novel index aimed to identify the key species in contaminated networks, Sensitivity Centrality, and based on sensitivity analysis. The index is computed from a dynamic ODE model parametrised from the estimated PCBs bioaccumulation model and compared with a set of established trophic indices of centrality. Results evidence the occurrence of PCBs biomagnification in the Adriatic food web, and highlight the dependence of bioaccumulation on trophic dynamics and external factors like fishing activity. We demonstrate the effectiveness of the introduced Sensitivity Centrality in identifying the set of species with the highest impact on the total contaminant flows and on the efficiency of contaminant transport within the food web.

Bioinformatics Challenges and Potentialities in Studying Extreme Environments

“…In two research works, Taffi and colleagues proposed a computational framework that integrates bioaccumulation information at the ecosystem level with genome-scale metabolic models of PCB degrading bacteria [27,28]. The authors applied their methods to the case study of the polychlorinated biphenyls (PCBs) bioremediation in the Adriatic food web.…”

Ecological Modelling for Ecosystem Sustainability

“…They highlighted that trace metals eroded from the sediment is an important delayed source. Taffi et al (2015) presented a computational framework for analyzing contaminated food webs with bioaccumulation model of PCBs in the Adriatic Sea, proposing a new keystoneness index based on sensitivity analysis. Zhang et al (2015b) applied hybrid evolutionary algorithm (HEA) to develop eight spatially-explicit models and a generic model for 2-day ahead forecasting of cyanobacteria dynamics in Lake Taihu, and the results proved the models were suitable for early warning of cyanobacteria blooms.…”

Integrating food webs with metabolic networks: modeling contaminant degradation in marine ecosystems

“…Biomass transfer among species of a food web can be modeled using allometric scaling rules describing body size, consumption and metabolism (Yodzis and Innes, 1992 ; Berlow et al, 2009 ). Similarly, the flow of contaminants through a food web can be estimated by mass-balance modeling of chemical transfer and adsorption (Wania and Mackay, 1999 ; Arnot and Gobas, 2004 ; Breivik et al, 2007 ; Nichols et al, 2009 ; Taffi et al, in press ). Such modeling approaches can be complemented by measurements of contaminant concentrations (Kelly et al, 2007 ).…”

“…Such modeling approaches can be complemented by measurements of contaminant concentrations (Kelly et al, 2007 ). Recently, a food web representing the major ecological groups of the Adriatic Sea and their predator-prey interactions (Coll et al, 2007 ) was integrated with PCB concentration data obtained from an extensive literature review (Taffi et al, in press ). The resulting model allowed prediction of the flow rates of PCBs among ecological groups and reproduced the finding that PCBs accumulate mostly in species at higher trophic levels and with lower total biomass.…”

“…Taffi et al ( 2014 ) have recently integrated a comprehensive food web of the Adriatic Sea with PCB concentration data and a metabolic model of P. putida . First, the authors conducted an extensive literature review to complement a food web reconstruction (Coll et al, 2007 ) with data of PCB concentrations among marine species (Taffi et al, in press ). Next, linear inverse modeling was used to infer unknown contaminant flows and concentrations based on the mass balance principle.…”