Balancing complexity and feasibility in Mediterranean coastal food-web models: uncertainty and constraints

Abstract

Mass-balance trophic models (Ecopath and EcoTroph) are valuable tools that can be used to describe ecosystem structure and functioning, identify target species to be monitored, and allow comparisons of ecosystem states under different management options. Nevertheless, the Ecopath modelling approach is constrained by 2 major sources of uncertainty: model complexity and input data quality. We developed an approach for identifying the optimum model structure that considers trade-offs between feasibility, complexity, and uncertainty, using a Mediterranean coastal ecosystem as a case study. We began with an existing well-documented and good-quality food-web model comprising 41 functional groups at Port-Cros National Park, France. Based on this model, we assessed the effects of different aggregation choices, driven by a simplification of sampling effort, on the Ecopath and EcoTroph model outputs. We identified the functional groups in which imprecise biomass input significantly influenced the food-web model, and measured the relative effects on the ecosystem trophic structure and ecosystem maturity and complexity indices. A simplified model comprising 32 functional groups was identified as the best compromise between model complexity and reliability. High trophic level predators, abundant primary producers, and groups with a high biomass and/or diversified diet significantly influenced the model structure. We concluded that the collection of local and accurate biomass data, especially for the most influential functional groups we identified, should be a priority when developing food-web models for similar ecosystems. Our method enables simplified and standardized models, while considering both the feasibility and reliability of the Ecopath and EcoTroph applications for Mediterranean coastal ecosystems.

Assessing interacting impacts of artisanal and recreational fisheries in a small Marine Protected Area (Portofino, NW Mediterranean Sea)

“…, Prato et al. ). Being both a preferred prey for many high trophic level predators and predators acting on a wide range of trophic levels, cephalopods occupy an important functional role in both coastal and pelagic ecosystems (Piatkowski et al.…”

“…, Prato et al. ), data quality was assessed applying the food web diagnostics proposed by Link () and the Data‐Reli toolbox developed by Lassalle et al. ().…”

Modelling dynamic ecosystems: venturing beyond boundaries with the Ecopath approach

“…Studies indicated that communication with stakeholders, particularly decision makers, should be encouraged before and during model development to ensure that ecosystem modelling work is tailored (1) to address relevant management objectives, questions and issues on the table, and (2) to facilitate the necessary buy-in and investment by decision makers into the process of producing scientific results for advising management. In this context, an interesting example was presented of how dialogue with the PortCross National Park (NW Mediterranean Sea) MPA managers is initiating improvements in terms of monitoring of key groups in MPA and stimulating keen interest and buy-in from the MPA managers (Prato et al 2014). Another example was provided in the context of management of marine resources in the Azores (Morato et al 2014), where managers obtained buy-in from fishers after they saw the improved catches due to closures for research purposes.…”

Trophodynamics in marine ecology: 70 years after Lindeman

“…Conversely, Muto et al (2014) showed that mercury biomagnification can be used to trace trophic positions in species of the northern Brazilian continental shelf. As an example of how to integrate such information, Prato et al (2014) built a food web model of the NW Mediterranean using field-derived information. They show the effects of biological articulation on food web indicators and identify taxa of little commercial interest but high trophodynamic im portance.…”

“…Sensitivity and uncertainty analysis (e.g. Pranovi et al 2014, Prato et al 2014 can test the robustness of trophodynamic models and identify key ecosystem elements (food web nodes, aggregation level; e.g. Jordán et al 2014) on which data collection needs to focus.…”