Chesapeake Bay Food Web: Robustness Analysis via Energy Cutoff in Complex Networks

TL;DR

The study addresses the robustness of the Chesapeake Bay food web by applying a threshold-based energy cutoff to a weighted energy-transfer network derived from $A_{ij}$. By constructing symmetric adjacency matrices $A^{(\theta)}_{ij}$ for $\theta \in [0,100]$ and computing standard network metrics, it reveals a percolation-like connectivity transition: the system remains globally connected up to $\theta_c \approx 40$, but fragments rapidly beyond this point as weaker links fail. The findings highlight the crucial role of weak intermodular connections and top predators, such as Carnivorous fish, in maintaining energy flow and ecosystem integrity, with direct implications for conservation strategies that protect energetic linkages as well as species. The work suggests extensions to directed analyses and extinction scenarios guided by weighted centralities to further understand resilience in ecological networks.

Abstract

The Chesapeake Bay, one of the largest estuaries in the United States, is an ecological system of great complexity and relevance. The food web is composed of thirty-six trophic components, all of which are functionally connected. In this work, the interactions among these components are numerically analyzed using complex network methods. An energy flow cutoff paradigm is applied to a weighted ecological network. The results reveal patterns characteristic of connectivity dynamics, evidencing both the initial robustness of the system and its tendency to fragmentation at higher values of the cutoff. From an applied perspective, the findings underscore the importance of conservation strategies that protect keystone species, such as carnivorous fish, which act as crucial connectors between the two main subnetworks. Although they are positioned at the top of the food web and are often assumed to be less critical to network stability, these species play a pivotal role in regulating populations of lower-level organisms, thereby maintaining the overall integrity of the ecosystem.

Figures (3)

• Figure 1: (a) Average degree $\langle k\rangle$, (b) Connectance $C$, (c) Average distance $L$, (d) clustering as a function of $\theta$ for the globally connected network regime ($0\le\theta\le40$).
• Figure 2: Number of connected components in the largest subnetwork $G$ (left axis) and the number of subnetworks $S$ (right axis) as a function of $\theta$.
• Figure 3: Network structure for four representative cutoff values: (a) $\theta = 40$, (b) $\theta = 55$, (c) $\theta = 69$, (d) $\theta = 100$.