Research

Ongoing anthropogenic alterations of the biosphere have shifted emphasis in conservation biology from individual species to entire ecosystems. Measures of modern ecosystem change, however, lack the temporal scales necessary to forecast future change under increasingly stressful and non-analogue environmental conditions. Accordingly, the assessment and reconstruction of ecosystem dynamics during previous intervals of environmental stress in deep time has garnered increasing attention and significance. The nature of the fossil record, though, raises questions about the difficulty and reliability of reconstructing paleocommunity and paleoecosystem-level dynamics. In this study, we assess the reliability of such reconstructions by simulating the fossilization of a highly threatened and disturbed modern Caribbean coral reef. Using a high-resolution Jamaican coral reef food web, we compare system properties of the modern and simulated fossil reefs, including guild richness and evenness, trophic level distribution, predator dietary breadth, food chain lengths, and modularity. Simulated fossilization resulted in loss of species (295 of 728), guilds (107 of 149), and trophospecies interactions (2368 of 4105), particularly zooplankton and other soft-bodied organisms. Nevertheless, the overall guild diversity, structure, and modularity of the reef ecosystem remained intact. Using methods developed previously, the fossilized community can be used to estimate food webs that are statistically indistinguishable from that of the modern coral reef community. These results have substantial implications for the integrity of fossil food web studies and coral reef conservation, and emphasize the validity and usefulness of paleoecological data to the field of conservation biology. The creation of deep-time paleocommunity food webs has the ability to enrich and advance our current knowledge of how natural systems behave, especially in response to future environmental changes.

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Modules represent groups, or sub-compartments of guilds with more mutual interactions than interactions with other guilds, i.e., dense groupings of links (Gross et al. 2009; Stouffer and Bascompte 2011). Compartmentalization is widespread in modern empirical networks (Krause et al. 2003; Rezende et al. 2009; Guimerà et al. 2010), and may increase network stability and persistence (Newman 2006; Gross et al. 2009; Stouffer and Bascompte 2011), preventing propagation of perturbations between modules (Krause et al. 2003; Newman 2006). During the MMR, we would expect an increase in modularity if the number and strength of species interactions increased, i.e., greater competition between species utilizing similar resources (Pascual and Dunne 2006).

The Louvain algorithm, a hierarchical clustering community detection method, was used to identify natural network divisions into subgroups, finding community structure by multi-level optimization of modularity (Blondel et al. 2008). Modularity is a measure of the strength of the division into modules, with higher values indicating greater compartmentalization (Yodzis 1989; Stouffer and Bascompte 2011). Higher modularity suggests a large number of interactions between guilds within modules, but sparse connections between guilds in different modules (Pascual and Dunne 2006; Roopnarine 2009b).

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