Ecological interactions in fossil assemblages

Project members: Anshuman Swain, Matthew Devereux and William F Fagan;

Status: Published in iScience

The Cambrian Period (541-485 Mya) represents a major stage in the development of metazoan-dominated assemblages with complex community structure and species interactions. Exceptionally preserved fossil sites have allowed specimen-based identification of putative trophic interactions to which network analyses have been applied. However, network analyses of the fossil record suffer from incomplete and indirect data, time averaging that obscures species coexistence, and biases in preservation, collection, and identification of both specimens and interactions. Here, we present a novel high-resolution fossil dataset from the Raymond Quarry (RQ) member of the mid-Cambrian Burgess Shale (7549 specimens, 61 taxa, ~510 Mya) affording new perspectives on these challenging issues. Further, we formulate a new measure of ‘preservation bias’ that aids identification of those assemblage subsets to which network analyses can be reliably applied. For sections with sufficiently low bias, abundance correlation network analyses predicted longitudinally consistent trophic and competitive interactions. These methods predicted previously postulated trophic interactions with 83.5% accuracy and demonstrated a shift from specialist-dominated assemblages to ones dominated by generalist and competitive interactions. This approach provides a robust, taphonomically corrected framework to explore and predict in detail the existence and ecological character of putative interactions in fossil datasets, offering new windows on ancient foodwebs.

Project members: Anshuman Swain, Sarah A MacCracken, Conrad C Labandeira and William F Fagan

Status: Published in Paleobiology

Vascular plants and their insect herbivores account for more than 40% of terrestrial biodiversity today and have dominated terrestrial ecosystems for over 300 million years. The associations between plants and herbivores are a cornerstone of modern and ancient terrestrial ecosystems, and even conservative estimates for the number of plant–insect interactions are in the tens to hundreds of millions.

Despite the availability of large amounts of observed plant–herbivore interaction data for extant communities and sophisticated mathematical methods to study these interactions, the evolutionary history of plant-insect systems and interactions is poorly known. Phylogenetic approaches may uncover co-evolutionary dynamics to disentangle these interactions, but the fossil record provides the best platform for understanding ancient plant–insect associations at macroevolutionary time scales. Complementary to, and in some cases more informative than phylogenetic analyses, the record of insect herbivory on fossil plants provides some of the most accessible, abundant and robust evidence of organisms interacting the distant past.

In this work, we aim to do the following- first, construct biologically meaningful network representations of herbivory in fossil plants and look at various network properties to understand the ecology, community structure and assembly of plant–insect associations in 12 assemblages. Second, use novel mathematical methods to decipher indirect ecological interactions and associations for these plant–insect associational assemblages. Third, compare network properties across temporal and environmental contexts to uncover differences in ecological structure and possible dynamics for the 12 plant–insect assemblages. We expect to see certain similarities in the network topology of similar types of forests across different time-periods due to environmental factors, despite the differences in plant community composition, which in turn will fuel the differences among them. Understanding these differences and similarities will be key to discerning patterns of interactions across environmental and ecological gradients.

Project members: Jack Shaw, Kate Wootton, Emily Coco, Dries Daems, Andew Gillreath-Brown, Anshuman Swain and Jennifer Dunne

Status: Published in Paleobiology; This project came out of a working group as a part of the Santa Fe Institute (SFI) CSSS 2019

Ecological communities are complex systems, often composed of thousands of interacting species. Advances in mathematical methods are beginning to permit quantitative insights into ecosystem functioning. Network analyses, in particular, of those interactions have unlocked critical features of community structure, stability, and responses to perturbations (e.g., climate change). To adequately act as a predictor of future conditions, ecological network theory needs to expand its temporal scope and incorporate a deep-time perspective for a more holistic approach. The geological record offers a multitude of case studies on how life responded to perturbations across different time scales. Studies of ancient interaction networks, as evidenced by fossils, reveal important paleoecological processes. However, the effects of information loss on ancient interaction networks are severely understudied. Earlier work on social networks has noted that random and selective information loss has important systematic effects on networks metrics, depending on the topology of the network. By contrast, many (paleo-) ecological studies do not account for key differences between modern and ancient interaction data, including the selective loss of pelagic and soft-bodied taxa during fossilization. As some of these characteristics are associated with particular network positions, it is essential to be aware of these potential biases when analyzing the fossil record. To address this topic, we applied an information loss pipeline, modelled on the selective loss of non-biomineralizing taxa during fossilization, to six modern trophic networks (five marine systems and one freshwater system). The structures of these “artificially fossilized” networks were compared with three ancient trophic networks (two marine systems and one lake system) preserved in fossil deposits. A comparison of community-level composition and topology of the food webs as well as node-specific network metrics showed that the effects of artificial fossilization on network structure were highly dependent on initial structure and the characters of taxa within the network. Some metrics, such as trophic position and omnivory index, displayed unique responses to selective information loss whereas others, including connectance and degree, were indistinguishable from random loss. It is clear that specific taphonomic biases must be factored into analyses of the ecological structure of food webs based on fossil evidence.