A computational exploration of resilience and evolvability of protein-protein interaction networks

Landscape-level variability and insect herbivore outbreak captured within modern forests provides a framework for interpreting the fossil record

Temporal patterns of plant-insect interactions are readily observed within fossil datasets but spatial variability is harder to disentangle without comparable modern methods due to limitations in preservation. This is problematic as spatial variability influences community structure and interactions. To address this we replicated paleobotanical methods within three modern forests, creating an analogous dataset that rigorously tested inter- and intra-forest plant-insect variability. Random mixed effects models, non-metric multidimensional scaling (NMDS) ordinations, and bipartite network- and node-level metrics were used. Total damage frequency and diversity did not differ across forests but differences in functional feeding groups (FFGs) were observed across forests, correlating with plant diversity, evenness, and latitude. Overall, we found higher generalized herbivory within the temperate forests than the wet-tropical, a finding also supported by co-occurrence and network analyses at multiple spatial scales. Intra-forest analyses captured consistent damage type communities, supporting paleobotanical efforts. Bipartite networks captured the feeding outbreak of Lymantria dispar caterpillars; an exciting result as insect outbreaks have long been unidentifiable within fossil datasets. These results support paleobotanical assumptions about fossil insect herbivore communities, provide a comparative framework between paleobotanical and modern communities, and suggest a new analytical framework for targeting modern and fossil outbreaks of insect feeding.

Sampling bias and the robustness of ecological metrics for plant-damage-type association networks

Plants and their insect herbivores have been a dominant component of the terrestrial ecological landscape for the past 410 million years and feature intricate evolutionary patterns and co-dependencies. A complex systems perspective allows for both detailed resolution of these evolutionary relationships as well as comparison and synthesis across systems. Using proxy data of insect herbivore damage (denoted by the damage type or DT) preserved on fossil leaves, functional bipartite network representations provide insights into how plant-insect associations depend on geological time, paleogeographical space, and environmental variables such as temperature and precipitation. However, the metrics measured from such networks are prone to sampling bias. Such sensitivity is of special concern for plant-DT association networks in paleontological settings where sampling effort is often severely limited. Here, we explore the sensitivity of functional bipartite network metrics to sampling intensity and identify sampling thresholds above which metrics appear robust to sampling effort. Across a broad range of sampling efforts, we find network metrics to be less affected by sampling bias and/or sample size than richness metrics, which are routinely used in studies of fossil plant-DT interactions. These results provide reassurance that cross-comparisons of plant-DT networks offer insights into network structure and function and support their widespread use in paleoecology. Moreover, these findings suggest novel opportunities for using plant-DT networks in neontological terrestrial ecology to understand functional aspects of insect herbivory across geological time, environmental perturbations, and geographic space.

A complex systems approach to aging biology

Having made substantial progress understanding molecules, cells, genes and pathways, aging biology research is now moving toward integration of these parts, attempting to understand how their joint dynamics may contribute to aging. Such a shift of perspective requires the adoption of a formal complex systems framework, a transition being facilitated by large-scale data collection and new analytical tools. Here, we provide a theoretical framework to orient researchers around key concepts for this transition, notably emergence, interaction networks and resilience. Drawing on evolutionary theory, network theory and principles of homeostasis, we propose that organismal function is accomplished by the integration of regulatory mechanisms at multiple hierarchical scales, and that the disruption of this ensemble causes the phenotypic and functional manifestations of aging. We present key examples at scales ranging from sub-organismal biology to clinical geriatrics, outlining how this approach can potentially enrich our understanding of aging.