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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., (© 2022 The Authors. Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

Earlier spring phenology observed in many plant species in recent decades provides compelling evidence that species are already responding to the rising global temperatures associated with anthropogenic climate change. There is great variability among species, however, in their phenological sensitivity to temperature. Species that do not phenologically "track" climate change may be at a disadvantage if their growth becomes limited by missed interactions with mutualists, or a shorter growing season relative to earlier-active competitors. Here, we set out to test the hypothesis that phenological sensitivity could be used to predict species performance in a warming climate, by synthesizing results across terrestrial warming experiments. We assembled data for 57 species across 24 studies where flowering or vegetative phenology was matched with a measure of species performance. Performance metrics included biomass, percent cover, number of flowers, or individual growth. We found that species that advanced their phenology with warming also increased their performance, whereas those that did not advance tended to decline in performance with warming. This indicates that species that cannot phenologically "track" climate may be at increased risk with future climate change, and it suggests that phenological monitoring may provide an important tool for setting future conservation priorities.

The covariance among a range of 20 network structural properties of food webs plus net primary productivity was assessed for 14 published food webs using principal components analysis. Three primary components explained 84% of the variability in the data sets, suggesting substantial covariance among the properties employed in the literature. The first dimension explained 48% of the variance and could be ascribed to connectance, covarying significantly with the proportion of intermediate species and characteristic path length. The second dimension explained 19% and was related to trophic species richness. The third axis explained 17% and was related to ecosystem net primary productivity. A distinct opposite clustering of connectance, the proportion of intermediate species, and mean trophic level vs. the proportion of top and basal species and path length suggests a dichotomy in food-web structure. Food webs appear either clustered and highly interconnected or elongated with fewer links.

Although an ecosystem's response to biodiversity loss depends on the order in which species are lost, the extinction sequences generally used to explore such responses in food webs have been ecologically unrealistic. We investigate how several extinction orders affect the minimum number of secondary extinctions expected within pelagic food webs from 34 temperate freshwater lakes. An ecologically plausible extinction order is derived from the geographically nested pattern of species composition among the lakes and is corroborated by species' pH tolerances. Simulations suggest that lake communities are remarkably robust to this realistic extinction order and highly sensitive to the reverse sequence of species loss. This sensitivity is not well explained by the known sensitivity of networks to the loss of highly connected species but appears to be better explained by our observation that trophic specialists preferentially consume widely distributed species at low risk of extinction. Our results highlight an important aspect of community organization that may help to maintain biodiversity amidst changing environments.