Biology subjects

Edwards, C. B.

Publications and source records attributed to Edwards, C. B..

7 recordsLinked to original sources

bioRxiv2026

Self-Organized Pattern Formation of a Common Tropical Alga

Recent in-situ observations within a tropical coral reef have revealed novel polygonal patterns of the calcifying green alga Halimeda. The observed patterns showed no evidence of a matching exogenous template in structural reef morphology, distribution of biological competitors for space, or other environmental factors, suggesting the pattern is the result of endogenous, nonlinear pattern forming dynamics. A simplified, spatially explicit numerical model is proposed that simulates a feedback whereby Halimeda preferentially grows in regions less conducive to the growth of corals (when corals are the dominant spatial competitor), and coral growth is inhibited in regions of dense Halimeda. Model results reveal self-organized emergent polygons of Halimeda cover that qualitatively match observations.

ecology↗

bioRxiv2023

Estimating butterfly population trends from sparse monitoring data using Generalized Additive Models

Concerns of declines in insects and population level responses to climate change have highlighted the importance of estimating trends in abundance and phenology from existing monitoring data. As the taxa with the most systematic monitoring data, butterflies are a frequent focus for understanding trends in insects. Even so, ecologists often have only sparse monitoring data for at-risk butterfly populations. As existing statistical techniques are typically poorly suited to such data, these at-risk populations are frequently excluded from analyses of butterfly trends. Here we present guidelines for estimating population trends from sparse butterfly monitoring data using generalized additive models (GAMs), based on extensive simulations and our experiences fitting hundreds of butterfly species. These recommendations include pre-processing steps, model structure choices, and post-hoc analysis decisions that reduce bias and prevent or mitigate biologically implausible model fits. We also present the ButterflyGamSim package for the programming language R, available at https://github.com/cbedwards/butterflyGamSims. This open source software provides tools for ecologists and applied statisticians to simulate realistic butterfly monitoring data and test the efficacy of different GAM model choices or monitoring schemes.

ecology↗

bioRxiv2021

Rapid decline in Western monarch butterflies leads to phenological and geographic Allee effects

Allee effects - the breakdown of biological processes at low population densities - are ecologically important because they can potentially drag already struggling populations to extinction. However, identifying and documenting Allee effects is challenging, especially for natural populations, because it is difficult to know when populations have dropped to critically low densities, and to observe them both above and below this threshold. Here, we compared demographic processes in the western monarch butterfly, Danaus plexippus, before and after the population had fallen below the size at which Allee effects were hypothesized to take hold. Comparisons drew on data we collected after a dramatic population crash in 2018, previously published data from other researchers, and community science data. We found no evidence for Allee effects in winter survival, the fraction of females mated in early spring, or eggs laid per day. We did identify a 43% decline in the distance of seasonal range expansion, which could reflect Allee effects in terms of summer population growth rates or density-dependent movement behavior. In addition, overwinter survival of western monarch butterflies has substantially declined since first estimated in 1975 and may be contributing to the long-term population decline. The lack of evidence for Allee effects and the recent rebound in population size provide a more hopeful view for monarch conservation in the future but do not supersede the documented density-independent population decline across the last several decades.

ecology↗

bioRxiv2021

Identifying synergies and antagonisms between plant defense traits in Asclepias syriaca

As a general rule, plants defend against herbivores with multiple traits. The defense synergy hypothesis posits that some traits are more effective when co-expressed with others compared to their independent efficacy. However, this hypothesis has rarely been tested outside of phytochemical mixtures, and seldom under field conditions. We tested for synergies between multiple defense traits of common milkweed (Asclepias syriaca) by assaying the performance of two specialist chewing herbivores on plants in natural populations. We employed regression and a novel application of Random Forests to identify synergies and antagonisms between defense traits. We found the first direct empirical evidence for two previously hypothesized defense synergies in milkweed (latex by secondary metabolites, latex by trichomes), and identified numerous other potential synergies and antagonisms. Our strongest evidence for a defense synergy was between leaf mass per area and low nitrogen content; given that these "leaf economic" traits typically covary in milkweed, a defense synergy could reinforce their co-expression. We report that each of the plant defense traits showed context-dependent effects on herbivores, and increased trait expression could well be beneficial to herbivores for some ranges of observed expression. The novel methods and findings presented here complement more mechanistic approaches to the study of plant defense diversity, and provide some of the best evidence to date that multiple classes of plant defense synergize in their impact on insects. Plant defense synergies against highly specialized herbivores, as shown here, are consistent with ongoing reciprocal evolution between these antagonists.

ecology↗

bioRxiv2020

Fitting phenological curves with GLMMs

Estimating population abundance is central to population ecology. With increasing concern over declining insect populations, estimating trends in abundance has become even more urgent. At the same time, there is an emerging in interest in quantifying phenological patterns, in part because phenological shifts are one of the most conspicuous signs of climate change. Existing techniques to fit activity curves (and thus both abundance and phenology) to repeated transect counts of insects (a common form of data for these taxa) frequently fail for sparse data, and often require advanced knowledge of statistical computing. These limitations prevent us from understanding both population trends and phenological shifts, especially in the at-risk species for which this understanding is most vital. Here we present a method to fit repeated transect count data with Gaussian curves using linear models, and show how robust abundance and phenological metrics can be obtained using standard regression tools. We then apply this method to eight years of Baltimore checkerspot data using generalized linear models (GLMs). This case study illustrates the ability of our method to fit even years with only a few non-zero survey counts, and identifies a significant negative relationship between population size and annual variation in thermal environment (in growing degree days). We believe our new method provides a key tool to unlock previously-unusable sparse data sets, and may provide a useful middle ground between ad hoc metrics of abundance and phenology and custom-coded mechanistic models.

ecology↗

bioRxiv2019

Future sea-level rise drives rocky intertidal habitat loss and benthic community change

Rocky intertidal ecosystems may be particularly susceptible to sea-level rise impacts but few studies have explored community scale response to future sea-level scenarios. Combining remote-sensing with large-area imaging, we quantify habitat extent and describe biological community structure at two rocky intertidal study locations in California. We then estimate changes in habitat area and community composition under a range of sea-level rise scenarios using a model-based approach. Our results suggest that future sea-level rise will significantly reduce rocky intertidal area at our study locations, leading to an overall decrease in benthic habitat and a reduction in overall invertebrate abundances, but increased densities of certain taxa. These results suggest that sea-level rise may fundamentally alter the structure and function of rocky intertidal systems. As large scale environmental changes such as sea-level rise accelerate in the next century, more extensive spatially-explicit monitoring at ecologically relevant scales will be needed to visualize and quantify the impacts to biological systems.

ecology↗

bioRxiv2018

Evolved phenological cueing strategies show variable responses to climate change

Several studies have documented a global pattern of phenological advancement that is consistent with ongoing climate change. However, the magnitude of these phenological shifts is highly variable across taxa and locations. This variability of phenological responses has been difficult to explain mechanistically. To examine how the evolution of multi-trait cueing strategies could produce variable responses to climate change, we constructed a model in which organisms evolve strategies that integrate multiple environmental cues to inform anticipatory phenological decisions. We simulated the evolution of phenological cueing strategies in multiple environments, using historic climate data from 78 locations in North America and Hawaii to capture features of climatic correlation structures in the real world. Organisms in our model evolved diverse strategies that were spatially autocorrelated across locations on a continental scale, showing that similar strategies tend to evolve in similar climates. Within locations, organisms often evolved a wide range of strategies that showed similar response phenotypes and fitness outcomes under historical conditions. However, these strategies responded differently to novel climatic conditions, with variable fitness consequences. Our model shows how the evolution of phenological cueing strategies can explain observed variation in phenological shifts and unexpected responses to climate change.

ecology↗