bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.10.13.758875

Climate change effects on terpene expression differ among populations and have consequences for herbivory in an invasive plant

Abstract

ABSTRACT 1. Plant secondary metabolites often moderate interactions with abiotic and biotic factors. For example, secondary metabolites often deter insect herbivores from and influence the extent of damage to plant tissues. However, little is known about how climate change may alter the expression of secondary metabolites and the nature of the resulting effects on plant-herbivore interactions. As climate change continues to shift environmental conditions away from historical norms, climate change effects on plant-herbivore interactions may have important consequences for the range expansion of invasive plants and the efficacy of biocontrol agents across the range. 2. In this study, we examined climate change effects on terpene expression in common tansy (Tanacetum vulgare) in four field transplant sites in Minnesota, U.S.A. that include experimental manipulation of precipitation and temperature. Each transplant site included genotypes from 10 natural populations that span climate variation across Minnesota. We quantified leaf terpene profiles in two years (2024 and 2025) using targeted gas chromatography-mass spectrometry. We surveyed insect herbivory to the same genotypes in experimental field sites to ask how terpene profiles and chemotypes contribute to the likelihood of herbivory. 3. We detected evidence that climate change manipulation altered terpene production and depended on source population. Similarly, the extent of temporal variation in terpene profiles depended upon source population. We also found variation in terpene profiles among sites, further emphasizing the role of the environment in shaping terpene production. These shifts in terpene profiles, in turn, influenced the likelihood of herbivory. Herbivory was higher at the southern compared to northern sites and susceptibility to herbivory was higher in the northern compared to southern populations, particularly at northern sites where average herbivory was lower. The likelihood of herbivory also varied among chemotypes and the frequency of chemotypes varied among source populations, suggesting a complex interplay between the historical and current environments, terpene production, and plant-herbivore interactions. 4. Synthesis. Together, our results suggest a combined role of the abiotic environment and population differentiation in moderating plant-herbivore interactions via shifts and variation in terpene profiles, which may influence invasive range dynamics and complicate the regional management strategies of common tansy.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Boehm, E. L., Briscoe Runquist, R., Moeller, D. A.. 2026-10-14. Climate change effects on terpene expression differ among populations and have consequences for herbivory in an invasive plant. https://doi.org/10.64898/2026.10.13.758875

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

On Motivating the Choice of Link Function in Binomial Regression Through A Latent Abundance Process

Ecologists commonly apply binomial regression to study binary data. Often, the link function in binomial regression is not purposefully chosen, but instead selected on the grounds of interpretation or computation efficiency. However, if the binary response is the result of a latent abundance process, then the link function implies assumptions for this underlying process. The most well-known example of this is the complementary log-log (cloglog) link, which has direct connections with the probability of a positive count under a latent Poisson distribution. If the binary response can be assumed to represent a truncated latent count, the cloglog link can be a better choice than the logit link. On the other hand, counts in ecology are often overdispersed, meaning the assumption of an underlying Poisson abundance process is unrealistic. In this article, we provide a framework for consideration of the link choice in binomial regression, in terms of the latent abundance process that binary responses can represent. Aside from the Poisson case mentioned above, we show that the cloglog link is the right choice if the latent abundance process represents the biomass of individuals, or if the latent abundance process comes from an overdispersed count distribution with a linear mean-variance relationship. For the case where the latent count follows a negative binomial distribution with a quadratic mean-variance relationship, we derive a new generalized complementary log-log (gcloglog) link function, which includes the case of the cloglog link as well as that of the logit link, where the latter implies assuming moderate overdispersion in the form of a geometric distribution. Two simulation studies demonstrate that cloglog and logit link binomial regression can exhibit bias and undercoverage when the latent count is more overdispersed than assumed, while gcloglog link models overcome this issue but in practice require replication in the binomial response for reliable estimation. Two real ecological datasets further illustrate how to use the gcloglog link binomial regression in practice including as a means of sensitivity analysis. We encourage ecologists to give more thought to the choice of link function in binomial regression, based on considering the latent abundance process and its properties.

ecology↗

Towards predictive ecological biogeography: Predicting vegetation type using fine-scale measurements of the abiotic environment

One of the goals of ecological biogeography is to accurately predict where major vegetation types, such as forests or grasslands, can establish themselves. Alas, our current understanding of the mechanisms by which environmental variables jointly influence vegetation types does not allow for such predictions. Here, we compile a database of local measurements of soil, weather, topography, and bedrock lithology for 6404 sites across the continental United States, which we complement with information about the vegetation around the measurement sites. By applying machine learning methods to a subset of the sites, we are able to train a machine that predicts - using only information about abiotic variables - the presence of forests or grasslands with nearly 90% accuracy on the rest of the sites. We find that while weather variables are statistically important for these predictions, a few soil variables prove to be the most powerful predictors. By separating the combined contributions of weather and soil, we show that soil texture is a better predictor under dry conditions than under wet conditions, while pH is important predictor regardless of the weather. Furthermore, from 136 sites undergoing grassland-to-forest succession, our analysis indicates that soil pH changes with a certain lag relative to vegetation change. Sites that have recently undergone a transition exhibit a higher pH, closer to that of grasslands, despite the presence of trees. The pH then decreases by about one unit over a 30-year period of forest development. Ultimately, our results indicate that fine-scale environmental measurements and historical ecological data can serve as a basis for quantitative bio-geographical predictions, which could eventually guide targeted conservation interventions.

ecology↗

Invasive Chinese tallow is associated with distinct rhizosphere microbial communities, core microbiomes, and functional potential relative to native Loblolly pine

Plant invasions frequently reshape belowground microbial communities, yet their effects on rhizosphere microbiome structure and function remain poorly understood. We compared the rhizosphere bacterial and fungal microbiomes of invasive Chinese tallow (Triadica sebifera) and native Loblolly pine (Pinus taeda) using 16S rRNA gene and ITS amplicon sequencing, together with microbial, functional, and soil analyses. Chinese tallow exhibited significantly greater bacterial and fungal richness and distinct microbial community composition than Loblolly pine. The invasive rhizosphere was enriched in plant-beneficial bacterial taxa, including Streptomyces, Bradyrhizobium, and Rhizobium, and ectomycorrhizal-associated fungi such as Russula and Cenococcum. This enrichment is consistent with enhanced nutrient acquisition, plant growth promotion, and stress tolerance, potentially favoring Chinese tallow establishment and persistence. Further, core microbiome and co-occurrence network analyses revealed extensive reorganization of persistent (Streptomyces, Russula) and highly connected microbial taxa that may be associated with Chinese tallow invasion. Functional predictions indicated greater representation of carbohydrate degradation, nitrogen fixation, plant growth promotion, nutrient mineralization, and ectomycorrhizal guilds in the Chinese tallow rhizosphere, whereas lignin degradation and saprotrophic or pathogen-associated fungal guilds were relatively more abundant under Loblolly pine. Soil physicochemical properties were also strongly correlated with dominant bacterial and fungal taxa, indicating that host-mediated microbial recruitment and environmental filtering jointly shaped rhizosphere community assembly. Overall, our findings identify rhizosphere microbiome reassembly as an important belowground feature associated with Chinese tallow invasion.

ecology↗