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Contrasting responses of plant invasion to favorable and adverse global change factor richness
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Scientists studied how an invasive weed (ragweed, a major allergy trigger) responds when multiple environmental stressors, like pollution, drought, warming, and even microplastics, pile up at once alongside helpful factors like extra CO2 or nutrients. They found that "bad" stressors and "good" growth boosters affect the weed's ability to invade native plant communities differently depending on how many pile up together, not just which ones are present. This matters because ragweed pollen is a leading cause of seasonal allergies, so understanding what helps or hinders its spread can inform strategies to control its expansion as climate and pollution con
This dataset was generated from a factorial pot experiment designed to examine how plant invasion responds to the richness, identity, directional effects, and interactions of multiple global change factors (GCFs). The experiment used the invasive plant Ambrosia artemisiifolia growing with native plant communities. Fourteen GCFs were classified into two contrasting pools based on their expected effects on plant growth: seven plant-growth-promoting (favourable) GCFs and seven plant-growth-inhibiting (adverse) GCFs. Within each pool, treatments consisted of randomly generated combinations of 1, 2, 4, or 6 co-occurring GCFs, together with a GCF-free control. Native communities differing in species composition were used to account for variation in recipient community identity. At harvest, aboveground and belowground biomass of A. artemisiifolia and the native communities were measured separately. These measurements were used to calculate total biomass of the invader, native communities, and whole communities, as well as the biomass proportion of A. artemisiifolia as a measure of invasion success.Files and variablesFile: GCFs2024.RmdDescription: The file contains the R code we used for data analysis in this study.File: data2024greenhouse_GCFs.csvDescription: This file contains the experimental treatment information and biomass measurements from the pot experiment. Each row represents one experimental pot. The file includes information on experimental units, native community identity, GCF pool, GCF richness and composition, individual GCFs included in each treatment combination, and aboveground and belowground biomass of Ambrosia artemisiifolia and the native community.VariablesID: Unique identifier for each experimental pot.OTC: Identifier of the glasshouse chamber associated with each experimental pot.RD1: Identifier for the first randomization/layout of experimental pots.RD2: Identifier for the second randomization/layout of experimental pots.Community: Identity of the native plant community.Factors_type: Type of GCF pool used in the treatment [PFN = favourable GCF pool; NFN = adverse GCF pool]Factors_n: GCF richness, i.e. the number of GCFs simultaneously applied to the experimental pot (0, 1, 2, 4, or 6).Factors_comb: Specific combination of GCFs applied to an experimental pot. Individual GCF codes are separated by underscores. “Control” denotes the GCF-free control.[PBS: microplastic pollution, H+: acid rain stress, SDBS: anionic-surfactant stress, NaCl: soil salinization, Cd: heavy-metal contamination, Dry: drought stress, LT: low-temperature stress, CO2: elevated CO2, N: N addition, P: P addition, K+M: K addition, H2O: water addition, F: fungicide application, HT: warming ]AB_native: Aboveground biomass of the native community (g).AB_target: Aboveground biomass of the target invasive species, Ambrosia artemisiifolia (g).BB_native: Belowground biomass of the native community (g).BB_target: Belowground biomass of the target invasive species, Ambrosia artemisiifolia (g).File: data2024greenhouse_HDI.csvDescription: This file contains the data formatted for hierarchical diversity–interaction (HDI) modelling. Each row represents one experimental pot. In addition to experimental identifiers, native community identity, GCF pool, GCF richness, GCF combination, and raw biomass measurements, the file contains seven proportional variables (p1–p7) representing the relative contribution of each GCF within a treatment combination. For a treatment containing n GCFs, each GCF present in the combination is assigned a value of 1/n, whereas GCFs absent from the combination are assigned a value of 0. For the GCF-free control, all seven proportional variables are 0.Variablesp1-p7: Proportional representation of each individual GCF within a treatment combination, used as predictor variables in the hierarchical diversity–interaction models. For treatments containing n GCFs, each GCF present is assigned a value of 1/n and each absent GCF a value of 0. In the adverse GCF pool, p1–p7 correspond respectively to PBS, H+, SDBS, NaCl, Cd, Dry, and LT. In the favourable GCF pool, p1–p7 correspond respectively to HT, CO₂, N, P, K+M, H₂O, and F. For GCF-free controls, p1–p7 are all 0.for other variables, the same with “data2024greenhouse_GCFs.csv”.
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