Phragmites australis is a cosmopolitan grass and often the dominant species in the ecosystems it inhabits. Due to high intraspecific diversity and phenotypic plasticity, P. australis has an extensive ecological amplitude and a great capacity to acclimate to adverse environmental conditions; it can therefore offer valuable insights into plant responses to global change. Here we review the ecology and ecophysiology of prominent P. australis lineages and their responses to multiple forms of global change. Key findings of our review are that: (1) P. australis lineages are well-adapted to regions of their phylogeographic origin and therefore respond differently to changes in climatic conditions such as temperature or atmospheric CO₂; (2) each lineage consists of populations that may occur in geographically different habitats and contain multiple genotypes; (3) the phenotypic plasticity of functional and fitness-related traits of a genotype determine the responses to global change factors; (4) genotypes with high plasticity to environmental drivers may acclimate or even vastly expand their ranges, genotypes of medium plasticity must acclimate or experience range-shifts, and those with low plasticity may face local extinction; (5) responses to ancillary types of global change, like shifting levels of soil salinity, flooding, and drought, are not consistent within lineages and depend on adaptation of individual genotypes. These patterns suggest that the diverse lineages of P. australis will undergo intense selective pressure in the face of global change such that the distributions and interactions of co-occurring lineages, as well as those of genotypes within-lineages, are very likely to be altered. We propose that the strong latitudinal clines within and between P. australis lineages can be a useful tool for predicting plant responses to climate change in general and present a conceptual framework for using P. australis lineages to predict plant responses to global change and its consequences.

Solar photovoltaic (PV) technology is being deployed at an unprecedented rate. However, utility-scale solar energy development is land intensive and its large-scale installation can have negative impacts on the environment. In particular, solar energy infrastructure can require extensive landscape modification that transforms soil ecological functions, thereby impacting hydrologic, vegetative, and carbon dynamics. However, reintroducing native vegetation to solar PV sites may be a means of restoring their soils. To this end, we investigated critical soil physical and chemical parameters at a revegetated photovoltaic array and an adjacent reference grassland in Colorado, United States. Seven years after revegetation, we found that carbon and nitrogen remained lower in the PV soil than in the reference soil and contained a greater fraction of coarse particles. We also found that the PV modules introduced heterogeneity in the soil moisture distribution, with precipitation accumulating along the lower edges of panels. The redistribution of soil moisture by panel arrays could potentially be used in concert with planting strategies to maximize plant growth or minimize soil erosion, and should be considered when evaluating the potential to co-locate vegetation with solar infrastructure.

Climate change may alter the physical properties that control soil water storage and fluxes in terrestrial ecosystems.

Fractal dimension (FD), estimated by box-counting, is a metric used to characterise plant anatomical complexity or space-filling characteristic for a variety of purposes. The vast majority of published studies fail to evaluate the assumption of statistical self-similarity, which underpins the validity of the procedure. The box-counting procedure is also subject to error arising from arbitrary grid placement, known as quantisation error (QE), which is strictly positive and varies as a function of scale, making it problematic for the procedure's slope estimation step. Previous studies either ignore QE or employ inefficient brute-force grid translations to reduce it. The goals of this study were to characterise the effect of QE due to translation and rotation on FD estimates, to provide an efficient method of reducing QE, and to evaluate the assumption of statistical self-similarity of coarse root datasets typical of those used in recent trait studies. Coarse root systems of 36 shrubs were digitised in 3D and subjected to box-counts. A pattern search algorithm was used to minimise QE by optimising grid placement and its efficiency was compared to the brute force method. The degree of statistical self-similarity was evaluated using linear regression residuals and local slope estimates. QE due to both grid position and orientation was a significant source of error in FD estimates, but pattern search provided an efficient means of minimising it. Pattern search had higher initial computational cost but converged on lower error values more efficiently than the commonly employed brute force method. Our representations of coarse root system digitisations did not exhibit details over a sufficient range of scales to be considered statistically self-similar and informatively approximated as fractals, suggesting a lack of sufficient ramification of the coarse root systems for reiteration to be thought of as a dominant force in their development. FD estimates did not characterise the scaling of our digitisations well: the scaling exponent was a function of scale. Our findings serve as a caution against applying FD under the assumption of statistical self-similarity without rigorously evaluating it first.

Despite the importance of fine roots for the acquisition of soil resources such as nitrogen and water, the study of linkages between traits and both population and community dynamics remains focused on aboveground traits. We address this gap by investigating associations between belowground traits and metrics of species dynamics. Our analysis included 85 species from a long‐term data set on the transition from old field to forest in eastern North America (the Buell‐Small Succession Study) and the new Fine‐Root Ecology Database. Given the prominent roles of life form (woody vs. non‐woody) and species origin (native vs. exotic) in defining functional relationships, we also assessed whether traits or their relationships with species dynamics differed for these groups. Species that reached their peak abundance early in succession had fine‐root traits corresponding to resource acquisitive strategies (i.e., they were thinner, less dense, and had higher nitrogen concentrations) while species that peaked progressively later had increasingly conservative strategies. In addition to having more acquisitive root traits than native species, exotics diverged from the above successional trend, having consistently thinner fine roots regardless of the community context. Species with more acquisitive fine‐root morphologies typically had faster rates of abundance increase and achieved their maximal rates in fewer years. Decreasing soil nutrient availability and increasing belowground competition may become increasingly strong filters in successional communities, acting on root traits to promote a transition from acquisitive to conservative foraging. However, disturbances that increase light and soil resource availability at local scales may allow acquisitive species, especially invasive exotics, to continue colonizing late into the community transition to forest.