Tyler Smith

Leaf and Life History Traits Predict Plant Growth in a Green Roof Ecosystem

Green roof ecosystems are constructed to provide services such as stormwater retention and urban temperature reductions. Green roofs with shallow growing media represent stressful conditions for plant survival, thus plants that survive and grow are important for maximizing economic and ecological benefits. While field trials are essential for selecting appropriate green roof plants, we wanted to determine whether plant leaf traits could predict changes in abundance (growth) to provide a more general framework for plant selection. We quantified leaf traits and derived life-history traits (Grime’s C-S-R strategies) for 13 species used in a four-year green roof experiment involving five plant life forms. Changes in canopy density in monocultures and mixtures containing one to five life forms were determined and related to plant traits using multiple regression. We expected traits related to stress-tolerance would characterize the species that best grew in this relatively harsh setting. While all species survived to the end of the experiment, canopy species diversity in mixture treatments was usually much lower than originally planted. Most species grew slower in mixture compared to monoculture, suggesting that interspecific competition reduced canopy diversity. Species dominant in mixture treatments tended to be fast-growing ruderals and included both native and non-native species. Specific leaf area was a consistently strong predictor of final biomass and the change in abundance in both monoculture and mixture treatments. Some species in contrasting life-form groups showed compensatory dynamics, suggesting that life-form mixtures can maximize resilience of cover and biomass in the face of environmental fluctuations. This study confirms that plant traits can be used to predict growth performance in green roof ecosystems. While rapid canopy growth is desirable for green roofs, maintenance of species diversity may require engineering of conditions that favor less aggressive species.

flowPloidy: An R package for genome size and ploidy assessment of flow cytometry data

Premise of the Study Despite advantages in terms of reproducibility, histogram analysis based on nonlinear regression is rarely used in genome size assessments in plant biology. This is due in part to the lack of a freely available program to implement the procedure. We have developed such a program, the R package flowPloidy. Methods and Results flowPloidy builds on the existing statistical tools provided with the R environment. This base provides tools for importing flow cytometry data, fitting nonlinear regressions, and interactively visualizing data. flowPloidy adds tools for building flow cytometry models, fitting the models to histogram data, and producing visual and tabular summaries of the results. Conclusions flowPloidy fills an important gap in the study of plant genome size. This package will enable plant scientists to apply a more powerful statistical technique for assessing genome size. flowPloidy improves on existing software options by providing a no‐cost workflow streamlined for genome size and ploidy determination.

Development and characterization of 11 microsatellite primers for the sedge Trichophorum planifolium (Cyperaceae)

Premise of the study: Microsatellite loci were developed for Trichophorum planifolium (Cyperaceae), an endangered woodland sedge protected under federal and provincial legislation in Canada, to explore patterns of population genetic diversity and differentiation in the species. Methods and Results: Sixty-three primer pairs were evaluated for amplification consistency and screened for polymorphisms in 96 samples collected from 12 populations of T. planifolium distributed through the range of the species. Of these, 11 loci were shown to be polymorphic, displaying two to six alleles. Mean observed heterozygosity across loci ranged from 0.00 to 0.06 among populations tested. Conclusions: The results suggest that the 11 primer pairs developed in this study will be useful for future studies of broad-scale genetic variation in T. planifolium and in guiding management protocols for the species in Canada.