| Literature DB >> 24978031 |
Jeremy Lundholm1, Amy Heim1, Stephanie Tran1, Tyler Smith2.
Abstract
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.Entities:
Mesh:
Year: 2014 PMID: 24978031 PMCID: PMC4076323 DOI: 10.1371/journal.pone.0101395
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
A list of all the species used in this experiment including their growth form, the treatments they were used in and their origin.
| Species | Code | Growth Form | Treatments | Origin |
|
| Sag. p | Creeping Forb (C) | Mono., C, C/T/S, G/C/S, G/C/T, D/C/S, D/C/T, D/G/S, All | Native |
|
| Dan. s | Graminoid (G) | Mono., G, G/C/S, G/C/T, G/T/S, D/G/S, D/G/T, D/G/C, All | Native |
|
| Des. f | Graminoid (G) | Mono., G, G/C/S, G/C/T, G/T/S, D/G/S, D/G/T, D/G/C, All | Native |
|
| Poa. C | Graminoid (G) | Mono., G, G/C/S, G/C/T, G/T/S, D/G/S, D/G/T, D/G/C, All | Introduced |
|
| Emp. n | Creeping Shrub (D) | Mono., D, D/C/S, D/C/T, D/G/C, D/G/S, D/G/T, D/T/S, All | Native |
|
| Gau. p | Creeping Shrub (D) | Mono., D, D/C/S, D/C/T, D/G/C, D/G/S, D/G/T, D/T/S, All | Native |
|
| Vac. v | Creeping Shrub (D) | Mono., D, D/C/S, D/C/T, D/G/C, D/G/S, D/G/T, D/T/S, All | Native |
|
| Sed. a | Succulents (S) | Mono., S, C/T/S, G/C/S, G/T/S, D/C/S, D/G/S, D/T/S, All | Introduced |
|
| Sed. r | Succulents (S) | Mono., S, C/T/S, G/C/S, G/T/S, D/C/S, D/G/S, D/T/S, All | Native |
|
| Sed. s | Succulents (S) | Mono., S, C/T/S, G/C/S, G/T/S, D/C/S, D/G/S, D/T/S, All | Introduced |
|
| Cam. r | Tall Forbs (T) | Mono., T, G/T/S, D/G/T, D/T/S, G/C/T, D/C/T, C/T/S, All | Native |
|
| Pla. m | Tall Forbs (T) | Mono., T, G/T/S, D/G/T, D/T/S, G/C/T, D/C/T, C/T/S, All | Native |
|
| Sol. b | Tall Forbs (T) | Mono., T, G/T/S, D/G/T, D/T/S, G/C/T, D/C/T, C/T/S, All | Native |
Mono. refers to the treatment planted with the species in monoculture; Nomenclature follows [Zinck 1998].
Figure 1Canopy species richness (A) and evenness (B) over four years (means±95% CI).
Treatments grouped by number of life-forms planted; original planted species richness was 3, 9, 15 for 1, 3, and 5 life-form groups respectively. Species evenness is 1/Simpson’s index. Sample sizes: 1 life-form treatements: n = 25; 3 life-form treatments: n = 50; 5 life-form treatment: n = 20.
Figure 2Canopy species richness (A) and evenness (B) in year four, by specific life-form combination (means±95% CI).
Sample sizes: 1 life-form treatments: n = 5 each; 3 life-form treatments: n = 5 each; 5 life-form treatment: n = 20.
Rainfall recorded at green roof site.
| Date Range | Total Rainfall |
| June 12-August 31, 2008 | 298.2 |
| June 12-August 31, 2009 | 349.9 |
| June 12-August 31, 2010 | 236.1 |
| April 1-August 31, 2009 | 639.7 |
| April 1-August 31, 2010 | 357.6 |
*Tipping bucket (TE525M, Campbell Scientific, Edmonton, AB) mounted 4 m above roof surface (installed June 2008).
Figure 3Change in abundance of 13 species in monoculture and mixtures over four years (mean±95% CI).
Change in abundance calculated using canopy density: (ln(canopy density in year 4) - ln(canopy density in year 1))/# days. A: D. spicata; B: S. acre; C: C. rotundifolia; D: E. nigrum; E: D. flexuosa; F: S. rosea; G: P. maritima; H: G. procumbens; I: S. procumbens; J: P. compressa; K: S. spurium; L: S. bicolor; M: V. vitis-idaea. In each panel, the farthest left bar is the monoculture; mixture life form codes: C = creeping forb; D = dwarf shrub; G = grass; S = succulent; T = tall forb. Sample sizes: 1 life-form treatments: n = 5; 3 life-form treatments: n = 5; 5 life-form treatment: n = 20.
Figure 4Principal components analysis of species, by leaf traits and life history variables.
Species abbreviations: Poa = P. compressa; Des = D. flexuosa; Dan = D. spicata; Traits in red: SLA = specific leaf area; LA = leaf area; LDMC = leaf dry matter content; HGT = plant height; R = ruderal score; S = stress-tolerance score; C = competitive score.
Multiple linear regression showing standardized coefficients from model averaging for final biomass and change in abundance in monoculture and five life-form treatments.
| Dependent Variable | Predictors | Model Averagedβ Coefficient | 95% ConfidenceInterval Lower bound | 95% ConfidenceInterval Upper bound |
|
|
| 0.73 | 0.30 | 1.16 |
|
| −0.11 | −0.57 | 0.35 | |
|
| 0.09 | −0.36 | 0.54 | |
|
| 0.41 | −0.22 | 1.03 | |
|
| 0.63 | 0.16 | 1.04 | |
|
| −0.43 | −0.94 | 0.07 | |
|
| −0.19 | −0.68 | 0.30 | |
|
|
| 0.39 | −0.03 | 0.81 |
|
| 0.02 | −0.49 | 0.53 | |
|
| −0.25 | −0.76 | 0.25 | |
|
| 0.24 | −0.54 | 1.03 | |
|
| 0.68 | 0.18 | 1.18 | |
|
| −0.61 | −1.15 | −0.07 | |
|
| 0.04 | −0.49 | 0.58 | |
|
|
| 0.76 | 0.29 | 1.23 |
|
| 0.10 | −0.43 | 0.64 | |
|
| −0.60 | −1.10 | −0.09 | |
|
| 0.53 | −0.07 | 1.14 | |
|
| 0.53 | 0.11 | 0.94 | |
|
| −0.61 | −1.14 | −0.07 | |
|
| 0.21 | −0.31 | 0.73 | |
|
|
| 0.48 | 0.02 | 0.94 |
|
| 0.37 | −0.19 | 0.94 | |
|
| −0.14 | −0.75 | 0.48 | |
|
| 0.30 | −0.57 | 1.18 | |
|
| 0.63 | 0.09 | 1.16 | |
|
| −0.62 | −1.18 | −0.06 | |
|
| −0.07 | −0.69 | 0.55 |