Shifts in aboveground biomass allocation patterns of dominant shrub species across a strong environmental gradient

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Abstract

Most plant biomass allocation studies have focused on allocation to shoots versus roots, and little is known about drivers of allocation for aboveground plant organs. We explored the drivers of within-and between-species variation of aboveground biomass allocation across a strong environmental resource gradient, i.e., a long-term chronosequence of 30 forested islands in northern Sweden across which soil fertility and plant productivity declines while light availability increases. For each of the three coexisting dominant understory dwarf shrub species on each island, we estimated the fraction of the total aboveground biomass produced year of sampling that was allocated to sexual reproduction (i.e., fruits), leaves and stems for each of two growing seasons, to determine how biomass allocation responded to the chronosequence at both the within-species and whole community levels. Against expectations, within-species allocation to fruits was least on less fertile islands, and allocation to leaves at the whole community level was greatest on intermediate islands. Consistent with expectations, different coexisting species showed contrasting allocation patterns, with the species that was best adapted for more fertile conditions allocating the most to vegetative organs, and with its allocation pattern showing the strongest response to the gradient. Our study suggests that co-existing dominant plant species can display highly contrasting biomass allocations to different aboveground organs within and across species in response to limiting environmental resources within the same plant community. Such knowledge is important for understanding how community assembly, trait spectra, and ecological processes driven by the plant community vary across environmental gradients and among contrasting ecosystems.

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  • Table 1. Summary of a three-way Analysis of Variance (F and P values) testing the effect of species, year, island size class and their interactive effects on different biomass allocation response variables; RA, LMF and SMF are the proportion of total shoot biomass produced in the growing season allocated to fruits, leaves and stems, respectively, and shoot turnover is the proportion of total shoot biomass produced in the growing season. Figures in bold indicate statistical significant at P < 0.05.
  • Fig 1. Biomass allocations of the 3 shrubs species, V.myrtillus (Vm), V. vitis idaea (Vv) and E. hermaphroditum (Eh) to different plant organs and their community weightedmean values (CWA) across the island size S, M and L are small, medium and large islands respectively; N = 10 islands of each.Within each group of three bars in each panel, bars topped by the same lower case letter are not significantly different from each other, and groups of three bars topped by the same capital letter are not significantly different among groups (P = 0.05; Tukey’s test).
  • Fig 2. Annual shoot biomass turnover of the 3 shrubs species, V.myrtillus (Vm), V. vitis idaea (Vv) and E. hermaphroditum (Eh) in (a) 2012 and (b) 2013, and their community weightedmean values (CWA) across the island size classes S, M and L are small, medium and large islands respectively; N = 10 islands of each.Within each group of three bars in each panel, bars topped by the same lower case letter are not significantly different from each other, and groups of three bars topped by the same capital letter are not significantly differences among groups (P = 0.05; Tukey’s test).
  • Table 2. Summary of a two-way Analysis of Variance (F and P values) testing the effect of island size class, year, and their interactive effects on different community-weighted biomass allocation response variables. RA, LMF and SMF are the proportion of total shoot biomass produced in the growing season allocated to fruits, leaves and stems, respectively, and shoot turnover is the proportion of total shoot biomass produced in the growing season. Figures in bold indicate statistical significant at P < 0.05.
  • Fig 3. The relationships between community-weighted averages of dwarf shrub biomass allocation response variables (reproductive allocation, leaf mass fraction, and stemmass fraction) and net primary productivity for 2012 and light availability for 2013 across the 30 islands.
  • Table 3. Results frommultiple stepwise regression testing relationships between species biomass allocation responses and environmental variables for 2012. For each response variable the most parsimonious model is presented based on Akaike Information Criteria (AIC). Values of t are shown for each selected response variable, along with adjusted R2 and P values for the regression models. For each of the response variables, the presented models contain only those variables for which t-values are shown.

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APA

Kumordzi, B. B., Gundale, M. J., Nilsson, M. C., & Wardle, D. A. (2016). Shifts in aboveground biomass allocation patterns of dominant shrub species across a strong environmental gradient. PLoS ONE, 11(6). https://doi.org/10.1371/journal.pone.0157136

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