Abstract
Plant functional traits reflect individual and community ecological strategies. They allow the detection of directional changes in community dynamics and ecosystemic processes, being an additional tool to assess biodiversity than species richness. Analysis of functional patterns in plant communities provides mechanistic insight into biodiversity alterations due to anthropogenic activity. Although studies have consi‐dered of either anthropogenic management or nutrient availability on functional traits in temperate grasslands, studies combining effects of both drivers are scarce. Here, we assessed the impacts of management intensity (fertilization, mowing, grazing), nutrient stoichiometry (C, N, P, K), and vegetation composition on community‐weighted means (CWMs) and functional diversity (Rao's Q) from seven plant traits in 150 grasslands in three regions in Germany, using data of 6 years. Land use and nutrient stoichiometry accounted for larger proportions of model variance of CWM and Rao's Q than species richness and productivity. Grazing affected all analyzed trait groups; fertilization and mowing only impacted generative traits. Grazing was clearly associated with nutrient retention strategies, that is, investing in durable structures and production of fewer, less variable seed. Phenological variability was increased. Fertilization and mowing decreased seed number/mass variability, indicating competition‐related effects. Impacts of nutrient stoichiometry on trait syndromes varied. Nutrient limitation (large N:P, C:N ratios) promoted species with conservative strategies, that is, investment in durable plant structures rather than fast growth, fewer seed, and delayed flowering onset. In contrast to seed mass, leaf‐economics variability was reduced under P shortage. Species diversity was positively associated with the variability of generative traits. Synthesis. Here, land use, nutrient availability, species richness, and plant functional strategies have been shown to interact complexly, driving community composition, and vegetation responses to management intensity. We suggest that deeper understanding of underlying mechanisms shaping community assembly and biodiversity will require analyzing all these parameters.
Highlights
| METHODSOur study was part of the framework of the Biodiversity Exploratories, a large-s cale and long-t erm research project studying functional biodiversity (Fischer et al, 2010b)
Our study found functional composition (CWM) and functional diversity (FD via Rao′s quadratic entropy equation (Rao’s Q)) of specific plant functional traits to be significantly related to land use, nutrient stoichiometry, species richness, production of aboveground plant biomass, and edaphic factors across 150 temperate grasslands
Our analyses indicate that land use, nutrient availability, species richness, and plant functionality interact via a complex network
Summary
Our study was part of the framework of the Biodiversity Exploratories, a large-s cale and long-t erm research project studying functional biodiversity (Fischer et al, 2010b). Ordination analyses of trait CWM and Rao’s Q revealed complex gradients of functional characteristics, species diversity, land-u se intensity, and plant stoichiometry. Communities with large C:N and N:P ratios consisted of species with increased height variability, lower SLA, and larger LDMC values, producing bigger or heavier seed and flowering later in the year. 439.119 56.824 32.565 93.331 with higher and more variable SLA and seed mass values, whilst mean flowering duration was decreased These communities consisted of species with more similar seed number and flowering onset (Table 3). Species richness and biomass production explain a greater share of observed variance of trait Rao’s Q in generative traits and SLA, whereas land use and nutrient stoichiometry explain a greater share of observed variance in height, LDMC, and flowering duration. Whilst nutrient stoichiometry overall explained a larger proportion of variance in functional composition (CWM) and diversity (Rao’s Q) of leaf economics and generative traits, land use better explained the observed variance in functional composition and diversity in generative and phenological traits (Figure 5)
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