Abstract

Relationships between functional leaf traits across large sets of plant species emphasized the existence of a major axis describing a trade-off between rapid acquisition and conservation of resources forming the so-called “leaf economics spectrum”. It is uncertain which environmental factors determine the economics spectrum and whether traits associated with reproduction co-vary with the economics spectrum. To determine these trait–environment relationships for agricultural ecosystems, this study was conducted at field, pasture, and heathland sites forming a strong land use gradient in Northwest Germany. The abundance of 49 species was recorded in 85 plots together with their traits (canopy height, specific leaf area, leaf N, leaf N:P, leaf and stem dry matter content, life cycle, reproductive investment (RI) in seed mass and seed number), as well as parameters describing soil resources and land use disturbances. RLQ multivariate analysis of the data set related an environmental table to a species trait table using a species abundance table to extract the joint structure between them. Thereafter, we clustered the species on the RLQ axis to extract functional groups. Traits associated with the leaf economics spectrum were strongly related to soil resources that co-varied with disturbance intensity. A division of the whole land use gradient into agricultural and heathland sites showed that RI was not decoupled from trait–environment relationships although the direction of the RI–environment relationship was opposite in the two subsets. Species were clumped rather than linearly arranged in the trait–environment space and the functional groups broadly corresponded to weed communities, pastures with differing intensities, and heathlands. The trade-off in plant economics responding to soil resources supports predictions of previous theoretical and empirical work. Different RI–environment relationships in agricultural sites and heathlands emphasize the relevance of local scales in trait–environment studies. In general, the results point to some of the biological mechanisms controlling functions and services of agricultural ecosystems.

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