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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Publications at this Location » Publication #388878

Research Project: Contributions of Climate, Soils, Species Diversity, and Management to Sustainable Crop, Grassland, and Livestock Production Systems

Location: Grassland Soil and Water Research Laboratory

Title: Community leaf dry matter content predicts plant production in simple and diverse grassland

Author
item Polley, Wayne
item Collins, Harold
item Fay, Philip

Submitted to: Ecosphere
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/3/2022
Publication Date: 5/13/2022
Citation: Polley, H.W., Collins, H.P., Fay, P.A. 2022. Community leaf dry matter content predicts plant production in simple and diverse grassland. Ecosphere. 13(5). Article e4076. https://doi.org/10.1002/ecs2.4076.
DOI: https://doi.org/10.1002/ecs2.4076

Interpretive Summary: Plant biomass production correlates with the values of leaf traits. Plants that grow rapidly typically have low values of leaf dry matter content (LDMC; ratio of leaf dry mass to leaf saturated mass) and high leaf and plant nitrogen concentration ([N]). However, there is evidence that the strength of production-trait relationships and sensitivity of plant production to change in leaf traits depends on environmental conditions and the species composition of plant communities. Large environmental or compositional effects would limit the consistency of trait-based predictions of biomass production. We tested effects of interannual variation in precipitation and differences in plant community composition (simple monoculture vs. diverse species mixture) on relationships between aboveground biomass production of grassland and two traits, LDMC and plant [N]. Biomass production and traits were derived from remote measurements of surface reflectance of sunlight. We found that grassland production varied in space and time mainly because community LDMC varied. However, both the strength of production-trait relationships and sensitivity of plant production to trait variation depended on precipitation and plant community composition. Greater precipitation increased the production response to trait change. Precipitation effects on production-trait relationships differed between communities. We conclude that trait-based predictions of grassland biomass production can be improved by incorporating variation linked to precipitation and plant community composition.

Technical Abstract: Plant growth correlates with values of collinear (covarying) traits from the leaf economics spectrum (LES). Environmental variation and differences in community composition may alter contributions of LES traits to plant production and thereby limit the consistency of trait-based growth predictions among years and plant communities. We tested effects of interannual variation (IAV) in precipitation and differences in grassland community composition (planted monoculture of switchgrass, Panicum virgatum, and mixture of perennial herbaceous species) on the utility of two traits from the LES (leaf dry matter content (LDMC) and plant [N]) to predict aboveground net primary production (ANP) during spring of 6 years. Spatial and temporal variation in spring ANP correlated with community-scale (species-abundance weighted) values of both traits, but community LDMC explained most of the variance in ANP. The ANP response to trait variation and the variance in ANP explained by trait values differed with precipitation and between communities, however. Greater precipitation increased the ANP response to trait variation by increasing slopes of ANP-trait regression relationships and increased the variance in ANP explained by trait values. Communities differed in response to precipitation variation and in the role of IAV in the [N]-LDMC relationship in explaining variance in ANP. Results indicate that mean trends in grassland ANP can be predicted using community-scale values of traits associated with the LES. Trait-based predictions of grassland production could be improved, however, by accommodating precipitation and community effects on ANP-trait relationships.