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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Rangeland Resources & Systems Research » Research » Publications at this Location » Publication #388192

Research Project: Adaptive Grazing Management and Decision Support to Enhance Ecosystem Services in the Western Great Plains

Location: Rangeland Resources & Systems Research

Title: Plant availability dictates how plant traits predict demographic rates

Author
item STEARS, ALICE - University Of Wyoming
item ADLER, PETER - Utah State University
item Blumenthal, Dana
item Kray, Julie
item MUELLER, KEVIN - Cleveland State University
item OCHELTREE, TROY - Colorado State University
item WILCOX, KEVIN - University Of Wyoming
item LAUGHLIN, DANIEL - University Of Wyoming

Submitted to: Ecology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/21/2022
Publication Date: 7/27/2022
Citation: Stears, A., Adler, P.B., Blumenthal, D.M., Kray, J.A., Mueller, K., Ocheltree, T., Wilcox, K., Laughlin, D. 2022. Plant availability dictates how plant traits predict demographic rates. Ecology. Article e3799. https://doi.org/10.1002/ecy.3799.
DOI: https://doi.org/10.1002/ecy.3799

Interpretive Summary: Plant traits can provide insight into how different species respond to environmental challenges, such as drought. However, the connections between traits and plant population responses are poorly understood. We used 15 years of demographic data, species-level trait measurements, and climate records in a shortgrass steppe ecosystem in Colorado to determine whether traits interact with drought to impact growth and survival. Plants with physiological and structural drought-tolerance traits did have higher survival in dry years, but also had lower growth rates in both wet and dry years. These results demonstrate that easy-to-measure traits that can be used to predict species survival during drought and to improve management of plant communities for drought resistance.

Technical Abstract: 1. Characterizing how plant traits mediate demographic responses to abiotic conditions may provide a mechanistic explanation of species responses to environmental variation. This is critical for understanding how drought, which will become more frequent and intense with global change, impacts plant communities and ecosystem services. We predicted that (1) species with low leaf turgor loss point (TLP) and high leaf and root dry matter content (LDMC and RDMC) would be more likely to survive and grow in dry years because of higher wilting resistance, and (2) these traits would weakly predict growth and survival in wet years. (3) Traits related to water use that most directly measure physiological mechanisms would predict demographic responses better than traits less directly related to water use. 2. We synthesized 15 years of demographic data, species-level trait measurements, and climate records in a shortgrass steppe ecosystem in Colorado. We fit generalized linear mixed effect models to determine whether traits interact with drought to impact growth and survival while accounting for plant size and intraspecific competition. 3. Plant size positively affected survival, and local intraspecific competition negatively affected growth and survival across all species. Graminoids with more negative TLP and higher LDMC and RDMC had higher survival rates in dry years. However, graminoids with less negative TLP and lower LDMC and RDMC were larger than species with high TLP, low LDMC and RDMC, in both wet and dry years. Forbs demonstrated similar yet more variable responses to drought. 4. Synthesis Traits that dictate the nature of a plant’s physiological response to drought mediate the effects of abiotic variation on demographic rates. Traits significantly mediated the impact of drought on survival, but not on growth, indicating that survival could be the primary demographic driver of species’ drought response in this system. TLP was a good predictor of survival in response to drought, but the easier-to-measure morphological traits LDMC and RDMC were equal or better predictors. These results advance our understanding of the mechanisms by which drought drives plant population dynamics, and will refine our predictions of how plant communities will respond to more intense and frequent drought.