Abstract

AbstractQuestionIs valuable information lost when plant trait group composition is used, rather than species composition, to describe plant community response to range management?LocationElkhead Watershed, Colorado, US.MethodsCurrent model‐building efforts use species composition to define changes in ecosystem state, but plant traits may offer a faster and more broadly applicable alternative. We (1) compare states defined by species composition to those defined by trait‐based groups of differing complexity and (2) determine how management and environmental site characteristics relate to species‐ and trait group‐defined states. We sampled 72 plots with different grazing and chemical shrub treatment histories on two soil types. We measured plant species composition in each plot and categorized species into trait groups using three classification schemes, which represented increasing numbers of traits and levels of classification complexity. The classifications employed easily measured traits that affect plant response to range management: life form, life history, resprouting ability, height, vegetative reproduction and N‐fixation. Using hierarchical cluster analysis, we identified states with similar species or trait group composition. We explored relationships between each set of potential states and management history and environmental factors using logistic regression.ResultsTrait‐based group composition and species composition identified many of the same potential states and responses to grazing and chemical shrub treatment. Relationships between species and trait group composition and management and environmental characteristics differed on the two soil types. Species composition was sensitive to more different management practices, on average, than trait group composition. Trait group composition revealed some relationships to management and environmental drivers that were not detected using species composition.ConclusionThis study confirms that species composition is a more sensitive indicator of sagebrush steppe response to range management, and some information is lost with a trait‐based approach. However, traits also add to depth of understanding by revealing additional community patterns related to different drivers. Using the most complex trait grouping scheme that is feasible in a particular study, and also looking for patterns based on simpler trait groups, will provide the most complete understanding of sagebrush steppe response to range management.

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