Is variation in inter-annual precipitation a mechanism for maintaining plant metabolic diversity?

Goud, Ellie M.; Prehmus, Sylvia K.; Sparks, Jed P.

doi:10.1007/s00442-021-05046-y

Cited by 4 publications

(5 citation statements)

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“…When variation in foliar δ 13 C is driven by stomatal conductance, enriched δ 13 C indicates stomatal closure which co‐limits CO 2 and water vapour diffusion. The combination of enriched δ 13 C, low φ , and small size in Carex canescens could indicate an ecological strategy to conserve water resources at the expense of carbon gain (Angert et al, 2009; Goud et al, 2021). On the other hand, Scirpus had the largest CO 2 and CH 4 flux rates and was also the largest, most light‐use efficient, and had relatively fast carbon metabolism (largest φ , depleted δ 13 C), indicating a strategy to maximize carbon gain across a range of light and water availabilities.…”

Section: Discussionmentioning

confidence: 99%

Graminoids vary in functional traits, carbon dioxide and methane fluxes in a restored peatland: Implications for modelling carbon storage

et al. 2022

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1. One metric of peatland restoration success is the re-establishment of a carbon sink, yet considerable uncertainty remains around the time-scale of carbon sink trajectories. Conditions post-restoration may promote the establishment of vascular plants such as graminoids, often at greater density than would be found in undisturbed peatlands, with consequences for carbon storage. Although graminoid species are often considered as a single plant functional type (PFT) in landatmosphere models, our understanding of functional variation among graminoid species is limited, particularly in a restoration context.2. We used a traits-based approach to evaluate graminoid functional variation and to assess whether different graminoid species should be considered a single PFT or multiple types. We tested hypotheses that greenhouse gas fluxes (CO 2 , CH 4 ) would vary due to differences in plant traits among five graminoid species in a restored peatland in central Alberta, Canada. We further hypothesized that species would form two functionally distinct groupings based on taxonomy (grass, sedge).3. Differences in gas fluxes among species primarily reflected variation in leaf physiology related to photosynthetic efficiency and resource-use, and secondarily by plant size. Multivariate analyses did not reveal distinct functional groupings based on taxonomy or environmental preferences. Rather, we identified functional groups defined by plant traits and carbon fluxes that are consistent with ecological strategies related to differences in growth rate, resource-acquisition and leaf economics, representing plants with either a strategy to grow quickly and invest in resource capture or to prioritize structural investment and resource conservation. These functional groups displayed larger average carbon fluxes compared to graminoid PFTs currently used in modelling. Synthesis.Existing PFT designations in peatland models may be more appropriate for pristine or high-latitude systems than those under restoration. Although replacing PFTs with plant traits remains a challenge in peatlands, traits related to leaf physiology and growth rate strategies offer a promising avenue for future applications.

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Section: Discussionmentioning

confidence: 99%

Graminoids vary in functional traits, carbon dioxide and methane fluxes in a restored peatland: Implications for modelling carbon storage

et al. 2022

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“…Contrary to expectations, the fastest growing plants were the most enriched in δ 13 C, which is typically associated with slower rates of leaf metabolism (Ellsworth et al, 2017; Farquhar et al, 1989; Goud et al, 2019). However, fast growth in combination with leaves relatively enriched in δ 13 C have been observed for other herbaceous plants (e.g., Asteraceae) when growth is achieved through adjusting biomass allocation rather than variation in individual leaf productivity (Goud et al, 2021). In support of this idea, milkweed species achieved faster growth by producing numerous large leaves and tall stems rather than adjusting leaf physiological performance.…”

Section: Discussionmentioning

confidence: 99%

“…In support of this idea, milkweed species achieved faster growth by producing numerous large leaves and tall stems rather than adjusting leaf physiological performance. Together, results for instantaneous leaf‐level gas exchange rates and δ 13 C suggest that the influence of leaf metabolism is often overwhelmed by differences in total plant leaf area and, therefore, does not consistently scale to whole‐plant growth (Agrawal et al, 2009; Goud et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…The species we studied were distributed along multivariate axes defined by traits, including LES, irrespective of variation in GR. In other words, plant size may define growth differences, while economics and metabolism may better differentiate between variation in plant ecology (i.e., niche preferences) and life history such as phenology (Goud et al, 2021). This finding is consistent with global analyses that found diversity in plant form and function to fall along two major axes of variation related to plant size and leaf economics (Dìaz et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

“…Some of these traits are expected to predict plant growth because they measure aspects of plant size, such as height, total leaf area (LA), root clonality, and seed mass (SM). For example, the total amount of LA available for photosynthesis can positively correlate with biomass accumulation (Goud et al, 2021; Weraduwage et al, 2015) and ecosystem carbon exchange (Goud et al, 2017; Stark et al, 2012; van Dijk et al, 2005). Root clonality may correspond to GR through increased vegetative reproduction and nutrient foraging ability (Keser et al, 2014; Klimešová & Martínková, 2004).…”

Section: Introductionmentioning

confidence: 99%

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A direct comparison of ecological theories for predicting the relationship between plant traits and growth

Goud

Agrawal

Sparks

2023

Ecology

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Despite long-standing theory for classifying plant ecological strategies, limited data directly links organismal traits to whole-plant growth. We compared trait-growth relationships based on three prominent theories: growth analysis, Grime's CSR triangle, and the leaf economics spectrum (LES). Under these schemes, growth is hypothesized to be predicted by traits related to biomass investments, leaf structure or gas exchange, respectively. In phylogenetic analyses of 30 diverse milkweeds (Asclepias spp.) and 21 morphological and ecophysiological traits, growth rate varied 50-fold and was best predicted by growth analysis and CSR traits, as well as total leaf area and plant height. Despite two LES traits correlating with growth, they contradicted predictions and leaf traits did not scale with root and stem characteristics. Thus, although combining leaf traits and whole-plant allocation best predicts growth, when destructive measures are not feasible, we suggest total leaf area and plant height, or easy-to-measure traits associated with the CSR classification.Predicting variation in plant growth is a long-standing problem in ecology. Because plants largely determine ecosystem productivity, estimating current and future plant growth is increasingly relevant as global change drivers impact ecosystem services 1,2 . As it is typically impractical to measure the total vegetative biomass of a community or ecosystem, an emerging method is to apply plant traits to predict growth rate. These trait-based approaches take advantage of a large body of literature that analyzes co-variation and trade-offs among plant traits [3][4][5][6] . Given that morphological and physiological characters are central to resource acquisition and allocation, they are likely to shape plant productivity in predictable ways. Three classic approaches have attempted to distill plant diversity into cohesive strategies and estimate growth based on defining characteristics: growth analysis, Grime's CSR triangle, and the leaf economics spectrum (Table 1). In growth analysis, growth rate is predicted by the relative allocation of biomass among roots, stems, and leaves 3,7 . Faster growing plants are expected to invest more in leaves relative to stems and roots. Due to the importance of leaf investment, growth rates are additionally dependent on specific leaf area (SLA), the ratio of leaf area to dry mass. Grime's CSR (competition-stress tolerant-ruderal) framework predicts that these three plant strategies have repeatedly evolved in response to combinations of stress and disturbance 8 . Until recently, the CSR framework was conceptual rather than empirically traitbased. However, Pierce et al. 2016 showed that three leaf traits were predictive of the scheme: average leaf surface area (individual leaf size, LS), SLA, and leaf dry matter content (LD). In this context, the C-strategy is defined by large LS and intermediate LD and SLA. The S-strategy has small LS and SLA with large LD, and R-strategy has small LS, small LD and large SLA 9 . The most commonly ap...

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Preface: honoring the career of Russell K. Monson

2021

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Is variation in inter-annual precipitation a mechanism for maintaining plant metabolic diversity?

Cited by 4 publications

References 36 publications

Graminoids vary in functional traits, carbon dioxide and methane fluxes in a restored peatland: Implications for modelling carbon storage

Graminoids vary in functional traits, carbon dioxide and methane fluxes in a restored peatland: Implications for modelling carbon storage

A direct comparison of ecological theories for predicting the relationship between plant traits and growth

Preface: honoring the career of Russell K. Monson

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