Evidence map›Paper›PMID 33038232›Full record

ArticleAnnals of botany2021

Intraspecific trait variability shapes leaf trait response to altered fire regimes.

Rachel M Mitchell, Greg M Ames, Justin P Wright

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Article in Annals of botany, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Rachel M MitchellSchool of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ, USA.
Greg M AmesDepartment of Biology, Duke University, Durham, NC, USA.
Justin P WrightDepartment of Biology, Duke University, Durham, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsUnderstanding impacts of altered disturbance regimes on community structure and function is a key goal for community ecology. Functional traits link species composition to ecosystem functioning. Changes in the distribution of functional traits at community scales in response to disturbance can be driven not only by shifts in species composition, but also by shifts in intraspecific trait values. Understanding the relative importance of these two processes has important implications for predicting community responses to altered disturbance regimes.

methodsWe experimentally manipulated fire return intervals in replicated blocks of a fire-adapted, longleaf pine (Pinus palustris) ecosystem in North Carolina, USA and measured specific leaf area (SLA), leaf dry matter content (LDMC) and compositional responses along a lowland to upland gradient over a 4 year period. Plots were burned between zero and four times. Using a trait-based approach, we simulate hypothetical scenarios which allow species presence, abundance or trait values to vary over time and compare these with observed traits to understand the relative contributions of each of these three processes to observed trait patterns at the study site. We addressed the following questions. (1) How do changes in the fire regime affect community composition, structure and community-level trait responses? (2) Are these effects consistent across a gradient of fire intensity? (3) What are the relative contributions of species turnover, changes in abundance and changes in intraspecific trait values to observed changes in community-weighted mean (CWM) traits in response to altered fire regime? KEY

resultsWe found strong evidence that altered fire return interval impacted understorey plant communities. The number of fires a plot experienced significantly affected the magnitude of its compositional change and shifted the ecotone boundary separating shrub-dominated lowland areas from grass-dominated upland areas, with suppression sites (0 burns) experiencing an upland shift and annual burn sites a lowland shift. We found significant effects of burn regimes on the CWM of SLA, and that observed shifts in both SLA and LDMC were driven primarily by intraspecific changes in trait values.

conclusionsIn a fire-adapted ecosystem, increased fire frequency altered community composition and structure of the ecosystem through changes in the position of the shrub line. We also found that plant traits responded directionally to increased fire frequency, with SLA decreasing in response to fire frequency across the environmental gradient. For both SLA and LDMC, nearly all of the observed changes in CWM traits were driven by intraspecific variation.

Indexed as

EcosystemFiresEcologyPhenotypePlant LeavesAristida strictacommunity-weighted meansdisturbanceecotonefireintraspecific variationlongleaf pinePinus palustrisspecific leaf area

Identifiers

PMID33038232
PMCPMC7988511

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.