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Abstract Grasslands are subject to climate change, such as severe drought, and an important aspect of their functioning is temporal stability in response to extreme climate events. Previous research has explored the impacts of extreme drought and post‐drought periods on grassland stability, yet the mechanistic pathways behind these changes have rarely been studied.Here, we implemented an experiment with 4 years of drought and 3 years of recovery to assess the effects of drought and post‐drought on the temporal stability of above‐ground net primary productivity (ANPP) and its underlying mechanisms. To do so, we measured community‐weighted mean (CWM) of six plant growth and nine seed traits, functional diversity, population stability and species asynchrony across two cold, semiarid grasslands in northern China. We also performed piecewise structural equation models (SEMs) to assess the relationships between ANPP stability and its underlying mechanisms and how drought and post‐drought periods alter the relative contribution of these mechanisms to ANPP stability.We found that temporal stability of ANPP was not reduced during drought due to grasses maintaining productivity, which compensated for increased variation of forb productivity. Moreover, ANPP recovered rapidly after drought, and both grasses and forbs contributed to community stability during the post‐drought period. Overall, ANPP stability decreased during the combined drought and post‐drought periods because of rapid changes in ANPP from drought to post‐drought. SEMs revealed that the temporal stability of ANPP during drought and post‐drought periods was modulated by functional diversity and community‐weighted mean traits directly and indirectly by altering species asynchrony and population stability. Specifically, the temporal stability of ANPP was positively correlated with functional divergence of plant communities. CWMs of seed traits (e.g. seed width and thickness), rather than plant growth traits (e.g. specific leaf area and leaf nutrient content), stabilized grassland ANPP. Productivity of plant communities with large and thick seeds was less sensitive to precipitation changes over time.These results emphasize the importance of considering both the functional trait distribution among species and seed traits of dominant species since their combined effects can stabilize ecosystem functions under global climate change scenarios. Read the freePlain Language Summaryfor this article on the Journal blog.
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Plant functional traits are dynamic predictors of ecosystem functioning in variable environments
Abstract A central goal at the interface of ecology and conservation is understanding how the relationship between biodiversity and ecosystem function (B–EF) will shift with changing climate. Despite recent theoretical advances, studies which examine temporal variation in the functional traits and mechanisms (mass ratio effects and niche complementarity effects) that underpin the B–EF relationship are lacking.Here, we use 13 years of data on plant species composition, plant traits, local‐scale abiotic variables, above‐ground net primary productivity (ANPP), and climate from the alpine tundra of Colorado (USA) to investigate temporal dynamics in the B–EF relationship. To assess how changing climatic conditions may alter the B–EF relationship, we built structural equation models (SEMs) for 11 traits across 13 years and evaluated the power of different trait SEMs to predict ANPP, as well as the relative contributions of mass ratio effects (community‐weighted mean trait values; CWM), niche complementarity effects (functional dispersion; FDis) and local abiotic variables. Additionally, we coupled linear mixed effects models with Multimodel inference methods to assess how inclusion of trait–climate interactions might improve our ability to predict ANPP through time.In every year, at least one SEM exhibited good fit, explaining between 19.6% and 57.2% of the variation in ANPP. However, the identity of the trait which best explained ANPP changed depending on winter precipitation, with leaf area, plant height and foliar nitrogen isotope content (δ15N) SEMs performing best in high, middle and low precipitation years, respectively. Regardless of trait identity, CWMs exerted a stronger influence on ANPP than FDis and total biotic effects were always greater than total abiotic effects. Multimodel inference reinforced the results of SEM analysis, with the inclusion of climate–trait interactions marginally improving our ability to predict ANPP through time.Synthesis. Our results suggest that temporal variation in climatic conditions influences which traits, mechanisms and abiotic variables were most responsible for driving the B–EF relationship. Importantly, our findings suggest that future research should consider temporal variability in the B–EF relationship, particularly how the predictive power of individual functional traits and abiotic variables may fluctuate as conditions shift due to climate change.
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- Award ID(s):
- 2224439
- PAR ID:
- 10556435
- Publisher / Repository:
- John Wiley & Sons Ltd
- Date Published:
- Journal Name:
- Journal of Ecology
- Volume:
- 111
- Issue:
- 12
- ISSN:
- 0022-0477
- Page Range / eLocation ID:
- 2597 to 2613
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1111/1365-2745.14197
