2021
DOI: 10.1111/nph.17279
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Fine‐root functional trait responses to experimental warming: a global meta‐analysis

Abstract: Whether and how warming alters functional traits of absorptive plant roots remains to be answered across the globe. Tackling this question is crucial to better understanding terrestrial responses to climate change as fine-root traits drive many ecosystem processes.We carried out a detailed synthesis of fine-root trait responses to experimental warming by performing a meta-analysis of 964 paired observations from 177 publications.Warming increased fine-root biomass, production, respiration and nitrogen concentr… Show more

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Cited by 88 publications
(70 citation statements)
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References 84 publications
(110 reference statements)
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“…Our result has been confirmed globally in a meta-analysis, demonstrating that soil warming increases fine root biomass production and FRB by 30% and 9%, respectively (Wang et al, 2021).…”
Section: Effects Of Soil Warming On Fine Root Biomasssupporting
confidence: 75%
See 1 more Smart Citation
“…Our result has been confirmed globally in a meta-analysis, demonstrating that soil warming increases fine root biomass production and FRB by 30% and 9%, respectively (Wang et al, 2021).…”
Section: Effects Of Soil Warming On Fine Root Biomasssupporting
confidence: 75%
“…The effect of soil warming on fine root dynamics and root‐associated bacterial–fungal communities in forests has largely remained unresolved, as most studies were short in terms of duration and differed in experimental approaches (Wang et al, 2021; Yuan et al, 2018). The long‐term forest soil warming experiment at Achenkirch in the Austrian alps, where regional climate models predict an above‐average increase in temperature (up to 3.3°C at the end of the 21st century) as compared to global average warming (Gobiet et al, 2014; Smiatek et al, 2009), offers an excellent opportunity to increase our understanding of how soil warming affects FRB, fine root production, fine root morphology, and root‐associated bacterial and fungal communities in temperate forests.…”
Section: Introductionmentioning
confidence: 99%
“…the negative effect of the warming treatment on root dynamics could have resulted from direct effects of increased temperature on physiological function (e.g., affecting carbon supply to roots or metabolic processes in roots) or from indirect effects on the soil chemical, biological, or physical environment (e.g., altered nutrient availability, microbial activity, or soil water content) (Reed et al, 2020). Other experiments have reported increased root production in response to imposed warming (Fitter et al, 1999;Forbes et al, 1997;Malhotra et al, 2020;Wan et al, 2004;Wang et al, 2021), but they were all located in temperate or boreal biomes (Cavaleri et al, 2015;Rustad et al, 2001) where temperatures reach below freezing and precipitation is usually no greater than 9.5 mm day −1 (Whitaker, 1975). Air temperatures at our study site in Puerto Rico fluctuate between 23°C (February) and 27°C (October), and rainfall is generally not limiting plant growth (annual average 8-12 mm day −1 ; ; hence, the temperature effects on plant-soil feedbacks are distinct from higher latitude ecosystems (Balser & Wixon, 2009).…”
Section: Responses Of Root Dynamics To the Warming Treatmentmentioning
confidence: 99%
“…Others show an increase in root production that is possibly due to enhanced nutrient availability or photosynthesis stimulation (Majdi & Öhrvik, 2004;Malhotra et al, 2020;Pugnaire et al, 2019;Wan et al, 2004;Wang et al, 2021;Zhou et al, 2012), or no response in root dynamics to soil warming (Dukes et al, 2005). However, most manipulative warming studies have focused on single-factor experiments, mostly in temperate and boreal ecosystems, with highly variable results (Norby et al, 2004;Zhou et al, 2012).…”
Section: Introductionmentioning
confidence: 99%
“…There can be no reproducibility without reuse, depending on the definition of the latter, but the benefits of reuse extend beyond reproducibility, to meta-analyses (e.g. Chivenge et al, 2011;Poorter et al, 2012;J. Wang et al, 2021), novel insight generation through data integration (e.g.…”
Section: Data-related Challengesmentioning
confidence: 99%