In one paragraphArticle in Global change biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from itWhat it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
18 authors.
Houkun ChuKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0003-4577-3042 Jianyang XiaResearch Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China.ORCID 0000-0001-5923-6665 Ashley BallantyneDepartment of Ecosystem and Conservation Sciences, University of Montana, Missoula, Montana, USA.
Kailiang YuKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Zheng FuKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0001-7627-8824 Song WangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0001-6365-2258 Dashuan TianKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Qinyu ZhengKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0009-0004-7132-1642 Jiaqiang LiaoKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0001-6709-7394 Ronglei ZhouKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Qin ZhangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0009-0006-0476-8510 Yakov KuzyakovDepartment of Soil Science of Temperate Ecosystems, University of Goettingen, Göttingen, Germany.ORCID 0000-0002-9863-8461 Shuli NiuKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0002-2394-2864 Jinsong WangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0002-3425-7387 Guirui YuKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0002-1859-8966 Funding
China Postdoctoral Science Foundation 2025M772580China Postdoctoral Science Foundation GZC20241692"Kezhen-Bingwei" Young Talents 2022RC004National Natural Science Foundation of China 32241035National Natural Science Foundation of China 32401384National Natural Science Foundation of China 32501476National Natural Science Foundation of China 32588202
6 · The paper itselfAbstract
Ecosystem respiration (ER) often responds asymmetrically to seasonal warming and cooling, producing thermal hysteresis. Yet, its global patterns and drivers remain unknown. Here, we used daily ER data from 324 eddy-covariance sites worldwide and revealed two contrasting hysteresis patterns in the temperature response of ER: clockwise hysteresis (ER is higher during the warming than cooling season) at 173 sites and counterclockwise hysteresis (ER is higher during the cooling than warming season) at 151 sites. The direction and magnitude of ER hysteresis were largely governed by the seasonal timing mismatch between precipitation and vegetation-derived substrate availability. Higher substrate availability during the warming season enhanced ER and promoted clockwise hysteresis, whereas moisture limitation suppressed ER during the warming season and caused counterclockwise hysteresis. These findings provide robust evidence that ER is a complex process responding to the availability of carbon substrate and regulated differentially by seasonal temperature and precipitation. Our results highlight that the hysteresis of terrestrial carbon release is a key aspect of the global carbon cycle, with important implications for understanding and projecting land carbon-climate feedbacks.
Indexed as
Carbon CycleClimate ChangeEcosystemTemperatureSeasonscarbon cycleecosystem respirationseasonal hysteresissoil water availabilitytemperature sensitivity
Identifiers
PMID42563364
PMCPMC13447921
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