Changes in above- versus belowground biomass distribution in permafrost regions in response to climate warming DOI Creative Commons
Hanbo Yun, Philippe Ciais, Qing Zhu

и другие.

Proceedings of the National Academy of Sciences, Год журнала: 2024, Номер 121(25)

Опубликована: Июнь 10, 2024

Permafrost regions contain approximately half of the carbon stored in land ecosystems and have warmed at least twice as much any other biome. This warming has influenced vegetation activity, leading to changes plant composition, physiology, biomass storage aboveground belowground components, ultimately impacting ecosystem balance. Yet, little is known about causes magnitude long-term above- ratio plants (η). Here, we analyzed η values using 3,013 plots 26,337 species-specific measurements across eight sites on Tibetan Plateau from 1995 2021. Our analysis revealed distinct temporal trends for three types: a 17% increase alpine wetlands, decrease 26% 48% meadows steppes, respectively. These were primarily driven by temperature-induced growth preferences rather than shifts species composition. findings indicate that wetter ecosystems, climate promotes growth, while drier such allocate more belowground. Furthermore, observed threefold strengthening effect over past 27 y. Soil moisture was found modulate sensitivity soil temperature but not wetlands. results contribute better understanding processes driving response distribution warming, which crucial predicting future trajectory permafrost feedback.

Язык: Английский

Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022 DOI Creative Commons
Muyi Li, Sen Cao, Zaichun Zhu

и другие.

Earth system science data, Год журнала: 2023, Номер 15(9), С. 4181 - 4203

Опубликована: Сен. 25, 2023

Abstract. Global products of remote sensing Normalized Difference Vegetation Index (NDVI) are critical to assessing the vegetation dynamic and its impacts feedbacks on climate change from local global scales. The previous versions Inventory Modeling Mapping Studies (GIMMS) NDVI product derived Advanced Very High Resolution Radiometer (AVHRR) provide biweekly data starting 1980s, being a reliable long-term time series that has been widely applied in Earth environmental sciences. However, GIMMS have several limitations (e.g., orbital drift sensor degradation) cannot continuous for future. In this study, we presented machine learning model employed massive high-quality Landsat samples consolidation method generate new version product, i.e., PKU (1982–2022), based AVHRR Moderate-Resolution Imaging Spectroradiometer (MODIS) data. A total 3.6 million were well spread across globe extracted biomes all seasons. exhibits higher accuracy than predecessor (GIMMS NDVI3g) terms R2 (0.97 over 0.94), root mean squared error (RMSE: 0.05 0.09), absolute (MAE: 0.03 0.07), percentage (MAPE: 9 % 20 %). Notably, effectively eliminates evident degradation effects tropical areas. consolidated high consistency with MODIS pixel value (R2 = 0.956, RMSE 0.048, MAE 0.034, MAPE 6.0 %) trend (0.9×10-3 yr−1). can potentially more solid basis studies. theoretical framework employs facilitate generation other land surface parameters. is open access available under Creative Commons Attribution 4.0 License at https://doi.org/10.5281/zenodo.8253971 (Li et al., 2023).

Язык: Английский

Процитировано

91
Persistent and enhanced carbon sequestration capacity of alpine grasslands on Earth’s Third Pole DOI Creative Commons
Yuyang Wang, Jingfeng Xiao, Yaoming Ma

и другие.

Science Advances, Год журнала: 2023, Номер 9(20)

Опубликована: Май 17, 2023

The carbon sequestration capacity of alpine grasslands, composed meadows and steppes, in the Tibetan Plateau has an essential role regulating regional cycle. However, inadequate understanding its spatiotemporal dynamics regulatory mechanisms restricts our ability to determine potential climate change impacts. We assessed spatial temporal patterns net ecosystem exchange (NEE) dioxide Plateau. grasslands ranged from 26.39 79.19 Tg C year-1 had increasing rate 1.14 between 1982 2018. While were relatively strong sinks, semiarid arid steppes nearly neutral. Alpine meadow areas experienced increases mainly because temperatures, while steppe weak due precipitation. Carbon on plateau undergone persistent enhancement under a warmer wetter climate.

Язык: Английский

Процитировано

81
Spring photosynthetic phenology of Chinese vegetation in response to climate change and its impact on net primary productivity DOI
Yingying Xue, Xiaoyong Bai,

Cuiwei Zhao

и другие.

Agricultural and Forest Meteorology, Год журнала: 2023, Номер 342, С. 109734 - 109734

Опубликована: Сен. 27, 2023

Язык: Английский

Процитировано

65
Satellite remote sensing of vegetation phenology: Progress, challenges, and opportunities DOI
Zheng Gong, Wenyan Ge, Jiaqi Guo

и другие.

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2024, Номер 217, С. 149 - 164

Опубликована: Авг. 29, 2024

Язык: Английский

Процитировано

26
Impacts of cascade dam construction on riparian vegetation in an alpine region DOI
Yihang Wang,

Nan Cong,

Yu Zhong

и другие.

Journal of Hydrology, Год журнала: 2025, Номер 652, С. 132665 - 132665

Опубликована: Янв. 4, 2025

Язык: Английский

Процитировано

3
Increased precipitation leads to earlier green-up and later senescence in Tibetan alpine grassland regardless of warming DOI
Pengfei Ma, Jingxue Zhao,

Haoze Zhang

и другие.

The Science of The Total Environment, Год журнала: 2023, Номер 871, С. 162000 - 162000

Опубликована: Фев. 3, 2023

Язык: Английский

Процитировано

36
Wet bias of summer precipitation in the northwestern Tibetan Plateau in ERA5 is linked to overestimated lower-level southerly wind over the plateau DOI Creative Commons
Tinghai Ou, Deliang Chen, Jianping Tang

и другие.

Climate Dynamics, Год журнала: 2023, Номер 61(5-6), С. 2139 - 2153

Опубликована: Янв. 16, 2023

Abstract The Tibetan Plateau (TP), also called the Third Pole, is considered to be “the world water tower”. northwestern TP (NWTP), which has an average elevation higher than 4800 m, arid region where summer precipitation largely overestimated by ERA5 global reanalysis product. We hypothesize that this wet bias mainly caused unrealistic lower-level winds trigger strong convection over region; it can reduced using a high-resolution regional climate model with large domain allows realistically representing interactions between Westerlies and Asian monsoons. Here, downscaling Weather Research Forecasting (WRF) driven was conducted (8°‒50° N, 65°‒125° E) at 9 km for period 1979‒2019 (WRF9km). Precipitation values from WRF9km were evaluated against satellite observations; compared ERA5, captured climatological NWTP much-reduced bias. overestimation excessive convective precipitation, likely linked vertical motions induced southerly wind.

Язык: Английский

Процитировано

31
Deep learning reveals rapid vegetation greening in changing climate from 1988 to 2018 on the Qinghai-Tibet Plateau DOI Creative Commons
Peiqing Lou, Tonghua Wu, Sizhong Yang

и другие.

Ecological Indicators, Год журнала: 2023, Номер 148, С. 110020 - 110020

Опубликована: Фев. 20, 2023

Vegetation dynamics in Qinghai-Tibet Plateau (QTP) have been debated recent decades. Most studies suggest that wetter and warmer climatic conditions would release low temperature constraints stimulate alpine vegetation growth. Other climate warming might inhibit growth by increasing soil moisture depletion the southern QTP. of previous relied on indices derived from satellite observations to retrieve large-scale changes, uncertainty makes it difficult accurately characterize trends Here, we developed a deep learning algorithm Google Earth Engine (GEE) platform map land use/cover change (LUCC) QTP, then infer gain loss their drivers during period 1988–2018. The QTP experienced rapid greening, which was dominated transitions bareland grassland (27.45 × 104 km2) meadow (17.43 Furthermore, although human activities influence succession at local scale, dominant influencing factors affecting greening are precipitation (q-statistic = 23.87 %) 11.01 %). A 30-year time series analysis clarified specific thus contributing understanding response mechanisms under providing reference for formulating reasonable ecological protection policies development strategies.

Язык: Английский

Процитировано

30
Experimental warming causes mismatches in alpine plant-microbe-fauna phenology DOI Creative Commons
Rui Yin,

Wenkuan Qin,

Xudong Wang

и другие.

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Апрель 15, 2023

Abstract Long-term observations have shown that many plants and aboveground animals changed their phenology patterns due to warmer temperatures over the past decades. However, empirical evidence for phenological shifts in alpine organisms, particularly belowground is scarce. Here, we investigate how activities of plants, soil microbes, fauna will respond warming an meadow on Tibetan Plateau, whether potential changes be synchronized. We experimentally simulate increase temperature by 2–4 °C according future projections this region. find promotes plant growth, microbial respiration, feeding 8%, 57%, 20%, respectively, but causes dissimilar during growing season. Specifically, advances faunal activity spring delays it autumn, while peak does not change; whereas increases growth respiration with only minor phenology. Such asynchrony organisms may alter ecosystem functioning stability.

Язык: Английский

Процитировано

30
Impacts of climate, phenology, elevation and their interactions on the net primary productivity of vegetation in Yunnan, China under global warming DOI Creative Commons
Chen Xu, Ya‐Ping Zhang

Ecological Indicators, Год журнала: 2023, Номер 154, С. 110533 - 110533

Опубликована: Июнь 24, 2023

Both net primary productivity (NPP) and vegetation phenology play essential roles in influencing the carbon sequestration of terrestrial ecosystems. However, relationship between NPP remains unclear under effects global warming. This study used Geodetector to analyze interaction mechanisms climate, phenology, elevation, Yunnan, China. The results are as follows. (1) is positively correlated with NDVI, LOS, EOS, TEMP, PREC SRAD, negatively ELEV, NDBI SOS. main factors leading variation differ region. (2) spatial distribution LOS Yunnan Province mainly influenced by monsoon, showing a pattern high southwest low northeast, reason for NPP. (3) In high-altitude region northwest altitude factor affecting variation. (4) tropical monsoon forest southern SRAD cause changes. (5) Despite having small effect on NPP, SOS was only phenological that showed significant linear reveals complex diverse interactions different regions provides new perspective understanding cycle ecological processes ecosystems

Язык: Английский

Процитировано

24