Climate warming advances plant reproductive phenology in China’s northern grasslands DOI Creative Commons
Lu Bai, Lei Tian,

Zhiguo Ren

et al.

Journal of Plant Ecology, Journal Year: 2024, Volume and Issue: 17(6)

Published: Aug. 26, 2024

Abstract Despite much recent progress, our understanding of plant phenology response to climate change remains incomplete. In particular, how and what extent warming affects the vegetative reproductive different functional groups in northern grassland ecosystems largely unexplored. Here, we compiled data 1758 observations from 25 individual studies carried out a meta-analysis relation temperature changes across range species China. We show that tended extend duration while having no effect on phenology. also identified specific sensitivities for phenological stages: 1.73 days °C−1 budding, −3.38 leaf spreading 0.56 yellow withered stage, respectively. Notably, resulted earlier shrubs semi-shrubs, but caused delay budding time sedges. terms phenology, sensitivity was −1.73 flowering time, −2.53 fruit ripening −0.11 shedding, Warming advanced repining all except legumes. Our results indicate elevated temperatures extended its grasslands, showing impact findings demonstrate differential responses warming, highlighting diverse growth strategies adaptation plants world.

Language: Английский

Mulching Practices Improve Soil Moisture and Enzyme Activity in Drylands, Increasing Potato Yield DOI Creative Commons

Wenhuan Song,

Fanxiang Han,

Zhengyu Bao

et al.

Agronomy, Journal Year: 2024, Volume and Issue: 14(5), P. 1077 - 1077

Published: May 19, 2024

Mulch is an important measure for improving agricultural productivity in many semiarid regions of the world. However, impacts various mulching materials on soil hydrothermal characteristics, enzyme activity, and potato yield fields have not been comprehensively explored. Thus, a two-growing-season field experiment (2020–2021) with four treatments (SSM, straw strip mulching; PMP, plastic film large ridge; PMF, double ridge-furrow full CK, no conventional planting as control) was conducted to analyze activities Loess Plateau Northwest China. The results indicated that practices had positive effect moisture, SSM, PMF increasing by 7.3%, 9.2%, respectively, compared CK. Plastic significantly increased temperature 1.3 °C, reduced 0.7 °C 0–30 cm layers whole growth period. On average, urease activity 0–40 14.2%, 2.8%, 2.7%, enhanced sucrase 19.2%, 8.6%, 5.7%, catalase 9.6%, while SSM decreased 10.1%. Mulching tuber water use efficiency based dry (WUE), 18.6%, 31.9%, 29.7%, WUE 50%, 57.0% over correlation analysis revealed moisture main factor influencing (r = 0.95**). could improve environment, regulate activities, promote increase. As sustainable protective measure, conducive ecological environment farmland development regional organic agriculture.

Language: Английский

Citations

5
Evapotranspiration Partitioning for Croplands Based on Eddy Covariance Measurements and Machine Learning Models DOI Creative Commons
Jie Zhang, Shanshan Yang, Jingwen Wang

et al.

Agronomy, Journal Year: 2025, Volume and Issue: 15(3), P. 512 - 512

Published: Feb. 20, 2025

Accurately partitioning evapotranspiration (ET) of cropland into productive plant transpiration (T) and non-productive soil evaporation (E) is important for improving crop water use efficiency. Many methods, including machine learning have been developed ET partitioning. However, the applicability models in with diverse rotations not clear. In this study, are used to predict E, T obtained by calculating difference between leading derivation ratio (T/ET). We evaluated six (i.e., artificial neural networks (ANN), extremely randomized trees (ExtraTrees), gradient boosting decision tree (GBDT), light (LightGBM), random forest (RF), extreme (XGBoost)) on at 16 flux sites during period from 2000 2020. The evaluation results showed that XGBoost model had best performance (R = 0.88, RMSE 6.87 W/m2, NSE 0.77, MAE 3.41 W/m2) when considering meteorological data, ecosystem sensible heat flux, respiration, content, remote sensing vegetation indices as input variables. Due unavailability observed E or data sites, we three other widely methods indirectly validate accuracy our based XGBoost. estimation were highly consistent their 0.83–0.91). Moreover, estimated (T/ET) different crops. On average, maize highest T/ET 0.619 ± 0.119, followed soybean (0.618 0.085), winter wheat (0.614 0.08), sugar beet (0.611 0.065). Lower was found paddy rice (0.505 0.055), barley (0.590 0.058), potato (0.540 0.088), rapeseed (0.522 0.107). These suggest easy applicable reveal obvious differences among crops, which crucial sustainability resources improvements

Language: Английский

Citations

0
Dynamic response of vegetation to meteorological drought and driving mechanisms in Mongolian Plateau DOI

Shuhui Gao,

Shengzhi Huang,

Vijay P. Singh

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: unknown, P. 132541 - 132541

Published: Dec. 1, 2024

Language: Английский

Citations

3
Trends in the phenology of the Hyrcanian Forests: Elevation and Climate Change Impacts DOI
Ahmad Abbasnezhad Alchin, Vahid Nasiri, Paweł Netzel

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 101588 - 101588

Published: May 1, 2025

Language: Английский

Citations

0
Impacts of climate change and human activities on vegetation dynamics on the Mongolian Plateau, East Asia from 2000 to 2023 DOI
Yujie Yan, Yiben Cheng, Zhiming Xin

et al.

Journal of Arid Land, Journal Year: 2024, Volume and Issue: 16(8), P. 1062 - 1079

Published: Aug. 1, 2024

Language: Английский

Citations

2
Linking Vegetation Phenology to Net Ecosystem Productivity: Climate Change Impacts in the Northern Hemisphere Using Satellite Data DOI Creative Commons

Hanmin Yin,

Xiaofei Ma,

Xiaohan Liao

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(21), P. 4101 - 4101

Published: Nov. 2, 2024

With global climate change, linking vegetation phenology with net ecosystem productivity (NEP) is crucial for assessing carbon storage capacity and predicting terrestrial changes. However, there have been few studies investigating the relationship between NEP in middle high latitudes of Northern Hemisphere. This study comprehensively analyzed phenological changes their drivers using satellite data. It also investigated spatial distribution further sensitivity to phenology. The results indicated that average land surface (LSP) was dominated by a monotonic trend area. LSP derived from different products retrieval methods exhibited relatively consistent responses climate. SOS POS showed higher negative correlation nighttime temperatures compared daytime temperatures. EOS than positive correlation. correlations VPD SOS, POS, proportion correlations. annual ranged 0 1000 gC·m−2. cumulative trends were mainly monotonically increasing, accounting 61.04%, followed decreasing trends, which accounted 17.95%. In high-latitude regions, predominant, while predominant middle-latitude regions. soil moisture (48.08% vs. 51.92%) basically predominantly negative. overall characterized greater LOS most areas. parameters (SOS, EOS) negative, (0.75 gC·m−2/d EVI 0.63 LAI 0.30 SIF). provides new insights theoretical basis exploring under change.

Language: Английский

Citations

1
Monitoring and Prediction of Land Surface Phenology Using Satellite Earth Observations—A Brief Review DOI Creative Commons
Mateo Gašparović, Ivan Pilaš, Dorijan Radočaj

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 12020 - 12020

Published: Dec. 22, 2024

Monitoring and predicting land surface phenology (LSP) are essential for understanding ecosystem dynamics, climate change impacts, forest agricultural productivity. Satellite Earth observation (EO) missions have played a crucial role in the advancement of LSP research, enabling global continuous monitoring vegetation cycles. This review provides brief overview key EO satellite missions, including advanced very-high resolution radiometer (AVHRR), moderate imaging spectroradiometer (MODIS), Landsat program, which an important capturing dynamics at various spatial temporal scales. Recent advancements machine learning techniques further enhanced prediction capabilities, offering promising approaches short-term cropland suitability assessment. Data cubes, organize multidimensional data, provide innovative framework enhancing analyses by integrating diverse data sources simplifying access processing. highlights potential satellite-based monitoring, models, cube infrastructure advancing research insights into current trends, challenges, future directions.

Language: Английский

Citations

1
Analysis of Changes in Forest Vegetation Peak Growth Metrics and Driving Factors in a Typical Climatic Transition Zone: A Case Study of the Funiu Mountain, China DOI Creative Commons
Jiao Tang, Huimin Wang,

Nan Cong

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(16), P. 2921 - 2921

Published: Aug. 9, 2024

Phenology and photosynthetic capacity both regulate carbon uptake by vegetation. Previous research investigating the impact of phenology on vegetation productivity has focused predominantly start end growing seasons (SOS EOS), leaving influence peak metrics—particularly in typical climatic transition zones—relatively unexplored. Using a 24-year (2000–2023) enhanced index (EVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS), we extracted examined spatiotemporal variation for season (POS) growth (defined as EVImax) forest Funiu Mountain region, China. In addition to quantifying factors influencing metrics, relationship between phenological metrics (POS was investigated. Our findings reveal that POS EVImax showed advancement increase, respectively, negatively positively correlated with productivity. This suggested variations increase analysis also heavily impacted precipitation, whereas SOS had greatest effect variation. highlighted significance considering climate variables well biological rhythms when examining global cycle shifts response change.

Language: Английский

Citations

1
The impact of drought on forest spring phenology in northern China DOI Creative Commons
Haowen Hu,

Pengcheng Xue,

Shaodong Huang

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 170, P. 113022 - 113022

Published: Dec. 25, 2024

Language: Английский

Citations

0
Climate warming advances plant reproductive phenology in China’s northern grasslands DOI Creative Commons
Lu Bai, Lei Tian,

Zhiguo Ren

et al.

Journal of Plant Ecology, Journal Year: 2024, Volume and Issue: 17(6)

Published: Aug. 26, 2024

Abstract Despite much recent progress, our understanding of plant phenology response to climate change remains incomplete. In particular, how and what extent warming affects the vegetative reproductive different functional groups in northern grassland ecosystems largely unexplored. Here, we compiled data 1758 observations from 25 individual studies carried out a meta-analysis relation temperature changes across range species China. We show that tended extend duration while having no effect on phenology. also identified specific sensitivities for phenological stages: 1.73 days °C−1 budding, −3.38 leaf spreading 0.56 yellow withered stage, respectively. Notably, resulted earlier shrubs semi-shrubs, but caused delay budding time sedges. terms phenology, sensitivity was −1.73 flowering time, −2.53 fruit ripening −0.11 shedding, Warming advanced repining all except legumes. Our results indicate elevated temperatures extended its grasslands, showing impact findings demonstrate differential responses warming, highlighting diverse growth strategies adaptation plants world.

Language: Английский

Citations

0