Interpreting the influences of multiple factors on forcing requirements of leaf unfolding date by explainable machine learning algorithms DOI Creative Commons
Chengxi Gao, Huanjiong Wang, Quansheng Ge

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112402 - 112402

Published: July 26, 2024

Language: Английский

Sensitivity of First Leaf Date to Temperature Change for Typical Woody Plants in Guiyang, China DOI Open Access

Wenjie Huang,

Lijuan Cao, Junhu Dai

et al.

Forests, Journal Year: 2025, Volume and Issue: 16(2), P. 300 - 300

Published: Feb. 9, 2025

The temperature sensitivity of plant phenology reflects how and to what extent plants respond climate change is significantly related their ability adapt change. Previous studies on the first leaf date (FLD) primarily focus temperate regions, with relatively few conducted in subtropical areas. This study analyzed observational data FLD 63 typical woody species from 1980 2019 Guiyang, located zone China. We quantified trend its changes then assessed impact sample size stability estimates. results showed that (1) significant warming occurred Guiyang during period, largest occurring spring. (2) vast majority (95.2%) an earlier period (19.0% at p < 0.05). most ranged −3 −1 days decades−1. median trends for all investigated was 1.97 (3) interannual variation negatively correlated preseason average (p Most between −5 °C−1, a mean −4.53 °C−1. (4) influenced Using randomly selected 20-year could limit standard deviation estimate 0.3 These suggest unfolding track closely like species. should be estimated based long-term observation data.

Language: Английский

Citations

0
The Widely Increasing Sensitivity of Vegetation Productivity to Phenology in Northern Middle and High Latitudes DOI Creative Commons
Longjun Wang, Peng Li, Y. Peng

et al.

Geophysical Research Letters, Journal Year: 2025, Volume and Issue: 52(4)

Published: Feb. 12, 2025

Abstract Although vegetation phenology generally alters productivity, spatiotemporal variations in this effect and its potential drivers remain unclear. We used satellite‐based gross primary productivity (GPP) data sets to analyze trends the sensitivity of spring GPP (spring S GP ) autumn (autumn ). also explored across northern middle high latitudes (>30°N) from 2001 2019. Our analysis revealed significant increases ( P < 0.05), with pronounced boreal forests tundra biomes. In contrast, significantly declined deserts xeric shrublands 0.05). Spring temperatures leaf area index (LAI) were key factors influencing , while LAI downward surface solar radiation drove variation . findings highlight critical role phenology‐productivity interactions achieving carbon goals need for future research on climate feedback mechanisms.

Language: Английский

Citations

0
Impacts of meteorological drought on peak vegetation productivity of grasslands from perspectives of canopy structure and leaf physiology DOI
Wenrui Bai, Huanjiong Wang, Jingfeng Xiao

et al.

International Journal of Biometeorology, Journal Year: 2025, Volume and Issue: unknown

Published: March 3, 2025

Language: Английский

Citations

0
Changes in peak greenness timing and senescence duration codetermine the responses of leaf senescence date to drought over Mongolian grassland DOI
Wenrui Bai, Huanjiong Wang, Junhu Dai

et al.

Agricultural and Forest Meteorology, Journal Year: 2023, Volume and Issue: 345, P. 109869 - 109869

Published: Dec. 21, 2023

Language: Английский

Citations

5
Turning Points in Vegetation Phenology Trends and Their Relationship to Climate in Arid Central Asia DOI
X.H. Nie, Xuan Zhang, Fanghua Hao

et al.

Journal of Geophysical Research Biogeosciences, Journal Year: 2024, Volume and Issue: 129(8)

Published: Aug. 1, 2024

Abstract Grassland phenology is highly sensitive to climate change. Here, we investigate the spatiotemporal patterns of start (start season (SOS)) and end (end (EOS)) dates growing quantify changes in their climatic controls over arid Central Asian grassland ecosystems during 1982–2015, which may improve model performance by considering shifts primary drivers under ongoing Our results suggest that temperature played a positive role advancing SOS date, with control on getting stronger as preseason conditions become warmer but not drier. For autumn phenology, rapid increase after 1999 combination reductions precipitation jointly contributed shift from delayed advanced EOS. The areas EOS regulated either or have changed between two subperiods. findings dynamic difference spring should be built into phenological models more accurately.

Language: Английский

Citations

1
Interpreting the influences of multiple factors on forcing requirements of leaf unfolding date by explainable machine learning algorithms DOI Creative Commons
Chengxi Gao, Huanjiong Wang, Quansheng Ge

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112402 - 112402

Published: July 26, 2024

Language: Английский

Citations

0