Divergent seasonal responses of above- and below-ground to environmental factors in alpine grassland DOI Creative Commons

Xiaojing Qin,

Xiaojun Nie, Xiaodan Wang

et al.

Frontiers in Plant Science, Journal Year: 2023, Volume and Issue: 13

Published: Feb. 6, 2023

Under current global warming, the relationship between season changes of plants and environmental factors is focused on high-elevation latitude regions. Due to desynchronized growth above- below-ground buffering soil, driving in leaf root show seasonal dynamics.We measured intensity alpine steppe over non-growing (October-April) growing (May-September). Air temperature, precipitation, soil moisture, temperature were used analyze correlation based rhythm.Results showed that an earlier spring a delayed dormancy autumn than was observed. Our results strongly suggest moisture plays more important role unfolding while consistent with withering shoots. Soil comes from melt phenology roots, which derived storage subsoil layer last autumn.Climate change will affect strong patterns characterized these precipitation-limited systems, especially fall shoulder seasons. As seasonality steppe, divergent responses fine would be explored.

Language: Английский

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

et al.

Agricultural and Forest Meteorology, Journal Year: 2023, Volume and Issue: 342, P. 109734 - 109734

Published: Sept. 27, 2023

Language: Английский

Citations

65
Variation of vegetation autumn phenology and its climatic drivers in temperate grasslands of China DOI Creative Commons

Rong Ma,

Xiangjin Shen, Jiaqi Zhang

et al.

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2022, Volume and Issue: 114, P. 103064 - 103064

Published: Oct. 18, 2022

Understanding the variation of autumn phenology and its climatic drivers is important for predicting terrestrial carbon cycles in temperate grasslands China. Using meteorological data GIMMS NDVI during 1982–2015, this study analyzed variations end date vegetation growing season (EOS) their relationships with climate The results showed that EOS was delayed by 1.62 days/decade across For different grassland types, 1.65, 1.66, 1.34 meadows, steppes, desert respectively. In terms change effects, increasing summer precipitation temperatures crucial delaying increase could delay EOS, especially whereas significantly meadows. addition, we found influences nighttime daytime warming on were asymmetric. Specifically, maximum temperature meadows minimum steppes had a weakly advancing effect Our highlights distinct monthly types indicates impacts should be included simulating ecosystems arid/semi-arid regions.

Language: Английский

Citations

53
Monitoring nature's calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications DOI Creative Commons
Xuanlong Ma, Xiaolin Zhu, Qiaoyun Xie

et al.

Global Change Biology, Journal Year: 2022, Volume and Issue: 28(24), P. 7186 - 7204

Published: Sept. 17, 2022

Abstract Vegetation phenology has been viewed as the nature's calendar and an integrative indicator of plant‐climate interactions. The correct representation vegetation is important for models to accurately simulate exchange carbon, water, energy between vegetated land surface atmosphere. Remote sensing advanced monitoring by providing spatially temporally continuous data that together with conventional ground observations offers a unique contribution our knowledge about environmental impact on ecosystems well ecological adaptations feedback global climate change. Land (LSP) defined use satellites monitor seasonal dynamics in surfaces estimate phenological transition dates. LSP, interdisciplinary subject among remote sensing, ecology, biometeorology, undergone rapid development over past few decades. Recent advances sensor technologies, fusion techniques, have enabled novel retrieval algorithms refine details at even higher spatiotemporal resolutions, new insights into ecosystem dynamics. As such, here we summarize recent LSP associated opportunities science applications. We focus remaining challenges, promising emerging topics believe will truly form very frontier research field.

Language: Английский

Citations

41
Response of Vegetation Phenology to the Interaction of Temperature and Precipitation Changes in Qilian Mountains DOI Creative Commons
Cheng Li,

Yuyang Zou,

Jianfeng He

et al.

Remote Sensing, Journal Year: 2022, Volume and Issue: 14(5), P. 1248 - 1248

Published: March 3, 2022

Located at the junction between continental climate region and marine region, Qilian Mountains have experienced significant change. Vegetation phenology in is sensitive to However, response of vegetation temperature precipitation change still unclear, same true for their interactions. First, we extracted grassland phenological parameters such as SOS (the start growing season), EOS end LOS length season) from revised MODIS-NDVI data during period 2000 2019. Second, analyzed trends parameters, temperature, precipitation. Furthermore, effects each meteorological element changes interaction on multiple were detected using GeoDetector method. The result implied that (1) most areas except northwestern mountain showed an advanced trend (10 d/10a); a delayed southeast (5 d/10a), d/10a) northwest; extended southeast, shortened northwest. (2) Compared with single period, different periods had higher impact phenology, maximum q-value increasing by about 0.4 parameter. (3) was inconsistently complete spatial distribution. Our research reveals elements periods. element, this can reflect more comprehensively.

Language: Английский

Citations

34
Spatiotemporal variation of autumn phenology responses to preseason drought and temperature in alpine and temperate grasslands in China DOI Creative Commons
Zhihui Yuan, Siqin Tong, Gang Bao

et al.

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 859, P. 160373 - 160373

Published: Nov. 19, 2022

Language: Английский

Citations

27
Climatic Constraints of Spring Phenology and Its Variability on the Mongolian Plateau From 1982 to 2021 DOI
Zhihui Yuan, Gang Bao, Altantuya Dorjsuren

et al.

Journal of Geophysical Research Biogeosciences, Journal Year: 2024, Volume and Issue: 129(2)

Published: Feb. 1, 2024

Abstract The start of vegetation growing season (SOS) plays an important role in the energy cycle between land and atmosphere. Due to limited temporal span a single satellite sensor through time, continuous variation SOS over 40 years has not been adequately quantified. Using overlapping periods (2001–2015) Global Inventory Modeling Mapping Studies (GIMMS) (1982–2015) Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference index (NDVI) (2001–2021) data sets, we construct NDVI set covering period 1982–2021 on Mongolian Plateau further map relative climatic constraint (divided into “temperature‐constrained,” “precipitation‐constrained,” “other” regions) for quantifying variability. We show that constructed high consistency continuity with earlier GIMMS data. Regions constrained by temperature account 55.3% plateau are located northwestern northeastern cold areas, while regions precipitation constitute 34.7% central southwestern drier regions. Importantly, temperature‐constrained continuously significantly advanced, total advance 4.8 days years. In contrast, precipitation‐constrained reversed from advancing delaying 2005. This suggests differentiating might be practical treatment reducing uncertainties trends previous studies. Interestingly, does correlate both chilling forcing temperatures, indicating less dependency chilling, which may have well considered previously.

Language: Английский

Citations

5
The underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems in the Northern and Eastern United States DOI Creative Commons
Yating Gu,

Yingyi Zhao,

Zhengfei Guo

et al.

Remote Sensing of Environment, Journal Year: 2023, Volume and Issue: 294, P. 113617 - 113617

Published: May 15, 2023

Language: Английский

Citations

13
Spatial-temporal dynamics of land surface phenology over Africa for the period of 1982–2015 DOI Creative Commons
Siqi Shi, Peiqi Yang, Christiaan van der Tol

et al.

Heliyon, Journal Year: 2023, Volume and Issue: 9(6), P. e16413 - e16413

Published: June 1, 2023

Knowledge of the dynamics vegetation phenology is essential for understanding vegetation-climate interactions. Although interest in study growing, Africa received far less attention compared to Northern Hemisphere. straddles northern and southern hemispheres, climate has a clear latitudinal gradient, which facilitates interaction between climate. In this study, longitudinal gradients temporal trends start growing season (SOS), peak (POS), end (EOS) were examined using long-term satellite dataset during 1982-2015. The variations these metrics larger than those Africa, especially from 6°N northwards 16°N. had no patterns due more complex systems. For variation, POS EOS exhibited gradient-decreasing rate Africa. Over period 1982 2015, overall 'later SOS', POS', EOS'. faster delay SOS resulted prolonged length (LOS) with 0.50 days/year on average while slower shorter LOS -0.12 contributes increase yearly-averaged Normalized Difference Vegetation Index (NDVI) 2000. Nevertheless, NDVI appeared have reached saturation around 2000s, although was still extending after 2000s. Overall, findings provide an view spatial land surface African continent, necessary component future studies response

Language: Английский

Citations

12
Ground-Based Hyperspectral Estimation of Maize Leaf Chlorophyll Content Considering Phenological Characteristics DOI Creative Commons
Yiming Guo, Shiyu Jiang,

Huiling Miao

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(12), P. 2133 - 2133

Published: June 13, 2024

Accurately measuring leaf chlorophyll content (LCC) is crucial for monitoring maize growth. This study aims to rapidly and non-destructively estimate the LCC during four critical growth stages investigate ability of phenological parameters (PPs) LCC. First, spectra were obtained by spectral denoising followed transformation. Next, sensitive bands (Rλ), indices (SIs), PPs extracted from all at each stage. Then, univariate models constructed determine their potential independent estimation. The multivariate regression (LCC-MR) built based on SIs, SIs + Rλ, Rλ after feature variable selection. results indicate that our machine-learning-based LCC-MR demonstrated high overall accuracy. Notably, 83.33% 58.33% these showed improved accuracy when successively introduced SIs. Additionally, model accuracies milk-ripe tasseling outperformed those flare–opening jointing under identical conditions. optimal was created using XGBoost, incorporating SI, PP variables R3 These findings will provide guidance support management.

Language: Английский

Citations

4
The role of developmental and climate factors in driving autumn phenology across the Northern Hemisphere DOI
Shuping Ji, Shilong Ren, Xiaoyang Zhang

et al.

Agricultural and Forest Meteorology, Journal Year: 2025, Volume and Issue: 368, P. 110548 - 110548

Published: April 14, 2025

Language: Английский

Citations

0