Spring photosynthetic phenology of Chinese vegetation in response to climate change and its impact on net primary productivity

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

Опубликована: Сен. 27, 2023

Язык: Английский

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Variation of vegetation autumn phenology and its climatic drivers in temperate grasslands of China

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2022, Номер 114, С. 103064 - 103064

Опубликована: Окт. 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.

Язык: Английский

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Monitoring nature's calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications

Global Change Biology, Год журнала: 2022, Номер 28(24), С. 7186 - 7204

Опубликована: Сен. 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.

Язык: Английский

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Response of Vegetation Phenology to the Interaction of Temperature and Precipitation Changes in Qilian Mountains

Remote Sensing, Год журнала: 2022, Номер 14(5), С. 1248 - 1248

Опубликована: Март 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.

Язык: Английский

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Spatiotemporal variation of autumn phenology responses to preseason drought and temperature in alpine and temperate grasslands in China

The Science of The Total Environment, Год журнала: 2022, Номер 859, С. 160373 - 160373

Опубликована: Ноя. 19, 2022

Язык: Английский

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Climatic Constraints of Spring Phenology and Its Variability on the Mongolian Plateau From 1982 to 2021

Journal of Geophysical Research Biogeosciences, Год журнала: 2024, Номер 129(2)

Опубликована: Фев. 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.

Язык: Английский

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The underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems in the Northern and Eastern United States

Remote Sensing of Environment, Год журнала: 2023, Номер 294, С. 113617 - 113617

Опубликована: Май 15, 2023

Язык: Английский

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Spatial-temporal dynamics of land surface phenology over Africa for the period of 1982–2015

Heliyon, Год журнала: 2023, Номер 9(6), С. e16413 - e16413

Опубликована: Июнь 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

Язык: Английский

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Ground-Based Hyperspectral Estimation of Maize Leaf Chlorophyll Content Considering Phenological Characteristics

Remote Sensing, Год журнала: 2024, Номер 16(12), С. 2133 - 2133

Опубликована: Июнь 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.

Язык: Английский

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Uncovering the shifts: land surface phenology in Botswana from satellite observations

Discover Sustainability, Год журнала: 2025, Номер 6(1)

Опубликована: Фев. 15, 2025

Язык: Английский

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