Soil moisture plays an increasingly important role role in constraining vegetation productivity in China over the past two decades

Agricultural and Forest Meteorology, Journal Year: 2024, Volume and Issue: 356, P. 110193 - 110193

Published: Aug. 14, 2024

Language: Английский

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Generalized Stomatal Optimization of Evolutionary Fitness Proxies for Predicting Plant Gas Exchange Under Drought, Heatwaves, and Elevated CO₂

Global Change Biology, Journal Year: 2025, Volume and Issue: 31(1)

Published: Jan. 1, 2025

ABSTRACT Stomata control plant water loss and photosynthetic carbon gain. Developing more generalized accurate stomatal models is essential for earth system predicting responses under novel environmental conditions associated with global change. Plant optimality theories offer one promising approach, but most such assume that conductance maximizes net assimilation subject to some cost or constraint of water. We move beyond this approach by developing a new, theory conductance, optimizing any non‐foliar proxy requires reserves, like growth, survival, reproduction. overcome two prior limitations. First, we reconcile the computational efficiency instantaneous optimization biologically meaningful dynamic feedback over lifespans. Second, incorporate non‐steady‐state physics in account temporal changes water, carbon, energy storage within its environment occur timescales stomata act, contrary previous theories. Our optimal compares well observations from seedlings, saplings, mature trees field greenhouse experiments. model predicts predispositions mortality during 2018 European drought captures realistic cues, including partial alleviation heat stress evaporative cooling negative effect accumulating foliar soluble carbohydrates, promoting closure elevated CO 2 . advance incorporating evolutionary fitness proxies enhance utility without compromising realism, offering promise future realistically accurately predict fluxes.

Language: Английский

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Estimating actual evapotranspiration across China by improving the PML algorithm with a shortwave infrared-based surface water stress constraint

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 318, P. 114544 - 114544

Published: Dec. 3, 2024

Language: Английский

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Widespread Sensitivity of Vegetation to the Transition From Normal Droughts to Flash Droughts

Geophysical Research Letters, Journal Year: 2025, Volume and Issue: 52(6)

Published: March 16, 2025

Abstract Global climate change has intensified flash droughts, which differ from traditional and have significant ecological impacts. However, differences in ecosystem responses to normal droughts China remain unclear, particularly terms of vegetation vulnerability resilience. Using a three‐dimensional clustering method, we identified disparities between these drought types 1982 2022 found that developed 40% faster than but caused more severe damage. With the transition sensitivity increased. Shapley's additive interpretation assessed role each environmental factor recovery. The results show characteristics drive resilience vegetation, whereas temperature vapor pressure deficit become significant. These insights provide deeper understanding tolerance under changing climatic conditions.

Language: Английский

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Mapping global leaf inclination angle (LIA) based on field measurement data

Earth system science data, Journal Year: 2025, Volume and Issue: 17(4), P. 1347 - 1366

Published: April 7, 2025

Abstract. Leaf inclination angle (LIA), the between leaf surface normal and zenith directions, is a vital trait in radiative transfer, rainfall interception, evapotranspiration, photosynthesis, hydrological processes. Due to difficulty of obtaining large-scale field measurement data, LIA typically assumed follow spherical distribution or simply considered be constant for different plant types. However, appropriateness these simplifications global are still unknown. This study compiled measurements generated first 500 m mean (MLA) product by gap-filling data using random forest regressor. Different generation strategies were employed noncrops crops. The MLA was evaluated validating nadir projection function (G(0)) derived from with high-resolution reference data. 41.47°±9.55°, value increases latitude. MLAs vegetation types order cereal crops (54.65°) > broadleaf (52.35°) deciduous needleleaf (50.05°) shrubland (49.23°) evergreen (47.13°) ≈ grassland (47.12°) (41.23°) (34.40°). Cross-validation shows that predicted presents medium consistency (r=0.75, RMSE = 7.15°) validation samples noncrops, whereas show relatively lower correspondence (r=0.48 0.60 crops, respectively) because limited strong seasonality. G(0) 0.68±0.11. out phase agrees moderately (r=0.62, 0.15). common assumptions may underestimate interception most products this could enhance our knowledge should greatly facilitate remote sensing retrieval land modeling studies. can accessed at https://doi.org/10.5281/zenodo.12739662 (Li Fang, 2025).

Language: Английский

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Mapping and Analyzing Winter Wheat Yields in the Huang-Huai-Hai Plain: A Climate-Independent Perspective

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(8), P. 1409 - 1409

Published: April 16, 2025

Accurate diagnostics of crop yields are essential for climate-resilient agricultural planning; however, conventional datasets often conflate environmental covariates during model training. Here, we present HHHWheatYield1km, a 1 km resolution winter wheat yield dataset China’s Huang-Huai-Hai Plain spanning 2000–2019. By integrating climate-independent multi-source remote sensing metrics with Random Forest model, calibrated against municipal statistical yearbooks, the exhibits strong agreement county-level records (R = 0.90, RMSE 542.47 kg/ha, MRE 9.09%), ensuring independence from climatic influences robust driver analysis. Using Geodetector, reveal pronounced spatial heterogeneity in climate–yield interactions, highlighting distinct regional disparities: precipitation variability exerts strongest constraints on Henan and Anhui, whereas Shandong Jiangsu exhibit weaker dependencies. In Beijing–Tianjin–Hebei, March temperature emerges as critical determinant variability. These findings underscore need tailored adaptation strategies, such enhancing water-use efficiency inland provinces optimizing agronomic practices coastal regions. With its dual ability to resolve pixel-scale dynamics disentangle drivers, HHHWheatYield1km represents resource precision agriculture evidence-based policymaking face changing climate.

Language: Английский

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Integrating MODIS-derived indices for eucalyptus stand volume estimation: an evaluation of MODIS gross primary productivity

Frontiers in Remote Sensing, Journal Year: 2025, Volume and Issue: 6

Published: May 14, 2025

Accurate estimates of stand volume dynamics in Eucalyptus plantations is critical for sustainable forest management and wood production. This study investigates the integration MODIS-derived indices, such as gross primary productivity (GPP), net photosynthesis (PSN) normalized difference vegetation index (NDVI), with traditional age-based methods to improve estimation plantations. MODIS GPP was first evaluated against flux tower measurements, showing moderate agreement systematic biases, particularly during periods highest lowest years after planting, an RMSE 19.65 gC m-2 8day-1 R2 0.38. Multiple linear regression (MLR) two machine learning models, including random (RF) stochastic gradient boosting (SGB), were used estimate by incorporating cumulative indices (Cgpp, Cpsn Cndvi) age. The SGB model showed best performance using full dataset, stands aged from 1.6 8.4 years, 22.63 m 3 ha-1, rRMSE 17.15% R 2 0.90. We that growth significantly improved model’s ability predict middle-aged mature stands. These results highlight utility products medium large-scale plantation management, providing scalable cost-effective monitoring volume.

Language: Английский

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An Insight into The Internal Consistency of MODIS Global Leaf Area Index Products

IEEE Transactions on Geoscience and Remote Sensing, Journal Year: 2024, Volume and Issue: 62, P. 1 - 16

Published: Jan. 1, 2024

Language: Английский

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A global dataset of the fraction of absorbed photosynthetically active radiation for 1982–2022

Scientific Data, Journal Year: 2024, Volume and Issue: 11(1)

Published: June 28, 2024

Abstract The fraction of absorbed photosynthetically active radiation (FPAR) is an essential biophysical parameter that characterizes the structure and function terrestrial ecosystems. Despite extensive utilization several satellite-derived FPAR products, notable temporal inconsistencies within each product have been underscored. Here, new generation GIMMS product, FPAR4g, was developed using a combination machine learning algorithm pixel-wise multi-sensor records integration approach. PKU NDVI, which eliminates orbital drift sensor degradation issues, used as data source. Comparisons with ground-based measurements indicate root mean square errors ranging from 0.10 to 0.14 R-squared 0.73 0.87. More importantly, our demonstrates remarkable spatiotemporal coherence continuity, revealing persistent darkening over past four decades (0.0004 yr −1 , p < 0.001). available for half-month intervals at spatial resolution 1/12° 1982 2022, promises be valuable asset in-depth analyses vegetation structures functions spanning last 40 years.

Language: Английский

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MODIS fPAR products do not reflect in-situ conditions in a tropical dry forest based on wavelet and cross-wavelet transforms

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: 36, P. 101298 - 101298

Published: July 14, 2024

The fraction of Photosynthetically Active Radiation (fPAR) plays a pivotal role in determining the carbon flux ecosystems. Although MODIS fPAR product has demonstrated effectiveness Northern Hemisphere, its validity still needs to be verified context Tropical Dry Forests (TDFs), which constitute 40% all tropical forests. This study utilized Wireless Sensor Network (WSN) generate an in-situ Green dataset at Santa Rosa National Park Environmental Monitoring Supersite, aiming validate products from 2013 2017. employs 2-flux estimation approach for dataset, followed by Savitzky–Golay derivative-based smoothing, univariate-wavelet transforms, and cross-wavelet analysis compare phenological variables between datasets. Our findings reveal significant temporal disparity ground-based data, with consistently lagging detecting onset green-up or senescence TDFs 18–55 days. However, annual inter-seasonal patterns were statistically (p < 0.05) replicated Notably, these deviate during extreme water conditions (droughts hurricanes), underestimating effects drought failing represent hurricane impact. Furthermore, do not effectively capture small-scale variations intra-seasonal differences. Therefore, this underscores limited accuracy observations TDFs. Consequently, caution is warranted when relying on monitor rapid changes Forests.

Language: Английский

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