Increased photosynthesis during spring drought in energy-limited ecosystems

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Ноя. 29, 2023

Drought is often thought to reduce ecosystem photosynthesis. However, theory suggests there potential for increased photosynthesis during meteorological drought, especially in energy-limited ecosystems. Here, we examine the response of (gross primary productivity, GPP) drought across water-energy limitation spectrum. We find a consistent increase eddy covariance GPP spring ecosystems (83% sites). Half sensitivity precipitation was predicted solely from wetness index (R2 = 0.47, p < 0.001), with weaker relationships summer and fall. Our results suggest increases 55% vegetated Northern Hemisphere lands ( >30° N). then compare these terrestrial biosphere model outputs remote sensing products. In contrast trends detected data, mean always declined under deficits after controlling air temperature light availability. While products captured observed negative ecosystems, models proved insufficiently sensitive deficits.

Язык: Английский

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Greening of India: Forests or Croplands?

Applied Geography, Год журнала: 2023, Номер 161, С. 103115 - 103115

Опубликована: Окт. 19, 2023

Язык: Английский

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Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation

PeerJ, Год журнала: 2023, Номер 11, С. e15593 - e15593

Опубликована: Июнь 23, 2023

The global potential distribution of biomes (natural vegetation) was modelled using 8,959 training points from the BIOME 6000 dataset and a stack 72 environmental covariates representing terrain current climatic conditions based on historical long term averages (1979-2013). An ensemble machine learning model stacked regularization used, with multinomial logistic regression as meta-learner spatial blocking (100 km) to deal autocorrelation points. Results cross-validation for classes show an overall accuracy 0.67 R2logloss 0.61, "tropical evergreen broadleaf forest" being class highest gain in predictive performances (R2logloss = 0.74) "prostrate dwarf shrub tundra" lowest -0.09) compared baseline. Temperature-related were most important predictors, mean diurnal range (BIO2) shared by all base-learners (i.e.,random forest, gradient boosted trees generalized linear models). next used predict future periods 2040-2060 2061-2080 under three climate change scenarios (RCP 2.6, 4.5 8.5). Comparisons predictions epochs (present, 2061-2080) that increasing aridity higher temperatures will likely result significant shifts natural vegetation tropical area (shifts forests savannas up 1.7 ×105 km2 2080) around Arctic Circle tundra boreal 2.4 2080). Projected maps at 1 km resolution are provided probability hard IUCN (six aggregated classes). Uncertainty (prediction error) also should be careful interpretation projections.

Язык: Английский

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Sensor-independent LAI/FPAR CDR: reconstructing a global sensor-independent climate data record of MODIS and VIIRS LAI/FPAR from 2000 to 2022

Earth system science data, Год журнала: 2024, Номер 16(1), С. 15 - 34

Опубликована: Янв. 4, 2024

Abstract. Leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR) are critical biophysical parameters for the characterization terrestrial ecosystems. Long-term global LAI/FPAR products, such as moderate resolution imaging spectroradiometer (MODIS) Visible Infrared Imaging Radiometer Suite (VIIRS), provide fundamental dataset accessing vegetation dynamics studying climate change. However, existing products suffer from several limitations, including spatial–temporal inconsistencies accuracy issues. Considering these this study develops a sensor-independent (SI) data record (CDR) based on Terra-MODIS/Aqua-MODIS/VIIRS standard products. The SI CDR covers period 2000 to 2022, at spatial resolutions 500 m/5 km/0.05∘, 8 d/bimonthly temporal frequencies available in sinusoidal WGS1984 projections. methodology includes (i) comprehensive analyses sensor-specific quality assessment variables select high-quality retrievals, (ii) application tensor (ST-tensor) completion model extrapolate LAI FPAR beyond areas with (iii) generation various projections resolutions, (iv) evaluation by direct comparisons ground indirectly through reproducing results trends documented literature. This paper provides analysis each step involved CDR, well ST-tensor model. Comparisons truth suggest an RMSE 0.84 (0.15 FPAR) units R2 0.72 (0.79), which outperform Terra/Aqua/VIIRS is characterized low time series stability (TSS) value, suggesting more stable less noisy than sensor-dependent counterparts. Furthermore, mean absolute error (MAE) also lower, that comparable retrievals. trend agree previous studies, enhanced capabilities utilize Overall, integration multiple satellite sources use advanced gap filling modeling techniques improve ensuring reliability long-term carbon cycle modeling, land policy development informed decision-making sustainable environmental management. open access under Creative Commons Attribution 4.0 License https://doi.org/10.5281/zenodo.8076540 (Pu et al., 2023a).

Язык: Английский

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Stronger increases but greater variability in global mangrove productivity compared to that of adjacent terrestrial forests

Nature Ecology & Evolution, Год журнала: 2024, Номер 8(2), С. 239 - 250

Опубликована: Янв. 3, 2024

Язык: Английский

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Enhanced future vegetation growth with elevated carbon dioxide concentrations could increase fire activity

Communications Earth & Environment, Год журнала: 2024, Номер 5(1)

Опубликована: Янв. 27, 2024

Abstract Many regions of the planet have experienced an increase in fire activity recent decades. Although such increases are consistent with warming and drying under continued climate change, driving mechanisms remain uncertain. Here, we investigate effects increasing atmospheric carbon dioxide concentrations on future using seven Earth system models. Centered time doubling, multi-model mean percent change emissions is 66.4 ± 38.8% (versus 1850 concentrations, fixed land-use conditions). A substantial associated enhanced vegetation growth due to biogeochemical impacts at 60.1 46.9%. In contrast, radiative impacts, including drying, yield a negligible response 1.7 9.4%. model representation processes remains uncertain, our results show importance dynamics dioxide, potentially important policy implications.

Язык: Английский

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AmeriFlux: Its Impact on our understanding of the ‘breathing of the biosphere’, after 25 years

Agricultural and Forest Meteorology, Год журнала: 2024, Номер 348, С. 109929 - 109929

Опубликована: Фев. 16, 2024

Язык: Английский

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The variability in sensitivity of vegetation greenness to climate change across Eurasia

Ecological Indicators, Год журнала: 2024, Номер 163, С. 112140 - 112140

Опубликована: Май 16, 2024

Climate change is one of dominators driving the greening vegetation worldwide, which expected to enhance land carbon sink and mitigate global warming. The sensitivity greenness climate fluctuant regulated by other environmental factors. However, drivers mechanisms behind remain unclear so far. Here, we hired long-term satellite-based index (NDVI), climatic variables, nitrogen deposition, atmospheric CO2 records investigate variations its across Eurasia. To obtain timeseries temperature (γNDVITEM) precipitation (γNDVIPRE), applied multi-regression models regressed on NDVI in each 9-year moving windows. results showed that area limited low temperatures substantially shrunk, while deficit increased during 1982–2015. Specifically, significantly decreasing γNDVITEM γNDVIPRE accounted for 29.8% 20.1%, respectively, remarkably increasing about 18.2% 24.5%, vegetated lands Declining was widely observed most biomes, including tropical subtropical moist broadleaf forests, temperate mixed coniferous croplands, deserts xeric shrublands. Substantially merely found montane grasslands shrublands, dry nonlinear regimes proved biome types. Spatially, rather than elevated factors (temperature, precipitation, radiation) jointly dominated nearly 45% 48% Eurasia respectively. Our uncovered apparent pattern changes highlighted necessity unfold underlying based plant physiology traits.

Язык: Английский

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Climate change enhances greening while human activities accelerate degradation in northern China's grasslands

The Science of The Total Environment, Год журнала: 2025, Номер 966, С. 178570 - 178570

Опубликована: Фев. 1, 2025

Язык: Английский

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Losses of Tree Cover in California Driven by Increasing Fire Disturbance and Climate Stress

AGU Advances, Год журнала: 2022, Номер 3(4)

Опубликована: Июль 6, 2022

Forests provide natural climate solutions for sequestering carbon and mitigating change, yet are increasingly threatened by increasing temperature disturbance. Understanding these threats requires accurate information on vegetation dynamics their drivers, which is currently lacking in many regions experiencing rapid change such as California. To address this, we combined remote sensing observations with geospatial databases to develop annual maps of cover (tree, shrub, herbaceous) disturbance type (fire, harvest, forest die-off) California at 30 m resolution from 1985 2021. Considering both changes fraction areal extent, lost 4,566 km2 its tree area (6.7% relative initial cover) since 1985. Substantial gains during the 1990s were more than offset fire-driven declines 2000, resulting greater shrub herbaceous area. Tree loss occurred all ecoregions but was most severe southern mountains, where losses wildfire not compensated regrowth undisturbed areas. Fires generally summer temperatures 17.5°C, whereas net gain often cooler areas, suggesting that ongoing warming threatening forests California's undergoing transformation, rates posing substantial potential risks integrity terrestrial sink.

Язык: Английский

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