Journal of Geophysical Research: Biogeosciences最新文献

Dissolved organic carbon (DOC) plays a vital role in the global carbon cycle, with river discharge as a major transport mechanism from land to ocean. As the second-largest freshwater contributor to oceans, Asia experiences significant hydroclimatic variations, yet, observations are patchy across watersheds and climate zones. Here, we compiled 1,593 DOC observations from 40 studies spanning most Asian climate zones to map large-scale patterns, and tested hydroclimatic controls for a set of representative watersheds (Yangtze, Yellow, Mekong, Ganges-Brahmaputra, and Rajang) where sufficient time series records exist. Our findings show DOC concentrations peaking near the equator (tropical rainforest) and again above ∼40°N (humid continental dry winter), with tributaries exhibiting higher and more variable levels than mainstems. Hydroclimatic responses were basin-dependent: DOC-precipitation correlation was not significant, yet DOC significantly differed across precipitation groups with highest means at low precipitation, indicating nonlinearity and likely thresholds; temperature effects diverged by basin; and soil moisture was a consistent positive driver, especially in Mekong and Yangtze. Overall, this study highlights that DOC behavior in Asia cannot be captured by uniform assumptions across basins and climate zones. As most existing observations are limited to short-term data sets, the impacts of hydroclimatic change on carbon transport remain uncertain and require long-term data sets. Future research should take an interdisciplinary approach by integrating hydrology, geomorphology, and climate indicators by fusing remote sensing based observations and advanced analytics, to address differences in DOC behavior and climate challenges.

The Tibetan Plateau, known as the Third Pole, is experiencing rapid warming and increasing atmospheric CO₂ concentration, which profoundly influences the growth of crops such as highland barley. However, it remains unclear how highland barley photosynthesis quantitatively responds to changes in CO₂ concentration and how the photosynthesis-CO₂ relationship responds to warming on the Tibetan Plateau. Here, we examined the photosynthesis-CO₂ relationship of highland barley leaves at the heading stage and its developmental response to experimental warming (+1 and +2°C). The photosynthetic CO₂ saturation concentration (C_a,sat) of highland barley leaves was 1,208.8 ± 533.4 ppm, exceeding the current atmospheric CO₂ concentration (419.3 ± 0.2 ppm in 2022, Waliguan). Experimental warming did not significantly affect the maximum photosynthetic rate (A_max, 39.0 ± 9.5 μmol m⁻² s⁻¹), C_a,sat (1,208.8 ± 533.4 ppm), the CO₂ compensation concentration (C_a,com, 58.9 ± 13.8 ppm), the maximum carboxylation rate of Rubisco (V_cmax, 142.8 ± 12.5 μmol m⁻² s⁻¹), and the maximum electron transport rate (J_max, 193.9 ± 31.0 μmol m⁻² s⁻¹) at a measurement temperature of 25°C. At +2°C warming, the carotenoid content of highland barley leaves increased by 5%–21%, whereas chlorophyll and anthocyanin contents were not significantly affected. Our findings highlight that the CO₂ fertilization effect on highland barley leaf photosynthesis is expected to continue and experimental warming may developmentally influence highland barley leaf photosynthesis by altering the leaf carotenoid content rather than the photosynthesis-CO₂ relationship.

Evapotranspiration (ET) is the largest outgoing water flux in the hydrologic cycle but the most difficult component to quantify. In arid and semi-arid regions, ET can be up to 99% of precipitation and thus critical for land and water managers to quantify accurately. We evaluate ECOSTRESS ET at various temporal scales in the arid and semi-arid region of southern Arizona for 2019–2022 including all four seasons annually and using in situ observations from six eddy covariance flux towers. Our results demonstrate that ECOSTRESS ET estimates have the highest accuracy at seasonal (R² = 0.61, RMSE = 0.76, p-value < 0.05) and annual (R² = 0.77, RMSE = 0.42, p < 0.05) temporal scales, indicating stronger performance over longer integration periods. Our results also indicate that OpenET estimates more closely align with in situ data trends compared with ECOSTRESS ET. Furthermore, this study demonstrates locally-adjusted ECOSTRESS ET estimates by integrating Sentinel-2A spectral indices. The locally-adjusted ECOSTRESS ET estimates perform well for the arid and semi-arid southern Arizona (improving R² from 0.28 to 0.85) highlighting the need for site-specific and finer spatial resolution data inputs for estimating ET in these challenging environments. Enhanced accuracy of ET measurements enables land and water managers to make more informed decisions regarding limited natural resources and conservation and deepen their understanding of hydrologic dynamics in regions where ET dominates the water balance.

Terrestrial ecosystems significantly mitigate atmospheric CO₂, yet substantial uncertainties remain in quantifying regional carbon source/sink dynamics. This study optimized the photosynthesis and respiration parameters in the Vegetation Photosynthesis and Respiration Model (VPRM) using net ecosystem exchange (NEE) data from evergreen forests and tree-crop mixed ecosystems in Southern China. To improve the midday NEE simulation, a vapor pressure deficit (VPD)-based parameterization scheme (VPRM_k) was developed to adjust half-saturation light intensity (PAR₀). Subsequently, the VPRM_k was incorporated into the Weather Research and Forecasting model (WRF) coupled with VPRM (WRF-VPRM) to assess the terrestrial ecosystem fluxes from 2013 to 2015. The optimized parameters (VPRM_opt) outperformed defaults (VPRM_default) in simulating NEE during both the dry and wet seasons but overestimated midday peaks by ∼25%. The simulation using the VPRM_k reduced this overestimation to 14.08% (dry season) and 9.08% (wet season), yielding mean daytime NEE biases of 0.13 and 0.01 μmol·m⁻²·s⁻¹, respectively. The regional mean annual NEE was −1.44 μmol·m⁻²·s⁻¹ during 2013–2015, and the carbon sink was strongest in summer (−2.91 μmol·m⁻²·s⁻¹) and weakest in winter (−0.10 μmol·m⁻²·s⁻¹). Primary sink centers were located in western Guangdong and its border with Guangxi, while source areas were clustered at the Guizhou-Hunan-Guangxi junction. During 2013–2015, the mean annual terrestrial ecosystem carbon sink in Southern China was −0.53 Pg C yr⁻¹, which was 179% higher than the main global flux inversion products (−0.19 Pg C yr⁻¹). These model results suggest deeper investigations into the carbon cycle in this region.

Over the past two decades, numerous studies have emphasized the importance of including organic matter (OM) in land surface models (LSMs) to accurately represent soil thermal and hydrological properties. This is particularly relevant in Arctic regions, where organic-rich soils are widespread. Consequently, most LSMs incorporate parameterizations that account for OM effects, although these implementations are often simplified. Recent advancements in global soil data sets now enable more precise modeling of soil properties by providing detailed inputs for soil composition and physical characteristics. This study focuses on the refinement of the representation of soil organic and mineral content and the revision of the parameterizations of heat capacity, thermal conductivity, and porosity in the ORCHIDEE LSM, using data from the SoilGrids 250m v2.0 database. The updated model is evaluated across multiple Arctic and boreal sites and compared against two earlier versions: (a) a Bulk version that neglects OM effects on the thermal processes and (b) a simplified version with a basic OM prescription. Results show that incorporating OM into thermal processes modeling significantly improves soil temperature simulations, particularly under the soil surface in the critical zone. For some sites, root mean square errors (RMSE) are reduced by up to 50% compared to the Bulk version, especially during the snow-free summer months. These findings highlight the value of high-resolution soil data sets, such as SoilGrids, for improving simulations of thermal dynamics in carbon-rich Arctic soils.

Arctic warming is altering vegetation and carbon dynamics with global implications, yet Earth System Model (ESM) predictions in the Arctic remain highly uncertain, in part due to historically limited data for model parameterization and validation. As such, ESMs typically represent Arctic ecosystems in an oversimplified manner. Recently, nine plant functional types (PFTs) designed to realistically represent tundra vegetation were integrated into the Energy Exascale Earth System Model (E3SM) Land Model (ELM) and parameterized using plot-scale observations from a single site. Additional evaluation was needed to determine their transferability across the Arctic. Here, we evaluated whether refined representation of tundra vegetation improved model accuracy by conducting spatially explicit 100 × 100 m resolution ELM simulations on Alaska's Seward Peninsula. Simulations with the default two-PFT configuration and with the nine Arctic-specific PFTs were benchmarked against observations of net ecosystem exchange, gross primary production, and aboveground biomass from multiple data streams including an eddy covariance flux tower, flux chambers, and aircraft and unoccupied aerial system hyperspectral remote sensing. Evaluation revealed that Arctic-specific PFT simulations produced more realistic landscape-level carbon exchanges, and better captured observed heterogeneity in biomass and productivity, explaining 60%–70% of spatial variance (R² = 0.6–0.7) compared to just 12%–18% (R² = 0.12–0.18) with the default configuration. However, the refined model failed to reproduce observed aboveground biomass for highly productive alder-willow communities, requiring further evaluation of carbon allocation parameterizations for tall shrubs that are increasingly expanding across tundra landscapes. Our results demonstrate that enhanced representation of vegetation heterogeneity boosts predictive understanding of tundra carbon dynamics, facilitating regional to pan-Arctic model and remote-sensing scaling.

The extent of projected ocean acidification is partly dependent on the natural variability of marine carbonate chemistry—which is higher in coastal systems than in the open ocean. However, there are limited empirical studies quantifying the rate, magnitude and drivers of coastal environmental variability, preventing accurate assessments for how species and their associated communities may respond to projected climate change. Here, we quantified the annual variability of pH, temperature and dissolved oxygen in a coralline algae reef, a globally distributed biodiverse habitat that may be one of the most sensitive to projected climate change. We found that coralline algae and their communities are exposed to pH values as low as those projected for 2100 (even under a low emission scenario) for 63% of the year, including most of autumn and all of winter. Annual fluctuations in pH ranged by 0.46 units, with identifiable patterns at diel to seasonal timescales driven by various biogeochemical factors. Biologically driven patterns in dissolved oxygen and pH were coupled at multiple periodicities, and temperature was coupled to pH during the winter. Tidal cycling additionally modulated biological forcing of pH, increasing the complexity of intra-seasonal pH variability. Forecasting this environmental variability to the future led to projections of new pH extremes well beyond all IPCC emission scenarios. However, persistent long-term exposure to low pH may increase the acclimation and adaptation potential of coralline algae and their associated communities, providing a level of optimism for the continued survival of this habitat despite sensitivity to projected climate change.

This study evaluates the effects of ground-based logging on soil properties and microarthropod biodiversity in Mediterranean beech (Fagus sylvatica L.) forests, with a focus on recovery over a 5-year period. Fieldwork was conducted in three study areas in southern Italy to compare three site types: recently harvested (2021, NEW), harvested 5 years prior (2017, OLD), and unharvested control (>40 years ago, CON). Soil samples were collected from skid trails (DIST) and from adjacent, not-trafficked areas (UND) to assess bulk density, penetration resistance, shear strength, organic matter content, and the QBS-ar index of microarthropod biodiversity. Logging machinery significantly compacted the soil in DIST_NEW, increasing bulk density by 19% compared with UND_NEW. Penetration resistance tripled (0.26 vs. 0.09 MPa in CON), and shear strength rose from 1.96 to 7.18 t m⁻². The QBS-ar index declined by 50% in comparison to the CON areas, indicating substantial biodiversity loss. After 5 years, partial recovery was observed in DIST_OLD, with bulk density and penetration resistance decreasing by 13% and 8%, respectively, though values remained above those in CON sites. These results highlight the lasting impacts of forest operations on soil health and microarthropod biodiversity. To reduce degradation, strategies such as permanent skid trail planning or use of protective technologies like logging mats are recommended. Continued research into deeper soil layers and various soil types is essential to guide more sustainable forest management practices.

Reservoirs with thicker sediments generally exhibit elevated carbon emissions; however, this relationship may not necessarily persist when emissions are assessed per unit thickness. A comprehensive understanding of this relationship is essential for accurately evaluating carbon emissions across various sedimentation patterns. This study proposes the concept of carbon emission intensity (CEI), defined as carbon emissions per unit mass or volume of sediment, evaluates its correlation with sediment thickness (ST) using 58 global data sets and clarifies the impact of ST on CEI through controlled incubation experiments. The results revealed a strong negative logarithmic correlation between CEI and ST (R² = 0.88), indicating that increasing ST substantially reduces CEI values. The observed trend can be attributed to the potential of thicker sediment layers to restrict oxygen penetration, promoting organic carbon (OC) burial. The incubation experiments reinforced this mechanism, revealing that although thicker sediments generated higher absolute carbon emissions, their CEI values were consistently lower. Oxygen penetration and active OC decomposition were found to be limited to the top few centimeters of sediment, independent of the total ST. The findings indicate that dam construction in narrow river sections could be strategically favorable, as these areas are more likely to accumulate thicker sediments characterized by lower CEI, reducing overall carbon emissions.