Global Biogeochemical Cycles最新文献

This study provides the longest trend analysis of Nitrogen (N) and phosphorus (P) surplus in France from 1920 to 2020, modeled with the CaSSiS model at both national and departmental levels. At the national scale, the century long average annual N surplus is about 37 ± 13 kg N per ha of utilized agricultural area (UAA) per year, while P surplus averages about 9 ± 7 kg P ha UAA⁻¹ year⁻¹. However, significant periods of change correspond to important agricultural and economic events such as the World Wars and major agri-environmental reforms. Analysis of N and P use efficiency (NUE and PUE, respectively) revealed varying trends over time. NUE averaged 67%, ranging from 52% to 78%, while PUE exhibited larger fluctuations, ranging from 30% to 130%. At the departmental level, N surplus fluctuated between −15 and 140 kg N ha UAA⁻¹, and P surplus ranged from −15 to 41 kg P ha UAA⁻¹. Temporal trends revealed an increase in N surplus in 96% of departments from 1920 to 1990, followed by a decline in about 89% of departments from 1990 to 2020. P surplus increased in all departments until 1974, followed by a consistent decrease. Analysis of five contrasting French departments highlighted the impact of agricultural practices on nutrient surplus. These findings underscore the importance of tailored nutrient management strategies to achieve balanced inputs and outputs, promoting sustainable agriculture and minimizing environmental impacts. This study contributes valuable insights for informed decision-making in nutrient management policies and practices.

While inland freshwater networks cover less than 4% of the Earth's terrestrial surface, these ecosystems play a disproportionately large role in the global cycles of [C]arbon, [N]itrogen, and [P]hosphorus, making streams and rivers critical regulators of nutrient balance at regional and continental scales. Foundational studies have established the relative importance of the hydrologic regime, land cover, and instream removal processes for controlling the transport and processing of C, N, and P in river networks. However, particulate C, N, and P can make up a large proportion of the total material in large rivers and during high flows. To constrain the patterns of the biogeochemistry of riverine particulates, we characterized and modeled dissolved and particulate concentration variability at the continental scale using open-access data from 27 National Ecological Observatory Network (NEON) sites across the United States. We analyzed these data using Boosted Regression Trees (BRTs) to statistically identify if land cover characteristics could predict nutrient quantity and quality of stream particulates. The BRT models revealed that land cover does not strongly predict particulate dynamics across NEON sites but indicate that instream processes might be more important than catchment characteristics alone. In addition, our study demonstrates the consistent importance of particulates relative to dissolved forms, highlighting their likely significance for biogeochemical processes along the freshwater continuum.

Coastal wetlands, including seagrass meadows, emergent marshes, mangroves, and temperate tidal swamps, can efficiently sequester and store large quantities of sediment organic carbon (SOC). However, SOC stocks may vary by ecosystem type and along environmental or climate gradients at different scales. Quantifying such variability is needed to improve blue carbon accounting, conservation effectiveness, and restoration planning. We analyzed SOC stocks in 1,284 sediment cores along >6,500 km of the Pacific coast of North America that included large environmental gradients and multiple ecosystem types. Tidal wetlands with woody vegetation (mangroves and swamps) had the highest mean stocks to 1 m depth (357 and 355 Mg ha⁻¹, respectively), 45% higher than marshes (245 Mg ha⁻¹), and more than 500% higher than seagrass (68 Mg ha⁻¹). Unvegetated tideflats, though not often considered a blue carbon ecosystem, had noteworthy stocks (148 Mg ha⁻¹). Stocks increased with tidal elevation and with fine (<63 μm) sediment content in several ecosystems. Stocks also varied by dominant plant species within individual ecosystem types. At larger scales, marsh stocks were lowest in the Sonoran Desert region of Mexico, and swamp stocks differed among climate zones; otherwise stocks showed little correlation with ecoregion or latitude. More variability in SOC occurred among ecosystem types, and at smaller spatial scales (such as individual estuaries), than across regional climate gradients. These patterns can inform coastal conservation and restoration priorities across scales where preserving stored carbon and enhancing sequestration helps avert greenhouse gas emissions and maintains other vital ecosystem services.

The Prairie Pothole Region (PPR) is the largest wetland complex in North America, with millions of wetlands punctuating the landscapes of Canada and the United States. Here, wetlands have been dramatically impacted by agricultural land use, with unclear implications for regional to global greenhouse gas (GHG) emissions budgets. By surveying wetlands across all three Canadian prairie provinces in the PPR, we show that emissions patterns of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) from aquatic habitats differ among wetlands embedded in cropland versus perennial landcover. Wetlands in cropped landscapes had double the aquatic diffusive emissions (20.6 ± 31.5 vs. 9.4 ± 17.3 g CO₂-eq m⁻² d⁻¹) largely driven by CH₄. Structural equation modeling showed that all three GHGs responded differently to the surrounding landscape properties. Emissions of CH₄ were the most sensitive to land use, responding positively to the elevated phosphorus content and lower sulfate content in cropped settings, despite higher organic matter content in wetlands in perennial landscapes. Aquatic N₂O emissions were negligible, while CO₂ emissions were high, but not strongly related to agricultural land use. While our estimates of aquatic CH₄ emissions from PPR wetlands were high (18.2 ± 41.4 mmol CH₄ m⁻² d⁻¹), accounting for fluxes from vegetated and soil habitats would lead to whole-wetland emissions rates that are lower and comparable to wetlands in other biomes. Our study represents an important step toward understanding wetland emission responses to land use in the PPR and other wetland-rich agricultural landscapes.

Oxygen Deficient Zones (ODZs) are the largest pelagic sinks of N containing nutrients in the ocean. The offshore Eastern Tropical North Pacific (ETNP) ODZ has been shown to be limited by organic matter. We propose zooplankton/forage fish as a key source of particulate and dissolved organic matter for N₂ production that has previously been ignored. We examined data sets from four cruises (April 2012, January 2017, April 2018, October 2019) at a station in the central ETNP. Backscattering data were used to determine zooplankton vertical migration depths (250–450 m, maximum at 270–280 m). Metazoan DNA concentrations, as measured by quantitative PCR, had a reproducible maximum at 270–280 m, confirming that these signals indicate the presence of zooplankton/forage fish. Additionally, a large maximum in sinking pteropod shells was found at 270 m, indicating that pteropods were part of the migrating community. While crustacean zooplankton have been shown to reduce respiration and excretion of ammonium under anoxia, we found intermittently measurable ammonium concentrations at 270 m. Here we show signatures consistent with organic matter of zooplankton/forage fish origin in the C:N and δ¹³C of suspended and sinking organic matter at the vertical migration depth that suggest transportation to these depths by migrating zooplankton/forage fish. Also coincident with the migration maximum was a reproducible-between-years maximum in the biological N₂ gas, and a repeatable shoulder on the nitrite maximum, which suggest that the migrating zooplankton partially fuels N loss. Thus, zooplankton/forage fish appear to be one source of organic matter which can fuel N₂ production in ODZs.

Wetlands are the largest and most climate-sensitive natural sources of methane. Accurately estimating wetland methane emissions involves reconciling inversion (“top-down”) and process-based (“bottom-up”) models within the global methane budget. However, estimates from these two model types are inherently interdependent and often reveal substantial discrepancies. To enhance the reliability of both approaches, we need a comprehensive understanding of wetland methane emissions and an independent high-resolution long-term flux data set. Here, we employed a data-driven random forest approach to identify key variables influencing methane emissions from subtropical freshwater wetlands in the Southeastern United States. The model-estimated monthly mean methane fluxes fit well with measured methane fluxes (R² = 0.67) at four representative FLUXNET-CH4 wetland sites across the region. Variable importance analysis highlighted the sensitivity of subtropical freshwater wetland methane emissions to variations in both temperature and water levels. High temperatures facilitate methanogenesis by enhancing microbial activities, while elevated water levels maintain anaerobic conditions necessary for methane production. Notably, the response of methane emissions to water level fluctuations is contingent on temperature conditions, and vice versa. Moreover, we constructed the first high-spatial-resolution (∼1 km × 1 km) and long-term (1982–2010) gridded regional wetland methane flux product for the Southeastern United States, estimating annual methane emissions from subtropical freshwater wetlands in the region at 4.93 ± 0.11 Tg CH₄ yr⁻¹ for 1982–2010. This new benchmark product holds promise for validating and parameterizing uncertain wetland methane emission processes in bottom-up models and provides improved prior information for top-down models.

Global changes strongly affect methane (CH₄) emissions and uptake. However, it is unclear how CH₄ emissions and uptake across rice paddy fields, uplands, and natural wetlands are affected by global change drivers, including nitrogen (N) addition, elevated carbon dioxide (eCO₂), warming (W), and precipitation (P). Here, we collected 1,250 observations of manipulated experiments from 303 publications during 1980–2020, encompassing 1,154 observations of single-factor experiments and 96 observations of two-paired experiments, and analyzed the effects of global change drivers on CH₄ emissions and uptake. Results showed CH₄ emissions were stimulated by eCO₂, W, and increased P (IP). CH₄ uptake was inhibited by N and IP but significantly enhanced by W and decreased P. The combined effects of the four global change drivers significantly inhibited CH₄ uptake (−9[−12, −6] %) and stimulated CH₄ emissions (13[7, 19] %). Two-factor interactions significantly reduced CH₄ emissions (−15[−27, −1] %) and insignificantly reduced uptake (−10[−19, 0] %). The interactive effects of any two global change drivers were mostly antagonistic. Random forest analysis indicated that the important factors affecting the responses of CH₄ emissions or uptake to different global change drivers varied. The structural equation model confirmed that climate, soil properties, and wetness index consistently played a remarkable role in regulating the responses of CH₄ emissions and uptake to global change drivers. This synthesis highlights an urgent need to consider the individual and interactive effects of multiple global change drivers on CH₄ emissions and uptake for a better understanding of the methane-climate feedback.

This study provides the first comprehensive quantification of three major greenhouse gases (GHGs, including CO₂, CH₄, and N₂O) budgets for Central and West Asia (CWA) from 2000 to 2020, including contributions from fossil fuels, industry, and managed and unmanaged terrestrial ecosystems. We use bottom-up (BU: inventories and process-based models) and top-down approaches (TD: atmospheric inversions) to elucidate CWA's GHG budget and its changes. BU and TD budgets consistently show that CWA was a significant and growing GHG source during the 2010s: average net emissions were 4,175 (range: 4,055–4,301) Tg CO₂eq yr⁻¹ based on BU and using global warming potentials over a 100-year period (GWP100), and slightly higher net emissions of 4,293 (3,760–4,826) Tg CO₂eq yr⁻¹ based on TD. BU estimates show that CO₂ emissions from fossil fuel combustion and fugitive releases were the dominant source, accounting for 61% of the total budget in the 2010s, with 2,554 (2,526–2,582) Tg CO₂eq yr⁻¹. Terrestrial natural ecosystems were a weak CO₂ sink and sources of CH₄ and N₂O, which together resulted in a decadal mean net GHG emission of 220.5 (114.5–332.8) Tg CO₂eq yr⁻¹. Non-CO₂ gases, primarily CH₄, contributed significantly to the region's GHG emissions, accounting for 32% (BU) and 24% (TD) of CWA's total GHG budget under GWP100, and increasing to 57% (BU) and 49% (TD) with GWP20, highlighting CH₄ stronger warming impact over shorter timescales. Overall, CWA contributed about 8% of global net GHG emissions in the 2010s, with about 10% of global CO₂, 7% of CH₄, and 3% of N₂O.

The Red Sea is an extremely warm tropical sea hosting diverse ecosystems, with marine organisms operating at the high end of their thermal tolerance. Therefore, in the context of global warming, it is increasingly important to understand the Red Sea ecosystem, including the variability of chlorophyll at different spatiotemporal scales. Using a coupled physical–biogeochemical model and in situ data, we investigate and quantify the diel cycle in Red Sea chlorophyll concentration for the first time, revealing near-sunset chlorophyll maxima at 17 ± 1 hr local time over the entire basin. This chlorophyll peak time is considerably later than those reported in most other oceans, reflecting the previously reported high irradiance and further suggesting potentially low grazing rates in the Red Sea. Model-based analyses reveal that chlorophyll diel cycle is predominantly controlled by light-driven circadian rhythm (i.e., irradiance), whereas longer-timescale (e.g., seasonal) chlorophyll variability is regulated by nutrient availability, suggesting a light-limited biological production on a diel timescale and a nutrient-limited production on a seasonal scale. The identified chlorophyll diel cycle comprises a fundamental component of the Red Sea ecology and has implications for chlorophyll remote sensing and in situ measurements. Our findings indicate that future field studies investigating phytoplankton growth and zooplankton grazing dynamics—such as phytoplankton community composition and zooplankton diel vertical migration—are still needed to further elucidate the revealed chlorophyll diel cycle in this potentially unique tropical sea.

Large-scale geographical distributions in nitrogen and carbon stable isotope ratios (δ¹⁵N and δ¹³C) of particulate organic matter (POM) are essential to understand the variation in the baseline of pelagic food webs in the Pacific Ocean, where phytoplankton production and biological N₂ fixation are highly variable because of heterogeneity of nitrate and iron supply. Here, we determined their isoscapes during summer and discussed potential factors characterizing regional ecosystems from the viewpoint of nitrogen cycling. We collected a total of 2,289 and 2,278 isotope values for δ¹³C and δ¹⁵N, respectively, by synthesizing previously published data with our newly measured data, and analyzed their relationships with temperature, concentrations of nitrate and chlorophyll-a, and N₂ fixation activity, obtained from databases. POM δ¹³C and δ¹⁵N regionally varied in ranges of −30 to −18‰ and −4 to 14‰, respectively. POM δ¹³C was correlated positively with temperature throughout the ocean. In contrast, POM δ¹⁵N was negatively correlated with nitrate concentration at high latitudes and with N₂ fixation activity at low latitudes. High values (>8‰) of POM δ¹⁵N were identified mainly in the marginal area of equatorial upwelling; the highest values (10–14‰) were in the subtropical Southeastern Pacific. Using the isotopic values and nitrate concentration, we classified the ecosystems into 10 groups. Our data demonstrated the distribution patterns of ecosystems with different degrees of nitrate utilization, which are presumably associated with iron supply, and ecosystems sustained by different nitrogen sources: diazotrophic nitrogen and nitrate supplied below the nitracline and/or horizontally advected.