High producing grazed pastures occupy almost one third of Aotearoa New Zealand (268,000 km2) and produce exported protein to feed more than 40 million people. Trends within farming systems include increasing rates of urea fertiliser use and greater concentrations of N via urine deposition, which enhance N2O emissions and NO3 losses. Focussing on N-sensitive lake catchments, we ask: what tools can reduce uncertainties in the sources and magnitude of N losses, quantify the potential to reduce excess N, and clarify rates of change in N budgets. Dual-isotope NO3 measurements differentiate urine and urea-derived sources (δ15N < 4 ‰) from mineralized soil organic N (δ15N of 4–8 ‰). Nitrate in streams draining the Rotorua region’s pumice soils and aquifers is dominated by urine and urea sources, compared to streams flowing from finer soils that only show these lower δ15N values when large runoff events activate surface flow paths. We have confirmed that shifts in stream water δ2H and δ18O toward the values observed in the major rainfall event coincide with elevated [NO3] and low δ15N representative of urine and urea-derived sources. A combination of δ2H and δ18O and Δ14C in dissolved inorganic carbon (DIC) largely confirmed tritium-based assessments, suggesting lag times of many decades in some aquifers, but rapid responses to recent N inputs elsewhere. In the Southland region, where tile drainage enables effective pasture growth, we explored flow responses in a drainage tile where NO3 consistently showed an imprint of denitrification (δ15N > 12 ‰). In this location following major rainfall, [NO3] remained stable but dissolved organic N concentrations increased, at times associated with stormwater δ2H and δ18O shifts. The Δ14C in DIC yielded apparent ages of several hundred years during low-flow periods, suggesting ongoing breakdown of soil organic matter releases N, which should be considered in farm and catchment N budgets. We conclude that monitoring N concentrations and multiple isotope species can resolve control points of N excess, which reveal targets for potential mitigation. Specifically, N content in clover-ryegrass pastures seasonally exceeds N demand in grazing animals, suggesting alternate species or feeds could reduce animal urinary N excretion, and therefore limit soil-derived N2O emissions and NO3 losses.
The ease with which radionuclide moves through the environment and is taken up by plants and animals is determined by its speciation and site-specific environmental characteristics. The peculiarities in climate, geomorphology and 137Cs speciation in the fallout were demonstrated to lead to differences in migration rates of 137Cs in the environment and rates of its natural attenuation. It has been revealed that in the exclusion zone the Fukushima-derived 137Cs is strongly bound to soil and sediment particles, which reduces potential bioavailability of this radionuclide. Substantial fraction of the deposited 137Cs on soil of the exclusion zone were found to be incorporated in hot glassy particles (“Cs balls”) insoluble in water. These particles are decomposing in the environment essentially slower as compared with Chernobyl derived fuel particles. Wash-off from the slopes of contaminated catchments and river transport are key long-term pathways for radionuclide dispersal from contaminated areas after the Fukushima accident. The climate conditions for the Fukushima Prefecture of Japan are characterized by higher annual precipitation (1300-1800 mm/year) with maximum rainstorm events during typhoon season. Typhoons Etou in 2015 and Hagibis in 2019 demonstrated the substantial redistribution of 137Cs on river watersheds and floodplains and in some cases natural self-decontamination occurred. Steep slopes of Fukushima catchments are conducive to higher erosion and higher particulate r-Cs wash-off. Irrigation ponds in Okuma and Futaba towns demonstrated persistent behavior of 137Cs similar to the closed lakes in Chernobyl, its concentration is decreasing slowly and showing regular seasonal variations: the 137Cs concentrations tend to grow in the summer and decrease in the winter.
We empirically test our earlier theoretical arguments about simplification of continuous-time random walk (CTRW) solute transport models, namely that without loss of generality the velocity-like term may be set to mean groundwater velocity, the dispersion-like term defined by a classical, velocity-independent dispersivity, and the so-called time constant, τ, set to unity. We also argue that for small-scale heterogeneous advection (HA) and mobile-immobile mass transfer (MIMT) CTRW transition time distributions, Ψ(t), are unaffected by mean flow velocity. To experimentally test these claims, we re-analyze two bench-scale transport experiments—one for HA, one for MIMT—each performed at multiple flow rates in otherwise identical conditions, and show it is possible to simultaneously explain all breakthrough curves in each, subject to the above constraints. We compare our calibrations with earlier efforts for the same data sets. In the HA calibration we identify a Ψ(t) of the same functional form as previous authors, and which yielded breakthrough predictions essentially identical to theirs, but with greatly differing parameters. This illustrates how values of individual CTRW parameters may not map one-to-one onto underlying physics. We recommend reporting complete model descriptions, discuss how the simplified approach assists in this and other theoretical considerations.
Lakes and reservoirs are a significant source of atmospheric methane (CH4), with emissions comparable to the largest global CH4 emitters. Understanding the processes leading to such significant emissions from aquatic systems is therefore of primary importance for producing more accurate projections of emissions in a changing climate. In this work, we present the first deployment of a novel membrane inlet laser spectrometer (MILS) for fast simultaneous detection of dissolved CH4, C2H6 and d13CH4. During a 1-day field campaign, we performed 2D mapping of surface water of Lake Aiguebelette (France). In the littoral (pelagic) area, average dissolved CH4 concentrations and d13CH4 were 391.9 ± 156.3 (169.8 ± 26.6) nmol L-1 and -67.3 ± 3.4 (-61.5 ± 3.6) ‰, respectively. The dissolved CH4 concentration in the pelagic zone was fifty times larger than the concentration expected at equilibrium with the atmosphere, confirming an oversaturation of dissolved CH4 in surface waters over shallow and deep areas. The results suggest the presence of CH4 sources less enriched in 13C in the littoral zone (presumably the littoral sediments). The CH4 pool became more enriched in 13C with distance from shore, suggesting that oxidation prevailed over epilimnetic CH4 production, that was further confirmed by an isotopic mass balance technique with the high-resolution transect data. This new in situ fast response sensor allows to obtain unique high-resolution and high-spatial coverage datasets within a limited amount of survey time. This tool will be useful in the future for studying processes governing CH4 dynamics in aquatic systems.
Estimates of net primary (NPP) and ecosystem production (NEP) are needed for tropical savanna, which is structurally diverse but understudied compared to tropical rainforest. Estimates of NPP and NEP are available from eddy covariance and inventory methods, but both approaches have errors and uncertainties. We used both methods to estimate carbon (C) fluxes for an upland mixed grassland and a seasonally flooded forest to determine the correspondence in C cycling components derived from these methods and assess the contribution of the various C cycling components to the overall NEP. Both techniques provided similar estimates of NPP, NEP, and gross primary production (GPP). Belowground NPP accounted for 49-53% of the total NPP for both ecosystems, followed by aboveground litter (26-27%) and wood (16-17%) production. Increases in water availability increased the potential for C storage, but the mechanism was different in the savanna types with an increase in soil moisture causing higher NPP in the mixed grassland but lower ecosystem respiration (Reco) in the Cerrado forest. Compared to other savanna ecosystems, the mixed grassland had a similar rate of Reco but lower productivity and C use efficiency (CUE = NPP/GPP = 0.28). The Cerrado forest had a high CUE (0.58) and similar C flux rates to other tropical savanna forests and woodlands. While our measurements are spatially and temporally limited, the agreement in C fluxes estimated using inventory and eddy covariance methods suggest that the C cycle estimates for these savanna ecosystems are robust.
Pialassa Baiona is a shallow temperate coastal lagoon influenced by a variety of factors, including regional climate change and local anthropogenic disturbances. To better understand how these factors influenced modern organic carbon (OC) sources and accumulation, we measured OC as well as stable carbon isotopes (d13C) in 210Pb-dated sediments within a vegetated saltmarsh habitat and a human impacted habitat. Relative Sea Level (RSL) at the nearby tide gauge station data and four different Sea Surface Temperature (SST) data sets were analyzed starting from 1900 to assess the potential effect of sea ingression and warming on the coastal lagoon sedimentary process. The source contribution calculated from the MixSIAR Bayesian model revealed a mixed sedimentary organic matter (OM) composition dominated by increasing marine-derived OM after the 1950s, parallel with decreasing autochthonous saltmarsh vegetation (Juncus spp.) in the saltmarsh habitat and riverine-estuarine-derived OM in the impacted habitat. RSL rise in the area (8.7±0.5 mm yr−1 in the period 1900-2014) has been mainly driven by the land subsidence, especially during the central decades of the last century, enhancing the sea ingression in the lagoon. Annual SST anomalies present, starting from the eighties, a continuous warming tendency from 0.034±0.01 to 0.044±0.009°C yr-1. No direct effect on sedimentary properties was detected; however, RSL influenced OM sediment properties, although this effect was different between the two habitats.
Soil organic carbon (SOC) stocks represent a large component of the global carbon cycle that is sensitive to warming. Modeling and empirical studies often assume that temperature responses of microbial physiological functions and extracellular enzymatic reactions are predictive of ecosystem-scale SOC decomposition responses to warming. However, temperature-dependent soil trophic interactions such as predation of microbial decomposers by other organisms have not yet been incorporated into quantitative SOC models. Here, we incorporated a microbial predator into a tri-trophic population ecology model and a global-scale predictive SOC model to determine how predation would affect soil community population dynamics and temperature sensitivity of SOC stocks. Predators increased SOC stocks and their dependence on substrate input rates. Top-down controls of predators on microbial biomass caused SOC warming responses to diverge from microbial temperature responses, with warming-induced SOC losses reduced or reversed when predators were more temperature-sensitive. Our results suggest that higher trophic levels can reduce the sensitivity of SOC to warming, and that differences in temperature sensitivity across trophic levels may be a key determinant of SOC warming responses.
Due to its substantial role on the Earth’s biogeochemical cycles and human health, nitrogen is recognized as one of the major water quality indicators of Sustainable Development Goal 6.3.2. Quantifying these potential impacts in large spatial scales still appears to be a grand challenge because of the high computational demand required by the distributed physically based global models and their intensive data requirements for calibration and validation. The former prevents a comprehensive analysis of the full spectrum of the model behavior under different conditions, and the latter impinges on the reliability of model-based inference. To tackle this problem, we developed a data-driven model using a spatio-temporal Random Forest algorithm to predict levels of nitrogen at 0.5-degree spatial resolution from 1992 to 2010 across the world. Several variables representing livestock, climate, hydrology, topography, etc. have been selected as predictors. The response variable of interest was nitrate–nitrite, which is responsible for the high risk of infant methemoglobinemia. Our results indicate that changes in the nitrogen concentration is mainly driven by cattle and sheep population, fertilizer application, precipitation, and temperature variability, implying livestock population, climate change, and anthropogenic forces can be important risk factors for global water quality deterioration. Furthermore, using the predicted levels of nitrogen, we characterized large-scale water quality patterns, and thus identified a few major ‘hot spots’ of water quality. The proposed model can also help assess potential impacts of future scenarios (e.g., livestock production or land use change) on global water quality conditions for better development of effective policy strategies.
Carbon fluxes from agroecosystems contribute to the variability in the carbon cycle and atmospheric [CO2]. In this study, we used the Integrated Science Assessment Model (ISAM) equipped with a spring wheat module to study carbon fluxes and their variability in spring wheat agroecosystems of India. First, ISAM was run in the site-scale mode to simulate the Gross Primary Production (GPP), Total Ecosystem Respiration (TER), and Net Ecosystem Production (NEP) over an experimental spring wheat site in the north India. Comparison with flux-tower observations showed that the spring wheat module in ISAM can match the observed flux patterns better than generic crop models. Next, regional-scale runs were conducted to simulate carbon fluxes across the country for the 1980-2016 period. Results showed that the fluxes vary widely, primarily due to variations in planting dates across regions. Fluxes peak earlier in the eastern and central parts of the country, where the crops are planted earlier. All fluxes show statistically significant increasing trends (p<.01) during the study period. The GPP, Net Primary Production (NPP), Autotrophic respiration (Ra), and Heterotrophic Respiration (Rh) increased at 1.272, 0.945, 0.579, 0.328, and 0.366 TgC/yr2, respectively. Numerical experiments were conducted to study how natural forcings like changing temperature and [CO2] and agricultural management practices like nitrogen fertilization and water availability could contribute to the increasing trends. The experiments revealed that increasing [CO2], nitrogen fertilization, and water added through irrigation contributed to the increase of carbon fluxes, with nitrogen fertilization having the strongest effect.