Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates.

The recent rise in atmospheric methane (CH4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year-1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.

Vertical Hydrologic Exchange Flows Control Methane Emissions from Riverbed Sediments.

CH4 emissions from inland waters are highly uncertain in the current global CH4 budget, especially for streams, rivers, and other lotic systems. Previous studies have attributed the strong spatiotemporal heterogeneity of riverine CH4 to environmental factors such as sediment type, water level, temperature, or particulate organic carbon abundance through correlation analysis. However, a mechanistic understanding of the basis for such heterogeneity is lacking. Here, we combine sediment CH4 data from the Hanford reach of the Columbia River with a biogeochemical-transport model to show that vertical hydrologic exchange flows (VHEFs), driven by the difference between river stage and groundwater level, determine CH4 flux at the sediment-water interface. CH4 fluxes show a nonlinear relationship with the magnitude of VHEFs, where high VHEFs introduce O2 into riverbed sediments, which inhibit CH4 production and induce CH4 oxidation, and low VHEFs cause transient reduction in CH4 flux (relative to production) due to reduced advective CH4 transport. In addition, VHEFs lead to the hysteresis of temperature rise and CH4 emissions because high river discharge caused by snowmelt in spring leads to strong downwelling flow that offsets increasing CH4 production with temperature rise. Our findings reveal how the interplay between in-stream hydrologic flux besides fluvial-wetland connectivity and microbial metabolic pathways that compete with methanogenic pathways can produce complex patterns in CH4 production and emission in riverbed alluvial sediments.

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions.

Wetlands are the largest natural source of methane (CH4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4 , but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model-iPEACE-reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes.

Coupling plant litter quantity to a novel metric for litter quality explains C storage changes in a thawing permafrost peatland.

Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO2 ) and methane (CH4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post-thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post-thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly through both plants and soil, contributing to higher CO2 and CH4  fluxes from decomposition. Thus, the increased C-storage expected from higher productivity was limited and the high global warming potential of CH4 contributed a net positive warming effect. Although post-thaw peatlands are currently C sinks due to high NPP offsetting high CO2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition.

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions.

Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.

Effect of Small Cage Guests on Dissociation Properties of Tetrahydrofuran Hydrates.

It is well understood that tetrahydrofuran (THF) molecules are able to stabilize the large cages (51264) of structure II to form the THF hydrate with empty small cages even at atmospheric pressure. This leaves the small cages to store gas molecules at relatively lower pressures and higher temperatures. The dissociation enthalpy and temperature strongly depend on the size of gas molecules enclathrated in the small cages of structure II THF hydrate. A high-pressure microdifferential scanning calorimeter was applied to measure the dissociation enthalpies and temperatures of THF hydrates pressurized by helium and methane under a constant pressure ranging from 0.10 to 35.00 MPa and a wide THF concentration ranging from 0.25 to 8.11 mol %. The dissociation temperature of binary He + THF and methane + THF hydrates increases along with an increase in the THF concentration in the liquid phase at a fixed pressure (e.g., 30 MPa), reaching a maximum value of 280.8 and 312.8 K, respectively, at stoichiometric concentration (5.56 mol % THF), and then remains nearly constant for even higher THF concentrations (>5.56 mol %). The effect of gas occupancy in the small cages on the dissociation enthalpy of He + THF and methane + THF mixed hydrates was further examined by using molecular dynamics (MD) simulations. The dissociation enthalpy of the He-THF mixed hydrates is independent of pressure with an average of 5.68 kJ/mol H2O over the pressure ranging from 0.10 to 30.0 MPa, consistent with the MD results of the He-THF mixed hydrates with low single occupancy (<23%) of helium molecules in the small cages. Consequently, the heat of adsorption of helium molecules in the small cages of the He-THF mixed hydrates is rather too weak to be identified. On the other hand, the dissociation enthalpy of the methane-THF hydrates increases from 9.11 to 10.01 kJ/mol H2O along with an increase in methane pressure over the pressure ranging from 5.0 to 30.0 MPa, consistent with the MD results of the methane-THF mixed hydrates with full occupancy of methane molecules in the small cages. These findings provide important information for the design of a potential medium of gas storage and transportation.

Reconstructing One-Articulated Networks with Distance Matrices.

Given a distance matrix M that represents evolutionary distances between any two species, an edge-weighted phylogenetic network N is said to satisfy M if between any pair of species, there exists a path in N with a length equal to the corresponding entry in M. In this article, we consider a special class of networks called a one-articulated network, which is a proper superset of galled trees. We show that if the distance matrix M is derived from an ultrametric one-articulated network N (i.e., for any species X and Y, the entry [Formula: see text] is equal to the shortest distance between X and Y in N), we can re-construct a network that satisfies M in [Formula: see text] time, where n denotes the number of species; further, the reconstructed network is guaranteed to be the simplest, in a sense that the number of hybrid nodes is minimized. In addition, one may easily index a one-articulated network N with a minimum number of hybrid nodes in [Formula: see text] space, such that on any given phylogenetic tree T, we can determine whether T is contained in N (i.e., if a spanning subtree [Formula: see text] of N is a subdivision of T) in [Formula: see text] time.

A learning framework for age rank estimation based on face images with scattering transform.

This paper presents a cost-sensitive ordinal hyperplanes ranking algorithm for human age estimation based on face images. The proposed approach exploits relative-order information among the age labels for rank prediction. In our approach, the age rank is obtained by aggregating a series of binary classification results, where cost sensitivities among the labels are introduced to improve the aggregating performance. In addition, we give a theoretical analysis on designing the cost of individual binary classifier so that the misranking cost can be bounded by the total misclassification costs. An efficient descriptor, scattering transform, which scatters the Gabor coefficients and pooled with Gaussian smoothing in multiple layers, is evaluated for facial feature extraction. We show that this descriptor is a generalization of conventional bioinspired features and is more effective for face-based age inference. Experimental results demonstrate that our method outperforms the state-of-the-art age estimation approaches.

Fluorescence excitation spectra of the b (1)Pi(u), b(') (1)Sigma(u) (+), c(n) (1)Pi(u), and c(n) (') (1)Sigma(u) (+) states of N(2) in the 80-100 nm region.

Fluorescence excitation spectra produced through photoexcitation of N(2) using synchrotron radiation in the spectral region between 80 and 100 nm have been studied. Two broadband detectors were employed to simultaneously monitor fluorescence in the 115-320 nm and 300-700 nm regions, respectively. The peaks in the vacuum ultraviolet fluorescence excitation spectra are found to correspond to excitation of absorption transitions from the ground electronic state to the b (1)Pi(u), b(') (1)Sigma(u) (+), c(n) (1)Pi(u) (with n=4-8), c(n) (') (1)Sigma(u) (+) (with n=5-9), and c(4) (')(v('))(1)Sigma(u) (+) (with v(')=0-8) states of N(2). The relative fluorescence production cross sections for the observed peaks are determined. No fluorescence has been produced through excitation of the most dominating absorption features of the b-X transition except for the (1,0), (5,0), (6,0), and (7,0) bands, in excellent agreement with recent lifetime measurements and theoretical calculations. Fluorescence peaks, which correlate with the long vibrational progressions of the c(4) (') (1)Sigma(u) (+) (with v(')=0-8) and the b(') (1)Sigma(u) (+) (with v(') up to 19), have been observed. The present results provide important information for further unraveling of complicated and intriguing interactions among the excited electronic states of N(2). Furthermore, solar photon excitation of N(2) leading to the production of c(4) (')(0) may provide useful data required for evaluating and analyzing dayglow models relevant to the interpretation of c(4) (')(0) in the atmospheres of Earth, Jupiter, Saturn, Titan, and Triton.