Journal of Geophysical Research: Biogeosciences

doi: 10.1002/jgrg.20106pmid: N/A

No abstract is available for this article.

Madani, Nima; Kimball, John S.; Affleck, David L. R.; Kattge, Jens; Graham, Jon; Bodegom, Peter M.; Reich, Peter B.; Running, Steven W.

doi: 10.1002/2014JG002709pmid: N/A

A common assumption of remote sensing‐based light use efficiency (LUE) models for estimating vegetation gross primary productivity (GPP) is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed constant biome maximum light use efficiency parameter (LUEmax) defines the maximum photosynthetic carbon conversion rate under these conditions and is a large source of model uncertainty. Here we used tower eddy covariance measurement‐based carbon (CO2) fluxes for spatial estimation of optimal LUE (LUEopt) across North America. LUEopt was estimated at 62 Flux Network sites using tower daily carbon fluxes and meteorology, and satellite observed fractional photosynthetically active radiation from the Moderate Resolution Imaging Spectroradiometer. A geostatistical model was fitted to 45 flux tower‐derived LUEopt data points using independent geospatial environmental variables, including global plant traits, soil moisture, terrain aspect, land cover type, and percent tree cover, and validated at 17 independent tower sites. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from the sparse tower network. Leaf nitrogen content and soil moisture regime are major factors explaining LUEopt patterns. GPP derived from estimated LUEopt shows significant correlation improvement against tower GPP records (R2 = 76.9%; mean root‐mean‐square error (RMSE) = 257 g C m−2 yr−1), relative to alternative GPP estimates derived using biome‐specific LUEmax constants (R2 = 34.0%; RMSE = 439 g C m−2 yr−1). GPP determined from the LUEopt map also explains a 49.4% greater proportion of tower GPP variability at the independent validation sites and shows promise for improving understanding of LUE patterns and environmental controls and enhancing regional GPP monitoring from satellite remote sensing.

Koyano, Hitoshi; Tsubouchi, Taishi; Kishino, Hirohisa; Akutsu, Tatsuya

doi: 10.1002/2014JG002676pmid: N/A

Recently, deep drilling into the seafloor has revealed that there are vast sedimentary ecosystems of diverse microorganisms, particularly archaea, in subsurface areas. We investigated the β diversity patterns of archaeal communities in sediment layers under the seafloor and their determinants. This study was accomplished by analyzing large environmental samples of 16S ribosomal RNA gene sequences and various geochemical data collected from a sediment core of 365.3 m, obtained by drilling into the seafloor off the east coast of the Shimokita Peninsula. To extract the maximum amount of information from these environmental samples, we first developed a method for measuring β diversity using sequence data by applying probability theory on a set of strings developed by two of the authors in a previous publication. We introduced an index of β diversity between sequence populations from which the sequence data were sampled. We then constructed an estimator of the β diversity index based on the sequence data and demonstrated that it converges to the β diversity index between sequence populations with probability of 1 as the number of sampled sequences increases. Next, we applied this new method to quantify β diversities between archaeal sequence populations under the seafloor and constructed a quantitative model of the estimated β diversity patterns. Nearly 90% of the variation in the archaeal β diversity was explained by a model that included as variables the differences in the abundances of chlorine, iodine, and carbon between the sediment layers.

Yu, Zhongjie; Slater, Lee D.; Schäfer, Karina V. R.; Reeve, Andrew S.; Varner, Ruth K.

doi: 10.1002/2014JG002654pmid: N/A

Methane (CH4) ebullition in northern peatlands is poorly quantified in part due to its high spatiotemporal variability. In this study, a dynamic flux chamber (DFC) system was used to continuously measure CH4 fluxes from a monolith of near‐surface Sphagnum peat at the laboratory scale to understand the complex behavior of CH4 ebullition. Coincident transmission ground penetrating radar measurements of gas content were also acquired at three depths within the monolith. A graphical method was developed to separate diffusion, steady ebullition, and episodic ebullition fluxes from the total CH4 flux recorded and to identify the timing and CH4 content of individual ebullition events. The results show that the application of the DFC had minimal disturbance on air‐peat CH4 exchange and estimated ebullition fluxes were not sensitive to the uncertainties associated with the graphical model. Steady and episodic ebullition fluxes were estimated to be averagely 36 ± 24% and 38 ± 24% of the total fluxes over the study period, respectively. The coupling between episodic CH4 ebullition and gas content within the three layers supports the existence of a threshold gas content regulating CH4 ebullition. However, the threshold at which active ebullition commenced varied between peat layers with a larger threshold (0.14 m3 m−3) observed in the deeper layers, suggesting that the peat physical structure controls gas bubble dynamics in peat. Temperature variation (23°C to 27°C) was likely only responsible for small episodic ebullition events from the upper peat layer, while large ebullition events from the deeper layers were most likely triggered by drops in atmospheric pressure.

Yao, Jian; Hockaday, William C.; Murray, Darrel B.; White, Joseph D.

doi: 10.1002/2014JG002619pmid: N/A

Fire‐derived black carbon (BC) in soil, including charcoal, represents an important part in terrestrial carbon cycling due to its assumed long persistence in soil. Soil BC concentrations for a woodland in central Texas, USA, was found from study plots with a fire scar dendrochronology spanning 100 years. BC values were initially determined from 13C nuclear magnetic resonance (NMR) spectroscopy. The NMR‐based BC concentrations were used to calibrate midinfrared vibrational spectra (MIRS) for evaluation as a less expensive and expedient technique. However, unexpectedly high BC values from the MIRS method were found for sites without evidence of fire for the past 100 years. Estimation of BC from NMR technique showed mean BC concentration of 2.73 ± 3.06 g BC kg−1 (0.91 ± 0.51 kg BC m−2) for sites with fire occurrence within the last 40 years compared with BC values of 1.21 ± 1.70 g BC kg−1 soil (0.18 ± 0.14 kg BC m−2) for sites with fire 40–100 years ago. Sites with no tree ring evidence of fire during the last 100 years had the lowest mean soil BC concentration of 0.05 ± 0.11 g BC kg−1 (0.02 ± 0.03 kg BC m−2). Molecular proxies of stability (lignin/N) and decomposition (Alkyl C/O‐Alkyl C) showed no differences across the sites, indicating low potential for BC mineralization. Modeled soil erosion and time since fire from fire scar data showed that soil BC concentrations were inversely correlated. These results suggest that the addition of BC may be limited by topography and timing of fire.

Jiménez, Eliana M.; Peñuela‐Mora, María Cristina; Sierra, Carlos A.; Lloyd, Jon; Phillips, Oliver L.; Moreno, Flavio H.; Navarrete, Diego; Prieto, Adriana; Rudas, Agustín; Álvarez, Esteban; Quesada, Carlos A.; Grande‐Ortíz, Maria Angeles; García‐Abril, Antonio; Patiño, Sandra

Abdel Aal, Gamal Z.; Atekwana, Estella A.; Revil, A.

doi: 10.1002/2014JG002659pmid: N/A

Previous studies have linked biogeophysical signatures to the presence of iron minerals resulting from distinct biophysicochemical processes. Utilizing geophysical methods as a proxy of such biophysicochemical processes requires an understanding of the geophysical signature of the different iron minerals. Laboratory experiments were conducted to investigate the complex conductivity and magnetic susceptibility signatures of five iron minerals disseminated in saturated porous media under variable iron mineral content and grain size. Both pyrite and magnetite show high quadrature and inphase conductivities compared to hematite, goethite, and siderite, whereas magnetite was the highly magnetic mineral dominating the magnetic susceptibility measurements. The quadrature conductivity spectra of both pyrite and magnetite exhibit a well‐defined characteristic relaxation peak below 10 kHz, not observed with the other iron minerals. The quadrature conductivity and magnetic susceptibility of individual and a mixture of iron minerals are dominated and linearly proportional to the mass fraction of the highly conductive (pyrite and magnetite) and magnetic (magnetite) iron minerals, respectively. The quadrature conductivity magnitude increased with decreasing grain size diameter of magnetite and pyrite with a progressive shift of the characteristic relaxation peak toward higher frequencies. The quadrature conductivity response of a mixture of different grain sizes of iron minerals is shown to be additive, whereas magnetic susceptibility measurements were insensitive to the variation in grain size diameters (1–0.075 mm). The integration of complex conductivity and magnetic susceptibility measurements can therefore provide a complimentary tool for the successful investigation of in situ biophysicochemical processes resulting in biotransformation or secondary iron mineral precipitation.

Cuss, C. W.; Shi, Y. X.; McConnell, S. M.; Guéguen, C.

doi: 10.1002/2013JG002598pmid: N/A

Dissolved organic matter is a ubiquitous constituent of natural waters that plays key roles in several important processes. The fluorescence properties of DOM have been linked to its functionality, but these properties may vary with pH. In this study Kohonen's self‐organizing maps (SOMs) were applied to excitation‐emission matrices (EEMs) of fresh dissolved organic matter (DOM) from three sources: senescent sugar‐maple leaves and white spruce needles, and humified white spruce needles, over a pH range of ~4.5 – 12.5. SOMs were applied to raw EEMs, EEMs reduced in dimensionality by pre‐processing using parallel factor analysis (PARAFAC), and PARAFAC loading proportions normalized to values at initial pH. Some separation of EEMs into source‐based clusters was achieved in the SOM of raw EEMs, but commingling was apparent and evidence of changes over pH gradients was overshadowed. SOMs of PARAFAC component proportions demonstrated clear source‐based clustering, and pH‐based gradients were visible for DOM from senescent and humified spruce needles. Changes in optical properties were obvious over pH gradients in the SOM of components normalized to starting condition. Component proportions decreased to values as low as 5% of the initial values for microbial humic‐like peak M and increased to as high as 278% for a humic‐like component. Tyrosine‐like fluorescence increased to 112% of initial over increasing pH in humified spruce leachates but decreased to as low as 45% in the other leachates. The combination of PARAFAC and SOM drastically enhanced visualization and interpretability of pH‐induced changes in DOM compared to either method alone.

Pumpanen, Jukka; Lindén, Aki; Miettinen, Heli; Kolari, Pasi; Ilvesniemi, Hannu; Mammarella, Ivan; Hari, Pertti; Nikinmaa, Eero; Heinonsalo, Jussi; Bäck, Jaana; Ojala, Anne; Berninger, Frank; Vesala, Timo

Obryk, M. K.; Doran, P. T.; Priscu, J. C.

doi: 10.1002/2014JG002672pmid: N/A

The thick permanent ice cover on the lakes of the McMurdo Dry Valleys, Antarctica, inhibits spatial lake sampling due to logistical constraints of penetrating the ice cover. To date most sampling of these lakes has been made at only a few sites with the assumption that there is a spatial homogeneity of the physical and biogeochemical properties of the ice cover and the water column at any given depth. To test this underlying assumption, an autonomous underwater vehicle (AUV) was deployed in Lake Bonney, Taylor Valley. Measurements were obtained over the course of 2 years in a 100 × 100 m horizontal sampling grid (at a 0.2 m vertical resolution). Additionally, the AUV measured the ice thickness (in water equivalent) and collected images looking up through the ice, which were used to quantify sediment distribution on the surface and within the ice. Satellite imagery was used to map sediment distribution on the surface of the ice. We present results of the spatial investigation of the sediment distribution on the ice cover and its effects on biological processes, with particular emphasis on photosynthetically active radiation (PAR). The surface sediment is a secondary controller of the ice cover thickness, which in turn controls the depth‐integrated PAR in the water column. Our data revealed that depth‐integrated PAR was negatively correlated with depth‐integrated chlorophyll‐a (r = 0.88, p < 0.001, n = 83), which appears to be related to short‐term photoadaptation of phytoplanktonic communities to spatial and temporal variation in PAR within the water column.