We use a numerical model of sulfur diagenesis in marine sediments to investigate the impact of kinetic isotope effects during sulfate reduction (KIESR) and sulfide oxidation (KIEOX) on  34 S values of dissolved sulfide and sedimentary pyrite formed from it. There are two versions of the model: one where rates of sulfide oxidation are limited by the molecular diffusion of oxygen from the water column, and another where sedimentary rates of oxidation are significantly enhanced due to an assumed bacterial transport of an oxidant such as nitrate into the sediment. The effective isotope discrimination at the sediment-water interface ( 34 SSWI =  34 SH2S  34 SSO4=) is greatest at low rates of reduction and/or high rates of sulfide oxidation.  34 SSWI cannot exceed the isotope effect associated with sulfate reduction, KIESR, without additional isotope effects such as fractionation during sulfide oxidation, i.e. KIEOX. When sulfide oxidation rates are controlled by diffusion of oxygen, the primary control on  34 SSWI is the rate of sulfate reduction and KIESR. Depth-profiles of sulfate reduction rates (SR) are described using a maximum rate (SRmax), usually at the SWI, and an efolding depth (Ze-SR), where Ze-SR is the depth where SR is equal to 1/e X SRmax. For a given e-folding depth,  34 SSWI is a strong linear function of rate of reduction. At low rates of sulfate reduction, large values of KIEOX, such as those observed during disproportionation of elemental sulfur, can cause additional isotopic depletion in pore water dissolved sulfide of up to 10‰ at 40 cm in the sediment, but only 1-2‰ at the sediment-water interface (SWI) Since  34 S of pyrite is primarily controlled by the isotope ratio of dissolved sulfide at the SWI,  34 SSWI, isotope effects during disproportionation should increase depletion in  34 S of pyrite by no more than about 7‰. If sulfide oxidation rates are enhanced by transport of oxidants such as nitrate into the sediment, it can be much more effective at increasing depletions in  34 S values of dissolved sulfide and pyrite, both at the sediment-water interface (SWI) and at depth. Under these circumstances, KIEOX could be responsible for the depletion of 10‰ or more observed in sulfur in the top 5 cm of sediments from the Peru Margin and other anaerobic environments. Finally, if pyrite formation is associated with even small kinetic isotope effect (KIEPYR ~ 1‰) and is a substantial sink for H2S near the SWI, it can result in a significant depletion in  34 SSWI.

Biogeochemical models must include a broad variety of biological and physical processes to test our understanding of the terrestrial carbon cycle and to predict ecosystem biomass and carbon fluxes. We combine the photosynthesis and biophysical calculations in the Simple Biosphere model, Version 2.5 (SiB2.5) with the biogeochemistry from the Carnegie‐Ames‐Stanford Approach (CASA) model to create SiBCASA, a hybrid capable of estimating terrestrial carbon fluxes and biomass from diurnal to decadal timescales. We add dynamic allocation of Gross Primary Productivity to the growth and maintenance of leaves, roots, and wood and explicit calculation of autotrophic respiration. We prescribe leaf biomass using Leaf Area Index (LAI) derived from remotely sensed Normalized Difference Vegetation Index. Simulated carbon fluxes and biomass are consistent with observations at selected eddy covariance flux towers in the AmeriFlux network. Major sources of error include the steady state assumption for initial pool sizes, the input weather data, and biases in the LAI.

We introduce a multistage model of carbon isotope discrimination during C3 photosynthesis and global maps of C3/C4 plant ratios to an ecophysiological model of the terrestrial biosphere (SiB2) in order to predict the carbon isotope ratios of terrestrial plant carbon globally at a 1° resolution. The model is driven by observed meteorology from the European Centre for Medium‐Range Weather Forecasts (ECMWF), constrained by satellite‐derived Normalized Difference Vegetation Index (NDVI) and run for the years 1983–1993. Modeled mean annual C3 discrimination during this period is 19.2‰; total mean annual discrimination by the terrestrial biosphere (C3 and C4 plants) is 15.9‰. We test simulation results in three ways. First, we compare the modeled response of C3 discrimination to changes in physiological stress, including daily variations in vapor pressure deficit (vpd) and monthly variations in precipitation, to observed changes in discrimination inferred from Keeling plot intercepts. Second, we compare mean δ13C ratios from selected biomes (Broadleaf, Temperate Broadleaf, Temperate Conifer, and Boreal) to the observed values from Keeling plots at these biomes. Third, we compare simulated zonal δ13C ratios in the Northern Hemisphere (20°N to 60°N) to values predicted from high‐frequency variations in measured atmospheric CO2 and δ13C from terrestrially dominated sites within the NOAA‐Globalview flask network. The modeled response to changes in vapor pressure deficit compares favorably to observations. Simulated discrimination in tropical forests of the Amazon basin is less sensitive to changes in monthly precipitation than is suggested by some observations. Mean model δ13C ratios for Broadleaf, Temperate Broadleaf, Temperate Conifer, and Boreal biomes compare well with the few measurements available; however, there is more variability in observations than in the simulation, and modeled δ13C values for tropical forests are heavy relative to observations. Simulated zonal δ13C ratios in the Northern Hemisphere capture patterns of zonal δ13C inferred from atmospheric measurements better than previous investigations. Finally, there is still a need for additional constraints to verify that carbon isotope models behave as expected.

Estimating discrimination against 13C during photosynthesis at landscape, regional, and biome scales is difficult because of large‐scale variability in plant stress, vegetation composition, and photosynthetic pathway. Here we present estimates of 13C discrimination for northern biomes based on a biosphere‐atmosphere model and on National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostics Laboratory and Institute of Arctic and Alpine Research remote flask measurements. With our inversion approach, we solved for three ecophysiological parameters of the northern biosphere (13C discrimination, a net primary production light use efficiency, and a temperature sensitivity of heterotrophic respiration (a Q10 factor)) that provided a best fit between modeled and observed δ13C and CO2. In our analysis we attempted to explicitly correct for fossil fuel emissions, remote C4 ecosystem fluxes, ocean exchange, and isotopic disequilibria of terrestrial heterotrophic respiration caused by the Suess effect. We obtained a photosynthetic discrimination for arctic and boreal biomes between 19.0 and 19.6‰. Our inversion analysis suggests that Q10 and light use efficiency values that minimize the cost function covary. The optimal light use efficiency was 0.47 gC MJ−1 photosynthetically active radiation, and the optimal Q10 value was 1.52. Fossil fuel and ocean exchange contributed proportionally more to month‐to‐month changes in the atmospheric growth rate of δ13C and CO2 during winter months, suggesting that remote atmospheric observations during the summer may yield more precise estimates of the isotopic composition of the biosphere.

The measured atmospheric CO2 growth rate is half that expected based on fossil fuel emissions. Modeling, isotope, and inversion studies place much of this “missing sink” in the northern hemisphere terrestrial biosphere. The global, atmospheric CO2 growth rate shows a great deal of inter-annual variability [Conway et al., 1994; LLoyd, 1999; Rayner and Law, 1999; Tans and Wallace, 1999; Bousquet et al., 2000; Fung, 2000]. The ocean fluxes show relatively low variability [Rayner and Law, 1999, Le Quéré et al., 2000], so growth rate variability is attributed primarily to changes in the terrestrial sink [Sarmiento, 1993, Conway et al., 1994; Trolier et al., 1996; Kaduk and Heimann, 1997; LLoyd, 1999; Houghton et al., 1998; Tans and Wallace, 1999; Houghton, 2000; Prince et al., 2000]. Climate, land use change, natural disturbance, CO2 fertilization, and nitrogen deposition all affect terrestrial CO2 fluxes [Conway et al., 1994; Bousquet et al., 2000, Fung, 2000, Houghton, 2000]. Climate is most important [Houghton, 2000], but how precipitation, temperature, and other climate factors control net terrestrial CO2 fluxes is unclear. Net Ecosystem Exchange (NEE) is the net CO2 flux from the terrestrial biosphere: GPP R NEE − = , (2) where R is respiration, and GPP is gross primary production or photosynthesis. Photosynthesis removes CO2 from the atmosphere and respiration returns CO2 to the atmosphere. A positive NEE indicates a net CO2 flux into the atmosphere. Breaking R into autotrophic and heterotrophic respiration gives GPP R R R NEE C R H − + + = , (3)

The present study employs a method for analysis of the sulfur isotopic composition of trace sulfate extracted from carbonates collected in Namibia in order to document secular variations in the sulfur isotopic composition of Neoproterozoic oceanic sulfate and to assess variations in the sulfur cycle that may have accompanied profound climatic events that have been described as the snowball Earth hypothesis. The carbonates in the Otavi Group of Northwest Namibia contain 3–295 ppm sulfate. Positive excursions, to a high of 40‰ (CDT), occur above the lower (Chuos Formation) and upper (Ghaub Formation) glacial intervals in the Rasthof and Maieberg cap carbonates, respectively. Positive excursions at the top of the Rasthof Formation (reaching 51‰) and within the overlying Gruis Formation (34‰) do not appear to correspond to glaciation. The δ34Ssulfate values within the Ombaatjie Formation exhibit shifts over relatively short stratigraphic intervals (tens of meters), varying between ∼15 and 25‰. Cap carbonates from Australia exhibit positive δ34Spyrite trends with amplitudes similar to those of Namibian δ34Ssulfate, although, more data are necessary to firmly establish these δ34S trends as global in nature. δ34Ssulfate excursions found in Namibian cap carbonates are consistent with the snowball Earth hypothesis in that they appear to reflect nearly complete reduction of sulfate in an isolated, anoxic global ocean, although, there are other mechanisms that may have facilitated these large shifts in δ34Ssulfate. Regardless, the low sulfate concentrations in Otavi carbonates, the high amplitude variability of the δ34Ssulfate curve, and the apparently full reduction of sulfate (as implied from δ34Spyrite data), even in strata low in Corg, suggest that Neoproterozoic oceanic sulfate concentrations were much lower than modern values. Additionally, the buildup of ferrous iron and banded-iron formations during the Sturtian glacial event would indicate that Fe supply exceeded sulfide availability during the glacials and/or that all sulfide was fixed and buried. This could be construed as further evidence in support of low oceanic sulfate (and sulfide) at this time.

It is well known that terrestrial photosynthesis and 13C discrimination vary in response to a number of environmental and biological factors such as atmospheric humidity and genotypic differences in stomatal regulation. Small changes in the global balance between diffusive conductances to CO2 and photosynthesis in C3 vegetation have the potential to influence the 13C budget of the atmosphere because these changes scale with the relatively large one‐way gross primary production (GPP) flux. Over a period of days to years, this atmospheric isotopic forcing is damped by the return flux consisting mostly of respiration, Fire, and volatile organic carbon losses. Here we explore the magnitude of this class of isotopic disequilibria with an ecophysiological model (SiB2) and a double deconvolution inversion framework that includes time‐varying discrimination for the period of 1981–1994. If the net land carbon sink and plant 13C discrimination covary on interannual timescales at the global scale, consistent with El Niño‐induced drought stress causing a decline in global GPP and C3 discrimination, then less interannual variability in ocean and land net carbon exchange is required to explain atmospheric trends in δ13C and CO2 as compared with previous studies that assumed discrimination was invariant.

We evaluated how climate influences interannual variability in the terrestrial Net Ecosystem Exchange (NEE) of CO2 using the Simple Biosphere Model, Version 2 (SiB2) for 1983 to 1993 on a global, 1° by 1° latitude/longitude grid with a 10‐min time step. We quantified climate influences on NEE, explained regional differences, and related NEE variability to the Arctic Oscillation (AO) and the El Niño‐Southern Oscillation (ENSO). The simulated NEE reproduces the salient features and magnitude of the measured global CO2 growth rate. The Northern Hemisphere shows a pattern of alternating positive and negative NEE anomalies that cancel such that the tropics dominate the global simulated NEE interannual variability. Climate influences have strong regional differences with precipitation dominating in the tropics and temperature in the extratropics. In tropical regions with drier soils, precipitation control of photosynthesis (i.e., drought stress) dominates; in nearly saturated soils, precipitation control of respiration dominates. Because of cancellation and competing effects, no single climate variable controls global or regional NEE interannual variability. Globally, precipitation accounts for 44% of NEE variability; followed by Leaf Area Index (23%), soil carbon (12%), and temperature (16%). The influence of ENSO on NEE variability is consistent with that expected for shifting precipitation patterns in the tropics. Except in northern Europe, temperature advection by the AO does not significantly influence NEE variability. Neither the AO nor ENSO fully explain the temperature influence on respiration or the simulated NEE anomaly pattern in the Northern Hemisphere.

Over the past decade, interest in the biogeosciences has expanded at a remarkable rate. This approach to the study of the Earth is by its very nature interdisciplinary and requires an enormous wealth of knowledge. It also requires the ability to make connections between various natural systems and processes. Over a slightly longer period, there has been a widespread effort to document the so‐called ‘average’ composition of geologic and biologic units. In a sense, Li has now helped us to take full advantage of this effort and bring this knowledge to bear on questions arising in the biogeosciences. That is because in his new book, A Compendium of Geochemistry: From Solar Nebula to the Human Brain , he has amassed an exhaustive list of data sets, gathered from numerous sources, and documenting the composition of the natural universe.