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Summary Despite decades of research to define optimal chamber design and deployment protocol for measuring gas exchange between the Earth's surface and the atmosphere, controversy still surrounds the procedures for applying this method. Using a numerical simulation model we demonstrated that (i) all non‐steady‐state chambers should include a properly sized and properly located vent tube; (ii) even seemingly trivial leakiness of the seals between elements of a multiple‐component chamber results in significant risk of measurement error; (iii) a leaking seal is a poor substitute for a properly designed vent tube, because the shorter path length through the seal supports much greater diffusive gas loss per unit of conductance to mass flow; (iv) the depth to which chamber walls must be inserted to minimize gas loss by lateral diffusion is smaller than is customary in fine‐textured, wet or compact soil, but much larger than is customary in highly porous soils, and (v) repetitive sampling at the same location is not a major source of error when using non‐steady‐state chambers. Finally, we discuss problems associated with computing the flux of a gas from the non‐linear increase in its concentration in the headspace of a non‐steady‐state chamber.

Methane flux was measured in situ in the Alaska Arctic tundra to assess the magnitude and controls on spatial variability of emissions. A total of 122 measurements were made at 57 spatially independent sites across the Alaska North Slope during the summer of 1987. Variability in rates of emissions was similar in magnitude on local and regional scales, ranging from 0 to 286.5 mg CH4 m−2 d−1 overall and often varying across two orders of magnitude within 0.5‐m distances. Primary control on rates of emissions was determined by the substrate and the position of the water table relative to the surface. Secondary controls were defined by the substrate temperature and the type and quantity of vegetation participating in the plant‐mediated release of CH4 to the atmosphere. Emission rates in the Arctic Foothills ranged from 0.2 mg CH4 m−2 d−1 for tussock tundra to 55.3 mg CH4 m−2 d−1 over wet meadows. Within the Arctic Coastal Plain, rates of emissions were highest on inundated terrestrial sites (72.2 mg CH4 m−2 d−1), decreasing nearly 12 fold on comparable sites where the water table was 5 cm or more below the surface (6.1 mg CH4 m−2 d−1). Emission rates increased linearly with substrate temperatures at 10‐cm depth, increasing nearly ninefold over the 6°C temperature range observed. Plant mediated release of CH4 to the atmosphere was directly proportional to green leaf area and represented 92–98% of the total emission rates over vegetated sites. Comparisons between boreal studies reflect similarities in environmental controls on emissions at local‐to‐regional scales and demonstrate the sensitivity of regional to global estimates to sampling bias. These results suggest that current published emissions rates may have overestimated the contribution of boreal ecosystems to the global CH4 budget by several fold.

1. The sources of nitrogen for phytoplankton were determined for a bloom-prone lake as a means of assessing the hypothesis that cyanobacteria dominate in eutrophic lakes because of their ability to fix nitrogen when the nitrogen : phosphorous (N : P) supply ratio is low and nitrogen a limiting resource. 2. Nitrogen fixation rates, estimated through acetylene reduction with 15 N calibration, were compared with 15 N-tracer estimates of ammonium and nitrate uptake monthly during the ice-free season of 1999. In addition, the natural N stable isotope composition of phytoplankton, nitrate and ammonium were measured biweekly and the contribution of N 2 to the phytoplankton signature estimated with a mixing model. 3. Although cyanobacteria made up 81-98% of phytoplankton biomass during summer and autumn, both assays suggested minimal N acquisition through fixation (<9% for the in-situ incubations; <2% for stable isotope analysis). Phytoplankton acquired N primarily as ammonium (82-98%), and secondarily as nitrate (15-18% in spring and autumn, but <5% in summer). Heterocyst densities of <3 per 100 fixer cells confirmed low reliance on fixation. 4. The lake showed symptoms of both light and nitrogen limitation. Cyanobacteria may have dominated by monopolizing benthic sources of ammonium, or by forming surface scums that shaded other algae.

Abstract. We employed a three-dimensional finite difference gas diffusion model to simulate the performance of chambers used to measure surface-atmosphere trace gas exchange. We found that systematic errors often result from conventional chamber design and deployment protocols, as well as key assumptions behind the estimation of trace gas exchange rates from observed concentration data. Specifically, our simulations showed that (1) when a chamber significantly alters atmospheric mixing processes operating near the soil surface, it also nearly instantaneously enhances or suppresses the postdeployment gas exchange rate, (2) any change resulting in greater soil gas diffusivity, or greater partitioning of the diffusing gas to solid or liquid soil fractions, increases the potential for chamber-induced measurement error, and (3) all such errors are independent of the magnitude, kinetics, and/or distribution of trace gas sources, but greater for trace gas sinks with the same initial absolute flux. Finally, and most importantly, we found that our results apply to steady state as well as non-steady-state chambers, because the slow rate of gas diffusion in soil inhibits recovery of the former from their initial non-steady-state condition. Over a range of representative conditions, the error in steady state chamber estimates of the trace gas flux varied from -30 to +32%, while estimates computed by linear regression from non-steadystate chamber concentrations were 2 to 31% too small. Although such errors are relatively small in comparison to the temporal and spatial variability characteristic of trace gas exchange, they bias the summary statistics for each experiment as well as larger scale trace gas flux estimates based on them.

Boreal peatlands occupy about 1.14 x 106 km2 in North America. Fires can spread into peatlands, burning the biomass, and if moisture conditions permit, burning into the surface peat. Charred layers in peat sections reveal that historically bogs in the subhumid continental regions and permafrost peatlands of the subarctic regions have been the most susceptible to fires. Fire return periods were estimated from the numbers and ages of the charred peat layers. Based on average moisture conditions of the surface, about 0.5% of the peatlands (6420 km2) can be expected to burn annually, but the surface peat layer is expected to burn only in a small portion of this area (1160 km2). Carbon losses from aboveground combustion, in the form of CO2, CO, CH4, and nonmethane hydrocarbons, are the highest in forested swamps at 2.03 Tg C ·year-1. Carbon losses due to combustion of surface peat is the highest in the driest peatlands (e.g., raised bogs underlain by permafrost) at 5.82 Tg C ·year-1. The total estimated carbon release due to aboveground combustion is 2.92 Tg C ·year-1 and due to belowground peat combustion is 6.72 Tg C ·year-1. These estimates of direct carbon emissions to the atmosphere due to wildfires suggest a globally significant, but relatively small source in contrast with emissions from wildfires in uplands. The effects of a possible climate change are expected to be most prominent in the continental and northern parts of North America. A lower water table would result in increased CO2 but decreased CH4 emissions from the peatlands. A drier climate may mean increased fire frequency and intensity, resulting in more fires in peatlands and an increased probability of the fires consuming part of the peat.Key words: fire, peatlands, carbon, boreal, permafrost, gas flux.

We compared linear regression with a diffusion‐based model for N2O flux estimation using non‐steady‐state chamber gas concentrations from a long‐term study of N cycling in a managed grass pasture on sandy soil in southern Texas. Of 2224 chamber deployments, 449 met criteria established for using the diffusion‐based model, which yielded flux estimates that averaged 54% larger than linear regression (n = 3). Although they represented only about 20% of all chamber deployments, this group included most of the data with greatest influence on the magnitude and dynamics of total N2O exchange at our site; e.g., of the 263 fluxes >10 g N ha−1 d−1, 192 (or 73%) were included. Apparently, application of a linear model to nonlinear chamber concentration data represents a potentially serious source of measurement bias that may influence not only summary statistics for the experiment, but also larger scale budgets based partially or wholly on those data.

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