The long-solved problem of the best-fit straight line: application to isotopic mixing lines

It has been almost 50 years since York published an exact and general solution for the best-fit straight line to independent points with normally distributed errors in both x and y. York's solution is highly cited in the geophysical literature but almost unknown outside of it, so that there has been no ebb in the tide of books and papers wrestling with the problem. Much of the post-1969 literature on straight-line fitting has sown confusion not merely by its content but by its very existence. The optimal least-squares fit is already known; the problem is already solved. Here we introduce the non-specialist reader to York's solution and demonstrate its application in the interesting case of the isotopic mixing line, an analytical tool widely used to determine the isotopic signature of trace gas sources for the study of biogeochemical cycles. The most commonly known linear regression methods – ordinary least-squares regression (OLS), geometric mean regression (GMR), and orthogonal distance regression (ODR) – have each been recommended as the best method for fitting isotopic mixing lines. In fact, OLS, GMR, and ODR are all special cases of York's solution that are valid only under particular measurement conditions, and those conditions do not hold in general for isotopic mixing lines. Using Monte Carlo simulations, we quantify the biases in OLS, GMR, and ODR under various conditions and show that York's general – and convenient – solution is always the least biased

Amazon rainforests green-up with sunlight in dry season

Metabolism and phenology of Amazon rainforests significantly influence global dynamics of climate, carbon and water, but remain poorly understood. We analyzed Amazon vegetation phenology at multiple scales with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite measurements from 2000 to 2005. MODIS Enhanced Vegetation Index (EVI, an index of canopy photosynthetic capacity) increased by 25% with sunlight during the dry season across Amazon forests, opposite to ecosystem model predictions that water limitation should cause dry season declines in forest canopy photosynthesis. In contrast to intact forests, areas converted to pasture showed dry-season declines in EVI-derived photosynthetic capacity, presumably because removal of deep-rooted forest trees reduced access to deep soil water. Local canopy photosynthesis measured from eddy flux towers in both a rainforest and forest conversion site confirm our interpretation of satellite data, and suggest that basin-wide carbon fluxes can be constrained by integrating remote sensing and local flux measurements

In situ permafrost thaw due to climate change drives holistic microbial community shifts with implications for methane cycling

Thawing permafrost is a potentially significant source of radiative forcing feedback due to increased emissions of methane, a biogenic greenhouse gas (GHG). This study investigated changes in the microbial community along a permafrost thaw gradient at Stordalen Mire, Sweden using 16S rRNA gene amplicon and metagenomic methods. In situ measurements of geochemical parameters, including CH4 and C isotopes, enabled linkage of community dynamics to significant shifts in C balance. The thaw gradient ranged from intact at a palsa (low productivity and GHG emissions), through partially thawed in a bog (high productivity, low GHG emissions) to a completely thawed fen (high productivity and GHG emissions). Microbial assemblages in both the palsa and fen were highly diverse (in both richness and evenness), consistent with climax communities. The microbial community in the bog had distinctly lower diversity, characteristic of ecosystem disturbance. The palsa community was dominated by Acidobacteria and Proteobacteria, as is typical of a range of soils including permafrost. Methanogens dominated both the bog and fen and were most abundant within the zone of water table fluctuation. Inferring methanogens’ production pathway from phylogeny showed a shift from mostly hydrogenotrophic methanogens in the bog towards acetotrophic methanogens in the fen. This corroborated porewater and flux emitted CH4 and CO2 carbon isotopic 13C signatures of CH4 and CO2. The fen, where the highest CH4 flux was recorded, was significantly richer in methanogenic archaea. A novel archaea, Candidatus Methanoflorens stordalenmirensis, was present at up to 70% relative abundance in the bog, enabling recovery of a population genome. The genome (and associated metaproteome) of ’M. stordalenmirensis’ indicates that hydrogenotrophic methane production is its main energy conservation pathway. ’Methanoflorens’ may be an indicator species of permafrost thaw, it is globally ubiquitous, and appears a major contributor to global methane production. Our results revealed a distinct difference in the microbial community structure and membership at each site, which can be directly associated with increasing methane emission and thaw state

Do plant species influence soil CO2 and N2O fluxes in a diverse tropical forest?

To test whether plant species influence greenhouse gas production in diverse ecosystems, we measured wet season soil CO2 and N2O fluxes close to ~300 large (>35 cm in diameter at breast height (DBH)) trees of 15 species at three clay-rich forest sites in central Amazonia. We found that soil CO2 fluxes were 38% higher near large trees than at control sites >10 m away from any tree (P < 0.0001). After adjusting for large tree presence, a multiple linear regression of soil temperature, bulk density, and liana DBH explained 19% of remaining CO2 flux variability. Soil N2O fluxes adjacent to Caryocar villosum, Lecythis lurida, Schefflera morototoni, and Manilkara huberi were 84%-196% greater than Erisma uncinatum and Vochysia maxima, both Vochysiaceae. Tree species identity was the most important explanatory factor for N2O fluxes, accounting for more than twice the N2O flux variability as all other factors combined. Two observations suggest a mechanism for this finding: (1) sugar addition increased N2O fluxes near C. villosum twice as much (P < 0.05) as near Vochysiaceae and (2) species mean N2O fluxes were strongly negatively correlated with tree growth rate (P = 0.002). These observations imply that through enhanced belowground carbon allocation liana and tree species can stimulate soil CO2 and N2O fluxes (by enhancing denitrification when carbon limits microbial metabolism). Alternatively, low N2O fluxes potentially result from strong competition of tree species with microbes for nutrients. Species-specific patterns in CO2 and N2O fluxes demonstrate that plant species can influence soil biogeochemical processes in a diverse tropical forest

A convergent spectroscopy-based approach for Vcmax across leaf age and growth environments.

Abstract OOS 2-2

An international network to monitor the structure, composition and dynamics of Amazonian forests (RAINFOR)

The Amazon basin is likely to be increasingly affected by environmental changes: higher temperatures, changes in precipitation, CO2 fertilization and habitat fragmentation. To examine the important ecological and biogeochemical consequences of these changes, we are developing an international network, RAINFOR, which aims to monitor forest biomass and dynamics across Amazonia in a co-ordinated fashion in order to understand their relationship to soil and climate. The network will focus on sample plots established by independent researchers, some providing data extending back several decades. We will also conduct rapid transect studies of poorly monitored regions. Field expeditions analysed local soil and plant properties in the first phase (2001–2002). Initial results suggest that the network has the potential to reveal much information on the continental-scale relations between forest and environment. The network will also serve as a forum for discussion between researchers, with the aim of standardising sampling techniques and methodologies that will enable Amazonian forests to be monitored in a coherent manner in the coming decades

Canopy-Atmosphere Exchange of Carbon, Water and Energy at Harvard Forest EMS Tower since 1991

Stomatal conductance influences both photosynthesis and transpiration, thereby coupling the carbon and water cycles and affecting surface–atmosphere energy exchange. The environmental response of stomatal conductance has been measured mainly on the leaf scale, and theoretical canopy models are relied on to upscale stomatal conductance for application in terrestrial ecosystem models and climate prediction. Here we estimate stomatal conductance and associated transpiration in a temperate deciduous forest directly on the canopy scale via two independent approaches: (i) from heat and water vapor exchange and (ii) from carbonyl sulfide (OCS) uptake. We use the eddy covariance method to measure the net ecosystem–atmosphere exchange of OCS, and we use a flux-gradient approach to separate canopy OCS uptake from soil OCS uptake. We find that the seasonal and diurnal patterns of canopy stomatal conductance obtained by the two approaches agree (to within ±6 % diurnally), validating both methods. Canopy stomatal conductance increases linearly with above-canopy light intensity (in contrast to the leaf scale, where stomatal conductance shows declining marginal increases) and otherwise depends only on the diffuse light fraction, the canopy-average leaf-to-air water vapor gradient, and the total leaf area. Based on stomatal conductance, we partition evapotranspiration (ET) and find that evaporation increases from 0 to 40 % of ET as the growing season progresses, driven primarily by rising soil temperature and secondarily by rainfall. Counterintuitively, evaporation peaks at the time of year when the soil is dry and the air is moist. Our method of ET partitioning avoids concerns about mismatched scales or measurement types because both ET and transpiration are derived from eddy covariance data. Neither of the two ecosystem models tested predicts the observed dynamics of evaporation or transpiration, indicating that ET partitioning such as that provided here is needed to further model development and improve our understanding of carbon and water cycling