Reevaluating growing season length controls on net ecosystem production in evergreen conifer forests.

Growing season length (GSL) is a key unifying concept in ecology that can be estimated from eddy covariance-derived estimates of net ecosystem production (NEP). Previous studies disagree on how increasing GSLs may affect NEP in evergreen coniferous forests, potentially due to the variety of methods used to quantify GSL from NEP. We calculated GSL and GSL-NEP regressions at eleven evergreen conifer sites across a broad climatic gradient in western North America using three common approaches: (1) variable length (3-7 days) regressions of day of year versus NEP, (2) a smoothed threshold approach, and (3) the carbon uptake period, followed by a new approach of a method-averaged ensemble. The GSL and the GSL-NEP relationship differed among methods, resulting in linear relationships with variable sign, slope, and statistical significance. For all combinations of sites and methods, the GSL explained between 6% and 82% of NEP with p-values ranging from 0.45 to < 0.01. These results demonstrate the variability among GSL methods and the importance of selecting an appropriate method to accurately project the ecosystem carbon cycling response to longer growing seasons in the future. To encourage this approach in future studies, we outline a series of best practices for GSL method selection depending on research goals and the annual NEP dynamics of the study site(s). These results contribute to understanding growing season dynamics at ecosystem and continental scales and underscore the potential for methodological variability to influence forecasts of the evergreen conifer forest response to climate variability.

A sprinkling experiment to quantify celerity-velocity differences at the hillslope scale.

Few studies have quantified the differences between celerity and velocity of hillslope water flow and explained the processes that control these differences. Here, we asses these differences by combining a 24-day hillslope sprinkling experiment with a spatially explicit hydrologic model analysis. We focused our work on Watershed 10 at the H. J. Andrews Experimental Forest in western Oregon. Celerities estimated from wetting front arrival times were generally much faster than average vertical velocities of δ2H. In the model analysis, this was consistent with an identifiable effective porosity (fraction of total porosity available for mass transfer) parameter, indicating that subsurface mixing was controlled by an immobile soil fraction, resulting in the attenuation of the δ2H input signal in lateral subsurface flow. In addition to the immobile soil fraction, exfiltrating deep groundwater that mixed with lateral subsurface flow captured at the experimental hillslope trench caused further reduction in the δ2H input signal. Finally, our results suggest that soil depth variability played a significant role in the celerity-velocity responses. Deeper upslope soils damped the δ2H input signal, while a shallow soil near the trench controlled the δ2H peak in lateral subsurface flow response. Simulated exit time and residence time distributions with our hillslope hydrologic model showed that water captured at the trench did not represent the entire modeled hillslope domain; the exit time distribution for lateral subsurface flow captured at the trench showed more early time weighting.

The role of stable isotopes in understanding rainfall interception processes: A review.

The isotopic composition of water transmitted by the canopy as throughfall or stemflow reflects a suite of processes modifying rainfall. Factors that affect isotopic composition of canopy water include fractionation, exchange between liquid and vapor, and selective transmittance of temporally varying rainfall along varying canopy flowpaths. Despite frequent attribution of canopy effects on isotopic composition of throughfall to evaporative fractionation, data suggest exchange and selection are more likely the dominant factors. Temporal variability in canopy effects is generally consistent with either exchange or selection, but spatial variability is generally more consistent with selection. However, most investigations to date have not collected data sufficient to unambiguously identify controlling processes. Using isotopic data for improved understanding of physical processes and water routing in the canopy requires recognizing how these factors and processes lead to patterns of isotopic variability, and then applying this understanding towards focused data collection and analysis.

Influence of leaching solution and catchment location on the fluorescence of water-soluble organic matter.

Organic matter (OM) plays a significant role in biogeochemical processes in soil and water systems. Water-soluble organic matter (WSOM) leached from soil samples is often analyzed as representative of potentially mobile OM. However, there are many WSOM extraction methods in the literature with no clear guidelines for method selection. In this study, four common leaching solutions (0.5 M K2SO4, 0.01 M CaCl2, 2 M KCl, and H2O) were used to extract WSOM from various locations within a forested catchment. Fluorescence spectroscopy was used to analyze the impact of extraction method on WSOM chemistry. While all four methods consistently identified chemical differences between WSOM from a north-facing slope, south-facing slope, and riparian zone, there were clear differences in fluorescence signals between the leaching methods. All three salt solutions contained WSOM with a higher fluorescence index and humification index than WSOM leached with H2O, suggesting the presence of salts releases different fractions of the soil organic matter. A parallel factor analysis (PARAFAC) model developed from the leachates identified a distinctive soil humic fluorophore observed in all samples and fluorescent artifacts present in H2O-leached samples.

PARduino: a simple and inexpensive device for logging photosynthetically active radiation.

Photosynthetically active radiation (PAR, 400-700 nm) is one of the primary controls of forest carbon and water relations. In complex terrain, PAR has high spatial variability. Given the high cost of commercial datalogging equipment, spatially distributed measurements of PAR have been typically modeled using geographic coordinates and terrain indices. Here, we present a design for a low-cost, field-deployable device for measuring and recording PAR built around an Arduino microcontroller-named PARduino. PARduino provides for widely distributed sensor arrays and tests the feasibility of using open-source, hobbyist-grade electronics for collecting scientific data. PARduino components include a quantum sensor, an EME Systems signal converter/amplifier and an Arduino Pro Mini microcontroller. Additional components include a real-time clock, a microSD Flash memory card and a custom printed circuit board. The components were selected for ease of assembly. We found strong agreement between the PARduino datalogger system and National Institute of Standards and Technology traceable sensors logged by an industry standard datalogger (slope = 0.99, SE < 0.01, P < 0.01; intercept = - 14.84, SE = 0.78, P < 0.01). The average difference between the two systems was 22.0 µmol m(-2) s(-1) with PARduino typically underestimating PAR. The average percentage difference between systems was 3.49%. On average, PARduino performed within the factory absolute calibration of the PAR sensor; however, larger errors occurred at low PAR levels. Using open-source technologies such as this can make it possible to develop a spatially distributed sensor network within the constraints of a typical research budget.