Wetting‐induced soil CO2 emission pulses are driven by interactions among soil temperature, carbon, and nitrogen limitation in the Colorado Desert
Data files
Jul 12, 2023 version files 2.28 MB
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CO2_rawfluxes.txt
2.21 MB
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IntegratedCO2Fluxes_BoydDeepCanyon.txt
39.68 KB
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IntegratedCO2Fluxes_NDepositionStudies.txt
17.07 KB
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README.md
10.60 KB
Abstract
Warming-induced changes in precipitation regimes, coupled with anthropogenically-enhanced nitrogen (N) deposition, are likely to increase the prevalence, duration, and magnitude of soil respiration pulses following soil wetting via interactions among temperature and C and N availability. Quantifying the importance of these interactive controls on soil respiration is a key challenge as pulses can be large terrestrial sources of atmospheric CO2 over comparatively short timescales. Using an automated sensor system, we measured soil CO2 flux dynamics in the Colorado Desert—a system characterized by pronounced transitions from dry-to-wet soil conditions—through a multi-year series of experimental wetting campaigns. Experimental manipulations included combinations of C and N additions across a range of ambient temperatures and across five sites varying in atmospheric N deposition. We found soil CO2 pulses following wetting were highly predictable from peak instantaneous CO2 flux measurements. CO2 pulses consistently increased with temperature, and temperature at time of wetting positively correlated to CO2 pulse magnitude. Experimentally adding N along the N deposition gradient generated contrasting pulse responses: adding N increased CO2 pulses in low N deposition sites, whereas adding N decreased CO2 pulses in high N deposition sites. At the lowest N deposition site, simultaneous additions of C and N during wetting led to the highest observed soil CO2 fluxes reported globally at 299.5 µmol CO2 m-2 s-1. Our results suggest that soils have the capacity to emit high amounts of CO2 within small timeframes following infrequent wetting, and pulse sizes reflect a non-linear combination of soil resource and temperature interactions. Importantly, the largest soil CO2 emissions occurred when multiple resources were flushed simultaneously in historically resource-limited desert soils, pointing to regions experiencing simultaneous effects of desertification and urbanization as key players in future global C balance.
Methods
Our eight field experiments, which varied in experimental manipu- lations of temperature and C and N substrates, all used the same measurement system to capture soil temperature, moisture, and CO2 fluxes before and after soil wetting. Prior to each field campaign, pairs of polyvinyl chloride (PVC) soil collars measuring 20-cm in diam- eter were installed to 5-cm depth and adjacent to each other under L. tridentata canopies or in interspaces between shrubs. One collar per pair was used for trace gas measurements and the other was used for soil temperature, moisture, and ancillary soil measurements. This secondary collar was necessary because temperature and moisture probes contained wiring attachments that would interfere with the chamber's ability to seal around the soil collar; however, we assumed that collar pairs would experience similar climate and edaphic conditions given their proximity to each other. Both collars in each pair received identical wetting treatments and collar pairs were situated at least 2 m apart from other pairs. Beginning at 15 min following wetting, soil temperature, moisture, and fluxes of CO2 were measured at 30-min intervals over 24-45 h. Soils were also measured for up to 24 h prior to wetting as an assessment of dry conditions. For these instantaneous measurements, we used a robotic chamber array and sampling procedure previously described in Andrews et al. (2022 AGEE). In this system, eight automated long-term chambers (LI- 8100-104; LI-COR Biosciences) with soil temperature (LI-8150-203 thermistor probe; LI-COR Biosciences) and moisture (LI-GS1 probe; LI-COR Biosciences) probe attachments were installed on soil PVC collars; probes were inserted to 5 cm below the soil surface and provided integrated measurements of 3–5 cm soil depth. Each chamber collected measurements on a 30-min interval. Air collected from an actively measuring chamber was passed through a multiplexer (LI-8150; LI-COR Biosciences) and delivered to a gas analyzer suite, including a CO2 infrared gas analyzer system (LI-8100A; LI-COR Biosciences), in a closed loop. Each chamber measurement sequence included a 30-s pre-measurement purge, a 2.5-min active measurement period of trace gas concentrations and soil climate status, and a 30-s post-measurement purge. All eight chambers were sampled at 30-min intervals over a 24- to 45-h measurement period.
Raw CO2 concentration and soil probe measurements were batch processed into fluxes and associated soil temperature and moisture data using algorithms adapted from previous work using this chamber array (Andrews et al., 2022 AGEE; Krichels et al., 2022). Instantaneous fluxes of CO2 were calculated as the regression coefficient of linear increase in gas concentration data during the 2.5-min active chamber measurement period, accounting for soil collar dimensions and atmospheric parameters following the Ideal Gas Law (Davidson et al., 2000). Instantaneous fluxes of CO2 were compiled and integrated with instantaneous soil temperature and moisture measurements using a publicly-available R script (Andrews & Krichels, 2021). Additional post-processing filtering steps were conducted when data failed to cross a threshold of data quality and control due to chamber or analyzer malfunctions. Our final eight-campaign dataset consisted of 22,553 CO2 fluxes and corresponding soil temperature and/or moisture measurements. From continuous measurements of each chamber, we constructed 24-h time series following wetting and extracted the magnitude and timing of maximum instantaneous flux. We also calculated 24-h cumulative CO2 fluxes using linear trapezoidal integration of chamber observations which occurred at 30-min intervals.
Usage notes
Statistical analyses were conducted in JMP 14 (2021) and data management and visualization were performed in R 4.1.3 (2021) and RStudio (RStudio Team, 2020).