Department of Plant and Soil Sciences, University of Delaware, Newark, DE 19716, USA.
Department of Plant and Soil Sciences, University of Delaware, Newark, DE 19716, USA.
Sci Total Environ. 2022 Jan 1;802:149715. doi: 10.1016/j.scitotenv.2021.149715. Epub 2021 Aug 21.
Tidal marshes store large amounts of carbon; however, little is known about the patterns, magnitudes, and biophysical drivers that regulate CO efflux from these ecosystems. Due to harsh environmental conditions (e.g., flooding), it is difficult to measure continuous soil CO efflux in tidal marshes. These data are necessary to inform empirical and process-based models and to better quantify carbon budgets. We performed automated (30 min) and manual (bi-monthly) soil CO efflux measurements, for ~20 months, at two sites in a temperate tidal marsh: tall Spartina (TS; dominated by S. cynosuroides) and short Spartina (SS; dominated by S. alterniflora). These measurements were coupled with water quality, canopy spectral reflectance, and meteorological measurements. There were no consistent diel patterns of soil CO efflux, suggesting a decoupling of soil CO efflux with diel variations in temperature and tides (i.e., water level) showing a hysteresis effect. Mean soil CO efflux was significantly higher at SS (2.15 ± 1.60 μmol CO m s) than at TS (0.55 ± 0.80 μmol CO m s), highlighting distinct biogeochemical spatial variability. At the annual scale, air temperature explained >50% of the variability in soil CO efflux at both sites; and water level and salinity were secondary drivers of soil CO efflux at SS and TS, respectively. Annual soil CO efflux varied from 287-876 to 153-211 g C m y at SS and TS, respectively, but manual measurements underestimated the annual flux by <67% at SS and <23% at TS. These results suggest that measuring and modeling diel soil CO efflux variability in tidal marshes may be more challenging than previously expected and highlight large discrepancies between manual and automated soil CO efflux measurements. New technical approaches are needed to implement long-term automated measurements of soil CO efflux across wetlands to properly estimate the carbon balance of these ecosystems.
潮汐沼泽储存了大量的碳；然而，对于调节这些生态系统 CO 排放的模式、幅度和生物物理驱动因素知之甚少。由于恶劣的环境条件（例如洪水），很难测量潮汐沼泽中连续的土壤 CO 排放。这些数据对于告知经验和基于过程的模型以及更好地量化碳预算是必要的。我们在一个温带潮汐沼泽的两个地点进行了自动化（30 分钟）和手动（每两个月）的土壤 CO 排放测量，持续了约 20 个月：高盐碱蓬（TS；主要由 S. cynosuroides 组成）和短盐碱蓬（SS；主要由 S. alterniflora 组成）。这些测量与水质、冠层光谱反射率和气象测量相结合。土壤 CO 排放没有一致的昼夜模式，这表明土壤 CO 排放与昼夜温度和潮汐（即水位）变化脱钩，表现出滞后效应。SS 的平均土壤 CO 排放明显高于 TS（2.15±1.60 μmol CO m s）（0.55±0.80 μmol CO m s），突出了明显的生物地球化学空间变异性。在年度尺度上，空气温度解释了两个地点土壤 CO 排放变化的>50%；水位和盐度分别是 SS 和 TS 土壤 CO 排放的次要驱动因素。SS 和 TS 的年土壤 CO 排放量分别为 287-876 和 153-211 g C m y，但手动测量低估了 SS 年通量的<67%和 TS 的<23%。这些结果表明，测量和模拟潮汐沼泽昼夜土壤 CO 排放的变异性可能比预期的更具挑战性，并突出了手动和自动土壤 CO 排放测量之间的巨大差异。需要新的技术方法来实施湿地的长期自动土壤 CO 排放测量，以正确估计这些生态系统的碳平衡。
