Informal Data AnalysisIRGA-Soil CO2 Respiration Project 2014

This research aims to explore seasonal and spatial variation in CO2 respiration at intensive monitoring plots in mature second-growth mixed forest. Soil CO2 respiration accounts for the majority of CO2 respiration in terrestrial ecosystems. Observing seasonal trends in this important flux is crucial to our understanding of carbon balance within the ecosystem. Recording long term trends inthis flux is helpful in determining the signifigance of the various biotic and abiotic factors affecting carbon flux within forest ecosystems. Soil net carbon efflux ratio (NCER) was measured over a seven-year period within the Evergreen Ecological Observation Network, a network of intensively-studied long term ecological monitoring plots adjacent to the Evergreen State College. NCER was recorded monthly using an ADC BioScientific LCpro+ infrared gas analyzer. Soil CO2 efflux exhibited significant spatial variation, which is likely attributable to differences in tree species stand dominance. However, abiotic factors such as microclimates and differences in soil series cannot be ruled out. Seasonal trends were also observed, with the highest CO2 efflux values being observed from late spring to earlyfall. This is likely due to increased soil or air temperature, as a positive correlation was observed between soil temperature and soil CO2 efflux.

This analysis found significant temporal and spatial variation in soil CO2 respiration. Overall averages for NCER are incomplete, however, as there is only data available from August to November for 50% of the plots in the intensive network. Some plots that had been recorded in previous years had to be abandoned as well due to the bad state they were in. The discontinued plots are C4, D4, and D7. Soil CO2 respiration was recorded as NCER- net carbon efflux rate, and the units are micromoles per square meter per second. Analysis of soil moisture relation to NCER was not included due to large gapsin data throughout the sampling period (2008-2014) and the inconsistent nature of the extant soil moisture data.

Figure 1. Average net carbon efflux ratio for all intensive plots by month (2008-2014)

This graph depicts the monthly average for CO2 efflux. The x-axis is the month in which IRGA readings were taken. The y-axis is the mean NCER value for all plots in the new intensive group.We can see here a peak CO2 respiration from June through September, and a low-point during the winter months. This is likely due to changes in ambient temperature. While it is possible that other abiotic factors such as intensity of solar radiation have an effect as well, the hypothesis appears to be confirmed when compared to an analysis of soil temperature.

Figure 2. Comparison of NCER between intensive plots by soil temperature (2008-2014)

This graph depicts soil respiration (NCER) plotted against soil temperature. The x-axis is soil temperature at the measurement site. The y-axis is the soil CO2 efflux (NCER). Each data point represents a measurement taken at one of the four sub-plots of each plot in the monitoring network. There is a significant positive correlation between soil CO2 respiration rate and soil temperature. This would also explain the higher NCER values seen during the summer months. Future work might focus on gathering solar radiation data for the understory of each plot as well as simultaneous IRGA readingsto explore any possible links between solar radiation and soil CO2 respiration.

Figure 3. Graph representing average net carbon efflux rate (NCER) by month for each plot throughout the sampling period (2008-2014)

Despite the incomplete monthly data for half of the network, there is still observable spatial variation insoil CO2 efflux among the plots. Many plots lack datapoints for January through August, so any spatialanalysis will be difficult until data is recorded for all plots for every month analyzed. Despite these missing datapoints, certain plots can be seen to have significantly higher peak soil CO2 respiration thanothers. Comparing the plots with the highest peak NCER (A11, B4, C5, A7) to a map of forest canopy for the sampling area reveals that these plots are dominated by Douglas Fir (Pseudotsuga menziesii) or Douglas Fir and mixed hardwoods. The apparent difference between minimum and maximum soil CO2respiration is far more pronounced in the Douglas fir dominated plots than in plots with other forest compositions. While this is by no means definitive, this suggests that the dominant overstory species ortotal overstory woody biomass may be important indicators of overall soil CO2 respiration. Also noteable is the rather drastic slope of average NCER values for Douglas fir dominated plots seen duringthe spring-summer and summer-fall transitions, which suggest that soil respiration in these forest types may be more responsive to temperature, at least in certain ranges. Future work might focus on comparing dominant overstory species and total overstory woody biomass with average net carbon efflux rate to determine any link. More readings for January through September for plots lacking data for those months, especially the other PSME dominated plots, would also be helpful in establishing a more meaningful spatial analysis.

Figure 4. Map of new intensive plots using NRCS soil series overlay in Google Earth

Location of intensive monitoring plots was plotted against an overlay of soil series downloaded from the NRCS web soil survey. The lines indicate boundaries between distinct soil series based on decades of samples. Each of these soil series has distinct properties that distinguish it from other soil series. With the exception of A7, every one of the plots with the highest peak NCER was located in Alderwood sandy loam soil. A7 was located in Giles silty loam. While not suggestive of any definite trend, it could suggest that some abiotic factor such as soil texture or particle size in these series was connected to the higher respiration rates seen in these plots. Further literature review and formal analysis would be beneficial in describing any trends relating soil CO2 efflux and soil characteristics inthe sampling area.