HFQLG Soil Moisture Monitoring – Aug 2009 to Sep 2012

HFQLG Soil Moisture Monitoring – Aug 2009 to Sep 2012 Prepared by:

David Young, North Zone Soil Scientist, Redding, CA (USFS, Region 5) Colin Dillingham, HFQLG Monitoring Coordinator, Quincy, CA (USFS, Plumas NF) Jianwei Zhang, Research Silviculturist, Redding, CA (USFS, PSW Research Station)

Executive Summary Continuous data-logging equipment was used to monitor soil moisture trends at two HFQLG activity areas from 2009 to present (one site from 2009-2011, one from 2011-present using the same equipment). Both sites had multiple paired activity units, comparing treated (thinned) and adjacent unthinned stands. Time since treatment varied for the sites. The units at Meadow Valley had thinning treatments completed in 2005-2007. Monitoring at Franc began the first year after treatments were completed, when differences due to treatment should be greatest. Soil moisture sensors, half with attendant soil temperature data, were installed at 10 inch increments from 10-40 inches depth in the soil profile. At both sites, differences between soil depths and stand treatments were highly significant (P < 0.0001), although trends were not consistent between sites and absolute differences are relatively small. Treated stands at Meadow Valley were on average dryer, having -5.1% volumetric water content (VWC) during the growing season and -3.6% VWC during the non-growing season. At Franc treated stands were more moist on average, with +1.5% VWC during the growing season and +1.4% VWC during the non-growing season. Soil moisture differences were not attributed to soil temperature differences, which were +1.2-1.9⁰C (+2.2-3.6⁰F) during the growing season at both sites, and -0.07⁰C (0.13⁰F) during the non-growing season at both sites. Trends are not universal at all soil depths or at all unit-pair replicates at each site, but overall effects are statistically clear. It must be noted that the absolute magnitude of differences are small enough to be within the error range for the technical accuracy of the soil sensors, so from an engineering view results are questionable; to waive this objection one must be willing to assume that sensors should mostly err in the same direction within comparable soils. In the authors’ opinion this is a reasonable assumption.

Introduction The original monitoring plan conducted as part of the HFQLG pilot program outlined monitoring questions and specified monitoring protocols meant to address those questions. One element related to soil moisture: Question 20): What is the effect of the proposed treatments on a) modeled water yield and b) soil moisture characteristics?

Original monitoring protocols may be found in the HFQLG Monitoring Plan, and will not be repeated here. Monitoring was conducted by Wayne Johannsen (Plumas NF soil scientist, retired), from 2001 to 2004. He generally found no soil moisture differences as a result of thinning and fuel reduction treatments. Because of the lack of differences, and the retirement of Wayne, further soil moisture monitoring was discontinued. The Pinchot Institute for Conservation, in response to a Forest Service request, formed an Independent Science Panel to carry out a review of monitoring pursuant to the HFQLG pilot program. Phase One review was completed in 2008, with the purpose of providing feedback helpful in making changes to the monitoring program prior to a more intensive review (Phase Two) and reporting to Congress. Among the Phase One recommendations was one regarding soil moisture: HFQLG Soil Moisture Monitoring Report – Meadow Valley and Franc

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“Soil Moisture. Although evaluation of soil moisture in early years did not identify a significant

difference between pre-treatment and post-treatment areas, the Panel recommends that soil moisture content sampling be continued because changes in soil properties may evolve over time. Testing during a single year so soon after treatment may not be adequate to characterize potential effects of the treatments on soil properties.” In 2009 soil moisture monitoring efforts were renewed, and protocols revised. Previous monitoring utilized a hand-held electronic soil moisture meter, requiring site visits at a point of time between August and September. Thus, soil moisture for each unit was represented by a single date, before and after treatments occurred. For renewed efforts, the HFQLG monitoring program funded the purchase of soil moisture sensors and dataloggers for continuous data recording, to enable soil moisture comparisons throughout the entire growing season. The equipment was installed in the Meadow Valley Sale Area (Mt. Hough Ranger District, Plumas NF) from 2009 to 2011, and moved to the Franc Sale Area (Sierraville Ranger District, Tahoe NF) from 2011 to present. The “treatments” consisted of commercial thinning and fuel reduction activities which emphasized thinning from below and removal of surface and ladder fuel components. Group selection units were not chosen for this monitoring. When comparing to an unthinned stand, one may expect warmer soil temperatures due to reduction of canopy cover and increased solar exposure. This should indirectly increase microbial and root activity in the soil, and evapotranspiration rates of individual trees. Effects upon soil moisture may be: 1) drier soil conditions due to evaporative loss with warmer temperatures and reduction in soil cover; 2) wetter soil conditions due to fewer evapotranspiration ‘pumps’ in the stand; 3) seasonally dependent effects; 4) temporal effects depending on time since treatment. Any such effects should be temporary in a thinning scenario, with site resources (nutrients and water) merely reallocated to fewer trees, in theory, although it should presumably take a few years for residual trees’ root systems to expand and fully reoccupy the soil volume. Warmer soils could perhaps accelerate the growth period and shorten the growing season to a soil-dry dormant period, resulting in the same productivity, just occurring faster. It is generally assumed that plant available soil water holding capacity should not be appreciably affected by activity operations as a result of near-surface compaction. The direct and indirect effects of soil environment changes due to such vegetation management activities are largely speculative, and whether they could be measured in a thinning scenario is questionable.

Methods Continuous-logging soil moisture sensors were installed in 4 Meadow Valley units, essentially repeating 4 of 5 units (and same approximate locations) which were pre-activity sampled by Wayne Johannsen in 2001 but not post-sampled. It was desired to monitor 4 sites concurrently, with treated and untreated paired comparisons, requiring 8 dataloggers and 32 sensors. When moved to the Franc Sale, measurements were expanded to 5 unit pairs. Decagon™ brand equipment was chosen for overall affordability and utility; use of this equipment does not imply any recommendation relative to similar equipment from other competitive sources. Sensors are high frequency dialectric models 10HS & EC-TM/TE, the latter collecting additional temperature data. The 10HS sensors “sense” a larger soil volume (approx. 1 liter), and were installed at the 10 and 30 inch depth increments. The EC-TM/TE sensors have an approximate 0.3 liter volume of influence and were installed at 20 and 40 inch depth increments. Both models output raw dialectric voltage readings and calculated volumetric water content (VWC), estimated using standard mineral soil calibration equations developed by the vendor. Specified sensor accuracy is +/- 3% VWC in cm3/cm3. The effort was not made to develop soil-specific HFQLG Soil Moisture Monitoring Report – Meadow Valley and Franc

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custom calibration equations because of the several soils and soil profile horizons involved, and it would apparently only improve the specified accuracy to +/- 2% VWC. The EM50 dataloggers have a capacity of 5 sensors, can operate for about 1 year with (5) AA batteries, utilize “stereo” serial ports for communication, and were set to record data hourly. The loggers are intended to be installed aboveground, having a weather resistant enclosure, but breathable to prevent moisture buildup. Installation was done by David Young and Colin Dillingham. Soil pits were excavated to 40+ inches depth, and sensors were installed roughly horizontal (actually at a slight sideways and downward angle to keep water from ponding on the impervious sensor surface). At Meadow Valley, sensors were inserted into the “undisturbed” pit face, and staggered left-right at alternating depths to avoid sensor interference. Extremely rocky soils at Franc precluded insertion in “intact” soil, so sensors were carefully placed in “pockets” of sieved soil from the appropriate depth, and also staggered left-right to the extent that large rocks could be avoided. The datalogger was fastened to a small post right next to the pit, and connections and testing completed before carefully backfilling the soil pit, attempting to restore the original soil density and source depth of the soil material. Loggers were downloaded occasionally, and batteries replaced going into each winter. Installation locations were carefully chosen to be as closely matched as possible except for stand density representing the treated and untreated (control) conditions. Precise location pairing attempted to match slope position, aspect, soils, microsite topography, and pre-thinning stand density. Respective of the greater watershed, at Meadow Valley 1 site was at the toe-slope near a meadow fringe, 2 were mid-slope, and 1 was near the ridge; at Franc 2 sites were lower slope position, 2 mid-slope, and 1 upper-slope. GPS location, as well as site and stand characteristics (basal area, crown cover, understory cover) were recorded for each installation point. Weather data (precipitation, air temperature) was obtained from the California Climate Data Archive website (http://www.calclim.dri.edu/ccda/data.html), using Quincy RAWS to represent Meadow Valley and Dog Valley RAWS to represent Franc , being the nearest stations with complete data for the time periods of interest. Statistical analyses were performed by Jianwei Zhang. Analysis was focused upon the above monitoring question, i.e. the statistical difference attributable to treatment, with date, unit pairs, and soil depth as replication variables. Since date could be further used as a trend variable, a mixed-model repeated-measures ANOVA was used in SAS™ software to amalgamate the data set, as well as account for missing data due to a few intermittent sensors. The two sites were analyzed separately. Many more detailed analyses could be performed comparing climate, soil temperature, and soil moisture trends by individual installation (unit pair) or soil depth increment, and/or incorporate stand data variables; this would be desirable as a future pursuit. However, this report is mostly limited to the primary monitoring question regarding the overall effect of treatments on soil moisture status. A note on statistics vs. engineering/technical properties of soil sensors: The difference between treated and untreated unit pairs is the primary metric of interest for analysis. The technical accuracy of the deployed soil sensors is +/- 3% VWC (absolute) and +/- 1⁰C for temperature. When analyzing pairs by differential water content, it is therefore possible to have a maximum of 6% difference due to error in sensor accuracy alone, in the event one paired sensor is 3% off in a positive direction and the other is 3% off in the negative direction (not probable, but possible); likewise we could have a maximum of 2⁰C difference from sensor accuracy error. Therefore differential water contents of < 6% VWC and < 2⁰C are dubious as being within the sensor error range, and may not be “real” differences, even if statistically significant. To trust the statistics within that differential error range, one must be willing to assume that sensors should in general err in the same direction, considering HFQLG Soil Moisture Monitoring Report – Meadow Valley and Franc

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that the error in absolute numbers should be due more to soil type relative to calibration equations rather than actual sensor output accuracy. Whether or not this assumption is accepted is relevant in concluding that statistically significant differences are valid where absolute differences are small.

Results and Discussion Climate Data Climate data representing the two sites (figures 1 and 2) exhibits cold wet winters and warm dry summers typical of California’s Mediterranean climatic zone. The Franc site, being very near the crest of the Sierra range, shows more summer precipitation, associated with spotty summer thunderstorms typical of the area. Precipitation events are reflected quite well in soil moisture status, with small events only showing up in the surface layer and large events showing up as moisture spikes in all depths. No effort was made to statistically discern precise relationships (e.g. how large an event is required to show up at various depths?). The climate data was generally used to qualitatively error-check spikes and dips in soil temperature and moisture data, and to differentiate the growing season from the non-growing season for statistical analysis, based upon consecutive freezing days (a 10 day period without freezing temperatures denoted the start of the growing season). At Meadow Valley the growing season for analysis was 6/1/10 to 10/31/10; the non-growing season followed from 11/1/10 to 5/30/11. At Franc the growing season was 6/1/12 to 9/8/12 (the last download date); the nongrowing season preceded the growing season, from 10/1/11 to 5/31/12. Soil Temperature Soil temperature data was only collected at 20 and 40 inch depth increments. The 20 inch depth is conventionally used to determine the soil temperature regime used at various categorical levels in USDA soil taxonomy. Soil temperature data was desired so that it might help explain possible differences in soil moisture. At Meadow Valley (figure 3) seasonal trends are apparent, with thinned stands having higher summer soil temps (particularly at 20 in depth) and cooler winter temps (particularly at 40 in depth). The two depths were significantly different for both growing and non-growing seasons (P < 0.0001). Temperatures were only significantly different for the growing season (P < 0.0001, versus P = 0.7677 for the non-growing season), with thinned stands having higher soil temps than unthinned stands. At Franc (figure 4) precisely the same seasonal trends are apparent, with thinned stands having higher summer soil temps (particularly at 20 in depth) and cooler winter temps (particularly at 40 in depth). Again, depths were significantly different for both growing and non-growing seasons (P < 0.0001) and temperatures were only significantly different for the growing season (P < 0.0001), although the non-growing season was much closer to being significant (P = 0.0833). The data concludes that soil temperatures are significantly [statistically] warmer in thinned stands during the summer growing season. The difference in absolute terms is less than 2⁰C (1.2⁰ at Meadow Valley, 1.9⁰ at Franc). This is notably within the technical accuracy/error range for the sensors used, so whether these differences are “real” is questionable, but probable. In ecological terms, a real difference of 2⁰C could be significant in accelerating soil chemical and biological processes.

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Figure 3. Meadow Valley site – soil temperature trends. Daily average temperatures in Celsius at two soil depths, and temperature differential by depth.

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Figure 4. Franc site – soil temperature trends. Daily average temperatures in Celsius at two soil depths, and temperature differential by depth.

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Soil Moisture Overall soil moisture trends by site, treatment, and depth are displayed in figures 5 and 6. At both sites, rain events are apparent in rapid spikes in soil moisture, which can be traced back to the climate graphs. The consistent drawdown of soil moisture during the summer growing season is also apparent. Realities of intermittent sensor data are also apparent – note Meadow Valley, unthinned, 40 inches depth. Each line is an average of several unit-pairs; when individual sensors stop recording data (due to being frozen, cable connection comes loose, misc. errors, etc.) the number of pairs composing the average changes, so the average may abruptly change also, which creates some analytical challenges. In running statistics the data that is “paired” to the missing data must be disregarded to avoid imbalanced comparisons (comparing two averages that have different number of reps). There are several instances of this in the data set at large. There are also several miscellaneous instances of obviously erroneous data, for no explicable reason (e.g. soil moisture declining radically for just a few hours, while otherwise quite stable for days). This kind of instance is attributed to sensor error, such as an incorrect voltage output or reading by the logger. Effort was made to clean up large errors (by interpolating or deleting) that might have a disproportionate effect on means, leading to magnified differences. Smaller errors were not sought out and cleaned up, assuming the data set is large enough to compensate for small-magnitude errors. Considering how water is normally distributed in the soil profiles, it is quite apparent at Meadow Valley that the sensors at 20 and 40 inches depth inherently report a higher VWC. This must be due to the applicability of the calibration equation to the particular soils at that site, and/or the different volumes of influence for the different sensors (i.e. rock content would be more likely to affect values for the sensors with larger volume of influence). These data could be normalized for more robust analysis and direct comparison of all depths, but were not for this reporting. These differences are not apparent at Franc, except perhaps in March and April when soils are at peak-high water contents from snowmelt. The soils at Franc are notably more homogeneous in texture with depth (sandy loams throughout the profile, vs. loams over clay loams at Meadow Valley), and the volumes of influence were further homogenized by sieving out rock and constructing measurement pockets large enough for the sensor type. At Meadow Valley, overall soil moisture differences are -3.9%, meaning treated stands are drier on average. Differences ranged from -1.0% to -6.7% at various depths. At Franc, overall soil moisture differences are +1.3%, meaning treated stands are more moist on average. Differences ranged from -0.8% to +2.9% at various depths. At both sites and in both seasons, differences between depth increments and treatments are highly significant (P < 0.0001), although trends were not consistent between sites and absolute differences are relatively small. Growing seasons were broken out to look more closely at differences when tree stands are or are not directly affecting soil moisture via growth demands. At Meadow Valley (figures 7 and 8), differences between soil depths and treatments are highly significant in both seasons (P < 0.0001). Combining depths for a “soil profile” average, thinned stands have 5.1% lesser soil moisture in the growing season and 3.6% lesser in the non-growing season. Differences are greatest at 30 & 40 inch depths during the growing season, which is the opposite of what might be expected IF soil temperature differences were a driving factor. Differences are greatest at 20 & 30 inch depths during the non-growing season, which doesn’t make much sense in terms of soil physics.

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At Franc (figures 9 and 10), differences between soil depths and treatments are again highly significant in both seasons (P < 0.0001). Combining depths for a “soil profile” average, thinned stands have 1.5% higher soil moisture in the growing season and 1.4% higher in the non-growing season. During the growing season, differences are most consistent at the 10 inch depth, negligible at the 30 inch depth, and 20 & 40 inch depths alternate from wetter to drier throughout the season. During the non-growing season, differences are greater at 10 & 20 inch depths, and soils are actually slightly drier at 30 & 40 inch depths during most of the season. In summary, soil moisture differences between thinned and unthinned stands are statistically significant at both sites, but one site is drier and one is moister on average for the whole soil profile. Meadow Valley has the drier soils, and this site has gone a longer time between treatments and monitoring. It is presumed that these thinned stands have had more time to expand crown and root systems post-thinning and fully take advantage of site resources. Increased net transpiration rates in these stands may be responsible for the drier soils. Conversely, the Franc site has the moister soils, and the site has gone only 1 season since treatments. Presumably this site has not had adequate time for residual trees to take full advantage of site resources, so fewer evapotranspiration ‘pumps’ are leaving soils more moist. This net transpiration explanation seems reasonable, but it is strictly speculative without research level monitoring of many possible causal factors.

Conclusions There are very-statistically-significant differences in soil moisture and temperature between treated and untreated stands. The absolute magnitude of differences is relatively small, and differences are inconsistent among sites, soil depths, and individual unit-pairs, so the ecological significance of these differences is unknown. The overall HFQLG monitoring question has been investigated, and overall results for the two monitored sites are statistically clear, albeit different. The different results may be a result of different times since treatment, fine-scale differences in climates (e.g. solar radiation), differences in soil types at the two sites, or a combination of these and other factors. It was not the purpose of this operational monitoring to determine cause (or effects) of differences in moisture, but simply to document status and trend as a function of vegetation management treatments. Longer temporal trends are likely necessary to better interpret findings. There are several curious differences and trends in the finer details of the data that are interesting and difficult to explain. It is desired to further analyze this data set, parsing out individual unit-pairs and soil depths and factoring in stand data metrics to investigate these trends more closely. It may also be desirable to leave the sensors in place at Franc and continue monitoring for several years to look at longer temporal trends. Barring Congressional renewal of the HFQLG program, and therefore a desire to relocate the monitoring equipment, it is the authors’ intent to continue actively monitoring the Franc site for several years to come.

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Volumetric Water Content (cm3/cm3)

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Figure 5. Overall soil moisture trends at Meadow Valley site by Treatment and Soil Depth (averages of 4 unit pairs). Differences (not shown) range from -1.0% to -6.7%, with absolute differences ranked by depth as 10