About this Journal Submit a Manuscript Table of Contents
Applied and Environmental Soil Science
Volume 2014 (2014), Article ID 627129, 5 pages
http://dx.doi.org/10.1155/2014/627129
Research Article

Using Capacitance Sensors for the Continuous Measurement of the Water Content in the Litter Layer of Forest Soil

1Laboratory of Forest Hydrology, Division of Environmental Science and Technology, Graduate School of Agriculture, Kyoto University, Kyoto 606-8502, Japan
2Kansai Research Center, Forestry and Forest Products Research Institute, Kyoto 612-0855, Japan
3College of Bioresource Sciences, Nihon University, Fujisawa, Kanagawa 252-0880, Japan

Received 7 January 2014; Revised 3 March 2014; Accepted 10 March 2014; Published 3 April 2014

Academic Editor: Davey Jones

Copyright © 2014 Mioko Ataka et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Little is known about the wetting and drying processes of the litter layer ( layer), likely because of technical difficulties inherent in nondestructive water content (WC) monitoring. We developed a method for continuously measuring the WC of leaf litter (the “LWC method”) in situ using capacitance sensors. To test variants of this approach, five (for the LWC_5) or ten (for the LWC_10 method) Quercus serrata leaves were attached around capacitance sensors. The output voltage used for each LWC method was linearly correlated with the gravimetric WC (LWC_5: ; LWC_10: ), producing different slopes for each calibration line. For in situ continuous measurements of WC in the layer, two sensors were used, one placed on top of the layer and the other at the boundary between the and mineral layers. The average continuous WC of the layer was then calculated from the output voltage of the two sensors and the calibration function, and this value was linearly correlated with the gravimetric WC . However, because the layer characteristics (e.g., thickness, water-holding capacity, and species composition) may differ among study sites, appropriate approaches for measuring this layer’s moisture properties may be needed.

1. Introduction

The litter layer ( layer) comprises the uppermost soil layer and plays an important role in the water dynamics of the forest floor. For example, this layer limits the amount of water that can infiltrate into and/or evaporate from the soil [13]. Despite the importance of the layer in hydrological processes, water dynamics in this layer are often overlooked in studies of forest hydrology, mainly because of the technical difficulties in making accurate measurements.

The layer, which contains annually refreshed litter, is also a significant source of carbon in soil for heterotrophic organisms. Owing to the input of labile organic matter, the microbial activity in this layer is typically higher than that of lower soil layers [4] and is mainly regulated by environmental factors (e.g., moisture and temperature) [5, 6]. In addition, the moisture status of this layer changes more rapidly than that of lower soil layers [7, 8] because the layer is directly exposed to rain, solar radiation, and wind. The wetting and drying cycles in this layer lead to dynamic temporal variations in CO2 efflux [9], which strongly relates to the soil carbon budget. In addition, temporal variations in CO2 efflux from the layer are associated with varied environmental factors, which were continuously measured at an interval of several tens of minutes in an improved automated chamber system [10, 11]. However, to evaluate CO2 efflux as a function of the layer’s wetting and drying processes, continuous measurements of both the WC of this layer and the CO2 flux are required.

Some researchers have attempted to continuously measure water content (WC) of the layer in situ [9, 12, 13]. Hanson et al. [13] used an approach based on the use of electrical-impedance grids for recording leaf wetness reported by Gillespie and Kidd [14]. This approach was used to monitor the resistance or voltage between two clips attached to Quercus prinus leaves 3 cm apart along the midvein. The method was also modified with the use of wood pieces instead of intact leaves to avoid changes in the water-holding capacity of the material through decomposition over time [9]. Börner et al. [12] tested a different approach that employed two-time-domain reflectometry (TDR) probes placed directly into the mineral soil and at the boundary of the layer and the surface of the mineral soil. These approaches used specialized techniques and calibration function specialized for the layer condition of their measurement sites because the layer condition (e.g., thickness, water-holding capacity, and species composition) is more variable than that of mineral soil layer. Therefore, appropriate approaches for measuring the layer’s moisture condition for individual forest types may be required.

Recently, a small and thin capacitance sensor was developed which allows measurement of WC in restricted areas. In this study, we developed a method that uses such capacitance sensors to measure the WC of leaf litter, which we termed the “LWC method.” To measure WC of leaf litter with capacitance sensors, some intact leaf litter was closely attached around the sensor with rubber bands. In the laboratory, the output voltage of the LWC method was calibrated against the gravimetric WC (WCweight) of the leaf litter attached to the sensor. Using this LWC method, we continuously measured the WC of the layer in situ () and compared the observed data with WCweight obtained by destructive sampling of the layer.

2. Site Description

We tested our approach for continuously measuring the layer’s WC in situ in the Yamashiro Experimental Forest (YMS) in the southern region of the Kyoto Prefecture, Japan (34°47′N, 135°50′E). The study site was a 1.7 ha watershed with an annual mean air temperature of 15.5°C (summer hourly maximum: 34.8°C; winter hourly minimum: −3.9°C) and an annual mean precipitation of 1449 mm. The rainy season generally occurs from early June to mid-July. Daily rates of evaporation from the forest floor are 0.4–0.8 mm day−1 for 1-2 days after precipitation, declining to 0.2-0.3 mm day−1 thereafter [15]. Here, the layer’s WC dynamically changes from wet to dry within a few days. The large changes of the L layer’s WC strongly influence on the evaporation rate from the forest floor the layer.

In this ecosystem, the soils are regosols of sandy loam or loamy sand and contain fine gravel (53% by mass) composed of residual quartz crystals from parent granite material [16]. The soil layer is generally thin and immature. In addition, deciduous broadleaved, evergreen broadleaved, and coniferous tree species account for 66%, 28%, and 6% of the living tree biomass, respectively [17]. The forest and the associated leaf litter are dominated by Quercus serrata Thunb, which accounted for 33% of the biomass at the time of the study. Thus, the layer is mostly composed of Quercus serrata litter at a thickness of approximately 3-4 cm.

3. Materials and Methods

3.1. The LWC Method

In this study, we used plate-type sensors (ECH2O EC-5, Decagon Devices Inc., Pullman, WA), which are suitable for closely attaching leaves around the sensors, for the continuous measurement of the layer’s WC. Each EC-5 sensor was operated at 70 MHz and consisted of a short two-prong (5.6 cm long) sensor, circuitry, and data cable. During the study, the supply voltage to the sensor was fixed at 3.5 V [18], and the corresponding output voltage was recorded with the data logger (Datamark LS-3000 PtV; Hakusan, Japan).

Leaf litter that had fallen in the previous year was collected from the forest floor in January 2013. The leaves were attached as homogeneously as possible on both sides of the sensors with rubber bands, and the leaf edges that extended beyond the sensors were tightly wrapped around the probes to prevent the creation of interstices between the sensor plate and leaves (Figure 1). As a result, the sensor plate was completely covered with leaves. Using this method, capacitance sensor could stably capture the WC of the attached leaves, which would be in equilibrium with WC of the surrounding layer.

627129.fig.001
Figure 1: Design and installation of sensors used in the LWC method.

To consider the effect of the amount of leaves that were attached to sensor on output voltage of the EC-5 sensor, we tested two variants of the LWC method, where five (the LWC_5 method) or ten (the LWC_10 method) Quercus serrata leaves were attached to the sensors.

3.2. Calibration

We assessed the relationship between the output voltage generated from the LWC method and the WCweight. To consider the effect of the amount of leaves attached to sensor on the output voltage from the EC-5 sensor, we measured the output voltage generated by the LWC_5 and LWC_10 methods and compared those voltages to the WCweight of the leaves attached to the sensor at various moisture conditions ( or 66). To create samples that ranged from near zero to the maximum WC, leaf samples were soaked in water for 48 hours and then allowed to naturally dry to different WC levels. Water droplets on leaf samples were shaken off before attaching sensors. After each measurement, the leaves were removed from the sensor and oven-dried at 65°C for 48 h. WC was calculated according to the following equation: where FW and DW are the fresh and dry weights of the leaf litter sample (g), respectively.

4. In Situ Measurement of WC in the L Layer

The WC of the layer was measured as WCweight and in the field. WCweight was measured on 12 sampling days from May to September 2013. Twelve PVC collars (area: 323 cm2) were placed in a 2 × 4 m area on January 2013, and 15 g (dry weight) of newly fallen leaf litter was placed in each collar. This weight corresponded to the approximate litter-fall mass at this site [17]. The thickness of the layer was approximately 3-4 cm. On each sampling day, we selected four or five leaves to use in calculations of WCweight in the layer of each collar and enclosed those samples in plastic bags. The fresh weight of the sample was measured in the laboratory within 24 h after sampling, and samples were oven-dried at 65°C for 48 h. The samples were returned to the collars within one week after collection.

In addition, the of the layer was continuously measured in 30 min intervals from May to September 2013. To compare and WCweight, one PVC collar equipped with a sensor for the measurement of the was placed adjacent to the sampling area, and 15 g of newly fallen leaf litter was supplied to the collar. Measurements of were made according to the LWC_5 method because the ratio of the leaf area to the unit ground surface area in each collar was approximately 4-5. In this study, measurements were conducted at two levels, on top of the layer and at the boundary between the layer and the mineral soils (Figure 1), to completely capture the large vertical variation in the WC inside the layer [19]. We estimated the WC of the layer using the average calculated from the output voltage of the two sensors and the calibration line of the LWC_5 method.

5. Results and Discussion

5.1. The LWC Method

The output voltage generated by the LWC method was calibrated by and linearly correlated with the WCweight of the leaves attached to the sensors (Figure 2; LWC_5: ; LWC_10: ). The output voltages resulting from the LWC_5 method ranged from 0.265 to 0.444 V for a range of WCweight from 0.026 to 2.637 g g−1, respectively. The output voltages resulting from the LWC_10 method ranged from 0.267 to 0.491 V for WCweight ranging from 0.000134 to 1.810 g g−1, respectively. However, different calibration functions were obtained for the LWC_5 and LWC_10 methods. This difference could be explained by differences in the thickness of the layer of leaves attached to the sensor plates. Imoto et al. [20] reported that EC-5 sensors could detect moisture to a maximum distance of 2-3 cm from the sensor plate. In this study, the total thicknesses of the sensor plates and attached leaves were 0.5 and 1 cm for the LWC_5 and LWC_10 methods, respectively.

627129.fig.002
Figure 2: The relationship between the LWC method’s output voltage and the gravimetric water content (WCweight) of the leaves attached to the sensors. Circles show the data collected with the LWC_5 method (, , ), where five Quercus serrata leaves were attached to the sensor with rubber bands. Squares show the data collected with the LWC_10 method (, , ), which used ten Quercus serrata leaves.

Both the LWC_5 and LWC_10 methods allowed for the measurement of WCweight of the leaves attached to the sensors (Figure 2), and the amount of leaf litter attached to the sensor could affect the output voltage of the sensor. Thus, we need to obtain individual calibration function between output voltage of the LWC method and WCweight of the leaves attached to the sensors, depending on the amount of leaves attached to the sensor.

5.2. Continuous Measurement of WC in the L Layer with the LWC Method

was continuously measured in the field and compared to WCweight of litter samples collected over 12 sampling days (Figures 3 and 4). was corrected to WCweight (). However, was larger than WCweight (Figure 3) when WC was very low. In this case, temporal variation in was very low (Figure 4). This result suggests that the sensors placed at the boundary between the layer and the mineral soil layers captured the moisture properties of the mineral soil, which remained wet even as the layer dried.

627129.fig.003
Figure 3: The relationship between the water content of leaf litter samples obtained using the LWC method () and the gravimetric water content (WCweight) (). Error bars represent the standard deviation.
627129.fig.004
Figure 4: Temporal variation in (a) hourly precipitation, (b) volumetric soil water content at a depth of 0–5 cm in mineral soil depth, and (c) water content obtained using the LWC method () and the gravimetric water content (WCweight; Square) in the layer in a temperate broad-leaved secondary forest at Yamashiro Experimental Forest (YMS) from May to September 2013. Error bars are standard deviations.

On the other hand, estimates of tended to be lower than WCweight with larger standard deviations at higher WC levels (Figure 3), especially on 6 July and 7 August, 2013 (Figure 4). These results suggest that the spatial variation in the WC of the layer was large among the experimental collars, even though the 12 collars were closely organized across a limited area (2 × 4 m). We suspect that the wetting and drying processes in the layer differed across even this limited area. In fact, there was a large spatial variation in solar radiation and rainfall on the forest floor after penetrating the canopy, which are factors associated with the wetting and drying of the layer. Therefore, in future studies, it will be important for investigators to first determine the appropriate areas for sensor placement. For example, to evaluate CO2 efflux from the layer during the drying and wetting cycles, the sensor should be placed near the object of CO2 flux measurement.

As seen in Figure 4(c), there were large fluctuations in of the layer, ranging from 0.235 to 8.434 g g−1. Such frequent fluctuations resulted from the drying and wetting cycles of this layer. The WC of the layer increased immediately after rainfall (within a few hours) and then decreased within a few days after rainfall, ultimately reaching a steady state. Tamai and Hattori [15] also reported that daily evaporation from the layer was larger, 1-2 days after rainfall than afterward. Furthermore, the wetting and drying cycles of the layer differed from those of the soil [9, 13]. The soil WC decreased steadily until the next rainfall even over the extended dry period from 1 to 15 June (Figure 4(b)). Moreover, increased following a small rainfall event between 28 and 30 May (Figure 4(c)), but that increase was not detected by the WC sensor in the soil. Thus, only the layer became wet as a result of rain, dew, and fog formation, which can input significant amounts of water into the ecosystem [21]. The continuous measurement of the WC of the layer therefore allowed for a better understanding of water movement and soil CO2 efflux on the forest floor.

6. Conclusion

We developed the LWC method for the continuous in situ monitoring of the WC of the layer. Output voltages resulting from both the LWC_5 and LWC_10 methods were strongly correlated with WCweight, demonstrating that both methods could be used for the intended purpose. The LWC_5 method also captured the temporal variation in WC in our study site reasonably well. However, we suspect that the amount of leaf litter required for attachment to the sensors and the installation of the sensors should be specific to the layer’s properties which can differ between sites. Thus, future studies should examine site-specific aspects of the experimental design for the LWC method.

Tamai and Hattori [15] described a model for estimating WC in the layer every 30 min as a function of solar radiation and rainfall. This model would be a suitable tool for estimating temporal variation in the layer’s WC at the forest stand level. However, spatial variation in the WC of the layer can be large on a forest floor. The LWC method allows for the measurement of the layer’s WC in a small area. A comparison between estimates of WC as calculated from this model and from the LWC method is needed to better understand the role of the layer in hydrological processes.

One disadvantage of the use of intact leaf litter as part of the LWC method is that the structure of litter changes with decomposition over time, altering the corresponding form of the calibration equation [9, 13]. Therefore, the use of synthetic fiber cloth, which has a similar water-holding capacity to leaf litter, may be required for long-term monitoring instead of natural leaf litter. This approach would also be applicable to the measurement of the WC of sticks and other hard objects. In general, the LWC method can provide estimates of the WC of the layer, and the continuous in situ measurement of WC could contribute to models of CO2 efflux from the layer following rainfall.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

This study was partly supported by a Grant-in-Aid for Scientific Research (B) (20380182). The authors also thank Dr. Yoshiko Kosugi and the members of the Forest Hydrology Laboratory at Kyoto University for the helpful advice and aid in field and laboratory measurements.

References

  1. H. T. Park, S. Hattori, and T. Tanaka, “Development of a numerical model for evaluating the effect of litter layer on evaporation,” Journal of Forest Research, vol. 3, pp. 25–33, 1998.
  2. K. B. Wilson, P. J. Hanson, and D. D. Baldocchi, “Factors controlling evaporation and energy partitioning beneath a deciduous forest over an annual cycle,” Agricultural and Forest Meteorology, vol. 102, no. 2-3, pp. 83–103, 2000. View at Publisher · View at Google Scholar · View at Scopus
  3. J. Ogée and Y. Brunet, “A forest floor model for heat and moisture including a litter layer,” Journal of Hydrology, vol. 255, no. 1–4, pp. 212–233, 2002. View at Publisher · View at Google Scholar · View at Scopus
  4. J. Šnajdr, V. Valášková, V. Merhautová, J. Herinková, T. Cajthaml, and P. Baldrian, “Spatial variability of enzyme activities and microbial biomass in the upper layers of Quercus petraea forest soil,” Soil Biology and Biochemistry, vol. 40, no. 9, pp. 2068–2075, 2008. View at Publisher · View at Google Scholar · View at Scopus
  5. A. M. O'Connell, “Microbial decomposition (respiration) of litter in eucalypt forests of South-Western Australia: an empirical model based on laboratory incubations,” Soil Biology and Biochemistry, vol. 22, no. 2, pp. 153–160, 1990. View at Scopus
  6. J. P. Schimel, J. M. Gulledge, J. S. Clein-Curley, J. E. Lindstrom, and J. F. Braddock, “Moisture effects on microbial activity and community structure in decomposing birch litter in the Alaskan taiga,” Soil Biology and Biochemistry, vol. 31, no. 6, pp. 831–838, 1999. View at Publisher · View at Google Scholar · View at Scopus
  7. X. Lee, H.-J. Wu, J. Sigler, C. Oishi, and T. Siccama, “Rapid and transient response of soil respiration to rain,” Global Change Biology, vol. 10, no. 6, pp. 1017–1026, 2004. View at Publisher · View at Google Scholar · View at Scopus
  8. K. Savage, E. A. Davidson, A. D. Richardson, and D. Y. Hollinger, “Three scales of temporal resolution from automated soil respiration measurements,” Agricultural and Forest Meteorology, vol. 149, no. 11, pp. 2012–2021, 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. W. Borken and E. Matzner, “Reappraisal of drying and wetting effects on C and N mineralization and fluxes in soils,” Global Change Biology, vol. 15, no. 4, pp. 808–824, 2009. View at Publisher · View at Google Scholar · View at Scopus
  10. E. Berryman, J. D. Marshall, T. Rahn, M. Litvak, and J. Butnor, “Decreased carbon limitation of litter respiration in a mortality-affected pinon-juniper woodland,” Biogeosciences, vol. 10, pp. 1625–1634, 2013.
  11. M. Jomura, Y. Kominami, and M. Ataka, “Differences between coarse woody debris and leaf litter in the response of heterotrophic respiration to rainfall events,” Journal of Forest Research, vol. 17, pp. 305–311, 2012. View at Publisher · View at Google Scholar · View at Scopus
  12. T. Börner, M. G. Johnson, P. T. Rygiewicz, D. T. Tingey, and G. D. Jarrell, “A two-probe method for measuring water content of thin forest floor litter layers using time domain reflectometry,” Soil Technology, vol. 9, no. 3, pp. 199–207, 1996. View at Publisher · View at Google Scholar · View at Scopus
  13. P. J. Hanson, E. G. O'Neill, M. L. S. Chambers, J. S. Riggs, J. D. Joslin, and M. H. Wolfe, “Soil respiration and litter decomposition,” in North America Temperate Deciduous Forest Responses to Changing Precipitation Regimes, P. J. Hanson and S. D. Wullschleger, Eds., pp. 163–189, Springer, New York, NY, USA, 2003.
  14. T. J. Gillespie and G. E. Kidd, “Sensing duration of leaf moisture retention using electrical impedance grids,” Canadian Journal of Plant Science, vol. 58, pp. 179–187, 1978.
  15. K. Tamai and S. Hattori, “Modeling of evaporation from forest floor in a deciduous broad-leaved forest and its application to basin,” Journal of Forest Research, vol. 76, pp. 233–241, 1994 (Japanese).
  16. S. Kaneko, N. Akieda, F. Naito, K. Tamai, and Y. Hirano, “Nitrogen budget of a rehabilitated forest on a degraded granitic hill,” Journal of Forest Research, vol. 12, no. 1, pp. 38–44, 2007. View at Publisher · View at Google Scholar · View at Scopus
  17. Y. Goto, Y. Kominami, T. Miyama, K. Tamai, and Y. Kanazawa, “Aboveground biomass and net primary production of a broad-leaved secondary forest in the southern part of Kyoto prefecture, central Japan,” Bulletin of Forestry and Forest Products Research Institute, vol. 387, pp. 115–147, 2003 (Japanese).
  18. H. R. Bogena, J. A. Huisman, C. Oberdörster, and H. Vereecken, “Evaluation of a low-cost soil water content sensor for wireless network applications,” Journal of Hydrology, vol. 344, no. 1-2, pp. 32–42, 2007. View at Publisher · View at Google Scholar · View at Scopus
  19. M. Ataka, Y. Kominami, M. Jomura, K. Yoshimura C Uematsu, and C. Uematsu, “CO2 efflux from leaf litter focused on spatial and temporal heterogeneity of moisture,” Journal of Forest Research, vol. 19, pp. 295–300, 2014.
  20. H. Imoto, T. Nishimura, and T. Miyazaki, “Calibration and applicability of EC-5 sensor,” Journal of the Japanese Society of Soil Physics, vol. 114, pp. 27–31, 2010 (Japanese).
  21. M. S. Carbone, C. J. Still, A. R. Ambrose et al., “Seasonal and episodic moisture controls on plant and microbial contributions to soil respiration,” Oecologia, vol. 167, no. 1, pp. 265–278, 2011. View at Publisher · View at Google Scholar · View at Scopus