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The effects of canopy alteration–induced atmospheric deposition changes on stream chemistry in Japanese cedar forest
Forest Ecology and Management 448 (2019) 85–93
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The effects of canopy alteration–induced atmospheric deposition changes on stream chemistry in Japanese cedar forest
T
⁎
Tomoki Odaa, , Naohiro Imamurab, Tomohiro Egusaa, Nobuhito Ohtec a
Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan Center for Forest Restoration and Radioecology, Forestry and Forest Products Research Institute, 1 Matsunosato, Tsukuba, Ibaraki 305-8687, Japan c Department of Social Informatics, Graduate School of Informatics, Kyoto University, 36-1 Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan b
A B S T R A C T
Changes in atmospheric deposition have long-term effects on forest ecosystems and streamwater chemistry. Atmospheric deposition changes with forest disturbance. Although many studies have investigated the effects of air pollution, the effects of the long-term changes in atmospheric deposition induced by canopy alteration on streamwater chemistry have not been investigated sufficiently. This study evaluated the changes in atmospheric deposition, separated into dry deposition and canopy leaching components, in a regrowth forest and the resultant effects on streamwater chemistry. The chemical budgets of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ were investigated in regrowth and mature Japanese cedar forests from 1998 to 2015 in paired catchments in the Fukuroyamasawa Watershed, central Japan. After forest cutting in 1999, the total deposition of all ions to forest soil decreased; the Cl−, NO3−, SO42−, Na+, and Mg2+ were significantly lower in the regrowth forest than in the mature forest at 14– 15 years due to lower dry deposition, although the canopy had closed. In comparison, the total deposition of K+ and Ca2+ increased with canopy regrowth and was higher in the 15-year-old regrowth forest than the mature forest due to increased canopy leaching. Stream outputs of NO3−, SO42−, K+, Mg2+, and Ca2+ were not affected by the changes in atmospheric deposition, but the stream outputs of Cl− and Na+ decreased gradually for 5–10 years and remained lower (70–90%) at 15 years than those in the mature forest, which is consistent with the lower dry deposition input. The results of this study suggest that not only the canopy alteration but also the edge effects of taller trees of adjacent catchments influence the dry deposition input change, and the long-term streamwater chemistry change in Japanese cedar regrowth forest.
1. Introduction The chemistry of the stream water flowing out of forests has a strong effect on downstream ecosystems and can also impact human life. The major factors controlling streamwater chemistry are geological weathering, atmospheric deposition, biological processes, and hydrological processes (Feller, 2005). Streamwater chemistry can change due to forest disturbances, such as forest harvesting (Likens et al., 1970; Neal et al., 1998; Swank et al., 2001; Feller, 2005) and defoliation (Swank et al., 1981; Webb et al., 1995; Eshleman et al., 1998; Ohte et al., 2003; Imamura et al., 2017). These forest disturbances have affected forest ecosystems and resulted in phenomena including increased weathering rates (Baily et al., 2003), decreases in atmospheric deposition (Reynolds et al., 1995; Oda et al., 2009), decreases in uptake nutrients by trees (Vitousek et al., 1979), and enhancement of microbial activities (Harvey et al., 1980; Byrd et al., 2000). The changes to forest ecosystems are long term, acting on timescales of several years to decades. Studies have provided examples in which streamwater chemistry recovered due to the restoration of forest vegetation (Neal et al., 1998; Martin et al., 2000; Swank et al., 2001). However, conditions have continued to deteriorate (Tokuchi et al.,
⁎
2013; Webster et al., 2016) in other cases, indicating that behavior differs among locations. Information on which to base long-term predictions of streamwater chemistry following forest disturbances, such as response and recovery times, is insufficient at present (Oda et al., 2018). Previous investigations of the fluctuations in streamwater chemistry following forest disturbances have generally focused on changes in the soil ecosystem, such as microbial activity and nutrient uptake by plants (Binkley and Brown, 1993; Martin et al., 2000; Burns and Murdoch, 2005). In addition to the internal chemical circulation processes in forest ecosystems, the fluctuation in atmospheric deposition is an important factor that determines streamwater chemistry. Changes in atmospheric deposition due to canopy regrowth can have important effects on forest nutrient cycling dynamics, as the canopy captures a large amount of dry fallout and leaches numerous chemicals (Reynolds et al., 1995; Feller, 2005; Martin et al., 2000; Oda et al., 2009). The amount of atmospheric deposition occurring in forests is known to vary and to depend on the state of the forest, for example its age, canopy structure, and tree height, in addition to the concentrations of substances in the atmosphere (Marques and Ranger, 1997; Malek and Astel, 2008; De Schrijver et al., 2008).
Corresponding author. E-mail address: [email protected] (T. Oda).
https://doi.org/10.1016/j.foreco.2019.05.058 Received 25 March 2019; Received in revised form 22 May 2019; Accepted 23 May 2019 Available online 12 June 2019 0378-1127/ © 2019 Elsevier B.V. All rights reserved.
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(Fig. 1). A mature mixed plantation of Cryptomeria japonica (Japanese cedar) and Chamaecyparis obtusa (Hinoki cypress) was planted from 1928 to 1931 over both catchments and remained until March 1999. In April 1999, the trees were clear cut from Catchment B; in April 2000, seedlings of the same species were planted. The planted stand density was approximately 3000 stems ha−1. Inferior trees were cleared and removed, and the remaining trees were pruned in the regrowth forest in March 2013, where ≤5% of the trees were harvested. In February 2014, due to heavy snow, the Japanese cedar trees in the replanted forest were damaged, and about 13% fell and left on the ground. In 2015, the stand densities in the study plots at Catchments A and B were 792 and 2550 stems ha−1, respectively (Table 1). Catchment B is defined as a regrowth forest and Catchment A as a mature forest. Japanese cedar and Hinoki cypress coexist in the catchments; their total basal areas in the survey plots were 19.7 and 6.7 m2 ha−1 in mature forest, and 4.5 and 0.17 m2 ha−1 in regrowth forest, respectively. We consider these Japanese cedars to be representative of the catchments. Four plots were set up in the catchments, designated A1, A2, B1, and B2 (Fig. 1). All trees in B1 and B2 and 80% of the trees in A1 and A2 were Japanese cedar. The canopy cover ratio and leaf area index (LAI) are mainly used as indicators of canopy alteration. The LAI and canopy cover ratio were calculated from hemispherical photographs taken using a fisheye lens in the Octobers of 2013 and 2015 (Table 1). Tree height, diameter at breast height, and stand density were measured in 2006, 2012, 2013, 2014, and 2015; the results are shown in Table 1. Trees grew gradually from 1999 to 2012 in the regrowth forest, and the canopy became fully closed in 2012 (Fig. 2).
The influence of depositional changes on streamwater chemistry has been examined in previous research and documented long-term fluctuations in solute concentrations (particularly those of NO3−, SO42−, and dissolved organic carbon) of streamwater due to the influence of acidic deposition (Aber et al., 1989; Martin et al., 2000; Lovett and Goodale, 2011). However, changes in chemical inputs during forest succession and their effects on streamwater chemistry have not been investigated sufficiently. Forest growth takes place over decades, during which changes in tree growth, canopy closure, and internal circulation occur. Precise evaluation of the effects of forest regrowth on changes in deposition in forests, such as dry deposition (DD) and canopy leaching (CL), is necessary for the forecasting of nutrient cycles and post-disturbance recovery of streamwater chemistry. In previous studies, the continuous measurement of deposition from the early growth stage after forest cutting has been limited, although some researchers have compared deposition among forest ages (Marques and Ranger, 1997; Malek and Astel, 2008). In addition, few studies have simultaneously observed the changes in atmospheric deposition along with forest regrowth and streamwater chemistry. This study evaluated the effects of canopy alteration-induced atmospheric deposition changes on stream chemistry in a regrowth forest. This study was conducted in a pair of small headwater catchments covered by same soil type and with the same bulk precipitation deposition in the Fukuroyamasawa experimental watershed at the Tokyo University forest in Japan. We evaluated changes in atmospheric deposition, including bulk precipitation, DD, and CL, using a canopy budget model (Draaijers and Erisman, 1995) with canopy alteration in 15 years after replanting, and examined the effects of changes in atmospheric deposition on the long-term changes in streamwater chemistry using a paired catchment approach.
2.2. Measurement 2. Methods 2.2.1. Precipitation, throughfall, and stemflow The precipitation volume was measured at a meteorological station located 200 m from the Fukuroyamasawa experimental watershed using a 0.5-mm tipping-bucket rain gauge (No.34-T, Ohta-Keiki, Tokyo, Japan) and a bulk sampler, which consisted of a 10-L plastic bottle collector with a 21-cm-diameter funnel, from April 2014 to March 2016. Bulk precipitation (BP) samples for chemical analysis were collected in 100-mL polyethylene bottles using a 10-L plastic bottle collector weekly to monthly. Throughfall (TF) volumes in the regrowth and mature forests were measured using 21 and 15 samplers, respectively, which were of the same design as the bulk sampler described above and were installed randomly in the B1, B2, A1, and A2 plots (Fig. 1) from April 2014 to March 2016 at weekly to monthly intervals. TF samples for chemical
2.1. Site description This study was conducted in a pair of small headwater catchments (Fukuroyamasawa Experimental Watershed, Catchment A, 0.8 ha; Catchment B, 1.1 ha) at the Tokyo University forest in Chiba, Chiba Prefecture, Japan (35°12′N, 140°06′E; Fig. 1). Both catchments are underlain by tertiary sedimentary rock. The soil type is common to both catchments and is classified as Cambisol. The altitude ranges from 126 to 230 m above sea level. The annual mean temperature was 14 °C (1994–2014), and the annual mean precipitation was 2,320 mm (1994–2014). Precipitation was higher during the summer season, and snow was rare. The study site is located < 10 km from the ocean, and the major source of pollution was Tokyo, located 70 km from the site
Fig. 1. Location (a) and topography (b) of the Fukuroyamasawa experimental watershed. The dashed line denotes the border between catchments A (mature) and B (regrowth). Squares at A1, A2, B1, and B2 are plots for the measurement of tree height, diameter at breast height, and atmospheric deposition. Black dots (●) show the location of throughfall collectors. 86
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Table 1 Stand age, tree height, mean diameter at breast height (DBH), leaf area index (LAI), canopy cover ratio, and stand density in catchments A and B. Age
Height (m)
DBH (cm)
LAI
Canopy cover (%)
Density (stem/ha)
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Catchment A (Mature) 2013 84 2015 86
25.0 –
5.9 –
36.0 –
12.8 –
2.7 2.0
0.2 0.6
92.0 84.0
1.5 7.0
792 792
Catchment B (Regrowth) 2006 6 2012 12 2013 13 2014 14 2015 15
6.1 9.8 10.1 10.9 11.0
2.2 3.4 3.3 3.9 3.8
7.3 9.3 12.1 12.6 13.0
3.4 5.5 4.4 5.0 5.0
– 3.0 3.2 – 2.5
– 0.8 0.6 – 0.3
– 91.5 93.9 – 89.5
– 4.0 2.8 – 2.9
3000 3000 – – 2550
the 21 and 15 TF samplers, respectively. In this study, the mean SF volume in the regrowth and mature forest from the six and four sampled stems were assumed to be representative of the SF volume in each catchment. The catchment-scale SF volume was estimated by multiplying the mean SF volume by the stand density and converting to millimeters.
analysis were collected in 30-mL polyethylene bottles from the same TF sampler after measurement of the TF volume, by measuring weight using a hand scale. Stemflow (SF) volumes in the regrowth (six stems) and mature forests (four stems) were measured using 70-L plastic tanks and 0.5-mm tipping-bucket rain gauges connected to wrapping hoses placed around the stems of Japanese cedar trees at a height of 1.3 m (Oda et al., 2011). SF samples were collected in 100-mL polyethylene bottles after being weighed with a hand scale from four stems in the regrowth forest and three stems in the mature forest at weekly to monthly intervals from April 2014 to March 2016.
2.3.2. Chemical analysis The pH values of BP, TF, SF, and stream water samples were measured after field sampling using a pH meter (D-54, Horiba, Kyoto, Japan). Water samples were filtered using 0.2-μm membrane filters, and the concentrations of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ were determined using ion chromatography (LC-10A, Shimadzu, Kyoto, Japan; DX-500, Thermo Fisher Scientific, Waltham, MA, USA).
2.2.2. Stream runoff Stream runoff was measured continuously from January 2012 to March 2016 at 10-min intervals using 90° V-notch weirs, the locations of which are labeled in Fig. 1. In 2015, weir A was sometimes buried under sediment, resulting in missing data for stream runoff in March and September in Catchment A. Stream water was sampled manually at weekly to monthly intervals at weirs of Catchments A and B from April 2014 to March 2016. For precise calculation of chemical outputs, highfrequency sampling during storm events is required (Oda et al., 2011). In this study, stream water samples during storm events (19–21 June 2012: total rainfall, 90 mm; 5–6 October 2014: 168 mm) were collected at 1–2-hour intervals using an automatic sampler (Model 900, American Sigma, New York, USA).
2.3.3. Flux calculation The BP chemical flux was calculated as the load during each observation period by multiplying the concentrations by the precipitation volume. TF and SF fluxes for each observation period were calculated by multiplying the volume-weighted mean concentrations with the mean TF and SF volumes. In addition, the spatial variation was evaluated by calculating the flux for each sampler for each period. The annual BP was calculated as the sum of the BP flux value of each period. The total annual deposition through the canopy (TD) in the regrowth and mature forests was determined as the sum of TF and SF fluxes. The difference of TD between the regrowth forest and mature forest were analyzed statistically considering the spatial variation. The annual BP, TF, and SF were calculated for the period April 2014 to March 2016. Normally, the water year was defined as January 1 to December 31, but for 2014 and 2015, annual BP, TF, and SF were calculated from April
2.3. Analysis 2.3.1. Throughfall and stemflow rates The TF volume during each observation period in the regrowth and mature forests was calculated as the mean TF volume measured using
1999
2005
2012
Fig. 2. Photographs of catchment B (regrowth forest) in 1999, 2005, and 2012. 87
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independent of canopy exchange. We determined the DDf as:
2014 to February 2015 and from April 2015 to March 2016, during the periods when the stream runoff, TF, and SF were measured simultaneously. Annual streamwater chemistry output loads (LSW) were calculated by integrating the hourly fluxes of dissolved ions. A regression method was used to estimate the hourly concentration because discharge was measured more frequently (Oda et al., 2011). These equations are expressed as follows:
C(t) = a log Q(t) + b
L SW =
∑ C(t)Q(t)
+
The CL of K , Mg
, and Ca
2+
was calculated by: (6)
Total CUs of H+ and NH4+ were assumed to equal the total CL of base cations (BC = K+ + Mg2+ + Ca2+) minus weak acid release (CLwa) (Schaefer et al., 1992):
(1)
CUNH4 + H = CLBC − CL wa ,
(7)
where CLwa was computed according to:
(2)
(8)
CL wa = TFwa + SFwa − BPwa +
NH4+ NH4+
were subsequently calculated based on The CUs of H and the total CU of H+ and and the assumption that H+ has an exchange efficiency six times greater than that of NH4+ (De Schrijver et al., 2004):
CUNH4 = CUNH4 + H × {(BP + TF + SF) NH4 /[(BP + TF + SF) NH4 + 6 × (BP + TF + SF)H]}
(9) NO3−
In this study, we assumed that the CU of was negligible because these values are typically lower than those for NH4+ (Stachurski and Zimka, 2002).
2.3.4. Analysis of TD and LSW changes in the regrowth forest To analyze the long-term changes in the TD and LSW in the regrowth forest following tree cutting, we obtained TD and LSW data for 1998, 2000, 2002, and 2006 in the same catchment in Oda et al. (2011) and added them to the observed data from 2012 and 2014–2015. Timeseries changes were assessed using the paired catchment approach. The long-term fluctuations in the regrowth-to-mature forest ratios of TD and LSW were examined, assuming that the ratio before cutting was unity. To evaluate the effect of TD changes on the LSW after forest regrowth, we also assessed the chemical budget. The chemical budget in the catchment is expressed as follows:
3. Results 3.1. TD and LSW in regrowth and mature forests The TF, SF, and LSW in 2014 (April 2014 to February 2015) and 2015 (April 2015 to March 2016) in the regrowth and mature forests are shown in Fig. 3. For all observed ions, TF accounted for the majority (≥90%) of TD, whereas SF was ≤10% of TD. The TD input values for Cl−, NO3−, SO42−, Na+, and Mg2+ were significantly lower in the regrowth forest than in the mature forest during 2014 and 2015 (t-test; all p < 0.05). In comparison, the TD values of NH4+, K+, and Ca2+ exhibited no significant difference between the regrowth and mature forests (both p > 0.05). During 2014, the LSW values for Cl−, SO42−, Na+, and K+ in the regrowth forest were lower than those in the mature forest, and the LSW values in the regrowth forest were higher for NO3−, Mg2+, and Ca2+ (Fig. 3). The NH4+ concentrations in the mature and regrowth forest were close to zero throughout the observation period.
(3)
where CEX is the chemical exchange rate in the catchment, and LD is the loss of groundwater to deep percolation. In this study, the deep percolation rate (D) was estimated at 500 mm yr−1 using the chloride mass balance method (Oda et al., 2008). The LD was calculated by multiplying D by the mean concentration observed during manual sampling. The output to input [(LSW + LD)/TD] ratios in the mature and regrowth forest were calculated for 2002–2014, excluding the period of tree cutting. When this ratio is near unity, input and output are balanced; when the value is > 1, other sources in the catchment are critical to the chemical balance.
3.2. Changes in TD and LSW in the regrowth forest The TD and LSW values during the growth process from pre-cutting to 15 years of regrowth are shown in Tables 2 and 3. The changes in the ratios of TD in the regrowth forest to that in the mature forest are shown in Fig. 4. After tree cutting in 1999 and planting in 2000, the TD for the regrowth forest clearly declined to 20–70% of the mature forest value, with the exception of NH4+. For Cl−, NO3−, SO42−, Na+, and Mg2+, the lower TD for the regrowth forest continued for 15 years. For K+ and Ca2+, the TD values clearly increased in the regrowth forest from 2006 to 2015, and were greater than those in the mature forest in 2015. Fig. 4 also shows the changes in the ratios of annual runoff and LSW in the regrowth forest to those in the mature forest. The ratios of Lsw increased for all ions just after clear-cutting. In 2000, the average ratio increase was 131% ( ± 9%), excluding NO3− and K+, which is in agreement with the increased rate of runoff (130%); greater increases of 1000% and 190%, respectively, were observed for NO3− and K+. The LSW values for Cl−, Na+, and K+ in the regrowth forest decreased to below the mature forest values, with regrowth-to-mature forest ratios of 77%, 90%, and 76%, respectively, in 2014 (Fig. 4). The LSW of Cl− was
2.3.5. Chemical budgets through the canopy To estimate the contributions of the DD and canopy exchange (CE) to the TD in the regrowth and mature forest catchments, we calculated annual DD and canopy exchange (CE) using the canopy budget model. CE refers to CL and canopy uptake (CU). The leaching of Na+, Cl−, and SO42− from leaves and branches is minor, and interaction with the canopy is negligible (Parker, 1983; Matzner et al., 2004). In this study, the TF + SF of Na+, Cl−, and SO42− were assumed to be due to BP + DD. The DD of K+, Mg2+, and Ca2+ occurred at the same rate as the deposition of particles containing a tracer ion (Draaijers et al., 1997). DD values for K+, Mg2+, and Ca2+ were calculated using the following equation:
DD = DDf × BP,
2+
CL = TF + SF − BP − DD
where C(t) is the solute concentration at time t, Q(t) is the runoff rate at time t (mm h−1), a and b are empirical parameters, and LSW is the load of solutes (kg ha−1). The calculation of LSW requires frequent observations, and the data were limited. In this study, we evaluated LSW using data from 2012 and 2014–2015, when frequent observations were made in both catchments. We used the C–Q relations of the 2012 and 2014–2015 periods in both catchments, which were derived from stream water concentrations and runoff rates during the sampling periods. LSW values in 2012, 2014, and 2015 were calculated for January to December 2012, April 2014 to February 2015, and April 2015 to March 2016, respectively.
TD + CEX = L SW + LD,
(5)
DDf = (TFNa + SFNa − BPNa)/BPNa
(4)
where DDf is the dry deposition factor. The majority of previous studies used Na+ as a tracer ion for calculation of the DD of base cations (Staelens et al., 2008). In these models, Na+ was used as the tracer ion because it is assumed to 88
89
17 12 10 21 21 20 9 4 5 8 8 10 13 4 4 17 25 33 15 10 8 5 3 2 40 22 31 38 44 40
b
a
Actual observation period was from April 2014 to February 2015. Actual observation period was from April 2015 to March 2016.
67 36 40 43 40 37 56 17 18 23 22 12 B (Regrowth) 1929 2151 2363 2088 1712 2286 Catchment 1998 2000 2002 2006 2014a 2015b
152 39 57 66 90 77
Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) This study This study 17 22 28 28 21 19 9 8 15 11 12 13 13 20 29 26 29 28 15 6 3 7 3 3 40 33 73 58 66 56 67 52 81 67 48 45
Ca2+ (kg ha−1) Mg2+ (kg ha−1) K+ (kg ha−1) NH4+ (kg ha−1) Na+ (kg ha−1) SO42− (kg ha−1) NO3− (kg ha−1)
56 41 56 46 30 32 152 70 141 110 148 112 A (Mature) 1929 1785 1961 1733 1477 1927
The DD values for all ions in the regrowth forest were lower than those in the mature forest, on separating the TD into the BP, DD, and CL in 2014 and 2015 (Fig. 5). In particular, the DD rates for Cl−, SO42−, and Na+ in the regrowth forest were at 22–51%, 51–54%, and 16–21%,
Catchment 1998 2000 2002 2006 2014a 2015b
3.3. Chemical budgets through the canopy in regrowth and mature forests
Cl− (kg ha−1)
significantly lower in the regrowth forest than in the mature forest after cutting (t-test; p = 0.02), whereas the changes in the LSW of SO42−, Na+, and K+ were not significant (t-test; p > 0.05). However, the declining trend of regrowth-to-mature forest ratios of the LSW values for Na+ and K+ since 2000 was obvious (linear regression analysis; p < 0.05). In comparison, the LSW values for Mg2+, and Ca2+ remained greater in the regrowth forest than in the mature forest in 2014. The LSW of NO3− increased immediately after cutting, and then fell to values of those in the mature forest within 6–12 years, nearly returned to their pre-cutting levels, and then increased again in the 14th year. The mean ratio [(LSW + LD)/TD] for Cl− in the regrowth forest was 1.0 ( ± 0.3), and that in the mature forest was 0.9 ( ± 0.07). This result shows that the atmospheric deposition of Cl− was a primary source of chemical output in both catchments. This result is consistent with studies that reported that Cl− is not reactive under typical catchment conditions and the source of streamwater output is atmospheric deposition (Peters and Ratcliffe, 1998). The mean ratios for Na+ and SO42− ranged from 1.4 to 2.2 in the regrowth and mature forests, which indicates that the TD input contributed approximately half of their chemical output. Mg2+ and Ca2+ exhibited (LSW + LD)/TD ratios of 2.6–7.9, which indicates that the contribution of TD was < 1/3 of their chemical output. The ratios for NO3− and K+ were 0.5 and 0.7, respectively, in mature forest, showing that chemical uptake was critical in the forest ecosystems.
Throughfall + Stemflow (mm)
Table 2 Total annual volumes of throughfall and stemflow rates and total deposition of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ in regrowth and mature forests from 1998 to 2015. The data for 1998–2006 were taken from Oda et al. (2011).
Fig. 3. Annual deposition of throughfall (TF), stemflow (SF), and stream water chemical load (LSW) of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ in the regrowth forest (RF) and mature forest (MF) from April 2014 to February 2015 (2014) and from April 2015 to March 2016 (2015). LSW in MF in 2015 are missing. The error bars represent the standard error.
Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) This study This study
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Table 3 Annual runoff and stream water chemical outputs of Cl−, NO3−, SO42−, Na+, K+, Mg2+, and Ca2+ in regrowth and mature forests from 1998 to 2015. The data for 1998–2006 were taken from Oda et al. (2011). Cl− (kg ha−1)
NO3− (kg ha−1)
SO42− (kg ha−1)
Na+ (kg ha−1)
K+ (kg ha−1)
Mg2+ (kg ha−1)
Ca2+ (kg ha−1)
Catchment A (Mature) 1998 910 2000 768 2002 895 2006 738 2012 985 2014a 655 – 2015b
79 65 76 57 96 66 –
18 28 14 19 8 10 –
73 58 69 53 63 39 –
62 51 60 48 65 43 –
8 7 8 9 9 13 –
22 18 21 17 19 13 –
82 66 78 65 69 45 –
Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) This study This study This study
Catchment B (Regrowth) 1998 867 2000 996 2002 1147 2006 915 2012 1193 2014a 786 2015b 1201
60 64 50 33 55 41 63
7 108 49 22 7 30 47
55 59 67 44 49 33 51
64 63 63 51 55 40 60
7 10 9 9 8 7 10
21 24 25 20 16 14 21
82 88 85 81 77 51 77
Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) This study This study This study
Runoff (mm)
a b
Actual observation period was from April 2014 to February 2015. Actual observation period was from April 2015 to March 2016.
Fig. 4. Changes in the regrowth-to-mature forest (RF/MF) ratios of total deposition (TD) and stream water chemical load (LSW) for Cl−, NO3−, SO42−, Na+, K+, Mg2+, and Ca2+ from 1998 to 2015. The dashed lines show the RF/ MF ratios of annual runoff.
Fig. 5. Forest canopy chemical budget in terms of bulk precipitation (BP), dry deposition (DD), and canopy leaching (CL) of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ in regrowth forest (RF) and mature forest (MF) from April 2014 to February 2015 (2014) and from April 2015 to March 2016 (2015).
respectively, of the mature forest values. The ratios of CL for K+ and Ca2+ in the regrowth forest were 91% and 140%, and 115% and 123%, of the mature forest values in 2014 and 2015, respectively (Fig. 5). The contribution of CL to the TD of K+, Mg2+, and Ca2+ was large (≥34%). In particular, the CL of K+ in the regrowth forest accounted for 22 and 27 kg ha−1yr−1 in 2014 and 2015, respectively, which accounts for 89% and 81% of the TDs. For K+, Mg2+, and Ca2+, the DD component was relatively small in the regrowth forest, whereas the CL component was larger, such that the TD equaled or exceeded that in the mature forest The TDs in regrowth and mature forests in 1998, 2002, 2006, 2014, and 2015 were separated into BP, DD, and CL using a canopy budget model (Table 4). The long-term changes in the DD in the regrowth
showed that DD values in the regrowth forest decreased for all ions after cutting and then approached those in the mature forest gradually over 15 years, but remained less than 60% of those of mature forest in 2015 (Fig. 6). In contrast, the CLs of K+, Mg2+, and Ca2+ in the regrowth forest decreased immediately after cutting, and then increased to similar or higher values of 91–140%, 63–80%, and 115–123% those in mature forest in 2014 and 2015, respectively.
90
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Table 4 Total deposition (TD), bulk precipitation (BP), dry deposition (DD), and canopy leaching (CL) of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ in regrowth and mature forests from 1998 to 2015. (kg ha−1) Catchment A (Mature)
Catchment B (Regrowth)
1998
2002
2006
2014a
2015b
1998
2006
2014a
2015b
Cl−
TD BP DD TD
152 77 74 56
141 57 84 56
110 62 48 46
148 74 74 30
112 41 71 32
152 77 74 56
66 62 4 23
90 74 16 22
77 41 35 12
NO3−
BP DD TD
3 53 67
18 38 81
18 28 67
30 0.3 48
22 10 45
3 53 67
18 4 43
30 −7 40
22 −10 37
SO42−
BP DD TD
33 34 40
40 41 73
37 30 58
31 18 66
27 18 56
33 34 40
37 8 38
31 9 44
27 10 40
Na+
BP DD TD
17 23 15
31 42 3
36 22 7
39 27 3
36 20 3
17 23 15
36 2 5
39 4 3
36 4 2
NH4+
BP DD CE TD
4 11
8 12
3 9
3 3
29
26
8 5 −10 28
4 11
13
3 3 −3 29
13
17
3 1 −1 25
8 −1 −4 33
K+
BP DD CL TD
2 2 10 9
4 5 21 15
7 4 15 11
2 2 24 12
5 3 20 13
2 2 10 9
7 0.4 10 8
2 0.3 22 8
5 1 27 10
Mg2+
BP DD CL TD
1 1 6 17
5 7 3 28
7 4 −1 28
5 3 4 21
4 2 6 19
1 1 6 17
7 0.4 0.4 21
5 1 3 21
4 0.5 5 20
Ca2+
BP DD CL
1 1 14
10 13 6
16 9 3
4 2 15
4 2 13
1 1 14
16 1 4
4 0.4 17
4 0.5 15
a b
Actual observation period was from April 2014 to February 2015. Actual observation period was from April 2015 to March 2016.
4. Discussion 4.1. Changes in atmospheric deposition with canopy regrowth In the regrowth forest, the TD values for all ions declined rapidly after clear-cutting, and the TD rates of Cl−, SO42−, NO3−, Na+, and Mg2+ remained lower than those in the mature forest over 15 years. This pattern is due to the smaller DD rates for these ions, consistent with previous findings for young regrowth forests. Potter et al. (1991) investigated DD transfer in a regenerated forest and showed that DD rates were around 2–5 times lower than those in a mature forest. There have been reports that the DD input is determined by the canopy height, canopy closure, and LAI (Lovett and Reiners, 1986; Erisman and Draaijers, 2003). In the present study, despite the higher LAI and canopy cover of the regrowth forest than of mature forest in 2015 (Table 1), the DD inputs were smaller than those in the mature forest. This result suggests that the changes in the DD input in the regrowth forest are related not only to canopy alterations, such as LAI and canopy cover changes, but also to lower tree height. This result is consistent with the results for other forests in Japan, which showed higher DD inputs in taller trees in broadleaf and coniferous forests (Imamura et al., 2012, 2018). Dry particles may have passed over the regrowth forest canopy and then been scavenged by the taller canopy of the surrounding mature forest. In general, wind speed is greater at higher altitudes, where a tall canopy would be able to capture more DD from such winds (Hofhansl et al., 2011). Gielis et al. (2009) also showed that DD velocities were lower for a regrowth plot than for surrounding taller trees. Wuyts et al. (2009) described an edge effect, in which TF deposition rates were smaller outside the steep forest edge where
Fig. 6. Changes in the regrowth-to-mature forest (RF/MF) ratios of dry deposition (DD) and canopy leaching (CL) for Cl−, NO3−, SO42−, Na+, K+, Mg2+, and Ca2+ from 1998 to 2015.
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with the previously reported response of NO3− after snow damage in Hubbard Brook Forest (Green et al., 2013). The LSW of NO3− and K+ are thought to be more strongly influenced by biological processes in the soil than by changes in atmospheric deposition, similar to studies that reported that the concentrations of NO3− and K+ vary depending on biological factors, such as tree uptake and microbial activity (Vitousek et al., 1979, Bormann and Likens, 1994; Likens et al., 1996). For the factors that influence long-term changes in streamwater chemistry, a time delay occurs due to water storage in the catchment. Gradual long-term fluctuations, such as those observed for Cl−, indicate the timescale of replacement in the catchment (Oda et al., 2009). Decreased DD occurs at the same time as canopy removal, but the replacement of stored water in the catchment basin takes time, such that the response of the LSW is delayed (Fig. 4). This process can also be applied to recovery, and even when DD recovers with tree growth, a time lag is expected and thus the response of LSW will be more gradual.
vegetation in front of the forest edge was cut or was lacking. The difference in tree height between regrowth and mature forests resulted in a forest edge, leading to lower DD in the regrowth forest. Moreover, the forest edge effect was more significant in coniferous forest than in deciduous forest (Wuyts et al., 2008). At this study site, the area covered by coniferous forest or clear-cut area was less than 1 ha, so the influence of the forest edge effect could be larger. The study result suggests that the recovery of chemical input may be delayed behind that of the canopy in small cutting areas under the influence of the surrounding tree height. The DD values for NO3− and NH4+ became negative (Table 4), likely due to nitrogen uptake into the canopy. Some studies have shown that nitrogen CU is an active process (Lovett et al., 1996). Coniferous trees have larger canopy storage capacities and longer water residence times in the canopy than broadleaf trees. Therefore, the nitrogen uptake might be greater in coniferous forests. TD rates for K+, Mg2+, and Ca2+ in the regrowth forest in the present study increased after 6 years and the TD rates of K+ and Ca2+ were similar to those in the mature forest when the trees of the regrowth forest were 14–15 years old. For these ions, the CL rates in the regrowth forest were larger than those in the mature forest in 2015. The results of the present study indicate that changes in CL in regrowth forest are correlated with canopy alteration. In general, K+, Mg2+, and Ca2+ in TF are thought to originate from CL (De Schrijver et al., 2007), and some studies have shown that CL is greater in young forests than in mature forests (Lovett and Lindberg, 1993; Malek and Astel, 2008). The results of the present study are in reasonable agreement with these previous findings.
5. Conclusion In this study, we examined the changes in atmospheric deposition separated into components of DD and CL that occurred along with forest canopy regrowth in Japanese cedar plantation forests and the effects of the deposition changes on stream chemistry 14–15 years after replanting. The TD values for Cl−, NO3−, SO42−, Na+, and Mg2+ were lower than in the mature forest due to the lower DD values although the LAI increased, whereas the CL of K+ and Ca2+ increased with the LAI in the regrowth forest. The canopy alteration effect contributed greatly to the CL changes, but the DD changes lagged behind the canopy regrowth due to the edge effect of the surrounding catchment in the regrowth forest. The results also revealed that the lower DD in the regrowth forest significantly affected long-term changes in the streamwater chemistry of Cl− and Na+ in the regrowth process. For other ions, no clear response to streamwater chemistry was found in relation to atmospheric deposition changes. In this study, although there was no direct relationship between canopy alteration and streamwater chemistry, changes in DD are significant in regrowth forest and persistent, and would affect the chemical cycle in the forest ecosystem. The results of this study suggested that not only canopy alteration but also edge effects of surrounding catchments influence long-term changes in the DD input and the streamwater chemistry in a small Japanese cedar regrowth forest.
4.2. Effects of atmospheric deposition changes on streamwater chemistry The LSW values fluctuated with forest regrowth in comparison with the mature forest. The decline in the LSW for Cl− and Na+ and the increase in the LSW for NO3− after cutting were obvious in this study (Fig. 4). Responses of these anions following forest cutting have been observed in previous studies (Reynolds et al., 1995; Martin et al., 2000; Neal et al., 2004). In addition, the streamwater chemistry recovered to its pre-cutting conditions in the early regrowth forest in as little as 4–5 years (Martin et al. 2000). In this study, the LSW for NO3− tended to approach the pre-cutting level in 6–12 years, whereas the LSW values for Cl− and Na+ did not tend to approach the pre-cutting level within 15 years (Fig. 4). The results of the chemical budget investigations indicate that the TD input reduction during the regrowth period caused by a decrease in DD was the main factor that determined the lower long-term LSW values for Cl− and Na+. However, there was no clear change in streamwater chemistry in the regrowth processes with increases in the LAI and the canopy cover ratio (Fig. 4, Table 1). This is thought to be due to the delayed recovery of DD compared with the recovery of LAI, as noted above, due to the edge effect of surrounding taller trees, especially in small regeneration areas. For SO42−, Mg2+, and Ca2+, the TD input fluctuated due to the decrease in DD and increased CL after cutting, but no significant changes in the LSW were found, indicating the presence of other sources, such as chemical weathering, in this catchment. This result indicated that the fluctuation in DD and CL with canopy alteration did not contribute clearly to the streamwater chemistry of these ions. However, the lower DD in the regrowth forest would affect the chemical circulation in the forest ecosystems. The increase in SO42− leaching due to air pollution and the subsequent recovery processes have been problematic (Driscoll et al., 1998). This study suggested that consideration of the TD changes with the changing canopy structure is necessary to evaluate the precise chemical balance in the forest ecosystems in regrowth forest. In addition, the LSW values of NO3− and K+ after forest cutting behaved differently than did those of other ions. After cutting in 1999, rapid fluctuations occurred, and after snow damage during 2013 and 2014, NO3− leaching increased again despite the absence of changes in the runoff rate and atmospheric deposition. Such fluctuations are consistent
Acknowledgements This study was financially supported by research funds of JSPS, Japan (26850096, 18K05721). This study was part of an integrated paired watershed project jointly conducted by the Laboratory of Forest Hydrology and Erosion Control Engineering and the University Forest in Chiba, the University of Tokyo. The authors appreciate two anonymous reviewers for their thoughtful comments. References Aber, J.D., Nadelhoffer, K.J., Steudler, P., Melillo, J.M., 1989. Nitrogen saturation in northern forest ecosystems. Bioscience 39 (6), 378–386. Bailey, S.W., Buso, D.C., Likens, G.E., 2003. Implications of sodium mass balance for interpreting the calcium cycle of a forested ecosystem. Ecology 84, 471–484. Binkley, D., Brown, T.C., 1993. Forest practices as nonpoint sources of pollution in NorthAmerica. Water Resour. Bull. 29, 729–740. Bormann, F.H., Likens, G.E., 1994. Pattern and Process in a Forested Ecosystem: Disturbance, Development and the Steady State Based on the Hubbard Brook Ecosystem Study. Springer, New York. Byrd, K.B., Parker, V.T., Vogler, D.R., Cullings, K.W., 2000. The influence of clear-cutting on Ectomycorrhizal fungus diversity in a Lodgepole Pine (Pinus contorta) stand, Yellowstone National Park, Wyoming, and Gallatin National Forest, Montana. Can. J. For. Res. 78, 149–156. Burns, D.A., Murdoch, P.S., 2005. Effects of a clearcut on the net rates of nitrification and N mineralization in a northern hardwood forest, Catskill Mountains, New York, USA.
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The effects of canopy alteration–induced atmospheric deposition changes on stream chemistry in Japanese cedar forest
T
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Tomoki Odaa, , Naohiro Imamurab, Tomohiro Egusaa, Nobuhito Ohtec a
Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan Center for Forest Restoration and Radioecology, Forestry and Forest Products Research Institute, 1 Matsunosato, Tsukuba, Ibaraki 305-8687, Japan c Department of Social Informatics, Graduate School of Informatics, Kyoto University, 36-1 Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan b
A B S T R A C T
Changes in atmospheric deposition have long-term effects on forest ecosystems and streamwater chemistry. Atmospheric deposition changes with forest disturbance. Although many studies have investigated the effects of air pollution, the effects of the long-term changes in atmospheric deposition induced by canopy alteration on streamwater chemistry have not been investigated sufficiently. This study evaluated the changes in atmospheric deposition, separated into dry deposition and canopy leaching components, in a regrowth forest and the resultant effects on streamwater chemistry. The chemical budgets of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ were investigated in regrowth and mature Japanese cedar forests from 1998 to 2015 in paired catchments in the Fukuroyamasawa Watershed, central Japan. After forest cutting in 1999, the total deposition of all ions to forest soil decreased; the Cl−, NO3−, SO42−, Na+, and Mg2+ were significantly lower in the regrowth forest than in the mature forest at 14– 15 years due to lower dry deposition, although the canopy had closed. In comparison, the total deposition of K+ and Ca2+ increased with canopy regrowth and was higher in the 15-year-old regrowth forest than the mature forest due to increased canopy leaching. Stream outputs of NO3−, SO42−, K+, Mg2+, and Ca2+ were not affected by the changes in atmospheric deposition, but the stream outputs of Cl− and Na+ decreased gradually for 5–10 years and remained lower (70–90%) at 15 years than those in the mature forest, which is consistent with the lower dry deposition input. The results of this study suggest that not only the canopy alteration but also the edge effects of taller trees of adjacent catchments influence the dry deposition input change, and the long-term streamwater chemistry change in Japanese cedar regrowth forest.
1. Introduction The chemistry of the stream water flowing out of forests has a strong effect on downstream ecosystems and can also impact human life. The major factors controlling streamwater chemistry are geological weathering, atmospheric deposition, biological processes, and hydrological processes (Feller, 2005). Streamwater chemistry can change due to forest disturbances, such as forest harvesting (Likens et al., 1970; Neal et al., 1998; Swank et al., 2001; Feller, 2005) and defoliation (Swank et al., 1981; Webb et al., 1995; Eshleman et al., 1998; Ohte et al., 2003; Imamura et al., 2017). These forest disturbances have affected forest ecosystems and resulted in phenomena including increased weathering rates (Baily et al., 2003), decreases in atmospheric deposition (Reynolds et al., 1995; Oda et al., 2009), decreases in uptake nutrients by trees (Vitousek et al., 1979), and enhancement of microbial activities (Harvey et al., 1980; Byrd et al., 2000). The changes to forest ecosystems are long term, acting on timescales of several years to decades. Studies have provided examples in which streamwater chemistry recovered due to the restoration of forest vegetation (Neal et al., 1998; Martin et al., 2000; Swank et al., 2001). However, conditions have continued to deteriorate (Tokuchi et al.,
⁎
2013; Webster et al., 2016) in other cases, indicating that behavior differs among locations. Information on which to base long-term predictions of streamwater chemistry following forest disturbances, such as response and recovery times, is insufficient at present (Oda et al., 2018). Previous investigations of the fluctuations in streamwater chemistry following forest disturbances have generally focused on changes in the soil ecosystem, such as microbial activity and nutrient uptake by plants (Binkley and Brown, 1993; Martin et al., 2000; Burns and Murdoch, 2005). In addition to the internal chemical circulation processes in forest ecosystems, the fluctuation in atmospheric deposition is an important factor that determines streamwater chemistry. Changes in atmospheric deposition due to canopy regrowth can have important effects on forest nutrient cycling dynamics, as the canopy captures a large amount of dry fallout and leaches numerous chemicals (Reynolds et al., 1995; Feller, 2005; Martin et al., 2000; Oda et al., 2009). The amount of atmospheric deposition occurring in forests is known to vary and to depend on the state of the forest, for example its age, canopy structure, and tree height, in addition to the concentrations of substances in the atmosphere (Marques and Ranger, 1997; Malek and Astel, 2008; De Schrijver et al., 2008).
Corresponding author. E-mail address: [email protected] (T. Oda).
https://doi.org/10.1016/j.foreco.2019.05.058 Received 25 March 2019; Received in revised form 22 May 2019; Accepted 23 May 2019 Available online 12 June 2019 0378-1127/ © 2019 Elsevier B.V. All rights reserved.
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(Fig. 1). A mature mixed plantation of Cryptomeria japonica (Japanese cedar) and Chamaecyparis obtusa (Hinoki cypress) was planted from 1928 to 1931 over both catchments and remained until March 1999. In April 1999, the trees were clear cut from Catchment B; in April 2000, seedlings of the same species were planted. The planted stand density was approximately 3000 stems ha−1. Inferior trees were cleared and removed, and the remaining trees were pruned in the regrowth forest in March 2013, where ≤5% of the trees were harvested. In February 2014, due to heavy snow, the Japanese cedar trees in the replanted forest were damaged, and about 13% fell and left on the ground. In 2015, the stand densities in the study plots at Catchments A and B were 792 and 2550 stems ha−1, respectively (Table 1). Catchment B is defined as a regrowth forest and Catchment A as a mature forest. Japanese cedar and Hinoki cypress coexist in the catchments; their total basal areas in the survey plots were 19.7 and 6.7 m2 ha−1 in mature forest, and 4.5 and 0.17 m2 ha−1 in regrowth forest, respectively. We consider these Japanese cedars to be representative of the catchments. Four plots were set up in the catchments, designated A1, A2, B1, and B2 (Fig. 1). All trees in B1 and B2 and 80% of the trees in A1 and A2 were Japanese cedar. The canopy cover ratio and leaf area index (LAI) are mainly used as indicators of canopy alteration. The LAI and canopy cover ratio were calculated from hemispherical photographs taken using a fisheye lens in the Octobers of 2013 and 2015 (Table 1). Tree height, diameter at breast height, and stand density were measured in 2006, 2012, 2013, 2014, and 2015; the results are shown in Table 1. Trees grew gradually from 1999 to 2012 in the regrowth forest, and the canopy became fully closed in 2012 (Fig. 2).
The influence of depositional changes on streamwater chemistry has been examined in previous research and documented long-term fluctuations in solute concentrations (particularly those of NO3−, SO42−, and dissolved organic carbon) of streamwater due to the influence of acidic deposition (Aber et al., 1989; Martin et al., 2000; Lovett and Goodale, 2011). However, changes in chemical inputs during forest succession and their effects on streamwater chemistry have not been investigated sufficiently. Forest growth takes place over decades, during which changes in tree growth, canopy closure, and internal circulation occur. Precise evaluation of the effects of forest regrowth on changes in deposition in forests, such as dry deposition (DD) and canopy leaching (CL), is necessary for the forecasting of nutrient cycles and post-disturbance recovery of streamwater chemistry. In previous studies, the continuous measurement of deposition from the early growth stage after forest cutting has been limited, although some researchers have compared deposition among forest ages (Marques and Ranger, 1997; Malek and Astel, 2008). In addition, few studies have simultaneously observed the changes in atmospheric deposition along with forest regrowth and streamwater chemistry. This study evaluated the effects of canopy alteration-induced atmospheric deposition changes on stream chemistry in a regrowth forest. This study was conducted in a pair of small headwater catchments covered by same soil type and with the same bulk precipitation deposition in the Fukuroyamasawa experimental watershed at the Tokyo University forest in Japan. We evaluated changes in atmospheric deposition, including bulk precipitation, DD, and CL, using a canopy budget model (Draaijers and Erisman, 1995) with canopy alteration in 15 years after replanting, and examined the effects of changes in atmospheric deposition on the long-term changes in streamwater chemistry using a paired catchment approach.
2.2. Measurement 2. Methods 2.2.1. Precipitation, throughfall, and stemflow The precipitation volume was measured at a meteorological station located 200 m from the Fukuroyamasawa experimental watershed using a 0.5-mm tipping-bucket rain gauge (No.34-T, Ohta-Keiki, Tokyo, Japan) and a bulk sampler, which consisted of a 10-L plastic bottle collector with a 21-cm-diameter funnel, from April 2014 to March 2016. Bulk precipitation (BP) samples for chemical analysis were collected in 100-mL polyethylene bottles using a 10-L plastic bottle collector weekly to monthly. Throughfall (TF) volumes in the regrowth and mature forests were measured using 21 and 15 samplers, respectively, which were of the same design as the bulk sampler described above and were installed randomly in the B1, B2, A1, and A2 plots (Fig. 1) from April 2014 to March 2016 at weekly to monthly intervals. TF samples for chemical
2.1. Site description This study was conducted in a pair of small headwater catchments (Fukuroyamasawa Experimental Watershed, Catchment A, 0.8 ha; Catchment B, 1.1 ha) at the Tokyo University forest in Chiba, Chiba Prefecture, Japan (35°12′N, 140°06′E; Fig. 1). Both catchments are underlain by tertiary sedimentary rock. The soil type is common to both catchments and is classified as Cambisol. The altitude ranges from 126 to 230 m above sea level. The annual mean temperature was 14 °C (1994–2014), and the annual mean precipitation was 2,320 mm (1994–2014). Precipitation was higher during the summer season, and snow was rare. The study site is located < 10 km from the ocean, and the major source of pollution was Tokyo, located 70 km from the site
Fig. 1. Location (a) and topography (b) of the Fukuroyamasawa experimental watershed. The dashed line denotes the border between catchments A (mature) and B (regrowth). Squares at A1, A2, B1, and B2 are plots for the measurement of tree height, diameter at breast height, and atmospheric deposition. Black dots (●) show the location of throughfall collectors. 86
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Table 1 Stand age, tree height, mean diameter at breast height (DBH), leaf area index (LAI), canopy cover ratio, and stand density in catchments A and B. Age
Height (m)
DBH (cm)
LAI
Canopy cover (%)
Density (stem/ha)
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Catchment A (Mature) 2013 84 2015 86
25.0 –
5.9 –
36.0 –
12.8 –
2.7 2.0
0.2 0.6
92.0 84.0
1.5 7.0
792 792
Catchment B (Regrowth) 2006 6 2012 12 2013 13 2014 14 2015 15
6.1 9.8 10.1 10.9 11.0
2.2 3.4 3.3 3.9 3.8
7.3 9.3 12.1 12.6 13.0
3.4 5.5 4.4 5.0 5.0
– 3.0 3.2 – 2.5
– 0.8 0.6 – 0.3
– 91.5 93.9 – 89.5
– 4.0 2.8 – 2.9
3000 3000 – – 2550
the 21 and 15 TF samplers, respectively. In this study, the mean SF volume in the regrowth and mature forest from the six and four sampled stems were assumed to be representative of the SF volume in each catchment. The catchment-scale SF volume was estimated by multiplying the mean SF volume by the stand density and converting to millimeters.
analysis were collected in 30-mL polyethylene bottles from the same TF sampler after measurement of the TF volume, by measuring weight using a hand scale. Stemflow (SF) volumes in the regrowth (six stems) and mature forests (four stems) were measured using 70-L plastic tanks and 0.5-mm tipping-bucket rain gauges connected to wrapping hoses placed around the stems of Japanese cedar trees at a height of 1.3 m (Oda et al., 2011). SF samples were collected in 100-mL polyethylene bottles after being weighed with a hand scale from four stems in the regrowth forest and three stems in the mature forest at weekly to monthly intervals from April 2014 to March 2016.
2.3.2. Chemical analysis The pH values of BP, TF, SF, and stream water samples were measured after field sampling using a pH meter (D-54, Horiba, Kyoto, Japan). Water samples were filtered using 0.2-μm membrane filters, and the concentrations of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ were determined using ion chromatography (LC-10A, Shimadzu, Kyoto, Japan; DX-500, Thermo Fisher Scientific, Waltham, MA, USA).
2.2.2. Stream runoff Stream runoff was measured continuously from January 2012 to March 2016 at 10-min intervals using 90° V-notch weirs, the locations of which are labeled in Fig. 1. In 2015, weir A was sometimes buried under sediment, resulting in missing data for stream runoff in March and September in Catchment A. Stream water was sampled manually at weekly to monthly intervals at weirs of Catchments A and B from April 2014 to March 2016. For precise calculation of chemical outputs, highfrequency sampling during storm events is required (Oda et al., 2011). In this study, stream water samples during storm events (19–21 June 2012: total rainfall, 90 mm; 5–6 October 2014: 168 mm) were collected at 1–2-hour intervals using an automatic sampler (Model 900, American Sigma, New York, USA).
2.3.3. Flux calculation The BP chemical flux was calculated as the load during each observation period by multiplying the concentrations by the precipitation volume. TF and SF fluxes for each observation period were calculated by multiplying the volume-weighted mean concentrations with the mean TF and SF volumes. In addition, the spatial variation was evaluated by calculating the flux for each sampler for each period. The annual BP was calculated as the sum of the BP flux value of each period. The total annual deposition through the canopy (TD) in the regrowth and mature forests was determined as the sum of TF and SF fluxes. The difference of TD between the regrowth forest and mature forest were analyzed statistically considering the spatial variation. The annual BP, TF, and SF were calculated for the period April 2014 to March 2016. Normally, the water year was defined as January 1 to December 31, but for 2014 and 2015, annual BP, TF, and SF were calculated from April
2.3. Analysis 2.3.1. Throughfall and stemflow rates The TF volume during each observation period in the regrowth and mature forests was calculated as the mean TF volume measured using
1999
2005
2012
Fig. 2. Photographs of catchment B (regrowth forest) in 1999, 2005, and 2012. 87
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independent of canopy exchange. We determined the DDf as:
2014 to February 2015 and from April 2015 to March 2016, during the periods when the stream runoff, TF, and SF were measured simultaneously. Annual streamwater chemistry output loads (LSW) were calculated by integrating the hourly fluxes of dissolved ions. A regression method was used to estimate the hourly concentration because discharge was measured more frequently (Oda et al., 2011). These equations are expressed as follows:
C(t) = a log Q(t) + b
L SW =
∑ C(t)Q(t)
+
The CL of K , Mg
, and Ca
2+
was calculated by: (6)
Total CUs of H+ and NH4+ were assumed to equal the total CL of base cations (BC = K+ + Mg2+ + Ca2+) minus weak acid release (CLwa) (Schaefer et al., 1992):
(1)
CUNH4 + H = CLBC − CL wa ,
(7)
where CLwa was computed according to:
(2)
(8)
CL wa = TFwa + SFwa − BPwa +
NH4+ NH4+
were subsequently calculated based on The CUs of H and the total CU of H+ and and the assumption that H+ has an exchange efficiency six times greater than that of NH4+ (De Schrijver et al., 2004):
CUNH4 = CUNH4 + H × {(BP + TF + SF) NH4 /[(BP + TF + SF) NH4 + 6 × (BP + TF + SF)H]}
(9) NO3−
In this study, we assumed that the CU of was negligible because these values are typically lower than those for NH4+ (Stachurski and Zimka, 2002).
2.3.4. Analysis of TD and LSW changes in the regrowth forest To analyze the long-term changes in the TD and LSW in the regrowth forest following tree cutting, we obtained TD and LSW data for 1998, 2000, 2002, and 2006 in the same catchment in Oda et al. (2011) and added them to the observed data from 2012 and 2014–2015. Timeseries changes were assessed using the paired catchment approach. The long-term fluctuations in the regrowth-to-mature forest ratios of TD and LSW were examined, assuming that the ratio before cutting was unity. To evaluate the effect of TD changes on the LSW after forest regrowth, we also assessed the chemical budget. The chemical budget in the catchment is expressed as follows:
3. Results 3.1. TD and LSW in regrowth and mature forests The TF, SF, and LSW in 2014 (April 2014 to February 2015) and 2015 (April 2015 to March 2016) in the regrowth and mature forests are shown in Fig. 3. For all observed ions, TF accounted for the majority (≥90%) of TD, whereas SF was ≤10% of TD. The TD input values for Cl−, NO3−, SO42−, Na+, and Mg2+ were significantly lower in the regrowth forest than in the mature forest during 2014 and 2015 (t-test; all p < 0.05). In comparison, the TD values of NH4+, K+, and Ca2+ exhibited no significant difference between the regrowth and mature forests (both p > 0.05). During 2014, the LSW values for Cl−, SO42−, Na+, and K+ in the regrowth forest were lower than those in the mature forest, and the LSW values in the regrowth forest were higher for NO3−, Mg2+, and Ca2+ (Fig. 3). The NH4+ concentrations in the mature and regrowth forest were close to zero throughout the observation period.
(3)
where CEX is the chemical exchange rate in the catchment, and LD is the loss of groundwater to deep percolation. In this study, the deep percolation rate (D) was estimated at 500 mm yr−1 using the chloride mass balance method (Oda et al., 2008). The LD was calculated by multiplying D by the mean concentration observed during manual sampling. The output to input [(LSW + LD)/TD] ratios in the mature and regrowth forest were calculated for 2002–2014, excluding the period of tree cutting. When this ratio is near unity, input and output are balanced; when the value is > 1, other sources in the catchment are critical to the chemical balance.
3.2. Changes in TD and LSW in the regrowth forest The TD and LSW values during the growth process from pre-cutting to 15 years of regrowth are shown in Tables 2 and 3. The changes in the ratios of TD in the regrowth forest to that in the mature forest are shown in Fig. 4. After tree cutting in 1999 and planting in 2000, the TD for the regrowth forest clearly declined to 20–70% of the mature forest value, with the exception of NH4+. For Cl−, NO3−, SO42−, Na+, and Mg2+, the lower TD for the regrowth forest continued for 15 years. For K+ and Ca2+, the TD values clearly increased in the regrowth forest from 2006 to 2015, and were greater than those in the mature forest in 2015. Fig. 4 also shows the changes in the ratios of annual runoff and LSW in the regrowth forest to those in the mature forest. The ratios of Lsw increased for all ions just after clear-cutting. In 2000, the average ratio increase was 131% ( ± 9%), excluding NO3− and K+, which is in agreement with the increased rate of runoff (130%); greater increases of 1000% and 190%, respectively, were observed for NO3− and K+. The LSW values for Cl−, Na+, and K+ in the regrowth forest decreased to below the mature forest values, with regrowth-to-mature forest ratios of 77%, 90%, and 76%, respectively, in 2014 (Fig. 4). The LSW of Cl− was
2.3.5. Chemical budgets through the canopy To estimate the contributions of the DD and canopy exchange (CE) to the TD in the regrowth and mature forest catchments, we calculated annual DD and canopy exchange (CE) using the canopy budget model. CE refers to CL and canopy uptake (CU). The leaching of Na+, Cl−, and SO42− from leaves and branches is minor, and interaction with the canopy is negligible (Parker, 1983; Matzner et al., 2004). In this study, the TF + SF of Na+, Cl−, and SO42− were assumed to be due to BP + DD. The DD of K+, Mg2+, and Ca2+ occurred at the same rate as the deposition of particles containing a tracer ion (Draaijers et al., 1997). DD values for K+, Mg2+, and Ca2+ were calculated using the following equation:
DD = DDf × BP,
2+
CL = TF + SF − BP − DD
where C(t) is the solute concentration at time t, Q(t) is the runoff rate at time t (mm h−1), a and b are empirical parameters, and LSW is the load of solutes (kg ha−1). The calculation of LSW requires frequent observations, and the data were limited. In this study, we evaluated LSW using data from 2012 and 2014–2015, when frequent observations were made in both catchments. We used the C–Q relations of the 2012 and 2014–2015 periods in both catchments, which were derived from stream water concentrations and runoff rates during the sampling periods. LSW values in 2012, 2014, and 2015 were calculated for January to December 2012, April 2014 to February 2015, and April 2015 to March 2016, respectively.
TD + CEX = L SW + LD,
(5)
DDf = (TFNa + SFNa − BPNa)/BPNa
(4)
where DDf is the dry deposition factor. The majority of previous studies used Na+ as a tracer ion for calculation of the DD of base cations (Staelens et al., 2008). In these models, Na+ was used as the tracer ion because it is assumed to 88
89
17 12 10 21 21 20 9 4 5 8 8 10 13 4 4 17 25 33 15 10 8 5 3 2 40 22 31 38 44 40
b
a
Actual observation period was from April 2014 to February 2015. Actual observation period was from April 2015 to March 2016.
67 36 40 43 40 37 56 17 18 23 22 12 B (Regrowth) 1929 2151 2363 2088 1712 2286 Catchment 1998 2000 2002 2006 2014a 2015b
152 39 57 66 90 77
Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) This study This study 17 22 28 28 21 19 9 8 15 11 12 13 13 20 29 26 29 28 15 6 3 7 3 3 40 33 73 58 66 56 67 52 81 67 48 45
Ca2+ (kg ha−1) Mg2+ (kg ha−1) K+ (kg ha−1) NH4+ (kg ha−1) Na+ (kg ha−1) SO42− (kg ha−1) NO3− (kg ha−1)
56 41 56 46 30 32 152 70 141 110 148 112 A (Mature) 1929 1785 1961 1733 1477 1927
The DD values for all ions in the regrowth forest were lower than those in the mature forest, on separating the TD into the BP, DD, and CL in 2014 and 2015 (Fig. 5). In particular, the DD rates for Cl−, SO42−, and Na+ in the regrowth forest were at 22–51%, 51–54%, and 16–21%,
Catchment 1998 2000 2002 2006 2014a 2015b
3.3. Chemical budgets through the canopy in regrowth and mature forests
Cl− (kg ha−1)
significantly lower in the regrowth forest than in the mature forest after cutting (t-test; p = 0.02), whereas the changes in the LSW of SO42−, Na+, and K+ were not significant (t-test; p > 0.05). However, the declining trend of regrowth-to-mature forest ratios of the LSW values for Na+ and K+ since 2000 was obvious (linear regression analysis; p < 0.05). In comparison, the LSW values for Mg2+, and Ca2+ remained greater in the regrowth forest than in the mature forest in 2014. The LSW of NO3− increased immediately after cutting, and then fell to values of those in the mature forest within 6–12 years, nearly returned to their pre-cutting levels, and then increased again in the 14th year. The mean ratio [(LSW + LD)/TD] for Cl− in the regrowth forest was 1.0 ( ± 0.3), and that in the mature forest was 0.9 ( ± 0.07). This result shows that the atmospheric deposition of Cl− was a primary source of chemical output in both catchments. This result is consistent with studies that reported that Cl− is not reactive under typical catchment conditions and the source of streamwater output is atmospheric deposition (Peters and Ratcliffe, 1998). The mean ratios for Na+ and SO42− ranged from 1.4 to 2.2 in the regrowth and mature forests, which indicates that the TD input contributed approximately half of their chemical output. Mg2+ and Ca2+ exhibited (LSW + LD)/TD ratios of 2.6–7.9, which indicates that the contribution of TD was < 1/3 of their chemical output. The ratios for NO3− and K+ were 0.5 and 0.7, respectively, in mature forest, showing that chemical uptake was critical in the forest ecosystems.
Throughfall + Stemflow (mm)
Table 2 Total annual volumes of throughfall and stemflow rates and total deposition of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ in regrowth and mature forests from 1998 to 2015. The data for 1998–2006 were taken from Oda et al. (2011).
Fig. 3. Annual deposition of throughfall (TF), stemflow (SF), and stream water chemical load (LSW) of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ in the regrowth forest (RF) and mature forest (MF) from April 2014 to February 2015 (2014) and from April 2015 to March 2016 (2015). LSW in MF in 2015 are missing. The error bars represent the standard error.
Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) This study This study
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Table 3 Annual runoff and stream water chemical outputs of Cl−, NO3−, SO42−, Na+, K+, Mg2+, and Ca2+ in regrowth and mature forests from 1998 to 2015. The data for 1998–2006 were taken from Oda et al. (2011). Cl− (kg ha−1)
NO3− (kg ha−1)
SO42− (kg ha−1)
Na+ (kg ha−1)
K+ (kg ha−1)
Mg2+ (kg ha−1)
Ca2+ (kg ha−1)
Catchment A (Mature) 1998 910 2000 768 2002 895 2006 738 2012 985 2014a 655 – 2015b
79 65 76 57 96 66 –
18 28 14 19 8 10 –
73 58 69 53 63 39 –
62 51 60 48 65 43 –
8 7 8 9 9 13 –
22 18 21 17 19 13 –
82 66 78 65 69 45 –
Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) This study This study This study
Catchment B (Regrowth) 1998 867 2000 996 2002 1147 2006 915 2012 1193 2014a 786 2015b 1201
60 64 50 33 55 41 63
7 108 49 22 7 30 47
55 59 67 44 49 33 51
64 63 63 51 55 40 60
7 10 9 9 8 7 10
21 24 25 20 16 14 21
82 88 85 81 77 51 77
Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) Oda et al. (2011) This study This study This study
Runoff (mm)
a b
Actual observation period was from April 2014 to February 2015. Actual observation period was from April 2015 to March 2016.
Fig. 4. Changes in the regrowth-to-mature forest (RF/MF) ratios of total deposition (TD) and stream water chemical load (LSW) for Cl−, NO3−, SO42−, Na+, K+, Mg2+, and Ca2+ from 1998 to 2015. The dashed lines show the RF/ MF ratios of annual runoff.
Fig. 5. Forest canopy chemical budget in terms of bulk precipitation (BP), dry deposition (DD), and canopy leaching (CL) of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ in regrowth forest (RF) and mature forest (MF) from April 2014 to February 2015 (2014) and from April 2015 to March 2016 (2015).
respectively, of the mature forest values. The ratios of CL for K+ and Ca2+ in the regrowth forest were 91% and 140%, and 115% and 123%, of the mature forest values in 2014 and 2015, respectively (Fig. 5). The contribution of CL to the TD of K+, Mg2+, and Ca2+ was large (≥34%). In particular, the CL of K+ in the regrowth forest accounted for 22 and 27 kg ha−1yr−1 in 2014 and 2015, respectively, which accounts for 89% and 81% of the TDs. For K+, Mg2+, and Ca2+, the DD component was relatively small in the regrowth forest, whereas the CL component was larger, such that the TD equaled or exceeded that in the mature forest The TDs in regrowth and mature forests in 1998, 2002, 2006, 2014, and 2015 were separated into BP, DD, and CL using a canopy budget model (Table 4). The long-term changes in the DD in the regrowth
showed that DD values in the regrowth forest decreased for all ions after cutting and then approached those in the mature forest gradually over 15 years, but remained less than 60% of those of mature forest in 2015 (Fig. 6). In contrast, the CLs of K+, Mg2+, and Ca2+ in the regrowth forest decreased immediately after cutting, and then increased to similar or higher values of 91–140%, 63–80%, and 115–123% those in mature forest in 2014 and 2015, respectively.
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Table 4 Total deposition (TD), bulk precipitation (BP), dry deposition (DD), and canopy leaching (CL) of Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+ in regrowth and mature forests from 1998 to 2015. (kg ha−1) Catchment A (Mature)
Catchment B (Regrowth)
1998
2002
2006
2014a
2015b
1998
2006
2014a
2015b
Cl−
TD BP DD TD
152 77 74 56
141 57 84 56
110 62 48 46
148 74 74 30
112 41 71 32
152 77 74 56
66 62 4 23
90 74 16 22
77 41 35 12
NO3−
BP DD TD
3 53 67
18 38 81
18 28 67
30 0.3 48
22 10 45
3 53 67
18 4 43
30 −7 40
22 −10 37
SO42−
BP DD TD
33 34 40
40 41 73
37 30 58
31 18 66
27 18 56
33 34 40
37 8 38
31 9 44
27 10 40
Na+
BP DD TD
17 23 15
31 42 3
36 22 7
39 27 3
36 20 3
17 23 15
36 2 5
39 4 3
36 4 2
NH4+
BP DD CE TD
4 11
8 12
3 9
3 3
29
26
8 5 −10 28
4 11
13
3 3 −3 29
13
17
3 1 −1 25
8 −1 −4 33
K+
BP DD CL TD
2 2 10 9
4 5 21 15
7 4 15 11
2 2 24 12
5 3 20 13
2 2 10 9
7 0.4 10 8
2 0.3 22 8
5 1 27 10
Mg2+
BP DD CL TD
1 1 6 17
5 7 3 28
7 4 −1 28
5 3 4 21
4 2 6 19
1 1 6 17
7 0.4 0.4 21
5 1 3 21
4 0.5 5 20
Ca2+
BP DD CL
1 1 14
10 13 6
16 9 3
4 2 15
4 2 13
1 1 14
16 1 4
4 0.4 17
4 0.5 15
a b
Actual observation period was from April 2014 to February 2015. Actual observation period was from April 2015 to March 2016.
4. Discussion 4.1. Changes in atmospheric deposition with canopy regrowth In the regrowth forest, the TD values for all ions declined rapidly after clear-cutting, and the TD rates of Cl−, SO42−, NO3−, Na+, and Mg2+ remained lower than those in the mature forest over 15 years. This pattern is due to the smaller DD rates for these ions, consistent with previous findings for young regrowth forests. Potter et al. (1991) investigated DD transfer in a regenerated forest and showed that DD rates were around 2–5 times lower than those in a mature forest. There have been reports that the DD input is determined by the canopy height, canopy closure, and LAI (Lovett and Reiners, 1986; Erisman and Draaijers, 2003). In the present study, despite the higher LAI and canopy cover of the regrowth forest than of mature forest in 2015 (Table 1), the DD inputs were smaller than those in the mature forest. This result suggests that the changes in the DD input in the regrowth forest are related not only to canopy alterations, such as LAI and canopy cover changes, but also to lower tree height. This result is consistent with the results for other forests in Japan, which showed higher DD inputs in taller trees in broadleaf and coniferous forests (Imamura et al., 2012, 2018). Dry particles may have passed over the regrowth forest canopy and then been scavenged by the taller canopy of the surrounding mature forest. In general, wind speed is greater at higher altitudes, where a tall canopy would be able to capture more DD from such winds (Hofhansl et al., 2011). Gielis et al. (2009) also showed that DD velocities were lower for a regrowth plot than for surrounding taller trees. Wuyts et al. (2009) described an edge effect, in which TF deposition rates were smaller outside the steep forest edge where
Fig. 6. Changes in the regrowth-to-mature forest (RF/MF) ratios of dry deposition (DD) and canopy leaching (CL) for Cl−, NO3−, SO42−, Na+, K+, Mg2+, and Ca2+ from 1998 to 2015.
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with the previously reported response of NO3− after snow damage in Hubbard Brook Forest (Green et al., 2013). The LSW of NO3− and K+ are thought to be more strongly influenced by biological processes in the soil than by changes in atmospheric deposition, similar to studies that reported that the concentrations of NO3− and K+ vary depending on biological factors, such as tree uptake and microbial activity (Vitousek et al., 1979, Bormann and Likens, 1994; Likens et al., 1996). For the factors that influence long-term changes in streamwater chemistry, a time delay occurs due to water storage in the catchment. Gradual long-term fluctuations, such as those observed for Cl−, indicate the timescale of replacement in the catchment (Oda et al., 2009). Decreased DD occurs at the same time as canopy removal, but the replacement of stored water in the catchment basin takes time, such that the response of the LSW is delayed (Fig. 4). This process can also be applied to recovery, and even when DD recovers with tree growth, a time lag is expected and thus the response of LSW will be more gradual.
vegetation in front of the forest edge was cut or was lacking. The difference in tree height between regrowth and mature forests resulted in a forest edge, leading to lower DD in the regrowth forest. Moreover, the forest edge effect was more significant in coniferous forest than in deciduous forest (Wuyts et al., 2008). At this study site, the area covered by coniferous forest or clear-cut area was less than 1 ha, so the influence of the forest edge effect could be larger. The study result suggests that the recovery of chemical input may be delayed behind that of the canopy in small cutting areas under the influence of the surrounding tree height. The DD values for NO3− and NH4+ became negative (Table 4), likely due to nitrogen uptake into the canopy. Some studies have shown that nitrogen CU is an active process (Lovett et al., 1996). Coniferous trees have larger canopy storage capacities and longer water residence times in the canopy than broadleaf trees. Therefore, the nitrogen uptake might be greater in coniferous forests. TD rates for K+, Mg2+, and Ca2+ in the regrowth forest in the present study increased after 6 years and the TD rates of K+ and Ca2+ were similar to those in the mature forest when the trees of the regrowth forest were 14–15 years old. For these ions, the CL rates in the regrowth forest were larger than those in the mature forest in 2015. The results of the present study indicate that changes in CL in regrowth forest are correlated with canopy alteration. In general, K+, Mg2+, and Ca2+ in TF are thought to originate from CL (De Schrijver et al., 2007), and some studies have shown that CL is greater in young forests than in mature forests (Lovett and Lindberg, 1993; Malek and Astel, 2008). The results of the present study are in reasonable agreement with these previous findings.
5. Conclusion In this study, we examined the changes in atmospheric deposition separated into components of DD and CL that occurred along with forest canopy regrowth in Japanese cedar plantation forests and the effects of the deposition changes on stream chemistry 14–15 years after replanting. The TD values for Cl−, NO3−, SO42−, Na+, and Mg2+ were lower than in the mature forest due to the lower DD values although the LAI increased, whereas the CL of K+ and Ca2+ increased with the LAI in the regrowth forest. The canopy alteration effect contributed greatly to the CL changes, but the DD changes lagged behind the canopy regrowth due to the edge effect of the surrounding catchment in the regrowth forest. The results also revealed that the lower DD in the regrowth forest significantly affected long-term changes in the streamwater chemistry of Cl− and Na+ in the regrowth process. For other ions, no clear response to streamwater chemistry was found in relation to atmospheric deposition changes. In this study, although there was no direct relationship between canopy alteration and streamwater chemistry, changes in DD are significant in regrowth forest and persistent, and would affect the chemical cycle in the forest ecosystem. The results of this study suggested that not only canopy alteration but also edge effects of surrounding catchments influence long-term changes in the DD input and the streamwater chemistry in a small Japanese cedar regrowth forest.
4.2. Effects of atmospheric deposition changes on streamwater chemistry The LSW values fluctuated with forest regrowth in comparison with the mature forest. The decline in the LSW for Cl− and Na+ and the increase in the LSW for NO3− after cutting were obvious in this study (Fig. 4). Responses of these anions following forest cutting have been observed in previous studies (Reynolds et al., 1995; Martin et al., 2000; Neal et al., 2004). In addition, the streamwater chemistry recovered to its pre-cutting conditions in the early regrowth forest in as little as 4–5 years (Martin et al. 2000). In this study, the LSW for NO3− tended to approach the pre-cutting level in 6–12 years, whereas the LSW values for Cl− and Na+ did not tend to approach the pre-cutting level within 15 years (Fig. 4). The results of the chemical budget investigations indicate that the TD input reduction during the regrowth period caused by a decrease in DD was the main factor that determined the lower long-term LSW values for Cl− and Na+. However, there was no clear change in streamwater chemistry in the regrowth processes with increases in the LAI and the canopy cover ratio (Fig. 4, Table 1). This is thought to be due to the delayed recovery of DD compared with the recovery of LAI, as noted above, due to the edge effect of surrounding taller trees, especially in small regeneration areas. For SO42−, Mg2+, and Ca2+, the TD input fluctuated due to the decrease in DD and increased CL after cutting, but no significant changes in the LSW were found, indicating the presence of other sources, such as chemical weathering, in this catchment. This result indicated that the fluctuation in DD and CL with canopy alteration did not contribute clearly to the streamwater chemistry of these ions. However, the lower DD in the regrowth forest would affect the chemical circulation in the forest ecosystems. The increase in SO42− leaching due to air pollution and the subsequent recovery processes have been problematic (Driscoll et al., 1998). This study suggested that consideration of the TD changes with the changing canopy structure is necessary to evaluate the precise chemical balance in the forest ecosystems in regrowth forest. In addition, the LSW values of NO3− and K+ after forest cutting behaved differently than did those of other ions. After cutting in 1999, rapid fluctuations occurred, and after snow damage during 2013 and 2014, NO3− leaching increased again despite the absence of changes in the runoff rate and atmospheric deposition. Such fluctuations are consistent
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