Introduction
Agriculture's expansion is taking place in some of the most rugged mountains
in the world, including the Hindu Kush Himalaya (Brown and Shrestha, 2000;
Tulachan, 2001), in India, China (Johda et al., 1992) and the Andes (Sarmiento
and Frolich, 2002). It is well established that watershed nutrient cycling
is tightly linked to land use and that conversion of natural forests to
agricultural lands causes nutrient enrichment, especially of N and P, in
streamwater (Omernik, 1976; Johnes, 1996; Tilman et al., 2001; Murty et al.,
2002; Allan, 2004; Uriarte et al., 2011; Evans et al., 2014). The impacts
are likely exacerbated by steep slopes and high precipitation as residence
time is reduced and leaching potential increased under such conditions
(Brouwer and Powell, 1998; Tokuchi et al., 1999). Thus, mountain agriculture
in the tropics and subtropics characterized with high precipitation is
likely to have a substantial negative impact on ecosystem function. Yet,
empirical studies in tropical or subtropical mountain watersheds are very limited.
In addition to nutrient output in streamwater, cultivation and fertilization
on agricultural lands could affect atmospheric deposition of nutrients
(i.e., nutrient input via wet and dry deposition). Fine particles suspended from
exposed lands and volatilized gases such as NH3 from manure are
scavenged by precipitation (van Breemen et al., 1982), which can then be
deposited back to the watersheds. However, in contrast to the large number
of reports on streamwater chemistry, few studies of watershed nutrient
cycling have examined the effects of land use on precipitation chemistry.
Proper landscape configuration could potentially mitigate the negative
effects of agriculture on watershed nutrient cycling. A study at the Hubbard
Brook Experimental Forest demonstrated that watershed-level responses were
most sensitive to areas of approximately 10–20 ha surrounding the
drainage area, where much of the variation in element fluxes occurred
(Johnson et al., 2000). Such understanding has led to the common practice of
establishing riparian buffer zones as a way to remove pollutants and prevent
nutrients from entering streamwater (reviewed by Muscutt et al., 1993).
Through proper landscape configuration, negative impacts of agriculture on
nutrient cycling in mountain watersheds may also be reduced without
sacrificing socioeconomic benefits of agriculture. However, what constitutes
a proper landscape configuration is likely to vary with climate and topography.
Here we examined the effects of mountain agriculture, mainly tea plantations,
on watershed nutrient cycling at the Feitsui Reservoir Watershed (FRW) in
subtropical Taiwan. We first compared streamwater chemistry across four
watersheds within the FRW, two with substantial agricultural land use and two
primarily covered with natural forests. To assess the effects of agriculture
on atmospheric deposition of nutrients and its role in watershed nutrient
retention, we focused on the pair of watersheds with the highest and lowest
tea plantation covers and compared their rainfall chemistry in relation to
streamwater chemistry. The FRW is characterized by high rainfall
(> 3000 mm; Taipei Feitsui Reservoir Administration), steep
slopes (on average 42 %), and heavy use of fertilizers in tea plantations
(425–2373 kg N ha-1 yr-1 and 99–551 kg P ha-1 yr-1;
Water Resources Agency, 2010; see Sect. 2 for details). Many
studies have demonstrated substantial nutrient efflux and sediment
production from surrounding tea plantations to the reservoir over the past
2 decades (Chang and Wen, 1997; Lu et al., 1999; Kuo and Lee, 2004; Li and
Yeh, 2004; Hsieh and Yang, 2006, 2007; Zehetner et al., 2008; Chiueh et al.,
2011; Wu and Kuo, 2012). Yet, to our knowledge none examined both the
effects of spatial configuration of agricultural lands on nutrient export and
the effects of agriculture on atmospheric deposition. The FRW is rare among
(sub)tropical mountain watersheds in that the effects of agriculture on its
streamwater quality have been intensively studied. With the addition of this
study, we believe that the FRW can serve as a classic case illustrating the
effects of agriculture on nutrient cycling in watersheds with rugged
topography and high precipitation, which can be very informative to other
less-studied (sub)tropical mountain watersheds.
We hypothesized that agriculture would increase nutrient output in
streamwater (H1) as well as atmospheric input of nutrients through
rainfall (H2). We also hypothesized that through the disruption of
natural vegetation, agriculture would increase nutrient leaching and
decrease the retention ratio of essential nutrient elements (H3). Our
specific predictions are that
watersheds with higher proportion of tea plantation cover have higher
concentrations and fluxes of fertilizer-associated ions in the streamwater
than forested watersheds (H1),
watersheds with higher proportion of tea plantation cover have higher
concentrations and fluxes of fertilizer-associated ions in the rainfall than
forested watersheds (H2),
watersheds with higher proportion of tea plantation cover have a lower
nitrogen retention ratio (in proportion to input) than forested watersheds (H3).
In addition, we explored (1) the role of landscape configuration in
mitigating agricultural effects by quantifying the dilution effects of a
forested watershed downstream from watersheds with substantial tea
plantation cover, and (2) the N and P dynamics associated with tea
plantations by quantifying the differences in their fluxes between a forested watershed
(background values) and a nearby watershed with substantial tea plantation cover.
Materials and methods
Study site
The FRW is located along the Peishi Creek of northern Taiwan, with a
drainage area of 303 km2. The elevation of the FRW ranges from 45 to
1127 m, with a mean slope of 42 % (Fig. 1). The underlying geology of the
FRW region is mainly argillite and slate with sandstone interbeds, and the
soils are mostly Entisols and Inceptisols with high silt contents (Zehetner
et al., 2008).
Location and land use distribution of the studied watersheds.
Annual precipitation is high and spatially varied, ranging from 3500 mm in
the southwest portion of the FRW to 5100 mm in the northwest during
2001–2010 (J. C. Huang, unpublished data). The vegetation is primarily
composed of secondary-growth, mixed broad-leaf forests dominated by Fagaceae
and Lauraceae (Chen, 1993). Approximately 16 % of the FRW is agricultural
land with tea plantations covering an area of 1200 ha, or 25 % of all
agricultural lands (Chang and Wen, 1997; Chou et al., 2007). In 1986 the FRW
was designated as a water resource protection area, followed by the
construction of the Feitsui Reservoir in 1987. Today, the reservoir provides
drinking water to the six million people in the Taipei metropolitan area. The forests
in the FRW have been protected (no cutting, thinning or converting to
agricultural use) since 1986. Therefore, current agricultural activities are
limited to private lands with a pre-existing agricultural use which still
has an impact at the study site.
Sampling regime
Four watersheds of the FRW (A1, A2, F1, F2; Fig. 1) with varying proportions
of tea plantation cover (22 % in A1, 17 % in A2, 2.9 % in F1, 0.4 %
in F2; Table 1) were included in this study. Other crops make up only a small proportions of the
watersheds (< 1 %), so they are not included in Table 1. Natural forests are the most dominant land
cover for all four watersheds (68 % in A1, 76 % in A2, 93 % in F1,
99 % in F2; Table 1), making tea plantation the primary contributor to the
differences in landscape across the four watersheds. Weekly samples of
streamwater were collected from all four watersheds. In addition, weekly
samples of rainwater were collected from the two watersheds with the lowest (F2)
and highest proportions of agricultural lands (A1). A1, A2, and F2 are
watersheds (< 3 km2) drained by first-order streams whereas F1
is a much larger watershed (86 km2) drained by a third order stream
that drains through A1 and A2 (Fig. 1). We collected weekly rainfall and
streamwater samples every Tuesday from September 2012 to August 2014.
Rainfall samples were collected using a 20 cm diameter polyethylene (PE)
bucket, from which a 600 mL subsample was taken and placed into a PE bottle
for transportation back to the laboratory. Streamwater samples were
collected by dipping a PE bucket into the stream and, similarly to rainfall
sampling, a 600 mL subsample was taken and placed into a PE bottle for
transportation back to the laboratory.
Water chemistry
All samples were transported back to the laboratory within 24 h.
Conductivity and pH of the water samples were measured on the same day of
collection. The samples were filtered through 0.45 µm filter paper.
Major cations (Na+, K+, Ca2+, Mg2+, NH4+) and
anions (Cl-, SO42-, NO3-) were analyzed by ion
chromatography on filtered samples using Dionex ICS 1000 and DX 120 (Thermo
Fisher Scientific Inc. Sunnyvale, CA, USA). PO43- was measured
using standard vitamin-C molybdenum-blue method with the detection limit of
0.01 µM (APHA, 2005). Prior to chemical analysis, samples were stored
at 4 ∘C without preservatives.
Basic information of the studied watersheds.
A1
A2
F1
F2
Area (km2)
2.92
1.36
86.04
0.67
Slope (%)
39.3
34.8
38.7
48.1
Land use (%)
Natural forest
68.0
75.5
93.5
99.2
Agriculture
22.1
17.1
2.87
0.38
Road
3.61
2.96
0.77
0.00
Building
1.54
1.31
0.35
0.00
Water body
0.69
0.19
1.12
0.00
Others
4.11
2.96
1.44
0.38
Data on rainfall and streamflow quantity of the watersheds were estimated
from the rain gauges and discharge gauges maintained by the Central Weather
Bureau and Water Resource Agency of Taiwan, respectively. The distance
between a watershed and its nearest rain gauges was 1.0–8.5 km, and that
between a watershed and its nearest discharge gauges was 3.0–5.0 km. The
weekly and monthly rainfall of a watershed was directly assigned to the
values registered at the nearest rain gauge (i.e., COA530 for A1 and COA540
for F2; Fig. 1, S1a). The weekly and monthly streamflow of a
watershed was estimated by the area ratio method in which the streamflow was
assigned to the values registered at the nearest discharge gauge
(i.e., 1140H099 for A1, A2, and F1, and 1140H097 for F2; Fig. S1b) and then
adjusted by the area ratio of the studied watershed relative to the
watershed where the discharge gauge was located. The validity of this method
has been confirmed for several watersheds in Taiwan (Huang et al., 2012; Lee et al., 2014).
Element fluxes
Weekly element fluxes through rainfall and streamflow of A1 and F2 were
derived by multiplying weekly concentrations by weekly rainfall/streamflow.
Monthly fluxes were accumulated from weekly fluxes, and when a weekly sample
spanned over 2 months, it was divided into the 2 months in proportion to
the rainfall/streamflow quantity.
In order to provide a more comprehensive understanding on how mountain
agriculture affects watershed nutrient cycling, we constructed and compared
N and P fluxes for watersheds with the highest (A1) and lowest (F2) tea
plantation cover. We made three assumptions in the calculation of watershed
nutrient fluxes. First, we assumed the input from dry deposition is 28 %
of that from precipitation for both watersheds. This value was based on a
study using the Na+ ratio method at the Fushan Experimental Forest (Lin et
al., 2000), a natural hardwood forest 17 km south of the FRW. Second, the
amount of fertilizer used is assumed to be close to 786 kg N ha-1 yr-1
and 171 kg P ha-1 yr-1, the values taken from a case
study in which the management practices (e.g., applications of fertilizers
and pesticides, time and yield of harvests) were carefully recorded by a
farmer in the same region as the current study (Tsai and Tsai, 2008).
Although only one farmer was involved in the case study, the values are
consistent with those reported by FAO (2002) and very close to the mean values
across 10 tea plantations in our study area (743 kg N ha-1 yr-1 ranging from
425 to 2373 kg N ha-1 yr-1, and 179 kg P ha-1 yr-1
ranging from 99 to 550 kg P ha-1 yr-1; Water Resources Agency,
2010). Adjusting for the proportion of agricultural lands (22.1,
0.38 %), the amounts of fertilizers used in A1 were estimated to be
173.7 kg N ha-1 yr-1 and 37.8 kg P ha-1 yr-1, and those in F2 to
be 3 kg N ha-1 yr-1 and 0.6 kg P ha-1 yr-1. There was
very little change in biomass of tea plantation after 10 years because tea
plants are regularly trimmed, with the litter left in the field, to maintain
the same height optimal for harvest. Thus, our third assumption is that N
and P is lost due to the uptake by tea trees being equivalent to the N and P in the harvested
tea leaves. The amount of N removed through tea harvest (113 kg ha-1 yr-1)
was taken from the same case study and the amount of P removed
(7.35 kg ha-1 yr-1) was calculated using the median of P : N ratios
(0.065) reported for tea trees in Taiwan (Tsai and Tsai, 2008). After
adjusting for the proportion of tea plantation cover, A1 was estimated to
have 25.0 kg N ha-1 yr-1 and 1.6 kg P ha-1 yr-1
removed through harvest, and F2 to have 0.43 kg N ha-1 yr-1 and
0.03 kg P ha-1 yr-1 removed through harvest. Using the following
mass balance model, we constructed fluxes of N and P of the two watersheds:
Ratioret=1-OUTriv+OUTharvINdep+INfer+INfix.
Here, Ratioret indicates the ratio of input to the watershed that was
retained within the watershed. The OUTriv and OUTharv are the
riverine export and harvest, respectively. The INdep, INfer, and
INfix indicate the atmospheric deposition, fertilizer application, and
biological fixation. Note that the biologic fixation term was not used for P
calculation. Since the tea plantation does not use leguminous crop as
fertilizers and the biological fixation in tropical forest is known to be
less than 10 kg N ha-1 yr-1 (Sullivan et al., 2014), the INfix
is assumed to be between 0 and 10 kg N ha-1 yr-1. We did not
include the loss through denitrification and volatilization within tea field
in the calculation of N retention ratio because we did not have good
estimates. However, the effects of such uncertainties and omissions on
estimating N retention ratio were discussed. We did not calculate the
retention ratio for P because the majority of P in watersheds was in
particulate forms (Smith et al., 1991) that were not analyzed in our study.
Statistical analysis
We used the general linear model with repeated measurements to compare
monthly concentration and flux of ions in streamwater among the four
watersheds (F1, F2, A1, A2), followed by Fisher's least significant
difference (LSD) post hoc comparisons. NH4+ was excluded from
streamwater analysis due to its low concentration. We used a one-tail paired
t test to examine if monthly ion concentration (volume weighted from weekly
samples) and flux in rainfall were higher at the watershed with higher
agricultural land cover (A1) than the more pristine watershed (F2). All
statistical analysis was conducted using SPSS 22.0 (IBM Corporation, New York).
Results
Streamwater chemistry
The concentrations of all analyzed ions in streamwater differed
significantly among the four watersheds (Table 2). A1, the watershed with
the highest proportion covered by tea plantations, had significantly higher
concentrations of all ions except H+ than the other three watersheds
(Table 2, Fig. 2). In contrast, F2, the watershed with the lowest proportion
covered by tea plantations, had the lowest concentrations of H+,
Na+, K+, Cl-, and NO3-. Furthermore, it is worth
noting that F2, the watershed with the steepest slopes, had the second
highest concentrations of ions rich in soils and soil solution, including
Ca2+, Mg2+, and SO42- (Table 2, Fig. 2).
Similar to ion concentration, the fluxes of all ions differed significantly
among watersheds (Table 2). A1 had the largest fluxes of K+, Ca2+,
Mg2+, NO3-, and SO42- and F2 had the smallest fluxes
of H+, Na+, K+, Mg2+, Cl-, and NO3-
(Table 2). PO43- flux was significantly larger at A1 and A2, which
were not so different from each other, than F1 and F2, which were also not
so different from each other (Table 2). Although the fluxes of Na+ and
Cl- differed significantly among A1, A2, and F1, these differences were
considerably smaller than the differences between the three watersheds and F2 (Table 2).
Rainfall chemistry
Five of the 10 measured ions had significant (p < 0.05) or
marginally significant (p < 0.1) higher concentrations in A1 than in F2
(H+, Na+, Cl-, NO3-, p < 0.05;
NH4+, p = 0.067; Table 3, Fig. 3). Furthermore, 7 of the
10 measured ions had significant or marginally significant higher fluxes in A1
than in F2 (H+, Ca2+, Cl-, p < 0.05; Na+,
Mg2+, NH4+, NO3-, p < 0.1; Table 3).
N and P fluxes
Because the proportion of agricultural cover was very low at F2
(i.e., 0.38 %) and the resulting fertilizer input and harvest output were small
and already accounted for (Table 4), we treated F2 as a background and
attributed the differences between A1 and F2 to agricultural activities. We
estimated stream N and P outputs from the tea plantation at A1 to be
approximately 105.7 and 1.6 kg ha-1 yr-1,
respectively (Table 4). Scaling up from 22 % of tea plantation cover to
100 %, the stream N and P outputs from A1 could reach as high as 450 and
7.3 kg ha-1 yr-1, respectively.
From our mass balance construction of element fluxes, N input exceeded
output at both watersheds (Table 4, Fig. 4). At A1, 35 % of the N input
(69 kg ha-1 yr-1) to the watershed was retained (Table 4, Fig. 4).
At F2, 72 % of the N input (15 kg N ha-1 yr-1) was retained
(Table 4, Fig. 4). For P, the output through streamflow (2.6 kg ha-1 yr-1)
was smaller than the input through atmospheric deposition (3.6 kg ha-1 yr-1)
at F2. At A1, the output of P through streamflow and
harvest (5.8 kg ha-1 yr-1) was greater than the input through
atmospheric deposition (4.6 kg ha-1 yr-1), but when fertilization
was taken into account, the total output of PO43--P was trivial
relative to the total P input (42.4 kg ha-1 yr-1) (Table 4).
Discussion
Streamwater chemistry
The watershed with the highest proportion of tea plantation cover (A1) had
the highest concentrations and fluxes of most ions in streamwater,
suggesting the role of agriculture on increasing nutrient output.
Furthermore, the fact that the output of fertilizer-associated ions
(NO3- and K+) matched the proportion of tea plantation
cover across the four watersheds (i.e., the rank of the proportion of tea
plantation cover from high to low: A1, A2, F1, and F2; rank of ion concentration
and flux from high to low: A1, A2, F1, and F2) strongly supports the effects of
agriculture on streamwater chemistry (H1).
However, streamwater chemistry is affected by complex processes beyond a
single factor of land use. For example, P is also an important component of
fertilizers but, unlike NO3- and K+, the concentration of
PO43- at F2 was not significantly different from that at A1 and A2, and
all were significantly higher than F1. Erosion is known to enhance leaching
loss of PO43- (Gaynor and Findlay, 1995; Turtola and Jaakkola,
1995; Liu et al., 2006; Chang et al., 2008; Lee et al., 2013). The greater
erosion and leaching associated with the steeper slopes of F2 may have
matched the effect of fertilization and led F2 to have a PO43-
concentration as high as A1 and A2. To further illustrate this topographic
effect, we compared streamwater chemistry between the two forested
watersheds (F1 and F2), removing the potential confounding effect of land
use. Indeed, the steeper F2 (48 %) had a higher PO43-
concentration than the less steep F1 (39 %) (Fig. 2, Table 2), despite
that F2 has a higher proportion of natural forest cover. Soil erosion is
arguably the greatest concern to most P mitigation programs because the
concentration of P on the surface of soil particles is often orders of
magnitude greater than that in a soil solution (Sharpley et al., 2002;
Kleinman et al., 2011). Therefore, it is not surprising that topography may
be a more important driver for riverine P than land use at our study site.
The enhanced erosion/leaching associated with the steeper slope at F2 may also
explain why F2 had the second highest concentration of SO42-,
Ca2+, and Mg2+, the ions that are abundant in soils.
Monthly ion concentration (volume-weighted from weekly samples) of
streamwater of watersheds A1, A2, F1, and F2.
Monthly ion concentration (volume-weighted from weekly samples) of
rainfall of watersheds A1 and F2.
Mean (±1 SE – standard error) monthly ion concentration
(volume-weighted from weekly samples) and flux of streamflow.
Ion
Concentration (µeq L-1)
Flux (meq m-2 mo-1)
A1
A2
F1
F2
diff
A1
A2
F1
F2
diff
H+
0.96 ± 0.006
1.22 ± 0.006
0.91 ± 0.007
0.76 ± 0.004
a, b, a, c
0.030 ± 0.001
0.038 ± 0.001
0.036 ± 0.001
0.016 ± 0.004
a, b, ab, c
Na+
266 ± 4.88
254 ± 3.65
233 ± 4.45
231 ± 4.10
a, b, c, c
76.4 ± 1.74
73.0 ± 1.70
80.1 ± 1.68
46.7 ± 0.90
a, b, ab, c
K+
282 ± 0.87
213 ± 6.27
125 ± 0.49
108 ± 3.63
a, b, c, d
8.24 ± 0.20
6.14 ± 0.14
4.27 ± 0.50
2.19 ± 0.36
a, b, c, d
Ca2+
306 ± 7.49
193 ± 5.41
170 ± 7.34
273 ± 8.04
a, b, c, d
87.0 ± 1.92
54.1 ± 1.17
55.8 ± 1.02
54.4 ± 1.00
a, b, b, b
Mg2+
255 ± 5.10
188 ± 4.25
148 ± 4.72
206 ± 5.78
a, b, c, d
72.5 ± 1.62
52.8 ± 1.15
49.2 ± 0.94
41.0 ± 0.74
a, b, b, c
Cl-
199 ± 4.00
182 ± 3.06
178 ± 4.76
145 ± 2.55
a, b, b, c
59.2 ± 1.51
53.2 ± 1.34
62.8 ± 1.49
29.8 ± 0.64
a, b, a, c
NO3-
209 ± 5.31
158 ± 2.80
28.3 ± 0.76
16.1 ± 0.95
a, b, c, d
62.9 ± 1.63
46.8 ± 1.19
10.2 ± 0.25
3.32 ± 0.078
a, b, c, d
SO42-
212 ± 6.29
123 ± 3.96
116 ± 3.96
183 ± 6.45
a, b, c, d
59.2 ± 1.30
33.9 ± 0.74
39.1 ± 0.78
35.7 ± 0.66
a, b, b, b
PO42-
1.50 ± 0.182
1.38 ± 0.174
0.72 ± 0.114
1.29 ± 0.026
a, b, b, a
1.14 ± 0.0030
1.08 ± 0.0054
0.69 ± 0.028
0.69 ± 0.0030
a, a, b, b
A1, A2, F1, and F2 denote the four watersheds; diff: post hoc comparisons
among the four watersheds with different letters indicating statistical
differences (p < 0.05).
Mean (±1 SE) monthly ion concentration
(volume-weighted from weekly samples) and flux of rainfall.
Ion
Concentration (µeq L-1)
Flux (meq m-2 mo-1)
A1
F2
A1
F2
H+
39 ± 6.7
31 ± 5.4*
12 ± 3.9
7.9 ± 1.5*
Na+
107 ± 24
84 ± 18*
30 ± 8.5
23 ± 6.5(*)
K+
8.0 ± 1.3
7.8 ± 1.3
2.2 ± 0.45
1.9 ± 0.32
Ca2+
21 ± 3.2
19 ± 4.4
5.7 ± 1.0
4.2 ± 0.61*
Mg2+
30 ± 5.8
26 ± 5.6
8.2 ± 2.1
6.5 ± 1.7(*)
NH4+
19 ± 2.9
15 ± 2.7(*)
5.1 ± 1.3
3.8 ± 0.67(*)
Cl-
140 ± 30
100 ± 22*
38 ± 11
28 ± 8.2*
NO3-
24 ± 3.9
18 ± 3.0*
7.0 ± 2.0
4.7 ± 0.90(*)
SO42-
58 ± 8.6
53 ± 7.7
15 ± 3.6
13 ± 2.4
PO43-
0.96 ± 0.03
0.63 ± 0.03
0.75 ± 0.30
0.51 ± 0.12
A1 and F2 denote the two watersheds; an asterisk * indicates a significant
difference between the two watershed (p < 0.05); an asterisk inside
a parenthesis (*) indicates a marginally significant difference between the
two watersheds (p < 0.1).
Schematic diagram of N fluxes of watersheds A1 and F2. A1 represents
a watershed with 22 % agricultural lands and 68 % forests (a);
F2 represents a watershed with 0.38 % agricultural lands and 99 %
forests (b) (unit: kg N ha-1 yr-1).
Inputs and outputs of nitrogen and phosphorus of watersheds A1 and F2.
See text for the assumptions made in the calculations of dry deposition,
fertilization, and harvest.
Nitrogen
Phosphorus
(kg ha-1 yr-1)
(kg ha-1 yr-1)
A1
F2
A1
F2
Input
Wet deposition
20.4
14.3
3.6
2.8
Dry deposition
5.7
4.0
1.0
0.8
Fertilization
173.7
3.0
37.8
0.6
Total
199.8
21.3
42.4
4.2
Output
Harvest
25.0
0.4
1.6
0.0
Stream output*
105.7
5.6
4.2
2.6
Total
130.7
6.0
5.8
2.6
* For stream output, only dissolved inorganic forms are considered.
Rainfall chemistry
We confirmed that agricultural activities can influence watershed nutrient
cycling via atmospheric deposition in our study site (H2). We found
higher concentrations and fluxes of NO3- and NH4+ in
rainfall at A1, a watershed with 22 % of tea plantation cover, compared to
F2, the watershed almost entirely covered by natural forests. Ammonium
sulfate, urea and calcium ammonium nitrate
[5Ca(NO3)2 ⋅ NH4NO3 ⋅ 10H2O], which contain a high quantity
of NO3- and NH4+ are commonly used N fertilizers in
Taiwan (Huang, 1994). Therefore, in tea plantations at FRW, substantial
suspension and volatilization of ammonium sulfate, urea, and calcium ammonium
nitrate likely contributed to the high concentrations and fluxes of
NO3- and NH4+ in rainfall at A1. On the other hand, the
concentrations of PO43- and K+ in rainfall were not higher
at A1 compared to F2, which may be explained by the low mobility of
PO43- and smaller quantity of P and K in fertilizers.
Once in the atmosphere, aerosols/chemicals can be transported to other
locations but most of them will be deposited in nearby ecosystems. In central
Taiwan, the high NH4+ concentration in precipitation in a high
elevation forest (2000 m) was attributed to mountain agriculture that
occurred 10 km away (Ding et al., 2011). With the predicted expansion of
agriculture to the mountains both in Taiwan and many other regions (Johda et
al., 1992; Brown and Shrestha, 2000; Tulachan, 2001), even pristine
ecosystems will not be free from the impacts (e.g., acidification and
eutrophication associated with H+ and NO3-) of agricultural activities.
Because Taiwan is a small island, sea salt aerosols are important components
of rainfall (Lin et al., 2000). The distance to the coast, specifically, has
been used to explain the variation of Na+ and Cl- concentrations in
precipitation among four sites in central Taiwan (Ding et al., 2011). The
higher concentrations and fluxes of Na+ and Cl-, and to a lesser
degree Mg2+, at A1 than at F2 likely reflected such oceanic influences.
The watersheds receive winter rains, along with sea salt aerosols, from the
north/northeast coasts (northeast monsoon). While A1 is located on the
windward side, F2 is on the leeward side. Therefore, a substantial
proportion of the sea salt aerosols may have been intercepted before they
can reach F2. Although summer rains move from the opposite direction, the
watersheds are relatively far from the west/southwest coasts (> 60 km),
making summer rains less important to the input of sea salt aerosols
to the watersheds.
In contrast to Na+ and Cl-, the differences in topographic
position and distance to the ocean between A1 and F2 seemed to have a limited
effect on SO42- deposition. Many studies reported significant
contributions of long-range-transported S and N from eastern China to Taiwan
via the northeast monsoon (Lin et al., 2005; Junker et al., 2009). Because A1 is
on the windward side of the northeast monsoon, it may experience a higher input of
pollutants from long-range transport than F2, which is on the leeward side.
The lack of significant differences in SO42- between the two
watersheds suggest that the two watersheds are too close to show
differential influences of pollutants that are transported from sources
several hundred kilometers away.
Landscape configuration and streamwater chemistry
The large differences in NO3- concentration and flux between F1
and A1, A2 highlight the role of landscape configuration on streamwater
chemistry. Both A1 and A2 are subwatersheds of F1; however, the influence
of tea plantation on A1 and A2 largely dissipated as water entered into
forested F1. Specifically, the concentration of NO3- was 70 %
lower at F1 than at A1 and A2. Comparing to the difference in concentration
and flux of NO3- between F1 and F2 (< 30 %), that
between F1 and A1, A2 is striking (> 300 %; Fig. 2). Thus, by
constraining agricultural activities away from the main stream and
maintaining natural cover of its watershed, the impact of agriculture on
nutrient enrichment could be reduced. Our result confirmed the importance of
landscape configuration on streamwater chemistry (Dillon and Molot, 1997;
Johnson et al., 1997; Palmer et al., 2004).
N and P output from agriculture
The per-hectare output of N from tea plantations reported here (450 kg ha-1 yr-1)
is extraordinary high compared to those reported for
many agricultural watersheds around the globe. For example, a study from
the Baltimore Ecosystem Study reported an annual output of NO3-N at
13–20 kg ha-1 yr-1 for a 7.8 ha watershed that is completely covered by
agricultural lands and has gentle slopes (Groffman et al., 2004). For the
four watersheds that were 30–40 % covered by row crops and received
fertilization at 50–70 kg N ha-1 yr-1 in the southeastern coastal
plain of the US, nutrient output through streamflow was < 6 kg N ha-1 yr-1
(Lowrance et al., 1985). In the Great Barrier
Reef, Australia, total output via streamflow was approximately 5 kg ha-1 yr-1
for NO3-N from a watershed with 29 % of the land
covered by pasture and 14 % by crop lands (Hunter and Walton, 2008).
High N output from agricultural lands is probably common in Taiwan and other
regions under intensive fertilizer use. It has been reported that
over-fertilization is common in Japan, Korea, and Taiwan, and despite an
estimated 23–63 % over-fertilization the use of fertilizers is still
increasing in the region (Ahmed, 1996). In the Danshui River of
northeastern Taiwan, the output of dissolved inorganic N ranged from
3 kg ha-1 yr-1 in relatively pristine headwaters covered mostly by
natural forests to 100 kg ha-1 yr-1 in a populated estuary (Lee et
al., 2014; Shih et al., 2015). In humid southeastern China, N output from a
watershed with 17.5 % of agricultural lands, steep slopes (the watershed has
a mean slope of 21 % and the site is located in the hilly upstream
region), and very heavy application of N fertilizers
(300–1000 kg ha-1 yr-1)
reached 73 kg ha-1 yr-1 (Chen et al., 2008),
approximately the same magnitude as those reported here. Our study clearly
demonstrated that high application of fertilizers in regions with high
rainfall and steep slopes could lead to an extremely high output of N and,
therefore, eutrophication risk for downstream watersheds. The misconception
that heavy fertilization leads to high economic profit has resulted in the
popular practice of heavy fertilization in tea plantations, commonly at a
level similar to or higher than that in our study site (740 kg N ha-1 yr-1).
For example, conventional N fertilization in tea plantations is
approximately 1100 kg ha-1 yr-1 in Japan, which is more than twice
the suggested amount with the same tea yield (Oh et al., 2006).
In contrast to N, most of the P fertilizer was retained within the
watershed or transported in particulate form so that dissolved P only
accounts for a small proportion of the input. In most agricultural
watersheds, the majority (> 90 %) of P leaves the watersheds in
particulate form (Smith et al., 1991), and the loss in dissolved form
(i.e., PO43-) through runoff is relatively minor (Brady and Weil, 1999).
Thus, while the dissolved form of P could respond to land use changes, a
complete P budget at watershed scale still requires reliable estimates on
the particulate P.
Watershed N fluxes
The 72 % N retention at F2 is likely an underestimate because the input
from biological N fixation (BNF) was not included in the calculation. Based
on a recent synthesis (Sullivan et al., 2014), BNF in tropical forests is not
as high as previously reported and, on average, is slightly less than
10 kg ha-1 yr-1 for secondary forests. Thus, adding BNF to N input could
increase the N retention ratio at F2 (assuming a BNF of 10 kg ha-1 yr-1,
the N retention ratio at F2 would increase from 72 to
81 %). The high N retention ratio of F2 suggests that the secondary
natural forest is probably still growing. In contrast, because N fertilizers
were applied at rates that are 1 order of magnitude greater than BNF at
A1, and high N fertilization is known to negatively affect BNF (Sanginga et
al., 1989; Fuentes-Ramírez et al., 1999), adding BNF to nutrient input
has little effect on the N retention ratio at A1 (assuming a BNF of 10 kg ha-1 yr-1,
the N retention ratio at A1 would increase from 35 to 37 %).
In addition to BNF, the calculation of the N retention ratio did not take into
account the loss through volatilization and denitrification. Because it
rains frequently at the FRW, soil moisture is likely high throughout the
year and, consequently, N loss through denitrification could be substantial.
In addition, because fertilizers are applied in solid form,
volatilization of NH3 could also be high. Thus, if both denitrification
and volatilization are taken into account, the N retention ratio at A1 is
even lower. The return of N back to the atmosphere through
denitrification and volatilization helps explain the higher atmospheric N
deposition at A1 than at F2. The low retention ratio and the resulting high
leaching loss of N at A1 impose a major threat to the streamwater quality
that could lead to reservoir eutrophication.
Surprisingly, from our construction of the N fluxes, the loss of N through
the annual harvest (25 kg ha-1 yr-1) at A1 approximately equals the
annual atmospheric deposition (26 kg ha-1 yr-1), of which only a
small portion should have come from fertilizers (atmospheric N deposition at
F2 is only 8 kg lower than at A1, suggesting that less than 8 kg of atmospheric
N deposition could potentially come from fertilizers). In other words, to
maintain the current harvest, not much N fertilization is actually required,
and most of the 173.7 kg N ha-1 yr-1 from fertilization is simply
lost through hydrological process (i.e., leaching) to the streams and the
Feitsui Reservoir and/or returned to the atmosphere, both of which could
have negative environmental impacts. Our construction of the element fluxes
clearly showed that the N fertilizers are applied at rates that are neither
ecologically nor economically sound, and such excessive fertilization may
cause fundamental changes in watershed nutrient cycling (Fig. 4).
Conclusions
Agricultural and forested watersheds in tropical/subtropical mountains could
have distinct patterns of nutrient cycling. Even a moderate proportion of
tea plantation cover (17–22 %) in mountain watersheds, when in combination
with steep slopes and high precipitation, could lead to much higher ion
concentrations in both streamwater (nutrient output) and rainwater (nutrient
input) and much lower N retention ratios at watershed scale. Thus, mountain
watersheds may be particularly vulnerable to agricultural expansion.
Topographic control is important in nutrient leaching from mountain
watersheds, particularly for ions that are rich in soils, such as
SO42-, Ca2+, and Mg2+.
Proper spatial configuration of agricultural lands in mountain watersheds
can mitigate the impact of agriculture on NO3- output by 70 %,
thus reducing the risk of eutrophication for streams and lakes.
The contribution of tea plantations to the N output in streamwater for one of
the studied watersheds (i.e., A1) is estimated at approximately 450 kg N ha-1 yr-1.
This level of fertilization exceeds previous reports
around the globe and can only be matched in magnitude by one study in China
where fertilizers were excessively applied.
The conservative construction of the N fluxes for the watersheds indicates
over-fertilization at one of the studied watersheds (i.e., A1), which likely
resulted in leaching of N and additional loss of N to the atmosphere via
volatilization and denitrification.