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RELATIONSHIPS BETWEEN SOIL NUTRIENT AVAILABILITY
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AT THE TREE SCALE
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WITH
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DENDROCHRONOLOGICAL TREE GROWTH
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PAUL R. SHEPPARD1,3
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PERE CASALS2
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EMILIA GUTIÉRREZ1
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1
Departament d'Ecologia and 2Departament de Biologia Vegetal
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Universitat de Barcelona
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08028 Barcelona España
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3
Current address:
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Laboratory of Tree-Ring Research
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The University of Arizona
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Tucson, AZ 85721 USA
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office: (520) 621-6474
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fax: (520) 621-8229
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sheppard@ltrr.arizona.edu
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Submitted for review for the Proceedings of the 9th North American Forest Soils Conference
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
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ABSTRACT
The objectives of this research were to demonstrate the potential role of soil nutrient availabil-
26
ity in explaining dendrochronological variation at the tree level and to assess the usefulness of
27
ion-exchange resins (IER) in dendrochronological research. Our 0.2-ha study site in the central
28
Spanish Pyrenees had an open montane to subalpine forest of Pinus uncinata Ram. and soils that
29
are generally shallow (<0.5 meters deep), dark brown, and sandy loamy in texture. We collected
30
two increment cores from 20 mature trees with which we constructed a time series of relative
31
growth for each tree. We buried within the root zone of each sampled tree one IER capsule,
32
which resided in the soil for 247 days. We extracted the resins and measured solutions for am-
33
monium, nitrate, phosphate, calcium, and potassium. We then searched for statistical relation-
34
ships between soil nutrient availability and indexed tree growth.
35
Both forms of nitrogen were highly variable spatially, and the pattern of nitrate variability was
36
related to geomorphic hillslope position. The single most important soil nutrient with respect to
37
decadal-scale dendrochronological tree-growth variables in this study was nitrogen, as nitrate
38
availability explained 32% of variation of average growth since 1970 and 22% of variation of
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trend in growth since 1950. The 20 measured nitrate availability values fall into two clear sub-
40
groups, one of nine trees with high nitrate availability and the other of 11 trees with low nitrate
41
availability. When the tree-growth data are grouped based on nitrate availability, the two result-
42
ant index chronologies since 1950 have different low-frequency features, i.e., trees with low ni-
43
trate availability are growing normally but trees with high nitrate availability are growing better
44
than expected. Possible mechanisms of nitrate variation since 1950 include light tree harvesting,
45
grazing, and regional-scale air pollution that includes forms of nitrogen. Regardless of the
46
source of extra nitrogen, soils probably play an important role in mediating nutrient availability
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
3
47
at the tree level. This research approach of analyzing soil nutrient availability in dendrochronol-
48
ogy might apply well in studies of forest sites that are clearly impacted by an obvious source of
49
air pollution.
50
Measuring and analyzing soil nutrient availability at the tree level can substantially enhance
51
environmental applications of dendrochronological research. IER is clearly an excellent method
52
for measuring soil nutrient availability, and we recommend wide use of IER for measuring soil
53
nutrient availability at the tree level in dendrochronological research of environmental topics.
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Keywords: dendrochronology, soil nutrient availability, ion-exchange resins, environmental sci-
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ence
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Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
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4
INTRODUCTION
An underlying basis for virtually all paleoenvironmental applications of dendrochronology is
the linear aggregate model (Cook, 1987):
Rt = At + Ct + D1t + D2t + Et
(1)
61
where t indicates time in calendar year and R is the observed time series of ring width (or more
62
broadly, any ring-growth variable) of a tree, which can be explained by some combination of
63
variation related to age or size of the tree (A), climate (C), endogenous or local disturbances (D1,
64
such as gap-phase dynamics, Spurr and Barnes, 1980), and exogenous or stand-wide disturb-
65
ances (D2, such as insect epidemics, Fritts and Swetnam, 1989), plus an error term (E) for varia-
66
tion in R that cannot otherwise be explained with available observations or data.
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Clearly, a general strategy in dendrochronology is to optimize the explained variance in Rt
68
with the predictor terms of the linear aggregate model and thereby maximize the paleoenviron-
69
mental interpretability of ring-growth data. For example, age- or size-related variation is ac-
70
counted for by standardizing measured values (Fritts, 1976) as follows:
It = Rt / At
(2)
71
where It is the time series of dimensionless indices with a mean of 1.0 and stationary variance
72
through time, and At (same as in Equation 1) is a tree-specific growth curve of expected ring-
73
width values empirically estimated from the measurement data. Additionally, in studies of past
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climate the effects of disturbance (D1t and D2t) are effectively reduced by sampling only trees
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without outward evidence of disturbance. Or, in studies of past forest disturbance the effects of
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climate (Ct) are accounted for first to better elucidate ring-growth responses to the type of dis-
77
turbance under study.
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
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5
Dendrochronologists continually try to decrease the error term of the linear aggregate model
79
(Et), and one way of improving the model is to add additional explanatory terms. Clearly, one
80
such additional term could relate to the quality of soil, which provides moisture and nutrients for
81
tree growth and which varies at virtually all spatial scales (Arnold and Wilding, 1991). Indeed,
82
Cook (1987, p. 43) specifically included soil characteristics as part of Et. Little past dendro-
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chronological research has included detailed soil information, and those investigations that have
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mentioned soil typically have provided only a general survey description of soil for the entire
85
site. Site-level soil information cannot improve the linear aggregate model because the model
86
applies at the tree level.
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Soil moisture is accounted for at the tree level in the linear aggregate model by the climate
88
term. For example, available moisture may be considered as precipitation and/or temperature-
89
driven evaporation as regulated by soil. That leaves soil nutrient availability, which can vary
90
dramatically in soils across short distances (Beckett and Webster, 1971; George et al., 1997) so
91
that neighboring trees might be growing in soils of substantially different quality. Adding this
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variation at the tree level to the linear aggregate model could significantly increase its predictive
93
power and consequently improve the interpretability of a dendrochronology. Accordingly, the
94
primary objective of this research was to demonstrate the potential role of soil nutrient availabil-
95
ity in explaining dendrochronological variation at the tree level.
96
A key facet of this research is accurately measuring soil nutrient availability for each tree in a
97
dendrochronological study. One reasonable way to do this is to bury ion-exchange resins (IER)
98
in the soil of the root zone of each tree and to leave them buried for some period of time to ab-
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sorb ionic forms of nutrients from soil. Later, after recovering the IER and performing standard
100
chemical laboratory procedures on them, relative soil nutrient availability is known (Yang et al.,
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
6
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1991). This technique has been used extensively in general forest soils research (Skogley and
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Dobermann, 1996), but we know of no prior dendrochronological research using IER. Accord-
103
ingly, secondary objectives of this research were to assess the usefulness of IER in dendrochron-
104
ological research and to begin defining field protocols for its wider use in tree-ring studies.
105
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METHODS
Study Site
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Our study site is located in the central Spanish Pyrenees and is adjacent to the Sant Maurici
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Reservoir of the Aigüestortas and Sant Maurici Reservoir National Park of Catalunya (42°30" N,
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1°30" E, 2000 m elevation). Topography throughout the park is typically extreme with very
110
steep hillslopes, but we located a 0.2-ha study site that had a moderately sloped (up to 30° slope
111
angle) subsite and an adjacent flat subsite. These subsites allowed for studying the influence of
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topography and geomorphic position on the relationship between soil nutrient availability and
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dendrochronological tree growth.
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The forest type is moderately open (~200 trees/ha) upper montane to subalpine conifer with
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Pinus uncinata Ram. as the dominant overstory tree species and Vaccinium spp. and grasses as
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the understory and ground cover species. A cursory field survey of the soils indicated that they
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are generally shallow (<0.5 meters deep), dark brown, and sandy loamy in texture with abundant
118
cobbles and weak structure. Weather records at the nearby town of Esterri indicate that climate
119
of this site is mesic (mean annual precipitation of 614 mm, evenly distributed across all months
120
of the year) and cool (mean annual temperature of 5° C).
121
Field Sampling
122
Trees
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
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7
In October 1996, we subjectively selected ten mature trees per subsite that were within several
124
meters of nearest-neighbor trees (Figure 1a). This resulted in a nearly complete sampling of the
125
mature trees that did not have outward signs of disturbance (e.g., growth scarring, irregular
126
crown form). We collected two increment cores along opposing radii of each tree; for trees in
127
the steep subsite, the opposing radii were parallel to the slope contour. We also recorded the lo-
128
cation and topographical microsite conditions of each tree.
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Soils
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For each sampled tree we buried one IER capsule (UNIBEST PST-1 capsules, Bozeman,
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Montana) within the root zone (1-2 meters from the trunk). We buried the capsules to as uniform
132
a depth as possible given microsite patterns of cobbles and boulders in the soil, typically 10-15
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cm deep, where we presumed tree roots to be most prolific (Hart and Firestone, 1989). The soil
134
particles removed while digging with a hand trowel were placed back into the hole over the cap-
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sule. We strove to ensure complete contact between the capsules and the surrounding mineral
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portion of the soil (Gibson, 1986; Skogley et al., 1996). In May 1997, we retrieved the IER cap-
137
sules, which had resided in the soil for 247 days spanning autumn, winter, and the first half of
138
spring, a time period that can be important with respect to nutrient availability (Giblin et al.,
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1994). We lightly rinsed capsules with de-ionized water in the field (Giblin et al., 1994) and
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stored them individually in marked plastic bags (Skogley et al., 1997).
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Laboratory and Quantitative Analysis
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Trees
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We air dried and glued all increment cores into grooved sticks with the transverse wood sur-
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face facing up (Phipps, 1985). We sanded the cores with successively finer wood abrasives to
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expose ring details at the cellular level (Stokes and Smiley, 1968). We crossdated the entire site
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
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collection of cores by matching patterns of relatively wide and narrow rings as well as other ring
147
features (e.g., latewood color, frost damaged cells) to account for the possibility of ring-growth
148
anomalies such as missing or false rings (Douglass, 1941). We then assigned year dates of for-
149
mation to all rings back in time beginning with the known year of 1996 for the outermost ring.
150
We measured the width of all dated rings to ±0.01 mm and checked the quality of the data for
151
dating and measurement errors using cross-correlation testing at multiple time lags (Program
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COFECHA, Holmes, 1983). These data are now archived in the International Tree-Ring Data
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Bank (Grissino-Mayer and Fritts, 1997). We then averaged the measured values for each year
154
held in common by both cores of each tree into a single time series for each tree. To remove the
155
age- and/or size-related growth trends from these time series, we divided measured values by
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curve fit values (At of Equation 2) for each tree. We selected a cubic-smoothing spline for this
157
step, and in particular we chose the spline whose flexibility left 75% of the variation at the 100-
158
year period in the resultant index series (Cook and Peters, 1981). This strategy allowed for anal-
159
ysis of trends in tree growth up to 50 years in length.
160
Soils
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We extracted all ions absorbed by the IER in three steps using 20 ml of 2 M HCl agitated for a
162
total of one hour (Dobermann et al., 1997; Skogley et al., 1997). This resulted in a 60-ml solu-
163
tion for each tree. We then measured the solutions for ammonium and nitrate (colorimetry),
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phosphate (visible spectrometry), calcium (atomic absorption spectrometry, Wright and Stuczyn-
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ski, 1996), and potassium (flame emission spectrometry, Wright and Stuczynski, 1996).
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Soil Nutrient Availability and Tree Growth
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We searched for quantitative relationships between (1) soil nutrient availability and (2) aver-
168
ages and trends of indexed tree growth using correlation and multiple regression tests as well as
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
9
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time-series and bivariate plots. We were interested primarily in analyzing relative tree growth of
170
the 20th century, but we had no a priori idea of what time frame to focus on. Consequently, we
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calculated the average growth index and trend in growth indices for each tree beginning from
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1900 to present, then from 1910 to present, etc., to find the point in time for which soil nutrient
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availability correlates significantly with tree growth.
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RESULTS
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The majority of total available nitrogen came from nitrate, which was nine times more availa-
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ble than ammonium and supplied 2.4 times more nitrogen that ammonium supplied (Table 1).
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Both forms of nitrogen were highly variable spatially, each with a coefficient of variation greater
178
than 100% across our 20 trees. In contrast, phosphate was relatively unavailable and less varia-
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ble. Calcium and potassium were also less variable, each with a coefficient of variation less than
180
80%, and they were more available than phosphate but less so than the nitrogen forms.
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All correlations between pairs of nutrients were positive (Figure 2). The nitrogen forms cor-
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related significantly with one another, and the spatial variation of total nitrogen was virtually
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equal to that of nitrate alone. Phosphorus correlated weakly with the other nutrients. Calcium
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and potassium correlated strongly with each other and with nitrate, but they correlated weakly
185
with ammonium.
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Our sequential search for quantitative relationships between soil nutrient availability and den-
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drochronological values of recent tree growth found that the average growth index since 1970
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and the trend in growth indices since 1950 have the strongest statistical models. In both cases,
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the best one-variable model by far uses nitrate as the predictor to explain 32% of variation of av-
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erage growth and 22% of variation of trend in growth (Figure 3). Both models are significant
191
and have normally distributed residuals that have no pattern related to predictor or predicted val-
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
10
192
ues. These two models are not independent of one another, as average growth since 1970 corre-
193
lates strongly (r = +0.88) with trend in growth since 1950.
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The 20 measured nitrate values fall into two clear subgroups, one of nine trees with more than
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10 µg/day/IER capsule and the other of 11 trees with less than 5 µg/day/IER capsule (Figure 4).
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The trees of each nitrate subgroup fall almost equally across both subsites, but the majority of
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trees with high nitrate (seven of nine) are growing either in the lower half of the steep subsite or
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in the half of the flat subsite that is adjacent to the margin of the two subsites (Figure 1).
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When the dendrochronological data are subdivided into two subsets based on nitrate availabil-
200
ity, the two resultant index chronologies (average of all trees within each site or subsite, Fritts,
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1976) since 1950 correlate strongly with one another (r = +0.78) but have different low-
202
frequency features (Figure 5). The chronology composed of high-nitrate trees has an average
203
index value since 1970 that is significantly above the mean of 1.0, and it has a significantly posi-
204
tive slope since 1950 (Figure 5a). By contrast, the chronology of low-nitrate trees has an average
205
index value since 1970 that is not significantly different from 1.0 and a negative slope since 1950
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that is not significantly different from zero (Figure 5b). The full-site chronology using all 20
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trees also has an average index value since 1950 that is not significantly different from 1.0 and a
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slope since 1950 that is not significantly different from zero (Figure 5c).
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A best-subsets regression analysis using all nutrients as candidate predictors showed that
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phosphate and potassium explain additional variation beyond that explained by nitrate for aver-
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age growth since 1970 and trend in growth since 1950 (Table 2). Both 3-variable models are
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significant and have high R2 values. In both cases, the coefficients for phosphate and potassium
213
are negative; coefficients for phosphate are significant, but those for potassium are not.
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DISCUSSION
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
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11
Soil Nutrient Availability
216
Soil processes that affect nutrient availability do so similarly to at least some degree for all
217
nutrients, as indicated by the result that all bivariate pairs of nutrients correlate positively. For
218
example, physical characteristics such as depth, texture, structure, porosity and permeability, and
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color as well as chemical characteristics such as pH and concentration gradients probably affect
220
the availability of all nutrients measured in this study (Pritchett and Fisher, 1987).
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However, as part of the nitrogen cycle, nitrate and ammonium availability are also affected by
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soil microbial activity that does not directly affect the other nutrients (Brady, 1974). Thus, it is
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reasonable that nitrate and ammonium availability correlate strongly with one another but typi-
224
cally more weakly with the other nutrients. In particular, the lack of a biological component in
225
the cycling of calcium and potassium may cause them to correlate only weakly with ammonium,
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the cation form of nitrogen. Similarly, phosphorus cycling lacks a direct biological component
227
as well as an abundant atmospheric source (Pritchett and Fisher, 1987), both of which may ex-
228
plain why phosphate correlates only weakly with nitrate, the anion form of nitrogen. The greater
229
mobility of nitrate in soil probably accounts for its much greater availability than that of ammo-
230
nium (Hart and Binkley, 1985).
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The influence of the biological component in nitrogen cycling may be the origin of the high
232
variability in nitrate and ammonium availability. Soil microbial activity, for example, is affected
233
by moisture and temperature (Adams et al., 1989), which can vary at microsite scales in forest
234
soils due to variation in tree canopy and litter layer patterns (Pritchett and Fisher, 1987). Thus, it
235
is reasonable that the coefficients of variation exceed 100% for both nitrogen forms. Conversely,
236
the physical and chemical processes that affect the other nutrients are probably more uniform,
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
12
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both spatially and especially temporally, so it is also reasonable that the coefficients of variation
238
of phosphate, calcium, and potassium are lower than those of the nitrogen forms.
239
It is impossible to know for certain from our data if the spatial pattern of nutrient availability
240
that exists today has existed for the last few decades. Perhaps future research using dendrochem-
241
ical analyses (Lewis, 1995) to determine elemental concentrations in dated tree rings could help
242
in this regard, though it appears that tree-ring nitrogen concentration in particular is not inter-
243
pretable for environmental availability of nitrogen at the time of ring formation (Poulson et al.,
244
1995). For now, we must assume that the geological Principal of Uniformitarianism, which as-
245
serts that patterns of environmental processes (e.g., spatial variation in relative soil nutrient
246
availability) are the same now as they were in the past (Bates and Jackson, 1984), applies at our
247
dendrochronological site for at least the last few decades.
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Soil Nutrient Availability and Dendrochronological Tree Growth
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The single most important soil nutrient with respect to decadal-scale dendrochronological
250
tree-growth variables in this study was nitrogen. Regardless of the origin of the spatial variation
251
in nitrate availability, trees with currently higher nitrate have been growing better since 1950
252
than trees with less nitrate, conforming to extensive forest-soils research that has shown nitrogen
253
typically to be the macronutrient most limiting to tree growth (Binkley and Hart, 1989). In par-
254
ticular, nitrogen is often deficient in coniferous forests with cool climates (Pritchett and Fisher,
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1987), such as our study site.
256
Even stronger soil nutrient-tree growth relationships are possible when phosphorus and potas-
257
sium enter with nitrogen in multivariate regression models. It is difficult, however, to rationalize
258
the negative signs of the coefficients for phosphorus and potassium, especially for phosphorus,
259
which is often deficient for tree growth (Pritchett and Fisher, 1987). Potassium is thought to be
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
13
260
adequately plentiful in most forest soils (Pritchett and Fisher, 1987), possibly explaining its weak
261
role in our multi-nutrient tree growth models. The differing signs of the coefficients make it dif-
262
ficult to combine nitrogen, phosphorus, and potassium into a single indicator of important nutri-
263
ent availability with which to independently distinguish between trees within the site.
264
The two groups of trees with high- versus low-nitrate availability transcend our original sub-
265
groups of flat versus steep subsites, and instead they follow a pattern more related to geomorphic
266
hillslope position. Most of the high-nitrate trees are in or near the backslope-footslope (Hall and
267
Olson, 1991) transition of the site. The hillslope of our site has a convex contour and a weakly
268
convex slope, which may cause surface and subsurface water and nutrients to flow through
269
and/or accumulate in the backslope-footslope transition zone (Hall and Olson, 1991). Thus, trees
270
of this geomorphic position may tend to have more available soil nutrients and therefore grow
271
slightly better than other trees (Hammer et al., 1991). However, this geomorphic interpretation is
272
not perfect: trees #8 and #15 are growing in the backslope-footslope zone (Figure 1) but have
273
low nitrate (Figure 4) while trees #2 and #4 are in the toeslope zone (Figure 1) but have high ni-
274
trate (Figure 4). Thus, quantifying the topographic microsite and geomorphic position of each
275
tree may not suffice as a substitute for actually measuring soil nutrient availability for each sam-
276
pled tree within a dendrochronological study site.
277
The ability to distinguish among trees within a site on the basis of independent environmental
278
variables–nitrate availability in this case–for the purpose of improving the environmental signal
279
contained in dendrochronologies is the essence of adding an additional explanatory term to the
280
linear aggregate model of dendrochronology to improve its strength. However, because our
281
measurements of nutrient availability are for only a single point in time, the additional explanato-
282
ry term must have a different subscript that that of other terms, as follows:
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
14
Rt = At + Ct + D1t + D2t + SNn + Et
283
284
(3)
where SNn is the sum of effects of all n soil nutrients that significantly affect tree growth.
The interpretability of the separate chronologies is now also enhanced relative to that of the
285
full-site chronology. The different decadal-scale patterns of the two subgroup chronologies are
286
at least statistically related to different nitrogen availability at the tree level, and additional re-
287
search should start with searching for the mechanisms that cause this statistical relationship. At
288
least three possibilities exist. One, light selection harvesting of trees took place around Sant
289
Maurici Reservoir (including our study site) in the late 1950s and late 1960s, and this manage-
290
ment event logically reduced below-ground competition for nitrogen (Pritchett and Fisher, 1987),
291
perhaps more so for some remaining trees than for others. Two, grazing is also allowed in the
292
National Park, and perhaps this redistributes nutrients in tree-specific ways (Beckett and Web-
293
ster, 1971).
294
Three, although our site is not near a large human population center that may be considered as
295
a source for heavy nitrogen deposition, the central Spanish Pyrenees are currently receiving dep-
296
osition of nitrogen that is above presumed ambient levels (Camarero and Catalan, 1993). This
297
deposition may reflect regional- to hemispheric-scale nitrate pollution that is noticeable in
298
Greenland ice data beginning in 1955 (Mayewski et al., 1986), and such low-grade nutrient input
299
can significantly affect tree growth throughout decades of time (Pritchett and Fisher, 1987).
300
Since trees take in much of their nitrogen as ionic forms through their roots (Kramer and Ko-
301
zlowski, 1979), it is reasonable to suspect that soil plays a central role at the tree level in mediat-
302
ing the availability of nitrogen from chronic pollution (Lammers and Johnson, 1991).
303
304
The research approach of analyzing soil nutrient availability at the tree level in dendrochronology might apply well in studies of forest sites that are clearly impacted by an obvious source
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
15
305
of air pollution. Such sites exist in southern California, for example, where we are initiating a
306
study using the soil nutrient-tree growth analysis described here. Some trees of some forests of
307
southern California have increasing growth indices since 1950, which have been tentatively in-
308
terpreted as evidence of direct CO2 stimulation of tree growth (Jacoby, 1986). It is physiologi-
309
cally reasonable that increasing CO2 may play a role in increasing tree growth (Kramer and Ko-
310
zlowski, 1979), but forests adjacent to and downwind of the Los Angeles metropolitan region are
311
also receiving substantial deposition of nitrogen from air pollution (Grant, 1995). If input of ni-
312
trogen is affecting tree growth in southern California, then soils may also be playing a role there
313
in mediating the effect of nitrogen availability at the tree level. A study combining soil and tree-
314
growth data at the tree level could help elucidate the situation in southern California and else-
315
where.
316
Use of IER and Dendrochronological Research
317
The fact that nitrate was more available than ammonium in our study contradicts some past
318
forest-soils research that has measured more ammonium present in soils than nitrate (Gross et al.,
319
1995; Huang and Schoenau, 1996a). However, measuring the amount of a nutrient present in
320
soil per se includes the potential nutrient pool, which in the case of nitrogen typically does not
321
relate reliably to what becomes available in mineralized forms (Binkley and Hart, 1989). Meas-
322
uring actual soil nutrient availability is preferable in this type of dendrochronological project that
323
analyzes variation at the tree level.
324
IER is clearly an excellent method for measuring soil nutrient availability. IER can stay in the
325
soil for reasonably long time periods (between a month and a year or longer, Skogley and
326
Dobermann, 1996), and therefore they can integrate bioavailability through more time than does
327
an instantaneous sampling of soil for the total amount of a nutrient present (Binkley and Hart,
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
16
328
1989). Placement of IER disturbs the soil only minimally (Carlyle and Malcolm, 1986), and the
329
resins are resistant to freezing and drying stresses in the field (Crabtree and Kirkby, 1985). The
330
IER are stationary in the soil, as are tree roots at the time scale of a year or less, and they absorb
331
only those ionic forms of nutrients that flow around them in the soil solution, as is also true for
332
tree roots (Binkley, 1984; Binkley and Hart, 1989). Thus, field use of IER closely approximates
333
soil-tree root interactions with respect to nutrient availability (Gibson, 1986). Tests of IER have
334
shown that this technique correlates well with other more labor-intensive methods as well as with
335
ecosystem process rates (Binkley et al., 1986). Furthermore, expressing values in relative units
336
such as mass of nutrient/time/mass of resin is valid (Carlyle and Malcolm, 1986) and acceptable,
337
if not preferable, in dendrochronological research, which typically also analyzes relative
338
measures of tree growth, i.e., standardized indices of growth.
339
A protocol suggestion is to bury more than one capsule or bag of IER per tree. Past research
340
using IER has found differences in soil nutrient availability in an area as small as one square me-
341
ter (Huang and Schoenau, 1996b). Given that root zones of mature trees can span an area of sev-
342
eral square meters (Pritchett and Fisher, 1987), it would be wise to have ample replication within
343
each tree to more confidently measure soil nutrient availability using IER. This would also more
344
closely match the typical dendrochronological sampling strategy where multiple increment cores
345
are collected from each sampled tree.
346
Additionally, it would be preferable to measure soil nutrient availability for different parts of
347
the annual cycle of tree growth and dormancy (Binkley and Hart, 1989). Our study analyzed
348
availability for the dormant season leading up to the probable start of cambial activity of Pinus
349
uncinata at our sites (Camarero et al. 1998). This sampling period includes a majority of the an-
350
nual precipitation as well as effects of snowmelt at the site (Lundell, 1989). However, another
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
17
351
protocol suggestion is to measure soil nutrient availability for the growing season itself–or for
352
shorter periods during the growing season–to assess the role that the point in time during cambial
353
activity has on soil nutrient-tree growth relationships (Casals et al., 1995).
354
CONCLUSION
355
Measuring and analyzing soil nutrient availability at the tree level can substantially enhance
356
environmental applications of dendrochronological research. With this soils information, it is
357
possible to distinguish between subgroups of trees within a tree-ring site and thereby construct
358
subchronologies that differ significantly, especially for variation at the decadal scale. Subchro-
359
nologies may then lead to different–and presumably improved–environmental interpretations rel-
360
ative to those based on a full-site chronology. IER are an excellent method for obtaining infor-
361
mation on soil nutrient availability since they function similarly to tree roots with respect to nu-
362
trient absorption or uptake and therefore accurately reflect nutrient availability to trees. We rec-
363
ommend wide use of IER for measuring soil nutrient availability at the tree level in dendro-
364
chronological research of environmental topics.
365
ACKNOWLEDGEMENTS
366
We thank managers of the Aigüestortas and Sant Maurici Reservoir National Park of Catalu-
367
nya, Jesus Julio Camarero, Joan Romanyà, Earl Skogley, Thomas Thompson, and Richard
368
Holmes for assisting this project in various ways. This study was funded with a NATO Postdoc-
369
toral Fellowship from the U.S. National Science Foundation to the first author.
370
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Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
23
Table 1. Descriptive statistics of nutrient availability (n = 20).
Nutrient as
ionic form
N as NH4+
N as NO3–
N as total N
P as PO4–3
Ca as Ca+2
K as K+
Average
(µg/day/IER capsule)
Ionic form
Nutrient
0.98
8.71
9.69
0.04
0.86
0.32
0.81
1.97
2.78
0.01
0.86
0.32
Coefficient of
variation (%)
104
107
102
57
58
79
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
24
Table 2. Multiple regression results using NO3–, PO4–3, and K+ as predictors of
tree growth (n = 20).
Coefficient (p value)
Model
NO3–
PO4–3
K+
R2
p level
Average growth
index since 1970
+0.010
(<0.001)
–2.35
(0.015)
–0.16
(0.059)
63%
<0.001
Trend in growth
indices since 1950
+0.001
(0.001)
–0.22
(0.058)
–0.15
(0.138)
45%
0.005
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
25
480
FIGURE CAPTIONS
481
Figure 1. (a) Plan view and (b) longitudinal profile of study site. Contour lines of (a) and verti-
482
cal reference scale of (b) are relative to the elevation of the flat subsite. Lines for trees
483
in (b) are not drawn to scale.
484
485
486
Figure 2. Correlation matrix of nutrient availability. The critical value at the 0.05 level for n =
20 is ±0.43 (Rohlf and Sokal, 1981).
Figure 3. Single-variable regression results using nitrate availability to explain (a) average
487
growth index since 1970 and (b) trend in growth indices since 1950. Dashed lines are
488
the 95% confidence limits.
489
Figure 4. Spatial-series plot of nitrate availability for each tree. Trees #1-#10 are in the flat sub-
490
site and trees #11-#20 are in the steep subsite (refer also to Figure 1). Dashed line is a
491
reference for distinguishing high- versus low-nitrate trees.
492
Figure 5. Time-series plots of index chronologies from 1950 to 1996 for (a) high-nitrate trees,
493
(b) low-nitrate trees, and (c) all trees of the site. Dashed line is 1.0 mean of the chro-
494
nology, light gray line is slope since 1950, and dark gray line is average since 1970.
495
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
496
26
Sheppard, Casals, Gutiérrez: Soil nutrients and tree growth.
N as NO3–
Total N
P as PO4–3
Ca+2
K+
N as NH4+
+0.52
+0.73
+0.22
+0.40
+0.19
27
N as NO3–
Total N
P as PO4–3
Ca+2
+0.96
+0.39
+0.65
+0.56
+0.38
+0.64
+0.51
+0.39
+0.46
+0.79