Download Effects of climate on deer bone S15N and 613C

Gecchimica et CosmochimicaActa, Vol. 60, No. 21, pp. 4161-4166,1996
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Effects of climate on deer bone S15N and 613C: Lack of precipitation effects on S15N
for animals consuming low amounts of Cg plants
A. B. CORMIE and H. P. SCHWARCZ
Department of Geology, McMaster University, Hamilton, ON L8S 4M1, Canada
(Received March 3, 1995; accepted in revised form June 21, 1996)
Abstract-We
have examined the relationship of bone collagen 615N and 613C to climatic variables,
humidity, temperature, and amount of precipitation using fifty-nine specimens of North American whitetailed deer (Odocoileus virginianus) from forty-six different locations. In previous studies of African
mammals there was a significant correlation between bone collagen S 15Nand local amount of precipitation. Results presented here similarly show an increase in 615N with decreasing amount of precipitation
but only for 25% of the animals, namely those consuming more than 10% C4 plants. These animals also
exhibited a significant correlation between S13C and temperature which mirrors previous observations
for grasses suggesting that these deer consume grasses during times of population and nutrient stress.
In contrast, even in dry areas containing high proportions of C4 grasses, the majority of the deer had
consumed low amounts of C4 plants and these deer did not have 6”N which correlate with amount of
precipitation. Only when deer deviated from their normal feeding patterns by consuming Ca plants or
grasses did their S15N correlate with amount of rainfall. For these animals, consumption of C, plants or
grasses may signal conditions of water and nutrient stress. An increase in S15N of bone collagen may
result from combined effects from excretion of concentrated urine (to conserve water) and increased
internal recycling of nitrogen (to conserve nitrogen).
1. INTRODUCTION
if grazing occurred since the proportion of Cq species among
grasses varies between O-82% (Teeri and Stowe, 1976) and
increases in areas of high summer temperatures (normal July
minimum temperature). In contrast, climatic effects should
be relatively low in strict browsers since the proportion of
Cq species among dicots varies only between 0.0 and 4.4%
(Stowe and Teeri, 1978) with increases in areas of low
humidity (mean summer pan evaporation).
Climate directly causes *3%0 variation in 613C of single
species of plants (Smith et al., 1976; Arnold, 1978; Winter
et al., 1982; Stuiver and Braziunas, 1987; Fraser et al., 1978)
mainly as a result of effects of water stress or humidity on
the stomata1 resistance and partial pressures of plant COZ
(Francey and Farquhar, 1982; O’Leary, 1981, 1988; Farquhar et al., 1982a,b, 1989; Tieszen, 1991). In addition,
conifers are about 3%0 lighter than deciduous trees (Stuiver
and Braziunas, 1987). However, since such variations
among plants are relatively small, they are less likely to
produce variations in bone S13C than would variations in
proportions of C3 and C4 plants.
In Africa, the 6 15Nand 6 j3C of elephant bone collagen is
higher in drier climates (Vogel et al., 1990). While there
are no differences in SL5N between C3 and C4 plants, the
increases in both S 13C and 6 15N in dry areas may be attributed to increases in proportion of dry adapted, C4 plants
along with coincidental decreases in contributions of fixed
nitrogen to the soils (cf. Vogel et al., 1990; Hastorf and
Deniro, 1985; Ambrose and Deniro, 1986b, 1989; Virginia
and Delwiche, 1982; Vogel, 1978a; Connie and Schwartz,
1994; Teeri and Stowe, 1976; Stowe and Teeri, 1978; Tieszen et al., 1979; Livingston and Clayton, 1980; Heaton et
al., 1986). However, other results from Africa suggest that
mammal bone collagen 6 “N may not be a simple reflection
The S 15Nof mammalian herbivore bone collagen is primarily
affected by variations in soil 615N at the base of the food
chain but there may be some variations due to root depth of
dietary plants, or to the amounts of leguminous or woody
plants in the animal’s diet (Cormie and Schwartz, 1994;
Ambrose and Deniro, 1986a, 1989; Vogel et al., 1990). The
S 13C are primarily affected by the amount of C3 as opposed
to C4 plants consumed by the animals, but there is some
variation due to the canopy effect on plants (cf. Connie and
Schwartz, 1994; Vogel, 1978a,b; Vogel et al., 1990; Van
Der Merwe, 1982; Van Der Merwe and Medina, 1991; Ambrose and Deniro, 1986a,b, 1989; Hobson and Schwartz,
1986).
Some studies have found relationships between 615N and
613C of mammalian bone collagen and climate. Van Klinken
et al. ( 1994) using 905 samples found significant correlations between mammalian bone collagen S 13Cand a number
of climatic variables in July: ( 1) number of hours of sunshine
(2) humidity, (3) temperature, and (4) amount of precipitation. These could reflect the effects of climate on dietary
plants. 613C of bone is greatly affected by the amount of C3
as opposed to C4 plants in an animal’s diet varying from
w-21.5%0 in animals consuming 100% C3 plants to
a--7.5%0 in animals consuming 100% C4 plants (after: Vogel, 1978a; Vogel et al., 1990; Van Der Merwe, 1982; Ambrose and Deniro, 1986a,b, 1989; Hobson and Schwartz,
1986; Walker and Deniro, 1986). Climate is known to affect
the proportions of C3 as opposed to C4 plants in an area and,
therefore, could be reflected in herbivore bone S13C (Teeri
and Stowe, 1976; Stowe and Teeri, 1978; Vogel, 1978a;
Tieszen et al., 1979; Livingston and Clayton, 1980). In
North America, such climatic effects on S 13Ccould be large
4161
4162
A.
B. Cormie and H. P. Schwartz
of local soil and plant 6’*N. These include observed differences in 6 15Nbetween browsers and grazers from the same
habitat and increases in herbivore-plant offsets in specific
locations relative to others and in open vs. forest habitats
(cf. Ambrose, 1991; Sealy et al., 1987; Heaton et al., 1986).
A negative correlation was found between 6 “N and annual amount of precipitation both for a single species (elephants) and for a variety of different species (Heaton et al.,
1986; Sealy et al., 1987). Drought tolerant species (mostly
browsers) were further found to have 6”N values 2-4%c
higher than obligate drinkers (mostly grazers) (Ambrose
and Deniro, 1986a, 1987; Ambrose, 199 1) . Drought tolerant
species may be able to cope during times of reduced consumption of water by exchanging urea for water in the kidneys osmotic pump and excreting concentrated urine (Ambrose, 1991) With the increase in concentration of the urine
there is a disproportionate excretion of “N-depleted urea
into the urine and an overall increase in the loss of nitrogen
(Ambrose and Deniro, 1986a, 1987; Ambrose, 1991).
Drought tolerant species, or browsers, have a tendency to
consume foods with higher amounts of bioavailable protein
and thus may compensate for this nitrogen loss (Ambrose
and Deniro, 1986a, 1987; Ambrose, 1991). Human 6 “N
values followed the precipitation effects of the mammals in
their diet (Heaton et al., 1986).
A reverse effect to that described above for browsers and
grazers was also found in Africa. In areas with <400 mm/
yr rainfall, animals consuming low protein foods (mostly
grazers) were found to have 6 “N values l-2%0 higher than
animals consuming high protein foods (mostly browsers)
(Sealy et al., 1987). It is possible that both ruminants and
animals that consume lower amounts of bioavailable protein
have higher S 15Ndue to increased microbial food processing
in the digestive tract and internal recycling of nitrogen (Sealy
et al., 1987). A ruminant such as deer can increase the
quantity of bioavailable nitrogen through microbial food processing in the rumen. This might increase the trophic level
and 615N of the amino acids (from digested microbes) absorbed by the animal and which enter the transamination
pool from which protein is synthesized. Excess nitrogen is
routed to the liver to form urea, some of which may be
recycled into the lumen to again support microbial growth.
An increase in the number of passes that the nitrogen makes,
via urea, through the microbe cycle could increase the S 15N
of conserved nitrogen relative to times when the amount of
recycling is lower (Sealy et al., 1987). Since protein content
and quality is lower in plants from arid areas (Sealy et al.,
1987; Ambrose, 1991) and may be lower in the CJ plants
adapted to such areas, it is possible that animals from a
single species such as deer might exhibit higher S15N in drier
areas.
This contrasts with the proposal of Ambrose ( 1991) that,
since urea is depleted in 15N,recycling urea into the rumen
would actually decrease S “N of intestinal microbes and bone
collagen. However, although ruminants constantly recycle
urea into the rumen (e.g., Somers, 1961), they do not appear
to have obviously lower 6 15N compared to nonruminants
(after: Sealy et al., 1987; Ambrose and Deniro, 1986a,
1989). Ambrose (1991) further argues that there are unlikely to be protein amount effects but that, instead, tissue
b “N should be viewed as dependent, in a simple manner,
on the mass balance between dietary inputs and excretory
outputs of nitrogen with increases in tissue 615N primarily
due to increased outputs of 15N-depleted urea, such as during
water stress. This view contrasts with empirical observations
of Hobson and Clark (1992b) who find significantly increased tissue-diet 6 15Noffsets in birds experiencing nutrient
stress. They propose that during times of nutrient stress there
may be greater tissue breakdown and internal recycling of
nitrogen with some fractionation during mobilization and/
or redeposition of amino acids.
We have previously examined the geographical distribution of S’“C and S15N of North American white-tailed deer
(Cormie and Schwartz, 1994). The deer represent a single
species of nonmigratory, browsing ruminant with a broad
geographical distribution and a fossil record extending back
2-3 million years. Therefore, white-tailed deer provide an
excellent opportunity to study variations in 6°C and 615N
of mammalian bone collagen as a result of geography or
climate (Cormie and Schwartz, 1994).
Most deer had low 613C, reflective of their normal browsing habits. However, proportions of C, plants increased in
two subpopulations of deer. In moist areas, high 6°C was
associated with low S15N due to consumption of corn, legumes, and other cultigens exposed to 15Ndepleted fertilizer.
In contrast, in drier areas with relatively high summer temperatures, high 6°C was associated with high 615N. We
suggested that in such areas a small number of the deer
consume some grasses as a result of population and nutrient
stress. Deer sometimes graze during times of population and
nutrient stress, but this is infrequent due to the poor resistance of deer to the parasites passed on by grasses (Hosley,
1956; Severinghaus and Cheatum, 1956). Thus, high 6 15N
in deer from such areas could result from a combination of
water stress and lower amounts of bioavailable protein in
the deer’s diet. A rough positive correlation between 6”N
and 6°C can be observed for white-tailed deer once the
likely influences of agriculture on 6 15Nand 6 13Care removed
(cf. Fig. 5 in Cormie and Schwartz, 1994).
In work presented here, we further examine variability in
b “C and 5 15N of a single species of herbivore by directly
comparing the 6°C and 615N results of North American
white-tailed deer to climate. We will specifically examine
whether the relationship between 615N and amount of rain
for deer resemble that shown earlier for African mammals
by Heaton et al. (1986) and whether results appear to be
affected by protein amount effects.
2. METHODS
The relationship of b 15N and 6’% to climate were studied using
results of cortical bone of tibia of fifty-nine modem, white-tailed
deer specimens from forty-six different locations in North America.
Preparation and analytical methods are described in Cormie et al.
( 1994a) and Cormie and Schwartz ( 1994). Methods of extracting
gelatin from bone have been developed for the study of fossil samples due to the potential for contamination
(e.g., Longin, 1971).
However, as is shown in Cormie et al. ( 1994a. incl. Tables 3,4, and
5), benefits appear to be few when dealing with modem specimens.
Therefore, for this studv, the CO, and N, for ah but two of the
results, were obtained from whole bone powders. As described in
Cormie et al. ( 1994a), prior to grinding to powder, all samples had
4163
Effect of climate on isotope composition of N and C in deer bones
been pre-cleaned and degreased, using carbon tetrachloride. The two
gelatins were prepared by the methods of Chisholm et al. (1983) in
which bone is demineralized in 1 N HCl, gelatinized in 3 pH acidified
water, filtered, then dried. The 613C of the whole bone results were
adjusted for direct comparisons to 6°C values in the literature by
subtracting 0.6%0.This adjusts for the 613Ccontribution from a small
amount of CO* from carbonate existing in fresh, whole bone (Connie
and Schwartz, 1994; Connie et al., 1994a).
Total variability on replicate preparations of whole bone powders
is t0.2%0 for 6”N (n = 45) and ?0.5%0 for 6°C In = 50). This
compares to a total ‘variability of ?0.2%0 for 615N‘(n = 14) and
t0.4%0 for 6°C (II = 12) for replicate gelatin extracts (Connie et
al., 1994a). Through analysis of error (Table 4 in Connie et al.,
1994a) the total variability in 6°C of whole bone powders, which
includes variability from small differences in amount of bone carbonate between deer, was found to be +0.6%0 (n = 14).
The 615N, 6°C values and map locations of the deer appear in
Cormie and Schwartz (1994)) while any known diets of the deer
are given in Connie et al. ( 1994b). The percentage of Cq plants in
the deer was determined by linear interpolation and assuming end
point values of -21.5 for an animal consuming 100% C3 plants and
-7.5 for an animal consuming 100% C, plants (Connie and
Schwartz, 1994; above).
Plots of relationships between S15N, SL3C,and six climatic variables, PPTy and PPT [annual and growing season averages of
monthly amounts of precipitation (cm/ma) 1, RHy and RH [annual
and growing season averages of daily (24 h) relative humidities
(% )], and 7’~and T [annualand growing season averages of temperatures (“C)] were visually inspected for any linear or curvilinear
relationships and to identify outlier results. Here, the growing season
is defined as the months of the year in which the average monthly
temperature is >O”C. In addition, we used simple linear regressions
in order to compare 613C and 615N to each of the six variables and
to each other. The climatic variables, given in Cormie et al. (1994b),
are from weather stations near to each deer sampling location and
were obtained from US NOAA (1983) and Environment Canada
( 1979- 1983) publications.
We also examined the relationships between 6”N and 613C and
the climatic variables by conducting stepwise multilinear regression
analyses using the STATPRO statistical package. The methods and
precautions used during such tests are outlined in Cormie et al.
( 1994b). Here, 6 “C and 6 “N were regressed against each other and
against the six predictor, climatic variables plus two transformations
(square and natural log) of each variable. In all, 6 15Nand its transformations (6”N*, and In ]615NI) were each tested against twentytwo predictor variables [S13C), ln 16’3CI, &13CZ,%Cq, PPTy In
PPYy, PPTy2, PPT, In PPT, PPT2, RHy In RHy, RHy’, RH, In
RH, RH’, Ty In T(“K)y, Ty2, T, In T(“K), T’]. Similarly, 613C
and its two transformations were tested against twenty-one predictor
variables (excluding %C,). Transformations were used in these tests
to reduce curvilinearity.
3. RESULTS
z
z
0’
0
8
0
It7
b
0.
0
4
qo
00
0 0
0
3
0 0 o.
0
00,
01
I
0
I
00
0
8 o” o
O
“OA4
I
I
400
O
0
I
800
I
I
I
1200
1600
PM (mm-w’)
FIG. 1.Relationship of S “N to yearly amount of precipitation [ppt
= PPTy * 1201. Results of animals consuming 510% C,
plants are represented by open circles, l l-20% by closed circles,
21-30% by closed triangles and >30% by closed squares.
(mm* yr-‘)
(1) RH (r = -0.748), (2) PPTy (above), (3) PPT (r =
-0.611),
and (4) RHy (r = -0.607) for the fifteen animals
consuming > 10% C4 plants. Eliminating the low S “N, low
pat outlier (QC-8) improves the relationship with PPTy for
the remaining fourteen animals (r = -0.858).
In contrast,
no statistically significant relationships with climate exist for
the forty-four animals consuming 510% C4 plants. Therefore, climate, in general, appears only to be reflected in the
S 15N of deer consuming more C4 plants.
In Fig. 2, data extrapolated from Heaton et al. (1986, Fig.
2c) appears with the subset of fifteen deer from this study
which had consumed > 10% C4 plants. Except for QC-8, our
results on animals consuming greater than 10% C4 plants,
follow the trends shown previously by Heaton et al. ( 1986).
Thus we also find a relationship between 615N and precipitation but only for animals consuming >lO% C4 plants. A
regression of the combined results from Fig. 2 (excluding
QC-8) gives
615N = 12.1 - 0.010. PPTy (mm/yr),
our results to those of Heaton et al.
( 1986), the 6 15N of fifty-nine deer specimen are plotted
against yearly amount of precipitation (PPTy - 120) in Fig.
1. Different symbols represent the amount of C, plants in
the diets of each deer. Open circles represent animals consuming less than 10% Cd, and closed symbols animals consuming more than 10% Cs plants. There is no significant (p
> 0.98) relationship between S’5N and PPTy (r = -0.086)
In order to compare
for the forty-four animals consuming
~10% C, plants despite the large range in yearly precipitation from 180 mm/ yr
to 1560 mm/yr. In contrast, a significant negative correlation
exists (r = -0.675) between 615N and PPTy for a subset of
fifteen animals which consumed more than 10% C4 plants
or with S r3C values greater than -20.1%0. In addition, statistically significant relationships were found between 6 “N and
r=-0.858,
(1)
n=35.
For the subgroup of fifteen deer consuming >lO% Cq
plants, there was a significant, positive correlation between
S 13C and T (r = 0.592). There were no significant correlations between St3C and any climatic variables for the fortyfour animals consuming ~10% Cq plants. However, the
highest correlations in this subset were with amount of rain
and humidity, rather than with temperature: ( 1) PPT (r
= -0.322),
= -0.311),
(2)
PPTy
(r
=
-0.318),
(3)
RHy
(r
and (4) RH (r = -0.294).
For all animals, the multilinear regression model with the
highest correlation shows increasing S15N with decreasing
average annual precipitation, increasing growing season temperature and increasing S 13C:
A. B. Cormie and H. P. Schwartz
0’
0
400
800
1200
1600
ppt (mm-yi’)
FIG. 2. 6 15Nbvs. ppr (mm *yr -’) from this study for white-tailed
deer consuming >lO% Cq plants (Fig. 1) plotted with results on
African mammals as extrapolated from Heaton et al. ( 1986) Fig.
2c. African animals are represented by the letters X (for elephants),
open triangles (for giraffe), open squares (for zebra), and crosses
(for wildebeest).
PPTy - 2.44. T
6”N* = 182 - 22.6.1n
- 50.9.ln
(6’3CJ;
R = 0.538,
There were no significant
any climatic
variables
multilinear
or to 6l’N.
n = 59.
correlations
(2)
of 6 ‘T to
4. DISCUSSION
The correlation between S 13C and Tin this study for animals consuming > 10% C4 plants mirrors previous observa-
tions for grasses (Teeri and Stowe, 1976) where %C, species
among grasses was found to increase with increase in summer temperatures. This provides some support for the Cormie and Schwartz ( 1994) suggestion that animals from drier
areas with high summer temperatures have high 613C due to
some grazing during periods of population and nutrient
stress. Furthermore, consumption of > 10% C4 plants could
indicate substantial consumption of grasses since the proportion of Cq species among grasses is not 100% but varies
from O-82% (Teeri and Stowe, 1976; above).
In contrast, 6°C of the forty-four animals consuming
~~10% Cq plants correlate with rain and humidity, rather
than with temperature and thus, appear to reflect a normal
browsing diet of dicots since the SC, species among dicots
correlates with humidity (Stowe and Teeri, 1978; above).
In North America, the proportions of C, species among
nongrass browse is very low and varies little with climate
(above). Thus, most deer from dry areas consume C3 plants
even when a high proportion of C4 grasses are present. Deer
have high 615N in dry areas only when they diverge from
their usual feeding patterns by consuming C, plants or
grasses. This observation might be accounted for by an interplay of both protein amount and water stress effects. The
animals may have consumed dry adapted plants including
C, plants or grasses which may have low protein content or
quality. Consumption of grasses could further signal that
these deer are in a general state of nutrient deprivation as a
result of food shortages and environmental stress. These deer
may increase quantities of bioavailable nitrogen via a number of possible mechanisms which could increase tissue
615N. Substantial proportions of excreted nitrogen are in the
feces and as nonurea in the urine (cf. Somers, 1961) with
the relative proportions of the excreted forms varying according to diet (cf. Somers, 1961; Livingston et al., 1962;
Epstein et al., 1957; Levinsky et al., 1959). With normal
diets, a steady state condition of isotopic mass balance may
exist between inputs and outputs of nitrogen. However, any
change in the proportions of the various excreted forms vs.
absorbed or recycled nitrogen and/or change in their 6 “N
could alter the isotopic mass balance of the system and,
hence, tissue S15N. Since the urea-diet 615N offset appears
to be more variable that of feces-diet (Steele and Daniel,
1978; Sutoh et al., 1987), factors affecting the urea cycle
may have a larger impact on tissue 6”N. Protein stressed
deer might increase quantities of bioavailable nitrogen
through increased microbial food processing in the rumen
and through increased recycling of nitrogen as urea back
into the rumen both to conserve nitrogen and to enhance
microbial growth. Kinetic isotopic effects which discriminate against 15Ncould take place during production of urea
and/or during filtration by the kidneys (after: Ambrose,
199 1) . Therefore, S 15Nof the excreted urea could decrease
with decrease in (a) the proportion of the substrate nitrogen
converted to urea and/or(b) the proportion of excreted over
conserved urea, both of which could lead to a net increase
in 615N of the retained nitrogen. In ruminants, during each
pass that the nitrogen makes through the urea cycle, escape
of “N-depleted urea into the urine could increase the 15Nof
the conserved nitrogen relative to times when amount of
recycling is lower. Further, since much of the nitrogen entering the urea cycle is from tissue breakdown (Mathews and
Van Holde, 1990), there could be additional contributions
of isotopically heavier nitrogen due to increased rates of
tissue breakdown. The isotopic mass balance of the system
could be altered, for instance, if muscle wasting occurred
but the rate of turnover of bone collagen remained stable
(after: Hobson and Clark, 1992b). Finally, this recycled
nitrogen likely has a higher 6 15Nthan dietary nitrogen. Thus,
any decrease in dietary input relative to recycled nitrogen
could ultimately increase the 6 15Nof nitrogen in the transamination pool. During times of adequate protein intake, the
slower turnover rates of collagen (after: Hobson and Clark,
1992a; Stockwell, 1983; Stenhouse and Baxter, 1976) might
ensure that a record of protein stress remains in the collagen
even if erased in other tissues.
There may also be mechanisms that operate in the gut to
increase 6 15Nof the absorbed nitrogen and decrease S 15Nof
feces. There may be an alteration of intestinal conditions to
favor an increase in the average 615N of microbe protein as
this might depend on available substrate and mix of microbes
(after: Macko et al., 1987; Mathews and Van Holde, 1990;
Steinhour et al., 1982; Sutoh et al., 1987). If the average
615N of microbes were generally higher than substrate nitro-
Effect of climate on isotope composition of N and C in deer bones
gen (cf. Sutoh et al., 1987), an increase in microbial activity
with increased urea recycling might produce the effects described by Sealy et al. (1987), above, or, similarly, might
cause an increase in the proportion of nitrogen absorbed
from microbes as opposed to plants. Alternatively, if some
portion of urea, the microbes or their breakdown products
remain in feces, increased microbial activity with greater
urea recycling might lead to greater removal, via feces, of
15N-depleted nitrogen from urea. Hints of such mechanisms
might be in the elephant data of Table 1 in Vogel et al.
(1990), which shows slightly lower dung-plant and higher
bone-dung S15N offsets in drier areas.
Since deer obtain most of their water from leaves, switching to a diet containing substantial grasses (with potentially
lower water content) could lead to additional water stress.
This along with lower amounts of water in the environment
might produce HzO-stress for these animals for which they
compensate by excreting concentrated urine with increased
loss of “N-depleted nitrogen. Not only could such urea excretion produce an increase in 6”N of retained nitrogen but
it could also increase the need for nitrogen, from microbially
produced protein, from tissue destruction and from recycling.
In this way, both H,O-stress and low protein amount effects
might increase S”N. Both may need to operate simultaneously so that their combined effects can be seen above variability in S 15Ndue to other causes (cf. Connie and Schwartz,
1994). It is also possible that HzO-stress may be the cause
of or occur at the same time as food shortages so the animals
are forced to graze during seasonally arid conditions. This
could produce a coincidental relationship between 615N and
both PPTy and 6 “C in drier areas.
In Fig. 2 there is one outlier result (QC-8) with low 615N
( 1.7%0) despite being from an area of relatively low rainfall
(436 mm). QC-8 is from an area where the animal might
have consumed agricultural crops including corn. This could
increase its S 13Ceven though the animal was not experiencing water or nutrient stress and could lower its S 15N(above).
The three animals with high S”N despite low consumption
of C4 plants (Fig. 1) are from relatively dry areas (SA-1,
ND-l, and OK-5) and thus might still be affected by water
stress effects. In addition, since there are likely to be low
amounts of Cq species among grasses in Saskatchewan (cf.
Teeri and Stowe, 1976), SA-1 could still exhibit low 613C
despite large consumption of grasses.
In contrast with observations for animals consuming
>lO% C4 plants, variability dominates the subset of fortyfour animals consuming ~10% C., plants. Browsers which
consume Cs plants may derive sufficient protein and water
from the leaves they eat so that the mechanisms that function
during times of protein and water stress are turned off and
variability due to other causes dominate. If most herbivores
in the African studies had 613C values >-20.1%0, this might
explain why there appears to be a relationship between 6 “N
and PPTy in those studies but not for the majority of North
American white-tailed deer of this study.
5. CONCLUSIONS
Earlier studies of African mammals showed that 6 15N of
bone collagen was inversely correlated with amount of pre-
4165
cipitation. In contrast, S15N of bone collagen of a majority
(75%) of white-tailed deer from across North America and
over a large range of rainfall amounts (180-1560 mm/yr),
has failed to reveal a correlation between 615N and amount
of precipitation. In North America, C, species make up only
a small fraction of browse, including that from dry areas.
Most deer consume their normal browse of C3 plants even
in dry areas where a high proportion of C4 grasses are present. Deer may be generally adapted to rainfall stress by
consuming C3 plants with high protein and moisture contents. Variability in S15N for these animals is mainly related
to variability in soil 615N at the base of the food chain.
An inverse correlation of 6”N and rainfall is only seen
in a subset of the animals whose collagen 613C values indicate that they consumed > 10% C., plants. In high precipitation areas, some animals may have high 613C associated
with low 6”N through consumption of agricultural crops.
However, in dry areas, we suggest that the tendency to high
615N occurring only in combination with a high C4 diet
indicates consumption of grasses and, thus, nutrient stress
leading to shortages of both protein and water. We suggest
that, in such animals, nutrient and water stress effects operate
together to produce high 615N. The mechanisms involved
may include alterations in both the 6 15Nand the proportions
of various forms of excreted vs. input and recycled nitrogen.
Acknowledgments-We are grateful to the many individuals and the
wildlife agencies, museums, and universities they represent for
kindly collecting and sending us modern deer samples. We sincerely
thank Bob Bowins and Martin Knyf for technical assistance and the
reviewers for their valuable comments. This research was partially
funded by NSERC grants to HPS.
Editorial hurdling: B. E. Taylor
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