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Author's personal copy
Earth-Science Reviews 106 (2011) 131–148
Contents lists available at ScienceDirect
Earth-Science Reviews
j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e a r s c i r ev
Review
The problem of isotopic baseline: Reconstructing the diet and trophic position of
fossil animals
Michelle M. Casey a,⁎, David M. Post b
a
b
Yale University, Department of Geology and Geophysics, P.O. Box 208109, New Haven, CT, 06520–8109, USA
Yale University, Department of Ecology and Evolutionary Biology, Osborn Memorial Laboratory, New Haven, CT, 06520–8106, USA
a r t i c l e
i n f o
Article history:
Received 8 February 2010
Accepted 13 February 2011
Available online 22 February 2011
Keywords:
nitrogen
carbon
food web
time averaging
vertebrate
invertebrate
a b s t r a c t
Stable isotope methods are powerful, frequently used tools which allow diet and trophic position reconstruction
of organisms and the tracking of energy sources through ecosystems. The majority of ecosystems have multiple
food sources which have distinct carbon and nitrogen isotopic signatures despite occupying a single trophic level.
This difference in the starting isotopic composition of primary producers sets up an isotopic baseline that needs to
be accounted for when calculating diet or trophic position using stable isotopic methods. This is particularly
important when comparing animals from different regions or different times. Failure to do so can cause erroneous
estimations of diet or trophic level, especially for organisms with mixed diets. The isotopic baseline is known to
vary seasonally and in concert with a host of physical and chemical variables such as mean annual rainfall, soil
maturity, and soil pH in terrestrial settings and lake size, depth, and distance from shore in aquatic settings. In the
fossil record, the presence of shallowing upward suites of rock, or parasequences, will have a considerable impact
on the isotopic baseline as basin size, depth and distance from shore change simultaneously with stratigraphic
depth. For this reason, each stratigraphic level is likely to need an independent estimation of baseline even within
a single outcrop. Very little is known about the scope of millennial or decadal variation in isotopic baseline.
Without multi-year data on the nature of isotopic baseline variation, the impacts of time averaging on our ability
to resolve trophic relationships in the fossil record will remain unclear. The use of a time averaged baseline will
increase the amount of error surrounding diet and trophic position reconstructions. Where signal to noise ratios
are low, due to low end member disparity (e.g., aquatic systems), or where the observed isotopic shift is small
(≤1‰) the error introduced by time averaging may severely inhibit the scope of one's interpretations and limit
the types of questions one can reliably answer. In situations with strong signal strength, resulting from high
amounts of end member disparity (e.g., terrestrial settings), this additional error maybe surmountable. Baseline
variation that is adequately characterized can be dealt with by applying multiple end-member mixing models.
© 2011 Elsevier B.V. All rights reserved.
Contents
1.
2.
3.
Introduction . . . . . . . . . . . . . . . . . . . . . . . .
1.1.
Two end-member mixing model . . . . . . . . . . .
Materials and methods . . . . . . . . . . . . . . . . . . .
2.1.
Sample collection . . . . . . . . . . . . . . . . . .
2.2.
Sample preparation and stable isotopic analysis . . . .
Results and discussion . . . . . . . . . . . . . . . . . . .
3.1.
Hypothetical food web. . . . . . . . . . . . . . . .
3.2.
Terrestrial ecosystems . . . . . . . . . . . . . . . .
3.2.1.
Sources of variation in terrestrial carbon . . .
3.2.2.
Sources of variation in terrestrial nitrogen . .
3.2.3.
Terrestrial baseline issues in the fossil record .
3.3.
Aquatic ecosystems . . . . . . . . . . . . . . . . .
3.3.1.
Sources of variation in aquatic carbon . . . .
3.3.2.
Sources of variation in aquatic nitrogen . . .
3.3.3.
Aquatic baseline issues in the fossil record . .
⁎ Corresponding author. Tel.: +1 763 229 3126; fax: +1 203 432 3134.
E-mail address: [email protected] (M.M. Casey).
0012-8252/$ – see front matter © 2011 Elsevier B.V. All rights reserved.
doi:10.1016/j.earscirev.2011.02.001
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132
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Author's personal copy
132
3.4.
Diagenesis . .
3.5.
Guidelines for
4.
Conclusions . . . .
Acknowledgements . . .
References . . . . . . .
M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
. . . . . . . . . .
estimating baseline
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1. Introduction
Stable isotopes are powerful tools for investigating the flow of
energy or material through biological systems such as food webs,
because isotopic compositions record information about both source
and processing of that material (Peterson and Fry, 1987). Variation in
the distribution of isotopic signatures of organic and inorganic
materials sets up an isotopic baseline, which can be used to trace
the dietary sources of organisms. The process of biological fractionation modifies this isotopic baseline, during which organisms
differentially use naturally occurring stable isotopes to build organic
tissues. The relatively small biological fractionation of carbon (b1‰)
after photosynthesis makes δ13C useful for tracing the identity and
relative contribution of different diet sources (Deniro and Epstein,
1978; Post, 2002b; McCutchan et al., 2003). The biological fractionation of nitrogen is relatively large (~3.4‰) making δ15N useful for
calculating the trophic position of consumers (Deniro and Epstein,
1981; Vander Zanden and Rasmussen, 2001; Post, 2002b; McCutchan
et al., 2003; Caut et al., 2009). In modern systems, stable isotopic
signatures are used extensively to reconstruct organismal diets and
trophic positions, calculate food-chain length, determine the path of
material through food webs, and examine niche partitioning between
species (Peterson and Fry, 1987; Post et al., 2000; Post, 2002a;
Bearhop et al., 2004; Takimoto et al., 2008; Walters and Post, 2008).
Because stable isotopic signatures of organisms are integrated among
dietary sources consumed at different times of the day or seasons,
these methods complement direct observations like gut content
analysis which records only short time periods preceding capture and
are available only for common, easily captured taxa (Peterson and Fry,
1987; Post, 2002b; McCutchan et al., 2003; Layman and Post, 2008).
Another advantage of stable isotopic methods is their ability to
capture the natural complexity of trophic interactions, such as trophic
omnivory, often missing in simple food chain models (Post, 2002b).
For this reason, stable isotopic trophic methods are now widely
applied to both fossil and living organisms in terrestrial, lacustrine,
and marine settings.
In the field of archeology, stable isotope methods have been
applied to the problem of determining human diet in the past.
Archeologists have used the difference in δ13C between C3 plants and
maize, a C4 plant, to identify the onset of agriculture in human
civilizations (Van der Merwe and Vogel, 1978). This technique was
further developed to examine dietary differences between social
classes (Schurr, 1992), test for links between agricultural intensification and economic or cultural complexity (Schurr and Schoeninger,
1995), and track population migration (Ambrose and Deniro, 1986;
Sealy and Van der Merwe, 1986; Pate, 1995). Subsequent archeological analyses have used the difference in the isotopic baseline of
carbon and nitrogen between terrestrial and marine systems to track
marine supplementation in the diets of ancient humans (Tauber,
1981; Schoeninger et al., 1983) or changes in nitrogen isotopic
signature to determine the age of weaning (Schurr, 1998). Archeologists and paleontologists have applied this technique to vertebrate
organisms to investigate the relative contribution of C3 and C4 plants
to diet (Wang et al., 1994; Macfadden and Cerling, 1996), niche
separation (MacFadden et al., 2004; Feranec and MacFadden, 2006;
Fricke and Pearson, 2008), age of weaning (Rountrey et al., 2007), and
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143
143
144
144
144
trophic structure (Ostrom et al., 1993) in organisms ranging from
dinosaurs to mammals.
Modern ecologists have successfully employed stable isotopic
methods to tackle long-standing questions within ecology. One
particularly lucrative application of stable isotopes is the use of δ15N
signature to calculate food-chain length in a variety of settings. Foodchain length, or the number of trophic levels between primary
producers and top predators within an ecosystem, is of immense
importance to a number of issues within trophic ecology including the
productivity of fisheries, the effects of trophic cascades on ecosystems,
and the bioaccumulation of toxins (Vander Zanden et al., 1999; Post,
2002a; Vander Zanden and Fetzer, 2007; Takimoto et al., 2008;
Walters and Post, 2008). δ15N derived estimates of food-chain length
provide a robust method for testing competing hypotheses for
variation in food-chain length, including resource availability,
ecosystem size, and disturbance (Post, 2002a; Vander Zanden and
Fetzer, 2007; Takimoto et al., 2008; McHugh et al., 2010). Application
of this method to fossil record could provide valuable information on
the nature of food-chain length in ecosystems before anthropogenic
disturbance, or the response of food-chain length to large scale
disturbances such as rapid climate changes or extinction events which
are difficult to recreate experimentally in modern settings.
Another successful application of stable isotopes to a long standing
ecological question was the use of multiple stable isotope tracers to
examine the fate of salt marsh primary productivity in marine food
webs. The extremely productive salt marsh plant Spartina alterniflora
does not appear to support upper trophic levels directly through
grazing, but indirectly as the dominant source of the detritus. The
presence of multiple potential food sources (e.g., phytoplankton, salt
marsh detritus, benthic algae, and upland organic matter) made it
impossible to determine the ultimate source of detrital material using
the isotopic signature of carbon alone. Peterson et al. (1985) were able
to use a combination of carbon, nitrogen, and sulfur stable isotopes to
demonstrate that a large proportion of the diet of ribbed mussels was,
in fact, derived from Spartina detritus. The simultaneous application of
multiple isotopic tracers detailed above has allowed researchers to
map the flow of energy through ecosystems in a quantitative manner
that was previously impossible. Utilization of this method in the fossil
record could further resolve issues of energy flow through different
types of ecosystems (Mae et al., 2007) or changes in energy flow
resulting from natural or anthropogenic ecosystem alterations.
While not an exhaustive list, the above examples demonstrate the
breadth of questions that can be addressed by stable isotopic
methods, some of which, like the ratio of C3 to C4 plants comprising
diet, have been widely and readily applied to fossil taxa while others,
such as food-chain length, have not. All of the above examples could
not be satisfactorily addressed without the use of stable isotopic
techniques and none of these applications could be performed
without an accurate estimation of isotopic baseline or end members
for mixing models. In particular, the salt marsh example highlights the
utility of multiple stable isotope tracers to examine food webs that
contain multiple potential sources of dietary carbon. Both aquatic and
terrestrial ecosystems commonly contain at least two distinct carbon
sources (e.g., littoral and pelagic producers in aquatic systems; C3 and
C4 plants in terrestrial systems) each with distinct δ13C and δ15N
signatures. Therefore, to accurately estimate the trophic position of an
Author's personal copy
M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
organism which feeds on multiple food sources, one must account for
the isotopic difference of the sources and the proportion of the
organism's diet each source constitutes. This is accomplished by
employing multiple end-member mixing models (Phillips, 2001)
which use n isotopic tracers to obtain an estimate of source
partitioning for n + 1 sources before calculating trophic position. For
the sake of simplicity, we will discuss the commonly used two endmember mixing model of Post (2002b). Increasingly complicated
models are necessary to deal with concentration-dependent mixing of
isotopic tracers (Phillips and Koch, 2002), uncertainty in source
isotopic signature (Phillips and Gregg, 2001), and systems including
more than n + 1 sources (Phillips and Gregg, 2003; Moore and
Semmens, 2008; Parnell et al., 2010).
1.1. Two end-member mixing model
By assuming that carbon and nitrogen move through the food web
with similar stoichiometry, mass-balance mixing models calculate the
contribution of each source to a mixture, in this case an organism's
diet (Moore and Semmens, 2008). The following two end-member
mixing model requires measurements of the δ15N and δ13C signatures
of (1) the organism of interest and (2) the base of both food webs
(e.g., littoral and pelagic primary producers) or organisms which
serve as reliable proxies (Post, 2002b):
15
15
15
trophic position¼ λ þ ðδ Nsc −½δ Nbase1 α þ δ Nbase2 ð1−αÞÞ=Δn
ð1Þ
where λ is the trophic position of the baseline proxy taxa (e.g.,
primary producers = 1); δ15Nsc is the nitrogen signature of the
secondary consumer in question; δ15Nbase1 is the nitrogen signature
of the first baseline proxy organism; δ15Nbase2 is the nitrogen
signature of the second baseline proxy organism; α is the proportion
of the secondary consumer's diet derived from base1; and Δn is the
mean trophic fractionation or discrimination per trophic transfer. The
mean Δn is approximately 3.4‰ (Deniro and Epstein, 1981; Minagawa
and Wada, 1984; Vander Zanden and Rasmussen, 2001; Post, 2002b;
McCutchan et al., 2003; Vanderklift and Ponsard, 2003; Barnes et al.,
2007). α is calculated using δ13C as:
13
13
13
13
α ¼ ½δ Cbase2 −ðδ Corg þ Δc torg Þ=ðδ Cbase2 −δ Cbase1 Þ ð2Þ
where δ13Corg is the carbon signature of the secondary consumer of
interest, Δc is the trophic fractionation of δ13C, torg is the trophic
position of the organism of interest, δ13Cbase1 is the carbon signature
of the baseline proxy organism for base1, and δ13Cbase2 equals the
carbon signature of the baseline proxy organism for base2. The trophic
fractionation of δ13C is typically assumed to be 0‰ thus removing the
term Δctorg (Deniro and Epstein, 1978; Vander Zanden and Rasmussen, 2001; Post, 2002b; McCutchan et al., 2003; Barnes et al., 2007;
Caut et al., 2009).
A number of other factors besides diet and trophic position can
affect the measured isotopic signatures of organisms and the amount
of individual variation within a species (Gannes et al., 1997;
McCutchan et al., 2003; Martinez del Rio et al., 2009). Observed
differences between the whole body isotopic signature, or that of bulk
diet, and specific tissues can be due to compositional differences
(Tieszen and Farge, 1993; Gannes et al., 1997) or isotopic routing
(Schwarcz, 1991; Martinez del Rio et al., 2009; Kelly and Martinez del
Rio, 2010). Isotopic routing occurs when the building blocks of certain
tissues are assimilated exclusively from a single food source
(Schwarcz, 1991). This process can confound dietary interpretations
by creating tissues whose isotopic signature does not reflect that of
the organism's bulk diet (Gannes et al., 1997; Martinez del Rio et al.,
2009). Compositional differences can be related to differences in
tissue type (e.g., muscle versus mantle tissue in molluscs) or
133
differences in lipid content. Because lipids are depleted in 13C relative
to carbohydrates and proteins, variations in lipid content can greatly
impact the carbon isotopic signature of organisms with essentially the
same diet (McConnaughey and McRoy, 1979; Post et al., 2007).
Uncertainty can be introduced by analytical error, though careful
attention to laboratory methodologies have been shown to markedly
reduce error (Jardine and Cunjak, 2005; Coplen et al., 2006; Mill et al.,
2008). These caveats are discussed extensively elsewhere and are not
the focus of this paper. Finally, when working with fossil organisms
one must consider problems regarding the indigeneity of isotopic
signatures which may have been altered by diagenesis. Considerable
work has been conducted in this area for fossil molluscs (Serban et al.,
1988; Macko et al., 1991; Engel et al., 1994; Qian et al., 1995) and
vertebrates (Ostrom et al., 1990, 1994). For more information on
dealing with diagenesis see Section 3.4 below. Each of these issues can
influence the reliability of the baseline or end member used to
estimate diet or trophic position.
Here we synthesize a combination of published and original data
from modern ecosystems to outline and discuss problems of baseline
and end member variation unique to paleontology. To do so, we will
tackle the following issues: 1) What are the causes and magnitudes of
baseline and end member variation in modern ecosystems? 2) What
sources of baseline and end member variation are of greatest concern
in the fossil record? 3) How does baseline and end member variation
introduce error into our estimates of diet and trophic position of fossil
organisms? 4) How can we account for baseline and end member
variation in our estimates of diet and trophic position? And finally, 5)
In what situations is the problem of baseline and end member
variation insurmountable for paleontological studies? Admittedly, the
number of complications increases when extending modern stable
isotopic methods into the fossil record, but so too do the number of
compelling opportunities to explore trophic interactions on timescales and within contexts not available to modern ecologists. The
fossil record provides a natural laboratory for examining the
replicated effects of large-scale physical, climatic, and anthropogenic
changes on factors like diet, trophic position, food-chain length, and
energy or material flow through food webs.
2. Materials and methods
While the bulk of the data presented in this review comes from the
published literature, a small amount of original data has been
included for the unique insights it affords the study of baseline
variation across multiple years in a single study locality, season, and
set of test organisms.
2.1. Sample collection
Living bivalves and gastropods were collected from the same
Milford, CT beach at the end of August in 2006, 2007, 2008, and 2009.
Species found include Mercenaria mercenaria (quahogs), Littorina
littorea (periwinkles), Ilyanassa obselta (mud snails), Geukensia
dessimus (ribbed mussels), Mytilus edulis (blue mussels), Neverita
duplicata (northern moon snail), and Urosalpinx cincera (oyster drills).
2.2. Sample preparation and stable isotopic analysis
Live animals were frozen in a − 60 °F freezer and thawed prior to
dissection. Whole body soft tissues were removed from the shells,
cleaned in deionised water, and digestive tracts squeezed to remove
undigested particles. Soft tissues were then dried in a 40 °C oven for 3
to 5 days and ground using a porcelain mortar and pestle. Whole body
samples were weighed out to 1 mg and placed in tin capsules. All
samples were analyzed on a Thermo Finnigan DeltaPlus Advantage
with Costech EA at the Yale Institute for Biospheric Studies (YIBS)
Earth Systems Center for Stable Isotopic Studies (ESCSIS). The
Author's personal copy
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M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
standard deviation of replicated animal standards (trout) within a
tray ranged between 0.02‰ and 0.24‰ for δ13C and 0.01‰ and 0.04‰
for δ15N. All isotopic signatures are expressed in standard per mil
notation:
δX ¼ ½ðRsample =Rstandard Þ−1 1000
ð3Þ
Standard reference is Pee Dee Belemnite for carbon and the
atmosphere for nitrogen. Carbon isotopic signatures of all animals
were lipid corrected after Post et al. (2007) using the following
relationship between C:N ratio and δ13C change due to lipid content:
13
13
δ Ccor ¼ δ Cuncor þ 0:99 ½C=Nratio−2:5
ð4Þ
Trophic position was estimated using the two end-member mixing
model of (Post, 2002b) detailed above with a Δn value of 3.4‰.
3. Results and discussion
3.1. Hypothetical food web
We start our discussion of baseline with a hypothetical example of
an extremely simplified terrestrial African ecosystem with C3 trees
and shrubs and C4 grasses forming the base of the food web. In
general, C3 plants have an average δ13C value of −27‰ and range
from −20‰ to − 35‰, while C4 plants average around −12‰ but
range from −11 to − 15‰ (Dawson et al., 2002). In this example
(Fig. 1a), C3 browse has a δ13C value of − 28‰ and the C4 grasses have
a δ13C value of −15‰. Antelopes, which are mixed grazers and
browsers, feed on both types of primary producers equally (50:50 diet
or α = 0.5) giving them an intermediate δ13C signature of − 21.5‰
assuming no trophic fractionation of carbon. Changes in this value
could yield valuable information on the changing dietary proportion
of the antelope's diet coming from C3 versus C4 plants (α) resulting
from behavioral, environmental, or evolutionary variation. For
instance, if the antelope switched to feed exclusively on C3 plants
(100:0 diet or α = 1.0), then its δ13C signature should be −28‰
(Fig. 1a). Feeding on the antelope are carnivorous lions and
omnivorous jackals. We assume that the omnivorous jackals feed
equally on antelopes and the berries and fruits of C3 plants giving
them a δ13C signature of − 24.75‰. We further assume that they do
not eat C4 plants so that changes in the value of δ13C reflect changes in
the dietary proportions of C3 plants and meat. The carnivorous lions
feeding exclusively on antelopes would have a δ13C signature of
−21.5‰, again assuming no trophic fractionation of carbon. Changes
in this value could result from the lions feeding on additional types of
prey or from changes in the δ13C of antelopes.
The δ13C values of C3 and C4 plants are not constant, however, in
nature. The δ13C signature of plants is affected by a myriad of factors
including water stress, soil moisture, humidity, irradiance, temperature, nitrogen availability, salinity, and the concentration of CO2 in
the atmosphere (Dawson et al., 2002). Variation in the δ13C values at
the base of the food web propagate up through all of the trophic
levels and might be incorrectly attributed to changes in diet or
climate by researchers only measuring the δ13C signature of their
organisms of interest. This is why it is so important to measure all
three variables in equation 2 (δ13Corg, δ13Cbase1, and δ13Cbase2) either
directly or by using proxies, especially when comparing across
ecosystems or ecological gradients. Failure to account for differences
in baseline can result in erroneous interpretations and a reduced
signal to noise ratio (Phillips and Gregg, 2001; Post et al., 2007). We
examine these effects in detail by returning to the hypothetical
example (Fig. 1).
In the original example (Fig. 1a), the disparity of the two end
members (or the difference between δ13C values of C3 and C4 plants)
is relatively large—13‰. An antelope with 100% of its diet coming
from C3 plants has a δ13C signature of − 28‰ versus an antelope
which feeds equally on C3 and C4 plants has a δ13C signature of
−21.5‰ (Fig. 1a). In this large end-member disparity scenario, a 50%
change in diet leads to a change of −6.5‰ in δ13Corg, while a 10% shift
in diet would yield a 1.3‰ difference in δ13Corg. As the isotopic
signatures of the end members vary within their established ranges,
Fig. 1. Hypothetical food web showing carbon isotopic compositions of C3 and C4 plants, herbivorous antelopes, omnivorous jackals, and carnivorous lions. a: Large end member
disparity scenario in which C3 and C4 plants differ by 13‰. b: Small end member disparity scenario in which C3 and C4 plants differ by 5‰.
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M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
the end-member disparity increases and decreases. A decrease in end
member disparity will decrease the change in δ13Corg expected for a
given change in α, or dietary proportion, decreasing the ability to
resolve changes in α relative to background noise (Phillips and Gregg,
2001; Post et al., 2007) caused by analytical error, variation in lipid
content, etc. Consider an expanded example involving a fundamentally similar food web where C3 and C4 plants have δ13C values of
−20‰ and − 15‰, respectively, giving it an end-member disparity of
only 5‰. In this example, the 50% change in dietary fraction (same as
above) results in a change of the δ13C signature from −17.5‰ to
−20‰ (Fig. 1b), a difference of only − 2.5‰. A 10% change in dietary
fraction would result in only 0.5‰ change in δ13C which can be very
difficult to discern within the limits of standard analytical error
(typically 0.2–0.4‰ for δ13C).
Failure to account for changes in isotopic baseline can also lead to
erroneous interpretations when comparing animals from different
locations or times. For example, the difference in δ13C between the
50:50 diet antelope in the first example where end member disparity was
large (Fig. 1a) and the 100:0 diet antelope in the second, small end
member disparity example (Fig. 1b), is only 1.5‰. If one used the end
member values from the Fig. 1a example (C3 = −28‰, C4 =−15‰) to
calculate the dietary proportion (α) of the 100:0 diet antelope from
Fig. 1b, then the +1.5‰ difference would be incorrectly calculated as a
12% increase in the proportion of C4 plants in the antelope's diet
(α =0.38) rather than the true 50% dietary increase in C3 plants
(α =1.0). Not only would the magnitude of the change be drastically
underestimated, but also the sign of the change would be the opposite of
our expectation for an increase in the consumption of C3 plants.
Researchers run the risk of encountering this problem any time they
use the same baseline value for multiple samples from different locations
or across millions of years.
Mixed diets make it important to use a multiple end-member
mixing model to calculate trophic position, because simply assuming
that nitrogen signature is a perfect index of trophic position can be
misleading. For example, the C3 and C4 plants in our hypothetical food
135
web (Fig. 2) have different δ15N signatures. The C3 browse has a δ15N
value of 10.5‰. If we assume that the antelope is consuming 100% C3
plant material, the food web is actually a single-source food chain
(Fig. 2a). In a single-source food chain, the nitrogen signature of any
given trophic level is easily predicted by simply adding Δn (which we
assume to be 3.4‰) to every full trophic level increase: herbivorous
antelope = 13.9‰, omnivorous jackal = 15.6‰, and carnivorous
lion = 17.3‰. If instead we assume the antelope consumes equal
portions C3 and C4 plant material and the C3 and C4 plants have
different δ15N signatures (e.g., C4 grasses have a δ15N value of 3‰,
Fig. 2b) then nitrogen signatures of upper trophic levels depend on
the proportion of the diet each source constitutes (α) and Δn. The
difference in δ15N between C3 and C4 plants in the multiple-source
example (Fig. 2b) is 7.5‰ (or roughly equal to two trophic levels
worth of nitrogen variation). The values in this example are based on
observed values from the work of Shearer et al. (1983). An antelope
with a diet of 50:50 C3 and C4 plants would have a δ15N signature of
10.15‰. This change in antelope signature would propagate up
through the food web changing the jackal's nitrogen signature to
13.73‰, and the lion's nitrogen signature to 13.55‰. The resulting
difference in the nitrogen signature of the jackal from 15.6‰ in the
single-source example to 13.73‰ in the multiple-source food web
could be attributed incorrectly to a decrease in trophic position of the
jackal and an increase in the proportion of plants in the diet without
proper consideration of baseline. Application of the two end member
mixing model described above to this situation would accurately
calculate the omnivorous jackal's trophic position as 2.5 in both cases.
If the δ15N values of the primary producers in Fig. 2b were reversed
(C3 = 3.0‰, C4 = 10.5‰) the 50:50 diet antelope would retain the
same δ15N value of 10.15‰ but the δ15N value of the jackal would
become 9.98‰. In this example the δ15N value of the jackal is lower
than that of the antelope even though the jackal occupies a higher
trophic position. Not only is δ15N not trophic position in these
examples, but the rank order of animals based solely on δ15N values
may not properly correspond to the trophic hierarchy.
Fig. 2. Hypothetical food web showing nitrogen isotopic compositions of C3 and C4 plants, herbivorous antelopes, omnivorous jackals, and carnivorous lions. a: Single source food
web. b: Multiple source food web.
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3.2. Terrestrial ecosystems
The example above demonstrates the necessity of measuring the
carbon and nitrogen isotopic signatures of all carbon sources at the
base of the food web in order to quantify the absolute values,
disparity, and variation of dietary end members. Baseline issues were
first recognized in aquatic systems where researchers have invested
more time and energy determining their causes and effects. Here we
summarize the available literature exploring the causes of isotopic
variation in carbon and nitrogen in modern terrestrial ecosystems
(Table 1) to help infer decisions about end member disparity and
baseline. Then we place this review of modern ecosystems into the
context of the unique problems this variation poses when working in
the fossil record.
3.2.1. Sources of variation in terrestrial carbon
Differences in the carboxylation reactions between the C3 and C4
photosynthetic pathways create differences in the δ13C signatures of
C3 and C4 plants (O'Leary, 1981; O'Leary, 1988; Marshall et al., 2007),
Table 1
Factors known to affect the isotopic composition of terrestrial baselines. A factor is
positively correlated with isotopic signature if an increase in that factor leads to an
increase (enrichment) in δ15N or δ13C values.
Factor
Terrestrial carbon
Stomatal
density
Branch
length
Canopy height
Leaf size
Leaf thickness
Salinity
Correlation Reference
−
Hultine and Marshall (2000)
+
Panek and Waring (1995)
+
+
+
−
Yoder et al. (1994)
Geber and Dawson (1990)
Vitousek et al. (1990)
(Bowman et al., 1989; Sandquist and
Ehleringer, 1995)
(Dawson et al., 2002; Swap et al., 2004)
(Stewart et al., 1995; Williams and Ehleringer,
1996; Schulze et al., 1998; Van de Water
et al., 2002; Swap et al., 2004; Liu et al., 2005;
Roden et al., 2005; Schulze et al., 2006)
Welker et al. (1993)
Ehleringer et al. (1986)
(Bowman et al., 1989; Hogberg et al., 1993;
Guehl et al., 1995)
(Ehleringer and Cooper, 1988; Chen et al., 2005,
2007a,b)
(Knight et al., 1995; Sparks and Ehleringer, 1997;
Cordell et al., 1999; Hietz et al., 1999;
Van de Water et al., 2002; De Lillis et al., 2004;
Townsend-Small et al., 2005; Li et al., 2007)
(Beerling et al., 1993; Bettarini et al., 1995;
Berry et al., 1997; Polley et al., 2002;
Aranjuelo et al., 2008)
Humidity
−
Mean annual −
rainfall
Temperature
Irradiance
Nitrogen
availability
Soil moisture
−
+
+
Elevation
+
CO2
−
+
Terrestrial nitrogen
Nitrogen
−
fixation
Denitrification +
Ammonia
+
volatilization
Nutrient
+
availability
Temperature
+
Aridity
+
pH
+
Rainfall
−
Soil maturity/
depth
Clay content
+
Altitude
+
Land use
+
+
(Deniro and Hastorf, 1985; Ambrose, 1991)
(Shearer and Kohl, 1986; Ambrose, 1991)
(Shearer and Kohl, 1986; Ambrose, 1991)
Swap et al. (2004)
(Bate, 1981; Granhall, 1981; Ambrose, 1991)
(Bate, 1981; Granhall, 1981; Ambrose, 1991)
Ambrose (1991)
(Shearer et al., 1978; Mariotti et al., 1980;
Ambrose, 1991; Swap et al., 2004)
(Shearer and Kohl, 1986; Vitousek et al., 1989;
Ambrose, 1991)
(Shearer and Kohl, 1986; Vitousek et al., 1989;
Ambrose, 1991)
(Shearer et al., 1978; Mariotti et al., 1980;
Ambrose, 1991; Swap et al., 2004)
Aranibar et al. (2008)
which have a mean δ13C of −27‰ and −12‰, respectively (Dawson
et al., 2002). There is considerable variation around these means with
C3 plants exhibiting more variation than C4 plants (Schulze et al.,
1998). For example, in Namibia, C3 plants range between −26.04‰
and −21.28‰ while C4 plants range between −13.9‰ and − 12.2‰
(Schulze et al., 1976). Within leaves, the δ13C signature is controlled by
the amount of available CO2 and the δ13C of atmospheric CO2. Increases
in the concentration of CO2 in the atmosphere from the burning of
fossil fuels have caused plant, animal, and atmospheric δ13C values to
decline (Bettarini et al., 1995; Ehleringer and Cerling, 1995; Cerling
and Harris, 1999; Williams et al., 2001; Long et al., 2005). The
availability of CO2 within the leaf controls the amount of discrimination that takes place, lower concentrations of CO2 lead to less
discrimination and more positive δ13C values. The discrimination
against 13C by the enzyme Rubisco during carboxylation sets the
fractionation factor for C3 plants while the ratio of intercellular to
atmospheric CO2 concentrations determines the extent to which that
fractionation is expressed. The CO2 concentration in leaves is
controlled by the relative rates of supply, or the opening of the leaf
stomata, and demand, or net assimilation (Farquhar et al., 1982;
Brugnoli et al., 1988). Opening of leaf stomata can lead to evaporation
and water loss so stomatal conductance is also affected by the plant's
water use (Swap et al., 2004). The δ13C signature of leaves can,
therefore, be impacted by a myriad of factors (see Table 1) that affect
water usage, supply, transport or loss (Dawson et al., 2002). For
example, the δ13C signature of leaves becomes more negative with
morphological changes including increasing stomatal density (Hultine
and Marshall, 2000), decreasing branch length (Panek and Waring,
1995), decreasing canopy height (Yoder et al., 1994), decreasing leaf
size (Geber and Dawson, 1990), and decreasing leaf thickness
(Vitousek et al., 1990). The δ13C signature of leaves is negatively
correlated with environmental factors such as salinity (Bowman et al.,
1989), humidity (Dawson et al., 2002; Swap et al., 2004), mean annual
rainfall (Swap et al., 2004), and temperature (Welker et al., 1993) and
positively correlated with irradiance (Ehleringer et al., 1986), nitrogen
availability (Bowman et al., 1989; Hogberg et al., 1993; Guehl et al.,
1995), and soil moisture (Ehleringer and Cooper, 1988). Genetic
factors can also influence plant δ13C (Dawson et al., 2002). The fact that
not all of these factors are independent means that the δ13C values of
plants may or may not correlate strongly with environmental
characteristics (e.g., altitude, latitude, temperature, and rainfall) in a
predictable manner (Comstock and Ehleringer, 1992). A number of
good studies exist which detail the shift in δ13C along different types of
gradients in different geographical areas (for a good review see
Marshall et al., 2007).
3.2.2. Sources of variation in terrestrial nitrogen
Unlike δ13C, the photosynthetic pathway of a plant does not
determine its δ15N signature. Instead the nitrogen signature of plants
is controlled by the balance of atmospheric fixation, denitrification,
and volatilization of ammonia within the soil (Shearer and Kohl, 1986;
Ambrose, 1991; Evans, 2007). As a result, the disparity in nitrogen
signatures of terrestrial plants is smaller than that for carbon and
complicated by the fact that the mean isotopic signatures are not
consistent. Aranibar et al. (2008) found the nitrogen signatures of C3
plants in Africa ranged between ~ 9.5‰ and ~ 3.5‰ while the nitrogen
signatures of C4 plants ranged between ~ 6.0‰ and ~ 3.0‰. Not only do
these ranges overlap, but the plant type with the greatest nitrogen
signature was not consistent (C3 N C4 in 4 of 6 cases versus C3 b C4 in 2
of 6 cases). Ambrose (1991) and Shearer et al. (1983) highlight the
large among-habitat variation in the δ15N signatures of plants ranging
from +3.0‰ to +13.0‰. In general, nitrogen fixers have lower δ15N
values than non-fixers (Deniro and Hastorf, 1985; Ambrose, 1991).
Denitrification and volatilization of ammonia increase nitrogen enrichment in soils (Shearer and Kohl, 1986; Ambrose, 1991). Increased
nutrient availability also increases nitrogen enrichment (Swap et al.,
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3.2.3. Terrestrial baseline issues in the fossil record
Using the modern mean isotopic signatures of C3 and C4 plants for
trophic or diet analysis in the fossil record is problematic because it may
not accurately reflect the mean isotopic values of the plants from the
time and place which you are studying. This could be due to any number
or combination of factors listed above. In particular, large shifts in the
concentration of CO2 in the atmosphere that have occurred over
geologic time have impacted the δ13C values of past plants and animals.
The change in atmospheric composition from the 1960s to the late
1990s resulted in a ~0.8‰ decrease in the δ13C of the atmosphere, a
~1.4‰ decrease in the δ13C signature of plants, and a ~1.0‰ decrease in
δ13C signature of primary consumers such as wildebeest (Cerling and
Harris, 1999). While the consequences of this change in CO2
concentration are potentially large and wide-ranging, this increase is
small relative to the magnitude of past changes in the atmospheric
concentration of CO2 (Royer et al., 2007). Long et al. (2005) and Cerling
and Harris (1999) have explicitly addressed the need to correct for
anthropogenically induced variation in atmospheric δ13C for samples
which span ~130 years but it is also important to control for much larger
natural variations in atmospheric δ13C over geologic timescales when
working with fossil taxa. Furthermore, the mean isotopic value of C3 and
C4 plants for a given geographical area or time period may not be
sufficient to accurately resolve the diets and trophic positions of fossil
animals because variation around those means decreases the signal to
noise ratio and makes patterns more difficult to resolve as demonstrated
in the first example food web (Fig. 1). Both of these problems could be
overcome through the application of a multiple end member mixing
model and an accurate estimate of isotopic baseline.
Averaging over time and space of fossil deposits is another
important concern. The transport and accumulation of animal
remains by predators, scavengers, or rivers mix together animals
from large geographic areas and long time spans (Behrensmeyer,
1991). Scavengers can transport remains several kilometers
(Behrensmeyer, 1991) potentially mixing individuals from multiple
habitats along numerous ecological gradients relevant to isotopic
signature (e.g., openness, altitude, rainfall, nutrient availability,
etc.). Modern estimates of time averaging for fluvial fossil deposits
range from 102 to 104 years (Behrensmeyer, 1982). Astronomically
driven climate change operates on the scale of 104–106 years (Hays
et al., 1976) sometimes causing extreme change in less than
10,000 years (Berger, 1988). These changes in climatic regime could
affect numerous factors regulating the isotopic signature of plants
listed above (e.g., temperature, rainfall, soil moisture, and floral
composition). This means that the isotopic baseline may differ not
only from fossil locality to locality but from organism to organism
within a single deposit. Whereas time averaging within deposits is
problematic, the time averaging that occurs within organisms, due
to the spatial and temporal integration of dietary signatures into
bones, helps mitigate the variation seen on short timescales (e.g.,
seasonal or yearly) but will not be sufficient to alleviate problems
associated with the mixing of individuals on millennial times scales.
Often, interesting paleoecological questions involve comparison
of diet or trophic characteristics of animals across habitats or
geographic regions. In some cases it is necessary to combine
specimens from different latitudes, altitudes, or habitats in order to
reach acceptable sample sizes due to rareness of a particular taxon
or a dearth of fossiliferous localities of a given age. Accounting for
differences in baseline is crucial to avoid misinterpretations when
comparing the isotopically derived diets or trophic positions of
individuals from multiple locations (see example above) in the
modern (Post et al., 2000; Post, 2002b). The isotopic baseline is
likely variable enough to warrant separate measurements of
isotopic baseline from multiple locations within a single time
slice no matter how well resolved. One needs to account for
differences in baseline in each new locality (even within the same
time period) and each new time period (even within the same
locality). It may be very difficult to account for isotopic baseline in
deposits with large amounts of time averaging due to the difficulty
of identifying a reliable proxy (see discussion of proxies below). If
reliable proxies cannot be identified, the result will be uncertainty
surrounding the signal to noise ratio of a given data set. When end
member disparity is high, as is the case for the difference in δ13C
between C3 and C4 plants in most terrestrial environments, and the
observed change in isotopic signature is large (N1‰), signal
strength can be assumed to be high and a moderate amount of
noise introduced through baseline variation may be acceptable
(Fig. 3). Where the signal to noise ratio is low, analyzing a large
number of samples may be necessary to resolve trophic relationships. Where the observed change in isotopic signature is small
(b1‰) and the amount of noise introduced through baseline
variation is uncertain, there will be limited scope for resolving
dietary and trophic differences.
3.3. Aquatic ecosystems
Carbon isotopic signature cannot be reliably used to distinguish
plants using C3, C4, or CAM photosynthetic pathways in aquatic
systems as it is in terrestrial systems (Keeley and Sandquist, 1992).
16
14
End member disparity (‰)
2004). Plants with nutrient demands which exceed supply show little to
no nitrogen discrimination (Marshall et al., 2007). These processes are
influenced by numerous environmental variables. Hot, arid soils inhibit
atmospheric N fixation (Bate, 1981; Granhall, 1981; Ambrose, 1991) and
are characterized by more open nutrient cycling (Swap et al., 2004)
resulting in higher δ15N values. Conversely, nitrogen signatures decrease
with increasing rainfall (Shearer et al., 1978; Mariotti et al., 1980;
Ambrose, 1991; Swap et al., 2004) and in cooler, moister soils due to
increased N fixation and mineralization rates (Ambrose, 1991). High pH
accelerates ammonia volatilization, increasing δ15N values. Soil δ15N also
increases with increasing soil maturity or depth, increasing clay content
relative to sand or silt (Shearer and Kohl, 1986; Vitousek et al., 1989;
Ambrose, 1991), increasing altitude (Shearer et al., 1978; Mariotti et al.,
1980; Ambrose, 1991; Swap et al., 2004), and increasing intensity of land
use such as cattle grazing (Aranibar et al., 2008). These environmental
factors may also affect Δn. The δ15N signature of herbivores decreases
with increasing rainfall more than would be expected if the parallel
pattern in plants was the sole cause (Heaton et al., 1986; Sealy et al.,
1987; Ambrose, 1991) however the mechanism for this change in Δn
remains unclear.
137
25
50
12
10
100
8
6
50
25
4
150
200
100
300
2
0
1
2
3
4
5
6
7
8
400
9
10
Noise (‰)
Fig. 3. The percent error introduced into a two-end member mixing model (isoclines)
as a function of the amount of analytical noise (stemming from failure to account for
lipid content or variation in end member signatures) and the end member disparity.
Percent error was calculated from 100 Δδ13C / (δ13Cbase1 × δ13Cbase2). Redrawn from Post
et al., 2007.
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Instead, the δ13C signatures of aquatic plants are dictated by
differences in boundary layer effects between littoral and pelagic
primary producers in lakes and estuaries (France, 1995a,b) or
between pools and riffles in streams (Finlay et al., 2002). Due to the
high diffusion resistance of CO2 in water, littoral plants are effectively
using a finite pool of dissolved CO2 from within the boundary layer.
Reduced turbulence surrounding littoral plants leads to thicker
boundary layers, decreased discrimination, and enriched δ13C values
(Keeley and Sandquist, 1992; France, 1995a) creating similar patterns
in both streams (riffles versus pools) and estuaries (nearshore versus
open water). The average enrichment of littoral primary producers
relative to pelagic primary producers is approximately 7‰ in lakes
and 6‰ in marine systems (France, 1995a). In aquatic systems the end
member disparity in a given ecosystem, or the amount of littoral
enrichment, is relatively constant (Fig. 4) while the absolute isotopic
values of littoral and pelagic primary producers are highly variable
among localities (Post, 2002b) and influenced by numerous physical
and chemical factors (Table 2). This is in contrast to terrestrial
ecosystems where the global mean isotopic signatures of C3 and C4
plants was constant and end member disparity was determined by
observed variation around those means.
Differences in isotopic baseline are generally more problematic in
aquatic systems than in terrestrial systems. First, the end member
disparity, or signal strength, is smaller in aquatic systems (~ 6–7‰)
compared with terrestrial systems (~15‰). Second, the global ranges
of carbon isotopic signature for littoral and pelagic plants overlap
entirely, though the two end members do not overlap within most
single lake ecosystems. For instance, Post (2002b) found that in any
single lake the mean difference between littoral and pelagic was ~6–7‰,
but that the δ13C signature varied between −14‰ and −28‰ for
littoral producers and −20‰ and −34‰ for pelagic producers among
lakes. This is also true of in nearshore marine settings where littoral
producers varied between −5‰ and −29‰ with a mean value of
−17‰ and pelagic producers varied between −17‰ and −31‰ with a
mean of −22‰ (France, 1995a). Pelagic producers range between
−10‰ and −31‰ in the open ocean (Degens et al., 1968). Finally,
Vander Zanden and Rasmussen (1999), working in lakes in Canada,
found evidence for a third isotopically distinct food source where the
littoral baseline = −23.8‰, the pelagic baseline= −28.4‰, and the
profundal baseline= −30.5‰.
Aquatic ecosystems also show great variability in the isotopic
baseline of nitrogen. The δ15N signature of freshwater particulate
organic matter (POM) ranges globally between −2.5‰ and 13.6‰
(Post, 2002b; Gu, 2009). In the marine realm, δ15N values of POM range
between approximately −3‰ and +10‰ with rare values of ≥20‰
(Owens, 1987). Post (2002b) shows the δ15N signatures of unionid
mussels from Keuka Lake and Cross Lake in New York (Fig. 5). The δ15N
-10
Littoral
13C
base
-15
-20
-25
-30
-35
100
Pelagic
101
102
103
104
105
106
107
Lake Area (ha)
Fig. 4. The relationship between lake size and δ13C value for both pelagic and littoral
primary producers from 25 lakes in eastern North America. Absolute isotopic values are
extremely variable while disparity of littoral and primary producers remains relatively
constant at ~ 4–8‰. Redrawn from Post, 2002b.
Table 2
Factors known to affect the isotopic composition of the aquatic baselines. A factor
is positively correlated with isotopic signature if an increase in that factor leads to
an increase (enrichment) in δ15N or δ13C values.
Factor
Correlation Reference
Aquatic carbon
Size
?
Growth rate
(seasonality)
Concentration
DIC
p C O 2
atmosphere
Temperature
−
(Gearing et al., 1984; Rau et al., 1990;
Wainwright and Fry, 1994)
(Wienke and Fisher, 1990; Fry and
Wainright, 1991)
(Smith and Walker, 1980; Goericke and Fry, 1994)
−
(Fogel and Cifuentes, 1993)
+
+
Light intensity
+
Lake size
Depth
Latitude
Aquatic nitrogen
Growth rate
(seasonality)
Concentration
DIN
Denitrification
+
−
−
(Sackett et al., 1965; Rau et al., 1991;
MacLeod and Barton, 1998; Rullkötter, 2006;
Michener and Kaufman, 2007)
(Wienke and Fisher, 1990; MacLeod and
Barton, 1998)
(Post, 2002b; Bade et al., 2004; Gu, 2009)
(Rau, 1978; Rau, 1980; Fry and Wainright, 1991)
(Rau et al., 1982; Rau et al., 1990)
+
Gu (2009)
−
(Miyake and Wada, 1967; Wu et al., 1997)
+
Nitrification
Nitrogen
fixation
Anthropogenic
input
±
−
Temperature
+
Depth
±
Connection
to ocean
+
Latitude
Light intensity
Number of
trophic levels
Distance
offshore/
salinity
Lake size
+
+
−
(Owens, 1987; Bickert, 2006; Montoya, 2007;
Gu, 2009)
(Lehmann et al., 2004; Syvaranta et al., 2008)
(Hoering and Ford, 1960; Delwiche and Steyn,
1970; Montoya, 2007)
(Cabana and Rasmussen, 1996;
Carpenter et al., 1998; Vander Zanden and
Rasmussen, 1999; Jennings and Warr, 2003;
Anderson and Cabana, 2005; Savage, 2005;
Leavitt et al., 2006; Xie et al., 2007)
(MacLeod and Barton, 1998; Jennings and
Warr, 2003)
(Mullin et al., 1984; Checkley and Entzeroth, 1985;
Owens, 1987; Checkley and Miller, 1989; Altabet
and Small, 1990; Montoya et al., 1992; Wu et al.,
1997; Post, 2002b; Jennings and Warr, 2003)
(Owens, 1987; Bilby et al., 1996;
Ben-David et al., 2004; Michener
and Kaufman, 2007)
Gu (2009)
MacLeod and Barton (1998)
(Minagawa and Wada, 1984; Fry, 1988;
Montoya, 1994; Wu et al., 1997)
(Wu et al., 1997; Jennings and Warr, 2003)
+
−
+
(Gu et al., 1994; Post, 2002b; Gu et al., 2006; Gu,
2009)
signatures of unionid mussels in Cross Lake are approximately 7‰
(roughly equal to two trophic levels) higher than those in Keuka Lake
even though they are both primary consumers and occupy the same
trophic level. Without accounting for baseline, the mussels in Cross Lake
appear to be eating fish when compared to the mussels from Keuka
Lake. This example highlights the importance of accounting for baseline
differences when comparing among environments, even those within a
single region or climatic regime. Furthermore, because of the difference
in number of sources, source identity, and the amount of isotopic
disparity between sources among aquatic systems mussels and snails
may not always be the most suitable baseline proxies available. It may be
necessary to take a few pilot samples in order to determine the best
means of accounting for baseline in each system (Michener and
Kaufman, 2007). It is also important to consider the amount of temporal
and spatial variability your baseline proxies must account for given the
organism of interest and natural history of each individual system (Post,
2002b).
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M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
15
Unionid Mussels
Projected Predator
δ15N (‰)
13
~1 trophic level
11
~1 trophic level
9
7
Keuka
Cross
Fig. 5. δ15N values for unionid mussels from Keuka Lake and Cross Lake in New York
State. A hypothetical predatory fish for Keuka Lake is projected ~ 3.4‰ (1 trophic level)
above the filter feeding mussels yet remain ~ 3.4‰ below the mussels from Cross Lake.
3.3.1. Sources of variation in aquatic carbon
The δ13C value of aquatic organic matter within the photic zone is
dictated by the isotopic signature of the dissolved inorganic carbon
(DIC) pool and the extent to which that pool is utilized (Degens et al.,
1968). The dominant form of DIC present in aquatic ecosystems is
determined by pH and alkalinity (Stumm and Morgan, 1981). In ocean
and stream settings, DIC is composed primarily of HCO−
3 (N90%) and
dissolved CO2 (b10%) (Bickert, 2006). In lakes with lower pH, DIC can
be composed entirely of CO2. Aquatic plants use mainly dissolved CO2
though some species have the ability to utilize HCO−
3 through active
transport (Keeley and Sandquist, 1992; Schulte et al., 2003). Changes
in the proportion of HCO−
3 and CO2 in the boundary layer, which is a
function of the pH; total carbon level; photosynthetic rate and amount
of turbulence can influence the use of HCO−
3 by plants (Keeley and
Sandquist, 1992). There are three sources of aquatic DIC: dissolved
atmospheric CO2, the products of terrestrial weathering, and
remineralized organic matter. Two types of organic matter can be
remineralized: in situ production which has little net affect on the
δ13C value of DIC and introduced terrestrial material such as leaf litter
or dissolved organic carbon (DOC) which can substantially alter the
δ13C value of DIC, especially in small lakes (Post, 2002b). The higher
the concentration of DIC, the more fully fractionation can be
expressed and the more negative the δ13C values of organic matter
become (Smith and Walker, 1980; Fogel and Cifuentes, 1993;
Goericke and Fry, 1994). HCO−
3 derived from the terrestrial dissolution of limestone has as δ13C value of approximately +1‰, while
dissolved CO2 has a δ13C value of − 7‰ when derived from the
atmosphere and ≤−27‰ when derived from the respiration of
organic matter (Keeley and Sandquist, 1992). Decreases in the δ13C of
the atmosphere, such as those seen over the last 50 years (Cerling and
Harris, 1999), have led to decreases in the δ13C of aqueous CO2 and of
DIC overall (Nozaki et al., 1978; Druffel and Benavides, 1986; Bohm et
al., 1996). There will be a time lag between the atmospheric change in
δ13C and the equilibration of aquatic DIC depending on the turnover
time of body of water, with equilibration being reached quickly in
small basins (Bohm et al., 1996). This time lag could be even longer in
littoral or infaunal species which are dependent on sediment turnover
rates (Moens et al., 2002).
Differences in relative contribution of each source determine the
δ13C value of DIC among ecosystems (Wachniew and Rozanski, 1997).
The relative proportion of each of these sources within a given
ecosystem can be affected by physical factors such as basin hydrology
and size. For example, the δ13C of both littoral and pelagic producers
decrease with decreasing lake size (Post, 2002b; Bade et al., 2004).
This difference likely reflects increased amount of primary production
fuelled by re-mineralized terrestrial organic matter (e.g., leaf litter
and DOC) in small lakes relative to large lakes (Post, 2002b). Water
temperature determines the solubility of CO2 resulting in increased
139
CO2 concentrations at colder temperatures (Michener and Kaufman,
2007). The δ13C of DIC in the open ocean is fairly uniform at
approximately 0‰ (Sackett and Moore, 1966; Sherr, 1982; Kroopnick,
1985). Unlike open ocean systems, the isotopic signatures of near
shore and estuary systems are more variable and are affected by
terrestrial inputs, in which the δ13C of DIC can vary between −5‰ and
−10‰, and the presence of a littoral food web (Michener and
Kaufman, 2007).
The extent to which the DIC pool is utilized strongly impacts the
isotopic signature of aquatic organic matter and the remaining DIC
pool. In marine systems, the isotopic signatures of benthic macroalgaes and diatoms become less depleted due to CO2 limitation
experienced during periods of rapid growth (Deuser, 1970; Wienke
and Fisher, 1990; Fry and Wainright, 1991). Changes in the rate or
extent of DIC utilization translate into changes in the isotopic
signature of the DIC pool and aquatic primary producers. Photosynthetic depletion of CO2 during the day and respiratory addition at
night leads to a steady enrichment of 12C through the course of the
season. For example, the δ13C of DIC in the Colorado de Mesa pool, CA,
USA, shifted from −15.5‰ in the early spring to − 21.2‰ in the late
spring (Keeley and Sandquist, 1992). Marine systems show similar
seasonal patterns with enriched δ13C values during the photosynthesis-dominated spring versus depleted values in the respirationdominated fall (Rullkötter, 2006) and enriched values in the dry
season relative to depleted rainy season values which are due to
increased delivery of freshwater and terrestrial organics (Simenstad
and Wissmar, 1985; Conkright and Sackett, 1986). The seasonal range
of phytoplankton δ13C values can be as high as 6‰, from − 19‰ to
−25‰ (Wainwright and Fry, 1994).
Factors related to growth rates, such as temperature, light, nutrient
availability, and latitude, also affect the δ13C values of plants and the
remaining DIC pool. Low rates of primary productivity in low nutrient,
or oligotrophic, lakes allow ample time for replacement of CO2 into
the boundary layer of aquatic plants and lead to depleted δ13C values
in aquatic plants (Keeley and Sandquist, 1992). In eutrophic settings
where rates of productivity are extremely high, discrimination against
13
C may be reduced when diffusion cannot replace CO2 fast enough.
However, high carbon levels in eutrophic lakes may offset this process
(Keeley and Sandquist, 1992). High temperatures are positively
correlated with 13C enriched plants in both freshwater (MacLeod
and Barton, 1998) and marine (Sackett et al., 1965) settings. Increased
light intensity has been shown to correlate with 13C enriched values of
macroalgaes (Wienke and Fisher, 1990; MacLeod and Barton, 1998).
High latitude primary producers show depleted δ13C values relative to
low latitude producers likely due to some combination of increased
dissolved CO2 concentration, decreased light intensity, availability of
trace elements, and decreased growth rates (Rau et al., 1982; Rau et
al., 1990).
The δ13C value of phytoplankton is affected by physical factors that
impact fractionation or limit phytoplankton access to certain DIC
pools. Temperature dictates the δ13C of organic matter by influencing
fractionation such that phytoplankton have more depleted values at
lower temperatures (e.g., −20‰ to −22‰ temperate phytoplankton
and −26‰ arctic phytoplankton) (Rau et al., 1991). Species specific
differences in cell geometry, membrane permeability, and potentially
even cell size affect the amount of 13C discrimination exhibited by
phytoplankton (Gearing et al., 1984; Rau et al., 1990; Wainwright and
Fry, 1994; Popp et al., 1998; Burkhardt et al., 1999). Differences in the
species composition between water masses (Fontugne and Duplessy,
1978) or seasonally within a water mass (Gearing et al., 1984)
translate into differences in the δ13C signature of phytoplankton. The
δ13C signatures of producers and consumers reflect changes in the
dominant DIC source with depth. Isotopic signatures are increasingly
depleted with increasing depth both in stratified lakes (Rau, 1978;
Rau, 1980; Vander Zanden and Rasmussen, 1999) and in marine
settings (Fry and Wainright, 1991).
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Aquatic organisms may feed on detritus or use forms of dissolved
organic carbon (DOC). Though the DOC pool is very large, containing
between 90 and 95% of all carbon in water (Benner, 2002), it typically
makes up a very small portion of an organism's diet, on the order of 1–
10% (Ferguson, 1982). It is difficult to impossible for many organisms
to utilize DOC including large organisms due to surface area to volume
constraints, freshwater organisms since DOC uptake is a sodium
dependent process (Wright and Manahan, 1989), and arthropods due
to their chitinous exoskeleton (Anderson and Stephens, 1969). DOC
uptake may constitute a significant portion of the diets of small
organisms or those with large surface area to volume ratios. Larval
forms of many invertebrates can derive as much as 100% of their
dietary needs from dissolved organic matter (Shilling and Manahan,
1990). Globally, open marine DOC ranges over approximately 4‰,
from −19.6‰ to −23.6‰ (Bauer, 2002). In a single region marine
DOC is fairly constant seasonally and over short distances (Fry et al.,
1998). The δ13C signature of marine DOC is negatively correlated with
salinity due to the input of depleted terrestrial material from
freshwater (Bauer, 2002). This results in higher variability of marine
DOC near shore which range from −20‰ to −29‰ (Bauer, 2002) and
within estuaries which range between − 24.6‰ and − 31.9‰
(Raymond and Bauer, 2001). The bulk DOC pool that gets measured
is defined operationally and is therefore extremely heterogeneous
with respect to age and compound identity, only ~12–15% of which
has been characterized chemically (Benner, 2002). Since we know
relatively little about what makes up the DOC pool and which
constituents organisms are using, there may be more consistent bias
in the carbon isotopic signature than the numbers quoted above
suggest.
3.3.2. Sources of variation in aquatic nitrogen
The δ15N value of aquatic organic matter from the photic zone is
determined by the isotopic signatures of the various sources of
dissolved inorganic nitrogen (DIN), both autochthonous and
allochthonous, and the extent to which the pool is utilized (Wada,
1980; Altabet et al., 1991; Voss et al., 1996). Allochthonous sources of
DIN included riverine input (often incorporating enriched agricultural
NH3) and N2 fixation (Jennings and Warr, 2003). Fixed nitrogen has a
depleted δ15N signature (0 to + 2‰) (Hoering and Ford, 1960;
Delwiche and Steyn, 1970; Brandes and Devol, 2002). Allochthonous
DIN is made up of the by-products of remineralized organic matter.
Nitrification and denitrification play an important role in influencing
the isotopic composition of DIN (Gu, 2009). Nitrification may result in
either enriched or depleted DIN depending on which by-products are
assimilated by phytoplankton (Lehmann et al., 2004; Syvaranta et al.,
2008) while denitrification results in enriched DIN (Owens, 1987).
The allochthonous sources are linked to autochthonous processes. For
instance, the depleted organic matter formed by nitrogen fixation
must pass through the nitrification pathway (remineralized NH+
4 ) in
order to affect the δ15N signature of nitrate (Montoya, 2007) which is
the dominant from of DIN in the oceans (Liu and Kaplan, 1989;
Sigman et al., 1997; Sigman et al., 2000). In some systems the
anaerobic oxidation of ammonium (anammox) may also play a small
role in influencing the isotopic composition of DIN (Bickert, 2006).
Remineralization can transform the products of in situ productivity or
imported organic matter. In lakes and streams, imported organic
matter commonly has a terrestrial isotopic signature, but imported
marine organic matter can be common in lakes with connections to the
ocean or populations of anadramous fish (Owens, 1987; Bilby et al.,
1996; Ben-David et al., 2004; Walters et al., 2009).
The relative contribution of these sources determines the δ15N
value of DIN. Numerous factors (Table 2) affect which of the above
processes are dominant in a given system. Lake size has a considerable
impact on the isotopic composition of the littoral baseline in lakes
(Post, 2002b) such that small lakes are 3.1‰ depleted relative to
medium-size lakes and 3.7‰ more depleted than large lakes (Gu,
2009). The reduced surface area to volume ratio in large lakes
decreases the importance of the terrestrial contribution relative to
small lakes (Gu et al., 1994; Post, 2002b; Gu et al., 2006). There may
also be an increased contribution of nitrogen fixing producers in small
lakes (Gu et al., 1994, 2006). Differences in the input of anthropogenic
nitrogen between lakes can vary greatly (Carpenter et al., 1998;
Anderson and Cabana, 2005; Savage, 2005; Vander Zanden et al.,
2005; Leavitt et al., 2006; Xie et al., 2007). Cabana and Rasmussen
(1996) showed that 68% of the observed difference in δ15N value
among unionid mussels could be explained by differences in the
density of human population in the watershed. The relative
importance of terrestrial input also plays a role in determining the
isotopic signature in marine systems. The concentrations of isotopically enriched riverine ammonia and nitrate are negatively correlated
with salinity (Vanbennekom and Wetsteijn, 1990) and salinity is
negatively correlated with marine δ15N (Jennings and Warr, 2003),
especially in estuaries. Even in the fully saline open ocean, the δ15N
signatures of NO−
3 and suspended organic matter (SPOM) are
negatively correlated with distance from shore (Wu et al., 1997).
In lakes there is a positive relationship between the δ15N signature
of littoral producers and the log of lake depth (Post, 2002b). This is
due to the predominance of denitrification and ammonification in the
suboxic profundal zones of stratified lakes and marine settings which
results in an enriched inorganic nitrogen pool (Wada and Hattori,
1978; Macko and Estep, 1984; Owens, 1987; Vander Zanden and
Rasmussen, 1999). The same process operates in suboxic marine
bottom waters where water column denitrification leads to pronounced fractionation (Bickert, 2006; Montoya, 2007). In addition,
the top of the water column becomes depleted due to the
remineralisation and assimilation of depleted NH3 at the surface
(Mullin et al., 1984; Checkley and Miller, 1989) and deeper waters
become enriched due to the rapid sinking of enriched fecal pellets and
detritus to the seafloor (Checkley and Entzeroth, 1985; Altabet and
Small, 1990; Montoya et al., 1992). The more trophic steps within an
ecosystem, the more enriched the fecal pellets of the animals at the
top trophic levels (Minagawa and Wada, 1984; Fry, 1988; Montoya,
1994). However, in oxic marine settings or areas of coastal upwelling
this trend is reversed, with bottom waters becoming increasingly
depleted with depth as the concentration of NO−
3 increases (Wu et al.,
1997; Jennings and Warr, 2003). These high concentrations of NO−
3
are the product of remineralized depleted ammonia, which occurs in
situ in oxic settings or is delivered from the deep ocean through
upwelling (Owens, 1987; Wu et al., 1997; Jennings and Warr, 2003).
The amount of isotopic discrimination exhibited by phytoplankton
is dictated by species composition (Wada and Hattori, 1978; Montoya,
1994; Montoya, 2007), the growth rate of the phytoplankton
community (Gu, 2009), and the extent to which the DIN pool is
used (Miyake and Wada, 1967; Wu et al., 1997). In marine settings
there is an inverse relationship between the δ15N value of particulate
organic matter (POM) and the concentration of DIN (Miyake and
Wada, 1967; Wu et al., 1997). In lakes, the relationship between DIN
concentration and δ15N of POM is unclear with evidence supporting a
positive correlation, a negative correlation, and no clear relationship
(Gu, 2009 and references therein). This discrepancy arises from the
fact that most marine systems are nitrogen limited whereas
freshwater systems are predominately phosphorous limited (Elser
et al., 1990; Gu, 2009). Nitrogen limitation is important because the
growth rate of phytoplankton also influences their fractionation of
nitrogen. Faster growth leads to greater utilization of the DIN pool,
decreased fractionation, and enriched δ15N signatures (Wada and
Hattori, 1978; Owens, 1987; Gu, 2009). Where nitrogen is limiting, an
increase in the concentration of DIN will trigger higher rates of
productivity. These opposing processes are further complicated by the
unpredictable prevalence of nitrogen fixing bacteria in some
eutrophic and oligotrophic systems (Estep and Vigg, 1985; Gu et al.,
1996, 2006; Montoya, 2007). The mean seasonal δ15N of POM is
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3.3.3. Aquatic baseline issues in the fossil record
The amplitude of seasonal variation in the isotopic composition of
aquatic primary producers is relatively well known in modern
environments. In modern isotopic studies, researchers use long
lived organisms as baseline proxy taxa because they represent a
weighted average of the isotopic values of the preceding months. This
methodology avoids the baseline issues that would arise when
comparing a long lived consumer of interest to an instantaneous
snapshot of the isotopic values garnered from short lived primary
producers at the base of the food web (Cabana and Rasmussen, 1996;
Post, 2002b). This method will serve as a viable solution in the fossil
record as well provided that reliable baseline proxy taxa be identified
and utilized. In the fossil record, any estimate of the isotopic signature
of an organism must be derived from hard parts such as shells or
bones. The organic components of these hard parts integrate isotopic
compositions over a much longer time frame than soft tissues,
resulting in an isotopic signal that can represent years rather than
months of the feeding ecology of the organism. To effectively choose
baseline proxies for studies conducted in the fossil record one needs
to know that nature of isotopic variation within aquatic ecosystems
on a year to year or decadal scale. The amplitude of yearly variation for
δ13C, as high as 6‰ (Wainwright and Fry, 1994), is large relative to the
end member disparity in a given ecosystem, in lakes 6–7‰ (France,
1995b; Post, 2002b). This large amount of variability could be
accounted for using baseline proxies from time averaged assemblages
if the range and value of baseline isotopic signatures are consistent
from year to year. In many cases, a small amount of time averaging
smoothes out short term variability thus decreasing noise and
allowing the clear identification of trends. If, however, the seasonal
variability is not consistent from year to year, the time averaging
inherent in shells and deposits will mask valuable signal.
There is a dearth of modern data that spans multiple years so it is
impossible to say how this amplitude of seasonal or yearly variation
translates into year to year variation. Does the isotopic composition of
aquatic producers move within the same ~6‰ range every year? Or
do the absolute values of each year's range change dramatically? Fig. 6
shows the nitrogen and carbon isotopic signatures for baseline proxy
organisms (the grazing snail L. littorea and filter feeding mussel G.
dessimus) collected from the a single field locality within Long Island
Sound at Milford, CT over the course of four years. This data shows a
6‰ shift between late summer values of baseline proxies from
consecutive years (August 2007 and July 2008) which is propagated
through the food web to higher trophic levels like the predatory
naticid gastropod N. duplicata. These data point to potentially
problematic amount of year to year variability in the isotopic
composition of the DIC pool in estuarine systems such as Long Island
Sound. Less variable offshore environments may show more amenable values of baseline variation. There is a critical need to conduct
more modern and sub-fossil studies to document the magnitude of
year to year variation at time periods long enough to address issues
related to time-averaging in marine shell beds.
Time averaging is typically minor in lacustrine deposits where it
can range between months and 103 years, but typically ranges
between 1 and 10 years (Cohen, 2003). Time averaging is much
more severe in marine settings. For example, Wood et al. (2006)
found bivalve shells at the surface that ranged in age from 0 to
2808 years old in modern sediments from the coast of Brazil.
Fossilized assemblages of marine bivalves also show ranges in age
on the scale of thousands of years regardless of the resolution of
sampling intensity (Kowalewski et al., 1998). Another troubling
aspect of time averaging is what Kowalewski et al. (1998) termed
“cryptic time averaging”, or differences in the amount of time
averaging exhibited by deposits that seemingly formed via identical
geologic or environmental processes. This amount of age variability
within a single unit could create a large problem when trying to use
proxy taxa to estimate baseline isotopic composition. For proxy taxa
to serve as a reliable approximation of baseline, they must faithfully
represent the isotopic composition of the primary producers growing
in the place and time that the organism of interest was growing. If the
proxy organisms are hundreds or thousands of years older or younger
than the organism of interest, their isotopic compositions may not be
15
2006
2007
2008
2009
14.5
Neverita
14
13.5
Neverita
13
Littoral
12.5
12
Pelagic
δ15N (‰)
significantly higher in eutrophic lakes (7.3‰) than in oligotrophic
lakes (4.6‰), despite high amounts of variability (Gu, 2009). This is
the opposite of marine systems where oligotrophic seas have enriched
δ15N values compared to eutrophic seas due to differences in nitrogen
recycling (Saino and Hattori, 1980; Minagawa and Wada, 1984;
Checkley and Entzeroth, 1985).
Seasonality affects species composition, growth rate, and the
extent of DIN utilization simultaneously. Near Woods Hole, MA, the
δ15N of POM varies between 7.5‰ and 12‰ over the course of the
year, a range of 4.5‰ (Wainwright and Fry, 1994). Further offshore,
near Georges Bank there was markedly less seasonal variability in
δ15N signature (Wainwright and Fry, 1994). In a survey of published
seasonal ranges for 36 lakes, Gu (2009) found seasonal amplitude (or
the difference between the maximum δ15N signature and the
minimum δ15N signature for an annual cycle) varied between 1.4‰
and 25.0‰. The value of the seasonal minimum can be controlled by
nitrogen fixing bacteria (Gu, 2009), uptake of isotopically light DIN
from external loading (Ostrom et al., 1998; Gu, 2009), or in situ
nitrification (Syvaranta et al., 2008; Gu, 2009; Hadas et al., 2009). The
value of the seasonal maximum is determined by high productivity or
higher starting DIN isotopic composition (Gu, 2009). The seasonal
variability in eutrophic lakes is large relative to that in oligotrophic
lakes because a larger proportion of the POM in oligotrophic lakes is
non-living organics so a large shift in the source of non-living organic
particulates would be necessary to get a large seasonal shift in an
oligotrophic setting (Gu, 2009).
Additional physical factors such as temperature, light, and latitude
affect the δ15N signature of primary producers. Temperature is
positively correlated with δ15N values for littoral producers in lakes
(MacLeod and Barton, 1998) and phytoplankton in marine settings
(Jennings and Warr, 2003). Increased light conditions also lead to
enriched δ15N values (MacLeod and Barton, 1998). Gu (2009)
reported a slight, though not significant, increase in the δ15N
composition of lakes with increasing latitude. However, the amplitude
of seasonal variability increases with latitude due to the increased
seasonality of factors like radiation and temperature at higher
latitudes (Gu, 2009).
141
11.5
11
10.5
-20
-18
-16
-14
-12
-10
-8
-6
10
δ13C (‰)
Fig. 6. Bi plot with δ13C values on the x-axis and δ15N values on the y-axis showing the
pelagic baseline proxy Guekensia dessima (circles) and littoral baseline proxy Littorina
littorea (squares) collected live from Long Island Sound each summer from 2006 to
2009 and predatory gastropods Neverita dulplicata (diamonds) collected live during the
summers of 2007 and 2008.
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M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
a
1
i
ii
iii
iv
Alpha
0.75
0.5
0.25
0
Individual Baselines
Multi-Year Baseline
b
3.5
i
ii
iii
iv
3
Trophic Position
applicable to the question, depending on the stability of that isotopic
baseline over a thousand year long span. However, the same time
averaged deposits may offer the best scenario in which to test the
variability of baseline signatures on millennial timescales. Large
accumulations of shells dated using amino acid racemization (e.g.,
Flessa et al., 1993; Kowalewski et al., 1998; Krause et al., 2010)
provide the opportunity to target proxy taxa of known ages to
examine the variability of isotopic signatures.
Pooling measurements of baseline from multiple years before
calculating trophic position can lead to change in either the absolute
value of estimated trophic position or the variation (Fig. 7b and c). The
dietary fraction (α) and trophic position of the predatory naticid
gastropod N. dulplicata were calculated for two samples collected
from Long Island Sound: 1) in August of 2007, n = 10 specimens; and
2) in August of 2008, n = 10 specimens. First, we estimated the mean
and standard deviation of (α), or the proportion of the organism's diet
derived from the pelagic food web, for each specimen using the
baseline estimate of its respective year. The mean and standard
deviation of alpha were plotted for 2007 specimens (Fig. 7a, i), and
2008 specimens (Fig. 7a, ii). The baseline estimates for the years 2006,
2007, 2008, and 2009 were averaged together to create a multi-year
baseline which we then used to recalculate alpha. The recalculated
mean and standard deviation of alpha were plotted for all specimens
(Fig. 7a, iii), and for just those from 2008 (Fig. 7a, iv).
This process was repeated for trophic position (Fig. 7b) with the
mean and standard deviations plotted for 2007 specimens (Fig. 7b, i),
2008 specimens (Fig. 7b, ii), all specimens using the multi-year
baseline (Fig. 7b, iii), and just the 2008 specimens using the multiyear baseline (Fig. 7b, iv). Despite the observed biogeochemical shifts
in the absolute values of δ13C and δ15N between snails collected in
2007 versus those collected in 2008 (Fig. 6), the mean and variation in
dietary proportion and trophic positions for the two years are nearly
identical (Fig. 7 i and ii). Increasing the number of years over which
both taxa of interest and baseline proxies span (Fig. 7 iii) substantially
increases the variation of observed dietary proportions and trophic
positions. This range of estimated trophic positions changed from
between 1.81 and 2.56 using the baseline from the appropriate time
interval to between 1.68 and 3.03 using the multi-year baseline. While
this amount of variability may be acceptable in some situations, it
would completely obscure changes in degree of trophic omnivory
such as those described by Kling et al. (1992) where the differences
between lakes were just slightly larger than 1‰. The range in
estimates of dietary proportion changed from 0 to 58% pelagic using
the baseline from the appropriate time interval to between 0% and
97% pelagic using the multi-year baseline.
The added variation reduces confidence in our ability to resolve
the true trophic position or dietary proportion of fossil organisms.
Using baseline estimated from multiple years to calculate trophic
position or dietary proportion for organisms from just one year
(2008) artificially increased the mean (Fig. 7, iv). For dietary
proportion, the mean changed from 0.24 to 0.82 while mean trophic
position changed from 2.27 to 2.71.
We then calculated trophic position using several multiple-year
baselines in which years were added sequentially (Fig. 7c). The absolute
value of the change in trophic position, between the original value using
the proper baseline and those calculated using a 2 year, 3 year, 4 year,
and mismatched single year baseline are plotted with error bars
representing their standard deviation. The magnitude and direction of
the error introduced by applying multiple year baselines varies
depending on the position of the year in question within the total
range of observed values. For example, the error in estimates of trophic
position increases as time averaging increases for snails from 2008
(Fig. 7c, gray squares) with the mismatched baseline yielding the
highest error. The error for snails from 2007 (Fig. 7c, black squares) is
highest at low levels of time averaging because the true baseline values
for 2007 happen to be similar to the four year mean. This artificial time
2.5
2
1.5
1
c
1
Change in Trophic Position
142
Individual Baselines
2 yr
3 yr
Multi-Year Baseline
4 yr
Mismatch
0.8
0.6
0.4
0.2
0
Fig. 7. Mean and standard deviation of parameter estimates for the predatory naticid
gastropod Neverita dulplicata collected live from Long Island Sound in August 2007
(n = 10 specimens) and July 2008 (n = 10 specimens). a: α, or dietary fraction and b:
trophic position— i: Using the 2007 baseline to for the snails collected in 2007 (black
squares). ii: Using the 2008 baseline for the snails collected in 2008 (gray squares). iii:
Using a pooled 2006, 2007, 2008, and 2009 baseline for all snails (black circles). iv:
Using the pooled 2006, 2007, 2008, and 2009 baseline for just the 2008 snails (gray
circles). c: absolute value of the difference between the original trophic position
estimate and the revised value calculated using averaged multi-year (2, 3, or 4 years) or
mismatched single-year baselines. Snails collected in 2008 = gray square, snails
collected in 2007 = black squares. Error bars represent standard deviation of trophic
position, where not visible error bars are smaller than the square. Trophic fractionation
assumed to be 3.4‰ in all cases.
averaging scenario is similar to the fossil record where there may be a
limited number of specimens of the organism of interest (predator) and
many specimens of the baseline proxy taxa. However, this artificial time
averaging scenario spans only four years whereas the actual time
averaging of fossil deposits are likely to span several hundred years. In
such cases, the observed shift in mean trophic position may be either
positive or negative. Until more data on the nature of baseline variation
on millennial time scales is available, researchers should use extreme
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M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
caution when using baseline proxy taxa to apply stable isotopic trophic
methods in time averaged marine systems.
Furthermore, averages of isotopic baseline derived from modern
systems are not suitable for use in calculating diets or trophic
positions in the fossil record. There are several sources of long-term
variation in the isotopic composition of lakes and oceans that play out
over geologic timescales. These include changes in the atmosphere,
such as changing partial pressure of CO2 (Long et al., 2005); changes in
the ocean, such as changing rates of ocean–atmosphere exchange
controlled by water temperature or ocean circulation patterns
(Shackleton, 1977; Broecker, 1982; Sarnethein et al., 1994; Bickert
and Mackensen, 2003), changing rates of organic matter burial,
changing net oceanic productivity (Berger and Vincent, 1986); and
changes in the global carbon cycle, such as changing weathering rates
on land and changing fluxes of gas from volcanic eruptions (Holser,
1997). These changes can have massive impacts on the isotopic
composition and operate on timescales from 101 to 105 years or more.
The presence of parasequences, or shallowing upward strata
bounded by flooding surfaces, within aquatic deposits has important
implications for the nature of changing isotopic baselines. In
lacustrine environments, cycles of lake deepening and drying out
can be driven by Milankovitch climatic variations (e.g., Olsen, 1986,
1990) and may result in substantial changes to lake size. In marine
deposits, parasequence formation is driven by sea level fluctuations
and leads to the formation of sequences (Van Wagoner et al., 1988).
This means that moving stratigraphically up or down within a single
core or outcrop, several of the important driving factors in
determining baseline isotopic composition are changing simultaneously. In marine settings, moving through parasequences means
changes in depth. But as one moves through sequences, depth and
distance from shore are changing in tandem (Van Wagoner et al.,
1988). Changes in depth and distance from shore may correlate with
additional changes in terrestrial input of DIC and DIN, salinity,
presence of bottom water oxygen which controls remineralisation
pathways, and light. In lacustrine settings, lake size, depth, position in
the littoral/profundal continuum, and presence or absence of
stratification may be changing concurrently as large, rift basin lakes
periodically dry out (Olsen, 1986). These changes highlight the
importance of measuring baseline independently for each stratigraphic horizon at which specimens of target species are collected and
analyzed.
3.4. Diagenesis
Diagenesis, as it affects the indigeneity of isotopic signatures, is of
great concern when working with fossilized organisms. To date, the
work in this area has centered on amino acid specific isotopic analysis
of molluscs (Serban et al., 1988; Macko et al., 1991; Engel et al., 1994;
Qian et al., 1995) and vertebrates (Ostrom et al., 1990, 1994). These
authors have compared the stable isotope values of the different
enantiomers of various amino acids in order to test for isotopic
contamination. Where the isotopic compositions of both enantiomers
match, the signature is deemed indigenous. Where the isotopic value
of the parent enantiomer, or that formed only in living tissues, does
not match the isotopic value of the daughter enantiomer, the sample
has likely been contaminated. In spite of these concerns, indigenous
signals are demonstrated to have been preserved for long periods of
time. For example, shell matrix proteins that make up the organic
matrix of mollusk shells can become encased within mineral crystals
(Crenshaw, 1980). Mineral encased proteins can be preserved in
shells as old as Middle Miocene (Hare and Abelson, 1968).
3.5. Guidelines for estimating baseline
It is important to account for baseline in some manner when
constructing food webs or calculating trophic positions and diet. This
143
can be done in a few ways: 1) by directly measuring carbon and
nitrogen signatures of primary producers (Aurioles-Gamboa et al.,
2009), 2) by measuring the carbon and nitrogen signatures of proxy
organisms (Cabana and Rasmussen, 1996; Post, 2002b), or 3) by
measuring the δ15N signature of a phylogenetically related or
ecologically similar organism whose feeding ecology is well constrained (Post, 2003). Measuring the primary producers directly can
be difficult or impossible in the fossil record and will yield only a brief
snapshot of baseline due to seasonal changes in isotopic signature and
the shorter turnover rates of primary producers relative to secondary
consumers (Post, 2002b; Gu, 2009). Good proxy taxa are primary
consumers which derive as much of their energy as possible from a
single food source, and integrate nutrients into their tissues over time
scales comparable to secondary consumers of interest (Cabana and
Rasmussen, 1996; Vander Zanden et al., 1999; Post, 2002b). Cabana
and Rasmussen (1996) and Post (2002b) have suggested using filterfeeding mussels as a proxy for the base of the pelagic food web and
surface-grazing snails as a proxy for the base of the littoral food web in
aquatic systems. These taxa are good temporal integrators and
adequately reflect the spatial variability of the primary producers on
which they feed in both lacustrine (Post, 2002b) and marine systems
(Fig. 6). This isotopic congruence makes the proxy method good for
food web reconstructions involving multiple, phylogenetically diverse
taxa or those comparing food webs from different ecosystems,
habitats, or localities. Obligate browsers or grazers could potentially
serve as appropriate terrestrial proxy taxa, but this method needs
further testing in terrestrial systems.
If, however, there is only a single organism of interest one may use
the isotopic signatures of another closely related population from the
same location to account for baseline differences (option 3 above).
Examples include Kling et al.'s (1992) work on copepods and Post's
(2003) work on largemouth bass. Post (2003) used a single cohort of
largemouth bass from a single lake to evaluate trophic position shifts
based on the δ15N signatures of piscivorous versus non-piscivorous
individuals. This was possible because, aside from the presence or
absence of fish, the diets of the piscivorous and non-piscivorous
individuals were virtually identical. Changes in the δ15N signature of
largemouth bass could therefore reliably be interpreted as variation in
Δn or trophic position. Because variation in Δn is normally distributed,
Post (2003) was able to look for individuals that deviated from that
normal distribution and identify those with a higher trophic position.
This method will not work properly where no phylogenetically or
functionally similar taxon or population is available, where the diet of
the comparison taxon is substantially different or not well constrained,
or where research questions dictate the comparison of multiple
functionally or phylogenetically unrelated taxa (e.g., Post et al., 2000).
Regardless of method, the isotopic baseline needs to be accounted for
within each location and each time period where fossils are collected
due to the myriad of factors controlling isotopic signature listed above.
The natural history of the system of interest will dictate the method
which is most suitable and no one method is appropriate in all cases.
Time averaging affects each of these methods for estimating
baseline. Measuring baseline using proxy taxa (option 2) in time
averaged deposits will create a baseline estimate with a large amount
of variation because of the high number of proxy taxa spanning
potentially long time intervals. This will add error to the estimates of
trophic position (Fig. 7). However, this method may be preferable to
using an ecologically or phylogenetically related taxon (option 3)
when the organism of interest and its relative are rare within the
deposit. When the probability of specimen preservation is low,
resulting in rare taxa, the chances of multiple specimens of rare taxa
from a single time being preserved are low. If this is the case, the
baseline information represented by the related taxon may be
incorrect and not relevant to the taxon of interest (Fig. 7c, mismatch).
Common taxa represent the baseline conditions during the life of the
target organism and also that of additional time slices. Where both the
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M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
target organism and the related taxon are common components of the
assemblage, option 3 will be appropriate but will have the same high
variation as option 2. Collecting and analyzing as many target
organisms as possible may provide a way to minimize this
discrepancy in amount of time averaging.
The most conservative way of avoiding the errors caused by
applying time averaged baselines would be to choose only localities
with exceptional preservation for analysis, thus minimizing or
entirely eliminating time averaging. Archeological shell middens
(Bernstein, 2002) and catastrophic death accumulations, such as
vertebrate ashfall deposits (Mead, 2000), offer snapshots of fossilized
communities that formed over relatively short time periods (1+ years
to hours, respectively), thus avoiding the problems of long-term time
averaging. Extensively dated fossil collections, like those produced
using amino acid racemization dating techniques (e.g., Krause et al.,
2010), may supply an additional means of overcoming the problems
of time averaging by providing important information regarding the
amount of time averaging present and the ages of individual
specimens. Until more is known about the nature of baseline variation
over time scales comparable to that of time averaging (hundreds to
thousands of years), the types of questions that can be addressed or
the scope of inferences that can be made in typical, time averaged
deposits may be limited due to the increased uncertainty surrounding
fossil estimates of trophic position and diet. This is not to say that
stable isotopic methods will never be useful in these instances, just
that the types of questions that can be answered with these methods
will be restricted. Questions related to trophic level, e.g., whether an
organism is a predator or an herbivore, require less isotopic resolution
than questions of trophic position, such as those related to degree of
omnivory. The other alternative is seeking deposits in which time
averaging is minimized, or the amount of time averaging is known.
4. Conclusions
There are a number of factors that combine to determine the stable
isotopic composition of fossil animals including diet, trophic position,
lipid content, diet to tissue effects, isotopic routing, diagenetic
alteration, and isotopic baseline. No single factor can be identified as
most important and failure to account for any of these factors may
result in discrepancies wrongly attributed to changes in baseline or
unreliable findings depending on the natural history of the system
and the nature of the scientific question posed. Baseline concerns are
of particular importance when comparing the trophic position of
organisms from different locations or times.
Differences in the isotopic signature of the baseline cause
disagreement between the raw δ15N value of an animal and its
relative trophic position, so an animal with a lower δ15N value may
still occupy a higher trophic position. Based on what is known about
the causes of baseline variation in modern terrestrial (Table 1) and
aquatic (Table 2) environments, factors that change in concert with
sequence stratigraphy (e.g., depth, distance from shore, and lake size)
or astronomical climate forcing (e.g., rainfall, temperature, and
humidity) are of the greatest concern in the fossil record. Failure to
account for baseline results in increased variability and adds to our
uncertainty regarding the true trophic position or diet of a fossil
organism. This error may be acceptable when expected isotopic
differences are large due to the scale of the animal's change in
behavior or the intensity of the signal strength. The amount of
uncertainty introduced by baseline may be problematic where the
signal strength is low (e.g., in aquatic systems), where the observed
isotopic shift is small (≥ 1‰), or where the anticipated behavioral
change is small (e.g., a 10% shift in dietary composition versus a 50%
shift in dietary composition or examining changes in the degree of
trophic omnivory). The most practical way to account for isotopic
baseline is by measuring the isotopic carbon and nitrogen signatures
of additional taxa from the same deposit. These taxa should have well
constrained diets and be ecologically similar to the organism of
interest in order to serve as a good baseline proxy.
Stable isotope methods are an extremely powerful tool for
estimating diet or trophic position, determining food chain length,
and resolving energy flow through ecosystems. The application of
these methods in the fossil record provides an opportunity to
reconstruct the diet and trophic position of extinct animals (Ostrom
et al., 1993) or evaluate various aspects of trophic ecology before
anthropogenic disturbance or in response to rapid climate change
(Fox-Dobbs et al., 2008). Given the numerous factors that affect the
value of isotopic baseline, it is extremely important to account for the
resultant differences in baseline by incorporating estimates of
baseline into multiple end member mixing models. Our review
highlights gaps in our knowledge which represent critical research
needs that must be addressed before baseline proxies and mixing
models can be reliably applied in the fossil record. Foremost amongst
these is the need to constrain the magnitude of temporal variation in
baseline on timescales relevant to time averaging (i.e., hundreds to
thousands of years). Such data will necessarily have to come from
extensive measurement of fossil and sub-fossil proxy taxa such as
mussel or snail shells. Long term data on baseline variation from
terrestrial, lacustrine, and marine ecosystems are required before we
can properly evaluate different methods of accounting for baseline in
time averaged fossil assemblages.
Acknowledgements
We would like to thank Gerry Olack for laboratory assistance;
Daniel Casey, Jo Wolfe, Úna Farrell and Emily Einstein for help with
field collecting; the Geological Society of America Graduate Student
Research Grant and the Paleontological Society Richard Osgood
Student Research Award for funding this research; and Erik Sperling,
Marc Laflamme, Adam Behlke, Donald Phillips, and one anonymous
reviewer for thoughtful comments.
References
Altabet, M.A., Small, L.F., 1990. Nitrogen isotopic-ratios in fecal pellets produced by
marine zooplankton. Geochimica et Cosmochimica Acta 54 (1), 155–163.
Altabet, M.A., Deuser, W.G., Honjo, S., Stienen, C., 1991. Seasonal and depth-related
changes in the source of sinking particles in the North-Atlantic. Nature 354 (6349),
136–139.
Ambrose, S.H., 1991. Effects of diet, climate and physiology on nitrogen isotope
abundances in terrestrial foodwebs. Journal of Archaeological Science 18 (3),
293–317.
Ambrose, S.H., Deniro, M.J., 1986. Reconstruction of African human diet using bonecollagen carbon and nitrogen isotope ratios. Nature 319 (6051), 321–324.
Anderson, C., Cabana, G., 2005. δ N-15 in riverine food webs: effects of N inputs from
agricultural watersheds. Canadian Journal of Fisheries and Aquatic Sciences 62 (2),
333–340.
Anderson, J.W., Stephens, G.C., 1969. Uptake of organic material by aquatic
invertebrates. VI. Role of epiflora in apparent uptake of glycine by marine
crustaceans. Marine Biology 4 (3), 243–249.
Aranibar, J.N., et al., 2008. Nitrogen isotope composition of soils, C-3 and C-4 plants
along land use gradients in southern Africa. Journal of Arid Environments 72 (4),
326–337.
Aranjuelo, I., Irigoyen, J.J., Sanchez-Diaz, M., Nogues, S., 2008. Carbon partitioning in N-2
fixing Medicago sativa plants exposed to different CO2 and temperature conditions.
Functional Plant Biology 35 (4), 306–317.
Aurioles-Gamboa, D., Newsome, S.D., Salazar-Pico, S., Koch, P.L., 2009. Stable isotope
differences between sea lions (Zalophus) from the Gulf of California and Galapagos
Islands. Journal of Mammalogy 90 (6), 1410–1420.
Bade, D.L., Carpenter, S.R., Cole, J.J., Hanson, P.C., Hesslein, R.H., 2004. Controls of delta C13-DIC in lakes: geochemistry, lake metabolism, and morphometry. Limnology and
Oceanography 49 (4), 1160–1172.
Barnes, C., Sweeting, C.J., Jennings, S., Barry, J.T., Polunin, N.V.C., 2007. Effect of
temperature and ration size on carbon and nitrogen stable isotope trophic
fractionation. Functional Ecology 21 (2), 356–362.
Bate, G.C. (Ed.), 1981. Nitrogen cycling in savanna exosystems. Terrestrial Nitrogen
Cycles: Ecological Bulletins, Stokholm, 33. 463–475 pp.
Bauer, J., 2002. Carbon isotopic composition of DOM. In: Hansell, D.A., Carlson, C.A.
(Eds.), Biogeochemistry of Marine Dissolved Organic Matter. Academic Press,
Amsterdam, the Netherlands, pp. 405–455.
Author's personal copy
M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
Bearhop, S., Adams, C.E., Waldron, S., Fuller, R.A., Macleod, H., 2004. Determining
trophic niche width: a novel approach using stable isotope analysis. Journal of
Animal Ecology 73 (5), 1007–1012.
Beerling, D.J., Mattey, D.P., Chaloner, W.G., 1993. Shifts in the delta-C-13 composition of
Salix herbacea L leaves in response to spatial and temporal gradients of atmospheric
CO2 concentration. Proceedings of the Royal Society of London. Series B, Biological
Sciences 253 (1336), 53–60.
Behrensmeyer, A.K., 1982. Time resolution in fluvial vertebrate assemblages. Paleobiology 8 (3), 211–227.
Behrensmeyer, A.K., 1991. Terrestrial vertebrate accumulations. In: Allison, P.A., Briggs,
D.E.G. (Eds.), Taphonomy: Releasing the Data Locked in the Fossil Record. Plenum
Press, New York, NY, pp. 291–335 (Chapter 6).
Ben-David, M., Titus, K., Beier, L.R., 2004. Consumption of salmon by Alaskan brown
bears: a trade-off between nutritional requirements and the risk of infanticide?
Oecologia 138 (3), 465–474.
Benner, R., 2002. Chemical composition and reactivity. In: Hansell, D.A., Carlson, C.A.
(Eds.), Biogeochemistry of Marine Dissolved Organic Matter. Academic Press,
London, UK, pp. 59–90.
Berger, A., 1988. Milankovitch theory and climate. Reviews of Geophysics 26 (4),
624–657.
Berger, W.H., Vincent, E., 1986. Sporadic shutdown of north-Atlantic deep-water
production during the glacial Holocene transition. Nature 324 (6092), 53–55.
Bernstein, D.J., 2002. Late Woodland use of coastal resources at Mount Sinai Harbor,
Long Island, New York. In: Kerber, J.E. (Ed.), A Lasting Impression: Coastal, Lithic,
and Ceramic Research in New England Archaeology. Greenwood Publishing,
Westport, CT.
Berry, S.C., Varney, G.T., Flanagan, L.B., 1997. Leaf delta C-13 in Pinus resinosa trees and
understory plants: variation associated with light and CO2 gradients. Oecologia 109
(4), 499–506.
Bettarini, I., Calderoni, G., Miglietta, F., Raschi, A., Ehleringer, J., 1995. Isotopic carbon
discrimination and leaf nitrogen-content of Erica arborea L along a CO 2
concentration gradient in a CO2 spring in Italy. Tree Physiology 15 (5), 327–332.
Bickert, T., 2006. Influences of geochemical processes on stable isotope distribution in
marine sediments. In: Schulz, H.D., Zabel, M. (Eds.), Marine Geochemistry. Springer,
Berlin, Germany, p. 346.
Bickert, T., Mackensen, A., 2003. Last glacial to Holocene changes in south Atlantic deep
water circulation. In: Wefer, G., Mulitza, S., Rathmeyer, V. (Eds.), The South Atlantic
During the Late Quaternary. Springer, Berlin, pp. 671–695.
Bilby, R.E., Fransen, B.R., Bisson, P.A., 1996. Incorporation of nitrogen and carbon from
spawning coho salmon into the trophic system of small streams: evidence from
stable isotopes. Canadian Journal of Fisheries and Aquatic Sciences 53 (1), 164–173.
Bohm, F., et al., 1996. Carbon isotope records from extant Caribbean and south Pacific
sponges: evolution of delta C-13 in surface water DIC. Earth and Planetary Science
Letters 139 (1–2), 291–303.
Bowman, W.D., Hubick, K.T., Voncaemmerer, S., Farquhar, G.D., 1989. Short-term
changes in leaf carbon isotope discrimination in salt-stressed and water-stressed C4 grasses. Plant Physiology 90 (1), 162–166.
Brandes, J.A., Devol, A.H., 2002. A global marine-fixed nitrogen isotopic budget:
implications for Holocene nitrogen cycling. Global Biogeochemical Cycles 16 (4).
Broecker, W.S., 1982. Ocean chemistry during glacial time. Geochimica et Cosmochimica Acta 46 (10), 1689–1705.
Brugnoli, E., Hubick, K.T., Voncaemmerer, S., Wong, S.C., Farquhar, G.D., 1988.
Correlation between the carbon isotope discrimination in leaf starch and sugars
of C-3 plants and the ratio of intercellular and atmospheric partial pressures of
carbon-dioxide. Plant Physiology 88 (4), 1418–1424.
Burkhardt, S., Riebesell, U., Zondervan, I., 1999. Effects of growth rate, CO2
concentration, and cell size on the stable carbon isotope fractionation in marine
phytoplankton. Geochimica et Cosmochimica Acta 63 (22), 3729–3741.
Cabana, G., Rasmussen, J.B., 1996. Comparison of aquatic food chains using nitrogen
isotopes. Proceedings of the National Academy of Sciences of the United States of
America 93 (20), 10844–10847.
Carpenter, S.R., et al., 1998. Nonpoint pollution of surface waters with phosphorus and
nitrogen. Ecological Applications 8 (3), 559–568.
Caut, S., Angulo, E., Courchamp, F., 2009. Variation in discrimination factors (Delta N-15
and Delta C-13): the effect of diet isotopic values and applications for diet
reconstruction. Journal of Applied Ecology 46 (2), 443–453.
Cerling, T.E., Harris, J.M., 1999. Carbon isotope fractionation between diet and
bioapatite in ungulate mammals and implications for ecological and paleoecological studies. Oecologia 120 (3), 347–363.
Checkley, D.M., Entzeroth, L.C., 1985. Elemental and isotopic fractionation of carbon and
nitrogen by marine, planktonic copepods and implications to the marine nitrogencycle. Journal of Plankton Research 7 (4), 553–568.
Checkley, D.M., Miller, C.A., 1989. Nitrogen isotope fractionation by oceanic zooplankton.
Deep-Sea Research Part a — Oceanographic Research Papers 36 (10), 1449–1456.
Chen, S.P., Bai, Y.F., Lin, G.H., Han, X.G., 2005. Variations in life-form composition and
foliar carbon isotope discrimination among eight plant communities under
different soil moisture conditions in the Xilin River Basin, Inner Mongolia, China.
Ecological Research 20 (2), 167–176.
Chen, S., Bai, Y., Lin, G., Huang, J., Han, X., 2007a. Isotopic carbon composition and
related characters of dominant species along an environmental gradient in Inner
Mongolia, China. Journal of Arid Environments 71 (1), 12–28.
Chen, S.P., Bai, Y.F., Lin, G.H., Huang, J.H., Han, X.G., 2007b. Variations in delta C-13
values among major plant community types in the Xilin River Basin, Inner
Mongolia, China. Australian Journal of Botany 55 (1), 48–54.
Cohen, A.S., 2003. Paleolimnology: The History and Evolution of Lake Systems. Oxford
University Press, Oxford. 525 pp.
145
Comstock, J.P., Ehleringer, J.R., 1992. Correlating genetic-variation in carbon isotopic
composition with complex climatic gradients. Proceedings of the National
Academy of Sciences of the United States of America 89 (16), 7747–7751.
Conkright, M.E., Sackett, W.M., 1986. A stable carbon isotope evaluation of the
contribution of terriginous carbon to the marine food web in Bayboro-Harbor,
Tampa-Bay, Florida. Contributions in Marine Science 29, 131–139.
Coplen, T.B., et al., 2006. New guidelines for delta C-13 measurements. Analytical
Chemistry 78 (7), 2439–2441.
Cordell, S., Goldstein, G., Meinzer, F.C., Handley, L.L., 1999. Allocation of nitrogen and
carbon in leaves of Metrosideros polymorpha regulates carboxylation capacity and
delta C-13 along an altitudinal gradient. Functional Ecology 13 (6), 811–818.
Crenshaw, M., 1980. Mechanisms of shell formation and dissolution. In: Rhoads, D.,
Lutz, R. (Eds.), Skeletal Growth of Aquatic Organisms. Plenum Press, New York, NY,
pp. 115–128.
Dawson, T.E., Mambelli, S., Plamboeck, A.H., Templer, P.H., Tu, K.P., 2002. Stable isotopes
in plant ecology. Annual Review of Ecology and Systematics 33, 507–559.
De Lillis, M., Matteucci, G., Valentini, R., 2004. Carbon assimilation, nitrogen, and
photochemical efficiency of different Himalayan tree species along an altitudinal
gradient. Photosynthetica 42 (4), 597–605.
Degens, E.T., Guillard, R.R., Sackett, W.M., Hellebus, Ja., 1968. Metabolic fractionation of
carbon isotopes in marine plankton .I. Temperature and respiration experiments.
Deep-Sea Research 15 (1), 1–9.
Delwiche, C.C., Steyn, P.L., 1970. Nitrogen isotope fractionation in soils and microbial
reactions. Environmental Science & Technology 4 (11), 929–935.
Deniro, M.J., Epstein, S., 1978. Influence of diet on distribution of carbon isotopes in
animals. Geochimica et Cosmochimica Acta 42 (5), 495–506.
Deniro, M.J., Epstein, S., 1981. Influence of diet on the distribution of nitrogen isotopes
in animals. Geochimica et Cosmochimica Acta 45 (3), 341–351.
Deniro, M.J., Hastorf, C.A., 1985. Alteration of N-15 N-14 and C-13 C-12 ratios of plant
matter during the initial-stages of diagenesis — studies utilizing archaeological
specimens from Peru. Geochimica et Cosmochimica Acta 49 (1), 97–115.
Deuser, W.G., 1970. Isotopic evidence for diminishing supply of available carbon during
diatom bloom in Black-Sea. Nature 225 (5237), 1069–1071.
Druffel, E.R.M., Benavides, L.M., 1986. Input of excess CO2 to the surface ocean based on
C-13/C-12 ratios in a banded Jamaican sclerosponge. Nature 321 (6065), 58–61.
Ehleringer, J.R., Cerling, T.E., 1995. Atmospheric CO2 and the ratio of intercellular to
ambient CO2 concentrations in plants. Tree Physiology 15 (2), 105–111.
Ehleringer, J.R., Cooper, T.A., 1988. Correlations between carbon isotope ratio and
microhabitat in desert plants. Oecologia 76 (4), 562–566.
Ehleringer, J.R., Field, C.B., Lin, Z.F., Kuo, C.Y., 1986. Leaf carbon isotope and mineralcomposition in subtropical plants along an irradiance cline. Oecologia 70 (4), 520–526.
Elser, J.J., Marzolf, E.R., Goldman, C.R., 1990. Phosphorus and nitrogen limitation of
phytoplankton growth in the fresh-waters of North-America — a review and
critique of experimental enrichments. Canadian Journal of Fisheries and Aquatic
Sciences 47 (7), 1468–1477.
Engel, M.H., Goodfriend, G.A., Qian, Y.R., Macko, S.A., 1994. Indigeneity of organicmatter in fossils — a test using stable-isotope analysis of amino-acid enantiomers in
Quaternary mollusk shells. Proceedings of the National Academy of Sciences of the
United States of America 91 (22), 10475–10478.
Estep, M.L.F., Vigg, S., 1985. Stable carbon and nitrogen isotope tracers of trophic
dynamics in natural-populations and fisheries of the Lahontan lake system,
Nevada. Canadian Journal of Fisheries and Aquatic Sciences 42 (11), 1712–1719.
Evans, R.D., 2007. Soil nitrogen isotope composition. In: Michener, R.H., Lajtha, K. (Eds.),
Stable Isotopes in Ecology and Environmental Science. Blackwell Publishing,
Chichester, UK, pp. 83–98.
Farquhar, G.D., Oleary, M.H., Berry, J.A., 1982. On the relationship between carbon
isotope discrimination and the inter-cellular carbon-dioxide concentration in
leaves. Australian Journal of Plant Physiology 9 (2), 121–137.
Feranec, R.S., MacFadden, B.J., 2006. Isotopic discrimination of resource partitioning
among ungulates in C-3-dominated communities from the Miocene of Florida and
California. Paleobiology 32 (2), 191–205.
Ferguson, J.C., 1982. A comparative-study of the net metabolic benefits derived from the
uptake and release of free amino-acids by marine-invertebrates. Biological Bulletin
162 (1), 1–17.
Finlay, J.C., Khandwala, S., Power, M.E., 2002. Spatial scales of carbon flow in a river food
web. Ecology 83 (7), 1845–1859.
Flessa, K.W., Cutler, A.H., Meldahl, K.H., 1993. Time and taphonomy — quantitative
estimates of time-averaging and stratigraphic disorder in a shallow marine habitat.
Paleobiology 19 (2), 266–286.
Fogel, M.L., Cifuentes, L.A., 1993. Isotope fractionation during primary production. In:
Engel, M.H., Macko, S.A. (Eds.), Organic Geochemsitry: Principles and Applications.
Plenum Press, New York, NY, pp. 73–98.
Fontugne, M., Duplessy, J.C., 1978. Carbon isotope ratio of marine plankton related to
surface-water masses. Earth and Planetary Science Letters 41 (3), 365–371.
Fox-Dobbs, K., Leonard, J.A., Koch, P.L., 2008. Pleistocene megafauna from eastern
Beringia: paleoecological and paleoenvironmental interpretations of stable carbon
and nitrogen isotope and radiocarbon records. Palaeogeography Palaeoclimatology
Palaeoecology 261 (1–2), 30–46.
France, R.L., 1995a. C-13 enrichment in benthic compared to planktonic algae —
foodweb implications. Marine Ecology-Progress Series 124 (1–3), 307–312.
France, R.L., 1995b. Differentiation between littoral and pelagic food webs in lakes
using stable carbon isotopes. Limnology and Oceanography 40 (7),
1310–1313.
Fricke, H.C., Pearson, D.A., 2008. Stable isotope evidence for changes in dietary niche
partitioning among hadrosaurian and ceratopsian dinosaurs of the Hell Creek
Formation, North Dakota. Paleobiology 34 (4), 534–552.
Author's personal copy
146
M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
Fry, B., 1988. Food web structure on Georges Bank from stable C, N, and S isotopic
compositions. Limnology and Oceanography 33 (5), 1182–1190.
Fry, B., Wainright, S.C., 1991. Diatom sources of C-13-rich carbon in marine food webs.
Marine Ecology-Progress Series 76 (2), 149–157.
Fry, B., Hopkinson, C.S., Nolin, A., Wainright, S.C., 1998. C-13/C-12 composition of
marine dissolved organic carbon. Chemical Geology 152 (1–2), 113–118.
Gannes, L.Z., O'Brien, D.M., Martinez del Rio, C., 1997. Stable isotopes in animal ecology:
assumptions, caveats, and a call for more laboratory experiments. Ecology 78 (4),
1271–1276.
Gearing, J.N., Gearing, P.J., Rudnick, D.T., Requejo, A.G., Hutchins, M.J., 1984. Isotopic
variability of organic-carbon in a phytoplankton-based, temperate estuary.
Geochimica et Cosmochimica Acta 48 (5), 1089–1098.
Geber, M.A., Dawson, T.E., 1990. Genetic-variation in and covariation between leaf gasexchange, morphology, and development in Polygonum arenastrum, an annual
plant. Oecologia 85 (2), 153–158.
Goericke, R., Fry, B., 1994. Variations of marine plankton delta-C-13 with latitude,
temperature, and dissolved CO2 in the world ocean. Global Biogeochemical Cycles
8 (1), 85–90.
Granhall, U., 1981. Biological nitrogen fixation in relation to environmental factors and
functioning of natural ecosystems. In: Clark, F.E., Rosswall, T. (Eds.), Terrestrial
Nitrogen Cycles. Ecological Bulletins, Stockholm, pp. 131–144.
Gu, B., 2009. Variations and controls of nitrogen stable isotopes in particulate organic
matter of lakes. Oecologia 160 (3), 421–431.
Gu, B.H., Schell, D.M., Alexander, V., 1994. Stable carbon and nitrogen isotopic analysis
of the plankton food-web in a sub-Arctic lake. Canadian Journal of Fisheries and
Aquatic Sciences 51 (6), 1338–1344.
Gu, B.H., Schelske, C.L., Brenner, M., 1996. Relationship between sediment and plankton
isotope ratios (delta C-13 and delta N-15) and primary productivity in Florida lakes.
Canadian Journal of Fisheries and Aquatic Sciences 53 (4), 875–883.
Gu, B.H., Chapman, A.D., Schelske, C.L., 2006. Factors controlling seasonal variations in
stable isotope composition of particulate organic matter in a soft water eutrophic
lake. Limnology and Oceanography 51 (6), 2837–2848.
Guehl, J.M., Fort, C., Ferhi, A., 1995. Differential response of leaf conductance, carbonisotope discrimination and water-use efficiency to nitrogen deficiency in maritime
pine and pedunculate oak plants. New Phytologist 131 (2), 149–157.
Hadas, O., Altabet, M.A., Agnihotri, R., 2009. Seasonally varying nitrogen isotope
biogeochemistry of particulate organic matter in Lake Kinneret, Israel. Limnology
and Oceanography 54 (1), 75–85.
Hare, P.E., Abelson, P.H., 1968. Racemization of amino acids in fossil shells. Carnegie
Institute Washington Yearbook 65, 526–528.
Hays, J.D., Imbrie, J., Shackleton, N.J., 1976. Variations in Earth's orbit — pacemaker of ice
ages. Science 194 (4270), 1121–1132.
Heaton, T.H.E., Vogel, J.C., Vonlachevallerie, G., Collett, G., 1986. Climatic influence on
the isotopic composition of bone nitrogen. Nature 322 (6082), 822–823.
Hietz, P., Wanek, W., Popp, M., 1999. Stable isotopic composition of carbon and nitrogen
and nitrogen content in vascular epiphytes along an altitudinal transect. Plant Cell
and Environment 22 (11), 1435–1443.
Hoering, T.C., Ford, H.T., 1960. The isotope effect in the fixation of nitrogen by
Azotobacter. Journal of the American Chemical Society 82 (2), 376–378.
Hogberg, P., Johannisson, C., Hallgren, J.E., 1993. Studies of C-13 in the foliage reveal
interactions between nutrients and water in forest fertilization experiments. Plant
and Soil 152 (2), 207–214.
Holser, W.T., 1997. Geochemical events documented in inorganic carbon isotopes.
Palaeogeography Palaeoclimatology Palaeoecology 132 (1–4), 173–182.
Hultine, K.R., Marshall, J.D., 2000. Altitude trends in conifer leaf morphology and stable
carbon isotope composition. Oecologia 123 (1), 32–40.
Jardine, T.D., Cunjak, R.A., 2005. Analytical error in stable isotope ecology. Oecologia 144
(4), 528–533.
Jennings, S., Warr, K.J., 2003. Environmental correlates of large-scale spatial variation in
the delta N-15 of marine animals. Marine Biology 142 (6), 1131–1140.
Keeley, J.E., Sandquist, D.R., 1992. Carbon — fresh-water plants. Plant Cell and Environment
15 (9), 1021–1035.
Kelly, L.J., Martinez del Rio, C., 2010. The fate of carbon in growing fish: an
experimental study of isotopic routing. Physiological and Biochemical Zoology
83 (3), 473–480.
Kling, G.W., Fry, B., O'Brien, W.J., 1992. Stable isotopes and planktonic trophic structure
in arctic lakes. Ecology 73 (2), 561–566.
Knight, J.D., Thies, J.E., Singleton, P.W., vanKessel, C., 1995. Carbon isotope composition
of N-2-fixing and N-fertilized legumes along an elevational gradient. Plant and Soil
177 (1), 101–109.
Kowalewski, M., Goodfriend, G.A., Flessa, K.W., 1998. High-resolution estimates of
temporal mixing within shell beds: the evils and virtues of time-averaging.
Paleobiology 24 (3), 287–304.
Krause, R.A., et al., 2010. Quantitative comparisons and models of time-averaging in
bivalve and brachiopod shell accumulations. Paleobiology 36 (3), 428–452.
Kroopnick, P.M., 1985. The distribution of C-13 of sigma-CO2 in the world oceans. DeepSea Research Part a — Oceanographic Research Papers 32 (1), 57–84.
Layman, C.A., Post, D.M., 2008. Can stable isotope ratios provide for community-wide
measures of trophic structure? Reply Ecology 89 (8), 2358–2359.
Leavitt, P.R., Brock, C.S., Ebel, C., Patoine, A., 2006. Landscape-scale effects of urban
nitrogen on a chain of freshwater lakes in central North America. Limnology and
Oceanography 51 (5), 2262–2277.
Lehmann, M.F., et al., 2004. Seasonal variation of the delta C-13 and delta N-15 of
particulate and dissolved carbon and nitrogen in Lake Lugano: constraints on
biogeochemical cycling in a eutrophic lake. Limnology and Oceanography 49 (2),
415–429.
Li, M.C., Liu, H.Y., Li, L.X., Yi, X.F., Zhu, X.J., 2007. Carbon isotope composition of plants
along altitudinal gradient and its relationship to environmental factors on the
Qinghai–Tibet Plateau. Polish Journal of Ecology 55 (1), 67–78.
Liu, K.K., Kaplan, I.R., 1989. The eastern tropical Pacific as a source of N-15-enriched nitrate
in seawater off southern-California. Limnology and Oceanography 34 (5), 820–830.
Liu, W.G., et al., 2005. delta C-13 variation of C-3 and C-4 plants across an Asian
monsoon rainfall gradient in arid northwestern China. Global Change Biology 11
(7), 1094–1100.
Long, E.S., Sweitzer, R.A., Diefenbach, D.R., Ben-David, M., 2005. Controlling for
anthropogenically induced atmospheric variation in stable carbon isotope studies.
Oecologia 146 (1), 148–156.
Macfadden, B.J., Cerling, T.E., 1996. Mammalian herbivore communities, ancient feeding
ecology, and carbon isotopes: a 10 million-year sequence from the Neogene of
Florida. Journal of Vertebrate Paleontology 16 (1), 103–115.
MacFadden, B.J., Higgins, P., Clementz, M.T., Jones, D.S., 2004. Diets, habitat preferences,
and niche differentiation of Cenozoic sirenians from Florida: evidence from stable
isotopes. Paleobiology 30 (2), 297–324.
Macko, S.A., Estep, M.L.F., 1984. Microbial alteration of stable nitrogen and carbon
isotope compositions of organic matter. Organic Geochemistry 6, 787–790.
Macko, S.A., Engel, M.H., Bada, J.L., Halstead, B., 1991. Assessment of indigeneity in
fossil organic matter: amino acids and stable isotopes (and discussion).
Philosophical Transactions of the Royal Society B, Biological Sciences 333
(1268), 367–374.
MacLeod, N.A., Barton, D.R., 1998. Effects of light intensity, water velocity, and species
composition on carbon and nitrogen stable isotope ratios in periphyton. Canadian
Journal of Fisheries and Aquatic Sciences 55 (8), 1919–1925.
Mae, A., Yamanaka, T., Shimoyama, S., 2007. Stable isotope evidence for identification of
chemosynthesis-based fossil bivavles associated with cold-seepages. Palaeogeography Palaeoclimatology Palaeoecology 245, 411–420.
Mariotti, A., Pierre, D., Vedy, J.C., Bruckert, S., Guillemot, J., 1980. The abundance of
natural nitrogen 15 in the organic matter of soils along an altitude gradient
(Chablais, Haute-Savoie, France). Catena 7, 293–300.
Marshall, J.D., Brooks, J.R., Lajtha, K., 2007. Sources of variation in the stable isotopic
composition of plants. In: Michener, R.H., Lajtha, K. (Eds.), Stable Isotopes in Ecology
and Environmental Science. Blackwell Publishing, Chichester, UK, pp. 22–60.
Martinez del Rio, C., Wolf, N., Carleton, S.A., Gannes, L.Z., 2009. Isotopic ecology ten
years after a call for more laboratory experiments. Biological Reviews 84 (1),
91–111.
McConnaughey, T., McRoy, C.P., 1979. Food-web structure and the fractionation of
carbon isotopes in the Bering Sea. Marine Biology 53 (3), 257–262.
McCutchan, J.H., Lewis, W.M., Kendall, C., McGrath, C.C., 2003. Variation in trophic shift
for stable isotope ratios of carbon, nitrogen, and sulfur. Oikos 102 (2), 378–390.
McHugh, P.A., McIntosh, A.R., Jellyman, P.G., 2010. Dual influences of ecosystem size
and disturbance on food chain length in streams. Ecology Letters 13 (7), 881–890.
Mead, A.J., 2000. Sexual dimorphism and paleoecology in Teleoceras, a North American
Miocene rhinoceros. Paleobiology 26 (4), 689–706.
Michener, R.H., Kaufman, L., 2007. Stable isotope ratios as tracers in marine food webs:
an update. In: Michener, R.H., Lajtha, K. (Eds.), Stable Isotopes in Ecology and
Environmental Science. Blackwell Publishing, Malden, MA, pp. 238–282.
Mill, A.C., Sweeting, C.J., Barnes, C., Al-Habsi, S.H., MacNeil, M.A., 2008. Massspectrometer bias in stable isotope ecology. Limnology and Oceanography —
Methods 6, 34–39.
Minagawa, M., Wada, E., 1984. Stepwise enrichment of 15N along food chains: further
evidence and the relation between [delta]15N and animal age. Geochimica et
Cosmochimica Acta 48 (5), 1135–1140.
Miyake, Y., Wada, E., 1967. The abundance ratio of 15N/14N in marine environments.
Records of Oceanographic Works of Japan 9, 37–53.
Moens, T., Luyten, C., Middelburg, J.J., Herman, P.M.J., Vincx, M., 2002. Tracing organic
matter sources of estuarine tidal flat nematodes with stable carbon isotopes.
Marine Ecology-Progress Series 234, 127–137.
Montoya, J.P., 1994. Nitrogen fractionation in the modern ocean: implications for the
sedimentary record. In: Zahn, R., Pedersen, T.F., Kaminski, M.A., Labeyrie, L. (Eds.),
Carbon Cycling in the Glacial Ocean: Constraints on the Ocean's Role in Global
Change. Springer, Berlin, pp. 259–279.
Montoya, J.P., 2007. Natural abundance of 15N in marine planktonic ecosystems. In:
Michener, R.H., Lajtha, K. (Eds.), Stable Isotopes in Ecology and Environmental
Science. Balckwell Publishing, Malden, MA, pp. 176–201.
Montoya, J.P., Wiebe, P.H., McCarthy, J.J., 1992. Natural abundance of N-15 in
particulate nitrogen and zooplankton in the Gulf-Stream region and warm-core
ring 86a. Deep-Sea Research Part a — Oceanographic Research Papers 39 (1A),
S363–S392.
Moore, J.W., Semmens, B.X., 2008. Incorporating uncertainty and prior information into
stable isotope mixing models. Ecology Letters 11 (5), 470–480.
Mullin, M.M., Rau, G.H., Eppley, R.W., 1984. Stable nitrogen isotopes in zooplankton —
some geographic and temporal variations in the north Pacific. Limnology and
Oceanography 29 (6), 1267–1273.
Nozaki, Y., Rye, D.M., Turekian, K.K., Dodge, R.E., 1978. 200-year record of C-13 and C-14
variations in a Bermuda coral. Geophysical Research Letters 5 (10), 825–828.
O'Leary, M.H., 1981. Carbon isotope fractionation in plants. Phytochemistry 20 (4),
553–567.
O'Leary, M.H., 1988. Carbon isotopes in photosynthesis. Bioscience 38 (5), 328–336.
Olsen, P.E., 1986. A 40-million-year lake record of early Mesozoic orbital climatic
forcing. Science 234 (4778), 842–848.
Olsen, P.E., 1990. Tectonic, climatic, and biotic modulation of lacustrine ecosystems;
examples from Newark Supergroup of eastern North America. Lacustrine basin
exploration; CAS studies and modern analogs. AAPG Memoir 50, 209–224.
Author's personal copy
M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
Ostrom, P.H., Macko, S.A., Engel, M.H., Silfer, J.A., Russell, D., 1990. Geochemical
characterization of high-molecular-weight material isolated from Late Cretaceous
fossils. Organic Geochemistry 16 (4–6), 1139–1144.
Ostrom, P.H., Macko, S.A., Engel, M.H., Russell, D.A., 1993. Assessment of trophic
structure of cretaceous communities based on stable nitrogen isotope analyses.
Geology 21 (6), 491–494.
Ostrom, P.H., Zonneveld, J.P., Robbins, L.L., 1994. Organic geochemistry of hard parts —
assessment of isotopic variability and indigeneity. Palaeogeography Palaeoclimatology Palaeoecology 107 (3–4), 201–212.
Ostrom, N.E., Long, D.T., Bell, E.M., Beals, T., 1998. The origin and cycling of particulate
and sedimentary organic matter and nitrate in Lake Superior. Chemical Geology
152 (1–2), 13–28.
Owens, N.J.P., 1987. Natural variations in N-15 in the marine-environment. Advances in
Marine Biology 24, 389–451.
Panek, J.A., Waring, R.H., 1995. Carbon-isotope variation in Douglas-fir foliage —
improving the delta-C-13–climate relationship. Tree Physiology 15 (10), 657–663.
Parnell, A.C., Inger, R., Bearhop, S., Jackson, A.L., 2010. Source partitioning using stable
isotopes: coping with too much variation. Plos One 5 (3).
Pate, F.D., 1995. Stable carbon-isotope assessment of hunter–gatherer mobility in
prehistoric South Australia. Journal of Archaeological Science 22 (1), 81–87.
Peterson, B.J., Fry, B., 1987. Stable isotopes in ecosystem studies. Annual Review of
Ecology and Systematics 18, 293–320.
Peterson, B.J., Howarth, R.W., Garritt, R.H., 1985. Multiple stable isotopes used to trace
the flow of organic-matter in estuarine food webs. Science 227 (4692),
1361–1363.
Phillips, D.L., 2001. Mixing models in analyses of diet using multiple stable isotopes: a
critique. Oecologia 127 (2), 166–170.
Phillips, D.L., Gregg, J.W., 2001. Uncertainty in source partitioning using stable isotopes.
Oecologia 127 (2), 171–179.
Phillips, D.L., Gregg, J.W., 2003. Source partitioning using stable isotopes: coping with
too many sources. Oecologia 136 (2), 261–269.
Phillips, D.L., Koch, P.L., 2002. Incorporating concentration dependence in stable isotope
mixing models. Oecologia 130 (1), 114–125.
Polley, H.W., Johnson, H.B., Derner, J.D., 2002. Soil- and plant-water dynamics in a C3/C4
grassland exposed to a subambient to superambient CO2 gradient. Global Change
Biology 8 (11), 1118–1129.
Popp, B.N., et al., 1998. Effect of phytoplankton cell geometry on carbon isotopic
fractionation. Geochimica et Cosmochimica Acta 62 (1), 69–77.
Post, D.M., 2002a. The long and short of food-chain length. Trends in Ecology &
Evolution 17 (6), 269–277.
Post, D.M., 2002b. Using stable isotopes to estimate trophic position: models, methods,
and assumptions. Ecology 83 (3), 703–718.
Post, D.M., 2003. Individual variation in the timing of ontogenetic niche shifts in
largemouth bass. Ecology 84 (5), 1298–1310.
Post, D.M., Pace, M.L., Hairston, N.G., 2000. Ecosystem size determines food-chain
length in lakes. Nature 405 (6790), 1047–1049.
Post, D.M., et al., 2007. Getting to the fat of the matter: models, methods and assumptions
for dealing with lipids in stable isotope analyses. Oecologia 152 (1), 179–189.
Qian, Y.R., Engel, M.H., Goodfriend, G.A., Macko, S.A., 1995. Abundance and stable carbon
isotope composition of amino acids in molecular weight fractions of fossil and artificially
aged mollusk shells. Geochimica et Cosmochimica Acta 59 (6), 1113–1124.
Rau, G.H., 1978. Conifer needle processing in a subalpine lake. Limnology and
Oceanography 23 (2), 356–358.
Rau, G.H., 1980. Carbon-13–carbon-12 variation in subalpine lake aquatic insects — food
source implications. Canadian Journal of Fisheries and Aquatic Sciences 37 (4), 742–746.
Rau, G.H., Sweeney, R.E., Kaplan, I.R., 1982. Plankton C-13–C-12 ratio changes with
latitude — differences between northern and southern oceans. Deep-Sea Research
Part a — Oceanographic Research Papers 29 (8), 1035–1039.
Rau, G.H., Teyssie, J.L., Rassoulzadegan, F., Fowler, S.W., 1990. C-13/C-12 and N-15/N-14
variations among size-fractionated marine particles — implications for their origin
and trophic relationships. Marine Ecology-Progress Series 59 (1–2), 33–38.
Rau, G.H., Takahashi, T., Desmarais, D.J., Sullivan, C.W., 1991. Particulate organic-matter
delta-C-13 variations across the Drake Passage. Journal of Geophysical ResearchOceans 96 (C8), 15131–15135.
Raymond, P.A., Bauer, J.E., 2001. Use of C-14 and C-13 natural abundances for evaluating
riverine, estuarine, and coastal DOC and POC sources and cycling: a review and
synthesis. Organic Geochemistry 32 (4), 469–485.
Roden, J.S., Bowling, D.R., McDowell, N.G., Bond, B.J., Ehleringer, J.R., 2005. Carbon and
oxygen isotope ratios of tree ring cellulose along a precipitation transect in Oregon,
United States. Journal of Geophysical Research-Biogeosciences 110 (G2).
Rountrey, A.N., Fisher, D.C., Vartanyan, S., Fox, D.L., 2007. Carbon and nitrogen isotope
analyses of a juvenile woolly mammoth tusk: evidence of weaning. Quaternary
International 169, 166–173.
Royer, D.L., Berner, R.A., Park, J., 2007. Climate sensitivity constrained by CO2
concentrations over the past 420 million years. Nature 446 (7135), 530–532.
Rullkötter, J., 2006. Organic matter: the driving force for diagenesis. In: Schulz, H.D.,
Zabel, M. (Eds.), Marine Geochemistry. Springer, Berlin, Germany, pp. 151–153.
Sackett, W.M., Moore, W.S., 1966. Isotopic variations of dissolved inorganic carbon.
Chemical Geology 1, 232–238.
Sackett, W.M., Eckelman, W.R., Bender, M.L., Be, A.W.H., 1965. Temperature dependence of
carbon isotope composition in marine plankton and sediments. Science 148 (3667),
235–237.
Saino, T., Hattori, A., 1980. N-15 natural abundance in oceanic suspended particulate
matter. Nature 283 (5749), 752–754.
Sandquist, D.R., Ehleringer, J.R., 1995. Carbon-isotope discrimination in the C-4 shrub
Atriplex confertifolia along a salinity gradient. Great Basin Naturalist 55 (2), 135–141.
147
Sarnethein, M., et al., 1994. Changes in east Atlantic deepwater circulation over the last
30,000 years: eight time slice reconstructions. Paleoceanography 9, 209–268.
Savage, C., 2005. Tracing the influence of sewage nitrogen in a coastal ecosystem using
stable nitrogen isotopes. Ambio 34, 143–148.
Schoeninger, M.J., Deniro, M.J., Tauber, H., 1983. Stable nitrogen isotope ratios of bonecollagen reflect marine and terrestrial components of prehistoric human diet.
Science 220 (4604), 1381–1383.
Schulte, S., et al., 2003. Stable carbon isotopic composition of the C37:2 alkenone: a
proxy for CO2(aq) concentration in oceanic surface waters? In: Wefer, G., Mulitza, S.,
Rathmeyer, V. (Eds.), The South Atlantic in the Late Quaternary: Reconstruction of
Material Budgets and Current Systems. Springer, Berlin, pp. 195–211.
Schulze, E.D., Ziegler, H., Stichler, W., 1976. Environmental-control of crassulacean acid
metabolism in Welwitschia mirabilis hook fil in its range of natural distribution in
Namib Desert. Oecologia 24 (4), 323–334.
Schulze, E.D., et al., 1998. Carbon and nitrogen isotope discrimination and nitrogen
nutrition of trees along a rainfall gradient in northern Australia. Australian Journal
of Plant Physiology 25 (4), 413–425.
Schulze, E.D., Turner, N.C., Nicolle, D., Schumacher, J., 2006. Leaf and wood carbon
isotope ratios, specific leaf areas and wood growth of Eucalyptus species across a
rainfall gradient in Australia. Tree Physiology 26 (4), 479–492.
Schurr, M.R., 1992. Isotopic and mortuary variability in a Middle Mississippian
population. American Antiquity 57 (2), 300–320.
Schurr, M.R., 1998. Using stable nitrogen-isotopes to study weaning behavior in past
populations. World Archaeology 30 (2), 327–342.
Schurr, M.R., Schoeninger, M.J., 1995. Associations between agricultural intensification
and social complexity — an example from the prehistoric Ohio Valley. Journal of
Anthropological Archaeology 14 (3), 315–339.
Schwarcz, H.P., 1991. Some theoretical aspects of isotope paleodiet studies. Journal of
Archaeological Science 18 (3), 261–275.
Sealy, J.C., Van der Merwe, N.J., 1986. Isotope assessment and the seasonal-mobility
hypothesis in the southwestern cape of South-Africa. Current Anthropology 27 (2),
135–150.
Sealy, J.C., Van der Merwe, N.J., Thorp, J.A.L., Lanham, J.L., 1987. Nitrogen isotopic
ecology in southern-Africa — implications for environmental and dietary tracing.
Geochimica et Cosmochimica Acta 51 (10), 2707–2717.
Serban, A., Engel, M.H., Macko, S.A., 1988. The distribution, stereochemistry and stable
isotopic composition of amino-acid constituents of fossil and modern mollusk
shells. Organic Geochemistry 13 (4–6), 1123–1129.
Shackleton, N.J., 1977. Tropical rainforest history and the equatorial Pacific carbonate
dissolution cycles. In: Anderson, N.R., Malahoff, A. (Eds.), Fate in Fossil Fuel CO2 in
the Oceans. Plenum, New York, NY, pp. 401–427.
Shearer, G., Kohl, D.H., 1986. N-2-fixation in field settings — estimations based on
natural N-15 abundance. Australian Journal of Plant Physiology 13 (6), 699–756.
Shearer, G., Kohl, D.H., Chien, S.H., 1978. N-15 abundance in a wide variety of soils. Soil
Science Society of America Journal 42 (6), 899–902.
Shearer, G., et al., 1983. Estimates of N-2-fixation from variation in the natural
abundance of N-15 in Sonoran Desert ecosystems. Oecologia 56 (2–3), 365–373.
Sherr, E.B., 1982. Carbon isotope composition of organic seston and sediments in a
Georgia salt-marsh estuary. Geochimica et Cosmochimica Acta 46 (7),
1227–1232.
Shilling, F.M., Manahan, D.T., 1990. Energetics of early development for the sea-urchins
Strongylocentrotus purpuratus and Lytechinus pictus and the Crustacean Artemia sp.
Marine Biology 106 (1), 119–127.
Sigman, D.M., et al., 1997. Natural abundance-level measurement of the nitrogen
isotopic composition of oceanic nitrate: an adaptation of the ammonia diffusion
method. Marine Chemistry 57 (3–4), 227–242.
Sigman, D.M., Altabet, M.A., McCorkle, D.C., Francois, R., Fischer, G., 2000. The delta N-15
of nitrate in the Southern Ocean: nitrogen cycling and circulation in the ocean
interior. Journal of Geophysical Research-Oceans 105 (C8), 19599–19614.
Simenstad, C.A., Wissmar, R.C., 1985. Delta-C-13 evidence of the origins and fates of
organic-carbon in estuarine and nearshore food webs. Marine Ecology-Progress
Series 22 (2), 141–152.
Smith, F.A., Walker, N.A., 1980. Photosynthesis by aquatic plants — effects of unstirred
layers in relation to assimilation of CO2 and HCO3- and to carbon isotopic
discrimination. New Phytologist 86 (3), 245–259.
Sparks, J.P., Ehleringer, J.R., 1997. Leaf carbon isotope discrimination and nitrogen
content for riparian trees along elevational transects. Oecologia 109 (3), 362–367.
Stewart, G.R., Turnbull, M.H., Schmidt, S., Erskine, P.D., 1995. C-13 natural-abundance in
plant-communities along a rainfall gradient — a biological integrator of water
availability. Australian Journal of Plant Physiology 22 (1), 51–55.
Stumm, W., Morgan, J.J., 1981. Aquatic Chemistry: An Introduction Emphasizing
Chemical Equilibria in Natural Waters. Wiley-Interscience, New York. 780 pp.
Swap, R.J., Aranibar, J.N., Dowty, P.R., Gilhooly, W.P., Macko, S.A., 2004. Natural
abundance of C-13 and N-15 in C-3 and C-4 vegetation of southern Africa: patterns
and implications. Global Change Biology 10 (3), 350–358.
Syvaranta, J., Tiirola, M., Jones, R.I., 2008. Seasonality in lake pelagic delta N-15 values:
patterns, possible explanations, and implications for food web baselines.
Fundamental and Applied Limnology 172 (3), 255–262.
Takimoto, G., Spiller, D.A., Post, D.M., 2008. Ecosystem size, but not disturbance,
determines food-chain length on islands of the Bahamas. Ecology 89 (11), 3001–3007.
Tauber, H., 1981. C-13 evidence for dietary habits of prehistoric man in Denmark.
Nature 292 (5821), 332–333.
Tieszen, L.L., Farge, T., 1993. Effect of diet quality and composition on the isotopic
composition of respiratory CO2, bone collagen, bioapatite, and soft tissues. In:
Lambert, J., Grupe, G. (Eds.), Molecular Archaeology of Prehistoric Human Bone.
Springer-Verlag, Berlin, Germany, pp. 123–135.
Author's personal copy
148
M.M. Casey, D.M. Post / Earth-Science Reviews 106 (2011) 131–148
Townsend-Small, A., McClain, M.E., Brandes, J.A., 2005. Contributions of carbon and
nitrogen from the Andes Mountains to the Amazon River: evidence from an
elevational gradient of soils, plants, and river material. Limnology and Oceanography 50 (2), 672–685.
Van de Water, P.K., Leavitt, S.W., Betancourt, J.L., 2002. Leaf delta C-13 variability with
elevation, slope aspect, and precipitation in the southwest United States. Oecologia
132 (3), 332–343.
Van der Merwe, N.J., Vogel, J.C., 1978. C-13 content of human collagen as a measure of
prehistoric diet in Woodland North-America. Nature 276 (5690), 815–816.
Van Wagoner, J.C., et al., 1988. An overview of the fundamentals of sequence stratigraphy
and key definitions. In: Wilgus, C.K., Hastings, B.S., Posamentier, H.W., Ross, C.A.,
Kendall, C.G.S.C. (Eds.), Sea-level Changes: An Integrated Approach. Society or
Ecomonic Paleontologists and Mineralogists, p. 407.
Vanbennekom, A.J., Wetsteijn, F.J., 1990. The winter distribution of nutrients in the
southern bight of the North-Sea (1961–1978) and in the estuaries of the Scheldt
and the Rhine Meuse. Netherlands Journal of Sea Research 25 (1–2), 75–87.
Vander Zanden, M.J., Fetzer, W.W., 2007. Global patterns of aquatic food chain length.
Oikos 116 (8), 1378–1388.
Vander Zanden, M.J., Rasmussen, J.B., 1999. Primary consumer delta C-13 and delta N15 and the trophic position of aquatic consumers. Ecology 80 (4), 1395–1404.
Vander Zanden, M.J., Rasmussen, J.B., 2001. Variation in delta N-15 and delta C-13
trophic fractionation: implications for aquatic food web studies. Limnology and
Oceanography 46 (8), 2061–2066.
Vander Zanden, M.J., Shuter, B.J., Lester, N., Rasmussen, J.B., 1999. Patterns of food chain
length in lakes: a stable isotope study. American Naturalist 154 (4), 406–416.
Vander Zanden, M.J., Vadeboncoeur, Y., Diebel, M.W., Jeppesen, E., 2005. Primary
consumer stable nitrogen isotones as indicators of nutrient source. Environmental
Science & Technology 39 (19), 7509–7515.
Vanderklift, M.A., Ponsard, S., 2003. Sources of variation in consumer-diet delta N-15
enrichment: a meta-analysis. Oecologia 136 (2), 169–182.
Vitousek, P.M., Shearer, G., Kohl, D.H., 1989. Foliar N-15 natural abundance in Hawaiian
rainforest — patterns and possible mechanisms. Oecologia 78 (3), 383–388.
Vitousek, P.M., Field, C.B., Matson, P.A., 1990. Variation in foliar Delta-C-13 in Hawaiian
Metrosideros polymorpha — a case of internal resistance. Oecologia 84 (3), 362–370.
Voss, M., Altabet, M.A., vonBodungen, B., 1996. delta N-15 in sedimenting particles as
indicator of euphotic-zone processes. Deep-Sea Research Part I — Oceanographic
Research Papers 43 (1), 33–47.
Wachniew, P., Rozanski, K., 1997. Carbon budget of a mid-latitude, groundwatercontrolled lake: isotopic evidence for the importance of dissolved inorganic carbon
recycling. Geochimica et Cosmochimica Acta 61 (12), 2453–2465.
Wada, E., 1980. Nitrogen isotope fractionation and its significance in biogeochemical
processes occurring in marine environments. In: Goldberg, E.D., Horibe, Y.,
Saruhashi, K. (Eds.), Isotope Marine Chemistry. Uchida Rokahuko Publishing
Company, Tokyo, pp. 375–398.
Wada, E., Hattori, A., 1978. Nitrogen isotope effects in the assimilation of inorganic
nitrogenous compounds by marine diatoms. Geomicrobiology Journal 1 (1),
85–101.
Wainwright, S.C., Fry, B., 1994. Seasonal-variation of the stable isotopic compositions of
coastal marine plankton from Woods-Hole, Massachusetts and Georges-Bank.
Estuaries 17 (3), 552–560.
Walters, A.W., Post, D.M., 2008. An experimental disturbance alters fish size structure
but not food chain length in streams. Ecology 89 (12), 3261–3267.
Walters, A.W., Barnes, R.T., Post, D.M., 2009. Anadromous alewives (Alosa pseudoharengus) contribute marine-derived nutrients to coastal stream food webs. Canadian
Journal of Fisheries and Aquatic Sciences 66 (3), 439–448.
Wang, Y., Cerling, T.E., Macfadden, B.J., 1994. Fossil horses and carbon isotopes —
new evidence for Cenozoic dietary, habitat, and ecosystem changes in NorthAmerica. Palaeogeography Palaeoclimatology Palaeoecology 107 (3–4),
269–279.
Welker, J.M., et al., 1993. Leaf carbon-isotope discrimination and vegetative responses
of Dryas octopetala to temperature and water manipulations in a high arctic polar
semidesert, Svalbard. Oecologia 95 (4), 463–469.
Wienke, C., Fisher, G., 1990. Growth and stable isotope composition of cold-water
macroalgae in relation to light and temperature. Marine Ecology-Progress Series
65, 283–292.
Williams, D.G., Ehleringer, J.R., 1996. Carbon isotope discrimination in three semi-arid
woodland species along a monsoon gradient. Oecologia 106 (4), 455–460.
Williams, D.G., et al., 2001. Carbon isotope discrimination by Sorghum bicolor under CO2
enrichment and drought. New Phytologist 150 (2), 285–293.
Wood, S.L.B., Krause, R.A., Kowalewski, M., Wehmiller, J., Simoes, M.G., 2006. Aspartic
acid racemization dating of Holocene brachiopods and bivalves from the southern
Brazilian shelf, South Atlantic. Quaternary Research 66 (2), 323–331.
Wright, S.H., Manahan, D.T., 1989. Integumental nutrient-uptake by aquatic organisms.
Annual Review of Physiology 51, 585–600.
Wu, J.P., Calvert, S.E., Wong, C.S., 1997. Nitrogen isotope variations in the subarctic
northeast Pacific: relationships to nitrate utilization and trophic structure. DeepSea Research Part I — Oceanographic Research Papers 44 (2), 287–314.
Xie, Y.X., Xiong, Z.Q., Xing, G.X., Sun, G.Q., Zhu, Z.L., 2007. Assessment of nitrogen
pollutant sources in surface waters of Taihu Lake region. Pedosphere 17 (2),
200–208.
Yoder, B.J., Ryan, M.G., Waring, R.H., Schoettle, A.W., Kaufmann, M.R., 1994. Evidence of
reduced photosynthetic rates in old trees. Forest Science 40 (3), 513–527.