Download Differential cell size optimization strategies produce distinct diatom

Journal of
Ecology 2007
95, 745–754
Differential cell size optimization strategies produce
distinct diatom richness–body size relationships in stream
benthos and plankton
Blackwell Publishing Ltd
SOPHIA I. PASSY
Department of Biology, University of Texas at Arlington, Box 19498, Arlington, TX 76019, USA
Summary
1 The relationship between species richness and body size is one of the most thoroughly
studied subjects in animal ecology; however, this relationship and its underlying
mechanisms are largely unknown in photosynthetic organisms, especially protists.
2 In this continental study, I first examined the number of diatom species across the cell
size spectrum in benthic and planktonic stream habitats. The relationship was rightskewed unimodal and was significantly different between the benthos and the plankton;
larger sizes were more speciose in the benthos, and smaller sizes in the plankton. The
species richness peaks were explained with allometric trade-offs between maximum
nutrient uptake rate and dispersal in the benthos but maximum nutrient uptake rate and
sinking resistance in the phytoplankton.
3 I also explored the cell size similarity among species and across environments. Small
diatoms were significantly more similar in size than large diatoms, and benthic diatoms
were significantly more similar than planktonic diatoms.
4 This is the first continental study on the richness–body size relationship in algae,
which suggests that the environmental differences between benthic and planktonic
habitats generated allometric trade-offs that have driven the cell size optimization
towards larger species in the benthos but smaller in the plankton. The patterns of cell
size similarity revealed a higher niche overlap in the benthos than in the phytoplankton
and among small species than among large species. These findings indicate that
interspecific competition in stream diatoms, which is a function of niche differentiation,
is habitat-specific and inversely related to cell size.
Key-words: allometric scaling laws, benthos, biodiversity, diatom, macroecology,
NAWQA, periphyton, phytoplankton, species richness, trade-offs.
Journal of Ecology (2007) 95, 745–754
doi: 10.1111/j.1365-2745.2007.01248.x
Introduction
© 2007 The Author
Journal compilation
© 2007 British
Ecological Society
The relationships of species richness with sampling
area, productivity and body size are probably the three
most extensively studied topics in ecology. While the
first two relationships have been examined by animal
and plant ecologists alike, the third one has been
grossly overlooked in the plant literature despite a long
and inspiring history of research in animal ecology (for
an exhaustive review see Allen et al. 2006). The change
in species richness with body size, i.e. the richness–body
Correspondence: Sophia I. Passy
(e-mail [email protected]).
size relationship, most often conforms to a rightskewed unimodal distribution (May 1986; Siemann
et al. 1996). Still, what mechanisms generate the
richness–body size relationship and whether it is
consistent with scale, latitude and habitat heterogeneity
and across taxonomic categories are subjects of active
research (Blackburn & Gaston 1994; Bakker & Kelt
2000; Gaston et al. 2001; Kozlowski & Gawelczyk
2002; Niklas et al. 2003; Knouft 2004; McClain 2004).
Traditionally, the unimodal shape of the richness–
body size relationship has been explained with various
allometric trade-offs, whereby small and large sizes are
advantageous under different conditions and the
richness peaks at intermediate sizes, which can be
746
S. I. Passy
© 2007 The Author
Journal compilation
© 2007 British
Ecological Society,
Journal of Ecology,
95, 745–754
beneficial under most conditions. However, as the
number of intermediate size species increases so does
the competition among them, which in turn forces
species towards sizes of lower adaptive value but
comparatively less intense negative interspecific
interactions. For example, a trade-off between speciation
and extinction, with speciation favouring small species
and extinction, small or large species, depending upon
environmental stability, generates unimodal distributions (Dial & Marzluff 1988). A unimodal distribution
could be the result of a trade-off between energy uptake
and energy conversion to offspring, with large species
being superior in resource acquisition and small species
superior in conversion of resources into reproductive
work (Brown et al. 1993). A trade-off between food
patch size increasing with consumer body size and
tolerance to low resource concentration in the patch
decreasing with consumer body size provided the
theoretical basis of the synthetic theory of biodiversity,
which predicted a unimodal but left-skewed richness–
body size relationship and higher body size similarity
in larger species (Ritchie & Olff 1999). A model
incorporating allometric scaling laws of the number of
individuals and speciation rate decreasing with body
size and active dispersal increasing with body size
produced maximum species richness at intermediate
body sizes (Etienne & Olff 2004). A trade-off between
production and mortality has also been invoked to
explain the unimodal body size distribution (Kozlowski
& Weiner 1997; Kindlmann et al. 1999).
A completely different suite of driving forces has
been proposed in elucidating the unimodal rightskewed richness–body size relationships in plants. It
has been suggested that large plant species were selected
against because they exhibit lower niche differentiation
and fecundity allocation, and require environmental
conditions that were uncommon throughout evolutionary history (Aarssen et al. 2006). The richness–
body size relationship in algae has received very little
attention and primarily in plankton studies (Havlicek
& Carpenter 2001; Scheffer & van Nes 2006). In the
periphyton this relationship remains unknown at
continental scales, although slightly right-skewed and
symmetrical distributions have been reported at regional
and watershed scales, respectively (Soininen &
Kokocinski 2006).
Diatoms differ from both animals and plants and it
is to be expected that the mechanisms generating their
richness–body size relationships are also different. For
example, diatom dispersal involves the mature organism
(like in animals) and not the reproductive structures
such as spores or seeds (like in plants). However, like
plants, diatoms are passive dispersers despite the
ability of many raphe-bearing species to move in their
immediate vicinity; therefore dispersal should scale
negatively with body size. The resources used by
diatoms, unlike animals, do not form discrete units such
as prey or patches of vegetation; consequently, the size
optimization in diatoms is not driven by the size of their
food. Unlike both animals and plants, diatom mortality is
a response to unfavourable environmental changes or
grazing but not a natural completion of their lives when
cell division, i.e. reproduction, takes place. Therefore,
mortality can affect but cannot govern the body size
distributions in diatoms. Finally, streams are highly
heterogeneous ecosystems where, even within a single
reach, there are areas of low and high disturbance (e.g.
the margins vs. the thalweg) and areas of lower and
higher nutrient levels (e.g. hard vs. soft substrates).
Hence, in each stream reach there are conditions of low
disturbance and higher nutrient levels that would support
large diatoms. This contrasts with terrestrial systems,
where undisturbed and nutrient-rich habitats required
by large plants were historically rare (Aarssen et al. 2006).
Important properties of algal communities, such
as taxonomic organization and biomass–richness
relationships, were shown to be significantly different
between planktonic and benthic stream algae (Passy &
Legendre 2006a,b). Planktonic communities comprised
fewer but more distantly related species and reached
peak biomass at lower species richness than benthic
communities. These differences were attributed to the
existence of fewer and shorter environmental gradients
in the phytoplankton, forcing a stronger niche differentiation among species. Taxonomic and biomassrichness structures of a community correlate with
organismal body size, which is thus expected to exhibit
different distributional patterns in the plankton and
benthos. To test this hypothesis, I examined the richness–
body size distributions of planktonic and benthic
diatoms collected from all major watersheds in the
United States by the National Water-Quality Assessment
(NAWQA) Program. I hypothesized that the richness–
body size relationship would be governed by similar
physiological but different ecological factors in the two
habitats. Nutrient uptake rate, which is determined by
algal cell size irrespective of the habitat, i.e. freshwater
or marine (Grover 1989; Aksnes & Egge 1991; Stolte
et al. 1994; Wen et al. 1997), is expected to drive the cell
size optimization in both planktonic and benthic diatoms. However, the environmental conditions in these
two habitats are vastly different and dispersal can be
hindered in the heterogeneous benthic environments.
Successful dispersal must include: dislodgement from
the substrate (emigration), entraining and remaining in
the water flow (suspension), and reaching suitable
substrates (immigration), where individuals can establish
and start reproducing. Dispersal is of much lesser
importance in the plankton, where algae dwell and
reproduce in their characteristic habitat or are constantly
imported from the benthos. Sinking, on the other hand,
which is strongly dependent on cell size, can interfere
with life-supporting processes in the phytoplankton
such as photosynthesis and growth. Therefore, it is
suggested here that cell size distributions can be
determined by the combined effect of nutrient uptake
rate and dispersal in the benthos, and by nutrient
uptake rate and sinking in the phytoplankton. While
747
Cell size
organization in
stream diatoms
data exist on algal nutrient uptake and sinking velocity
(discussed below), to my knowledge there is no comprehensive research on diatom dispersal but only
partial studies on immigration and emigration, which
do influence dispersal but do not equate with it. Here,
dispersal was specifically examined in an independent
data set, derived from an extensive 2-year spatial
survey of three reaches in Batavia Kill, a highland
stream in New York State (Passy & Blanchet 2007).
The objectives of the present study were: (i) to determine the continental richness–body size relationships in planktonic and benthic diatoms; (ii) to assess
whether these relationships could be explained with the
interplay of physiological and ecological allometries,
derived from independent investigations; and (iii) to
determine how similar in biovolume diatoms are along
their cell size spectrum, which has implications for their
niche differentiation and consequently competition
strength.
Materials and methods
 
The NAWQA data set
© 2007 The Author
Journal compilation
© 2007 British
Ecological Society,
Journal of Ecology,
95, 745–754
The NAWQA data set analysed here contains 4778
diatom samples from more than 50 major river basins
and aquifers across the USA, including sites in Alaska
and Hawaii. Three habitat types, defined by the
NAWQA, were quantitatively sampled for algae: hard
substrates in richest targeted habitats (RTH), soft
substrates in depositional targeted habitats (DTH),
and phytoplankton (for details see http://water.usgs.gov/
nawqa/protocols/OFR02-150/OFR02-150.pdf). RTH
maintain the taxonomically richest community and
encompass the following habitats: (i) shallow riffles in
areas with coarse-grained substrates (epilithon); (ii)
woody snags in reaches with fine-grained substrates
(epidendron); and (iii) macrophytes where riffles or
woody snags are absent (epiphyton). DTH microalgae
are found in organically rich or sandy depositional
areas along the stream margins, including epipelic and
epipsammic habitats. Both RTH and DTH were
sampled from a defined area of substrate. Phytoplankton
is a community of suspended algae collected from 1 L
of water in nutrient-rich streams or 5 L of water in
unproductive, nutrient-poor streams. More information
on the habitats and sampling techniques is given in
Passy & Legendre (2006b). The NAWQA data set
comprises 2699 RTH, 1682 DTH and 397 phytoplankton
samples collected year round between March 1993 and
September 2003.
Sample processing and algal enumeration and identification, followed by assessment of algal biovolumes,
were carried out by specialized phycology laboratories
(for details see http://diatom.acnatsci.org/nawqa/
protocols.asp). Briefly, soft algae and diatoms were
enumerated, followed by diatom identification in
permanent mounts prepared from acid-digested samples.
Biovolume was calculated for all taxa in a sample after
approximation to simple geometric figures. In this
study only the diatoms were considered because they
are truly single celled algae and diatom cell biovolume
is equivalent to organismal body size. Many diatoms
form colonies but there is no exchange of materials
among cells and therefore the colonial habit is unlikely
to directly influence the nutrient uptake rate. Colonies
and cell shapes deviating from a sphere can greatly
reduce the sinking velocity of planktonic diatoms and
this was partially taken into consideration in the
calculation of sinking resistance (see below).
The Batavia Kill data set
Spatial surveys of algae were carried out in 2001 and
2002 in three 100-m cobble-bottom reaches within a
5-km stretch of Batavia Kill, an upland stream within
the New York City Watershed (Passy & Blanchet 2007).
The three reaches differed in geomorphic status and
canopy cover. The upstream reach was geomorphically
stable, with significantly greater depth and larger particle
size than the other two reaches. The midstream and
downstream reaches were geomorphically unstable.
After the first survey, the downstream treatment reach
was subjected to a large-scale restoration, including the
re-channelling and bank stabilization of 1.6 km of
stream. Canopy cover, measured in the three reaches in
both years, averaged 82% in the stable reach and 17%
in the midstream reach. The treatment reach was
completely deforested before and after the first year of
restoration. Algae were collected in a regular spatial
grid approximately every 50 cm across the stream and
every 10 m along the stream from 7.55 cm2 of rock surface.
Samples were preserved in 4% formaldehyde. The
surveys were conducted during 11–13 July 2001 and
9 –11 July 2002, with 248 and 223 samples collected,
respectively. For diatom identification, samples were
digested with acids and mounted in Naphrax®
(PhycoTech Inc., St Joseph, MI, USA). At least 300
frustules were counted with a 100 × 1.35 NA oil immersion
objective. Biovolume data for the diatom species were
obtained from the NAWQA data set, which includes
numerous sites in New York State.
 
The NAWQA data set
Body size frequency distributions were explored in the
following way. The average cell biovolume for each
species across all samples was calculated and lntransformed. In each habitat, the ln-biovolume
spectrum was subdivided into 12 classes (bin size of one
unit on a ln-scale) and the number of species in each
class was counted. The results were generally robust to
increases in bin size; a decrease in bin size allowed the
emergence of small local peaks but did not alter the
position of the major peak, which remained invariant.
748
S. I. Passy
The three habitats were analysed with a contingency
table testing the null hypothesis that species richness
distributions were independent of habitat type. The
significance of skewness and kurtosis in ln-biovolume
was determined by dividing the absolute value of the
respective statistic by its standard error; if the ratio was
greater than 2 then the statistic was significantly
different from zero ( 11 2004).
For all samples in a habitat, the ratio of larger-tosmaller diatom species adjacent in size (henceforth
referred to as biovolume ratio) was examined as a
function of the ln-biovolume of the larger diatom using
a LOWESS smoother. The smoothing technique suggested a threshold behaviour of the dependent variable,
which showed a different linear response on both sides
of a threshold value of the predictor. This behaviour
was modelled with a piece-wise linear regression using
 11. The model was defined in  as follows:
¥ = b0 + b1x + b2(x – z)(x > z)
eqn 1
if x < z then ¥ = b0 + b1x
if x > z then ¥ = b0 – b2z + (b1 + b2)x
where ¥ = estimate of biovolume ratio, b 0 = intercept of the first regression line, b1 = slope of the first
regression line, b0 – b2z = intercept of the second regression line, b1 + b2 = slope of the second regression line,
z = a threshold value of x where the slope changes,
x = ln-biovolume of the larger species in the ratio. In
order to standardize the variables across habitats
and remove the influence of extreme values biovolume ratios larger than 10 were removed from all
analyses.
The Batavia Kill data set
© 2007 The Author
Journal compilation
© 2007 British
Ecological Society,
Journal of Ecology,
95, 745–754
The frequency of each species in the samples from each
of the three reaches was used as a measure of dispersal,
i.e. the likelihood of a particular species reaching all
habitats. Thus, species with high frequencies are
good dispersers and vice versa. While dispersal has
traditionally been measured in actively dispersing
species in terms of the distance they can travel away
from a source, to my knowledge there are no investigations
that explicitly measured the dispersal capabilities of
diatom species in nature. Diatoms are passive dispersers
and their successful dissemination depends on their
size. Smaller cells have lower probability of sinking (see
eqn 3 below) and can thus travel farther than large cells;
moreover, they have a higher probability of benthic
immigration, especially at high current velocities
(Stevenson 1996). In addition, dispersal is controlled
by the population size (Finlay et al. 2002), i.e. the higher
the number of potential colonists the higher the chance
that at least one individual would reach a location.
However, the number of individuals is an allometric
function (Etienne & Olff 2004; S. I. Passy, unpublished
data) and therefore the examination of species frequency
as a function of body size would account for the number
of individuals as well. Species frequencies within and
across individual reaches in the 2 years studied were
examined with a curve-fitting program (TableCurve
2D 5.01). The following parsimonious equation, which
produced consistently good fits of the frequency–
biovolume relationships, was used:
¥ = b0 + b1x–1
eqn 2
where ¥ = species frequency, b0 = intercept, b1 = slope,
and x = ln-biovolume. Homogeneity of slopes across
reaches was tested with , which ensured that
this relationship was not dependent on reach type. The
dispersal in the benthic samples from the NAWQA
data set was subsequently calculated as the inverse of
ln-biovolume and standardized to range between 0 and 1.
  
Maximum nutrient uptake rate, ρmax (µmol cell–1 h–1),
which reflects the sustained nutrient flux required to
support maximal growth, is a power function of cell
biovolume, V (µm3): ρmax ∝ V 0.66 (Irwin et al. 2006).
Although maximum uptake rate per unit biovolume
has been suggested to decrease with cell size in algae
(Irwin et al. 2006 and references therein), in the case of
diatoms, which have specific cell structure, it is expected
to be size-independent for the following reasons.
Diatom biovolume comprises two distinct parts: the
cytoplasm with all cell organelles, including chloroplasts,
and a large central vacuole, which contains mostly water
but also ions, salts and sugars, and is used primarily as
a depot for nutrients and storage products. The
cytoplasm is metabolically active and requires nutrients
to execute all anabolic processes, whereas the vacuole is
comparatively inert. The cytoplasm is confined to a
thin layer under the frustule, particularly pronounced
in pennates, and being proportionate to the cell surface
scales with the square of cell length (V 2/3). Thus,
expressing nutrient uptake per unit anabolically active
biovolume, i.e. the part of the cell biovolume that needs
nutrients, would give ρmax ∝ V 0.660V –0.667 = V –0.007. An
exponent of –0.007 is sufficiently close to zero to
suggest size-independence of per biovolume nutrient
uptake.
The maximum nutrient uptake rate was calculated as
V0.66 for diatoms in all three studied habitats and standardized to range between 0 and 1.
 
Sinking velocity for phytoplankton species is a
function of their size and form resistance of nonspherical cells as indicated by the Ostwald’s modification
of Stoke’s law (Graham & Wilcox 2000):
2 2
−1 −1
vs = gr ( q ′ − q )v φ
eqn 3
9
749
Cell size
organization in
stream diatoms
where vs = sinking velocity, g = gravitational acceleration of the earth, r = radius of a spherical volume,
equivalent to that of the algal cell, q′ = density of the
algal cell, q = density of water, ν = viscosity of water,
and φ = dimensionless form resistance. All terms in this
equation except r and φ are considered constants and
therefore with no effect on variable standardization.
Using the NAWQA biovolume V (µm3) data, sinking
velocity was calculated as V 2/3, which is proportionate
to the square of the cell radius. The sinking velocity was
then converted to sinking resistance by calculating the
inverse of vs, i.e. V –2/3, and the resistance was standardized
to a range between 0 and 1. Standardization was carried
out separately for centrics and pennates, which have
comparatively low and high φ, respectively (Reynolds
1984). This rationale was used to determine the lower
and upper bound of v s for species differing in form
resistance.
Results
In all habitats, the biovolume frequency distributions,
which were equivalent to biovolume–species richness
distributions (measurements of ln(Biovolume) were
equivalent to the numbers of species in each habitat),
were unimodal, significantly right-skewed (|Skewness |/
SE of Skewness > 2), and significantly leptokurtic
(| Kurtosis |/SE of Kurtosis > 2) (Table 1, Fig. 1). While
skewness was comparable among the three habitats,
kurtosis was much more severe in the benthos than in
the plankton, which had a flatter species richness–lnbiovolume distribution. Contingency table analysis
revealed a significant difference between benthos and
plankton (χ2 = 52.499, d.f. = 22, P = 0.0002), rejecting
the null hypothesis of habitat-independent biovolume
distributions. The maximum species richness was
observed at ln-biovolume between 8 and 9 (at 8.9) in the
benthos, while in the phytoplankton, the peak spanned
several biovolume classes, from 6 to 9, with ln-biovolume
between 6 and 7 being slightly more speciose than the
Fig. 1 Diatom richness–biovolume distributions in benthic
and planktonic stream habitats from all major watersheds in
the US. DTH = depositional targeted habitats, RTH = richest
targeted habitats.
rest (Fig. 1). These findings indicate that smaller sizes
were more speciose in the plankton and larger sizes in
the benthos. Species richness distributions were not
significantly different in the two benthic habitats
(χ2 = 2.939, d.f. = 11, P = 0.992). Notably, there were
substantially more species to the left of the optimum
than to the right in the benthos, i.e. smaller biovolume
classes were much more speciose than larger ones.
This trend also occurred in the phytoplankton but was
much less pronounced (Fig. 1).
The frequency, a proxy measure of dispersal, was
calculated for all diatom species in the three studied
reaches of Batavia Kill individually and altogether,
within and across years. Frequency was a negative power function of ln-biovolume (Fig. 2) and
this relationship was independent of reach type as
Table 1 Basic statistics of ln-biovolume in the three habitats.
Note that n equals the number of observations, which is also
equal to the number of species as each observation of lnbiovolume was taken from a different species. SES,
SEK = standard error of skewness and kurtosis, respectively
© 2007 The Author
Journal compilation
© 2007 British
Ecological Society,
Journal of Ecology,
95, 745–754
Basic statistics
DTH
RTH
Phytoplankton
n
Minimum
Maximum
Mean
95% CI
Skewness
SES
Skewness/SES
Kurtosis
SEK
Kurtosis/SEK
1512
2.0
13.88
7.38
7.29–7.48
0.34
0.06
5.42
0.90
0.13
7.17
1644
2.0
13.88
7.36
7.27–7.45
0.32
0.06
5.23
0.94
0.12
7.76
722
2.7
13.88
6.91
6.78–7.05
0.47
0.09
5.12
0.62
0.18
3.40
Fig. 2 Frequency of 49 diatoms in 2001 and 65 diatoms in
2002 within three 100-m reaches of Batavia Kill, NY, as a
function of their ln-biovolume. Data fits were generated from
the following regression model: frequency = b0 + b1(lnbiovolume)–1. In 2001 b0 = –59.37, b1 = 970.13; in 2002 b0 =
–53.77, b1 = 752.67. These regression parameters were not
significantly different between the 2 years and were statistically
equivalent to the respective parameters in the individual reaches.
750
S. I. Passy
Table 2  of species frequency as a function of ln (biovolume)–1, reach, and their interaction in the 2 years of study of
Batavia Kill. To eliminate correlation between effects, the independent variable was centred by subtracting the mean.
R2 = coefficient of determination, n = number of observations, SS = sum of squares, MS = mean square, and d.f. = degrees of
freedom
Source
SS
d.f.
MS
F-ratio
P-value
2001, n = 135, R2 = 0.19
Biovolume
Reach
Biovolume × Reach
Error
23583.11
2677.46
323.03
113770.6
1
2
2
129
23583.11
1338.73
161.51
881.94
26.74
1.52
0.18
0.00001
0.22
0.83
2002, n = 158, R2 = 0.13
Biovolume
Reach
Biovolume × Reach
Error
13343.19
54.74
631.88
91424.72
1
2
2
152
13343.19
27.37
315.94
601.48
22.18
0.05
0.53
0.00001
0.96
0.59
demonstrated by  (Table 2). Biovolume explained
19% of the frequency variance in 2001 and 13% in 2002
and these results were highly significant (Table 2). Therefore,
despite substantial differences in geomorphic and light
conditions among the three reaches, the relationship
between diatom dispersal and biovolume remained
invariant. Pooling all reaches together produced a
frequency–biovolume relationship that was statistically
equivalent to the relationships in individual reaches.
This indicates that dispersal was also insensitive to the
scale of observation, i.e. local within-reach vs. broader
between-reach. Dispersal in the two benthic habitats of
the NAWQA data set was estimated as the inverse of
species ln-biovolume. Nutrient uptake rate was calculated
and plotted as a function of ln-biovolume together
with the dispersal estimates (Fig. 3a,b). The largest
ln-biovolume (14.88) in all habitats was identified as an
outside value by stem-and-leaf plots and was not
included in the calculations of nutrient uptake rate,
dispersal, and sinking resistance (below). Optimal
biovolume was expected at the intersection of dispersal
and nutrient uptake, i.e. at ln-biovolume values where
neither of these processes was limiting. Such intersection
was observed at ln-biovolume of 8.9 in DTH and RTH,
which exactly corresponded to the value of ln-biovolume
with the highest number of species.
Sinking resistance was determined separately for the
two large diatom groups (centrics and pennates), which
differ in form resistance. An optimal biovolume range
was expected between the intersections of the standardized nutrient uptake rate and sinking resistance.
Indeed, these intersections were observed at ln-biovolume
of approximately 5.9 and 7.2 (Fig. 3c), which corresponded
to the most speciose ln-biovolume values (Fig. 1).
The biovolume ratio of species adjacent in size
increased significantly (P < 0.00001) and non-linearly
with ln-biovolume of the larger species in all habitats
(Table 3). Piece-wise linear regressions explained
between 31 and 34% of the variance in biovolume ratio
and showed that its rate of increase was not uniform
along the biovolume gradient. This rate was very low
(0.04 ≤ b1 ≤ 0.07) at lower values of ln-biovolume but
changed abruptly at a threshold value of ln-biovolume,
above which the biovolume ratio rapidly increased
(1.96 ≤ (b1 + b2) ≤ 2.32). The biovolume ratio was close
to 1 below the threshold but much higher than 1 above
it (Fig. 4a–c), indicating that species adjacent in size
had nearly identical biovolumes below the threshold
© 2007 The Author
Journal compilation
© 2007 British
Ecological Society,
Journal
of Ecology,
Fig. 3 Nutrient
uptake rate and dispersal as power functions of ln-biovolume in DTH (a) and RTH (b). Nutrient uptake rate and sinking resistance as
power
functions of ln-biovolume in phytoplankton (c).
95,
745–754
751
Cell size
organization in
stream diatoms
Table 3 Coefficients of determination (R2), regression coefficients, and 95% confidence intervals (CI) of piece-wise
linear regressions of biovolume ratio vs. ln (biovolume) in the
three studied habitats. Regression parameters that are not
significantly different at P < 0.05 across habitats are in italic.
P < 0.00001 in all regressions. n = number of observations;
b0 = intercept; z = threshold value of the independent variable,
where the slope of the fitting curve changes from b1 to b1 + b2
Coefficients
DTH
RTH
Phytoplankton
n
R2
b0
95% CI
b1
95% CI
b1 + b2
95% CI
z
95% CI
79 072
0.34
0.905
0.895–0.915
0.039
0.037–0.041
1.958
1.933–1.982
9.296
9.286–9.305
95 822
0.31
0.861
0.850–0.872
0.054
0.052–0.055
2.010
1.983–2.037
9.228
9.216–9.241
10 566
0.33
0.757
0.707–0.807
0.073
0.065–0.081
2.320
2.213–2.428
9.307
9.262–9.353
but disparate ones above the threshold. The rate of
biovolume ratio increase with ln-biovolume was
significantly different across habitats; it was highest in
phytoplankton and lowest in DTH (Table 3, Fig. 4d).
© 2007 The Author
Journal compilation
© 2007 British
Ecological Society,
Journal of Ecology,
95, 745–754
The threshold value was significantly higher in
phytoplankton and DTH than in RTH.
Discussion
The richness–biovolume relationship was unimodal
right-skewed in both benthic and planktonic diatoms
from the US running waters. However, there were
significant differences between the two habitats. In the
benthos, the biovolume distributions were more strongly
leptokurtic, displaying a distinct peak of species
richness at ln-biovolume between 8 and 9. The position
of this peak was exactly predicted by an allometric
trade-off between nutrient uptake rate and dispersal.
Smaller species (to the left of the peak) were limited by
their ability to acquire resources, whereas larger species
(to the right of the peak) were limited by their dispersal
capabilities. Here I examined only the physiological
aspect of the resource uptake limitation but it should
be noted that it is further exacerbated by the strong
competition in the benthos where larger species, by
virtue of their taller stature, gain better access to light
and nutrients from the water column and can create a
resource-depleted environment for the smaller species
Fig. 4 Biovolume ratio as a function of ln-biovolume of the larger species in the pair in DTH (a), RTH (b) and phytoplankton
(c). The fits for the three habitats, produced by piece-wise linear regressions, are plotted together in (d).
752
S. I. Passy
© 2007 The Author
Journal compilation
© 2007 British
Ecological Society,
Journal of Ecology,
95, 745–754
in the lower stories. The richness peak can be interpreted
as an outcome of cell size optimization, where species
were not severely limited by their ability to either
sequester resources or disperse. Considering that the
majority of species (61%) was observed to the left of the
richness peak and only a minor portion of the species
to the right of it (13%) suggests that constraints on
dispersal in the benthos are much more important than
physiological restrictions for diatom cell size organization.
Tolerance for low nutrient levels, well documented in
small diatoms (Cattaneo et al. 1997; Wunsam et al. 2002),
and production of storage vacuoles can offset a poor
nutrient sequestration and explain why there are so
many species with suboptimal abilities to obtain
nutrients. The ineffectiveness of large diatoms to reach
all locations where they would be competitively superior
due to mechanical constraints and lower numbers of
individuals takes a toll on their diversification, which is
evident in their minor contribution to the overall species
richness. Additionally, high profile diatoms have a
higher susceptibility to physical disturbance from shear
stress or grazing (Steinman 1996; Stevenson 1996) and
chemical disturbance from various forms of pollution
(Cattaneo et al. 1998), which will further limit their
diversification.
Phytoplankton had a flatter biovolume distribution
with much higher relative richness of smaller size
classes than the benthos. An allometric trade-off
between nutrient uptake rate and sinking resistance
accounted for part of the richness peak containing the
most speciose biovolume, i.e. ln-biovolume between 6
and 7. However, unlike dispersal, sinking resistance
varies not only with cell size but also with a number of
other factors such as form resistance, density of the
cell, water temperature and turbulence, and is therefore
more adequately represented by a band rather than a
curve. Here, I treated the centric and pennate diatoms
as two homogeneous groups, implicitly differing in
form resistance. This, however, is an oversimplification
because there is substantial variability of form resistance and cytoplasmic density within each group,
which, if accounted for, would have generated a much
larger spectrum of sinking resistance variability. Smaller
species (to the left of the peak) were limited by nutrient
uptake and represented 15% of all planktonic diatoms,
while large species (to the right of the peak) were controlled by sinking resistance and accounted for 11% of
all species. As both tails of the biovolume distribution
in the phytoplankton contained a comparable number
of species, it is logical to assume that the two mechanisms described here exert similar impact on diatom
cell size organization. The reason may be in their
common cellular roots, e.g. the amount of nutrient per
cell determines nutrient uptake but also sinking resistance, as the excess nutrients stored in the cell as oils
reduce its density and consequently its sinking velocity.
Selective grazing can also contribute to a reduced
number of smaller species that are more vulnerable to
herbivory than larger diatoms. Finally, large diatoms
are more likely to be exported into the phytoplankton
following disturbance events in the benthos.
The continental richness–biovolume relationships
of freshwater diatoms (class Bacillariophyceae) were
significantly right-skewed in all habitats, which is
common for higher taxonomic levels (e.g. class) and at
larger geographical scales (Kozlowski & Gawelczyk
2002). There are different hypotheses for the prevalence
of right-skewed distributions, including size-biased
speciation and extinction, macroevolutionary constraint
on small sizes, the fractal nature of the environment
and body size optimization (Kozlowski & Gawelczyk
2002). Probably a combination of these mechanisms is
responsible for the shape of the present distributions;
however, the macroevolutionary constraint on small
sizes, also known as the ‘reflecting barrier’, is particularly relevant in diatoms. According to this hypothesis,
distributions cannot extend below the natural barrier
of the lower limit of body size, where physiological
constraints reflect diversification toward larger sizes
(Kozlowski & Gawelczyk 2002 and references
therein). This is why richness–body size distributions
are not simply left truncated but humped. While this
mechanism may not be unequivocal across animal
lineages of widely varying lower size, it is apparent in
diatoms with a lower size limit set by the minimum size
of the eukaryotic cell, which, on average, does not fall
below 10 µm in diameter. Spherical shapes with the
same biovolume as the smallest diatoms in the NAWQA
data set would exhibit diameters as low as 2.4 µm, i.e.
below the lower limit of most eukaryotic cells, where
algal maximum nutrient uptake rate, and metabolic
and nutrient storage abilities are expected to be
diminished. Thus, the existence of a left barrier and an
optimization mechanism (maximizing nutrient uptake
rate) that drives diversification away from it can account
for the right-skewed richness–biovolume distributions
in diatoms.
In all three habitats, the biovolume ratio increased
along the cell size gradient with a distinct change of
rate at a threshold ln-biovolume value of around 9.3
(very close to the richness peak). The piece-wise response
of biovolume ratio to diatom size indicated that there
were two distinct groups of species. Below the threshold,
the biovolume ratios approached 1, i.e. diatoms adjacent
in size were nearly identical. Above the threshold,
diatoms displayed large distances in size. This finding
is exactly opposite to the predictions of the synthetic
theory of biodiversity (Ritchie & Olff 1999), which postulated a decreasing body size ratio with organismal size
in local communities. The reason for this controversy is
in the underlying trade-offs. The synthetic theory
assumes a decreasing number of available patches (only
the large ones) but increasing tolerance for low resource
concentration in large species. Although this theory
was supported by empirical data on large mammals
and terrestrial plants, its premises cannot apply
to unicellular algae. Diatoms inhabit a continuously
changing environment with pronounced gradients
753
Cell size
organization in
stream diatoms
© 2007 The Author
Journal compilation
© 2007 British
Ecological Society,
Journal of Ecology,
95, 745–754
of nutrient and light (Borchardt 1996; Hill 1996) and
not discrete patches (pertains mostly to benthic forms).
In addition, algae encompass small species that are
generally better adapted to low resource concentrations
than large species (Cattaneo et al. 1997; Li 2002;
Wunsam et al. 2002; Jiang et al. 2005; Irwin et al. 2006)
(pertains to benthic and planktonic diatoms alike).
The analysis of biovolume ratios in this study reveals
that small species form a continuum where there is a
species for every possible size and the distance between
species adjacent in size approaches zero. The lack of
discontinuities in the biovolume ratios suggests that
smaller species (below the biovolume threshold) form a
single guild. The notion that species identical in size
within trophic levels are also ecologically equivalent
has become an ecological axiom. Therefore, small
species with near nil differences in biovolume are expected
to occupy very similar niches, and in coexistence to
experience high niche overlap, the amount of which can
be estimated from the size similarity among species.
Thus, the size similarity was the greatest in DTH but
the lowest in phytoplankton, suggesting a significantly
higher niche overlap in the benthos than in the phytoplankton. This hypothesis was put forth to explain the
higher taxonomic distances in the phytoplankton
compared with the benthos (Passy & Legendre 2006a)
and is fully corroborated by the present rigorous
analysis of the cell size structure of diatom communities.
The highest biovolume similarity in DTH was probably
forced by environmental conditions of unstable substrates
and sediment-borne contaminants favouring a
comparatively taxonomically uniform community of
low-profile, motile and pollution-tolerant species
(Passy & Legendre 2006a).
The high number of small species in a community
has been explained mechanistically with the corresponding number of suitable patches. For example,
the complex behaviour of large species may involve
the utilization of a combination of patches, each one
being sufficient to maintain a different small species
(Hutchinson & MacArthur 1959). Furthermore, small
species can exploit patches that are unavailable to large
species due to their inability to perceive them or fit within
them (Morse et al. 1985; Ritchie & Olff 1999; Aarssen
et al. 2006). The remarkable biovolume similarity of
small species documented here offers a complementary,
functional explanation of the high richness of small
species, i.e. small species exhibit much higher niche
overlap, which is counterbalanced by their high tolerance to resource limitation (and environmental adversity in general). Indeed, species sufficiently similar to
possess equal competitive abilities have been shown in
a theoretical study to maintain stable coexistence and
high diversity (Scheffer & van Nes 2006). Additionally,
the superior dispersal of small species prevents local
extinctions by a constant re-supply of new colonists.
Larger species (above the biovolume threshold)
displayed substantial differences in cell size, which
suggests the existence of multiple guilds. The members
of different guilds have differential resource requirements
and experience less competition in sympatry than the
members of the same guild. In addition, the superior
capabilities of large species to acquire resources would
further relax their resource competition. The piecewise linear nature of the diatom biovolume similarity
can also be interpreted as a competition gradient whereby
competition remains strong up to a threshold value of
ln-biovolume, beyond which the negative interspecific
interactions sharply decline. The classical paper by
Hutchinson (1959) explored the size ratio of co-occurring
competitors within mammals and birds and suggested
that a ratio of about 1.28 is necessary for niche differentiation. Across the three habitats in this study, the
average biovolume ratio of species below the ln-biovolume
threshold was between 1.14 and 1.21, but between 2.02
and 3.05 above that threshold. This indicates that small
species of diatoms experience much stronger interspecific
competition than multicellular organisms, whereas the
competition among large diatoms is alleviated.
In conclusion, this is the first continental study on
the richness–body size relationship in algae to suggest
that the environmental differences between the benthos
and the plankton are responsible for allometric tradeoffs driving cell size optimization towards larger species in
the benthos and smaller species in the plankton. The
patterns of biovolume similarity revealed a higher niche
overlap in the benthos than in the phytoplankton and
among small species than among large species. Therefore,
the interspecific competition in stream diatoms, being a
function of niche differentiation, is habitat-specific and
inversely related to cell size.
Acknowledgements
I thank Don Charles for kindly providing the data set
and Mark Ritchie for his comments on this project. I
am grateful to Jim Grover for stimulating discussions
and an insightful review, Christer Nilsson, Barney
Davies and two anonymous reviewers for their suggestions,
which substantially improved the manuscript. Financial
support under grant #C004307 from the New York
State Department of Environmental Conservation is
gratefully acknowledged. This manuscript is submitted
for publication with the understanding that the United
States Government is authorized to reproduce and
distribute reprints for governmental purposes. The
views and conclusions contained in this document are
those of the author and should not be interpreted
as necessarily representing the official policies, either
expressed or implied, of the US Government.
References
Aarssen, L.W., Schamp, B.S. & Pither, J. (2006) Why are there
so many small plants? Implications for species coexistence.
Journal of Ecology, 94, 569–580.
Aksnes, D.L. & Egge, J.K. (1991) A theoretical model for
nutrient-uptake in phytoplankton. Marine Ecology-Progress
Series, 70, 65 –72.
754
S. I. Passy
© 2007 The Author
Journal compilation
© 2007 British
Ecological Society,
Journal of Ecology,
95, 745–754
Allen, C.R., Garmestani, A.S., Havlicek, T.D., Marquet, P.A.,
Peterson, G.D., Restrepo, C., Stow, C.A. & Weeks, B.E.
(2006) Patterns in body mass distributions: sifting among
alternative hypotheses. Ecology Letters, 9, 630 –643.
Bakker, V.J. & Kelt, D.A. (2000) Scale-dependent patterns in
body size distributions of neotropical mammals. Ecology,
81, 3530 –3547.
Blackburn, T.M. & Gaston, K.J. (1994) Animal body-size
distributions: patterns, mechanisms and implications.
Trends in Ecology and Evolution, 9, 471– 474.
Borchardt, M.A. (1996) Nutrients. Algal Ecology: Freshwater
Benthic Ecosystems (eds R.J. Stevenson, M.L. Bothwell &
R.L. Lowe), pp. 183–227. Academic Press, San Diego, CA.
Brown, J.H., Marquet, P.A. & Taper, M.L. (1993) Evolution
of body size: consequences of an energetic definition of
fitness. American Naturalist, 142, 573–584.
Cattaneo, A., Asioli, A., Comoli, P. & Manca, M. (1998)
Organisms’ response in a chronically polluted lake supports
hypothesized link between stress and size. Limnology and
Oceanography, 43, 1938 –1943.
Cattaneo, A., Kerimian, T., Roberge, M. & Marty, J. (1997)
Periphyton distribution and abundance on substrata of
different size along a gradient of stream trophy. Hydrobiologia,
354, 101–110.
Dial, K.P. & Marzluff, J.M. (1988) Are the smallest organisms
the most diverse? Ecology, 69, 1620 –1624.
Etienne, R.S. & Olff, H. (2004) How dispersal limitation
shapes species-body size distributions in local communities.
American Naturalist, 163, 69– 83.
Finlay, B.J., Monaghan, E.B. & Maberly, S.C. (2002)
Hypothesis: the rate and scale of dispersal of freshwater
diatom species is a function of their global abundance.
Protist, 153, 261–273.
Gaston, K.J., Chown, S.L. & Mercer, R.D. (2001) The animal
species-body size distribution of Marion Island. Proceedings
of the National Academy of Sciences (USA), 98, 14493 –
14496.
Graham, L.E. & Wilcox, L.W. (2000) Algae. Prentice Hall,
Englewood Cliffs, NJ.
Grover, J.P. (1989) Influence of cell shape and size on algal
competitive ability. Journal of Phycology, 25, 402– 405.
Havlicek, T.D. & Carpenter, S.R. (2001) Pelagic species size
distributions in lakes: are they discontinuous? Limnology
and Oceanography, 46, 1021–1033.
Hill, W. (1996) Effects of light. Algal Ecology: Freshwater
Benthic Ecosystems (eds R.J. Stevenson, M.L. Bothwell &
R.L. Lowe), pp. 121–148. Academic Press, San Diego, CA.
Hutchinson, G.E. (1959) Homage to Santa Rosalia or why are
there so many kinds of animals? American Naturalist, 93,
145 –159.
Hutchinson, G.E. & MacArthur, R.H. (1959) A theoretical
ecological model of size distributions among species of
animals. American Naturalist, 93, 117–123.
Irwin, A.J., Finkel, Z.V., Schofield, O.M.E. & Falkowski, P.G.
(2006) Scaling-up from nutrient physiology to the sizestructure of phytoplankton communities. Journal of Plankton
Research, 28, 459– 471.
Jiang, L., Schofield, O.M.E. & Falkowski, P.G. (2005)
Adaptive evolution of phytoplankton cell size. American
Naturalist, 166, 496–505.
Kindlmann, P., Dixon, A.F.G. & Dostalkova, I. (1999) Does
body size optimization result in skewed body size distribution
on a logarithmic scale. American Naturalist, 153, 445 – 447.
Knouft, J.H. (2004) Latitudinal variation in the shape of the
species body size distribution: an analysis using freshwater
fishes. Oecologia, 139, 408 – 417.
Kozlowski, J. & Gawelczyk, A.T. (2002) Why are species’
body size distributions usually skewed to the right?
Functional Ecology, 16, 419– 432.
Kozlowski, J. & Weiner, J. (1997) Interspecific allometries are
by-products of body size optimization. American Naturalist,
149, 352–380.
Li, W.K.W. (2002) Macroecological patterns of phytoplankton
in the northwestern North Atlantic Ocean. Nature, 419,
154 –157.
May, R.M. (1986) The search for patterns in the balance of
nature: advances and retreats. Ecology, 67, 1115–1126.
McClain, C.R. (2004) Connecting species richness, abundance
and body size in deep-sea gastropods. Global Ecology and
Biogeography, 13, 327–334.
Morse, D.R., Lawton, J.H., Dodson, M.M. & Williamson,
M.H. (1985) Fractal dimension of vegetation and the distribution of arthropod body lengths. Nature, 314, 731–733.
Niklas, K.J., Midgley, J.J. & Rand, R.H. (2003) Sizedependent species richness: trends within plant communities
and across latitude. Ecology Letters, 6, 631–636.
Passy, S.I. & Blanchet, F.G. (2007) Algal communities in
human-impacted stream ecosystems suffer beta-diversity
decline. Diversity and Distributions, doi: 10.1111/j.14724642.2007.00361.x.
Passy, S.I. & Legendre, P. (2006a) Power law relationships
among hierarchical taxonomic categories in algae reveal a
new paradox of the plankton. Global Ecology and Biogeography,
15, 528–535.
Passy, S.I. & Legendre, P. (2006b) Are algal communities
driven toward maximum biomass? Proceedings of the Royal
Society B-Biology Sciences, 273, 2667–2674.
Reynolds, C.S. (1984) The Ecology of Freshwater Phytoplankton.
Cambridge University Press, Cambridge.
Ritchie, M.E. & Olff, H. (1999) Spatial scaling laws yield a
synthetic theory of biodiversity. Nature, 400, 557–560.
Scheffer, M. & van Nes, E.H. (2006) Self-organized similarity,
the evolutionary emergence of groups of similar species.
Proceedings of the National Academy of Sciences of the
United States of America, 103, 6230–6235.
Siemann, E., Tilman, D. & Haarstad, J. (1996) Insect species
diversity, abundance and body size relationships. Nature,
380, 704–706.
Soininen, J. & Kokocinski, M. (2006) Regional diatom body
size distributions in streams: does size vary along environmental, spatial and diversity gradients? Ecoscience, 13,
271–274.
Steinman, A.D. (1996) Effects of grazers on freshwater
benthic algae. Algal Ecology: Freshwater Benthic Ecosystems
(eds R.J. Stevenson, M.L. Bothwell & R.L. Lowe), pp. 341–
373. Academic Press, San Diego, CA.
Stevenson, R.J. (1996) The stimulation and drag of current.
Algal Ecology: Freshwater Benthic Ecosystems (eds R.J.
Stevenson, M.L. Bothwell & R.L. Lowe), pp. 321–340.
Academic Press, San Diego, CA.
Stolte, W., McCollin, T., Noordeloos, A.A.M. & Riegman, R.
(1994) Effect of nitrogen-source on the size distribution
within marine-phytoplankton populations. Journal of
Experimental Marine Biology and Ecology, 184, 83–97.
® 11 (2004) Statistics I.  Software, Inc, Richmond,
CA.
TableCurve 2D (2002) Version 5.01 for Windows. SYSTAT
Software, Inc, Richmond, CA.
Wen, Y.H., Vezina, A. & Peters, R.H. (1997) Allometric
scaling of compartmental fluxes of phosphorus in freshwater
algae. Limnology and Oceanography, 42, 45 –56.
Wunsam, S., Cattaneo, A. & Bourassa, N. (2002) Comparing
diatom species, genera and size in biomonitoring: a case
study from streams in the Laurentians (Quebec, Canada).
Freshwater Biology, 47, 325 –340.
Received 8 November 2006; revision accepted 22 March 2007
Handling Editor:Christer Nilsson