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\begin{document}

\title{Smaller species experience mild adversity under shading in an old-field
plant community}



\author[1]{Kelly Balfour}%
\author[1]{Danielle Greco}%
\author[1]{Riley Gridzak}%
\author[1]{Gillian Piggott}%
\author[2]{Brandon Schamp}%
\author[3]{Lonnie Aarssen}%
\affil[1]{Queen's University}%
\affil[2]{Algoma University}%
\affil[3]{Queens University}%


\vspace{-1em}



  
  \date{June 10, 2024}


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\selectlanguage{english}
\begin{abstract}
Plant competition experiments commonly suggest that larger species have
an advantage, especially in light acquisition. However, within crowded
natural vegetation, where competition evidently impacts fitness, most
resident species are relatively small. It remains unclear, therefore,
whether the size-advantage observed in controlled experiments is
realized in habitats under intensive competition. We tested for evidence
of a size-advantage in competition for light in an old-field plant
community composed of herbaceous perennial species. We investigated
whether larger species contributed to reduced light penetration (i.e.,
greater shading), and examined the impact of shade on smaller species by
testing whether their abundance and richness were lower in plots with
less light penetration. Light penetration in plots ranged from
0.3-72.4\%. Plots with greater mean species height had significantly
lower light penetration. Plots with lower light penetration had
significantly lower small species abundance and richness. However, the
impact of shade on small species abundance and richness was relatively
small (R\textsuperscript{2} values between 8\% and 15\%) and depended on
how we defined ``small species''. Significant effects were more common
when analyses focused on individuals that reached reproduction; focusing
on only flowering plants can clarify patterns. Our results confirm that
light penetration in herbaceous vegetation can be comparable to levels
seen in forests, that plots with taller species cast more shade, and
that smaller species are less abundant and diverse in plots where light
penetration is low. However, variation in mean plot height explained
less than 10\% of variation in light penetration, and light penetration
explained 5-15\% of variation in small species abundance and richness.
Coupled with the fact that reproductive small species were present even
within the most heavily shaded plots, our results suggest that any
advantage in light competition by large species is limited. One
explanation is that some small species in these communities are shade
tolerant.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Evidence from neighbour removal studies clearly indicates that plant
communities are highly competitive (e.g., Clements et al. 1929; Grime
1973; Tilman 1989; Gurevitch et al. 1992). Research also indicates that
variation in plant functional traits is important in determining
competitive ability and predicting the suppression of neighbour growth
(Aarssen and Keogh 2002). For example, larger plant species are
generally considered superior to smaller species when competing for
pollinators (e.g., Donnelly et al. 1998), seed dispersal agents (e.g.,
Thomson et al. 2011), and for light (e.g., Weiner 1990; Schwinning and
Weiner 1998). We refer to the competitive advantage commonly attributed
to relatively tall plant species as the ``size-advantage hypothesis''
(e.g., Tracey and Aarssen 2014; Tracey et al. 2017).

Light is an essential resource, and light limitation can negatively
impact plant growth (Bazzaz 1979; Tilman 1985; Grubb 1998). Light
availability varies across the growing season (Bachmann et al. 2018),
with canopy maturation (Ballar\selectlanguage{ngerman}é 1994), and with community density
(Givnish 1982). When competing species vary in size, competition for
light is said to be size-asymmetric (Lamb et al. 2009; DeMalach et al.
2017), with larger plants expected to dominate light competition by
intercepting more light per unit size than smaller plants (Anten and
Hirose 1998; DeMalach and Kadmon 2017). This growth of larger species
imparts additional light limitation on smaller species while also
reducing their own likelihood of being shaded (Anten 2005). When soil
resources are adequate, natural communities can support the growth of
tall plant species, which are able to limit the light reaching smaller
plant species. For example, soil fertilization can result in increased
light limitation and reduced grassland diversity (Borer et al. 2014).
However, despite a perceived size-advantage in terms of expected
negative impact on small species survival, growth and reproduction,
small plants remain both ubiquitous and abundant within herbaceous
vegetation (Aarssen et al. 2006). There is also little evidence of
deterministic organization of species according to size in herbaceous
communities (Schamp et al. 2008). Recent research has shown that species
with larger body size in fact do not dominate neighbourhood biomass
production in old-field vegetation (Tracey et al. 2017), nor do they
recruit more offspring from the soil seed bank (Tracey and Aarssen
2019).

Light limitation has been studied extensively in forests (Canham et al.
1990; Canham et al. 1994; Gilliam and Roberts 2003; Gommers et al.
2013), but whether the impact of light limitation in forests is
comparable to that in herbaceous vegetation remains unclear. While
grasslands and old-fields are largely dominated by herbaceous species,
distinct canopy layers have attributed vertical complexity to forests
(Parker and Brown 2000; Miedema et al. 2019). In contrast, researchers
have implied higher abundance and even distribution of light within
herbaceous communities. However, several studies counter this widespread
assumption, and collectively argue that light heterogeneity exists in
herbaceous communities (Bazzaz 1990; Kelly and Canham 1992; Ballaré
1994; Körner 1995; Liira et al. 2002; Heger 2016; Huber et al. 2021).
Herbaceous vegetation exhibits a layered canopy structure (Körner 1995;
Liira et al. 2002) which, according to experimental studies, can reduce
light penetration to the ground level to as low as 3\% (Spehn et al.
2000), comparable to the 18-27\% observed in some forests (Bartemucci et
al. 2006). However, we struggled to find many published assessments of
light penetration in herbaceous communities. One study found a reduction
in diversity of small plant species in experimental plots under
fertilization as ground-level light penetration decreased (Borer et al.
2014). Other experimental studies have also assessed the impact of light
availability on herbaceous vegetation (e.g., Semchenko et al. 2012;
Bachmann et al. 2018); however, analyses have yet to examine light
conditions in unmanipulated communities (e.g., absent of seeding,
fertilization, watering treatments).

It remains unclear how small species persist in herbaceous vegetation
despite their apparent disadvantage in light competition, but the
ubiquity of small species, on every scale from regional floras to local
neighbourhoods, suggests that these species either avoid or tolerate
low-light conditions. In woodlands, species that remain shaded under the
herbaceous canopy may minimize light requirements through high
photosynthetic efficiency and low light compensation points (Boardman
1977; Givnish 1988; Ballaré et al. 1997; Valladares and Niinemets 2008).
In this case, there may be little to no change in small species
abundance or richness associated with the amount of shade cast by taller
vegetation. Smaller species may also rely on light from canopy gaps and
sunflecks, which are commonly observed in forests (Chazdon and Pearcy
1991), and are likely important within herbaceous communities as well.
Greater heterogeneity in canopy height in herbaceous communities and
higher frequency of disturbance can increase the incidence of canopy
gaps and sunflecks, allowing more light to penetrate towards the soil
surface, which may thus support a greater number of small species
(Chesson and Huntley 1997; Roxburgh et al. 2004). Additionally, small
species may rely on early season light availability prior to canopy
closure; although seasonal variation in light has been understudied in
herbaceous communities, small species have been found to flower earlier
in the season (Du and Qi 2010; Sun and Frelich 2011; Segrestin et al.
2020). Early growth and flowering by small species may reduce
competition for light, as well as for pollinators, allowing these
species to coexist with larger, later flowering species (Jensen et al.
2019).

In this study, we sought to answer two important questions concerning
the presumed advantage that larger species have in light competition
within a temperate mesic old-field community. First, we examined
patterns of light penetration through the standing vegetation to
determine whether sample plots containing taller resident species have
significantly reduced light penetration. Second, we tested whether the
species abundance and richness of smaller plants were lower in sample
plots where light penetration was lowest. The goal of this research was
to better reconcile experimental evidence that large plant species enjoy
a competitive advantage for light with the widespread prevalence of
small plant species in natural communities.

\textbf{Methods}

\emph{Study site}

We conducted this experiment from June to August 2006 within a 67.5 m x
50 m old-field meadow (known locally as the ``Cemetery Field'') located
at the Queen's University Biological Station, north of Kingston,
Ontario, Canada (44° 32' 23'' N, 76° 22' 3'' W). For about 50 years
preceding this work, this field was harvested for hay annually
(excluding 2005 and 2006) but has not otherwise been disturbed. In July
2005, the field was divided into 486 plots, each 1 m x 1 m, separated by
1 m laneways to minimize the impact of edge effects and disturbance
during data collection (Piggott 2007). Of these 486 pre-existing plots,
49 were randomly chosen for data collection in this study.

\emph{Data collection}

Monthly, from June to August 2006, we measured light intensity
(photosynthetically active radiation; PAR) within each of the 49 plots
using a LI-COR L1--250A light meter (\selectlanguage{greek}µ\selectlanguage{english}mol
s\textsuperscript{-1}n\textsuperscript{-2}; LI-COR Biosciences, Lincoln,
USA). Each plot was divided into nine equal squares in a 3 x 3 grid,
with three measurements taken in the center of each plot row, directly
above the canopy, and nine measurements taken at ground-level in each
square (Fig. 1). We calculated the percentage of light penetration based
on the mean light intensity at ground-level for each of the nine
locations in the plot and the mean above-canopy light intensity measured
above each plot row {[}100 \selectlanguage{ngerman}× (ground-level light intensity /
above-canopy light intensity){]}.

From June to August 2006, we collected abundance data by quantifying the
number of rooted units per species in each plot (i.e., ramets, Schamp et
al. 2016), and determined plot-level species richness from these
abundance data. We monitored plot-level abundance biweekly, which was
further classified into two census types: total abundance of each
species (including all rooted units in a plot, both reproductive and
nonreproductive), and flowering abundance of each species (including
only reproductive rooted units in a plot). Species maximum height (cm)
data were collected for all species in the dataset from specimens
measured at the study site (not in sample plots) and in nearby
old-fields at the Queen's University Biological Station. The number of
values recorded per species ranged between 5-20, and the largest value
per species was used as the maximum height for that species.

\emph{Data analyses: variation in the light environment}

We quantified light penetration in our grassland community to determine
how much light variation exists and to identify sources of that
variation. We examined light penetration across plots to assess
variation across the site (`interplot light variation'), within plots to
quantify heterogeneity in light penetration (`intraplot light
variation'), and across months to determine how light penetration
changed throughout the growing season (`temporal light variation'). To
quantify interplot light variation, we calculated mean light penetration
(\%) within a plot during one sampling event, and further calculated
variance (\selectlanguage{greek}σ\selectlanguage{english}\textsuperscript{2}) between these means for each month
(N=3). For intraplot light variation, we calculated the variance in
light penetration within each plot for each month (N=147). Finally, to
quantify temporal variation, we calculated variance in mean light
penetration for each plot across months (June, July, August; N=49).

Additionally, to assess how light penetration levels differ across June,
July, and August, we performed a one-way repeated measures ANOVA using
mean light penetration as the response variable and plot as the
within-subject factor, followed by a Bonferroni post hoc test to
determine significant differences between months. We visually assessed
normality and checked for equal variances among months using a Mauchly's
test for sphericity. For these analyses, we used the `anova\_test' and
`pairwise\_t\_test' functions from the package `rstatix' v0.6.0
(Kassambara 2020).

\emph{Data analyses: species size effects on --- and responses to ---
light penetration}

Because there is no standard definition of ``small species'' we compared
two approaches: 1) small species were regarded as those smaller than the
first quartile of species height for all species in the focal community
(`1st quartile', \textless{}53.25 cm, N=15), 2) small species were
regarded as those smaller than the median of species height in the
community (`median', \textless{}83 cm, N=29; Fig. 2). Comparing results
across these two definitions allowed us to test whether any significant
patterns were sensitive to our method of defining small species.

We tested whether plots with larger species had lower light penetration.
Specifically, we fit linear models with mean plot height (mean
plot-level maximum height weighted by species plot-level abundance) and
large species abundance (including all species which are not considered
``small'' by either definition, \textgreater{}83 cm) as predictors and
mean light penetration as the response variable. We also tested whether
small species abundance and richness responded to variation among plots
in light penetration. We fit linear models with small species abundance
and richness (for both `1\textsuperscript{st} quartile' and `median'
defined small species) as response variables. Light penetration and mean
intraplot variation in light penetration (calculated for each plot at
each sampling event and averaged across months) were our predictor
variables. We checked the variance inflation factor to ensure that there
was not a high degree of multicollinearity between our variables.

We used the package `stats' from R.4.0.3 (R Core Team 2020) for
modeling, and checked statistical assumptions using residual vs. fitted,
normal quantile-quantile, scale location, and constant leverage plots
(`ggfortify' v.0.4.11; Tang 2016). We log\textsubscript{10}-transformed
variables where necessary to meet assumptions. For our multiple linear
regressions, we used the Akaike Information Criterion corrected for
small sample sizes for model selection (AICc). Where multiple models
were within two units of the lowest AICc score, we used the full model
average (via the `model.avg' function from the `MuMIn' v1.43.17 package;
Barto\selectlanguage{polish}ń \selectlanguage{english}2020) to determine the significance of predictors.

Finally, to assess the collective response of small species to light
availability, we performed distance-based redundancy analyses (dbRDA)
using Bray-Curtis dissimilarities. Additionally, we used the `decorana'
function from the package `vegan' v.2.5-6 (Oksanen 2019) to confirm
linearity of responses. We conducted RDA with mean light penetration and
mean intraplot variation as possible predictors using the `capscale'
function from `vegan' v.2.5-6 (Oksanen 2019). We compared models using
AICc scores, selecting the model with the lowest score.

\textbf{Results}

\emph{Variation in the light environment}

Light penetration within our old-field site ranged from 0.3-72.4\%
(\emph{n} = 440, \selectlanguage{greek}\emph{μ} \selectlanguage{english}= 16.6\% \selectlanguage{ngerman}± 12; Fig. S1A). The highest variance
in light penetration occurred between plots (\emph{n} = 3, median
interplot variance=77.3), followed by variance across months (\emph{n} =
49, median temporal variance = 57.4) with within-plot light penetration
varying the least (\emph{n} = 147, median intraplot variance = 26.2;
Fig. 3). Intraplot variance in light penetration ranged from 0.07-1546.5
(\emph{n} = 147, \selectlanguage{greek}\emph{μ} \selectlanguage{english}= 88.3 \selectlanguage{ngerman}± 15.3; Fig. S1B). Mean light
penetration was highest in June (20.2\%), lowest in July (13.6\%), and
slightly higher in August (15.9\%). Light penetration differed
significantly across months (repeated measures ANOVA,\emph{F}
\textsubscript{2,96} = 9.2, \emph{P} \textless{} 0.001; Fig. 4); with a
posthoc test revealing that light penetration in June was significantly
different than in both July (Bonferroni,\emph{P}
\textsubscript{adj}\textless{}0.001; Fig. 4A) and August (Bonferroni,
\emph{P} \textsubscript{adj} = 0.036; Fig. 4B), but that the last two
months did not significantly differ (Bonferroni,\emph{P}
\textsubscript{adj} = 0.4; Fig. 4C). High variance in light penetration
among sample plots further justified our plot-level approach to
hypothesis testing.

\emph{Species size and light penetration}

Light penetration was significantly lower in plots with greater
plot-level mean height (R\textsuperscript{2} = 0.08, \emph{P} = 0.025;
Fig. 5) but was unassociated with large species abundance. Mean
intraplot variation in light penetration was significantly positively
correlated with mean light penetration (Spearman correlation,
\emph{rho}= 0.49, \emph{P} \textless{} 0.001; Fig. S2).

Small species abundance and richness in plots were significantly higher
in plots with high light penetration, but not for both definitions of
small species. Small species under the `1\textsuperscript{st} quartile'
definition had significantly higher flowering abundance in plots with
higher light penetration (R\textsuperscript{2} = 0.08, \emph{P} = 0.027;
Fig. 6A). Median flowering abundance and richness were significantly
higher in plots with increased light penetration (Abundance:
R\textsuperscript{2}=0.1, \emph{P} = 0.012; Richness: \emph{P} = 0.014,
R\textsuperscript{2} = 0.1; Figs. 6B,D). The richness of small species
(1\textsuperscript{st} quartile) did not significantly change with light
penetration (Fig. 6C, Table S1). Within-plot variation in light
penetration was not significantly related to small species abundance or
richness using either definition (Table S1).

The composition of small plant species defined using the median
significantly changed with mean plot-level light penetration
(dbRDA1,\emph{P} = 0.031, pseudo-\emph{F} \textsubscript{1,47} = 2.06;
Fig. 7), but was unaffected by mean intraplot variation. Mean plot-level
light penetration explained 4.2\% of the total variation in plot
composition for `median' small species. Eighteen species had higher
abundances associated with higher light penetration (as demonstrated by
positive loadings along the light penetration axis), while eight species
tended to have lower abundances associated with higher light penetration
(as demonstrated by negative loadings along the light penetration axis;
Fig. 7). Conversely, `1\textsuperscript{st} quartile' small species
composition was unaffected by mean light penetration or mean intraplot
variation, and neither were retained as axes.

We performed analyses using both total abundance and flowering
abundance; however, because the analyses of flowering abundance were
more informative, we have focused on these. Half of the analyses using
the total number of individuals demonstrated significant relationships
between light penetration and small species abundance and richness,
compared to two-thirds of analyses using only the number of flowering
individuals. We provide further information on analyses using the total
number of individuals in the supplementary material (Fig. S3-S7).

\textbf{Discussion}

\emph{Understanding variation in the light environment}

To understand the effects of light limitation on small plant species in
a herbaceous plant community, we first characterized variation in light
penetration within-plots, among-plots, and across time through the
growing season. Despite existing assumptions that light is not
heterogeneously distributed within herbaceous communities, light
penetration across plots in our community ranged from 0.3-72.4\% (Fig.
S1A). Light penetration also varied within plots and across the growing
season, and the degree of variance in light penetration among intraplot,
interplot, and temporal measures was similar (Fig. 3). Light penetration
significantly increased from June to July as well as from June to August
but did not differ between July and August; thus, maximum canopy
development was reached by July.

Analyses of light penetration through the canopy of natural herbaceous
plant communities are rare (e.g., Kelly and Canham 1992); those that
exist are often conducted on communities that have been subjected to an
experimental treatment. These include various fertilization (e.g., Urbas
and Zobel 2000; Semchenko et al. 2012; Borer et al. 2014), watering
(e.g., Semchenko et al. 2012), mowing (e.g., Urbas and Zobel 2000;
Bachmann et al. 2018), herbivory (e.g., Izaguirre et al. 2006; Borer et
al. 2014), and shading or illumination treatments (e.g., Urbas and Zobel
2000; Izaguirre et al. 2006; Semchenko et al. 2012). Varied experimental
treatments, along with differences among studies in how the light
environment is quantified (e.g., 5cm from the ground by Kelly and Canham
1992; 3-150 cm from the ground by Bachmann et al. 2018), make it
difficult to compare across studies, and to get a general sense of light
environments in herbaceous communities. However, when species richness
was manipulated via seeding, analyses of old-field meadow and grassland
communities have described ranges of percent light penetration similar
to our community, with averages as low as 13\% in 8-species mixtures
(Spehn et al. 2000), 20-32\% in 16-species mixtures (Bachmann et al.
2018), and 3\% in 32-species mixtures (Spehn et al. 2000). Within our
community, total species richness ranged from 13-29 among plots; thus,
the ranges of light penetration and species richness recorded in our
non-experimental study site are comparable to findings from experimental
herbaceous study sites.

Because the herbaceous canopy lacks shrubs and trees, it is a widely
held view that light is both highly abundant and relatively homogenous
within herbaceous communities. However, average light penetration within
our community (5-29\%) is comparable to 18-27\% light penetration
through a mixed wood temperate forest (Bartemucci et al. 2006) and, for
some plots, 0.4-6.7\% light penetration through a tropical forest
(Valladares et al. 2002). While herbaceous canopies are likely slower to
close, many small plant species in herbaceous communities persist
underneath these canopies. While shade tolerance is generally accepted
as supporting the ability of small plant species to survive in forest
understories, it remains an open question whether shade tolerance plays
a similar role in herbaceous plant communities.

\emph{Testing hypotheses related to species size and light penetration}

According to the size-advantage hypothesis, larger species are
competitively superior to smaller species, mainly due to their ability
to intercept light, shading plants below (e.g., Schwinning and Weiner
1998; Anten 2005; Tracey and Aarssen 2014; Tracey et al. 2017).
Consistent with this, we found that light penetration significantly
decreased with mean plot height (Fig. 5). Importantly, the height of
species in sample plots, as measured here, left approximately 90\% of
variation in plot-level light penetration unexplained. Some of this
unexplained variation is inevitably due to the way in which we estimated
plot height -- future assessments based on measuring the heights of all
plant species in plots would be of benefit but were not possible for
this study. Regardless, this result highlights that while tall species
have the capacity to shade smaller plants, the biological significance
of this advantage may be greatly reduced by the size distributions of
tall species in plots, and by other factors that contribute to variation
in composition within herbaceous plant communities. Inevitably, other
factors, like the available soil nutrients, can limit the height of the
canopy by controlling which species can persist (Borer et al. 2014).
Large species with large minimum reproductive size thresholds (Tracey
and Aarssen 2019) may be less likely to persist in low soil nutrient
settings and self-thinning among tall plant species may create regular
gaps, allowing light to reach smaller species (Schamp and Aarssen 2014).
Thus, nutrient limitation and competition among tall species may
decrease the abundance of large plant individuals per area,
simultaneously increasing light penetration and altering the importance
of light as a previously limited resource. Herbivory can also impact
canopy development directly, and indirectly by influencing plant
investments in herbivore defense.

We found evidence that small species abundance and richness are limited
by light penetration; these patterns were consistent when we considered
reproductive plants and small species were defined as those below the
median height of species in the community, but inconsistent when small
species were defined as those in the first quartile of species heights
in the community. These findings were less consistent across both
definitions of small species when we did not focus on reproductive
plants (Table S1). Importantly, the coefficients of determination
(R\emph{\textsuperscript{2}} ) for regressions between light penetration
and our response variables, when significant, ranged between 8-11\%
(Fig. 6). Furthermore, only 4.2\% of the variation in the composition of
small species, defined using the median, was explained by light
penetration (Fig. 7). Low light penetration had a significant, but
meagre impact on small species abundance and richness in this community.

These results, in combination with the above results showing that large
species contribute only slightly to patterns of light penetration,
provide useful context for understanding the conundrum of small species
diversity in natural systems in spite of experimental observations that
small species are at a competitive disadvantage. First, light
penetration in herbaceous systems is relatively low, but less so earlier
in the growing season (i.e., June in this study system). It is possible
that some small species take advantage of higher light penetration early
in the growing season. This is consistent with observations that smaller
plant species often flower earlier in the season (Du and Qi 2010; Sun
and Frelich 2011; Segrestin et al. 2020). Second, within-plot variation
in light penetration, reflecting heterogeneity in plot canopy structure,
had no impact on small species abundance and richness, suggesting that
local sunflecks are relatively unimportant in maintaining small species
in herbaceous communities. This may be because plots with more variation
in canopy structure tended to be less shaded on average, reducing the
role of sunflecks as a critical source of light. Third, the fact that
small species richness is only modestly impacted by light penetration
suggests that many small species possess some mixture of shade avoidance
and shade tolerant strategies that allow them to persist in shaded
conditions. Shade tolerance may contribute to increased reproductive
economy in smaller species (Aarssen 2008). Shade tolerant species
implement morphological and physiological traits which increase
efficiency of carbon gain and stress tolerance, allowing them to persist
under low light conditions (Valladares and Niinemets 2008).
Additionally, small species richness, defined using the
1\textsuperscript{st} quartile, was no lower when light penetration was
lowest, indicating that the richness of the 25\% smallest species in the
community was maintained under increasingly low light availability.
Adaptation to low light levels via phenotypic plasticity in
morphological traits may explain the persistence of small species
richness under low light (Ballaré 1994; Urbas and Zobel 2000; Hallik et
al. 2009; Niinemets et al. 2015), as some individuals may express traits
associated with greater light capture (e.g., high specific leaf area;
Valladares and Niinemets 2008), thus maintaining species presence under
reduced abundance. The characteristics of the light environment in our
community, and likely the characteristics of many resident small species
ensure that any disadvantage they suffer in competition for light is
minimal.

The effects of shading on small species abundance and richness were more
consistently observed and stronger in general when we focused on
reproductive individuals in sample plots. This demonstrates that
although `median' small species were able to persist under low light
with no detected loss in abundance or richness, some were not successful
enough to reach reproductive maturity. The presence of flowering
individuals in a sample plot is evidence of a species' capacity to
successfully establish in that environment. Our results make it clear
that light penetration does indeed affect which small species can find
success, but its impact on small species abundance and richness is
relatively minor (8-15\% of variation explained). Our results also
support the contention that focusing censuses on flowering species when
studying coexistence, can clarify plant community dynamics (Schamp et
al. 2016, Schamp and Jensen 2019).

\textbf{Conclusion}

The size of resident species in old-field vegetation plots had a
significant impact on light penetration; however, it appears that this
impact is quite limited. This should be studied further, with more
thorough assessments of plot-level height, to clarify the degree to
which large species have the capacity to shade smaller species in
herbaceous communities. Small plant species abundance and richness were
significantly lower when light penetration was lower; however, this
impact was once again relatively small. Our results are consistent with
the results of competition experiments that reveal a size-advantage in
competition, but add context by demonstrating that, in our study
community, this advantage has only a very small impact on small species.
Several possible explanations exist. For example, mitigating impacts on
large plants, like herbivory, may reduce the capacity for large species
to outcompete small species for light. It is also possible that one or
more of several characteristics of small species (early season growth
and reproduction, shade tolerance) contribute to greater reproductive
economy of small species (Aarssen 2008). This study also adds to the
sparse body of literature on the light environment in unmanipulated
herbaceous plant communities.

\textbf{Acknowledgments:} Funding was provided by a discovery grant to
LA from the Natural Sciences and Engineering Research Council of Canada
(NSERC). Summer salary for GP was provided by an Undergraduate Summer
Research Award from NSERC. Jennifer Waugh provided field assistance, and
the staff of the Queen's University Biological Station provided
logistical support for this project. The authors declare that there is
no conflict of interest.

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\textbf{Figures}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1:} Experimental plot setup for measuring light
penetration. Plots were laid out in 1 m x 1 m squares divided into a 3 x
3 grid for a total of nine equal subsections within each plot. We took
three light intensity measures (\selectlanguage{greek}µ\selectlanguage{english}mol
s\textsuperscript{-1}n\textsuperscript{-2}) at the center of each row
directly above the canopy, with an additional nine measurements (one in
each subsection) at the ground-level. We then calculated three measures
of percentage of light penetration for each plot by taking the mean
light intensity at the ground-level for each row and using the equation:
100 \selectlanguage{ngerman}× (ground-level light intensity / above-canopy light intensity).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2:} Frequency of maximum height (cm) values for species
that occur at our old-field site (N=58). Vertical lines mark the cutoff
points for each of the small species definitions: species below the
first quartile (`1\textsuperscript{st} quartile'; dashed light blue,
N=15, \textless{}53.25 cm), and species below the median height
(`median', dotted light red, N=29, \textless{}83 cm).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Figure 3:} Interplot, intraplot, and temporally driven variance
in light penetration (calculated as 100 \selectlanguage{ngerman}× ground-level light
intensity/above canopy light intensity; \selectlanguage{greek}µ\selectlanguage{english}mol
s\textsuperscript{-1}n\textsuperscript{-2}). To quantify intraplot
variation, variance was calculated within each plot for each month
(N=147, median=26.2). For interplot variation, mean light penetration
was calculated for each plot, and variance in these means was calculated
for each month (N=3, median=77.3). Temporal variation was also
quantified using mean light penetration for each plot. Variance in
individual plot means across months (June, July, August) were calculated
(N=49, median=57.4). Boxes represent the 25th to 75th percentiles of the
data, and whiskers represent the 10th and 90th percentiles.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Figure 4:} Comparisons of light penetration (\%) between June
and July (A), June and August (B), and July and August (C). Boxplots
show absolute differences in light penetration within each plot between
month pairings. Line plots show change in mean light penetration for
each plot between month pairings. Mean light penetration at the plot
level was significantly different between months (repeated measures
ANOVA, F\textsubscript{2,96}=9.2, \emph{P} \textless{} 0.001). Mean
light penetration in June was significantly higher than in July
(Bonferroni, \emph{P} \textsubscript{adj} \textless{} 0.001) and August
(Bonferroni, \emph{P} \textsubscript{adj} = 0.036). July and August did
not significantly differ (Bonferroni, \emph{P} \textsubscript{adj} =
0.4). Between June and July, 37 plots decreased in light penetration
while 12 plots increased. Between June and August, 31 plots decreased in
light penetration, while 18 plots increased. Between July and August, 22
plots decreased in light penetration while 27 plots increased. Boxes
represent the 25th to 75th percentiles of the data, and whiskers
represent the 10th and 90th percentiles. Lines coloured in black
represent plots that decreased in light penetration from the first to
the second month, and lines coloured in goldenrod represent plots that
increased in light penetration from the first to the second month. Month
pairings marked by an asterisk (*) significantly differed in mean light
penetration.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Figure 5:} Mean plot-level maximum height weighted by species
plot-level abundance (`mean plot height', cm) vs. mean light penetration
(\%) per plot. Mean light penetration significantly declined with mean
plot height (\emph{P} = 0.025, R\textsuperscript{2} = 0.08).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\textbf{Figure 6:} Flowering abundance of small species under the first
quartile height (`1\textsuperscript{st} quartile'; A), flowering
abundance of small species under the median height (`median', B),
flowering richness of `1st quartile' small species (C) and flowering
richness of `median' small species (D) vs. mean light penetration (\%)
per plot. We used log\textsubscript{10} transformations on `1st
quartile' and `median' small species flowering abundance and fit all
with linear models. Flowering `1\textsuperscript{st} quartile' small
species (A; \emph{P} = 0.027, R\textsuperscript{2} = 0.08), flowering
`median' small species (B; \emph{P} = 0.012, R\textsuperscript{2} =
0.11) as well as richness of flowering `median' small species
(D;\emph{P} = 0.014, R\textsuperscript{2} = 0.10) significantly declined
as mean light penetration decreased. Flowering `1st quartile' species
richness was not significantly affected by light penetration (C).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image7/image7}

\end{center}
\end{figure}

\textbf{Figure 7:} Distance-based redundancy analysis (dbRDA) ordination
for composition of flowering species smaller than the median height
(`median', N = 26, \textless{}83cm) with mean light penetration as a
constrained axis. Light penetration (`LP', grey arrow) explained 4.2\%
of the total variation in `median' species flowering abundance among
plots (dbRDA1, \emph{P} = 0.031, pseudo-F\textsubscript{1,49}=2.06).
Each point represents a plot. Species abbreviations are as follows:
Bar\emph{Barbarea vulgaris} ; Cer \emph{Cerastium fontanum} ;
Chr\emph{Chrysanthemum leucanthemum} ; Cli \emph{Clinopodium vulgare} ;
Dan\emph{Danthonia spicata} ; Ele \emph{Eleocharis compressa} ;
Equ\emph{Equisetum arvense} ; Fra \emph{Fragaria virginiana} ;
Hie\emph{Hieracium aurantiacum} ; Jun \emph{Juncus tenuis} ;
Mit\emph{Mitchella repens} ; Oen \emph{Oenothera perennis} ; Oxa
\emph{Oxalis stricta} ; Pan \emph{Panicum capillare} ; P.la
\emph{Plantago lanceolata} ; P.ma \emph{Plantago major} ; Poa
\emph{pratensis} ; Pot \emph{Potentilla recta} ; Pru \emph{Prunella
vulgaris} ; Rum \emph{Rumex acetosella} ; Sis\emph{Sisyrinchium
montanum} ; Ste \emph{Stellaria graminea} ; Tar\emph{Taraxacum
officinale} ; Tra \emph{Tragopogon pratensis} ; T.au\emph{Trifolium
aureum} ; T.re \emph{Trifolium repens} .

\selectlanguage{english}
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