Journal of Experimental Marine Biology and Ecology
301 (2004) 193 – 224
www.elsevier.com/locate/jembe
Effects of simultaneous changes in light, nutrients,
and herbivory levels, on the structure and function
of a subtropical turtlegrass meadow
Silvia E. Ibarra-Obando a,*, Kenneth L. Heck Jr. b,c,
Patricia M. Spitzer b
a
Centro de Investigación Cientı́fica y Educación Superior de Ensenada (CICESE),
Km 107 carretera Tijuana-Ensenada, Ensenada, Baja California, Mexico
b
Dauphin Island Sea Laboratory (DISL), 101 Bienville Boulevard, Dauphin Island, AL 36528, USA
c
Department of Marine Science, University of South Alabama, Mobile, AL 36688, USA
Received 6 August 2002; received in revised form 24 September 2003; accepted 1 October 2003
Abstract
The interactive effects of light, nutrients, and simulated herbivory on the structure and
functioning of a subtropical turtlegrass bed were analyzed monthly from May to October 2001 in
Perdido Bay, FL. For each of the three factors, two levels were evaluated in a factorial design with
four replicates per treatment. The variables included: light, at ambient and 40% reduction; nutrients,
at ambient and 2 ambient concentrations; and herbivory, with no herbivory and simulated effects
of a density of 15 sea urchins/m2. In practice, light levels turned out to be 40% of surface PAR for
ambient conditions, and 16% for shaded plots. Biomass removed as herbivory represented, on
average, slightly less than 20% of the above-ground biomass. Separate three-way ANOVAs found no
significant three-way interactions for any of the response variables, and few two-way interactions.
There were no significant nutrient effects on turtlegrass above-ground biomass, although nutrient
additions produced significant decreases in epibiont biomass, and net above-ground primary
production (NAPP); significant increases in below-ground biomass during the peak of the growing
season. Shoot density and average number of leaves per shoot increased significantly, while the C/N
ratio of the oldest leaf in the enriched plots decreased significantly. Light reduction significantly
negatively affected all response variables, except below-ground biomass, shoot density and leaf
length. Herbivory had isolated and inconsistent significant effects on below-ground biomass, shoot
density, average number of leaves per shoot, and leaf length and width. Overall, our results indicate
that nutrients are not limiting in Perdido Bay, and that nutrient additions had mostly detrimental
effects. Light appeared to be the most important variable limiting seagrasses growth and abundance,
* Corresponding author. P.O. Box 434844, San Diego, CA 92143-4844, USA. Tel.: +52-646-1-75-0500x24265; fax: +52-646-1-75-05-45.
E-mail address: [email protected] (S.E. Ibarra-Obando).
0022-0981/$ - see front matter D 2003 Elsevier B.V. All rights reserved.
doi:10.1016/j.jembe.2003.10.001
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and as with terrestrial plants, seagrasses seemed to respond more to light and nutrients than to
herbivory. However, it is essential that additional tests of the single and interactive effects of the three
key factors of light, nutrients and herbivory be done to evaluate the generality of our work, since our
study is the first of its kind in seagrass meadows.
D 2003 Elsevier B.V. All rights reserved.
Keywords: Growth and abundance; Seagrasses; Simulated herbivory; Thalassia testudinum; Top-down and
bottom-up controls
1. Introduction
Marine plant populations are thought to be limited primarily by physical disturbance,
herbivory, light, and nutrients (Estes and Peterson, 2000). For seagrasses, nutrient supply,
light availability, and/or physical factors have received most attention. Light availability
affects seagrass productivity, depth distribution, and abundance (Backman and Barilotti,
1976; Vincente and Rivera, 1982; Dennison, 1987; Dennison et al., 1993; Duarte, 1991),
and the consequences of physiological stress associated with light limitation are diminished growth, increased shoot mortality, and limited depth distribution (Kenworthy and
Fonseca, 1996). Uncertainty still remains as to what extent nutrients limit the growth and
development of seagrasses meadows (Powell et al., 1989; Hemminga et al., 1991; Agawin
et al., 1996; Terrados et al., 1999). Nitrogen availability is believed to be a major factor
controlling seagrass growth in the temperate zone (Short, 1983; Hemminga et al., 1994). In
contrast, in tropical environments, phosphorus can be limiting due to its tendency to
become adsorbed to carbonate sediments (Short et al., 1985). Nutrient content of leaves
has been used as an indicator of the relative availability of nitrogen and phosphorus in
coastal ecosystems, and a positive correlation between nutrient concentrations in leaf
tissue and seagrass standing crop and primary production has been reported (Fourqurean et
al., 1992; Perez et al., 1994). Nutritive quality of seagrass leaves has been demonstrated to
control grazing activities by vertebrates, although invertebrates are thought to be extreme
generalists in their diets (Valentine and Heck, 2001). Herbivory has increasingly been
recognized as a widespread and underestimated trophic pathway in seagrass meadow food
webs (see review in Valentine and Heck, 1999).
To date, changes in the above-mentioned limiting variables have been analyzed
separately, or at most, changes in two of them have been considered concurrently. For
example, the effect of reduction in light availability on the structure and productivity of
seagrass beds has been analyzed by Bulthuis (1983), Neverauskas (1988), Gordon et al.
(1994), Czerny and Dunton (1995), Fitzpatrick and Kirkman (1995), and Shafer (1999),
among others. The effect of nutrient additions to sediments or the water column has been
studied by Tomasko and Lapointe (1991), Lapointe et al. (1994), Agawin et al. (1996), Lee
and Dunton (1999), Wear et al. (1999), all of whom reported that nutrient enrichment and
the light reduction that results from it, negatively impacted seagrass vigor. Short et al.
(1995) used mesocosms to experimentally measure the separate effects of shade and
nutrients, as well as their interaction, and quantitatively assess their impact on seagrass
growth, morphology, and biomass. They found shading to be the primary effect of nutrient
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195
loading, as algae became abundant at the expense of eelgrass, Zostera marina. Shading
reduced eelgrass growth and biomass, as did nutrient enrichment, but direct shading
resulted in longer leaves, while enrichment resulted in shorter leaves.
Herbivory under natural and simulated conditions has been studied by Kirkman and
Young (1981), Heck and Valentine (1995), Cebrián and Duarte (1998), Cebrián et al.
(1998), Valentine et al. (1997, 2000), and Maciá (2000). Valentine et al. (1997, 2000) and
Maciá (2000) found that sea urchin, Lytechinus variegatus, herbivory stimulated increased
production of turtlegrass shoots during summer, so that no significant differences in aboveground biomass between control and grazed treatments could be measured. However, an
important seasonality existed, as intense herbivory at the end of the growing season (fall
and winter), or in spring could create unvegetated patches. Valentine and Heck (2001)
analyzed the effect of nutrient enrichment on sea urchin grazing, finding that when
provided with seagrass leaves containing high C/N ratios, sea urchins would ate larger
amounts of grass. This was interpreted as a compensatory response for the low nitrogen
content of their forage.
The need to understand the combined effects of multiple limiting resources on marine
plant growth has been recognized (Valentine and Heck, 1999; Estes and Peterson, 2000);
however, the single and interactive effects of light, nutrients and herbivory have only been
tested in freshwater (Sumner and McIntire, 1982; Winterbourn, 1990; Rosemond, 1993),
and terrestrial environments (Gertz and Bach, 1994). In general, these studies found that
the effects of grazing on community structure were closely related to the response of the
flora to physical processes (light and nutrients). For example, Rosemond (1993) reported
that the interaction between light, nutrients, and herbivory produced the greatest effects on
algal biomass and productivity; morever, these effects were much greater and, in some
cases, different from the response of single factor manipulations. A continuum of plant
responses to herbivory has been noted for terrestrial plants, with the impact of herbivory
being a function of plant association, nutrient availability, and timing of grazing
(Maschinski and Whitham, 1989). For seagrasses, a continuum of responses to grazing
pressure, ranging from negligible effects on shoot production at low intensity, to
stimulatory effects at intermediate intensity and negative effects at high intensity has
been reported (see review by Williams and Heck, 2001). In this study, we analyzed the
interactive effects of light, nutrients and herbivory as they influenced the structure and
function of turtlegrass, Thalassia testudinum meadows. Based on our review of the
existing literature we expected some combination of top-down (herbivory) and bottom-up
factors (light, nutrients) would control the distribution and abundance of seagrasses. T.
testudinum was selected for study, as it is the dominant species in the extensive seagrass
meadows in the Gulf of Mexico and the Caribbean Sea (Den Hartog, 1977).
2. Materials and methods
2.1. Study site
Perdido Key is located in northwest Florida near the Alabama border (30j18.5VN;
87j23VW) (Fig. 1). It is a natural barrier island stretching for about 23 km along the
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Fig. 1. Location of the study site, Perdido Bay, FL.
northern Gulf of Mexico. Climate is subtropical with an average summer temperature of
27 jC, and average winter temperature of 13 jC. Average rainfall is 157.5 cm. Lunar tides
are diurnal and average 0.5 m. Winds are predominantly from the northwest in winter and
the southeast in summer, and they control the height of waves and direction of longshore
transport (Kent, 1976). Waves have moderately high energy, with breaker heights between
27 cm and 1.5 m (Gorsline, 1966). Major rivers drain into Pensacola Bay and into the Gulf
of Mexico through Pensacola Pass, at the eastern end of Perdido Key. Variable flow
regimes sometimes set up an east – west salinity gradient along the exposed shoreline,
depending on winds, tides, and river discharge (Schropp et al., 1991; Rakocinski et al.,
1996; Wear et al., 1999). Sediment is dominated by fine-to medium-grained quartz sand
with small amount of shell hash and organic matter ( < 6%) (Kent, 1976; Rakocinski et al.,
1993). Monospecific and mixed beds of the three seagrass species most widely distributed
in the Gulf of Mexico, and along the coast of Florida are present: T. testudinum Banks ex
könig, Halodule wrightii Ascherson, and Syringodium filiforme Kützing (Wear et al.,
1999). The site selected for this study is known as Johnson Beach, which occurs within the
Gulf Islands National Seashore Park (Fig. 1).
2.2. Experimental design
Three factors—light, nutrients, and herbivory—were manipulated at two levels. For
light, ambient levels, and approximately 40% reduction were used. The 40% light reduction
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197
level was established as a middle point of reported values of 50% reduction during brown
tide conditions (Dunton, 1994; Onuf, 1996), and 35 –50% under experimental conditions
(Bulthuis, 1983; Neverauskas, 1988), both of which produced significant changes in
structural and functional characteristics of seagrass species. For Perdido Bay, a 50%
reduction in light levels due to dock shading was reported by Shafer (1999). Light was
reduced by 0.635 cm polyethylene mesh tied on the top and south and east sides of the
selected plots. Mesh was periodically cleaned to prevent greater light reduction due to
fouling or siltation. Although we did not have a control treatment for mesh artifacts, the fact
that simple shading structures do not substantially modify water flow or environmental
variables other than light has been demonstrated by Backman and Barilotti (1976), and
Fitzpatrick and Kirkman (1995). For example, Fitzpatrick and Kirkman (1995) compared
the growth of Posidonia australis under clear and black plastic, and found that leaf growth
under clear plastic was no different than the growth of seagrass in control areas (no shade).
For nutrients, we used ambient levels, and a target of two times natural concentrations.
Enrichment was carried out using 1.8 kg slow release Osmocote fertilizer per experimental
plot (18% ammonium and 6% phosphate by weight; N/P release ratio, 3:1). Nutrients were
placed inside PVC tubes (6 cm diameter 30 cm long with twenty 1-cm holes) at the
center of each plot. Plots without nutrient additions had empty PVC tubes on their center.
Tubes were replaced every 2 months to assure that a high nutrient concentration was
maintained. Once in the laboratory, nutrients remaining in the collected tubes were dried to
constant weight to calculate nutrient loading rates in the field (Wear et al., 1999; Heck et
al., 2000).
For herbivory, densities of 15 sea urchins m 2 were simulated by cutting in half all
leaves on each shoot, as no sea urchins are present at the study site. Clipping to different
blade lengths to mimic a herbivory gradient by herbivores was used by Cebrián et al.
(1998) for seven seagrass species. Results indicated that the pattern of variation in leaf
growth per shoot with the intensity of clipping treatment differed notably among
populations, with no apparent site or species-specificity. In our study, clipping was
repeated monthly from July to September, and the leaf biomass removed was brought
to the laboratory to assess its dry and ash free dry weight (see below). We clipped all
leaves to a similar length to mimic the ‘‘mowed lawn’’ appearance of seagras meadows
that are intensively grazed by sea urchins (e.g., Rose et al., 1999). The simulated sea
urchin density represents the mean density encountered in St. Joseph Bay, northeastern
Gulf of Mexico (Valentine and Heck, 1991; Heck and Valentine, 1995). For the marine
environment, a mean value of 60% reduction in vascular plant standing crop as a result of
herbivory has been reported in the review by Lodge et al. (1998). In St. Joseph Bay, sea
urchin consume between 50% and 90% of the annual above-ground turtle grass production
(Valentine et al., 1997). As we were interested in simulating moderate, but still substantial
amounts of herbivory, we uniformly cropped 50% of the above-ground biomass.
The experiment’s three main effects, light (ambient and 40% reduction), nutrients
(ambient and 2 ambient concentrations), and simulated herbivory (no herbivory and
simulated herbivory of 15 sea urchins/m2) were tested in a factorial design. For each
treatment four replicates were used for a total of 32 plots. The experiment was started on
May 15, 2001. Shortly after this date however, the shaded plots were disturbed by high
waves and were reestablished on May 31st. The experiment lasted approximately 6
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months (May –October). Time zero samples (n = 20) were collected haphazardly just
outside the experimental plots to establish initial conditions without disturbing the actual
plots. The following variables for T. testudinum were measured at time zero and on a
monthly basis: shoot density (number of shoots m 2); average number of leaves per shoot;
oldest leaf length and width (cm); above- and below-ground biomass (g DW m 2);
epibiont biomass (g DW m 2), and areal Net Above-ground Primary Production (NAPP)
(g DW m 2 day 1). Leaf C/N ratio (Ag of either C or N/mg DW of leaf tissue) was
determined at time zero, middle and end of the experiment.
2.3. Field and laboratory procedures
Two shallow beds parallel to the shore, dominated by T. testudinum but containing
smaller amounts of H. wrightii, were selected for study. The first bed contained all plots
with nutrient additions (16); the second contained a similar number of plots without
nutrient additions. To avoid possible cross-contamination, the two beds were approximately 25 m apart (Heck et al., 2000), with the nutrient-addition block being closer to the
shore. For each treatment, square plots of 0.5 m2 area were marked with rebar stakes and
PVC tubes at the four corners. Distance between treatments was also 0.5 m2.
At the beginning of the experiment (May) and 1 month later, water samples were
collected from each experimental plot to determine inorganic nutrients and water column
Chl a concentrations. Water samples were collected at the canopy height (Heck et al.,
2000) with 60 ml acid-washed plastic syringes that were kept on ice until arrival at the
laboratory, where they were filtered through a GF/F filter, placed in acid-washed 60 ml
plastic bottles, and frozen. Concentrations of ammonium, nitrate + nitrite, and phosphate
(AM) were determined using standard wet chemical techniques (Alpkem Manual, 1988)
adapted for use on an Alpkem RFA/2 Nutrient Autoanalyzer. Chl a was determined using a
Turner Designs Model 10 Fluorometer, after the acidification method of Lorenzen
(Strickland and Parsons, 1972).
Cores of 7.6 cm internal diameter 15 cm deep were used to collect T. testudinum
samples. Sampled areas were marked with plastic flags inserted into the sediment to
prevent resampling. Seagrass samples were sieved, placed in marked plastic bags, and kept
cool until arrival at the laboratory where they were frozen for later analyses. Cores
provided material to assess shoot density, leaf density per shoot, length and width of oldest
blade, epibiont biomass and above- and below-ground turtlegrass biomass. Turtlegrass
epibionts were removed by scraping leaves with a razor blade, and their biomass
determined as indicated below for leaves. Leaves were placed in aluminum pans, oven
dried at 80 jC for 24 h ( F 0.01g). Ash-free dry weight was determined by placing dried
samples in a muffle furnace at 500 jC for 5 h (Valentine et al., 2000). Roots and rhizomes
were processed similarly. To estimate the C/N ratios in turtlegrass leaves, a shoot at
random was collected from each plot and kept cool until arrival at the laboratory, where
they were frozen. Epibionts from the oldest leaf of each shoot were removed, and the blade
cut in small pieces and dried for 24 h. Preweighed subsamples were then combusted in a
Carlo Erba 1500 CN Analyzer.
Areal NAPP was assessed as described by Dennison (1990). For each plot, all leaves
on all shoots inside a 0.01 m2 quadrat were punctured with a probe at the top of the leaf
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199
sheath. Marked shoots were flagged in order to facilitate finding them after 11 –14 days,
when they were removed with a corer and returned to the laboratory where they were
frozen until being processed. Areal NAPP was estimated by measuring new growth distal
to the hole in punctured blades, and all new growth of unpunctured leaves that appeared
on the marked shoots. Biomass of all new leaf tissue formed during the 11– 14 day
incubation period therefore represented above-ground production. This material was dried
to constant weight ( F 0.01 mg) at 80 jC, and ash-free dry weight was determined as
indicated previously for blade biomass. Weights are expressed as leaf production in g
AFDW m 2 day 1.
Water temperature and salinity were determined during every visit to the field with an
Orion 140 conductivity meter. Ambient light and underwater light were measured with a
Licor spherical (4 C) sensor and LI-1000 data logger.
At the end of the experiment, one sediment core per plot was taken for grain size
analysis. Samples were passed through a 62-A sieve to separate the silt–clay fraction,
using the wet sieving method described by Buchanan and Kain (1971).
2.4. Statistical analysis
Chl a and water column nutrient concentrations at the two selected areas, before and
after enrichment, were analyzed with a Kruskall– Wallis test, as data failed the normality
Fig. 2. Recorded values for water temperature (jC) and salinity (x) during the study period.
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Table 1
Water column dissolved inorganic nutrients (Am), and chlorophyll a (mg l
turtlegrass beds before and after enrichment
1
) concentrations in the selected
Date
Area
NO3 + NO2 (Am)
NH4 (Am)
PO4 (Am)
Chl a (mg l
May 15
June 14
Ambient
Enriched
0.34 F 0.02
0.93 F 0.17*
( p = 0.0006)
2.81 F 0.36
2.1 F 0.23
0.14 F 0.005
0.12 F 0.005*
( p = 0.005)
2.25 F 0.25
4.66 F 0.28*
( p = 0.000)
1
)
Values represent mean F 1 S.E. n = 20 on May 15, and n = 16 on June 14. Significant differences ( p < 0.05) are
indicated with an asterisk. Phosphate concentrations between the two dates differ statistically but not analytically.
and equal variance test. The same test was used to analyze grain-size data and percent
biomass removed as herbivory.
One-way ANOVA was used to analyze the homogeneity of the two selected areas with
respect to the response variables at the beginning of the experiment.
Because two of the response variables differed significantly between blocks at T0 (see
below), we analyzed values of response variables after calculating the standardized
difference with respect to time zero. For each variable, the monthly mean was subtracted
from the May (T0) mean, and the result divided by the May mean [i.e. (June mean – May
mean)/May mean]. Once the standardized differences were obtained, they were analyzed
with a three-way ANOVA after testing for normality and variance homogeneity. No
transformations were used. The significance level was set at 0.05. The software used was
Sigmastat 2.0.
3. Results
3.1. Environmental conditions
Mean water temperature during the study period was 26.9 F 1.16 jC ( F 1. S.E.).
Values of 29 jC or higher were measured between June 14 and September 5, with a peak
of 31.4 jC on July 24. A steady reduction characterized the end of summer – beginning of
autumn period, with a reading of 17.9 jC by the end of the experiment. Salinity varied
between 30.3x(May 15) and 24.0x(August 20), with a mean of 27.08 F 0.68x. Low
salinities were associated with summer rains (Fig. 2). Percent sand in sediment samples
ranged between 76.95% and 94.95%, without any significant difference between treatments ( p = 0.3541).
Table 2
Nutrients delivered in the enriched plots
Period
Initial
weight (g)
Nutrients
delivered (g)
Enrichment
Daily nitrogen
rate (g day 1) delivery (g day
May 11 – July 9 1804.03 F 0.45 1544.57 F 34.13 26.18 F 0.58
July 10 – Sept. 4 1800.01 F 0.004 1377.54 F 42.94 24.60 F 0.77
Sept. 5 – Oct. 30 900.31 F 0.05
592.37 F 23.41 10.77 F 0.43
4.97 F 0.11
4.67 F 0.15
2.05 F 0.08
1
Daily phosphorus
) delivery (g day 1)
1.57 F 0.03
1.48 F 0.05
0.65 F 0.03
Values represent mean F 1 S.E; n = 16. Loadings were reduced in half during the cooler temperatures by the end
of the experiment.
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3.2. Experimental variables
The concentration of nitrite and nitrate in the water column practically tripled within a
month of enrichment, and Chlorophyll a concentration doubled. Ammonium and
phosphate concentrations remained stable (Table 1). From May 11 through September
Fig. 3. Recorded light values in the ambient and shaded plots. Top figure, values expressed as Ae/s/m2. Bottom
figure, values expressed as percentage of surface light reaching the bottom. The low light level for August 20
corresponds to a summer storm.
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4, the enriched plots received an average of 4.82 g N day 1 and 1.52 g P day 1 loadings
that were reduced in half by the cooler temperatures in the final part of the experiment
(Table 2).
Light values measured for both, shaded and unshaded plots reflected the annual cycle
of insolation. Mean light values for ambient treatments ranged from a low of
202.32 F 9.54 AE s 1 m 2 on August 20, to peak values, of 1489 F 120.47on July 12,
and of 1524.57 F 93.13 on October 30 (Fig. 3a). The grand mean for ambient treatments
was 911.89 F 36.93 AE s 1 m 2. The lowest recorded mean light level for shaded
treatments was 65.44 F 6.79 AE s 1 m 2 also on August 20, during a summer storm, and
the highest, 698.64 F 88.68 on July 12 (the value recorded on May 15 was not considered
valid, as it represents a single reading Fig. 3a). The grand mean for shaded treatments was
362.58 F 20.57 AE s 1 m 2. The range of values expressed as percentages was:
16.70 F 0.92 (August 20); 58.23 F 4.74 (July 12); 64.22 F 4.13 (October 30) for ambient
treatments. Range of percentages for shaded treatments was: 5.42 F 0.61 (August 20) –
27.26 F 4.00 (October 31) (Fig. 3b). Corresponding means are 39.94 F 1.53% and
15.84 F 0.89%. In general, light reduction imposed by shading was much greater than
the 40% originally planned.
Between July and September, mean percent biomass removed in the herbivory treatments ranged from 11.5 F 2.6% to 17.1 F 5.0% of above-ground biomass, with no
significant differences between treatments ( p > 0.05). Monthly percentages significantly
differed in September with 42.2 F 13.6%, in the 40% light, nutrition addition treatment
significantly greater than all other treatments ( p = 0.056) (Table 3).
3.3. Response variables
When the experiment started, epibiont biomass ( p = 0.002) and leaf length ( p = 0.011)
significantly differed between the two areas (Figs. 4 and 5). Over time, however, all
significant changes clearly resulted from treatment effects. For each response variable,
ANOVA values for main factors and their interactions are provided in Appendices A –I.
Epibiont biomass showed the greatest response, as nutrient additions surprisingly
produced significant negative effects throughout the experiment. In October, there was a
significant interaction between nutrients and light. No significant differences were found
for the effects of simulated herbivory ( p>0.05) (Fig. 4; Appendix A).
Table 3
Percent biomass removed in the simulated herbivory treatments
Treatment
July (%)
August (%)
September (%)
Ambient light, Nu +
40% light, Nu +
Ambient light, Nu
40% light, Nu
Global averages
10.1 F 3.1
16.4 F 2.6
17.9 F 2.2
19.2 F 1.7
15.9 F 1.4
16.9 F 7.8
6.5 F 2.5
6.7 F 1.9
16.0 F 5.5
11.5 F 2.6
8.9 F 2.2
42.2 F 13.6 * ( p = 0.056)
7.9 F 1.0
9.4 F 5.3
17.1 F 5.0
Values represent mean F 1 S.E. For each treatment, n = 4, global averages, n = 16. Significant differences
( p < 0.05) are indicated with an asterisk.
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Fig. 4. Standardized change in epibiont biomass (g AFDW/g AFDW scraped blade) as a function of different
nutrient, light, and herbivory levels. Asterisks indicate significant differences.
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Fig. 5. Standardized change in leaf length (mm) as a function of different nutrient, light and herbivory levels.
Asterisks indicate significant differences.
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Fig. 6. Standardized change in leaf width (mm) as a function of different nutrient, light and herbivory levels.
Asterisks indicate significant differences.
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Fig. 7. Standardized change in turtlegrass above-ground biomass (g AFDW/m2) as a function of different nutrient,
light, and herbivory levels. Asterisks indicate significant differences.
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Fig. 8. Standardized change in below-ground biomass (g AFDW/m2) as a function of different nutrient, light and
herbivory levels. Asterisks indicate significant differences.
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Fig. 9. Standardized change in NAPP (g AFDW/m2/day) as a function of different nutrient, light and herbivory
levels. Asterisks indicate significant differences.
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Fig. 10. Standardized change in density (number of shoots/m2) as a function of different nutrient, light and
herbivory levels. Asterisks indicate significant differences.
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Fig. 11. Standardized change in number of leaves per shoot as a function of different nutrient, light and herbivory
levels. Asterisks indicate significant differences.
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Fig. 12. Standardized change in leaf C/N ratio as a function of different nutrient, light and herbivory levels.
Asterisks indicate significant differences.
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Changes in nutrient and light levels did not produced significant effects on leaf length
( p > 0.05); however, simulated herbivory resulted in significantly shorter leaves by the
end of the experimental period ( p = 0.008) (Fig. 5; Appendix B). Leaf width was
significantly reduced by shading ( p = 0.018) and simulated herbivory ( p = 0.042), but no
significant differences were associated with nutrient enrichment ( p = 0.255) (Fig. 6;
Appendix C).
Above-ground biomass significantly increased between May and October in the control
plots ( p = 0.007), while it remained almost the same in the nutrient addition treatments.
Light reduction produced a significant decrease in above-ground biomass, while ambient
light levels favored a steady increase ( p < 0.001). No significant differences resulted from
simulated herbivory ( p > 0.05) (Fig. 7; Appendix D).
After an initial reduction, below-ground biomass increased in response to enrichment,
although significant differences were only found at the peak of the growing season, July
( p < 0.001) and August ( p = 0.007). No significant differences were associated with
changes in light or simulated herbivory ( p > 0.05) (Fig. 8; Appendix E).
NAPP was negatively affected by nutrient additions ( p = 0.048) and light reduction
( p = 0.006), while no significant effects were associated with simulated herbivory (Fig. 9;
Appendix F).
Shoot density significantly increased (practically doubling) in the enriched treatment
( p = 0.024), but no significant ( p > 0.05) differences resulted from changes in light or
simulated herbivory (Fig. 10; Appendix G).
Nutrient additions favored an increase in the average number of leaves per shoot
( p < 0.001), while light reduction promoted their reduction ( p < 0.001). No significant
differences ( p > 0.05) resulted from simulated herbivory (Fig. 11; Appendix H).
During August, the C/N ratio of the oldest leaves showed a significant reduction in the
enrichment treatment ( p = 0.004), indicating that a portion of nitrogen we delivered had
been taken up by the shoots. Although this trend existed in October, the difference was not
significant ( p = 0.066). Light reduction promoted a significant reduction in the C/N ratio in
October ( p = 0.010). No significant differences ( p > 0.05) were found as a result of
simulated herbivory (Fig. 12; Appendix I).
4. Discussion
During the course of the experiment there was never a time in which there were
significant three way interactions, and shoots responded more often to changes in nutrients
and/or light than to herbivory. While nutrient additions triggered positive (shoot density,
and average number of leaves per shoot), negative (NAPP and epibiont biomass), and
essentially no responses (above-ground biomass), light reductions, when significant,
always had a negative effect on response variables. Simultated herbivory produced
relatively few significant effects and there were no consistent effects of leaf cutting on
any of the response variables, indicating that plants effectively compensated for leaf loss
under most conditions.
Gertz and Bach (1994) examined how light and nutrients influenced the ability of
tomato plants to compensate for defoliation. In their experiment, nutrients affected plant
S.E. Ibarra-Obando et al. / J. Exp. Mar. Biol. Ecol. 301 (2004) 193–224
213
growth rate much more strongly than did light. Light and nutrients, however, each
influenced how herbivory affected plant growth. Defoliation significantly decreased
growth rate only under conditions of low light and high nutrients. Biomass was low in
all treatments, except high levels of both light and nutrients, and it was under these
conditions that defoliation significantly decreased biomass. Gertz and Bach (1994)
concluded that herbivore impacts on plant growth are strongly condition-dependent. As
already stated, in our experiment light was the most common limiting factor (see
Appendices), and no three-way interactions were found; however, a combined effect of
light and simulated herbivory on NAPP was evident in July ( p = 0.041) and August
( p = 0.010), indicating that no compensatory growth took place under low-light conditions
(Appendix F and Fig. 9). The same was true for leaf width in September (Light Herbivory, p = 0.010), while in October, both factors had independent significant effects
(Light, p = 0.018; Herbivory, p = 0.042) (Fig. 6). Simulated herbivory also had an effect on
leaf length under conditions of high nutrients and high light (Fig. 5), which resembles
what Gertz and Bach (1994) reported for biomass.
In a study designed to analyze the effect of different environmental conditions (depth)
and herbivory on the structure and function of T. testudinum beds in the Florida Keys,
Valentine et al. (2000) found that the impacts of sea urchin grazing were highly variable.
While there was a clear seasonal pattern of stimulatory effects in the shallow bed ( < 2 m),
no significant effects were measured in the deep bed (6– 7 m). Valentine et al. (2000)
concluded that the lack of a significant effect at the deep site could represent the combined
effect of the low sea urchin density used (0, 4 and 8 individuals/m2), and the low light
levels at the site. Valentine et al. (2000) also emphazised the need to develop a more
complete understanding of the mechanisms by which seagrasses can compensate for losses
of tissues under varying environmental conditions, as they estimated that below-ground
production more than doubled at the shallow site as a result of grazing. With a lag of 1 –2
months between significant simulated herbivory effects and increases in below-ground
biomass, our data seem to agree with their observations (Fig. 8). In our experiment,
although we intended to simulate 50% herbivory, actual levels turned out to be slightly
below 20% (Table 3), a fact that likely minimized the measured effects. In addition,
despite the fact that others have used clipping to simulate herbivory on seagrass species
(e.g. Cebrián et al., 1998), simulated herbivory is often a poor surrogate for real herbivory
on land plants (Strauss and Agrawal, 1999), as simulated and real herbivory can evoke
different responses in plants in terms of induction of phytochemicals and effects on fitness.
Because there are no existing comparisons of the simulated and actual effects of herbivory
on seagrasses, we urge that our conclusions on the effects of herbivory be accepted
provisionally.
The negative effects of experimental light reduction on seagrass bed structure and
functioning are summarized in Table 4. The light reduction in our experiment represents an
intermediate value with respect to those imposed by others. Most prior shading studies
show simultaneous reductions in shoot density and above-ground biomass; however,
Bulthuis (1983) found that under light reduction of 35– 25%, shoot density Heterozostera
tasmanica in Western Port, Australia was not reduced significantly, although biomass was.
Similar results were reported for Posidonia, near Adelaide, Australia by Neverauskas
(1988) and our results are in general agreement with these two studies. Bulthuis (1983)
214
Table 4
Results of experimental light reduction studies
Species
Study site
Light reduction Shoot
Above-ground Epiphyte Growth
(%)
density biomass
biomass rate
Backman and
Barilotti (1976)
Bulthuis (1983)
Zostera marina
Agua Hedionda,
CA, USA
Western Port,
Australia
Adelaide, Australia
63
(
35 – 25
9–2
50
(=)
( )
(=)
Princess Royal
Harbour, Australia
P. australis
New South Wales,
Australia
Thalassia testudinum Corpus Christi
Bay, TX, USA
Halodule wrightii
80 – 99
(
)
1 – 10
(
)
14 – 10
(
)
16 – 13
(
)
Short et al. (1995)
Zostera marina
(
)
Lee and
Dunton (1997)
Ruiz and
Romero (2001)
This study
T. testudinum
94, 61, 41,
21, 11
14 – 5
(
)
(
)
17 – 10
(
)
(
)
(
5 – 27
(=)
(
)
(
Heterozostera
tasmanica
Neverauskas (1988) Posidonia sinuosa,
and P. angustifolia
Gordon et al. (1994) P. sinuosa
Fitzpatrick and
Kirkman (1995)
Czerny and
Dunton (1995)
P. oceanica
T. testudinum
Mesocosm
experiment
Corpus Christi
Bay, TX, USA
Fraile Island,
Spain
Perdido Bay, FLA,
USA
Reductions in the measured variables are indicated by (
)
(
No. of leaves Leaf
Leaf
per shoot
length width
)
(=)
( )
(
(
)
)
(
(
)
)
(
)
(
)
(
)
(+)
(+)
( )
(
)
(
( )
autumn
(=) autumn
or winter
( )
), increases by (+), and no significant changes by (=).
)
(=)
(=)
(=)
(=)
(+)
(
)
)
(
)
(
)
)
(
)
(
)
(=)
(
)
(
)
S.E. Ibarra-Obando et al. / J. Exp. Mar. Biol. Ecol. 301 (2004) 193–224
Author
S.E. Ibarra-Obando et al. / J. Exp. Mar. Biol. Ecol. 301 (2004) 193–224
215
found that the effect of experimental light reduction was related to the reduction level, and
the time of year, as there are seasonal differences in the light requirements of seagrasses.
For our experiment, it seems that either a longer period of shading or increased light
reduction would have resulted in shoot density reduction. Although Hemminga (1998)
described the possibility of a higher epiphyte biomass as a result of a reduced leaf turnover
rate under reduced light, studies summarized in Table 4 show a consistent decrease in
epiphyte biomass with shading. This could result from leaf defoliation (Lee and Dunton,
1997), decreased algal growth rates or increased consumption of nutrient enriched
epiphytes by grazers. At present we cannot discriminate among these alternative
explanations.
In general, leaf length, seems to respond more than leaf width, although our data as well
as those of Lee and Dunton (1997), showed a reduction in turtlegrass leaf width in the
shaded plots (Table 4).
Another consequence of light reduction in our study was the significant decrease in leaf
C/N ratio (Fig. 12). C/N ratios are dependent on growth conditions, with plants from lownutrient environments having significantly higher C/N ratios (Atkinson and Smith, 1983;
Fourqurean et al., 1992); however, tissue nutrient-content may not always represent
ambient nutrient conditions for plant growth, as there are seasonal differences in N-uptake
rates and dilution processes (Lee and Dunton, 1999). Increased N assimilation caused by
N enrichment may require increases in photosynthetic C-fixation and/or C metabolism
(Lee and Dunton, 1999). Low light environments increase the importance of nitrogen
uptake/assimilation by leaves, as activity of the root/rhizome system is photosynthesisdependent (Pregnall et al., 1984; Zimmerman et al., 1987). Our data seem to indicate that
nutrients taken up by the leaves in the enriched plots were not used, as photosynthesis was
reduced by shading.
Nutrient enrichment can promote seagrass decline through a change in the internal
balances of nutrient supply that impairs carbohydrate metabolism. In this case, a potential
synergism between warm temperatures, water-column nutrient enrichment, and reduced
light availability could explain seasonal reductions in seagrass performance (Burkholder et
al., 1994; Burke et al., 1996). This mechanism could explain why nutrient additions in
Perdido Bay had a detrimental effect on the seagrass-epibiont complex (Figs. 4 and 9). Our
results point towards the importance of the interactive effects of nutrients and light, more
than their independent effects, and indicate that light was most often the limiting variable.
Further evidence that nutrients were not limiting in Perdido Bay comes from the
significant increase in below-ground biomass at the peak of the growing season, indicating
that nutrients not being used in leaf growth were accumulated in the rhizomes (Fig. 8).
During an enrichment experiment in Perdido Bay, Wear et al. (1999) reported an increase
in primary production of the turtlegrass –epiphyte complex, with no effect on leaf biomass.
This lack of response of the above-ground biomass to enrichment coincides with our
observations, and seems to indicate that nutrient additions had a detrimental effect on
turtlegrass shoots, as our control plots had higher above-ground biomass (Fig. 7). The
interaction of nutrient additions and light limitation may have prevented us from observing
the increase in NAPP and epibiont biomass reported by Wear et al. (1999). It is also
possible that the nutrient enriched seagrass leaves were consumed by herbivorous adult
pinfish (Lagodon rhomboides) at increased rates, similar to what was reported by
216
S.E. Ibarra-Obando et al. / J. Exp. Mar. Biol. Ecol. 301 (2004) 193–224
McGlathery (1995), who found parrotfish feeding at enhanced rates on nutrient rich
turtlegrass in Bermuda.
5. Conclusion
Our results indicate that in the shallow waters of Perdido Bay light is the most
important limiting variable. The negative effects of light reduction were enhanced when
nutrients were added, possibly as a result of impaired carbohydrate metabolism as
mentioned by Burkholder et al. (1994) and Burke et al. (1996) or possibly because rate
of herbivory on nutrient enriched leaves increased. As new shoots with a larger number of
leaves were being formed, above-ground biomass remained stable. Shoot response to
bottom-up control was the dominant characteristic of our study, with simulated herbivory
having a less important role. This finding agrees with results reported for freshwater and
terrestrial environments. However, it is important to note that our work is a first step in
evalulating the complexity of interactions among light, nutrients and herbivory, and that
additional experiments are required to evaluate the generality of our results.
Acknowledgements
We thank C. Davis, R. Rogers, S. Harter, L. Gallagher, M. Goecker, L. Kramer, A.
Willman, and A. Spivak, for their help during field work, J. Cowan, L. Linn, J. Daniel for
their help with chemical analyses, G. Chaplin and A. Gunter for technical support, F.J.
Ponce and J.M. Domı́nguez for the figures, and John Valentine and an anonymous reviewer
whose comments helped improve the ms. This study was carried out during the tenure of a
Fullbright Sabbatical Scholarship granted to the first author, and additional support was
provided by the Dauphin Island Sea Laboratory. This is DISL contribution no. 349. [RW]
Appendix A . Epibiont biomass ANOVA values for main factors and their interactions
Factors and interactions
Test statistics
June
July
August
September
October
Nutrients
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
1
7.316
0.012*
1
0.266
0.611
1
0.868
0.361
1
0.019
0.892
1
0.181
0.674
1
10.643
0.003*
1
1.131
0.298
1
0.157
0.695
1
0.149
0.703
1
0.92
0.347
1
8.463
0.008*
1
5.542
0.027*
1
0.889
0.355
1
2.859
0.104
1
0.378
0.544
1
22.822
< 0.01*
1
7.713
0.01*
1
0.004
0.949
1
2.817
0.106
1
2.105
0.16
1
15.18
< 0.01*
1
18.11
< 0.01*
1
0.954
0.338
1
4.483
0.045*
1
0.763
0.391
Light
Herbivory
Light Nutrients
Light Herbivory
S.E. Ibarra-Obando et al. / J. Exp. Mar. Biol. Ecol. 301 (2004) 193–224
217
Appendix A (continued)
Factors and interactions
Test statistics
June
Nutrients Herbivory
df
F value
p value
df
F value
p value
1
0.871
0.36
1
0.515
0.48
Light Nutrients Herbivory
July
1
2.979
0.097
1
0.341
0.565
August
1
0.372
0.548
1
0.081
0.778
September
1
0.209
0.651
1
3.172
0.088
October
1
0
0.998
1
0.002
0.965
Significant values are indicated with an asterisk.
Appendix B . Leaf length ANOVA values for main factors and their interactions
Factors and interactions
Test statistics
June
July
August
September
October
Nutrients
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
1
5.541
0.027*
1
1.39
0.25
1
1.896
0.181
1
0.00212
0.964
1
0.549
0.466
1
0.0491
0.826
1
0.000744
0.978
1
13.362
0.001*
1
0.701
0.411
1
0.121
0.731
1
0.281
0.601
1
0.000235
0.988
1
2.254
0.146
1
0.967
0.335
1
4.081
0.055
1
5.062
0.034*
1
0.273
0.606
1
0.111
0.742
1
1.783
0.194
1
0.278
0.603
1
0.0509
0.823
1
7.287
0.013*
1
4.937
0.036*
1
0.0000642
0.994
1
1.802
0.192
1
1.538
0.227
1
0.000657
0.98
1
0.36
0.554
1
1.152
0.294
1
0.477
0.496
1
8.254
0.008*
1
0.23
0.636
1
0.436
0.515
1
0.991
0.329
1
0.26
0.615
Light
Herbivory
Light Nutrients
Light Herbivory
Nutrients Herbivory
Light Nutrients Herbivory
Significant values are indicated with an asterisk.
Appendix C . Leaf width ANOVA values for main factors and their interactions
Factors and interactions
Test statistics
June
July
August
September
October
Nutrients
df
F value
p value
df
F Value
p value
1
0.465
0.502
1
1.95
0.175
1
1.395
0.249
1
5.176
0.032*
1
1.83
0.189
1
0.364
0.552
1
4.024
0.056
1
12.649
0.002*
1
0.628
0.018*
1
1.1358
0.255
Light
(continued on next page)
218
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Appendix C (continued)
Factors and interactions
Test statistics
June
July
August
September
October
Herbivory
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
1
0.344
0.563
1
0.225
0.64
1
0.173
0.681
1
0.945
0.341
1
0.173
0.681
1
0.0453
0.833
1
0.0003
0.986
1
0.291
0.595
1
0.479
0.495
1
0.291
0.595
1
0.172
0.682
1
0.869
0.361
1
0.919
0.347
1
0.0161
0.807
1
0.433
0.517
1
0.093
0.763
1
1.427
0.244
1
0.916
0.348
1
0.148
0.704
1
0.522
0.477
1
4.602
0.042*
1
0.198
0.66
1
0.591
0.45
1
0.289
0.596
1
0.0157
0.901
Light Nutrients
Light Herbivory
Nutrients Herbivory
Light Nutrients Herbivory
Significant values are indicated with an asterisk.
Appendix D . Above-ground biomass ANOVA values for main factors and their
interactions
Factors and interactions
Test statistics
June
July
August
September
October
Nutrients
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
1
5.773
0.024*
1
0.207
0.654
1
0.296
0.591
1
0.114
0.738
1
0.147
0.705
1
0.133
0.298
1
1.014
0.324
1
0.196
0.662
1
2.863
0.104
1
0.00228
0.962
1
0.631
0.435
1
0.543
0.468
1
1.217
0.281
1
0.0139
0.907
1
1.986
0.172
1
7.524
0.011*
1
0.0705
0.793
1
2.654
0.116
1
0.0888
0.768
1
0.494
0.489
1
0.0472
0.83
1
31.197
< 0.001*
1
88.955
< 0.001*
1
0.0806
0.779
1
2.018
0.168
1
0.0648
0.801
1
3.324
0.081
1
2.015
0.169
1
8.742
0.007*
1
21.006
< 0.001*
1
0.289
0.596
1
2.936
0.1
1
0.0329
0.858
1
0.523
0.477
1
0.74
0.398
Light
Herbivory
Light Nutrients
Light Herbivory
Nutrients Herbivory
Light Nutrients Herbivory
Significant values are indicated with an asterisk.
S.E. Ibarra-Obando et al. / J. Exp. Mar. Biol. Ecol. 301 (2004) 193–224
219
Appendix E . Below-ground biomass ANOVA values for main factors and their
interactions
Factors and interactions
Test statistics
June
July
August
September
October
Nutrients
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
1
1.794
0.195
1
2.801
0.108
1
8.5665
0.008*
1
0.083
0.776
1
1.586
0.221
1
1.198
0.285
1
0.054
0.819
1
17.1
< 0.001*
1
0.0082
0.929
1
0.118
0.734
1
0.849
0.366
1
1.169
0.29
1
0.238
0.63
1
0.17
0.683
1
8.84
0.007*
1
1.658
0.21
1
0.756
0.393
1
2.892
0.102
1
0.199
0.659
1
0.519
0.478
1
0.212
0.649
1
3.206
0.086
1
4.416
0.046*
1
0.188
0.669
1
20.48
0.165
1
0.00623
0.938
1
0.136
0.716
1
1.665
0.209
1
0.0181
0.894
1
3.085
0.092
1
0.118
0.734
1
0.523
0.477
1
0.0988
0.756
1
0.0307
0.862
1
0.0871
0.77
Light
Herbivory
Light Nutrients
Light Herbivory
Nutrients Herbivory
Light Nutrients Herbivory
Significant values are indicated with an asterisk.
Appendix F. NAPP ANOVA values for main factors and their interactions
Factors and interactions
Test statistics
June
July
August
September
October
Nutrients
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
1
0.0581
0.812
1
0.78
0.386
1
0.11
0.744
1
0.000263
0.987
1
0.0584
0.811
1
0.124
0.727
1
0.844
0.368
1
2.41
0.134
1
0.002
0.962
1
0.276
0.605
1
4.671
0.041*
1
0.847
0.367
1
5.042
0.034*
1
1.443
0.241
1
0.346
0.562
1
0.91
0.35
1
7.781
0.01*
1
1.82
0.19
1
5.197
0.032*
1
11.35
0.003*
1
3.778
0.064
1
0.000354
0.985
1
1.038
0.318
1
0.0288
0.867
1
1.358
0.048
1
9.065
0.006*
1
3.154
0.088
Light
Herbivory
Light Nutrients
Light Herbivory
Nutrients Herbivory
0.708
0.408
1
0.657
0.426
1
0.393
0.536
(continued on next page)
220
S.E. Ibarra-Obando et al. / J. Exp. Mar. Biol. Ecol. 301 (2004) 193–224
Appendix F (continued)
Factors and interactions
Test statistics
June
July
August
September
October
Light Nutrients Herbivory
df
F value
p value
1
0.708
0.408
1
0.381
0.543
1
1.588
0.22
1
0.163
0.69
1
0.0123
0.912
Significant values are indicated with an asterisk.
Appendix G . Shoot density ANOVA values for main factors and their interactions
Factors and interactions
Test statistics
June
July
August
September
October
Nutrients
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
1
0.023
0.88
1
0.763
0.394
1
7.109
0.0016*
1
1.579
0.225
1
0.414
0.528
1
0.288
0.598
1
0.068
0.797
1
33.446
< 0.001*
1
1.602
0.218
1
0.2
0.659
1
0.272
0.607
1
0.0394
0.844
1
0.2
0.659
1
0.483
0.494
1
0.538
0.471
1
0.013
0.911
1
25.058
< 0.001*
1
0
0.991
1
0.795
0.382
1
0.506
0.484
1
0.006
0.941
1
8.489
0.008*
1
17.092
< 0.001*
1
0.0441
0.835
1
3.139
0.089
1
0.188
0.669
1
0.199
0.659
1
1.49
0.234
1
5.824
0.024*
1
0.721
0.404
1
0.0445
0.835
1
0.721
0.404
1
0.0032
0.955
1
0.0254
0.875
1
0.375
0.546
Light
Herbivory
Light Nutrients
Light Herbivory
Nutrients Herbivory
Light Nutrients Herbivory
Significant values are indicated with an asterisk.
Appendix H . Average number of leaves per shoot ANOVA values for main factors
and their interactions
Factors and interactions
Test statistics
June
July
August
September
October
Nutrients
df
F value
p value
df
F value
p value
df
F value
p value
1
3.967
0.062
1
1.416
0.249
1
2.511
0.13
1
84.476
< 0.001*
1
2.526
0.125
1
0.0254
0.875
1
2.857
0.104
1
0.245
0.625
1
12.619
0.002*
1
27.539
< 0.001*
1
6.4
0.018*
1
0.00466
0.946
1
40.417
< 0.001*
1
17.105
< 0.001*
1
1.988
0.171
Light
Herbivory
S.E. Ibarra-Obando et al. / J. Exp. Mar. Biol. Ecol. 301 (2004) 193–224
221
Appendix H (continued)
Factors and interactions
Test statistics
June
July
August
September
October
Light Nutrients
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
1
0.14
0.713
1
0.194
0.665
1
0.016
0.902
1
1.388
0.254
1
0.103
0.751
1
0.024
0.878
1
0.33
0.571
1
2.025
0.168
1
1.64
0.213
1
0.512
0.481
1
0.014
0.905
1
0
0.995
1
4.276
0.05*
1
0.578
0.454
1
1.11
0.303
1
2.009
0.169
1
0.515
0.48
1
0.376
0.546
1
0.00335
0.954
1
0.00036
0.985
Light Herbivory
Nutrients Herbivory
Light Nutrients Herbivory
Significant values are indicated with an asterisk.
Appendix I. C/N ratio ANOVA values for main factors and their interactions
Factors and interactions
Test statistics
August
October
Nutrients
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
df
F value
p value
1
9.87
0.004*
1
2.287
0.144
1
0.0664
0.799
1
8.264
0.008*
1
0.521
0.478
1
1.286
0.268
1
2.694
0.114
1
3.719
0.066
1
7.934
0.01*
1
0.391
0.538
1
1.129
0.299
1
0.0184
0.0893
1
0.0133
0.909
1
0.158
0.695
Light
Herbivory
Light Nutrients
Light Herbivory
Nutrients Herbivory
Light Nutrients Herbivory
Significant values are indicated with an asterisk.
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