DYNAMICS OF CARBON ALLOCATION
IN A DEEP WATER POPULATION OF THE DECIDUOUS KELP,
Pleurophycus gardneri (LAMINARIALES)
A thesis Presented to the F acuity of California State
University at Monterey Bay through Moss Landing Marine
Laboratories
In Partial Fulfillment
of the Requirements for the Degree
Master of Science in Marine Science
by
Clare Margaret Dominik
March 25, 2004 ABSTRACT
Pleurophycus gardneri (Laminariales) is common in the low intertidal in the Pacific
Northwest, but dominates many deep (30 to 40 m) reefs in central California. Seasonal dynamics of productivity and resource allocation of a deep-water population of this deciduous, stipitate kelp were studied to understand how blade abscission affects the annual carbon budget.
Patterns of growth, metabolism, carbon storage and mobilization were measured monthly for one year relative to in situ light and temperature, and used to model the annual carbon budget. The carbon budget model was used to determine if blade abscission effectively reduced respiratory demand during winter when light availability was lowest. Blade growth occurred between
February and July, followed by senescence and sloughing from August to December.
Concentrations of laminaran and mannitol increased in the blades from the onset of sloughing until just prior to blade abscission (mid-December) suggesting translocation may have occurred from the blade to the stipe and holdfast. The initial model overestimated net production most probably because it failed to account for movement of the blade relative to the incident light.
Sensitivity analysis resulted in the best fit when blades were assumed to utilize only 25 to 50% of ambient irradiance at 30m. The model indicated that blades could be retained over the winter assuming they received 25 to 50% of in situ irradiance. Thus, abscission was not necessary for metabolic survival and abscission may be related to other factors such as reduction in winter storm/surge induced damage/loss or enhanced spore dispersal through drift of abscised blades with sori.
Keywords: Carbon budget, photosynthesis and abscission.
2 INTRODUCTION
Autumnal leaf abscission has commonly been associated with conservation of energy in deciduous trees by synchronously senescing and dropping leaves. Large respiratory requirements of the leaves cannot be met during shortened winter photoperiods (Addicott 1982).
Translocation of cellular material occurs from the leaves to the phloem during senescence
(Pennell and Lamb 1997) prior to abscission for storage and possible utilization over the winter
(Addicott 1982). Among most deciduous trees, cold temperatures and/or light (day-length) are the most influential cues for abscission. Light is also a common limiting factor for many plants in marine kelp dominated systems (Schiel and Foster 1986, Dean 1985). Canopy cover of
Macrocystis pyrifera can limit light availability and growth of understory algae (Reed and Foster
1984, Wantanabe et al. 1992, Edwards 1998). Disturbance by large storms can increase light availability to under-story plants in shallow water by removing over-story layers (Graham 1997).
These seasonal or episodic events can allow algae that would otherwise be excluded due to insufficient light, to establish and grow.
In northern latitudes, kelps have a variety of physiological mechanisms that allow them to
survive seasonally through alternating periods of nutrient limitation during the summer and light
limitation in winter (Gagne et al. 1982). Laminaria solidungula utilized stored carbohydrates
accumulated during summer to complete 90% of its annual linear blade growth during the virtual
darkness of the Arctic winter (Dunton and Schell 1986, Chapman and Craigie 1977, 1978, Mann
1973 ). Summer accumulation of carbohydrates for use during winter requires periods of high
summer irradiance combined with nutrient limitation that prevents growth.
3 Cellular photoacclimation increases photosynthetic efficiency and thus can contribute to survival when light availability is low. Algae from deep water may contain more accessory pigments, which harvest light more efficiently at low light intensities (Ramus 1983). Another characteristic includes thinner thalli compared to algae in shallow water, resulting in lower respiration rates that promotes survival in low light (Markager and Sand-Jensen 1992).
Another potential way algae can survive the low light conditions of winter is to reduce total biomass and thus, respiratory demand. Abscission of reproductive tissues is common among brown algae, including Nereocystis sp., Fucus spp.. and Ascophyllum sp., and also possibly among A/aria sp., Lessoniopsis sp.. Pterogophora sp. (Addicott 1982). It is unclear whether Laminaria sinclarii truly abscises or whether the blade is removed by physical abrasion
(Markham 1972). Pleurophycus gardneri (Laminariales) is a deciduous perennial (Germann
1986) or pseudoperennial (Sears and Wilce 1975) and is the only kelp known now to undergo synchronous defoliation of the vegetative (photosynthetic) blade each winter. Germann (1989) suggested abscission of the senescent blade may be more advantageous than its retention because the high photosynthetic efficiency and low respiration of the stipe and the holdfast may compensate for loss of greater photosynthetic surface area of the blade, which has large respiratory requirements. The perennial stipe and holdfast may also function as a reservoir for carbohydrates translocated from the blade before abscission.
The distribution of Pleurophycus gardneri was originally reported to be from Montague
Island, Alaska to Fort Bragg, California, in the low intertidal to upper subtidal (Abbott and
Hollenberg 1976). Individuals are common in the northern part of the range but comparatively
rare in the south. VanBlaricom et al. (1986) found low densities of P. gardneri (<1 individual -2) m at depths above 15m, and much higher densities (up to 10 plants m-2) in deep water off the
4 coast of Big Sur, California. Stands of plants with densities of 5 plants m-2 have recently been observed at depths between 27 and 34m in Carmel Bay, California (Spalding eta!. 2003). These observations prompted this investigation into the ability of a kelp previously thought restricted to intertidal regions, to flourish at 30m depth almost 500 km south of its originally reported southern limit.
Many species ofLaminariales have been rigorously studied to examine the relationships between light availability (Luning 1979, Dunton 1985, Dunton and Jodwalis 1988, Dunton and
Schell 1986), translocation and production of carbohydrates (Luning et a!. 1973, Chapman and
Craigie 1978), nitrate concentrations and growth (Chapman et al. 1978, Germann et al. 1987).
The objective of this study was to explore the dynamics of carbon assimilation and its utilization for growth by Pleurophycus gardneri in this deep water habitat. Physiological rate measurements, in situ growth studies and chemical analysis were used to construct a numerical carbon budget model. This model was used to explore 1) whether abscission is an effective mechanism for reducing whole plant respiratory demand and, 2) the length of time that perennial tissues can survive on storage carbohydrates alone during the winter.
METHODS
To create this model all inputs and outputs of the plants were quantified to establish net
production with respect to carbon. Light was the major driver of the model, and Zimmerman et
al. 0994) have shown that production estimates based on instantaneous irradiance measurements
are more accurate than hours of daily irradiance saturated photosynthesis (HsAT) to model daily
carbon gain by a plant. Instantaneous light measurements and photosynthetic production estimates yielded a d · · . . . . gross pro uctmn estimate from winch losses (respiratiOn and sloughmg) were
5 subtracted. Chemical composition (carbohydrate and pigment concentrations) was determined to evaluate source/sink relationships among the four different tissue types of the plant. Plant size,
1 defined as total carbon (gC planf ) summed from each tissue type, and plant growth and/or sloughing were quantified and used to evaluate the models ability to predict changes in plant size as a function oflight availability. Carbon budget models of hypothetical plants retaining blades suggests what would happen to plant size if abscission did not occur.
Study Site
The study area was located in 30m of water at the East Pinnacles (36°33'35" N,
121°57'53" W), approximately 1.5 km offshore from Stillwater Cove, Carmel Bay, California.
High relief granite pinnacles interspersed with large boulders and small sand channels characterized the area. Pinnacle tops above 20 m depth support a canopy ofMacrocystis pyrifera, which is thinned annually by winter storms. The stipitate kelps Pterygophora califomica, Eisenia arborea, and Pleurophycus gardneri were interspersed with giant kelp at 20 m but higher densities of P. gardneri were found in deeper water outside the giant kelp canopy.
Fleshy red and geniculate coralline algae comprised a variably abundant algal turf underneath the stipitate kelps. Stipitate kelps outside the kelp canopy periodically lay flat and overlap one another when there is no surge or current (typically during summer months) providing shading and structure much like a sub-surface "canopy." Nongeniculate coralline algae, along with red and occasionally green encrusting algae, generally occupied the primary substrate interspersed with encrusting invertebrates (see also Spalding et al. 2003).
Light Availability
Photosynthetically active radiation (PAR, 400 to 700 nm) was measured using a newly calibratedLiCorLI193SA l . . sea ar lffadiance sensor (LI COR Inc., USA) and data logger moored
G at 30m depth at East Pinnacles throughout the study. The sensor was mounted on top of a cement block (40 em off the bottom), and placed on a flat rock (about 8 m x 2m) outside the kelp canopy. All macroalgae on this rock was removed in October 1999, and the site was maintained free of macroalgae within 1 m of the sensor throughout the study to avoid shading the light sensor. Subsequent recruitment and growth of Pleurophycus gardneri on the remainder of the cleared rock produced plants of known age that were used to determine the relationship between plant age and periodicity of ring formation in the stipe. The irradiance sensor was cleaned of epiphytes and the data logger retrieved every month. The sensor was removed for thorough cleaning and calibrated against another calibrated laboratory spherical quantum sensor
(QSL 100, Biospherical Instruments Inc., USA) every 2 to 3 months. In situ irradiance was averaged over one minute and recorded at 15-minute intervals during daylight hours.
Temperature was also recorded every 15 minutes using a factory-calibrated temperature logger
(Stowaway logger; Onset Computer Corp., USA) that was checked against a lab chiller each month(± 0.5° C). Brief interruptions ofirradiance (June 2000) and temperature (July 2000) measurements occurred due to equipment malfunction.
Growth Phenology
Nine to ten adult (stipe length >40 em) sporophytes were randomly selected and tagged within a 20 m radius of the light meter each month from June 2000 to May 2001, for growth measurements and subsequent samples. Only intact individuals mostly free of grazing marks and
epiphytes were tagged to reduce the variability in biomass measurements resulting from
processes other than photosynthetic carbon assimilation and utilization. Grazing was rare during the gr · owmg season but common after sloughing began in late July (qualitative visual estimates
that about 60% of plants observed had partially grazed blades). Plants with minor
7 peripheral grazing were used (grazing was not quantified) during the late summer and fall because of a lack of available non-grazed plants. Tagged plants were collected after approximately 4 weeks, placed in black plastic bags, brought to the surface, and stored in coolers during transport to the lab to prevent light or temperature shock. Plants were kept in running seawater aquaria at in situ temperatures for no more than 24 hours before physiological measurements began. Continuous shading (about 50 to 75% reduction of ambient, similar to in situ values) was provided to prevent photo-damage. All measurements were completed within five days of collection.
Blade growth ( cm2 collection interval· I) was measured in situ using the hole punch method on tagged plants when the abscission scar was absent (Fig. 1a.) (June 2000 to November
2000) to quantify new growth and the loss from sloughing. Growth and sloughing rates were estimated by punching a hole, small enough to minimize wounding (Parke 1948) but large enough to leave a visible scar, through the midrib of each tagged plant 10 em above the base of the blade using a 0.5 em diameter cork borer (Fig. 2). Absolute growth rate was calculated according to:
2 1 Growth (cm collection intervar ) =(Db- Dt1) * (Wb) Eqn. 1. where Dt1 was the distance from the hole punch to the base of the blade, and Wt1 was blade width measured at the beginning of the month when plants were selected (Dt2, and Wt2 are similar measurements at the end of the collection period) (Fig. 2). Sloughing was calculated similarly according to:
2 1 Sloughing (cm collection intervar ) = (Lt1- Lt2) * (Wt2) Eqn. 2.
was the length of the blade from the distal end to the initial hole punch mark at time t1.
was the length of the blade from the distal end to the hole punch at time t2. Blade area
8 (cm 2 collection intervar1 of growth or sloughing) was calculated as if the blade was a rectangle.
These estimates were similar to those based on conversion oftotal plant biomass (wing: gFW =
2 2 2 2 0.04 (cm )(R = 0.96, n = 10), midrib: gFW = 0.12 (cm ) (R = 0.97, n = 10) using wet and dry weights of measured areas of both tissues. Frills of the wing tissue add area to the blade, which most likely compensates for any loss in area when calculated as a rectangle, although the actual shape resembles a truncated ellipse.
During spring (February to May 2001) when the abscission scar was present the increase in the mean population blade size was due to new growth only. Using the equation of a rectangle
2 1 to calculate the area of all new blade tissue, average blade growth ( cm collection intervar ) each month was subtracted from the total blade area from the previous month (e.g. growth rate for
March= Average blade area March- Average blade area for February). Conversion factors were used to normalize fresh to dry weight (using DW as %FW) and normalized to whole plant size using DW per plant (Table 1). Dry weight was converted to grams of carbon planf1 for use in the carbon budget model.
Wing (W), midrib (M), stipe, (S), and holdfast, (H) (Fig. 2) of each collected plant was weighed (fresh weight = FW) monthly. Sub-samples of each tissue type were used to obtain fresh weight and dry weight (after three days in a drying oven at 60° C). Sorus persistence and condition were noted qualitatively. Growth rings in the stipe at the stipe holdfast junction (about
()·25 em above the last hapteron, Figure 2) were counted monthly beginning in July of2000 in
.plants collected for growth measurements. Light and dark elliptical bands were counted in thin
under ad"Issectmg · microscope· and largest diameter (ellipse) was measured. An
observer also counted light and dark bands from random individuals to verify ring ~ttful& technique.
9 Photosynthesis and Respiration
Monthly measurements of photosynthesis and dark respiration were made using tissue
samples excised from the collected plants (n = 9 or 10). Photosynthetic rate was determined
polarographically using 2 cm2 sections of wing and midrib tissue cut between 10 em and 40 em
above the base of the blade. Samples of stipe tissue were cut below the second growth
constriction (Fig. 2) and holdfast samples were taken from the youngest haptera (outer-most and
least fouled). Photosynthesis and dark respiration were measured following Zimmerman et a!.
(1989) using an oxygen electrode in a water-jacketed incubation chamber (5 ml vol; Rank Bros.,
U.K.). The incubation chamber was maintained at the average in situ temperature recorded
during the month prior to collection which ranged from 9° C in February 2001 (± 0.5° C) to 12.5°
C in October(± 0.5° C). Respiration was measured in complete darkness; photosynthesis was
measured at ten irradiances (one plant per irradiance level) using an incandescent light source
(Fiber-Lite High Intensity Illuminator Series 180, Dolan-Jenner Instruments Inc., USA, 150-watt
bulb) to construct monthly photosynthesis vs. irradiance (P vs. E) curves. These tissue samples
were oriented normal to the irradiance path.
Chemical Composition
Mannitol and laminaran were extracted from samples of ground, dry tissue (IN, M, S and
H) using hot ethanol (Chapman and Craigie 1977). Mannitol was analyzed by the periodate
acid method (Lambert and Neish 1950) standardized using D-mannitol.
·····~!llJinru:an concentrations were determined using the anthrone reagent method (Yemn and Willis ... , .....,. ;;·j,1';J~.~~).standardized with D-glucose. Mannitol and laminaran concentrations were converted to
based on their molecular formulas (I mol mannitol or laminaran = 6 mol carbon= 72
10 Chlorophyll (a and c) and fucoxanthin were extracted from fresh tissue samples using a
two-step DMSO, methanol-acetone extraction procedure. Pigments were measured
spectrophotometrically, and pigment concentrations calculated following Seely et al. (1972).
Tissue carbon content was determined from dry ground samples of each tissue type. Carbon
analysis was preformed by Analytical Laboratory Services, Marine Science Institute, UC Santa
Barbara using the Dumas combustion method (automated organic elemental analyzer CEC
440HA, Exeter Analytical, USA, standardized against acetanilide± 0.3% precision).
Statistical Analysis
Monthly gross P vs. E curves were constructed for each tissue type using the exponential
function of Webb et aJ. (1974). Parameter values and variance estimates for the maximum rate
of light-saturated photosynthesis (Pl\M:x) and the light-limited initial slope (a) were estimated
using an iterative, least-squares non-linear curve fitting routine based on the Marquardt
Levenberg algorithm in Sigma Plot (Jande! Scientific). Dark respiration (R) was measured and
subtracted from gross production in the carbon budget model at each IS-minute interval
continuously throughout the year. Metabolic measurements were converted from oxygen based
1 to carbon based units using a photosynthetic and respiratory quotient of 1.2 and 1.0 mol 0 2 mor
C02 respectively. Because monthly P vs. E curves were constructed from 10 independent
· samples measured at I 0 different irradiances each month, the analysis produced an aggregate
ofPMAX and a for each month for the four tissue types. Only one P vs. E curve per j;;;~~~th was obtained due to resource limitations. The single monthly estimate ofP"~' and a and
variance estimates calculated according to Zimmerman et aJ. (1987) were tested
temporal variation using multiplet-tests and using the Bonferroni correction.
11 Respiration, growth, sloughing and chemical composition measurements were analyzed for temporal differences using a one-way ANOV A (p::; 0.05) and LSD (least significant difference) planned multiple comparison tests (Sokal and Rohlf 1969). For most months n = 10, except for September and November n = 9 and February n = 4 to 6 depending on the amount of
1 1 tissue present for analysis. Growth and sloughing data (g C planf collection intervar ) were transformed (-.J(x + 0.01)) due to unequal variances. Mannitol and laminaran content data (mg C
planf1) were transformed using log transformation. Pigment content of the wing (mg Pigment g
1 FW- ) and midrib chlorophyll content data met all assumptions; however, stipe fucoxanthin data
were log transformed, and stipe chlorophyll and holdfast pigment data were square-root
1 transformed. Plant size data (g C planf ) met all assumptions for the ANOVA without
transformation. Post-hoc differences are indicated on all graphs by different heights of the line
running horizontally through the data on each relevant figure (post-hoc results presented in
Appendix 1). Monthly means that were significantly different from some but not all other
months have a vertically sloping line running across them.
Carbon Budget
The carbon budget model based on rates of light dependent photosynthesis, dark
l"e!>piraticm and sloughing was used to calculate monthly changes in plant size. Photosynthetic
2.!1fc>ducticm was calculated from in situ irradiance recorded at 15-minute intervals according to
et al. ( 197 4) equation below:
Eqn. 3.
phases of growth (all plant parts present), the carbon budget was calculated
(W M s H) p Sl h' • · , = lifo" cw. M, s, H)- oug mg (Bindel- R cw. M, s, H) Eqn. 4. where R is dark respiration. The model was seeded with initial plant size in May 2000, calculated by subtracting growth and adding sloughing from plant size measured in June 2000.
This calculation was performed for all months and the predictive ability of the back calculation
was assessed by regression against measured plant size. Net photosynthetic production (PNET)
was added to the seed value (minus losses from sloughing and respiration) to predict changes in
plant size at each !5 minute interval:
New Plant Size= Old Plant Size+ (PNET *Time) Eqn. 5.
where PNET was negative, due to greater losses (R and sloughing) than gross production, plant
size decreased. Plant size increased when PNET was positive (i.e. when production exceeds
losses). All parameters were converted to grams of carbon planf1 15 minutes·1 using conversion
factors (Table I). The carbon budget calculations were validated by linear regression against
measured plant size.
To test the potential impact of blade respiratory demand on whole plant carbon balance
during winter, average daily PNET was modeled with blades throughout the year with no
sloughing and analyzed for significant differences within a given month, abscission vs. no
"'-'''"1ssro:n. using a one-sample t-test. Average daily values ofPNET without abscission had no
llat1Iral variance during the winter months (due to zero variance in the model) and therefore
assumption of equal variance for an ANOVA The assumption of the t-test was that
~·variation about the model calculation was equal to the variation in the natural population.
det errmne· d whether the model mean could be randomly sampled from the natural
(with abscission), or whether PNET without abscission was higher or lower than the
This will determine whether abscission was beneficial to the plant based on
"~"''uu~m alone.
13 RESULTS
Irradiances at 30 m at East Pinnacles were highly variable, ranging from almost 0 to
almost 4 mol quanta m-2 d-1 in the summer, mostly due to the effects of plankton blooms and/or
persistent coastal stratus common to this region of central California (personal observation).
Average winter irradiances were consistently lower ranging from almost 0 to about 1 mol quanta
m-2 d-1 (Fig. 3, daily averaged temperature vs. light comparison in Appendix 2). Daily average
temperatures were highest from August to February, ranging from almost 9.5°C to 14°C;
temperatures were lowest from March to July, ranging from 8.5° C to 12.5° C.
GJ"Owth Phenology
Pleurophycus gardneri sporophytes grew for approximately 5 months from February to
July (Fig. 1b). Growth was highest in spring and slowed dramatically between June and July.
Blade sloughing began in August and September, as indicated by the loss of the abscission scar
from the distal end of the blade (Fig. 1a). Sloughing continued without growth until only the
; !lfllxiinall/3 of the blade remained in November. Prior to abscission, the upper portion of the
(between the meristem and where the stipe narrowed) began to darken. Abscission was c·.•~mpllete:dby mid-December and the bladeless period lasted until the beginning of February
<.•!Jl"•owth rings at the base of the stipe were annual. The stipe cross section of most new
•\recruiited February to March 2000) collected in the clearing around the light meter
three light bands but only two dark bands in June 2002, approximately 2.5 years after
A subsequent cohort recruited to the clearing. They were easily distinguished from
March 2000 cohort by their small size, and few survived most likely due to self-
14 shading from the adults. The highest number of rings counted in the adult plants collected for
growth measurements was 5 (all ring data in Appendix 3).
2 Most Pleurophycus gm·dneri produced a variably sized (20 to 75 cm ) sorus patch on the
midrib of the blade between April and June. Sari persisted until September when the patches
were sloughed along with vegetative blade tissue. A secondary sari developed proximal to the
spring patches on about half of the plants (per. obs.) prior to abscission in mid-November.
Photosynthesis and Respiration
The photosynthetic parameters P~L' and a were temporally constant throughout the
study. Respiration was also constant over time except the stipe, where respiration during winter
was significantly lower, however the difference is small (Table 2, Appendix 1b). Metabolic rates
(PMAX and R) and photosynthetic efficiency (a) were highest in wing tissue, followed by midrib
and then stipe and hold fast (Table 3, Appendix 1b). The wing tissue had a peak PMA.-xfR of 35 in
May and a low of 10 in November. Generalized P vs. E curves for wing tissue of deep plants
and intertidal plants (Germann 1986) demonstrate that deep plants exhibit higher low light
•. 1llililzation efficiencies than intertidal plants on a weight or chlorophyll specific basis (Fig. 4a, b
Chemical Composition
1 Carbohydrate concentrations (mgC planf ) decreased while plants were growing,
during sloughing and continually decreased after abscission through blade initiation
in spring (Fig. 5). Laminaran accounted for only 1 to 2% of dry weight (DW).
represented up to 8% of the total DW and averaged 5% DW. Summer and fall
were significantly higher than winter and spring concentrations for both
mannitol (Table 2, Appendix lc).
15 Concentrations offucoxanthin and chlorophyll (a and c) in wing and midrib tissues peaked in late summer and decreased significantly by late fall (Fig. 6, Table 2, Appendix ld).
Initial spring pigment concentrations were low in the wing and midrib and gradually increased through spring. Chlorophyll concentrations in the stipe began increasing in winter and were highest in spring, while concentrations in the holdfast nearly doubled in winter then returned to lower concentrations in April (Fig. 7, Table 2, Appendix ld). Fucoxanthin concentrations in the stipe and holdfast were significantly higher in some late summer and spring months than some fall and winter months (Fig. 7, Table 2, Appendix 1d)_ However, post-hoc results were ambiguous and only October holdfast fucoxanthin concentrations were clearly different from all
the others (Fig. 7, Appendix 1d). Wing tissues always had the highest pigment concentrations
followed by the midrib, stipe, and holdfast. The average ratio of Chi a: Chi c for the wing tissue
was 5, and the Chi a: Fucoxanthin ratio was 1.8 (Table 4). Relative size of the wing and midrib
in g C planf1 was significantly lower in spring (during blade initiation) than in the previous
summer (Fig. 8a, Table 2, Appendix 1e). The carbon in the stipe increased during sloughing as
day-length decreased and growth ceased, while carbon content of the hold fast remained
Cm'bon Budget
Back-calculated plant size and measured plant size had high predictive power (y = 0.917x
2 R = 0.8728, p < 0.0001, Table 5) and the relationship was used to estimate initial plant
2000 (seed value). Modeled plant size estimated by the carbon budget was
correlated with measured plant size. However, the model greatly overestimated
summer, spring and fall and underestimated plant size during winter at 100%
16 irradiance (Fig. 9a, b). Based on secondary regression analysis the slope of modeled vs.
measured plant size at 100% irradiance was not significantly different from one (Table 5).
Differences in irradiance measured by the spherical quantum sensor and collected by the
planar P. gardneri blade could account for the discrepancy between modeled and measured plant
size. The scalar irradiance sensor is engineered to collect light from all directions. Light
absorption by a flat planar blade, like that of P. gardneri, exhibit a cosine response, known as the
cosine law, to the incident light field. Downwelling irradiance experienced by the blade is
proportional to the cosine angle between the leaf normal and the incident beam (Kirk 1994,
Zimmerman 2003). Water motion alters the orientation of the blade surface relative to the
submarine light field, and some combination of this and differences in stipe length, blade density
and overlap (self-shading), likely results in less light available to the blade than measured by the
spherical sensor (360°).
Model sensitivity to reductions in light collection efficiencies was tested by reducing
irradiance to 75%, 50%, 25%, 15% and 10% of ambient. Both the 50% (Fig. 1Oa, b) and 25%
lla, b) irradiance models resulted in the highest predictive power of plant size. Neither
nor 50% of irradiance resulted in modeled vs. measured plant size intercepts significantly .. i 70!~~~~ereJrtt from zero (Table 5). Based on R2 values the 25% irradiance provided the best fit of the (Fig. 12a, b, c) accounted for 76% of the model variation while the 50% irradiance
73% of the variation. Secondary regression analysis determined that the regression of
vs. measured plant size for 25% or 50% irradiance did not have a slope different from
S). The annual PNETfor 25% irradiance was -0.16 gC plant -'and the annual PNET for 5.14 gC pla nr' · s·1m!lar . valu,es for I 0 and 15% irradiance were extremely low due to 10 to 20 days out of the year above HsAT thus, they were not reasonable estimates
17 although-the R2 value for 15% irradiance was high. Some value between 25% and 50% of irradiance yields the highest predictive power of the model thus both were evaluated for differences between PrmT modeled with and without abscission.
Both 25% and 50% of the measured irradiance were used to evaluate the effect of
1 retaining the blade year round on average daily whole plant PNET (gC planf ) through the fall and winter. The model was initialized with plant size from May 2000 but no sloughing or abscission was allowed. Respiration and growth were the only possible fates for the photosynthetically fixed carbon driven by the irradiance time series_ The modeled Pl'JET values without abscission are represented as a single point over the measured PNET data with abscission for both 25% and
50% irradiance in Fig. 13 a, b. Hypothetical retention of the blade yielded higher mean Pl'JET in
late summer and spring than the run allowing abscission at 25% irradiance, and lower PNET in
winter. Under both scenarios Pl'JET was positive only for June 2000 and May 2001 (Fig. 13a).
The 50% irradiance simulation without sloughing or abscission yielded consistently higher and
positive values ofPl'mT for all months except May 2001 (Fig. 13b ). Annual P]','ET for 25% with
no abscission was 1.22 gC planf1 and annual Pl'JET for 50% with no abscission was 11.74 gC
Stipe and holdfast survival utilizing soluble carbohydrates alone was calculated assuming
~-.Ph<)tosynttht!tic production of the perennial tissues to determine how long they could survive
OJEllleless period. Dividing the carbohydrate content of the stipe and holdfast in November by
respiration rate of the stipe and holdfast tissues in winter indicated reserves would
months. Production of stipe and holdfast could only account for 20 to 30% of the
load over the winter.
18 DISCUSSION
Pleurophycus gardneri is unique among the Laminariales in having a life history
characterized by annually deciduous blades. Germann (1986) suggested that abscission was
triggered by temperature and resulted in lower respiratory load during winter providing an
adaptation for persistence during the winter period of low light availability. Liining and Kadel
(1993) later showed that abscission was triggered by day length, indicating that abscission inP.
gardneri is under photoperiodic control which is consistent with the respiratory load hypothesis.
The carbon budget calculated here, however, demonstrates that the potential advantage gained
through abscission is not a metabolic adaptation for conservation of carbon because there is
sufficient irradiance. Thus, abscission may be related to other factors such as spore dispersal, as
suggested by the second sari patch produced in late fall. Abscission of sari is common among
Laminariales (Addicott 1982), and perhaps this alga simply abscises the whole blade rather than
just the sorus. The release of the blade prior to winter may also increase winter survivorship by
decreasing drag.
Photosynthesis measurements were performed with sample surfaces oriented normal to
light, which maximizes the incident flux. The orientation of blades in the field, however, is
· i'~"''Y oriented normal to the incident flux because they are in constant motion. With 76 to 73%
'; S-I~fthe variation in the model explained using 25 to 50% of in situ irradiance, this corresponds to
liJltiual average blade orientation of± 60 to 75' from the horizontal. Under low surge
~~mons, fronds can lay flat and shade each other periodically during periods of high blade
addition to blade orientation, light quality may have a significant effect on in situ ofth. d ts eep water kelp. Morel (1978) demonstrated that the photosynthetically
19 usable radiation (PUR) available to deep-dwelling phytoplankton was dominated by poorly
absorbed green/yellow light after passing through multiple light absorbing layers. PUR is that
portion of PAR which is spectrally available for photosynthesis due to the "color" of the water.
A 3-fold difference between measured PAR and PUR at 1% of surface irradiance can occur
depending on optical water type (Morel 1978). Considering the difference in using a spherical
sensor vs. a cosine sensor (360° vs. 180°) and the potential difference in PAR vs. PUR, the
estimate here that 25 to 50% of measured scalar irradiance was used for photosynthesis appears
reasonable. Further refinement of this carbon budget model would require investigating the
effects of water motion on blade angle and light absorption, PAR vs. PUR, self-shading and how
such processes affect the individual carbon budget. Such adjustments of the plant model would
allow determination of potential lower depth limits of this alga based on irradiance data.
Winter irradiances measured at 30 m at East Pinnacles were similar to those of the Arctic
2 1 under seasonal ice cover in winter (0 to 1 mol quanta m- d- ) (Chapman and Lindley 1980,
Dunton 1990). However, the Arctic benthos receives higher irradiances during the summer (up
2 1 8 mol quanta m- d- ). During nutrient limitation in Arctic summer, some kelps cease growth
divert all production to carbohydrate storage (Chapman and Lindley 1980, Dunton 1990).
){c 'J:!J,ese stored carbohydrates are used to fuel 90% of annual plant growth during the winter period g~< [·}\siS~!'.darkntess when nutrients are abundant. Summer irradiances at the East Pinnacles, however,
and highly variable due to plankton blooms and coastal stratus, and day-lengths are much
than in the Arctic summer. This may inhibit the accumulation oflarge internal carbon
by Pleurophycus gardneri in comparison to other kelps including intertidal populations
but most Laminariales can accumulate up to 15 to 20% dry weight (DW) in
(German 1986, Wantanabe et al. 1992). The deep water P. gardneri population
20 only accumulated about 5 to 9% DW as carbohydrates, with the stipe the main reservoir, or sink, and the blade the main source. Some portion of blade carbohydrates may have been translocated to the stipe and holdfast prior to blade abscission. Carbon content of the stipe decreased during spring because ofremobilization and utilization of carbohydrates for growth of the blade.
Germann (1989) suggested this was not possible due to lack of spring blade growth in complete darkness. Because P. gardneri is under photoperiodic control, acropetal translocation of carbohydrate stores in the perennial stipe and holdfast remains a likely possibility. Reserves
accumulated prior to abscission were sufficient for winter respiratory requirements, allowing for
two months of respiration during winter and a buffer of about another month during blade
initiation in spring. In addition, stipe and holdfast produced 20 to 30% of the respiratory
requirement over the winter, which was augmented by slightly reduced respiration rates and a
higher fucoxanthin to chlorophyll a ratio during winter.
Although no major seasonal photoacclimation was evident in this study, a. was two-fold
higher in these deep water plants than in intertidal plants measured by Germann (1989) (Table 4,
5). Respiration rates were also slightly lower than the intertidal plants (Table 4). Wing
density of deep plants was also less than intertidal plants (1 0 and 14 mg DW cm-2
d . enslty of L. hyper bore a from Scotland at 10 m was about I 0 mg DW cm-2 Markager and
(1992) found that the thinner thalli of algae growing in deep water resulted in lower
rates, which may explain the slight difference in respiration of deep vs. intertidal P.
21 Plant size and morphology differed somewhat between the deep water assemblage and intertidal Pleurophycus gardneri plants studied by Germann (1986). Maximum stipe lengths were generally twice as long ( 40 to 50 em) in the deep plants while blade area was similar. Stipes of deep plants exhibited a "step-like" pattern of growth (referred to as growth constrictions, see
Fig. 2). The top of the stipe was flat and broad near the blade junction, narrowing and becoming elliptical with each constriction (with slight turning and rounding between constrictions) and round toward the holdfast. Although stipe growth was not quantitatively measured during the
bladeless period, cell expansion or growth was observed just below the meristem, as indicated by
several centimeters of new, lightly pigmented tissue. Growth rings in the basal portion of the
stipe of deep water P. gardneri were unexpected because they are absent in intertidal plants
(Germann 1986). Validation of growth ring chronology allowed assessment of maximum
observed age of 5 years in this deep water population. These plants abscised one month later
tban intertidal plants and remained bladeless for two months, instead of two weeks like intertidal
plants (Germann 1986).
Some of these morphological and physiological differences may be adaptions to
;:&,survivin;rr in a deep water environment. Higher water motion in the intertidal may cause plants
longer stipes to be removed, effectively decreasing the average stipe length compared to
plants. Longer stipes of deep plants may provide a larger sink to store carbohydrates and
plants to remain b ladeless 4 times longer. Higher photosynthetic efficiency suggests that
Water plants have photoacclimated to the low light environment (Fig. 5). Deep plants can
low light more efficiently per unit biomass and chlorophyll than intertidal plants. Deep
almost double the pigment concentrations of the intertidal plants, which is another
~nloto;lccllim;aticm response to a low light environment (Ramus et al. 1976). Although deep water Pleurophycus gardneri did not accumulate large carbohydrate reserves compared to other kelps, the annual carbon budget is tightly balanced. Despite the potential benefit demonstrated by the model of retaining the blade, classic photoacclimation and seasonally depressed respiration in the perennial parts apparently allow this kelp to persist in deeper water. Without the reserves either produced in or translocated to the perennial stipe and holdfast the plant would die before blade initiation in spring. This study clearly demonstrates
that models, which incorporate photosynthetic production, must account for angle of incident
light relative to the photosynthetic area exposed and quality vs. quantity of in situ irradiance
measured.
ACKNOWLEDGEMENTS
I thank R. Zimmerman for all his teaching and support in the lab, M. Foster for proposing
this study and advice on experimental design, and N. Welschmeyer for review and comments.
Many thanks go to J. Schuytema for the scientific illustration. J. Heine, L. Bradford, A Bullard
and J. Felton provided logistical support and field assistance. Funding was provided by the
Packard Foundation, the P ADI AWARE Foundation, the Earl and Ethyl Meyers Oceanographic
and NOAA National Undersea Research Progran1 (NURP) Monterey Bay Initiative.
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W stipitate understory kelp, Pterygophora ca/ifornica Ruprecht, to shading by the giant kelp, Macrocystis pyr(fera C. Agardh. J Exp Mar Bioi Ecol159: 237-252 WL, Newton M, Starr D (1974) Carbon dioxide exchange of Alnus ntbra: a mathematical model. Oecologia 17: 281-291 EW, Willis AL (1954) The estimation of carbohydrates in plant extracts by anthrone. BiochemJ 57: 508-514 27 Zimmerman RC (2003) A biooptical model of irradiance distribution and photosynthesis in seagrass canopies. Limnol Oceanogr 48: 568-585 Zimmerman RC Unpublished Old Dominion University, Department of Ocean Earth and Atmospheric Science, Oceanography/Physics Bldg., 460 Elkhorn Ave. Room 406a, Norfolk, Virginia, 23529. email [email protected]. Zimmerman RC, Beeler SooHoo JB, Kremer JN and Argenio DZD (1987) Evaluation of variance approximation techniques for non-linear photosynthesis-irradiance models. Mar Biol95: 209-215 Zimmerman RC, Kremer JN (1986) In situ and chemical composition of the giant kelp, Jvfacrocystis pyrifera: response to temporal changes in ambient nutrient availability. Mar Ecol Prog Ser 27: 277-285 Zimmerman RC, Smith RD, Alberte RS (1989) Thermal acclimation and whole-plant carbon balance in Zostera marina L. (eelgrass). J Exp Mar Bioi Ecol130: 93-109 Zimmerman RC, Cabello-Pasini A, Alberte RS (1994) Modeling daily production of aquatic macrophytes from irradiance measurements: a comparative analysis. Mar Ecol Prog Ser 114: 185-196 Zimmerman RC, Steller DL, Kohrs DG, Alberte RS (2001) Top-down impact through bottom-up mechanism. In situ effects of limpet grazing on growth, light requirements and survival of the eelgrass Zostera marina. Mar Ecol Prog Ser 218: 127-140 28 Table 1. Conversion table for normalizing to grams carbon per plant. Mean(± 1SE, n = 10, except Sept and Nov n = 9, Feb win1:1; n = 8) DWas%FW Wing Midrib Stipe Holdfast Jun 12 (0.5) 10 (0.3) 21 (0.6) 19 (0.6) Jul 13 (0.5) 11 (0.3) 24 (0.7) 21 (0.8) Aug 14 (0.4) 11 (0.6) 25 (0.6) 24 (0.5) Sep 14 (0.3) 10 (0.5) 25 (0.4) 22 (0.8) Oct 14 (0.4) 10 (0.6) 26 (0.3) 24 (0.8) Nov 14 (0.4) 10 (0.3) 27 (0.5) 23 (0.8) Dec ABSCISED 28 (0.4) 24 (0.7) Jan BLADELESS 26 (0.5) 23 (0.6) Feb 9 (0.5) 11 (0.6) 25 (0.6) 23 (0.3) Mar 9 (0.2) 8 (0.3) 23 (0.4) 21 (0.5) Apr 9 (0.2) 9 (0.1) 21 (0.5) 21 (0.7) May 6 (0.2) 5 (0 1) 13 (0.2) 13 (0.3) gDWplanf1 Wing Midrib Stipe Holdfast Jun 8.3 (0.91) 3.0 (0.34) 4.8 (0.39) 1.5 (0.18) Jul 10.3 (0.88) 4.0 (0.42) 7.0 (0.88) 1.8 (0.12) Aug 8.2 (0.62) 4.1 (0.31) 7.3 (0.74) 1.9 (0.21) Sept 6.0 (0.94) 3.4 (0.62) 6.8 (0.99) 2.0 (0.26) Oct 3.2 (0.43) 3.3 (0.54) 10.4 (1.08) 2.2 (0.24) Nov 1.7 (0.19) 2.0 (0.27) 8.5 (0.74) 2.0 (0.22) Dec ABSCISED 8.7 (0.67) 1.9 (0.18) Jan BLADELESS 9.1 (0.86) 1.7 (0.12) Feb 0.2 (.02) 0.1 (0.02) 6.8 (0.57) 1.6 (0.13) Mar 1.0 (0.11) 0.4 (0.04) 6.2 (0.57) 1.8 (0.14) Apr 2.8 (0.23) 0.9 (0.05) 4.7 (0.38) 1.7 (0.14) May 2.5 (0.18) 1.0 (0.07) 4.5 (0.53) 1.0 (0.12) gCgDW Wing Midrib Stipe Holdfast Jun 0.25 (0.004) 0.23 (0.006) 0.32 (0.003) 0.31 (0.004) Jul 0.25 (0.005) 0.23 (0.007) 0.32 (0.004) 0.30 (0.004) Aug 0.23 (0.021) 0.25 (0.014) 0.33 (0.011) 0.33 (0.004) Sep 0.21 (0.049) 0.21 (0.010) 0.33 (0.003) 0.33 (0.006) Oct 0.24 (0.003) 0.22 (0010) 0.34 (0.003) 0.32 (0.004) Nov 0.23 (0.015) 0.22 (0.011) 0.35 (0.004) 0.33 (0.004) Dec ABSCISED 0.35 (0.004) 0.31 (0.005) Jan BLADELESS 0.35 (0.006) 0.32 (0.009) Feb 0.22 (0 026) 0.26 (0.001) 0.35 (0.002) 0.32 (0.009) Mar 0.23 (0.004) 0.21 (0.005) 0.32 (0.008) 0.33 (0 010) Apr 0.20 (0.019) 0.21 (0.003) 0.29 (0.030) 0.32 (0.007) May 0.22 (0.006) 0.20 (0.002) 0.30 (0.007) 0.30 (0.006) Table 2. ANOVA results for differences in parameters by tissue type among months. Significance represented by* < 0.05 ** < 0.01 *** < 0.001. Treatment df MS F p Significance Respiration Wing 9 0.00706 1.94 0.0619 n.s. Error 62 0.00363 Midrib 9 0.00019 1.05 0.4112 n.s. Error 60 0.00018 Stipe 11 0.00010 3.29 <0.001 *** Error 98 0.00003 Holdfast 11 0.00033 0.94 0.5100 n.s. Error 81 0.00036 Carbon content Wing 9 7.0130 32.248 <0.001 *** Error 82 0.2170 Midrib 9 1.0990 24.097 <0.001 *** Error 82 0.0460 Stipe 11 5.1100 8.65 <0.001 *** Error 106 0.5910 Holdfast 11 0.1200 4.294 <0.001 *** Error 106 0.0280 Growth Blade 9 3.32800 233.527 <0.001 *** Error 89 0.01400 Sloughing Blade 5 1.231 23.597 <0.001 *** Error 53 0.052 Table 2 continued. Treatment df MS F p Significance Chi Wing 9 0.17200 20.93 <0.001 *** Error 84 0.00800 Midrib 9 0.01200 7.10 <0.001 *** Error 84 0.00200 Stipe 11 0.01800 8.24 <0.001 *** Error 106 0.00200 Holdfast 11 0.00800 2.44 0.0089 ** Error 106 0.00300 Fucoxanthin Wing 9 0.02500 10.46 <0.001 *** Error 84 0.00200 Midrib 9 0.00600 7.22 <0.001 *** Error 84 0.00100 Stipe 11 0.17600 2.49 0.0091 ** Error 106 0.07100 Holdfast 11 0.00500 3.52 <0.001 *** Error 106 0.00100 Mannitol Total Plant 11 6.414 18.988 <0.001 *** Error 106 0.338 Laminaran Total Plant 11 4.038 15.844 <0.001 *** Error 106 0.255 Table 3. Annual mean values for wing, midrib, stipe and holdfast tissues for PMA.x, alpha, and respiration.FW =fresh weight Values in parentheses represent± 1 standard error estimate determined according to Zimmerman eta!. 1987. Parameter Wing Midrib Stipe Holdfast 2 2 1 1 1 Alpha (!lmol0 m s llmol quanta- gFW m- ) 0.0287 (0.008) 0.0111 (0.003) 0.0023 (0.006) 0.0079 (0.022) 1 1 PMA.X (!lmol02 gFW min- ) 0.4987 (0.052) 0.1941 (0.018) 0.0443 (0.004) 0.0502 (0.019) 1 1 Respiration (!lmol02 gFW min- ) 0.0306 (0.009) 0.0202 (0.005) 0.0112 (0.002) 0.0133 (0.003) Table 4. Comparative average values for tissue composition, photosynthesis and respiration of deep water versus intertidal populations of P. gardneri, and comparisons with other kelps. Data are for blade tissues unless otherwise noted. Deep Inte•·tidal Macrocystis pyrifera, Pterogoplwra califomica Parameter P. gardneri P. gardneri * = Macrocystis pyr(fera only (this study) (Germann 1986) (Zimmerman and Kremer 1986, Zimmerman unpubl.) Carbon (% DW) 20 - 25 26 - 30 33 * Mannitol (% FW) 0.5 1.44 0.5 * Lamminaran (% FW) 0.2 0.024 0.2 * Chi a: Chic 5 3 1.7, 3.5 (stipe) 0.35 0.3 Chi a : Fucoxanthin 1.8 1.7 0.56, 0.5 (stipe) 1 0.6 1 1 Respiration (Jl11lol 02 gFW min" ) 0.03 0.05 0.05, 0.02 1 1 Pm (f.Lmol 02 gFW min" ) 0.5 0.5 0.6, 0.42 Alpha 0.029 0.009 0.009, 0.007 2 2 1 1 1 (f.lmol 02 m s gFW min· Jl1110l quanta. ) Pn/R 16 10 12,20 (stipe) 5 2 1 1 Pm Chi a· (f.Lmol02 mg Chl a ·I min" ) 1.1 1.9 3.7, 4.5 2 1 Ek~Pm I Alpha (f.LE m· s" ) 17 56 67,64 1 Fucoxanthin (mg gFW ) 0.25 0.1 0.5, 0.8 1 Chi a (mg gFW ) 0.45 0.27 0.22, 0.40 Table 5. Regression analysis for modeled versus measured plant size for all irradiance correction factors, and back calculation. StmJmary of standard regression Ho: slope, intercept= 0 Slope Regression % Irradiance (df, n) r2 slope(+/- SE) ANOVA F value Slope p Intercept(+/- SE) Intercept p 100 (1, II) 0.67 2.07 (+/- 0.48) 18.41 0.0020 -3.06 (+/- 2.00) 0.165 75 (1, 11) 0.70 1.91 (+/- 0.42) 20.75 0.0014 -2.93 (+/- 1.76) 0.131 50 (1, II) 0.73 1.70 (+/- 0.34) 24.80 0.0008 -2.72 (+/- 1.42) 0.089 25 (1, 11) 0.76 1.36 (+/- 0.25) 29.23 0.0004 -2.36 (+/- 1.05) 0.052 15 (1, II) 0.74 1.18 (+/- 0.23) 25.87 0.0007 -2.18 (+/- 0.97) 0.052 10 (!,II) 0.70 1.08 (+/- 0.24) 20.68 0.0014 -2.08 (+/- 0.99) 0.066 Back-calculated (1, II) 0.87 0.917 (+/- 0.12) 61.75 0.000026 0.25 (+/- 0.53) 0.641 StmJmary of second order regression Ho: slope= 1 % Irradiance (df, n) Slope ( +/- SE) !(0.05,9)=2.262 95%CL p 100 (1, II) 2.07 (+/- 0.48) 2.39 1.09 >0.05 75 (!,II) 1.91 (+/- 0.42) 1.97 0.95 >0.05 50 (1, II) 1.70 (+/- 0.34) 1.44 0.77 >0.05 25 (!, 11) 1.36 (+/- 0.25) 0.52 0.57 >0.05 15 (1,11) 1.18 (+/- 0.23) 0.14 0.52 >0.05 10 (!,II) 1.08 (+/- 0.24) 0.03 0.54 >0.05 Back-calculated (I, II) 0.917 (+/- 0.12) 0.06 0.27 >0.05 FIGURE LEGEND Figure 1. Morphology and growth of Pleurophycus gardneri (a) Growth phenology (b) Blade growth and sloughing (x ± 1 SE). Horizontal lines running through the data at different heights indicate significant temporal differences among monthly means determined by LSD post-hoc analysis (dashed for growth and solid for sloughing). Figure 2. Measurements made to determine in situ growth (June 2000- November 2000). Labels on the right show where each tissue type is located. Figure 3. Time series of daily average temperature and total daily irradiance. Figure 4. Generalized P vs. E curves for wing tissue of deep and intertidal P. gardneri (a) per unit biomass and (b) per unit chlorophyll demonstrating classic photoacclimation of deep plants vs. intertidal. Figure 5. Laminaran and mannitol soluble carbohydrates (x ± I SE). Horizontal lines running through the data at different heights indicate significant temporal differences among monthly means determined by LSD post-hoc analysis (solid for laminaran and dashed for mannitol). Figure 6. Chlorophyll (a and c) and fucoxanthin concentrations for wing and (X± 1 SE). Horizontal lines running through the data at different heights indicate significant temporal differences among monthly means determined by LSD post-hoc analysis (dashed for midrib and solid for wing). 7. Chlorophyll (a and c) and fucoxanthin concentrations for stipe and holdfast (x± I SE). Horizontal lines running through the data at different heights indicate significant temporal differences among monthly means determined by LSD post-hoc analysis (dashed for stipe solid for holdfast). Figure 8. Plant size expressed in grams carbon for the (a) wing, midrib, (b) stipe and holdfast (X± 1 SE). Horizontal lines running through the data at different heights indicate significant temporal differences among monthly means determined by LSD post-hoc analysis (dashed for midrib and holdfast and solid for wing and stipe). Figure 9. Measured and modeled plant size at 100% irradiance (a) PNETat 100% irradiance (b) Measured plant size versus plant size predicted by the model using 100% of irradiance measured at 30m. Figure 10. Measured and modeled plant size at 50% irradiance (a) PNETat 50% irradiance (b) Measured plant size versus plant size predicted by the model using 50% of irradiance measured at 30 m. Figure ll. Measured and modeled plant size at 25% irradiance (a) PNETat 25% irradiance (b) Measured plant size versus plant size predicted by the model using 25% of irradiance measured at 30 m. Figure 12. Regression analysis for all irradiance correction factors (a) Slope of regression (b) Intercept of regression (c) R2 of regression. Figure 13. Daily PNET at different irradiances (a) Average daily PNET using 25% irradiance correction factor (b) Average daily PJ>..'ET using 50% irradiance correction factor. Asterisks indicate months when abscission was not significantly different than no abscission. ,-,.:~,m" Ia & b. Growth Phenology Abscission Scar J J A S 0 N D J F M A M 2000 2001 b. Growth and Sloughing 1111 Blade Sloughing t:;. Blade Growth :f -: • :f-.: ;f, J J A s 0 N D J F M A M 2000 2001 Figure 2. In situ growth rate Plant at time t1 Plant at time t2 1Lt2 - Lt11= Sloughing collection interval-1 Growth rate ·~ collection :.. ~ Stipe length -...n intervai-1 Figure 4a & b 0.6 a. P vs. E, biomass -·.s ...... s 0.4 -. - .. " . - ,- • .. - • " 0 0.2 ... ---Deep - - - -Intertidal -0 §_ • " 0 50 100 150 2 1 Irradiance (J.Unol quanta rn- s - ) 1.8 b. P vs. E, chlorophyll . - - 1.6 -- - ~ • -- -- '• EO 1.4 .. .. -- s • ~ 1.2 ' co:! :;:: u 1 g 0.8 ,. •" "' 0.6 , 0 ., 7 -0 ---Deep - - - -Intertidal )::: 0.4 9.. 0.2 0 " 0 50 100 150 . -2 -1 Irradmnce (J.llllol quanta m s ) Figure 5. 650 600 550 • Laminaran ,-.., 500 ...... o Mannitol ...... § 450 -0.. u 400 on ~ 350 v +-' ~ ------, '"d~ 300 ;>-. ..c: 0 250 ~ u 200 150 100 ·~._ - -2- --- 50 o~~~~~~~--~~~--~~~--~~ J J A S 0 N D J F M A M 2000 2001 Figure 6. 0.40 Wing ,-...., 0.35 • ~ ' D Midrib ~ ~ 0.30 b1) b1) 8 '--' 0.25 1"""'""1 ...... l::: t o:S 0.20 I § ' :><: 0 (.) 0.15 ;::i ~ g D g '--' - Ll ------[3 - 0 . ,{]- - - -0 0.10 • D 0.05 J J A s 0 N D J F MA M 0.8 • Wing ,-...., 0.7 ! ~ ! D Midrib ~ ~ 0.6 b1) b1) 8 0.5 ~ 1"""'""1 -£ 0.4 ! 0., 0 !-; 0 0.3 g ' -..c:u bl g '-- - D ------0- g li 0.2 D • li 0.1 J J A s 0 N D J F MAM 2000 2001 Figure 7. 0.060 o Stipe .-, 0.055 ,...... , • Holdfast ·~ 0.050 Th 0.045 0.040 '._/s -~------~-r~-~--- -r- '"2' 0.035 ·-~ 0.030 ~ 0.025 (.) &: 0.020 ! lo..ooJ ' ! 0.015 0 0 010 -+--r---r---r-..---.---.----.---,.-r---u---u---r---, J J A S 0 N D J F M A M 0.16 o Stipe .....--- 0.14 • Holdfast I ~ ~ 0.12 b.[) g 0.10 ,...... , -~ 0.08 ~ .Q 0.06 0 ...... 0.04 J J A S 0 N D J F M A M 2000 2001 Figure 8a & b. 4 a. ,--.... ~ • Wing '.;....> § 3 D Midrib -0.. b1J '-" ~ 0 .£:! 2 8 u (!.) ;:::l tJJ tJJ 1 ,- -g- a ·-t-< a .. g· ' ' • • 0 J .T A SOND .T FMAM 4 b. Stipe Holdfast ~ v ~ ~ ~ 2 ~ v v v v ------. v .TJASONDJFMAM 2000 2001 Figure 9 a & b. a. 100% Irradiance 12 10 1111 Measured Plant Si:ze 0 Modeled Plant Si:ze ~ "'§ 8 0. uen ~ 6 N "iil" ~ 4 0::" 2 0 June July Aug Sept Oct Nov Dec Jan Feb March April May b. 100% Irradiance 12 ..,~ 10 y = 2.074x- 3.0635 fj R2 =0.6717 -a u 8 bJJ ~ Q) -~ Ul 6 ~ § ~ "0 Q) 4 Qj "0 ~ 2 0 0 1 2 3 4 5 6 7 8 1 Measured Plant Size (gC plant " ) Figure 10 a & b. a. 50% Irradiance 9 8 7 lll Measured Plant Si>E 0 Modeled Plant Si>E 2 1 0 June July Aug Sept Oct Nov Dec Jan Feb March April May b. 50% Irradiance 9 8 • ~ -; 7 y = 1.6952x- 2. 7227 R2 =0.7338 0.6""' u • ';;'"" 5 .!:I §"' 4 ;;: ., 3 .!! ~ "0 :E 2 •• 0 0 1 2 3 4 5 6 7 8 Measured Plant Size (gC plant -I ) Figure II a & b. a. 25% Irradiance 7 6 II Measured Planl Size D Modeled Plaot Size 0 Jll!le July Aug Sept Ocl Nov Dec Jan Feb March April May b. 25% Irradiance 7 6 y = l.3582x- 2.3576 R2 = 0.7646 0+------.------r------.-----~------.------r------, 0 1 2 3 4 5 6 7 Measured Plant Si2e (gC plant _, ) Figure 12a, b, c. 3 a. 1=1 ...... 0 rJl rJl (!) ;.... 2 biJ (!) ~ ~ 0 (!) 1 0.. 0 -r:/1 0 1=1 ...... 0 -5 -r rJl rJl (!) ;.... -4 -~ biJ (!) ~ ~ -3 0 +-> 0.. -2 (!) u ;.... (!) +-> -1 1=1 - 0 0.76 1=1 ...... 0 [/) [/) (!) 0.72 (!)bb ~ '-!-; 0 <'4 0.68 ~ 0 1015 25 50 75 100 % Irradiance Correction Factor Figure 13a, b. ,-... ~ ' a. 25% Irradiance correction factor '"d 0.06 ~ ' § • abscission -0.. 0.04 u D modeled no abscission bi} '-" E-< 0.02 ~ D ~ >-. ' ...... 0.00 -cod ~ (!) -0.02 ;.....~ (!) ~ -0.04 * * J J A 0 N D J F M AM 0.12 s ,-... ~ b. 50% Irradiance correction factor '"d' ~ 0.10 '...... fa • abscission -0.. 0.08 D u modeled no abscission b/) '-" E-< 0.06 D ~ \ __,>-. 0.04 \ 0 -D-o C'j \ ,q , ·- , 0 D-o' ' (!) 0.02 D , & ' o· 0 (!) 0.00 -<>- -0.02 J J A s 0 N D J F MAM 2000 2001 Appendix 1a. Post hoc results for blade growth and sloughing. LSD test for SLOUGHING in gC planf1 nls =not significant Post Hoc Tests * = < 0.05 MAIN EFFECT: MONTH ** = < 0.001 MONTH 2000 June Jul~ August September October November MEAN 0.00 0.04 0.03 0.48 0.97 0.5 2000 June July n!s August n!s nls September ** ** ** October ** ** ** * November ** ** ** n!s * LSD test for GROWTH in gC planf1 nls = not significant Probabilities for Post Hoc Tests * = < 0.05 MAIN EFFECT: MONTH ** = < 0.001 MONTH 2001 February March Aeril May 2000 June July August September October November MEAN 0.04 1.08 2.27 2.37 0.84 0.2 0.05 0.007 0 0 2001 February March ** April ** ** May ** ** nls 2000 June ** n!s ** ** July ** ** ** ** ** August n!s ** ** ** ** ** September n!s ** ** ** ** ** * October n!s ** ** ** ** ** * n!s November nls ** ** ** ** ** * n/s n/s Appendix lb. Post hoc results for stipe respiration and res12iration across tissue t~12es. LSD test for STIPE RESPIRATION in gC planf1 n/s =not significant Probabilities for Post Hoc Tests * = < 0.05 MAIN EFFECT: MONTH ** = < 0.001 MONTH 2001 January February March AJ2ril May 2000 June July August Se12tember October November December 2001 January February n/s March n/s n/s April n/s n/s n/s May n/s n/s n/s n/s 2000 June * n/s n/s * n/s July ** n/s * * n/s n/s August n/s n/s n/s n/s n/s * * September n/s n/s n/s n/s n/s n/s * n/s October n/s n/s n/s n/s n/s * * n/s n/s November n/s n/s n/s n/s n/s * ** n/s n/s n/s 2000 December n/s * * n/s * * ** n/s * n/s n/s Appendix lc. Post hoc results for carbohdrate concentrations. LSD test for LAMINARAN and MANNITOL below in mgC planf1 n/s =not significant Probabilities for Post Hoc Tests *=<0.05 MAIN EFFECT: MONTH •• = < 0.001 MONTH 2000 June July August Sept. October Nov. Dec. 2001 January February March April May MEAN 145.0 95.8 41.2 99.8 144.5 32.7 30.0 26.7 12.4 25.8 37.3 35.3 2000 July n/s August n/s n/s September * ** * October * ** ** * November n/s n/s n/s ** •• December n/s n/s n/s ** ** n/s 2001 January * n/s n/s ** ** n/s n/s February •• •• ** ** ** ** •• •• March n/s n/s n/s ** ** n/s n/s n/s •• April n/s n/s n/s • •• n/s n/s * ** n/s May n/s n/s n/s •• ** n/s n/s n/s •• n/s n/s MONTH 2001 January February March April May 2000 June July August Sept. October Nov. Dec. MEAN 200.8 236.8 94.3 88.9 48.8 135.0 493.0 406.7 236.6 363.3 363.9 224.9 2001 January February n/s March * ** April * •• n/s May ** ** * * 2000 June * •• n/s n/s * July ** •• * * n/s • August • * ** •• •• ** ** September n/s n/s • ** ** •• •• n/s October * n/s ** •• ** ** ** n/s n/s November * n/s •• •• ** •• •• n/s n/s n/s 2000 December n/s n/s •• •• ** •• Appendix 1d. Post hoc results for all pigments and all tissue types. LSD test for WING CHLOROPHYLL mg gFW1 n/s = not significant Probabilities for Post Hoc Tests *=<0.05 MAIN EFFECT: MONTH **=<0.001 MONTH 2001 February March April May 2000 JtUle July August September October November MEAN 0.27 0.43 0.4 0.32 0.48 0.56 0.66 0.73 0.56 0.54 2001 February March ** April • n/s May n!s * • 2000 June ** n/s n/s •• July ** • •• •• • August •• ** •• •• •• • September ** ** •• •• ** ** n!s October ** * •• •• • n!s * • November •• * * ** n/s n!s * ** n!s LSD test for MIDRIB CHLOROPHYLL mg gFW1 MEAN 0.15 0.26 0.2 0.19 0.23 0.26 0.27 0.27 0.23 0.21 2001 February March •• April * * May * ** n/s 2000 June ** n/s n!s • July •• n/s • •• n/s August ** n/s •• •• * n/s September ** n/s * ** n/s n/s n/s October •• n/s n!s * n!s n!s n!s n!s November * * n/s n/s n!s * * • n/s Appendix 1d. Post hoc results for all pigments and all tissue types. LSD test for STIPE CHLOROPHYLL and HOLDFAST below in mg gFW1 n/s =not significant Probabilities for Post Hoc Tests *=<0.05 MAIN EFFECT: MONTH ** = < 0.001 MONTH 2001 January February March April May 2000 June July August September October November December MEAN 0.08 0.08 O.ll 0.09 0.10 0.06 0.07 0.05 0.04 0.04 0.05 0.07 2001 January February * March * ** April * •• n!s May • ** n/s n!s 2000 Jm1e n!s • • • * July n!s * • • • n!s Angnst n!s n/s •• •• •• n/s • September n/s n!s •• ** •• n!s * n!s October n/s n!s •• •• ** * • n!s n/s November n!s n!s •• •• ** • • n/s n/s n/s 2000 December n!s n!s •• •• •• * • n/s n!s n/s n/s MEAN 0.13 0.08 0.14 0.05 0.05 0.07 0.05 0.06 0.06 0.05 0.05 0.14 2001 January February • March n/s * April n/s n/s * May n!s * * n!s 2000 June n!s n!s * n!s n!s July n!s n/s * n!s n!s n!s Angnst n/s n!s * n!s n/s n!s n/s September n/s n/s * n!s n!s n!s n/s n!s October n!s * * n!s n!s * n!s n!s n!s November n!s n!s • n/s n!s * n/s n/s n/s n/s 2000 December n/s * n!s * * * • • • • • Appendix 1d. Post hoc results for all pigments and all tissue types. LSD test for WING FUCOXANTHIN and MIDRIB below in mg gFW1 n/s = not significant Probabilities for Post Hoc Tests • =< 0.05 MAIN EFFECT: MONTH ** = < 0.001 MONTH 2001 February March April May 2000 June July August September October November MEAN 0.12 0.2 0.22 0.22 0.24 0.27 0.3 0.33 0.26 0.23 2001 February March * April ** n/s May ** n/s n/s 2000 June ** n/s n/s n/s July ** * * * n/s August ** ** * ** * n/s September ** ** ** ** ** n/s n/s October ** * n/s * n/s n/s n/s * November ** n/s n/s n/s n/s n/s • ** n/s MEAN 0.06 0.1 0.09 0.1 0.1 0.12 0.12 0.12 0.1 0.1 2001 February March ** April ** n/s May ** n/s n/s 2000 June ** n/s n/s n/s July ** n/s * * n/s August ** n/s * * n/s n/s September ** n/s * * n/s nls n/s October ** n/s n/s n/s n/s n/s n/s n/s November ** n/s n/s n/s n/s n/s n/s n/s n/s Appendix 1d. Post hoc results for all pigments and all tissue types. LSD test for STIPE FUCOXANTHIN and HOLDFAST below in mg gFW1 n/s = not significant Probabilities for Post Hoc Tests *=<0.05 MAIN EFFECT: MONTH •• = < 0.001 MONTH 2001 January February March April May 2000 June July August September October November December MEAN 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.04 0.03 0.04 0.04 0.04 2001 January Febmary n/s March n/s • April n/s • n/s May n/s • n/s n/s 2000 Jtme n/s n/s n/s n/s n/s July n/s • n/s n/s n/s n/s August n/s n/s n/s * n/s n/s * September n/s n/s • • • n/s * n/s October n/s n/s n/s • n/s n/s • n/s n/s November n/s n/s n/s • n/s n/s • n/s n/s n/s 2000 December n/s n/s • • • n/s • n/s n/s n/s n/s MEAN 0.02 0.03 0.04 0.04 0.04 0.04 0.03 0.03 0.03 0.02 0.02 0.02 2001 January Feb mary n/s March • • April • • n/s May • • n/s n/s 2000 June • n/s n/s n/s n/s July n/s n/s • n/s n/s n/s August n/s n/s * n/s n/s n/s n/s September n/s n/s n/s n/s n/s n/s n/s n/s October * • ** • •• •• * • • November n/s n/s • • • • n/s n/s n/s n/s 2000 December n/s n/s * • • • n/s Appendix 1e. Post hoc results for wing and midrib carbon content. LSD test for WING CARBON and MIDRIB below in g C planf1 n/s = not significant Probabilities for Post Hoc Tests *=<0.05 MAlN EFFECT: MONTH •• = < 0.001 MONTH 2001 February March April May 2000 June July August September October November MEAN 0.035 0.236 0.552 0.558 2.100 2.640 1.840 1.270 0.780 0.387 2001 February March n/s April n/s n/s May n/s n/s !tiS 2000 June •• •• •• •• July •• ** •• •• • August •• •• •• ** n/s ** September •• ** • • •• •• • October • * !tiS n/s ** •• •• • November n/s n/s n!s n/s ** •• •• •• n/s MEAN 0.037 0.09 0.186 0.195 0.697 0.919 0.999 0.711 0.705 0.431 2001 February March n/s April n/s n/s May n/s n/s n!s 2000 June ** •• •• •• July ** ** •• ** * August ** •• •• •• • n/s September •• •• ** •• n/s • • October ** •• * •• n/s • * n/s November • • • * • •• ** • • Appendix 1e. Post hoc results for stipe and holdfast carbon content. 1 LSD test HOLD FAST CARBON and STIPE below in g C planf nls =not significant Probabilities for Post Hoc Tests * = < 0.05 MAIN EFFECT: MONTH •• = < 0.001 MONTH 2001 January February March April May 2000 June July August September October November December MEAN 0.54 0.52 0.59 0.54 0.3 0.47 0.56 0.64 0.67 0.72 0.66 0.6 2001 January February n/s March n/s n/s April n/s n/s n/s May * • •• • 2000 June n/s nls nls nls • July n/s n/s nls nls •• nls August n/s n/s n/s n/s •• • nls September n/s nls n/s n/s •• • nls nls October * • nls * •• * * nls n/s November n/s n/s nls n!s ** * n/s nls n/s n/s 2000 December n/s 1Jis nls nls ** nls nls n/s n/s nls nls MEAN 3.16 2.41 2 1.33 1.36 1.51 2.27 2.42 2.25 3.49 2.97 3.02 2001 January Feb mary * March •• n/s April ** * nls May ** * nls n/s 2000 June •• * 1Jis n/s n/s July • n/s nls * • • August • n/s nls • * * nls September * nls nls • • * nls nls October n/s * •• •• ** •• •• * ** November nls 1J!s • ** ** •• * • • n/s 2000 December n/s n/s • ** •• •• * • • n/s nls Appendix 2. Timeseries of continuous scalar irradiance and temperature at East Pinnacles, Carmel Bay. 3.5 14 --Inadiance -o- Temperature 3 12 _,.-.., '"0 ";'s 2.5 IOu~ o:l 0 § '-' & 2 8 ~ -0 E-< g >, ~ :a 0.5 2 0 ~h,-,,---.-~~~~~ .. -.~~~~•••~~.-~~-,~,~.~-"~"=,-r,--.~,-~,·-~~~.~~--.~~.-,-,.,-~~nr,.~~~~•.-11 0 7/18/00 9/6/00 10/26/00 12115/00 2/3/01 3/25/01 5/14/01 7/3/01 8/22/0l Appendix 3a. Data from Pleurophycus gardneri that recruited to clearing around light meter in Feb. -March 2000. Date is date of collection. Date Plant Stipe Length (em) #Rings Stipe Diameter (em) 1116/01 1 14 0 0.7 1116/01 2 23 0 0.8 1/16/01 3 15.5 0 0.7 1/16/01 4 18 0 0.8 5/4/01 1 27 1.5 0.8 5/4/01 2 24 1.5 0.8 5/4/01 3 24.5 1.5 0.8 5/4/01 4 28 1.5 0.8 5/4/01 5 39 1.5 0.8 5/4/01 6 27 1 0.7 5/4/01 7 22 1.5 0.7 5/4/01 8 29 1 0.7 8/14/01 1 30 1.5 0.7 8114/01 2 40.5 1.5 0.9 8/14/01 3 35.5 2 0.8 8/14/01 4 25 1.5 0.7 8/14/01 5 30.5 1.5 0.8 8/14/01 6 36.5 2 0.9 8/14/01 7 33 1.5 0.9 8/14/01 8 32 1.5 0.7 8/14/01 9 22 1.5 0.6 6/15/02 1 41.5 1.5 1 6/15/02 2 38 2.5 I 6/15/02 3 27 1.5 0.8 6/15/02 4 31 2.5 0.7 6/I5/02 5 35.5 2.5 1 6/15/02 6 40.5 2.5 1 6/15/02 7 37.5 2.5 I 6/15/02 8 33 2.5 1 6115/02 9 35.5 2 0.9 6/15/02 IO 38 2.5 0.9 Appendix 3b. Raw data on ring number, stipe diameter and len!,>th from monthly samples. Blank means no data. collection sample date ring# stipe diameter (em) stipe length (em) 44 7/25/00 2 62 45 7/25/00 2 55 46 7/25/00 2 46 47 7/25/00 I 36 48 7/25/00 2 46 49 7/25/00 I 38 50 7/25/00 1 32 51 8/24/00 3 42 52 8/24/00 3 31 53 8/24/00 2 45 54 8/24/00 1 49.5 55 8/24/00 34 56 8/24/00 2 45 57 8/24/00 1 77 58 8/24/00 2 58 59 8/24/00 2 50 60 8/24/00 2 50 61 9/28/00 4 41 62 9128/00 3 45 63 9/28/00 I 49 64 9/28/00 2 45 65 9/28/00 2 61 66 9/28/00 2 48 67 9/28/00 4 45 68 9/28/00 I 37 69 9/28/00 I 21 7l 10/22/00 5 54 72 10/22/00 4 70 73 10/22/00 3 54 74 10/22/00 5 50 75 10/22/00 4 66 76 10/22/00 3 42 77 10/22/00 3 49 78 10/22/00 3 53 79 10/22/00 2 33 80 10/22/00 4 42.5 81 11/15/00 2 1.1 49 82 11/15/00 2.5 1.1 60 Appendix 3b continued. collection sample date ring# stipe diameter (em) stipe length (em) 83 11/15/00 3.5 1.2 60 84 11115/00 1.5 1 47 85 11/15/00 1.5 0.9 36.5 86 11115/00 4.5 1.1 48 87 11/15/00 1.5 1 52 88 11115/00 3 1.1 43 89 11115/00 3.5 1.1 40 90 11/15/00 91 12116/00 2.5 1 57 92 12/16/00 3 0.9 44.5 93 12/16/00 2.5 1.1 61 94 12116/00 2.5 1 54 95 12116/00 2.5 1 52 96 12116/00 3 1.1 37.5 97 12116/00 3 1.2 57 98 12/16/00 2.5 1.1 54 99 12116/00 3.5 1.1 43 100 12116/00 3.5 1.1 43 101 1116/01 2 1.1 47 102 1/16/01 4.5 1.3 49 103 1116/01 2.5 1.1 47 104 1116/01 3.5 1.1 47 105 1116/01 2.5 1 60 106 1116/01 4.5 1.3 59 107 1116/01 3.5 1.2 51 108 1116/01 3.5 1.2 54 109 1116/01 3.5 1 58 llO 1116/01 2.5 1.1 35 11l 2114/01 1.5 0.9 51 ll2 2114/01 2.5 1.2 51 113 2114/01 0.5 0.9 41 114 2114/01 1.5 1.1 42 115 2114/01 2.5 1.1 51 l16 2114/01 1.5 1 44 117 2114/01 3.5 1.1 33 118 2/14/01 1.5 1 39 119 2/14/01 4.5 1 45 120 2/14/01 3.5 1.1 52 121 3/12/01 2.5 1.1 49 122 3/12/01 1.5 1 43 Appendix 3b continued. collection sample date ring# stipe diameter (em) stipe lengtb (em) 118 2/I4/0I l.5 I 39 II9 2/l4/0l 4.5 I 45 120 2/I4/0l 3.5 l.l 52 I2I 3/l2/0l 2.5 l.l 49 I22 3/I2/0l l.5 I 43 I23 3/12/01 3 l.l 62 I24 3/12/01 1.5 1.1 59 125 3/12/01 1.5 1 41 126 3/12/01 1.5 l.l5 44.5 127 3/12/01 1.5 1.1 37 128 3/l2/0l 1.5 I 37.5 129 3/12/01 2.5 1.15 36 130 3/12/01 3.5 1.1 39 131 4/l4/01 2.5 1 39 132 4/l4/0l 2 0.9 46 133 4/l4/0l 2.5 0.95 38 134 4/l4/01 2.5 1 40 135 4/l4/0l 2.5 1 51 136 4/l4/0l 2.5 0.9 41 137 4/14/01 2 0.9 33 Appendix 3b continued. Regression analysis of rings in monthly samples. 90 y ~ 5.0529x + 32.77 1 Analysis of Variance 80. R ~ 0.2!68 70 . • Sums of Mean ~ Squares df Squares F p-Ievel ! 60 • • ~50- ~ Regress. 3236.7813 I 3236.7813 28.787373 4.9227E-07 § I J ·-t ..., 40 . • Residual 11693.504 104 112.43754 0 !..-t I I .e- 30 - I • I • Total 14930.285 iii • 20 • Regression Summary for Dependent Variable: STIPLEN 10- I R= .46561035 R'= .21679299 Adjusted R'= .20926216 F(1,104)=28.787 p<.OOOOO Std.Error of estimate: 10.604 0 2 3 4 5 6 St. Err. St. Err. Ring Number BETA ofBETA B ofB t(l04) p-Ievel Intercpt 32.770283 2.4684513 13.275645 4.02393E-24 RINGNUM 0.4656103 0.0867804 5.0528715 0.9417535 5.36538647 4.92273E-07 Regression Summary for Dependent Variable: STIPDIAM R= .73962285 R'= .54704197 Adjusted R'= .54047736 F(I,69)=83.332 p<.OOOOO Std.Error of estimate: .11486 St. Err. St. Err. BETA ofBETA B ofB t(69) p-level 1.411.2 - Intercpt 0.7369735 0.0332061 22.1939043 3.93035E-33 ~ l. RINGNUM 0.7396229 0.0810223 0.1171635 0.0128347 9.12863588 1.74182E-13 g § 0.8 - Analysis of Variance i5 • • 0 0.6- Sums of Mean 0. y~O.ll72x+0.737 ~ 0.4- • 2 Squares df Squares F p-level R "" 0.547 Regress. 1.0994388 1 1.0994388 83.331993 1.7418E-13 0.2- Residual 0.91035 69 0.0131935 0 ~------,----~~--~--. ---,·------. Total 2.0097887 0 2 3 4 5 Ring Number Appendix 3c. Summary of second order regression Ho: sloee = I for both the monthly sameles and the one random sample. Slope SE ofsloee df t 95%CL X-95%CL X+95%CL p t(0.05, dt) random stipelength 15.152 1.186 10.000 12.778 2.642 12.510 17.794 <0.05 2.228 sample stipe diam 0.207 0.031 10.000 6.736 0.068 0.138 0.275 <0.05 2.228 monthly stipelength 5.053 0.942 104.000 5.365 1.867 3.185 6.920 <0.05 1.983 rings stipe diam 0.117 0.013 69.000 9.129 0.026 0.092 0.143 <0.05 1.995 Appendix 3d. One random sample collected on 4-14-0 I outside study site to avoid adult bias in monthly collections. All size classes were represented. Plant Ring # Diameter Length Measurements are for stipe in em. I 2.5 1.05 46 2 3.5 1.25 58 3 2.5 1.05 56 4 0.5 0.5 18 5 0.5 0.85 20 6 1.5 0.85 35 7 0.5 0.7 15.5 8 1 0.7 22 9 0.5 0.7 17 10 0.5 0.7 22 11 0.5 0.5 15 12 0.5 0.5 12.5 Regression Summary for Dependent Variable: STlPDIAM R= .90521556 R2= .81941521 Adjusted R2= .80135674 F(1,10)=45.376 p<.00005 Std.Error of estimate: .10728 St. Err. St. Err. BETA ofBETA B ofB t(IO) p-level Intercpt 0.52947 0.0483 10.9617 6.809E-07 RINGNUM 0.90522 0.13438 0.20664 0.03068 6.73615 5.129E-05 Analysis of Variance; DV: STlPDIAM (randring.sta) Sums of Mean Squares df Squares F p-Ievel Regress. 0.52221 1 0.52221 45.3757 5.1E-05 Residual 0.11509 10 0.01151 Total 0.63729 Regression Summary for Dependent Variable: STlPELG R= .97071521 R2= .94228802 Adjusted R2= .93651682 F(1,10)=163.27 p<.OOOOO Std.Error of estimate: 4.1467 St. Err. St. Err. BETA ofBETA B ofB t(10) p-Ievel Intercpt 9.77513 1.86704 5.23564 0.0003812 RINGNUM 0.97072 0.07597 15.1516 1.18577 12.7779 1.615E-07 Analysis of Variance; DV: STlPELG (randring.sta) Sums of Mean Squares df Squares F p-Ievel Regress. 2807.47 1 2807.47 163.274 1.6E-07 Residual 171.948 10 17.1948 Total 2979.42 Appendix 3d continued. 81.5 y = 0.2066x + 0.5295 Q '-' 2 R 0.8194 I E 1 --~~_.~~~!l~~------.~ ~ t: ., ao.5 • .g. 70 y = 15.152x + 9.7751 s 60 R2 =0.9423 2.- 50 40 tc: ~ 30 .S. 20