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Development of Allometric Relations for Three Mangrove Species in South Florida for Use in the Greater Everglades Ecosystem Restoration (Smith and Whelan, 2006)
Ó Springer 2006
Wetlands Ecology and Management (2006) 14:409–419
DOI 10.1007/s11273-005-6243-z
-1
Development of allometric relations for three mangrove species in South
Florida for use in the Greater Everglades Ecosystem restoration
Thomas J. Smith III1,* and Kevin R.T. Whelan2,3
1
U.S. Geological Survey, Florida Integrated Science Center, 600 Fourth Street South, St. Petersburg, 33701
Florida, USA; 2U.S. Geological Survey, Florida Integrated Science Center, c/o Department of Biological
Sciences, Florida International University, OE Bldg - Rm 167, Miami, 33199 Florida, USA; 3South Florida/
Caribbean Inventory and Monitoring Network Office, U.S. National Park Service, 18001 Old Cutler Road,
Suite 419, Palmetto Bay, 33157 Florida, USA; *Author for correspondence (e-mail: Tom_J_Smith@usgs.gov;
phone: +727-803-8747; fax: +727-803-2030)
Received 2 June 2005; accepted in revised form 21 December 2005
Key words: Biogeographic comparison, Biomass, Diameter, Height, Power law, Restoration, Scaling
relation
Abstract
Mathematical relations that use easily measured variables to predict difficult-to-measure variables are
important to resource managers. In this paper we develop allometric relations to predict total aboveground
biomass and individual components of biomass (e.g., leaves, stems, branches) for three species of man-
groves for Everglades National Park, Florida, USA. The Greater Everglades Ecosystem is currently the
subject of a 7.8-billion-dollar restoration program sponsored by federal, state, and local agencies. Biomass
and production of mangroves are being used as a measure of restoration success. A technique for rapid
determination of biomass over large areas is required. We felled 32 mangrove trees and separated each
plant into leaves, stems, branches, and for Rhizophora mangle L., prop roots. Wet weights were measured in
the field and subsamples returned to the laboratory for determination of wet-to-dry weight conversion
factors. The diameter at breast height (DBH) and stem height were also measured. Allometric equations
were developed for each species for total biomass and components of biomass. We compared our equations
with those from the same, or similar, species from elsewhere in the world. Our equations explained ‡93% of
the variance in total dry weight using DBH. DBH is a better predictor of dry weight than is stem height and
DBH is much easier to measure. Furthermore, our results indicate that there are biogeographic differences
in allometric relations between regions. For a given DBH, stems of all three species have less mass in
Florida than stems from elsewhere in the world.
Abbreviations: DBH – diameter at breast height
Florida Bay and the Florida Keys in the south and
Introduction
is over 150 km from east to west in places. The
The Greater Everglades Ecosystem extends for vast freshwater wetlands of the region have been
350 km from Lake Tohopekaliga in the north to extensively ditched, diked, and drained for
410
agricultural development (Bottcher and Izuno an estimate of the biomass for both living and
1994), urban water supply, and flood protection dead plants. With a calculated biomass figure it is
(Light and Dineen 1994). The greatly altered possible to determine a change in biomass from
drainage patterns have led to a decrease in fresh- one time to another based on change in DBH.
water inflow to the southern Everglades estuaries When summed for all individuals and for each
of more than 50% (Smith et al. 1989). Questions species within a known area, biomass and pro-
exist concerning the impacts of increasing fresh- ductivity can be expressed on an areal basis.
water inflows to coastal wetlands. Scaling relations have been used to estimate forest
At present, the Greater Everglades is the site of biomass and productivity in temperate regions
a massive ecosystem restoration program, the (Rochow 1974; Whittaker and Marks 1975) and
Comprehensive Everglades Restoration Project tropical regions Day et al. 1987; Clough and Scott
(CERP) (Davis and Ogden 1994; Porter and Porter 1989).
2002). Numerous water-control structures will be Several researchers have developed relations to
removed, canals filled, and dikes leveled, all to predict aboveground biomass using DBH for
restore the quantity and quality of water in the mangroves from a variety of areas (Woodroffe
system. 1985; Putz and Chan 1986; Clough and Scott 1989;
Mangrove forests dominate the coastal portion Silva et al. 1991; Fromard et al. 1998). However,
of the Everglades within Everglades National no allometric equations have been developed for
Park, an International Biosphere Preserve (Smith mangroves in Florida an area at the northern limit
et al. 1994). What will be the effect on primary of their distribution which is 25° N latitude.
production or species composition in mangrove Standing biomass as well as litterfall in mangroves
forests as freshwater flow is altered? As CERP decreases as latitude increases, as demonstrated by
progresses resource managers need simple but Saenger and Snedaker (1993).
accurate tools to measure restoration success. We The purpose of this work was to develop allo-
discuss the development of a simple tool for the metric relations for above ground biomass and
rapid measurement of biomass and change in DBH for the three mangrove species found in
biomass over time using allometric, or scaling, Everglades National Park: Avicennia germinans
relations. (L.) Sterns (black mangrove), Laguncularia race-
Scaling relations are fundamental in ecological mosa (L.) Gaertn. (white mangrove) and Rhizo-
studies from the level of the individual organism to phora mangle L. (red mangrove). We also tested
the examination of patch structure across land- for relations between DBH and different compo-
scapes (Horn 1971; Niklas 1994). In forest ecology nents of total biomass (leaves, stems, and bran-
these relations have been used to examine how an ches) for each species. Finally, we compared our
individual tree’s crown architecture changes dur- allometric equations with those developed for the
ing growth from seedling to sapling to adult stat- same, or similar, species from other regions of the
ure (Aiba and Kohyama 1997), how life history globe.
traits and tree structure vary among species
(Whittaker and Woodwell 1968; Coomes and
Grubb 1998) and to explain density-dependant
Methods
and gap-dynamic processes in whole forest stands
(Alvarez-Buylla 1994). Allometric relations
Nomenclature
‘‘characterize harmonious growth with changing
proportions’’ usually with a logarithmic associa-
The nomenclature for mangrove names follows
tion (Lieth and Whittaker 1975). They are devel-
Tomlinson (1986).
oped by establishing relations between some easily
measured individual plant parameter(s) and some
variable that is much harder to measure. For trees,
Site descriptions
the diameter at breast height (DBH) of the trunk is
commonly used, allowing for non-destructive
Individuals of the three mangrove species were
assessment of biomass and growth rates. Once
collected from three locations in Everglades
developed, the equation can be used to calculate
411
National Park (Figure 1): the Black Forest Sample collection and processing
(25°08¢54¢¢ N, 80°55¢00¢¢ W); Mud Bay
We collected 32 specimens of the three mangrove
(25°16¢08¢¢ N, 81°05¢02¢¢ W); and Highland Beach
species: 8 black, 10 white, and 14 red. We choose
(25°30¢0¢¢, 81°12¢0¢¢ W). Historically, the Black
Forest was dominated by large Avicennia that were individuals with straight trunks that showed no
obvious signs of damage (hurricane, lightning,
devastated by the Labor Day hurricane of 1935
wind, or insect damage). We did not choose
(Craighead 1971). Currently, the site is a mixed
stunted, dwarfed, or multi-stemmed specimens
stand with all three species present in various size
because they have extremely different allometric
classes. The Mud Bay location is a well-developed
relations (Clough et al. 1997). Such individuals
stand of red and black mangroves with many
were rare in our study area. After an individual
stems in larger DBH classes. Hurricane Andrew
was selected its DBH was measured at 1.4 m above
crossed directly over the Highland Beach site in
August 1992 (Smith et al. 1994). Although this site the sediment surface or above the highest prop
root for Rhizophora (a commonly accepted pro-
had been disturbed, recovery was underway and
cedure, see Clough and Scott 1989). Each speci-
numerous small-stemmed individuals of all three
men was cut at ground level and total stem height
species were readily available for sampling.
Figure 1. The southern peninsula of Florida showing the approximate boundaries of Everglades National Park (ENP). We collected
samples from the Black Forest (BF), Mud Bay (MB), and Highland Beach (HB).
412
was measured. All above-ground biomass was Using the equations to assess the Everglades
harvested and separated into four components: restoration
stem, branches, leaves, and prop roots (Rhizophora
As CERP proceeds one of the expected impacts is
only). We measured these components in the field
using a spring scale of appropriate size to get wet- altered salinity regimes in the lower Shark River
estuary. Growth rate and biomass accumulation in
weight biomass. We collected sub-samples of each
mangroves is at least partially related to sediment
component from each tree. These were returned to
pore-water salinity (Sobrado 1999; Tuffers et al.
the laboratory and dried to a constant mass at
70 °C using a standard drying oven and re- 2001). We used the allometric equations to derive
biomass estimates for several long-term plots
weighed. Wet-weight to dry-weight conversion
along the Harney River (Smith 2004). The plots
factors were calculated and averaged by compo-
were established in 1998. Stems were identified and
nent and by species. With this information we
calculated an estimate of dry weight. individually tagged with aluminum tree tags. DBH
was measured as described above. The plots have
been re-sampled four times. We calculated the
total biomass of each stem from the species specific
Calculations
regression equation. Growth was calculated as the
We used the equation: log10 y ¼ a log10 ðDBHÞ þ b change in total biomass between sampling inter-
vals. Individual growth estimates were summed for
to relate dry biomass to DBH (where y = above-
ground dry biomass in kg and DBH is in cm). each plot by species and by time interval. Sediment
Similar equations have been used by other pore-water salinity was also measured in the plots
at a depth of 30 cm which is in the middle of the
researchers (Putz and Chan 1986; Day et al. 1987;
root zone. We calculated the mean salinity for
Clough and Scott 1989; Fromard et al. 1998). We
each sampling interval for each plot. We then re-
also examined the relations of stem height to bio-
gressed the change in biomass, for each species,
mass using the same equation (Whittaker and
plot, and sampling interval against mean salinity.
Marks 1975; Clough 1992). For each species sep-
arate regressions were calculated for each compo-
nent of biomass (stem, branch, and leaf for all
species and also prop-roots for Rhizophora) using Results and discussion
the Statistical Analysis System software package.
Total biomass was determined by summing the Biomass vs. stem height and DBH
individual components for each species and then
Both stem height and DBH were excellent pre-
another regression was performed.
dictors of total above-ground biomass for all three
species (Figures 2, 3) with total variance explained
(R2) greater than 0.92 in all cases (Table 1). DBH
Biogeographic comparisons
yielded R2s that were slightly higher than those for
stem height. However, we consider the difference
We compared our allometric equations for Avi-
to be insignificant. The best fits were higher for
cennia and Laguncularia with those generated by
Laguncularia than for either Avicennia or Rhizo-
Fromard et al. (1998) at 4–5° N latitude and by
phora. Given these results, and the fact that DBH
Day et al. (1987) at 18° N. We included the
is measured very accurately and with great ease in
equations of Silva et al. (1991) from 23° S for
the field, whereas stem height is very difficult to
comparisons with R. mangle. We also compared R.
measure non-destructively, we consider only DBH
mangle with Rhizophora species (R. apiculata, R.
for the remainder of the study.
mucronata, R. stylosa) from the Indo-West Pacific
region (Putz and Chan 1986; Clough and Scott
1989). Our comparisons spanned only the range of
DBHs reported in other studies. We did not Stem, branch, leaf, and prop root biomass vs. DBH
extrapolate predicted values from reported equa-
Highly significant relationships were found for
tions past the data ranges over which they had
all components of above-ground biomass and
been calculated.
413
DBH for all three species. In general, regressions allocate more biomass to branches than either
for stem biomass had higher variance explained Avicennia or Laguncularia over the entire range
(R2s ‡ 0.95) than did regressions for branch and of DBHs measured (Figure 5). Rhizophora also
leaf biomass (Table 1 and Figures 4–6). The seems to allocate more biomass to leaf tissue
latter two components of biomass were much than Avicennia and Laguncularia, but only at
more variable. No differences were found among larger DBHs (Figure 6). For Rhizophora, prop
species with respect to total stem biomass and root biomass was significantly related to DBH
DBH (Figure 4). However, Rhizophora seems to (Figure 7).
Total Dry Biomass vs DBH
2.50
2.00
Log10 Total Biomass
1.50
1.00
0.50
0.00
-0.50
-1.00
-1.50
-0.50 -0.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50
Log10 dbh
Figure 2. Total dry biomass as a function of DBH for the three mangrove species. Avicennia = diamonds with solid line, Laguncu-
laria = squares with dotted line, and Rhizophora = triangles with dashed line.
Total Dry Biomass vs Height
2.50
2.00
1.50
Log10 Total Biomass
1.00
0.50
0.00
-0.50
-1.00
-1.50
0.00 0.25 0.50 0.75 1.00 1.25 1.50
Log10 stem height
Figure 3. Total dry biomass as a function of stem height for the three mangrove species. Symbols as in Figure 2.
414
Table 1. Results from the regression analyses are given. Biogeographic comparisons
R2
Regression Parameters a b
Our equations give the lowest estimate of biomass
Total Dry Biomass vs. height for all three species when compared to results from
À1.124
2.641 0.921
Avicennia
other studies (Table 2, see our Figures 8–10 for
À1.355
2.585 0.973
Laguncularia
references). A mangrove with a given DBH will
À0.769
2.357 0.931
Rhizophora
have a greater predicted biomass near the equator
Total Dry Biomass vs. DBH
than one with the same DBH that is growing in a
À0.395
1.934 0.951
Avicennia
À0.441
1.930 0.977
Laguncularia location to the north or south of the equator. The
À0.112
1.731 0.937
Rhizophora
differences are least for Laguncularia and greatest
Stem Dry Biomass vs. DBH
for Rhizophora. For example, Laguncularia with a
À0.590
2.062 0.982
Avicennia
DBH 10 cm is predicted to have 60 kg dry mass in
À0.692
2.087 0.981
Laguncularia
French Guiana (Fromard et al. 1998), 50 kg dry
À0.510
1.884 0.958
Rhizophora
Branch Dry Biomass vs. DBH mass in the Yucatan of Mexico (Day et al. 1987),
À1.090
1.607 0.773
Avicennia
and 45 kg dry mass in the Florida Everglades (the
À1.282
1.837 0.951
Laguncularia
present study, see Figure 8). Unfortunately the
À0.853
1.784 0.958
Rhizophora
studies by Fromard et al. (1998) and Day et al.
Leaf Dry Biomass vs. DBH
(1987) spanned a small range in DBH (1–10 cm).
À0.855
0.985 0.714
Avicennia
À1.043
1.160 0.889
Laguncularia Therefore we could not compare to the largest
À0.843
1.337 0.927
Rhizophora
Laguncularia trees we sampled (18 cm). For Avi-
Prop Root Dry Biomass
cennia, specimens 10 cm DBH are predicted to be
À1.041
0.160 0.821
Rhizophora
equal in biomass for French Guiana and Florida
Parameters: a=slope of the regression line, b=intercept of the (%35 kg), and both of these areas will be less than
regression line, R2=coefficient of determination. All regression
predicted for Mexico (67.5 kg, see Figure 9). As
equations are significant at the p .05 level. DBH size ranges,
DBH increases for Avicennia, the predicted bio-
in cm, were: Avicennia (0.7–21.5), Laguncularia (0.5–18.0), and
mass for French Guiana and Florida also diverge
Rhizophora (0.5–20.0).
(Figure 9). At a DBH of 20 cm, Avicennia in
Stem Biomass vs DBH
2.50
2.00
1.50
Log10 Stem Biomass
1.00
0.50
0.00
-0.50
-1.00
-1.50
-0.50 -0.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50
Log10 dbh
Figure 4. Stem dry biomass as a function of DBH for three mangrove species. Symbols as in Figure 2.
415
Branch Biomass vs DBH
2.00
1.50
Log10 Branch Biomass
1.00
0.50
0.00
-0.50
-1.00
-1.50
-2.00
-0.50 -0.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50
Log10 dbh
Figure 5. Branch dry biomass as a function of DBH for three Florida mangrove species. Symbols as in Figure 2.
Leaf Biomass vs DBH
1.00
0.50
Log10 Leaf Biomass
0.00
-0.50
-1.00
-1.50
-0.50 -0.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50
Log10 dbh
Figure 6. Leaf dry biomass as a function of DBH. Symbols as in Figure 2.
French Guiana are predicted to weigh some researchers so comparisons are limited to French
246 kg, whereas in Florida the same size stem is Guiana, Florida, Australia and Malaysia. A Rhi-
predicted to weigh a mere 136 kg (Figure 9). The zophora in Florida with a 20 cm DBH stem is
predicted to have approximately %140 kg of
differences are most striking however for Rhizo-
phora (Figure 10). At smaller size classes (<10 cm above-ground dry biomass (this study). Rhizo-
DBH) differences are indicated with stems in phora from northern Australia, French Guiana
Australia, Malaysia, French Guiana and Puerto and Malaysia are predicted to have from 300–
Rico predicted to have more biomass than stems in 350 kg of dry biomass (Figure 10).
Florida, Mexico or Brazil (Figure 10). Larger The general outcome of the model comparisons is
stems (>15 cm DBH) were not measured by many that allometric relations differ by species and region
416
Rhizophora prop roots
2.0
1.5
Log10 dry mass
1.0
0.5
0.0
-0.5
-1.0
-1.5
-2.0
-0.50 -0.30 -0.10 0.10 0.30 0.50 0.70 0.90 1.10 1.30 1.50
log10 dbh
Figure 7. Rhizophora prop root biomass as a function of DBH.
Table 2. Regression equations developed by other studies.
Species DBH Range cm Equation Reference
a b
Atlantic/Caribbean
À1.561
1–10 logey = a logeDBH+b 2.507 Day et al. (1987)
A. germinans
À1.592
1–10 logey = a logeDBH+b 2.192 Day et al. (1987)
L. racemosa
À1.580
1–10 logey = a logeDBH+b 2.302 Day et al. (1987)
R. mangle
y = b (DBH)a
1–32 2.4 0.140 Fromard et al. (1998)
A. germinans
y = b (DBH)a
1–10 2.5 0.102 Fromard et al. (1998)
L. racemosa
y = b (DBH)a
1–42 2.6 0.128 Fromard et al. (1998)
R. mangle
y = b ea(DBH)
3–11 0.3 1.41 Silva et al. (1991)
R. mangle
Indo-West Pacific
À0.767
5–31 log10y = alog10DBH + b 2.516 Putz and Chan (1986)
R. apiculata
À0.979
Rhizophora spp. 3–25 log10y = alog10DBH + b 2.685 Clough and Scott (1989)
Laguncularia racemosa
THIS STUDY Day Fromard
150
Predicted Dry Biomass
100
50
0
5 10 15 20
Diameter at Breast Height
Figure 8. Predicted total biomass for Laguncularia racemosa based on the allometric equations from Day et al. (1987) as shown by
dashed line, from Fromard et al. (1998) as shown by dotted line, and by this study as shown by solid line. Predicted values have been
calculated and plotted only for the range in DBHs reported by each study.
417
Avicennia germinans
THIS STUDY Day Fromard
350
300
Predicted Dry Biomass
250
200
150
100
50
0
5 10 15 20 25
Diameter at Breast Height
Figure 9. Predicted total biomass for Avicennia germinans based on the allometric equations from Day et al. (1987) as shown by dashes
line, from Fromard et al. (1998)as shown by dotted line, and by this study as shown by solid line. Predicted values have been calculated
and plotted only for the range in DBHs reported by each study.
Rhizophora species
THIS STUDY Golley Silva Day Fromard Clough Putz
350
300
Predicted Dry Biomass
250
200
150
100
50
0
5 10 15 20
Diameter at Breast Height
Figure 10. Predicted total biomass for Rhizophora spp. based on the allometric equations from this study and other studies as shown in
the legend.
and do not necessarily follow latitudinal or general Using the equations to assess the Everglades resto-
area trends. The biomass values generated with ration
allometric equations should be considered with
Mean sediment salinity predicted change in bio-
caution when used to extrapolate outside of the size
mass relatively well for Laguncularia but not for
range sampled or from areas with inherently dif-
Rhizophora or Avicennia (Figure 11). This is not
ferent environmental parameters (for example,
totally unexpected as Laguncularia is the least
salinity, nutrients, hydrological exchange, stem
tolerant species. Both Avicennia and Rhizophora
density, net primary productivity, and herbivory).
418
Harney River Transect Plots
50
Change in Biomass
25
0
-25
-50
10 20 30
Mean Salinity
Figure 11. Change in biomass as a function of mean sediment porewater salinity for plots along the Harney River in Everglades
National Park. The regression equations for Avicennia (squares) and Rhizophora (diamonds) are not significant. The regression for
Laguncularia is significant. The regression equation is: Change in biomass = À1.691*(mean salinity) + 26.905, r2 = 0.38, p < 0.01.
have broad salinity tolerances with Avicennia References
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Chicago, IL, USA. grove, Avicennia marina. Wetlands Ecol. Manage. 9: 225–232.
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Wetlands Ecology and Management (2006) 14:409–419
DOI 10.1007/s11273-005-6243-z
-1
Development of allometric relations for three mangrove species in South
Florida for use in the Greater Everglades Ecosystem restoration
Thomas J. Smith III1,* and Kevin R.T. Whelan2,3
1
U.S. Geological Survey, Florida Integrated Science Center, 600 Fourth Street South, St. Petersburg, 33701
Florida, USA; 2U.S. Geological Survey, Florida Integrated Science Center, c/o Department of Biological
Sciences, Florida International University, OE Bldg - Rm 167, Miami, 33199 Florida, USA; 3South Florida/
Caribbean Inventory and Monitoring Network Office, U.S. National Park Service, 18001 Old Cutler Road,
Suite 419, Palmetto Bay, 33157 Florida, USA; *Author for correspondence (e-mail: Tom_J_Smith@usgs.gov;
phone: +727-803-8747; fax: +727-803-2030)
Received 2 June 2005; accepted in revised form 21 December 2005
Key words: Biogeographic comparison, Biomass, Diameter, Height, Power law, Restoration, Scaling
relation
Abstract
Mathematical relations that use easily measured variables to predict difficult-to-measure variables are
important to resource managers. In this paper we develop allometric relations to predict total aboveground
biomass and individual components of biomass (e.g., leaves, stems, branches) for three species of man-
groves for Everglades National Park, Florida, USA. The Greater Everglades Ecosystem is currently the
subject of a 7.8-billion-dollar restoration program sponsored by federal, state, and local agencies. Biomass
and production of mangroves are being used as a measure of restoration success. A technique for rapid
determination of biomass over large areas is required. We felled 32 mangrove trees and separated each
plant into leaves, stems, branches, and for Rhizophora mangle L., prop roots. Wet weights were measured in
the field and subsamples returned to the laboratory for determination of wet-to-dry weight conversion
factors. The diameter at breast height (DBH) and stem height were also measured. Allometric equations
were developed for each species for total biomass and components of biomass. We compared our equations
with those from the same, or similar, species from elsewhere in the world. Our equations explained ‡93% of
the variance in total dry weight using DBH. DBH is a better predictor of dry weight than is stem height and
DBH is much easier to measure. Furthermore, our results indicate that there are biogeographic differences
in allometric relations between regions. For a given DBH, stems of all three species have less mass in
Florida than stems from elsewhere in the world.
Abbreviations: DBH – diameter at breast height
Florida Bay and the Florida Keys in the south and
Introduction
is over 150 km from east to west in places. The
The Greater Everglades Ecosystem extends for vast freshwater wetlands of the region have been
350 km from Lake Tohopekaliga in the north to extensively ditched, diked, and drained for
410
agricultural development (Bottcher and Izuno an estimate of the biomass for both living and
1994), urban water supply, and flood protection dead plants. With a calculated biomass figure it is
(Light and Dineen 1994). The greatly altered possible to determine a change in biomass from
drainage patterns have led to a decrease in fresh- one time to another based on change in DBH.
water inflow to the southern Everglades estuaries When summed for all individuals and for each
of more than 50% (Smith et al. 1989). Questions species within a known area, biomass and pro-
exist concerning the impacts of increasing fresh- ductivity can be expressed on an areal basis.
water inflows to coastal wetlands. Scaling relations have been used to estimate forest
At present, the Greater Everglades is the site of biomass and productivity in temperate regions
a massive ecosystem restoration program, the (Rochow 1974; Whittaker and Marks 1975) and
Comprehensive Everglades Restoration Project tropical regions Day et al. 1987; Clough and Scott
(CERP) (Davis and Ogden 1994; Porter and Porter 1989).
2002). Numerous water-control structures will be Several researchers have developed relations to
removed, canals filled, and dikes leveled, all to predict aboveground biomass using DBH for
restore the quantity and quality of water in the mangroves from a variety of areas (Woodroffe
system. 1985; Putz and Chan 1986; Clough and Scott 1989;
Mangrove forests dominate the coastal portion Silva et al. 1991; Fromard et al. 1998). However,
of the Everglades within Everglades National no allometric equations have been developed for
Park, an International Biosphere Preserve (Smith mangroves in Florida an area at the northern limit
et al. 1994). What will be the effect on primary of their distribution which is 25° N latitude.
production or species composition in mangrove Standing biomass as well as litterfall in mangroves
forests as freshwater flow is altered? As CERP decreases as latitude increases, as demonstrated by
progresses resource managers need simple but Saenger and Snedaker (1993).
accurate tools to measure restoration success. We The purpose of this work was to develop allo-
discuss the development of a simple tool for the metric relations for above ground biomass and
rapid measurement of biomass and change in DBH for the three mangrove species found in
biomass over time using allometric, or scaling, Everglades National Park: Avicennia germinans
relations. (L.) Sterns (black mangrove), Laguncularia race-
Scaling relations are fundamental in ecological mosa (L.) Gaertn. (white mangrove) and Rhizo-
studies from the level of the individual organism to phora mangle L. (red mangrove). We also tested
the examination of patch structure across land- for relations between DBH and different compo-
scapes (Horn 1971; Niklas 1994). In forest ecology nents of total biomass (leaves, stems, and bran-
these relations have been used to examine how an ches) for each species. Finally, we compared our
individual tree’s crown architecture changes dur- allometric equations with those developed for the
ing growth from seedling to sapling to adult stat- same, or similar, species from other regions of the
ure (Aiba and Kohyama 1997), how life history globe.
traits and tree structure vary among species
(Whittaker and Woodwell 1968; Coomes and
Grubb 1998) and to explain density-dependant
Methods
and gap-dynamic processes in whole forest stands
(Alvarez-Buylla 1994). Allometric relations
Nomenclature
‘‘characterize harmonious growth with changing
proportions’’ usually with a logarithmic associa-
The nomenclature for mangrove names follows
tion (Lieth and Whittaker 1975). They are devel-
Tomlinson (1986).
oped by establishing relations between some easily
measured individual plant parameter(s) and some
variable that is much harder to measure. For trees,
Site descriptions
the diameter at breast height (DBH) of the trunk is
commonly used, allowing for non-destructive
Individuals of the three mangrove species were
assessment of biomass and growth rates. Once
collected from three locations in Everglades
developed, the equation can be used to calculate
411
National Park (Figure 1): the Black Forest Sample collection and processing
(25°08¢54¢¢ N, 80°55¢00¢¢ W); Mud Bay
We collected 32 specimens of the three mangrove
(25°16¢08¢¢ N, 81°05¢02¢¢ W); and Highland Beach
species: 8 black, 10 white, and 14 red. We choose
(25°30¢0¢¢, 81°12¢0¢¢ W). Historically, the Black
Forest was dominated by large Avicennia that were individuals with straight trunks that showed no
obvious signs of damage (hurricane, lightning,
devastated by the Labor Day hurricane of 1935
wind, or insect damage). We did not choose
(Craighead 1971). Currently, the site is a mixed
stunted, dwarfed, or multi-stemmed specimens
stand with all three species present in various size
because they have extremely different allometric
classes. The Mud Bay location is a well-developed
relations (Clough et al. 1997). Such individuals
stand of red and black mangroves with many
were rare in our study area. After an individual
stems in larger DBH classes. Hurricane Andrew
was selected its DBH was measured at 1.4 m above
crossed directly over the Highland Beach site in
August 1992 (Smith et al. 1994). Although this site the sediment surface or above the highest prop
root for Rhizophora (a commonly accepted pro-
had been disturbed, recovery was underway and
cedure, see Clough and Scott 1989). Each speci-
numerous small-stemmed individuals of all three
men was cut at ground level and total stem height
species were readily available for sampling.
Figure 1. The southern peninsula of Florida showing the approximate boundaries of Everglades National Park (ENP). We collected
samples from the Black Forest (BF), Mud Bay (MB), and Highland Beach (HB).
412
was measured. All above-ground biomass was Using the equations to assess the Everglades
harvested and separated into four components: restoration
stem, branches, leaves, and prop roots (Rhizophora
As CERP proceeds one of the expected impacts is
only). We measured these components in the field
using a spring scale of appropriate size to get wet- altered salinity regimes in the lower Shark River
estuary. Growth rate and biomass accumulation in
weight biomass. We collected sub-samples of each
mangroves is at least partially related to sediment
component from each tree. These were returned to
pore-water salinity (Sobrado 1999; Tuffers et al.
the laboratory and dried to a constant mass at
70 °C using a standard drying oven and re- 2001). We used the allometric equations to derive
biomass estimates for several long-term plots
weighed. Wet-weight to dry-weight conversion
along the Harney River (Smith 2004). The plots
factors were calculated and averaged by compo-
were established in 1998. Stems were identified and
nent and by species. With this information we
calculated an estimate of dry weight. individually tagged with aluminum tree tags. DBH
was measured as described above. The plots have
been re-sampled four times. We calculated the
total biomass of each stem from the species specific
Calculations
regression equation. Growth was calculated as the
We used the equation: log10 y ¼ a log10 ðDBHÞ þ b change in total biomass between sampling inter-
vals. Individual growth estimates were summed for
to relate dry biomass to DBH (where y = above-
ground dry biomass in kg and DBH is in cm). each plot by species and by time interval. Sediment
Similar equations have been used by other pore-water salinity was also measured in the plots
at a depth of 30 cm which is in the middle of the
researchers (Putz and Chan 1986; Day et al. 1987;
root zone. We calculated the mean salinity for
Clough and Scott 1989; Fromard et al. 1998). We
each sampling interval for each plot. We then re-
also examined the relations of stem height to bio-
gressed the change in biomass, for each species,
mass using the same equation (Whittaker and
plot, and sampling interval against mean salinity.
Marks 1975; Clough 1992). For each species sep-
arate regressions were calculated for each compo-
nent of biomass (stem, branch, and leaf for all
species and also prop-roots for Rhizophora) using Results and discussion
the Statistical Analysis System software package.
Total biomass was determined by summing the Biomass vs. stem height and DBH
individual components for each species and then
Both stem height and DBH were excellent pre-
another regression was performed.
dictors of total above-ground biomass for all three
species (Figures 2, 3) with total variance explained
(R2) greater than 0.92 in all cases (Table 1). DBH
Biogeographic comparisons
yielded R2s that were slightly higher than those for
stem height. However, we consider the difference
We compared our allometric equations for Avi-
to be insignificant. The best fits were higher for
cennia and Laguncularia with those generated by
Laguncularia than for either Avicennia or Rhizo-
Fromard et al. (1998) at 4–5° N latitude and by
phora. Given these results, and the fact that DBH
Day et al. (1987) at 18° N. We included the
is measured very accurately and with great ease in
equations of Silva et al. (1991) from 23° S for
the field, whereas stem height is very difficult to
comparisons with R. mangle. We also compared R.
measure non-destructively, we consider only DBH
mangle with Rhizophora species (R. apiculata, R.
for the remainder of the study.
mucronata, R. stylosa) from the Indo-West Pacific
region (Putz and Chan 1986; Clough and Scott
1989). Our comparisons spanned only the range of
DBHs reported in other studies. We did not Stem, branch, leaf, and prop root biomass vs. DBH
extrapolate predicted values from reported equa-
Highly significant relationships were found for
tions past the data ranges over which they had
all components of above-ground biomass and
been calculated.
413
DBH for all three species. In general, regressions allocate more biomass to branches than either
for stem biomass had higher variance explained Avicennia or Laguncularia over the entire range
(R2s ‡ 0.95) than did regressions for branch and of DBHs measured (Figure 5). Rhizophora also
leaf biomass (Table 1 and Figures 4–6). The seems to allocate more biomass to leaf tissue
latter two components of biomass were much than Avicennia and Laguncularia, but only at
more variable. No differences were found among larger DBHs (Figure 6). For Rhizophora, prop
species with respect to total stem biomass and root biomass was significantly related to DBH
DBH (Figure 4). However, Rhizophora seems to (Figure 7).
Total Dry Biomass vs DBH
2.50
2.00
Log10 Total Biomass
1.50
1.00
0.50
0.00
-0.50
-1.00
-1.50
-0.50 -0.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50
Log10 dbh
Figure 2. Total dry biomass as a function of DBH for the three mangrove species. Avicennia = diamonds with solid line, Laguncu-
laria = squares with dotted line, and Rhizophora = triangles with dashed line.
Total Dry Biomass vs Height
2.50
2.00
1.50
Log10 Total Biomass
1.00
0.50
0.00
-0.50
-1.00
-1.50
0.00 0.25 0.50 0.75 1.00 1.25 1.50
Log10 stem height
Figure 3. Total dry biomass as a function of stem height for the three mangrove species. Symbols as in Figure 2.
414
Table 1. Results from the regression analyses are given. Biogeographic comparisons
R2
Regression Parameters a b
Our equations give the lowest estimate of biomass
Total Dry Biomass vs. height for all three species when compared to results from
À1.124
2.641 0.921
Avicennia
other studies (Table 2, see our Figures 8–10 for
À1.355
2.585 0.973
Laguncularia
references). A mangrove with a given DBH will
À0.769
2.357 0.931
Rhizophora
have a greater predicted biomass near the equator
Total Dry Biomass vs. DBH
than one with the same DBH that is growing in a
À0.395
1.934 0.951
Avicennia
À0.441
1.930 0.977
Laguncularia location to the north or south of the equator. The
À0.112
1.731 0.937
Rhizophora
differences are least for Laguncularia and greatest
Stem Dry Biomass vs. DBH
for Rhizophora. For example, Laguncularia with a
À0.590
2.062 0.982
Avicennia
DBH 10 cm is predicted to have 60 kg dry mass in
À0.692
2.087 0.981
Laguncularia
French Guiana (Fromard et al. 1998), 50 kg dry
À0.510
1.884 0.958
Rhizophora
Branch Dry Biomass vs. DBH mass in the Yucatan of Mexico (Day et al. 1987),
À1.090
1.607 0.773
Avicennia
and 45 kg dry mass in the Florida Everglades (the
À1.282
1.837 0.951
Laguncularia
present study, see Figure 8). Unfortunately the
À0.853
1.784 0.958
Rhizophora
studies by Fromard et al. (1998) and Day et al.
Leaf Dry Biomass vs. DBH
(1987) spanned a small range in DBH (1–10 cm).
À0.855
0.985 0.714
Avicennia
À1.043
1.160 0.889
Laguncularia Therefore we could not compare to the largest
À0.843
1.337 0.927
Rhizophora
Laguncularia trees we sampled (18 cm). For Avi-
Prop Root Dry Biomass
cennia, specimens 10 cm DBH are predicted to be
À1.041
0.160 0.821
Rhizophora
equal in biomass for French Guiana and Florida
Parameters: a=slope of the regression line, b=intercept of the (%35 kg), and both of these areas will be less than
regression line, R2=coefficient of determination. All regression
predicted for Mexico (67.5 kg, see Figure 9). As
equations are significant at the p .05 level. DBH size ranges,
DBH increases for Avicennia, the predicted bio-
in cm, were: Avicennia (0.7–21.5), Laguncularia (0.5–18.0), and
mass for French Guiana and Florida also diverge
Rhizophora (0.5–20.0).
(Figure 9). At a DBH of 20 cm, Avicennia in
Stem Biomass vs DBH
2.50
2.00
1.50
Log10 Stem Biomass
1.00
0.50
0.00
-0.50
-1.00
-1.50
-0.50 -0.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50
Log10 dbh
Figure 4. Stem dry biomass as a function of DBH for three mangrove species. Symbols as in Figure 2.
415
Branch Biomass vs DBH
2.00
1.50
Log10 Branch Biomass
1.00
0.50
0.00
-0.50
-1.00
-1.50
-2.00
-0.50 -0.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50
Log10 dbh
Figure 5. Branch dry biomass as a function of DBH for three Florida mangrove species. Symbols as in Figure 2.
Leaf Biomass vs DBH
1.00
0.50
Log10 Leaf Biomass
0.00
-0.50
-1.00
-1.50
-0.50 -0.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50
Log10 dbh
Figure 6. Leaf dry biomass as a function of DBH. Symbols as in Figure 2.
French Guiana are predicted to weigh some researchers so comparisons are limited to French
246 kg, whereas in Florida the same size stem is Guiana, Florida, Australia and Malaysia. A Rhi-
predicted to weigh a mere 136 kg (Figure 9). The zophora in Florida with a 20 cm DBH stem is
predicted to have approximately %140 kg of
differences are most striking however for Rhizo-
phora (Figure 10). At smaller size classes (<10 cm above-ground dry biomass (this study). Rhizo-
DBH) differences are indicated with stems in phora from northern Australia, French Guiana
Australia, Malaysia, French Guiana and Puerto and Malaysia are predicted to have from 300–
Rico predicted to have more biomass than stems in 350 kg of dry biomass (Figure 10).
Florida, Mexico or Brazil (Figure 10). Larger The general outcome of the model comparisons is
stems (>15 cm DBH) were not measured by many that allometric relations differ by species and region
416
Rhizophora prop roots
2.0
1.5
Log10 dry mass
1.0
0.5
0.0
-0.5
-1.0
-1.5
-2.0
-0.50 -0.30 -0.10 0.10 0.30 0.50 0.70 0.90 1.10 1.30 1.50
log10 dbh
Figure 7. Rhizophora prop root biomass as a function of DBH.
Table 2. Regression equations developed by other studies.
Species DBH Range cm Equation Reference
a b
Atlantic/Caribbean
À1.561
1–10 logey = a logeDBH+b 2.507 Day et al. (1987)
A. germinans
À1.592
1–10 logey = a logeDBH+b 2.192 Day et al. (1987)
L. racemosa
À1.580
1–10 logey = a logeDBH+b 2.302 Day et al. (1987)
R. mangle
y = b (DBH)a
1–32 2.4 0.140 Fromard et al. (1998)
A. germinans
y = b (DBH)a
1–10 2.5 0.102 Fromard et al. (1998)
L. racemosa
y = b (DBH)a
1–42 2.6 0.128 Fromard et al. (1998)
R. mangle
y = b ea(DBH)
3–11 0.3 1.41 Silva et al. (1991)
R. mangle
Indo-West Pacific
À0.767
5–31 log10y = alog10DBH + b 2.516 Putz and Chan (1986)
R. apiculata
À0.979
Rhizophora spp. 3–25 log10y = alog10DBH + b 2.685 Clough and Scott (1989)
Laguncularia racemosa
THIS STUDY Day Fromard
150
Predicted Dry Biomass
100
50
0
5 10 15 20
Diameter at Breast Height
Figure 8. Predicted total biomass for Laguncularia racemosa based on the allometric equations from Day et al. (1987) as shown by
dashed line, from Fromard et al. (1998) as shown by dotted line, and by this study as shown by solid line. Predicted values have been
calculated and plotted only for the range in DBHs reported by each study.
417
Avicennia germinans
THIS STUDY Day Fromard
350
300
Predicted Dry Biomass
250
200
150
100
50
0
5 10 15 20 25
Diameter at Breast Height
Figure 9. Predicted total biomass for Avicennia germinans based on the allometric equations from Day et al. (1987) as shown by dashes
line, from Fromard et al. (1998)as shown by dotted line, and by this study as shown by solid line. Predicted values have been calculated
and plotted only for the range in DBHs reported by each study.
Rhizophora species
THIS STUDY Golley Silva Day Fromard Clough Putz
350
300
Predicted Dry Biomass
250
200
150
100
50
0
5 10 15 20
Diameter at Breast Height
Figure 10. Predicted total biomass for Rhizophora spp. based on the allometric equations from this study and other studies as shown in
the legend.
and do not necessarily follow latitudinal or general Using the equations to assess the Everglades resto-
area trends. The biomass values generated with ration
allometric equations should be considered with
Mean sediment salinity predicted change in bio-
caution when used to extrapolate outside of the size
mass relatively well for Laguncularia but not for
range sampled or from areas with inherently dif-
Rhizophora or Avicennia (Figure 11). This is not
ferent environmental parameters (for example,
totally unexpected as Laguncularia is the least
salinity, nutrients, hydrological exchange, stem
tolerant species. Both Avicennia and Rhizophora
density, net primary productivity, and herbivory).
418
Harney River Transect Plots
50
Change in Biomass
25
0
-25
-50
10 20 30
Mean Salinity
Figure 11. Change in biomass as a function of mean sediment porewater salinity for plots along the Harney River in Everglades
National Park. The regression equations for Avicennia (squares) and Rhizophora (diamonds) are not significant. The regression for
Laguncularia is significant. The regression equation is: Change in biomass = À1.691*(mean salinity) + 26.905, r2 = 0.38, p < 0.01.
have broad salinity tolerances with Avicennia References
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