Download Community secondary production as a measure of ecosystem

BULLETIN OF MARINE SCIENCE. 87(4):913–937. 2011
http://dx.doi.org/10.5343/bms.2010.1043
COMMUNITY SECONDARY PRODUCTION AS
A MEASURE of ecosystem function:
a case study with AQUATIC
ECOSYSTEM FRAGMENTATION
Lori Valentine-Rose, Andrew L Rypel, and Craig A Layman
ABSTRACT
Secondary production is a composite measure of an animal population’s density,
biomass, and growth over time. Thus, secondary production converts animal
abundance and biomass data into a functional measure of energy flow through
an ecosystem. In the present study, we used community secondary production
as a composite measure of ecosystem functional response to anthropogenic
disturbance, and applied this approach to examine effects of fragmentation on tidal
creek ecosystems in The Bahamas. Community fish production decreased from a
mean of 901 g m−2 yr−1 in unfragmented creeks to 166 g m−2 yr−1 in downstream areas
of fragmented creeks to 29 g m−2 yr−1 upstream of creek blockages in fragmented
creeks. When compared with several univariate measures (species richness,
evenness, abundance, biomass), community composition (by ordination), and
community distribution (via rank-curve analysis), community secondary production
appeared to be the most consistent variable for distinguishing between three creek
fragmentation categories. These data suggest that small, non-significant declines
in diversity or other structural metrics can yield disproportionately large declines
in ecosystem function. We suggest community secondary production can be an
important component of future assessments of anthropogenic impacts, especially
when alterations in diversity or community structure are small, but potentially have
dramatic impacts on ecosystem function.
Human alteration of earth’s ecosystems is widespread and ongoing (Vitousek 1997,
Foley et al. 2005), and habitat degradation is a leading cause of these declines (Ehrlich
and Ehrlich 1981, Tilman et al. 1994). One common consequence of habitat alteration is biodiversity loss, which can drive dramatic changes in ecosystem function
(Naeem et al. 1994, Chapin et al. 2000, Cardinale et al. 2006). As such, understanding the relationship between habitat degradation, biodiversity loss, and ecosystem
function has become a central subdiscipline in the biological sciences (Chapin et al.
1997, Loreau et al. 2001).
Many studies that evaluate ecosystem responses to habitat alteration have focused
on structural response variables. For example, changes in species richness, abundance, or biomass are commonly used as indicators of ecosystem response to disturbance (Micheli 1999, Ceballos et al. 2005, Brooks et al. 2006, Cardinale et al. 2006,
Mouillot et al. 2006). However, these structural variables may indicate little about
ecosystem functional responses to habitat and biodiversity loss (Walker et al. 1999).
A more thorough understanding of anthropogenic impacts may be gleaned from
measures of ecosystem function that reflect and integrate multiple underlying processes (Pauly et al. 2002, Bellwood et al. 2004, Kremen and Ostfeld 2005, Mouillot
et al. 2006).
Bulletin of Marine Science
© 2011 Rosenstiel School of Marine and Atmospheric Science
of the University of Miami
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Open access content
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BULLETIN OF MARINE SCIENCE. VOL 87, NO 4. 2011
Secondary production is a composite measure of an animal population’s density,
biomass, and growth over time (Benke 1993). Thus, secondary production converts
animal abundance and biomass data into a functional measure of energy flow through
an ecosystem. When secondary production is measured for multiple taxa across an
entire community, the sum of these values (defined as community secondary production) serves as a powerful response variable that reflects high levels of biological
organization (Huryn and Wallace 1987, Edgar and Shaw 1995b, Huryn 1998, Cowley
and Whitfield 2002). In terrestrial ecosystems, plant community primary production has been used extensively to evaluate response to disturbance and to examine
biodiversity-ecosystem function relationships (Naeem et al. 1994, Tilman et al. 1994,
1996, Hector et al. 1999, Tilman et al. 2001, Haberl et al. 2002, Hooper et al. 2005,
Tilman et al. 2006). However, in faunal communities, community biomass typically
is used as a surrogate for community production. Direct estimates of secondary production at the population-level have been generated in various marine systems, e.g.,
mangroves (Faunce and Serafy 2008), oyster reefs (Peterson et al. 2003), artificial
patch reefs (Powers et al. 2003), seagrass (Edgar and Shaw 1995a, McCay and Rowe
2003), and salt marshes (Kneib 2003, McCay and Rowe 2003). Yet, community-wide
approaches to production in marine systems have been less common, and have usually focused on invertebrate communities (Cebrian 2002, Munari and Mistri 2007,
Madsen et al. 2008).
In the present study, we demonstrate how community secondary production of
fishes can be used as a composite measure of ecosystem response to anthropogenicdriven disturbance and apply this approach to examine effects of aquatic ecosystem
fragmentation on tidal creek ecosystems in The Bahamas. We provide new estimates
of community-wide secondary production in sub-tropical mangrove habitats and
hypothesized that (1) increased fragmentation would correlate with significantly diminished secondary production of fish communities, and (2) community secondary
production would be a more sensitive variable to identify effects of ecosystem fragmentation relative to other structural response variables (e.g., richness, abundance,
and biomass).
Methods
Site Description.—Our study systems were eight clear-water, mangrove-lined tidal
creeks on the eastern shore of Andros Island, The Bahamas (Table 1). At low tide, water is
restricted to the main creek channels providing permanent habitat for fishes (i.e., most fishes
remain in the main creek channels even on the lowest tides). Main channel areas may contain
multiple habitat types (e.g., mangrove, rock, seagrass, or sand) and vary substantially in
microtopography among systems. Intertidal flats typically have a sandy, biogenically-derived
substrate with interspersed dwarf red, Rhizophora mangle Linnaeus, and black, Avicennia
germinans (Linnaeus) Linnaeus, mangroves. More detailed information on these systems
can be found in previous studies (Layman et al. 2007, Rypel et al. 2007, Valentine-Rose et al.
2007a, Valentine-Rose and Layman 2011).
In The Bahamas, estuary fragmentation results from construction of roads lacking flow
conveyance structures (i.e., bridges or culverts), thereby decreasing habitat quality and altering floral and faunal assemblages (Layman et al. 2004, Valentine-Rose et al. 2007b,
Rypel and Layman 2008). Similar to Dynesius and Nilsson (1994), we devised a three category system for classifying the relative degree of fragmentation in tidal creeks (ValentineRose et al. 2007b). The study sections of each creek were classified as either: unfragmented
(UF, those with no blockage), fragmented-upstream (FU, those upstream of a major flow
valentine-rose et al.: secondary production of fish communities
915
Table 1. Physical and biological charcteristics of study tidal creeks on Andros Island, The Bahamas. % columns
refers to the proportions of various habitats available to fishes in each creek. N/A represents a habitat area so
expansive that it could not be calculated in the field, but nonetheless was dry at low tide and therefore contained
no fish species.
Max depth Fragmentation
%
%
%
Area
Ecosystem
(low tide, m2) (low tide, m) classification mangrove seagrass sand
Bowen up
N/A
0.10
FU
0
0
N/A
Man-o-War up
1,650
0.25
FU
10
0
86
Love Hill up
831
0.50
FU
18
1
36
Davis up
384
0.50
FU
54
0
46
Conch up
150
0.25
FU
67
0
0
Davis down
10,020
0.50
FD
10
2
84
Man-o-War down
11,718
0.25
FD
2
0
59
Love Hill down
8,350
3.00
FD
20
9
33
Bowen down
2,439
2.00
FD
33
27
10
Conch down
1,415
0.05
FD
11
0
21
Somerset
16,245
0.50
UF
14
73
3
Buryin Peace
1,810
0.50
UF
24
10
6
White Bight
1,008
1.00
UF
18
1
23
% Species
rock richness
N/A
0
4
6
45
9
0
0
33
6
4
23
39
9
38
23
30
11
68
0
10
25
60
21
58
16
blockage), and fragmented-downstream (FD, those on the ocean-side of a major flow blockage). Fragmentation categories for each surveyed creek are provided in Table 2.
Survey Methodology.—All production data were derived from field estimates of fish
densities and lengths from surveys in May 2005. At each study site, we first calculated the spatial extent of four main habitat types (rock, mangrove roots and/or pneumatophores, sand/
silt, and seagrass) in the main channel of each creek at low tide. We then divided each habitat
into 25 equally-sized sections, and in each subsection, we randomly selected a 1-m 2 area for
survey. Fish densities and lengths in each random area were then estimated with 1-m 2 visualized quadrats using underwater visual census (UVC, Valentine-Rose et al. 2007b). Surveys
were taken within 2 hrs of low tide to facilitate estimates of fish biomass, because fishes were
constricted to the main channel during this time (Valentine-Rose et al. 2007b). While this
may have resulted in inflated per unit area (m−2) estimates of subtidal channel areas, the extrapolated values of whole-creek production (see below) were more robust because surveys
were conducted when fish biomass could be quantified most accurately. At the survey time,
the investigator approached the predetermined quadrat area within ~2 m, waited ~1 min for
fishes to acclimate to the observer’s presence, and then noted the number and length (L) of all
individuals within the quadrat. For fragmented tidal creeks, this protocol was conducted in
each habitat type both upstream and downstream of the road blockage. Further information
on survey methodologies for production estimations in tidal creeks can be found in previous
studies (Valentine-Rose et al. 2007a, Valentine-Rose and Layman 2011).
Ages for each individual fish were estimated using a rearrangement of the Von Bertalanffy
growth function that used fish lengths from the above surveys to predict age (Appendix 1).
For two common species [gray and schoolmaster snapper, Lutjanus griseus (see Table 3 for
fish species authorities) and Lutjanus apodus, together accounting for 18% of abundance
and 20% of productivity], in situ growth parameters were developed by ageing otolith annuli from individuals in unfragmented and fragmented creeks on Andros and Abaco Islands
(Valentine-Rose et al. 2007b, Rypel and Layman 2008). Published Von Bertalanffy growth
functions (Appendix 1) from similar habitats were used for all other species. When more than
one published growth rate was available for the same species in similar habitats, an average of
those growth rates was used. When growth rates were not available for a species (n = 13, totaling 12% of abundance and 17% of productivity), growth rates from the most closely related
taxa from the most similar habitats and environmental conditions were used. While growth
data for all individual taxa in all creeks would be most desirable, here we focus on higherorder community-based metrics of production. We therefore assume that individual-based
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BULLETIN OF MARINE SCIENCE. VOL 87, NO 4. 2011
Table 2. Univariate results for fish communities in unfragmented (UF), fragmented downstream (FD), and
fragmented upstream (FU) tidal creeks in Andros Island, The Bahamas. SOM = Somerset, WB = White Bight,
BP = Buryin Peace, LH = Love Hill, DAV = Davis, MOW = Man-o-War, BOW = Bowen, CNC = Conch
Sound. DE = abundance m−2, BI = biomass g m−2, PR = production g m−2 yr−1, SP = total number of species per
creek, H’ = Shannon diversity, E = Shannon evenness. * indicates a P value < 0.05 for ANOVA comparisons.
1, 2, or 3 indicates significance in Bonferroni comparisons between (1) UF and FD, (2) UF and FU, and (3) FD
and FU creeks. – indicates an insignificant ANOVA or Bonferroni comparison at the 0.05 α-level. Dominance
is based on largest value of each metric (i.e., highest DE, BI, or PR). E. spp. = Eucinostomus spp. and includes
E. jonesi, E. gula, and E. lefroyi. See Table 3 for full species names.
Tidal creek
SOM
WB
BP
LH
DAV
MOW
BOW
LH-Up
MOW-Up
CNC-Up
DAV-Up
ANOVA
Bonferroni
Fragmentation
category
UF
UF
UF
FD
FD
FD
FD
FU
FU
FU
FU
Dominance
DE BI
PR SP H’
E
DE
7.0 384 1,006 25 2.30 0.71 L. griseus
9.0 762 952 16 2.19 0.79 L. apodus
8.0 1,711 746 21 2.19 0.72 E. spp.
7.0 848 397 23 2.14 0.68 E. spp.
3.0
83
82 23 2.32 0.74 L. griseus
3.0
25
74 9 1.54 0.70 L. griseus
2.0
50 111 11 1.59 0.66 E. spp.
0.6
6
71 9 1.88 0.85 L. griseus
0.5
14
30 6 1.22 0.68 L. griseus
0.2
2
14 6 1.48 0.83 L. apodus
0.0
0
0 0 0.00 0.00
N/A
*
*
*
*
–
–
1,2 2,3 1,2 –
Dominance
BI
L. griseus
L. apodus
L. griseus
L. griseus
L. apodus
L. griseus
S. testudineus
L. griseus
L. griseus
S. testudineus
N/A
Dominance
PR
S. iserti
L. griseus
L. griseus
L. griseus
S. testudineus
E. spp.
E. spp.
L. griseus
L. griseus
L. griseus
N/A
differences in some metrics (e.g., growth) are less important than the overall community-level
patterns we sought to describe.
Secondary Production.—Secondary production calculations utilized an adapted form
of the “instantaneous growth method” (Waters 1977, Valentine-Rose et al. 2007b, ValentineRose and Layman 2011). This methodology involves summing the accumulation of biomass
for a population across fish age-classes (Waters 1977). To calculate fish biomass, in situ
length/weight (L/W) regressions were derived based on field-collected individuals ranging
over the entire size distribution in creeks for that species. Individuals were collected by seining or hook-and-line from each tidal creek in May 2004 (1 yr prior to the survey period). For
species that could not be collected in high enough abundance to derive L/W regressions in
situ (n = 22, totaling 7% of abundance and 11% of productivity), published L/W regressions
derived from similar environments were used (Appendix 2). Age-class biomass was calculated by multiplying the density of each age-class by weights predicted from L/W regressions,
and total biomass was found by summing age-class biomass estimates for each species. Thus,
low tide estimates of biomass were calculated for each species in each habitat in each creek
(example calculation in Appendix 3).
Annual secondary production was calculated for all species in each habitat of each creek
by subtracting current total biomass estimates from total biomass estimates predicted 1 yr
later by Von Bertalanffy growth functions. Production was calculated for each habitat, and
then each habitat production value was weighted by the percentage of that habitat type in the
survey area. Weighted habitat production values were then summed, giving total creek production for each species (example calculation in Appendix 3). Individual species’ production
values were then summed for all species in each creek (or upstream/downstream area of each
creek) to yield estimates of total fish community production (g m−2 yr−1) for each tidal creek. It
is important to note that annual fish production estimates calculated with the instantaneous
growth method are frequently developed using samples taken from a single month (Huryn
1996, 1998, Peterson et al. 2003, Powers et al. 2003). This is possible because in the increment
valentine-rose et al.: secondary production of fish communities
917
summation method, accrued biomass is summed across the representative age-classes rather
than across months (e.g., in the size-frequency method of production calculation).
To support the assumption that a single month survey was representative of fish production
across the creek systems despite migration, mortality, and recruitment variation, additional
surveys were conducted monthly (January–October 2005). Statistical analysis via a two factor (A: unfragmented vs fragmented, and B: month) repeated measures analysis with repetition on one factor (month) suggested that natural variability of secondary production within
tidal creeks among months was not significant (F4, 39 = 0.04, P = 0.99), while differences in
secondary production between creek fragmentation categories was significant (F1, 39 = 63.21,
P < 0.001). This further suggests among-creek comparisons based on a single set of surveys
(May 2005) are sufficient to compare fish secondary production among creek fragmentation
categories. Similar precautions should be taken to assess in-stream variability when repeating
this methodology.
Assumptions.—These production estimates are intended for comparisons among tidal
creeks within our study (i.e., relative comparisons). Care should be taken in extending these
numbers for comparisons with community production estimates in other systems. Due to
the limitations of our sampling method, our values are not exact whole-ecosystem values,
as they do not include in situ growth rates for every species. However, the use of published
growth rates from similar environmental conditions to estimate secondary production is a
common practice when in situ growth rates cannot be obtained (Waters 1977, Benke 1993,
Peterson et al. 2003, Powers et al. 2003). Furthermore, we assume our samples represent the
whole of the fish communities although cryptic, transient, nocturnal, or small fishes might
have been undersampled. Presumably these fishes would be undersampled consistently across
study sites and thus should not affect the relative comparisons among creeks. Error in production estimates also may have resulted from using the same growth rates in both fragmented
and unfragmented tidal creeks (for species other than gray and schoolmaster snapper). Since
growth rates of several fishes are slower in fragmented tidal creeks (Rypel and Layman 2008),
differences in community secondary production estimates among fragmentation categories
are likely conservative (i.e., production differences between fragmented and unfragmented
creeks were likely underestimated).
Production estimates, regardless of these assumptions, may be more sensitive than abundance or biomass data because production adjusts these data to account for rapid growth of
smaller species and individuals, transforming data to an energetics (i.e., functional) scale.
Therefore, the above-mentioned limitations do not compromise the value of the estimates in
our study to indicate ecosystem functional response to fragmentation among sites.
Density, Diversity, Evenness, and Rank-Production.—To evaluate alternative structural and functional response variables, total creek weighted (by habitat) densities for each
species in each creek were derived from the above-described methodology, and Shannon diversity and evenness indices were calculated for each tidal creek fish community.
Rank curves provide a graphical representation of the distribution of species richness, diversity, and evenness within a community (Begon et al. 2006). Rank curves may be preferable
to diversity indices alone because no information is lost through collapsing patterns into a
single value. Rank curves have most commonly been based on relative abundance or biomass
(reviews in Tokeshi 1990, 1993, Fesl 2002) in plant, bird, or insect communities where large
ranges in size and abundance (i.e., a mixture of very small, abundant individuals and large,
less abundant individuals) are not common among species (Motomura 1932, Fisher et al. 1943,
Preston 1948, MacArthur 1957, Whittaker 1977, Tokeshi 1990, 1993). However, because of the
size and abundance differences among species in fish communities, traditional metrics (i.e.,
biomass and abundance) may not be strong enough to elucidate patterns among fish communities in different areas. Because production integrates abundance, size, and growth into
a single functional metric, it may be more sensitive to differences in communities in various
locations. To demonstrate the difference that alternative response variables can have on the
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BULLETIN OF MARINE SCIENCE. VOL 87, NO 4. 2011
interpretation of species distribution within an ecosystem, we developed rank-abundance,
-biomass, and -production curves separately (Magurran 1988).
Statistical Analysis.—Single-factor ANOVA was used to compare differences in abundance, biomass, production, species richness, diversity, and evenness among UF, FD, and FU
creek categories. When appropriate, data were log-transformed to meet assumptions of normality. If ANOVA indicated a P-value < 0.05, Bonferroni post-hoc t-test analysis was performed to indentify which categories differed significantly.
We used non-metric multidimensional scaling (NMDS) to test if species contribution to
community production varied among UF, FD, and FU creek categories. To demonstrate the
difference that alternative response variables can have on interpretation of community composition within an ecosystem, we developed NMDS for relative community abundance and
biomass as well. NMDS graphically represents, in two dimensions, relationships between objects using the Bray-Curtis similarity index (Bray and Curtis 1957). In ordination plots, as
distance between points (i.e., species presence recorded in a single census) increases, similarity of biotic species composition between the two surveys decreases. Analysis of similarities
(ANOSIM), a multivariate, non-metric analog to MANOVA, was used to test for significant
differences in contribution to relative production between tidal creek categories for each
functional group designation. If ANOSIM revealed significant (P < 0.05) effects, then similarity percentage analysis (SIMPER, Clarke and Warwick 1994) was used to identify which
species or group contributed to the observed differences. All NMDS, ANOSIM, and SIMPER
analyses were conducted in Primer 5 (version 5.2.9, PRIMER-E Ltd., Plymouth, UK). To determine potential differences alternative response variables can have on the interpretation of
community distribution within an ecosystem, we used DOM-DIS (dominance-distribution)
in Primer 6 (version 6, PRIMER-E Ltd., Plymouth, UK) to analyze differences among UF, FD,
and FU creeks in community abundance, biomass, and production rank-curves.
Results
Secondary Production.—Fish community production (i.e., as a univariate metric) differed significantly between two creek fragmentation categories (F = 51.5, P <
0.0001), sometimes by as much as an order of magnitude (Table 2). Post-hoc comparisons revealed significant differences in community production between UF and FD
categories (UF > FD, Tukey’s: P < 0.0001) and UF and FU categories (UF > FU, Tukey’s:
P < 0.0001). FU and FD categories did not differ significantly (Tukey’s: P = 0.14, Fig.
1). Community production ranged from 746 to 1006 g m−2 yr−1 in unfragmented tidal
creeks, from 74 to 397 g m−2 yr−1 in downstream areas of fragmented creeks, and from
0 to 71 g m−2 yr−1 in upstream areas of fragmented tidal creeks (Table 2, see Table 3 for
production values for each population and habitat). Univariate estimates of community abundance and biomass were also significantly different among fragmentation
categories (F = 23.8, P < 0.001; F = 51.5, P < 0.0001, respectively), and abundance most
closely paralleled differences in community production regarding creek fragmentation category differentiation (Bonferroni multiple comparisons, Table 2).
Community composition (i.e., a multivariate metric) based on either abundance or
biomass did not differ significantly among fragmentation categories (ANOSIM: r =
0.05, P = 0.32; r = 0.01, P = 0.88, respectively; Fig. 2). Community composition using
production as the measure did differ significantly among all fragmentation categories (ANOSIM: r = 0.42, P = 0.02). This difference was due to communities dominated by production of reef species, those associated most often with complex reef
habitat as adults, vs bay species, generalists associated with shallow inshore habitats
throughout their life cycles (defined in Nagelkerken et al. 2000 and listed in Table 2).
valentine-rose et al.: secondary production of fish communities
919
Figure 1. Mean community secondary production of fishes in Bahamian tidal creeks classified
into three fragmentation categories. Error bars represent the mean ± 1 SE. Letters denote categories that do not differ significantly (Bonferroni P > 0.05) from one another.
In UF creeks, a larger proportion of production was comprised of reef species (e.g.,
Scarus iserti, Haemulon sciurus, Haemulon parra, and Halichoeres bivattatus; Table
3). A larger proportion of production in FD creeks was made up of bay species (e.g.,
Eucinostomus spp., Sphoeroide testiduneus, Gerres cinereus, and Sphyraena barracuda) than in UF creeks. FU creeks had low species richness, and secondary production
was typically dominated by one species (Lutjanus griseus, Table 3).
Because production of only two, albeit dominant, species was calculated using in
situ derived growth rates that differed between fragmentation categories, differences
in community production estimates between fragmentation categories was likely
due to one of two factors: differences in individual species’ abundances or differences in individual species’ size distributions among fragmentation categories (i.e., the
other main components to production calculations). Differences between UF and FU
creek categories were primarily due to a decrease in species richness (Table 2), and
lower biomass for those species absent in FU creek areas (i.e., obviously no biomass
for nonexistent species). When comparing UF and FD fragmentation categories, in
which species richness was similar (Table 2), underlying reasons for production differences varied. For example, based on the species-specific results discussed above,
some species had a greater proportion of production in UF creeks primarily due to
greater abundance (S. iserti: 120 UF, 15 FD; H. sciurus: 23 UF, < 1 FD; H. parra: 35 UF,
< 1 FD; mean values, standard deviations not included for simplicity). But size distributions drove differences in production between UF and FD creeks for species present in both creek categories. For example, for Eucinostomus spp., there was a greater
proportion of smaller individuals in FD creeks, and since smaller individuals grow
faster, more biomass would be expected to be produced over the course of a year.
Horse-eye jack
Mutton snapper
Schoolmaster snapper
Cubera snapper
Gray snapper
Yellowtail snapper
Mojarra spp.2
Yellow-finned mojarra
French grunt
Sailor’s choice grunt
Blue-striped grunt
Caranx latus (Agassiz, 1831)
Lutjanus analis (Cuvier, 1828)
Lutjanus apodus (Walbaum, 1792)
Lutjanus cyanopterus (Cuvier, 1828)
Lutjanus griseus (Linnaeus, 1758)
Ocyurus chrysurus (Bloch, 1791)
Eucinostomus spp.
Gerres cinereus (Walbaum, 1792)
Haemulon flavolineatum (Desmarest, 1823)
Haemulon parra (Desmarest, 1823)
Haemulon sciurus (Shaw, 1803)
Chaetodontidae
Chaetodon capistratus (Linnaeus, 1758)
Chaetodon ocellatus (Bloch, 1787)
2
1
N
R
C, N
C, N
C, N
B
B
C, N
C, N
C, R
C, N
C, N
C, R
C, N
R
EFG
Needlefish spp. includes Atlantic needlefish (S. marina) and redfin needlefish (S. notata)
Mojarra spp. includes slender mojara (Eucinostomus jonesi), mottled mojara (E. lefroyi), and silver jenny (E. gula).
Haemulidae
Gerreidae
Lutjanidae
Four-eye butterfly
Spotfin butterfly
Nassau grouper
Epinephelus striatus (Bloch, 1792)
Carangidae
Serranidae
Needlefish spp.1
Common name
Strongylura spp.
Species
Belonidae
F
F
F
M
M
F
M
S
M
S
S
S
S
S
S
Growth
1.4 (2.8)
0.1 (0.1)
1.5 (1.7)
FD
8.4 (5.4)
0
4.9 (8.5)
13.2 (10.9)
10.8 (18.4)
36.0 (39.0)
34.1 (54.6)
2.1 (2.1)
0.1 (0.2)
0
2.6 (3.9)
2.2 (3.6)
21.1 (9.8)
6.8 (6.2)
0
0.1 (0.1)
40.4 (40.0)
5.5 (3.2)
74.3 (126.3) 6.5 (5.6)
35.4 (16.9) 27.2 (26.7)
0
2.1 (4.1)
0
0.2 (0.3)
39.8 (29.6)
UF
0.6 (1.0)
0
0
0
0
2.4 (2.2)
1.2 (1.9)
0
2.9 (4.5)
0.3 (0.6)
12.0 (14.6)
0
0
0
0
FU
Table 3. Mean (± SD) total creek weighted production values (g m2 yr−1), and ecological functional group (EFG) classification (Nagelkerken 2000) of fish taxa
in tidal creeks on Andros Island, The Bahamas. UF = unfragmented tidal creeks, FD = downstream areas of fragmented tidal creeks, FU = upstream areas of
fragmented tidal creeks, N = nursery, R = reef, B = bay, C = commercial. Relative growth rates of the species (F = fast growth rate, M = medium growth rate, S
= slow growth) are provided for qualitative comparisons. Species listed phylogenetically.
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EFG
R
B
B
R
R
R
R
R
N
N
N
R
N
B
B
R
Common name
Sergeant major
Dusky damselfish
Beaugregory
Slipperydick
Yellowhead wrasse
Blackear wrasse
Puddingwife
Bluehead wrasse
Striped parrotfish
Parrotfish spp.3
Doctorfish
French angel
Great barracuda
Checkered puffer
Porcupinefish
Spotted goatfish
M
M
M
S
M
M
M
M
F
F
S
S
F
F
F
F
Growth
3
Parrotfish spp. includes bucktooth parrotfish (S. radians), redband parrotfish (S. aurofrenatum), and stoplight parrotfish (S. viride).
Species
Pomacentridae
Abudefduf saxatilis (Linnaeus, 1758)
Stegastes adustus (Troschel, 1865)
Stegastes leucostictus (Müller and Troschel, 1848)
Labridae
Halichoeres bivittatus (Bloch, 1791)
Halichoeres garnoti (Valenciennes, 1839)
Halichoeres poeyi (Steindachner, 1867)
Halichoeres radiatus (Linnaeus, 1758)
Thalassoma bifasciatum (Bloch, 1791)
Scaridae
Scarus iserti (Bloch, 1789)
Sparisoma spp.
Acanthuridae
Acanthurus chirurgus (Bloch, 1787)
Pomacanthus paru (Bloch, 1787)
Sphyraenidae
Sphyraena barracuda (Walbaum, 1792)
Tetraodontidae
Sphoeroide testudineus (Linnaeus, 1758)
Diodontidae
Diodon hystix (Linnaeus, 1758)
Mullidae
Pseudupeneus maculates (Bloch, 1793)
Table 3. Continued.
18.4 (18.4)
0.3 (0.7)
0
11.8 (13.3)
5.6 (7.5)
4.5 (8.7)
4.6 (9.3)
37.6 (74.2)
0.1 (0.1)
3.0 (4.9)
0
0
0
0.2 (0.4)
15.3 (17.5)
0.1 (0.1)
1.0 (0.8)
FD
15.7 (15.7)
9.4 (9.5)
28.3 (48.5)
1.8 (2.9)
0.1 (0.2)
86.4 (50.1)
0.4 (0.4)
14.9 (24.3)
1.9 (3.0)
1.7 (3.0)
0.6 (1.0)
0.7 (1.2)
22.5 (25.9)
0.1 (0.1)
1.4 (1.8)
UF
0
0
3.5 (3.6)
0
0
0
12.6 (21.8)
0
0
0
0
0
0
3.8 (3.7)
0
0.3 (0.4)
FU
valentine-rose et al.: secondary production of fish communities
921
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BULLETIN OF MARINE SCIENCE. VOL 87, NO 4. 2011
Figure 2. Non-metric Multi Dimensional Scaling (NMDS) ordinations of relative (A) density (N),
(B) biomass (B), and (C) production (P) surveys of Bahamian tidal creeks classified into three
fragmentation categories. Tidal creek abbreviations: BOW Bowen, BP Buryin Peace, CONCH
Conch Sound, DAV Davis, LH Love Hill, MOW Man-o-War, SOM Somerset, WB White Bight.
valentine-rose et al.: secondary production of fish communities
923
Rank-Production.—Species richness, diversity, and evenness were not significantly different in any two fragmentation comparisons (Bonferroni multiple comparisons, all P-values > 0.05, Table 2). These patterns were apparent when comparing
rank-abundance, -biomass, and -production curves among the three fragmentation
categories (Fig. 3). In rank-abundance plots, slopes and shapes showed little difference among fragmentation categories (DOM-DIS: r = 0.36, P = 0.71). This pattern
reflects little difference in species richness, diversity, and evenness comparisons
among fragmentation categories. Rank-biomass curves also showed little separation
in slope and shape among fragmentation categories (DOM-DIS: r = 0.17, P = 0.81).
Slopes of biomass curves were steeper compared to abundance and production, suggesting that biomass was less evenly distributed in fish communities (i.e., some species contributed very high biomass and while others contributed little). Compared
to rank-abundance and -biomass curves, rank-production curves showed the most
separation in slope and shape among fragmentation categories, and approached significance (DOM-DIS: r = 0.63, P = 0.061).
The “dominant” species within each creek changed when using different variables
to identify dominance (i.e., greatest abundance, greatest biomass, or greatest production), resulting in different patterns among fragmentation categories (Table 2). For
example, only two creeks (Man-o-War and Love Hill upstream) had the same species
(L. griseus) with the highest abundance, biomass, and productivity. All other creeks
had different results for dominant species between at least two defining variables, and
two creeks had different dominant species for all three variables. When dominance
was assigned based on abundance, no patterns were apparent among fragmentation
categories, as each creek tended to have a unique dominant species (Table 2). When
dominance was assigned based on biomass, again, no patterns were apparent among
fragmentation categories because the species with the highest biomass tended to be
L. griseus or L. apodus in all creeks. However, when the most productive species was
used to assign dominance, distinct patterns emerged. While unfragmented creeks
were dominated by commercially important (L. griseus) or reef (S. iserti) species,
downstream areas of fragmented creeks were dominated by generalist bay species
such as S. testudineus and Eucinostomus spp. Upstream areas of fragmented creeks
were also dominated by L. griseus, but this single species made up a much larger proportion of relative production compared to UF creeks (Fig. 2) and consisted entirely
of age-0 individuals.
Discussion
Our data suggest that community secondary production can be a more sensitive
response variable (compared with species richness, diversity, density, and biomass)
when assessing ecosystem-level impacts of tidal creek fragmentation. Even when declines in species richness and diversity were small and non-significant, these changes
drove a disproportionate erosion of ecosystem function (i.e., production). Our study
complements the suggestion by the US NOAA National Marine Fisheries Service
that of the four criteria used to identify essential fish habitat (presence-absence, density, growth, and production), production may be the most distinguishing and sensitive metric (Able 1999, Searcy et al. 2007). Below we examine (1) possible effects of
ecosystem fragmentation on secondary production of fishes, (2) the implications of
using various univariate and multivariate metrics to interpret ecological data, and (3)
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BULLETIN OF MARINE SCIENCE. VOL 87, NO 4. 2011
Figure 3. Rank-abundance (DE), -biomass (BI), and -production (PR) curves in unfragmented
(UF), fragmented-downstream (FD), and fragmented-upstream (FU) creek areas in The Bahamas.
the potential usefulness of rank-production curves in examining effects of human
impacts like marine ecosystem fragmentation.
Secondary production was significantly lower in fragmented creeks for all analyses. Significant declines in community secondary production imply major changes
to the energetic structure of fish communities and marine food webs. Previous work
on effects of tidal creek fragmentation have documented how numerous biotic and
abiotic factors can be altered following fragmentation (Layman et al. 2007, ValentineRose et al. 2007a, Allgeier et al. 2010, Layman et al. 2011). As in most cases of aquatic
valentine-rose et al.: secondary production of fish communities
925
ecosystem fragmentation (Pringle 2001, 2003a,b), variability in physiochemical conditions increases and habitat heterogeneity decreases (Roman et al. 1984, Warren
et al. 2002, Valentine-Rose et al. 2007a), both of which may serve to directly affect
primary and secondary production (Valentine-Rose et al. 2007b, Allgeier et al. 2010).
These changes may have lead to the selective decrease in production of dominant
species in our marine systems. For example, fish production in UF creeks was dominated by parrotfishes—important herbivores that associate with reef and seagrass
habitat. However, production of parrotfishes was significantly lower in FD creeks,
and parrotfishes were not found in FU creeks, likely a response to these underlying
changes in habitat and physiochemical conditions (Valentine-Rose et al. 2007a).
As with any space-for-time comparative study, underlying ecological mechanisms
can be questioned. In the present case, there are multiple reasons to believe that
the fragmentation is the major driver in production differences among creeks. First,
recent restoration projects led to a rapid increase in secondary production following
removal of the sources of creek fragmentation (Valentine-Rose and Layman 2011),
consistent with the assumption that ecosystem fragmentation initially drove the differences in production values among creeks. Second, more recently blocked creek
systems tend to have higher abundance and biomass of fishes than those blocked for
many decades (C Layman, per obs). Third, local fishermen also confirm that many
currently-blocked creeks supported productive fisheries before they were fragmented.
Fragmented creeks had a higher proportion of smaller fishes. Differences in fish
growth rates and decreased migration into fragmented creeks are likely key sources
for variation in fish sizes among creek fragmentation categories. Significantly slower
growth rates have been documented for two fish species in fragmented tidal creeks
(Valentine-Rose et al. 2007b, Rypel and Layman 2008), mirroring patterns of fishes
in fragmented freshwater rivers (Rypel et al. 2006, Penczak 2007, Rypel and Bayne
2009, Weyl et al. 2009). Growth differences among creek fragmentation categories
are likely the product of structural and functional modifications to tidal creek food
webs follwing fragmentation. For example, fragmented creeks support lower diversity and abundance of prey items (Valentine-Rose et al. 2007a) and an increase in
trematode parasite loads for fishes (Rypel and Layman 2008), both of which can
function to reduce fish growth. Therefore, a greater proportion of small individuals
in fragmented creeks may be a product of slower growth rates of fishes in these systems. If this is the case, production differences between UF and FD/FU creeks may
be even greater than our data suggest.
Further, tidal creek fragmentation may result in a physical exclusion of large motile
fishes. Fragmented tidal creeks are often shallower due to increased siltation and a
lack of flow (Valentine-Rose and Layman 2011), thereby impeding access to these
areas by larger individuals. Concomitant with the loss of larger fishes, there may also
be decreased predation on smaller individuals due to fewer large predators, as well as
decreased predator detection and capture efficiency in the more turbid downstream
waters (Aksnes and Giske 1993). Targeted studies of growth rates (Faunce and Serafy
2008, Rypel and Layman 2008) and predation rates (Rypel et al. 2007) in these systems may reveal which of these processes are most important in driving production
differences among tidal creeks (Searcy et al. 2007).
The most important general finding of our study was that community secondary
production was the best metric for discerning ecosystem-level effects of tidal creek
fragmentation on fish communities. Considering all univariate and multivariate
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metrics used to discriminate among fragmentation categories in our study, secondary production was the only metric that consistently distinguished ecosystems based
on fragmentation categories. Even in creeks where declines in diversity or changes
to community structure due to fragmentation were minor (e.g., Love Hill), this was
associated with significant declines in fish production. Abundance and biomass are
two of the most commonly used ecological response variables, yet our results suggest
that analysis of secondary production estimates may be essential for more integrated
ecological patterns to emerge. For example, studies of species “dominance” normally define the dominant as either the most abundant species or the species with
greatest biomass (Ricklefs and Miller 2000). Although univariate abundance and
production metrics paralleled in discriminating between fragmentation categories,
defining dominance by different metrics (i.e., abundance, biomass, or production)
suggested conflicting interpretations of how communities were structured and how
they were affected by fragmentation. Defining dominance by biomass revealed no
differences among fragmentation categories. According to the dominant abundant
species, fragmentation reduced a different species in each creek with no apparent
pattern. However, production of selective discrete functional groups appeared to be
particularly sensitive to the effects of tidal creek fragmentation (e.g., reef-associated
parrotfishes discussed above). UF creeks also had higher production of commercially
important and top predator species.
Rank-production curves provided a novel way to view how community distribution
patterns differed among fragmentation categories, and again, secondary production
was the most sensitive metric in this approach. Rank-production in UF creeks was
best approximated by a lognormal curve, where many species had similar relative
production and there were relatively few dominant or rare species. The lognormal
pattern is typical for stable and well developed communities (Ugland and Gray 1982,
Sugihara 1989). FU creeks had the steepest rank-production curve (most similar to
a convex curve), indicating dominance by few taxa. Evenness of production among
species was highest in FD creeks, and appeared to be approximately linearly distributed (except for the rarest species). While detailed examination of rank models was
beyond the scope of the present study, using production in developing future models of community distribution may be an important tool and deserves further consideration. Studies that have not found significant changes following anthropogenic
disturbances in rank-abundance analyses (e.g., Hoyle and Harborne 2005) may have
reached different conclusions if secondary production were employed as the measure
of dominance (but see Buffagni and Comin 2000).
We showed how community secondary production can be an integrative variable
for assessing effects of ecosystem fragmentation, and perhaps a more sensitive metric
with which to assess affects of ecosystem fragmentation. However, diversity remains
a key metric, even though diversity alone showed less clear patterns among fragmentation categories (species richness and community secondary production were
significantly and positively related; linear regression: r2 = 0.46, P = 0.02). Our study
should not be construed as rationale that fisheries managers or conservation biologists focus on production over diversity. Instead these data are best interpreted as
examples of how even non-significant declines in diversity can lead to disproportionately large declines in ecosystem function. Community secondary production
estimates could therefore be an especially useful tool in scenarios where diversityor community-based metrics do not detect an anthropogenic effect, but where an
valentine-rose et al.: secondary production of fish communities
927
ecosystem-level effect is nonetheless suspected (e.g., Hoyle and Harborne 2005). In
a broader context, it is often assumed that diversity change reduces species richness regardless of particular species or functional groups (Micheli 1999, Ceballos et
al. 2005, Cardinale et al. 2006), yet here we showed that when realistic impacts on
ecosystems occur (Zavaleta and Hulvey 2004, Bracken et al. 2008), disproportionate
and specific changes in production of important functional groups result. In sum, we
recommend that community secondary production be considered in future studies
of anthropogenic stress on ecosystem function.
Acknowledgments
This study would not have been possible without the ideas, efforts, and persistence of D
Albrey Arrington. We owe sincere thanks to M Blackwell, Bahamas Environmental Research
Center, The Natural Conservancy Bahamas, Forfar Field Station, and the College of The
Bahamas for providing research facilities, support, and help with logistics and planning. This
project was funded by the National Science Foundation through an IGERT training grant to
A Ward and the University of Alabama (DGE0319143), NSF OCE0746164, the Acorn Alcinda
Foundation, and an RJKOSE grant through The Nature Conservancy. We would also like to
thank the many Androsians that assisted with field work, particularly C “Tutu” Bains. We
thank A Benke, J Benstead, and all anonymous reviewers for their time and advice reviewing
this manuscript.
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Date SuBmitted: 19 May, 2010.
Date Accepted: 16 June, 2011.
AvailaBle Online: 20 July, 2011.
Addresses: (LV-R) Department of Life Sciences, Hill College, 2712 Mayfield Dr, Cleburne, Texas
76033. (ALR) Department of Fish and Wildlife Conservation, Virginia Tech, 100 Cheatham
Hall, Blacksburg, Virginia 24061-0321. (CAL) Marine Sciences Program, Department of
Biological Sciences, Florida International University, 3000 NE 151st Street, North Miami,
Florida 33181. Corresponding Author: (LV-R) E-mail: <[email protected]>.
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Appendix 1. Growth rate data used for fishes from Bahamian tidal creeks. Parameters are given for the
Von Bertalanfy (VB) growth equation, Lage+1 = L∞ (1 − e−k(t−t0)), where Lage = field estimated lengths, L∞ =
asymptotic maximum length, t0 = age at zero length, and k = Brody growth coefficient with all lengths L
representing standard length (SL, mm). Temperatures given for published VB equations used (°C), while for
those experienced in situ during the sampling month were 33–35 °C in upstream areas of fragmented creeks
(FU) and 25–30 °C in unfragmented (UF) creeks and downstream areas of fragmented (FD) creeks. Growth
rates for schoolmaster in unfragmented tidal creeks fit a linear model, SL, mm = 24.711 (age, y) + 50.826
(Valentine-Rose et al. 2007). Citations for this appendix are located below.
Species/common name
Belonidae
Strongylura spp.
Needlefish spp.
Serranidae
Epinephelus striatus (Bloch, 1792)
Nassau grouper
Carangidae
Caranx latus (Agassiz, 1831)
Horse-eye jack
Lutjanidae
Lutjanus analis (Cuvier, 1828)
Mutton snapper
Lutjanus apodus (Walbaum, 1792)
Schoolmaster snapper
FD and FU
Lutjanus cyanopterus (Cuvier, 1828)
Cubera snapper
Lutjanus griseus (Linnaeus, 1758)
Gray snapper
UF
FD
FU
Ocyurus chrysurus (Bloch, 1791)
Yellowtail snapper
Gerreidae
Eucinostomus spp.
Mojarra spp.
Gerres cinereus (Walbaum, 1792)
Yellow-finned mojarra
Haemulidae
Haemulon flavolineatum (Desmarest, 1823)
French grunt
Haemulon parra (Desmarest, 1823)
Sailor’s choice grunt
Haemulon sciurus (Shaw, 1803)
Blue-striped grunt
Chaetodontidae
Chaetodon capistratus (Linnaeus, 1758)
Four-eye butterfly
Chaetodon ocellatus (Bloch, 1787)
Spotfin butterfly
Pomacentridae
Abudefduf saxatilis (Linnaeus, 1758)
Sergeant major
Stegastes adustus (Troschel, 1865)
Dusky damselfish
Stegastes leucostictus (Müller and Troschel, 1848)
Beaugregory
L∞
k
t0
1,230 0.610
°C Location
27.0 India
698 0.145 −1.080
Florida Keys
560 0.143 −1.730 27.0 Cuba
696 0.246
27.2 Cuba
Ref
8
3
13
9
1,054 0.100
416 0.061 −1.900
The Bahamas
877 0.125
27.2 Cuba
947
238
191
413
0.036 −2.500
0.303 0.140
0.352 0.100
0.279 −0.355
18
19
Andros and Abaco
18
Islands, The Bahamas
South Florida
207 0.430
27.0 Mexico
268 0.600
27.0 Cuba
208 0.350
27.2 Jamaica
7
1
19
4
224 0.179
349 0.240 −0.270 27.2 SW Cuba
19
305 0.220 −0.140 27.2 SW Cuba
19
334 0.300
0.000
Puerto Rico
2
182 1.700
27.0 India
12
182 1.700
27.0 India
12
189 0.850
27.0 India
12
108 0.450
27.0 Jamaica
20
108 0.450
27.0 Jamaica
20
valentine-rose et al.: secondary production of fish communities
933
Appendix 1. Continued.
Species/common name
Labridae
Halichoeres bivittatus (Bloch, 1791)
Slipperydick
Halichoeres garnoti (Valenciennes, 1839)
Yellowhead wrasse
Halichoeres poeyi (Steindachner, 1867)
Blackear wrasse
Halichoeres radiatus (Linnaeus, 1758)
Puddingwife
Thalassoma bifasciatum (Bloch, 1791)
Bluehead wrasse
Scaridae
Scarus iserti (Bloch, 1789)
Striped parrotfish
Sparisoma spp.
Parrotfish spp.
Acanthuridae
Acanthurus chirurgus (Bloch, 1787)
Doctorfish
Pomacanthus paru (Bloch, 1787)
French angel
Sphyraenidae
Sphyraena barracuda (Walbaum, 1792)
Great barracuda
Tetraodontidae
Sphoeroide testudineus (Linnaeus, 1758)
Checkered puffer
Mullidae
Pseudupeneus maculates (Bloch, 1793)
Spotted goatfish
L∞
k
170 0.750
t0
°C Location
Florida
Ref
14
400 0.600
28.2 US Virgin Islands
16
400 0.600
28.2 US Virgin Islands
16
400 0.600
28.2 US Virgin Islands
16
170 0.750
Florida
14
290 0.600
27.0 The Bahamas
5
260 0.200
27.2 Caribbean
17
258 0.254
28.2 US Virgin Islands
14
272 0.500
395 0.214
27.0 Jamaica
28.2 US Virgin Islands
10
14
25.0 Florida
14
1,560 0.113
1,780 0.087
6
250 0.510
25.4 Biscayne Bay
15
235 0.350
27.0 Jamaica
11
254 0.700
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valentine-rose et al.: secondary production of fish communities
935
Appendix 2. Length-weight regression data sources. 1 = present study, 2 = Bohnsack and Harper (1988)1.
Parameters represent the equation, log W = log a + b log L, where L = length (mm), W = weight (g), and a and
b are coefficients.
Species/common name
Belonidae
Strongylura spp.
Needlefish spp.
Serranidae
Epinephelus striatus (Bloch, 1792)
Nassau grouper
Carangidae
Caranx latus (Agassiz, 1831)
Horse-eye jack
Lutjanidae
Lutjanus analis (Cuvier, 1828)
Mutton snapper
Lutjanus apodus (Walbaum, 1792)
Schoolmaster snapper
Lutjanus cyanopterus (Cuvier, 1828)
Cubera snapper
Lutjanus griseus (Linnaeus, 1758)
Gray snapper
Ocyurus chrysurus (Bloch, 1791)
Yellowtail snapper
Gerreidae
Eucinostomus spp.
Mojarra spp.
Gerres cinereus (Walbaum, 1792)
Yellow-finned mojarra
Haemulidae
Haemulon flavolineatum
(Desmarest, 1823) French grunt
Haemulon parra (Desmarest, 1823)
Sailor’s choice grunt
Haemulon sciurus (Shaw, 1803)
Blue-striped grunt
Chaetodontidae
Chaetodon capistratus (Linnaeus, 1758)
Four-eye butterfly
Chaetodon ocellatus (Bloch, 1787)
Spotfin butterfly
Pomacentridae
Abudefduf saxatilis (Linnaeus, 1758)
Sergeant major
Stegastes adustus (Troschel, 1865)
Dusky damselfish
Stegastes leucostictus (Müller and Troschel, 1848)
Beaugregory
Labridae
Halichoeres bivittatus (Bloch, 1791)
Slipperydick
Halichoeres garnoti (Valenciennes, 1839)
Yellowhead wrasse
Halichoeres poeyi (Steindachner, 1867)
Blackear wrasse
Halichoeres radiatus (Linnaeus, 1758)
Puddingwife
Thalassoma bifasciatum (Bloch, 1791)
Bluehead wrasse
a
b
Source
Location
Min–max Length
(mm) measure
−7.19 3.62
1
Andros Island 160–350
SL
−4.89 3.03
2
Puerto Rico 210–635
FL
−5.36 3.23
2
Florida
32–377
FL
−4.83 3.03
2
St. Croix
260–630
FL
−4.30 2.91
1
Andros Island 50–180
SL
−4.06 2.75
1
Andros Island 74–310
SL
−4.27 2.87
1
Andros Island 40–290
SL
−3.15 2.33
2
−4.46 2.94
Puerto Rico
29–562
FL
1
Andros Island 19–100
SL
−4.07 2.77
1
Andros Island 40–200
SL
−5.04 3.15
2
−4.44 2.98
Florida
32–389
FL
1
Andros Island 50–135
SL
−4.4 2.94
1
Andros Island 63–174
SL
−4.84 3.18
2
Florida
43–115
TL
−4.48 2.98
2
Florida
103–181
TL
−4.78 3.14
2
Florida
18–143
FL
−4.39 3.02
1
Andros Island 25–70
SL
−4.39 3.02
1
Andros Island 25–70
SL
−4.81 2.93
2
Florida
36–152
TL
−5.65 3.37
2
Florida
26–105
TL
−5.65 3.37
2
Florida
26–105
TL
−4.92 3.03
2
Florida
24–36
TL
−4.88 2.91
2
Florida
15–118
TL
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BULLETIN OF MARINE SCIENCE. VOL 87, NO 4. 2011
Appendix 2. Continued.
Species
Scaridae
Scarus iserti (Bloch, 1789)
Striped parrotfish
Sparisoma spp.
Parrotfish spp.
Acanthuridae
Acanthurus chirurgus (Bloch, 1787)
Doctorfish
Pomacanthus paru (Bloch, 1787)
French angel
Sphyraenidae
Sphyraena barracuda (Walbaum, 1792)
Great barracuda
Tetraodontidae
Sphoeroide testudineus (Linnaeus, 1758)
Checkered puffer
Mullidae
Pseudupeneus maculates (Bloch, 1793)
Spotted goatfish
a
b
Source
Location
Min–max Length
(mm)
measure
−5.14 3.35
1
Andros Island 38–60
−5.75 3.42
2
Florida
130–240
FL
−5.92 3.53
2
Florida
39–304
FL
−4.81 3.12
2
Florida
21–413
TL
−4.81 2.88
1
Andros Island 150–500
SL
−3.94 2.77
1
Andros Island 70–185
SL
−4.82 3.02
2
Florida
149–290
SL
FL
Bohnsack JA, Harper DE. 1988. Length-weight relationships of selected marine reef species
from the southeastern United States and the Caribbean. NOAA Tech Memorandum NMFSSEFC-215, 31 p.
1
valentine-rose et al.: secondary production of fish communities
937
Appendix 3. Example of calculation of annual production: schoolmaster snapper in White Bight
tidal creek, Andros Island, The Bahamas. DE = density 25 m−2, BI = biomass g 25 m−2, PR =
secondary production, and PR (weighted) = PR multiplied by percentage of habitat contribution
for each habitat. Equations can be found in the Methods section.
Creek:
White Bight
Rock 58%
Total
Mangrove 18%
Total
Seagrass 23%
Total
Sand 1%
Total
Total PR
Age (i)
0
1
2
3
4
0
1
2
3
4
0
1
0
1
DE
24
18
7
1
0
41
8
22
20
0
3
0
1
0
BIage field
BIage + 1
400
1,563
1,745
811
0
4,519
0
3,078
7,593
2,935
930
14,536
266
1,320
5,484
12,887
0
19,957
0
5,313
11,926
6,585
9,306
33,130
12
0
12
0
244
244
4
0
4
0
85
85
PR g m−2 yr−1
PR (weighted)
g m−2 yr−1
401
232
527
95
9
2
3
0.03
329