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Many of the most abundant fish species using mangroves in the Caribbean also use other habitat types through daily home range movements and ontogenetic habitat shifts. Few studies, however, have considered the structure of the surrounding seascape when explaining the spatial distribution of fish within mangroves. This study develops an exploratory seascape approach using the geographical location of mangroves and the structure of the surrounding seascape at multiple spatial scales to explain the spatial patterns in fish density and number of species observed within mangroves of SW Puerto Rico. Seascape structure immediately surrounding mangroves was most influential in determining assemblage attributes and the density of juvenile Haemulon flavolineatum, which were significantly higher in mangroves with high seagrass cover (>40%) in close proximity (< 100 m) than mangroves with low (<40%) or no adjacent seagrasses. Highest mean density of juvenile Ocyurus chrysurus was found in offshore mangroves, with high seagrass and coral reef cover >40 and >15%, respectively) in close proximity (<100 m). In contrast, juvenile Lutjanus griseus responded at much broader spatial scales, and with highest density found in extensive onshore mangroves with a large proportion (> 40%) of seagrass within 600 m of the mangrove edge. We argue that there is an urgent need to incorporate information on the influence of seascape structure into a wide range of marine resource management activities, such as the identification and evaluation of critical or essential fish habitat, the placement of marine protected areas and the design of habitat restoration projects.
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MARINE ECOLOGY PROGRESS SERIES
Mar Ecol Prog Ser
Vol. 348: 273284, 2007
doi: 10.3354/meps07052
Published October 25
INTRODUCTION
Mangroves are generally considered to offer an
important nursery function for many fish species and
have been linked to highly productive coastal fisheries
worldwide (Blaber 2000, Manson et al. 2005, Faunce &
Serafy 2006). It is now increasingly acknowledged,
however, that mangroves may not always function in
isolation to support fish populations (Sheaves 2005,
Adams et al. 2006). In many regions, mangroves are
connected to a mosaic of habitat types (e.g. seagrasses,
coral reefs) through the movements of fish at a range of
scales in time and space (Parrish 1989, Mumby et al.
2004, Pittman et al. 2004). In Caribbean mangroves,
many of the most frequently observed fish species use
multiple habitat types through daily home range
movements (Rooker & Dennis 1991, Nagelkerken et
al. 2000, Verweij et al. 2006) and broader scale
onshoreoffshore ontogenetic habitat shifts (Cocheret
de la Morinière 2002, Christensen et al. 2003, Mumby
et al. 2004). As such, the nursery function of Caribbean
mangroves may depend on spatial connectivity to
other habitat types (Sheaves 2005); an attribute of the
speciesenvironment relationship, which is deter-
mined primarily by the interaction between animal
mobility and the composition and spatial arrangement
of resources across the seascape.
Nevertheless, a spatially explicit and quantitative
consideration of the surrounding seascape structure is
still a relatively novel approach in marine ecology.
Concepts and analytical techniques developed in
landscape ecology, however, provide an existing
© Inter-Research 2007 · www.int-res.com*Email: simon.pittman@noaa.gov
Using seascape types to explain the spatial patterns
of fish in the mangroves of SW Puerto Rico
Simon J. Pittman*, Chris Caldow, Sarah D. Hile, Mark E. Monaco
NOAA/NOS/CCMA Biogeography Team, 1305 East-West Highway, Silver Spring, Maryland 20910, USA
ABSTRACT: Many of the most abundant fish species using mangroves in the Caribbean also use
other habitat types through daily home range movements and ontogenetic habitat shifts. Few stud-
ies, however, have considered the structure of the surrounding seascape when explaining the spatial
distribution of fish within mangroves. This study develops an exploratory seascape approach using
the geographical location of mangroves and the structure of the surrounding seascape at multiple
spatial scales to explain the spatial patterns in fish density and number of species observed within
mangroves of SW Puerto Rico. Seascape structure immediately surrounding mangroves was most
influential in determining assemblage attributes and the density of juvenile Haemulon flavolineatum,
which were significantly higher in mangroves with high seagrass cover (>40%) in close proximity
(<100 m) than mangroves with low (<40%) or no adjacent seagrasses. Highest mean density of juve-
nile Ocyurus chrysurus was found in offshore mangroves, with high seagrass and coral reef cover
(>40 and >15%, respectively) in close proximity (<100 m). In contrast, juvenile Lutjanus griseus
responded at much broader spatial scales, and with highest density found in extensive onshore man-
groves with a large proportion (>40%) of seagrass within 600 m of the mangrove edge. We argue that
there is an urgent need to incorporate information on the influence of seascape structure into a wide
range of marine resource management activities, such as the identification and evaluation of critical
or essential fish habitat, the placement of marine protected areas and the design of habitat restora-
tion projects.
KEY WORDS: Seascape structure · Mangroves · Seagrasses · Coral reef ecosystems · Spatial scale ·
Fish · Puerto Rico · Caribbean
Resale or republication not permitted without written consent of the publisher
Mar Ecol Prog Ser 348: 273284, 2007
framework that can be readily applied to shallow-
water marine systems (Robbins & Bell 1994). Land-
scape ecology has been defined as the study of pro-
cesses occurring across spatially heterogeneous
mosaics and the biotic responses to the resultant pat-
terns (Turner 1989). The underlying premise is that the
composition and spatial arrangement of mosaic ele-
ments affect ecological processes in ways that would
be different if the composition and arrangement were
different (Dunning et al. 1992, Wiens et al. 1993). From
an operational perspective, an exploratory seascape
approach must quantify environmental variability at
multiple spatial scales (Pittman & McAlpine 2003,
Pittman et al. 2004). A single-scale approach cannot
incorporate important interactions occurring at other
scales and is particularly inappropriate for studies of
multi-species assemblages. Species, and even differ-
ent life-stages of the same species, vary in their
response to the environment due to functional differ-
ences in dietary requirements, habitat specialisations,
body size and movements (Addicott et al. 1987, Wiens
1989, Wiens et al. 1993). Furthermore, comparing the
strength of the speciesenvironment association
across scales allows determination of the scale exhibit-
ing the strongest influence, typically referred to as the
‘characteristic scale’ (Holland et al. 2004).
The present study links daytime underwater fish
census data collected within mangroves of the La
Parguera Natural Wildlife Reserve (SW Puerto Rico)
with geographical and seascape variables quantified
within circles of different radii surrounding fish sur-
vey sites. We focus on the spatial patterns of density
for 2 species of Haemulidae (Haemulon flavolineatum
and H. sciurus) and 3 species of Lutjanidae (Lutjanus
apodus, L. griseus and Ocyurus chrysurus), as well as
the density and number of species of the fish assem-
blage observed within mangroves. We develop an
exploratory approach (1) to identify the characteristic
scale(s) of response to habitat by examining the
strength of the correlation between the fish response
variable and individual seascape variables across the
scale range and (2) at these characteristic scales, we
then examine the influence of multivariate seascape
structure to identify the mangroves and associated
seascape types that support the highest and lowest
density of fish and number of fish species across the
region.
MATERIALS AND METHODS
Study area. Fish censuses were conducted between
2001 and 2006 within mangroves of the La Parguera
region of SW Puerto Rico (Fig. 1). The data was col-
lected as part of a larger project designed to monitor
and characterise fishhabitat relationships across
Caribbean coral reef ecosystems (National Oceanic
and Atmospheric Administration’s Caribbean Coral
Reef Ecosystem Monitoring Program).
The shoreline and islands of the area are lined with
mangrove communities dominated by the red man-
grove Rhizophora mangle. To the west, the onshore
mangroves are extensive and extend to approximately
800 m from the land. To the east, there are less exten-
sive fringing mangroves and many small mangrove
islands. Adjacent sediments support seagrasses (domi-
nated by Thalassia testudinum), macroalgae and
unvegetated sand and sandy mud interspersed with
coral reefs and patch reefs, which vary in patch size
and benthic community composition. The tidal range is
relatively small (<0.5 m), and mangrove prop roots at
the seaward edge of the mangrove stands are continu-
ally immersed throughout the tidal cycle. For all man-
groves sampled, mean water depth was 66 cm (range
30 to 152 cm).
Sampling fish. A total of 145 spatially random man-
grove survey sites were selected using a geographical
information system (GIS) and a nearshore benthic
habitat map for Puerto Rico (Kendall et al. 2002).
Sampling was conducted in winter (January/February/
March) and fall (August/September/October) seasons
each year, with approximately 10 to 12 spatially ran-
dom sites selected across the study area for each field
season. To quantify fish abundance, observers identi-
fied, counted and estimated the body lengths (fork
length, FL) of all fish sighted within a 25 m long by 4 m
wide belt transect (100 m
2
) using a standard daytime
underwater visual census technique (adapted from
Brock 1954). Transects were placed to directly follow
the edge of the mangrove tree-line. Lengths were esti-
mated in size-class ranges with 5 cm increments (i.e.
<5, 5 to 10, 10 to 15 cm). For individual species, only
juveniles and sub-adults were included in the analysis
and were distinguished based on lengths less than the
mean length at maturity reported by García-Cagide
et al. (1994).
Environmental data. Two types of spatial data were
acquired: (1) geographical variables and (2) spatially
explicit seascape variables. Geographical variables
included distance to shore and the geographical loca-
tion (latitude and longitude) of each fish transect
extracted from the spatial data using a GIS. Seascape
variables included the relative proportion of major
habitat types (percent cover of mangroves, seagrasses,
coral reefs and unvegetated sediments), the number of
habitat types (habitat richness) and mean water depth
quantified within circles of different radii (50, 100, 200,
300, 400, 500 and 600 m) surrounding each fish tran-
sect. Each circle surrounding a fish transect is referred
to here as a seascape sample unit. The proportion and
274
Pittman et al.: Seascape types and spatial patterns of fish in mangroves
richness of habitat types were extracted from the
nearshore benthic habitat map for Puerto Rico. To cap-
ture the full range of heterogeneity represented in the
map, habitat richness was calculated as the total num-
ber of habitat classes within a seascape sample unit
from all available classes at the level of ‘habitat type’
(maximum 13 habitat classes). Mean water depth in
the surrounding seascapes was quantified from a
bathymetric model developed using a triangulated
interpolated network (TIN) on depth soundings data
(National Geophysical Data Center) and supple-
mented by data from SCUBA divers. Vertical accuracy
of the TIN model was validated (mean vertical error
<0.3 m) using an independent set of bathymetric data.
The TIN model was then converted into a raster map
(5 × 5 m spatial resolution).
Scale selection. The range of radii for seascape sam-
ple units selected includes both sub-home range and
supra-home range spatial scales for juvenile Haemuli-
dae and Lutjanidae. Information on the scale of move-
ment was based on the average maximum distance
travelled for multiple individuals of each species using
existing data from acoustic tracking and mark/recap-
ture studies for durations ranging from hours to months
(Table 1). The maximum distance travelled during rou-
tine daily movements is considered an appropriate
measure for scaling ecologically relevant environmen-
tal patterns (Addicott et al. 1987). In the present study,
a maximum radius of 600 m was selected to minimise
overlap among sample units.
Statistical analyses. To examine the strength and
directionality of the fish response to the individual
seascape variables, and to determine the characteristic
scale, we calculated the Spearman rank correlation
coefficient (rho = r) between all response variables and
all seascape variables at each spatial scale. We tested
for significance of the observed r by comparing it with
a simulated distribution of r from re-sampled data
275
Fig. 1. Location of the study area in SW Puerto Rico. Map showing the 4 major habitat types included in this study as delineated
in the NOAA’s benthic habitat map
Mar Ecol Prog Ser 348: 273284, 2007
using 1000 random permutations. The spatial scale
with the greatest proportion of maximum r across all
predictor variables was selected as the characteristic
scale for each species/assemblage attribute. Following
Holland et al. (2004), we took the scale of maximum
correlation to be the scale of maximum response. In
addition, the presence of spatial dependence in the
response variables was tested using the global Moran’s
I statistic (Moran 1950).
To examine the association between multivariate
seascape structure and the spatial patterns of fish den-
sity and number of species, we first defined seascape
structural types at characteristic scales using hierarchi-
cal cluster analysis with complete linkage applied to a
Bray-Curtis sample dissimilarity matrix (Primer v5 soft-
ware, Plymouth Marine Laboratory). Bray-Curtis dis-
similarities were calculated on the untransformed pro-
portion of each habitat type (mangroves, seagrasses,
coral reefs and unvegetated sediments) in the sea-
scapes surrounding all mangrove sample sites. This
technique partitioned the multiple gradients of habitat
abundance across the study area into distinct struc-
tural types that were then represented on a dendro-
gram. Similarity percentages (SIMPER) analysis was
used to identify the seascape variables that contributed
most to the dissimilarity between groups (Clarke &
Warwick 1994).
Non-metric multidimensional scaling (nMDS) plots
were used to (1) delineate the seascape structural
types in ordination space and (2) display overlays of
fish density and number of species by sample site. Sites
in close proximity to one another in the ordination
space are the most similar in structure, whereas sites
that plot farther away from each other are less similar
(Clarke & Warwick 1994). The goodness-of-fit of the
ordination is ranked by the stress index, which mea-
sures how well a particular plot of similarities corre-
sponds to the observed distance matrix. Stress values
range from 0 to 1, where low values (<0.05) indicate
a good fit and high values (>0.2) indicate a poor
fit (Kruskal 1964). The nonparametric Kruskal-Wallis
1-way analysis of variance test, followed by Dunn’s
multiple pairwise comparison test, was used to exam-
ine differences in the fish response among seascape
structural types.
RESULTS
Within the mangroves of SW Puerto Rico 176 188
individual fish of 96 species from 32 families were
observed. The most frequently occurring fish species
were Lutjanus apodus (100% of samples), Stegastes
leucostictus (76%), Haemulon sciurus (77%), H. flavo-
lineatum (77%), Sphyraena barracuda (65%), Abu-
defduf saxatilis (59%) and Chaetodon capistratus
(58%). Lutjanus griseus and Ocyurus chrysurus were
observed in 46 and 12% of samples, respectively.
Spatial autocorrelation
The response data were not significantly spatially
autocorrelated (Moran’s I = –0.49 to 0.14, p > 0.1) and
therefore the geographical distribution of samples was
not considered to have biased correlation coefficients
calculated to determine the characteristic scales.
Determining a characteristic scale of response
For density and number of species of assemblages,
and for density of Haemulon flavolineatum and Ocyu-
rus chrysurus, correlation coefficients were highest
at the 100 m radius scale for 3 or more of the 6 seascape
variables, and thus the 100 m radius scale was con-
sidered the characteristic scale for subsequent analysis
(Table 2). In contrast, Lutjanus griseus density was
most strongly correlated at the 600 m scale for 4 out of
6 seascape variables, and thus the 600 m radius scale
was considered the characteristic scale for subsequent
analysis (Table 2). More ambiguous was Haemulon
sciurus, which showed significant correlations at
the 600 m (seagrass cover) and 200 m scales (unvege-
276
Species Life stage No. Mean (SD) Mean (SD) max. Location Source
of fish duration (d) distance (m)
Haemulidae
Haemulon flavolineatum Juvenile 25 90.7 (30.9) 105.3 (66.8) Puerto Rico Bouwmeester (2005)
H. flavolineatum Sub-adult 28 198.6 (129.6) 93.6 (68.1) Puerto Rico Bouwmeester (2005)
H. sciurus Sub-adult/adult 10 11.3 (9.3) 279.2 (227.9) St. John, USVI Beets et al. (2003)
Lutjanidae
Lutjanus griseus Juvenile/sub-adult 10 64.3 (0.48) 648 (1216) Florida www.adoptafish.net
Table 1. Approximate scale of movements for haemulids and lutjanids from a range of studies using mark/recapture and
acoustic tracking
Pittman et al.: Seascape types and spatial patterns of fish in mangroves
tated cover), but with strongest correlation at the
600 m scale (Table 2).
Defining seascape structural types
At both the 100 and 600 m spatial scales, cluster
analysis identified 7 groupings of samples that were
>35% dissimilar to each other, of which the largest 6
groups were labelled Seascape Types A, B, C, D, E & F.
The groups were easily delineated on nMDS ordination
plots, with low stress values of 0.05 (100 m seascapes)
and 0.09 (600 m seascapes), indicating ‘excellent’ and
‘good’ 2-dimensional representation of the data struc-
ture, respectively (Fig. 2). Mean (±SD) dissimilarity was
54 ± 10.2% for all pairs of 100 m seascape types and
50 ± 12.1% for 600 m seascape types.
100 m radius seascape types
To improve interpretation, the six 100 m seascape
types were further grouped into 2 highly dissimilar
groups based on seascape characteristics. This division
was delineated on the ordination with a broken line
(Fig. 2). Highest pairwise percentage dissimilarity for
100 m seascapes was between 100A & F (76%), 100B &
F (67%), 100C & F (63%) and 100A & E (65%).
Seascape Structural Types 100E & F were the least
structurally heterogeneous 100 m radius seascapes,
composed of onshore mangroves (<800 m from shore),
surrounded by relatively shallow water (<2 m), with
low seagrass cover (<40%) and no coral reefs in close
proximity. The most structurally heterogeneous 100 m
radius seascapes were 100A & B, composed of offshore
(>800 m from shore) mangrove islands, with high sea-
grass cover (>40%) in close proximity. In addition,
Seascape Type 100A had the largest proportion of coral
reefs (>15%), and Seascape Type 100B had the deepest
adjacent waters and the largest proportion of seagrass
cover (>70%). Seascape Types 100C & D were mostly
onshore mangroves, with very similar structural char-
acteristics, but 100C mangroves had higher adjacent
seagrass cover (mean of 64 versus 50.6%) (Table 3).
Mean pairwise similarity percentages determined that
distance to shore (39 ± 5.6%) and the proportion of
mangroves (25 ± 5.8%) and unvegetated cover (22 ±
8.4%) in the seascape contributed most to the differ-
ences between Seascape Types 100A, B & C and 100E
& F (Table 3).
600 m radius seascape types
The six 600 m radius seascape types were divided
into 3 types with maximum dissimilarity and delineated
with a broken line on the ordination (Fig. 2). Highest
pairwise dissimilarity was calculated for 600A & E
(62%), 600A & C (57%), 600A & B (53%), 600B & D
(54%) and 600B & C (47%). Seascape Structural Types
600A & F were the least heterogeneous 600 m radius
seascapes, composed of onshore mangroves (<800 m
from shore), with low to medium seagrass and man-
grove cover (<40%) and very low (<5%) or no coral
reefs (Table 3). Types 600D & C were considered the
most highly heterogeneous of the onshore seascapes,
with higher seagrass cover (>40%), low unvegetated
cover (<25%), low coral reef cover (<8%) and medium
habitat richness (4 to 8 classes). Types 600B & E were
the most highly heterogeneous seascapes, composed of
relatively small offshore mangrove islands, surrounded
by deeper water (>15 m mean water depth), with the
largest proportion of coral reefs (>10%), low-medium
seagrass cover (>30%), relatively high unvegetated
cover (>20%) and habitat richness (6 to 13). Mean pair-
wise similarity percentages determined that distance to
277
Response Seascape variable
% Habitat Mean water
Mangrove Seagrass Coral reef Unvegetated richness depth
Assemblage
Density 100 (–0.31) 100 (0.33) 100 (0.16) 100 (–0.31) 600 (0.31) 300 (0.31)
Number of species 100 (–0.23) 500 (0.33) 50 (–0.14) 100 (–0.22) 100 (–0.17) 200 (–0.16)
Haemulidae
Haemulon flavolineatum 100 (–0.27) 100 (0.33) n.s. 100 (–0.21) 500 (0.16) 300 (0.25)
H. sciurus n.s. 600 (0.25) n.s. 200 (–0.26) 50 (–0.16) n.s.
Lutjanidae
Ocyurus chrysurus 100 (–0.22) 100 (0.18) 100 (0.12) 500 (0.14) 50 (–0.11) 300 (0.19)
Lutjanus griseus 600 (0.43) 100 (–0.34) 500 (–0.45) 600 (–0.21) 600 (–0.38) 600 (–0.44)
L. apodus n.s. n.s. n.s. n.s. n.s. n.s.
Table 2. Characteristic scales (bold) for the fish response to seascape variables and the associated maximum correlation
coefficient (in parentheses). All correlation coefficients are statistically significant (p < 0.05). n.s.: not significant
Mar Ecol Prog Ser 348: 273284, 2007
shore (42 ± 4.1%) and the proportion of seagrasses in
the seascape (27 ± 8.2%) contributed most to the differ-
ences between all 3 groups of seascape types.
Linking fish density and number of species to
seascape types
Assemblages
Fish assemblage density within mangroves was
significantly higher (Kruskal-Wallis, K = 22.6, p <
0.001) in seascapes with high seagrass cover (>40%) in
close proximity (<100 m). This was demonstrated by
significantly higher fish densities in mangroves of
Seascape Types 100A, B, C & D when compared to
Seascape Types 100E & F (Fig. 3). Overall, highest
mean assemblage density was recorded for the most
structurally heterogeneous seascape types (100B & A),
composed of offshore mangroves, with high seagrass
cover and with close proximity to coral reefs and
deeper water areas. Lowest mean density was
recorded for the least heterogeneous seascapes (100E
& F), composed of onshore mangroves, with little or no
seagrass cover or coral reefs in close proximity. Mean
number of species was also higher in the more struc-
turally heterogeneous seascape types, but
significant differences were only detected
between Seascape Types 100B and 100E & F
(Kruskal-Wallis, K = 17.7, p < 0.001). Highest
mean number of species was reported for the
100B seascapes, characterised as offshore
mangroves with deeper adjacent water and
the highest seagrass cover (Fig. 3).
Haemulidae
Haemulon flavolineatum were observed
using mangroves in all seascape structural
types, but with markedly higher mean densi-
ties found within mangroves of seascape
types with high adjacent seagrass cover
(Fig. 4). Significantly higher mean density
was recorded for the 100B seascape type
when compared with the lowest mean den-
sity recorded for 100E & F seascapes
(Kruskal-Wallis, K = 13.5 p < 0.05). In fact, H.
flavolineatum was only recorded in 1 sample
from Seascape Type 100F. Haemulon sciurus
were widely distributed amongst mangroves
across the region, with a relatively high
mean density recorded in both offshore
(600B & E) and onshore mangroves (600C &
D) with adjacent seagrasses (Fig. 5). Lowest
mean density was found in mangroves (600A
& F) that were closest to shore, with no coral
reefs within 600 m (Kruskal-Wallis, K = 11.2,
p < 0.05).
Lutjanidae
Ocyurus chrysurus were absent from
onshore mangroves in Seascape Type 100F,
and only 1 individual was sighted from the
17 samples in 100E seascapes (Fig. 4). High-
est mean density was reported from the
278
Stress: 0.05
B
A
C
D
E
F
Shallow water onshore
High mangrove
Low seagrass in group E
No seagrass in group F
No coral reef
Low habitat richness
Offshore mangroves in groups A & B
Low-medium mangrove
High seagrass
High coral reef in group A
Medium-high habitat richness
Shallow water onshore
Medium-high mangrove & seagrass
Low unvegetated
Low coral reef
Medium habitat richness
Stress: 0.09
A
E
B
F
D
C
Deeper water offshore
Low mangrove
Low-med seagrass
High unvegetated
Low-medium coral reef
High habitat richness
Shallow water onshore
Low-medium mangrove & seagrass
No coral reef & low habitat richness
a
b
Fig. 2. Structural dissimilarity amongst (a) 100 m seascape structural types
and (b) 600 m seascape structural types using non-metric multidimen-
sional scaling plots (nMDS) showing the relative dissimilarity in seascape
composition (percent cover of seagrasses, mangroves, coral reefs and
unvegetated sediments) for all samples. Seascape structural types are
encircled and labelled (A, B, C, D, E & F) according to cluster groups iden-
tified using a hierarchical cluster analysis. The groups of seascapes with
highest structural dissimilarity are separated with broken lines
Pittman et al.: Seascape types and spatial patterns of fish in mangroves
279
B
A
C
D
E
F
B
C
D
A
E
F
a
b
0
2
4
6
8
10
12
14
16
ACE
Seascape types (cluster groups)
0
20
40
60
80
100
120
ACE
BDF
BDF
Seascape types (cluster groups)
Mean fish density (per 100 m
2
)Mean no. species (per 100 m
2
)
Fig. 3. Distribution of (a) fish assemblage density and (b) number of fish species within mangroves overlaid on an nMDS ordina-
tion of seascape structural dissimilarity at the 100 m radius scale. Grey circles are proportional in size to the value of density or
number of fish species observed at each survey site. Seascape structural types are encircled and labelled (A, B, C, D, E & F)
according to cluster groups identified using a hierarchical cluster analysis. The accompanying charts show mean (±SE) of (a) fish
assemblage density and (b) number of species for each seascape type
Habitat variable Seascape type
ABCDEF
100 m radius spatial extent
Mangrove (%) 22.6 (1.3) 14.2 (0.7) 24.7 (1.1) 42.3 (0.9) 57.2 (2.1) 56 (10.6)
Seagrass (%) 52.3 (2.8) 85.5 (1.5) 64 (1.6) 50.6 (1.2) 29.8 (2.5) <1 (<0.1)
Coral reef (%) 27.4 (1.6) 2.1 (0.6) 1.4 (0.5) 0.5 (0.3) 0 0
Unvegetated (%) 0.3 (0.3) 0.1 (<0.1) 1.7 (1.1) 6 (1.7) 6.9 (2.7) 39.8 (9.4)
Number of habitat types 4.2 (0.1) 2.9 (0.1) 3.1 (0.1) 2.7 (0.1) 2.9 (0.2) 2.4 (0.2)
Mean depth (m) 1.6 (0.1) 4.5 (0.5) 4.1 (0.5) 2.4 (0.2) 1.4 (0.1) 1.4 (0.2)
Distance to shore (km) 1.2 (0.1) 0.9 (0.1) 0.4 (0.1) 0.3 (<0.1) 0.3 (<0.1) 0.2 (0.01)
600 m radius spatial extent
Mangrove (%) 21.5 (1.4) 3.7 (0.4) 8.3 (0.6) 32.7 (1.9) 2.9 (0.4) 8.3 (1.5)
Seagrass (%) 15.9 (1.5) 26.2 (0.6) 66.8 (2.2) 53.4 (1.2) 42.8 (1.2) 32.5 (0.8)
Coral reef (%) 0 14.1 (0.8) 2.1 (0.5) 0.26 (0.1) 15.2 (1.2) 1.2 (0.7)
Unvegetated (%) 24.9 (3.4) 49.1 (2.7) 6.6 (0.6) 5.91 (0.8) 32.5 (2.2) 25.9 (5.2)
Number of habitat types 4.10 (0.2) 8.1 (0.3) 5.9 (0.2) 5.8 (0.2) 8.3 (0.4) 5.4 (0.6)
Mean depth (m) 4.7 (0.6) 27.2 (1.7) 13.1 (0.6) 5.0 (0.3) 21.6 (1.0) 14.5 (2.1)
Distance to shore (km) 0.15 (<0.1) 0.9 (0.03) 0.3 (<0.1) 0.47 (<0.1) 0.7 (0.1) 0.06 (<0.1)
Table 3. Characterisation of 100 and 600 m seascape structural types using mean (±SE) value for environmental variables
from samples grouped by cluster grouping
Mar Ecol Prog Ser 348: 273284, 2007
mangrove islands (100A & B) farthest offshore, with
high seagrass cover and close proximity to high coral
reef cover. In fact, Seascape Types 100A & B accounted
for 71% of the O. chrysurus sighted within mangroves
of the study area. Mean density followed a similar
pattern to Haemulon flavolineatum, but no significant
differences (Kruskal-Wallis, K = 6.9, p > 0.05) were
detected for density of O. chrysurus between seascape
structural types. Lutjanus griseus were observed using
mangroves in all seascape types, with highest mean
density in the most heterogeneous of the shallow
onshore mangroves of 600C (Fig. 5). In contrast to the
other species studied here, significantly lower mean
density of L. griseus was recorded for offshore man-
groves 600B & E (Kruskal-Wallis, K = 29.2, p < 0.001).
L. apodus was not significantly correlated with any
seascape variables.
DISCUSSION
In the present study, we developed a multi-scale
seascape approach to explain spatial patterns in fish
density and number of species. Our study revealed
considerable spatial complexity in the densities of fish
throughout the mangroves of SW Puerto Rico, which
could not be explained adequately by any single envi-
ronmental variable alone. We found that an under-
standing of the distribution patterns of fish with spa-
tially complex life cycles and multi-habitat home-
range movements necessitates consideration of both
the geographical location of the mangrove and the
structure of the surrounding seascape, particularly the
amount of seagrasses. Furthermore, it appears that
quality and suitability of a particular seascape type is
species specific and likely determined by the biologi-
280
a
B
A
C
F
D
E
Haemulon flavolineatum
0
10
20
30
40
50
60
70
ACE
ACE
Seascape types (cluster groups)
Seascape types (cluster groups)
Mean fish density (per 100 m
2
)Mean fish density (per 100 m
2
)
A
B
C
F
E
D
Ocyurus chrysurus
b
0
1
2
3
4
BDF
BDF
Fig. 4. Distribution of (a) Haemulon flavolineatum density and (b) Ocyurus chrysurus density within mangroves overlaid on an
nMDS ordination of seascape structural dissimilarity at the 100 m radius scale. Grey circles are proportional in size to the value
of density observed at each survey site. Seascape structural types are encircled and labelled (A, B, C, D, E & F) according to
cluster groups identified using a hierarchical cluster analysis. The accompanying charts show mean (±SE) of (a) H. flavolineatum
density and (b) O. chrysurus density for each seascape type. Fish illustrations provided courtesy of Bohlke & Chaplin (1993)
Pittman et al.: Seascape types and spatial patterns of fish in mangroves
cal characteristics of a species (e.g. mobility, life-
history strategy and resource requirements).
Determining a characteristic scale of response
Our multi-scale approach allowed us to identify the
scale(s) at which seascape structure had the most influ-
ence on fish. Fish that were likely to have exhibited rel-
atively fine-scale movements responded more strongly
to seascape structure immediately surrounding man-
groves. In contrast, juveniles of fish capable of broader
scale movements were found to respond more strongly
to seascape structure at broader spatial scales. Overall,
we found that the strongest bivariate correlations more
frequently occurred at the 100 m radius spatial scale for
fish assemblage density and number of species, as well
as for density of Haemulon flavolineatum and Ocyurus
chrysurus. In contrast, Lutjanus griseus and Haemulon
sciurus appeared to respond to seascape structure at
markedly broader spatial scales, suggesting that selec-
tion of a single scale for multi-species studies may be
inappropriate and that characteristic scales may vary
markedly between species even within a family.
Our results show good agreement between the char-
acteristic scale selected for each species and the
281
A
E
B
F
D
C
Haemulon sciurus
a
0
5
10
15
20
25
ACE
ACE
Mean fish density (per 100 m
2
)Mean fish density (per 100 m
2
)
Lutjanus griseus
A
E
B
F
D
C
b
0
2
4
6
8
10
12
14
BDF
BDF
Seascape types (cluster groups)
Seascape types (cluster groups)
Fig. 5. Distribution of (a) Haemulon sciurus density and (b) Lutjanus griseus density within mangroves overlaid on an nMDS ordi-
nation of seascape structural dissimilarity at the 600 m radius scale. Grey circles are proportional in size to the value of density
observed at each survey site. Seascape structural types are encircled and labelled (A, B, C, D, E & F) according to cluster groups
identified using a hierarchical cluster analysis. The accompanying charts show mean and standard error of (a) H. sciurus density
and (b) L. griseus density for each seascape type. Fish illustrations provided courtesy of Bohlke & Chaplin (1993)
Mar Ecol Prog Ser 348: 273284, 2007
known spatial extent of fish movements estimated by
fish tracking and tagging studies. For example, mark/
recapture experiments on juvenile and sub-adult
Haemulon flavolineatum in SW Puerto Rico revealed
a mean maximum distance moved of 105.3 m for 25
small juveniles (7.6 to 12.1 cm FL) and 93.6 m for 28
larger juveniles (10.9 to 14.9 cm FL) (Bouwmeester
2005). In addition, underwater observations of H.
flavolineatum at St. Croix have shown that schools of
juvenile grunts will move distances of 100 to 300 m to
feed at night in seagrass beds (Ogden & Ehrlich 1977).
Juvenile Ocyurus chrysurus is also thought to exhibit
relatively high site fidelity. Watson et al. (2002) carried
out daytime observations of newly settled O. chrysurus
(<7 cm FL) in seagrass beds of the British Virgin
Islands, with mean home ranges of <35 m
2
. Further-
more, Lindholm et al. (2005) reported high site fidelity
for 9 sub-adult O. chrysurus (21.5 to 26.5 cm FL) in the
Florida Keys, with the majority of acoustic detections
occurring at a single reef.
For Haemulon sciurus juveniles, our analysis found a
stronger response at broader spatial scales than for
H. flavolineatum, indicating that the characteristic scale
may vary between species within a family. Interestingly,
acoustic tracking of H. sciurus in St. John, US Virgin
Islands, showed that fish were moving greater distances
(mean 279 m, max. 767 m) than has been shown for sim-
ilar-sized H. flavolineatum (Beets et al. 2003). Support for
the broader scale response of Lutjanus griseus also
comes from acoustic tracking in Florida, with a mean
maximum distance travelled of 648 m, with the smallest
juveniles showing relatively high site fidelity and larger
juveniles making extensive movements (S. Whitcraft un-
publ. data). Unfortunately, insufficient data is available
on juvenile Lutjanus apodus to determine relevant spa-
tial scales. In our study, L. apodus did not respond signif-
icantly to individual seascape variables at any scale, and
additional analysis revealed that densities of juveniles
were not significantly different between seascape struc-
tural types. This indicates that either L. apodus does not
respond to the structure of the surrounding seascape, or
may respond to unmeasured variability such as the pres-
ence/absence of mangroves or perhaps to seascape
structure outside the scale range included in this study.
The importance of a relatively fine scale structure
(<100 m) for fish assemblages may relate to the pre-
ponderance of relatively small fish (mean 9.4 cm FL)
found using mangroves of SW Puerto Rico. In our
study, the species with the finest scale response were
also species with the largest proportion of small juve-
niles (Haemulon flavolineatum <10 cm = 90.8%; Ocy-
urus chrysurus <15 cm = 88.9%) of all focal species.
Kramer & Chapman (1999) found a strong positive lin-
ear allometric scaling relationship (r
2
= 0.73) between
body size and home range size for 29 tropical marine
fish, implying that, in general, smaller bodied fish sam-
ple their environment at finer spatial scales than do
larger bodied fish. Alternatively, scale differences may
be related to species-specific functional connectivity
between inshore juvenile habitat and offshore adult
habitat. Cocheret de la Morinière et al. (2002) pro-
posed that Lutjanus griseus (as well as L. apodus and
H. sciurus) are capable of long-distance, post-settle-
ment, life-cycle migrations (PLCM) that connect
inshore nursery habitats to adult habitats on offshore
coral reefs. In contrast, in the same study, the authors
differentiated H. flavolineatum and O. chrysurus as
exhibiting a stepwise PLCM with multiple spatial
shifts, with each sub-movement occurring at finer spa-
tial scales than those in long distance PLCM species.
Linking fish density and number of species to
seascape types
Across SW Puerto Rico, mangroves with extensive
seagrass beds (>40% of the seascape) in close proxim-
ity (<100 m) supported higher mean fish density and
number of species than mangroves with little or no sea-
grasses in close proximity. Elsewhere, several
seascape ecology studies that have incorporated the
distribution of surrounding habitat types have also
found that the presence, amount and proximity of sea-
grasses has emerged as an important explanatory vari-
able for fish spatial distributions in both mangroves
(Pittman et al. 2004) and coral reefs (Kendall et al.
2003, Grober-Dunsmore 2007).
However, we also found that not all mangrove-sea-
grass combinations were used equally, with offshore
mangrove-seagrass-dominated seascapes supporting
higher mean assemblage density and higher Haemu-
lon flavolineatum and Ocyurus chrysurus density than
onshore mangroves with adjacent seagrasses. O. chry-
surus was the most restricted in distribution, with only
offshore mangroves in close proximity (100 m) to high
coral reef (>15%) and seagrass cover (>40%) support-
ing high densities. Our results, therefore, indicate that
the preference of O. chrysurus for mangroves and
adjacent seagrasses is more specific than that indi-
cated by Nagelkerken et al. (2002), and the assignment
of equal ecological function to all mangrove-seagrass-
dominated seascapes across a region may be ecologi-
cally unrealistic.
A different spatial pattern of mangrove use was
found for Lutjanus griseus, with higher densities in
onshore mangroves. At the spatial extents examined in
this study ( 600 m radial extents), the presence of coral
reefs in close proximity to mangroves was not an
important determinant of fish densities for L. griseus.
Instead, higher densities of L. griseus were found in
282
Pittman et al.: Seascape types and spatial patterns of fish in mangroves
seascapes with extensive mangroves and extensive
seagrasses, but not necessarily in close proximity to
one another. A third response type was distinguished
for Haemulon sciurus densities, which did not differ
significantly between onshore or offshore mangroves
and seagrasses, but exhibited lowest densities within
onshore mangroves >600 m from coral reefs.
The functional significance of close proximity of man-
groves and seagrasses requires further investigation,
although it is likely that useable resources, such as sea-
grasses in close proximity, will provide a higher quality
habitat for many species than mangroves alone. This
may result from a sensitive dependence on the require-
ment for seagrass as settlement substratum (Pollux et
al. 2007), combined with the well-documented impor-
tance of seagrasses as feeding grounds for haemulids
and lutjanids (Ogden & Ehrlich 1977, Verweij et al.
2006). Furthermore, close proximity of highly struc-
tured habitat types may also provide an effective corri-
dor that enhances survival during spatial transitions be-
tween habitat types (Dorenbosch et al. 2004).
Evidence now exists demonstrating that many early
stage fish are capable of active habitat selection
through well-developed sensory and locomotory func-
tions (Leis & McCormick 2002), and that behavioural
preferences for settlement substratum may be medi-
ated by the amount of substratum (McDermott &
Shima 2006). Yet virtually nothing is known about the
process of hierarchical selection of habitat from region
to seascape to individual patch. For example, larval or
spawning adult fish may select patches suitable for
settlement and spawning that are also surrounded by
resources capable of supporting the sequence of
developmental stages and post-settlement movements
required to complete the life cycle. Further studies are
required to elucidate on the complex functional inter-
action between seascape structure and the various
ecological processes (settlement, predation, competi-
tion, growth rate, etc.) that determine fish species dis-
tribution patterns in nearshore marine environments.
Furthermore, future seascape studies should investi-
gate the influence of spatial and thematic resolution
when using benthic habitat maps and may also use-
fully incorporate additional environmental variables at
multiple scales, including substratum rugosity and the
physical and chemical properties of the surrounding
water.
Implications for resource management
The tendency to homogenise or subsume ecologically
important habitat variability in order to increase opera-
tional effectiveness has serious implications for the way
that we understand and manage our environment.
There is now an urgent need to understand the influ-
ence of seascape structure and to begin to incorporate
seascape spatial patterning into resource management
strategies. For instance, when designating manage-
ment units such as critical habitat for multi-habitat
users, it is important to look beyond individual habitat
types toward identification of critical seascapes at
scales appropriate to the movements of target species.
However, the apparent diversity of the species-specific
response to seascape structure, combined with a lack of
information on which structural types form optimal
habitat, highlight the need for a wider application of the
multi-scale seascape approach, with the specific objec-
tive of informing management. With regard to environ-
mental change, if seascape structure as a whole is
important, then its functional integrity may change
through the loss or gain of a single habitat type. Loss of
seagrasses adjacent to mangroves may mean that man-
groves can no longer be used by some species due to
reduction of supplementary or complementary food re-
sources, or of critical settlement substratum, or by dis-
rupting the functional connectivity between mangroves
and coral reefs. The results presented here are consis-
tent with the recommendation for conservation efforts
to protect seascapes with high connectivity between
mangroves, seagrasses and coral reefs (Mumby et al.
2004). In addition, we add the caveat that a seascape
type providing optimal function for one species may be
sub-optimal for another species.
Acknowledgements. This research was supported by NOAA’s
Coral Reef Conservation Program. We thank the staff of the
Biogeography Team at NOAA’s Center for Coastal Monitor-
ing and Assessment for field data collection; the Department
of Marine Science at the University of Puerto Rico
(Mayaguez) for field support; Captain Nazario for boat trans-
portation whilst in Puerto Rico; and E. Finnen for GIS techni-
cal support. We also extend a massive thank you to K. M.
Pittman and 4 anonymous reviewers for extensive comments
that helped in the refinement of this manuscript.
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Editorial responsibility: Otto Kinne (Editor-in-Chief),
Oldendorf/Luhe, Germany
Submitted: December 5, 2006; Accepted: May 14, 2007
Proofs received from author(s): October 2, 2007
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Seascape ecology is an emerging pattern‐oriented and integrative science conceptually linked to landscape ecology. It aims to quantify multidimensional spatial structure in the sea and reveal its ecological consequences. The seascape ecology approach has made important advances in shallow coastal environments, and increasing exploration and mapping of the deep seabed provides opportunities for application in the deep ocean. We argue that seascape ecology, with its integrative and multiscale perspective, can generate new scientific insights at spatial and temporal scales relevant to ecosystem‐based management. Seascape ecology provides a conceptual and operational framework that integrates and builds on existing benthic ecology and habitat mapping research by providing additional pattern‐oriented concepts, tools and techniques to (1) quantify complex ecological patterns across multiple scales; (2) link spatial patterns to biodiversity and ecological processes; and (3) provide ecologically meaningful information that is operationally relevant to spatial management. This review introduces seascape ecology and provides a framework for its application to deep‐seabed environments. Research areas are highlighted where seascape ecology can advance the ecological understanding of deep benthic environments.
... Emphasis is placed on the choice of conceptual model for representing seascape structure (patch matrix, patch mosaic, gradient models; McGarigal et al. 2009), understanding and quantifying the effects of thematic and spatial map resolution, map classification, the scale of analyses, and any bias caused by the propagation of spatial errors through the analytical process (Kendall et al. 2011, Wedding et al. 2011, Lecours et al. 2015, Lecours 2017. Adopting such novel, multi-scale techniques from landscape ecology has advanced spatial predictive modelling, with examples from shallow tropical waters (Pittman et al. 2007, Purkis et al. 2008, Wedding et al. 2008, Stamoulis et al. 2018, temperate waters (Pittman & Costa 2010), Arctic waters (Huettmann et al. 2011, Misiuk et al. 2018, deep-sea environments (Ross & Howell 2013), and the global ocean (Wei et al. 2010). Application of machine-learning algorithms that allow interactions between predictor variables across multiple spatial scales have enabled seascape heterogeneity to be better considered, leading to new hypotheses on ecological responses and boosted model performance (Huett mann & Diamond 2006, Pittman & Brown 2011, Humphries et al. 2018, Lacharité & Brown 2019. ...
... Sub-optimal sampling designs could result from the lack of consideration of the 4Cs, with potential to bias results in comparative studies leading to erroneous conclusions on the effectiveness of management actions. Where benthic maps are available, seascape ecology can help recognise context-dependency (Bradley et al. 2020) and can facilitate re-analyses of historical data with inclusion of seascape patterns and shift focus to habitat mosaics, or 'seascape types' (sensu Pittman et al. 2007) instead of single habitat types (Pasher et al. 2013, Bradley et al. 2020). Although few examples exist, spatially explicit simulation modelling can be used to optimise sampling designs that account for seascape patterns, processes, and scale (Albert et al. 2010, Zurell et al. 2010, Hovel & Regan 2018. ...
... Structural characteristics of the seafloor, specifically topographic complexity and depth, are key drivers in fish distribution (Friedlander and Parrish, 1998;Pittman et al., 2007). Typically, higher demersal fish biodiversity is found over areas with high topographical complexity (e.g. ...
... Según el estándar de clasificación ecológica marina y costera de los Estados Unidos -CMECS, por sus siglas en inglés-FGDC (2012), los biotopos son la combinación de ensamblajes de especies específicos caracterizados por representar patrones espacialmente reconocibles, donde además se incluyen aspectos ambientales específicos. Cuando se delimitan múltiples tipos de hábitats también se ha utilizado el término "tipos de paisaje" (Pittman et al. 2007;Nagelkerken et al., 2015), donde cada tipo es una unidad. El término "unidad", en ecología del paisaje puede ser definido a cualquier escala; por ello también puede conformar un mosaico de múltiples parches de asociaciones de organismos y/o presentar una topografía compleja con varias geoformas; así mismo también se han utilizado términos similares para clasificar el océano abierto, es decir complejos oceánicos a "unidades de paisaje oceánicas" (Bowman et al., 2018). ...
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The cartography of ecological units at a detailed level requires differentiating them by the associations of coral species, but also by the use of physical and biotic attributes. Remote sensors have limitations to perform this type of discrimination; this is not only due to the spectral response of the coral species, which is very similar, but also to their variation in abundance, which can be considerable within the same ecological unit; the abundance can be so low, that their identification can go unnoticed when interpreting satellite images. In order to provide clues to propose criteria for the delimitation of ecological units, in the present study, and through the use of Bray-Curtis similarity index and multivariate analyzes, spatial distribution patterns of biotic assemblages and their relationship with the geomorphology in the Seaflower Biosphere Reserve were identified and analyzed, both, at the level of reef complexes [Serrana, Roncador, Quitasueño and Providence Island (SRQP)], and in the particular case of San Andrés Island (SAI) coral reefs. In general, spatial distribution trends among the identified biotic assemblages were recognised with respect to geomorphology, when they nested to one or two specific geomorphological units. This shows that the geomorphological units, rather than indicate the presence of a particular ecological unit, provide indications of a series of possibilities. In some cases, the patterns were expressed within the geomorphological units, which suggest the need to carry out analyses at a more detailed geomorphological scale. On the other hand, the increase in the abundance of macroalgae seems to create noise in the identification of ecological units, and that these present a high abundance does not necessarily indicate that the richness or the coral abundance should be low, which implies the need to establish delimitation thresholds. It is concluded that in order to establish criteria for the delimitation of ecological units at higher detail, the spatial distribution patterns of biotic assemblages are indispensable. Consequently, four criteria are proposed for the delimitation of ecological units (1. Biotic, 2. Biotic-Geomorphology-Zoning, 3. Biotic-Cover (Remote sensing), 4. Biotic-Macroalgae), which in addition to including biotic assemblages and geomorphological aspects, they must be complemented with various physical attributes that make up the landscape of these coral areas.
... typology, extent and diversity) and configuration (i.e. spatial arrangement and geometrical complexity) on nekton distribution in estuaries and coastal lagoons (Irlandi and Crawford 1997;Pittman et al. 2007;Staveley et al. 2017;Scapin et al. 2018). Seascape studies have major implications for ecosystem management and biodiversity conservation, tackling ecological issues from a large-scale perspective and taking into account spatial heterogeneity (Mumby 2006;Engelhard et al. 2016;Betzabeth and de los Ángeles 2017). ...
Article
Fisheries are a staple human activity supported by coastal lagoons. Together with water quality and trophic status, lagoon morphology is acknowledged as one of the main ecological drivers of fishery yields; however, the role of lagoon seascape structure is still poorly understood. This paper investigates how morphological variables, habitat distribution and seascape diversity and complexity affect yields of artisanal fishery performed with fyke nets in the Venice Lagoon (northern Adriatic Sea, Italy). Two spatial scales were considered in the analysis, with water quality parameters (temperature, salinity, dissolved oxygen, turbidity, water residence times, N, P and chlorophyll-a concentrations) being measured at a fine, fyke-net scale and morphological (average bottom elevation and sediment grain size) and habitat features (habitat proportion, diversity and complexity) being measured at a broader, seascape scale. Generalised linear mixed models were employed to model 8 years of nekton and green crab catches, disentangling the role of broad-scale morphology and seascape from that of fine-scale water quality. Broad-scale variables clearly influenced fishery target species. Among them, lagoon residents were associated with specific morphological and habitat characteristics, while marine migrants showed a stronger link with overall habitat diversity and complexity. This evidence emphasises how artisanal fishery in the Venice Lagoon relies on the conservation of morphological and habitat heterogeneity. Moreover, it highlights how habitat restoration performed at the seascape level should also be taken into account, in addition to controlling hydrology and water quality, when managing fishery resources in coastal lagoons.
... typology, extent and diversity) and configuration (i.e. spatial arrangement and geometrical complexity) on nekton distribution in estuaries and coastal lagoons (Irlandi and Crawford 1997;Pittman et al. 2007;Staveley et al. 2017;Scapin et al. 2018). Seascape studies have major implications for ecosystem management and biodiversity conservation, tackling ecological issues from a large-scale perspective and taking into account spatial heterogeneity (Mumby 2006;Engelhard et al. 2016;Betzabeth and de los Ángeles 2017). ...
Article
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Fisheries are a staple human activity supported by coastal lagoons. Together with water quality and trophic status, lagoon morphology is acknowledged as one of the main ecological drivers of fishery yields; however, the role of lagoon seascape structure is still poorly understood. This paper investigates how morphological variables, habitat distribution and seascape diversity and complexity affect yields of artisanal fishery performed with fyke nets in the Venice Lagoon (northern Adriatic Sea, Italy). Two spatial scales were considered in the analysis, with water quality parameters (temperature, salinity, dissolved oxygen, turbidity, water residence times, N, P and chlorophyll-a concentrations) being measured at a fine, fyke-net scale and morphological (average bottom elevation and sediment grain size) and habitat features (habitat proportion, diversity and complexity) being measured at a broader, seascape scale. Generalised linear mixed models were employed to model 8 years of nekton and green crab catches, disentangling the role of broad-scale morphology and seascape from that of fine-scale water quality. Broad-scale variables clearly influenced fishery target species. Among them, lagoon residents were associated with specific morphological and habitat characteristics, while marine migrants showed a stronger link with overall habitat diversity and complexity. This evidence emphasises how artisanal fishery in the Venice Lagoon relies on the conservation of morphological and habitat heterogeneity. Moreover, it highlights how habitat restoration performed at the seascape level should also be taken into account, in addition to controlling hydrology and water quality, when managing fishery resources in coastal lagoons.
... Seagrasses can be nurseries from which juvenile fish move to adjacent habitats or serve as feeding or sheltering grounds (Nagelkerken, 2000;Dorenbosch, 2004;Nakamura and Sano, 2004). Within seagrass habitats, fish communities can be affected, among other factors, by seagrass patch size and shape (Salita et al., 2003), but also by the seascape context -the spatial organization of the various elements of the submarine landscape, including the availability of adjacent alternative structured habitats (Dorenbosch et al., 2007;Pittman et al., 2007;Unsworth et al., 2008). Along the east coast of the Adriatic Sea (Croatia), Posidonia oceanica beds occur at depths ranging from 0 to about 36 meters on unconsolidated sediments and flat rock or rock boulders (Zubak et al., 2020). ...
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Marine underwater habitats dominated by seagrass Posidonia oceanica play an essential role in fish community assembly, affecting taxonomic and functional diversity, abundance and fish behavior. The value of seagrasses as habitat depends on the spatial arrangement of the seascape elements and the availability of alternative habitats. Little is known about the effect of the seascape context of P. oceanica meadows on fish assemblages in the Mediterranean Sea. To identify P. oceanica meadows' relative importance as a habitat for fishes, fish communities in the Croatian Adriatic Sea were investigated, using SCUBA lure-assisted visual census. The results show a significant effect of different arrangements of P. oceanica meadows' seascape elements and surrounding habitats on fish community structure. Fragmented mosaic meadows with P. oceanica growing directly on and between rocky-algal reefs/boulders had significantly higher fish abundances compared to both types of continuous meadows (bordering rock and bordering sand). Continuous meadows bordering sand harbored the highest number of unique species. Evidence that alternative structured habitats within proximity to seagrass beds may affect the community structure of associated fish assemblages is provided, highlighting the need to consider P. oceanica meadows' seascape context in conservation management and experimental design for fish community structure.
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Mangroves and seagrasses are important nurseries for many marine species, and this function is linked to the complexity and context of these habitats in coastal seascapes. It is also connected to bathymetric features that influence habitat availability, and the accessibility of refuge habitats, but the significance of terrain variation for nursery function is unknown. To test whether seafloor terrain influences nursery function, we surveyed fish assemblages from mangrove and seagrass habitats in 29 estuaries in eastern Australia with unbaited underwater cameras and quantified the surrounding three-dimensional terrain with a set of complementary surface metrics (that is, depth, aspect, curvature, slope, roughness) applied to sonar-derived bathymetric maps. Terrain metrics explained variability in assemblages in both mangroves and seagrasses, with differing effects for the entire fish assemblage and nursery species composition, and between habitats. Higher depth, plan curvature (concavity or convexity) and roughness (backscatter) were negatively correlated with abundance and diversity in mangroves and positively linked to abundance and diversity in seagrass. Mangrove nursery species (6 species) were most abundant in forests adjacent to flats with concave holes, rough substrates and low-moderate depths, whereas seagrass nursery species (3 species) were most abundant in meadows adjacent to deep channels with soft mounds and ledges. These findings indicate that seafloor terrain influences nursery function and demonstrate contrasting effects of terrain variation in mangroves and seagrass. We suggest that incorporating three-dimensional terrain into coastal conservation and restoration plans could help to improve outcomes for fisheries management, but contrasting strategies might be needed for different nursery habitats.
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The mechanisms that govern fauna-habitat associations across multiple spatial scales remain largely undefined. Can environmental factors structure fauna-habitat associations over both local and global spatial scales, alongside biogeographical processes and patterns? We compare the extent to which the use of mangroves by fishes is consistent within and between biogeographic locations, and whether any similarities and differences can be attributed to the environmental context of those forests, such as the physical environment, seascape composition and constraints on access by fishes. We focus on three important proxies of these structuring forces for fish—salinity, distance to reefs and tidal amplitude. Using directly comparable remote underwater visual census from a range of diverse environmental contexts in the Central and Eastern Indo-Pacific, we examine similarity in the family-level taxonomic composition of fish assemblages in mangrove forests. Local environmental context appears to explain similarities and differences in mangrove association by fishes at both regional and local scales across the Indo-Pacific. There were strong consistencies in taxonomic composition in similar environmental contexts despite geographic separation. Tidal amplitude was a powerful explanatory factor that interacted with both distance to reef and salinity in partitioning variation in fish assemblage structure. Substantial differences in the use of mangroves between regions appear to be independent of historical biogeography, relating instead to local context. Our findings suggest that the effects of local context on habitat suitability can play out over biogeographical scales, and global similarities in fauna-habitat associations may be partially explained by comparable environmental contexts, with important management implications.
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Mangrove forests are one of the world's most threatened tropical ecosystems with global loss exceeding 35% (ref. 1). Juvenile coral reef fish often inhabit mangroves, but the importance of these nurseries to reef fish population dynamics has not been quantified. Indeed, mangroves might be expected to have negligible influence on reef fish communities: juvenile fish can inhabit alternative habitats and fish populations may be regulated by other limiting factors such as larval supply or fishing. Here we show that mangroves are unexpectedly important, serving as an intermediate nursery habitat that may increase the survivorship of young fish. Mangroves in the Caribbean strongly influence the community structure of fish on neighbouring coral reefs. In addition, the biomass of several commercially important species is more than doubled when adult habitat is connected to mangroves. The largest herbivorous fish in the Atlantic, Scarus guacamaia, has a functional dependency on mangroves and has suffered local extinction after mangrove removal. Current rates of mangrove deforestation are likely to have severe deleterious consequences for the ecosystem function, fisheries productivity and resilience of reefs. Conservation efforts should protect connected corridors of mangroves, seagrass beds and coral reefs.
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In June 2000, the National Ocean Service and University of Puerto Rico initiated a long-term reef-fish-monitoring program in La Parguera, Puerto Rico. Objectives of this ongoing work are to: 1) develop spatially-explicit estimates of reef fish habitat utilization patterns to aid in defining essential habitats, and 2) provide a quantitative and ecologically sound foundation to delineate marine reserve boundaries. Central to this effort are recently completed digital and georeferenced benthic habitat maps for the near-shore waters of Puerto Rico. The GIS-based map served as a framework for development of a spatially stratified reef-fish-monitoring program across the shelf. Simultaneous collections of fish size and abundance data, and micro-scale habitat distribution and quality data were taken along a 25 x 4 m transect for each monitoring station. Sampling included coral reef, mangrove, and seagrass habitats within three cross-shelf zones unique to the insular shelf of La Parguera (inner lagoon, outer lagoon, and bank-shelf). A total of 106 stations were surveyed during the first year of sampling. Over 50,000 fishes, representing 123 species and 36 families were counted. Analyses showed clear patterns of habitat utilization across the seascape, and ontogenetic shifts in habitat selection within some species. Results also indicated that habitat type was more important than cross-shelf location in determining spatial patterns among reef fishes in the study area. Mesoscale spatially-explicit logistic models were developed to estimate distribution and expected density of some species among habitats.
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Similar to nearshore systems in temperate latitudes, the nursery paradigm for tropical back-reef systems is that they provide a habitat for juveniles of species that subsequently make ontogenetic shifts to adult populations on coral reefs (we refer to this as the nursery function of back-reef systems). Nevertheless, we lack a full understanding of the importance of the nursery function of back-reef systems to the maintenance of coral reef fishes and invertebrate populations; the few studies that have examined the nursery function of multiple habitats indicate that the relationship between juvenile production in back-reef habitats and their subsequent contribution to adult populations on reefs remain poorly understood. In this synopsis we (1) synthesize current knowledge of life history, ecological and habitat influences on juvenile distribution patterns and nursery function within back-reef systems; (2) outline a research strategy for assessing the nursery function of various habitat types in back-reef systems; and (3) discuss management recommendations, particularly in regard to how improved knowledge of the nursery function of back-reef systems can be used in fisheries and ecosystem management, including habitat conservation and restoration decisions. The research strategy builds on research recommendations for assessing the nursery function of temperate habitats and includes 4 levels of research: (1) building conceptual models to guide research and management; (2) identifying juvenile habitat use patterns; (3) measuring connectivity of juvenile and adult populations between habitats; and (4) examining ecological processes that may influence patterns assessed in Level 2 and Level 3 research. Research and modeling output from Levels 1 to 4 will provide an improved ecological understanding of the degree and importance of interconnections between coral reef and adjacent back-reef systems, and will provide information to managers that will facilitate wise decisions pertaining to habitat conservation, habitat restoration, and ecosystem-based management, and the maintenance of sustainable fisheries.
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Mangroves are important nursery and feeding areas for fish. Their rich invertebrate faunas render them productive feeding areas, while their shallow waters and structural complexity provide sanctuary habitats at a variety of scales. However, in most parts of the world mangroves are available to fish for only part of the time because they are alternately inundated and exposed by the high-tide/low-tide cycle. As a result, few fish can use mangroves exclusively but must migrate in and out of the mangroves with the tide, occupying alternative habitats when mangroves are unavailable. These movements connect the mangroves and the alternative habitats to form an 'interconnected habitat mosaic'. Living in a habitat mosaic puts limits on the patterns of life possible in mangrove systems, complicates trophic structures, and creates the need for tactics and strategies to meet the challenges imposed by movement among components of the mosaic. Moreover, this biological connectivity means that understandings of trophic relationships, life-history strategies, predation and mortality, and patterns of distribution and abundance must be set in a spatially and temporally variable context. Despite the obvious consequences and importance of biological connectivity in mangrove ecosystems, it has often not been given appropriate consideration in the development of theories and paradigms.
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Day-night changes in fish communities were quantified in 6 associated shallow-water biotopes within a single bay: mangroves, seagrass beds, algal beds, channel, fossil reef boulders, and notches in fossil reef rock. All biotopes, except the algal beds, showed a strong reduction in fish density and species richness at night, caused by absence of diurnally active fishes and migrations of Haemulidae and Lutjanidae to the seagrass beds. The fish fauna of the different biotopes showed a relatively high dissimilarity between day and night. This dissimilarity is largely caused by absence of Acanthuridae, Chaetodontidae, Labridae, Pomacentridae, Scaridae and Sparidae at night. These fishes seek shelter at night in, amongst others, the channel, notches and boulders. The balloonfish Diodon holocanthus utilised almost all biotopes as shelter as well as feeding sites. The wide distribution of its preferred food (molluscs) probably explains its distribution in most biotopes at night. The nocturnally active Haemulidae and Lutjanidae, on the other hand, migrated from their daytime shelter sites to the seagrass beds at night to feed. Some of these fishes also migrated to the algal beds to feed. The preference of Haemulidae and Lutjanidae for the seagrass bed as a feeding biotope, instead of other bay biotopes, appears to be related to the relatively high availability of their preferred food (Tanaidacea and Decapoda) as determined by digestive tract analysis. Other bay biotopes showed much lower densities of such food items compared to the seagrass beds.
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There has been much controversy over the degree to which mangroves and seagrass beds function as nursery habitats for the juveniles of fish species that live on coral reefs as adults. In previous studies we have shown that the juveniles of at least 17 Caribbean reef-fish species are highly associated with bays containing mangroves and seagrass beds as nurseries, and that juveniles of these species are absent in bays lacking such habitats. In this study we therefore hypothesised that on islands lacking these bay nursery habitats, adults of these fish species will be absent or show low densities on the coral reef. Densities of the 17 species were compared between the reefs of Caribbean islands with and without mangroves and seagrass beds. On reefs of islands lacking these habitats, complete absence or low densities were observed for 11 of the 17 species, several of which are of commercial importance to fisheries. This finding suggests a Very important nursery function of such habitats and implies that the densities of several fish species on coral reefs are a function of the presence of nearby bays containing mangroves and seagrass beds as nurseries. The results indicate that degradation or loss of these habitats could have significant impacts on reef-fish stocks in the Caribbean.
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Species respond to habitat at different spatial scales, yet many studies have considered this response only at relatively small scales. We developed a technique and accompanying software (Focus) that use a focal patch approach to select multiple sets of spatially independent sites. For each independent set, regressions are conducted between the habitat variable and counts of species abundance at different scales to determine the spatial scale at which species respond most strongly to an environmental or habitat variable of interest. We applied the technique to determine the spatial scales at which 12 different species of cerambycid beetles respond to forest cover. The beetles responded at different scales, from 20 to 2000 meters. We expect this technique and the accompanying software to be useful for a wide range of studies, including the analysis of existing data sets to answer questions related to the large-scale response of organisms to their environment.
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We studied the settlement patterns of three Caribbean coral reef fishes in three different habitat types: mangroves, seagrass beds, and coral reefs. The settlement patterns of the three species were not random and could best be explained by active habitat selection during settlement. "Acanthurus bahianus" preferentially settled on the shallow reef flat and in adjacent seagrass beds, "Lutjanus apodus" settled exclusively into mangroves, and "Ocyurus chrysurus," settled into both mangroves and seagrass beds. The settlement patterns of these three species reflect their habitat utilization during later juvenile stages. This study, therefore, suggests that the higher juvenile densities in mangroves and seagrass beds are determined by habitat selection during settlement rather than by post-settlement processes. This habitat selection during settlement is in accordance with the assumed importance of mangroves and seagrass beds as juvenile habitats of coral reef fishes and underlines the pressing need for their conservation.