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Effect of water quality variation on fish assemblages in an anthropogenically impacted tropical estuary, Colombian Pacific

  • Universidad Nacional de Colombia - Sede Palmira

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In tropical estuaries, fish diversity varies spatially and temporally due to behavioral processes such as reproductive migrations, predator avoidance, and foraging, which are affected by water quality. Eutrophication is one of the main factors affecting water quality in estuaries. The objective of this study was to determine variation in fish assemblage explained by fluctuating water quality in the Buenaventura Bay. Fish were captured using artisanal trawl nets during the wet, dry, and transitional seasons at four sampling sites. Additionally, alkalinity; phosphate, nitrite, and nitrate concentrations; dissolved oxygen; pH; temperature; and suspended solids were measured. Multivariate analysis was used to assess the effect of water quality on fish assemblage. In Buenaventura Bay, the assemblage composition of Pseudupeneus grandisquamis, Daector dowi, and Citharichthys gilberti was affected by nitrate concentration. Moreover, large fish biomasses were associated with high nitrite concentration, intermediate salinity, and low dissolved oxygen, suggesting that these estuaries are dominated by species tolerant to poor water quality. Species richness was associated with low nitrate and phosphate concentrations, more suitable water quality indicators, and intermediate temperatures. These results suggest that the deteriorating water quality of estuaries as a result of the anthropogenic impact could increase dominance and decrease richness, resulting in structural changes of fish assemblages.
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/Published online: 30 April 2020
Environmental Science and Pollution Research (2020) 27:2574025753
Effect of water quality variation on fish assemblages in an
anthropogenically impacted tropical estuary, Colombian Pacific
Guillermo Duque
&Diego Esteban Gamboa-García
&Andrés Molina
&Pilar Cogua
Received: 13 January 2020 /Accepted: 21 April 2020
#The Author(s) 2020
In tropical estuaries, fish diversity varies spatially and temporally due to behavioral processes such as reproductive migrations,
predator avoidance, and foraging, which are affected by water quality. Eutrophication is one of the main factors affecting water
quality in estuaries. The objective of this study was to determine variation in fish assemblage explained by fluctuating water
quality in the Buenaventura Bay. Fish were captured using artisanal trawl nets during the wet, dry, and transitional seasons at four
sampling sites. Additionally, alkalinity; phosphate, nitrite, and nitrate concentrations; dissolved oxygen; pH; temperature; and
suspended solids were measured. Multivariate analysis was used to assess the effect of water quality on fish assemblage. In
Buenaventura Bay, the assemblage composition of Pseudupeneus grandisquamis,Daector dowi,andCitharichthys gilberti was
affected by nitrate concentration. Moreover, large fish biomasses were associated with high nitrite concentration, intermediate
salinity, and low dissolved oxygen, suggesting that these estuaries are dominated by species tolerant to poor water quality.
Species richness was associated with low nitrate and phosphate concentrations, more suitable water quality indicators, and
intermediate temperatures. These results suggest that the deteriorating water quality of estuaries as a result of the anthropogenic
impact could increase dominance and decrease richness, resulting in structural changes of fish assemblages.
Keywords Estuarine fish .Tropical estuary .Inorganic pollution .Nitrates .Nitrites .Phosphates .Buenaventura Bay
The geographic, biotic, and abiotic factors affect fish richness
and abundance in estuaries (Brown et al. 2007). The geo-
graphic factors include connectivity, while the biotic factors
include reproductive migrations, predator avoidance, and for-
aging (Sheaves et al. 2015) and the abiotic factors include
salinity, temperature, dissolved oxygen, sediments, and nutri-
ents, among others (Menegotto et al. 2019; Rau et al. 2019).
The fluctuation of these physicochemical variables determines
the water quality, influencing the dynamic of aquatic organ-
isms and regulating the ecological processes (Ji 2008).
Water quality of estuarine ecosystems can be characterized
using the concentration ranges of nitrogen, phosphorous, and
dissolved oxygen, among other characteristics, which pro-
mote appropriate ecosystem functioning and support the gen-
eration of ecosystem services (Foley et al. 2015; Pouso et al.
2018). In particular, the Colombian Pacific region is strongly
socioeconomically dependent on the ecosystem services for
the local fish consumption and the commercialization of fish-
ery resources (Saavedra-Díaz et al. 2016; Salas et al. 2019;
Villanueva and Flores-Nava 2019). However, previous studies
Responsible editor: Vedula VSS Sarma
*Guillermo Duque
Diego Esteban Gamboa-García
Andrés Molina
Pilar Cogua
Facultad de Ingeniería y Administración, Universidad Nacional de
Colombia Sede Palmira, Palmira, Valle del Cauca, Colombia
Facultad de Ciencias Agrarias, Universidad Nacional de Colombia
Sede Palmira, Palmira, Valle del Cauca, Colombia
Universidad Nacional de Colombia Sede Caribe, San Andrés y
Providencia, Colombia
Facultad de Ciencias Básicas, Universidad Santiago de Cali,
Cali, Valle del Cauca, Colombia
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
from this region suggest that pollutant concentrations affect
benthic communities (Martínez et al. 2019) and that these
pollutants are bioaccumulating in organisms of commercial
interest (Duque and Cogua 2016; Gamboa-García et al.
2020) as well as in organisms at higher trophic levels
(Gamboa-García et al. 2018b).
Water quality is affected by anthropogenic waste discharge,
which in turn affects pollutant concentrations and physicochem-
ical variables and, ultimately, ecological processes such as the
nutrient cycles, primary production, trophic relationships, and
consumerspecies dynamics (Barletta et al. 2019; Jickells et al.
2017;Lemleyetal.2017;Nieetal.2018; Warry et al. 2016). In
particular, the effect of eutrophication of coastal ecosystems
caused by nutrients from rivers and discharge from adjacent
communities on fish assemblages remains unknown.
Eutrophication may positively affect fish assemblage by increas-
ing secondary production through a bottom-up trophic cascade
or may negatively affect fish assemblage by subjecting fish to
physiological stress or hypoxia (de Mutsert et al. 2016; Fong and
Fong 2018; Kenworthy et al. 2016;Nelsonetal.2019; Villafañe
et al. 2017; Wilkerson and Dugdale 2016).
Taking into consideration the multiple potential environ-
mental impacts, it is critical to study estuarine biodiversity
and its dynamics at different scales to understand their pro-
cesses and mechanisms (Duque et al. 2018; França et al. 2011;
Sheaves and Johnston 2009; Teichert et al. 2017; Vilar et al.
2013), as well as to elucidate the effects of eutrophication in
these ecosystems. Species richness, abundance, and fish bio-
mass can be measured to assess the effect of variations in
nutrient concentrations in the ecosystem. Fish biomass, in
particular, may be a key variable because certain species are
sensitive to gaining or losing weight as a result of eutrophica-
tion (de Mutsert et al. 2016), and may affect the total of each
fish population biomass as well.
We hypothesized that (i) the diversity of fishes varies
among sampling seasons and sites, (ii) the abundance of the
most representative fish species of the estuary can be ex-
plained by changes in water quality, and (iii) the fish species
richness and fish biomass are associated with changes in water
quality. The main objective of this study was to assess the
effect of water quality on estuarine fish diversity, which would
enable the evaluation of potential eutrophication in
Buenaventura Bay.
Materials and methods
Study area
This study was carried out in the estuary of Buenaventura Bay
at the Tropical Eastern Pacific (77° 16Wto3°56N). The
estuary spans approximately 70 km
and has a 16-km-long
and 5-m-deep central canal. The unique seawater inflow is
known as La Bocana and is formed by Punta Bazán in the
north and Punta Soldado in the south, which are approximate-
ly 1.6 km apart (Castaño 2002).
The rivers Dagua (66 m
into this bay (Otero 2004). Moreover, this bay has one of the
highest levels of humidity and precipitation worldwide, with ~
6980 mm of average annual rainfall and two wet seasons (from
September to November and April to June) with an average
monthly rainfall of 567 mm, which represents a significant fresh-
water source (Cantera and Blanco 2001). The access channel for
ships is 9.5 and 11.3 m deep during the low and high tides,
respectively; however, as a result of maintenance dredging activ-
ities and canal expansion, the depth at the channel may reach
more than 16 m (Montenegro and Torres 2016).
In the estuary, there are two well-differentiated zones: the
interior and the exterior bays. Within the interior bay, port
activities combined with (i) waste from fishing, logging, and
mining activities; (ii) discharge from rivers that flow into the
bay; and (iii) domestic discharge from the same municipality
have contributed to the increasing levels of potential pollut-
ants. These pollutants are mainly wastewater which include,
nitrates, nitrites, sulfates, phosphates, and coliforms, increas-
ing the organic matter in both, during the low and high tides
(IIAP 2013). In contrast, the exterior bay is influenced by a
larger touristic complex and it is more marine influenced
(Cantera and Blanco 2001; Palacios and Cantera 2017).
Field sampling
In order to study the different hydroclimatic conditions of the
bay, we conducted three sampling trips at different seasons.
The first one during the wet season (November 2018, total
month precipitation= 753.8 mm), the second one in the dry
season (March 2019, total month precipitation = 321.2 mm),
and the last one in the transitional season (July 2019, total
month precipitation = 469.2 mm) (IDEAM 2020). The four
sampling sites represent a wide range of water salinity, water
quality, nutrient availability, and fish assemblage dynamics.
All samples were taken at sites with water less than 8 m depth.
We sampled four sites within the estuary: The first one going
from the inside of the bay to the outside was the river estuary
(RE, 77° 633.1W and 3° 5051.5N), which is the innermost
site and is influenced by the Dagua River that flows into it. This
site (RE) is the closest sampling site to the urban area of
Buenaventura Bay, with around 300,000 inhabitants (DANE
2019). The second site was the inner estuary (IE, 77° 724.9
W and 3° 524.4N), which is also located in the internal estuary
but is characterized for being a little further from the river dis-
charge and the main urban area. The third site was the outer
estuary (OE, 77° 935.9W and 3° 5058.7N), which is located
in the external estuary and is characterized by having more
compacted bottoms and further away from the main urban area.
Nevertheless, this site is located near the district of La Bocana,
Environ Sci Pollut Res (2020) 27:2574025753
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which is inhabited by approximately 3000 people who are highly
dependent on marine resources for their own consumption, for
tourism (9000 a year approximately), and for supplying the main
urban area markets (Escobar-Cárdenas 2009), which is the largest
portion of the fish landings (no data); The fourth site was the
marine estuary (ME, 77° 1211.4W and 4952.44N),
which is the outermost site and is more influenced by marine
conditions and has tourism along the year (15,000 approximate-
ly). The average distance between sampling sites was 4 km
(Fig. 1).
During each season and at each site, an artisanal trawling
net was used for sampling with three replicates. Each trawl
sampling lasted 10 min and was performed with a net with
2.54-cm mesh size and 8-m width at the mouth.
Water quality variables, including salinity, dissolved oxy-
gen, pH, temperature, and suspended solids, were measured in
situ using a multi-parameter probe YSI 556 MPS.
Additionally, water samples were collected to determine alka-
linity as well as nitrite, nitrate, and phosphate concentrations
using a portable photometer YSI 9300.
In order to characterize the community structure, the cap-
tured fish were identified to the species level and counted, and
their total length, standard length, and weight were measured.
Fish identification was performed using published taxonomic
keys (Fischer et al. 1995a,b;FroeseandPauly2017;
Marceniuk et al. 2017; Robertson and Allen 2015; Tavera
et al. 2018).
Data analysis
Community structure variations were assessed using species
richness (i.e., number of species) and biomass (in g m
calculated using all the captured fish. Abundanceanalysis was
performed using only the most representative species, which
were selected using the mean of the highest percent frequency
(Eq. 1), abundance (Eq. 2), and weight (Eq. 3)(Martinsetal.
Frequency ¼100 fish species presence
total fish count
Abundance ¼100 number of fish by species
total number of fish
Weight ¼100 individual fish weight by species
total weight
The spatiotemporal analysis was addressed by calculating
species richness and biomass and checking normality, using
square root transformation when required. Analysis of vari-
ance was performed using season, site, and their interaction as
main factors, and Tukeys post hoc test was used to examine
statistically significant differences (p<0.05).
In order to assess water quality, the inorganic nitrogen was
measured (nitrites and nitrates, mg L
), inorganic phospho-
rous (phosphates mg L
), and dissolved oxygen (mg L
), as
recommended by Lemley et al. (2015). Moreover, the analysis
included salinity (PSU, practical salinity units), temperature
(°C), and suspended solids (g L
) measurements.
Additionally, the effect of water quality on the abundances
of the most important species (defined by their frequency)
was calculated by a canonical correspondence analysis
(CCA) using the log(x+ 1) transformed matrix within the R
environment (R Core Team 2013).
On the other hand, the variation in species richness and
biomass explained by water quality was calculated by
Fig. 1 Sampling sites within the
Buenaventura Bay estuary: RE =
river estuary, IE= inner estuary,
OE = outer estuary, ME = marine
25742 Environ Sci Pollut Res (2020) 27:2574025753
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biological descriptors using Bayesian Generalized Additive
Models (GAMs). The models were evaluated by using differ-
ent variable combinations, and these were compared to select
the best model using Akaike information criterion (AIC). For
each variable, the presented models were selected considering
aΔAIC > 2 between the model and the next lowest AIC
(Krause et al. 2019; Martins et al. 2015). All statistical analy-
ses were performed within the R environment (R Core Team
It is important to mention that GAMs were used because
traditional statistical methods are difficult to interpret when
the variables have non-linear relationships (Rudy et al.
2016). Moreover, GAMs have been used for a wide range of
applications, including medicine as well as fishery and envi-
ronmental studies, among others areas of research (Amorós
et al. 2018; de Souza et al. 2018; Elith et al. 2008;Tangetal.
Spatiotemporal variation in fish assemblages
It was collected a total of 69 species belonging to 30 families.
The highest species richness was observed during the transi-
tional season at the RE (20 ± 2) and OE (20 ± 2) (F=10.19,
Tukeysp< 0.001) sites (Table 1). However, the highest bio-
mass (F= 8.69, Tukeysp< 0.001) was observed during the
wet season at the ME site (4.4 ± 2.4 g m
The most representative species (defined using the mean of
frequency, abundance, and biomass) were Sphoeroides
trichocephalus (57.85%), Cathorops multiradiatus
(19.73%), Achirus klunzingeri (18.06%), Lile stolifera
(16.7%), and Pseudupeneus grandisquamis (16.31%). The
highest abundance of Sphoeroides trichocephalus was record-
ed during the transitional season at the RE site (227 ± 14.9
fish) (F=2.16,Tukeysp< 0.05), whereas the highest abun-
dance of Cathorops multiradiatus was recorded during the
wet season at the ME site (51.7 ± 35.4 fish) (F= 18.76,
Tukeysp< 0.001). In contrast, the abundance of Achirus
klunzingeri did not show significant differences when the sea-
son and sampling site interaction was analyzed, and abun-
dance was the highest at the OE site (F=5.08, Tukeysp<
0.01). Similarly, the abundance of Lile stolifera was the
highest during the wet season at the IE site (F= 3.24,
Tukeysp< 0.05). In addition, the abundance of Achirus
klunzingeri was the highest during the dry season at the OE
site (F= 15.14, Tukeysp<0.001)(Table2).
Spatiotemporal variation in water quality
In Buenaventura Bay, the highest salinity was recorded during
the dry season (22.24 ± 2.05 PSU), followed by the transition-
al season (21.17± 1.38 PSU) and the wet season (15.83 ± 0.87
PSU) (F= 1212.01, Tukeysp< 0.001). Moreover, spatial
analysis revealed a salinity gradient, in which salinity was
the lowest in the inner bay (RE and IE) and increased closer
to the sea (OE and ME) (F= 139.51, Tukeysp< 0.001). The
highest salinity was recorded during the dry season at the ME
site (25.56 ± 0.15 PSU) (F= 31.78, Tukeysp<0.001)
(Table 3).
The mean water temperature of the Buenaventura Bay was
the highest during the transitional season (28.82± 0.23 °C),
followed by the wet season (28.09 ± 0.10 °C) and the dry
season (27.01± 0.36 °C) (F= 2252.09, Tukeysp<0.001).
In addition, a spatial pattern was observed, in which the mean
water temperature was the lowest closer to the sea (ME) (F=
96.05, Tukeysp< 0.001). The highest mean water tempera-
ture was recorded during the transitional season at the RE site
(29.00 ± 0.11 °C), and the lowest water temperature was ver-
ified during the dry season at the ME site (26.42 ± 0.02 °C)
(F= 27.10, Tukeysp<0.001).
Across all seasons and sampling sites, the highest concen-
tration of dissolved oxygen was recorded during the wet sea-
son at the RE (6.92 ± 0.29 mg L
), IE (7.17 ± 0.39 mg L
and OE (7.18 ± 0.37 mg L
)sites(F= 11.41, Tukeysp<
0.001). Between seasons, the highest concentration of dis-
solved oxygen was recorded during the wet season (6.92±
0.54 mg L
), followed by the dry (5.65 ± 0.67 mg L
the transitional (5.35 ± 0.48 mg L
)(F= 115.06, Tukeysp<
0.001) seasons. Spatially, the site with the highest dissolved
oxygen concentration was at the ME site (6.31 ± 0.67 mg L
Table 1 Fish species richness and biomass (mean ± standard deviation).
Results from Tukeys pairwise comparisons (two-way p0.05) are
represented with letters for each variable, which are read vertically from
letters a to d. Means were calculated using three replicates. RE,river
estuary; IE, inner estuary; OE, outer estuary; ME, marine estuary
Season Site Fish
Species richness Biomass
Nov 2018 (wet) RE 6 ± 4.6
1.2 ± 0.1
IE 13.8 ± 2.9
1.8 ± 0.5
OE 9.7 ± 3.2
1.2 ± 0.8
ME 15.7 ± 2.1
4.2 ± 2.4
March 2019 (dry) RE 10 ± 4.0
1.2 ± 1.1
IE 7.7 ± 1.5
0.7 ± 0.1
OE 16.7 ± 2.5
2.6 ± 0.8
ME 6.7 ± 4.0
0.7 ± 0.5
July 2019 (transitional) RE 20 ± 2.0
3.8 ± 1.1
IE 13.3 ± 3.8
4.0 ± 0.9
OE 20 ± 2.0
3.5 ± 0.9
ME 7 ± 0.1
0.4 ± 0.2
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Considering the season and sampling site interaction, the
highest concentration of nitrates was recorded during the tran-
sitional season at the IE site (2.56± 0.03 mg L
Tukeysp< 0.001). Among seasons, the highest nitrate con-
centration was recorded during the transitional season (2.15 ±
0.47 mg L
)(F= 92.78, Tukeysp< 0.001). Spatially, the
highest nitrate concentrations were recorded in the inner zone
(RE = 1.73 ± 0.65 mg L
, IE = 1.56 ± 0.75 mg L
decreased toward the sites closer to the sea (OE = 1.46 ±
0.18 mg L
, ME = 1.41 ± 0.5 mg L
)(F= 5.16, Tukeys
p< 0.01) (Table 3).
Across all seasons and sampling sites, the highest concen-
tration of nitrites was recorded during the transitional season
at the IE site (0.17 ± 0.01 mg L
)(F= 9.23, Tukeysp<
0.001). Similarly, nitrite concentration was the highest during
the transitional season (0.13 ± 0.03 mg L
Table 3 Nutrient concentrations across seasons and sampling sites
(mean ± standard deviation). Results from Tukeyspairwise
comparisons (two-way p0.05) are represented with letters for each
water quality variable, which are read vertically from letters a to d.
Means were calculated using three replicates. RE, river estuary; IE,
inner estuary; OE, outer estuary; ME, marine estuary. According to
reports on Australian and African estuaries, nutrient eutrophication
levels can be used to determine water quality. Nitrogen: optimal (<
), low (0.11.0 mg L
), and extremely low (>1.0 mg L
inorganic phosphorous: optimal (< 0.01 mg L
), low (0.010.1mgL
and extremely low (> 0.1 mg L
); dissolved oxygen: optimal (>
), low (25mgL
), and extremely low (<2 mg L
et al. 2015,2017)
(mg L
(mg L
(mg L
Dissolved Oxygen
(mg L
Salinity (PSU) Temperature
wet (Nov 2018) RE 1.64 ± 0.17
0.08 ± 0.01
0.18 ± 0.06
6.92 ± 0.29
14.53 ± 0.27
27.97 ± 0.03
IE 0.96 ± 0.14
0.06 ± 0.02
0.15 ± 0.03
7.17 ± 0.39
15.96 ± 0.50
28.13 ± 0.08
OE 1.27 ± 0.05
0.03 ± 0.01
0.07 ± 0.01
7.18 ± 0.37
16.16 ± 0.18
28.21 ± 0.01
ME 1.14 ± 0.21
0.06 ± 0.01
0.08 ± 0.02
6.43 ± 0.81
16.68 ± 0.21
28.06 ± 0.02
(July 2019)
RE 2.52 ± 0.01
0.11 ± 0.02
0.08 ± 0.01
5.48 ± 0.30
21.49 ± 0.87
29.00 ± 0.11
IE 2.56 ± 0.03
0.17 ± 0.01
5.00 ± 0.14
20.24 ± 0.83 cd 28.83 ± 0.03
OE 1.51 ± 0.13
0.12 ± 0.02
0.13 ± 0.08
4.93 ± 0.11
19.95 ± 0.24
28.96 ± 0.02
ME 2.02 ± 0.35
0.10 ± 0.02
0.07 ± 0.02
6 ± 0.17
23.01 ± 0.39
28.47 ± 0.09
dry (March 2019) RE 1.04 ± 0.03
0.03 ± 0.01
0.12 ± 0.01
5.24 ± 0.09
20.54 ± 0.24
27.17 ± 0.07
IE 1.18 ± 0.1
0.04 ± 0.01
0.15 ± 0.04
5.35 ± 0.24
21.32 ± 0.39
27.20 ± 0.09
OE 1.60 ± 0.17
0.06 ± 0.02
5.51 ± 0.13
21.53 ± 0.13
27.23 ± 0.10
ME 1.07 ± 0.1
0.08 ± 0.01
6.50 ± 0.94
25.56 ± 0.15
26.42 ± 0.02
Table 2 Abundance of the most representative fish species of
assemblages (mean ± standard deviation). Results from Tukeys
pairwise comparisons (two-way p0.05) are represented with letters,
which are read vertically from letters a to d, for each fish species.
Means were calculated using three replicates. RE, river estuary; IE,
inner estuary; OE, outer estuary; ME,marineestuary;S_tri,
Sphoeroides trichocephalus;C_mul,Cathorops multiradiatus;A_klu,
Achirus klunzingeri;L_sto,Lile stolifera;P_gra,Pseudupeneus
Season Site Fish species
S_tri C_mul A_klu L_sto P_gra
Nov 2018 (wet) RE 139 ± 27.8
1 ± 1.7
0.7 ± 1.2 0.7 ± 0.6
0.3 ± 0.6
IE 65.7 ± 18.6
0.3 ± 0.6
0.7 ± 0.6 9.3 ± 8.4 c 0.7 ± 0.6
OE 51 ± 18.5
2 ± 1.7 a 2.3 ± 0.6
ME 5 ± 2.0
51.7 ± 35.4
0.3 ± 0.6
March 2019 (dry) RE 78.3 ± 135.7
3.7 ± 2.3
1.3 ± 2.3 2.7 ± 3.1
3.7 ± 0.6
IE 23.3 ± 18.5
0.3 ± 0.6
2 ± 1.0
OE 91.3 ± 35.2
0.7 ± 0.6 1 ± 1.0
16.3 ± 5.1
ME 1 ± 1.7
0.3 ± 0.6
2.7 ± 3.1
July 2019 (transitional) RE 227 ± 14.9
10.7 ± 3.2
2 ± 1.0
8.3 ± 8.1
1 ± 1.0
IE 121 ± 112.3
1.3 ± 1.2 0.3 ± 0.6
OE 193 ± 67.6
0.7 ± 1.2
1.3 ± 0.6 2.3 ± 2.1
ME 23.3 ± 7.6
0.7 ± 0.6
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Tukeysp< 0.001) and ranged from high concentrations in the
inner estuary (IE = 0.09 ± 0.06 mg L
, RE = 0.074 ±
0.04 mg L
) to low concentration toward the sites closer to
the sea (F= 10.83, Tukeysp<0.001).
Along the estuary, the highest concentration of phosphates
was recorded during the wet season at the RE site (0.18 ±
0.06 mg L
)(F=4.01, Tukeysp< 0.01). Although phos-
phate concentration comparisons were not statistically signif-
icant across seasons (F= 1.94), a gradient was detected with
the inner sites presenting higher concentrations (IE = 0.13 ±
0.04 mg L
, RE = 0.12 ± 0.05 mg L
) than the sites closer to
the sea (OE= 0.09± 0.06 mg L
, ME = 0.07 ± 0.01 mg L
(F=5.36,Tukeysp< 0.01) (Table 3).
Effect of water quality variation on the abundance
of the most representative fish species
The canonical correspondence analysis (CCA) suggested that
the distribution of the most representative estuarine fish spe-
cies and the water quality variables nitrites, nitrates, tempera-
ture, and dissolved solids were significantly correlated on the
first and second ordination axes (r=0.86andr= 0.77, respec-
tively), which explained 32% of the variance between fish
species and water quality and physicochemical variables
(Table 4). The results of the permutational testwere significant
(p= 0.001), indicating that the relationships between fish spe-
cies abundance and water quality variables were significant.
The first axis was positively correlated with nitrites and
temperature and negatively correlated with total dissolved
solids, thus representing the temporal gradient of water qual-
ity, with the dry season samples at one end and wet and
transitional season samples at the other (Fig. 2and Table 4).
The second axis was negatively correlated with nitrites, tem-
perature, and pH, thus differentiatingbetween the seasons and
sampling sites with extreme environmental conditions and the
rest of the sampling sites, with the wet season at the ME site
together with the dry season at the RE site at one end and the
rest of the seasonsite combinations at the other end.
The water quality variables nitrite concentration, tempera-
ture, total dissolved solids, nitrate concentration, and pH sig-
nificantly affected fish assemblage and habitat distribution
comprised by the seasonsampling site interactions.
Moreover, the habitats comprised by the interaction of the
transitional season with the OE and IE sites as well as of the
wet season with the IE site displayed the highest nutrient eu-
trophication, pH, and temperature, although no particular fish
assemblage was associated to these environmental conditions.
Conversely, the environmental conditions characteristic of the
interaction between the dry season and the OE, ME, and RE
sites displayed the lowest nutrient eutrophication and temper-
atures but the highest concentration of dissolved solids, and
these conditions were associated with a fish assemblage of
three species (Fig. 2and Table 4).
It was determined a fish assemblage was composed of
Sphoeroides trichocephalus,Lile stolifera,Achirus
klunzingeri,andOphioscion typicus, which plotted close to
the origin of the axes, suggesting that these fish species are
not affected by the water quality gradient (Fig. 2). A second
fish assemblage composed of Pseudupeneus grandisquamis,
Daector dowi,andCitharichthys gilberti was associated with
Fig. 2 Canonical correspondence analysis ordination plot illustrating the
relationships between the abundance of the most representative species
with sampling sites and water quality variables. Thearrows indicate water
quality variables. Alk =alkalinity,DO = dissolved oxygen, Na =nitrates,
Ni = nitrites, P= phosphates, TDS = total dissolved solids, Te m =
temperature. Unfilled circles represent the combination between seasons
(dry = dry season, rain = wet season, and inter = transitional season) and
sampling sites (RE = river estuary, IE = inner estuary, OE =outerestuary,
ME = marine estuary)
Table 4 Canonical correspondence analysis (CCA) of the most repre-
sentative estuarine fish species and water quality variables. The correla-
tions between fish species abundance and water quality variables are
indicated in italics
Total inertia 1.12
model pvalue 0.001
% of variation explained 20 12
% of variation explained (cumulative) 20 32
Speciesenvironment correlations 0.86 0.77
pvalue 0.001 0.009
Water quality indicator variables pvalue
Nitrites 0.52 0.62 0.001
Temperature 0.76 0.46 0.001
Total dissolved solids 0.37 0.02 0.001
Nitrates 0.22 0.37 0.04
pH 0.09 0.53 0.05
Phosphates 0.17 0.34 0.23
Alkalinity 0.40 0.07 0.24
Dissolved oxygen 0.11 0.09 0.31
Environ Sci Pollut Res (2020) 27:2574025753
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
the dry seasons and low nitrite concentration and temperatures
but high total dissolved solid concentrations (Fig. 2). Finally, a
third fish assemblage composed of Cathorops multiradiatus
and Urotrygon rogersi was associated with low nitrite concen-
tration, temperatures, and pH but high dissolved oxygen con-
centrations (Fig. 2).
Effects of water quality on fish species richness
and biomass variation
The totality of the water quality variables was included in the
univariate GAM. The total fish biomass was significantly af-
fected by concentrationof nitrates, nitrites, and total dissolved
solids; salinity; temperature; and dissolved oxygen (p<0.05),
suggesting that each variable affects fish biomass separately
but only accounts for little variation (Table 5). The largest
variation was explained by concentrations of nitrates (43.4%
(Adj. R
= 0.25)) and total dissolved solids (31.4% (Adj. R
0.35)), and salinity (28.9% (Adj. R
= 0.23)), respectively. The
model fit for each explanatory variable was low; therefore, a
multivariate analysis was performed to assess the overall ef-
fect on fish biomass.
On the other hand, fish species richness was significantly
and individually affected by temperature; salinity; and con-
centrations of total solids, nitrites, and dissolved oxygen
(p< 0.05) but explained only little variation (Table 5). The
largest variation was explained by temperature (39.5% (Adj.
= 0.34)) and salinity (30.2% (Adj. R
=0.24)). Likewise,
the model fit for each explanatory variable was low; therefore,
a multivariate analysis was performed to assess the overall
effect on fish species richness.
Multivariate analysis showed that the best model for fish
biomass included nitrites and dissolved oxygen concentra-
tions and salinity (AIC = 117.97). This model revealed a
positive relationship between fishbiomass and nitrate concen-
tration and non-linear relationships between salinity (degree =
4) and dissolved oxygen concentration (degree = 2.7) and ex-
plained 64.2% of variation (Adj. R
= 0.54). In contrast, the
best multivariate model for fish species richness included ni-
trates, phosphates, temperature, and pH (AIC = 208.17) and
revealed a negative relationship of fish species richness with
phosphate and nitrate concentrations as well as a non-linear
relationship with temperature (degree = 2.7) and explained
61.2% of variation (Adj. R
= 0.52) (Table 6).
The total fish biomass showed a positive relationship with
nitrite concentration and a non-linear relationship with salinity
and dissolved oxygen concentrations, peaking around 17 PSU
for salinityand decreasing at 5.5 mg L
for dissolved oxygen
(Fig. 3).
In contrast, fish species richness showed a negative rela-
tionship with nitrate concentration and was the highest at
mean temperatures between 28 and 29 °C but showed no
significant relationship with pH (Fig. 4).
In summary, fish biomass was the largest at higher nitrite
concentrations, intermediate salinities between 16 and
18 PSU, and dissolved oxygen between 5 and 5.5 mg L
which were the lowest recorded in this study. However, fish
species richness was the highest at lower nitrate and phosphate
concentrations and temperatures between 28 and 29 °C.
Spatiotemporal variation in fish biomass and species
In Buenaventura Bay, the fish assemblages varied across sea-
sons and sampling sites. Among the 69 fish species collected,
Table 5 Results of univariate generalized additive models (GAM)
assessing variation in estuarine fish biomass and species richness.
Model fit (Adj. R
), percentage of variation explained by each variable,
as well as the polynomial grade associated with each variable.
Abbreviations:Alk, alkalinity; DO, dissolved oxygen; Na, nitrates; Ni,
nitrites; P, phosphates; TDS, total dissolved solids; Tem , temperature;
Sal, salinity
Smoothing effect S (Na) S (Ni) S (P) S (Alk) S (Sal) S (Tem) S (TDS) S (pH) S (OD)
Biomass edf 4.72 1 1 1 2.92 1.25 3.07 3.22 1.11
F-value 3.32 8.85 0.43 1.04 2.94 7.6 3.13 1.44 4.31
pvalue 0.01* 0.005** 0.52 0.31 0.04* 0.003** 0.03* 0.28 0.03*
Variation explained (%) 43.4 20.7 1.25 2.98 28.9 27.4 31.4 19.4 14.9
Adj. R
0.35 0.18 0.02 0.001 0.23 0.25 0.25 0.11 0.12
Species richness edf 1 1 1 1 2.72 2.94 2.75 2.44 1.08
F-value 2.34 4.14 1.9 0.1 3.62 5.01 3.74 1.2 4.89
pvalue 0.13 0.05* 0.18 0.75 0.02* 0.003** 0.02* 0.35 0.03*
Variation explained (%) 6.43 10.9 5.29 0.3 30.2 39.5 31 14.4 15.4
Adj. R
0.04 0.08 0.03 0.03 0.24 0.34 0.25 0.08 0.13
*p<0.05;**p< 0.01; ***p<0.001
25746 Environ Sci Pollut Res (2020) 27:2574025753
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
25 (36%) accounted for 90% of the biomass, 16 (23%) were
present in at least 30% of the trawling events, and 15 (22%)
accounted for 90% of the abundance. The presence of domi-
nant species has been previously reported in other studies in
this region (Molina et al. 2020) as well as in other tropical
estuaries (Castillo-Rivera et al. 2010) and might be explained
by the tolerance of these species to a wide range of environ-
mental conditions characteristic of these ecosystems (Sheaves
et al. 2015).
In this study, the lowest species richness was recorded dur-
ing the wet season in the inner estuary (n= 6, 8.7%) and
during the dry season in the outer estuary (n=7, 10.14%).
The extreme salinities might explain the lower species rich-
ness, as few organisms tolerate these extremes (González-
Sansón et al. 2016). This trend has been previously reported
in other estuaries from the same region, where the lowest fish
species richness was recorded during the seasons with the
lowest salinity (n= 4, 6.3%) (Páez et al. 2018).
Nevertheless, the dominance of some species and the lower
species richness during certain seasons and at some sampling
sites could also be explained by multiple anthropogenic im-
pacts (Fausch et al. 1990; Harrison and Whitfield 2004). In
fact, other anthropogenically impacted estuaries followed sim-
ilar trends. For example, in an Ecuadorian estuary character-
ized by high population density and mangroves disturbed by
shrimp farming, four fish species (12%) accounted for 90% of
the fish abundance (Shervette et al. 2007). Similarly, in a
Mexican coastal lagoon characterized by high population den-
sity and tourist activities, only eight fish species (12.5%)
accounted for 90% of the fish abundance (Páez et al. 2018).
In the Buenaventura Bay, 25 fish species (36%) accounted for
90% of the fish abundance, suggesting that this ecosystem is
resilient to the multiple anthropogenic disturbances.
Nonetheless, dominant species might thrive in highly dis-
turbed estuarine ecosystems, thus threatening biodiversity
within these ecosystems.
On the other hand, the most abundant fish species was
Sphoeroides trichocephalus (Tetraodontidae), in particular
during the transitional season and at sites with contrasting
characteristics: river discharge (RE) and compacted bottoms
(OE). The transitional season corresponds to the July month,
which is one of the periods of highest flux of tourism in the
Dagua basin and Bocana sand beaches (Herrera et al. 2007;
Fig. 3 Effect of water quality
predictor variation on fish
biomass (multivariate analysis:
GAM). Plots represent
relationships indicated by the best
fitting GAM (Tabl e 6).Smoothed
functions are presented as solid
lines; dashed lines denote 2
standard errors
Table 6 Results for multivariate analysis (GAM). Results assessing
variation in estuarine fish biomass and species richness. Number of
species (n), model fit (Adj. R
and AIC), percentage of deviance
explained by each model, and the linear coefficient or polynomial grade
associated with each variable. The coefficient is presented between
parentheses and specifies a direction for linear relationships
Biomass Species richness
Adj. R
0.54 0.52
Dev. explained (%) 64.2 61.2
AIC 117.97 208.17
Coefficient or polynomial grade
Nitrates (4.9)*
Nitrites 1.21*
Phosphates (42.1)*
Alkalinity ――
Salinity 4**
Temperature 2.7***
Total dissolved solids ――
pH 1.6
DO 2.7
*p<0.05;**p< 0.01; ***p<0.001;removed during model selection
Environ Sci Pollut Res (2020) 27:2574025753
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Ospina Niño 2017). The Dagua River drains into the RE site,
and Bocana is close to the OE site, which may suggest that
during this time there is an increase in anthropogenic dis-
charges over these areas, which, paradoxically, is related to
higher abundances of S. trichocephalus. Moreover, the wide
environmental distribution of this species may be explained
by the differential niche use of juvenileand adult fish (Velasco
and Wolff 2000). Juvenilesmight benefit from murkier waters
for predator avoidance, while adults might exploit multiple
bottom types for foraging. Finally, S. trichocephalus has been
reported to tolerate extreme environmental conditions, which
allows it to occupy most of the available habitats within the
estuary throughout the year (Molina et al. 2020).
Spatiotemporal variation in water quality
In the studied site, it was recorded a temporal gradient in
which salinity was the highest during the dry season, followed
by the transitional and wet seasons, as well as a spatial gradi-
ent in which salinity was the lowest in the inner sites and
highest in the outer sites. This pattern has been previously
reported in studies in the same bay and was characterized by
salinities below 26 PSU due to high rainfall and runoff from
the Dagua and Anchicayá Rivers (Cantera et al. 1999;
Gamboa-García et al. 2018a,2020;Molinaetal.2020).
Nitrate and nitrite concentrations were the highest during
the transitional season and at the inner sites, whereas phos-
phate concentration was the highest during the wet season and
at the inner sites. During seasons with the highest rainfall,
erosion and runoff increase the discharge of nutrients of the
organic matter from mangroves, as well as the anthropogenic
runoff that flows into river basins (Nie et al. 2018), in this case
the Dagua and Anchicayá Rivers, which might explain the
observed patterns. The Dagua River basin, which includes
the municipalities of Dagua and Buenaventura, is character-
ized by anthropogenic pressures including human settlements,
tourism activities, farming, and the consequent use of fertil-
izers and mining, among others. Moreover, the inner areas of
the estuary are directly affected by domestic wastewater run-
off from the Buenaventura Bay. Additionally, pollution and
mangrove logging impacts have been reported upstream of the
mouth of the Dagua River (Cantera et al. 1999;Romeroetal.
2006), which could have an effect on nutrient cycling in these
ecosystems. This agrees with reports from northern Brazil
(Goiana Riverestuary), where the highest phosphorusconcen-
tration was reported during the season with the highest rainfall
and within the inner estuary (Costa et al. 2017).
In this study, most of the sites and seasons presented a mod-
erate to low water quality. For example, the lowest dissolved
oxygen concentrations were recorded during the transitional sea-
son and at the IE (5.00 ± 0.14 mg L
) and OE (4.93 ± 0.11) sites,
which were classified as moderate. However, these sites were
classified as having low water quality due to their nutrient and
inorganic phosphorus concentrations. These results highlight the
susceptibility to low water quality along the Buenaventura Bay
estuary and during the year. Nevertheless, a study in the Tumaco
Bay (Colombian Pacific, closer to Ecuador) reported that phos-
phate concentration had a range of 0.2 ± 0.1 mg L
and nitrite
plus nitrate concentrations of 1.9 ± 1.8 mg L
(Guzmán et al.
2014), which were similar to the ranges found in Buenaventura
Bay. In that study, a phytoplankton characterization was per-
formed, and an oceanographic analysis, which suggested that
despite the susceptibility of the Tumaco Bay, water quality was
improved by the hydrodynamics of the system, which may flow
away the pollutants. Therefore, the variation in the water quality
and the resilience of the fish community in Buenaventura Bay
Fig. 4 Effect of water quality
predictor variation on fish species
richness (multivariate analysis:
GAM). Plots represent
relationships indicated by the best
fitting GAM (Table 6). Smoothed
functions are presented as solid
lines; dashed lines denote 2 stan-
dard errors
25748 Environ Sci Pollut Res (2020) 27:2574025753
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
may be explained by its hydrodynamic regime, the prominent
tide range, and the high seasonal variation of river flow, which,
similar to Tumaco bay, may improve the ecosystem services.
Effect of water quality on variations in assemblage
of the most representative fish species
In the estuary of Buenaventura Bay, the most representative
fish species were distributed across three assemblages accord-
ing to water quality variables. The dry season on one side, and
wet and transitional seasons on the other, strongly affected fish
assemblage structure. The environmental variables that were
correlated most strongly with the fish assemblages were mean
nitrite concentration and temperature. One assemblage was
composed of Sphoeroides trichocephalus,Lile stolifera,
Achirus klunzingeri,andOphioscion typicus. These species
were recorded across seasons and sampling sites in more than
45% of the trawling events, suggesting that these fish species
are tolerant of water quality variation. This trend has been
previously reported for the estuarine resident species in
Buenaventura Bay (Molina et al. 2020), as well as in other
estuaries around the world (Cabral et al. 2011;Francoetal.
2006;Martinhoetal.2007). In general, species with a wide
physiological tolerance breadth tend to predominate in these
ecosystems (Potter et al. 2015). For example, Sphoeroides
annulatus is classified as euryhaline and tends to dominate a
great proportion of assemblages it is part of (Chávez Sánchez
et al. 2008). Interestingly, this trend has also observed in the
Buenaventura Bay as this species represented the highest
abundance during the wet and transitional seasons and was
tolerant to nutrient concentration variation, dissolved oxygen,
and temperature changes.
On the other hand, a second fish assemblage composed of
Pseudupeneus grandisquamis,Daector dowi,and
Citharichthys gilberti was the most susceptible to nitrite con-
centration and temperature, and was only reported during the
dry season. Previous studies have reported the effect of inor-
ganic nitrogen concentration (Wilkerson and Dugdale 2016)
as well as temperature on fish assemblages (Harrison and
Whitfield 2006;Molinaetal.2020; Rau et al. 2019). Even
though these species were only recorded during the season
with the highest salinity, they were also classified as being
highly dependent on bottom characteristics considering their
movement and foraging behavior (Ramírez-Luna et al. 2008;
Rau et al. 2019). Therefore, the increasing nitrite concentra-
tion in combination with increasing temperatures due to solar
radiation could result in a bottom-up nutrient control, which
could increase the eutrophication conditions and negatively
affect the fish assemblages. Moreover, increased nitrite con-
centration (Camargo and Alonso 2006; Schlacher et al. 2007)
and water temperature (Jeffries et al. 2016; Madeira et al.
2016) could represent physiologically stressful surroundings
for fishes.
Furthermore, a third fish assemblage of fishes composed of
Cathorops multiradiatus and Urotrygon rogersi was recorded
during the wet season in the outer bay and was associated with
low pH and high dissolved oxygen concentrations, which is
characteristic of the runoff of the rivers Dagua and Anchicayá
(Cantera and Blanco 2001). The distribution of species
forming this assemblage is consistent with that reported in
previous studies from this region (Castellanos-Galindo et al.
2006;Molinaetal.2020). Moreover, the highest abundance of
Cathorops multiradiatus and Urotrygon rogersi recorded in
the outer estuary region might be explained by the runoff of
the rivers that creates environmental conditions to adjacent
waters, facilitating resource provisioning to the most marine
species (Elliott et al. 2007;Potteretal.2015;Molinaetal.
2020). Finally, fish assemblages varied mostly temporally as
an effect of nitrite concentration and temperature, suggesting
that water quality and estuarine ecosystem services in the
Buenaventura Bay are susceptible to eutrophication and
highlighting the complexity and ecological relevance of the
Effect of water quality on fish species richness
and biomass variation
In the estuary of Buenaventura Bay, fish species richness and
biomass were affected by water quality. Higher biomasses
were recorded in low-quality waters, enriched with nitrites
and with a low dissolved oxygen. This trend was reported
during a hypoxia event in a Mexican estuary, where the fish
species representing the highest biomass benefited from the
bottom-up effect as a result of primary and secondary produc-
tion and could also tolerate low dissolved oxygen concentra-
tions, which allowed themto avoid predators (de Mutsert et al.
2016). In summary, in the Buenaventura Bay, the increased
fish biomass and dominance of certain species could be an
indicator of the effect of low water quality.
In contrast, fish species richness was the highest at intermedi-
ate salinities, which is consistent with results from the Málaga
Bay, an adjacent estuary to the Buenaventura Bay, where the
highest species richness was recorded at intermediate salinities
(Castellanos-Galindo and Krumme 2015). These open estuaries
are characterized by a wide salinityrange:low-salinityhabitats
(under 10 PSU) that are unsuitable for marine fish in some re-
ported estuaries (Martino and Able 2003), as well as
intermediate-salinity habitats. Thus, these relatively intermediate
salinities could provide a salinity ecotone, which could be toler-
ated by resident estuarine species as well as marine species that
also depend on the estuary ontogenetically.
Furthermore, a low species richness was reported in
low-quality waters, characterized by high nitrate and
phosphate concentrations. Increased nitrate and phos-
phate concentrations have been previously linked to an-
thropogenic activities (Camargo and Alonso 2006;
Environ Sci Pollut Res (2020) 27:2574025753
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Smith 2003; Wilkerson and Dugdale 2016), such as
wastewater runoff from urban settlements into estuaries,
which in turn affects ecological cycles (Berbel et al.
2015). This suggests that the presence of these nutrients
indicates a disturbed and low-quality habitat as a result
of urban wastewater runoff, which contains nutrients as
well as other pollutants. Consequently, fish could suffer
from pathologies of different organs, such as the gills,
liver, and kidney, or become more susceptible to para-
sites (Schlacher et al. 2007). Moreover, this could affect
their vitality, affecting community structure and ecosys-
tem functioning. Thus, the effect of anthropogenic nu-
trient runoff on fish assemblages may be evident in
Buenaventura Bay, particularly in relation to nitrates,
as this nutrient presented the highest concentrations in
most of the estuary.
Considering the socioeconomic importance of the
Buenaventura Bay estuary for the region for tourism
and fishing for livelihood and commercial purposes, it
is critical to monitor, control, and treat anthropogenic
runoff that might flow into the estuary. In addition,
the relevant authorities should develop initiatives to
monitor and assess septic tanks from rural communities
and tourist centers adjacent to the sea. This study high-
lights the importance of assessing inorganic pollution
within estuaries, and future studies should complement
this with histopathology of fish and its potential effect
on human health, in addition, chlorophyll-a and micro-
biological analyses. Moreover, fish assemblages could
be used as ecosystem functioning indicators, and certain
fish populations should be permanent monitored.
Acknowledgments We thank the Universidad Nacional de Colombia for
their administrative support. We also thank the Ecología y Contaminación
Acuática research group for their support in the field, sample processing,
and data analysis.
Funding information We received from the Universidad Nacional de
Colombia financial support of the project: Efectos de los cambios en la
calidad del agua en las comunidades de macroinvertebrados y peces del
estuario Bahía de Buenaventuracódigo Hermes 42118. We also received
from the Universidad Santiago de Cali financial support of the project:
Fortalecimiento de grupos de investigacióncódigo: 934-621118-204.
Data availability The data in this study are available upon reasonable
request to the corresponding author.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
Ethics approval The methods in this study were approved by the ethics
committee of the Environmental Studies Institute (Spanish acronym:
IDEA) of the Universidad Nacional de Colombia and follow internation-
al, national, and institutional animal use and care guidelines.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing, adap-
tation, distribution and reproduction in any medium or format, as long as
you give appropriate credit to the original author(s) and the source, pro-
vide a link to the Creative Commons licence, and indicate if changes were
made. The images or other third party material in this article are included
in the article's CreativeCommons licence, unless indicated otherwise in a
credit line to the material. If material is not included in the article's
Creative Commons licence and your intended use is not permitted by
statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this
licence, visit
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... Freshwater organisms particularly freshwater invertebrates and fish are more sensitive to nitrate than marine animals where salinity reduces the effect of nitrate toxicity (Camargo et al. 2005). Also, high nitrate concentration has been shown to influence the survival and growth of aquatic fauna (Duque et al. 2020). High levels of chloride along with other ions like Mg ++ , Ca ++ , CO 3 −− , HCO 3 − lead to the salinization of freshwater bodies and are destructive to freshwater organisms especially small invertebrates (Elphich et al. 2010). ...
... During the present study, monsoon season, on the one hand, and premonsoon and postmonsoon season, on the other, profoundly affected prawn abundance pattern as low abundance of prawn species was associated with low water quality. Rashed-un-Nabi et al. (2011) and Duque et al. (2020) reported a similar trend in the case of the abundance of Macrobrachium villosimanus and fish species, where the least abundance was associated with degraded water quality. M. dayanum and M. kistnense were reported across all seasons and sites, indicating their wide range of tolerance to variations in water quality parameters. ...
Full-text available
The freshwater rivers from Shiwalik Himalayas have abundant prawn resources of high economic value and play a major role in the livelihood of local fishermen. The present study aimed to determine the variation in prawn abundance explained by changes in water quality among three different streams (Gho Manhasa stream, Chadwal stream and Nagri stream). The highest abundance of prawns was found in the Gho Manhasa during the premonsoon season and lowest in the Chadwal stream during the monsoon season. Chadwal stream witnessed maximum anthropogenic activities resulting in the decline of the water quality affecting prawn fauna. Cluster analysis based on similarity in terms of prawn abundance revealed that the Chadwal stream is different from the other two streams whereas non-metric multidimensional scaling plot based on species abundance corresponding to different seasons and physiochemical parameters showed the water quality of the monsoon season of the Chadwal stream to be extremely different. Principal component analysis showed clear separation across various sites and seasons based on physicochemical parameters. Karl Pearson correlation coefficient and canonical correspondence analysis indicated that the turbidity, total dissolved solids, nitrate, chloride, calcium, magnesium and dissolved oxygen are significant parameters influencing the abundance of prawns. The population of Macrobrachium dayanum and Macrobrachium kistnense was very less in the Chadwal stream owing to unfavorable physicochemical parameters. Therefore, conservation measures are suggested which should be immediately implemented before the streams witness a further decline in their populations.
... Wang et al. 2021) and fishes (e.g. Duque et al. 2020). On the other hand, little research has been done on how calcified macroalgae respond to this kind of anthropogenic disturbance. ...
Calcified macroalgae are essential components of marine ecosystem, yet much of their physiology remains to be understood. Here, the nutrient (NO3– and PO4–3) uptake physiologies of two branched macroalgae, Actinotrichia fragilis (Nemaliophycidae) and Amphiroa fragilissima (Corallinophycidae), and the non-geniculate rhodolith Sporolithon sp. (Corallinophycidae) were examined. Sporolithon sp. had the lowest uptake rate through time and the three calcified macroalgae had a surge in NO3– and PO4–3 uptake that occurred between 3 and 20 min, with a maximum uptake at 3 min, after which the nutrient uptake rates declined. The NO3– uptake of the three calcified macroalgae followed Michaelis-Menten kinetics. For NO3– uptake, Sporolithon sp. had the lowest Km (2.72 ± 0.97 µM), Vmax (0.08 ± 0.01 µmol gDW–1 h–1), Vmax/Km (0.05 ± 0.03 µmol gDW–1 h–1 µM⁻¹) and α (0.01 ± 0.00 µmol gDW–1 h–1 µM⁻¹), while A. fragilis had the highest Km (12.35 ± 0.71 µM) and Vmax (6.41 ± 0.23 µmol gDW–1 h–1), and A. fragilissima had the highest Vmax/Km (1.52 ± 0.26 µmol gDW–1 h–1 µM⁻¹) and α (0.37 ± 0.01 µmol gDW–1 h–1 µM⁻¹). Moreover, the PO4–3 uptake rate of the three species was faster at higher PO4–3 levels. These differences in species-specific nutrient uptake traits are likely caused by differences in morphology. These traits are important for survival and proliferation of this group of marine organisms, particularly in a nutrient-variable environment.
... Hal itu tampak dari mulai sedikitnya populasi dan keberagaman ikan. Diversitas ikan dipengaruhi oleh migrasi ikan, predator, dan kualitas air pada perairan tersebut (Duque et al., 2020) ...
Full-text available
A buffer zone is an area designated to protect a conservation area from being disturbed by the surrounding environment. The concept of a buffer zone can be adopted to protect an area or land from contamination by factories, household, and agricultural waste. Teluk Sinar Village is a village located in a freshwater swamp area where there are mines around this area. Further, agricultural practices in the area still use chemicals that leave residues and can pollute the environment, including water pollution. The problem partner is the low level of knowledge about the impact of water pollution on organisms, including human health. Through this community service, it will be a solution to understanding the effects of water pollution for members of the Bunga Seroja Farmer Group through the concept of buffer zone technology. The community service was conducted by the lecture method and gave a pocket book. It significantly increases the knowledge and understanding of farmers about the buffer zone concept.
... In the Guartinaja wetland, NO 3 values were high, ranging between 1.8 mg/L and 3 mg/L, which could induce eutrophication processes in the wetlands. These nutrient values, compared to other studies in tropical wetlands, range from 0.0005 to 6 mg/L [64][65][66][67][68][69][70]. ...
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This research demonstrated the feasibility of applying Sentinel-2 images to generate empirical models and estimate physicochemical parameters concentration, particularly nutrients in the wetland system called Bajo Sinú wetlands complex, Colombia. Spearman correlations were determined between water quality parameters, which were monitored at 17 points in the wetland on 5 February 2021, with Sentinel-2 images reflectance values from the same monitoring date; the correlations allowed the identification of statistically significant bands in the multiple linear regression algorithm implementation to determine empirical water quality models. The results show significant correlations between the optically active parameters, TSS-Turbidity, which in turn correlated with the optically inactive parameters Turbidity-NO 3 and TSS-DO, as well as non-optically active parameters among themselves, TDS-NO 3 and TDS-TP; the empirical models presented higher than 74.5% fit (R 2), particularly DO (R 2 = 0.948), NO 3 (R 2 = 0.858) and TP (R 2 = 0.779) were the models with the highest fits (R 2). These models allowed us to properly estimate the spatial distribution of nutrient-forming compounds in the wetlands complex. The determinant role played by turbidity in this type of water body is highlighted; it acts as a connecting constituent that makes the estimation of water quality parameters without spectral response through remote sensing feasible. Sentinel-2 images and multiple linear regression algorithms have been shown to be effective in estimating the concentration of water quality parameters without spectral response, such as NO 3 and TP in shallow tropical wetlands, due to the processes of transformation, interaction and dependence between the different environmental variables in aquatic ecosystems.
... Further, a systematic monitoring of relevant local environmental parameters needs to be established and tailored to complement the fisheries monitoring and assessments specific to the country. In addition to the 4 environmental parameters analyzed in this study, salinity, dissolved oxygen, and bottom temperature, which together are also considered as water quality indicators, may be important to consider in future analyses given that they are shown to also have significant effects on fish stock abundance and assemblage (Zhang et al., 2009;Duque et al., 2020;Chiarini et al., 2022). ...
Full-text available
The Visayan Sea is one of the major traditional fishing grounds in the Philippines and is likewise considered as a top contributor to the country’s overall fisheries production. However, fisheries surveys conducted over the past couple of decades have documented changes in the abundance and composition of catches and stocks toward an increasing dominance of invertebrates and low trophic levels fish families. Assessments of the commercially-important pelagic and demersal stocks were used to estimate population parameters that already exceed the sustainable reference limits. These traditional assessments point exclusively to fishing as the likely cause of the observed status and trends, but they fail to incorporate the potential influence of trophic interactions and variable environmental conditions despite a nationally-legislated mandate to apply an ecosystem approach to assessing and managing the country’s fisheries. Thus, an ecosystem model (Ecopath with Ecosim) of the Visayan Sea was constructed to investigate the role and extent of the fishery, trophic interactions, and changing environmental conditions as drivers of stock abundance and ecosystem dynamics. The results suggest that fishing and its corresponding trophic effects are the major drivers of invertebrate and fish biomass and catches in the Visayan Sea over the past two decades, while the environmental trends provide explanations for patterns that cannot be explained by fishing alone. Incorporating sea surface temperature variations and primary productivity anomalies produced the best-fitting models for most of the observed biomass and catch trends. The catches of the small pelagics (i.e., sardines and mackerels) were likewise found to be particularly affected by rainfall, while the biomass and catch of the small demersal fishes also show a sensitivity to chlorophyll-a concentrations. The primary productivity anomalies further showed a significant correlation with the Pacific Decadal Oscillation (PDO), which suggests that bottom-up trophic controls in the system may be affected by long-term regional climatic changes. These findings validate the applicability and necessity of the ecosystem modeling approach in assessing exploited marine ecosystems to complement the analyses from typically single-species population assessments, especially in the face of increasing environmental variability and projected climate change scenarios.
... Nitrate concentration in streams ranged from less than 1.0 mg/l to 5.0 mg/L (Chapman and Kimstach, 1996). A negative correlation was obtained between CPUE vs nitrate similar to the results shown by Duque et al. (2020). ...
Full-text available
The quality of water is very critical for fish survival and growth in a water body. However, little is known about the state of the Bhini Stream's water quality and its relationship to fish catch. The focus of this study was to evaluate water quality parameters in the Bhini Stream and see if there was a correlation between them and fish catch per unit effort. Monthly samples were gathered using a three-level stratified sampling method. Temperature, depth, transparency, pH, TDS, EC, DO, alkalinity, hardness, chloride, sulphate, phosphate, nitrate, and fish catch (CPUE) were all monitored simultaneously in each of the three strata of the stream. The water quality characteristics were within the permissible range for fish production. There were no significant differences in water quality parameter concentrations between the riverine, transitional, and lacustrine zones (p>0.05). TDS and nitrates from fertilisers used on nearby fields and brought to the stream by runoff or floods were significantly and negatively correlated with CPUE (r=0.84, p<0.05; r=0.71, p<0.05). 13 fish species all belonging to order Cypriniformes were reported from the stream with Schistura denisoni being reported for the first time from the River Ravi.
... Physicochemical degradation caused by intense land-use activities, moreover, pose a serious threat to biological communities in streams, such as compositional changes in functional fish structure (tolerance and trophic groups) and declines in fish diversity and abundance (Choudri et al., 2017;Duque et al., 2020;Kim et al., 2019;Shetty et al., 2015). Altered environments also favor the proliferation of invasive alien species (IAS) that have greater tolerance to elevated levels of nutrients and organic matter. ...
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Functional trait and biological integrity approaches in stream ecology enable the determination and prediction of aquatic community responses to a variety of environmental stressors, such as chemical pollution, habitat disturbance, and biological invasion. Here, we used multi-trait based functional groups (FGs) to predict the functional responses of fish assemblages to the physicochemical and ecological health gradients in a temperate stream. The multi-metric biological integrity model (mIBI model) was used to evaluate stream ecological health. The FGs were derived from the distance matrix of trophic, tolerance, and physical habitat traits among fish species. The leading water quality indicators (conductivity [EC], total suspended solids [TSS], and chlorophyll-a [CHL-a]) varied conspicuously with the stream gradient and anthropogenic pollution. The multi-metric water-pollution index (mWPI) showed differences in chemical health from upstream to downstream. Monsoon precipitation may have affected the variations in fish species and associated changes linked to irregular chemical health. The fish FGs varied more by space (longitudinal) than by season (premonsoon and postmonsoon). Functional metrics, which reflected trophic and tolerance traits, as well as vertical position preference, were strongly correlated with water quality degradation downstream. Changes were evident in FG (II, III, and IV) combinations from the upstream to downstream reaches. Furthermore, the structure of the fish assemblages from FG-II and FG-III was significantly correlated with chemical ( R ² = 0.43 and 0.35, p < 0.001) and ecological health ( R ² = 0.69 and 0.66, p < 0.001), as well as the metrics of mWPI. In conclusion, the results indicate significant variations in both trait-based FGs and biological integrity among stream-fish communities, influenced by chemical water quality gradients. The causes included longitudinal zones and intensifying degradation of water quality downstream. Therefore, multi-trait based FGs can facilitate ecological health assessment and develop the mIBI model based on fish assemblages by reflecting the prevailing chemical health status of streams and rivers.
An IoT-based smart water monitoring system is of prime importance to control the threats related with aquaponics farming. Thus, it helps to provide a remarkable boost to improve the yield and productivity. Water quality directly impacts growth rates, feed efficiency, and the overall health of the fish, plants, and bacteria. The major issue in the aquaponics farming business is the lack of knowledge about species selection based on the water quality parameters. The proposed system provides a farming prediction for cold water, warm water fish, plants, and bacteria to improve the aquaponics farming business. Initially, the proposed system collects data using IoT sensors. After that, data cleaning is performed by removing missing values and outliers. Next, features correlated with the sensed data are obtained, and unwanted features are removed. Then, we propose a novel M-SMOTE algorithm to address the imbalanced class problem. Finally, the proposed approach employs the multi-model classification for the aquaponic ecosystem. The proposed method utilizes the mechanism of optimal prediction based on voting to evaluate the performance of six classifiers. The proposed method chooses the XGBoost and the random forest (are the best classifiers) based on the voting principle. The experimental results reveal that the proposed method’s results offer a new state-of-the-art aquaponics farming prediction model with an accuracy of 99.13%.
Identifying the key determinants and their impacts on water quality and fish community structure is imperative to environmental assessment and ecosystem conservation. The main objectives of this study were to assess the factors driving water quality, fish assemblages, and ecological health in a temperate lotic ecosystem using a long-term (12 years) dataset. The results indicate that sewage treatment plants significantly negatively impact river water quality and are primary pollution sources. Temporal fluctuations showed that the summer monsoon adversely influenced TN and EC due to dilution effects while increasing the COD and TSS in the water. Annual variations and the Mann–Kendall test demonstrated increasing trends in COD, TN:TP ratio, and CHL-a but a decreasing trend of TP with the impoundment. Artificial barriers (weirs) in the river created more favorable algal growth conditions due to increased water residence time. COD and TSS levels in the river were significantly affected by soil erosion. The environmental disturbance measures index indicated that all sites were severely degraded. Fish composition analysis suggested that exotic fish species such as, Lepomis macrochirus and Micropterus salmoides, dominated the community structure and negatively impacted native species after the installation of weirs. Our findings indicate that fish guilds and the IBI model are controlled by nutrient enrichment, organic matter, algal production, and land use/land cover. Water quality governs the biological health of the river. Overall, evaluation of the river's ecological health based on the multi-metric WPI and the IBI revealed that the river has a “poor” to “very poor” ecological status. The outcomes of this study may aid policymakers in managing and restoring the river.
Zhanjiang Mangrove National Nature Reserve (ZMNNR) is the largest mangrove natural reserve in China. We conducted the first comprehensive isotope study on the ZMNNR. Primary producers, including mangroves, grasses, microphytobenthos (MPB), etc. Formed the lowest trophic level. Gastropods and bivalves, crustaceans and carnivorous fish were on the 2nd, 3rd and 4th trophic levels, respectively. In Zhanjiang tidal estuary, mangroves contributed about 1/3 of the carbon sources for consumers, substantially smaller than those in swamps and lagoons, but higher than those in river delta mangroves. The major carbon sources to the food web shifted from particulate organic matter (POM), consisting of detritus of mangrove leaves and phytoplankton, perennial grasses and mangrove leaves in the high tide zone to invasive Spartina alterniflora, POM and mangrove leaves in the low tide mudflat. Insignificant contributions of MPB were due to restricted light penetration by the dense mangroves in the high tide zone, and prolonged submersion and sediment resuspension in the low tide mudflat. Aquaculture effluents caused substantially higher δ15N values of all primary producers and consumers in the ZMNNR. In addition, high nutrient content and N/P ratios in aquatic effluents might allow cyanobacteria in MPB to be outcompeted by other fast growing microorganisms. Aquaculture effluents might also contribute to shortened trophic levels and promotion of the dominance of resistant species in the ZMNNR. We call for a sustainable development strategy to conserve the valuable ecosystem in the ZMNNR.
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En los ecosistemas costeros del Pací co colombiano se ha detectado la presencia del metal en diferentes compartimentos ambientales. El objetivo del presente trabajo fue determinar los niveles de mercurio total (HgT) en plumas y cáscara de huevo de pelícanos (Pelecanus occidentalis) en la Bahía de Buenaventura y en Bahía Málaga. Se realizaron tres colectas de plumas encontradas en los ecosistemas (2012-2014), una colecta de cáscara de huevos durante (mayo 2014)- y una colecta de plumas de pieles de pelícanos de la zona (1964), pertenece a la colección del museo INCIVA. El análisis de mercurio se realizó por medición directa con el DMA-80, que consiste en espectrometría de absorción atómica después de descomposición térmica y amalgamiento. MERCURIO TOTAL EN PLUMAS DE Pelecanus occidentalis EN EL PACÍFICO VALLECAUCANO Universidad Nacional de Colombia Universidad Nacional de Colombia 34 Diego Esteban Gamboa-García - Guillermo Duque - Rosa del Pilar Cogua Romero - María Eufemia Freire Tigreros Se determinaron concentraciones de HgT p.s. en plumas tanto en juveniles (2.11±0.59 µg/g en Buenaventura, 0.49±0.05 µg/g en Bahía Málaga) como en adultos (2.79 µg/g en Buenaventura; 5.23 µg/g en Bahía Málaga). Los niveles de HgT p.s. en plumas de algunos pelícanos superaron los 0.5 µg/g, lo que sugiere un posible riesgo en el éxito reproductivo de los individuos. Los resultados demostraron que tanto en la bahía de Buenaventura como en Bahía Málaga, hay presencia de mercurio en el ecosistema que está siendo bioacumulado a través de las cadenas tró cas piscívoras.
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La bahía de Buenaventura es un estuario tropical con una rica diversidad que presenta un alto grado de intervención antrópica, destacándose los cambios en las concentraciones de materia orgánica (MO), la cual provoca desbalances en el ecosistema. Los poliquetos, por su rápida respuesta ante alteraciones ambientales, son situados como organismos con potencial bioindicador. En el presente estudio se determinaron las familias con mejor respuesta (cambios de abundancia) ante variaciones en la concentración de MO. Los ejemplares fueron recolectados en cuatro muestreos en los meses de abril, junio, septiembre y noviembre de 2015, en dos estaciones, empleando una draga para extraer sedimento y un tamiz de 0.5 mm de ojo de malla para separar los organismos, que fueron preservados y posteriormente identificados hasta el nivel de familia. Se midieron in situ variables fisicoquímicas, mientras en el laboratorio se determinó la composición granulométrica del sedimento y su contenido de materia orgánica a partir de muestras colectadas con corazonador. La influencia de la MO sobre la abundancia de poliquetos se evaluó usando análisis de componentes principales y correlaciones de Spearman (α=0.1). Se observaron diferencias ambientales entre sitios y épocas de muestreo, y correlaciones entre MO y sedimentos gruesos (inversa) y finos (directa). Se colectaron 917 individuos, pertenecientes a 26 familias, siendo las más abundantes Capitellidae, Maldanidae y Nereididae. Se identificaron cuatro familias sensibles a cambios en la concentración de MO, las familias Cossuridae, Maldanidae y Paraonidae presentaron correlaciones directas y la familia Hesionidae presentó una correlación inversa. Estas cuatro familias tienen potencial bioindicador de contaminación por MO por lo que es pertinente ahondar en su estudio.
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Three fish assemblages (functional groups according to estuary use) were examined, which presented different responses to environmental variations, mainly associated to the dry and rainy seasons and high and low salinities and temperatures in the Buenaventura Bay estuary, Colombia, Tropical Eastern Pacific. In total, 4674 individuals were collected, belonging to 69 species of 29 families. The most abundant species was Sphoeroides trichocephalus (35% of the total density). The assemblage of estuarine-resident fishes showed high tolerance to environmental variations since these were present all along the estuary and throughout the year. The assemblage of marine estuarine–dependent species was associated with the rainy season and low salinities and temperatures. The assemblages of marine estuarine opportunist fishes were associated with areas of higher environmental variability in both seasons, dry and rainy. Fish species belonging to the same functional group showed variations in their response to environmental changes which evidenced complex spatial and temporal dynamics. Understanding these changes is necessary to generate effective management plans based on scientific ecological knowledge, which include environmental impacts present in this estuary such as microplastics, heavy metals, and effects of dredging, and their effects on the ecosystem.
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The environmental health of Buenaventura Bay, a highly impacted tropical estuary, is influenced by numerous human activities, including mining upstream. Large- and small-scale fishing plays an important role in the local economy, so we investigated the dynamic processes of bioaccumulation of mercury at basal trophic levels. Four samples were taken at each of the four locations in Buenaventura Bay during each of the four seasons of 2015. We measured the total mercury content (T-Hg, dry weight) in sediments and in muscle tissue across 17 macroinvertebrate species. The most abundant were the blue crab (C. arcuatus) and the mantis shrimp (S. aculeata aculeata). Blue crab showed an average muscle T-Hg value exceeding the limit of 0.2 g·g⁻¹, which is the maximum T-Hg level suggested for food consumption by vulnerable humans and populations: pregnant women, children, and the community that feeds from this source of protein on a daily basis. It was found that, 6.22% of individuals exceeded the 0.5 g·g⁻¹ level, which is the maximum T-Hg level suggested for food consumption by the general population: the population that consumes it sporadically. Significantly high values of T-Hg in blue crab and mantis shrimp occurred during low salinity conditions in the estuary, suggesting that Hg mainly originates from river runoff during the rainy season. Nevertheless, the biota-sediment accumulation factor (BSAF) was favored in high salinity, which could mean greater availability of Hg for higher levels of the estuarine food web in the dry season and in marine waters. In general, the T-Hg levels in some samples exceeded 0.2 g·g⁻¹. Therefore this pollutant must be monitored due to its biomagnification potential and as a threat to human health, especially that for the local population of fishermen and their families.
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Buenaventura the to environmental distribution bay of is variables. macroinvertebrates characterized The objective by a in great the of bay dynamic the and present its of habitat, work environmental was however to determine variables. it is necessary the There espatio-temporal to is document descriptive on variation information its dynamics in the concerning in structure relation and composition of macroinvertebrates and their relationship with the environmental variables. Four sampling (April-June-September-November) were carried out throughout 2015, in four stations (Estuary River-Internal Estuary-External Estuary-Marine Estuary). At each station three samples of sediments, physicochemical variables of the water and macroinvertebrates were collected. A total of 532 individuals were found in 17 species and 9 families. The abundance varied from 0.7±1.2 to 29.7±7.4 individuals per trawl and the richness varied from 0.3±1.2 to 4.7±1.2 species per trawl. The multiple regression analysis suggests an influence of the variables salinity and percentage of clays on the structure and composition of macroinvertebrates in the bay. The abundance and richness of macroinvertebrates was higher when the salinity conditions prevailed in the estuary.
El mercurio es un metal persistente que puede causar graves efectos ecológicos en los ecosistemas. El objetivo del presente estudio es relacionar las anormalidades nucleares de los eritrocitos (ENA), la frecuencia de eritrocitos inmaduros (EI) con la concentración de mercurio total (HgT) en peces de la bahía de Buenaventura. Las especies colectadas son Lisa (Mugil cephalus), Loca (Stellifer fuerthii) y Canchimalo (Cathorops multiradiatus). Todas las especies estudiadas presentaron mercurio en la sangre. Las especies M. cephalus y C. multiradiatus muestran altas correlaciones negativas entre ‰ ENA y las concentraciones de HgT en sangre (0.76, 0.91). Para S. fuerthii y C. multiradiatus se presentan altas correlaciones negativas (0.77, 0.67) entre ‰ EI con los niveles de HgT en sangre. Las variables biológicas fueron relacionadas con los niveles de HgT en músculo, donde C. multiradiatus obtuvo correlaciones fuertes (0.67, 0.69) para peso total y para la longitud total. Todas las especies bioacumulan activamente el HgT, confirmando la presencia de este contaminante en el ecosistema
Environmental filtering is a major mechanism structuring ecological communities. However, it is still not clear how different abiotic drivers composing the environmental filter interact with each other to determine local species assemblage and create spatial patterns in species distribution. Here, we evaluated the effects of two strong and uncorrelated environmental variables (salinity and sediment properties) on the β‐diversity of an estuarine macrobenthic community while accounting for spatial effects. Our results show that the benthic community composition has a strong spatial structure along the estuary, which can be greatly explained by salinity and sediment variation. Salinity is most associated with species replacement (turnover), whereas sediment is more important for species loss (nestedness). However, the effects of sediment variation on nestedness are mainly detected at smaller spatial scale (estuarine sectors), whereas the effects of salinity on species turnover are stronger as spatial scale increases (entire estuary). Our findings suggest that environmental filters can drive both turnover and nestedness components of β‐diversity but that their relative importance depends on the spatial scale of investigation. Although abiotic drivers associated with detrimental effects (sediment) usually result in nestedness, larger spatial scales encompass abiotic drivers associated with different suitable conditions (salinity), increasing the relative importance of the replacement component of species β‐diversity. This article is protected by copyright. All rights reserved.
The study explores the fine scale spatial and temporal distribution of the entire demersal fish and flatfish assemblages in a brackish ecosystem with a special focus on the abiotic and biotic drivers influencing the abundance of the three commercially and ecologically important flatfish species, namely flounder (Platichthys flesus), plaice (Pleuronectes platessa) and dab (Limanda limanda). Using a 12 year time series obtained by a summer survey in the western Baltic Sea, at least three distinct demersal fish species assemblages were identified. Their spatial distribution was relatively stable over time and could be linked to environmental gradients. The demersal fish assemblages were dominated by few species and differed primarily in the percentage of common species. Both, the demersal and the flatfish assemblage were structured according to different habitat preferences. While there were species-specific differences, boosted regression tree modelling (BRT) showed that interannual fluctuations explained a large percentage of the variance in flatfish abundance whereby salinity, water temperature and sediment type were identified as the most important abiotic drivers. Dab was mainly influenced by sediment type and high salinity, while for flounder the main driver was water temperature. Plaice was also impacted by salinity, but was primarily influenced by biotic variables. The availability of benthic prey organisms in the area was verified as biotic driver for flatfish, especially for plaice. The results underline the importance of accounting for fine scale spatial heterogeneity in marine spatial planning in the Baltic Sea and comparable brackish water ecosystems and highlight the importance of considering benthic prey availability and diet analyses in demersal fish monitoring programs.
While ecotoxicology has long recognised the importance of identifying levels at which contaminants pose threats to biota, most estimates of species responses to toxicants are derived from controlled laboratory studies and may hold limited relevance to natural systems. However, designing appropriate field-based studies investigating contaminant induced changes in assemblages has been challenging, partially due to the difficulty in identifying comparable uncontaminated reference sites. The aim of this study is to characterise the effects of heavy metal contamination on natural fish assemblages using an ecologically relevant catchment-scale design. We hypothesise that environmental variables, including discharge, sediment, and landscape variables, can be used to characterise differences in fish species richness and abundances between sites contaminated with heavy metals and uncontaminated reference sites. We apply a geographic information systems approach that uses assemblage–environment relationships developed using hydrologic model outputs, land cover, and topographic data from uncontaminated reference sites to predict expected fish species richness and abundance at sites contaminated with heavy-metals within the Big River catchment in south-eastern Missouri, U.S.A. These predicted levels of richness and abundance are then compared to observed assemblages at contaminated sites to estimate the potential impacts of historical lead mining activities on freshwater taxa. We developed models that characterised variation in Centrarchidae (bass and sunfish) richness and abundance, Cyprinidae (minnows) abundance, and Percidae (darters) richness using variables including streamflow regime, suspended sediment concentration, and land cover at uncontaminated sites. Using these relationships, we predicted expected fish species richness and abundance at heavy metal contaminated sites across the Big River catchment and found a significant reduction in centrarchid abundance from field-collected data compared to predicted estimates. Our results suggest that centrarchids, which tend to occupy a higher trophic level than cyprinids and percids, have lower abundances at sites contaminated with heavy metals than predicted by assemblage–environment relationships. These decreases in abundance are not associated with decreases in centrarchid species richness, cyprinid abundance, or percid richness. This geographic information systems-based approach provides a useful and ecologically relevant framework for understanding the response of taxa to the presence of contaminants without assuming habitat equivalence across sites. Our findings also suggest the need for further research regarding how heavy metals impact fishes of varying trophic levels in natural settings.
Estuarine pollution imposes rapid, increasing and lasting environmental modifications. In the present review, especial attention is given to estuaries in South America (SA), where legislation, policies and actions to guarantee environmental quality remain ineffective. There, the majority of estuaries face uncontrolled occupation of its margins by urban and industrial centres, agriculture and aquaculture expansion, water extraction and flow control. The lack of basic sanitation and poor environmental management (including territories within Marine Protected Areas) often lead to hydrological alterations, high nutrient loads, and the presence and dynamics of pollutants (nutrient loads, persistent organic pollutants (POPs), metals and plastic debris) along the entire estuarine ecocline.Organic enrichment has increased dissolved oxygen consumption, withwide spatio-temporal variability along latitudes and estuarine gradients. The toxicity, biogeochemistry and availability of metals and POPs depend on the annual fluctuations of salinity, water renewal, dissolved oxygen levels, suspended particulate loads, sediment mobility, grain size and composition at the sink. Plastic debris from land sources are widespread in estuaries,where they continue to fragment into microplastics. River basins are themain contributors of plastics to estuaries, whose transportation and accumulation are subjected to interannual water flow variations. Although some systems seems to be in a better condition in relation to others around the world (e.g. Goiana and Negro estuaries), many others are among the most modified worldwide (e.g. Guanabara Bay and Estero Salado System).We propose that, estuarine conservation plans should consider year-round fluctuations of the ecocline and the resulting cycles of retention and flush of environmental signals and their influence on trophic webs over the whole extent of estuarine gradients.