Journal of Threatened
Taxa | www.threatenedtaxa.org | 26 September 2024 | 16(9): 25816–25830
ISSN 0974-7907
(Online) | ISSN 0974-7893 (Print)
https://doi.org/10.11609/jott.7832.16.9.25816-25830
#7832 | Received 16
January 2022 | Final received 15 August 2024 | Finally accepted 17 August 2024
Habitat heterogeneity and
taxonomic diversity of fish fauna in estuaries:
a study from southern Sri Lanka
Kirivithanage Sandun Nalaka
Bandara
Department of Zoology, Faculty of
Natural Sciences, The Open University of Sri Lanka, Nawala, Nugegoda 11222, Sri
Lanka.
Department of Zoology, Faculty of
Science, University of Ruhuna, Matara 81000, Sri Lanka.
Editor: Mandar Paingankar, Government Science
College Gadchiroli, Maharashtra, India. Date
of publication: 26 September 2024 (online & print)
Citation: Bandara, K.S.N. (2024). Habitat heterogeneity and taxonomic
diversity of fish fauna in estuaries: a study from southern Sri Lanka. Journal of Threatened Taxa 16(9):
25816–25830. https://doi.org/10.11609/jott.7832.16.9.25816-25830
Copyright: © Bandara 2024. Creative Commons Attribution 4.0 International License. JoTT allows
unrestricted use, reproduction, and distribution of this article in any medium
by providing adequate credit to the author(s) and the source of publication.
Funding: This study was funded by the Environment Foundation (Guarantee)
Limited, Sri Lanka under the fauna and flora study for Dedduwa development
project.
Competing interests: The author declares that he has no known
competing financial interests or personal relationships that could have
appeared to influence the work reported in this paper.
Author details: Dr.
Sandun Bandara is a senior lecturer in the Department
of Zoology at the Open University of Sri Lanka. He is
keen on aquatic ecology, fisheries biology, life history strategies of fishes
and conservation biology. Currently, he is the senior coordinator of the course
unit ‘Ecology’ in the department.
Acknowledgements: I would like to acknowledge Ms.
Zaineb Akbarally and Ms. Chaturangi Wickramaratne of the Environment Foundation
(Guarantee) Limited for their cooperation and support extended to this study. I
am also thankful to Prof. U. S. Amarasinghe, Prof. Sevvandi Jayakody, Dr.
Suranjan Fernando, Dr. Kumudu P. Kopiyawattage and Ms. Achini Wathsala for
their valuable comments in preparing this manuscript.
Abstract: A survey was conducted to
identify fish fauna related to the dominant habitats, viz., (i) Honduwa Lake
(stagnate water), (ii) estuarine area with mangroves, (iii) freshwater marshy
area with floating aquatic vegetation, (iv) canals, and (v) river, in the Dedduwa
estuary of southern Sri Lanka. Thirty-nine species of fish including two
endemics (to the island) were identified, including members of major migratory
families such as Anguillidae and Megalopidae. Based on the abundance of
species, the Bray-Curtis similarity index indicated a clear separation of the
canal and freshwater marsh, with other studied areas. Similarly, the taxonomic
diversity of the canal and freshwater marsh was high, indicating high variation
and diversity of the species and genera. Protection of mangroves and related
habitats is important to maintain the stability and long-term existence of fish
fauna in the estuary. Effective monitoring is proposed for detecting and
eliminating illegal encroachments, mangrove clearance, and illegal fishing
activities. Moreover, improving the knowledge and awareness among members of
the local community, politicians, and environment officers about the importance
of the region’s biodiversity implementing strong policies, and creating a
strong responsible stakeholder bond are required to ensure the long-term
sustainability of the estuary.
Keywords: Brackishwater, catadromy,
conservation, fish diversity, fish migration, mangroves, taxonomic
distinctness.
INTRODUCTION
Estuaries are considered one of
the most productive coastal ecosystems in the tropics (Whittaker & Likens
1975; Whitfield & Elliott 2011; Sreekanth et al. 2017). Ecologically,
estuaries are highly significant as they provide critical ecosystem services
including coastal protection (Barbier 2020), carbon sequestration (Douglas et
al. 2022; Das et al. 2023), sediment filtration (Schubel & Carter 1984;
Teuchies et al. 2013), and habitat enrichment (Cardoso 2021; Denis et al.
2022). These ecosystem services are essential in sustaining the coastal
biodiversity and well-being of aquatic taxa (Cardoso 2021). Among the various
ecological services, the most significant is habitat provisioning and
maintaining ecosystem integrity in coastal environments (Blaber et al. 1989;
Sreekanth et al. 2020). Estuaries form a transition zone between river and
maritime environments and are hence always influenced by tidal fluctuation and
freshwater fluxes (Potter et al. 2010). These heterogenous physico-chemical
changes featured unique and variable habitat formations such as mangroves,
shallow open waters, freshwater and saltwater marshes, swamps, sandy beaches,
mud and sand flats, rocky shores, river deltas, tidal pools, and seagrass beds
enhancing the habitat complexity and species composition in estuaries (Hagan
& Able 2003). The diversified habitats in the estuaries are known to
provide nurseries and feeding grounds for fish essentially for larval stages
(Potter et al., 2013; Guerreiro et al. 2021). Therefore, estuaries provide refuges
for a wide variety of fishes including both marine and freshwater species to
complete their life cycles (Blaber et al. 1989; Whitfield & Elliott 2002;
Elliott et al. 2007).
Distribution of fishes in an
estuary is fundamentally determined by habitat heterogeneity, prey predator
relationship, and water chemistry (Jackson et al. 2001; Maes et al. 2005; Kadye
et al. 2008; Sreekanth et al. 2020). The productivity of the habitats is
equally important to determine the dietary compositions of fishes (Hagan & Able
2003). The climatic fluctuations and changes in precipitation determine the
level of productivity (e.g., accumulation of autochthonous and allochthonous
nutrients) and trophic relationship among fishes (Gillanders et al. 2011;
Sreekanth et al. 2019). The lowland reaches of rivers are characterized by high
levels of suspended solids inducing high turbidity (Cyrus & Blaber 1987).
Hence, productivity is largely determined by the nutrient loads from the upper
reaches of the river. In the freshwater–seawater transition zone, these
particles are effectively ‘trapped’ due to flocculation and converging
suspended sediment fluxes (Kranck 1981). River mouths, estuaries, or
transitional waters represent the transition between freshwater and marine
environments and are influenced by both aquatic realms (Robinson et al. 1999).
This makes estuaries unique ecosystems with a range of salinity gradients, from
freshwater to seawater in addition to lentic and lotic habitats (Ruhl 2013).
Fish species with the ability to tolerate huge salinity gradients can be
identified in these various habitats and microhabitats (Barletta et al. 2005;
Breine et al. 2011). Hence, species richness in estuaries is commonly dominated
by marine species (Whitfield 1999; Franco et al. 2008). Moreover, fishes show
migration between estuaries and other ecosystems and are also benefited by the
estuaries markedly in larval development and predator avoidance (Dando 1984;
Leggett 1984).
Estuaries in Sri Lanka are highly
characterized by the variability in size, shape, configuration, ecohydrology,
and tidal fluxes (Miththapala 2013). These wetlands cover approximately 93,075
ha in Sri Lanka’s coastal zone (Department of Coast Conservation and Coastal
Resource Management 2018). Though these ecosystems provide important habitats
for fish taxa, proper ecological studies are scarce to determine the pattern of
fish assemblages associated with the various habitats. Ministry of Forestry and
Environment (1999) reported 53 fish species in mangrove ecosystems in Sri
Lanka. Estuaries a highly dynamic ecosystems, and these facts provide essential
evidence to determine conservation priorities in coastal environment
management. These mangrove and estuarine areas are increasingly subjected to
degradation due to anthropic interventions including tourism, sewage disposal,
the introduction of exotic species, and river diversions (Samarakoon &
Samarawickrama 2012; Miththapala 2013). Therefore, these ecosystems are
particularly important for integrating sound ecological management with
sustainable economics (Meire et al. 2005). Hence, the current study was
conducted to understand the common characteristics of habitat heterogeneity and
fish faunal assemblages associated with estuarine ecosystems.
MATERIALS AND METHODS
Study area
Dedduwa estuary is fed by the
Bentota River and is situated in the southwestern part of Sri Lanka.
Ecologically, the Dedduwa estuary is remarkably important as it comprises
diversified mangroves and related estuarine habitats, which provide essential
living environments for assemblages of fauna and flora. The study area is
approximately 8 km2 (Figure 1) and consists of five different
types of habitats, viz.: (i) ‘Honduwa’ Lake (lentic), (ii) marshy area
with associate aquatic vegetation, (iii) mangroves, (iv) canals, and (v) river.
The Honduwa area is characterized by stagnant saline water (approximately 0.95
km2). There are two major canals connected to Honduwa; one runs
through the inland and connects to the estuary and the other is from the estuary
to the sea. Therefore, the Honduwa Lake often experiences the gradients of
salinity fluctuation. The maximum depth is approximately 2.1 m. Sonneratia
caseolaris and Rhizophora apiculata are the most dominant
mangroves in the area with other associates such as Dillenia suffruticosa, Derris
trifoliate, and Acrostichum aureum. The marshy area is
approximately 0.1 km2. This area contains open water with floating
aquatic vegetation. Most of the open water area is covered by aquatic
vegetation such as Aponogeton crispus, Pistia stratiotes, Ceratophyllum
demersum, Ipomoea aquatica, Hydrilla verticillata, Utricularia
aurea, Nympoides spp., Nymphaea spp., Eichhornia
crassipes, and Salvinia molesta. The floating and marginal
vegetation provide vital refugees for aquatic invertebrates. Hence, this marshy
area is rich with wetland ichthyofauna. Some areas are entirely infested with
invasive aquatic plants like Salvinia molesta and submerged
during the rainy period. Therefore, the abundance of aquatic fauna possibly
shows great fluctuations year-round. Water pools with aquatic weeds provide
good nursery grounds for small fishes. This area is highly influenced by human
alterations. Hence, associated vegetation has been invaded by invasive plants
such as Annona glabra and Typha angustifolia. The
marsh located next to Honduwa Lake (see Figure 1) is approximately 0.86 km2 in
extent. This area contains mixed vegetation of mangroves and freshwater aquatic
plants. Most of the area has open water and is probably ideal for euryhaline
fish species. Much of the riparian vegetation is densely covered by alien D.
suffriticosa which provides a shady environment for aquatic fauna. A
patchy distribution of mangroves can be seen in the marginal areas and provide
nursery grounds for various fish species. The canal contains slow-moving water.
Due to less salinity compared to the estuary or river mouth and high
turbulence, this water may provide proper living environments for rheophilic
freshwater species and anadromous fishes. The canal extends for 2.19 km and
most of the area is covered by mangroves. This is an important migratory
pathway for both marine and brackish water fish species and is highly
influenced by tidal fluctuations. Mixed vegetation with several species of
mangrove (e.g., the considerable distribution of Nypa fruticans)
and mangrove associates can be seen in the area.
Data collection
Fish samples were collected from
September to October 2019 in each of the five sites using a dragnet of the
dimension of 1.5 x 1.5 m with a 2 mm mesh size. Although some other sampling
methods such as gillnets cast nets and traps were also used, the data collected
from those sampling methods were excluded from analysis due to the
inconsistency of the samplings. Every accessible location with different
biological (e.g., different vegetation types) and physical characteristics
(e.g., in different water depths and flow rates) was surveyed, and data were
collected for the analysis. Altogether 117 samples were collected for the
analysis covering all the habitat types (Table 1). The number of individuals of
different species caught in every sampling effort was recorded separately. The
anthropogenic activities that were carried out at each sampling site were
observed such as disposal of sewage and fishing activities. Also, the abundance
of microhabitat types was noted in different segments of the river and estuary
(see Table 5 in the results section).
Diversity indices
The diversity of fish in each
site was estimated using the following different methods in Primer V.5.2.2
software (Clark & Warwick 2001).
Shannon-Wiener index (H’)
(Shannon 1948)
where pi = the
proportion of species i relative to the total number of species
Margalef diversity index (d)
(Margalef 1958)
where S is the number of species,
and N is the total number of individuals in the sample.
Brillouin index (Brillouin 1956),
HB, was calculated using:
where N is the total
number of individuals in the sample, ni is the number of individuals
belonging to the ith species, and s is the species
number. The Brillouin index measures the diversity of a collection, as opposed
to the Shannon index which measures a sample.
Fisher’s alpha, S (Fisher
et al. 1943)
This is a parametric index of
diversity given below assumes that the abundance of species follows the ln
series distribution:
where S is the number of
taxa, N is the number of individuals
where α the diversity index
Simpson index, D (Simpson
1949)
where N is the total number of
individuals in the sample, and n is the number of individuals belonging to a
certain species. It measures the ‘evenness’ of the community ranging from 0 to
1.
Pielou’s evenness index (J)
(Pielou 1969, 1975)
If H is the observed
Shannon-Wiener index, the maximum value this could take is log(S), where S is
the total number of species in the habitat.
Taxonomic distinctness tests
To determine the taxonomic
distance the following approach was adopted. Species were classified to all
major taxonomic levels in a Linnean classification following the taxonomy of
the fauna (Beesley et al. 1998). A constant path length (ω = 1) between levels
was used to calculate the taxonomic distance between species pairs (Warwick
& Clarke 1995). Average Taxonomic Distance (AvTD) was calculated using
presence/absence data from each site. Using each separate dataset, taxonomic
distinctness was quantified using the TAXDTEST procedure in the PRIMER-V.5.2.2
software package (Clarke & Warwick 2001). The ‘variation in taxonomic
distinctness’ [VarTD, Lambda (+)] between every pair of species recorded in a
study. It matches the previously defined ‘average taxonomic distinctness’
[AvTD, Delta (+)], which is the mean path length through the taxonomic tree
connecting every pair of species in the list. VarTD is simply the variance of
these pairwise path lengths and reflects the unevenness of the taxonomic tree.
Samples from the master list were used to generate an expected distribution of
values, including a mean and 95% confidence interval. The expected distribution
was represented visually as a funnel plot, showing values for different numbers
of species, and the observed values were overlaid on the plot. This was used to
test the null hypothesis that each observed value had the same value as one
predicted using the master list, rejected at the 5% significance level (Clarke
& Warwick 2001; Smith & Rule 2002), i.e., sites falling outside the 95%
confidence limits were interpreted as having an AvTD value significantly lower
(or higher) than expected.
Comparative analysis of
ichthyofaunal diversity and abundance
To compare the diversity and
abundance of fish in each habitat type, the mean abundance data of each species
were used. The similarities of fish communities among sampling sites were
determined by the Bray-Curtis similarity coefficient (Bray & Curtis 1957).
The ln (x+1) transformation was used before analysis due to the presence of
zero values. The ordination of non-metric Multidimensional Scaling (MDS) of
sampling sites was determined based on the Bray-Curtis similarity matrix
(Clarke & Warwick 2001) using the PRIMER-5 software package (Version
5.2.2). Bray-Curtis similarity analysis was done by using two different
approaches. One approach was the analysis performed by separating abundance
data for the different species into the five habitat types identified (Table 1)
and the second approach was considering all the sampling locations as a single
data set and freely clustered it according to the similarity of species
composition in each location.
RESULTS
Altogether 41 species of fish
were identified including marine, true estuarine, and freshwater species (Table
2). A higher number of species was recorded at the Honduwa Lake and the estuary
(18 species in each habitat) while the lowest (12 species) was recorded
associated with the river (Table 4). Of these, Clarias brachysoma and Horadandia
atukorali were the endemic freshwater species identified. Species namely Oryzias
dancena, Etroplus suratensis, Ambassis ambassis, Butis butis, and Bhava
vittatus were identified in all five different habitat types (Table 2). The
results of the present study did not show any dominant group in the assemblage.
In Honduwa Lake, estuary, and river the most dominant species were Ambassis
ambassis, Butis butis, O. dancena, and Etroplus suratensis
contributing 88.4%, 77.9%, and 74.5 % in abundance respectively (Figure 2). The
most abundant species in freshwater marsh habitats were Horadandia atukorali
(42.3%) and in the canal area was Ehirava fluviatilis (29%) (Figure 2).
The occurrence of dominant species in saline waters (e.g., estuarine area and
Honduwa Lake) showed approximately a similar pattern in abundance. Comparing
saline habitats with freshwater habitats (e.g. marsh with aquatic vegetation) a
remarkable difference in patterns of species dominance was observed (Figure 2).
When the Bray-Curtis similarity
index based on the abundance of fish species is considered, the freshwater
marshy habitat was separated from other sampling sites at about the 28.9% level
of similarity (Figure 3). The similarity level of fish abundance in the canal
area with Honduwa Lake is approximately 51.2% (Figure 3). Also, the canal area
with Honduwa Lake further separated from the rest of the sampling sites in the
MDS ordination (Figure 4). The diversity indices Shanon, Brillouin, and Simpson
showed the highest diversity in river and canal habitats. Margelef index showed
the highest species richness in estuarine habitats. The evenness of the
species is approximately high in estuary and canal (Table 3).
The Bray Curtis similarity
analysis for the species abundance of different habitats indicated five
distinct clusters in a 25% similarity level (Figure 5). It differentiates the
freshwater marsh and the canal into a single cluster (I) possibly due to the
similarity of habitat choices of freshwater fishes associated with the two
areas (e.g., low salinity). Honduwa Lake, canal, estuary, and some sampling
locations in the river are grouped into a single cluster at 20% similarity
level. As majority of the species in these four habitats are common except a
few species such as Megalops cyprinoides, Scatophargus argus, Monodactylus
argentius. These four habitats were somewhat similar due to the presence of
mangroves. B. butis and A. Ambassis, are almost equally
distributed among canal, estuary, river, and Honduwa Lake, indicating
approximately a similar species composition among sites. At the 25% similarity
level, this cluster split into two distinct clusters, possibly due to the
higher number of A. ambassis and B. butis caught in cluster V
compared to cluster IV. Cluster II and III contained different species whereas
Cluster III contained O. dancena and E. suratensis which were not
observed in Cluster II. The Margelef species richness index was higher in
clusters I and IV which were associated with freshwater/canal habitat and a
combination of canal, estuary, Honduwa Lake, and river respectively. Simpson
index was high in clusters I, II, and V (Table 4). The values of Fisher and
Pielou’s indices are comparatively higher in clusters I, II and V. Similarly,
Shannon and Brillouin indices indicate high species richness and evenness in
clusters I, II, and V (Table 4).
The taxonomic diversity of the
area is within the expected diversity (see Figure 6A). The taxonomic diversity
is expressed as observed average taxonomic distinctions (Figure 6A) and
variation of taxonomic distinctions (Figure 6B). Honduwa Lake and the estuary
are occupied by nearly similar species. Therefore, taxonomic diversity shows an
approximately similar variation (Figure 6A). The canal includes species in
different genera such as Anguilla, Eleotris, and Channa and
therefore, the canal is different from the other four habitats with
taxonomic diversity (Figure 6A). Freshwater habitat was occupied by distinctive
genera such as Rasbora, Anabas, Horadandia, Channa, Clarias, Heteropneustes,
and Puntius. Therefore, freshwater habitats also showed high and
distinctive taxonomic diversity beyond the expected taxonomic variation
compared to other habitats (Figure 6B). The overall taxonomic diversity is
shown in Fig. 7 indicating probability contours (back-transformed ellipses)
between AvTD and VarTD with a range of sublist sizes.
The fish fauna seems influenced
by the various fishing activities of the fishers. Though commercial fishing
activities are uncommon, artisanal fishers operate their vessels in every
accessible area. Brush piles were found in Honduwa Lake in the northern part of
the estuary. Encircling nets were operated in the river, Honduwa Lake, and the
estuarine area. No operation of encircling nets was observed in the canal
segment (Table 5).
DISCUSSION
The fish fauna of estuarine
systems has long been regarded as dominated by estuarine-dependent or
estuarine-opportunistic marine species, with the movement of fishes among
different salinity gradients being largely determined by the distribution of
various habitats and tidal influences (Vieira & Musick 1994). The current
finding of 41 fish species from the estuary and related habitats provides
insight into the importance of habitat assessment and biodiversity
conservation. The fish assemblage in the area is highly vulnerable to being
threatened due to the proposed future development activities. Some species have
a wide distribution and are found in several habitats while others show a more
confined distribution restricted to specialized habitats (see Figure 2). The
current study reveals that the distribution of fish species in Honduwa Lake,
the Dedduwa Estuary, and the river shows a closely similar pattern. The
distribution of species in the canal and freshwater marsh area is different
from Honduwa Lake, estuarine area, and river (Figure 4). The variation of
salinity could be the major limiting factor for the species distribution among
these habitats. The major difference among the three systems is that the
Honduwa and the estuarine area act as a lentic ecosystem while the river is a
lotic ecosystem. This difference may have also brought about differences in
ichthyofaunal diversity and distribution among habitats.
According to the results
presented in this study, the species distribution in the two different salinity
gradients in freshwater and brackish water habitats is comparatively different
(Figure 3). The species with a wide range of distribution probably are
euryhaline (Bulger et al. 1993). Majority of the species recognized as the
juvenile stage which denoted mangroves of the riparian habitat provide proper
feeding and nursery ground for juvenile stages. The glass eels of Anguilla spp.
found from the canal area provides evidence of the breeding migration of the
catadromous species (Table 2). IUCN (2011), describes the breeding migration of
Anguilla bicolor (Level fin eel) in the Kala Oya River basin of Sri
Lanka and further explains the importance of seagrass beds as refuges of the
glass eels. The current finding of glass eels associated with canals and estuaries
is particularly important because it explains the eel migration and probably a
good indicator of future conservation actions. Nevertheless, the presence of
fishes with different migration types such as Amphidromous, Anadromous,
Potadromous, and Oceanodromous highlights the importance of the estuary for
stabilizing the community structure of fishes (Table 2).
The results show the freshwater
habitats (e.g. canal and marsh) are clearly distinguished from brackish water
habitats according to the species composition (Figure 6). These canals in more
inland areas are connected with freshwater habitats and provide perfect
habitats for Polyhaline (conditions ranging from a salinity of 18 –30 ppt),
Mesohaline (waters with a salinity between 5 and 18 ppt), and Oligohaline
(waters with salinity from 0.5–5 ppt) species (Karleskint 1998) because with
high salinity influx, those species probably migrate towards the headwaters of
the canal and streams probing for fewer salinity areas (Table 2).
In this analysis, different
indices were used to describe the diversity of fish fauna in different habitats
in the estuarine area. Because different diversity indices give results in
different integrity. The Shannon index is based on percentage composition by
species (Magurran 1988). When the randomness of the sampling cannot be
guaranteed, the Brillouin index was used to calculate the heterogeneity
(Southwood & Henderson 2000). This is because several sampling locations
were inaccessible, due to the abundance of crocodiles, snags, and high water depth. Shannon index gives similar results where
proportional abundance and number of species in the sample remain constant
(Magurran 1988). The Brillouin index measures diversity as opposed to the
sample. Both Shanon and Brillouin indices have given approximately similar
results as indicated by Magurran (2004). Simpson index is more biased towards
the most abundant species rather than species richness (May 1975). Pielou’s
evenness is an index that measures diversity along with species richness.
Compared with indices such as Simpson’s index or Shannon’s index, a more
thorough description of a community structure can be interpreted using Pielou’s
evenness (Heip & Herman 2001). Margalef’s diversity index is a species
richness index (Gamito 2010). Many species richness measures suffer from the
problem that they are strongly dependent on sampling effort. The greater the
sampling effort potentially the higher the index value. Thus, comparing metrics
from samples collected with differing levels of sampling effort can be
difficult and possibly misleading (Gamito 2010). As mentioned above (see
methodology section) data generated from the alternative sampling efforts were
excluded from the analysis, and the analysis may have been affected due to insufficient
representation of fish species in the samples. Further considering the
diversity measurements, Fisher’s Alpha (α) is widely used as a diversity
index to compare communities varying in the number of individuals (N), because
theoretically independent of sample size. This is highly dependent on the
sample size and the total number of species (Magurran 1988). Hence, Honduwa
Lake habitat and estuarine area (Table 3) and Cluster I and IV (Table 4) show
higher Fisher’s alpha indices.
The average taxonomic
distinctness index (AvTD, Δ+) measures the average taxonomic distance between
species at a site, or the average path length joining every pair of individuals
in a sample, using a standard Linnean classification, i.e. species, genus,
family, order, class etc. (Warwick & Clarke 1995). The variation in
taxonomic distinctness index (VarTD, Λ+) measures the variation in the average
distance between species pairs (Clarke & Warwick 2001). The taxonomic
diversity of the fish fauna observed in the area is within the expected range
(Figure 6) confirming the high accuracy of the sampling. Except for migratory
species, the distribution of the fish fauna in the estuarine areas is
location-specific (Bruno et al. 2013). This specifies the ecological
significance and conservation needs of the different types of habitats to
conserve different species. Results show the freshwater habitats are unique to
several endemic species, especially around marshes including Horadandia
atukorali and Clarias brachysoma. These two species are highly
localized for aquatic habitats with submerged vegetation (Pethiyagoda 1991).
The area is extremely popular for
the tourism industry. The high visitor pressure and pollution of the freshwater
systems seem to be a major threat to the freshwater fish fauna. The loss of
riparian habitats was also observed during the field observations. Freshwater
species abundance was higher in inland marshes and canals where there is less
tidal effect. Though, mesohaline freshwater species like Channa spp. and
Puntius spp. (Table 2) were observed in these freshwater segments, those
species were not detected in the brackish water areas. The abundance and
distribution of freshwater species increased notably with rainfall. These
abiotic factors are important to explain the range expansion of the freshwater
species in estuarine systems (Drinkwater & Frank 1994).
CONCLUSIONS
Fish fauna in the Dedduwa estuary
provides insight into habitat preference and fish assemblages. The mutualistic
relationship between fishes and habitats promotes the stability and
functionality of this wetland habitat. The presence of the two endemic and vulnerable
species—Horadandia atukorali and Clarias brachysoma—in marshy
freshwater habitat and catadromous migration of Anguilla spp. highlights
the conservation importance. In the current study freshwater systems are
associated with canals where water quality is often vulnerable due to
anthropogenic inputs such as sewage and solid waste and are likely to have
noticeable impacts on the freshwater and amphidromous fishes. Though the
species richness in the studied habitat was approximately similar, higher variations
were observed in the abundance of different species. This demonstrates the
habitat-orientated species distribution and ontogenetic habitat shifting of
different species in the study area. The presence of fish species with
different migratory habits denoted the importance of the estuary as a refuge
and feeding ground for juvenile fish during their critical development stages.
Therefore, current habitat alterations and pollution loads from different
sources would affect the movement of the fishes and must be kept to be minimum.
Table 1.
Summary of the sampling efforts of five different aquatic habitats in the
Dedduwa estuary, Sri Lanka.
|
Habitat |
Total number of
samples |
|
Honduwa Lake area |
27 |
|
Estuarine area |
24 |
|
Canal area |
32 |
|
Rivermouth |
15 |
|
Mashy area with floating
aquatic vegetation |
19 |
Table 2.
Checklist of ichthyofauna recorded from the different habitats in the Dedduwa
estuary, Sri Lanka. Endemic species are mentioned in bold letters. The
migratory habit of relevant fishes is also mentioned as superscripted
abbreviations after the scientific name. All the abbreviations are explained
after the table.
|
|
Family |
Scientific name (abbreviation) |
Common name |
Conservation status |
Habitats |
Salinity range |
Source |
|||||
|
|
|
|
|
NCS |
GCS |
HLH |
ES |
RI |
FWM |
CN |
|
|
|
1. |
Adrianichthyidae |
Oryzias dancena (OD) |
Rice fish |
NE |
LC |
+ |
+ |
+ |
+ |
+ |
Polyhaline |
Roberts 1998 |
|
2. |
Ambassidae |
Ambassis ambassis Oce.
(AA) |
Commerson's glassy |
NE |
LC |
+ |
+ |
+ |
+ |
+ |
Polyhaline |
Fricke 1999 |
|
3. |
Anabantidae |
Anabas testudineus Pot. (AT) |
Climbing perch |
LC |
LC |
|
|
|
+ |
|
Mesohaline |
Talwar and Jhingran 1991 |
|
4. |
Anguillidae |
Anguilla spp.Cat. (AS) |
Eel |
|
|
|
|
|
|
+ |
Polyhaline |
Kottelat 2013 |
|
5. |
Aplocheilidae |
Aplocheilus parvus (AP) |
Dwarf panchax |
LC |
LC |
|
|
|
+ |
|
Mesohaline |
Seegers 1997 |
|
6. |
Ariidae |
Arius maculatus Pot.
(AM) |
Spotted catfish |
NE |
NE |
+ |
|
|
|
|
Polyhaline |
Kailola 1999 |
|
7. |
Carangidae |
Caranx sexfasciatus Amp. (CS) |
Bigeye trevally |
NE |
LC |
+ |
+ |
+ |
|
+ |
Polyhaline |
Paxton 1989 |
|
8. |
Channidae |
Channa punctata Pot. (CP) |
Spotted snakehead |
LC |
LC |
|
|
|
+ |
|
Mesohaline |
Pethiyagoda 1991 |
|
9. |
Channidae |
Channa striata Pot.
(CS) |
Striped snakehead |
LC |
LC |
|
|
|
+ |
+ |
Mesohaline |
Pethiyagoda 1991 |
|
10. |
Cichlidae |
Etroplus suratensis (ES) |
Pearl spot |
LC |
LC |
+ |
+ |
+ |
+ |
+ |
Mesohaline |
Pethiyagoda 1991 |
|
11. |
Cichlidae |
Oreochromis niloticus Pot. (ON) |
Nile tilapia |
EX |
LC |
|
|
+ |
|
|
Mesohaline |
Trewavas 1983 |
|
12. |
Clariidae |
Clarias brachysoma* (CB) |
Walking catfish |
VU |
NE |
|
|
|
+ |
|
Oligohaline |
Pethiyagoda 1991 |
|
13. |
Clupeidae |
Anodontostoma chacunda Ana. (AC) |
Chacunda gizzard shad |
NE |
LC |
|
+ |
|
|
|
Polyhaline |
Whitehead 1985 |
|
14. |
Clupeidae |
Dayella malabarica Amp. (DM) |
Day's round herring |
NE |
LC |
|
+ |
|
|
|
Polyhaline |
Whitehead 1985 |
|
15. |
Clupeidae |
Ehirava fluviatilis Amp. (EF) |
Malabar sprat |
NE |
LC |
|
|
|
|
+ |
Polyhaline |
Whitehead 1985 |
|
16. |
Cyprinidae |
Plesiopuntius bimaculatus (PB) |
Redside barb |
LC |
LC |
|
|
|
+ |
|
Oligohaline |
Pethiyagoda 1991 |
|
17. |
Cyprinidae |
Bhava vittatus (PV) |
Silver barb |
LC |
LC |
+ |
+ |
+ |
+ |
+ |
Mesohaline |
Pethiyagoda 1991 |
|
18. |
Cyprinidae |
Rasbora dandia (RD) |
Broadline striped rasbora |
LC |
LC |
|
|
|
+ |
|
Oligohaline |
Silva et al. 2010 |
|
19. |
Cyprinidae |
Horadandia atukorali* (HA) |
Green carplet |
VU |
|
|
|
|
+ |
+ |
Mesohaline |
Pethiyagoda 1991 |
|
20. |
Eleotridae |
Butis butis Amp. (BB) |
Duckbill sleeper |
NE |
LC |
+ |
+ |
+ |
+ |
+ |
Polyhaline |
Hoese 1986 |
|
21. |
Eleotridae |
Eleotris fusca Amp. (EF) |
Dusky sleeper |
NE |
LC |
|
|
|
|
+ |
Polyhaline |
Maugé 1986a |
|
22. |
Gerreidae |
Gerres filamentosus Amp. (GF) |
Whipfin silver-biddy |
NE |
LC |
+ |
+ |
|
|
|
Polyhaline |
Woodland 1984 |
|
23. |
Gerreidae |
Gerres limbatus Amp. (GL) |
Saddleback silver-biddy |
NE |
LC |
+ |
+ |
|
|
|
Polyhaline |
Iwatsuki et al. 2001 |
|
24. |
Gobiidae |
Glossogobius giuris Amp. (GG) |
Tank goby |
LC |
LC |
+ |
|
+ |
+ |
|
Polyhaline |
Maugé 1986b |
|
25. |
Gobiidae |
Caragobius urolepis Amp. (CU) |
Scaleless worm goby |
NE |
LC |
|
|
+ |
|
|
Mesohaline |
Kottelat et al. 1993 |
|
26. |
Gobiidae |
Oligolepis cf. acutipennis
Amp. (OA) |
Sharptail goby |
NE |
LC |
|
|
+ |
|
|
Polyhaline |
Maugé 1986b |
|
27. |
Gobiidae |
Gobius malabaricus Amp. (GM) |
Malabar goby |
NE |
LC |
|
+ |
+ |
|
|
Polyhaline |
Maugé 1986b |
|
28. |
Hemiramphidae |
Hyporhamphus limbatus Pot. (HL) |
Congaturi halfbeak |
NE |
LC |
+ |
|
|
|
|
Polyhaline |
Collette and Su 1986 |
|
29. |
Heteropneustidae |
Heteropneustes fossilis (HF) |
Asian stinging catfish |
LC |
LC |
|
|
|
+ |
|
Mesohaline |
Rainboth 1994 |
|
30. |
Leiognathidae |
Leiognathus equulus Amp. (LE) |
Common ponyfish |
NE |
LC |
+ |
+ |
|
|
|
Polyhaline |
James 1984 |
|
31. |
Lutjanidae |
Lutjanus argentimaculatus Oce. (LA) |
Mangrove red snapper |
NE |
LC |
+ |
+ |
+ |
|
|
Polyhaline |
Allen 1985 |
|
32. |
Megalopidae |
Megalops cyprinoides Amp. (MC) |
Indo-Pacific tarpon |
NE |
DD |
+ |
|
|
|
+ |
Polyhaline |
Whitehead 1984 |
|
33. |
Monodactylidae |
Monodactylus argenteus (MA) |
Silver moony |
NE |
LC |
|
+ |
|
|
|
Polyhaline |
Heemstra 1984 |
|
34. |
Mugilidae |
Mugil cephalus Cat. (MC) |
Flathead grey mullet |
NE |
LC |
+ |
|
|
|
+ |
Polyhaline |
Harrison 1995 |
|
35. |
Osphronemidae |
Pseudosphromenus cupanus (PC) |
Spiketail parasidefish |
LC |
LC |
|
|
|
+ |
+ |
Mesohaline |
Pethiyagoda 1991 |
|
36. |
Osphronemidae |
Trichopodus trichopterus (TT) |
Three spot gourami |
EX |
LC |
|
|
|
+ |
|
Oligohaline |
Rainboth 1996 |
|
37. |
Osphronemidae |
Trichopodus pectoralis (TP) |
Snakeskin gourami |
EX |
LC |
|
|
|
+ |
|
Oligohaline |
Rainboth 1996 |
|
38. |
Scatophagidae |
Scatophagus argus Amp. (SA) |
Spotted scat |
NE |
LC |
+ |
|
|
|
|
Polyhaline |
Schofield 2021 |
|
39. |
Sillaginidae |
Sillago sihama Amp.
(SS) |
Silver sillago |
NE |
LC |
+ |
+ |
|
|
|
Polyhaline |
McKay 1992 |
|
40. |
Soleidae |
Brachirus orientalis Ana. (BO) |
Oriental sole |
NE |
NE |
|
+ |
|
|
|
Polyhaline |
Munroe 2001 |
|
41. |
Tetraodontidae |
Chelonodon patoca Ana.
(CP) |
Milk spotted puffer |
NE |
LC |
|
+ |
|
|
+ |
Polyhaline |
Kottelat et al 1993 |
|
Amp.—Amphidromous |
Ana.—Anadromous | Cat.—Catadromous | CN—Canal | DD—Data deficiency | E—English | ES—Estuary |
EX—Exotics | FWM—Freshwater marshy area | GCS—Global conservation standards |
HLH—Honduwa Lake habitat | LC—Least concern | NCS—National conservation
standards | Oce.—Oceanodromous | Pot—Potamodromous | RI—River | S—Sinhala |
VU—Vulnerable; */bold—Endemic |
||||||||||||
Table 3.
Different diversity indices and related diversity values were calculated to
represent the fish diversity of studied habitats in the Dedduwa Estuary, Sri
Lanka.
|
|
S |
N |
Margelef index |
Pielou’s evenness |
Fisher evenness |
Brillouin |
Shanon |
Simpson index |
|
Honduwa |
18 |
576 |
2.67 |
0.55 |
3.52 |
1.54 |
1.59 |
0.74 |
|
River |
12 |
213 |
2.04 |
0.81 |
2.72 |
1.90 |
2.03 |
0.84 |
|
Estuary |
18 |
164 |
3.06 |
0.59 |
4.41 |
1.60 |
1.72 |
0.74 |
|
Canal |
15 |
377 |
2.74 |
0.74 |
4.01 |
1.89 |
2.02 |
0.84 |
|
Freshwater |
16 |
253 |
2.52 |
0.68 |
3.38 |
1.79 |
1.90 |
0.77 |
|
S—Total number of species or
species richness | N—Number of individuals tested for the analysis. |
||||||||
Table 4.
Different diversity indices and related diversity values were calculated to
represent the fish diversity of the Dedduwa Estuary, Sri Lanka, for different
given clusters in Bray-Curtis similarity analysis in Figure 6.
|
Cluster |
S |
N |
Margelef index |
Pielou’s evenness |
Fisher evenness |
Brillouin |
Shanon |
Simpson index |
|
I |
18 |
346 |
2.91 |
0.67 |
4.03 |
1.86 |
1.94 |
0.78 |
|
II |
13 |
403 |
2.00 |
0.78 |
2.56 |
1.96 |
2.02 |
0.79 |
|
III |
11 |
747 |
1.51 |
0.46 |
1.82 |
1.07 |
1.09 |
0.51 |
|
IV |
18 |
406 |
2.83 |
0.51 |
3.85 |
1.40 |
1.47 |
0.68 |
|
V |
14 |
227 |
2.40 |
0.80 |
3.29 |
1.80 |
1.91 |
0.81 |
|
S—Total number of species or
species richness | N—Number of individuals tested for the analysis. |
||||||||
Table 5. The
presence of aquatic vegetation and related anthropogenic activities at the five
sampling sites of the Dedduwa Estuary, Sri Lanka.
|
|
Presence of aquatic vegetation |
Anthropogenic activities |
|||
|
|
Presence of mangroves |
Presence of aquatic weeds |
Encircling nets |
Disposal of waste |
Brush park |
|
Honduwa Lake habitat |
H |
- |
+ |
- |
+ |
|
Estuary |
H |
- |
+ |
- |
- |
|
River |
H |
- |
+ |
+ |
- |
|
Canal |
L |
+ |
- |
- |
- |
|
Freshwater marsh |
- |
+ |
- |
+ |
- |
|
H—high | L—Low |
+/-—Presence/Absence. |
|||||
For
figures – click here for full PDF
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