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RESEARCH PAPER
Fish distribution patterns in the White Drin (Drini i Bardhë) river,
Kosovo
Linda Grapci-Kotori
1
, Theocharis Vavalidis
2,6
, Dimitris Zogaris
3
, Radek Šanda
4
, Jasna Vukić
5
,
Donard Geci
1
, Halil Ibrahimi
1
, Astrit Bilalli
1
and Stamatis Zogaris
6,*
1
Department of Biology, Faculty of Mathematical and Natural Sciences, University of Prishtina “Mother Theresa”, 10 000 Prishtina,
Republic of Kosovo
2
Laboratory of Ichthyology, Department of Zoology, School of Biology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
3
Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, 38446 Volos, Greece
4
National Museum, Department of Zoology, 115 79 Prague, Czech Republic
5
Department of Ecology, Charles University, 128 44 Prague, Czech Republic
6
Institute of Marine Biological Resources and Inland Waters, Hellenic Centre for Marine Research, Anavissos, 19013 Attiki, Greece
Received: 31 January 2020 / Accepted: 27 May 2020
Abstract –Fish assemblages and their distributions in the western Balkan rivers have rarely been
investigated. This study provides initial insights into the spatial patterns of fish distributions in the main-
stem of the White Drin in Kosovo. Sampling primarily utilized back-pack electrofishing at 11 sites along the
river’s entire main stem, recording 21 species. Identification of most fish species was confirmed through
DNA barcode analyses; two yet unnamed species are present and some taxonomic problems were
discovered. The abundance of non-native species was low (5.9% of the catch) but seven of the eight non-
natives have established populations. A longitudinal fish zonation pattern was described for the first time in
this river; fish assemblages in an upstream-to-downstream gradient were characterized by a decrease of
cold-water species (salmonids, minnows) and an increase of large-river cyprinids and non-native species.
Multivariate ordination and network analyses demarcate preliminary fish assemblage types and specific
environmental and anthropogenic pressure attributes are shown to influence assemblage structure. Natural
assemblage patterns may be locally disrupted by anthropogenic pressures such as pollution and
hydromorphological disturbances, however most sites show semi-natural features and conditions.
Recommendations for conservation and further research are provided.
Keywords: rivers / fish zones / Balkans / endemic species / taxonomy
Résumé –Distribution des poissons dans la rivière White Drin (Drini i Bardhë), Kosovo. Les
assemblages de poissons et leur répartition dans les rivières des Balkans occidentaux ont rarement fait
l’objet d’études. Cette étude donne un premier aperçu des schémas spatiaux de distribution des poissons
dans le cours principal de la White Drin au Kosovo. L’échantillonnage a principalement été réalisé par pêche
électrique à dos sur 11 sites le long du cours principal de la rivière, avec collecte de 21 espèces.
L’identification de la plupart des espèces de poissons a été confirmée par des analyses de codes-barres ADN;
deux espèces non encore identifiées sont présentes et certains problèmes taxonomiques ont été découverts.
L’abondance des espèces non indigènes était faible (5,9% des prises), mais sept des huit espèces non
indigènes ont établi des populations. Un modèle de zonage longitudinal des poissons a été décrit pour la
première fois dans cette rivière; les assemblages de poissons dans un gradient d’amont en aval ont été
caractérisés par une diminution des espèces d’eau froide (salmonidés, vairons) et une augmentation des
cyprinidés de grande rivière et des espèces non indigènes. Des analyses d’ordination et de réseau
multivariées délimitent les types préliminaires d’assemblages de poissons et il est démontré que des indices
de pression environnementaux et anthropiques spécifiques influencent la structure des assemblages. Les
modèles d’assemblage naturels peuvent être localement perturbés par des pressions anthropiques telles que
la pollution et les perturbations hydromorphologiques, mais la plupart des sites présentent des
*Corresponding author: zogaris@hcmr.gr;zogaris@gmail.com
Knowl. Manag. Aquat. Ecosyst. 2020, 421, 29
©L. Grapci-Kotori et al., Published by EDP Sciences 2020
https://doi.org/10.1051/kmae/2020020
Knowledge &
Management o
f
A
quatic
Ecosystems
www.kmae-journal.org
Journal fully supported by Office
français de la biodiversité
This is an Open Access article distributed under the terms of the Creative Commons Attribution License CC-BY-ND (https://creativecommons.org/licenses/by-nd/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work is properly cited. If you remix, transform, or build upon the material, you may not distribute the modified material.
caractéristiques et des conditions semi-naturelles. Des recommandations pour la conservation et des
recherches supplémentaires sont fournies.
Mots clés : rivières / zones piscicoles / Balkans / espèces endémiques / taxonomie
1 Introduction
Knowledge of fish assemblages provide a unique view into
river biota, framing a reference for monitoring river health and
conservation. River fish distributions are not randomly
ordered, they show spatial assemblage structure; specific
conditions and anthropogenic pressures affect them
(Matthews, 1998;Sutela et al., 2010). In many jurisdictions,
such as in the European Union, governments are obliged to
classify their surface water bodies on the basis of a typology
that is relevant to natural species assemblage structure (EU,
2003). Fish are therefore important in classifying aquatic
systems both at the longitudinal river scale and regional scale
and this has important implications for policy-relevant
monitoring and water management (Aarts and Nienhuis,
2003;Zogaris et al., 2009). Classifications of fish assemblages
are also critically important in biodiversity conservation, since
individual fish assemblage or community units may warrant
conservation actions (Angermeier and Schlosser, 1995;
Angermeier and Winston, 1999). Fish assemblage classifica-
tions are also dependent on a knowledge of fish taxonomy, an
active research area in recent years, especially in globally
important biodiversity regions such as the Balkans (Kottelat
and Freyhof 2007;Vavalidis et al., 2019). In this study, we
focus on a poorly-explored hotspot for fish diversity in Europe,
a tributary of the Drin river in the western Balkans.
Since the break-up of Yugoslavia in the early 1990s and
serious civil strife and war in the region the study of river
biodiversity has been sidelined for decades (Skoulikidis et al.,
2009). The Ohrid-Drin-Skadar river system (hereafter ODS)
being the largest river basin (19,686 km
2
) in the Southeast
Adriatic Freshwater Ecoregion is an understudied biodiversity
hotspot (Freyhof and Brooks 2011;Darwall et al., 2014;
Ibrahimi et al., 2014;WWF/TNC 2019). We focus on one of
the two main tributary branches of this river system, the White
Drin (Drini i Bardhë) in Kosovo. Basic knowledge of fish
assemblage distributions are poorly documented (Grapci-
Kotori et al., 2010;Wenke, 2017) and unusually for a
European river, there are still serious problems with fish
taxonomy in the ODS as a whole (for example, Marková et al.,
2010;Palandačićet al., 2015). However, there is active interest
in applying biomonitoring and bioassessment to European
Union standards (Grapci-Kotori et al., 2013). This study
provides insights for fish distribution spatial structure in the
main stem of the White Drin, focusing on species-level
taxonomy and fish community assemblage classification, in an
effort to help build baselines for biodiversity and river health
monitoring.
2 Study area and methods
2.1 River catchment
The ODS has two main tributaries: the White Drin, arising
from Northwestern Kosovo and the Black Drin from Lake
Ohrid (North Macedonia, Albania) which is also fed by
subterranean waters from Lake Prespa (North Macedonia,
Albania, Greece). The basin discharges in the Adriatic near the
Albania-Montenegro border. Much of the system within
Albania and North Macedonia has been artificially impounded
by five high hydroelectric dams (Skoulikidis et al., 2009;
Spirkovski et al., 2017). The free-flowing part of the White
Drin (Drini i Bardhë) is 109 km long and comprises a
catchment of 4340 km
2
; all within the Republic of Kosovo. It
has the highest river water flow in Kosovo and is the second
most significant sub-basin of the Drin (Grapci-Kotori et al.,
2010). Nearly the entire White Drin valley is located on an
upland plateau between 300 to 450 m. a.s.l. and is nearly
surrounded by high alpine mountains with a continental
temperate climate. This spring-fed river hosts extensive cold
and cool-water conditions that are rare in low-relief
topography conditions in the Mediterranean river catchments.
These river conditions are influenced by a rather long period of
winter freezing and a strong spring freshet flooding. Although
river flow drops in the summer, it does not decrease markedly
such as in most other Mediterranean rivers; the entire main-
stem and major tributaries sustain perennial flow conditions.
The White Drin catchment crosses the Kosovo-Albanian
border at the lowest point (280 m. a.s.l.), near Vermicë, where
the river condition is already affected by the permanent
impounding due to the Albanian hydroelectric-dam of Fierza
on the main stem of the Drin.
2.2 Sampling
Fish sampling was conducted at 11 sites along the
longitudinal axis of the main stem of the White Drin during
low river flow (July 2019); while three sites sampled in
summer had been previously sampled in winter as well
(December 2017). The sampling network covered representa-
tive reaches along a 95 km distance within the entire area of the
flow of the river’s main stem in Kosovo, from just a few
hundred meters downstream of the White Drin springs to near
the Kosovo-Albania border. The sites were distributed as
evenly as possible and with a representative cover of all
available natural habitats (Fig. 1).
Sampling consisted primarily of electrofishing, following
approaches used through the European Union Water Frame-
work Directive (EU WFD) monitoring protocols (CEN, 2003)
which has been applied in several areas of the Balkans
(IMBRIW, 2013;Zogaris et al., 2018). Sampling was located
at a river stretch usually demarcated by physical boundary
features to minimize fish escape during electrofishing (e.g.
riffle areas, changes in instream habitats, natural or artificial
barriers). A high-quality battery-powered back-pack electro-
fishing unit was used (Smith Root 24L DC pulsed, 1.5 KW,
35–100 Hz, max 980 V.). At each site, a single pass of at least a
100 m river stretch was completed, without using a stop-net
(average fishing-time was 71 min). At all sites, fish were
collected in large water-filled buckets and processed on shore.
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L. Grapci-Kotori et al.: Knowl. Manag. Aquat. Ecosyst. 2020, 421, 29
Fish were identified to species or genus level in the field;
counted, measured to size-class intervals and most were
released back to the river (following a technique described in
Dußling et al., 2004;IMBRIW, 2013). Selected specimens
where collected for lab inspection (see below) and photogra-
phy in a portable aquarium. All fish were rapidly inspected for
significant DELT anomalies such as external deformities,
eroded fins, lesions and tumours (Sanders et al., 1999),
however only severely unhealthy fish were recorded as having
DELTs.
In all sampling sessions, the same operator electrofished
and the same or similar field crews participated in order to
ensure that effort was consistent among sites. The field crew
consisted of one electrofisher operator (who also usually
carried the back-pack generator and a dip-net) and at least three
other participants with dip-nets. At the three lower river
reaches where river depth exceeded waist-high in the majority
of the channel, back-pack electrofishing was supplemented by
a combination of fishing methods to adequately sample the
assemblage. In two sites electrofishing through wading was
supplemented by electrofising by boat (using the same
generator), while cast net samples and/or overnight gill-nets
were also used at another three sites (see Tab. 2). The gill nets
used were two simple and relatively short nylon nets (7 m long
and 1.5 m high; 4 cm mesh-size); this size of mesh is aimed to
catch relatively large-sized fish, which may escape electro-
fishing in deeper waters. The gill-nets were tied to tree
branches and set for about 8 hours (at night); they were used
only at the deepest water site (site: Vermice19). The cast net
was a local fishermen’s costume-made cast net; it was used
by an experienced local fishermen for about one hour
(sites: Ura19, Rogove19). These supplementary tools and
methods provided increased effort which was commensurate
with the much deeper water and wider wetted-width river
conditions in the lower river sites.
2.3 Species identifications
Species nomenclature follows Kottelat and Freyhof (2007)
with particular additions promoted in recent publications
(Zupančičet al., 2010;Marková et al., 2010;Palandačićet al.,
2015,2017). To verify field identifications a subset of 107
selected specimens of 12 species were screened in the
laboratory through DNA barcoding analyses. After the
specimens were sacrificed using a high dose of clove-oil a
piece of fin tissue was extracted and stored in 96% ethanol for
subsequent molecular analyses (specimens are housed in the
HCMR Fish Museum and the Prague Museum). Mitochondrial
DNA markers were applied in species identification. The
DNA extraction, PCR reaction mix and PCR product
purification follow Šanda et al. (2008). For most species
cytochrome b was applied due to availability of the best
comparative data, and the above amplification protocol. For
the genus Gobio, cytochrome c oxidase subunit I (COI) was
more appropriate for comparison, and PCR protocol and
primers followed Geiger et al. (2014). In the case of the genus
Salmo a control region was used, following laboratory
procedure described in Duftner et al. (2003). Sequencing
was carried out by the Macrogen Service Centre Europe
(Amsterdam, Netherlands) using the amplification primers.
Sequences were aligned manually and revised in BioEdit
(v.7.0.9). Sequence comparison with published data was
Fig. 1. Free-flowing White Drin catchment in Kosovo and the 11 surveyed sites along its main stem. The name of the nearest village or main
place-name is provided (see Table 2 for equivalent sample names used in analyses).
Page 3 of 15
L. Grapci-Kotori et al.: Knowl. Manag. Aquat. Ecosyst. 2020, 421, 29
conducted by BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi).
Newly recorded haplotypes were deposited in GenBank (see
Supplementary Table 1).
2.4 Environmental data collection
As defined in the IMBRIW protocol (2013), environmental
and habitat parameters were recorded and calculated at
each study site. These include classic physicochemical
parameters, i.e. conductivity (mScm
1
, Cond), dissolved
oxygen (mg L
1
, DO), pH and water temperature (
C, T). In
addition, habitat parameters, i.e. visual on-site estimations
include:mean wetted width (m, WW), mean and maximum
depth (cm, D), stream velocity (categories of mean flow
speed), substrate coarseness, as well as relative in-stream
habitats, estimated in percent cover at the site (pools, glides,
runs, rifles, rapids) and vegetation cover (scaled cover of
helophytes and aquatic macrophytes). In the analyses some of
the data were combined to genaralize conditions i.e. substrate
types were defined as “course”(rock, boulders, cobbles) and
“fine”(pebble, gravel, sand, silt). Finally, spatial and
geographical parameters, i.e. distance from source (m, Dist)
and elevation (m, El) were calculated from recent satellite
images and GIS application.
2.5 Anthropogenic pressures data
Anthropogenic degradation of the sampled river sites was
assessed based on the identification of anthropogenic pressures
known to influence and impact fish (see Degerman et al., 2007;
Schinegger et al., 2012, for criteria and relevant references). In
order to provide a rapid assessment of the level of
anthropogenic impact (degradation) of each site we chose
selected pressures for which we could rapidly gather on-site
knowledge as has been done in other Balkan countries (Zogaris
et al., 2018). Twelve anthropogenic pressure categories were
assessed based on our on-site observations (recorded in the
sampling field protocol), published pressure assessments (i.e.
available recent chemical measurements) and remotely sensed
data (recent Google Earth images). The assessed parameters
were scored by the authors based on best available
information, established pressure-impact criteria and expert
judgement. The quality condition of each site based on the
severity of each pressure is given on a scale of 1 to 5 following
the EU WFD standard (i.e. 1 = high, 2 = good, 3 = moderate,
4 = poor, 5 = bad). Some pressures were assessed at a five-class
scale (i.e. 1 = least impacted to 5 = highly impacted) others in
three point classes (i.e. 1, 3, 5 or 1, 2, 5); assessment scoring
has lower degrees of certainty in some pressure types so the
class scale is reduced to three classes. The following twelve
pressure parameters were assessed as follows (increment
score measures applied given in parentheses): Channel
modification (1–5); Instream habitat modification (1, 3, 5);
Artificial embankment (1–5); Riparian vegetation modifica-
tion (1–5); Barrier upstream (1,2,3); Barrier downstream
(1,3,5); Barrier basin (1,3,5); Water abstraction (1,3,5);
Hydropeaking (1,2,5); Hydrological modification (1,3,5),
Impoundment (1–5); Pollution (1,2,5). Finally, a preliminary
degradation index was calculated for each site by simply
summing the scores and dividing by the number of pressures
assessed.
2.6 Data analysis
Abundance data during electrofishing runs (number of fish
per single run) were converted to area densities (i.e.
individuals*100 m
2
) to provide a proxy for catch-per-unit
effort (CPUE) where the unit of effort is the extent of area
surveyed. The surface area sampled at each site was estimated
from its geometrical characteristics on-site (careful visual
measurement and estimation of reach length and cross-
sectional width in the field; and through recent Google Earth
images). In the four sampling events where supplementary
gears were used we considered species CPUE data from all
gear types to be comparable in terms of potential sampling
bias.
Assessment of the importance of the different physico-
chemical, habitat and spatial variables was conducted by
applying multivariate statistics. In all analyses samples used
assessed fish density per site; log (xþ1) transformation was
used for the analyses in fish densities, environmental/habitat
and pressure variables. In order to detect differences between
sampling sites in terms of environmental/habitat and pressure
characteristics PCA analyses was applied for each set of
variables. Before PCA we tested possible correlation between
variables with Spearman’s rank correlation. To explore the
spatial pattern of fish distribution, to identify areas with similar
fish assemblages and to compare these assemblages among
areas, a non-parametric multidimensional scaling (MDS) was
performed using fish densities (individuals*100 m
2
). MDS
portray the compositional differences between sampled sites
in an ordination that provides a visual indication of how
similar sites are to one another. For all the above analyses
the Primer 6 statistical package was used (Clarke and
Gorley, 2006).
We also investigated possible gradation changes in fish
communities using bipartite networks. In such networks each
site is linked only with the species it contains, and each species
only with sites where they occurred. Through this kind of
classification grouping, species identities are not lost, as in a
resemblance matrix (Leroy et al., 2019), giving the opportunity
to detect modules, which represent aggregated sets of species
(Dormann and Strauss, 2014). The “Bipartite”package
(Dormann et al., 2008)inR(R Development Core Team,
2017) was employed in this analysis.
To further examine fish responses to environmental-
habitat and pressure variables the CANOCO procedure was
used. (CANOCO 4.5 for Windows; Ter Braak and Smilauer,
2002). By applying DCA, the length of gradient in the first axis
was calculated at 3.2, indicating that the Standard Deviation of
species turnover is not too high (i.e. less than 4) so we analyzed
the data by Redundancy Analysis (RDA). Prior to RDA
analysis, the Monte Carlo test was used, under 499
permutations, to specify the statistical significant habitat
environmental and pressure variables. To avoid variables
that are correlated and thus have no unique contribution to
the regression, variables only with inflation factor <20 were
used.
3 Results
As shown in Table 1,21fish taxa were recorded from a
total of 3301 specimens during the summer (2019) and 507
Page 4 of 15
L. Grapci-Kotori et al.: Knowl. Manag. Aquat. Ecosyst. 2020, 421, 29
specimens in the winter expedition (2017). The species
represent 21 genera and 10 families (in Cypriniform fish we
follow the families of Schönhuth et al., 2018). Of the 13 native
species, 10 are range-restricted almost exclusively within the
Southeast Adriatic Ecoregion. This represents a very high
endemicity, approximately 77% of native fish species being
unique to this ecoregion (ecoregion boundaries follow Abell
et al., 2008). Five taxa are considered endemic to the ODS or at
least the northern part of the Southeast Adriatic Ecoregion (i.e.
species of Phoxinus, Barbus, Barbatula, Alburnoides, Eudon-
tomyzon). Another five are restricted within the wider
Southeast Adriatic Ecoregion (i.e.: species of Cobitis,
Pachychilon, Alburnus, Chondrostoma and probably Gobio).
Eight species are non-native, this includes five species
which are “translocated”from nearby ecoregions. All but one
non-native species (Oncorhynchus mykiss) show signs of being
established with self-reproducing populations. Non-native
species still have a comparatively low effect on the fish
assemblage, comprising only 5.9% of the total catch; Rhodeus
amarus being the only non-native species exceeding 100
individuals within the total catch.
The most abundant species were Alburnoides ohridanus,
Phoxinus sp., Alburnus scoranza,Pachychilon pictum and
Squalius platyceps (in descending order of abundance);
accounting for 79.9% of all individuals collected. The most
widespread species (frequency of occurrence >80% samples)
were: Squalius platyceps, Alburnus scoranza, Pachychilon
pictum,Barbus sp. and Alburnoides ohridanus. The most
range-restricted species (occurrence <20% samples) were:
Sander lucioperca, Salaria fluviatilis, Oncorhynchus mykiss,
Eudontomyzon stankokaramani, Carassius gibelio, Cyprinus
carpio and Cobitis ohridana.Table 2 provides a summary of
basic environmental and catch data for each sample in
descending order (sampled sites ordered from an upstream to
downstream gradient as in the map in Fig. 1).
3.1 Fish taxonomy and fish assemblage
characterization
19 of the 21 taxa are identified to valid species, though in
some cases the identification is tentative; four species being of
uncertain taxonomic status (Tab. 1, see discussion for details).
DNA barcoding considerably helped in species identification.
The two species that remain unnamed belong to genera
Phoxinus and Barbus, though both are identified to known, but
yet undescribed evolutionary lineages.
MDS ordination shows a progression of grouping from
upstream to downstream, with distinctive cold water sites
located upstream. The three sites sampled in summer and
winter maintained similar assemblage structure (Fig. 2).
Table 1. List of all species (1); distinction of provenance and taxonomy (i.e. Native or non-native/ certainty of identification; with “þ”checked
using DNA molecular analyses) (2); Endemicity, showing region and non-native status: A: Alien, T: translocated non-native (3); Total number
collected (4), Frequency of occurrence at sites F.O. (5), length-class range collected in total (6); and, total percent deformations documented of
% collected (7).
1234567
Species
(Family)
Provenance/
Taxonomy
Endemicity Total
number
F.O. Length
Class
Range
Total DELTS
(% of total
caught)
Alburnoides ohridanus
(Leuciscidae)
Native/CertainþNorthern Southeast
Adriatic
985 11 <5, 11–15 0.9
Alburnus scoranza (Leuciscidae) Native/CertainþSoutheast Adriatic 589 12 <5, 16–20 0.2
Barbatula sturanyi (Nemacheilidae) Native/CertainþODS Basin 64 8 <5, 11–15 0
Barbus sp. (Cyprinidae) Native/CertainþODS Basin 204 11 <5, 26–30 3.4
Carassius gibelio (Cyprinidae) Non-native/Uncertain Non-Native A 4 2 6–10, 21–25 25
Chondrostoma ohridanus (Leuciscidae) Native/CertainþSoutheast Adriatic 47 6 6–10, 26–30 0
Cobitis ohridana (Cobitidae) Native/Uncertain Southeast Adriatic 1 1 6–10. 0
Cyprinus carpio (Cyprinidae) Non-native/Certain Non-Native T 1 1 21–25. 0
Eudontomyzon stankokaramani
(Petromyzontidae)
Native/Certain ODS Basin 11 2 11–15, 16–20 0
Gobio skadarensis /ohridanus (Gobionidae) Native/UncertainþSoutheast Adriatic 125 9 <5, 11–15 5.6
Oncorhynchus mykiss (Salmonidae) Non-native/Certain Non-Native A 3 2 21–25,26–30 0
Pachychilon pictum (Leuciscidae) Native/CertainþSoutheast Adriatic 557 11 <5, 16–20 2.3
Perca fluviatilis (Percidae) Non-native/Certain Non-Native T 18 3 <5, 11–15 0
Phoxinus sp. (Leuciscidae) Native/CertainþODS Basin 720 6 <5, 6–10 0
Pseudorasbora parva (Gobionidae) Non-native/Certain Non-Native A 37 6 <5, 6–10 0
Rhodeus amarus (Acheilognathidae) Non-native/CertainþNon-Native T 118 9 <5, 6–10 0
Sabanejewia balcanica (Cobitidae) Non-native/CertainþNon-Native T 28 7 <5, 11–15 0
Salaria fluviatilis (Blenniidae) Native /Certain Peri-Mediterranean 3 2 6–10,11–15 0
Salmo farioides (Salmonidae) Native/UncertainþWestern Balkans 92 8 6–10, 31–35 3.3
Sander lucioperca (Percidae) Non-native/Certain Non-Native T 13 2 6–10, 26–30 0
Squalius platyceps (Leuciscidae) Native/CertainþSoutheast Adriatic 205 12 <5, 51–55 2.9
Page 5 of 15
L. Grapci-Kotori et al.: Knowl. Manag. Aquat. Ecosyst. 2020, 421, 29
Table 2. List of all samples with important parameters: Site sample name and in parentheses the nearest toponym as in Map (Fig.1)
(1); geographic coordinates at centre of sampling site (2); Sampling method (1: electrofishing, 2:boat electrofishing, 3: cast-net, 4: gill-net)
(3); Distance from the source (spring of the White Drin) in meters (4); Elevation a.s.l. in meters (5); Degradation score: sum of scores divided by
12 (total number of anthropogenic pressures assessed) (6); Native species number (7); Non-native species number (8); Number of individuals
collected (9); Estimated fish density at site density (individuals*100 m
2
) (10); length-class ranges of all fish species collected (11); Number of
serious deformities, lesions, or tumors (DELTS) on the fishes (12).
123456789101112
Site name
(and nearest
toponym)
Geographic
Location
Sampling
Method
Distance
from
source
Elevation Degradation
index
Native Non-
native
Number of
individuals
Fish
density
Length-
class
range
DELTS
1.Valet19
(Valet)
42.736638
20.311722
1 618 531 2.91 1 1 34 7.55 6–10, 26–30 0
2.Dubove19
(Dubovë)
42.716944
20.364166
1 6881 469 2.41 3 1 383 212.77 <5, 31–35 0
3.Zllak19
(Zllakoqan)
42.662222
20.535752
1 25972 394 2.66 8 0 405 225.00 <5, 21–25 0
3.Zllak17
(Zllakoqan)
42.662222
20.535752
1 25972 394 2.66 8 0 267 70.26 <5, 11–15 2
4.Kline19
(Klinë)
42.609305
20.567000
1 34860 373 3.75 9 1 224 124.44 <5, 21–25 4
4.Kline17
(Klinë)
42.609305
20.567000
1 34860 373 3.75 8 2 100 76.92 <5, 26–30 2
5.Nora19
(Nora)
42.591552
20.572052
1 38384 369 3.16 9 1 131 43.67 <5, 21–25 4
5.Nora17
(Nora)
42.591552
20.572052
1 38384 369 3.16 8 1 139 75.14 <5, 11–15 4
6.Kramovik19
(Kramovik)
42.491055
20.513444
1 54722 347 3.91 7 3 746 165.78 <5, 21–25 3
7.Drinas19
(Drinas)
42.416222
20.523222
1 65267 330 3.25 8 4 304 86.86 <5, 26–30 4
8.Ura19
(Ura)
42.353555
20.539583
1,2,3 74855 334 2.41 9 2 350 175.00 <5, 21–25 2
9.Rogove19
(Rogovë)
42.318166
20.591527
1,3 82039 308 2.33 7 4 279 111.60 <5, 51–55 1
10.Kursha19
(Kurshë)
42.292583
20.639277
1 87453 301 2.50 7 3 218 72.67 <5, 16–20 1
11.Vermice19
(Vermicë)
42.256375
20.651088
1,2,4 94151 293 3.25 6 7 245 98.00 <5, 31–35 2
Fig. 2. MDS ordination for White Drin samples based on fish densities (individuals*100 m
2
). Sites to the right half of the ordination are in
coldwater conditions. Kline and Nora sites are in a cool-warm water transition that is also seasonally heavily polluted. The left hand grouping
includes warm water assemblages.
Page 6 of 15
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Bipartite network analyses suggests the existence of four
preliminary fish assemblage types (Fig. 3). The downstream
segments had the highest species richness and diversity per
site. Three cold-water species occurred exclusively in the
upstream cold water reaches, while several species, including
most non-natives were found exclusively in the most
downstream warm water sections respectively.
3.2 Fish responses to environmental, habitat and
pressure parameters
PCA for environmental and habitat variables identifies
potential parameters that characterize site conditions (Fig. 4).
Spearman’s correlation shows that distance from source was
highly correlated with altitude (−0.996) and fine substrate with
coarse substrate (−0.987). From the analyses distance from
source and fine substrate were excluded.
RDA analyses for environmental and habitat variables
(Fig. 5a) show that hydromorphological and habitat parameters
are important in influencing fish assemblages. In terms of
environmental and habitat variables fish species partition
primarily between cold-water and the large-river species
(Fig. 5a). Temperature, a key physico-chemical parameter,
may have an overriding importance, but other notable
parameters are shown to include the overall size and dominant
morphology of the river, indicated by wetted width and the
presence of slow-flowing habitats and fine sediment conditions
(i.e. areas where helophytes develop). Species–variables
relation was explained by 87.1% in the fourth axis although
only water temperature was statistical significant (p= 0.002)
according to Monte Carlo test; the model was not statistically
significant both in the 1st (F-ratio = 3.341; p-value = 0.2800)
and in all axes (F-ratio = 2.107; p-value = 0.0680).
In the ordination of anthropogenic pressures (Fig. 5b),
certain pressures are identified as noteworthy and may play a
role in fish community dynamics, prominent ones including
barriers (especially downstream barriers), hydrograph modi-
fication (through water diversions) and pollution. Anthropo-
genic hydromorphological modifications are probably
important (channelization, downstream barriers, impounding
Fig. 3. Assemblage level modules of White Drin River fishes in bipartite network analyses. Darker shades in each square indicate higher
population density values.
Page 7 of 15
L. Grapci-Kotori et al.: Knowl. Manag. Aquat. Ecosyst. 2020, 421, 29
of waters due to barriers and hydrological modification)
however it is not possible to interpret the influence of some
pressure types without monitoring data (i.e. the effects of
pollution or local habitat degradation from river quarrying,
for example). Species–variables relation was explained by
93.3% in fourth axis and it was statistically significant both
in 1st (F-ratio = 4.5; p-value = 0.02) and in all other axes
(F-ratio = 2,228; p-value = 0.02). According to Monte Carlo test
statistically significant variables are river channelization
(p= 0.042) and barriers in the basin (downstream) (p= 0.002).
Fig. 4. PCA graph for environmental and habitat variables. Only variables with scores >0.2 in at least one of the two axes are presented in the
ordination. PCA values presented in table.
Fig. 5. RDA ̶analyses for a) environmental and habitat variables, and b) anthropogenic pressures. Abbreviated names refer to the following
variables: cond: conductivity (mS/cm), dmean: mean depth (m), dmax: maximum depth (m), temp: water temperature (
°
C), wwidth: wetted
width (m), helophytes: % cover of helophytes, slope: Slope (‰), velocity: average river velocity (average m/sec classes), D.O.: Dissolved
oxygen (mg/l). hydropeak: Water level hydropeaking (below hydroelectric power plants), barr ds: Artificial barriers Upstream, barr ds:
Artificial barriers downstream, chann: River channelization, imp: Impoundment due to barriers and dams, hydro mod: Hydrograph
modification, wat abstr: Water abstraction, poll obs: Pollution observed visually on-site.
Page 8 of 15
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In terms of assessed pressures at the site-scale (Fig. 6),
most river reaches that were inspected show a low or moderate
degree of influence from selected pressures known to influence
fish communities. The most widespread and severe recorded
pressures were: basin-scale barriers to fish movement (major
dams in the basin), seasonal hydrological modification due to
river diversions (thus affecting the river’s natural hydrograph)
and pollution. Other pressure types show low or slight
modification scores at most sites.
4 Discussion
4.1 Taxonomic implications
The western Balkans still have serious gaps and instability
in freshwater fish taxonomy (Bogutskaya and Ahnelt, 2019;
Vavalidis et al., 2019). Several fish genera in the ODS are
represented by two species and exact distribution patterns in
the basin are poorly documented (Simonović, 2001; Grapci-
Kotori, 2010; Wenke, 2017). Furthermore, the potential for
misidentifications due to human-mediated translocations is a
serious problem in the region (Koutsikos et al. 2012,Piria
et al., 2018,Koutsikos et al., 2019a;Vukićet al., 2019).
Considering these facts, species identification, the most
important starting point for any conservation-relevant analysis,
is in many taxa difficult. In such cases, DNA barcoding is a
useful tool. We interpret our most important findings here.
In this study we retain two of our identifications to genus
level (Phoxinus and Barbus). The genus Phoxinus recently
underwent enormous taxonomic changes (Palandačićet al.,
2017;Vucićet al., 2018;Corral-Lou et al., 2019). Eight
different evolutionary lineages were identified by Palandačić
et al. (2015), two of which occur in the ODS. Phoxinus
karsticus inhabits the Lake Skadar catchment (and part of the
Neretva drainage), whereas a yet unnamed Phoxinus species
was reported from Lake Ohrid and its vicinity (Palandačić
et al., 2015,2017). All 15 genetically analysed specimens from
the White Drin belong to the native “Phoxinus sp. 5”of
Palandačićet al. (2017). Moreover, two species of Barbus
were also reported from the ODS by Marková et al. (2010):
presumably the introduced Barbus balcanicus from a small
river near the confluence of White and Black Drin (in Albania),
and a yet undescribed species from several localities in the
ODS, though none of them from the White Drin. All six
genetically analysed specimens from White Drin belong to the
native undescribed Barbus of Marková et al. (2010), obviously
widespread throughout the ODS.
Two species of the genus Gobio are also reported from the
ODS: G.ohridanus and G.skadarensis, formerly presumed
endemic to Lake Ohrid and the Lake Skadar area, respectively
(Kottelat and Freyhof, 2007). However, the taxonomy of this
genus in this area remains unresolved. The published data, all
molecular (Šanda et al., 2005; Mendel et al., 2008;Geiger
et al., 2014) are not fully congruent, since other populations
from the Southeast Adriatic Ecoregion are genetically very
closely related. Gobio species are also frequently translocated
by humans (Aparicio et al., 2013;Bianco, 2014;Jelićet al.,
2016) and other Gobio species are present in the neighbouring
ecoregions (Geiger et al., 2014). Our sequences of all twelve
specimens analysed genetically from the White Drin are most
similar to G. ohridanus sequences from Lake Ohrid (Geiger
et al., 2014). The majority of the specimens bear identical
haplotypes as those in the above mentioned publication, and in
case of yet not reported haplotypes the maximum difference is
0.15% (see Suppl. 1), so we may tentatively consider the White
Drin population as being closest to G. ohridanus. On the other
hand, the next genetically most similar species, G.skadarensis,
differs only 0.61–0.77%. The observed values of genetic
differentiation are very small and further research is needed to
solve this issue; therefore we refer to our Gobio specimens as
Fig. 6. Prevalence of the degree of degradation caused by anthropogenic pressures for fish at the 11 surveyed sites (assessed on-site and through
available recent measurements and remote sensing). The degree of degradation is given by a five-point scale (from least impacted to severely
degraded condition; i.e. 1 = high, 2 = good, 3 = moderate, 4 = poor, 5 = bad).
Page 9 of 15
L. Grapci-Kotori et al.: Knowl. Manag. Aquat. Ecosyst. 2020, 421, 29
G.ohridanus/skadarensis. This provisional nomenclature is
used in an attempt to provide an unbiased operational name
solely for this publication.
An unexpected situation was detected in the genus
Squalius; the ODS is assumed to host S. platyceps (Zupančič
et al., 2010). Of the nine specimens analysed in our study,
seven were identified as S. platyceps. However, one specimen
bears mtDNA of S. prespensis and one of S. cephalus. It is not
clear, if these species are present in the White Drin
(respectively in the ODS), and what is their status. In many
Squalius populations ancient genetic introgression was
detected, so the mtDNA could be misleading in species
identification (Perea et al., 2016;Sousa-Santos et al., 2019;
Buj et al., 2020). Furthermore, introductions of Squalius were
also reported from the western Balkans (Jelićet al., 2016).
Without further detailed study, it is not possible to decide if
more species occur sympatrically in the White Drin or if the
observed pattern only reflects introgressive hybridisation, either
ancient, or recent,resulting from human-mediated introduction.
A taxononomically difficult group in the area are the trout
(Salmo), where several species are reported from the ODS
(Kottelat and Freyhof, 2007). The most widespread species is
expected to be S.farioides, but other species are present in the
neighbouring drainages and the introductions of non-native
Salmo species are well documented in the Balkans (Piria et al.,
2018,Koutsikos et al., 2019b). The mitochondrial data can
provide only limited information since the supposed species-
level taxa bear similar or even identical haplotypes (Geiger
et al., 2014). All ten analysed Salmo specimens in our study
belong clearly to the Adriatic evolutionary lineages and we
tentatively identify them as native S.farioides.
Even presumably widespread and common species pose
risks of identification errors in this region. The taxonomy of
Chondrostoma in the ODS has been unclear for a long time
since two species were reported from the drainage; C.scoranza
considered endemic to Lake Skadar and presumed extinct
(Kottelat and Freyhof, 2007) and C.nasus (Elvira, 1987).
Geiger et al., (2014) demonstrate that C.ohridanus inhabits the
entire ODS. All six genetically investigated specimens from
the White Drin are native C.ohridanus. Moreover, a single
species of Alburnus (A.scoranza) was reported from the ODS
(Kottelat and Freyhof, 2007) while several morphologically
similar species occur in the surrounding basins (Buj et al.,
2010) with reports of translocations throughout the Mediter-
ranean catchments (e.g. Bianco, 2014;Jelićet al., 2016;Sousa-
Santos et al., 2018). In our case all 20 genetically investigated
specimens from the White Drin are native A.scoranza.
Similarly, a single species of Alburnoides (A.ohridanus)is
reported from the ODS, formerly presumed to be endemic to
Lake Ohrid (Kottelat and Freyhof, 2007). However, Stier-
andová et al. (2016) demonstrate this species is more
widespread in the ODS. Several morphologically similar
species occur in the surrounding basins, some not yet described
(Stierandová et al., 2016;Barbieri et al., 2017) and a recent
translocation was reported from the western Balkans (Vukić
et al., 2019). All 15 genetically investigated specimens
inspected from White Drin are native A.ohridanus. Finally,
two Barbatula species were reported from the ODS,
B. sturanyi from Lake Ohrid and the Black Drin, and B.
zetensis from the Lake Skadar basin (Kottelat and Freyhof,
2007). Another species, B. barbatula, occurs in the Danube
and Vardar basins (Šedivá et al., 2008) and anthropogenic
translocations have been documented (Tutman et al., 2017). A
single specimen analysed genetically from the White Drin in
this study is confirmed as native B. sturanyi. Also, Cobitis,a
rare loach in the system, was morphologically identified as
Cobitis ohridana, a widespread species in the Southeast
Adriatic ecoregion (Šanda et al., 2008) but DNA was not
screened in the few specimens caught. It is known that another
Cobitis species of unclear origin (possibly hybridogenetic)
occurs in the ODS (Perdices et al., 2008,Šanda et al., 2008)
so care is needed in confirming this species’distribution (Buj
et al., 2015).
The identity of some of the introduced species is
sometimes not easy to determine. For example, two species
of Rhodeus, both morphologically highly similar (Kottelat and
Freyhof, 2007), occur in the neighboring drainages. One of
them, R.amarus was identified and classified as introduced in
ODS (Bartáková et al., 2019). All ten genetically analyzed
specimens from the White Drin are also R.amarus, suggesting
this introduced species is widespread in the ODS. A single
specimen of Sabanejewia balcanica, a widespread species in
the Danube and some north Aegean rivers, showing
considerable intraspecific genetic diversity (Mare
sová et al.,
2011) was also DNA barcoded, and confirms the morphologi-
cal identification. Because this species was never documented
from the ODS in the past (Šorić, 1990,1992;Rakaj et al., 1995;
Bohlen et al., 2003;Šanda et al., 2008), we consider it recently
introduced by humans. Finally, the identification of some
species remains tentative since DNA analysis was not
completed. The field identification of Carassius gibelio is
provisional since the morphologically highly similar species
C. auratus (feral form) has been detected genetically in Lakes
Ohrid and Skadar and C.lansdorfiiin several nearby drainages
(Kalous et al., 2013). Carassius gibelio is tentatively identified
here based on morphological characters since genetic analyses
was not conducted.
The results show clearly, that the White Drin basin is more
similar to Lake Ohrid and the Black Drin rather than to the
Lake Skadar sub-drainage. In all cases, where we were able to
genetically compare the species pairs reported from the ODS,
the White Drin populations were identified as the species
previously reported only from Lake Ohrid and the Black Drin.
4.2 Preliminary fish assemblage patterns and
limitations of the study
This study provides the first attempt to implement a
standarized fish assemblage sampling method along the entire
main-stem of the White Drin upstream of the Albanian dam
impounded area. The initiative was effective in sampling
nearly all known fish taxa in the river (Simonovic, 2001;
Grapci-Kotori et al., 2010) and providing relative abundance
data along with site accounts of environmental parameters and
selected anthropogenic pressures. Our quantitative bipartite
network analysis identified four modules that may reflect an
equal number of geographically discrete fish assemblage types
in the river’s main stem; this was broadly corroborated by the
MDS ordination analysis. The distributional pattern resembles
the classic fish zonation (Huet, 1959) in the upper part of the
river but the assemblages are dominated by regional endemics
not found in central European rivers. As expected, fish species
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L. Grapci-Kotori et al.: Knowl. Manag. Aquat. Ecosyst. 2020, 421, 29
richness in the White Drin exhibited a gradual downstream
increase; a discrete cold-water assemblage is prevalent in the
upstream cold water sections. Further research into a fish-
based typology of the White Drin is required in order to
confirm and map the assemblage pattern (Vila-Gispert et al.,
2002), to consider the effects of the tributary network (Hitt and
Angermeier 2011) and to build a biotic typology for fish-based
bioassessment (Aarts and Nienhuis, 2003) in this part of the
ODS.
We acknowledge some limitations in our study with
regards to the precision of the fish abundance data, assessed
environmental parameters and anthropogenic pressure varia-
bles. To define and validate fish community assemblage types,
we should take care when utilizing quantitative fine-scale data
since relative abundance parameters in the samples may be
influenced by several factors, such as seasonal changes and
sampling bias. Fish sampling is not easily kept consistent in
such varied main-stem river conditions. Locally supplement-
ing back-pack electrofishing with gill-net, boat-based electro-
fishing and cast net data was deemed essential in areas such as
the three non-wadable sites in the lower part of the river.
Applying additional sampling gears may perform better than
electrofishing in assessing both river health and biodiversity in
medium and large-river conditions (Zajicek and Wolter, 2018;
Zajicek et al., 2018). Finally, a potential confounding factor
that is hard to interpret may also be overfishing pressure by
amateur fishers. Our work therefore represents an exploratory
snap-shot towards fish assemblage classification; more surveys
and monitoring are required to confirm and further interpret
these results.
In terms of assessing anthropogenic pressures, our survey
follows a rapid assessment procedure that provides a standard
framework that is widely used (Schineggar et al., 2012);
however it is not a holistic diagnosis and cannot cover all forms
of disturbance that may influence fish assemblages. Some
aspects, such as pollution, are poorly registered in this study
since the issue of pollution is poorly monitored in Kosovo’s
rivers (Waschak, 2012); and this should be ameliorated in
future pressure-impact analyses.
Through our attempts at identifying important anthropo-
genic pressures, we show that the majority of the investigated
sites were not severely influenced by anthropogenic structural
changes to major habitats (i.e. instream habitat degradation,
channelization, upstream barriers, embankments and riparian
vegetation degradation gave good assessment scores at most
sites). In fact, the in-stream and riparian habitat conditions in
most sites had a wide and wooded riparian zone and were in
rather good condition of ecosystem integrity. In future studies,
in order to explore ecological quality in a holistic sense, we
highly recommend the use of riparian and landscape scale
assessment applications (Wiens, 2002;Fausch et al., 2002;
Townsend et al., 2003) and propose that supplementary
methods to assess pressures at the riparian and landscape scale
should be incorporated in the analyses, to complement on-site
field-based assessments (e.g. Chatzinikolaou et al., 2011;
Dimitriou et al., 2012;Vlami et al., 2019).
The fish communities of the White Drin seem to retain a
semi-natural pattern (i.e. low alien species abundance)
primarily influenced by natural longitudinal gradient river
changes. However, the creation of longitudinal barriers (high
dams) at the wider river basin scale has had serious baseline
affects. Some fish populations have been extirpated; these
include natural eel (Anguilla anguilla) populations and other
migratory fishes, perhaps also including Alosa fallax
(Spirkovski et al., 2017). Other fishes have also vanished
due to the dams in the main Drin river downstream of the
Kosovo Border (e.g. Acipenser naccarii, Acipenser sturio,
Petromyzon marinus)(Knezevic, 1981;Rakaj, 1995;Simo-
novic 2001). Historical research would help to explore if these
or other large-river migratory fishes once reached the White
Drin catchment.
4.3 Conservation implications
Fish assemblage research helps to identify unmet
conservation needs. Fish are sensitive to interruptions in the
river longitudinal continuum (such as dams); and, as long-lived
species, they indicate degradation that may have taken place in
the past (e.g. through assessments with respect to size, age,
reproduction success and fish health condition) (Schmutz
et al., 2000;Sutela et al., 2010;Benejam et al., 2010). The
White Drin faces pressures and threats that reflect on its fish
assemblages; however, since historic fish assemblage data are
unavailable, we are faced with the difficultly of interpreting
conditions that are influenced both by natural and anthropo-
genic changes at multiple scales (Schmutz et al., 2000). We
tentatively point to certain insights of conservation and
research interest from our study so far:
–Non-native fish translocation is a very serious biodiver-
sity threat, especially when it originates from neighbour-
ing river basins. Three neighbouring freshwater
ecoregions with very different ichthyofaunas exist
within Kosovo’s territory (Abell et al., 2008); this poses
very serious risks for human-mediated river basin non-
native fish contamination. In bordering ecoregions we
must be especially aware of same-genera “sister species”
introduction; their establishment and hybridization with
native species may represent an irreversible anthropo-
genic impact to biodiversity. The spread of many alien
and translocated fishes in the Balkans is usually
associated with fishery practices (stocking), poorly-
controlled fishing practices (bait-fish translocations) and
by dam creation (Shumka et al.,2008;Gashi et al., 2016;
Piria et al., 2018;Koutsikos et al., 2019a). Prevention of
un-regulated fish transport, strict fisheries enforcement
and genetic monitoring (Leese et al., 2018)isan
imperative for conservation.
–Pollution is potentially a serious problem for fishes of the
White Drin; but there is little chemical monitoring data
available to effectively interpret how it affects fishes.
Urban sewage waters are commonly discharged un-treated
into the rivers, since few sewage treatment plants are in
operation (Wenke, 2017). Locally, pollution may have an
overriding affect on the fish community and this was
presumed to be the situation in the river’s mid-section; at
the two peri-urban sites near Kline. At these locations, the
observed heavy benthic siltation was also probably
anthropogenic and may also negatively influence fish
(Wood and Armitage, 1997;Sutela et al., 2010). At these
and other sites, we also documented fish-health problems
by inspection of “DELT”anomalies; these are known to
often be associated with severely polluted conditions
Page 11 of 15
L. Grapci-Kotori et al.: Knowl. Manag. Aquat. Ecosyst. 2020, 421, 29
(Sanders et al., 1999). Since river-caught fish are widely
consumed by local populations we must stress that
this problem also represents a potential human health risk.
–Although hydromorphological conditions are in fairly
good status in many parts of the White Drin, water
abstraction structures and the influence of dams is a
widespread pressure and growing threat. Since many of the
Drin’sfishes are migratory or undergo seasonal movements
(Simonovic, 2001), barriers to movement are a severe
problem even if these are located far from the main-stem, in
the river’s tributaries. It is well documented that a large
number of small hydroelectric plants are currently being
planned and being built in the White Drin’s tributaries
(Bajçinovci et al., 2019). The main stem of the river and
important reaches in its tributaries should be protected
from future proposed dams or barriers. The problem of
barriers to fish movement may be more severe than
pollution for fishes; however, this issue is poorly studied in
Kosovo.
–Over-fishing and illegal fishing are evident in Kosovo and
are widespread in the Western Balkans (e.g. Milo
sevićand
Talevski, 2015). In our survey, we found that fish were
generally small-sized (indicating a scarcity of larger
longer-lived specimens) and illegal gill-netting and cast-
net fishing was widely observed. Standardized quantitative
fish monitoring is required to better interpret the effects of
this pressure.
Finally some of the sites in both the upper part of the main-
stem (i.e. cold-water sites with the endemic Phoxinus minnow
assemblages) and the lower reaches that are not yet influenced
by impoundments (e.g. Ura, Rogovȅ, and Kurshȅsites)
represent outstanding examples of natural and semi-natural
river corridor habitats in this river and they should be further
studied and considered for conservation within new protected
areas. For a complete conservation plan, including an
assessment of possible climate change effects on the biota
(Reid et al., 2019), fish surveys and monitoring using a
standardized methodology should be established on the White
Drin and all its tributaries.
Supplementary Material
Supplementary Table 1.
The Supplementary Material is available at https://www.kmae-
journal.org/10.1051/kmae/2020020/olm.
Acknowledgements. Funding for this study was provided by
the Ministry of Education Sciences and Technology of
Kosovo., ref. nr. 5210, 17/12/2018. The field work-electro-
fishing was carried out with permit of the Ministry of
Agriculture nr. 2689/3. JV was supported by the institutional
resources of the Ministry of Education, Youth, and Sports of
the Czech Republic. RS by the Ministry of Culture of the
Czech Republic (DKRVO 2019-2023/6.V.b National Museum,
00023272). The authors are grateful for editorial assistance by
Elena Oikonomou and Vassiliki Vlami and the field assistance
provided by Rinor Berisha, Lis Kotori, Egzona Pepaj and
Erlinda Sallauka.
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Cite this article as: Grapci-Kotori L, Vavalidis T, Zogaris D, Šanda R, VukićJ, Geci D, Ibrahimi H, Bilalli A, Zogaris S. 2020. Fish
distribution patterns in the White Drin (Drini i Bardhë) river, Kosovo. Knowl. Manag. Aquat. Ecosyst., 421, 29.
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