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Vol. 19, 3/2011 MORAVIAN GEOGRAPHICAL REPORTS
35
ANGLERS’ CHOICE OF FISHERIES
IN THE CZECH REPUBLIC
Josef NAVRÁTIL, Stanislav MARTINÁT, Kamil PÍCHA , Jana NAVRÁTILOVÁ
Abstract
The spatial pattern of anglers’ movements among fisheries was analyzed using detrended correspondence
analysis (DCA), canonical correspondence analysis (CCA) and gravity modelling. Anglers choose, on the
national level, a destination fishery mainly according to its spatial position, as longitude and latitude
are the primary significant factors revealed by the forward selection procedure of CCA (the first two DCA
axes explain 5.9% and the first two CCA axes 5.3% of variability). Distance as a spatial attribute is not
only the main factor determining travel to all of Czech fisheries but also travel to specific tourist fisheries.
Distance travelled is also influenced by the type of fishery – trout fisheries (Beta coefficient = 1.725)
and fisheries on reservoirs larger than 80 ha (Beta coefficient = 1.760) are attended by anglers from the
more distant local organizations. The mobility of anglers also varies with the number of inhabitants of
their domicile – the impact of distance between the local organization and fishery is strongest for the
smallest towns (up to 500 inhabitants, Beta coefficient = 2.456) and weakest for large cities (with more
than 50 thousand inhabitants, Beta coefficient = 1.923).
Shrnutí
Výběr rybářských revírů sportovními rybáři v České republice
Prostorová struktura pohybů rybářů po revírech byla analyzována detrendovanou korespondenční analýzou
(DCA), kanonickou korespondenční analýzou (CCA) a gravitačním modelem. Na národní úrovni rybáři
volí revír především na základě jeho polohy, protože hlavními signifikantními vysvětlujícími proměnnými
vybranými metodou dopředného výběru CCA byly zeměpisná šířka a zeměpisná délka polohy revíru (první
dvě osy DCA vysvětlují 5,9 % a první dvě osy CCA 5,3 % vysvětlitelné variability souboru). Vzdálenost však
není jen hlavním faktorem návštěvy revírů všeobecně, ale taktéž hlavním faktorem návštěvnosti specifických
turistických revírů. Vliv vzdálenosti na výběr revíru je však taktéž závislý na typu revíru – z větších
vzdáleností jsou navštěvovány revíry pstruhové (beta koeficient = 1,725) a revíry na velkých nádržích (beta
koeficient = 1,760). Mobilita rybářů je závislá na počtu obyvatel místa jejich obvyklého pobytu. Vliv vzdálenosti
mezi revírem a sídlem místní organizace odkud rybář pochází je největší pro malá sídla (do 500 obyvatel,
beta koeficient = 2,456) a nejmenší pro velká města (nad 50 000 obyvatel, beta koeficient = 1,923).
Keywords: recreational fisheries, angling, tourism, gravity models, DCA, CCA, Czech Republic
1. Introduction
Recreational fishing is one of the most significant water-
based recreational activities in the Czech Republic
(Navrátil, Švec, 2008) as well as in other countries
(e.g. Upneja et al., 2001; Arlinghaus et al., 2002). It has
been linked to a wide range of environmental issues
(Arlinghaus, 2006a) as well as recreational issues
(Navrátil et al., 2009). There are numerous social benefits
that result from the recreational fishing (Floyd et al.,
2006) as well as economic benefits (Oh et al., 2005a).
Human dimensions of recreational shing
Research into the human dimensions of recreational
fishing has focused on many fields, among them,
in particular, since the first half of the 1970’s (as
mentioned e.g. by Morgan, 2006) different approaches
to the characterisation of recreational anglers in terms
of: the numbers of fish caught, numbers of fish kept or
the art of angling (e.g. Lockwood et al., 2001; Marta
et al., 2001; Vigliano et al., 2000), socio-psychological
characteristics of recreational anglers (Mangun,
O'Leary, 2001; Wilde, Pope, 2004), economic aspects
of recreational fishing looking at the fisherman’s
expenditures, or the revenue gained by establishments
offering recreational fishing (e.g. León et al., 2003;
Oh et al., 2005a; Toivonen et al., 2004). There are
several typologies of anglers elaborated e.g. according
to their motivation and satisfaction with angling
MORAVIAN GEOGRAPHICAL REPORTS 3/2011, Vol. 19
36
(Holland, Ditton, 1992), the specialization of angler
(Oh, Ditton, 2006), the link with a favourite place of
angling (Hammitt et al., 2004) or angler’s consumptive
orientation (e.g. Kyle et al., 2007). Because the
recreational fishing is considered foremost as a male
recreational activity, gender issues are also of interest
(e.g. Toth, Brown, 1997; Schroeder et al., 2006).
Special attention is paid to angler preferences in order
to inform management options (reviewed e.g. by Oh et
al., 2005b) especially with respect to the environment
and natural resources protection (summarized e.g. by
Arlinghaus, 2006a).
Recreational fishing is considered to be not only
recreational, but also popular tourist activity (Wilson
et al., 2001; Ditton et al., 2002). It has been found
that in some cases non-resident anglers represent
an important part of the angling community, not
only in marine areas (León et al., 2003), but also on
inland fisheries (Butler et al., 2009). It could play an
important role in specific inland tourist destinations,
seeing that angling related activities are one of those
criteria used by destination managers to
diversify tourist opportunities and services of their 1.
region by making packages of individual tourist
attractions and
tie local communities with visitors by supporting 2.
special fishing activities (Wilson et al., 2001).
Recreational fishing related information is also utilized to
promote a region by respective destination management
(Cawley et al., 2002). Ditton et al. (2002) summarizes
the known differences between local and non-resident
anglers, which are similar to those reported also from
Canada (Fisheries and Oceans Canada, 2007).
Anglers’ destinations
As recreational fishing is closely bound to tourism, the
fishing site choice is one of the most important topics
for managers (Hunt, 2005). The fishing site choice is
studied using two main approaches. (literature review
on site choice see Song, Li, 2008; Nicolau, Más, 2008).
The main aim of researchers is to identify factors
affecting decisions to travel when analyzing large
databases of statistical data using, especially, ordinary
least squares estimations or multinomial logit models
(Lyons et al., 2009) or analyzing data gathered by
specialized questionnaire surveys based, above all, on
different discrete choice models (last summarized by
Albaladejo-Pina and Díaz-Delfa, 2009).
Different types of choice modelling are popular also
in recreational fishing site choice, which encompasses
most of all the travel cost method (Hunt, 2005). Thus,
the recreational fishing has a spatial dimension. The
other modelling variables are fishing quality, water
area, water quality, aesthetics and presence of a boat
ramp (Hunt, 2005). These analyses (as many others)
are entirely based on surveys of anglers, where
preferences of each randomly sampled angler are
crucial for these models (Arlinghaus, 2006a). However,
large-scale data dealing with anglers’ communities
rather than with anglers as individuals (small scale),
gathered from different types of national household
surveys are also interesting for the management of
recreation fisheries (Aas, 1996) and are often used
by researchers to address the issue of predicting
future angling participation – literature review on
this topic is provided by Walsh et al. (1989) for the
older publications and by Arlinghaus (2006b) for the
latest ones. Thus, the site choice is possible to study
on a large scale. Information retrieved from anglers’
national surveys were formerly studied, especially the
specific geographical dimension e.g. by Aas (1996) or
Ditton et al. (2002). However, there are only two such
anglers’ national surveys in the Czech Republic for
years 2003 (Spurný et al., 2003) and 2009 (Spurný et
al., 2009) and both did not study the destinations of
anglers as tourists. The data on recreational fishing
and spatial consequences of angling can be obtained
from the summaries of fish kept on fisheries (Pivnička,
Rybář, 2001; Smutný, Pivnička, 2001; Humpl et
al., 2009; Jankovský et al., 2011), in particular, the data
concerning the spatial pattern of anglers’ movements,
distance travelled and differences among the types of
fisheries and differences among the types of anglers’
residence. The advantage of the database is its
completeness, so the parent population is available.
As mentioned recently, there is still a lack of studies
focused on fishing patterns in the inland recreational
fisheries (Pereira et al., 2008). Spatial consequences of
recreational fishing have not been studied in Europe
since the work of Aas (1996), with the exception of
urban-rural consequences (Arlinghaus, Mehner, 2004;
Arlinghaus et al., 2008; Arlinghaus, Mehner, 2003).
That is why we set up the following two objectives for
this paper:
to analyze the spatial pattern of anglers’ movements 1.
to the fisheries, and
to test determinants of spatial fishery choice on 2.
a large scale based on fish kept summaries.
Our hypotheses are:
Hypothesis 1 (H1): travel of anglers to fisheries is •
not independent of space but continuously changes
with its gradients.
Hypothesis 2 (H2): fishery choice is determined by •
the character of fishery.
Hypothesis 3 (H3): fishery choice is determined by •
the urban-rural character of anglers’ residence.
Vol. 19, 3/2011 MORAVIAN GEOGRAPHICAL REPORTS
37
2. Methods
Study area – recreational shing in the Czech Republic
The execution of fishing rights in the Czech Republic
is implemented by the fisheries. Fishing rights in the
fisheries are executed by the fishery users or owners,
especially by organizational units of fishing unions.
There are two main fishing unions in the Czech
Republic and a small number of other ones, which are
incomparably smaller.
The biggest fishing union in the Czech Republic is
the Czech Anglers Union with about 220,000 adult
and 50,000 youth members registered as at the
end of 2002, which was more than 2.2% of the
total population of the Czech Republic (Czech
Anglers Union, 2009). The Czech Anglers Union
operates 35,200 hectares of fisheries, where the Union
members crop approximately 3,200 tons of different
fish species each year. The second biggest union is the
Moravian Anglers Union (for spatial distribution of
both unions see Fig. 1).
To be allowed to angle in the fisheries operated by the
Union, a fisherman has to hold a fishing license and to
buy a permit to fish.
The members are obliged by the Fishing rules to file all
fish kept in a prescribed way. Particular fisheries are
operated by basic organization units, which are local
organizations of the Union, created on a territorial
basis. A member of the Union is a member of a local
organization, usually at the town of or in proximity to
his permanent address.
Data set
This paper is based upon data from the Czech
Anglers Union that supplied information from the
year 2002 (Czech Anglers Union, 2003). The database
contains for each fishery (n = 1,103) the numbers
of fish kept by members of each local organization
(n = 371) separately. This information is an appropriate
substitution for attendance of anglers to the fishery
since the number of attendances was well correlated
(R = 0.92; p < 0.001) with the numbers of fish kept for
the same period for fisheries and local organizations
of the Moravian Anglers Union (2003). Memberships
in local organizations were considered as the anglers’
origin point in the sense of permanent address. This
database was complete with available data on fisheries
and local organizations characteristics.
Three typologies of fisheries were adopted. First,
the fisheries were classified into types based on
information cited in the list of fisheries. Water
reservoirs were divided into two categories according
to the area size of fishery – the area of 80 hectares was
taken as a boundary. The category of reservoirs up
to 80 hectares includes a majority of ponds, technical
reservoirs, pools, river branches and flooded mines.
Fig. 1: General map of the Czech Republic with local organizations of the Czech Anglers Union according to their
location within NUTS 3 regions of the Czech Republic
MORAVIAN GEOGRAPHICAL REPORTS 3/2011, Vol. 19
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The category of reservoirs over 80 hectares includes
dam reservoirs, flooded gravel-pits and sand-pits.
Watercourses were also divided into two categories.
A watercourse body having an area in hectares of
at least 1.5-multiples of its length in kilometres was
labelled as a river; other watercourses were classified
as brooks. Second, the fisheries were divided according
to the list of fisheries into trout waters and non-
trout waters. Third, the fisheries with the highest
(> 300 pieces) and lowest number of fish (< 40%) kept
by members of local organizations located in the same
district (NUTS 4 region as the main spatial pattern
of geographical organization of the Czech Republic)
were picked out from the whole dataset and labelled as
a tourist fishery. The numbers of inhabitants of local
towns were added to local organizations.
The locations of local organizations and fisheries
were digitalized to point layers in the geographical
information system (GIS) JANITOR J/2 (Pala, 2008).
All the above mentioned data were interconnected
spatially in GIS ArcView 3.2 (ESRI, 1999). The main
reason to do this was to find for each fishery local
organizations that are ‘close’ to each fishery. The
closeness was considered on three geographic levels –
for each fishery were found:
local organization operating the fishery; 1.
local organizations in the same district (NUTS 4) 2.
as the fishery;
local organizations in the same region (NUTS 3) as 3.
the fishery.
Data analysis
The dataset forms a seemingly incomprehensible
and impenetrable mass of information in which we
wanted to uncover the relationships (if there were
any) among anglers and destinations. Multivariate
data analyses techniques are considered to evaluate
this state (Podani, 2000).
Our objective is to assess relations between the
angler’s origin and the fishery where he angles. It
applies, that
there are anglers from different local organizations 1.
fishing in each fishery and
the anglers from one local organization angle in 2.
different fisheries.
The structure of anglers in particular fisheries could be
then considered as an analogy to the structure of plant
and/or animal species in different types of habitats.
The structure of anglers in a fishery corresponds to
the character of the site. Changes in the composition
of a community in different sites have a character of
gradients. Our goal is to identify those gradients (if
they ever exist).
Thus, the overall variations in anglers’ origins among
all fisheries of the Czech Anglers Union was examined
by gradient analysis. We are looking for the greatest
variability that could be visualized using the ordination
diagrams for the fisheries (destinations) and local
organizations (origins) (ter Braak, Šmilauer, 2002).
Unconstrained ordination based on the unimodal
response model with detrending second and higher
axes by segments (Hill, Gauch, 1980) – Detrended
Correspondence Analysis (DCA) was performed by
CANOCO 4.5 package (ter Braak, Šmilauer, 2002). The
numbers of fish kept were log-transformed and some
local organizations were down-weighted (those local
organizations, whose members kept small numbers
of fish). The data were analysed analogically as the
communities of organisms in ecology (the object of the
analysis is the anglers’ structure according to their
origin in particular fisheries, which is quantified by
the number of fish kept).
We used the canonical correspondence analysis (CCA) to
test the ability of independent factors (latitude of fishery,
longitude of fishery, type of fishery, urban/rural type of
respective local organization) to explain variation in
fish amounts kept in fisheries. To find the main factors
involved in the constrained ordination model, forward
selection was used and factors were stepwise added into
the model with a threshold of p < 0.001 to entry (Lepš,
Šmilauer, 2003; Navrátilová et al., 2006; ter Braak,
Šmilauer, 2002). The effects of all canonical axes were
tested by the permutation test – 999 permutations, full
model (Navrátilová et al., 2006).
The same DCA as the above-described analysis was
performed for tourist fisheries as a partial DCA (DCAt).
Two approaches were used to reveal the determinants
of spatial fishing site choices. First, the differences
among fishery types were investigated by One-
way ANOVA with the Tukey unequal N HSD test.
Differences between the whole data set and tourist
fisheries among the fishery types were searched using
the chi-square test.
The significance of distance on the choice of the fishing
site is in our interest as a key concept of space (Knox,
Marston, 2001). The distance decay parameter (Beta
value) is thus calculated from doubly constrained
gravity model with power function (Robinson, 1998)
performed by iterative algorithm of Flowmap
software 7.3 (Breukelman et al., 2009). Higher Beta
values indicate a stronger impact of distance on
travel behaviour (Robinson, 1998). Beta values were
calculated for
each type of fishery to test the impact of attributes 1.
of fisheries and
Vol. 19, 3/2011 MORAVIAN GEOGRAPHICAL REPORTS
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for five types of local organizations divided according 2.
to the number of inhabitants in its locality (up
to 500; from 500 to 5,000; from 5,000 to 15,000;
from 15,000 to 50,000; 50,000 and more) to test the
urban-rural pattern.
Convergence criterion was set to 0.1% and Beta values
were calculated according to the logarithmic distance
of the observed average trip length (Breukelman et
al., 2009).
3. Results
Spatial pattern of anglers movement
The overall variation in anglers’ origins for all
fisheries of the Czech Anglers Union was examined
by gradient analysis. The explained variability of the
first two DCA axes is 6% (Tab. 1). The first DCA axis
is markedly longer than the other axes (Tab. 1, Fig. 2);
we can thus consider it to be the most important
gradient according to which the fisheries differentiate
one from the other. The gradient along the first
axis can be designatet as geographical because the
fisheries of the western part of the Czech Republic
(Karlovy Vary Region, Plzeň Region) have separated
along this gradient from the Moravian fisheries of the
eastern part of the Czech Republic (Olomouc Region,
Zlín Region, Moravian-Silesian Region). Between
these quite outstanding groups, we can find the
fisheries of eastern Bohemia (Hradec Králové Region,
Pardubice Region) and a more extensive grouping of
northern Bohemia (Liberec Region, Ústí Region),
middle Bohemia (Prague, Central Bohemia Region)
and southern Bohemia (South-Bohemian Region).
The first DCA axis thus represents a territorial
gradient in the attendance of fisheries in the sense
of longitude, as the scores of the first DCA axis was
very well correlated with the longitude of the fishery
location (Fig. 3a).
There have been quite significantly separated northern
Bohemian fisheries from the fisheries of southern
Bohemia alongside the second axis. Therefore, we
can consider even the second axis as the axis of the
geographical gradient, this time in the sense of
latitude as the scores of the second DCA axis were
well correlated with the latitude of fishery location
(Fig. 3b). Its importance in the dataset is however
markedly lower than that of the first axis.
CCA was applied to test a hypothesis about the
influence of space on the variation of anglers’ origin
on fisheries (H1). The variation of anglers origin
Tab. 1: Summary of detrended correspondence analysis
(DCA) of all 1,103 fisheries of the Czech Anglers Union,
canonical correspondence analysis (CCA), and partial
detrended correspondence analysis (DCAt) of 49 tourist
fisheries (DCAt)
Axis DCA DCAt
Eigenvalue
1 0.776 0.602
2 0.397 0.242
3 0.344 0.168
Total inertia 19.859 4.913
Length of
gradient
1 10.635 6.417
2 5.804 3.538
3 6.444 3.411
Cumulative
percentage vari-
ance of fisheries
data
1 3.900 12.300
2 5.900 17.200
3 7.600 20.600
Fig. 2: Position of fisheries in the ordination diagram based on DCA. Fisheries categorized according to their location
in regions of the Czech Republic (for legend see Fig. 1)
MORAVIAN GEOGRAPHICAL REPORTS 3/2011, Vol. 19
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is significantly explained by longitude, latitude,
non-trout and trout type of fishery. Together they
explained for 5.8% of total variability. All four axes
were significant ant thus the relationship between the
anglers’ origins and the fishery location was highly
significant. Eigenvalues of the first two axes in CCA are
only slightly smaller than in DCA, this indicating that
the variables included in CCA really captured much of
the variation in the anglers’ origin data (Navrátilová
et al., 2006).
The same DCA was performed for tourist fisheries.
Even in that category, there is one main gradient
(Tab. 1) – geographic in the sense of the longitude
(Fig. 4a). The second gradient can be labelled as an
‘impact of the capital Prague’. The third axis has then
a significance of a geographic gradient in the sense of
the latitude (Fig. 4b).
Determinants of spatial shery choice on the large scale
The differences in the share of members of a respective
local organization on the numbers of fish kept between
trout and non-trout fisheries (Tab. 2) were found as well
as differences among particular fishery types (Tab. 3).
In the trout fisheries, the members of the respective
local organization take a lower share of the fish kept
than in the non-trout waters. With the increasing
geographical generalization, the differences between
the trout and non-trout fisheries are decreasing but
still remain significant. Within the defined fishery
Fig. 3: Correlation of the location of fisheries between DCA axes coordinates and geographical coordinates for 1st
DCA axis and longitude (a) and for 2nd DCA axis and latitude (b) (for legend see Fig. 1)
Vol. 19, 3/2011 MORAVIAN GEOGRAPHICAL REPORTS
41
types, differences exist in the shares of members of
respective local organizations on the fish kept as well.
To the highest degree, members of respective local
organizations account for the fish kept in the up-
to 80 hectares water reservoirs, to the lowest degree
they account for the fish kept in the over 80 hectares
reservoirs. Between the two cited groups, we can find
rivers and brooks that differ from the both types of
reservoirs but they do not differ one with another. The
differences among the particular types decrease when
enlarging the geographical unit.
Similar are results of Beta value of distance-decay rate
(Tab. 4). Beta value counted for trout fisheries is lower
than Beta value for non-trout fisheries. Beta values lower
than 2 were found in the reservoirs over 80 hectares and
in the rivers. By contrast, the highest values were found
in the reservoirs of up to 80 hectares.
A difference in the representation of particular types
of fisheries was found between tourist fisheries and
all fisheries (χ
2
= 75.206, p < 0.001). In the group of
tourist fisheries, the representation of the fisheries on
over 80 ha reservoirs and rivers is significantly higher.
No differences were found in the representation of the
trout and non-trout fisheries.
Attendance distance is manifested by a decrease on the
part of members of these local organizations who are
furthest away from fisheries based on a count of the
Fig. 4: Position of tourist fisheries in the ordination diagram based on DCAt according to the 1st and 2nd axes
of DCAt (a) according to the 1st and 3rd axes of DCAt (b). Tourist fisheries categorized according to their location
in regions of the Czech Republic (for legend see Fig. 1).
Geographical generalization →
Type of fisheries
% share of home local
organizations
% share of districts' local
organizations
% share of regions' local
organizations
mean (S.E.) mean (S.E.) mean (S.E.)
River 61.02a (1.65) 72.89a (1.52) 86.70a (1.11)
Reservoirs up to 80 hectares 70.64b (1.47) 83.75b (1.10) 91.63b (0.81)
Brook 58.21a (1.29) 72.58a (1.13) 85.72a (0.88)
Reservoirs over 80 hectares 39.07c (4.85) 59.69a (3.97) 84.87ab (3.14)
Geographical generalization →
Type of fisheries
% share of home local
organizations
% share of districts' local
organizations
% share of regions' local
organizations
mean (S.E.) mean (S.E.) mean (S.E.)
Non-trout 65.10 (1.02) 78.23 (0.84) 89.48 (0.59)
Trout 56.21 (1.52) 71.02 (1.33) 84.45 (1.08)
Tab. 2: Percentage shares of the members of local organizations originating from identical geographical units where
a fishery is situated. Means in all three cases differ significantly (Tukey unequal N HSD test, p > 0.05).
Tab. 3: Percentage shares of the members of local organizations originating from identical geographical units where
a fishery is situated – types of fisheries. Means with the same letter do not differ significantly (Tukey unequal N HSD
test, p > 0.05).
MORAVIAN GEOGRAPHICAL REPORTS 3/2011, Vol. 19
42
total fish kept (Fig. 5). This impact varies according
to the number of inhabitants in the town of the local
organisation. The impact of distance is more important
in cases involving rural local organizations rather than
urban ones. The lowest Beta value of distance-decay
rate was found in large towns and it was increasing
stepwise up to the highest value in rural local
organizations (Tab. 4).
4. Discussion
Spatial pattern of anglers’ movement
Hypothesis 1 (H1) was that the travelling of anglers
to fisheries does not depend on space but continuously
changes with its gradients. If anglers’ choice of a fishery
depends mainly on natural, economic, aesthetic,
social and other similar conditions, the result of our
gradient analysis would be with no obvious gradient
and it would come to the mixing of fisheries in the
ordination diagram. Indeed, if a spatial relation as
a main characteristic has appeared, it is obvious
that, it plays a main role in the choice of a fishery
by anglers on the level of the whole Czech Republic.
The main gradient is represented by a geographical
position significantly correlating with the longitude.
The reason for it is the extension of the form of the
Czech Republic in an East-West orientation. Thus,
the country forms the longest possible gradient. As
the second main (independent) gradient significantly
correlates with the latitude, they both form together
a model of the real spatial pattern of fisheries (compare
Fig. 1 and Fig. 2), which is close to the anamorphous
map based on an angler’s spatial behaviour (Golledge,
Stimson, 1997). These dependences are statistically
confirmed by the results of CCA.
The explained variability of the whole set of fisheries
is not high. It is because of the excessive heterogeneity
of the data – there are many local organizations whose
members kept no fish on many fisheries – so the gradient
of the first axis is very long (Lepš, Šmilauer, 2003). In
other words, many fisheries are of local importance only
and anglers travel most often to their closest fisheries.
Fig. 5: Share of fish kept by members of local organizations in fisheries according to the distance of a fishery of the
respective local organization (n = 371). The figure presents averages and 0.95 confidence intervals
Tab. 4: Beta values for the urban-rural gradient of local
organizations (LO) and types of fisheries
Beta value
Type of fishery
Trout 1.725
Non-trout 1.952
Type of fishery
Brook 2.075
Reservoirs up to 80 hectares 2.148
River 1.830
Reservoirs over 80 hectares 1.760
Number of inhabitants of a LO quarters
Up to 500 2.456
From 500 to 5,000 2.323
From 5,000 to 15,000 2.223
From 15,000 to 50,000 2.156
Over 50,000 1.923
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43
Regarding data from all fisheries, it seems to be
a trivial finding because the pattern is given by the fact
“an angler travels to and around the closest fishery”.
However, if we set eyes on the analogical analysis
performed with only data from tourist fisheries, we
learn that the pattern stays similar. On a national scale,
anglers choose a fishery mainly according to the spatial
position. The tourist fisheries are similar according to
the origin of anglers fishing there, although they are
different in size, hydrological character and also even
in the fish stock (Humpl et al., 2009). It can result even
from the relatively high spatial diversity of fisheries
all over the Czech Republic – in the majority of the
territory, the fisheries of all types are accessible within
one-day of car travel. The tourist fisheries have thus
a spatial character on the regional principle and no
special fishery exists to which anglers from all over the
Czech Republic would travel.
Spatial closeness is notable above all at the level of
NUTS 3 regions (see Fig. 2). It might be due to the
most widespread type of fishing licenses. They are
valid within the territorial units of the Czech Anglers
Union, which are larger than NUTS 3 regions of the
Czech Republic. The same fishing license as in the
anglers domicile, the anglers use (with no need of
extra payment) also during their weekend recreation
at weekend houses that are most often localized in the
hinterland of towns (Muller, 2002; Mottiar, 2006). In the
case of the Czech Republic, this means within a region
of NUTS 3 (Fialová, 2001) and therefore territorial
units of the Czech Anglers Union, too. Anglers quite
often use weekends for fishing close to their weekend
houses that are very often close to a body of water (e.g.
Muller, 2002; Fialová, 2001), which is a phenomenon
well known in other parts of Europe (e.g. Sipponen,
Muotka, 1996).
Highly notable is the impact of anglers travelling from
the capital city, Prague, to all regions surrounding
middle Bohemia. The reason is the highest
concentration of inhabitants in the Czech Republic
and the highest amount of travels in absolute numbers
(as in Ditton et al., 2002).
Determinants of spatial shery choice
The spatial pattern of anglers’ movements analyzed
on the basis of the number of fish kept according to
the local organization is influenced by the character
of particular fisheries (see Tab. 2, Tab. 3), thus
hypothesis 2 (H2) was confirmed.
The higher share of fish kept by members of other
local organizations in trout fisheries than in non-trout
fisheries, as well as the lower Beta value, could have
been caused by its location, especially in mountain and
submontane areas and, thus, at relatively large distance
from urban centres. Likewise, it is caused by the
different species structure of fish stock, which is a strong
motivator to participate in recreational fishing as a form
of tourism (Fisheries and Oceans Canada, 2007).
The fishery size is an important identifier of the
tourism importance as well (see Tab. 3, Tab. 4). Of the
highest importance in tourism are big reservoirs. It
holds generally that big natural or artificial reservoirs
belong to the most important recreational areas of
inland territories (Ritchie, Crouch, 2003) and in the
Czech Republic the reservoirs beside the mountain
areas are the most important recreational areas for
domestic tourism (Navrátil, Švec, 2008). The big
reservoirs are also related to the largest commercial
offer of accommodation for anglers in the Czech
Republic (Navrátil, 2004); analogically, it is valid for
large fisheries on the watercourses as well.
We can see a common impact of friction of distance
(e.g., Haggett, 2001; Knox, Marston, 2001) in the
increase of the share on the fish caught by the
territorially respective anglers for the bigger territorial
units (Tab. 2, Tab. 3), which is very important also in
tourist activities (e.g. Jensen, Korneliussen, 2002;
Prideaux, 2002; Zilinger, 2007), as confirmed in this
study (Tab. 4).
Small reservoirs are most often attended by members of
their local organization at all geographical levels. That
could be a demonstration of the quality of offer that
generally decreases the weakening impact of distance
on human activity (e.g. Haggett, 2001) reported also
for recreational activities (Becken, 2001). Bigger
fisheries are always recreational areas – therefore
better equipped with recreational and also angling
infrastructures, including the more diversified and
superior fish stock.
The lowest value of the distance-decay parameter
in case of the largest towns would confirm a high
mobility of urban anglers (Arlinghaus et al., 2008)
in combination with high pressure on fisheries. The
values of the distance-decay parameter decreasing
simultaneously with a decrease of the number
of inhabitants in point of the local organisation
headquarters could be evidence of lower mobility of
rural population (e.g. Haggett, 2001) and confirm our
third hypothesis (H3).
5. Managerial implications
Based on the analysis of fish kept in the fisheries of the
Czech Anglers Union it was proved that some impacts
of space and place were of big importance. Among
MORAVIAN GEOGRAPHICAL REPORTS 3/2011, Vol. 19
44
the main findings with the importance for fishery
management in relation to anglers we have to cite:
important spatial closeness of movement among •
the fisheries,
non-negligible existence of angling as a tourist •
activity,
higher mobility of attendants of trout fisheries •
compared to the attendants of non-trout fisheries,
importance of big reservoirs as a main destination •
for angler-tourists.
Acknowledgement
We are grateful to officials and members of the
Czech Anglers Union and the Moravian Anglers
Union who participated in this research. We would
especially like to thank the managers of both
organizations who kindly lent us data for analysis,
which is a part of dissertation of the first author.
Authors also thank Elizabeth George and Jiri
Moudry for language revision and Jan Motloch for
help with programming macros.
This paper was compiled with the support from
the Czech Science Foundation – GACR 403/09/
P053 “The typology of tourist's attitudes towards
environment, the case of waters in landscape”, long-
term research plan of the Ministry of Education,
Youth and Sports of the Czech Republic –
MSM 6007665806 and is a part of European
Social Fund and Ministry of Education, Youth
and Sports of the Czech Republic Operational
Programme Education for Competitiveness – VK
0178 „Studies of rural development economics
at the University of South Bohemia in České
Budějovice“.
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Authors´ addresses:
RNDr. Josef NAVRÁTIL, Ph.D.
Department of Trade and Tourism, Faculty of Economics
University of South Bohemia in České Budějovice
Studentská 13, 370 05 České Budějovice, Czech Republic
e-mail: jnav@ef.jcu.cz
Mgr. Stanislav MARTINÁT
Department of Environmental Geography, Institute of Geonics, Academy of Sciences,v. v. i.
Drobného 28, 602 00 Brno, Czech Republic
e-mail: martinat@geonika.cz
Ing. Kamil PÍCHA, Ph.D.
Department of Trade and Tourism, Faculty of Economics
University of South Bohemia in České Budějovice
Studentská 13, 370 05 České Budějovice, Czech Republic
e-mail: kpicha@ef.jcu.cz
Mgr. Jana NAVRÁTILOVÁ, Ph.D.
Department of Functional Ecology, Institute of Botany, Academy of Sciences,v. v. i.
Dukelská 135, 379 82 Třeboň, Czech Republic
e-mail: navratilova@butbn.cas.cz
