PRIMARY RESEARCH PAPER

Assessing lake typologies and indicator fish speciesfor Italian natural lakes using past fish richnessand assemblages

Pietro Volta • Alessandro Oggioni •

Roberta Bettinetti • Erik Jeppesen

Received: 6 January 2011 / Revised: 12 April 2011 / Accepted: 16 April 2011 / Published online: 29 April 2011

� Springer Science+Business Media B.V. 2011

Abstract In order to establish a fish-based typology

of Italian lakes and identify possible reference and

indicator fish species for each lake type, we analysed

historical data on fish assemblages of all Italian

natural lakes [0.5 km2 from the period prior to the

major decline in water quality in the 1950s. General

linear regression models showed the ecoregion and

lake altitude being the best predictors of fish species

richness. The number of species was significantly

higher in the Alpine than in the Mediterranean

ecoregion. Among Alpine lakes, the number of fish

species increased significantly with lake volume

whilst decreased with altitude. In the Mediterranean

lakes, none of the selected parameters was significant.

Cluster analysis of fish assemblages (presence/

absence) divided the lakes of the Alpine and Med-

iterranean ecoregions into four and two types,

respectively. Pike (Esox lucius), rudd (Scardinius

erythrophthalmus) and tench (Tinca tinca) were the

main indicator species for the small and mostly

shallow lakes in both the Alpine (Type 1) and

Mediterranean (Type 6) ecoregions, minnow (Phox-

inus phoxinus) for the alpine high altitude lakes

(Type 2) and landlocked shad (Alosa fallax lacustris),

European whitefish (Coregonus lavaretus) and burbot

(Lota lota) for the large and very deep alpine lakes

(Type 4). The European whitefish was the only

indicator species for the deep Mediterranean lakes

(Type 5). These species and associated fish assem-

blages may be useful indicators in future assessments

of the ecological status of Italian lakes according to

the European Directives (2000/60/EC and 2008/105/

EC).

Keywords Fish fauna �Biodiversity �Bioindicators �Reference conditions � Biomonitoring � Pollutants

Handling editor: P. Noges

Electronic supplementary material The online version ofthis article (doi:10.1007/s10750-011-0720-6) containssupplementary material, which is available to authorized users.

P. Volta (&) � A. Oggioni

CNR-Institute of Ecosystem Study, L.go Tonolli 50,

28922 Verbania Pallanza, Italy

e-mail: p.volta@ise.cnr.it

R. Bettinetti

Department of Chemical and Environmental Sciences,

University of Insubria, Via Valleggio 11, 22100 Como,

Italy

E. Jeppesen

National Environmental Research Institute, Aarhus

University, Vejlsøvej 25, 8600 Silkeborg, Denmark

E. Jeppesen

Greenland Climate Research Centre (GCRC), Greenland

Institute of Natural Resources, Kivioq 2, P.O. Box 570,

3900 Nuuk, Greenland

E. Jeppesen

Sino-Danish Centre for Education and Research (SDC),

Beijing, China

123

Hydrobiologia (2011) 671:227–240

DOI 10.1007/s10750-011-0720-6

Introduction

During the past 50 years, fish assemblages in lakes

and reservoirs have been widely investigated at a

regional and ecoregional scale in many North and

Central European countries. Such studies have linked

the characteristics of the fish community with phys-

ico-chemical and morphological variables of the

lakes, as well as with geographical and climatic

variables and anthropogenic pressures (e.g. Eckmann,

1995; Holmgren & Appelberg, 2000; Jeppesen et al.,

2000; Tammi et al., 2003; Penczak et al., 2004;

Diekmann et al., 2005; Mehner et al., 2005; Garcia

et al., 2006; Eros et al., 2009). In contrast, only few

studies have been conducted in countries around the

Mediterranean Sea (Godinho et al., 1998; Argillier

et al., 2002; Irz et al., 2002, 2004; Carol et al., 2006).

In Italy, most studies of freshwater fishes have

considered taxonomic issues (Bianco, 1998; Bianco

& Ketmaier, 2001; Ketmaier et al., 2003; Marchetto

et al., 2010), and most studies focusing on ecological

and biogeographical investigations have been spa-

tially scattered (Galli et al., 2007; Orban et al., 2007;

Pedicillo et al., 2008; Volta & Jepsen, 2008;

Lorenzoni et al., 2009; Volta et al., 2009; Volta &

Giussani, 2010) and not encompassed wide geo-

graphical or temporal scales. At present, Italian lakes

are only divided into three very general categories:

those suitable for salmonids, percids and cyprinids,

respectively. The environmental and fishing author-

ities do not consider lake types or classify lakes

according to type of fish assemblages. In conse-

quence, environmental assessments and conservation

measures are based on limited information of refer-

ence conditions. However, with the establishment of

the Water Framework Directive (WFD; EU, 2000),

there is an urgent need for expanding our knowledge

of biological communities (including fish) in Italian

lakes. The WFD requires assessment of the ecolog-

ical status of lakes using four biological elements

(phytoplankton, macrophytes, macrobenthos and fish)

supported by physical–chemical and hydromorpho-

logical information. The present status of each

biological quality element (BQE) has to be compared

with the community in a ‘near-natural state’, i.e. a

situation of minimum or no anthropogenic distur-

bance, the so-called ‘reference state’. To determine

the reference state, the WFD proposes a comparison

of the statuses of the BQEs of a particular waterbody

with those of another waterbody of the same type, but

in a ‘near-natural’ (least disturbed) state. If this is not

feasible, use of historical data, modelling or expert

judgement is required.

Although the use of historical data involves a

degree of uncertainty due to the different quality and

quantity of data (often only qualitative data are

available), it may provide important information on

the composition and structure of the fish assemblages

in a near-natural state (Steedman et al., 1996).

Therefore, identifying indicator fish species for

different lake types using historical data and thereby

defining the minimum required fish assemblages for

each lake type in a near-natural state might be an

effective approach to overcome the present lack of

reference sites. Furthermore, the Directive 2008/105/

EC (EU, 2008), amending the WFD 2000/60/EC,

includes fish for the monitoring of the levels of

pollutants that are hardly measurable in water

(Galassi & Cassi, 2001; Belpaire & Goemans,

2007), such as mercury, hexachlorobenzene and

hexachlorobutadiene. However, identification of ref-

erence species that can realistically be used as

bioindicators in freshwaters is still subject to debate

(Bettinetti et al., 2010). Therefore, the elaboration of

a list of lake type specific fish species present prior to

pollution is also important for the risk assessment of

pollutants.

The present study describes the fish assemblages in

all Italian natural lakes with a surface area [0.5 km2

prior to major anthropogenic disturbance. The year

1950 was a significant time threshold between low

and high level of anthropogenic pressures on lakes, as

it corresponds to the period between low and high

human development in Italy (before and after the

Second World War). This is particularly true for

eutrophication which, although it began to increase

already in the 18th century, did not seriously affect

the Italian lakes until the 1950s (Guilizzoni et al.,

1982; Margaritora, 1992; Marchetto et al., 2004;

Salmaso et al., 2007). We therefore explore the fish

assemblages prior to 1950 and relate our findings to

limnological characteristics and the geographical

location of the lakes in order to establish a fish-based

typology of Italian lakes and to identify possible

reference and indicator fish species for each lake

type.

228 Hydrobiologia (2011) 671:227–240

123

Materials and methods

Study area

This study considers all natural lakes[0.5 km2 located

in the Italian peninsula. The 46 lakes covered a

latitudinal and longitudinal range between 46�450N–

37�300N and 7�220E–14�180E, respectively. From a

zoogeographical point of view, Italy is divided into

two different ichthyogeographical districts (Bianco,

1995; Abell et al., 2008): the Padano-Venetian district

(from the Alps to the eastern edge of the Apennine

mountains facing the Adriatic Sea) and the Tuscano-

Latium district (facing the Tyrrhenean Sea and the

insular regions), being identical with the two separated

ecoregions identified by the WFD guidelines: the

Alpine and the Mediterranean. Hence, we a priori

separated the lakes as belonging to either the Alpine or

the Mediterranean ecoregion, corresponding more or

less to north and south of the River Po.

Data collection and elaboration

To determine the reference state, we analysed the

available literature data extracted from the historical

library of the Italian Institute of Hydrobiology

(presently CNR-Institute of Ecosystem Study) which

holds documents covering a period from 1700 to

1950 (see Appendix I—Electronic supplementary

materials). Most of the documents are from the period

1850–1930 and include scientific papers and reports

from universities and research institutions and notes

in technical reports from the Ministry of Agriculture

and fisheries authorities on regional economies and

commercial trades. The data achieved from this

historical analysis were checked against those from

recent publications (Tortonese, 1971; Tortonese,

1975; Gandolfi et al., 1991) functioning as the official

(Ministry of the Environment) reference publications

on the Italian fish fauna: scientific names of the fish

species in this study are those included in Gandolfi

et al. (1991).

Thirty-five fish species were included in the

database, belonging to 9 orders and 14 families

(Table 1). Barbel Barbus plebejus, lamprey Lampetra

planeri, grayling Thymallus thymallus, sturgeon

Acipenser spp. and eel were excluded from the

analyses since they are not usually present in lakes or

typical sea migratory species without a predictable

life span in freshwaters. The fish assemblages

included in the database consisted of a mixture

between native and a few non-native species, the

latter being introduced or translocated at different

times from Eastern Europe, Austria, Switzerland and

USA to the Alpine ecoregion and later from north to

south (Gandolfi et al., 1991). This holds true for 7

species: carp, char, European whitefish, ‘bondella’

whitefish, black bullhead, largemouth bass and

pumpkinseed. Also, perch was translocated from

north to the south during the first decades of the

1900s, and big-scale smelt was introduced to lakes in

central Italy from coastal waters.

Data on available morphometric, geographical and

limnological characteristics of lakes including lake

area, maximum depth, volume, altitude and catch-

ment area, alkalinity and retention time were

obtained from LIMNO, the national database of

Italian lakes (Tartari et al., 2004). Data were log-

transformed before statistical analyses and checked

for multicollinearity. Hence, lake area and maximum

depth were excluded since they were highly corre-

lated (r [ 0.80, P \ 0.05) with lake volume both in

the alpine and in the Mediterranean lakes.

General linear regression models (STATISTICA

software) were used to assess the relationship

between the number of species (dependent variable),

the lake characteristics (independent variable) and the

ecoregion (categorical variable) within the whole

dataset. Multiple linear regression was used to assess

the same relationships within each single ecoregion.

Differences between the number of fish species

between ecoregions were tested by Student t test.

Additionally, we calculated the average ratio between

the number of indicator species and the total number

of fish species in each lake (called later as dispersal

ratio) and we used it as a measure of the dispersal

effectiveness. The higher is the ratio, the higher is the

number of species shared within a lake type, indicat-

ing higher dispersal effectiveness. The relationship of

dispersal ratio with the other lake parameters was

tested by general linear regression models, using

ecoregion as categorical variable and other parame-

ters as independent continuous variables.

Lake typology

We divided the lakes into types with similar fish

assemblages, based on the fish data collected, and for

Hydrobiologia (2011) 671:227–240 229

123

Table 1 List of species included in the database with order, family, common name (if not available in English the Italian name is

given) and ecoregion

Order Family Species Common name Ecoregion

Atheriniformes Atherinidae Atherina boyeri Big-scale sand smelt M

Risso 1810

Clupeiformes Clupeidae Alosa fallax lacustris Landlocked shad A

Lacepede 1803

Cypriniformes Cyprinidae Alburnus alburnus alborella Bleak A; M

De Filippi 1844

Carassius carassius Crucian carp A

Linnaeus 1758

Chondrostoma soetta Italian nase A

Bonaparte 1840

Chondrostoma genei ‘Lasca’ A

Bonaparte 1839

Cobitis taenia Spined loach A; M

Linnaeus 1758

Cyprinus carpio Carp A; M

Linnaeus 1758

Leuciscus cephalus Chub A; M

Linnaeus 1758

Leuciscus souffia ‘Vairone’ A; M

Risso 1826

Orthrias barbatulus Stone loach A

Linneaus 1758

Phoxinus phoxinus Common minnow A

Linnaeus 1758

Rutilus erythrophthalmus ‘Triotto’ A

Zerunian 1982

Rutilus pigus ‘Pigo’ A

Lacepede 1804

Rutilus rubilio ‘Rovella’ M

Bonaparte 1837

Scardinius erythtrophthalmus Linnaeus 1758 Rudd A; M

Tinca tinca Tench A; M

Linnaeus 1758

Gadiformes Gadidae Lota lota Burbot A

Linnaeus 1758

Gasterosteiformes Gasterosteidae Gasterosteus aculeatus Three-spined stickleback A; M

Linnaeus 1758

Perciformes Blennidae Salaria fluviatilis ‘Cagnetta’ A; M

Asso 1801

Centrarchidae Lepomis gibbosus Pumpkinseed A; M

Linnaeus 1758

Micropterus salmoides Largemouth bass A; M

Lacepede 1802

230 Hydrobiologia (2011) 671:227–240

123

each lake type we identified indicator fish species for

the reference state. The lake types were identified by

means of cluster analysis using a dissimilarity matrix

calculated from the fish communities occurring in the

lakes prior to 1950. We used the Jaccard index as it is

considered a useful index for identifying ecological

gradients (Faith et al., 1987) and a presence/absence

approach (Heino et al., 2010). For identifying lake

types, we first conducted an assessment of the best

linkage method using the ‘cophenetic correlation

coefficient’ function in R software (VEGAN pack-

age). The cophenetic correlation for a cluster tree is

defined as the linear correlation coefficient between

the distances obtained from the tree and the original

distances (or dissimilarities) used to construct the

tree. Thus, it is a measure of how well the tree

represents the dissimilarities among observations and

it has a statistical meaning indicating the statistical

differences between the different clusters and there-

fore the robustness of the results (Becker et al., 1988).

We chose the Average Linkage Method as it reached

the highest cophenetic value (0.97). The numerical

analyses were carried out by means of R Software

version 2.11.0 (R Development Core Team, 2010)

and Vegan Community Ecology Package version

1.17-2-8 (Oksanen et al., 2010).

Table 1 continued

Order Family Species Common name Ecoregion

Percidae Perca fluviatilis Perch A, M

Linnaeus 1758

Stizostedion lucioperca Pikeperch A

Linnaeus 1758

Gobidae Orsinogobius punctatissimus ‘Panzarolo’ A

Canestrini 1864

Padogobius martensi Padanian goby A

Gunther 1861

Salmoniformes Coregonidae Coregonus lavaretus European whitefish A; M

Linnaeus 1758

Coregonus macrophthalmus ‘Bondella’ A

Nusslin 1882

Esocidae Esox lucius Pike A; M

Linnaeus 1758

Salmonidae Salmo carpio ‘Carpione del Garda’ A

Linnaeus 1758

Salmo trutta lacustris Trout A

Linnaeus 1758

Salvelinus alpinus Char A

Linnaeus 1758

Salmo trutta macrostigma Mediterranean trout M

Dumeril 1858

Salmo trutta marmoratus Marble trout A

Linnaeus 1758

Salmo trutta trutta Trout A

Linnaeus 1758

Scorpaeniformes Cottidae Cottus gobio Bullhead A

Linnaeus 1756

Siluriformes Ictaluridae Ictalurus melas Black bullhead A

Rafinesque 1820

Hydrobiologia (2011) 671:227–240 231

123

Differences in morphometric and chemical charac-

teristics of lake types were tested by Mann–Whitney

statistical test (SYSTAT Software). Significant levels

were set at P \ 0.05.

Indicator fish species identification

Indicator fish species, i.e. guiding and accompanying

fish species, were determined according to Gassner

et al. (2005) and Volta and Oggioni (2010). Guiding

fish species were those that discriminate well between

lake types, i.e. ideally are present in one lake type and

absent in the others. Guiding species were defined by

an occurrence of 100% in one lake type and by a

value of factor a B 7, where a is:

a ¼ ðRpiÞ � range,

‘pi’ is the occurrence (between 0 = absent and

1 = ubiquitous) of a fish species in one lake type

and ‘range’ is the number of lake types where the

species is present. Factor ‘a’ enables selection of

species indicative of one lake type, i.e. species which

are present in all lakes of a particular type, but rare in

the other types.

Accompanying fish species were defined by an

occurrence C80% in one lake type.

Results

General linear regression models (R2 = 0.694,

P \ 0.001) show ecoregion and lake altitude being

the best predictor of fish species richness in Italian

lakes (P = 0.028 and P = 0.027, respectively). The

dispersal ratio (R2 = 0.479, P \ 0.001) was explained

significantly only by the altitude (P = 0.017). The

number of species was significantly higher (t test,

P \ 0.001) in the lakes in the Alpine ecoregion

(n = 34) than in the Mediterranean ecoregion

(n = 13), the average being 12.5 (±3.1) and 7.6

(±2.8) species, respectively. Limited to Alpine lakes

(R2 = 0.724, P \ 0.001), the number of fish species

increases with lake volume (b = 0.569), whilst

decrease significantly with altitude (b = -0.22). In

the Mediterranean lakes, instead none of the selected

parameters contributed to explain significantly the fish

species richness (R2 = 0.487, P = 0.314).

Cluster analysis of the presence/absence of fish

revealed different lake types (Fig. 1a, b). By

maximizing the homogeneity within clusters and the

heterogeneity between clusters, four lake types in the

Alpine ecoregion and two lake types in the Mediter-

ranean were identified. Main lake type characteristics

are shown in Table 2. The lake types were charac-

terized by significant differences in morphometric

and physico-chemical variables as well as in fish

species richness (Table 3).

Sixteen relatively shallow (20.0 ± 15.2 m) and

small (2.9 ± 3.4 km2) lakes were included in Type 1

of the Alpine ecoregion. They are located mostly in

the lowlands (altitude 245.0 ± 74.4 m a.s.l.), just

beyond the moraine edge of the old glaciers, follow-

ing a wide longitude range. Phytophilic species such

as pike, tench and rudd were the guiding species

accompanied by bleak, perch, carp and Padanian

goby (Table 4; Fig. 2).

The second group comprised three high altitude

(1198 ± 242.6 m a.s.l.) lakes located in North-East

Italy. They had low species richness (3.7 ± 1.2) and

were characterized by cold stenothermal and sensitive

species such as the small cyprinid, common minnow,

which is the guiding species, bullhead and salmonids.

Where streams were absent, char was the only

salmonid present, while trout, requiring streams for

reproduction, was only present in lakes associated with

streams.

Type 3 comprised the deep (75.9 ± 50.4 m) but

small (3.5 ± 3.8 km2) lakes located in the north-east.

They constitute an ‘intermediate environment’

between the very deep (Type 4) and shallow (Type

1) lakes. Compared to Type 1, these lakes differed

significantly in depth, but not in area. Therefore,

phytophilic species such as pike, rudd and tench had

the highest indicator value, although trout was still

included in the accompanying species group. The

Italian nase was also accompanying species in these

lakes together with perch and carp.

Type 4 comprised seven large (115.6 ±

136.6 km2) and very deep (238.0 ± 144.1 m) subal-

pine lakes in north-west Italy. The number of species

present was generally high (14.0 ± 4.8) due to the

availability of several different habitats. A well

oxygenated and cold hypolimnion is a suitable habitat

for the sensitive cold stenothermal burbot and Euro-

pean whitefish, which were guiding species, and for

trout. Gregarious euritherm zooplanktivorous species

such as the landlocked shad were also guiding species

in this type of lakes. The number of accompanying

232 Hydrobiologia (2011) 671:227–240

123

species was large and included: littoral (padanian

goby), phytophylic (pike, rudd, tench), gregarious

(bleak) and tolerant (perch, carp) species.

In contrast, in the Mediterranean ecoregion,

two main types were identified of which the first

(Type 5) includes the deep (98.7 ± 66.1 m) and large

Fig. 1 Dendrogram

grouping the natural lakes

of Italian Alpine (a) and

Mediterranean

(b) ecoregions based on the

reconstructed fish

community. ‘Y’ axis

‘height’ indicates the

dissimilarity between

groups

Table 2 Average (±SD) lake types characteristics

Type 1 Type 2 Type 3 Type 4 Type 5 Type 6

N. lakes 16 3 7 7 6 7

Catchment area (km2) 33.2 ± 32.7 101.7 ± 113.8 136.0 ± 213.8 2299.9 ± 2453.9 97.7 ± 101.9 90.2 ± 96.3

Altitude (m a.s.l.) 245.0 ± 74.4 1198 ± 242.6 466.6 ± 206.4 189.4 ± 65.6 418.1 ± 270.1 363.3 ± 149.0

Lake area (km2) 2.9 ± 3.4 0.7 ± 0.2 3.5 ± 3.8 115.6 ± 136.6 32.1 ± 45.2 19.9 ± 47.7

Maximum depth (m) 20.0 ± 15.2 24.5 ± 12.6 75.9 ± 50.4 238.0 ± 144.1 98.7 ± 66.1 7.8 ± 5.4

Lake volume (km3) 28.8 ± 36.1 6.9 ± 1.9 65.1 ± 666.6 16880.4 ± 19922.2 2442.7 ± 3703.9 89.7 ± 218.7

Alkalinity (meq l-1) 2.7 ± 1.0 2.9 ± 1.2 2.0 ± 0.7 1.0 ± 0.8 3.5 ± 1.0 3.5 ± 0.8

Retention time (years) 2.7 ± 5.7 0.2 ± 0.2 2.6 ± 3.0 7.8 ± 8.7 170.5 ± 171.6 4.9 ± 11.8

N. fish species 7.9 ± 1.6 3.7 ± 1.2 11.0 ± 3.2 17.4 ± 4.8 8.3 ± 2.3 5.6 ± 2.0

Hydrobiologia (2011) 671:227–240 233

123

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11

.71

)5

0.8

4(–

11

.70

)7

3.9

(±1

7.8

)A

ltit

ud

e(P

=0

.03

5),

Alk

alin

ity

(P=

0.0

01

),

Ret

enti

on

tim

e(P

=0

.03

5),

N.

fish

spec

ies

(P=

0.0

01

)

Cat

chm

ent

area

(P=

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38

),L

ake

area

(P=

0.0

26

),

Alt

itu

de

(P=

0.0

04

),

Max

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th

(P\

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),L

ake

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=0

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2),

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nit

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(P\

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),N

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ies

(P\

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57

6.1

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8.4

)M

axd

epth

(P=

0.0

01

),

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ev

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me

(P=

0.0

14

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on

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e

(P=

0.0

08

),N

.fi

sh

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ies

(P=

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14

)

Ty

pe

65

6.7

6(–

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8)

86

.4(±

22

.5)

234 Hydrobiologia (2011) 671:227–240

123

Table 4 Indicator (guiding and accompanying fish species) in the different lake types of Alpine (Types 1–4) and Mediterranean

(Types 5–6) Italian ecoregions

Type 1 Type 2 Type 3 Type 4 Type 5 Type 6

Guiding fish species Pike Minnow Pike Burbot Whitefish Pike

Rudd Rudd Shad Rudd

Tench Tench Whitefish Tench

Accompanying fish species Bleak Bullhead Carp Bleak Carp Carp

Carp Trout Italian nase Chub Perch Perch

Perch Char Perch Carp Pike

Padanian goby Trout Padanian goby Rudd

Perch Tench

Pike

Rudd

Tench

Trout

Fig. 2 Box & Whisker plots showing median, 25th and 75th

percentiles, minimum, maximum and outliers of geographical

(coordinates and altitude), morphometric (catchment area, lake

area, maximum depth and lake volume), and limnological

(alkalinity and retention time) characteristics and specie

richness (n. species) for the different lake types

Hydrobiologia (2011) 671:227–240 235

123

(32.1 ± 45.2 km2) lakes of Central Italy, mostly of

volcanic origin and located in the Latium region. The

number of species was relatively high (8.3 ± 2.3), and

European whitefish was the guiding species. The

second (Type 6) comprised all the shallow (7.8 ±

5.4 m) lakes of Central and South Italy; these were

characterized by a few typically phytophilic and highly

tolerant species (5.6 ± 2.0) such as tench, rudd

and carp.

Discussion

The implementation of the WFD requires as a first

step identification of waterbody types including sites

with reference conditions for each biological quality

element (WFD CIS, 2003). Typology of waterbodies

is usually based on physico-chemical variables and

hydromorphological characteristics. However, if ref-

erence sites at national scale are scarce or missing,

use of alternative methods to establish reference

benchmarks is required.

Fish are the only group of freshwater organisms for

which adequate historical information may be avail-

able, which makes them useful indicators of the

reference state of freshwaters (Schmutz et al., 2000).

The quality of historical data is variable and the

information on fish composition of lakes is often

biased towards commercial interesting species, non-

commercial species often being excluded from fishery

statistics. Also, historical data may include synonyms

and unclear taxonomy that are not easy to update to the

current nomenclature. However, even though use of

historical data is somewhat uncertain they may provide

valuable information on the composition and structure

of the fish assemblages in a near-natural state (Steed-

man et al., 1996). In our study, we checked for

synonyms, and all fish species were validated with the

current official Italian taxonomy (Gandolfi et al.,

1991). Moreover, our data have been gathered from

multiple sources coupling scientific observations,

paintings and photos from universities, research and

fisheries institutions, commercial and fisheries statis-

tics and local information from leasing contracts and

fish market trades. Also, due to the different sources

considered, the data cover the whole geographical

range and lake sizes enabling a satisfactory recon-

struction of the fish assemblages in the first decades of

the twentieth century in Italian lakes.

Using data for all Italian natural lakes [0.5 km2,

we obtained six lake types, four in the Alpine

ecoregion and two in the Mediterranean ecoregion

showing differences both in fish richness and com-

position. The fish assemblages were significantly

influenced by a complex set of geological, climato-

logical and limnological variables. According to

statistical analyses, the ecoregion is an important

factor explaining the fish species richness in Italian

lakes. The Alps and Apennines have acted as barriers

modulating the fish distribution by slowing down

migrations from Alpine areas to Mediterranean ones

(Bianco, 1995; Hewitt 1999; Griffiths, 2006; Reyjol

et al., 2007). For instance, the number of fish species

was lower in the deep of Type 5 situated mainly in

volcanic areas of central Italy and therefore isolated

than in those of Type 4, belonging to the river Po

basin and therefore linked to Adriatic Sea. In

addition, species with high mobility and migratory

behaviour, such as trout, chub and nase, are common

species in deep lakes in the North, while they are less

frequently occurring in the more isolated deep lakes

in the Mediterranean ecoregion.

As in other studies (see Zhao et al., 2006), we

found species richness to decrease with lake altitude.

We also found that the dispersal effectiveness

decreased with altitude, which is not surprisingly as

high altitude watersheds are less assessable for fish

migrations than those at low altitudes (e.g. Albert &

Crampton, 2010).

However, although barriers and glaciation events

likely determine species richness, species that over-

come such factors face various abiotic and biotic

constraints and opportunities modulating the fish

assemblages (Griffiths, 2006).

Also, fish species richness was highest in large and

deep lakes, while small and shallow lakes had

relatively simple fish communities. This holds true

for both high and low altitude lakes and confirms

previous findings covering a wider (Jackson &

Harvey, 1989; Tonn et al., 1990; Amarasinghe &

Welcomme, 2002; Zhao et al., 2006) and a smaller

geographical area (Eckmann, 1995; Irz et al., 2002).

Lake morphology (depth, surface and catchment

area) and altitude affects physical and chemical

characteristics such as retention time, nutrient con-

centrations and primary productivity (Wetzel, 1975).

Deep and large lakes and high altitude lakes are often

oligo-mesotrophic in the natural state, while shallow

236 Hydrobiologia (2011) 671:227–240

123

lakes are typically meso-eutrophic (Noges, 2009). We

found that high altitude or deep lakes sustain

populations of sensitive/intolerant fish species such

as salmonids (trout, char), bullhead and coregonids,

while shallow and relatively small lakes were char-

acterized mainly by phytophilic and benthivorous-

tolerant species. This is in line with numerous studies

in the northern hemisphere showing that enhanced

primary productivity reinforced by specific morpho-

metric characteristics of shallow lakes leads to a shift

in fish communities from Salmoniformes (mainly

coregonids) to phytophilic or tolerant species (Mar-

shall & Ryan, 1987; Persson et al., 1991; Holmgren

& Appelberg, 2000; Mehner et al., 2005; Garcia

et al., 2006). Furthermore, at species level, Heino

et al. (2010) found that pike and perch were among

the most common species in meso-eutrophic boreal

lakes, while brown trout was common in deep

oligotrophic lakes in the same region. Mehner et al.

(2007) found vendace Coregonus albula and burbot

to be the most indicative fish species of deep and

oligotrophic lakes in the European ‘Central Plains’

ecoregion.

We identified indicator fish species for each lake

type in the near-natural state, which may be used in the

assessment of ecological status according to the

relevant EU directives in combination with appropri-

ate metrics. Noble et al. (2007) suggested development

of metrics for young-of-the-year indicator (sentinel)

species supplemented by an examination of their

population age structure. Zick et al. (2007) and

Gassner & Wanzenbock (2007) applied size structure

indices (Gablehouse, 1984) to char and whitefish

populations in Austrian lakes, and Volta (2010) did the

same to three deep Italian lakes exhibiting differences

in trophic status and fishing pressure. Size structure

indices may be useful proxies for the determination of

age structure, a labour-demanding process that is

currently a demand of the WFD.

The indicator fish species may potentially also be

used as biomonitors for aquatic chemicals when

concentrations are at or below the detection level

(Barron et al., 1996; Volta et al., 2009) and may

provide information allowing assessment of the threats

posed by water contamination to aquatic communities

(Koponen et al., 2001; Volta et al., 2009).

The indicator species identified in our study

include pelagic and littoral feeders, benthivores and

zooplanktivores, prey and top predators, representing

different lake environments and common fish food

webs. The species are moreover easy to capture by

standardized techniques such as gillnetting and

electrofishing, enabling the development of routine

surveys and effective monitoring programs.

In conclusion, we have developed a fish-based

typology of Italian natural lakes [0.5 km2 supple-

mented with a list of indicator reference fish species for

each lake type to be used in the assessment of the

ecological and chemical quality of natural Mediterra-

nean lakes. As most of the species are of commercial

and recreational value, they are relevant as a reference

for managers of both fisheries and the environment.

The reference species and assemblages can further be

used as a basis when changes in the ichthyofauna of

lakes at local and ecoregional scale are studied and for

implementation of lake type specific management and

restoration measures, when necessary.

Acknowledgments P. Volta (PV) and E. Jeppesen (EJ) were

partially funded by the EU-FP7 WISER project; PV also by

LIFE? INHABIT and CIPAIS (Commissione Internazionale

per la Protezione delle Acque Italo-Svizzere), and EJ also by

EU-FP7 REFRESH, CRES and The Danish Council for

Independent Research: Natural Sciences (272-08-0406). We

thank Anne Mette Poulsen for most valuable editorial

comments and the two anonymous referees for the valuable

comments which improved the manuscript importantly.

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