Species are transported accidentally or intentionally all over the world outside their native geographic areas (Williamson 1999) by man, who since early times has attempted to adapt and shape the world in which he lives to suit his own requirements (Elvira 2001). Although the main introductions of exotic fishes into countries outside their natural range are a relatively recent phenomenon, introductions of some species in Europe are believed to date back to Roman times, such as the carp (
The Amur sleeper (or Chinese sleeper),
Feeding ecology of a species is related to its population dynamics and further analysis gives us an understanding of habitat preferences, prey selection, predation, evolution, competition and energy transfer between ecosystems. This ecological information is of great value for the development of conservation strategies and for that reason, it is essential for the protection of species and ecosystems (Braga et al. 2012). The relationship between predator and prey indicates the persistence of species over time (Melián, Bascompte 2002) and the population dynamics is directly related to the community resistance to environmental perturbations (Dunne et al. 2002). Feeding ecology is of great importance due to the fact that diet composition shows from where the animals derive their sustenance and, at the same time, indicates potential food competitors and predator-prey interactions (Ahlbeck et al. 2012). Invasion of exotic species in a community with closely partitioned resources may lead to the elimination of native species as the existing food and the reduction of space resources (Moyle et al. 1986). The knowledge about the use of food resources by invading species, primary prey and feeding ecology gives us the opportunity to predict the effect of an alien species on the existing ecosystem (Carman et al. 2006).
There are many new studies regarding biological features of Amur sleeper, as parasitological studies (Sokolov et al. 2014; Sokolov, Zhukov 2014; Sokolov, Protasova 2014; Drobiniak et al. 2014) and molecular genetics studies (Xue et al. 2013; Chen et al. 2014), but the feeding ecology of this alien species has been poorly studied in the recent years. It appears that the only published papers on the diet of Amur sleeper in Europe are Koščo et al. (2008), Grabowska et al. (2009) and Kati et al. (2015). Food composition of the Amur sleeper seems to be highly size dependent. Zooplankton (microcrustaceans) are the main prey items for the young fish, macroinvertebrates – for intermediate size classes (larvae of insects, mollusks) and amphibian larvae or fish – for larger (older) specimens (Koščo et al. 2008; Pupina, Pupins 2012). However, the most dangerous aspect is the potential consumption of eggs and young fish by the Amur sleeper, which is a serious threat to native fish species (Koščo et al. 2008). The Amur sleeper may be considered as one of the most successful invaders of aquatic communities in shallow water bodies (Koščo et al. 2003).
The study aimed at comprehensive assessment of the Amur sleeper feeding behavior correlated with the possible competitiveness analysis of fish species in relation to the feeding mode. We investigated the food spectra of 349 specimens captured in autumn 2012 at 12 sampling sites on the Siret River, Romania. Our objective was to investigate the diet, the characteristics of the prey and the feeding behavior of the Amur sleeper. This is the first investigation into the diet of the
The study was carried out in the Moldavian Plateau, the eastern Romania, in the Siret River (Fig. 1). The Siret has its source at 1238 m in the Ukrainian Carpathians, north of Mount Long (1382 m). In the territory of Romania, the Siret collects all tributaries descending from the eastern slopes of the Carpathians: Suceava, Moldova, Bistrita, Trotus, Putna, Buzău and Râmnicu Sărat (right) and Bârlad (left; the only important tributary) and then flows into the Danube. The length of the watercourse is 726 km, the flow rate is 235 m3/second and the total area of the Siret basin is 44 835 km2, which make it the largest basin in Romania (Diaconu 1971). The climate is temperate continental.
All the fish (349 individuals) were captured by electrofishing at 12 sampling sites in the river during October of 2012. GPS coordinates and physicochemical parameters (altitude, water and air temperature, pH, conductivity) were measured for every sampling site.
The sampling sites were selected so as to accurately determine the biological aspects as well as the aquatic vegetation (periphyton, macrophytes), riparian vegetation (shrubs, reed, herbaceous plants) and the substrate structure (rockfill, gravel, sand, mud). After the correlation of all parameters mentioned above, we establish 3 representative sampling points – the Galbeni village where the fish sampling was conducted on two occasions, the Cleja village (3 fish samplings) and the Răcăciuni village (1 fish sampling).
Fish were deposited
We calculated the abundance of prey and prey diversity. To estimate the dietary importance of each prey category, we calculated the percentage or proportion of each food category (i.e. the number of individuals of a prey type divided by the total number of individuals expressed as a percentage) and the frequency of occurrence (defined as a proportion of fish containing a given prey category). The Costello (1990) graphical method was applied to describe the feeding strategy and prey importance: a plot of % vs. frequency of occurrence).
Sampling sites for Amur Sleeper in the Siret River, RomaniaFigure 1
To analyze how the diet changes with fish length, we divided the Amur sleeper individuals into two functional size classes: < 70 mm Sl and ≥ 70 mm Sl, following Koščo et al. (2008).
Trait-based analysis of Amur sleeper diet was used to complement the taxonomic-based analysis. We used morphological (e.g. body size, body shape or morphological defences) and macroinvertebrate behavioral traits (e.g. drift tendency, locomotion or movement trajectory), following De Crespin De Billy, Usseglio-Polatera (2002). To find relationships between food selectivity and fish morphological features and environmental factors, the redundancy analysis (RDA) was used.
The diet of
Cannibalism was observed in two cases. In several cases, we also found small pieces of plastic, stones and colored fibers in digestive tracts.
At all sampling sites,
Feeding strategy displayed by the Costello (1990) graphic method for Amur sleeper in relation size classes – A (< 70 mm Sl) and B ( ≥ 70 mm Sl) Acronyms used to abbreviate the macroinvertebrate groups, genus or species binomial nomenclature: Figure 2
Mean frequencies and proportions of each taxa in the total content of
Total
< 70 mm Sl
≥ 70 mm Sl
Frequency
Proportion
Frequency
Proportion
Frequency
Proportion
ase
75.08
43.90
66.26
38.19
85.51
50.22
bae
59.47
26.98
58.90
30.92
60.14
22.32
chi
44.19
17.48
47.24
21.09
40.58
13.22
cor
11.30
2.71
1.84
0.55
22.46
5.15
phy
11.30
1.85
11.04
2.23
11.59
1.30
val
8.31
1.33
1.84
0.74
15.94
1.93
hyd
8.64
1.23
6.13
1.13
11.59
1.36
hal
3.99
0.76
4.91
1.05
2.90
0.42
ind
3.65
0.56
3.07
0.50
4.35
0.63
tip
4.32
0.43
1.84
0.22
7.25
0.68
erp
1.00
0.38
1.23
0.64
0.72
0.08
coe
4.65
0.37
2.45
0.22
7.25
0.56
lym
1.66
0.34
1.84
0.33
1.45
0.35
cae
1.33
0.28
1.84
0.48
0.72
0.04
elo
2.33
0.26
1.23
0.22
3.62
0.29
sim
0.66
0.23
0.00
0.00
1.45
0.51
psy
1.66
0.15
1.23
0.17
2.17
0.12
ost
0.33
0.13
0.61
0.25
0.00
0.00
dyt
1.00
0.09
1.23
0.12
0.72
0.04
oli
1.00
0.08
0.61
0.09
1.45
0.07
pis
0.66
0.07
0.61
0.10
0.72
0.04
cer
1.00
0.07
1.23
0.07
0.72
0.07
trr
1.00
0.07
0.61
0.03
1.45
0.12
set
0.33
0.07
0.00
0.00
0.72
0.14
hcu
0.33
0.04
0.00
0.00
0.72
0.09
gom
0.33
0.03
0.00
0.00
0.72
0.07
fag
0.33
0.03
0.00
0.00
0.72
0.07
mel
0.66
0.03
0.61
0.02
0.72
0.04
str
0.33
0.02
0.00
0.00
0.72
0.05
hel
0.33
0.02
0.61
0.03
0.00
0.00
for
0.33
0.01
0.00
0.00
0.72
0.03
Feeding strategy displayed by the Costello (1990) graphic method for Amur sleeper in relation to sampling sites – Galbeni (n=132), Cleja (n=152), Răcăciuni (n=65) Acronyms used to abbreviate the macroinvertebrate groups, genus or species binomial nomenclature – see Fig. 2Figure 3
With respect to the sampling sites,
Redundancy analysis (RDA) of the relationship between Amur sleeper food composition and fish morphology (weight, length and width) and environmental parameters (characteristics of the bottom substrate: rocks, mud, gravel, sand and the prevailing type of vegetation) Acronyms used to abbreviate the macroinvertebrate groups, genus or species binomial nomenclature – see Fig. 2Figure 4
Mean frequencies and proportions of each taxa at each sampling site – Galbeni (n=132), Cleja (n=152), Răcăciuni (n=65)
Total
Galbeni
Cleja
Răcăciuni
F
P
F
P
F
P
F
P
ase
75.08
43.90
73.60
40.58
76.58
56.15
75.38
29.36
bae
59.47
26.98
61.60
26.98
43.24
15.28
83.08
46.96
chi
44.19
17.48
53.60
22.12
41.44
19.85
30.77
4.50
cor
11.30
2.71
8.80
1.81
5.41
0.76
26.15
7.76
phy
11.30
1.85
23.20
4.25
3.60
0.21
1.54
0.04
val
8.31
1.33
4.80
0.41
6.31
1.39
18.46
3.00
hyd
8.64
1.23
4.80
0.50
5.41
1.35
21.54
2.44
hal
3.99
0.76
4.00
0.37
6.31
1.65
0.00
0.00
ind
3.65
0.56
4.80
0.67
0.90
0.06
6.15
1.20
tip
4.32
0.43
3.20
0.27
4.50
0.65
6.15
0.36
erp
1.00
0.38
1.60
0.13
0.90
0.90
0.00
0.00
coe
4.65
0.37
6.40
0.55
4.50
0.38
1.54
0.04
lym
1.66
0.34
2.40
0.43
0.90
0.30
1.54
0.22
cae
1.33
0.28
0.00
0.00
0.00
0.00
6.15
1.29
elo
2.33
0.26
2.40
0.33
3.60
0.33
0.00
0.00
sim
0.66
0.23
0.00
0.00
0.00
0.00
3.08
1.08
psy
1.66
0.15
0.00
0.00
0.90
0.23
6.15
0.30
ost
0.33
0.13
0.80
0.32
0.00
0.00
0.00
0.00
dyt
1.00
0.09
0.00
0.00
0.00
0.00
4.62
0.39
oli
1.00
0.08
0.00
0.00
0.90
0.13
3.08
0.15
pis
0.66
0.07
0.00
0.00
0.90
0.15
1.54
0.08
cer
1.00
0.07
1.60
0.15
0.00
0.00
1.54
0.04
trr
1.00
0.07
0.00
0.00
2.70
0.19
0.00
0.00
set
0.33
0.07
0.00
0.00
0.00
0.00
1.54
0.31
hcu
0.33
0.04
0.00
0.00
0.00
0.00
1.54
0.19
gom
0.33
0.03
0.00
0.00
0.00
0.00
1.54
0.15
fag
0.33
0.03
0.80
0.07
0.00
0.00
0.00
0.00
mel
0.66
0.03
0.00
0.00
0.90
0.05
1.54
0.04
str
0.33
0.02
0.00
0.00
0.00
0.00
1.54
0.10
hel
0.33
0.02
0.80
0.04
0.00
0.00
0.00
0.00
for
0.33
0.01
0.80
0.03
0.00
0.00
0.00
0.00
Regarding macroinvertebrate trait analysis, our data indicate that
Although
The prey with low to moderate tendency to drift in the water column dominated in
Traits-based analysis for the total content of
Traits
Categories
Total
< 70 mm
≥ 70 mm
mean
SE
mean
SE
mean
SE
Potential size of the prey
0.5-1 cm
28.71
1.31
31.79
1.94
25.06
1.64
1-2 cm
61.89
1.49
58.02
2.16
66.46
1.94
2-4 cm
5.25
0.53
5.78
0.84
4.62
0.56
4-8 cm
0.53
0.13
0.39
0.15
0.70
0.22
5-25 cm
3.60
0.47
4.01
0.76
3.13
0.47
Locomotion and substrate relation
Flier
0.70
0.11
0.33
0.11
1.14
0.20
Surface swimmer
0.22
0.06
0.19
0.08
0.25
0.10
Full water swimmer
15.71
0.79
15.96
1.01
15.42
1.23
Crawler
51.04
0.54
51.47
0.65
50.53
0.89
Burrower
4.98
0.41
4.74
0.57
5.26
0.58
Interstitial
22.91
0.62
22.32
0.86
23.61
0.90
Temporarily attached
4.44
0.38
5.00
0.57
3.79
0.49
Permanently attached
0.05
0.02
0.01
0.01
0.10
0.05
Food
Microorganisms
0.22
0.04
0.30
0.07
0.13
0.03
Detritus < 1mm
19.35
0.38
20.52
0.55
17.96
0.50
Dead plant ≥ 1mm
27.95
0.81
26.16
1.11
30.06
1.15
Living microphytes Living macrophytes
26.92 14.40
0.52 0.28
28.38 14.16
0.79 0.44
25.20 14.70
0.63 0.31
Dead animal ≥ 1mm
3.86
0.23
3.82
0.32
3.91
0.33
Living microinvertebrates
3.87
0.28
3.24
0.33
4.61
0.46
Living macroinvertebrates
3.34
0.34
3.29
0.45
3.39
0.52
Vertebrates
0.09
0.05
0.13
0.08
0.05
0.04
Feeding habits
Absorber
0.02
0.01
0.02
0.02
0.02
0.01
Deposit feeder
11.86
0.51
13.85
0.77
9.50
0.61
Shredder
47.41
1.89
42.88
2.67
52.76
2.60
Scraper
27.43
1.28
30.88
1.93
23.36
1.56
Filter-feeder
5.18
0.45
5.30
0.66
5.04
0.60
Piercer
2.50
0.41
1.19
0.41
4.03
0.74
Predator
3.78
0.47
3.70
0.73
3.86
0.57
Parasite
1.83
0.15
2.17
0.22
1.43
0.19
Substrate
Boulders/pebbles
13.52
0.35
14.83
0.51
11.96
0.45
Gravel
8.35
0.14
8.86
0.20
7.74
0.19
Sand
6.82
0.11
7.23
0.15
6.34
0.15
Silt
1.92
0.16
2.20
0.24
1.59
0.18
Macrophytes
30.83
0.41
30.04
0.57
31.75
0.57
Microphytes
8.11
0.34
7.37
0.49
8.99
0.47
Twigs/roots
12.43
0.19
12.78
0.28
12.02
0.23
Organic detritus/litter
12.19
0.30
10.75
0.36
13.90
0.46
mud
5.84
0.21
5.95
0.33
5.70
0.25
Current velocity
Null
36.95
0.99
34.00
1.52
40.44
1.15
Slow
38.29
0.45
37.29
0.65
39.48
0.61
Medium
15.00
0.77
17.25
1.18
12.33
0.91
Fast
9.76
0.51
11.46
0.78
7.75
0.59
Tendency to drift in the water column
None
2.22
0.39
1.78
0.62
2.73
0.43
Weak
31.91
0.90
31.27
1.43
32.68
0.99
Medium
41.59
0.46
40.46
0.66
42.92
0.63
High
24.28
0.80
26.49
1.27
21.67
0.86
Tendency to drift at the water surface
None
9.00
0.77
6.32
0.93
12.17
1.21
Weak
56.85
1.69
54.12
2.46
60.08
2.24
Medium
22.44
1.02
25.93
1.51
18.33
1.23
High
11.71
0.67
13.64
1.04
9.42
0.76
Trajectory on the bottom substrate or in the drift
None
18.20
0.98
19.67
1.45
16.46
1.26
Linear
38.28
0.96
34.64
1.37
42.57
1.26
By random
22.71
0.71
21.13
1.03
24.59
0.92
Oscillatory
20.81
1.05
24.56
1.51
16.38
1.34
Movement frequency
Continuous
66.29
1.44
60.11
2.11
73.58
1.73
Discontinuous
33.71
1.44
39.89
2.11
26.42
1.73
Diel drift behavior
None
9.42
0.70
9.18
1.00
9.69
0.97
Nocturnal
31.72
0.68
29.91
0.95
33.86
0.94
Dawn
21.75
0.24
22.29
0.37
21.11
0.29
Daylight
13.93
0.43
14.81
0.63
12.90
0.55
Dusk
23.17
0.28
23.79
0.43
22.44
0.33
Agility
None (sluggish)
5.16
0.68
4.36
0.99
6.10
0.90
Weak
26.34
0.82
25.48
1.28
27.35
0.95
High
68.50
0.96
70.16
1.47
66.55
1.14
Aggregation tendency
Weak
30.15
0.37
30.14
0.51
30.16
0.53
High
69.85
0.37
69.86
0.51
69.84
0.53
Concealment
Fixed accessory
0.76
0.20
0.66
0.31
0.88
0.24
Movable accessory
6.38
0.53
7.57
0.80
4.97
0.66
Solidly colored
64.40
0.36
64.81
0.53
63.92
0.49
Variable
12.02
0.44
10.03
0.59
14.37
0.61
Patterned
16.44
0.42
16.93
0.64
15.86
0.52
Body shape
Cylindrical
60.18
1.50
66.32
2.14
52.93
1.93
Spherical
1.35
0.25
0.32
0.17
2.56
0.49
Conical
2.98
0.50
3.22
0.76
2.68
0.63
Flattened
35.49
1.48
30.13
2.11
41.82
1.92
Hydrodynamic
0.00
0.00
0.00
0.00
0.00
0.00
Body flexibility
None
8.58
0.91
5.53
1.08
12.19
1.47
Weak
25.79
0.70
24.85
0.98
26.90
1.00
High
65.63
0.93
69.62
1.25
60.91
1.29
Morphological defences
Cerci, silk, spine
18.79
1.12
21.39
1.75
15.72
1.27
None
81.21
1.12
78.61
1.75
84.28
1.27
However,
The population of
The results of Amur sleeper prey trait analysis are consistent with the current knowledge about the biology and feeding ecology of this species. Living generally in vegetated habitats of the littoral zone with muddy bottom and stagnating water,
In conclusion, Amur sleeper presents a generalistic and flexible feeding strategy by having the ability to feed on available food resources within easy reach, such a feeding behavior is characteristic of successful invaders (Koščo et al. 2008; Grabowska et al. 2009). By feeding on organisms inhabiting different niches of the riverine ecosystem, Amur sleeper is potentially able to rapidly expand its range and colonize a new river environment (Semenchenko et al. 2011). Studies of invasive fish species in European countries indicate that they hold similar characteristics such as opportunistic feeding strategy and a broad diet spectrum (Grabowska, Grabowski 2005).