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Keywords:

  • Anguilla anguilla ;
  • downstream migration dynamics;
  • European eel management plan;
  • silver eel escapement;
  • regulated lowland river system;
  • Baltic Sea

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

In the light of the European wide efforts to increase the spawning biomass of the European eel, a reliable measurement of the escapement of mature silver eel is necessary to prove the effectiveness of the conservation management measures. The seaward migration of mature eel is commonly viewed as a seasonal phenomenon with concentrated migration peaks occurring in spring and autumn. To verify the assumed seasonal silver eel migration events for regulated lowland rivers, a stow-net system was installed in the Warnow River located in north-eastern Germany. Between 2008 and 2011, the stow-net system was operated from March to December each year. The eel harvest was documented on a weekly base including the documentation of weight and length, the silvering stage and the tissue sampling for the molecular identification of the eel species. During the 4 year monitoring period, a continuous downstream migration of female and male silver eels was observed. Additionally, single migration peaks were recorded in each year occurring between April and December. Moreover, female and male silver eels showed varying downstream migration dynamics. Based on a Chi-squared Automatic Interaction Detection (CHAID) tree analysis, it was shown that during periods of a daily minimum air temperature over 10.4 °C, increased discharge levels and increased wind speeds, higher weekly migration rates of silver eels were likely. Furthermore, the results indicated that both sexes differed in their responses to migration triggering environmental factors. The presented results might be helpful to design more efficient eel conservation management strategies in regulated lowland rivers.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

The panmictic, catadromous European eel (Anguilla anguilla, L.) population (Als et al. 2011) has dramatically declined in the last decades (Dekker 2009; ICES (International Council for the Exploration of the Sea) 2010). Today, the European eel is considered to be outside safe biological limits [ICES (International Council for the Exploration of the Sea) 2010]. Various oceanic and continental factors have been identified as possible causes, each with varying degrees of empirical or conceptual support (e.g., Dekker 2008, 2009; ICES 2010). For example, changing oceanic conditions may impair the nutrient conditions for eel larvae as well as the survival rate during the transport towards the Gulf Stream, resulting in a reduced number of glass eel arriving at the European continent (Friedland et al. 2007; Bonhommeau et al. 2008; Durif et al. 2011). During the continental life phase in freshwater and coastal waters, eels are negatively impacted by various factors like overexploitation, pollution, diseases, parasite infections, predation, obstacles to migration (e.g., hydropower use) and habitat loss (Dekker 2008, 2009; ICES 2008). All these potential factors act simultaneously (Starkie 2003; Dekker 2009). Although the causes of the alarming decline of European eel throughout Europe are not fully understood, conservation actions are urgently needed (Dekker 2009; ICES 2010). To facilitate the development of effective management strategies as dictated by the European Union [EC (European Commission) 2007)], a detailed understanding of the seaward migration dynamics of the mature silver eels is needed.

The transformation from yellow eel stage to the silver eel stage indicates the end of the continental growth phase of the European eel and the start of the return to their spawning ground (Tesch 2003). The silvering process prepares the eel for the marine life phase, which include various morphological and physiological changes (Tesch 2003; Rousseau et al. 2009). The start of metamorphosis as well as the start of the downstream migration depends on both exogenous and endogenous factors (Tesch 2003; Bruijs & Durif 2009). It is generally assumed that silver eels begin their active spawning migration at the end of the silvering process (Acou et al. 2008). Beside the full completion of the silvering process, it was further shown that the start of the spawning migration is influenced by external environmental factors like discharge levels, weather conditions or moon phase (Tesch 2003). For example, increased migration rates were reported during periods of higher discharge levels together with high precipitation rates (Tesch 2003). Various studies also reported that high migration rates are associated with periods of low atmospheric pressure, sudden decrease in air temperature and decreased light intensity (Feunteun et al. 2000; Durif et al. 2003; Haro 2003; Acou et al. 2008; Bruijs & Durif 2009). The downstream migration of the silver eel is described as a seasonal phenomenon where concentrated seaward movements can be observed (Tesch 2003). Depending on the latitude and altitude, weather and discharge conditions, these migration peaks can occur between autumn and may and last until the early spring (e.g., van Ginneken et al. 2007; Bruijs & Durif 2009). Female silver eels tend to maximise size and migrate at an optimal body size, whereas males migrate at smaller sizes and younger ages compared with females (Helfman et al. 1987). Furthermore, due to variation in swimming speed associated with different sized silver eels (Palstra & van den Thillart 2010; Quintella et al. 2010), males should start their migration earlier than females to arrive simultaneously at the spawning ground originating from the same river system or region (van Ginneken & Maes 2005; Quintella et al. 2010).

However, in contrast to the well-studied mechanism of the upstream migration of glass eels, the downstream migration of silver eels remains less understood (e.g., Feunteun et al. 2003; Tesch 2003). The current knowledge on silver eel migration dynamics is based on only a few studies (e.g., Vøllestad et al. 1986; Poole et al. 1990; Haro 2003; Acou et al. 2008; Bilotta et al. 2011). Additionally, commercial fishery landings provide some information on silver eel migration dynamics (e.g., Vøllestad et al. 1986; Poole et al. 1990; Laffaille et al. 2006). Therefore, a more detailed understanding of the migration behaviour is needed for the development of more effective management measures that take into account, for example, the potential heterogeneous migration dynamics of female and male silver eels. To overcome these shortcomings, long-term standardised monitoring studies at different river systems are required.

Based on the implementation of the European eel regulation (EC 2007), we monitored the downstream migration of silver eels in a regulated lowland river in north-eastern Germany draining into the Baltic Sea. Referring to earlier silver eel migration studies, we hypothesised that the silver migration should be a seasonal phenomenon with migration peaks in the spring and autumn. It was further expected that we would detect different migration patterns between female and male silver eels indicated by time delayed migration peaks of both sexes. However, it is questionable if the predictions of previous studies would hold true in a regulated river system, as the natural flow dynamics are restrained. As the migration behaviour is influenced by various environmental factors, we also aimed to identify factors that are responsible for higher migration rates in a regulated river system.

Study area

The study was conducted at the Warnow River located in north-eastern Germany. The Warnow River has a total length of 161 km with an overall catchment area of 3230 km² where more than 200 lakes over 1 ha can be found (Selig & Schlungbaum 2002). Near the city of Rostock, the river is divided by a weir into two parts; the 148-km-long freshwater part and the brackish estuary connected to the Baltic (Selig & Schlungbaum 2002). The weir is primarily operated to provide drinking water and prevents the entrance of brackish water into the freshwater part. The freshwater part of the Warnow River represents a regulated slow-flowing lowland river (StÄLU (Staatliche Ämter für Landwirtschaft und Umwelt) 2013) with average current velocities of 0.05–0.10 m·s−1 (Selig & Schlungbaum 2002). Based on natural recruitment and stocking activities, eel is found in nearly all flowing and standing waters of the Warnow River system (Winkler et al. 2007). In the study area, eel is harvested by commercial and recreational fisheries (Winkler et al. 2007; Dorow & Arlinghaus 2009, 2011).

Material and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

Sampling programme

After a thorough evaluation of possible methodological approaches (see Bilotta et al. 2011 for possible approaches), a stow-net system with four fyke net-like bags was installed in the Warnow River (54°3′46′′ N; 12°10′43′′ E). Stow-net systems were typical commercial fishing gear in the study region to capture migrating silver eels in running waters. As the stow-net system was located shortly before the end of the freshwater part of the system, nearly the complete silver eel migration activity originating from freshwater habitats is detected by the monitoring system. The complete river width (45 m) was covered by the stow-net system. We were unable to fish the complete water column because boat traffic occurs at this river section. Depending on the water level, a distance of 2–2.50 m existed between the top of the stow-net system and the water surface, resulting in overall fished area of the river cross-section of 65–75%. The discharge rate varied between 2.1 and 57.8 m³·s−1 with a mean value of 18.2 m³·s−1 (StÄLU (Staatliche Ämter für Landwirtschaft und Umwelt) 2013). To avoid a collapse of the fishing gear at low water velocities, the 12-m-long stow-net bags were stretched by an anchor line. Based on the experiences of commercial fishers, we installed four chambers similar to fyke nets near the end of each stow-net, which prevented the escape of the eels. The mesh size was 10 mm resulting in a full selectivity of eel over 34 cm (Bevacqua et al. 2009). The monitoring programme on the silver eel migration was started in 2006. Necessary adjustments of the stow-net system (e.g., position in the river, modification of the weir net) were made in 2006 and 2007. Since 2008, the stow-net system was operated without any further adaptations allowing a comparison of fishing seasons from 2008 to 2011.

The selected stow-net system approach necessitated the removal of the monitoring instrument during periods of ice coverage (December until March of each fishing season, Table 1). Referring to previous studies (Vøllestad et al. 1986; Poole et al. 1990; Haro 2003; Klein Breteler et al. 2007; Acou et al. 2008; Simon et al. 2012; Verbiest et al. 2012) and a telemetry study of female silver eels in the Warnow River (Dorow et al. 2012), only minor migration activities can be expected during the winter months. To prevent damages of the fishing gear, the stow-net system was also removed during periods with unusually high discharge levels (Table 1). Additionally, the stow-net system was pulled out at water temperatures above 25 °C to avoid mortality induced by high water temperature (Table 1). Overall, the stow-net system was installed from mid-April to the beginning of December each year (Table 1).

Table 1. Eel harvest (monitoring period 2008–2011) at the monitoring station at the Warnow River, Kessin (Germany), shown as total eel harvest, number and percentage of yellow and silver eels; the proportion of female and male silver eels is based on the index of Durif et al. (2005, 2009); different letters indicate significant differences in the mean weekly silver eel harvest rate between the monitoring years based on the anova
YearFishing period (calendar week)Total number of yellow eelsTotal number of silver eelsMean silver eel harvest rate/weekNumber and percentage of male silver eelsNumber and percentage of female silver eels
  1. Stow-net system was removed during the calendar weeks 29–30.

  2. Stow-net system was removed during the calendar week 32–35 and 46.

200816–5233562616.9 (±22.6 SD)a244 (39%)382 (61%)
200911–5235269116.4 (±13.5 SD)a193 (28%)498 (72%)
201014–4714694629.6 (±24.2 SD)b284 (30%)662 (70%)
201111–5229898031.5 (±25.7 SD)b445 (45%)535 (55%)
Mean 283 (±93.1 SD)811 (±178.3SD)23.0 (±22.5 SD)292 (±7.9 SD)535 (±7.9 SD)

During the monitoring period 2008–2011, the stow-net system was controlled twice per week. The complete catch, including eel and other species, was recorded for each of the four bags separately (for analyses of the bycatch see Blume et al. 2011). All eels were held in an adequate fish tank installed close to the stow-net system in the Warnow River. Mortality of eels as a consequence of being caught by the stow-net system or holding was not observed during the 4 year monitoring period.

A standardised documentation of the eel harvest was carried out once a week. Before recording various morphometric parameters, eels were anesthetised with 2-phenoxyethanol. The length, total biomass, eye diameters and the length of the pectoral fins were measured to calculate the silvering stage according to Durif et al. (2005, 2009). The silvering stage (Durif et al. 2005, 2009) was computed for each eel directly during the inspection. To further characterise the eels, the differentiation of the lateral line (occurrence of black dots) and the formation of a colour contrast was visually assessed (Acou et al. 2005). According to the calculated silvering stage, the eel were marked with an elastomer colour (Curtis 2006; Imbert et al. 2007; Simon 2007; Delcourt et al. 2011; Simon & Dörner 2011) combination shortly behind the anus indicating the harvest year and the silvering stage (yellow or silver eel). Moreover, a tissue sample was taken from each eel for the molecular species identification (Frankowski & Bastrop 2010) to exclude anthropogenic introduced Anguilla rostrata from further analysis (Frankowski et al. 2009). After completion of the investigation, the marked eels were released 25 km above the monitoring station to conduct a mark–recapture experiment (Dorow & Ubl 2011).

During the stow-net controls, the water temperature was measured. Data on the daily water discharge level (m³·s−1) were provided by the STAUN MV. Information on various climate factors (e.g., air temperature, cloud amount, rainfall, atmospheric pressure) for the study period 2008 till 2011 was generated using the data recording of the nearest DWD (German Weather Service) station located in Warnemuende which is 20 km away from the monitoring station. The moon phases were classified in four stages (full, new, decreasing and increasing). All considered parameters (mean values or moon stage) were related to the monitoring fishing week.

Statistical analysis

The standardised fishing conditions during the fishing seasons (2008 until 2011) provided the basis for the analysis of the silver eel migration dynamics. In the analysis of the migration dynamics, only eel catches for the first time (unmarked fishes) and only eels of the species A. anguilla were included. The eel harvest for each silvering stage was summarised for the fishing week. The silvering stages FIII till FIV were pooled as female silver eels (Table 2). Silvering stages I and FII were summarised as yellow eels and the stage MII represented male silver eels (Table 2). The mean weekly migration rate for silver eels was calculated for each year separately (Table 1), based on the weekly migration rate per week. We used one-way anova with an appropriate post hoc test (Tuckey-B) to detect significant differences regarding the mean weekly harvest rate during the 4 year monitoring period.

Table 2. Mean values with standard deviation of various parameters for the different silvering stages (Durif et al. 2005, 2009); also the results of the visual evaluation of the presence of a colour contrast and black corpuscles on the lateral line are given; only unmarked European eels are included
 Stadium
IFIIFIIIFIVFVMII
N34977713741715311162
Total length (mm)397 (±32.6)538 (±71.4)657 (±79.6)857 (±64.1)625 (±91.2)413 (±24.8)
Weight (g)94.8 (±27.8)269.2 (±122.8)537.7 (±211.1)1298.4 (±276.6)462.0 (±215.6)120.6 (±32.6)
K (Fulton's condition factor)0.15 (±0.03)0.16 (±0.03)0.180 (±0.02)0.21 (±0.03)0.18 (±0.02)0.17 (±0.03)
Mean eye diameter (mm)4.2 (±0.7)5.6 (±0.6)7.3 (±0.7)10.1 (±1.0)8.6 (±1.0)6.9 (±0.8)
Presence of corpuscles (% yes)21.542.483.194.995.692.8
Colour contrast (% yes)47.560.483.794.993.996

A Spearman's rank correlation analysis was conducted to identify correlations between the observed weekly migration rates and the selected environmental factors. Afterwards, to account for potential correlations between environmental variables, we applied a principal component analysis (PCA with a varimax rotation) to all environmental variables to extract the main modes of environmental variability.

Finally, to determine the environmental conditions associated with high migration rates of overall silver eels, and specifically of both female and male silver eels, a decision tree analysis was applied. Decision tree, as a predictive analysis tool, is produced by classification algorithm that identifies various ways of splitting a data set into branch-like segments (deVille 2006). One of the most often applied classification procedure is the Chi-squared Automatic Interaction Detection (CHAID) tree analysis (Breiman et al. 1984; Gehrke et al. 1998; De'ath & Fabricius 2000; Magidson & Vermunt 2005). In the conducted CHAID analysis, all environmental parameters previously used in the correlation analysis were integrated. This segmentation technique represents an effective approach for obtaining meaningful segments that are predictive of a normal or ordinal criterion variable (Magidson & Vermunt 2005). This analysis is a recursive partitioning method that relates a potentially large numbers of predictor variables to a single dependent variable (Magidson & Vermunt 2005). The dependent variable is categorised by the CHAID algorithm (Kass 1980), resulting in a sequential merge and split procedure based on chi-square tests (Wilkinson 1992). The splitting procedure also indicates automatically the thresholds for the predictor variables and orders them according their importance on explaining the observed variability. Simply speaking, significant predictors can be identified explaining the variability of the dependent variable. The resulting graphical diagrams are suited to analyse complex ecological–environmental data (De'ath & Fabricius 2000). Trees form groups of cases with similar response values by repeated binary splitting (see Figs 2–4). Each of the terminal nodes is characterised by the mean value of the dependent variable, the number of cases in the group, the threshold of the predictor variable which formed the divisions leading to the groups. From the eel management perspective, the results of the CHAID analysis can be used to forecast under which environmental conditions high migration rates of silver eels are likely. All analysis was conducted with SPSS 18 (SPSS Inc., Chicago, Illinions, USA).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

In all 4 years, downstream migrating yellow and silver eels were observed (Table 1). Anthropogenic introduced American eels (= 35; 20 female and eight male silver and seven yellow eels), and recaptures of marked eel have been excluded from further analysis. A total of 4374 European eels were caught with a mean eel harvest of around 1100 eels per year (Table 1).

The different silvering stages varied regarding the morphometric parameters in the expected way (Table 2). For example, the undifferentiated eels (stage I) had the smallest length and weight as well as showed the lowest values on the eye diameter (Table 2). Except for the stage FV, the morphometric parameters increased from stage FII to FIV (Table 2), whereas the female silver eels of stage FIV had an average length of 857 mm and mean weight of nearly 1300 g. The female silver eels of stage FV were on average smaller in length, weight and mean eye diameter compared with the eels of stadium FIV (Table 2). Male silver eels had an average length of 413 mm and weight of 121 g. Overall, female and male silver eels were characterised by a higher Fulton′s condition factor compared with the yellow eel stages (I and FII). The presence of a colour contrast and the differentiation of the lateral line increased with the silvering stage (I–FV and MII, Table 2).

Beside the seaward migration of silver eels, also the downstream movement of yellow eels was documented in each year (Table 1). Except 2010, the number of caught yellow eels remained stable with an average number of around nearly 330 yellow eels per year (Table 1). In contrast, the number of the downstream migrating silver eels increased in the 4 year monitoring period (Table 1). For example, 626 silver eels were recorded in 2008, 3 years later 980 silver eels were documented. Overall, significant higher mean harvest rates per week of silver eel were observed in the years 2010 and 2011 compared with the years 2008 and 2009 (anova F = 5.02, d.f. = 144, < 0.05). Generally, in all four fishing periods, more female silver eels were observed (Table 1). However, the proportion of male silver eels changed, resulting in a nearly balanced sex ration in 2011 (Table 1).

Generally, the harvest rates of silver eels varied within the four monitoring periods (Fig. 1). Surprisingly, a continuous downstream migration of silver eels at a low level was detectable between April and December in each year (Fig. 1). Furthermore, in each year single migration peaks occurred which account for up to 30% of the total silver eel run in the specific year. However, these migration peaks appeared at different times during the 4 year monitoring period (Fig. 1). For example, in 2008 the highest downstream migration activity took place in May; in 2010, three events (April, September and November) of higher migration activities were documented (Fig. 1). The monthly analysis of the proportion of the different mature female silvering stages (FIII–FIV) indicated that stage FIII was predominant. Only during April 2008, November 2009 and November 2011, the percentage of the stage FV was higher than the fraction of stage FIV. The mean fraction of stage FIII during the 4 year monitoring period was 66.4% with a range of 32.7–98.6% per month. Stage FV occurred with a mean proportion of 25.1% per month (range 0 till 60%). Compared with the stages FIII and FV, the stage FIV was observed at a minor level with average rate of 8.5% per month (range 0 till 32.4%).

image

Figure 1. Temporal variation of overall silver eel harvest rates on a weekly basis observed in the Warnow River during the monitoring period 2008–2011. Differences of harvest rates of female and male silver eels are shown separately.

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The sex determination of silver eels (Table 2) allowed for the separate examination of the downstream migration dynamics of female and male silver eels (Fig. 1). In all 4 years, a continuous migration of both female and male silver eels was detected at low level (Fig. 1). However, downstream movements were not fully simultaneous (Fig. 1). For example, periods with simultaneous downstream migration activities of both sexes were documented during spring 2008, 2009 and 2011. Further, simultaneous migration peaks of female and male silver eels occurred in the winter of each year, and a clear autumn migration peak for both sexes was detected in 2011 (Fig. 1). In contrast, time-delayed migration activities appeared in the summer and autumn of the years 2008, 2009 and 2010 (Fig. 1). Especially, the migration dynamics in the second half of 2009 indicated that increased migration rates of female silver eels can occur during a period of very low male migration activities (Fig. 1).

To test relationships between environmental factors and the migration activities of silver eels in the Warnow River (Fig. 1), the weekly harvest rates were correlated with various environmental parameters (Table 3). No significant relationship was found for the influence of the moon phase, mean atmospheric pressure, change in atmospheric pressure, wind velocity and precipitation amount on the overall migration activity or the migration dynamics of female and male silver eels. The overall silver eel harvest rate correlated positively with the water temperature, air temperature and the temperature range in 1 week (Table 3). The relationship between overall silver eel migration rate and the parameters cloud amount and relative air humidity negatively correlated (Table 3). It was further found that female and male silver eel migration activities differed in their relationship to the tested environmental factors. For example, a significant relationship between water temperature and migration rate was only detectable for female silver eels (Table 3). In contrast, the harvest rate of male silver eels was more strongly affected by the discharge level. Furthermore, the migration dynamics of female silver eels seem to correlate in a higher degree with the air temperature parameters (Table 3). Otherwise, for both sexes, significant correlations were provable for the linkage between harvest rate and the parameters cloud amount and relative air humidity.

Table 3. Correlation coefficients between the weekly harvest rates (overall, female and male silver eels) and different environmental factors and regression factors, respectively
Parameter (on week basis)Correlation coefficient (Spearman-rho)
Overall silver eel migration activityMigration activity of female silver eelsMigration dynamics of male silver eels
  1. Only significant factors are shown; *= < 0.05, **= < 0.01.

Water temperature0.346**0.336**0.143
Mean discharge level0.04−0.090.262**
Mean cloud amount−0.164*−0.165*−0.201*
Mean relative air humidity−0.225**−0.199*−0.188*
Mean air temperature0.326**0.349**0.083
Mean minimum air temperature0.382**0.390**0.125
Mean maximum air temperature0.384**0.364**0.183*
Mean difference between minimum and maximum air temperature0.266**0.203*0.252**
Regression factor temperature0.341**0.354**0.071
Regression factor temperature difference0.143*0.1040.219**
Regression factor atmospheric pressure−0.089−0.078−0.012

The principal component analysis resulted in three major components explaining nearly 60% of the observed variances. The first factor included all air and water temperature variables; factor 2 consisted of the indicators reflecting the degree of temperature differences; and factor 3 based on the atmospheric pressure parameters (Table 3). The resulting regression coefficients of the temperature component correlated positively with the overall migration rate and the migration activity of female silver eels (Table 3) underlining the influence of the temperature on seaward movement of silver eels. Further, the degree of change in the air temperature (regression factor 2) also correlated positively with the overall migration rate and migration rate of male silver eels. No significant correlations were found for the identified atmospheric pressure component.

By means of the CHAID analysis, the minimum air temperature peer week was identified as the most important predictor of the overall silver eel migration rate (Fig. 2). Higher harvest rates were associated with minimum air temperatures over 10.4 °C. The mean discharge level was the second most important factor if the minimum air temperature exceeded 10.4 °C. Significant lower migration activities were likely during periods with discharge levels less than 6.4 m³·s−1; whereas discharge levels of over 6.4 m³·s−1 tend to result in higher downstream movement activities. The nodes 5 and 6 indicated that during periods of low discharge levels, the harvest rate was positively linked to the mean air temperature (Fig. 2). Under conditions with a minimum air temperature over 10.4 °C and a discharge level over 6.4 m³·s−1, the nodes 7 and 8 reflected further the influence of the mean wind velocity on the migration rate. Periods with a mean wind velocity under 4.3 m·s−1 were associated with higher overall harvest rates compared with weather situations with higher average wind speeds.

image

Figure 2. Classification tree analysis Chi-squared Automatic Interaction Detection (CHAID) of the mean silver eel harvest rate per week (±SD) indicating the influence of various environmental factors on the migration activity which resulted in the nodes 0–8. The top node contains the entire samples (100%); all further nodes contain a subset of the sample. Number of events per week (n) and percentages are split into the subordinated nodes below as well as the identified predictor variable responsible for the splitting is shown. Predicted values indicate expected values of mean harvest rate peer week.

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For female silver eels, the precipitation amount was identified as the most important predictor variable (Fig. 3). When rainfall exceeded 26.5 mm/m2*week, higher migration rates of female silver eels were likely. During periods with minor weekly precipitation amount, the mean cloud amount seemed to further influence the migration rate of female silver eels, whereas higher migration rates were associated with periods of low cloud amounts. Similar to female silver eels, the cloud amount was first predictor variable for the harvest rates of male silver eels. Higher migration rates occurred during periods with a mean cloud amount less than 4.7 (Fig. 4). During periods with higher cloud amounts, increasing discharge rates positively influenced the migration activities of male silver eels.

image

Figure 3. The variation of the mean harvest rate per week (±SD) of migrated female silver eels in the regulated lowland Warnow River was investigated using a Chi-squared Automatic Interaction Detection (CHAID) tree analysis. Based on the CHAID, the nodes 0–4 were identified indicating the most important environmental predicator variables for the female migration activity. The node at the top contains the total sample (100%), and further nodes reveal a subset of the sample. Every node contains the number of events per week (n) and percentage which resulted from the splitting procedure. Expected values of mean harvest rate peer week were given as predicted values.

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image

Figure 4. Classification tree analysis Chi-squared Automatic Interaction Detection (CHAID) of mean harvest rate per week (±SD) for male silver eels; the identified nodes 0–4 show the most important predictor variables for the male silver eel migration activity. Each node shows the number of events per week (n) and percentage which are partitioned into the two nodes directly below. Predicted values are expected values of mean harvest rate peer week.

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

According to the European eel recovery action plan (EC 2007), the member states are requested to monitor the different life stages of the European eel on river basin scale (EC 2007). Because the target of the European eel regulation is linked to the development of the silver eel escapement (EC 2007), a special focus exists on the modelling or experimental quantification of the annual silver eel escapement (Bilotta et al. 2011). Against this background, we used an experimental stow-net system approach to monitor the downstream migration of silver eels in a regulated lowland river in north-eastern Germany. After the necessary adjustments, the installed stow-net system turned out to be a reliable monitoring instrument for the downstream migration of eels during the time period 2008 until 2011.

During the monitoring period 2008–2011, downstream migrating female and male silver eels as well as yellow eels were document in each year. The morphometric parameters of the different silvering stages were consistent with the values presented by Durif et al. (2009). At the same time, the presented percentage of the presence of the colour contrast and the differentiation of the lateral line for stages I and FII indicate that the exclusive use of these visual criteria would cause an underestimation of the proportion of yellow eels (compare Ubl & Dorow 2010; Dorow & Ubl 2012).

The occurrence of the American eel A. rostrata (Le Sueur) in the study area was caused by stocking activities in the yearly 2000er years (Frankowski et al. 2009). The European eel and the American eel are characterised by many similarities regarding their life history, morphology and ecological claims. Using a mark-recapture approach Prigge et al. (2013) were able to show that mature American female eels are able to actively migrate to the outlet of the Baltic Sea. Our study adds to the migration behaviour of incorrectly stocked American eels by showing that mature American silver eels also actively perform the downstream migration.

The observed downstream migration of yellow eels can be primarily linked to two behavioural patterns. On the one hand, it is known that yellow eels have a home range (Baras et al. 1998) and were therefore captured during their regular feeding migration. On the other hand, different life-history strategies of yellow eels have been identified where regular migrations between freshwater and brackish water can occur (Daverat & Tomás 2006; Shiao et al. 2006; Lin et al. 2007). Therefore, it is conceivable that the detected downstream migration of yellow eels can be related to active movements between freshwater and coastal waters. More detailed investigations (telemetry studies or microchemical analysis of the otoliths) would be needed to identify the dominant behavioural pattern of the yellow eel migration behaviour in the Warnow River.

During the 4 year monitoring period, we found an increasing trend in the total number of seaward migrating silver eels as well as in the weekly migration rate. Assuming a constant recruitment mainly based on continuous eel stocking activities in the connected lakes upstream the monitoring station (Ubl & Jennerich 2008), this trend was unexpected and provided the first indication of the variation of the downstream migration dynamics of silver eels in the Warnow River. Regarding stocking as the primary recruitment source (Ubl & Jennerich 2008) in the study area, a minor fluctuating sex ratio of the migrating silver eel was expected (compare Laffaille et al. 2006). However, we found a decreasing proportion of female silver eels caused by increasing numbers of male silver eels. One possible explanation of the sex ratio change might be the increase in the minimum size limit for eels from 45 to 50 cm in the year 2009, which may limit the commercial and recreational harvest of male silver eels. At the same time, the varying proportion of female and male silver eels during the 4-year monitoring period might also indicate that the downstream migration of both sexes is triggered differently by environmental factors.

Generally, the downstream migration of silver eels is considered as a seasonal phenomenon, which occurred in spring and between September and December each year (e.g., Vøllestad et al. 1986; Poole et al. 1990; Haro 2003; Acou et al. 2008). In agreement with these previous studies, we observed single migration peaks in all 4 years (2008–2011). However, beside the expected high migration periods (spring and autumn), silver eel migration peaks were also recorded in the summer (e.g., July 2009, June 2011) or in winter with water temperatures less than 5 °C (December 2008, 2009 and 2011). The increased downstream migration activities during spring can be attributed to mature silver eels that stop their seaward movement at a specific point in the winter and wait for improving migration conditions in the next spring (Acou et al. 2008).

The observed continuous downstream migration as well as the increased migration rates during the summer months might be related to the previously described temporally discontinuous spawning migration of mature eels (e.g., Aarestrup et al. 2008). Accordingly, silver eels are able to detect beneficial downstream migration conditions all year and can therefore conduct their seaward movement outside of the expected high migration periods. Especially, during the silvering stage FIII, eels seemed to be able to migrate under a wide range of environmental conditions. Referring to Aarestrup et al. (2008), summer downstream migrating silver eels use advantageous conditions to leave the freshwater habitat and stay afterwards in the coastal waters until the autumn to continue the spawning migration out of the Baltic Sea. This behavioural pattern of a ‘stopover’ in coastal or brackish waters was also observed for female silver eels in the Warnow River using a telemetry experiment (Dorow et al. 2012).

The beginning of the spawning migration is supposed to relate to the geographical place of the continental life phase ensuring that seaward migrating eels arrive almost at the same time in the spawning area (van Ginneken & Maes 2005). Based on the total area of the Warnow River system, a major influence of the geographical place on the observed migration dynamics can be excluded. It is more likely that the observed migration peaks are caused by beneficial downstream conditions. In previous studies, concentrated migration peaks were linked to favourable environmental conditions like discharge levels, specific weather conditions or the moon phase (Tesch 2003). Generally, the explorative correlation analysis revealed various environmental parameters, which positively or negatively influence the overall migration dynamics. In contrast to previous studies (e.g., Cullen & McCarthy 2003; Tesch 2003; Acou et al. 2008), some exceptions regarding the relationship between migration rate and the tested environmental factors were found. Furthermore, the tested migration triggering factors seemed to influence the activity of female and male silver eels differently.

The discharge level was previously identified as one of the primary triggers of the silver eel downstream migration, whereas higher migration rates were associated with high run-off events (e.g., Feunteun et al. 2000; Haro 2003; Jansen et al. 2007; Bruijs & Durif 2009). The results of the correlation analysis partly support these findings as the weekly male silver eel harvest rates positively correlated with the discharge amount. However, the nonsignificant linkage between discharge level and the overall silver eel migration as well as the female silver eel migration rate might indicate that the migration intensity of mature female eels is less affected by the discharge level in regulated river systems. In contrast, the CHAID analysis revealed that the discharge level was the second most important predictor for the overall silver eel migration and confirmed the linkage between discharge and the male silver eel migration rate. Therefore, we conclude that the discharge level in a regulated river (determined by rain events, water demands or water level needs) can be seen as one of the major environmental factor for the seaward movement activity of silver eels.

Generally, silver eel migration occurred over a broad temperature range in the Warnow River, which is in agreement with previous studies (Vøllestad et al. 1986; Bruijs & Durif 2009). In contrast to Vøllestad et al. (1986), we also found a positive relationship between various indicators of the temperature (air and water temperature) and migration rate. However, our results also suggest that silver eels are sensitive to short-term temperature changes, which were previously shown by Haro (2003) and Bruijs & Durif (2009). These findings are confirmed by the principal component analysis that exposed two temperature factors which correlated with the silver eel migration activity. Moreover, the influence of the temperature on the migration activity was displayed by the CHAID analysis for the overall migration rate.

It is well accepted that eels are strongly photophobic and the light intensity influences the seaward migration activity of silver eel (see Bruijs & Durif 2009). However, the influence of the moon phase remains unclear (see Bruijs & Durif 2009). On the one hand, several publications highlighted the relationship between moon phase and migration activity (Boetius 1967; Tesch 2003) showing that silver eel movements mainly occur during the last quarter of the moon cycle (Tesch 2003). On the other hand, the influence of the moon phase is often questioned by other studies (Deelder 1954; Haraldstad et al. 1985; Vøllestad et al. 1986; Bruijs & Durif 2009) failing to link moon phase and high migration events. In the Warnow River, no significant relationship between moon phase and migration rate was detectable supporting the studies questioning the influence of the moon phase on the migration rate (Deelder 1954; Haraldstad et al. 1985; Vøllestad et al. 1986; Bruijs & Durif 2009). Accordingly, it seems likely that the migration rate depends to a higher degree on the light intensity (Bruijs & Durif 2009). The light intensity is controlled, for example, by water turbidity and cloudiness. The linkage of both factors on the migration activity of silver eels was previously discussed (Durif et al. 2003; Durif & Elie 2008). By means of the CHAID analysis, the cloud amount was identified as a predictor variable for the migration rate, particularly for female silver eels. In contrast to previous studies (Durif & Elie 2008; Bruijs & Durif 2009), in the Warnow River, higher migration rates were more likely under conditions with low cloud amounts.

Specific atmospheric or weather conditions are known to cause higher migration rates (Bruijs & Durif 2009). For example, atmospheric depressions during storm periods can induce higher migration rates. However, no significant correlations were found in our study between migration rate and wind speeds as well as the tested atmospheric pressure parameters (including the regression factor identified by the principal component analysis). Therefore, it might be the case that atmospheric changes have only a nondetectable minor influence on the migration activity in regulated lowland rivers like the Warnow River. In contrast, the amount of rainfall was significantly linked to the migration activity of female silver eel as higher harvest rates were more likely over a certain weekly rain level.

The different swimming performance of both sexes (van Ginneken & Maes 2005) might further add to the varying migration dynamics of female and male silver eels. Therefore, periods with time-delayed peaks of female and male silver eels might be caused by the fact that both sexes need to start their spawning migration at different times to arrive at the same time at the spawning ground. However, we also observed simultaneous peaks of higher migration rates of female and male silver eels, which contradict the single factor explanation of the swimming speed on the silver eel migration dynamics. Accordingly, the silver eel migration activities can be seen as a complex interplay of individual characteristics and environmental parameters, whereas the river characteristics contribute to the variation of the migration dynamics.

Several methodical limitations need to be mentioned that are associated with the survey method or the simplifying assumptions. For example, the assumption of a constant sex ratio of eels in the freshwater area upstream of the monitoring station needs to be tested to eliminate this potential bias source on the evaluation of the migration dynamics. Further, we cannot exclude a downstream migration during ice coverage. Using a telemetry experiment, we were able to show only minor migration activities of female silver eels at water temperatures less than 3 °C (Dorow et al. 2012). Therefore, it is likely that male silver eels also stop migrating below a certain water temperature threshold. As the migration activity is triggered by the discharge level, which also impact the water level, the fishing efficiency of the stow-net system might vary with different discharge rates. So far, our results indicate that the stow-net system operates during a wide range of discharge rates with minor changes of the water level. Only during unusual run-off events does the stow-net system need to be removed so that silver eels could not be detected.

Conclusion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

The presented results show that the quantification of the amount of silver eels during the presumed migration window (spring and autumn) would cause an underestimation of the annual silver eel escapement. Hence, future monitoring programmes, particularly in slow-flowing and regulated rivers, should ensure that silver eel monitoring programmes are conducted throughout the year. The observed continuous downstream spawning migration, together with the simultaneous and time-delayed migration peaks of female and male mature eels, further suggests that the downstream migration behaviour of the European eel is characterised by a higher plasticity than previously assumed. Despite individual criteria, various environmental factors were shown to influence the spawning migration of silver eels in a regulated lowland river. By means of the CHAID analysis, environmental conditions were identified where higher migration rates are likely. By knowing these high migration windows, more efficient management strategies can be developed if necessary separately for female and male silver eels.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

The project was funded by the European Union and the State of Mecklenburg-Vorpommern. The field work was conducted in cooperation with the Association of Fish and Environment of MV. We thank all persons who helped out during the field work, especially Sabine Jennerich and Dietmar Lill. The StAUN MV provided water discharge level data. We appreciate the suggestions of two anonymous reviewers and the associated editor who helped us to improve an earlier version of the manuscript. We thank Jessica Beardmore for the cross-check on the language.

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  3. Introduction
  4. Material and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References
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