How much hatchery-reared brown trout move in a large, deep subalpine lake? An acoustic telemetry study

doi:10.21203/rs.3.rs-4316469/v1

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How much hatchery-reared brown trout move in a large, deep subalpine lake? An acoustic telemetry study

https://doi.org/10.21203/rs.3.rs-4316469/v1

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Fish movement into large, deep lakes has been rarely investigated due to the complexity and extent of such ecosystems. Among the different monitoring methods available, acoustic telemetry enables to study spatial ecology of aquatic organisms and to investigate their behavior in lentic environments.

In this study, movement of 69 hatchery-reared adult brown trout (size 43–61 cm) marked with acoustic transmitters was monitored in the large and deep subalpine Lake Lugano (Switzerland and Italy). Trout were tracked for six consecutive months by 7 hydrophones (April-August 2022), positioned in a non-overlapping array.

Trout movement was reconstructed using R packages specific for acoustic telemetry (Actel and RSP), which also allowed to translate tracking information into utilization distribution (UD) areas for each fish.

The effects of different environmental variables (rainfall, water discharge of the two main tributaries of Lake Lugano, atmospheric pressure, cloud coverage and moon phases) on trout movement was tested, but none of these variables seemed to correlate with fish movement.

Although trout marked with acoustic transmitters were hatchery-reared fish, the extent of their total movement throughout the study period was unexpected, with many trout moving for more than 100 km in few months.

The extent of such movement patterns is potentially related to an explorative behavior, which is more pronounced in hatchery-reared fish due to their more aggressive and bolder attitude.

The association of these behavioral traits, shaped by domestication, could expose hatchery-reared fish to higher risks and post-release mortality in the wild.

Acoustic telemetry

fish movement

brown trout

stocking

spatial ecology

Animal telemetry technologies have increasingly advanced in recent years, providing new and easy-access ways to study animal movement over large areas (18, 50, 64). Acoustic tracking or telemetry is one the most used methods for studying animal spatial ecology over a range of habitats and taxa, especially in aquatic environments (18, 37, 49, 52). It has been widely used for long-term studies on fish movement at small or large scale (36), to quantify fish stock structure (75), migratory routes (17, 112), and habitat utilization in response to abiotic and biotic stimuli (14).

Despite acoustic telemetry is a well-established approach for these types of studies, its application over large spatial areas requires great investments both in economic and operative terms (50). For this reason, most of the telemetry studies carried out so far have focused either on small study areas or on specific portions of large aquatic environments, such as bays or fjords (34, 35, 77, 95). A few studies have investigated fish movement in deep large lakes, due to the complexity and extension of such ecosystems (2, 50). However, studying movement of fish species relevant either for conservation and/or human activities (such as commercial and recreational fishing) can reveal important information about their behavior, ecological needs and environmental constraints (73, 80).

Fish stocking is still a common practice in almost all freshwater ecosystems (8, 99), thus, studying movement of stocked fish in the wild could help to evaluate stocking effectiveness, also in relation to harvesting (73). As a result, rearing and stocking programs could be adjusted to apply proper management strategies to meet fishery needs as well as reaching conservation targets (27, 28, 73).

Among freshwater fish brown trout (Salmo trutta Linnaeus, 1758) play a significant role in sustaining professional and recreational fisheries all over the world (11, 79), representing a remarkable economic income (45). Brown trout economic relevance has led to a massive introduction of this species in both lentic and lotic environments to increase fisheries yield and/or to restore wild populations (24, 78, 84, 97). Stocking brown trout is carried on at different life stages (eggs, larvae, alevins, adults) depending on local needs and hatchery production capacity (10, 62). Hatchery-reared trout are commonly released at adult stages, since they increase the number of catchable fish both in the short and long term (10). Releasing hatchery-reared trout at adult stages has the advantage to reduce predation pressure exerted by birds and other piscivorous fish since larger sizes are usually associated with lower predation risks (106). On the other hand, fish reared in tanks are subjected to domestication processes, which can be more pronounced as time spent in captivity increases (47, 60).

Domestication can affect both fish behavior and phenotype (55, 82, 91, 94). For example, domestication selects sedentary individuals that invest more in growth rather than in movement, which is also a consequence of the low flow rate conditions in the hatchery tanks (20, 32, 98). Furthermore, space limitation and over-density conditions of the rearing environment heavily reduce domesticated fish swimming performances (90, 91). Domestication can also cause a selection of individuals being more aggressive, explorative and bolder than their wild counterpart (54, 55, 106), showing an association of behavioral traits known as “behavioral syndrome”, i.e. a suite of behavioral traits that tend to co-vary together in different situations (26, 103, 105).

Predator-free rearing environments cause as well a selection of bolder individuals that tend to show relaxed antipredator behaviors once released into a wild environment, reducing predator vigilance and promoting exploratory attitudes (6, 33, 55, 59, 106). Moreover, larger and older hatchery-reared fish have elevated energetic demands compared to younger counterparts, increasing their willing to take exploratory risks in order to search for feeding opportunities (3, 59, 106). Risks associated to predation are reduced for larger individuals (43, 89, 106) however, the trade-off between benefits associated with exploration and the high energetic costs of travelling long distances can influence the post-release survival of adult hatchery fish (59). Another downside of the distinct aggressiveness and boldness of hatchery-reared fish is their higher vulnerability to hook and line capture (63, 107). Exploratory behavior can as well expose fish to a greater risk of capture by different fishing gears such as gillnets used by professional fishermen (19, 86).

In this study, we used a fine-scale acoustic telemetry array to monitor the movement of adult stocked brown trout over a large and deep peri-alpine lake (Lake Lugano). This study was conducted over six consecutive months (March-August 2022) using fixed station array. Specific objectives were to: (i) assess the fate of stocked adult brown trout by monitoring their movement and its extent in the lake, (ii) identify possible differences in behavioral strategies based on the daily home range (95% of space use) patterns across the study period, (iii) determine whether space use was influenced by environmental factors such as rainfall, water discharge of the main tributaries in the study area, atmospheric pressure, cloud coverage and moon phases.

Movement and fate of hatchery-reared adult trout was expected to be deeply influenced by domestication effects, negatively affecting adaptation success to a wild environment (22).

Study area

Lake Lugano is a natural lake located at the southern fringe of the Central Alps, on the border between southern Switzerland and northern Italy (Fig. 1).

Lake Lugano has a catchment area of 565.6 km² and is characterized by a humid temperate climate known as “Insubric climate”. Winters are mild (January average daily temperature = 3.3°C), summers are hot and humid (July average daily temperature = 22.1°C), and yearly precipitation is high (annual average = 1559 mm). Because of the mild winters, the lake remains ice-free throughout the winter (40).

It is fed by numerous small mountain streams, among which the most important are Vedeggio, Cassarate and Cuccio, while its main outlet is Tresa River, which connects Lake Lugano to Lake Maggiore.

Lake Lugano is a relatively large lake with a surface area of 48.9 km², 63% of which belongs to Switzerland and 37% to Italy. It has an average width of roughly 1 km and a maximum width of about 3 km at the bay of Lugano. It lies at 271 m above sea level and its maximum depth is of 288 m (23).

The lake is divided into 3 main basins. The northern basin and the southern basin, divided by a natural moraine, and finally the small Ponte Tresa basin (74).

The northern basin is the largest (27.5 km²), the deepest (max. depth = 288 m, medium depth = 171 m) and the one with the longest renewal time (12.3 years). It has a meromictic regime due to the process of eutrophication that started in the second half of the last century (12). Epilimnic water temperature during summer thermal stratification reaches 16–18°C, while hypolimnic water is steady throughout the year with a temperature of 6°C (12, 76).

The southern basin is smaller (21.4 km²), shallower (max. depth = 95 m, medium depth = 55 m) and has a short residence time (1.4 years). This basin has a monomictic regime therefore it turns over at the end of every winter (12, 76) when temperature reaches 5–6°C along all the water column. Thermal stratification starts in April and extends until the end of the year. Epilimnetic water temperature during summer exceed 24°C (with a peak of 27°C recorded in 2018) while hypolimnetic water is more stable due to stratification with a temperature of 6.5°C.

Ponte Tresa basin is the smallest (1.1 km²), the shallowest (max. depth = 50 m, medium depth = 33 m) and has renewal time of 0.4 years. It is characterized by a monomictic regime, with a complete mixing around February and March when temperatures reach 5–6°C along all the water column. Epilimnetic temperature can reach 24°C during summer while hypolimnetic temperature is relatively more stable with temperature that range from 4.5°C to 6.5°C (111).

Study species and tagging procedure

The studied species is brown trout Salmo trutta Linnaeus, 1758. Brown trout is a Salmonid native of the Atlantic, North, White and Baltic Sea Basins, from Spain to Chosha Bay (Russia), it is also present in Iceland and Great Britain. It is native also to the upper Danube and Volga drainages. Due to its importance in aquaculture and sport fisheries, it is one of the most frequently reared species among freshwater fishes. As a consequence, its original distribution has been altered by human introductions outside its natural range in Europe, North America, southern and montane eastern Africa, Pakistan, India, Nepal, Japan, New Zealand and Australia (11, 70).

It usually inhabits cold streams, rivers, lakes and also many anadromous populations are known. The tolerance towards temperature (0.0–26.0°C depending on life cycle stages; Elliott and Elliot 2010), salinity (0–35‰), pH (5.0–9.0), dissolved oxygen (2.5–8.6 mg L^-1; (85)) and other abiotic factors are the reason of its complex ecology. Thanks to this ecological plasticity, brown trout con be found in three main ecotypes: anadromous, lacustrine and resident.

This study was conducted on stocked fish coming from the hatchery located in Maglio di Colla, Lugano (Switzerland). Only fish larger than 40 cm were selected for the surgical implantation, following the tag-to-body weight ratio of 2% (58, 116).

Sixty-nine fish were tagged, measured (total length; mean ± SD = 540 ± 37 mm, min = 430, max = 610) and weighted (total weight; mean ± SD = 2101 ± 407 g, min = 1191, max = 2979). T-Bar tags (red color) were externally implanted in the dorsal part of the fish for immediate identification in case of recapture.

After these steps, fish were implanted with internal acoustic transmitter (LOTEK MM-R-11-28, approx. 202 days battery life with 60 s pulse rate, frequency = 69 kHz, weight = 10.0 g, size (ØxL) = 12 x 60 mm; MM-R-11-45, approx. 1573 days battery life with 60 s pulse rate, frequency = 69 kHz, weight = 14.0 g, size (ØxL) = 12 x 72 mm). The tag implantation procedure followed the one adopted by previous acoustic telemetry studies (13, 21, 87). Every fish (on an empty stomach) has been anesthetized with eugenol solution (0.2 mg L^-1) until loss of equilibrium. Fish were placed in a v-shaped tagging support, the transmitter was surgically implanted into the body cavity through a small incision (< 15 mm) made with a cutfix stainless scalpel #10 and then the incision was closed with a sterile synthetic absorbable surgical suture. All fish were kept in the hatchery for a week after tagging and before release to monitor the recovery from tagging procedure.

Fish were then randomly divided in four groups and released in four different sites (Fig. 1).

Acoustic receiver network

Seven acoustic telemetry receivers (LOTEK WHS 6000L − 69 kHz, weight in air = 1 Kg, size (ØxL) = 60 x 370 mm, 4 x D-cell lithium batteries with a life of 6–10 month) were positioned in seven different locations (Fig. 1). Receivers were deployed in a non-overlapping array because of the large surface area of Lake Lugano.

Receivers were placed in strategic locations such as obligated passages (Ponte Tresa, Diga Nord and Diga Sud) or at river mouths (Vedeggio, Magliasina, Maroggia, Cassarate) (Fig. 1).

Detection range could vary from 150 m to 500 m depending on thermal stratification, wave height and signal code collision (18). To reduce as much as possible the effect of thermal stratification on detection range, all receivers were placed at the same depth of 15 m.

Six receivers were mounted on the mooring chains of pre-existing buoys, except for the one located in Ponte Tresa channel that was fixed on a pole positioned on a submerged shoal. All receivers were attached to supports with cable ties, mounted upright with transducer oriented towards the surface (31).

The coordinates of every receiver station were recorded with a GPS (Global Positioning System) receiver.

Data processing

Receivers were retrieved on the 27th of August 2022 with the help of the Cantonal Police of Ticino.

Data from receivers were downloaded using the WHS Host software (WHS Host x64 Build, v1.5.2870.1, Lotek Wireless Inc. 2012). Raw detection data were saved as.csv and then manually filtered to select only detections belonging to tagged animals. All following steps in data processing were done with R version 4.2.2. using the R package actel (39). Duplicated detections and detections that did not fall within the deployment period (March-August 2022) were removed.

Possible detections created by acoustic tag collisions (interference between multiple overlapping transmission; (50, 104)) or ambient noise (30) were tested. If an animal was detected by two different receivers consecutively and the time interval between detections was shorter than the time needed for the fish to swim between the two locations, the second detection was removed. This process was done manually inspecting temporary files created by actel function explore(). In addition, receivers placed in the proximity of forced passages were also used to validate fish movement among stations.

Mortality assessment

The different criteria commonly used to assess mortality in fish telemetry studies are: amounts of detections, cease in detections, stationary or variable horizontal space use (65), stationary or variable depth use, stationary or variable acceleration, harvest info or observation of fate and predation evidence (67).

In this study, the criteria used to assess mortality were limited to cease in detections, stationary or variable horizontal space use and harvest info and/or observation of fate.

Distances calculation

To assess brown trout movement and its extent in Lake Lugano the total and daily distances travelled were calculated using the R package RSP (88).

The function runRSP() was used to compute the overall shortest in-water path. This function splits fish movement into tracks, which are formed if a fish is not detected for a minimum or maximum time by a receiver. To calculate the total distance covered by each individual during the study period min. time was set to 10 minutes and max time to 300 hours. The length of the total RSP track was then calculated for each fish with the function getDistances().

Daily distance travelled by each fish was instead calculated with the function runRSP() setting the min. time to 10 minutes and the max. time to 24 hours. Based on these values, tracks were split if a fish did not move between receiver within 24h, thus, a fish moving repeatedly for more than one day could have tracks lasting multiple days. In order to standardize daily distances travelled by each fish, the length of each track calculated by the function getDistances() was divided by the number of days of the track.

Utilization distribution (UD)

Utilization distribution represents the likelihood for a studied organism to occupy a point in the space at any given time, in this case it can be seen as a measure of the relative time spent by a fish at a certain point during the study period (66).

Daily UD was calculated for each individual using a dynamic Brownian Bridge Movement Model (dynBBMM). The BBMM applies a conditional random walk between successive pairs of locations considering time between locations, distance between locations and Brownian motion variance (related to animal mobility; (51)). In addition, the dynBBMM considers the time differences between sampled positions and their respective accuracy providing a more accurate utilization distribution that better describes the use of space (71).

Data were analyzed with the R package RSP (88). First, the daily track travelled by each individual was calculated using the function runRSP() setting a min. time of 10 minutes and a max. time of 24 hours, to compute the daily shortest in-water path. The daily path travelled by each fish (track) was then used to calculate the dynBBMM with the function dynBBMM() with timeframe argument set to 24 hours. Daily UD were obtained for each fish and then core areas (50% UD; area of most intense use) and extended range areas (95% UD; area of less intense use) were calculated with the function getAreas().

Statistical analysis

Functions included in the R package ts2net (38) were used to transform one or multiple time series (daily UD for each fish) into networks. A network represents time series by nodes, which are clustered together in case of similarity.

The distance between every pair of time series is calculated using a cross correlation function and stored in a distance matrix D. Then, this distance matrix is transformed into an adjacency matrix A from which a nearest neighbor network (Є-NN network) is constructed. The network allows to identify cluster of individuals with common spatial behavior.

The correlation between each individual daily UD and daily values of some abiotic factors potentially affecting fish behavior was tested using Pearson correlation coefficient. Correlation with rainfall, atmospheric pressure (Lugano Weather Station), cloud cover, lunar phases (data referred to Lugano location by interpolation of values from multiple stations) and water discharge of Vedeggio and Cassarate stream (the two main tributaries in the area covered by receivers) was investigated. Environmental data were downloaded from the Environmental Observatory of Switzerland (117)and from Visual Crossing: Weather Data and Weather API (118).

Sample description and mortality

Following data filtering, distances and UD calculations (see Fig. 2 for an example of UDs), the dataset used for the analysis included a total of 18 individuals.

51 fish were excluded from the analysis based on the mortality criteria listed above: 33 fish (48%) were excluded because their detections ceased during the study period (see Fig. 3.a for an example), 12 fish (12%) because were captured and retained by recreational/professional anglers, 5 fish (7%) because they were never recorded, whereas 1 fish because it stationed for the entire study period in one location (see Fig. 3.b for an example) suggesting its potential death. Cease in detection observed for some fish could also be linked to their movement in an area not covered by receivers but, in order to standardize the dataset and avoid misinterpretations in behavior, only fish detected for the entire study period were analyzed.

Brown trout movement: travelled distances

The average total distance travelled by the analyzed trout was 137.6 ± 124.5 km (mean ± SD; calculated as the mean of total distance covered by each individual). 55% of the fish travelled more than 100 km during the study period whereas the fish that moved the most travelled for 410.9 km (Fig. 4.a).

The fish with the highest movement rate (average daily distance travelled) travelled 3.8 ± 3.7 km d^− 1 (mean ± SD; calculated as the mean of daily distance travelled by each individual; Fig. 4.b) whereas the average movement rate among the analyzed fish was 1.5 ± 1.2 km d^− 1 (mean ± SD). Instead, the highest maximum daily distance measured among individuals in the sample was 15.8 km.

Brown trout space use

The highest average value (Fig. 5) of core area measured among the fish analyzed was 0.8 ± 0.8 km² (mean ± SD; calculated as the mean of daily individual 50% UD), whereas the highest average value of the extended range was 2.8 ± 3.1 km² (mean ± SD; calculated as the mean of daily individual 95% UD). Among all individuals analyzed, the largest daily core area measured was 7.2 km², whereas the largest daily extended range was 17.1 km².

Daily space use pattern

In order to identify common movement patterns across the study period, fish space use trends were compared using a cluster analysis. Since this study was focused on the extension of brown trout movement, only the variation of daily extended range (95% UD) was compared among individuals.

Eight different patterns (corresponding to 8 different spatial behavioral groups) were identified, but only 4 of them (Fig. 6) formed groups composed by more than one individual (3 clusters made of 3 fish, 1 made of 5 fish), whereas 4 individuals did not fall into any other behavioral group.

Group a) performed large movements during two main periods, utilizing a large portion of Lake Lugano area: one at the beginning and one at the end of the study period. Instead, the period with reduced mobility lasted about a month and corresponded to the start of summer season.

Fish belonging to this group were all released at the same release site located near the station of Cassarate (see Fig. 1). Moreover, the inspection of their movement profiles provided by actel(), showed a tendency to use the same part of the lake. These fish remained in the northern basins except for small and brief movements in the southern basin.

Space use pattern of group b) was similar to the one of group a). The main difference of this second group was the presence of an additional movement window (about one month long) in the middle of the two windows observed for group a). Period of reduced mobility was shorter (about a month) and some rare peaks in space use (fast movements) were recorded.

Fish of this group were released at different release sites. Instead, a common pattern of movement across stations was observed. Individuals left the area in the proximity of the release site immediately after being released, performing long travels back and forth (corresponding to the first movement window). 4 out of 5 fish, after the first broad movement, returned to the release site area where they remained until the end of the study period. The other individual released in the northern basin moved and remained in the southern basin.

Fish from group c) showed a time window of greater space use at the beginning of the study period (approximately lasting two month) followed by a period of limited movements, which resulted in a small area usage, lasted until the end of the study period.

Fish belonging to this group were released in different sites were and no similarities were observed among individual movement profiles.

Individuals from group d) showed a space use pattern consisting in brief but broad movements alternated with periods of reduced mobility. These fish moved throughout all the study period but increased their movement between the beginning of May and the middle of June.

Fish from this group were released at different release sites and occupied different areas of the lake. A common trend observed was that, after longer or shorter movements (in space and time), individuals returned in the proximity their release site.

Correlation between space use and abiotic factors

The influence of abiotic factors on fish space use was assessed using Pearson correlation test.

Daily rainfall values (Lugano Weather Station) were not significantly different (daily rainfall mean ± SD = 3.01 ± 7.6 mm) from the ones of the previous 5 years for the period March-August (mean ± SD = 4.2 ± 0.66 mm; calculated as the mean of daily rainfall mean). Only the space use of one individual was weakly correlated with rainfall (Table 1).

Atmospheric pressure (barometer installed at 301 m above sea level) was quite stable (mean ± SD = 981.0 ± 6.2 hPa) during the study period. 4 individuals showed a weak correlation with atmospheric pressure variations (Table 1).

Cloud cover data (percentage of sky covered by clouds) were highly variable (mean ± SD = 36.6 ± 25.4%) during the study period and showed a weak correlation with the space use of only 2 individuals (Table 1).

Lunar cycle (values representing the portion of lighted moon) allowed to predict change in space use of only 3 individuals (Table 1).

Cassarate stream is the main tributary of the northern basin. The stream had a limited water discharge (mean ± SD = 0.71 ± 0.48 m³ s^− 1) during the study period compared to the one measured in the previous 5 years for the same period (mean ± SD = 2.02 ± 0.30 m³ s^− 1; calculated as the average of daily water discharge mean). Variation in space use of 3 individuals was weakly correlated with water discharge variation of this stream (Table 1).

Vedeggio stream is the main tributary of the southern basin. The stream underwent considerable fluctuations of water discharge (mean ± SD = 1.39 ± 1.20 m³ s^− 1) during the study period. Variation in space use of only 1 individual had a weak correlation with Vedeggio stream flow variation (Table 1).

Table 1

Results of Pearson correlation test for rainfall, atmospheric pressure, cloud cover, lunar phase, water discharge of Cassarate stream (Q Cassarate) and water discharge of Vedeggio stream (Q Vedeggio). Values of p showing a statistical significative correlation (p < 0.05) were marked with an asterisk (*).
Rainfall			Pressure		Cloud cover		Lunar phase		Q(Cassarate)		Q(Vedeggio)
Tag	r	p-value	r	p-value	r	p-value	r	p-value	r	p-value	r	p-value
12510	-0.091	0.249	0.021	0.794	-0.024	0.758	-0.274	< 0.01*	0.067	0.399	0.042	0.598
12511	0.019	0.806	0.061	0.441	-0.026	0.74	0.25	< 0.01*	0.033	0.676	0.068	0.392
12515	0.07	0.379	0.239	< 0.01*	-0.105	0.183	-0.169	0.032*	-0.014	0.862	0.011	0.889
12521	-0.067	0.395	-0.004	0.957	-0.052	0.513	0.072	0.365	-0.181	0.021*	-0.121	0.124
12523	-0.013	0.873	0.324	< 0.01*	-0.127	0.107	0.125	0.112	-0.08	0.315	-0.07	0.379
12525	0.019	0.815	-0.044	0.579	0.03	0.702	-0.04	0.613	0.178	0.024*	0.106	0.18
12528	-0.088	0.265	0.008	0.923	0.202	0.010*	-0.143	0.07	0.03	0.702	-0.031	0.694
12529	0.164	0.037*	-0.11	0.164	0.206	0.009	0.131	0.098	0.116	0.142	0.069	0.385
12532	0.047	0.556	0.215	< 0.01*	0.005	0.952	-0.05	0.532	-0.061	0.439	0.073	0.355
12540	0.126	0.11	-0.053	0.5	0.284	< 0.01*	-0.107	0.177	0.067	0.395	-0.027	0.733
12543	0.009	0.914	-0.022	0.786	0.063	0.428	0.056	0.477	0.05	0.532	0.029	0.716
12550	0.051	0.519	-0.079	0.318	0.007	0.93	0.094	0.232	0.047	0.549	0.057	0.474
12551	0.015	0.846	-0.026	0.745	0.051	0.519	-0.052	0.513	-0.08	0.311	-0.119	0.131
12552	-0.069	0.383	-0.053	0.504	-0.014	0.855	-0.066	0.402	-0.184	0.019*	-0.206	< 0.01*
12555	-0.016	0.839	0.152	0.054	0.042	0.596	-0.047	0.549	0.035	0.658	-0.032	0.687
12582	-0.013	0.867	-0.271	< 0.01*	0.072	0.363	0.029	0.71	-0.05	0.529	-0.006	0.937
12593	-0.008	0.919	0.073	0.356	-0.014	0.858	0.062	0.432	-0.056	0.483	-0.092	0.245
12600	0.085	0.28	-0.124	0.117	0.034	0.667	0.111	0.158	0.093	0.241	0.104	0.188

In this study, movement of stocked adult brown trout over a large alpine lake has been investigated for six months using a non-overlapping acoustic telemetry array.

Most of the hatchery-reared trout covered large portions of Lake Lugano in relatively short periods (total distance covered 138 ± 125 km), although a great variability in the movement patterns among the analyzed fish was observed. These results are in line with the ones obtained by Schulz and Berg 1992 (101) in Lake Constance, where 50% of the tagged adult brown trout performed movement of more than 100 km in one season, alternating short movements in restricted areas (random movement phases) to long travels to distant lake areas (excursion phases).

The movement extent of the hatchery-reared trout observed in this study was unexpected, considering that several works have underlined how hatchery-reared fish exhibit reduced swimming performances compared with wild fish (16, 44, 69, 81).

For instance, Pedersen et al. 2008(93) found that wild brown trout have swimming performance up to 23% higher than hatchery-reared counterparts (mean 23–25%).

This difference was also observed in other salmonids such as Salmo salar L., in which wild fingerlings display higher growth rate, better fin quality and better stress-recovery potential compared to hatchery-reared counterparts (81).

The long distances travelled by some of the studied fish were associated to a large usage of Lake Lugano area (max daily core area:7.2 km², max daily extended range: 17.1 km²). Most of the analyzed fish showed a much higher extended range area compared to the core one, displaying a strong explorative behavior.

The more pronounced explorative behaviors exhibited by hatchery-reared trout have already been observed by other studies (4, 48), which suggested the key role of the hatchery environment in shaping fish behavior, leading to a greater dispersion in the wild (29, 113).

Moreover, among individuals in a fish population there could be many different personalities associated with different behavioral traits, which usually tend to co-variate together. This association between behavioral traits is known as “behavioral syndrome” (103, 105). According to the behavioral syndrome hypothesis, fish with fast exploration strategy are often also more aggressive and bolder in a novel environment (103, 105). These behavioral traits can be non-adaptive under natural conditions resulting in greater energetic costs (108), increasing exposure to predation (53, 100) and fishing (19, 48). Indeed, Alòs et al. 2012(5) demonstrated that all fishing techniques, including the least efficient one (i.e. fixed spot fishing), exerted consistent negative selection on activity-like behaviors, namely exploratory, aggressive and bold behaviors. Among others, gears used by professional anglers (i.e. gillnets) represent a major threat to populations maintained by stocking practices due to the high probability for a highly mobile fish to encounter nets, leading to greater harvest. The exploratory and bold behavior of hatchery-reared brown trout associated to their reduced plasticity could result in a high post-release mortality.

Assessing the mortality of studied animals in acoustic telemetry experiments is important to avoid biased data interpretations, especially when they can influence management and conservation decisions (67). Based on the mortality criteria used, 51 fish out of 69 potentially died after the release (74% post-release mortality), a mortality rate similar or even higher than the one observed by other telemetry studies carried out on hatchery-reared fish (68, 109). On the other hand, wild fish seem to have a better post-release survival compared to hatchery-reared fish (1), for example Schulz and Berg 1992 (101) observed 8% post-release mortality on wild adult brown trout. Nevertheless, it must be acknowledged that the mortality assessment criteria used in this study to avoid incorrect data interpretation and improper conclusions may have caused the exclusion of some fish that moved to areas not covered by receivers (cease in detections criterion), or that may have stopped performing extensive movements remaining within a single receiver detection range (stationary or variable horizontal space use criterion). Another factors that could lead to erroneous mortality estimations is, for instance, the variability in detection efficiency, which can be caused by background noise, transmitter signal collisions, seasonal or daily variation in water phisico-chemical properties and signal interferences with substrate (56, 102). Besides, dead animals or expelled tags (from predation event or tag rejection; (46)) can be covered by sediment in few days, greatly or totally reducing the detection efficiency (114).

Assessing predation events on tagged fish is as well a very challenging task since the tag could be retained in the living predator after consumption, introducing a potential “predation bias” (115). Therefore, further mortality investigations (i.e. transmitters with heart rate/depth sensors), or the extension of the monitoring activity on Lake Lugano, will help to quantify the post-release survival of hatchery-reared brown trout in this lake.

Nevertheless, many recaptures were reported by recreational anglers at different time after the release, showing how some of the released fish actively predate on fish baits and are able to adapt to the lake environment in few weeks (fish in Fig. 7 grew 12 cm and put on 600 g in only 9 months).

Movement patterns of brown trout tagged in this study could be grouped into four major groups, showing different post-release behavior and usage of Lake Lugano. Most of these fish performed great movements after the release, followed by a period with reduced mobility. Some of the fish after this period of reduced mobility returned to a more explorative behavior, whereas some fish stopped moving for the entire study duration. Few fish performed continuous movement throughout the entire study period.

The long distances travelled by some of the studied fish, associated with their extensive usage of Lake Lugano area, could be also explained by the use of lake currents. In elongated and deep subalpine lakes such as Lake Lugano, currents are controlled by thermal stratification, wind forces and Coriolis force (7). Passive use of currents as a transportation system(9) can reduce energetic costs associated with movements, especially in large alpine lakes where resources are distributed in patches (e.g., school of baitfish) over large distances (15).

Environmental factors such as atmospheric conditions (42, 92), lunar cycles (14) and hydrological changes (61, 83, 110) are also important drivers behind fish movement and activity inside aquatic ecosystems. Besides, other studies pointed out that direction, timing and extent of fish movements may be influenced by a variety of other variables including turbidity (72), chemical factors such as pH (41), oxygen levels (96) and thermal stratification (25, 57). In this study, the environmental data available and correlated with fish movement included rainfall, water discharge of the two main tributaries of Lake Lugano, atmospheric pressure, cloud coverage and moon phases. None of the environmental factors tested were able to predict changes in trout space use, only 12 analyzed fish showed a weak correlation with environmental variables. However, it must be pointed out that the lack of information regarding fish vertical distribution (transmitters used were not equipped with depth sensor) limits further assumptions about the relation between fish space use and environmental changes.

This study provides insights into adult stocked brown trout spatial behavior in a large and deep lake over six months. Results underline how adult stocked brown trout, despite their scarce attitude to sustained swimming and/or foraging in a wild environment, can perform unexpected movements in large deep lakes.

Moreover, from the results of the space use analysis, domestication seems to have a remarkable influence on the behavioral strategies adopted by the studied fish once released in the wild. Hatchery-reared fish reduced plasticity induces individuals to reiterate exploratory movements potentially leading to higher risks and mortality, i.e. high energy consumption, predation and fishing. A high post-release mortality seems to occur on hatchery-reared brown trout, even though mortality rate estimations should be further investigated due to the limited number of receivers deployed, especially for a large area like the one of Lake Lugano.

The influence of environmental factors on tagged trout movement has also been analyzed, but none of the variables tested seem to heavily influence brown trout post-release behavior.

Acknowledgements

This study was supported by Interreg ITA-CH SHARESALMO (Grant no. 599030), LIFE15 NAT/IT000823 IdroLIFE and LIFE21-NAT-IT-PREDATOR Projects. We thank the office of hunting and fishing of Canton Ticino and the Cantonal Police of Ticino, Switzerland, for the data collection, field work and revisions. We thank Cesare Puzzi and Andrea Tersigni (G.R.A.I.A. srl) for the support during the tagging and monitoring activities. We thank Milan Riha for the insightful comments regarding data analysis.

Funding

Funding for this study was provided by the project Interreg ITA-CH SHARESALMO (Grant no. 599030).

Author information

Authors and Affiliations

CNR-IRSA, Largo Tonolli 50, 28922 Verbania Pallanza, VB, Italy.

Stefano Brignone, Luca Minazzi, Pietro Volta

Ufficio della caccia e della pesca, Repubblica e Cantone Ticino, Via F. Zorzi 13, 6500 Bellinzona

Christophe Molina, Tiziano Putelli

Author contributions

SB: project design, data collection, data analysis, writing, editing. LM: data collection, data analysis, writing, editing. CM: project design, data collection, editing. TP: project design, editing. PV: project design, writing, editing.

Corresponding Author:

Stefano Brignone, email: [email protected]

Data Availability

Data and analysis code will be made available upon request.

Declarations

Ethics approval and consent to participate

Scientific research for this paper was conducted under the project “Conservazione dei salmonidi autoctoni”, N° TI-27-2020 permit released by Dipartimento della sanità e della socialità Esperimenti sugli animali Autorizzazione/decisione delle autorità.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

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No competing interests reported.

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How much hatchery-reared brown trout move in a large, deep subalpine lake? An acoustic telemetry study

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Abstract

Figures

Introduction

Methods

Study area

Study species and tagging procedure

Acoustic receiver network

Data processing

Mortality assessment

Distances calculation

Utilization distribution (UD)

Statistical analysis

Results

Sample description and mortality

Brown trout movement: travelled distances

Brown trout space use

Daily space use pattern

Correlation between space use and abiotic factors

Discussions

Conclusions

Declarations

References

Additional Declarations

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