Linköping University | Department of Physics, Chemistry and Biology Bachelors thesis, 16 hp | Educational Program: Biology Spring term 2020 |
LITH-IFM-G-EX—20/3878--SE
Impact of the Warm Summer of
2018 on Growth of Roach (Rutilus
rutilus) in Lake Tåkern, Sweden
Emil Pedersen
Examiner, György Barbaras Supervisor, Anders Hargeby
Avdelning, institution
Division, Department
Department of Physics, Chemistry
and Biology
URL för elektronisk version
ISBN
ISRN:
LITH-IFM-G-EX--20/3878--SE
_________________________________________________________________
Serietitel och serienummer ISSN
Title of series, numbering ______________________________ Språk Language Svenska/Swedish Engelska/English ________________ Rapporttyp Report category Licentiatavhandling Examensarbete C-uppsats D-uppsats Övrig rapport _____________ Titel Title
Impact of the Warm Summer of 2018 on Growth of Roach (Rutilus rutilus) in Lake Tåkern, Sweden
Författare Author Emil Pedersen Nyckelord Sammanfattning Abstract
Climate change will lead to higher temperatures and longer summers in the future, which will likely influence the growing season of fish living in temperate lakes. The warm summer of 2018 in Sweden matches prognoses for normal summers at the end of the century and can thus be used to investigate the effect of temperature related factors on fish growth. In this study I used back-calculation of the growth of roach (Rutilus rutilus) caught in Lake Tåkern, Sweden, to find differences in growth during 2018’s hot summer versus the period 2012-2017. I compared growth during these years with results from a similar study from Lake Tåkern in 1978. For this comparison I used 1977 as a representative year for the 1970’s. I applied sclerochronology to the scales to determine age and growth. The results show that growth in terms of length increment was faster in 2018 than in 2012 – 2016. The results indicate that 2018 had an effect on the whole roach population, since significant differences were found across age groups. Additional comparisons between 1977 and 2018 showed no significant difference. Differences in roach growth rate between 2012-2018 could be caused by the differences in mean temperature during the roaches growing season, since 2018 was abnormally warm, and the difference between 1997 and 2018 could be attributed to 1977’s fish death. This means that if the pattern of climate change continues, roach growth rates will increase in the future regardless of age group.
Datum
Date
Contents
1 Abstract ... 1
2 Introduction ... 1
3 Materials and Methods ... 3
3.1 Age determination and back-calculation……….4
3.2 Data analysis.………..5
4 Results ... 6
5 Discussion ... 8
6 Societal and ethical effects ... 10
7 Acknowledgments.……….………11
8 References.……….12
1 Abstract
Climate change will lead to higher temperatures and longer summers in the future, which will likely influence the growing season of fish living in temperate lakes. The warm summer of 2018 in Sweden matches prognoses for normal summers at the end of the century and can thus be used to investigate the effect of temperature related factors on fish growth. In this study I used back-calculation of the growth of roach (Rutilus rutilus) caught in Lake Tåkern, Sweden, to find differences in growth during 2018’s hot summer versus the period 2012-2017. I compared growth during these years with results from a similar study from Lake Tåkern in 1978. For this comparison I used 1977 as a representative year for the 1970’s. I applied sclerochronology to the scales to determine age and growth. The results show that growth in terms of length increment was faster in 2018 than in 2012 – 2016. The results indicate that 2018 had an effect on the whole roach population, since significant differences were found across age groups. Additional comparisons between 1977 and 2018 showed no significant difference. Differences in roach growth rate between 2012-2018 could be caused by the differences in mean temperature during the roaches growing season, since 2018 was abnormally warm, and the difference between 1997 and 2018 could be attributed to 1977’s fish death. This means that if the pattern of climate change continues, roach growth rates will increase in the future regardless of age group.
Keywords: Age group, Aging, Annual length increment, Climate Change, Population, Roach, Scales, Temperature
2 Introduction
In a world undergoing climate change it is becoming increasingly important to understand how it will influence populations and ecosystems (Giorgi et al. 2001). According to modeled climate scenarios CCPR4 and 8 (Sjökvist et al. 2019), the temperature and precipitation pattern of the hot summer of 2018 can be used as an illustration of ordinary summers in Sweden by the end of the century. Comparing the observed change in body size of the common roach (Rutilus
rutilus) in 2018 and years in the past (e.g., 1977, which will be used as a representative year
from the 1970’s) may give us insights into how climate change has affected their growing season.
Sclerochronology is the science of studying the individual life history of an organism using the calcified tissues of the organism. Sclerochronology in fish can be used to better understand population dynamics and to follow the populations development (SLU. 2012). This can be both important for academic research since information about how climate change impacts fish populations both in age structure and growth is a complex problem that needs further study (Rijnsdorp et al. 2009). From an economic point of view, knowing a population’s state can give information on how much fish can be harvested from lake or sea regions. The additional knowledge gained from this study about the interaction with roach growth rates will further help with the above-mentioned tasks of understanding dynamics in roach populations.
We applied schlerochronology to determine the age of individual R. rutilus specimens by examining their scales. The procedure of age determination involves looking at small ridges on the surface of the scales called circuli (SLU. 2012). When the scales grow as the fish grows, these circuli get added to the scale with different intervals depending on the different growing seasons (Dijk et al. 2002). The growing seasons depend greatly on water temperature, with growth switching to non-growth when the water temperature drops below 12 oC (Dijk et al. 2002). In the same study by Dijk et al. They found that the temperature preference of roaches under normal conditions was around 27 oC but showed a broad maximum in growth rates between 20 oC and 27 oC. While the roaches are in their growing season, their circuli get added on slower which increases the inter-circulus distance, which in turn changes during the non-growth season so that the circuli are added in a much tighter formation (SLU. 2012). This creates a “winter ring” where there is a noticeable switch from the non-growth season to the growing season (Figure 1).
The aim of this study is to compare annual body growth during 2018 with annual growth during 2011-2017 to assess the possible role of elevated temperature on roach growth rates.
To relate the growth rate in recent years to the 1970s, 1977 was particularly interesting because it was a relatively cold year in relation to the period of 2011-2019 (SMHI. 2020) However it also had a period of recurring fish death during the winter, that lead to a decrease in food competition. This leads to an increase in growth rate for the remaining fish that survived during the 1970’s (Bengtsson & Hargeby. 1978).
3 Materials and Methods
The roach (Rutilus rutilus) used in the analyses were collected from Lake Tåkern, by means of test-fishing with multi-mesh survey gills in August 2019 (Skog. 2020). In total, 75 specimens were used in this study. To prepare the roach scales for analysis, they were first separated after being removed from the envelopes holding the sample. To do this, tweezers were used to gently pry the scales from each other in a way that would not damage or warp the scales. After this came the sclerochronological analysis. This was performed with a Leitz Wetzlars type microscope at 100x magnification with an ocular micrometer to measure the scales. With its use, I counted the total number of winter rings on each scale. Finally, the age of each specimen was equated with the number of winter rings. The specimen shown in figure 1 would therefore be considered a 1-year-old (SLU, 2012).
Figure 1. Winter rings shown as tight formations of circuli around the scale,
arrows indicates the position of the winter ring. By Unknown author – Popular Science Monthly Volume 35, Public Domain, https://commons.wikimedia.org/w/index.php?curid=11768653.
I then measured the distance between the winter rings and the center of the scale (Figure 1). Since there were several scales from the same specimen in the same container, it was important to determine age from several scales of the same specimen to confirm that the pattern was consistent across scales. This is especially important for the age determination of the fish, as individual scales may be damaged or otherwise difficult to read. For the other measurements (radius and distance between winter rings and the center of the scale), a random scale of the specimen was used.
3.1 Age determination and back-calculation
After calculating the growth between each year for each specimen, I performed a linear regression of fish body length at capture on measured scale radius (Figure 2). The relationship is sufficiently tight for one to use the fitted linear function to accurately back-calculate body length when only the scale radius is known.
Figure 2. Simple linear regression testing the relationship between roach body length and scale radius with its associated regression expression and R2. N=79
We used it to determine specimen’s length at a yearly interval. The calculation of the annual growth during specific years was conducted by subtracting the length at a certain year from the length at the previous year.
Data on roach growth in 1977 were available from a similar study (Bengtsson & Hargeby. 1978). The aging and back-calculation were performed using the same methods as in the present study on material from 2019. Growth in 1977 was close to the average (102%) for all sizes of roach caught with gill nets in June 1978 (n=56).
3.2 Data analysis
Unpaired t-test was performed to compare the growth data between 2018-2019 and previous collected data from 1977-1978 from the same lake (Bengtsson & Hargeby. 1978). A test for homogeneity of variances was used on log-transformed data to the requirements of ANOVA. A one-way-ANOVA was used on back-calculated growth to test for differences in annual growth across the years 2011-2018. To see between which years there is a difference, a post-hoc Tukey test was used on the same data. Finally, to see if there was any difference between age groups, the data was grouped by age. The grouped data was then subjected to further Tukey tests. The age groups that were tested were 2-7 years. The group that consisted of 8-year-old fish was discarded as there was only one specimen in that group, and the young-of-the-year group was also discarded as it was not relevant.
4 Results
Table 1 and Figure 3 summarize the growth differences across 2012-2018. They show that there is significant differences between 2018 and 2013, 2014, 2015 and 2016. Note that the low number of specimens in years 2012 and 2013 likely leads to results with low power for those years.
Table 1. Results from a one-way ANOVA for annual growth as length increments for roach 2012-2018. SS = Sum of squares, df = degrees of freedom, MS = Mean square.
___________________________________________________________________________ Source of variation_____SS_____df______MS______F______p-value__________________ Between Groups 1.350 6 0.22508 7.52 0.000
Within Groups 4.577 153 0.02992
Total_____________ 5.928 159_____________________________________________
Figure 3. Back calculated growth as length increments for roaches caught in 2019 in Lake Tåkern. Each box diagram shows that year’s growth for all specimens that were caught in 2019. A common lowercase a/b means there is no significant difference between the years. Numbers
Among all age groups except 4-year-year-old fishes, there was a significantly higher growth rate in 2018 than in the years before (Figure 4). In the group of 4-year-old fish there was only a significant difference in growth rates between 2015 and 2018. In Table 2 in the appendix shows the statistical results for the Tukey tests in detail.
Figure 4. Growth as body length increments for separate age groups of roaches from Lake Tåkern caught in 2019. Bars indicate the mean, whiskers ± 1 standard deviation. A common lowercase a/b indicates that there was no significant difference between the years (Tukey HSD post-hoc test). The numbers besides the age is the number of specimens in that age group.
The results for the t-test below comparing 2011-2018 and 1977.
(Mean = 35.1 ± 13.9) and 1977 (Mean = 35.5 ± 10.2) was made to see if there were any differences. The test statistics were as follows t121=1.979, p = .766976.
5 Discussion
The results showed that regarding the effect of the warm summer of 2018 versus the period of 2012-2017. In 2018 there were significant increase in roach growth rate compared to 2013, 2014, 2015 and 2016. The temperature in Sweden during the growth season for the roach during 2018 were elevated, and in southern Sweden temperatures could reach 5 oC above the mean. This includes the area around Lake Tåkern (SMHI. 2018). This means that temperature could be a major contributor to the growth increase during 2018.
It is also important to note that if I had a higher number of individuals for the years 2012 and 2013, it would increase the power of the tests. Since the cause of this difference in growth rate cannot be easily explained (Rijnsdorp et al. 2009), further studies that focus more on the causes of these differences could shine more light on factors causing the discrepancy. This in turn would let us to predict patterns more easily in roach populations going forward.
The results for the second question that focused on age group specific differences in growth. Showed that regardless of age, 2018 influenced the growth rate almost across all age groups. And since roach diet shifts during their lifecycle (Persson, 1983), this could mean that across all different age groups food became more available than they were the years before, or that the predation on roaches was lower this year. So that the roach could spend less time exhibiting watchful behavior and more time feeding (Tang et al. 2017). Alternatively, it could also mean that temperature was the limiting factor for growth across all age groups.
And the last question, if 2018’s warmer summer would lead to a significantly higher growth rate when compared to the summer of 1977 leads to the conclusion that no difference in growth rate could be see between the year 2018 and 1977. In 1977 the temperature colder than average (Persson et al, 2015). This begs the question of why this lower temperature does not seem to impact the growth rate of the roach from 1977, since roach should clearly benefit from
of 1977 should point towards that 2018 would be a better year than 1977 for roach growth rate (Specziár et al. 1997). But this is not shown in this study.
In a study on fish community recovery, Ruuhijärvi et al. (2010) discuss how mortality in previous years is often a reason for high roach growth during subsequent years. This should mean that the fish death that occurred during the winter of 1977 (Bengtsson & Hargeby. 1978) should have been a major contributor to the growth rate during 1977. Ruuhijärvi et al.(2010) found that in their study a 75 % fish death during the growing season was not a major variable when compared to mean temperature increases during the growing season. Though in the subsequent year the fish death was the cause of a major increase in recruitment and growth. This seems to point towards the same conclusion that this study does, that temperature is indeed a great major force behind the growth of roach but that fish deaths such as the one in 1977 can also be a major cause of growth rate increases.
In conclusion I have determined that the temperature of 2018 is one of the strong drivers for roach growth rate and concluded that both abiotic and biotic influences could affect the growth rate of roach. It could be interesting for further studies to focus on how the temperature affect the spawning times of roaches in shallow lakes as Lake Tåkern, since a link between climate and spawning times have been found by Stoessel et al. (2014), and this in turn will give us a deeper understanding of climates effect on population dynamics. It would also be good to further investigate the different aspects ecosystems impact on this topic. To be able to separate effects of temperature on growth efficiency from effects of production of food items.
6 Societal & ethical considerations
These kinds of questions are important when you consider the status of several fish communities like the Atlantic cod, and how information about the health and growth surrounding that population can help in providing vital information that can be used to better managing these important food sources (SLU, 2012). All the fish were collected with authorization by the laboratory animal ethics committee in Linköping, Sweden.
7 Acknowledgements
I would like to thank my supervisor Anders Hargeby and my examiner György Barabas as well as my opponents Johan Karlsson and Jennie Johansson.
8 References
Bengtsson, T & Hargeby, A. 1978. Fiskundersökningar I Tåkern 1977 — Tillväxt och
ålderssammansättning hos mört, sarv, sutare, ruda, abborre. Unpublished. BSc thesis.
Linköping University.
Dijk, P. V., Staaks, G., & Hardewig, I. (2002). The effect of fasting and refeeding on
temperature preference, activity and growth of roach, Rutilus rutilus. Oecologia, 130(4), 496–
504. doi: 10.1007/s00442-001-0830-3
G. Persson, ”Sveriges klimat 1860- 2014 Underlag till Dricksvattenutredningen,” Norrköping, 2015.
Giorgi, F., Whetton, P. H., Jones, R. G., Christensen, J. H., Mearns, L. O., Hewitson, B., ... & Jack, C. (2001). Emerging patterns of simulated regional climatic changes for the 21st century
due to anthropogenic forcings. Geophysical research letters, 28(17), 3317-3320.
Mooij, W., Domis, L. D. S., & Hülsmann, S. (2008). The impact of climate warming on water
temperature, timing of hatching and young-of-the-year growth of fish in shallow lakes in the Netherlands. Journal of Sea Research, 60(1-2), 32–43. doi: 10.1016/j.seares.2008.03.002
Persson, L. (1983). Food Consumption and the Significance of Detritus and Algae to
Intraspecific Competition in Roach Rutilus rutilus in a Shallow Eutrophic Lake. Oikos, 41(1),
118. doi:10.2307/3544353
Rijnsdorp, A. D., Peck, M. A., Engelhard, G. H., Möllmann, C., & Pinnegar, J. K. (2009).
Resolving the effect of climate change on fish populations. ICES Journal of Marine Science, 66(7), 1570-1583. doi:10.1093/icesjms/fsp056
Ruuhijärvi, J., Rask, M., Vesala, S., Westermark, A., Olin, M., Keskitalo, J., & Lehtovaara, A. (2010). Recovery of the fish community and changes in the lower trophic levels in a eutrophic
lake after a winter kill of fish. Hydrobiologia, 646(1), 145-158.
Sjökvist, E., Abdoush, D. & Axén, J. Sommaren 2018 - en glimt av framtiden? Reports of the
Swedish Meteorological and Hydrological Institute (SMHI) 52, 1–40 (2019).
Skog, M. 2020. Changes in the fish community over 40 years in Lake Tåkern, Sweden. Master thesis. IFM Biology. Linkoping university.
SLU (Swedish agricultural University) 2012. Metodhandbok för åldersbestämning av fisk. Instutionen av akvatiska resurser, SLU. 10th edition
SMHI. Klimatdata – Månadens väder och vatten i Svergie. (n.d.). Retrieved June 17, 2020, from
https://www.smhi.se/klimat/klimatet-da-och-nu/manadens-vader-och-vatten- sverige/manadens-vader-i-sverige/juli-2018-langvarig-hetta-och-svara-skogsbrander-1.137248
Specziár, A., Tölg, L., & Bíró, P. (1997). Feeding strategy and growth of cyprinids in the
littoral zone of Lake Balaton. Journal of Fish Biology, 51(6), 1109–1124. doi:
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Stoessel, D. J. (2014). Age, growth, condition and reproduction of roach Rutilus rutilus
(Teleostei : Cyprinidae), in south-eastern Australia. Marine and Freshwater Research, 65(3),
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Tang, Z., Huang, Q., Wu, H., Kuang, L., & Fu, S. (2017). The behavioral response of prey fish
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9 Appendix
Table 2. Tukey Test. Results for the age group specific Tukey tests for roaches that turned out significant. ___________________________________________________________________________ Age Group__________________q-value____________p-value______________________ Comparisons 3-year 2016-2018 11.4432 .0038 2017-2018 13.1272 .0007 4-year 2015-2018 13.8726 .0352 5-year 2014-2018 16.4956 .0216 2015-2018 14.9354 .0454 2016-2018 15.4179 .0363 2017-2018 14.5463 .0447 6-year 2013-2018 24.1694 .0014 2014-2018 24.7457 .0011 2015-2018 24.1873 .0014 2016-2018 23.4712 .0019 2017-2018 17.0377 .0287 7-year 2012-2018 29.3586 .0005 2013-2018 28.2421 .0007 2014-2018 29.8072 .0004 2015-2018 31.453 .0002 2016-2018 31.2949 .0003 2017-2018 21.5218 .0082__________________________
