Vulnerability of rotifers and copepod nauplii to predation by Cyclops kolensis (Crustacea, Copepoda) under varying temperatures in Lake Baikal, Siberia
As lakes warm worldwide, temperature may alter plankton community structure and abundance by affecting not only metabolism but also trophic interactions. Siberia’s Lake Baikal presents special opportunity for studying shifting trophic interactions among cryophilic zooplankton species in a rapidly warming lake. To understand how warming may affect trophic interactions among plankton, we studied predator–prey relationships of a copepod predator (Cyclops kolensis) with three prey types: two rotifer species (Gastropus stylifer and Keratella cochlearis) and copepod nauplii. We hypothesized that the less evasive Gastropus and Keratella would be more susceptible to predation than nauplii. We exposed a starved predator to individuals of each prey type and observed encounters, ingestions, and escapes. Contrary to our hypothesis, Keratella were consumed at lower rates than nauplii, due to higher probability of ingestion after encounter with nauplii. In a second experiment, we assessed how predation varied across a thermal gradient, confining all three prey types and one starved predator at 5° temperature increments (5–20°C). Predation outcomes mirrored observational feeding trials, and predation outcomes were independent of temperature. Rotifers’ relatively high reproductive rate may present a mechanism to withstand predation should copepod’s preferred nauplii prey become less abundant in a warmer Baikal.
KeywordsFreshwater food webs Rotifera Coldwater stenotherms Zooplankton
As lakes warm worldwide (O’Reilly et al., 2015), aquatic communities are likely to shift in composition and interactions (Moore et al., 1996), both as a result of direct effects on metabolism (Huey, 1991; Dell et al., 2011) and indirect effects mediated through trophic pathways (Dell et al., 2014). The variety of responses to warming magnifies potential for relationships, such as competition and predation, to change under warmer or more variable temperature regimes (Huey, 1991; Seifert et al., 2015), but these changes may be difficult to predict. Temperature-induced changes in planktonic composition and activity have important implications for ecosystem functioning (e.g., Elliott et al., 2006), determining carbon flow to higher trophic levels (Schabetsberger et al., 2009; Schmidt et al., 2009), nutrient cycling (Lehman, 1980; Higgins et al., 2006; Hambright et al., 2007), occurrence of nuisance algal blooms (Rigosi et al., 2015), and greenhouse gas production (Tadonléké et al., 2012). Furthermore, temperature-mediated changes can alter plankton assemblage composition and abundance, as well as interactions among planktonic species, which can eventually contribute to temporal mismatching of consumers with their resources (Thackeray et al., 2010). These effects of temperature change on communities can become even more complex when metabolic rate and overall activity of aquatic organisms differ across taxa (Dell et al., 2014). For example, a rotifer trophic web comprised of predatory Asplanchna brightwellii Gosse, 1850, herbivorous Brachionus calyciflorus Pallas, 1766, and a green alga, ingestion rates increased for both of the consumers, but the greatest increases occurred at different temperature ranges; thus, outcomes of their interactions would differ depending on the range and rates of temperature change (Seifert et al., 2015).
Plankton community structure and function may respond to warming most strongly in cold lakes that have been historically dominated by coldwater taxa, such as Lake Baikal in Siberia (Moore et al., 2009). In addition to being the world’s deepest and most voluminous lake, Lake Baikal is also the oldest and most biodiverse lake, and exhibits exceptionally high occurrences of endemism (Kozhov, 1963; Kozhova & Izmest’eva, 1998). The endemic Baikalian plankton tend to be coldwater stenotherms. They are well adapted to life under ice for half the year where average temperatures are about 1°C (e.g., Bondarenko et al., 2006; Melnik et al., 2006; Hampton et al., 2008), with optimal growth rates at temperatures below 10°C for prominent endemic plankton species (Kozhov, 1963; Richardson et al., 2000). However, the highest annual diversity of rotifer assemblages occurs in the late-summer and fall months (Pomazkova & Kuzevanova, 1989) when surface temperatures average about 8°C and can occasionally exceed 16°C (Hampton et al., 2008), and cold-tolerant endemics co-occur with warm-adapted, cosmopolitan species (Kozhov, 1963; Kozhova & Izmest’eva, 1998; Hampton et al., 2008, 2014; Izmest’eva et al., 2016). Warming in Siberia has occurred nearly twice as fast as global air temperatures, and Lake Baikal has warmed approximately twice as fast as ambient air temperature, with average surface temperatures increasing by 0.2°C decade−1 since 1946 (Shimaraev et al., 2002; Hampton et al., 2008). Furthermore, increases in cosmopolitan plankton abundances during summer have been observed, such as the 12-fold increase of Cyclops kolensis Lilljeborg, 1901 over the past six decades (Izmest’eva et al., 2016). Concurrent with this warming, endemic plankton species abundance has either not changed or has declined in summer months (Hampton et al., 2008; Izmest’eva et al., 2016). The extent, to which these changes may have occurred through direct effects on metabolism, or indirectly through food web changes, is unknown.
Here we experimentally explored the potential for trophic interactions between rotifers and their predators to change with shifting temperature. While the Baikal plankton is dominated by herbivorous Epischura baikalensis Sars, 1900, predatory C. kolensis and a variety of herbivorous rotifers can occasionally become more numerous (Kozhov, 1963; Pomazkova & Kuzevanova, 1989). Perhaps because the pelagic waters are frequently a near monoculture of Epischura (Izmest’eva et al., 2016), the ecology of rotifers in Baikal, including interactions with their prospective predators such as Cyclops, is not well documented in the international scientific literature. Cyclopoid–rotifer interactions can be highly species-specific due to the many predator avoidance strategies that rotifers exhibit as well as variation in recruitment–temperature relationships among zooplankton species (Brandl, 2005; Zhang et al., 2015). Increasing surface temperatures in Lake Baikal in conjunction with increasing predatory cyclopoid abundance likewise could intensify cyclopoid predation pressure on rotifers. The relative paucity of knowledge on ecology of Baikal’s rotifers and the potential for characteristics of Baikal populations to have diverged from those found elsewhere together heighten the need to focus on interactions for these species under changing temperatures. We exposed Gastropus stylifer Imhof, 1891 and Keratella cochlearis Gosse, 1851 to predation by co-occurring cyclopoid copepods (C. kolensis), and compared these interactions with cyclopoid response to copepod nauplii. The two central objectives of our experiments were (1) to measure outcomes of predator–prey interactions for each prey type, and (2) to determine whether these outcomes changed in response to temperature. We hypothesized that the less evasive rotifers would be consumed at higher rates than nauplii by C. kolensis and that the results of predator–prey interactions may change across a temperature gradient as movement rates of predators and prey change in a taxon-specific manner.
Our overarching approach was to collect experimental animals in the field, starve individual cyclopoid predators, and expose them to rotifer and nauplii prey in both an observational experimental arena and one in which temperature could be manipulated.
On August 19, 2015, plankton were collected with a 64 µm net approximately 50–100 m offshore from Bolshie Koty (51°54′21.8046″ N, 105°3′59.043″ E), where water column depth ranged from 10 to 50 m, by towing the net behind a rowboat at a depth approximately 1–2 m below the surface. G. stylifer, K. cochlearis, and copepod nauplii were chosen as prey because they were in high availability relative to other prey. Predators (C. kolensis) and prey were sorted in the laboratory under ×10–30 magnification. We chose only gravid (showing well-developed, dark ovaries) female C. kolensis for experiments, in order to reduce variation that can occur with predator size, stage, and sex (Allan, 1976; George, 1976; Gilbert & Williamson, 1983). Before each of the two experiments, prey were sorted into separate containers, targeting prey without eggs but recognizing that many of them would later produce eggs at various times during the experiment.
Plankton enumeration and community description
Although three samples were collected for enumeration on August 19, 2015 at the same time and location as the experimental animals, problems with preservation necessitated using data from Irkutsk State University’s Biological Research Institute’s regular sampling to characterize the plankton community at a different location. These samples for plankton enumeration and community description data were collected from the long-term plankton monitoring site “Point No. 1” (51°52′48″ N, 105°05′02″ E) on August 19, 2015, where a team of researchers from the Irkutsk State University’s Biological Research Institute has sampled plankton every 7–10 days for more than seven decades (Silow et al., 2016). Zooplankton samples in this long-term program are collected using a 100 µm zooplankton net, which can allow smaller rotifers to pass through the mesh. Samples were collected between 0 m (15.0°C) and 10 m (14.5°C) and immediately preserved with formalin. Samples were then concentrated over a period of 5 days. Analysis of the sample consisted of accounting for the presence and abundance of each species within one-unit volume for that sample collection. Systematic identification of each species was conducted by a counting method according to the standard protocols (Kozhova et al., 1978).
Predator–prey behavioral observations
In order to address our first objective of measuring outcomes of predator–prey interactions for the focal prey species, we directly observed predator–prey interactions for each combination of potential predator and prey type. Individual predators were isolated in GF/F-filtered water without prey at 15°C for 7–24 h before the start of the experiment. We incubated the prey with 64 µm filtered water to remove other animals but to provide some potential food for them, and held them at 15°C for 18–24 h before the start of the experiment.
To initiate the experiment, we placed 30 individuals of a single prey species into 2 ml of 0.7 µm GF/F-filtered lake water in a well plate under ×10 magnification. We made no effort to include or exclude food for prey. A single predator was added to each predator treatment. Interactions were observed for 15 min or a total of three prey ingestions, whichever occurred first. We noted encounters, attacks, and ingestions, following the methods of Gilbert & Williamson (1978). Cross-observer comparisons indicated that subjective interpretation of attacks among observers compromised data quality; consequently, we focus our analyses on encounters and ingestions. A total of nine replicates were executed for each of the three prey species, at room temperature of approximately 20°C. Data were analyzed with a Type 1 one-way ANOVA (lm in R; R Core Team, 2016) to determine whether prey type significantly influenced encounters, ingestions, and ingestions per encounter. A post hoc Tukey HSD test was then performed for significant ANOVA models.
Temperature–predator incubation experiment
To address our second objective, determining whether predator–prey interactions were affected by warming, we incubated predators with prey at varying temperatures, and assessed whether the outcomes of predator–prey interactions changed in response to temperature. Individual predators were isolated and held in GF/F-filtered Baikal water without prey at 15°C for 24 h before the start of the experiment. We incubated the prey with 64 µm filtered water to remove other animals but to provide some potential food for them and held them at 15°C for 24 h before the start of the experiment.
To initiate the experiment, we placed five individuals of each prey species into 20 ml of 0.7 µm GF/F-filtered lake water for a total of 15 prey per container. Again, no effort was made to include or exclude food for prey. A single copepod adult was added to each predator treatment, and no predator was added to control treatments. Ten replicates of the predator treatment and five replicates of the control treatment were incubated at 5, 10, 15, and 20°C under low-intensity fluorescent light for 10 h. The control treatment at 10°C had two replicates due to a lack of adequate prey. At the end of the experiment, we preserved the contents of each dish with Lugol’s and remaining prey were counted. Data were analyzed using a Type 3 two-way ANOVA (lm in R; R Core Team, 2016), to accommodate the design imbalance (Shaw & Mitchell-Olds, 1993) created by the lower replication of the 10°C control, with treatment (i.e., with or without predator) and temperature (i.e., 5, 10, 15, and 20°C) as factors. A post hoc Tukey HSD test was performed for significant ANOVA models.
Plankton enumeration and community description
Due to problems with preservation of our original samples, zooplankton community enumerations (individuals l−1) from a single sample were used from a different location on the same day, collected as part of the long-term plankton monitoring project at Irkutsk State University’s Biological Research Institute from “Point No. 1” (51°52′48″ N, 105°05′02″ E) for a depth from 0 to 10 m on the same day as experimental animals were collected
Predator–prey behavioral observations
Temperature–predator incubation experiment
Contrary to our expectations, the rotifer Keratella was less vulnerable to predation than copepod nauplii, due to Keratella’s low probability of ingestion after encounter, with more variable results for the rotifer Gastropus. Nauplii were highly susceptible to predation, as demonstrated by both their relatively high probability of ingestion after encounter and the reduction of naupliar survivorship in predator treatments across a temperature gradient. Since Epischura nauplii were nearly three times more abundant than Cyclops nauplii (Table 1), the majority of nauplii consumed were almost certainly Epischura, though we did not screen for a specific taxon of nauplii. Contrary to our results, many studies have shown that nauplii are better defended against cyclopoid predation than are the rotifers due to effective escape responses and sometimes due to larger size (Williamson, 1980). Copepods usually prefer smaller prey between 150 and 200 µm (Plassmann et al., 1997), such as rotifers, although physical defenses such as those of Keratella, can deter predation (Gilbert & Williamson, 1978; Gilbert & Stemberger, 1984; Stemberger & Gilbert, 1984; Devetter & Sed'a, 2006; Sarma et al., 2011; Nandini et al., 2014). Rotifers’ swimming patterns also can affect probability of detection by predators (Williamson, 1980). When defenses are lacking, some rotifer species are less preferred prey presumably due to their inability to satiate the predator for proportional energy expenditure (Stemberger, 1985). Altogether, literature demonstrates that larger size, physical defenses, and behavior are frequently, but not always, effective defenses against copepod predators, but the outcomes of predator–prey interactions can be highly species-specific and difficult to predict, in spite of these generalities (e.g., Stemberger, 1985; Brandl, 2005).
Temperature did not appear to alter predation rates across these taxa, although the rotifers appeared to reproduce more in the 15°C treatment, suggesting that life history can play a strong role in determining population-level outcomes of predator–prey dynamics. Rotifers have generally shown increased reproduction at temperatures greater than 15°C (Halbach, 1973; Pourriot & Clement, 1981; Pourriot & Rougier, 1997), and the egg development time for some rotifers can be on the order of 6 h (Kostopoulou & Vadstein, 2007). Since strong, species-specific relationships between temperature and population growth in rotifers can result in changes that occur on short time scales of hours and days (Edmondson, 1946; Halbach, 1973), there is likely some range of temperature in which rotifers may replace themselves more rapidly than they are removed by Cyclops. Beyond rotifer replacement, temperature may have more complex effects on predator–prey outcomes at the level of populations through shifts in timing and magnitude of Cyclops recruitment (Ekvall & Hansson, 2012) or through increases in top-down predation pressures by larger consumers (Gyllström et al., 2005). When considering the inter-generational effects of temperature change on community structure, Pavón-Meza et al. (2007) demonstrated in Brachionus that temperature and food availability can influence body size and spine length, factors which can affect predation. Although Dell et al. (2014) demonstrated that predator–prey interactions are likely to shift in tandem with gradually changing temperatures, long-term changes in temperature at Baikal do not appear to be synchronous across species. Temperature increases in Lake Baikal have been correlated with 12-fold increases in cyclopoid abundance, while the endemic, herbivorous Epischura have not shown significant population changes despite increase in their algal food source (Izmest’eva et al., 2011, 2016). Considering the large increase in C. kolensis over the past 60 years, it is conceivable that the rotifers may experience an increased predation pressure even if they do not elicit as strong a predatory response from C. kolensis as do nauplii. In the context of our experiments, temperature could play a critical role for zooplankton community dynamics between generations, but within the short time span of our experiments, predation at different temperatures did not alter outcomes of predator–prey interactions.
While much work has already explored the predation patterns of copepods on rotifers, patterns tend to be species-specific, whereas rotifers avoid predation through a host of defense mechanisms and behavioral patterns (Brandl, 2005). In a review of cyclopoid predation on rotifer prey, Brandl (2005) compiled extensive information of known cyclopoid predation on rotifer species, as well as synthesized general trends among cyclopoid and rotifer species. Community composition, predator satiation, and prey density can play major roles in prey selection, in addition to species-specific defenses.
Significance in the context of a changing climate
Located in the heart of Siberia, Lake Baikal remains a hotspot for endemic biodiversity of coldwater stenotherms (Moore et al., 2009). With increasing water temperatures in lakes worldwide, it is unclear how coldwater-adapted species will respond and alter plankton communities. In the case of these Lake Baikal rotifers, we did not see evidence that their abundance might be reduced through changes in Cyclops predation. If anything, rotifers may prosper at somewhat higher temperatures in spite of predation, due to their ability to rapidly reproduce with increasing average temperatures (Halbach, 1973; Pourriot & Rougier, 1997; Pourriot & Clement, 1981). However, while the patterns we observed here were independent of temperature, the dominant herbivore in Lake Baikal, E. baikalensis, is known to be intolerant of temperatures above 15°C (Kozhov, 1963; Afanasyeva, 1977), which could precipitate major plankton community changes. With Baikal’s average water temperatures increasing rapidly (Hampton et al., 2008) in concert with climate change, it is possible that copepod nauplii, typically the most abundant prey type, might become less abundant and prompt C. kolensis to prey more heavily on rotifer prey.
We would like to thank the faculty, students, staff, and mariners of the Irkutsk State University’s Biological Research Institute Biostation for expert field and laboratory support, Marianne Moore, Bart De Stasio, and Eugene Silow for helpful advice; Dick Keefe for translation assistance; and Steve Powers, Stephanie Labou, and Steve Katz for diverse technical and statistical assistance. Funding was provided by the National Science Foundation (NSF-DEB-1136637) to S.E.H., a Fulbright Fellowship to M.F.M., and the Russian Ministry of Education and Science Research Project (No. GR 01201461929; 1354-2014/51).
- Afanasyeva, E. L., 1977. Biology of Epischura in Lake Baikal. Nauka, Novosibirsk, 144 pp.Google Scholar
- Gyllström, M., L. A. Hansson, E. Jeppesen, F. G. Criado, E. Gross, K. Irvine, T. Kairesalo, R. Kornijów, M. R. Miracle, M. Nykänen, & others, 2005. The role of climate in shaping zooplankton communities of shallow lakes. Limnology and Oceanography 50: 2008–2021.Google Scholar
- Halbach, U., 1973. Life table data and population dynamics of the rotifer Brachionus calyciflorus Pallas as influenced by periodically oscillating temperature. In Effects of Temperature on Ectothermic Organisms. Springer, Berlin: 217–228.Google Scholar
- Izmest’eva, L. R., M. V. Moore, S. E. Hampton, C. J. Ferwerda, D. K. Gray, K. H. Woo, H. V. Pislegina, L. S. Krashchuk, S. V. Shimaraeva & E. A. Silow, 2016. Lake-wide physical and biological trends associated with warming in Lake Baikal. Journal of Great Lakes Research 42: 6–17.CrossRefGoogle Scholar
- Kozhova, O. M. & L. R. Izmest’eva, 1998. Lake Baikal: Evolution and Biodiversity. Backhuys Publishers, Leiden: 447 pp.Google Scholar
- Kozhova, O. M., N. G. Mel’nik & G. I. Pomazkova (eds). 1978. Инcтpyкция пo oбpaбoткe пpoб плaнктoнa cчeтным мeтoдoм (Instructions for Processing and Counting Plankton Samples). Publications of Irkutsk State University: 1–50.Google Scholar
- Melnik, N. G., N. A. Bondarenko, O. I. Belykh, V. V. Blinov, V. G. Ivanov, I. V. Korovyakova, T. Y. Kostornova, M. I. Lazarev, N. F. Logacheva, G. I. Pomazkova, P. P. Sherstyankin, L. M. Sorokovikova, L. I. Tolstikova & E. P. Tereza, 2006. Distribution of pelagic invertebrates near a thermal bar in Lake Baikal. Hydrobiologia 568: 69–76.CrossRefGoogle Scholar
- Moore, M. V., C. L. Folt & R. S. Stemberger, 1996. Consequences of elevated temperatures for zooplankton assemblages in temperate lakes. Archiv für Hydrobiologie 135: 289–319.Google Scholar
- Nandini, S., F. S. Zúñiga-Juárez & S. S. S. Sarma, 2014. Direct and indirect effects of invertebrate predators on population level responses of the rotifer Brachionus havanaensis (Rotifera): direct and indirect effects of invertebrate predators. International Review of Hydrobiology 99: 107–116.CrossRefGoogle Scholar
- O’Reilly, C. M., S. Sharma, D. K. Gray, S. E. Hampton, J. S. Read, R. J. Rowley, P. Schneider, J. D. Lenters, P. B. McIntyre, B. M. Kraemer, G. A. Weyhenmeyer, D. Straile, B. Dong, R. Adrian, M. G. Allan, O. Anneville, L. Arvola, J. Austin, J. L. Bailey, J. S. Baron, J. D. Brookes, E. de Eyto, M. T. Dokulil, D. P. Hamilton, K. Havens, A. L. Hetherington, S. N. Higgins, S. Hook, L. R. Izmest’eva, K. D. Joehnk, K. Kangur, P. Kasprzak, M. Kumagai, E. Kuusisto, G. Leshkevich, D. M. Livingstone, S. MacIntyre, L. May, J. M. Melack, D. C. Mueller-Navarra, M. Naumenko, P. Noges, T. Noges, R. P. North, P.-D. Plisnier, A. Rigosi, A. Rimmer, M. Rogora, L. G. Rudstam, J. A. Rusak, N. Salmaso, N. R. Samal, D. E. Schindler, S. G. Schladow, M. Schmid, S. R. Schmidt, E. Silow, M. E. Soylu, K. Teubner, P. Verburg, A. Voutilainen, A. Watkinson, C. E. Williamson & G. Zhang, 2015. Rapid and highly variable warming of lake surface waters around the globe: global lake surface warming. Geophysical Research Letters 42: 10773–10781.CrossRefGoogle Scholar
- Pomazkova, G. I. & E. N. Kuzevanova, 1989. Динaмикa чиcлeннocти и cтpyктypa плaнктoнныx кoлoвpaтoк oзepa Бaйкaл пo мнoгoлeтним дaнным (1946–1985 гг.) (Dynamics and structure of planktonic rotifers of Lake Baikal according to long-term data (1946–1985)). Proceeding of the III Rotifer Symposium: 89–92.Google Scholar
- Pourriot, R. & P. Clement, 1981. Action de facteurs externes sur la reproduction et le cycle reproducteur de reitfè (External factors affecting reproduction and reproductive cycle of rotifers). Acta Ecologia: Ecologia Generalis 2: 135–151.Google Scholar
- Pourriot, R. & C. Rougier, 1997. Taux de reproduction en fonction de la concentration en nourriture et de la température chez trois espèces du genre Brachionus (Rotifères) (Reproduction rates in relation to food concentration and temperature in three species of the genus Brachionus (Rotifera)). Annales de Limnologie: International Journal of Limnology 33: 23–31.CrossRefGoogle Scholar
- R Core Team. 2016. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna [available on internet at http://www.R-project.org/].
- Rigosi, A., P. Hanson, D. P. Hamilton, M. Hipsey, J. A. Rusak, J. Bois, K. Sparber, I. Chorus, A. J. Watkinson, B. Qin & others, 2015. Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems. Ecological Applications 25: 186–199.Google Scholar
- Sarma, S. S. S., R. A. L. Resendiz & S. Nandini, 2011. Morphometric and demographic responses of brachionid prey (Brachionus calyciflorus Pallas and Plationus macracanthus (Daday)) in the presence of different densities of the predator Asplanchna brightwellii (Rotifera: Asplanchnidae). Hydrobiologia 662: 179–187.CrossRefGoogle Scholar
- Shimaraev, M. N., L. N. Kuimova, V. N. Sinyukovich & V. V. Tsekhanovskii, 2002. Manifestation of global climate change in Lake Baikal during the 20th century. Doklady Earth Sciences 383A: 288–291.Google Scholar
- Thackeray, S. J., T. H. Sparks, M. Frederiksen, S. Burthe, P. J. Bacon, J. R. Bell, M. S. Botham, T. M. Brereton, P. W. Bright, L. Carvalho, T. Clutton-Brock, A. Dawson, M. Edwards, J. M. Elliott, R. Harrington, D. Johns, I. D. Jones, J. T. Jones, D. I. Leech, D. B. Roy, W. A. Scott, M. Smith, R. J. Smithers, I. J. Winfield & S. Wanless, 2010. Trophic level asynchrony in rates of phenological change for marine, freshwater and terrestrial environments: phenological change across major environments. Global Change Biology 16: 3304–3313.CrossRefGoogle Scholar