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Understanding how variance in environmental factors affects physiological performance, population growth, and persistence is central in ecology. Despite recent interest in the effects of variance in single biological drivers, such as temperature, we have lacked a comprehensive framework for predicting how the variances and covariances between multiple environmental factors will affect physiological rates. Here, we integrate current theory on variance effects with co-limitation theory into a single unified conceptual framework that has general applicability. We show how the framework can be applied (1) to generate mathematically tractable predictions of the physiological effects of multiple fluctuating co-limiting factors, (2) to understand how each co-limiting factor contributes to these effects, and (3) to detect mechanisms such as acclimation or physiological stress when they are at play. We show that the statistical covariance of co-limiting factors, which has not been considered before, can be a strong driver of physiological performance in various ecological contexts. Our framework can provide powerful insights on how the global change-induced shifts in multiple environmental factors affect the physiological performance of organisms.
The understanding of environmentally induced changes in the biochemical composition of phytoplankton species is of great importance in both physiological studies and ecological food web research. In extensive laboratory experiments we tested the influence of two different temperatures (10 degrees C and 25 degrees C) and a phosphorus supply gradient on the sterol concentrations of the three freshwater phytoplankton species Scenedesmus quadricauda, Cryptomonas ovata and Cyclotella meneghiniana. The diatom C. meneghiniana was additionally exposed to a silicate gradient. In two separate experiments we analysed (1) possible interactive effects of temperature and phosphorus supply and (2) the effect of four phosphorus levels and three silicate levels on algal sterol concentrations. We observed that sterol concentrations were higher at 25 degrees C than at 10 degrees C in S. quadricauda and C. meneghiniana, but were not affected by temperature in C. ovata. Interactive effects of temperature and phosphorus supply on sterol concentrations were found in C. meneghiniana. This presumably was due to the bioconversion of one sterol (24-methylenecholesterol) into another (22-dihydrobrassicasterol). Increasing phosphorus supply resulted in species-specific effects on sterol concentrations, viz. an optimum curve response in S. quadricauda, a saturation curve response in C. meneghiniana and no change in sterol concentration in C. ovata. Effects of silicate supply on the sterols of C. meneghiniana equalled the effects of phosphorus supply. Albeit we did not observe a general trend in the three phytoplankton species tested, we conclude that sterol concentrations of phytoplankton are strongly affected by temperature and nutrient supply. Interactive effects point out the importance of taking into account more than just one environmental factor when assessing the effects of environmentally induced changes on phytoplankton sterol concentrations.
We tested, in the laboratory, the influence of light intensity, temperature, and phosphorus (P) supply on fatty acid (FA) concentrations of four freshwater algae: the green algae Scenedesmus quadricauda (Turpin) Breb. and Chlamydomonas globosa J. Snow, the cryptophyte Cryptomonas ovata Ehrenb., and the diatom Cyclotella meneghiniana Kutz. We investigated the main and interactive effects of two variables on algal FA concentrations (i.e., light intensity and P supply or temperature and P supply). Interactive effects of light intensity and P supply were most pronounced in C. meneghiniana, but were also found in S. quadricauda and C. ovata. Changes in several saturated and unsaturated FA concentrations with light were more distinct in the low-P treatments than in the high-P treatments. Interactive effects of temperature and P supply on various FA concentrations were observed in all four species, but there was no consistent pattern. In lake ecosystems, P limitation often coincides with high light intensities and temperatures in summer. Therefore, it is important to examine how combinations of these environmental conditions affect FA concentrations of primary producers that are important sources of FAs for higher trophic levels.
1. The polyunsaturated fatty acid eicosapentaenoic acid (EPA) plays an important role in aquatic food webs, in particular at the primary producerconsumer interface where keystone species such as daphnids may be constrained by its dietary availability. Such constraints and their seasonal and interannual changes may be detected by continuous measurements of EPA concentrations. However, such EPA measurements became common only during the last two decades, whereas long-term data sets on plankton biomass are available for many well-studied lakes. Here, we test whether it is possible to estimate EPA concentrations from abiotic variables (light and temperature) and the biomass of prey organisms (e.g. ciliates, diatoms and cryptophytes) that potentially provide EPA for consumers. 2. We used multiple linear regression to relate size- and taxonomically resolved plankton biomass data and measurements of temperature and light intensity to directly measured EPA concentrations in Lake Constance during a whole year. First, we tested the predictability of EPA concentrations from the biomass of EPA-rich organisms (diatoms, cryptophytes and ciliates). Secondly, we included the variables mean temperature and mean light intensity over the sampling depth (020 m) and depth (08 and 820 m) as factors in our model to check for large-scale seasonal- and depth-dependent effects on EPA concentrations. In a third step, we included the deviations of light and temperature from mean values in our model to allow for their potential influence on the biochemical composition of plankton organisms. We used the Akaike Information Criterion to determine the best models. 3. All approaches supported our proposition that the biomasses of specific plankton groups are variables from which seston EPA concentrations can be derived. The importance of ciliates as an EPA source in the seston was emphasised by their high weight in our models, although ciliates are neglected in most studies that link fatty acids to seston taxonomic composition. The large-scale seasonal variability of light intensity and its interaction with diatom biomass were significant predictors of EPA concentrations. The deviation of temperature from mean values, accounting for a depth-dependent effect on EPA concentrations, and its interaction with ciliate biomass were also variables with high predictive power. 4. The best models from the first and second approaches were validated with measurements of EPA concentrations from another year (1997). The estimation with the best model including only biomass explained 80%, and the best model from the second approach including mean temperature and depth explained 87% of the variability in EPA concentrations in 1997. 5. We show that it is possible to predict EPA concentrations reliably from plankton biomass, while the inclusion of abiotic factors led to results that were only partly consistent with expectations from laboratory studies. Our approach of including biotic predictors should be transferable to other systems and allow checking for biochemical constraints on primary consumers.