Refine
Has Fulltext
- no (8)
Year of publication
- 2019 (8) (remove)
Document Type
- Article (8) (remove)
Language
- English (8)
Is part of the Bibliography
- yes (8)
Keywords
- BEMOVI (1)
- Bayesian inference (1)
- Brachionus calyciflorus (1)
- Common garden experiments (1)
- Extreme habitats (1)
- Extremophiles (1)
- Field conditions (1)
- Herbivorous insects (1)
- Keratella cochlearis (1)
- Movement ecology (1)
- Nutritional quality (1)
- Plant-soil feedback (1)
- Risk avoidance behavior (1)
- Rotifers (1)
- Selective herbivory (1)
- Zooplankton (1)
- algae (1)
- biogeochemistry (1)
- chemostat experiments (1)
- community assembly (1)
- functional traits (1)
- lake (1)
- ocean (1)
- ordinary differential equation (1)
- parameter estimation (1)
- population dynamics (1)
- predator prey (1)
- time series analysis (1)
- trait variability (1)
Predator-prey cycles rank among the most fundamental concepts in ecology, are predicted by the simplest ecological models and enable, theoretically, the indefinite persistence of predator and prey(1-4). However, it remains an open question for how long cyclic dynamics can be self-sustained in real communities. Field observations have been restricted to a few cycle periods(5-8) and experimental studies indicate that oscillations may be short-lived without external stabilizing factors(9-19). Here we performed microcosm experiments with a planktonic predator-prey system and repeatedly observed oscillatory time series of unprecedented length that persisted for up to around 50 cycles or approximately 300 predator generations. The dominant type of dynamics was characterized by regular, coherent oscillations with a nearly constant predator-prey phase difference. Despite constant experimental conditions, we also observed shorter episodes of irregular, non-coherent oscillations without any significant phase relationship. However, the predator-prey system showed a strong tendency to return to the dominant dynamical regime with a defined phase relationship. A mathematical model suggests that stochasticity is probably responsible for the reversible shift from coherent to non-coherent oscillations, a notion that was supported by experiments with external forcing by pulsed nutrient supply. Our findings empirically demonstrate the potential for infinite persistence of predator and prey populations in a cyclic dynamic regime that shows resilience in the presence of stochastic events.
Estimating parameters from multiple time series of population dynamics using bayesian inference
(2019)
Empirical time series of interacting entities, e.g., species abundances, are highly useful to study ecological mechanisms. Mathematical models are valuable tools to further elucidate those mechanisms and underlying processes. However, obtaining an agreement between model predictions and experimental observations remains a demanding task. As models always abstract from reality one parameter often summarizes several properties. Parameter measurements are performed in additional experiments independent of the ones delivering the time series. Transferring these parameter values to different settings may result in incorrect parametrizations. On top of that, the properties of organisms and thus the respective parameter values may vary considerably. These issues limit the use of a priori model parametrizations. In this study, we present a method suited for a direct estimation of model parameters and their variability from experimental time series data. We combine numerical simulations of a continuous-time dynamical population model with Bayesian inference, using a hierarchical framework that allows for variability of individual parameters. The method is applied to a comprehensive set of time series from a laboratory predator-prey system that features both steady states and cyclic population dynamics. Our model predictions are able to reproduce both steady states and cyclic dynamics of the data. Additionally to the direct estimates of the parameter values, the Bayesian approach also provides their uncertainties. We found that fitting cyclic population dynamics, which contain more information on the process rates than steady states, yields more precise parameter estimates. We detected significant variability among parameters of different time series and identified the variation in the maximum growth rate of the prey as a source for the transition from steady states to cyclic dynamics. By lending more flexibility to the model, our approach facilitates parametrizations and shows more easily which patterns in time series can be explained also by simple models. Applying Bayesian inference and dynamical population models in conjunction may help to quantify the profound variability in organismal properties in nature.
Isolated extreme habitats are ideally suited to investigate pivotal ecological processes such as niche use, local adaptation and dispersal. Extremophilic animals living in isolated habitats face the problem that dispersal is limited through the absence of suitable dispersal corridors, which in turn facilitates local adaptation. We used five rotifer isolates from extremely acidic mining lakes with a pH of below 3 as model organisms to test whether these isolates are acidotolerant or acidophilic, whether they survive and reproduce at their niche edges (here pH 2 and circum-neutral pH) and whether local adaptation has evolved. To evaluate potential dispersal limitation, we tested whether animals and their parthenogenetic eggs survive and remain reproductive or viable at unfavourable pH-conditions. All five isolates were acidophilic with a pH-optimum in the range of 4-6, which is well above the pH (< 3) of their lakes of origin. At unfavourable high pH, in four out of the five isolates parthenogenetic females produced a high number of non-viable eggs. Females and eggs produced at favourable pH (4) remained vital at an otherwise unfavourable pH of 7, indicating that for dispersal no acidic dispersal corridors are necessary. Common garden experiments revealed no clear evidence for local adaptation in any of the five isolates. Despite their acidophilic nature, all five isolates can potentially disperse via circum-neutral water bodies as long as their residence time is short, suggesting a broader dispersal niche than their realized niche. Local adaptation might have been hampered by the low population sizes of the rotifers in their isolated habitat and the short time span the mining lakes have existed.
Under natural conditions, aboveground herbivory and plant-soil feedbacks (PSFs) are omnipresent interactions strongly affecting individual plant performance. While recent research revealed that aboveground insect herbivory generally impacts the outcome of PSFs, no study tested to what extent the intensity of herbivory affects the outcome. This, however, is essential to estimate the contribution of PSFs to plant performance under natural conditions in the field. Here, we tested PSF effects both with and without exposure to aboveground herbivory for four common grass species in nine grasslands that formed a gradient of aboveground invertebrate herbivory. Without aboveground herbivores, PSFs for each of the four grass species were similar in each of the nine grasslands-both in direction and in magnitude. In the presence of herbivores, however, the PSFs differed from those measured under herbivory exclusion, and depended on the intensity of herbivory. At low levels of herbivory, PSFs were similar in the presence and absence of herbivores, but differed at high herbivory levels. While PSFs without herbivores remained similar along the gradient of herbivory intensity, increasing herbivory intensity mostly resulted in neutral PSFs in the presence of herbivores. This suggests that the relative importance of PSFs for plant-species performance in grassland communities decreases with increasing intensity of herbivory. Hence, PSFs might be more important for plant performance in ecosystems with low herbivore pressure than in ecosystems with large impacts of insect herbivores.
Negative phototactic response to UVR in three cosmopolitan rotifers: a video analysis approach
(2019)
Genetic divergence is impacted by many factors, including phylogenetic history, gene flow, genetic drift, and divergent selection. Rotifers are an important component of aquatic ecosystems, and genetic variation is essential to their ongoing adaptive diversification and local adaptation. In addition to coding sequence divergence, variation in gene expression may relate to variable heat tolerance, and can impose ecological barriers within species. Temperature plays a significant role in aquatic ecosystems by affecting species abundance, spatio-temporal distribution, and habitat colonization. Recently described (formerly cryptic) species of the Brachionus calyciflorus complex exhibit different temperature tolerance both in natural and in laboratory studies, and show that B. calyciflorus sensu stricto (s.s.) is a thermotolerant species. Even within B. calyciflorus s.s., there is a tendency for further temperature specializations. Comparison of expressed genes allows us to assess the impact of stressors on both expression and sequence divergence among disparate populations within a single species. Here, we have used RNA-seq to explore expressed genetic diversity in B. calyciflorus s.s. in two mitochondrial DNA lineages with different phylogenetic histories and differences in thermotolerance. We identify a suite of candidate genes that may underlie local adaptation, with a particular focus on the response to sustained high or low temperatures. We do not find adaptive divergence in established candidate genes for thermal adaptation. Rather, we detect divergent selection among our two lineages in genes related to metabolism (lipid metabolism, metabolism of xenobiotics).
Trait-based approaches to investigate (short- and long-term) phytoplankton dynamics and community assembly have become increasingly popular in freshwater and marine science. Although the nature of the pelagic habitat and the main phytoplankton taxa and ecology are relatively similar in both marine and freshwater systems, the lines of research have evolved, at least in part, separately. We compare and contrast the approaches adopted in marine and freshwater ecosystems with respect to phytoplankton functional traits. We note differences in study goals relating to functional trait use that assess community assembly and those that relate to ecosystem processes and biogeochemical cycling that affect the type of characteristics assigned as traits to phytoplankton taxa. Specific phytoplankton traits relevant for ecological function are examined in relation to
herbivory, amplitude of environmental change and spatial and temporal scales of study. Major differences are identified, including the shorter time scale for regular environmental change in freshwater ecosystems compared to that in the open oceans as well as the
type of sampling done by researchers based on site-accessibility. Overall, we encourage researchers to better motivate why they apply trait-based analyses to their studies and to make use of process-driven approaches, which are more common in marine studies. We further propose fully comparative trait studies conducted along the habitat gradient spanning freshwater to brackish to marine systems, or along geographic gradients. Such studies will benefit from the combined strength of both fields.