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Comparison of the life-history parameters and competition outcome with Moina macrocopa between two morphs of Brachionus forficula.

ABSTRACT: In rotifers, the costs of morphological defenses, especially the development of long spines, have been investigated for several decades. However, the obtained results were inconsistent and the underlying reasons were complicated. Investigations on more species might be helpful to find out the reasons. In the present study, Brachionus forficula was selected as the model organism. The differences in developmental durations, life-table demography, starvation resistant time and the competitive ability with Moina macrocopa were compared between B. forficula with long (LPS) and short (SPS) posterior spines. The results showed that LPS showed relatively longer durations of juvenile stage at 1.0?×?106, 2.0?×?106 and 4.0?×?106 cells/ml Scenedesmus obliquus, and longer embryo stage at 2.0?×?106 cells/ml S. obliquus than SPS. The intrinsic rate of population increase and net reproduction rate were lower in LPS than SPS, suggesting the energy input to reproduction decreased. The starvation resistant time was also reduced in LPS, in comparison to SPS, further supporting that LPS consumed more energy, which might be directed to the development of long spines. All these results revealed that LPS spent more energy for individual growth than SPS, which might be used to develop long spines. Moreover, the maximum population density and population growth rate of LPS were always lower than those of SPS, suggesting that LPS might have a weaker competition ability with M. macrocope than SPS.

SUBMITTER: Ge YL

PROVIDER: S-EPMC5902482 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Comparison of the life-history parameters and competition outcome with Moina macrocopa between two morphs of Brachionus forficula.

Ge Ya-Li YL Luo Tong T Ge Cui-Cui CC Zhan Rong R Yu Jin-Hang JH Xi Yi-Long YL Zhang Gen G

Scientific reports 20180416 1

In rotifers, the costs of morphological defenses, especially the development of long spines, have been investigated for several decades. However, the obtained results were inconsistent and the underlying reasons were complicated. Investigations on more species might be helpful to find out the reasons. In the present study, Brachionus forficula was selected as the model organism. The differences in developmental durations, life-table demography, starvation resistant time and the competitive abili ...[more]

PMID: 29662078

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Project description:Biological processes exhibit complex temporal dependencies due to the sequential nature of allocation decisions in organisms' life cycles, feedback loops and two-way causality. Consequently, longitudinal data often contain cross-lags: the predictor variable depends on the response variable of the previous time step. Although statisticians have warned that regression models that ignore such covariate endogeneity in time series are likely to be inappropriate, this has received relatively little attention in biology. Furthermore, the resulting degree of estimation bias remains largely unexplored. We use a graphical model and numerical simulations to understand why and how regression models that ignore cross-lags can be biased, and how this bias depends on the length and number of time series. Ecological and evolutionary examples are provided to illustrate that cross-lags may be more common than is typically appreciated and that they occur in functionally different ways. We show that routinely used regression models that ignore cross-lags are asymptotically unbiased. However, this offers little relief, as for most realistically feasible lengths of time-series conventional methods are biased. Furthermore, collecting time series on multiple subjects-such as populations, groups or individuals-does not help to overcome this bias when the analysis focusses on within-subject patterns (often the pattern of interest). Simulations, a literature search and a real-world empirical example together suggest that approaches that ignore cross-lags are likely biased in the direction opposite to the sign of the cross-lag (e.g. towards detecting density dependence of vital rates and against detecting life-history trade-offs and benefits of group living). Next, we show that multivariate (e.g. structural equation) models can dynamically account for cross-lags, and simultaneously address additional bias induced by measurement error, but only if the analysis considers multiple time series. We provide guidance on how to identify a cross-lag and subsequently specify it in a multivariate model, which can be far from trivial. Our tutorials with data and R code of the worked examples provide step-by-step instructions on how to perform such analyses. Our study offers insights into situations in which cross-lags can bias analysis of ecological and evolutionary time series and suggests that adopting dynamical models can be important, as this directly affects our understanding of population regulation, the evolution of life histories and cooperation, and possibly many other topics. Determining how strong estimation bias due to ignoring covariate endogeneity has been in the ecological literature requires further study, also because it may interact with other sources of bias.

Dataset Information

Comparison of the life-history parameters and competition outcome with Moina macrocopa between two morphs of Brachionus forficula.

Publications

Comparison of the life-history parameters and competition outcome with Moina macrocopa between two morphs of Brachionus forficula.

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