Comparing growth patterns of three species: Similarities and differences

Growth modeling approach with the Verhulst coexistence dynamic properties for regulation purposes

For this research, the properties of the logistic growth model for independent and coexisting species were used to set definitions for the possible regulation of one or two growth variables through their coupling parameters. The present analysis is done for the single-species Verhulst model without coupling, the single-species Verhulst model coupled with an exogenous signal, and the two-species Verhulst coexistence growth model which represents six different ecological regimes of interaction. The models' parameters, such as the intrinsic growth rate and the coupling, are defined. Finally, the control results are expressed as lemmas for regulation, and they are shown using a simulation example of a fish population growing independent of human interaction (no harvesting, no fishing) and the simulation of the regulation of said population when the coupling of fish and humans is involved (harvesting, fishing).

Transcriptomic signals of mitochondrial dysfunction and OXPHOS dynamics in fast-growth chicken

Introduction

Birds are equipped with unique evolutionary adaptations to counter oxidative stress. Studies suggest that lifespan is inversely correlated with oxidative damage in birds. Mitochondrial function and performance are critical for cellular homeostasis, but the age-related patterns of mitochondrial gene expression and oxidative phosphorylation (OXPHOS) in birds are not fully understood. The domestic chicken is an excellent model to understand aging in birds; modern chickens are selected for rapid growth and high fecundity and oxidative stress is a recurring feature in chicken. Comparing fast- and slow-growing chicken phenotypes provides us an opportunity to disentangle the nexus of oxidative homeostasis, growth rate, and age in birds.

Methods and Results

We compared pectoralis muscle gene expression patterns between a fast and a slow-growing chicken breed at 11 and 42 days old. Using RNAseq analyses, we found that mitochondrial dysfunction and reduced oxidative phosphorylation are major features of fast-growth breast muscle, compared to the slow-growing heritage breed. We found transcriptomic evidence of reduced OXPHOS performance in young fast-growth broilers, which declined further by 42 days.

Discussion

OXPHOS performance declines are a common feature of aging. Sirtuin signaling and NRF2 dependent oxidative stress responses support the progression of oxidative damage in fast-growth chicken. Our gene expression datasets showed that fast growth in early life places immense stress on oxidative performance, and rapid growth overwhelms the OXPHOS system. In summary, our study suggests constraints on oxidative capacity to sustain fast growth at high metabolic rates, such as those exhibited by modern broilers.

Bertalanffy-Pütter models for avian growth

This paper explores the ratio of the mass in the inflection point over asymptotic mass for 81 nestlings of blue tits and great tits from an urban parkland in Warsaw, Poland (growth data from literature). We computed the ratios using the Bertalanffy-Pütter model, because this model was more flexible with respect to the ratios than the traditional models. For them, there were a-priori restrictions on the possible range of the ratios. (Further, as the Bertalanffy-Pütter model generalizes the traditional models, its fit to the data was necessarily better.) For six birds there was no inflection point (we set the ratio to 0), for 19 birds the ratio was between 0 and 0.368 (lowest ratio attainable for the Richards model), for 48 birds it was above 0.5 (fixed ratio of logistic growth), and for the remaining eight birds it was in between; the maximal observed ratio was 0.835. With these ratios we were able to detect small variations in avian growth due to slight differences in the environment: Our results indicate that blue tits grew more slowly (had a lower ratio) in the presence of light pollution and modified impervious substrate, a finding that would not have been possible had we used traditional growth curve analysis.

Forecasting the final disease size: comparing calibrations of Bertalanffy-Pütter models

Using monthly data from the Ebola-outbreak 2013-2016 in West Africa, we compared two calibrations for data fitting, least-squares (SSE) and weighted least-squares (SWSE) with weights reciprocal to the number of new infections. To compare (in hindsight) forecasts for the final disease size (the actual value was observed at month 28 of the outbreak) we fitted Bertalanffy-Pütter growth models to truncated initial data (first 11, 12, …, 28 months). The growth curves identified the epidemic peak at month 10 and the relative errors of the forecasts (asymptotic limits) were below 10%, if 16 or more month were used; for SWSE the relative errors were smaller than for SSE. However, the calibrations differed insofar as for SWSE there were good fitting models that forecasted reasonable upper and lower bounds, while SSE was biased, as the forecasts of good fitting models systematically underestimated the final disease size. Furthermore, for SSE the normal distribution hypothesis of the fit residuals was refuted, while the similar hypothesis for SWSE was not refuted. We therefore recommend considering SWSE for epidemic forecasts.

The growth of domestic goats and sheep: A meta study with Bertalanffy-Pütter models

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We studied 122 mass-at-age data for goats, sheep, and wildlife.

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We used Bertalanffy-Pütter models to obtain better fitting growth curves.

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The Brody model had an acceptable fit to 70% of the data.

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For 39% of data the best-fitting BP-model had a discernable inflection-point.

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For these models, maximal weight gain per day was 55% higher than natal weight gain.

Growth literature often uses the Brody, Gompertz, Verhulst, and von Bertalanffy models. Is there a rationale for the preference of these classical named models? The versatile five-parameter Bertalanffy-Pütter (BP) model generalizes these models. We revisited peer-reviewed publications from the years 1970–2019 that fitted growth models to together 122 mass-at-age data of sheep and goats from 19 countries and studied the best-fit BP-models using the least-squares method. None of the named models was ever best-fitting. However, for 70% of the data a single non-sigmoidal model had an acceptable fit (normalized root mean squared error 〈 5% and F-ratio test 〉 5% in comparison to the best-fit): the Brody model. The inherently non-sigmoidal character was further underlined, as there were only 39% of the data, where the best-fitting BP-model had a discernible inflection point. For these data, conclusions of biological interest could be drawn from the sigmoidal best-fit BP-models: the maximal weight gain per day was about 55% higher than the natal weight gain per day.