Konstadia Lika

Temperature tolerance and energetics: a dynamic energy budget-based comparison of North Atlantic marine species

Temperature tolerance and sensitivity were examined for some North Atlantic marine species and linked to their energetics in terms of species-specific parameters described by dynamic energy budget (DEB) theory. There was a general lack of basic information on temperature tolerance and sensitivity for many species. Available data indicated that the ranges in tolerable temperatures were positively related to optimal growth temperatures. However, no clear relationships with temperature sensitivity were established and no clear differences between pelagic and demersal species were observed. The analysis was complicated by the fact that for pelagic species, experimental data were completely absent and even for well-studied species, information was incomplete and sometimes contradictory. Nevertheless, differences in life-history strategies were clearly reflected in parameter differences between related species. Two approaches were used in the estimation of DEB parameters: one based on the assumption that reserve hardly contributes to physical volume; the other does not make this assumption, but relies on body-size scaling relationships, using parameter values of a generalized animal as pseudo-data. Temperature tolerance and sensitivity seemed to be linked with the energetics of a species. In terms of growth, relatively high temperature optima, sensitivity and/or tolerance were related to lower relative assimilation rates as well as lower maintenance costs. Making the step from limited observations to underlying mechanisms is complicated and extrapolations should be carefully interpreted. Special attention should be devoted to the estimation of parameters using body-size scaling relationships predicted by the DEB theory.

Life History Implications of Allocation to Growth Versus Reproduction in Dynamic Energy Budgets

We compare the implications of determinate vs. indeterminate growth of a parthenogenetic iteroparous ectotherm at constant food density in the context of the dynamic energy budget theory, which specifies the tight links between life history traits, such as feeding, aging, growth and reproduction. We do a comparative analysis using, as measure of fitness, the life span reproduction, the population growth rate, and the conversion efficiency of food to biomass. When extrinsic mortality is constant, indeterminate growth cannot maximize fitness if measured by the population growth rate or the conversion efficiency, except when mortality is low, in which case both types of animals are similar. If the fitness measure is life span reproduction, indeterminate growth maximizes fitness even with constant mortality, provided it is not very high. When mortality decreases with size, indeterminate growth maximizes fitness for almost all measures of fitness. Finally, we suggest an evolutionary link between allocation strategies and expected life span. In populations of long living species, each type of animal can establish in the population of the other. In populations of short living species, determinate growers can invade, and displace, a population of indeterminate ones. However, when the mortality risk of organisms with small size is much higher than those of large size, indeterminate growers can be superior.

The bijection from data to parameter space with the standard DEB model quantifies the supply–demand spectrum

The standard Dynamic Energy Budget (DEB) model assumes that food is converted to reserve and a fraction κ of mobilised reserve of an individual is allocated to somatic maintenance plus growth, while the rest is allocated to maturity maintenance plus maturation (in embryos and juveniles) or reproduction (in adults). The add_my_pet collection of over 300 animal species from most larger phyla, and all chordate classes, shows that this model fits energy data very well. Nine parameters determine nine data points at abundant food: dry/wet weight ratio, age at birth, puberty, death, weight at birth, metamorphosis, puberty, ultimate weight and ultimate reproduction rate. We demonstrate that, given a few other parameters, these nine data points also determine the nine parameters uniquely that are independent of food availability: maturity at birth, metamorphosis and puberty, specific assimilation, somatic maintenance and costs for structure, allocation fraction of mobilised reserve to soma, energy conductance, and ageing acceleration. We provide an efficient algorithm for mapping between data and parameter space in both directions and found expressions for the boundaries of the parameter and data spaces. One of them quantifies the position of species in the supply-demand spectrum, which reflects the internalisation of energetic control. We link eco-physiological properties of species to their position in this spectrum and discuss it in the context of homeostasis. Invertebrates and ray-finned fish turn out to be close to the supply end of the spectrum, while other vertebrates, including cartilaginous fish, have stronger demand tendencies. We explain why birds and mammals up-regulate metabolism during reproduction. We study some properties of the bijection using elasticity coefficients. The properties have applications in parameter estimation and in the analysis of evolutionary constraints on parameter values; the relationship between DEB parameters and data has similarities to that between genotype and phenotype.

Resource allocation to reproduction in animals

The standard Dynamic Energy Budget (DEB) model assumes that a fraction κ of mobilised reserve is allocated to somatic maintenance plus growth, while the rest is allocated to maturity maintenance plus maturation (in embryos and juveniles) or reproduction (in adults). All DEB parameters have been estimated for 276 animal species from most large phyla and all chordate classes. The goodness of fit is generally excellent. We compared the estimated values of κ with those that would maximise reproduction in fully grown adults with abundant food. Only 13% of these species show a reproduction rate close to the maximum possible (assuming that κ can be controlled), another 4% have κ lower than the optimal value, and 83% have κ higher than the optimal value. Strong empirical support hence exists for the conclusion that reproduction is generally not maximised. We also compared the parameters of the wild chicken with those of races selected for meat and egg production and found that the latter indeed maximise reproduction in terms of κ, while surface‐specific assimilation was not affected by selection. We suggest that small values of κ relate to the down‐regulation of maximum body size, and large values to the down‐regulation of reproduction. We briefly discuss the ecological context for these findings.

Prediction of marine species distribution from presence–absence acoustic data: comparing the fitting efficiency and the predictive capacity of conventional and novel distribution models

The accurate representation of species distribution derived from sampled data is essential for management purposes and to underpin population modelling. Additionally, the prediction of species distribution for an expanded area, beyond the sampling area can reduce sampling costs. Here, several well-established and recently developed habitat modelling techniques are investigated in order to identify the most suitable approach to use with presence–absence acoustic data. The fitting efficiency of the modelling techniques are initially tested on the training dataset while their predictive capacity is evaluated using a verification set. For the comparison among models, Receiver Operating Characteristics (ROC), Kappa statistics, correlation and confusion matrices are used. Boosted Regression Trees (BRT) and Associative Neural Networks (ASNN), which are both within the machine learning category, outperformed the other modelling approaches tested.

The AmP project: Comparing species on the basis of dynamic energy budget parameters

We developed new methods for parameter estimation-in-context and, with the help of 125 authors, built the AmP (Add-my-Pet) database of Dynamic Energy Budget (DEB) models, parameters and referenced underlying data for animals, where each species constitutes one database entry. The combination of DEB parameters covers all aspects of energetics throughout the full organism’s life cycle, from the start of embryo development to death by aging. The species-specific parameter values capture biodiversity and can now, for the first time, be compared between animals species. An important insight brought by the AmP project is the classification of animal energetics according to a family of related DEB models that is structured on the basis of the mode of metabolic acceleration, which links up with the development of larval stages. We discuss the evolution of metabolism in this context, among animals in general, and ray-finned fish, mollusks and crustaceans in particular. New DEBtool code for estimating DEB parameters from data has been written. AmPtool code for analyzing patterns in parameter values has also been created. A new web-interface supports multiple ways to visualize data, parameters, and implied properties from the entire collection as well as on an entry by entry basis. The DEB models proved to fit data well, the median relative error is only 0.07, for the 1035 animal species at 2018/03/12, including some extinct ones, from all large phyla and all chordate orders, spanning a range of body masses of 16 orders of magnitude. This study is a first step to include evolutionary aspects into parameter estimation, allowing to infer properties of species for which very little is known.

Modeling the dynamic modulation of light energy in photosynthetic algae.

An integrated cell-based dynamic mathematical model that take into account the role of the photon absorbing process, the partition of excitation energy, and the photoinactivation and repair of photosynthetic units, under variable light and dissolved inorganic carbon (DIC) availability is proposed. The modeling of the photon energy absorption and the energy dissipation is based on the photoadaptive changes of the underlying mechanisms. The partition of the excitation energy is based on the relative availability of light and DIC to the cell. The modeling of the photoinactivation process is based on the common aspect that it occurs under any light intensity and the modeling of the repair process is based on the evidence that it is controlled by chloroplast and nuclear-encoded enzymes. The present model links the absorption of photons and the partitioning of excitation energy to the linear electron flow and other quenchers with chlorophyll fluorescence emission parameters, and the number of the functional photosynthetic units with the photosynthetic oxygen production rate. The energy allocation to the LEF increases as DIC availability increases and/or light intensity decreases. The rate of rejected energy increases with light intensity and with DIC availability. The resulting rate coefficient of photoinactivation increases as light intensity and/or as DIC concentration increases. We test the model against chlorophyll fluorescence induction and photosynthetic oxygen production rate measurements, obtained from cultures of the unicellular green alga Scenedesmus obliquus, and find a very close quantitative and qualitative correspondence between predictions and data.

Fish distribution predictions from different points of view: comparing associative neural networks, geostatistics and regression models

Accurate prediction of species distributions based on sampling and environmental data is essential for further scientific analysis, such as stock assessment, detection of abundance fluctuation due to climate change or overexploitation, and to underpin management and legislation processes. The evolution of computer science and statistics has allowed the development of sophisticated and well-established modelling techniques as well as a variety of promising innovative approaches for modelling species distribution. The appropriate selection of modelling approach is crucial to the quality of predictions about species distribution. In this study, modelling techniques based on different approaches are compared and evaluated in relation to their predictive performance, utilizing fish density acoustic data. Generalized additive models and mixed models amongst the regression models, associative neural networks (ANNs) and artificial neural networks ensemble amongst the artificial neural networks and ordinary kriging amongst the geostatistical techniques are applied and evaluated. A verification dataset is used for estimating the predictive performance of these models. A combination of outputs from the different models is applied for prediction optimization to exploit the ability of each model to explain certain aspects of variation in species acoustic density. Neural networks and especially ANNs appear to provide more accurate results in fitting the training dataset while generalized additive models appear more flexible in predicting the verification dataset. The efficiency of each technique in relation to certain sampling and output strategies is also discussed.

Do experimental units of different scale affect the biological performance of European sea bass Dicentrarchus labrax larvae

The effects of different tank volumes (2000, 500 and 40 l) on European sea bass Dicentrarchus labrax larval rearing, relating to growth, survival, quality and stress variables, were investigated. A dynamic energy budget (DEB) model was used to analyse the results. The hydrodynamics of the tanks exhibited differences, with the water currents in the 2000 l tanks to be almost one order of magnitude stronger than those in the 40 l ones. Important differences in fish growth were observed between small and large tank-rearing volumes, with the smallest tank resulting in the slowest growth. Based on the DEB model analysis, growth differences were related to feeding rates, with growth in the smaller tank limited by food availability. Differences in survival rates were not statistically significant among the tank-rearing volumes. The quality evaluation of the fry (in terms of swimbladder, jaw and skeletal abnormalities) showed differences, with the smallest tank having the highest percentage of deformed individuals. This could be attributed to both the feeding variances and the hydrodynamics in the tanks. No differences were observed in terms of whole-body cortisol at the two developmental stages; flexion, and when the larvae body was fully covered by melanophores; when analysis was performed. This indicates that the allostatic load exerted on fish of different groups was similar and inside the fish-coping abilities range, in terms of the cortisol response axis. The selection of the experimental scale is of importance, especially when the results are to be transferred and applied on an industrial scale.

Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model

Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) that link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstract variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.