Towards the Construction of a Mathematically Rigorous Framework for the Modelling of Evolutionary Fitness

Is it good to be bad? An evolutionary analysis of the adaptive potential of psychopathic traits

Although psychopathy is widely conceptualised as a mental disorder, some researchers question the maladaptive nature of psychopathy, and argue that it might be advantageous from an evolutionary point of view. According to this view, psychopathy can be seen as an evolutionary adaptative strategy that relies on deception and manipulation to gain short-term reproductive benefits. Psychopathy is also identified as a fast life strategy in response to early life stress and an adaptation to harsh environments. This paper investigates the evidence that psychopathic traits are adaptive, while also addressing the limitations of current evolutionary models of psychopathy based on frequency-dependent selection and life history theory. We review recent studies on the fitness correlates of psychopathy and find that psychopathic traits present potential adaptive trade-offs between fertility and mortality, and offspring quantity and quality. On a proximate level, individual differences in stress reactivity and environmental risk factors in early development predispose to psychopathy through gene-environment interactions. We propose that environmental, developmental, social and cultural factors can mediate the relationship between psychopathic traits and fitness and therefore should be considered to make accurate predictions on the adaptive potential of psychopathy. We end by outlining gaps in the literature and making recommendations for future evolutionary research on psychopathy.

Exploring Evolutionary Fitness in Biological Systems Using Machine Learning Methods

Here, we propose a computational approach to explore evolutionary fitness in complex biological systems based on empirical data using artificial neural networks. The essence of our approach is the following. We first introduce a ranking order of inherited elements (behavioral strategies or/and life history traits) in considered self-reproducing systems: we use available empirical information on selective advantages of such elements. Next, we introduce evolutionary fitness, which is formally described as a certain function reflecting the introduced ranking order. Then, we approximate fitness in the space of key parameters using a Taylor expansion. To estimate the coefficients in the Taylor expansion, we utilize artificial neural networks: we construct a surface to separate the domains of superior and interior ranking of pair inherited elements in the space of parameters. Finally, we use the obtained approximation of the fitness surface to find the evolutionarily stable (optimal) strategy which maximizes fitness. As an ecologically important study case, we apply our approach to explore the evolutionarily stable diel vertical migration of zooplankton in marine and freshwater ecosystems. Using machine learning we reconstruct the fitness function of herbivorous zooplankton from empirical data and predict the daily trajectory of a dominant species in the northeastern Black Sea.

Biological system energy algorithm reflected in sub-system joint work distribution movement strategies: influence of strength and eccentric loading

To better understand and define energy algorithms during physical activity as it relates to strength and movement strategy of the hip, knee and ankle, a model of increasing eccentric load was implemented in the current investigation utilizing a countermovement jump and a series of drop jumps from different heights (15, 30, 45, 60, 75 cm). Twenty-one participants were grouped by sex (men, n = 9; women, n = 12) and muscle strength (higher strength, n = 7; moderate strength, n = 7; lower strength, n = 7) as determined by a maximal squat test. Force plates and 3D motion capture were utilized to calculate work for the center of mass (COM) of the whole body and individually for the hip, knee and ankle joints. Statistically significant lower net work of the COM was observed in women and lower strength participants in comparison to men and moderate strength and higher strength participants respectively (p ≤ 0.05). This was primarily due to higher negative to positive work ratios of the COM in women and lower strength participants during all jumps. Furthermore, the COM negative work was primarily dissipated at the knee joint in women and in the lower strength group, particularly during the higher drop jump trials, which are representative of a demanding eccentric load task. A definitive energy algorithm was observed as a reflection of altering joint work strategy in women and lower strength individuals, indicating a possible role in knee joint injury and modulation of such by altering muscular strength.

Modelling optimal behavioural strategies in structured populations using a novel theoretical framework

Understanding complex behavioural patterns of organisms observed in nature can be facilitated using mathematical modelling. The conventional paradigm in animal behavior modelling consists of maximisation of some evolutionary fitness function. However, the definition of fitness of an organism or population is generally subjective, and using different criteria can lead us to contradictory model predictions regarding optimal behaviour. Moreover, structuring of natural populations in terms of individual size or developmental stage creates an extra challenge for theoretical modelling. Here we revisit and formalise the definition of evolutionary fitness to describe long-term selection of strategies in deterministic self-replicating systems for generic modelling settings which involve an arbitrary function space of inherited strategies. Then we show how optimal behavioural strategies can be obtained for different developmental stages in a generic von-Foerster stage-structured population model with an arbitrary mortality term. We implement our theoretical framework to explore patterns of optimal diel vertical migration (DVM) of two dominant zooplankton species in the north-eastern Black Sea. We parameterise the model using 7 years of empirical data from 2007-2014 and show that the observed DVM can be explained as the result of a trade-off between depth-dependent metabolic costs for grazers, anoxia zones, available food, and visual predation.

Revealing Evolutionarily Optimal Strategies in Self-Reproducing Systems via a New Computational Approach

Modelling the evolution of complex life history traits and behavioural patterns observed in the natural world is a challenging task. Here, we develop a novel computational method to obtain evolutionarily optimal life history traits/behavioural patterns in population models with a strong inheritance. The new method is based on the reconstruction of evolutionary fitness using underlying equations for population dynamics and it can be applied to self-reproducing systems (including complicated age-structured models), where fitness does not depend on initial conditions, however, it can be extended to some frequency-dependent cases. The technique provides us with a tool to efficiently explore both scalar-valued and function-valued traits with any required accuracy. Moreover, the method can be implemented even in the case where we ignore the underlying model equations and only have population dynamics time series. As a meaningful ecological case study, we explore optimal strategies of diel vertical migration (DVM) of herbivorous zooplankton in the vertical water column which is a widespread phenomenon in both oceans and lakes, generally considered to be the largest synchronised movement of biomass on Earth. We reveal optimal trajectories of daily vertical motion of zooplankton grazers in the water column depending on the presence of food and predators. Unlike previous studies, we explore both scenarios of DVM with static and dynamic predators. We find that the optimal pattern of DVM drastically changes in the presence of dynamic predation. Namely, with an increase in the amount of food available for zooplankton grazers, the amplitude of DVM progressively increases, whereas for static predators DVM would abruptly cease.