The role of oxidative stress as an underlying mechanism in life-history trade-offs

A key aspect underpinning life-history theory is the existence of trade-offs. Trade-offs occur because resources are limited, meaning that individuals cannot invest in all traits simultaneously, leading to costs for traits such as growth and reproduction. Such costs may be the reason for the sub-maximal growth rates that are often observed in nature, though the fitness consequences of these costs would depend on the effects on lifetime reproductive success. Recently, much attention has been given to the physiological mechanism that might underlie these life-history trade-offs, with oxidative stress (OS) playing a key role. OS is characterised by a build-up of oxidative damage to tissues (e.g. protein, lipids and DNA) from attack by reactive species (RS). RS, the majority of which are by-products of metabolism, are usually neutralised by antioxidants, however OS occurs when there is an imbalance between the two. There are two main theories linking OS with growth and reproduction. The first is that traits like growth and reproduction, being metabolically demanding, lead to an increase in RS production. The second involves the diversion of resources away from self-maintenance processes (e.g. the redox system) when individuals are faced with enhanced growth or reproductive expenditure. Previous research investigating trade-offs involving growth or reproduction and self-maintenance has been equivocal. One reason for this could be that associations among redox biomarkers can vary greatly so that the biomarker selected for analysis can influence the conclusion reached about an individual’s oxidative status. Therefore the first aim of my thesis was to explore the strength and pattern of integration of five biomarkers of OS (three antioxidants, one damage and one general oxidation measure) in wild blue tit (Cyanistes caeruleus) adults and nestlings (Chapter 2). In doing so, I established that all five biomarkers should be included in future analyses, thus using this collection of biomarkers I explored my next aims; whether enhanced growth (Chapters 3 and 4) or reproductive effort (Chapter 5) can lead to increased OS levels, if these traits are traded off against self-maintenance. I accomplished these aims using both a meta-analytic and experimental approach, the latter involving manipulation of brood size in wild blue tits in order to experimentally alter growth rate of nestlings and provisioning rate (a proxy for reproductive expenditure) of adults. I also investigated the potential for redox integration to be used as an index of body condition (Chapter 2), allowing predictions about future fitness consequences of changes to oxidative state to be made. A growth – self-maintenance trade off was supported by my meta-analytic results (Chapter 4) which found OS to be a constraint on growth. However, when faced with experimentally enhanced growth, animals were typically not able to adjust this trade-off so that oxidative damage resulted. This might support the idea that energetically expensive growth causes resources to be diverted away from the redox system; however, antioxidants did not show an overall reduction in response to growth in the meta-analysis suggesting that oxidative costs of growth may result from increased RS production due to the greater metabolism needed for enhanced growth. My experimental data (Chapter 3) showed a similar pattern, with raised protein damage levels (protein carbonyls; PCs) in the fastest growing blue tit chicks in a brood, compared with their slower growing sibs. These within-brood differences in OS levels likely resulted from within-brood hierarchies and might have masked any between-brood differences, which were not observed here. Despite evidence for a growth – self-maintenance trade off, my experimental results on blue tits found no support for the hypothesis that self-maintenance is also traded off against reproduction, another energetically demanding trait. There was no link between experimentally altered reproductive expenditure and OS, nor was there a direct correlation between reproductive effort and OS (Chapter 5). However, there are various factors that likely influence whether oxidative costs are observed, including environmental conditions and whether such costs are transient. This emphasises the need for longitudinal studies following the same individuals over multiple years and across a wide range of habitats that differ in quality. This would allow investigation into how key life events interact; it might be that raised OS levels from rapid early growth have the potential to constrain reproduction or that high parental OS levels constrain offspring growth. Any oxidative costs resulting from these life-history trade-offs have the potential to impact on future fitness. Redox integration of certain biomarkers might prove to be a useful tool in making predictions about fitness, as I found in Chapter 2, as well as establishing how the redox system responds, as a whole, to changes to growth and reproduction. Finally, if the tissues measured can tolerate a given level of OS, then the level of oxidative damage might be irrelevant and not impact on future fitness at all.

Assessments of training load in elite youth soccer

One of the most popular sports globally, soccer has seen a rise in the demands of the game over recent years. An increase in intensity and playing demands, coupled with growing social and economic pressures on soccer players means that optimal preparation is of paramount importance. Recent research has found the modern game, depending on positional role, to consist of approximately 60% more sprint distance in the English Premier League, which was also found to be the case for frequency and success of discrete technical actions (Bush et al., 2015). As a result, the focus on soccer training and player preparedness is becoming more prevalent in scientific research. By designing the appropriate training load, and thus periodization strategies, the aim is to achieve peak fitness in the most efficient way, whilst minimising the risk of injury and illness. Traditionally, training intensity has been based on heart rate responses, however, the emergence of tracking microtechnology such as global positioning system (GPS) and inertial sensors are now able to further quantify biomechanical load as well as physiological stress. Detailed pictures of internal and external loading indices such as these then combine to produce a more holistic view of training load experience by the player during typical drills and phases of training in soccer. The premise of this research is to gain greater understanding of the physical demands of common training methodologies in elite soccer to support optimal match performance. The coaching process may then benefit from being able to prescribe the most effective training to support these. The first experimental chapter in this thesis began by quantify gross training loads of the pre-season and in-season phases in soccer. A broader picture of the training loads inherent in these distinct phases brought more detail as to the type and extent of external loading experienced by soccer players at these times, and how the inclusion of match play influences weekly training rhythms. Training volume (total distance) was found to be high at the start compared to the end of pre-season (37 kilometres and 28 kilometres), where high cardiovascular loads were attained as part of the conditioning focus. This progressed transiently, however, to involve higher-speed, acceleration and change-of-direction stimuli at the end of pre-season compared to the start and to that in-season (1.18 kilometres, 0.70 kilometres and 0.42 kilometres high-intensity running; with 37, 25 and 23 accelerations >3m/s2 respectively) . The decrease in volume and increase in maximal anaerobic activity was evident in the training focus as friendly matches were introduced before the competitive season. The influence of match-play as being a large physical dose in the training week may then determine the change in weekly periodisation and how resulting training loads applied and tapered, if necessary. The focus of research was then directed more specifically to the most common mode of training in soccer, that also featured regularly in the pre-season period in the present study, small-sided games (SSG). The subsequent studies examined numerous manipulations of this specific form of soccer conditioning, such as player numbers as well as absolute and relative playing space available. In contrast to some previous literature, changing the number of players did not seem to influence training responses significantly, although playing format in the possession style brought about larger effects for heart rate (89.9%HRmax) and average velocity (7.6km/h-1). However, the following studies (Chapters 5, 6 and 7) revealed a greater influence of relative playing space available to players in SSG. The larger area at their disposal brought about greater aerobic responses (~90%HRmax), by allowing higher average and peak velocities (>25km/h-1), as well as greater distance acceleration behaviour at greater thresholds (>2.8m/s2). Furthermore, the data points towards space as being a large determinant in strategy of the player in small-sided games (SSG), subsequently shaping their movement behaviour and resulting physical responses. For example, higher average velocities in a possession format (8km/h-1) reflects higher work rate and heart rate load but makes achieving significant neuromuscular accelerations at a high level difficult given higher starting velocities prior to the most intense accelerations (4.2km/h-1). By altering space available and even through intentional numerical imbalances in team numbers, it may be easier for coaches to achieve the desired stimulus for the session or individual player, whether that is for aerobic and neuromuscular conditioning. Large effects were found for heart rate being higher in the underloaded team (85-90%HRmax) compared to the team with more players (80-85%HRmax) as well as for RPE (5AU versus 7AU). This was also apparent for meterage and therefore average velocity. It would also seem neuromuscular load through high acceleration and deceleration efforts were more pronounced with less numbers (given the need to press and close down opponents, and in a larger area relative to the number of players on the underloaded team. The peak accelerations and deceleration achieved was also higher when playing with less players (3-6.2m/s2 and 3-6.1m/s2) Having detailed ways in which to reach desired physical loading responses in common small training formats, Chapter 8 compared SSG to larger 9v9 formats with full-size 11v11 friendly matches. This enabled absolute and relative comparisons to be made and to understand the extent to which smaller training formats are able to replicate the required movements to be successful in competition. In relative terms, it was revealed that relative acceleration distance and Player Load were higher in smaller 4v4 games than match-play (1.1m.min-1 and 0.3m.min-1 >3m/s2; 16.9AU versus 12AU). Although the smallest format did not replicate the high-velocity demands of matches, the results confirmed their efficacy in providing significant neuromuscular load during the training week, which may then be supplemented by high-intensity interval running in order to gain exposure to more maximal speed work. In summary, the data presented provide valuable information from GPS and inertial sensor microtechnology which may then be used to understand training better to manipulate types of load according to physical conditioning objectives. For example, a library of resources to direct planning of drills of varying cardiovascular, neuromuscular and perceptual load can be created to give more confidence in session outcomes. Combining external and internal load data of common soccer training drills, and their application across different phases and training objectives may give coaches a powerful tool to plan and periodize training.