The importance of the velodrome & mesocosms in endurance experiments
The velodrome or any other set of environmental conditions that more effectively mimic the field dynamics that an elite athlete experiences in competition is critical. Tests using mesocosms should be included in all endurance-training camps & integrated throughout all protocols.
In ecology, scale and context dependencies shape many of the dynamics associated with the outcome of a given experiment or even measurement of natural patterns. Historically, this generated a set of counterarguments against synthesis efforts and was summarized as ‘every place is different and the local ecology reflects these differences’ so you cannot combine them. In meta-analyses, this problem is often labeled the comparing of apples and oranges argument. Nonetheless, after extensive studies in both the same and many different ecosystems, ecology crossed the threshold into ‘big data’, and we now use synthesis tools extensively to explore the relative importance of local versus global drivers of change. However, at an individual experiment level, there is a still a tension between detailed, local, controlled experiments, i.e. in pots in the greenhouse with everything controlled as best we can, to field experiments that incorporate both the most likely factors that shape the outcome of competition trials for instance but also all the other covariates that influence the identity of the winner. There are of course best practices associated with each scale of inquiry, for instance how to do greenhouse studies best or how to interpret them appropriately, but a really fantastic comprise that is underutilized are mesocosms. Imagine trying to manipulate and control all the dynamics of a lake and having a set of replicate lakes for every major treatment. There have been experiments that effectively executed this scale of experimentation, but it is costly and relatively infrequent. Using large tubs to simulate a lake that you control as best you can is a balance between whole lake manipulations and experiments in the lab using small volumes of water in dishes.
The perfect analogy is the Red Bull endurance camp 2.0 testing for fatigue effects in the lab on fixed bikes, i.e., a 4k time trial with full instrumentation estimating VO2 etc., versus a 4k trial on a velodrome track. Importantly, the differences between these two sets of testing conditions are likely a critical driver of fatigue differences and should be handled appropriately. All athletes were not velodrome or track competitors, and the level of concentration and thus potential capacity for this trial to induce fatigue through indirect pathways is unique. There are of course numerous advantages to testing performance strictly in the lab or in measuring less factors in the more ‘natural’ context of the field, but the velodrome is a mesocosm that approximates more of the conditions associated with actual racing is an excellent step. Consequently, there is an excellent opportunity to use this general approach in mapping, manipulating, and measuring human performance (the 3Ms) regardless of whether it is athletic, managerial, or cognitive testing.
If we accept that exploring the hypothesis that novel environments approximating the conditions of competition associated with human performance in any domain are critical, then we can consider the following design ideas.
(1) Scale. Unpacking and expanding testing human performance onto mesocosm-length gradients is an invaluable tool in hacking competitive outcomes. Fixed bike versus short track for instance is an important agent of heterogeneity to incorporate.
(2) Challenge. Novel challenges can promote increased performance both cognitively and physically. In this context, keeping speed up, controlling the bike in banks, and riding a good line were important factors that impact fatigue and also potentially enhanced performance through adrenaline.
(3) Simulate field/race competition conditions. Embracing and negotiating limited variability (i.e. greater than lab on fixed bike but not a bmx course) in testing conditions challenges and promotes plasticity and is also likely an effective agent of endurance in any endeavor.
(4) Effects on fatigue. Concentration on non-muscle memory tasks likely impacts the capacity for a set of tests to explore the central governor model of fatigue. Cognitive demands under the assumptions of this model mediate the anticipatory responsiveness of an athlete.
(1) Ideally, testing should alternate between lab and velodrome or mesocosm. Three days of intensive lab testing introduced a sequential/serial effect on the performance of subjects in the velodrome. What if the velodrome testing was done first and it also introduces more fatigue? Would the lab results look very different? There are numerous options, but logistics will likely prevail in design decisions. Alternate daily between lab and velodrome. Use two complete stations, lab and mescosm, and randomly assign athletes to each set of treatments by environment randomly across all days. Etc.
(2) In all endurance camp training/testing, add a simple cognitive function test. Lumosity games, Sudoku, puzzles, tetris, or something short that is easy to complete but functions as a comparator to the physical stress currently implemented. The test should also measure and provide quantitative cognitive function or performance estimates (most cool apps do that now). These data could be an additional estimate for mental or potential central governor interactions with fatigue. Presumably, concentration also changes nonlinearly with physical fatigue, and this relationship can then be examined. The entire experience of camp induces fatigue very broadly because of travel, sleep patterns, diet, and the intensity of the logistics. Hence, record the residual effects, if any, on cognitive function by using new puzzles etc. after the camp is over for a period of time. Mix some of the gaming function, e-sports metrics with the responses recorded for these athletes in endurance camps.
(3) Compare lab results for standard measures, such as emg, to race condition datasets for each athlete. This would provide an external baseline outside of the context of the training camp to ‘calibrate’ the intensity and relative importance of the protocols applied during the controlled testing. Repeat and continue after training camps end to explore whether the process of experimentation in the lab/mesocosm has a residual performance effect. Measure some of the response variables for each athlete a week after the camp on a trial ride.
Ultimately, synthesis of short-term intensive experimentation on human performance is enhanced if better approximations of competition are explored and if we increase both the elasticity and time span of the responses measured. Human performance does not however have to end here. Mindfulness of fatigue impacts on performance more generally will benefit all of us, and a better understanding of the relative impact of the central governor on helping us push through tasks, and when, is invaluable.