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Applying ecological and evolutionary theory to video game data

It has been a while since I posted something. Since my last post, I moved to McGill University and started a new postdoc (funded through a NSERC fellowship). I figured I would present a project that I have been thinking about throughout the last few years. My goal is to get it going at full speed in the coming year. It involves applying an ecological approach to investigate and design massive multiplayer online video games (MMOGs). It would benefit many ecological disciplines directly by providing a way to assess how good we are at predicting and manipulating ecosystems. Hopefully, it would also benefit game designers, by providing some tools to handle the erratic and complex behavior of players.

Nintendo_video_games

Collection of video games for Nintendo consoles. Credits TarkusAB (wikipedia commons).

Now many of you are probably having a mental image of video games that looks a lot like this or this. The video game is a well-designed set of challenges that you tackle, sometimes through an avatar. Such video games are fun and very additive, but there are very different types of games out there. Games can now have an online component, allowing players to interact with each other in real time. Halo is a good example. Looking at its fan-supported encyclopedia shows the complexity and dynamism of the game’s content. These games are made up of interactions among hundreds of thousands or millions of players every day in real time. For example many, many players are constantly online in New Eden, the virtual world in which Eve-Online takes place. The scale of such interactions is comparable to the amount of interactions one would observe in some populations of free-ranging animals, or within an ecological community. Interactions among players are often occurring in a virtual world that has a clear spatial component and that is persistent (it continues to change and shift even when players are offline). Virtual worlds have their own dynamics, economies, and culture.

 

The behavior of players, and their interactions now make up a significant portion of the content of many video games. A challenge of game design is to develop a substrate that will allow players to interact and behave in diverse ways, ultimately impacting how much, how frequently, and how long players will stick to the game. Player behavior and the pattern of their interactions are very hard to predict and to control. As a result, designing MMOGs is major challenge. Many, many nascent game companies go bankrupt every month because their main project fails to recruit the critical mass of players that is required for the game content to emerge. Even when these games survive their first steps of development, they still require important and frequent updates (or patches), readjusting the rules governing interactions, or fixing a potential loophole that some players have come to exploit. These patches can themselves introduce substantial chaos. In one notable case, players’ unanticipated behavior and interactions drove a huge pandemic, killing thousands of characters and perturbing the game World of Warcraft for months. To tackle this huge challenge, game design is now informed more and more by analytics. Companies use GIS (geographic information systems) and statistical analyses to inform the development of their games, optimize the gameplay, and maximize player retention. However, the quantity of data available from video games poses the challenge of figuring out which questions or parameters should deserve the most attention.

 

The main idea behind my new project is that video game design could be informed by ecological and evolutionary theory. Ecologists deal with many of the same types of data analysis issues outlined above. In fact, they often tackle these challenges with much less data! Ecological and evolutionary theory can point out which type of data should be the most valuable to understand player behavior and interactions. Ecological and evolutionary theory can also point out which aspects of players’ behavior and interactions should be the most important in promoting stable or resilient game dynamics, or in maximizing player retention. Much like conservation, ecologically-informed game design could also enable us to build virtual worlds supporting a higher diversity of players. In turn, data on player behavior and interactions could be very valuable to test and refine ecological or evolutionary processes, which are often very hard to quantify and observe (or manipulate) in nature. Some economists have already started analyzing virtual economies, and some biologists are getting more and more interested in using video games to inform their research. I have multiple analyses on the way, so stay tuned! A student, Julien Céré also recently started his PhD on these ideas, in partnership with the company Behaviour Interactive. He aims to apply game theory and social network theory to analyze the behavior of players in specific multiplayer games. Although he is just starting, we have been getting a very good attention from the media. Keep an eye for his progress as he goes through his PhD!

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Intra-individual variability in cortisol, exploration and life history.

We recently published a paper looking at chipmunk stress reactivity, and its links with life-time exploration patterns and reproductive output in eastern chipmunks. It investigates how individual cortisol stress response is associated to its lifetime exploration pattern and its reproductive output. It also presents a way to study the stress reactivity of individuals in the wild, over many months.

1114px-Eastern_Chipmunk,_Ontario,_Canada

My thesis tested the idea that behaviour and life history can co-evolve whenever behaviour mediate how individuals negotiate life history trade-offs. On important such trade-off is the one between what an individual invests in its current reproduction (for example how many offspring to produce this year) and what it can invest in its future reproduction, or how likely it is to survive to see other reproductive seasons and how many offspring it will be able to produce. Some individuals will favor current reproduction, at the expense of their future reproduction, while some others will limit their current reproduction in order to have a higher survival and potentially more breeding attempts over their life. Whenever individuals are on different life history trajectories, we can expect them to differ in their propensity to express behavioural traits that are good for their current reproduction (for example being aggressive, faster explorer or bold), or their future reproduction (for example being shy, risk averse and exploring the environment slowly). I showed that, in eastern chipmunks, individuals with a faster exploration pattern will typically reproduce earlier and attain their lifetime maximum fecundity earlier in their life, compared to slower exploring individuals. You can read more about this here and here.

The main control mechanism regulating both the behaviour and life history involves a group of hormones called gluco-corticoids, like cortisol and corticosterone. Cortisol (the main gluco-corticoid in chipmunks) helps regulating behaviour and life history traits during the stress response, that is observed in most vertebrate animals whenever the environment is perturbed and threatens the individual’s survival and future reproduction. During the stress response, GC will shut-down functions associated with current reproduction and shunt the organism’s resources to functions that promote survival (and consequently future reproduction). In nesting birds, the stress response will inhibit parental and foraging behaviour, and can favor individual survival at the expense of their current reproduction. An interesting aspect is that animals facing a very short or demanding reproductive season may even down-regulate their ability to produce cortisol under stress, to prevent energy from being diverted from reproduction.

Based on these hypotheses, fast exploring chipmunks should have a higher stress reactivity when exposed to the various perturbation of their natural environment. At the same time, chipmunks that invest more in their reproduction in a given year (by producing a larger litter) should down-regulate their stress reactivity. We found that, indeed, individuals showed consistent differences in the variability of their cortisol level, that covaried with their exploration level. This result is really interesting because it suggest that the links between individual behaviour and stress reactivity we observe in laboratory settings, over short period of time in many species are probably still relevant in natural conditions, over significant portions of the animals’ lives. We also found that individuals with slower exploration patterns exhibited cortisol levels that were more variable (suggesting they have a higher stress reactivity). Another key finding, is that even after correcting for individual differences in exploration, we also observed that females raising a larger litter exhibited even less variable cortisol levels. This suggests that females could actually down-regulate cortisol stress reactivity according to their reproductive effort a given year.

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Contaminants as a neglected source of variation in behaviour (from Raphaël Royauté and me)

Raphael Royauté and I recently published a small commentary on how contaminants can alter phenotypic variation in animal populations. We think this a fascinating idea from an evolutionary standpoint and a nice opportunity to collaborate with ecotoxicologists.

 

The main idea is pretty simple: exposure and accumulation to a lot of contaminants (toxic byproducts of human activities such as pesticides or heavy metals) are determined by how animals acquire resources. For example, foraging patterns and diet, habitat use, or dominance and aggressiveness can all affect which contaminants an animal will encounter and how much exposure it will experience. Contaminants, in turn, affect all these resource acquisition behaviours. Food intake, activity patterns, and predation responses are all affected by organosphophate pesticides, and anxiolytics amongst other. Raphael has some very interesting work on this (read it here).

 

 

Animal behaviour is also closely associated with life history, or resource allocation strategy. For example, individuals with lower survival rates or with earlier should express risk taking behaviour to a greater extent. Contaminants surely affect many aspects of an animal’s life history, like its growth rate, survival and fecundity, and so contaminants could have additional, long lasting effects on behaviour through life history and resource allocation patterns.

 

 

These two sets of effects between behaviour and contaminant exposure or accumulation can feedback into each other. As a result, individuals in a population will experience differing rates of exposure and accumulation. Contaminants will not only affect the average behaviour expressed by a group of exposed individuals, but also affect the amount of behavioural variation that is expressed in the whole population. For example, individuals with higher foraging activity may accumulate a larger dose of contaminant over their lifespan. Whether a contaminant amplifies or masks phenotypic variation depends on how it affects behaviour, and how behaviour affects contaminant exposure (Figure 1).

 

Honey bee workers feed on nectar and pollen contaminated with neurotoxic insecticides. Returning foragers also expose other bees and larvae of the colony to contaminated food. Depending on their social role within the hive, individuals may be exposed to different doses of insecticides. Insecticides impair foraging activity, navigation skills, olfactory memory and learning. A feedback loop could exist between the social role or behaviour of individuals and their contamination (picture credit: en.wikipedia.org).

Honey bee workers feed on nectar and pollen contaminated with neurotoxic insecticides. Returning foragers also expose other bees and larvae of the colony to contaminated food. Depending on their social role within the hive, individuals may be exposed to different doses of insecticides. Insecticides impair foraging activity, navigation skills, olfactory memory and learning. A feedback loop could exist between the social role or behaviour of individuals and their contamination (picture credit: en.wikipedia.org).

 

Contaminant-driven changes in behavioural variation may be transient. For example, at low, nonlethal doses, exposure to pesticides will affect animals for a few minutes or hours only. In some other cases, the changes in behavioural variation may be long lasting. Endocrine disrupters can have developmental effects, affecting behaviour in a permanent way. In all cases, contaminants effects on behaviour variation could have important implication for the ability of populations to respond to their environment.

 

 

Feedbacks between contaminants and behaviour are fascinating from an evolutionary ecological point of view. Think about how much phenotypic variation is actually driven by contaminants in natural populations of fishes, bees, or birds? How consistent is the effect contaminants on phenotypic variation and how does it affect the population’s response to selective pressures? Behavioural, or life history variation also have huge impacts on the interaction between the population and its community, or affect its dynamic over time.

 

Pharmaceuticals released into streams can affect the boldness of individuals. Bolder individuals end up accumulating more contaminants than shy co-specific, leading to strong differences in boldness among exposed individuals. Read the cool results from Brodin et al. at doi: 10.1126/science.1226850. (picture credit: en.wikipedia.org).

Pharmaceuticals released into streams can affect the boldness of individuals. Bolder individuals end up accumulating more contaminants than shy co-specific, leading to strong differences in boldness among exposed individuals. Read the cool results from Brodin et al. at doi: 10.1126/science.1226850. (picture credit: en.wikipedia.org).

 

Contaminant – behaviour feedbacks also have implication for ecological risk assessments and ecotoxicology. It prompts us to take into account the variation in phenotype and how it is affected by contaminants when conducting toxicological assays. Toxicological assays available for the major classes of contaminants (heavy metals, pesticides, pharmaceuticals, etc) typically shows important variability in the individuals’ response to contaminants. Understanding, or even simply modelling this variability would greatly improve predictive power.

 

 

Investigating these feedbacks is surely a complex thing to do in most systems. It requires to have a mechanistic approach, assessing the effect of the contaminant on behaviour, and then the effect of behaviour on contaminant exposure and accumulation, potentially by monitoring changes in life history. Of course all of this involves following temporal variation in behaviour and contaminant levels in marked individuals. This surely is a challenge. Yet, these types of approaches are already implemented in research programs following hormones in wild populations instead of contaminants. We see these challenges as a great opportunity for collaboration between evolutionary ecologists and ecotoxicologists. Part of Raphael’s PhD thesis was focused on this topic, but we are also interested in getting in touch with researchers having an ecotoxicological background!

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