Animals have a lot to gain by foraging together. One of the biggest costs while feeding is having your attention focused on the food obscured by the rocks at the bottom of a river, or the prey trying to squirm away from you in the tall grass - and not on a predator that could be watching from just out of sight. Similarly, the world is a big place, and especially with mobile prey or ephemeral food patches, you might have to invest a lot of time to actually find food. Having other pairs of eyes scanning your surroundings while you eat or helping you find food is a huge benefit. Yet, how do socially-foraging animals actually decide when to eat as a group? Is it necessary for them to communicate their hunger state to each other? In a 2003 paper by Rands and colleagues, a very simple model for social foraging in a pair of animals showed that the mere existence of benefits to foraging together is sufficient to evolve synchronous foraging and 'leader' and 'follower' roles, even without knowledge on the state of your partner.
Article details
- Rands SA, Cowlishaw G, Pettifor RA, Rowcliffe JM, Johnstone RA. 2003. Spontaneous emergence of leaders and followers in foraging pairs. Nature. 423: 432-434.
- Corresponding author (Dr. Sean Rands) is currently affiliated with the School of Veterinary Sciences, University of Bristol, UK
Very brief summary
Rands et al. build a dynamic model where two animals make decisions on when to rest or forage. Each animal makes its own decision, and the decisions can be coordinated, sometimes coordinated, completely independent, etc. Resting increases the risk of starvation but decreases the risk of predation, while foraging decreases the risk of starvation but increases the risk of predation. If there is any benefit to foraging together, a pair of animals will forage together (not too surprising). What's more interesting is that one animal will begin to always be relatively well-fed and the other animal will always be hungrier. This hungrier animal becomes the "pace-maker" that decides when the two animals forage, as it is always closer to starvation. Because it's too costly to not forage together, the better-fed individual will follow, maintaining its high energy reserves.
Glossary
- model - a description of a system using relationships between variables. (This is an incredibly broad definition, but models can cover essentially anything.)
o Example: A system can be the nutrient composition of a forest's soil, with the variables being the amount of rainfall and erosion, the frequency of fires, the age of the forest, etc.
o Example: A system can be the nutrient composition of a forest's soil, with the variables being the amount of rainfall and erosion, the frequency of fires, the age of the forest, etc.
- dynamic model - a model where the outputs change over time.
o Example: the number of elk in a forest, depending on the forest's carrying capacity and hunting efforts by local hunters. As the number of elk in the forest changes, the predicted number of elk for the next year will be different.
- forage - to seek and eat food.
- robust - strong. The outcome of a model is robust when it's not dependent on very specific contexts or starting conditions. It's the difference between a model that predicts drunk patrons' dating successes at a bar on Thursdays, when only beer is being served, each beer is 5% alcohol, there are between 94 and 102 people in the bar, and hip hop music is being played... versus a model that can accommodate wider ranges in the inputs.
o Example: the number of elk in a forest, depending on the forest's carrying capacity and hunting efforts by local hunters. As the number of elk in the forest changes, the predicted number of elk for the next year will be different.
- forage - to seek and eat food.
- robust - strong. The outcome of a model is robust when it's not dependent on very specific contexts or starting conditions. It's the difference between a model that predicts drunk patrons' dating successes at a bar on Thursdays, when only beer is being served, each beer is 5% alcohol, there are between 94 and 102 people in the bar, and hip hop music is being played... versus a model that can accommodate wider ranges in the inputs.
- state-dependence - the outcome depends on what state you're in (which can change). This 'state' could be hunger level, reproductive status, emotional state, etc.
Article summary-----------------------------------------------------------------------------------
Article summary-----------------------------------------------------------------------------------
Biological context
The risk of starving versus the risk of getting eaten yourself is the largest trade-off in an animal's decision on whether or not to forage. Foraging minimizes the risk of starvation, but it increases the chance of getting caught by a predator as you're wandering around and then focusing on eating your food while out in the open. Resting minimizes the chance of a predator finding you, but depletes your energy reserves. What is the best strategy for survival?
Building the model
Previously, dynamic programming had been used to successfully examine the trade-off between starvation and predation on short-term, minute-to-minute decisions by individual foragers. Rands and colleagues decided to extend the logic to pairs of individuals by creating a dynamic games model, which uses similar rules but allows for modeling the behavior of groups.
In their model, either one or two animals make the decision to either forage or rest.
- Foraging: decreases risk of starving, increases risk of getting caught by a predator
- Resting: decreases risk of predation, increases risk of starvation
Note that it's possible to forage and not find any food, and for a predator to catch you while resting. An animal takes into account its energetic reserves vs. the risk of predation and then makes a decision to forage or rest. Its energetic reserves change. Then, it evaluates its new reserves and makes a decision again. And so on (assuming it isn't caught by a predator). The model finds what choices an animal should make over repeated turns to maximize its lifespan.
In the first part, an animal makes its decisions based solely on its own reserves; it's essentially the only member of its species in existence. In the second part of the model, there are two animals making decisions, and the decisions of one can influence the other (or, if the animals live longer if they ignore each other, the other animal's decisions will have no influence). Because the calculations are computationally expensive, the authors decided to only model pairs of foragers, though they argue their model could be extended to groups.
Foraging alone
By yourself, the answer is straightforward: spend the minimum amount of time looking for and eating food to pass some threshold for energy reserves, then spend all other time resting. This makes sense if you think of the extremes: there's no point in waiting until you're nearly starved before hurrying out to find food because you might not find the food immediately. On the other hand, there's no need to forage constantly to attain 99% fuel reserves when 50 or 60% is just fine (and when going home early decreases the chance of a predator finding you and turning all that investment in the future into a waste of time). Not foraging constantly makes even more sense if you consider that fat stores are heavy and can, for example, impede a bird's ability to fly. (Side note: I love the title for the linked paper - "Impaired predator evasion in fat blackcaps (Sylvia atricapilla))
The answer gets a little more complicated if you're with someone else who's trying to decide when to forage. You have a few possible options:
1. Forget the other guy. I'm going to find some farmer's garden to sack by myself. (Activities uncorrelated; D' = 0)
2. I dislike that other guy so much, I'm going to stay in the burrow while he's out, and leave as soon as he comes back. (Activities completely anticorrelated; D' = -1)
3. He's not so bad once you get to know him. Let's rest and feed together at the same time. (Activities completely correlated; D' = 1)
Here, D' is the relative disequilibrium parameter. Note that D' can also be some value between -1 and 1, representing partial (anti)correlation. If there is no benefit to foraging together, and assuming there's plenty of food to go around, option 1 happens: you and your partner are uncorrelated. Both of your energetic reserves settle at the same level, which is just around some threshold for when you should stop resting and go out to forage.
Foraging together
If there is some benefit to foraging together, Rands et al.' model shows that the two animals' resting and foraging decisions will become tightly synchronized. This benefit can be either a decrease in the risk of predation (e.g. someone can keep watch while the other eats) or an increase in the chance/speed of finding food; either option leads to this synchrony in activity. It's just not worth the cost to forage by yourself.
Interestingly, a gap forms in the energy reserves between you and your partner. The model shows that over time, one animal will begin to stay at low reserves and the other will stay at high reserves. The animal that is closer to starvation will become the 'pace-maker,' deciding when the two should forage.
This outcome is robust, as the authors thoroughly varied the parameters in the model (e.g. mean energetic gain from a foraging bout, energetic loss over time, predation risk while resting vs. foraging), and the same result emerged every time. This is important because ultimately, a model needs to tell us something about the natural world. Social foraging is incredibly widespread across taxa, meaning this is a behavior that has evolved numerous times under extremely different contexts. (e.g. a lion and a starling have drastically different ecological pressures, but both forage in groups.) Certain parameter values will be more relevant to some species than others. If the outcome of the model still holds through a wide range of parameter values, it's a good sign that the model can tell us something relevant to many animal groups in nature.
Conclusions
If it's beneficial for two animals to forage together, synchronized foraging will emerge, as well as 'leader' and 'follower' roles. The simplicity of the model and its robustness indicate the model's results are applicable to a wide range of taxa and can easily evolve. No advanced problem-solving skills, expert knowledge of the environment, or even any sort of communication are required for this outcome to occur. It is only required that an animal knows how hungry it is, the fact that is safer (or more profitable) to forage with a conspecific, and to be able to quickly incorporate its partner's decision to rest or forage into its own decision on what to do.
Full text of the article can be found here.
The risk of starving versus the risk of getting eaten yourself is the largest trade-off in an animal's decision on whether or not to forage. Foraging minimizes the risk of starvation, but it increases the chance of getting caught by a predator as you're wandering around and then focusing on eating your food while out in the open. Resting minimizes the chance of a predator finding you, but depletes your energy reserves. What is the best strategy for survival?
Building the model
Previously, dynamic programming had been used to successfully examine the trade-off between starvation and predation on short-term, minute-to-minute decisions by individual foragers. Rands and colleagues decided to extend the logic to pairs of individuals by creating a dynamic games model, which uses similar rules but allows for modeling the behavior of groups.
In their model, either one or two animals make the decision to either forage or rest.
- Foraging: decreases risk of starving, increases risk of getting caught by a predator
- Resting: decreases risk of predation, increases risk of starvation
Note that it's possible to forage and not find any food, and for a predator to catch you while resting. An animal takes into account its energetic reserves vs. the risk of predation and then makes a decision to forage or rest. Its energetic reserves change. Then, it evaluates its new reserves and makes a decision again. And so on (assuming it isn't caught by a predator). The model finds what choices an animal should make over repeated turns to maximize its lifespan.
In the first part, an animal makes its decisions based solely on its own reserves; it's essentially the only member of its species in existence. In the second part of the model, there are two animals making decisions, and the decisions of one can influence the other (or, if the animals live longer if they ignore each other, the other animal's decisions will have no influence). Because the calculations are computationally expensive, the authors decided to only model pairs of foragers, though they argue their model could be extended to groups.
Foraging alone
By yourself, the answer is straightforward: spend the minimum amount of time looking for and eating food to pass some threshold for energy reserves, then spend all other time resting. This makes sense if you think of the extremes: there's no point in waiting until you're nearly starved before hurrying out to find food because you might not find the food immediately. On the other hand, there's no need to forage constantly to attain 99% fuel reserves when 50 or 60% is just fine (and when going home early decreases the chance of a predator finding you and turning all that investment in the future into a waste of time). Not foraging constantly makes even more sense if you consider that fat stores are heavy and can, for example, impede a bird's ability to fly. (Side note: I love the title for the linked paper - "Impaired predator evasion in fat blackcaps (Sylvia atricapilla))The answer gets a little more complicated if you're with someone else who's trying to decide when to forage. You have a few possible options:
1. Forget the other guy. I'm going to find some farmer's garden to sack by myself. (Activities uncorrelated; D' = 0)
2. I dislike that other guy so much, I'm going to stay in the burrow while he's out, and leave as soon as he comes back. (Activities completely anticorrelated; D' = -1)
3. He's not so bad once you get to know him. Let's rest and feed together at the same time. (Activities completely correlated; D' = 1)
Here, D' is the relative disequilibrium parameter. Note that D' can also be some value between -1 and 1, representing partial (anti)correlation. If there is no benefit to foraging together, and assuming there's plenty of food to go around, option 1 happens: you and your partner are uncorrelated. Both of your energetic reserves settle at the same level, which is just around some threshold for when you should stop resting and go out to forage.
Foraging togetherIf there is some benefit to foraging together, Rands et al.' model shows that the two animals' resting and foraging decisions will become tightly synchronized. This benefit can be either a decrease in the risk of predation (e.g. someone can keep watch while the other eats) or an increase in the chance/speed of finding food; either option leads to this synchrony in activity. It's just not worth the cost to forage by yourself.
Interestingly, a gap forms in the energy reserves between you and your partner. The model shows that over time, one animal will begin to stay at low reserves and the other will stay at high reserves. The animal that is closer to starvation will become the 'pace-maker,' deciding when the two should forage.
This outcome is robust, as the authors thoroughly varied the parameters in the model (e.g. mean energetic gain from a foraging bout, energetic loss over time, predation risk while resting vs. foraging), and the same result emerged every time. This is important because ultimately, a model needs to tell us something about the natural world. Social foraging is incredibly widespread across taxa, meaning this is a behavior that has evolved numerous times under extremely different contexts. (e.g. a lion and a starling have drastically different ecological pressures, but both forage in groups.) Certain parameter values will be more relevant to some species than others. If the outcome of the model still holds through a wide range of parameter values, it's a good sign that the model can tell us something relevant to many animal groups in nature.
Conclusions
If it's beneficial for two animals to forage together, synchronized foraging will emerge, as well as 'leader' and 'follower' roles. The simplicity of the model and its robustness indicate the model's results are applicable to a wide range of taxa and can easily evolve. No advanced problem-solving skills, expert knowledge of the environment, or even any sort of communication are required for this outcome to occur. It is only required that an animal knows how hungry it is, the fact that is safer (or more profitable) to forage with a conspecific, and to be able to quickly incorporate its partner's decision to rest or forage into its own decision on what to do.
Full text of the article can be found here.
- Racoon pair: Animals Time
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