What can vampire bats teach us about human cooperation?

I have been asked this question several times by journalists and people during outreach events. So here’s my answer:

If you really want to understand human cooperation, you should study humans. Specifically, we should study how humans cooperate with each other under natural circumstances across a wide diversity of cultures. And we should manipulate the factors that we think drive natural forms of human cooperation to see if we can make cooperative behaviors go up and down. Such experiments must be smarter than the participants. It’s no good to merely ask experimental subjects “How much would you sacrifice to help a stranger in situation X?” and expect that the person won’t take into account the very real potential costs and benefits of being watched or judged, and the fact that the sacrifice is hypothetical and not real. The experiments must also not interpret confusion as choice. For those interested in evolved human nature, the experiments must also be natural enough to mimic scenarios that would have been important throughout our evolutionary past. Human brains might not be designed for one-shot anonymous economic interactions, just like we are not built for social isolation (or perceiving faces as inside out).

If you want to understand the evolution of cooperation more generally, you need multiple approaches, including both theoretical and empirical work with a diversity of organisms. Vampire bats are just an interesting piece of that complex puzzle.

Of course, studying vampire bats won’t tell us how humans cooperate. But they might give us general insights into how cooperation works in a long-term social relationship. This is simply because, compared with people and other primates, cooperative relationships in vampire bats are easier to measure and manipulate.

Vampires groom and share food with each other in a small dark corner of a cave or tree, which can be simulated in captivity. They are small, so you can easily house many in a lab space. In that way, they are a bit like highly cooperative lab rats. And do not underestimate what we have learned about humans from rodents! Obviously, we can do experiments with bats and rodents that we can’t do with humans. But by using simple tractable “model organisms” like monogamous voles, we have also gained extraordinary insights into the biological basis of complex behaviors such as romantic attachment and empathy.

Finally, and paradoxically,  I think it’s often easier to understand cooperation in a strange alien system like bats, because I am less self-deluded about how well I understand them. The study of humans always comes with the curse and blessing of being the subject. Like every human being, I have powerful intuitions about myself and about human nature: I think I understand human cooperation way more than I actually do. I think I know why I do what I do and why I care about what I do, but I don’t really. I’m overconfident that my subjective experience gives me some direct insight into my own and others’ cognition and behavior. We have intuitive folk wisdoms and ideologies about human cooperation that must be largely discarded before we can even think clearly about it.

With vampire bats, it’s easier to admit ignorance. I only have hypotheses about the function of their behaviors, not ideological beliefs. I have no idea how they think, or how similar or different they are to people. It’s a total mystery. The only windows I have are the experiments.





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  • Jan 14, Bambi Seminar, Smithsonian Tropical Research Institute, Barro Colorado Island, Panama — “The Reciprocity Controversy”
  • Jan 19, talk at University of Washington, Psychology Department — “Why do vampire bats share food?”
  • Jan 20, talk at University of Washington, Psych Dept, Animal Behavior Group — “Reciprocity with and without social bonding”
  • Feb 8-9, I’ll be at University of Toronto, where I was just hired as a Postdoctoral Fellow by Dr. John Ratcliffe. John is a cognitive ecologist, which means he studies how natural selection shapes cognitive traits. For example, he showed that, unlike other animals yet studied, vampire bats don’t form taste aversions because live blood can’t be adulterated or toxic, and he has done interesting work (with me and others) supporting the notion that a bat’s foraging ecology can shape how it learns. While working for John, I’ll remain at the Smithsonian Tropical Research Institute in Panama with my study colony of common vampire bats.


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Is the ingroup-outgroup bias just two points on a social distance spectrum?

Looking into the human literature on the evolution of cooperation, I feel that studies on humans are often conducted and interpreted poorly compared to studies of cooperation in ants, bacteria, fish, and other nonhuman primates. One point of confusion involves wrong assumptions about what individual humans should maximize and how well they should do it. But another (which I will discuss here) is an overwhelming focus in the social sciences on human groups as homogenous entities in conflict with each other.

According to much of the social psychology literature, humans conceptualize others into an “ingroup” and “outgroup”. This intuitive tribalistic categorization is considered a basic facet of human nature, and many research articles have been written about its causes and consequences.  I will give a couple of random examples. This paper in Science states,

Humans regulate intergroup conflict through parochial altruism; they self-sacrifice to contribute to in-group welfare and to aggress against competing out-groups. Parochial altruism has distinct survival functions, and the brain may have evolved to sustain and promote in-group cohesion and effectiveness and to ward off threatening out-groups.

A paper I just saw yesterday on learning and empathy,  states,

Deficits in empathy for out-group members are pervasive, with negative societal impact. It is therefore important to ascertain whether empathy toward out-groups can be learned and how learning experiences change empathy-related brain responses. 

An implicit notion is that empathy is essentially a dichotomous variable extended to the ingroup but not the outgroup. The prototypical experiment demonstrating the ingroup bias will divide participants into arbitrary groups like “red team” and “blue team” which then predictably leads to all manner of competitive attitudes and biases wherein the ‘reds’ are more judgmental towards the ‘blues’ and more generous and empathetic to fellow ‘reds’. One of the original classic cases is the Robbers Cave study.

This ingroup vs outgroup phenomenon is important, but it’s often over-emphasized to the point of distorting the complexity of the evolutionary design of human social cognition. For example, some influential authors believe that the bias towards cooperating with groupmates and aggressing against outgroupers amounts to a group-level altruistic trait that is only explainable by some form of group selection. A multi-level selection model would assume that, although ancestral humans spent much time competing with fellow groupmates for mates and resources– the real key to their survival and reproduction was successful competition with other tribes. The idea here is that competition between tribes was so severe that it led to heritable tendencies to put the average reproductive success of the group ahead of one’s own relative survival and reproduction within the group.

But humans are not eusocial insects! It is not our evolved human nature to give up one’s life for the group. Humans tend to help their group, because doing so simply helps their own direct fitness. Our tendency for human tribalism is mutually beneficial, not altruistic in the evolutionary sense*. I would hope everyone would agree on these basic points, and yet I’m not so sure when I read the literature.

(*One point of confusion here is that multi-level selection has a different definition of altruism, which allows this human tribalism to be called “altruistic” whereas the orthodox inclusive fitness definition means we can never be as “altruistic” as ants and slime mold. I think this is one additional reason that many social scientists prefer the multi-level selection terminology that most evolutionary biologists don’t prefer.)

Human evolutionary history is not a mere series of tribal wars. Selection continues on between these conflicts. Given that the majority of social behaviors occur ‘within-group’, it is unclear whether the ingroup fitness effects are overshadowed by the fitness effects of intergroup conflict (as assumed in the narrative given above). Within each of our ‘ingroups’, we are still closer to some group members than others (although one might not even detect this fact if one is focused solely on intergroup conflict). A machine well-designed for navigating a social world (i.e. a human’s social brain) would surely possess adaptations for dealing with cooperation and conflict within the group, and not simply sit idle waiting in anticipation for the next tribal war.

Upon closer inspection, a social group is really a social network. And upon even further inspection, the links in that network are weighted differently and change over time. A more nuanced individualistic approach is therefore to imagine that people place others on a spectrum of dynamic social distance, with close friends and family on one end and threatening strangers on the other.

So what happens when experimenters place strangers into red and blue teams? They are sampling two points on that spectrum, thereby creating the discrete group mentality that they claim they are revealing. A complex continuous variable is reduced to a simple discrete one.

A similar mistake is easy to make when we think about discrete personality types. For each personality trait, say extravert vs introvert, there is a continuous spectrum which probably approximates a normal distribution. Most of us are not truly ‘extraverts’ or ‘introverts’ but are rather just average and in the middle. But I’m always surprised by the number of people who think that people actually come in these distinct categories or types and that being moderate or average is therefore rare: “Are you an introvert or extravert? You must be one or the other!”

If you surveyed people who considered themselves definite extraverts or introverts, then placed them in two groups, and tested their behavior–you would see an exaggerated difference between these groups for two reasons. First there is the biased sampling. Second, there is a priming effect. The result would obscure the real complexity and flexibility of human personality often taken for granted: most of us are extraverted or introverted to a near optimal degree for the current social situation.

The same thing is true of human cooperation. Humans are obviously very good at flexibly treating others as either competitors, collaborators, or a mix of both. Of course it makes sense to act tribal when you are divided into warring tribes. But the real question is, how constrained are people in acting this way, when it would go against their own self-interest?

The ingroup-outgroup bias might be reducible to simpler cognitive biases. The first is that people generalize or stereotype people, places, and things into various categories. People prefer to chunk continuous measures into discrete types. It’s easier for us to think in chunks. This is one of the facets of psychological essentialism, where even young children intuitively assume that concepts like bird, female, or red have an underlying discrete reality, even without evidence. This pervades much amateur thinking about biology (e.g. “A virus must be alive or not, so which is it?”).

Another cause of tribalism is the acquisition and enforcement of social norms, which are themselves properties of groups. The difference between adherence to social norms and group loyalty can be subtle (or even identical) when groups are identified by social and cultural norms. Human social groups are often not defined by actually knowing the individuals in the group, but rather by markers such as dress (football jerseys, suits, or tribal garb), language or dialect, or by belief systems such as religions or political parties. In these cases, each individual could switch groups. So I could become a Dallas Cowboys fan, or join Islam, or become a citizen of Spain. But in other cases, group membership is more fixed, as when it is defined by biological traits like race or sex. But here again, the neat-and-tidy discrete lines between ingroup-outgroup may break down. A person might appear to be more “racist” towards a homeless black person than towards a black person wearing a suit and tie. In other words, being a certain race or religion is perhaps not an absolute cue of being an outgroup, it is just one of many cues that the person’s brain uses to decide how socially distant an individual is to them. The subconscious machinery might function to assess questions like: How likely is this person to be an ally to me in a conflict? If a tribal conflict breaks out, what will it be about? And will we be on the same side or opposing sides?

If I’m correct about this, then people’s ingroup-outgroup bias should itself be highly malleable. In a situation where I think I might be caught in a political war, I will suddenly see my country as my ingroup. But if I see a religious war brewing, then I might then see my religion as my ingroup. That is, our loyalties should be context-dependent. If you and I are different races/sexes/religions in one tribe, we will largely forget that when we join forces to fight an army from a completely different tribe. Then when the tribal war is over, those race/sex/religion issues will re-emerge.

But I might be wrong. Perhaps in our evolutionary history, groups were so stable and homogenous that such strategic social positioning was never necessary. Perhaps social group identity is more real and stable than I am imagining. I don’t know. Do people have one set of social instincts for regulating inter-group conflict and another set for regulating intragroup conflict? Or do we have just one set for both situations?

Is the ingroup-outgroup bias a separate evolved cognitive bias serving its own evolutionary function? Or is it merely a byproduct of intuitive essentialism and adherence to social norms? (Or is it somewhere in the middle? 😛 )

One way to answer these questions would be to describe the distribution of perceived social distances in a person’s social network. Are there two discrete humps? One for ingroup or one for outgroup? Or is there a smooth curve? How does this distribution differ in different societies around the world? Social distance itself could be measured either objective or subjectively– and that difference itself might be interesting. Perhaps this has all been done already? Let me know in the comments.

I need to read more of the literature about human social networks. But so far I don’t see people answering the questions that fill my mind.

My own concern is more that the ingroup-outgroup distinction sadly oversimplifies the conversation about human cooperation. If you give people simple questions (ingroup or outgroup?) you will get simple answers. But real social life is full of nuance, as we all recognize simply from being human. Ponder the strategic logic underlying these phrases:

“A friend in need, is a friend indeed.”

“The enemy of my enemy is my friend.”

“A friend to all, is a friend to none.”

There are even less obvious facets to the adaptive design of human friendships. For example, two friends who are better friends with each other than with you, are both less ‘valuable’ to you than two friends that don’t know each other (see the evidence). Even nonhuman animals appear to make strategic social decisions about bonding that are contingent on their shifting place in a social network. In baboons, females are more willing to make new friends when a close relative dies. In vampire bats, those individuals who form more non-kin relationships do better when their kin partners are unavailable to help them.

Many primates not only create and manage their own ‘ingroups’ but they probably manage each social relationship individually according to what is happening in all their other relationships (much like in a market). And moreover, in each population, there might be different social management strategies that are under frequency-dependent selection. Rather than focusing so much on ingroup-outgroup bias in humans, these are the kinds of design principles of social cognition that, in my opinion, would be more illuminating to investigate.

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New review of bat cooperation

Most of the 1,300 species of bats live in groups. Indeed, some are quite social, with relationships that last for years. For the latest issue on the evolution of direct benefits cooperation in Philosophical Transactions BJerry Wilkinson was asked to write a review on cooperation in bats and he co-wrote the article (PDF) with Kisi Bohn, and Danielle Adams and me. We summarized evidence of cooperation among unrelated bats while they roost, forage, feed and care for their offspring. In particular, we highlight two species we have studied in detail: vampire bats and greater spear-nosed bats– cases which suggest that some bats cooperatively invest in non-kin bonds for long-term social benefits.

Besides reviewing previous published work, we used this review to put out some previously unpublished results on food sharing in vampire bats (the similarities between donation size in captive and wild bats) and more on social structure and evidence for ‘babysitting’ behavior in greater spear-nosed bats. We also make some neat predictions such as that heat generation in greater spear-nosed bats is under paternal genetic control due to patterns of genetic relatedness.

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The other review articles look really interesting!


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Field notes on vampire catching

Dec 12, 2015

I caught my first group of common vampire bats and brought them to the field station. It was important that all the females I captured came from the same roost. At 5:52 pm on Dec 12, 2015, I started observing the entrance (a 1 meter high triangular hole) to a large hollow-tree vampire roost. One or two Saccopteryx bilineata roosted just inside the entryway to the left. Further up and right, there were easily more than a hundred vampire bats staring back at me. The floor of the roost was a pool of black liquid, a mixture of urine and digested blood. The overwhelming ammonia fumes bleached the bats’ fur and made it impossible to breathe when sticking one’s head inside.

My plan was to catch the bats as they exited the tree by trapping them in a large screened area directly in front of the entrance. Then I would scoop them up in hand nets and toss them in a small cage. My worry was that the bats would detect the trap from the entrance, then fly back in the tree or never leave. So I decided to let the bats fully investigate the screen trap and fly through it on the first night. Bats must have to habituate to sudden changes to the area in front of their roost, when for example, a large tree branch falls in front of the exit. After a brief investigation with no negative experiences, they should become accustomed to these obstacles such as fallen tree branches or bat gates. The roost was large enough that I did not fear them switching to another.

My other goals were to note what time the bats started to emerge, to see if they emerge in one large group or small clusters, and to record social calls and echolocation from the emerging bats.

I positioned a 4 x 4 meter screen tent (with two opposite-wall doors) at the entrance and tied the first door directly to the roost entrance. I opened the second door (4 meters directly in front of the entrance door). Bats could fly straight through both tent doors, but those turning as they exit would encounter mesh screen walls. I positioned an Avisoft microphone 2 meters directly in front of the exit allowing me to get high-quality recordings from flying bats as they flew directly towards the microphone at a distance of 0-6 meters. Vampire bat calls are low intensity, so the microphone gain was set to max. I was positioned about 7 meters farther back where I could monitor the recording and record events with an infrared-sensitive camcorder.

At about 6:40 pm, the two Saccopteryx entered the tent and flew back in repeatedly. At 6:55 pm one roosted on the side wall, then it flew out the door. The first vampire bat came out at 7:06 pm; it entered then flew back in to the roost. For the next hour, 1-3 vampires entered the tent about once every 1-10 minutes.

This was good news: it meant the bats were coming out gradually, allowing us to maybe catch one or a few at a time in hand nets. Of the bats that entered the tent, 50-75% flew out and then looped back into the roost, but this activity may have been one or a few of the same individuals. Sometimes they crashed into the side walls. The remaining bats flew out the door. At least one bat landed and crawled a bit on the mosquito netting wall and I could observe it echolocating back and forth across the tent interior. I also observed 2 bats flying back through the tent and into the roost from the outside. It was too difficult given the poor infrared lighting to get an accurate count of bats entering or exiting the tent. Finally, I noticed that at least one bat was circling me while I sat watching.

From 8:11 until 9:11 pm, I counted 9 singles, 3 pairs, and 3 triplet flights into the tent (24 total), and these led to 6 crashes, 7 exits from the tent, and 1 return flight from the outside. Five bats then exited without circling or crashing at the following times: 9:11, 9:13, 9:20, 9:21, 9:22. I then stopped observing. I wanted to make sure that the remaining bats would have time to feed during the night. So at 9:30 pm, I detached, untied, and moved the tent away from the tree (about 15 meters away) and left.

To me, it seemed that a few bats were checking out the tent and then eventually leaving. There were many bats still inside the tree when I peered inside at 9:30 pm. Based on what I saw, I thought it was likely we could catch 20-40 females before 9 pm. With a 5-h drive, this would put us back home at 2 am.

But I was wrong…

Dec 13, 2015

PhD student Victoria Flores, her partner Michael Le Chevallier, my wife Michelle Nowak, and I set up the screen tent outside the roost and waited. This time the second door was zipped shut.  A storm sounded like it was approaching, so I decided to not wait for dumping rain and to flush the bats out by crawling inside. I had a bit of trouble squeezing in. Michelle (my very brave wife) entered first after putting a garbage bag over her upper body. I crawled in afterwards. It was the most disgusting place I’ve ever been. I’ll just put it this way: it was like crawling into the rectum of a vampire bat.

Unfortunately, the living wall of bats skittered upwards and could not be reached from the floor inside the hollow. The ammonia fumes also meant we could not spend time inside the tree without poisoning ourselves. We waited outside.

After disturbing the bats so much, it was clear that they knew we were there and they were not coming out. I decided to switch capture strategies at 9:30 pm. We took down the screen tent trap, covered the roost entrance, and quickly set mist nets in a U-formation around the entrance. We then backed away behind the tree and entrance, then turned off all our white lights.

We began consistently catching male vampire bats. Many of them were coming into this roost. Next, we began catching a mix of male and female bats exiting the roost. Many seemed younger based on their appearance, and the females often did not yet have a bare patch around the nipple, meaning they had not nursed a pup yet. We caught maybe 2-3 males for every female. I suspect most of the adult females stayed inside the roost, and came out after we left at 12:38 am.

We caught 19 males and 22 females and took them on the 6+ hour drive back to Gamboa. All the bats survived this grueling all night drive. Victoria and Michelle took turns driving, because only they knew how to drive standard. We kept them in a rabbit cage and a bird cage lined with plastic mesh. I kept worrying that the bats would escape their cages and begin feeding on us in the car. (One of the doors actually became slightly ajar, but no bats escaped–thankfully).

We arrived back at 730am, and the were left alone with thawed cow blood at 8am. Thick black plastic was draped over the cage to make them feel less stressed and encourage feeding.

I was surprised at how many male bats were coming to visit this tree early in the night. I had observed this same pattern of early male visits near Lamanai, Belize. I set nets outside a maternity colony in some ancient ruins and instead of catching females coming out, I caught many males going in. Also in Belize, I noticed that early in the night, we caught only males. Then at 2 am, we began catching all adult females. In his field studies in Costa Rica, Jerry Wilkinson had previously observed that males not only compete over access to large female groups in hollow trees but also visit the female roosts during the night (presumably before or after the female leave to forage).

Thanks so SO much to Victoria, Michael, and Michelle for all their help. The bats are hopping around in the flight cage and we are finally ready now for our behavioral experiments after a long delay.




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How we define “reciprocity”: the good, the broad, and the ugly

I hope this is the last blogpost I ever write about semantics. I always want to point people to a good reference on what the words that I use mean (and there isn’t a short quick guide), and Wikipedia does not work here.

People use the terms “reciprocal altruism” and “reciprocity”in very different ways in the scientific literature. So it’s very confusing for a new student in this field. I don’t use the term “reciprocal altruism” at all (because it is not altruism). Instead, I use the term “reciprocity”. Authors have very strong and contrasting opinions on what this word means, and I’m frequently told by overconfident researchers (and reviewers) that I don’t understand the original concept, or perhaps I haven’t read it carefully enough. But I wrote a review of its meaning and the history of its meaning, and the Prof. Trivers (who coined the term and invented the concept) wrote me to tell me he agreed and loved the paper. So there.

For the deeply confused, there are 3 basic ways that people will often use the term reciprocity. I call them the good, the broad, and the ugly:

The good

Direct reciprocity occurs when an organism makes cooperative investments that are in some way contingent on the experience (or memory) of cooperative returns from the recipient. This behavior requires repeated interactions, cognition, and in most cases, individual recognition. I call this definition “good” because  I believe it is most in line with what Trivers meant by reciprocal altruism.

An example: Monkey A grooms Monkey B on day 1, which causes monkey B to share its food with Monkey A on day 3. In contrast, Monkey C has never groomed Monkey B, which causes Monkey B to not groom or share food with Monkey C. Over many generations, monkeys that do not take past experience into account like this, when deciding who to groom or give food to, have fewer offspring.

This is similar to what Frans de Waal called “attitudinal reciprocity”. I like this definition, but I like the next one too.

The broad

A broader usage of reciprocity says that it occurs when an organism makes cooperative investments in a recipient that are in some way contingent on cooperative returns from the recipient, regardless of the mechanism. Note that this does not require cognition. So even plants and fungi can perform this version of reciprocity. This has also been called reciprocal rewards, sanctions, partner choice, or reciprocation. I like this definition too, although it means that all enforced forms of mutual benefits are a form of reciprocity.

An example: A plant provides carbon to Fungi A and Fungi B, and both Fungi A and B provide phosphorus to the plant. One day, Fungi A stops providing phosophorus to the plant. The plant responds by only providing carbon to Fungi B. As a result, Fungi A dies (or reproduces less). Plants that alter their carbon outputs to fungi based on the returns have higher reproductive success than those that do not.

What makes this different than “cooperation” more generally is that the plant’s actions reward and punish the cooperative partner based on the partner’s returns. In other forms of cooperation, the investments in the partner might be fixed. For example, in a byproduct mutualism, the plant might even be leaking carbon as a waste product, in which case it might not benefit from contingently altering its output one way or another.

The ugly

Some people define reciprocity as when organisms make cognitively calculated cooperative investments based on the cognitive expectation of the cooperative returns from the recipient. I call this the ugly definition because, although common, it’s a distortion of the original concept, it’s not what we should expect animals to do, and it’s not really even what humans do most of the time in their social lives, unless they are nasty Machiavellian psychopaths.

An example: Monkey A wants to get food from Monkey B. Monkey A doesn’t enjoy grooming Monkey B, but it believes that if it grooms Monkey B today, then B might give it food later. So Monkey A grooms Monkey B with the expectation of getting a reward later. Monkey B doesn’t want to give food to Monkey A but now it thinks that if it gives A some food now, than later when B has no food maybe A will feed it. So Monkey B suppresses it’s desire to eat all its food, and feeds A based on the expectation of a reward.

This has been called “calculated reciprocity” and I don’t think it’s very important except when 1) animals are trained to do it and or 2) humans are not relying on their normal intuitive emotion-based guidance systems, because the situation is relatively novel from an evolutionary perspective (like a business transaction between strangers), or maybe because they lack normal prosocial emotions (like a person that has to take a moment to calculate the costs and benefits of trying to help a friend who begins choking).

To make strictly “rational” economic decisions, a person must use calculated reciprocity. And people often use calculated reciprocity when playing a social dilemma game. However, the vast majority of reciprocity that occurs in humans is subconscious and is built into our intuitive emotions. When we invest time and energy in friendships, we do it intuitively and we find it inherently rewarding. We don’t think “I will give my friend a ride home, but I better get something out of this next week” (well, at least not most of us, most of the time).

For this reason, many social scientists think that friendship has nothing to do with reciprocity. But this is confusing reciprocity the good with reciprocity the ugly. People believe, and they will report, that their devotion to their friends is unconditional and unbreakable. But is that true? When someone invests in a cooperative relationship like a friendship, and they experience something that is not an adequate “return”, they will experience negative emotions like sadness or anger or disappointment. These emotions are not an accident. This “social pain” prevents us from being socially exploited in the same way that the sensation of pain can prevent us from getting burnt by touching a flame. Social pain can reduce social investments in others and in effect it can punish social partners (if only in a subtly way). This is not the same as consciously or strategically punishing someone for their behavior.

In other words, people don’t need to use calculated reciprocity, because their emotions are already strategically designed to do the job. And that’s still reciprocity.

If we want to understand friendships, we might not need a new theory that is an alternative to reciprocity. We might just need a better and deeper understanding of how reciprocity actually works. This means taking into account how social bonding is regulated by emotions (Do more emotional people have more social bonds? Are people who are most generous, also most spiteful when cheated?  Do more variable emotional experiences make social bonds stronger or weaker?). It also means testing exactly how cooperative investments are influenced by various social factors (such as short-term experience, long-term experience, partner options, supply and demand of partners, one’s assessment of one’s own value as a social partner, etc). These are tests that can be done with both human and non-humans (including  <wink-wink> vampire bats!).


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VampCam featured at Smithsonian and some recent papers

The VampCam is being featured on the STRI website frontpage. There’s an inaccuracy though– it gives the wrong name of the authors on the study they discuss. I did that social grooming study in collaboration with the Organization for Bat Conservation and co-author Lauren Leffer, an undergraduate at the University of Maryland.

I’ve been in Gamboa, Panama at the Smithsonian Tropical Research Institute (STRI) for a few months now and I love it here! One of the best aspects is simply being around so many brilliant biologists who work here and are also coming and going throughout the year. Here’s a neat video about STRI:

There has been a lot of neat studies on cooperation and reciprocity recently. Here are some recent and relevant ones.

From the Taborksy Lab…

There’s a special issue of Philosophical Transactions B on “Solving the puzzle of collective action through inter-individual differences: evidence from primates and humans

Also, just a few more:

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