Climate-conflict research, before the IRB...

Finding old papers on temperature manipulation is turning into a hobby of mine. I actually had to go to the library to dig up this gem. From Rohles, Frederick H. "Environmental psychology: A bucket of worms." Psychology Today 1.2 (1967): 55-63.

Projections of labor capacity loss under climate change

Reductions in labour capacity from heat stress under climate warming
John P. Dunne,  Ronald J. Stouffer , Jasmin G. John

Abstract: A fundamental aspect of greenhouse-gas-induced warming is a global-scale increase in absolute humidity. Under continued warming, this response has been shown to pose increasingly severe limitations on human activity in tropical and mid-latitudes during peak months of heat stress. One heat-stress metric with broad occupational health applications is wet-bulb globe temperature. We combine wet-bulb globe temperatures from global climate historical reanalysis and Earth System Model (ESM2M) projections with industrial and military guidelines for an acclimated individual’s occupational capacity to safely perform sustained labour under environmental heat stress (labour capacity)—here defined as a global population-weighted metric temporally fixed at the 2010 distribution. We estimate that environmental heat stress has reduced labour capacity to 90% in peak months over the past few decades. ESM2M projects labour capacity reduction to 80% in peak months by 2050. Under the highest scenario considered (Representative Concentration Pathway 8.5), ESM2M projects labour capacity reduction to less than 40% by 2200 in peak months, with most tropical and mid-latitudes experiencing extreme climatological heat stress. Uncertainties and caveats associated with these projections include climate sensitivity, climate warming patterns, CO2 emissions, future population distributions, and technological and societal change.

Not a major surprise to regular readers of FE, but still important. For more serious stuff on this topic, see here, here and here. For more entertaining experiments, see here and here. If you're still reading and want more, click here.

Temperature and Jewish persecution

"Recommendations" on Google scholar is getting very good. Here's a new working paper out that it flagged for me, and it hit remarkably close to home  -- it's the most recent working paper since this one that I emailed to my parents. (We've posted on climate shocks on and human conflict many previous times.)

Climate and Conflict in East Africa (carefully interpreting statistical results revisited)

Andrew Revkin asked for thoughts on a recent PNAS paper on conflict. He posted a watercolor regression plot that Marshall Burke and I made, but I guess he (understandably) didn't have space for my lengthy statistical commentary.  Read my appendix to Revkin's post on the G-FEED blog here.

figure explained here

An American, a Canadian and a physicist walk into a bar with a regression... why not to use log(temperature)

Many of us applied staticians like to transform our data (prior to analysis) by taking the natural logarithm of variable values.  This transformation is clever because it transforms regression coefficients into elasticities, which are especially nice because they are unitless. In the regression

log(y) = b* log(x)

b represents the percentage change in y that is associated with a 1% change in x. But this transformation is not always a good idea.  

I frequently see papers that examine the effect of temperature (or control for it because they care about some other factor) and use log(temperature) as an independent variable.  This is a bad idea because a 1% change in temperature is an ambiguous value. 

Imagine an author estimates

log(Y) = b*log(temperature)

and obtains the estimate b = 1. The author reports that a 1% change in temperature leads to a 1% change in Y. I have seen this done many times.

Now an American reader wants to apply this estimate to some hypothetical scenario where the temperature changes from 75 Fahrenheit (F) to 80 F. She computes the change in the independent variable  D:

DAmerican = log(80)-log(75) = 0.065

and concludes that because temperature is changing 6.5%, then Y also changes 6.5% (since 0.065*b = 0.065*1 = 0.065).

But now imagine that a Canadian reader wants to do the same thing.  Canadians use the metric system, so they measure temperature in Celsius (C) rather than Fahrenheit. Because 80F = 26.67C and 75F = 23.89C, the Canadian computes

DCanadian = log(26.67)-log(23.89) = 0.110

and concludes that Y increases 11%.

Finally, a physicist tries to compute the same change in Y, but physicists use Kelvin (K) and 80F = 299.82K and 75F = 297.04K, so she uses

Dphysicist = log(299.82) - log(297.04) = 0.009

and concludes that Y increases by a measly 0.9%.

What happened? Usually we like the log transformation because it makes units irrelevant. But here changes in units dramatically changed the predication of this model, causing it to range from 0.9% to 11%! 

The answer is that the log transformation is a bad idea when the value x = 0 is not anchored to a unique [physical] interpretation. When we change from Fahrenheit to Celsius to Kelvin, we change the meaning of "zero temperature" since 0 F does not equal 0 C which does not equal 0 K.  This causes a 1% change in F to not have the same meaning as a 1% change in C or K.   The log transformation is robust to a rescaling of units but not to a recentering of units.

For comparison, log(rainfall) is an okay measure to use as an independent variable, since zero rainfall is always the same, regardless of whether one uses inches, millimeters or Smoots to measure rainfall.

[Cross-posted at G-FEED]

Mashup: watercolor regression of reported rapes and daily temperature in US counties

I was working with Matthew Ranson's crime and temperature data recently for a review article when Andrew Gelman tossed in his two cents on replotting the main figures, so figured I'd see how one of the plots looked if we showed the results as a watercolor regression, since that was a recent innovation that arose from discussions on FE and Gelman's blog (watercolor regression is a type of visually-weighted regression).

I found the rape-vs-temperature plot particularly striking/perplexing/upsetting/interesting (yes, county, month-by-county and year-by-county effects have been removed from the data), so I converted the number of rape cases reported each month into percentages of the mean monthly number of reported rape cases. Temperature is the monthly mean (across days) of daily maximum temperature. Dark coloration depicts the probability that the conditional mean is at a specified value, and the estimated mean is the thin white line.

Click to enlarge

This is the largest sample I've run the watercolor regression code on (N > 1.4M), but it took less than ten minutes to plot with a few hundred resamples and 300 bins in the x-variable.  As my first attempt to use the code to show real data, I think I'm pretty satisfied with how clear the depiction of uncertainty is, without distracting from the main message (an issue described here).

[I've posted a Matlab function to compute and plot watercolor regressions here and Felix Schönbrodt posted an implementation in R here.]

Temperature, Human Health, and Adaptation

Apropos of last week's post on aggression, Marshall's post on temperature extremes, and this blog's alternate name, please see Olivier Deschênes' new NBER working paper, "Temperature, Human Health, and Adaptation: A Review of the Empirical Literature":

This paper presents a survey of the empirical literature studying the relationship between health outcomes, temperature, and adaptation to temperature extremes.  The objective of the paper is to highlight the many remaining gaps in the empirical literature and to provide guidelines for improving the current Integrated Assessment Model (IAM) literature that seeks to incorporate human health and adaptation in its framework. I begin by presenting the conceptual and methodological issues associated with the measurement of the effect of temperature extremes on health, and the role of adaptation in possibly muting these effects. The main conclusion that emerges from the literature is that despite the wide variety of data sets and settings most studies find that temperature extremes lead to significant reductions in health, generally measured with excess mortality. Regarding the role of adaptation in mitigating the effects of extreme temperature on health, the available knowledge is limited, in part due to the lack of real-world data on measures of adaptation behaviors. Finally, the paper discusses the implications of the currently available evidence for assessments of potential human health impacts of global climate change.

High temperatures cause violent crime and implications for climate change

I've posted about high temperature inducing individuals to exhibit more violent behavior when driving,  playing baseball and prowling bars.  These cases are neat anecdotes that let us see the "pure aggression" response in lab-like conditions. But they don't affect most of us too much. But violent crime in the real world affects everyone. Earlier, I posted a paper by Jacob et al. that looked at assault in the USA for about a decade - they found that higher temperatures lead to more assault and that the rise in violent crimes rose more quickly than the analogous rise in non-violent property-crime, an indicator that there is a "pure aggression" component to the rise in violent crime.

A new working paper "Crime, Weather, and Climate Change" by recent Harvard grad Matthew Ranson puts together an impressive data set of all types of crime in USA counties for 50 years. The results tell the aggression story using street-level data very clearly:

Note that all crime increases as temperatures rise from 0 F to about 50 F.  It seems reasonable to hypothesize that a lot of this pattern comes from "logistical constraints", eg. it's hard to steal a car when it's covered in snow. But above 60 F, only the violent crimes continue to go up: murder, rape, and assault.  The comparison between murder and manslaughter is elegantly telling, as manslaughter should be less motivated by malicious intent.

Ranson goes on to make projections about the expected effect of climate change:

Between 2010 and 2099, climate change will cause an additional 30,000 murders, 200,000 cases of rape, 1.4 million aggravated assaults, 2.2 million simple assaults, 400,000 robberies, 3.2 million burglaries, 3.0 million cases of larceny, and 1.3 million cases of vehicle theft in the United States.

This is pretty serious stuff. Ranson also shows that these effects haven't changed much over time, so the prospects for adaptation may be low. And there's no reason to believe that this relationship, which is probably neuro-physiological, doesn't hold outside of the USA.

Two percent per degree Celsius

That's the magic number for how worker productivity responds to warm/hot temperatures.

In my 2010 PNAS paper, I found that labor-intensive sectors of national economies decreased output by roughly 2.4% per degree C and argued that this looked suspiously like it came from reductions in worker output. Using a totally different method and dataset, Matt Neidell and Josh Graff Zivin found that labor supply in micro data fell by 1.8% per degree C.  Both responses kicked in at around 26C.

Chris Sheehan just sent me this NYT article on air conditioning, where they mention this neat natural experiment:

[I]n the past year, [Japan] became an unwitting laboratory to study even more extreme air-conditioning abstinence, and the results have not been encouraging. After the Fukushima earthquake and tsunami knocked out a big chunk of the country’s nuclear power, the Japanese government mandated vastly reduced energy consumption. To that end, lights have been dimmed and air-conditioners turned down or off, so that offices comply with the government-prescribed indoor summer temperature of 82.4 degrees (28 Celsius); some offices have tried as high as 86. 

Unfortunately, studies by Shin-ichi Tanabe, a professor of architecture at Waseda University in Tokyo who has long been interested in “thermal comfort,” found that while workers tolerated dimmer light just fine, every degree rise in temperature above 25 Celsius (77 degrees Fahrenheit) resulted in a 2 percent drop in productivity. Over the course of the day that meant they accomplished 30 minutes less work, he said.

I have said before that empirical social science should strive to replicate results and obtain similar parameters. I think we are getting there on this one.

And in case anyone is [still] listening, I [still] think that persistently reduced labor productivity may be one of the largest economic impacts of anthropogenic climate change.

I couldn't locate the Tanabe study (it sounds like it might be in Japanese), but his lab looks really cool (pun intended, but also true): they focus almost exclusively on thermal comfort and productivity. Instead of the Fukushima study, Tanabe sent me this one, which is also relevant and contains the magic number:

Temperature and infrastructure

Once while presenting this paper on temperature's influence on economic performance, someone in the audience asked whether any of the observed declines in output could be due to stress on infrastructure. I honestly replied that I didn't know, but that it seemed like a possibility.  If high temperatures began to interfere with the structure or integrity of steel, concrete or other materials used in infrastructure, existing systems might begin to slow down or fail.

Apparently, this is mechanisms is beginning to become an issue. One of today's cover stories in the New York Times described various infrastructure failures that are emerging around the country as effects of the persistent and extreme heat. Some highlights:

On a single day this month here, a US Airways regional jet became stuck in asphalt that had softened in 100-degree temperatures, and a subway train derailed after the heat stretched the track so far that it kinked — inserting a sharp angle into a stretch that was supposed to be straight. In East Texas, heat and drought have had a startling effect on the clay-rich soils under highways, which “just shrink like crazy,” leading to “horrendous cracking....” 

Excessive warmth and dryness are threatening other parts of the grid as well. In the Chicago area, a twin-unit nuclear plant had to get special permission to keep operating this month because the pond it uses for cooling water rose to 102 degrees; its license to operate allows it to go only to 100....

When railroads install tracks in cold weather, they heat the metal to a “neutral” temperature so it reaches a moderate length, and will withstand the shrinkage and growth typical for that climate. But if the heat historically seen in the South becomes normal farther north, the rails will be too long for that weather, and will have an increased tendency to kink. 

I don't know of any work on the economic or social impact of these types of failures. And I similarly don't know of any theory explaining how we ought to alter our patterns of infrastructure investment, based on the realization that this will continue into the future. The NYT article describes a few ad hoc adaptive measures that companies are starting to adopt, but since the lifetime of new infrastructure will extend into 2040 (or longer), we would do well to plan. This seems like an area ripe for research.

Temperature and generally antisocial behavior

Not only do people honk horns and hit you with baseball pitches more when it's hot out, but you also get worse customer service...

The effects of temperature on service employees' customer orientation: an experimental approach
Peter Kolba, Christine Gockelb & Lioba Wertha

Abstract: Numerous studies have demonstrated how temperature can affect perceptual, cognitive and psychomotor performance. We extend this research to interpersonal aspects of performance, namely service employees' and salespeople's customer orientation. We combine ergonomics with recent research on social cognition linking physical with interpersonal warmth/coldness. In Experiment 1, a scenario study in the lab, we demonstrate that student participants in rooms with a low temperature showed more customer-oriented behaviour and gave higher customer discounts than participants in rooms with a high temperature – even in zones of thermal comfort. In Experiment 2, we show the existence of alternative possibilities to evoke positive temperature effects on customer orientation in a sample of 126 service and sales employees using a semantic priming procedure. Overall, our results confirm the existence of temperature effects on customer orientation. Furthermore, important implications for services, retail and other settings of interpersonal interactions are discussed.

High temperature causes violent crime

There is a well developed literature on temperature and agression (evidence from horn-honking and baseball), but the identification of causal effects/external validity is sometimes questionable. Here's a 2007 paper I ran into that has clean statistics for violent crime in several US states (although the focus of the paper is not actually the causal affect of weather on crime).  I find the table somewhat incredible.

The Dynamics of Criminal Behavior: Evidence from Weather Shocks 

Author(s): Brian Jacob, Lars Lefgren, Enrico Moretti (NBER working paper)

We should rename this the Temperature Blog

When I first showed these results to people, more than one of my senior colleagues said "It can't be true, you made a mistake."  But now that business faculty are working on the problem, I might be willing to declare that we have reached stage two of acceptance.

Severe Weather and Automobile Assembly Productivity

Gérard P. Cachon, Santiago Gallino and Marcelo Olivares


Abstract: It is expected that climate change could lead to an increased frequency of severe weather. In turn, severe weather intuitively should hamper the productivity of work that occurs outside. But what is the effect of rain, snow, fog, heat and wind on work that occurs indoors, such as the production of automobiles? Using weekly production data from 64 automobile plants in the United States over a ten-year period, we find that adverse weather conditions lead to a significant reduction in production. For example, one additional day of high wind advisory by the National Weather Service (i.e., maximum winds generally in excess of 44 miles per hour) reduces production by 26%, which is comparable in order of magnitude to the estimated productivity drop during the launch of a new vehicle. Furthermore, the location with the best weather (Arlington, Texas) only loses 2% of production per year due to the weather, whereas the location with the most adverse weather (Lordstown, OH) suffers an annual production loss of 11%. Our findings are useful both for assessing the potential aggregate productivity shock associated with inclement weather as well as guiding managers on where to locate a new production facility - in addition to the traditional factors considered in plant location (e.g., labor costs, local regulations, proximity to customers, access to suppliers), we add the prevalence of bad weather.



Welfare Costs of Long-Run Temperature Shifts
Ravi Bansal, Marcelo Ochoa

Abstract: This article makes a contribution towards understanding the impact of temperature fluctuations on the economy and financial markets.  We present a long-run risks model with temperature related natural disasters.  The model simultaneously matches observed temperature and consumption growth dynamics, and key features of financial markets data.  We use this model to evaluate the role of temperature in determining asset prices, and to compute utility-based welfare costs as well as dollar costs of insuring against temperature fluctuations. We find that the temperature related utility-costs are about 0.78% of consumption, and the total dollar costs of completely insuring against temperature variation are 2.46% of world GDP.  If we allow for temperature-triggered natural disasters to impact growth, insuring against temperature variation raise to 5.47% of world GDP. We show that the same features, long-run risks and recursive-preferences, that account for the risk-free rate and the equity premium puzzles also imply that temperature-related economic costs are important.  Our model implies that a rise in global temperature lowers equity valuations and raises risk premiums.

Temperature, Aggregate Risk, and Expected Returns
Ravi Bansal, Marcelo Ochoa

Abstract: In this paper we show that temperature is an aggregate risk factor that adversely affects economic growth.  Our argument is based on evidence from global capital markets which shows that the covariance between country equity returns and temperature (i.e., temperature betas) contains sharp information about the cross-country risk premium; countries closer to the Equator carry a positive temperature risk premium which decreases as one moves farther away from the Equator.  The differences in temperature betas mirror exposures to aggregate growth rate risk, which we show is negatively impacted by temperature shocks.  That is, portfolios with larger exposure to risk from aggregate growth also have larger temperature betas; hence, a larger risk premium.  We further show that increases in global temperature have a negative impact on economic growth in countries closer to the Equator, while its impact is negligible in countries at high latitudes.  Consistent with this evidence, we show that there is a parallel between a country's distance to the Equator and the economy's dependence on climate sensitive sectors; in countries closer to the Equator industries with a high exposure to temperature are more prevalent.  We provide a Long-Run Risks based model that quantitatively accounts for cross-sectional differences in temperature betas, its link to expected returns, and the connection between aggregate growth and temperature risks.



More related material here.

Energy and temperature are substitutes in the production of health

This week in AEJ Applied:

Climate Change, Mortality, and Adaptation: Evidence from Annual Fluctuations in Weather in the US 
Olivier Deschênes and Michael Greenstone

Abstract: Using random year-to-year variation in temperature, we document the relationship between daily temperatures and annual mortality rates and daily temperatures and annual residential energy consumption. Both relationships exhibit nonlinearities, with significant increases at the extremes of the temperature distribution. The application of these results to "business as usual" climate predictions indicates that by the end of the century climate change will lead to increases of 3 percent in the age-adjusted mortality rate and 11 percent in annual residential energy consumption. These estimates likely overstate the long-run costs, because climate change will unfold gradually allowing individuals to engage in a wider set of adaptations.

More on temperature's substitutes/compliments here and here.

(h/t Michael O)

Temperature and worker output

Earlier this week I was at a small but excellent conference on adaptation to climate change, hosted at PERC in Bozeman (Michael Greenstone's keynote is covered here).  Lots of interesting results and ideas came up, but this was one of the most exciting outcomes for me.

Matt Neidell was presenting his working paper (joint with Josh Graff Zivin) on "Temperature and the Allocation of Time: Implications for Climate Change" when he put up this graph. It shows the number of minutes in a day that individuals (who work in outdoor or temperature-exposed sectors in the USA) spent working as a function of maximum temperature (in Fahrenheit) that day.  The interesting part of the graph is that on hot days, people work for less time.

Wolfram Schlenker then commented something like, "60 minutes out of an 8-hr work day? That's a huge effect!" And I thought "hmmm... 12.5% sounds familiar..." and then pulled up this graph from my own work on my computer.  The panel shows total output for similar sectors (in 28 countries, not including the USA) as a function of average daily temperature (in Celsius).  The graph shows that national output in several [non-agricultural] industries seemed to decline with temperature in a nonlinear way, declining more rapidly at very high daily temperatures.

Matt's graph uses micro-data from the American Time Use Survey combined with interpolated daily weather station data while mine uses total national production from UN national accounts combined with degree-day reconstructions from NCEP reanalysis, so they are completely different data sets utilizing completely different methods, but the results look extremely similar!  On hot days, output in non-agricultural sectors drops and workers work less.

Furthermore, not only do the shape of the response-functions look similar, but the magnitudes of the responses are similar (recall Wolfram's comment).  In Matt's graph, a day with maximum temperatures near 102.5 F (39.2 C) reduces time working by about 60 minutes (12.5% of an 8 hr day) relative to a day with maximum temperatures near 77.5 F (25.3 C).  In my graph, a day with average temperatures near 30.5 C reduces output to around 90% of what it would be relative to a day with average temperatures near 27 C.  Since daily average temperature is usually computed by averaging daily max and min temperatures, variations in average temperature should be approximately one half of variation in the max.  Using this rule to convert to common units, Matt and Josh found time worked fell by about 1.8% per 1 C in daily mean temperature [12.5%/((39.2 C-25.3 C)/2)] while I found that national output fell by about 2.9% per 1 C in daily mean temperature [10/(30.5-27)].  These numbers are not exactly identical, but they are certainly not statistically different give the uncertainty in both of our models.  In fact, I would say that they are extremely close given how different our techniques are.  To me, this feels like a research success.

It's worth noting that reductions in worker output have never been included in economic models of future warming (see here and here) despite the fact that experiments fifty years ago showed that temperature has a strong impact on worker output (see here and here).  In my dissertation I did some back-of-the-envelope estimates using the above numbers and found that productivity impacts alone might reduce per capita output by ~9% in 2080-2099 (in the absence of strong adaptation).  This cost excedes the combined cost of all other projected economic losses combined (eg. see here and here).

$20B/yr to air condition troops in Iraq and Afghanistan

When I've presented my work on thermal stress and economic productivity (also see here, here, here and here for related work) most people's first response is, "so... poor countries should use more air conditioning?" to which is say "Yes, but..." and then discuss the fact that air conditioning isn't exactly cheap if you have $1000/year to live on (so this investment may not always be worth it for poor individuals). To do this, I usually point out that and AC costs at least $100 to buy and $10/month (at least) in electricity costs.  But my casual back of the envelope estimates of operational costs might be way off.  I had been assuming that electricity and ACs could be obtained in a poor country for the same price I can get these goods in New York.  I was probably being too optimistic.

Listening to NPR today, I heard this report:

The amount the U.S. military spends annually on air conditioning in Iraq and Afghanistan: $20.2 billion. 

That's more than NASA's budget. It's more than BP has paid so far for damage during the Gulf oil spill. It's what the G-8 has pledged to help foster new democracies in Egypt and Tunisia. 

"When you consider the cost to deliver the fuel to some of the most isolated places in the world — escorting, command and control, medevac support — when you throw all that infrastructure in, we're talking over $20 billion," Steven Anderson tells weekends on All Things Considered guest host Rachel Martin. Anderson is a retired brigadier general who served as Gen. David Patreaus' chief logistician in Iraq. 

Why does it cost so much? 

To power an air conditioner at a remote outpost in land-locked Afghanistan, a gallon of fuel has to be shipped into Karachi, Pakistan, then driven 800 miles over 18 days to Afghanistan on roads that are sometimes little more than "improved goat trails," Anderson says. "And you've got risks that are associated with moving the fuel almost every mile of the way." 

Anderson calculates more than 1,000 troops have died in fuel convoys, which remain prime targets for attack. Free-standing tents equipped with air conditioners in 125 degree heat require a lot of fuel. Anderson says by making those structures more efficient, the military could save lives and dollars.

This suggests the annual price of AC for each of our 70,000 troops is $31,428.57 per soldier, two orders of magnitude over my ~$200 back of the envelope estimate. I'm certain that this price is not the actual consumer price that we would observe for air conditioners being used by residents in the long-run, but it's so much larger than my previous estimate that I may have to reconsider how effective I think AC expansion is for mitigating the economic impact of high temperatures.

Are Temperature and Incentives Compliments or Substitutes? Evidence from 1947

Here's another gem from the lab of Norman Mackworth (which in my head is looking increasingly like the Dharma Initiative): "High Incentives Versus Hot and Humid Atmospheres in a Physical Effort Task" N. H. Mackworth (British Journal of Psychology, 1947).  The setup is very similar to my last post, except this time the workers are doing arm curls until complete exhaustion:

But Mackworth varied whether the worker was encouraged to push themselves to do more (verbally and visually).  In all cases, the workers with encouragement did more arm curls.  But at high temperatures, this margin dropped substantially (see fig). In this case, it seems like moderate temperatures and incentives are compliments.  This sounds like unfortunate news for hot developing countries...

[For a review of what's happened since 1947 in this field of ergonomics, see the book chapter here.]

Are Temperature and Human Capital Compliments or Substitutes? Evidence from 1946

My own work has focused on whether economic productivity can be influence by temperature through its impact on worker productivity. I recently dug up "Effects of Heat on Wireless Telegraphy Operators Hearing and Recording Morse Messages" by N. H. Mackworth (British Journal of Industrial Medicine, 1946) and have decided its one of my favorite papers. The British military asked Norman Mackworth to put Morse code operators in rooms of varying temperature and humidity and recorded the number of errors they made. These guys were put to work in 3 hour stretches, decoding random sequences of letters and numbers for 5-7 weeks (see fig).  

The main result is stark.  The operators who were considered "exceptionally skilled" (based on their error rates at low temperatures) were hardly affected by the heat. But the less skilled operators had error rates that went through the roof when temperatures rose (see below). Apparently, moderate temperatures and human capital are substitutes (at least in this situation). This is good news for many of the hot, developing countries around the world...

How important is brain temperature? Ask a large predator fish

This is the kind of thing I can't believe they didn't teach me in elementary school.  I knew the platypus was exceptional among mammals for its beak and eggs, but I never knew that some cold-blooded animals (ectotherms) were actually partially warm-blooded (regional endothermy is the technical name). 

I was doing a literature review of the effects of temperature on brain function and cognition, when I ran across this amazing literature. In a famous 1982 Science article, Francis Carey of WHOI demonstrated that swordfish had evolved a specialized organ that simply sat next to their brain and kept it warm by burning calories quickly.  This was important, he argued, because these fish rapidly dove to depths where the water temperature was 20 degrees (C) colder than their normal environment. Because brain function is important to these hunters, it seemed reasonable that it was worth it for them to evolve specialized organs to keep their brains warm.

Sound too fantastic? Since then, cranial endothermy has also been documented in some varieties of sharks and tuna.  Because these species are so far from one another (in an evolutionary sense) and many of their more closely related relatives didn't have brain heaters, its thought that these different groups evolved similar organs independently from one another. This would suggest that maintaining a relatively more stable brain temperature might have large benefits.  Now, does this apply to humans?...

Temper and Temperature in Major League Baseball

Another recent (slightly amusing but) good one from Psychological Science. (Related here and here).

Temper, Temperature, and Temptation
Heat-Related Retaliation in Baseball
Richard P. Larrick, Thomas A. Timmerman, Andrew M. Carton and Jason Abrevaya

Abstract: In this study, we analyzed data from 57,293 Major League Baseball games to test whether high temperatures interact with provocation to increase the likelihood that batters will be hit by a pitch. Controlling for a number of other variables, we conducted analyses showing that the probability of a pitcher hitting a batter increases sharply at high temperatures when more of the pitcher’s teammates have been hit by the opposing team earlier in the game. We suggest that high temperatures increase retaliation by increasing hostile attributions when teammates are hit by a pitch and by lowering inhibitions against retaliation.