Pioneering research led by the UK Centre for Ecology & Hydrology (UKCEH) has devised the first system that classifies lakes globally, placing each of them in one of nine ‘thermal regions’ (see map).

Lakes are grouped depending on their seasonal patterns of surface water temperatures, with the coldest thermal region including lakes in Alaska, Canada, northern Russia and China, and the warmest covering lakes in equatorial South America, Africa, India and south-east Asia.

By incorporating climate change models, the scientists predict that by the year 2100, for the most extreme climate change scenario, average lake temperature will be around 4 degrees Celsius warmer and that 66 per cent of lakes globally will be classified in a warmer thermal region than they are now.

The study — carried out by UKCEH, the Universities of Dundee, Glasgow, Reading and Stirling, plus the Dundalk Institute of Technology — was funded by the Natural Environment Research Council (NERC) and has been published in the journal Nature Communications.

Professor Stephen Maberly of UKCEH, lead author of the study, explains: “Thanks to cutting-edge analysis using satellite images of more than 700 lakes, taken twice a month over 16 years, we produced the first global lake temperature classification scheme. By combining this with a lake model and climate change scenarios we were able to identify that northern lakes, such as those in the UK, will be particularly sensitive to climate change.”

Even relatively small changes in temperature can have a significant negative impact on aquatic wildlife, affecting the speed at which organisms grow and feed, and when they reproduce. As species do not react in the same way, prey and predators have increasingly different breeding and feeding cycles, reducing the amount of potential food available.

Warming also increases the risk of harmful algal blooms, which can have a negative impact on aquatic plants and fish.

Professor Maberly says: “Cold-water fish species in particular can be stressed by warmer temperatures. The potential negative impact on salmonids such as salmon, trout and Arctic charr, for example, is concerning because they play a central ecological role within food webs and also have great economic importance.”

The research is aimed at scientists interested in freshwater ecology, climate change, greenhouse gas emissions and biogeochemical cycles.

Professor Andrew Tyler of the University of Stirling, who led the overall project, GloboLakes, says: “This is an example of pioneering UK-led research that has delivered the capability to monitor our inland waters at the global scale from satellite based platforms.

“This is not only yielding new insights into the impacts of climate change, but also the evidence base from which to better manage these ecologically sensitive environments and mitigate against the effects of change.”

An app to classify lakes into the nine thermal regions is available in the R programming language at GitHub — https://github.com/ruth-odonnell/LakeThermalRegions/

New research using 40 years of global data, led by Colorado State University, has found that exposure to rising high temperatures has been substantially moderated by the migration of rainfed corn, wheat and rice. Scientists said continued migration, however, may result in significant environmental costs.

The study, “Climate adaptation by crop migration,” is published March 6 in Nature Communications.

“There’s substantial concern about the impacts of climate change on agriculture and how we can adapt to those changes,” said Nathan Mueller, assistant professor in the Department of Ecosystem Science and Sustainability at CSU and a senior author on the paper.

“We often think about how farmers can adapt to shifting climate conditions by changing crop varieties or planting dates. But farmers have also been changing what crops they are growing over time, collectively leading to large-scale shifts in crop distribution. This pathway of adaptation has been underexplored.”

40 years of data from around the world

Using new, high-resolution datasets on crop areas around the world, the research team analyzed the location of crops, climate, and irrigation from 1973 to 2012. They focused on rainfed crops, since they are highly sensitive to changes in temperature and extreme weather.

“We found that on average, over these cropland areas, things are getting warmer,” said Mueller, also a researcher in the CSU College of Agricultural Sciences.

The study showed that exposure to increased high temperatures for corn, wheat and rice was much less than it would have been if the crops were positioned where they were in the 1970s.

CSU postdoctoral fellow and first author Lindsey Sloat said this does not mean there is an unlimited capacity for farmers to adapt to climate change by shifting where they grow crops.

“If you add new farmland, that comes with massive environmental consequences,” she said. “Land use change in agriculture is one of the biggest drivers of biodiversity loss, with consequences for carbon storage. We can mitigate some of the effects of climate change by increasing irrigation, but there are also environmental costs on that front.”

Researchers also found that unlike the other crops, there has been a huge expansion in the production of soybeans, and that these crops are being grown in hotter areas around the world.

Next steps

Sloat said the research team will next delve into analyzing other climate variables, moving beyond temperature to consider how changes in a harvested area can alter exposure to other extreme climate conditions.

“Since this migration has been extensive enough in the past to substantially alter exposure to climate trends, we need to think about what our agricultural landscapes are going to look like in the future as warming increases,” said Mueller.

Co-authors on the paper include Steven Davis from the University of California, Irvine; James Gerber, Deepak Ray and Paul West from the University of Minnesota; and Frances Moore from the University of California, Davis.

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Materials provided by Colorado State University. Original written by Mary Guiden. Note: Content may be edited for style and length.

Can walls and flat surfaces be recognized using sound waves? Mathematicians have been studying this question from a theoretical standpoint for quite some time.

“The basic scenario is a room with flat walls, and maybe a ceiling and a floor,” explains Prof. Gregor Kemper of the Chair of Algorithmic Algebra at TUM. The room is not assumed to be rectangular. It is also possible to measure the slope of the walls. Several microphones and a loudspeaker are contained in the room.

Speaker and microphones are placed on a drone

Previous studies have already mathematically proven that four microphones and a loudspeaker are sufficient to pinpoint the walls and also calculate their inclination. To prepare for this, the microphones have to be brought into the room at random positions, which will take quite some time and in some situations will be altogether impossible.

That is why Kemper and Boutin took the idea one step further. In their theoretical approach, they mounted the loudspeaker and four microphones on a drone — making measurement much more practical, because the equipment does not have to be installed in the room.

The algorithm can match echoes to a wall

The basic principle remains unchanged in the current approach: When the loudspeaker sends out a sound impulse, the waves bounce back from the walls. These direct reflections of the impulse are referred to as first order echoes. The biggest problem arising in the mathematical feasibility study: “Every microphone detects a large number of echoes. We need to be able to decide with certainty which echoes are coming from which wall,” says Kemper.

The transit time — the time delay between emitting the sound pulse and receiving its echo — can be determined very precisely using the microphones. All transit times from a given wall have a specific relationship with one another. Kemper and Boutin developed a new algorithm that uses this relationship to assign individual echoes to a particular wall.

Once the echoes have been assigned to the right walls, the position and inclination of the walls are calculated using a geometric approach similar to that used by GPS when determining location data.

Ghost walls can be created by chance

The calculation can go wrong, however. That is because some echoes might satisfy the conditions of the mathematical relationship by chance. This leads to the identification of walls that are actually not there, so-called ghost walls.

“Naively, the probability of ghost walls would be expected to be higher when the microphones are mounted on a drone,” explains Kemper. “This is because, in contrast to microphones mounted freely in space, they have less freedom of movement due to their rigid mounting on the drone. Instead of twelve, they have only six degrees of freedom.”

Drone in ideal position for measurements

The question of how likely it is for such ghost walls to arise in the measurement process leads to the core statement of the paper: Kemper and Boutin have proved that the drone’s freedom of motion is sufficient for the probability of placing it in a “good” position — meaning a position where no ghost walls are detected — to be equal to 1. In other words, such a placement is a near certainty.

“The six degrees of freedom of the drone are sufficient for the microphones to be almost certainly in an optimal position for the measurement,” says Kemper. The only prerequisite is that the microphones are not arranged in a common plane on the drone.

A first step towards practical applications

In a next step, the researchers’ scenario will become more realistic: They hope to find a mathematical solution for when errors or inaccuracies occur during measurement. They also intend to study configurations with the loudspeaker and microphones mounted on ground-based vehicles.

“In Western cultures, caffeine is stereotypically associated with creative occupations and lifestyles, from writers and their coffee to programmers and their energy drinks, and there’s more than a kernel of truth to these stereotypes,” wrote Darya Zabelina, assistant professor of psychology and first author of the study recently published in the journal Consciousness and Cognition.

While the cognitive benefits of caffeine — increased alertness, improved vigilance, enhanced focus and improved motor performance — are well established, she said, the stimulant’s affect on creativity is less known.

In the paper, Zabelina differentiates “convergent” from “divergent” thinking. The former is defined as seeking a specific solution to a problem, for example, the “correct” answer. The latter is characterized by idea generation where a large set of apt, novel or interesting responses would be suitable. Caffeine was shown to improve convergent thinking in the study, while consuming it had no significant impact on divergent thinking.

For the study, 80 volunteers were randomly given either a 200mg caffeine pill, equivalent to one strong cup of coffee, or a placebo. They were then tested on standard measures of convergent and divergent thinking, working memory and mood. In addition to the results on creativity, caffeine did not significantly affect working memory, but test subjects who took it did report feeling less sad.

“The 200mg enhanced problem solving significantly, but had no effect on creative thinking,” said Zabelina. “It also didn’t make it worse, so keep drinking your coffee; it won’t interfere with these abilities.”

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Materials provided by University of Arkansas. Note: Content may be edited for style and length.