It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Monday, March 02, 2020
Links Among Human Health, Animal Health, and Ecosystem Health
Annual Review of Public Health
Vol. 34:189-204 (Volume publication date March 2013)
First published online as a Review in Advance on January 16, 2013
In the face of growing world human and animal populations and rapid environmental change, the linkages between human, animal, and environmental health are becoming more evident. Because animals and humans have shared risk to health from changing environments, it seems logical to expand the perspective of public health beyond a single species to detect and manage emerging public health threats. Mitigating the effects of climate change, emerging pathogens, toxicant releases, and changes in the built environment requires a retooling of global public health resources and capabilities across multiple species. Furthermore, human and animal health professionals must overcome specific barriers to interprofessional collaboration to implement needed health strategies. This review outlines the relationships between human, animal, and ecosystem health and the public health challenges and opportunities that these links present.
Two evolutionary spaces illustrate how a small change in environmental conditions with few immediate effects opens up a gradual path toward regime change. Credit: Andre de Roos
When a grassland becomes a desert, or a clearwater lake shifts to turbid, the consequences can be devastating for the species that inhabit them. These abrupt environmental changes, known as regime shifts, are the subject of new research in Nature Ecology & Evolution which shows how small environmental changes trigger slow evolutionary processes that eventually precipitate collapse.
Until now, research into regime shifts has focused on critical environmental thresholds, or "tipping points," in external conditions—eg when crossing a certain temperature threshold triggers a sudden shift to desertification. But the new model by Catalina Chaparro-Pedraza and SFI External Professor André de Roos, both at the University of Amsterdam, reveals how a small change in the external environment, with little immediate impact, can induce slow evolutionary changes in the species that inhabit the system. After what the researchers call a "considerable delay," wherein species slowly evolve a new trait or behavior over generations, the regime shift manifests as a delayed reaction.
"Instead of looking for a straightforward relationship between environmental tipping points and ecosystemic collapse, our work brings evolution into the picture," Chaparro-Pedraza explains. "Even though the outcome is the same, we think it's critically important to map out different paths that lead to regime shifts so we can predict and eventually prevent them."
In their model, the researchers demonstrate how these evolution-induced, delayed regime shifts arise in communities of salmon. At different stages of their lives, salmon live in freshwater and marine ecosystems, which both have entirely different biological communities. When a slight change in the marine environment reduces the mortality exposure of the saltwater salmon population, the immediate effects are minor. However, it initiates an evolutionary process that slowly drives individual character traits, like the optimal body size for migrating from the river to an open ocean, to a critical threshold where a regime shift occurs. Remarkably, this regime shift produces dramatic changes in community composition in both the freshwater and marine communities simultaneously, even though nothing changed in the environmental conditions of the freshwater community.
Understanding the role of evolutionary processes in regime shifts could also shed light on other complex, interdependent systems. De Roos and Chaparro-Pedraza also examined data from the 2008 financial crisis, which, according to de Roos, "seem pretty much in line with the adaptation-induced regime shift we report in this paper." In this example, the 2008 crash can be seen as the delayed regime shift. The deregulation of the financial system in the 1970s and 1980s would be the environmental change with a negligible immediate effect, and the documented trend of banks changing their debt-to-asset ratio would be analogous to the evolutionary process triggered by the environmental change.
"Regime shifts don't just happen in ecosystems," says de Roos. "They also appear in systems like stock markets. Our model shows the evolutionary mechanism by which a sudden change—like an ecosystem or financial collapse—may be the result of a small environmental change in the distant past."
More information: P. Catalina Chaparro-Pedraza et al. Ecological changes with minor effect initiate evolution to delayed regime shifts, Nature Ecology & Evolution (2020). DOI: 10.1038/s41559-020-1110-0
Coronavirus: Domestic livestock strains are commonplace
Strains of coronavirus can occur annually in domestic cattle herds. Credit: Texas A&M AgriLife photo by Kay Ledbetter
Many people are hearing about coronavirus for the first time as COVID-19 affecting humans causes concern all across the world. But coronaviruses are not new to livestock and poultry producers, according to a Texas A&M AgriLife veterinary epidemiologist.
According to the Centers for Disease Control and Prevention, common human coronaviruses usually cause mild to moderate upper-respiratory tract illnesses, like the common cold. Most people get infected with one or more of these viruses at some point in their lives.
But the CDC is now responding to an outbreak of respiratory disease caused by a novel or new coronavirus that was first detected in Wuhan City, Hubei Province, China.
"Coronavirus is a common virus in livestock herds and poultry flocks seen routinely worldwide," said Heather Simmons, DVM, Institute for Infectious Animal Diseases, IIAD, associate director as well as Texas A&M AgriLife Extension Service's associate department head and extension program leader for Veterinary Medical Extension. IIAD is a member of the Texas A&M University System and Texas A&M AgriLife Research.
Wildlife in China may be human strain carriers
"In wildlife, bats are known to carry over 100 different strains of coronavirus, and wild civets are the source of the coronavirus that causes SARS (Severe Acute Respiratory Syndrome), first reported in China in 2002-2003," Simmons said. "Although our understanding is still limited, wild pangolins (a scaly anteater) sold at live markets may be associated with the recently reported coronavirus outbreak in China."
Bats, civets and pangolins are all commonly sold at live markets in China, she said. Coronaviruses from wildlife are dangerous since they have the potential to mutate, adapt and spill over to new species, including humans.
"That is the concern now, this new strain of coronavirus has emerged to cause disease in humans," Simmons said. "It is important to create an understanding of the difference between coronaviruses occurring in domestic livestock and poultry compared to coronaviruses that spill over from wildlife to humans."
Coronavirus in domestic livestock doesn't jump to humans
Simmons said, to date, the coronaviruses in livestock are not considered reportable diseases because their main effect is as an economic burden to livestock producers.
They are known to occur worldwide annually, with some of the most common coronaviruses found in production animals to include the scours and winter dysentery in beef and dairy cattle, porcine respiratory coronavirus in swine and avian infectious bronchitis in poultry.
The World Health Organization has reported that while another coronavirus, MERS-CoV, is known to be transmitted from dromedary camels to humans, other coronaviruses circulating in domestic animals have not yet infected humans.
"That's what is very important to understand at this time," Simmons said. "We have been dealing with these diseases for a long time but as of yet, we have not seen cases worldwide transmitted from livestock to humans or vice versa."
What does coronavirus look like in livestock?
While coronaviruses have a high morbidity, or rate of illness, in livestock and poultry they are generally considered to have low mortality, rate of death, Simmons said. Coronaviruses will affect either the respiratory system or the gastrointestinal system, depending on the species and the age of the animal.
Coronavirus in cattle
In calves, diarrhea commonly occurs in animals under three weeks of age due to a lack of obtaining antibodies when the calf does not get enough colostrum from the mother in order to build up immunity. Clinical signs include severe dehydration and diarrhea. The severity of the clinical signs depends on the age of the calf and their immune status. This is often seen by producers in the winter months as the virus is more stable in cold weather. The second clinical syndrome, winter dysentery is found in adult cattle. Clinical signs include bloody diarrhea with decreased mild production, loss of appetite with some respiratory signs. Bovine coronaviruses can also cause mild respiratory disease or pneumonia in calves up to six months. The virus is shed in the environment through nasal secretions and through feces.
Coronavirus in swine
There are multiple coronaviruses that affect swine. Like cattle, they affect the respiratory or gastrointestinal tract. In sows and piglets, porcine respiratory coronavirus usually presents with no clinical signs. If clinical signs do occur, it may be a transient cough within the herd and spread of this disease occurs through aerosolized methods.
Coronavirus in poultry
Infectious bronchitis virus, or IBV, is a rapidly spreading respiratory disease in young chicks. Clinical signs in laying hens include reduced production, eggshell abnormalities and decreased internal egg quality.
How to treat
Livestock producers should consult with a veterinarian for treatment, Simmons said. Treatment in livestock herds and poultry flocks typically includes supportive therapy of fluids. Antibiotics are not indicated for viral infections but may be used if a secondary bacterial infection occurs.
Water vapor (gray) and sea surface temperature (blue to red) from the high-resolution E3SMv1. Just above center you can see a hurricane and the track of cold water (green) it produces trailing behind it. Credit: Mat Maltrud / Los Alamos National Laboratory
Earth supports a breathtaking range of geographies, ecosystems and environments, each of which harbors an equally impressive array of weather patterns and events. Climate is an aggregate of all these events averaged over a specific span of time for a particular region. Looking at the big picture, Earth's climate just ended the decade on a high note—although not the type one might celebrate.
In January, several leading U.S. and European science agencies reported 2019 as the second-hottest year on record, closing out the hottest decade. July went down as the hottest month ever recorded.
Using new high-resolution models developed through the U.S. Department of Energy's (DOE) Office of Science, researchers are trying to predict these kinds of trends for the near future and into the next century; hoping to provide the scientific basis to help mitigate the effects of extreme climate on energy, infrastructure and agriculture, among other essential services required to keep civilization moving forward.
Seven DOE national laboratories, including Argonne National Laboratory, are among a larger collaboration working to advance a high-resolution version of the Energy Exascale Earth System Model (E3SM). The simulations they developed can capture the most detailed dynamics of climate-generating behavior, from the transport of heat through ocean eddies—advection—to the formation of storms in the atmosphere.
"E3SM is an Earth system model designed to simulate how the combinations of temperature, winds, precipitation patterns, ocean currents and land surface type can influence regional climate and built infrastructure on local, regional and global scales," explains Robert Jacob, Argonne's E3SM lead and climate scientist in its Environmental Science division. "More importantly, being able to predict how changes in climate and water cycling respond to increasing carbon dioxide (CO2) is extremely important in planning for our future."
"Climate change can also have big impacts on our need and ability to produce energy, manage water supplies and anticipate impacts on agriculture" he adds, "so DOE wants a prediction model that can describe climate changes with enough detail to help decision-makers."
Facilities along our coasts are vulnerable to sea level rise caused, in part, by rapid glacier melts, and many energy outages are the result of extreme weather and the precarious conditions it can create. For example, 2019's historically heavy rainfalls caused damaging floods in the central and southern states, and hot, dry conditions in Alaska and California resulted in massive wild fires.
And then there is Australia.
To understand how all of Earth's components work in tandem to create these wild and varied conditions, E3SM divides the world into thousands of interdependent grid cells—86,400 for the atmosphere to be exact. These account for most major terrestrial features from "the bottom of the ocean to nearly the top of the atmosphere," collaboration members wrote in a recent article published in the Journal of Advances in Modeling Earth Systems.
"The globe is modeled as a group of cells with 25 kilometers between grid centers horizontally or a quarter of a degree of latitude resolution," says Azamat Mametjanov, an application performance engineer in Argonne's Mathematics and Computer Science division. "Historically, spatial resolution has been much coarser, at one degree or about 100 kilometers. So we've increased the resolution by a factor of four in each direction. We are starting to better resolve the phenomena that energy industries worry about most—extreme weather."
Researchers believe that E3SM's higher-resolution capabilities will allow researchers to resolve geophysical features like hurricanes and mountain snowpack that prove less clear in other models. One of the biggest improvements to the E3SM model was sea surface temperature and sea ice in the North Atlantic Ocean, specifically, the Labrador Sea, which required an accurate accounting of air and water flow.
"This is an important oceanic region in which lower-resolution models tend to represent too much sea ice coverage," Jacob explains. "This additional sea ice cools the atmosphere above it and degrades our predictions in that area and also downstream."
Increasing the resolution also helped resolve the ocean currents more accurately, which helped make the Labrador Sea conditions correspond with observations from satellites and ships, as well as making better predictions of the Gulf Stream.
Another distinguishing characteristic of the model, says Mametjanov, is its ability to run over multiple decades. While many models can run at even higher resolution, they can run only from five to 10 years at most. Because it uses the ultra-fast DOE supercomputers, the 25-km E3SM model ran a course of 50 years.
Eventually, the team wants to run 100 years at a time, interested mainly in the climate around 2100, which is a standard end date used for simulations of future climate.
Higher resolution and longer time sequences aside, running such a model is not without its difficulties. It is a highly complex process.
For each of the 86,400 cells related to the atmosphere, researchers run dozens of algebraic operations that correspond to some meteorological processes, such as calculating wind speed, atmospheric pressure, temperature, moisture or the amount of localized heating contributed by sunlight and condensation, to name just a few.
"And then we have to do it thousands of times a day," says Jacob. "Adding more resolution makes the computation slower; it makes it harder to find the computer time to run it and check the results. The 50-year simulation that we looked at in this paper took about a year in real time to run."
Another dynamic for which researchers must adjust their model is called forcing, which refers mainly to the natural and anthropogenic drivers that can either stabilize or push the climate into different directions. The main forcing on the climate system is the sun, which stays relatively constant, notes Jacob. But throughout the 20th century, there have been increases in other external factors, such as CO2 and a variety of aerosols, from sea-spray to volcanic.
For this first simulation, the team was not so much probing a specific stretch of time as working on the model's stability, so they chose a forcing that represents conditions during the 1950s. The date was a compromise between preindustrial conditions used in low-resolution simulations and the onset of the more dramatic anthropogenic greenhouse gas emissions and warming that would come to a head in this century.
Eventually, the model will integrate current forcing values to help scientists further understand how the global climate system will change as those values increase, says Jacob.
"While we have some understanding, we really need more information—as do the public and energy producers—so we can see what's going to happen at regional scales," he adds. "And to answer that, you need models that have more resolution."
One of the overall goals of the project has been to improve performance of the E3SM on DOE supercomputers like the Argonne Leadership Computing Facility's Theta, which proved the primary workhorse for the project. But as computer architectures change with an eye toward exascale computing, next steps for the project include porting the models to GPUs.
"As the resolution increases using exascale machines, it will become possible to use E3SM to resolve droughts and hurricane trends, which develop over multiple years," says Mametjanov.
"Weather models can resolve some of these, but at most for about 10 days. So there is still a gap between weather models and climate models and, using E3SM, we are trying to close that gap."
The E3SM collaboration's article, "The DOE E3SM Coupled Model Version 1: Description and Results at High Resolution," appeared in the December 2019 issue of Journal of Advances in Modeling Earth Systems.
More information: Peter M. Caldwell et al. The DOE E3SM Coupled Model Version 1: Description and Results at High Resolution, Journal of Advances in Modeling Earth Systems (2019). DOI: 10.1029/2019MS001870
Above-average autumn temperatures expected even if El Nino unlikely
by World Meteorological Organization
Credit: WMO
Above average temperatures are expected in many parts of the globe in the next few months, even without the presence of a warming El Niño event, according to the World Meteorological Organization.
WMO's El Niño/Southern Oscillation (ENSO) Update said that there is a 60% chance of ongoing ENSO-neutral conditions continuing during March-May 2020. The chances for an El Niño or La Niña are 35% and 5% respectively. For the June-August 2020 season, the chance for ENSO-neutral is 55%, that for El Niño is 20-25% and that for La Niña is also 20-25%.
The El Niño/Southern Oscillation is a naturally occurring phenomenon involving fluctuations of ocean surface temperatures in the equatorial Pacific, coupled with changes in the overlying atmospheric circulation. It has a major influence on weather and climate patterns and is linked to hazards such as heavy rains, floods and drought. El Niño typically has a warming influence on global temperatures, whilst La Niña has the opposite effect.
El Niño and La Niña are not the only naturally occurring phenomena that drive global climate patterns. WMO has therefore introduced a new Global Seasonal Climate Update, currently in a trial phase, which factors in other climate drivers such as the Indian Ocean Dipole.
The Global Seasonal Climate Update said that above average sea surface temperatures are likely across sizeable portions of the globe, both in the tropics and extra-tropics. As a result, the forecast for March-May 2020 leans towards above-normal land temperature, particularly at tropical latitudes.
The global warming trend also contributes to the above-average sea surface temperature and air temperature forecast, it said.
"Even ENSO neutral months are warmer than in the past, as air and sea surface temperatures and ocean heat have increased due to climate change. With more than 90% of the energy trapped by greenhouse gases going into the ocean, ocean heat content is at record levels," said WMO Secretary-General Petteri Taalas.
"Thus, 2016 was the warmest year on record as a result of a combination of a strong El Niño and human-induced global warming. 2019 was the second warmest year on record, even though there was no strong El Niño. We just had the warmest January on record. The signal from human-induced climate change is now as powerful as that from a major natural force of nature," said Mr Taalas.
Even though ENSO neutral conditions have prevailed since last July, there was a strong positive phase of the Indian Ocean Dipole (IOD) – sometimes known as the "Indian Niño." This was linked to drought which contributed to bush fires in Australia, and above average rainfall and flooding in Eastern Africa, the latter setting the scene for the current desert locust crisis in the region. The Indian Ocean Dipole is now neutral.
Above normal precipitation is expected just north of the equator in the central tropical Pacific and southwestern Indian Ocean extending into eastern equatorial Africa. Elevated probabilities of below-normal precipitation extend over much of the rest of the western tropical and extratropical Pacific. Below-normal precipitation is also likely for northern South America, Central America and the Caribbean, and southern Africa, according to WMO's Global Seasonal Climate Update. Southeast Asia, Oceania and western Australia, as well as southern Africa, Central America and the Caribbean, all also experienced drier to much drier than normal anomalies over the preceding November-January season. An outlook for continued dry conditions in these sub-regions suggests that they should be closely monitored in the coming months.
WMO Global Seasonal Climate Updates are based on climate model predictions around the world from WMO Global Producing Centres of Long Range Forecasts.
Both tools are used by planners within the United Nations system, and complement information issued by National Meteorological and Hydrological Services, WMO Regional Climate Centres and Regional Climate Outlook Forums as a source of information for country-level decision-making by disaster managers, for planning in climate-sensitive sectors, and by governments.
All over the world, the rate at which humans consume fresh water is now approaching or surpassing the rate at which water sources are being naturally replenished, creating water shortages for people and ecosystems. In the western US, water shortages are becoming more frequent and more severe, and are putting many species of fish inhabiting western rivers at risk—but the scarcity of water is also risking the growth of cities in the region like Los Angeles and Phoenix.
An important new study published this week inNature Sustainabilityfinds that irrigated crop production accounts for 86 percent of all water consumed in the western US—and of all the water used on western farms, by far the largest portion goes to cattle-feed crops such as alfalfa and grass hay. To alleviate the severe shortage of water in the region—especially in the Colorado River basin—the study's authors suggest that rotational fallowing farmland, leaving the land uncultivated for a period of time, could be a simple and affordable means of dramatically reducing water use in the region.
Study co-author and principal investigator Ben Ruddell, who is also director of NAU's School of Informatics, Computing, and Cyber Systems, leads the FEWSION project, a multi-institutional team effort launched in 2016 and funded through the National Science Foundation (NSF), to assess the nation's food, energy and water systems. The broader FEWSION research team contributed the data-intensive maps it has produced of these coupled human-natural systems. NAU assistant research professor Richard Rushforth, the lead data scientist on FEWSION, also co-authored the study.
Beef and dairy production depleting water supply
The study set out to assess river flow depletion across the US, identify the factors driving this depletion and evaluate options to reduce vulnerability to water shortages. The researchers estimate that two-thirds of the cattle feed being irrigated from western US rivers ends up as beef products, with the remainder going to dairy products.
"The groundbreaking maps produced by FEWSION made it possible to link river depletion through the supply chain to irrigated alfalfa and hay and to beef and dairy production, then to urban consumers of beef and dairy in each city and county in the US," Ruddell said.
According to the study, the team's findings "led to closer examination of the water use and ecological impacts associated with irrigation of cattle-feed crops. We pinpointed locations where these crops were being grown and modelled their associated depletion of river flow in local sub-watersheds. We then conducted an international supply-chain analysis to identify the locations where cattle-feed crops are transported and where the resulting beef products are consumed, thereby specifically linking end consumers of beef to effects on rivers. We subsequently explored the benefits and consequences of reduced feed-crop production and beef consumption through the lenses of water security, river ecosystem health, food security and agricultural economies."
"We're using a lot of water to grow the cows that are the source of our burgers, steaks and milk," Ruddell points out. "In the Colorado River basin, that cattle feed water use is nearly three times greater than all the water used for urban, industrial and electrical power purposes combined."
Along with the study's lead author and FEWSION contributor Brian Richter, Ruddell was surprised by some of their findings.
"I can hardly believe that such a large fraction of our western water problems are linked to irrigation of cattle feed, or that such a large fraction of our western water problems could be fixed with a single prescription—fallowing. It's rare that science clearly finds a 'silver bullet' that solves such a big problem so well, and so affordably," Ruddell said.
"Although the idea for this study of the US food energy and water system was proposed as part of the FEWSION project," he noted, "the roots of the ideas go back decades and involve many of the pioneers of river science and environmental sustainability—including Brian Richter, who is one of the founders of the science of river management for environmental flows. It takes a long time, generous research funding, and a broad team with diverse interdisciplinary skills for synthetic ideas like this to become a reality."
Water security will depend on collaboration, choice, policy
Scientists from 12 universities worldwide collaborated on the study, including Columbia University, Baylor University, the National University of Singapore, Nanjing Audit University and the University of Twente.
Ultimately, they conclude, "Water security and river health in the western US will depend on the willingness of urban and rural water users to collaborate in design of demand-management strategies, the ability of political leaders to secure funding to implement those strategies and the willingness of beef and dairy consumers to reduce their consumption or select products that do not depend on irrigated cattle-feed crops.
"My favorite food is cheeseburgers!" Ruddell admitted. "Individual choice, in addition to collective politics and policy, are important here. We need to be willing to pay a little more for more sustainable beef and dairy products, and we must strongly support politicians and policies that are willing to invest in solutions to the western water problem—including infrastructure, environmental flows and smart economic solutions like fallowing. Act with your votes and with your dollars. This is a problem we can afford to solve!"
More information: Richter, B.D., Bartak, D., Caldwell, P. et al. Water scarcity and fish imperilment driven by beef production. Nat Sustain (2020). DOI: 10.1038/s41893-020-0483-z , https://doi.org/10.1038/s41893-020-0483-z
Profit-prediction system may lower suicide rates among indebted Indian farmers
Researchers from the College of Information Sciences and Technology are taking steps to address the alarming rate of suicides among indebted farmers in India, by developing a deep-learning algorithm as the first step in a decision-support system that could predict future market values of crops.
More than 11,000 Indian farmerscommitted suicidein 2016, according to the National Crime Records Bureau. While the high rate of self-inflicted fatalities could be attributed to a number of reasons, financial distress and inability to sellcropsdue to widespread fluctuation in the country's produce marketpricesis among them, according to Amulya Yadav, assistant professor of information sciences and technology and principal investigator on the project.
"In India, the government has set minimum support prices for crops, but does not try to explicitly force these prices upon the buyers," said Yadav. "The actual price at which the crop sells at market is based on supply and demand."
Yadav explained that many Indian farmers take out loans to buy seeds, fertilizer and equipment, and to transport their harvest to market. But if the farmers are unable to sell their crops at minimum support prices, they can't pay back their loans or make a profit to sustain themselves—leading to financial distress.
Government markets will buy crops at the minimum support prices, but these markets are sometimes far away from farmers' villages, which adds transportation and fuel costs. Yadav also notes that there are often long lines at the markets and that the government will only buy a limited quota.
"So the remaining people will have to go back, and they've wasted a lot of money," he said. "They end up selling their crops to third-party vendors that don't guarantee minimum support prices, and [the farmers] don't make a profit."
Yadav is aiming to improve the lives of farmers by helping them predict future market prices. The algorithm that his team developed can accurately predict future market prices based on past pricing and volume patterns.
"This system assumes that you're trying to maximize the profit of a single farmer," said Yadav. "We're trying to make a prediction to him or her as to where and when they should sell their crop."
He continued, "Instead of selling their crops on the very next day after harvest in the local market, this algorithm could potentially give a recommendation that they should wait five days and travel 40 kilometers to a different market, where the prices are predicted to be very high."
To create the algorithm, Yadav and his team analyzed data records of more than 1,300 Indian markets from the past 11 years, which included maximum and minimum prices of every crop sold in each market. Then, they developed a deep learning model to find useful patterns from that data. The team's studies show that their model performs better than the current standard.
"This gives us hope that we are now going to go ahead and try to build the entire system that we envision," said Yadav. "Once the system gets built, we are hopeful that it can help farmers maximize the profits that they earn. And hopefully as an indirect benefit lead to fewer farmer suicides in India and in other countries around the world."
Yadav worked with Alexander Woodruff, 2019 graduate of Penn State in information sciences and technology, and Hangzhi Guo, an undergraduate student at Wenzhou Kean University. They presented their research at the Association for the Advancement of Artificial Intelligence Conference on AI earlier this month.Model suggests well-designed subsidies can help farmers and give consumers better food choices
Professor Aaron Kay's research examines bias, including gender bias and inequality. His work has illuminated gender bias in people's perceptions of creativity and documented the unintended effects of the "Lean In" call to women, finding that its messages may perpetuate the idea that women are responsible for gender inequality, and the burden rests on them to bridge the gap by changing their own behavior at work.
Work by Kay and collaborators, including Fuqua professor Grainne Fitzsimons, continues to shape the conversation in forums such as the Harvard Business Review and the Los Angeles Times on the biases that influence our decisions, how those biases inform who we hire, what we expect from those individuals and how we recognize their contributions.
In this Fuqua Q&A, Kay discusses how society has changed since he started his research in 2001, and how that has influenced the trajectory of his research.
Where is the conversation about bias in the workplace now compared to 20 years ago?
When I first started researching bias, and specifically gender bias, it was hard to get the public, and especially companies, to take notice. Now, organizations are some of the best consumers of this information. It is a great change to see. It makes the research easier to conduct and creates the opportunity for the research to have a bigger impact.
What are some of the biases people face, and what impact do they have?
One area this research has explored is so-called 'positive stereotypes." It's important to remember that bias doesn't always appear to be negative or discriminatory in the traditional sense. Many stereotypes may seem positive or even flattering. But these biases, even when the implications appear positive, create expectations that can limit the options women and other groups, such as military veterans, have in the workplace and in their careers. They also tend to open the door for other antiquated beliefs or stereotypes about the same group, as the research has shown.
To what degree are companies using your research to address these issues?
Companies reach out often with questions on how to make their workplace more diverse, or to talk about what might be preventing them from attracting and keeping a more diverse workforce. My research on word choice in job listings is one area in which companies ask for help. Avoiding words associated with a gender, for example, a words as compassionate or nurturing that are often associated with women, is a straightforward and tractable solution. There is software now, too, that has turned that research into usable tools. I also get asked to simply educate companies on the state of research on diversity and inequality. That is something I really enjoy doing.
What will it take to create gender equality in the workplace? What role do men play?
Bias doesn't just sit in people's minds. It is deeply embedded in the system, workplace practices, norms and policies. To achieve greater equality, we need deep-rooted changes to the system. Researchers are helping identify these systemic problems, but people who hold the power need to help change the system with new policy. Both men and women hold these positions of power, but men will need to play a prominent role because, as we know, there are far more men in positions of influence right now.
What are you investigating now in your research?
Following our research on the impact of the "Lean In" movement, one area I am working on is how popular self-help advice in business might actually perpetuate inequality in the workplace. We saw this result from the Lean In messaging, but we've also looked at other domains. For example, the dialog around work being solely a vehicle for people to follow their passions and achieve a meaningful life can sometimes result in workers being underpaid and exploited. We are also working to understand the consequences of the widely-discussed notion of the power of positive thinking—can this actually lead to more victim blame? In general, I think it is important for scholars and academics to use empirical tools to explore the impacts of trendy business ideas and anecdotes that are appealing, but haven't been rigorously vetted.
Two updated datasets published to LawAtlas.org today show minimal change in state fair housing laws and city nuisance property ordinances since 2017, in spite of the continued housing crisis in the United States.
These laws are part of the existing landscape of statutes, regulations, and ordinances intended to establish a framework for safe and equitable housing in the US. Yet, we know little about how they function as tens of millions of Americans continue to suffer from poor housing options and dangerous housing conditions.
"These datasets are an invaluable resource for housing rights advocates, public health practitioners and others who work on issues related to housing discrimination and eviction. They also provide a foundation for legal epidemiology researchers working at the intersection of housing and health to explore the public health impact of these laws—some of which have been around for generations and have largely gone unstudied," said Lindsay K. Cloud, JD, director of the Policy Surveillance Program's Center for Public Health Law Research at Temple University's Beasley School of Law.
The data published today include laws and policies in effect from August 1, 2017 through August 1, 2019. The city nuisance property ordinances dataset captures laws from the 40 largest US cities, while the state fair housing dataset captures laws from all 50 states and the District of Columbia.
City nuisance property ordinances impose penalties on property owners based on the conduct of their tenants, sometimes requiring the eviction of those tenants. These policies were originally designed to regulate substance use and crime, but many ordinances establish a wide range of activities that the city considers to be a nuisance. These activities can include calls to law enforcement, which may discourage tenants from calling the police in life-threatening situations.
"Nuisance property ordinances could have a significant impact on public health since they may force tenants to choose between calling 911 and being threatened with eviction," explained Kathleen Moran-McCabe, JD, a special projects manager at the Center who managed the update to these data. "These laws can have a disproportionate effect on domestic violence survivors, and people with disabilities, who may have to call for emergency help more often than others. While some cities exempt domestic violence incidents or calls to police from being considered a nuisance, many cities do not have exemptions in their nuisance ordinances."
While the majority of the cities' laws were relatively unchanged since 2017, the data released today show important changes to the laws in Chicago, Columbus, Ohio, and Dallas.
Chicago and Columbus both added exemptions for domestic violence. Chicago expanded its exemption for emergency calls to apply to any calls related to domestic or sexual violence or an individual's disability—not just calls made by the property owner. Columbus added an exemption to its law that prevents domestic violence incidents from being labeled nuisance activities.
Dallas has adopted a policy that allows the Dallas Police Department to designate a building as a "habitual criminal property" if certain criteria are met, including being associated with five or more law enforcement reports of criminal activity within one year. The police department may require owners now to post a sign at the building to show its habitual criminal status, and may face fines.
The Fair Housing Act was passed as part of the Civil Rights Act of 1968 to prohibit discrimination in housing. Since then, a majority of states have enacted congruent policies to advance FHA's aims. As of August 1, 2019, every state except Mississippi has its own laws that seek to supplement protections against discrimination in housing-related transactions.
Changes to these laws since 2017 have been minimal, but those states that have changed their law tend to focus on the nature of protections for various populations:
New Hampshire added gender identity as a protected class in 2019, bringing the total to 20 states with this protection.
Five states now include domestic violence victims as a protected class, up from four in 2017.
Source of income protections—which may specifically include or exclude housing vouchers—is also now protected from discrimination in 12 states, up from 11 in 2017 (New York added source of income, including housing vouchers, as a protected class).
"The State Fair Housing dataset is a valuable resource as we continue to seek to understand the impact of housing laws, associated regulations, and the implementation of policies on local practices, as well as broader effects on public health outcomes," said Adrienne Ghorashi, JD, a program manager at the Policy Surveillance Program who led the update of these data. "As federal protections against housing discrimination have been stalled or scaled back, understanding the effects of state laws becomes even more critical to advancing equity in housing."
More information: City Nuisance Property Ordinances. Policy Surveillance Program, Center for Public Health Law Research, Temple University Beasley School of Law. February 28, 2020. lawatlas.org/datasets/city-nui … -property-ordinances
State Fair Housing Protections. Policy Surveillance Program, Center for Public Health Law Research, Temple University Beasley School of Law. February 28, 2020. lawatlas.org/datasets/state-fa … otections-1498143743
In coastal communities prone to hurricanes and tropical storms, people typically turn to engineered solutions for protection: levees, sea walls and the like. But a natural buffer in the form of wetlands may be the more cost-effective solution, according to new research from the University of California San Diego.
In the most comprehensive study of its sort to date, UC San Diego economists show that U.S. counties with morewetlandsexperienced substantially less property damage from hurricanes and tropical storms over a recent 20-year period than those with fewer wetlands.
A major focus of the study is estimating the monetary value of wetlands' property-protecting services. On average, the marginal value of one square kilometer of wetlands is estimated at $1.8 million per year. The study also finds there is considerable spatial variation in the value of wetlands' protective services, with their value in heavily populated areas that are at frequent risk of being hit by major storms often being considerably higher.
The paper, titled "Coastal wetlands reduce property damage during tropical cyclones," is published in the Proceedings of the National Academy of Sciences.
Richard Carson, a professor in the UC San Diego Department of Economics, is the senior author and recent doctoral alumna Fanglin Sun, now a researcher at Amazon, is the first author.
"Wetlands play a critical role in helping to reduce property damage from storms. With coastal areas under increasing threat from more powerful storms due to climate change, it's critical to prevent further destruction of existing wetlands," Carson said. "Government should also actively seek to restore wetlands that have been lost."
To arrive at their calculations, the co-authors analyzed the effects all tropical cyclones on the Atlantic and Gulf coasts between 1996 and 2016: 88 hurricanes and tropical storms that hit 232 U.S. counties.
They worked with precise storm tracks and used highly detailed geo-spatial data—enabling them to make estimates at not just the county level but down to the neighborhood too—taking into account a number of factors, including property values and local elevation, as well as building codes. The relative protection from wetlands is greatest, it turns out, in areas with the weakest building codes.
They studied freshwater and saltwater wetlands, as well as forested wetlands (or mangroves) and scrub/shrub wetlands. All types of wetlands, they find, contribute significantly to reductions in property damage from storms.
The co-authors say their model can be used to estimate property damage both under different climate-change conditions and under different scenarios of wetland loss, too. To illustrate the latter, they apply their model to Hurricane Irma, which made landfall in 2017, just outside the study's sample period. If the 19 Florida counties affected by the storm had not lost 2.8% of their wetland coverage between 1996 and 2016, damage from Irma would have been lower by about $430 million, a significant amount for a single storm.
The co-authors hope that the estimates detailed in their PNAS paper are useful for both policymakers and the public alike.
They also point out that storm protection for property is just one of the ecological services that wetlands provide. Wetlands also serve as habitat for fish and wildlife, filter industrial, residential and agricultural runoff, support outdoor recreational opportunities and sequester carbon, benefits that were not addressed in this study.
