Can localized fertilization become a key strategy for green agricultural development?

Higher Education Press

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Credit: Liyang WANG1,2 , Dan LIAO1,2 , Zed RENGEL3,4 , Jianbo SHEN2

In agricultural ecosystems, there exists a remarkable heterogeneity in the spatial and temporal distribution of soil nutrients. This heterogeneity can cause the nutrient concentrations that different roots of the same plant are exposed to vary by several orders of magnitude, which undoubtedly poses a great challenge to plant growth. In the face of such a complex soil environment, plants have gradually developed a series of coping strategies during the long evolutionary process. Their roots can keenly sense the nutrient-rich hotspots and make corresponding responses. However, traditional fertilization methods are difficult to precisely meet the needs of plants. They not only result in nutrient waste but also cause environmental pollution. Therefore, localized fertilization, as a new strategy, has attracted widespread attention.

Since plants have their unique nutrient acquisition mechanisms in the natural environment, how will the roots of plants behave in the context of artificially intervened localized fertilization? In fact, the response of plant roots to heterogeneous nutrients is quite unique. Morphologically, in nutrient-rich areas, the roots will exhibit a proliferation phenomenon, specifically manifested as an accelerated root elongation rate, an increase in total root length, and an increase in lateral root branching. Physiologically, in nutrient-rich patches, the physiological activities of plant roots will be significantly enhanced, and the nutrient absorption rate will also increase accordingly. In addition, rhizosphere microorganisms also play an important role in the nutrient acquisition of plants. Mycorrhizal fungi form symbiotic associations with plant roots, facilitating nutrient absorption.

A review study (DOI: 10.15302/J-FASE-2024575) conducted by the research team led by Professor Jianbo Shen from China Agricultural University and published in Frontiers of Agricultural Science and Engineering shows that as an important rhizosphere management strategy, localized fertilization has obvious advantages. It can reduce the fixation of insoluble nutrients in the soil, adjust the morphological structure of the roots, and promote the roots' capture of nutrients. Taking the intensive agricultural system in the North China Plain as an example, localized fertilization has increased the yield of maize by 5% to 15%, while significantly reducing the amount of fertilizer applied. Its incremental amplification effect is achieved through changing the root morphology to increase the absorption area, enhancing the root physiological processes to improve nutrient activation ability, and stimulating specific microbial communities to strengthen the underground interactions. For example, the local application of phosphorus and ammonium nitrogen can stimulate root proliferation, and the root exudates in nutrient-rich patches will accelerate. There are also studies indicating that localized fertilization can activate the soil microbial community, regulate the ethylene signal of plants, and promote root growth and nutrient absorption.

Currently, localized fertilization has been applied in actual production. The base fertilizer commonly used in maize production in the United States is a typical example. In China, it is also being gradually promoted and has been listed as one of the main agricultural promotion technologies by the Ministry of Agriculture and Rural Affairs. Overall, localized fertilization has demonstrated many advantages. It has significantly improved the nutrient utilization efficiency, reduced fertilizer waste, and achieved an increase in crop yield with less fertilizer input, which has been effectively verified in the intensive agricultural system of the North China Plain. At the same time, it is more environmentally friendly, reducing the risk of environmental pollution caused by excessive fertilization. By stimulating the activities of beneficial rhizosphere microorganisms, it can also improve the soil microecological environment and promote soil health. With these advantages, localized fertilization shows great potential in promoting the process of green agricultural development. However, to truly become a key strategy for green agricultural development, further in-depth research is needed to overcome the existing challenges such as salt damage, ammonium toxicity, and the influence of inherent soil fertility, so as to provide more solid and powerful support for the sustainable development of agriculture.

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Journal

Frontiers of Agricultural Science and Engineering

DOI

10.15302/J-FASE-2024575 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

Soil–plant–microbe interactions in the rhizosphere: incremental amplification induced by localized fertilization

 

A diabetes paradox: Improved health has not boosted workforce prospects

Addressing economic factors may be just as vital for improving workforce participation among people with the disease, new research shows

University of Southern California

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Advances in medical technology have led to significant health improvements in people with diabetes, but workforce participation has not improved for this population.

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Credit: USC Schaeffer Center

Advances in medical technology over the last 30 years have made it easier to detect and treat diabetes, leading to significant health improvements in people with the disease. Despite this, workforce participation among people with diabetes has not improved over time, finds new USC Schaeffer Center research in JAMA Health Forum.

Historically, workforce participation rates have been much lower among people with diabetes due to factors like health complications, time needed to manage the disease and workplace barriers. But the surprising failure of substantial health gains to drive economic progress in this population — a phenomenon that researchers call the “diabetes paradox” — suggests that rising diabetes prevalence poses a growing threat to the labor market and strain on government disability programs.

“Given the major health improvements in the diabetes population, we would have expected to see more people in the workforce,” said study author Jack Chapel, a scholar at the Schaeffer Center and research assistant professor at the USC Price School of Public Policy. “Instead, there is a large and growing population of people with diabetes who are having challenges with labor market performance that should be addressed.”

Researchers analyzed 20 years of National Health Interview Survey data (1998-2018) on nearly 250,000 Americans ages 40-64. This age range includes a person’s peak earning years and coincides with a period when most diabetes diagnoses occur — about 1 in 7 Americans ages 45-64 have diagnosed diabetes, according to federal data. 

However, compared to peers without diabetes, they were consistently 21-24 percentage points less likely to be in the labor force and 12-13 percentage points more likely to claim disability benefits. Even after adjusting for demographic differences, these gaps were large and persistent: 8-11 percentage points and 4-6 percentage points, respectively.

The study findings suggest expanded access to powerful new anti-obesity medications, which could prevent or delay diabetes, could have positive effects on the labor market. And for those with diabetes, health improvements alone may not be enough to help them return to the workforce.

Unpacking the Paradox

The diabetes paradox may be partly explained by shifts in who is diagnosed, disparities in access to medical advances and the changing nature of work, researchers said.

•  Improved access to healthcare may have allowed more people from economically disadvantaged backgrounds to receive a diagnosis that might have otherwise been missed. For instance, diabetes diagnoses increased following the Affordable Care Act’s expansion of Medicaid to low-income adults a decade ago.
   
• People with more resources may be likely to benefit from advances in diabetes prevention; consequently, those who are diagnosed more recently may have more limited economic prospects. Researchers noted the gap in educational attainment among people with diabetes and the overall population has continued to widen.
   
• Jobs commonly available to people with lower levels of education have remained physically demanding — and in some cases, have even become more demanding over time. People diagnosed with diabetes are more likely to be in the demographic seeking those jobs, making it harder for them to remain in the workforce and to instead seek disability benefits. Analysis of more recent data found a small uptick in employment among people with diabetes during the COVID-19 pandemic, suggesting that work-from-home policies improved their employment prospects.

There may be some good news buried in the findings. If more people with worse economic prospects — due to reasons unrelated to health — are diagnosed with diabetes, it seems likely that overall economic outcomes for this group would have declined.

“The fact that economic outcomes have remained stable might mean things are actually improving beneath the surface,” said study author Matthew Kahn, a senior scholar at the Schaeffer Center and Provost Professor of Economics and Spatial Sciences at the USC Dornsife College of Letters, Arts and Sciences. “My hunch is that the expansion of health care access to the poor and the proactive steps taken by those diagnosed with pre-diabetes has meant that the new cohort of people diagnosed with diabetes is more economically vulnerable than in previous decades, complicating comparison over time.”

To better understand labor trends among people with diabetes and identify opportunities to improve workforce participation, researchers said more clinical trials for diabetes prevention and management therapies should assess economic outcomes like employment.

About the Study

Other authors are Dana Goldman and Bryan Tysinger of the USC Schaeffer Center. Please see the study for author disclosures.

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Journal

JAMA Health Forum

DOI

10.1001/jamahealthforum.2025.0756 

Article Title

Long-Term Health Improvements and Economic Performance Among Individuals With Diabetes

Article Publication Date

16-May-2025

 

USTC achieves krypton-81 dating of 1-kilogram Antarctic ice

University of Science and Technology of China

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Left: Antarctic ice core and the bubbles contained in it. Right: Vacuum-ultraviolet light source and metastable krypton atom beam device.

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Credit: Image by Prof. ZHENG’s team

A team led by Prof. Zheng-Tian Lu and Prof. Wei Jiang from the University of Science and Technology of China (USTC), have developed a novel technique known as All-Optical Atom Trap Trace Analysis. In collaboration with American glaciologists, they have successfully performed krypton-81 dating on 1-kilogram samples of ancient Antarctic ice using this method. This advance provides a powerful new tool for studying paleoclimate changes on million-year timescales. The findings were published in the Nature Communications.

Deep ice cores drilled from the Antarctic continent and the Greenland ice sheet—often extending a couple of kilometers in depth—serve as invaluable archives of Earth’s past climate and ice sheet evolution. The basal ice at the bottom of these cores may preserve records of major climatic transitions, but accurately dating this ice has long been a challenge due to stratigraphic disturbances. Krypton-81, a rare radioactive isotope, is an ideal tracer for dating ice. However, only a few hundred krypton-81 atoms are present in each kilogram of ancient ice, making their detection an extreme technical challenge.

To tackle this, the USTC team developed an all-optical single-atom detection technique in 2021 [Phys. Rev. Lett. 127, 023201 (2021)]. Over the past four years, the team has further advanced the method to handle real ice core samples. By developing a high-brightness, narrow-bandwidth vacuum-ultraviolet light source, they efficiently produced metastable krypton atoms and dramatically reduced sample cross-contamination by two orders of magnitude—all while enabling non-destructive measurement. This breakthrough reduces the required sample size to just 100 nanoliters of krypton gas (equivalent to about 1 kg of ice) and extends the upper dating limit to 1.5 million years.

Using this technology, the USTC team collaborated with glaciologists including Professor Michael Bender and Dr. Sarah Shackleton from Princeton University to date two 1-kg ice samples from Taylor Glacier, Antarctica. The results—approximately 130,000 years old—closely match the independently established ice stratigraphy, confirming the accuracy and reliability of krypton-81 dating.

This work makes krypton-81 dating feasible for small ice core samples. The USTC team is now working with glaciologists both in China and abroad to systematically apply the method to basal ice from Greenland, Antarctica, and the Tibetan Plateau. The new dating approach opens exciting research avenues for investigating Greenland ice sheet stability, the development timeline of Tibetan glaciers, and identifying ancient ice that spans the Mid-Pleistocene Transition—advancing both glaciology and paleoclimate science.

This achievement marks a successful collaboration between Chinese physicists and American earth scientists, uniting expertise in quantum physics and glaciology to advance global climate science.

For more information, visit the USTC lab webpage: https://atta.ustc.edu.cn

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Journal

Nature Communications

DOI

10.1038/s41467-025-59264-6 

Article Title

81Kr dating of 1 kg Antarctic ice

Article Publication Date

12-May-2025

 

What genetic changes made us uniquely human? -- The human intelligence evolved from proximal cis-regulatory saltations

Higher Education Press

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The cis-regulatory element frequency (CREF) matrix that represent the transcriptional regulation and the saltation from apes to human

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Credit: Xiaojie Li, Jianhui Shi, Lei M. Li

On its 125th anniversary, Science magazine posed 125 unsolved scientific questions, among which “What genetic changes made us uniquely human?” was listed as one of the 25 core problems. Yet the divergence rate between the alignable genomes of humans and chimpanzees is as little as 1.23%. Scientists hypothesized that gene regulation might account for their dramatic phenotypic differences.

Recently, Quantitative Biology published a research article entitled “The human intelligence evolved from proximal cis-regulatory saltations” in which the focus shifted from protein sequences to their regulatory regions. They represented proximal regulatory sequences of genes using the cis-regulatory element frequency (CREF) matrix. The transcriptional regulatory information from humans and extant ape species—such as chimpanzees, bonobos, and gorillas—was transformed into orthogonal modules that could be aligned and compared.

The researchers extracted 10 principal regulatory modules from the whole-genome data and ranked them in descending order of binding energy. By comparing the CREF modules of four hominid species, they discovered that two regulatory modules underwent saltations: one between the 4th and 5th eigen-levels and another between the 9th and 10th. The newly regulated gene targets include those associated with long-term memory, cochlea development, learning, exploration behavior, social behavior, and regulation of sleep and happiness. Without any a priori, the CREF module can largely explain the saltation of human cognition and intelligence, offering a new quantitative paradigm for studying the evolution of gene regulation.

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Journal

Quantitative Biology

DOI

10.1002/qub2.88 

Method of Research

Experimental study

Subject of Research

Human tissue samples

Article Title

The human intelligence evolved from proximal cis-regulatory saltations

 

Very different mammals follow the same rules of behavior

Research hints at an underlying architecture that orders the movements of animals

Max Planck Institute of Animal Behavior

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Meerkats in the Kalahari Research Centre, Northern Cape, South Africa. 

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Credit: Vlad Demartsev

In the natural world—where predators pounce, prey flee, and group members feed and sleep in solidarity—animal behavior is glorious in its variety. Now, new research suggests there may be an underlying architecture that orders the movements of animals as they go about their very different lives. And it’s more widespread than previously imagined.

In a study spanning meerkats in the Kalahari desert, coatis in Panama’s rainforest, and spotted hyenas in Kenya’s savanna, researchers have discovered that the daily actions of these animals show surprisingly similar patterns. Whether a meerkat scratches in the sand for scorpions or a coati rests in the canopy, a shared ordering of the behaviors persists across different landscapes, species, individuals, and types of behaviors. To the international team of fourteen authors, led by researchers at the Max Planck Institute of Animal Behavior, the findings are unexpected and—possibly—profound.

“We assumed there would be differences,” said Pranav Minasandra, a postdoctoral researcher at MPI-AB and lead author of the study in PNAS. After all, differences are apparent when comparing meerkats, coatis, and hyenas, which occupy dissimilar environments and ecological roles. “But we found common patterns in how animals switch between behaviors, regardless of what species and which individual. It's as if their behavior was built on the same hidden algorithm.”

Uncovering underlying patterns

The hidden algorithm came to light in data that were collected from wild animals tagged with accelerometers—the same small sensors in phones and watches that track our activity. The species studied are all social mammals, but they differ in their ecology and behavior. Spotted hyenas are large carnivores, meerkats are small burrowing animals, and coatis are racoon-sized tree-dwellers. Accelerometers measure posture changes many times each second and the recordings can continue for several days. These high-resolution motion traces collected from animals were then classified using machine learning into behavioral states like lying, foraging, and walking. For instance, a meerkat might lie down for 10 minutes then briefly stand up to look around for 20 seconds before moving around to search for food for another few minutes.

“This approach allowed us to capture detailed behavioral sequences over days and even weeks from multiple individuals across three distinct species,” says Ariana Strandburg-Peshkin, group leader at MPI-AB and senior author on the study.

Across behaviors, individuals, and species, one common principle emerged: the longer an animal stays in one behavioral state, the less likely it is to change it in the next moment. “This was unexpected,” adds Minasandra.

Imagine a hyena walking continuously for 10 minutes. Most people would probably guess that the hyena would be more likely to stop over time, and the authors did too. “We originally thought the probability of switching behaviors would increase over time, as we assumed it would not be optimal to lock-in to any behavior.” Remarkably, this kind of lock-in, also called a decreasing hazard function, was consistent across all studied animals and species.

The authors further examined how current behavior predicts future actions—a concept they call "predictivity decay." Predictivity decay reflects the increasing difficulty in predicting behavior the further we look into the future, primarily due to random, unpredictable variations. The shape of the decay graph conveys how decision-making systems across different timescales interact to generate animals' behavioral sequences.  “We found that the pattern of predictivity decay was remarkably consistent across all animals studied, implying a shared architecture beneath the surface.”

Why these patterns?

The study raises a big question: Why do such patterns occur? The authors propose two broad explanations.

First is positive feedback: the longer an animal remains in a state—say, lying down—the more likely that staying put is rewarded, whether because it’s warm, safe, or socially reinforced. Behavior becomes self-reinforcing.

The second possibility is multi-timescale decision-making. Instead of a single internal clock governing when to switch behaviors, animals may integrate cues from many processes—internal hunger, external threats, social context—each with its own tempo. The interplay of these overlapping signals could generate the observed patterns.

Future studies may explore whether these patterns hold in other animals beyond the three mammals in the study: non-social species, across developmental stages, or under different ecological pressures. There’s also the question of whether these long-time behaviors offer advantages—perhaps by optimizing attention, conserving energy, or enhancing group coordination.

Says co-author Meg Crofoot, Director of the Department for the Ecology of Animal Societies: “What this study suggests is that real animals, be they hunting, hiding, or resting, are guided by hidden structures that seem to echo across life’s branches.”

White-nosed coatis in Panama

Hyenas in Maasai Mara National Reserve, Kenya

Credit

Christian Ziegler / Max Planck Institute of Animal Behavior

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Journal

Proceedings of the National Academy of Sciences

DOI

10.1073/pnas.2503962122 

Method of Research

Data/statistical analysis

Subject of Research

Animals

Article Title

Behavioral sequences across multiple animal species in the wild share common structural features

Article Publication Date

15-May-2025