The numbers at the heart of the study are striking. Using a machine learning framework trained on an extensive database of field observations, the researchers estimated global average phosphorus use efficiency of 25.1 percent for maize, 25.0 percent for rice and 24.2 percent for wheat. In other words, roughly three-quarters of the phosphorus entering these systems never ends up in the harvested crop. Some of it lingers in soils as legacy reserves that may benefit future seasons, but a substantial fraction is lost to erosion, runoff and leaching, driving freshwater eutrophication, harmful algal blooms and coastal dead zones. At the same time, the world’s reserves of mineable phosphate rock are finite, geographically concentrated and increasingly subject to price volatility and geopolitical disruption, making chronic inefficiency both an environmental liability and a strategic food-security risk.

What sets the new work apart from earlier global nutrient assessments is its insistence on feasibility. Previous studies have mapped theoretical ceilings for nutrient efficiency, but theoretical potential means little to a smallholder in sub-Saharan Africa who lacks access to enhanced-efficiency fertilizers, or to a mechanized grain operation in North America constrained by cost and equipment. To close this gap, the team built a predictive framework that filters raw technical potential through three successive layers of real-world constraints. The first layer accounts for plant phosphorus uptake limits, the second for environmental risks such as nutrient loss to waterways, and the third and most consequential for barriers to adoption, including economic feasibility, infrastructure, farmer capacity and regional socio-economic context.

The results of this constrained scenario analysis are notable for their restraint. Rather than promising dramatic transformation, the study finds that under realistic feasibility conditions, management interventions could deliver absolute phosphorus use efficiency gains of 5.2 to 6.0 percentage points across the three cereal crops. That may sound incremental, but scaled across the hundreds of millions of hectares devoted to maize, rice and wheat, it translates into enormous quantities of phosphorus retained in the food system rather than squandered in waterways or locked in soils. Crucially, the researchers identified adoption barriers as the dominant limiting factor in their framework, a finding that reframes the phosphorus challenge as much as a question of policy, economics and extension services as one of soil chemistry.

Within the family of management practices evaluated, two interventions emerged as the largest contributors to feasible efficiency gains across all three crops: changes in cropping system and changes in fertilizer type. Cropping system changes include shifting from continuous monoculture toward crop rotations and intercropping arrangements, practices long known to improve nutrient cycling, stimulate root architectures that explore soil phosphorus more thoroughly and harness complementary microbial communities. Fertilizer type changes encompass the substitution of conventional mineral phosphorus inputs with organic fertilizers such as livestock manure and compost, as well as enhanced-efficiency formulations and microbial fertilizers that improve the solubility and plant availability of phosphorus while reducing fixation reactions that render applied nutrients unavailable in acidic or calcareous soils.

The methodological machinery behind these conclusions is as interesting as the findings themselves. The team compiled a global field-observation database covering phosphorus use efficiency measurements from long-term experiments across diverse climates, soils and management regimes. Machine learning models, including ensemble learners trained on this database, were then applied to global gridded datasets of climate, soil properties, aridity, and cropping and fertilizer management to generate wall-to-wall maps of phosphorus use efficiency for maize, rice and wheat. To interpret the drivers of the predictions, the researchers deployed SHAP value analysis and partial-dependence techniques, which quantify how individual variables such as soil pH, organic carbon, precipitation and fertilizer rate push predictions up or down across the global land surface.

Skeptics of machine learning in the geosciences rightly worry about models extrapolating beyond the environments they were trained on, producing confident nonsense for regions with no field data. The authors confronted this problem directly. Their analytical workflow incorporated a rigorous area of applicability assessment, using a Dissimilarity Index and Mahalanobis distance metrics to classify every global grid cell as high, medium or low prediction confidence, and their reporting of feasible improvement potential is restricted to high-confidence areas. They also cross-validated the model’s estimated management effects against causal-forest estimates of conditional average treatment effects across nine management contrasts, comparing rotation versus monoculture, intercropping, residue retention, band and deep fertilizer placement, enhanced-efficiency, microbial and organic fertilizers, and reduced tillage. The agreement between these independent estimation approaches strengthens confidence that the identified management signals are genuine rather than statistical artifacts.

The spatial texture of the results matters as much as the global averages. Efficiency levels and feasible gains vary dramatically by region and cropping system, and the study’s maps reveal where interventions would deliver the greatest returns. In regions with decades of accumulated soil phosphorus surpluses, the analysis indicates that reducing application rates, rather than adding new technology, is a key lever, allowing crops to draw down legacy reserves while maintaining yields. In regions with depleted soils, modest phosphorus additions remain essential for productivity and food security, which is why the framework deliberately balances efficiency gains against crop uptake constraints. This differentiation underpins the study’s central policy message: phosphorus management should be regionally calibrated, not dictated by one-size-fits-all global targets, in order to support sustainable intensification while protecting freshwater ecosystems.

The broader implications ripple outward through the planetary boundaries framework. Excessive phosphorus flows to aquatic ecosystems are among the most transgressed biophysical limits, while phosphate rock depletion threatens the long-term resilience of the food system. By demonstrating that feasibility-constrained efficiency improvements of five to six percentage points are achievable with existing technologies and practices, the study offers a quantified, spatially actionable roadmap for easing both pressures simultaneously. It also underscores the role of open science in accelerating that effort: the field-observation database underpinning the analysis is publicly available through figshare, the custom code for data processing, model training and analysis is released on GitHub, and source data accompany the paper. The work was funded by the National Natural Science Foundation of China, the Natural Science Foundation of Jiangsu Province, the Chinese Academy of Sciences and university research funds, reflecting the scale of investment now directed at nutrient stewardship.

For farmers, agribusinesses and policymakers, the takeaway is twofold. First, the biggest wins lie not in exotic technologies but in adopting rotations, intercropping, organic and enhanced-efficiency fertilizers, and smarter placement, practices that are proven, locally adaptable and often cost-neutral over time. Second, the binding constraint is adoption, which means agricultural extension, credit access, infrastructure and incentives deserve as much attention as agronomic research. As phosphate rock becomes scarcer and water quality pressures intensify, the difference between a quarter and a third of applied phosphorus reaching the world’s cereal harvest may prove decisive for whether agriculture can feed ten billion people within planetary limits. This study turns that aspiration into a measurable, mappable and, most importantly, feasible target.

Subject of Research: Global patterns and feasible improvement potential of phosphorus use efficiency in cereal croplands

Article Title: Global patterns and feasible improvement potential of phosphorus use efficiency in cereal croplands

Article References: Sun, Y., Hu, H., Tan, R.-X., Helfenstein, J., McDowell, R. W., Gu, B., Ni, H., Huang, W., Ding, J., Xue, K., Qian, C., Zhou, J., Zhou, Z.-H., Zhang, J., & Liang, Y. (2026). Global patterns and feasible improvement potential of phosphorus use efficiency in cereal croplands. Nature Food. https://doi.org/10.1038/s43016-026-01419-9

Image Credits: AI Generated

DOI: 10.1038/s43016-026-01419-9

Keywords: phosphorus use efficiency, cereal croplands, machine learning, Nature Food, sustainable agriculture, fertilizer management, cropping systems, food security, eutrophication, phosphate rock, nutrient management, spatial mapping

The distinction between being childfree and simply not yet having children is central to the study. Researchers define childfree adults as people who do not have children and do not want to have children in the future. This category therefore excludes adults who are childless because of infertility, circumstance, delayed family planning or uncertainty about whether they will eventually become parents. According to figures from the National Survey of Family Growth, the childfree share of non-parents aged 15 to 44 increased from 13.8 percent in 2002 to 29.4 percent in 2023. The new research examines how that expanding population is distributed geographically.

Zachary Neal and Jennifer Watling Neal of Michigan State University analyzed responses from 20,118 adults who participated in an online survey conducted between August 30 and October 8, 2024. The data came from the Civic Health and Institutions Project, a survey initiative designed to examine social attitudes, civic life and institutional conditions across the United States. By linking respondents’ reported reproductive intentions with their state of residence, the researchers estimated the prevalence of childfree adults in each state and tested whether state-level characteristics could help explain the differences.

The resulting map reveals substantial variation. California had the highest estimated proportion of childfree adults, at approximately 22 percent, followed by Michigan at 19.9 percent and New Hampshire at 19.4 percent. At the other end of the distribution, Louisiana had the lowest estimated share, at 9.4 percent, while North Dakota and South Dakota each registered about 10 percent. In practical terms, the estimates suggest that roughly one in five adults in some states may be childfree, compared with about one in ten in others.

Despite these differences, the pattern did not form the kind of clear regional clusters researchers might expect if childfree living were primarily driven by a shared political culture or geographic identity. The study found no strong evidence that childfree adults were concentrated in broad regions such as the Northeast, South, Midwest or Southwest. Instead, the highest proportions appeared in certain individual states, making the national distribution more fragmented than a simple cultural map of the country.

Some state characteristics were associated with higher childfree prevalence. Childfree adults were more common in highly populous states and in states with a higher cost of living. These relationships may reflect the pressures and opportunities associated with urbanized economies. Housing, childcare, education, healthcare and career advancement can all influence the perceived financial and logistical consequences of parenthood. Large states also tend to contain metropolitan areas where alternative lifestyles are more visible, social networks are more diverse and traditional expectations about marriage and family may be less restrictive.

However, state-level associations became less important when the researchers considered individual characteristics. Adults who were single, older or male were more likely to be childfree, according to the analysis. These factors do not necessarily operate independently. Relationship status can affect both the likelihood of having children and the expectations surrounding future parenthood, while age changes the probability that a person who currently has no children will eventually become a parent. Sex differences may reflect a combination of reproductive expectations, social pressure, relationship patterns and the way people report their intentions.

The researchers’ statistical approach is important because it separates contextual effects from individual effects. A state may have a high childfree rate not because living there directly causes people to reject parenthood, but because the state contains a larger share of people with characteristics already associated with being childfree. This distinction is known as compositional versus contextual explanation. A compositional explanation points to the makeup of the population; a contextual explanation suggests that the surrounding environment changes individual behavior. In this study, composition appeared to matter more than context.

The findings also complicate efforts to use state policy as a tool for reversing population decline. Governments concerned about falling birth rates sometimes consider policies intended to encourage parenthood, such as financial incentives, expanded childcare, housing assistance or restrictions affecting reproductive decisions. But if childfree intentions are driven predominantly by individual circumstances and durable preferences, state policies may have limited power to change them. The study does not show that state conditions are irrelevant, nor does it establish that people’s choices are completely fixed. It indicates instead that broad state characteristics alone are insufficient to explain why some adults do not want children.

The study has limitations. Because the survey data are observational, the researchers can identify associations but cannot prove that living in a particular state causes someone to become childfree. The analysis also operates at the state level, meaning it cannot reveal how childfree adults are distributed within cities, suburbs or rural communities. Online surveys may introduce sampling and reporting biases, and reproductive intentions can change over time for some respondents. Even so, the results offer one of the clearest national pictures yet of where childfree adults are estimated to live and why geography alone provides an incomplete explanation.

As the childfree population grows, the issue is becoming increasingly visible in debates about demographic change, housing, work and public policy. The new study suggests that the United States does not have a single “childfree region.” Instead, childfree adults are spread across the country, with their prevalence varying from state to state but their individual profiles proving more informative than any simple geographic divide. California and Michigan may have roughly one in five adults who are childfree, while Louisiana and the Dakotas may have closer to one in ten, but the deeper story is national: the decision not to become a parent is shaped primarily by people’s lives, identities and circumstances rather than by a single state-level formula.

Subject of Research: Not applicable

Article Title: The spatial distribution of the U.S. childfree population: Does state context matter?

News Publication Date: 12-Aug-2026

Web References: https://doi.org/10.1371/journal.pone.0352872

References: Neal ZP, Neal JW (2026) The spatial distribution of the U.S. childfree population: Does state context matter? PLOS One 21(8): e0352872. https://doi.org/10.1371/journal.pone.0352872

Image Credits: Neal, Neal., 2026, PLOS One, CC BY 4.0

Keywords: childfree adults, United States, reproductive intentions, population distribution, demography, family formation, social science, survey research, state context, birth rates