Observational evidence for groundwater influence on crop yields in the United States.

As climate change shifts crop exposure to dry and wet extremes, a better understanding of factors governing crop response is needed. Recent studies identified shallow groundwater-groundwater within or near the crop rooting zone-as influential, yet existing evidence is largely based on theoretical crop model simulations, indirect or static groundwater data, or small-scale field studies. Here, we use observational satellite yield data and dynamic water table simulations from 1999 to 2018 to provide field-scale evidence for shallow groundwater effects on maize yields across the United States Corn Belt. We identify three lines of evidence supporting groundwater influence: 1) crop model simulations better match observed yields after improvements in groundwater representation; 2) machine learning analysis of observed yields and modeled groundwater levels reveals a subsidy zone between 1.1 and 2.5 m depths, with yield penalties at shallower depths and no effect at deeper depths; and 3) locations with groundwater typically in the subsidy zone display higher yield stability across time. We estimate an average 3.4% yield increase when groundwater levels are at optimum depth, and this effect roughly doubles in dry conditions. Groundwater yield subsidies occur ~35% of years on average across locations, with 75% of the region benefitting in at least 10% of years. Overall, we estimate that groundwater-yield interactions had a net monetary contribution of approximately $10 billion from 1999 to 2018. This study provides empirical evidence for region-wide groundwater yield impacts and further underlines the need for better quantification of groundwater levels and their dynamic responses to short- and long-term weather conditions.

OASIS: An interpretable, finite-sample valid alternative to Pearson's X2 for scientific discovery.

Contingency tables, data represented as counts matrices, are ubiquitous across quantitative research and data-science applications. Existing statistical tests are insufficient however, as none are simultaneously computationally efficient and statistically valid for a finite number of observations. In this work, motivated by a recent application in reference-free genomic inference [K. Chaung et al., Cell 186, 5440-5456 (2023)], we develop Optimized Adaptive Statistic for Inferring Structure (OASIS), a family of statistical tests for contingency tables. OASIS constructs a test statistic which is linear in the normalized data matrix, providing closed-form P-value bounds through classical concentration inequalities. In the process, OASIS provides a decomposition of the table, lending interpretability to its rejection of the null. We derive the asymptotic distribution of the OASIS test statistic, showing that these finite-sample bounds correctly characterize the test statistic's P-value up to a variance term. Experiments on genomic sequencing data highlight the power and interpretability of OASIS. Using OASIS, we develop a method that can detect SARS-CoV-2 and Mycobacterium tuberculosis strains de novo, which existing approaches cannot achieve. We demonstrate in simulations that OASIS is robust to overdispersion, a common feature in genomic data like single-cell RNA sequencing, where under accepted noise models OASIS provides good control of the false discovery rate, while Pearson's [Formula: see text] consistently rejects the null. Additionally, we show in simulations that OASIS is more powerful than Pearson's [Formula: see text] in certain regimes, including for some important two group alternatives, which we corroborate with approximate power calculations.

Polyvalent s-block elements: A missing link challenges the periodic law of chemistry for the heavy elements.

The Periodic Law of Chemistry is one of the great discoveries in cultural history. Elements behaving chemically similar are empirically merged in groups G of a Periodic Table, each element with G valence electrons per neutral atom, and with upper limit G for the oxidation and valence numbers. Here, we report that among the usually mono- or di-valent s-block elements (G = 1 or 2), the heaviest members (87Fr, 88Ra, 119E, and 120E) with atomic numbers Z = 87, 88, 119, 120 form unusual 5- or 6-valent compounds at ambient conditions. Together with well-reported basic changes of valence at the end of the 6d-series, in the whole 7p-series, and for 5g6f-elements, it indicates that at the bottom of common Periodic Tables, the classic Periodic Law is not as straightforward as commonly expected. Specifically, we predict the feasible experimental synthesis of polyvalent [RaL-n] (n = 4, 6) compounds.

Normal table of embryonic development in the Anji salamander Hynobius amjiensis (Hynobiidae).

We established a normal embryonic development table for the Anji salamander Hynobius amjiensis, a critically endangered tailed amphibian of the family Hynobiidae with a very limited distribution in East China, following the standards set by the early developmental table of vertebrates. Put together 32 embryonic stages for the Anji salamander was defined. The total embryonic period from oviposition to hatching is approximately 30 days at 9 °C. Stages 1-16 represent early development from cleavage to neurulation. Stages 17-32 represent organogenesis documenting later developmental events such as tail, gill, and limb formation, and hatching (Stage 32). We provided a detailed description of the external morphology and color changes of the head, trunk, limbs, tail, external gills, and balancers at various stages from egg-laying to hatching. We also described several cases of abnormal embryonic development. The establishment of the embryonic development table in H. amjiensis contributes to better understanding of the ontogeny in tailed amphibians, distinguishing closely related species, and identifying abnormal embryonic amphibians.

Normal Table of Xenopus development: a new graphical resource.

Normal tables of development are essential for studies of embryogenesis, serving as an important resource for model organisms, including the frog Xenopus laevis. Xenopus has long been used to study developmental and cell biology, and is an increasingly important model for human birth defects and disease, genomics, proteomics and toxicology. Scientists utilize Nieuwkoop and Faber's classic 'Normal Table of Xenopus laevis (Daudin)' and accompanying illustrations to enable experimental reproducibility and reuse the illustrations in new publications and teaching. However, it is no longer possible to obtain permission for these copyrighted illustrations. We present 133 new, high-quality illustrations of X. laevis development from fertilization to metamorphosis, with additional views that were not available in the original collection. All the images are available on Xenbase, the Xenopus knowledgebase (http://www.xenbase.org/entry/zahn.do), for download and reuse under an attributable, non-commercial creative commons license. Additionally, we have compiled a 'Landmarks Table' of key morphological features and marker gene expression that can be used to distinguish stages quickly and reliably (https://www.xenbase.org/entry/landmarks-table.do). This new open-access resource will facilitate Xenopus research and teaching in the decades to come.

The expansion of chemical space in 1826 and in the 1840s prompted the convergence to the periodic system.

The periodic system, which intertwines order and similarity among chemical elements, arose from knowledge about substances constituting the chemical space. Little is known, however, about how the expansion of the space contributed to the emergence of the system-formulated in the 1860s. Here, we show by analyzing the space between 1800 and 1869 that after an unstable period culminating around 1826, chemical space led the system to converge to a backbone structure clearly recognizable in the 1840s. Hence, the system was already encoded in the space for about two and half decades before its formulation. Chemical events in 1826 and in the 1840s were driven by the discovery of new forms of combination standing the test of time. Emphasis of the space upon organic chemicals after 1830 prompted the recognition of relationships among elements participating in the organic turn and obscured some of the relationships among transition metals. To account for the role of nineteenth century atomic weights upon the system, we introduced an algorithm to adjust the space according to different sets of weights, which allowed for estimating the resulting periodic systems of chemists using one or the other weights. By analyzing these systems, from Dalton up to Mendeleev, Gmelin's atomic weights of 1843 produce systems remarkably similar to that of 1869, a similarity that was reinforced by the atomic weights on the years to come. Although our approach is computational rather than historical, we hope it can complement other tools of the history of chemistry.

Electronegativity and chemical hardness of elements under pressure.

SignificanceOver the years, many unusual chemical phenomena have been discovered at high pressures, yet our understanding of them is still very fragmentary. Our paper addresses this from the fundamental level by exploring the key chemical properties of atoms-electronegativity and chemical hardness-as a function of pressure. We have made an appropriate modification to the definition of Mulliken electronegativity to extend its applicability to high pressures. The change in atomic properties, which we observe, allows us to provide a unified framework explaining (and predicting) many chemical phenomena and the altered behavior of many elements under pressure.

A periodic table of monosaccharides.

It is important to recognize the great diversity of monosaccharides commonly encountered in animals, plants, and microbes, as well as to organize them in a visually interesting style that also emphasizes their similarities and relatedness. This article discusses the nature of building blocks, monosaccharides, and monosaccharide derivatives-terms commonly used in discussing "glycomolecules" found in nature. To aid in awareness of monosaccharide diversity, here is presented a Periodic Table of Monosaccharides. The rationale is given for construction of the Table and the selection of 103 monosaccharides, which is largely based on those presented in the KEGG and SNFG websites of monosaccharides, and includes room to enlarge as new discoveries are made. The Table should have educational value and is intended to capture the attention and foster imagination of those not very familiar with glycosciences, and encourage researchers to delve deeper into this fascinating area.

Nonlinear life table response experiment analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers.

Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. We extend regression LTREs to incorporate nonlinear (second-order) terms and compare the accuracy of both approaches for three previously published demographic datasets. We show that the second-order approach equals or outperforms the linear approach for all three case studies, even when all of the underlying vital rate functions are linear. Nonlinear vital rate responses to driver changes contributed most to population growth rate responses, but life history changes also made substantial contributions. Our results suggest that moving from linear to second-order LTRE analyses could improve our understanding of population responses to changing environments.

Elevating water table reduces net ecosystem carbon losses from global drained wetlands.

Drained wetlands are thought to be carbon (C) source hotspots, and rewetting is advocated to restore C storage in drained wetlands for climate change mitigation. However, current assessments of wetland C balance mainly focus on vertical fluxes between the land and atmosphere, frequently neglecting lateral carbon fluxes and land-use effects. Here, we conduct a global synthesis of 893 annual net ecosystem C balance (NECB) measures that include net ecosystem exchange of CO2, along with C input via manure fertilization, and C removal through biomass harvest or hydrological exports of dissolved organic and inorganic carbon, across wetlands of different status and land uses. We find that elevating water table substantially reduces net ecosystem C losses, with the annual NECB decreasing from 2579 (95% interval: 1976 to 3214) kg C ha-1 year-1 in drained wetlands to -422 (-658 to -176) kg C ha-1 year-1 in natural wetlands, and to -934 (-1532 to -399) kg C ha-1 year-1 in rewetted wetlands globally. Climate, land-use history, and time since water table changes introduce variabilities, with drainage for (sub)tropical agriculture or forestry uses showing high annual C losses, while the net C losses from drained wetlands can continue to affect soil C pools for several decades. Rewetting all types of drained wetlands is needed, particularly for those formerly agriculture-used (sub)tropical wetlands where net ecosystem C losses can be largely reduced. Our findings suggest that elevating water table is an important initiative to reduce C losses in degraded wetlands, which could contribute to policy decisions for managing wetlands to enhance their C sequestration.

Exact confidence intervals for population growth rate, longevity and generation time.

By quantifying key life history parameters in populations, such as growth rate, longevity, and generation time, researchers and administrators can obtain valuable insights into its dynamics. Although point estimates of demographic parameters have been available since the inception of demography as a scientific discipline, the construction of confidence intervals has typically relied on approximations through series expansions or computationally intensive techniques. This study introduces the first mathematical expression for calculating confidence intervals for the aforementioned life history traits when individuals are unidentifiable and data are presented as a life table. The key finding is the accurate estimation of the confidence interval for r, the instantaneous growth rate, which is tested using Monte Carlo simulations with four arbitrary discrete distributions. In comparison to the bootstrap method, the proposed interval construction method proves more efficient, particularly for experiments with a total offspring size below 400. We discuss handling cases where data are organized in extended life tables or as a matrix of vital rates. We have developed and provided accompanying code to facilitate these computations.

Categorical linkage-data analysis.

Analysis of integrated data often requires record linkage in order to join together the data residing in separate sources. In case linkage errors cannot be avoided, due to the lack a unique identity key that can be used to link the records unequivocally, standard statistical techniques may produce misleading inference if the linked data are treated as if they were true observations. In this paper, we propose methods for categorical data analysis based on linked data that are not prepared by the analyst, such that neither the match-key variables nor the unlinked records are available. The adjustment is based on the proportion of false links in the linked file and our approach allows the probabilities of correct linkage to vary across the records without requiring that one is able to estimate this probability for each individual record. It accommodates also the general situation where unmatched records that cannot possibly be correctly linked exist in all the sources. The proposed methods are studied by simulation and applied to real data.

Invariances in relations between aging, exposure to external hazards, and mortality reflected in life table aging rate (LAR) patterns examined through the lens of generalized Gompertz-Makeham law.

According to the Gompertz law, the age-dependent change in the logarithm of mortality (life-table aging rate, LAR) is equal to the population-averaged age-independent biological aging rate (γ), and LAR would be constant if aging were the only cause of mortality increase. However, LAR is influenced by population exposures to the external hazards. If they were constant, according to the Gompertz-Makeham law (GML), LAR would be below γ at lower ages and asymptotically and monotonically approach γ with increasing age. Actually, LAR trajectories derived from data on mortality in different countries and historical periods feature systematic undulations. In the present investigation, mortality-vs.-age trajectories were modeled based on a generalized GML (gGML). Unlike the canonical GML terms, which are population-specific constants, the respective terms of the gGML are represented with some population-specific functions of age. Invariant in gGML are the modes of translation of these functions into the dependency of mortality on age: linear for population exposure to the irresistible external hazards or exponential for population-averaged ability to withstand the resistible external and internal hazards. Modeling suggests that, at earlier ages, LAR undulations are attributable to changes in population exposures to the former hazards. However, only their unrealistically high levels can produce the transient increase in LAR at about 65 to 90 years. This pervasive undulation of LAR-vs.-age trajectory is rather caused by an increment in γ. Reasons to regard gGML as a genuine natural law, which defines relations between mortality, aging and environment, are discussed.

Model-based comparisons of post-treatment free IgE and FEV1 between omalizumab asthma dosing tables in the United States and European Union.

AIMS: Omalizumab is an anti-immunoglobulin E (IgE) monoclonal antibody that was first approved by the United States (US) Food and Drug Administration (FDA) for the treatment of allergic asthma in 2003. The pivotal trials supporting the initial approval of omalizumab used dosing determined by patient's baseline IgE and body weight, with the goal of reducing the mean free IgE level to approximately 25 ng/mL or less. While the underlying parameters supporting the dosing table remained the same, subsequent studies and analyses have resulted in approved alternative versions of the dosing table, including the European Union (EU) asthma dosing table, which differs in weight bands and maximum allowable baseline IgE and omalizumab dose. In this study, we leveraged modelling and simulation approaches to predict and compare the free IgE reduction and forced expiratory volume in 1 second (FEV1) improvement with omalizumab dosing based on the US and EU asthma dosing tables. METHODS: Previously established population pharmacokinetic-IgE and IgE-FEV1 models were used to predict and compare post-treatment free IgE and FEV1 based on the US and EU dosing tables. Clinical trial simulations (with virtual asthma populations) and Monte Carlo simulations were performed to provide both breadth and depth in the comparisons. RESULTS: The US and EU asthma dosing tables were predicted to result in generally comparable free IgE suppression and FEV1 improvement. CONCLUSIONS: Despite the similar free IgE and FEV1 outcomes from simulations, this has not been clinically validated with respect to the registrational endpoint of reduction in annualized asthma exacerbations.

Robustly estimating the demographic contribution of immigration: Simulation, sensitivity analysis and seals.

Identifying important demographic drivers of population dynamics is fundamental for understanding life-history evolution and implementing effective conservation measures. Integrated population models (IPMs) coupled with transient life table response experiments (tLTREs) allow ecologists to quantify the contributions of demographic parameters to observed population change. While IPMs can estimate parameters that are not estimable using any data source alone, for example, immigration, the estimated contribution of such parameters to population change is prone to bias. Currently, it is unclear when robust conclusions can be drawn from them. We sought to understand the drivers of a rebounding southern elephant seal population on Marion Island using the IPM-tLTRE framework, applied to count and mark-recapture data on 9500 female seals over nearly 40 years. Given the uncertainty around IPM-tLTRE estimates of immigration, we also aimed to investigate the utility of simulation and sensitivity analyses as general tools for evaluating the robustness of conclusions obtained in this framework. Using a Bayesian IPM and tLTRE analysis, we quantified the contributions of survival, immigration and population structure to population growth. We assessed the sensitivity of our estimates to choice of multivariate priors on immigration and other vital rates. To do so we make a novel application of Gaussian process priors, in comparison with commonly used shrinkage priors. Using simulation, we assessed our model's ability to estimate the demographic contribution of immigration under different levels of temporal variance in immigration. The tLTRE analysis suggested that adult survival and immigration were the most important drivers of recent population growth. While the contribution of immigration was sensitive to prior choices, the estimate was consistently large. Furthermore, our simulation study validated the importance of immigration by showing that our estimate of its demographic contribution is unlikely to result as a biased overestimate. Our results highlight the connectivity between distant populations of southern elephant seals, illustrating that female dispersal can be important in regulating the abundance of local populations even when natal site fidelity is high. More generally, we demonstrate how robust ecological conclusions may be obtained about immigration from the IPM-tLTRE framework, by combining sensitivity analysis and simulation.

Redefining 'state-of-the-art' for integrated population models with immigration.

Research Highlight: Christian, M., Oosthuizen, W. C., Bester, M. N., & de Bruyn, P. N. (2024). Robustly estimating the demographic contribution of immigration: Simulation, sensitivity analysis and seals. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.14053. Immigration can have profound consequences for local population dynamics and demography, but collecting data to accurately quantifying it is challenging. The recent rise of integrated population models (IPMs) offers an alternative by making it possible to estimate immigration without the need for explicit data, and to quantify its contribution to population dynamics through transient Life Table Response Experiments (tLTREs). Simulation studies have, however, highlighted that this approach can be prone to bias and overestimation. In their new study, Christian et al. address one of the root causes of this issue by improving the estimation of time variation in vital rates and immigration using Gaussian processes in lieu of traditionally used temporal random effects. They demonstrate that IPM-tLTRE frameworks with Gaussian processes produce more accurate and less biased estimates of immigration and its contribution to population dynamics and illustrate the applicability of this approach using a long-term data set on elephant seals (Mirounga leonida). Results are validated with a simulation study and suggest that immigration of breeding females has been central for population recovery of elephant seals despite the species' high female site fidelity. Christian et al. thus present new insights into population regulation of long-lived marine mammals and highlight the potential for using Gaussian process priors in IPMs. They also illustrate a suite of 'best practices' for state-of-the-art IPM-tLTRE analyses and provide an inspirational example for the kind of ecological modelling workflow that can be invaluable not just as a starting point for fellow ecologists picking up or improving their own IPM-tLTRE analyses, but also for teaching and in contexts where model estimates are used for informing management and conservation decision-making.

Temporal relationship between haemodynamic changes and activation of closed-loop stimulation during a tilt-induced vasovagal syncope.

AIMS: A dual-chamber pacemaker with closed-loop stimulation (CLS) mode is effective in reducing syncopal recurrences in patients with asystolic vasovagal syncope (VVS). In this study, we explored the haemodynamic and temporal relationship of CLS during a tilt-induced vasovagal reflex. METHODS AND RESULTS: Twenty patients underwent a tilt test under video recording 3.9 years after CLS pacemaker implantation. Three patients were excluded from the analysis because of no VVS induced by the tilt test (n = 1) and protocol violation (n = 2). In 14 of the remaining 17 patients, CLS pacing emerged during the pre-syncopal phase of circulatory instability when the mean intrinsic heart rate (HR) was 88 ± 12 b.p.m. and systolic blood pressure (SBP) was 108 ± 19 mmHg. The CLS pacing rate thereafter rapidly increased to 105 ± 14 b.p.m. within a median of 0.1 min [inter-quartile range (IQR), 0.1-0.7 min] when the SBP was 99 ± 21 mmHg. At the time of maximum vasovagal effect (syncope or pre-syncope), SBP was 63 ± 17 mmHg and the CLS rate was 95 ± 13 b.p.m. The onset of CLS pacing was 1.7 min (IQR, 1.5-3.4) before syncope or lowest SBP. The total duration of CLS pacing was 5.0 min (IQR, 3.3-8.3). Closed-loop stimulation pacing was not observed in three patients who had a similar SBP decrease from 142 ± 22 mmHg at baseline to 69 ± 4 mmHg at the time of maximum vasovagal effect, but there was no significant increase in HR (59 ± 1 b.p.m.). CONCLUSION: The reproducibility of a vasovagal reflex was high. High-rate CLS pacing was observed early during the pre-syncopal phase in most patients and persisted, although attenuated, at the time of maximum vasovagal effect. REGISTRATION: ClinicalTrials.gov identifier: NCT06038708.

A Critical Review of Groundwater Table Fluctuation: Formation, Effects on Multifields, and Contaminant Behaviors in a Soil and Aquifer System.

The groundwater table fluctuation (GTF) zone is an important medium for the hydrologic cycle between unsaturated soil and saturated aquifers, which accelerates the migration, transformation, and redistribution of contaminants and further poses a potential environmental risk to humans. In this review, we clarify the key processes in the generation of the GTF zone and examine its links with the variation of the hydrodynamic and hydrochemistry field, colloid mobilization, and contaminant migration and transformation. Driven by groundwater recharge and discharge, GTF regulates water flow and the movement of the capillary fringe, which further control the advection and dispersion of contaminants in soil and groundwater. In addition, the formation and variation of the reactive oxygen species (ROS) waterfall are impacted by GTF. The changing ROS components partially determine the characteristic transformation of solutes and the dynamic redistribution of the microbial population. GTF facilitates the migration and transformation of contaminants (such as nitrogen, heavy metals, non-aqueous phase liquids, and volatile organic compounds) through colloid mobilization, the co-migration effect, and variation of the hydrodynamic and hydrochemistry fields. In conclusion, this review illustrates the limitations of the current literature on GTF, and the significance of GTF zones in the underground environment is underscored by expounding on the future directions and prospects.

Short-Term Groundwater Level Fluctuations Drive Subsurface Redox Variability.

As global change processes modify the extent and functions of terrestrial-aquatic interfaces, the variability of critical and dynamic transitional zones between wetlands and uplands increases. However, it is still unclear how fluctuating water levels at these dynamic boundaries alter groundwater biogeochemical cycling. Here, we used high-temporal resolution data along gradients from wetlands to uplands and during fluctuating water levels at freshwater coastal areas to capture spatiotemporal patterns of groundwater redox potential (Eh). We observed that topography influences groundwater Eh that is higher in uplands than in wetlands; however, the high variability within TAI zones challenged the establishment of distinct redox zonation. Declining water levels generally decreased Eh, but most locations exhibited significant Eh variability, which is associated with rare instances of short-term water level fluctuations, introducing oxygen. The Eh-oxygen relationship showed distinct hysteresis patterns, reflecting redox poising capacity at higher Eh, maintaining more oxidizing states longer than the dissolved oxygen presence. Surprisingly, we observed more frequent oxidizing states in transitional areas and wetlands than in uplands. We infer that occasional oxygen entering specific wetland-upland boundaries acts as critical biogeochemical control points. High-resolution data can capture such rare yet significant biogeochemical instances, supporting redox-informed models and advancing the predictability of climate change feedback.

Non-flooding conditions caused by water table drawdown alter microbial network complexity and decrease multifunctionality in alpine wetland soils.

Several soil functions of alpine wetland depend on microbial communities, including carbon storage and nutrient cycling, and soil microbes are highly sensitive to hydrological conditions. Wetland degradation is often accompanied by a decline in water table. With the water table drawdown, the effects of microbial network complexity on various soil functions remain insufficiently understood. In this research, we quantified soil multifunctionality of flooded and non-flooded sites in the Lalu Wetland on the Tibetan Plateau. We employed high-throughput sequencing to investigate the microbial community responses to water table depth changes, as well as the relationships between microbial network properties and soil multifunctionality. Our findings revealed a substantial reduction in soil multifunctionality at both surface and subsurface soil layers (0-20 cm and 20-40 cm) in non-flooded sites compared to flooded sites. The α-diversity of bacteria in the surface soil of non-flooded sites was significantly lower than that in flooded sites. Microbial network properties (including the number of nodes, number of edges, average degree, density, and modularity of co-occurrence networks) exhibited significant correlations with soil multifunctionality. This study underscores the adverse impact of non-flooded conditions resulting from water table drawdown on soil multifunctionality in alpine wetland soils, driven by alterations in microbial community structure. Additionally, we identified soil pH and moisture content as pivotal abiotic factors influencing soil multifunctionality, with microbial network complexity emerging as a valuable predictor of multifunctionality.