Natural Variation Research Articles

Chromosome-level assembly of the Clinopodium gracile genome

Clinopodium gracile is an important medicinal herb in the Lamiaceae family. This species lacks corresponding genomic resources, which significantly limits the study of its active compound synthesis pathways, breeding practices, and assessment of natural genetic variations. We assembled the chromosomal-level genome of C. gracile using Oxford Nanopore (ONT) technology and Hi-C sequence. The assembled genome is 307.3 Mb in size and consists of 9 chromosomes. The scaffold N50 was 36.3 Mb. The BUSCO completeness (Embryophyta_db10) of the genome was 97.2%. The genome annotates 40,083 protein coding genes. C. gracile and S. miltiorrhiza diverged approximately 30.615 million years ago. C. gracile has not undergone recent species-specific WGD events. A high proportion of young LTRs indicates a recent transposable element (TE) transposition burst in C. gracile.

Optimal Planning of Standalone Rural Microgrid With Effective Dispatch Strategies and Battery Technology

ABSTRACTMicrogrids are a viable substitute for traditional power systems because they may deliver cleaner, more dependable, affordable power with fewer losses. However, the microgrid's performance is impacted by the variable nature of renewable energy sources. Battery storage is a crucial component of microgrid planning since it defines the system's techno‐economic feasibility. A standalone rural microgrid is designed in the current study, employing three distinct battery types: lithium‐ion, lead acid, and zinc‐bromine flow. The suggested microgrid's techno‐economic analysis employs three distinct dispatch mechanisms, that is, cycle charging, load flow, and complete dispatch. The case study of the suggested framework is carried out in Lucknow (India). The system comprises PV/battery/wind energy system/diesel and battery. The simulation results suggest that the optimal system with the least electrification cost is 0.113 $/kWh using complete dispatch strategies and a zinc‐bromine battery. It has 206 kWh zinc‐bromine flow batteries, a 10 kW converter, a 20 kW PV, a 13‐kW diesel generator, and a Combined dispatch strategy. The system's net present cost per unit cost of energy is $40 275 and 0.113 $/kWh for the chosen region, respectively. Compared to the other two battery technologies for hybrid systems, the zinc‐bromine flow battery technology is also shown to be the most environmentally friendly. Among the three battery technologies available, zinc‐bromine flow is best used in a particular location's hybridized operation.

Comparison of magnification corrected optic disc size by slit-lamp biomicroscopy, fundus photography, and optical coherence tomography

Abstract PURPOSE: Optic disc size measurement is essential for determining landmarks, lesions, and distances of the retina. Due to the size variability in nature and when measured with different instruments, newer methods to compare sizes between different instruments are needed. We aimed to determine the comparability of slit lamp, fundus photography, and optical coherence tomography (OCT) measurements of optic disc size after correcting for both ocular and instrument magnification. MATERIALS AND METHODS: In this prospective, observational study, optic disc size was measured by slit-lamp biomicroscopy, fundus photography, and OCT. Instrument and ocular magnification was calculated, and the measured size was corrected for both using the Littman formula. The corrected values were analyzed using Bland–Altman plots and intra-class correlation (ICC) for agreeability and correlation, respectively. Linear regression analysis was conducted to estimate the systematic errors and interconvertibility in cases of high correlation. RESULTS: Fifty-six eyes were included for the analysis. Uncorrected and corrected values for each method had excellent correlation and agreeability (ICC absolute agreement >0.75, P < 0.01). Among magnification corrected values, slit lamp and OCT had excellent correlation and agreement (ICC consistency = 0.846, confidence interval 0.75–0.91, P < 0.01). This pair had R 2 = 0.73 on linear regression (P < 0.01). Linear regression formulas for interconverting uncorrected and corrected values for the three methods had variable accuracy (R 2 from 0.47 to 0.66). CONCLUSION: Uncorrected values of different methods for disc size measurement cannot be compared directly; they need ocular and instrument magnification correction. Among the three methods compared, the best interconvertible pairs of measurement were magnification corrected slit lamp and OCT values.

Algorithmic Persuasion with Evidence

In a game of persuasion with evidence, a sender has private information. By presenting evidence on the information, the sender wishes to persuade a receiver to take a single action (e.g., hire a job candidate, or convict a defendant). The sender’s utility depends solely on whether the receiver takes the action. The receiver’s utility depends on both the action and the sender’s private information. We study three natural variations. First, we consider the problem of computing an equilibrium of the game without commitment power. Second, we consider a persuasion variant, where the sender commits to a signaling scheme and the receiver, after seeing the evidence, takes the action or not. Third, we study a delegation variant, where the receiver first commits to taking the action if being presented certain evidence, and the sender presents evidence to maximize the probability the action is taken. We study these variants through the computational lens, and give hardness results, optimal approximation algorithms, and polynomial-time algorithms for special cases. Among our results is an approximation algorithm that rounds a semidefinite program that might be of independent interest, since, to the best of our knowledge, it is the first such approximation algorithm in algorithmic economics.

Latent Growth Model with Categorical Indicators: Comparison of the Different Estimators

Despite its potential usage in social and behavioral sciences, there has been limited research on Latent Growth Models (LGM) with categorical indicators. The categorical nature of binary or ordinal variables violates the multivariate normality assumption of the traditional maximum likelihood (ML) estimator. Alternative estimators can be employed, such as marginal maximum likelihood (MML), categorical weighted least squares (c-WLS), and categorical diagonally weighted least squares (c-DWLS). A Monte Carlo simulation study was conducted to compare the performance of the three estimators in the context of categorical LGM. The results revealed that the MML estimator performed the best for the correctly specified linear growth model, whereas the robust c-DWLS or c-WLS estimator excelled in correctly specified quadratic growth model. The robust c-DWLS and c-WLS estimators were more sensitive to model misspecifications. The findings of the present study provide important implications and practical recommendations for empirical researchers using categorical LGM.

Bioelastic state recovery for haptic sensory substitution.

The rich set of mechanoreceptors found in human skin1,2 offers a versatile engineering interface for transmitting information and eliciting perceptions3,4, potentially serving a broad range of applications in patient care5 and other important industries6,7. Targeted multisensory engagement of these afferent units, however, faces persistent challenges, especially for wearable, programmable systems that need to operate adaptively across the body8-11. Here we present a miniaturized electromechanical structure that, when combined with skin as an elastic, energy-storing element, supports bistable, self-sensing modes of deformation. Targeting specific classes of mechanoreceptors as the basis for distinct, programmed sensory responses, this haptic unit can deliver both dynamic and static stimuli, directed as either normal or shear forces. Systematic experimental and theoretical studies establish foundational principles and practical criteria for low-energy operation across natural anatomical variations in the mechanical properties of human skin. A wireless, skin-conformable haptic interface, integrating an array of these bistable transducers, serves as a high-density channel capable of rendering input from smartphone-based 3D scanning and inertial sensors. Demonstrations of this system include sensory substitution designed to improve the quality of life for patients with visual and proprioceptive impairments.

The shape of the corpus callosum is different in bipolar disorder.

Bipolar disorder (BD) is a recurrent chronic disorder characterised by fluctuations in mood and energy disposition. Diseases could lead to degenerative alterations in brain structures such as corpus callosum (CC). Studies demonstrated that abnormalities in CC are associated with BD symptoms. The present study aims to analyse the CC of the patients with statistical shape analysis (SSA) and compare the findings with healthy controls. Forty-one BD patients and 41 healthy individuals in similar age groups, which included 23 female and 18 male subjects, participated in the study. CC was marked with landmarks on the mid-sagittal images of each individual. The mean 'Procrustes' point was calculated, and shape deformations were analysed with thin-plate spline analysis. Significant differences were observed in the shape of CC between the two groups, where maximum CC deformation was observed in posterior region marks in BD patients. There was no significant difference between the CC area of the BD patients and controls. CC analysis conducted with SSA revealed significant differences between patients and healthy controls. The study findings emphasised the abnormal distribution of white matter in CC and the variable subregional nature of CC in BD patients. This study may enable the development of more targeted and effective treatment strategies by taking into account biological factors and understanding the differences in the brain regions of individuals with BD.

AmbiBias Contrast: Enhancing debiasing networks via disentangled space from ambiguity-bias clusters

The goal of debiasing in classification tasks is to train models to be less sensitive to correlations between a sample’s target attribution and periodically occurring contextual attributes to achieve accurate classification. A prevalent method involves applying re-weighing techniques to lower the weight of bias-aligned samples that contribute to bias, thereby focusing the training on bias-conflicting samples that deviate from the bias patterns. Our empirical analysis indicates that this approach is effective in datasets where bias-conflicting samples constitute a minority compared to bias-aligned samples, yet its effectiveness diminishes in datasets with similar proportions of both. This ineffectiveness in varied dataset compositions suggests that the traditional method cannot be practical in diverse environments as it overlooks the dynamic nature of dataset-induced biases. To address this issue, we introduce a contrastive approach named “AmbiBias Contrast”, which is robust across various dataset compositions. This method accounts for “ambiguity bias”— the variable nature of bias elements across datasets, which cannot be clearly defined. Given the challenge of defining bias due to the fluctuating compositions of datasets, we designed a method of representation learning that accommodates this ambiguity. Our experiments across a range of and dataset configurations verify the robustness of our method, delivering state-of-the-art performance.

Drosophila Toxicogenomics: genetic variation and sexual dimorphism in susceptibility to 4-Methylimidazole

Background4-methylimidazole is a ubiquitous and potentially carcinogenic environmental toxicant. Genetic factors that contribute to variation in susceptibility to its toxic effects are challenging to assess in human populations. We used the Drosophila melanogaster Genetic Reference Panel (DGRP), a living library of natural genetic variation, to identify genes with human orthologs associated with variation in susceptibility to 4-methylimidazole.ResultsWe screened 204 DGRP lines for survival following 24-hour exposure to 4-methylimidazole. We found extensive genetic variation for survival, with a broad sense heritability of 0.82; as well as genetic variation in sexual dimorphism, with a cross-sex genetic correlation of 0.59. Genome-wide association analyses identified a total of 241 candidate molecular polymorphisms in or near 273 unique genes associated with survival. These polymorphisms had either sex-specific or sex-antagonistic effects, and most had putative regulatory effects. We generated interaction networks using these candidate genes as inputs and computationally recruited genes with known physical or genetic interactions. The network genes were significantly over-represented for gene ontology terms involving all aspects of development (including nervous system development) and cellular and organismal functions as well as canonical signaling pathways, and most had human orthologs.ConclusionsThe genetic basis of variation in sensitivity to acute exposure to 4-methylimidazole in Drosophila is attributable to variation in genes and networks of genes known for their effects on multiple developmental and cellular processes, including possible neurotoxicity. Given evolutionary conservation of the underlying genes and pathways, these insights may be applicable to humans.

Integrating agricultural land suitability and farmers' perception on crop selection in a water-stressed region of eastern India

CONTEXTThe choice of crops for cultivation should be ideally based on the appropriateness of a specific parcel of land for a particular crop. This is a multi-criteria problem associated with a host of natural conditioning variables including topography, climate and pedology. However, in a country like India, where agriculture is often traditional and subsistence-based, the farmers' choice of crop selection is usually influenced by numerous factors and therefore, may not be explained solely by the spatial variation in the agricultural land suitability. OBJECTIVEThis study is an attempt to understand the intricacies involved in the farmers' selection of crops by integrating the dual aspects of agricultural land suitability and the farmers' understanding of the land. The Kumari River Basin in eastern India has been selected for this study. This area is characterized by acute scarcity of water. METHODSThe basic methodology involved extracting systematic information on conditional factors such as topography, climate and soil. After normalizing different parameters by the Fuzzy Membership Function, a reiterative Principal Component Analysis modified Analytical Hierarchy Process was applied to these conditional rasters to derive an index of agricultural land suitability of the studied basin. Furthermore, the crop-specific suitability of paddy and maize was also considered by employing the Boolean Logic. RESULTS AND CONCLUSIONSIt is observed that the lower domain of the Kumari Basin is characterized by greater land suitability as compared to the upper and middle domains and the most important factors behind this distribution include slope, potential evapotranspiration and soil fertility. Crop-specific land suitability suggests that, by and large, the suitability of maize is greater than that of paddy in the basin, except for the lower domain where paddy is more suitable to cultivate. However, a study of the perception of the local farmers reveals that although they are aware of this fact, they prefer paddy over maize and are more inclined towards cultivating paddy. The chief reasons cited by them include the high demand for paddy in the area and the absence of a Minimum Support Price for maize. SIGNIFICANCEThis study is possibly an instance where the agricultural land suitability analysis has been substantiated by a field-based perception survey of the farmers which is expected to help in understanding the complexities of crop selection in this part of India.

Genome-wide associated study identifies FtPMEI13 gene conferring drought resistance in Tartary buckwheat.

Tartary buckwheat is known for its ability to adapt to intricate growth conditions and to possess robust stress-resistant properties. Nevertheless, it remains vulnerable to drought stress, which can lead to reduced crop yield. To identify potential genes involved in drought resistance, a genome-wide association study on drought tolerance in Tartary buckwheat germplasm was conducted. A gene encoding pectin methylesterase inhibitors protein (FtPMEI13) was identified, which is not only associated with drought tolerance but also showed induction during drought stress and abscisic acid (ABA) treatment. Further analysis revealed that overexpression of FtPMEI13 leads to improved drought tolerance by altering the activities of antioxidant enzymes and the levels of osmotically active metabolites. Additionally, FtPMEI13 interacts with pectin methylesterase (PME) and inhibits PME activity in response to drought stress. Our results suggest that FtPMEI13 may inhibit the activity of FtPME44/FtPME61, thereby affecting pectin methylesterification in the cell wall and modulating stomatal closure in response to drought stress. Yeast one-hybrid, dual-luciferase assays, and electrophoretic mobility shift assays demonstrated that an ABA-responsive transcription factor FtbZIP46, could bind to the FtPMEI13 promoter, enhancing FtPMEI13 expression. Further analysis indicated that Tartary buckwheat accessions with the genotype resulting in higher FtPMEI13 and FtbZIP46 expression exhibited higher drought tolerance compared to the others. This suggests that this genotype has potential for application in Tartary buckwheat breeding. Furthermore, the natural variation of FtPMEI13 was responsible for decreased drought tolerance during Tartary buckwheat domestication. Taken together, these results provide basic support for Tartary buckwheat breeding for drought tolerance.

Crucial Roles of Brassinosteroids in Cell Wall Composition and Structure Across Species: New Insights and Biotechnological Applications.

Brassinosteroids (BR) are steroidal phytohormones essential for plant growth, development, and stress resistance. They fulfil this role partially by modulating cell wall structure and composition through the control of gene expression involved in primary and secondary cell wall biosynthesis and metabolism. This affects the deposition of cellulose, lignin, and other components, and modifies the inner architecture of the wall, allowing it to adapt to the developmental status and environmental conditions. This review focuses on the effects that BR exerts on the main components of the cell wall, cellulose, hemicellulose, pectin and lignin, in multiple and relevant plant species. We summarize the outcomes that result from modifying cell wall components by altering BR gene expression, applying exogenous BR and utilizing natural variability in BR content and describing new roles of BR in cell wall structure. Additionally, we discuss the potential use of BR to address pressing needs, such as increasing crop yield and quality, enhancing stress resistance and improving wood production through cell wall modulation.

Shallow Groundwater Quality Assessment and Pollution Source Apportionment: Case Study in Wujiang District, Suzhou City

Groundwater serves as a crucial resource, with its quality significantly impacted by both natural and human-induced factors. In the highly industrialized and urbanized Yangtze River Delta region, the sources of pollutants in shallow groundwater are more complex, making the identification of groundwater pollution sources a challenging task. In this study, 117 wells in Wujiang District of Suzhou City were sampled, and 16 groundwater quality parameters were analyzed. The fuzzy synthetic evaluation method was used to assess the current status of groundwater pollution in the study area; the principal component analysis (PCA) was employed to discern the anthropogenic and natural variables that influence the quality of shallow groundwater; and the absolute principal component scores–multiple linear regression (APCS-MLR) model was applied to quantify the contributions of various origins toward the selected groundwater quality parameters. The results indicate that the main exceeding indicators of groundwater in Wujiang District are I (28%), NH4-N (18%), and Mn (14%); overall, the groundwater quality is relatively good in the region, with localized heavy pollution: class IV and class V water are mainly concentrated in the southwest of Lili Town, the north of Songling Town, and the south of Qidu Town. Through PCA, five factors contributing to the hydrochemical characteristics of groundwater in Wujiang District were identified: water–rock interaction, surface water–groundwater interaction, sewage discharge from the textile industry, urban domestic sewage discharge, and agricultural non-point source pollution. Additionally, the APCS-MLR model determined that the contributions of the three main pollution sources to groundwater contamination are in the following order: sewage discharge from the textile industry (10.63%) > urban domestic sewage discharge (8.69%) > agricultural non-point source pollution (6.26%).

Poleward Migration of the Latitude of Maximum Tropical Cyclone Intensity—Forced or Natural?

Abstract Past studies have shown a significant observed poleward trend in the latitude at which tropical cyclones reach their lifetime maximum intensity (LMI), especially in the northwest Pacific basin. Given the brevity of the historical record, it remains difficult to separate the forced trend from internal variability of the climate system. A recently developed tropical cyclone downscaling model is used to downscale the Community Earth System Model, version 2 (CESM2), preindustrial control simulation. It is found that the observed trend in the latitude at which tropical cyclones reach their LMI in the northwest Pacific is very unlikely to be caused by internal variability. The same downscaling model is then used to downscale CESM2 simulations under historical forcing. The resulting trend distribution shows a significant poleward migration of tropical cyclone LMI even after regressing out both natural variability and the part of the forced warming pattern that projects onto natural variability. The results indicate that the observed poleward migration of the latitude at which tropical cyclones reach their LMI in the northwest Pacific basin is likely to be, at least in part, forced. However, the magnitude of the projected poleward trend in climate models can be significantly modulated by the simulated spatial pattern of ocean warming. This highlights how discrepancies between models and observations, with regard to projected changes to the equatorial zonal sea surface temperature gradient under anthropogenic forcing, can lead to large uncertainties in projected changes to the LMI latitude of tropical cyclones. Significance Statement Observations in the northwest Pacific basin show that the latitude at which tropical cyclones are at their most intense has been trending northward in the recent half century. These changes are important since tropical cyclones could bring hazardous weather to coastal areas that are poorly equipped to handle them. Here, we show that natural variations in Earth’s climate are very unlikely to explain the observed poleward trend in the latitude that tropical cyclone reach their maximum intensity. We find that it is much more likely that the observed trend is forced by human-related emissions, though the spatial pattern of warming in response to greenhouse emissions can have significant impacts on the magnitude of the trend.

Bilateral symmetry assessment of healthy forearm kinematics using 4D-CT

Advanced stage distal radio-ulnar joint (DRUJ) injury may warrant radius corrective osteotomy or arthroplasty. These procedures aim to restore geometry, function and kinematics and could benefit from preoperative planning where the contralateral forearm is typically used as reference. Natural variations regarding geometry and function between forearms are known but kinematic differences are not. This work aimed to quantify bilateral differences in forearm kinematics. Consequently, 4D-CT data of ten healthy volunteers was acquired, imaging motion of both forearm joints. Segmentation and registration of the radius and ulna bones resulted in a 3D representation of forearm rotation. Subsequently, the forearm rotation axis, radius translation along the ulna and radius rotation around its own inertial axis were calculated. The rotation axis of the right arm was mirrored to set up a comparison with the left arm. All other differences were calculated directly. The mean angle and distance between forearm rotation axes were 0.6° and 0.8 mm. The mean difference in radius translation along the ulna was 0.9 mm. On average, radius rotation around the radius’ inertial axis differed 2.6°, between forearms. This study’s findings can benefit DRUJ surgery preoperative planning and postoperative kinematic evaluation.Level of evidence: IV.

EIF2Bβ confers resistance to Turnip mosaic virus by recruiting ALKBH9B to modify viral RNA methylation.

Eukaryotic translation initiation factors (eIFs) are the primary targets for overcoming RNA virus resistance in plants. In a previous study, we mapped a BjeIF2Bβ from Brassica juncea representing a new class of plant virus resistance genes associated with resistance to Turnip mosaic virus (TuMV). However, the mechanism underlying eIF2Bβ-mediated virus resistance remains unclear. In this study, we discovered that the natural variation of BjeIF2Bβ in the allopolyploid B. juncea was inherited from one of its ancestors, B. rapa. By editing of eIF2Bβ, we were able to confer resistance to TuMV in B. juncea and in its sister species of B. napus. Additionally, we identified an N6-methyladenosine (m6A) demethylation factor, BjALKBH9B, for interaction with BjeIF2Bβ, where BjALKBH9B co-localized with both BjeIF2Bβ and TuMV. Furthermore, BjeIF2Bβ recruits BjALKBH9B to modify the m6A status of TuMV viral coat protein RNA, which lacks the ALKB homologue in its genomic RNA, thereby affecting viral infection. Our findings have applications for improving virus resistance in the Brassicaceae family through natural variation or genome editing of the eIF2Bβ. Moreover, we uncovered a non-canonical translational control of viral mRNA in the host plant.

English

Coffee breeding programs aim at developing superior genotypes, which entail exploring the genetic variability existing in conilon/robusta coffee. This study aimed at examining the variability and estimate genetic param of physical and physiological nature in Coffea canephora seeds in order to provide bases for the selection of genotypes for superior seeds quality. Forty-three C. canephora genotypes were evaluated for 11 physical and physiological seed traits. Estimates of genetic param, environmental variance, phenotypic variance, genotypic variance, broad-sense heritability, variation index and Pearson's correlation were obtained. The Dissimilarity between genotypes was obtained by generalized Mahalanobis distance. The dendrogram was constructed using unweighted pair group method with arithmetic mean (UPGMA). C. canephora genotypes presented high germination potential and exhibited genetic diversity for all seed traits, with estimates of genetic variance greater than environmental variance. Heritability reached values above 96.0% and all genetic variation indices found were higher than unity. The UPGMA hierarchical method grouped the genotypes in three groups. The physical traits (circumference, area and roundness) were those that contributed the most to explaining the dissimilarity between genotypes. Genotypes Alecrim, AP, Bamburral, Z39 and Tardio C were the most divergent. The results revealed the presence of genetic variability between C. canephora genotypes and greater genetic than environmental influence on the characters of seeds, indicating that selection for the studied traits showed favorable conditions in terms of immediate gain.

Generating spatially realistic environmental null models with the shift‐&‐rotate approach helps evaluate false positives in species distribution modelling

Abstract To circumvent reporting spurious correlations, species distribution models often explicitly account for spatial autocorrelation, for example by including spatially structured random effects. The validity of statistical inference derived from such models has been tested by simulations using null environmental predictors that do not have any causal dependency with the response. Such null environmental predictors can be obtained by permutations of the original predictors or by simulating spatial structures resembling the original predictors. In such approaches, it is important that the permuted or simulated predictors reflect the nature of spatial variation present in the original predictors. Here we present a novel approach for generating realistic null predictors by a shift‐&‐rotate (S&R) approach: we extract environmental variables after randomly translating and rotating the sampling area within a window of defined environmental layers. In this way, the null environmental variables have fully realistic spatial variation and covariation, but no relationship to the response variable. We implement the S&R approach to three main R‐functions and demonstrate with a simulation study how they can be used to untangle causal versus non‐causal relationships within species distribution modelling. These methods allow us to quantify the predictive power attributed within the models due to non‐causal correlations generated by the realistic structure of the environmental covariates. In our case study, we identify when a model incorrectly estimates parameter values, yet still has high predictive power due to the structured nature of the predictor variables. The use of null models is imperative in ecological modelling for testing the accuracy of statistical inference in complex ecological systems and the choice of these null models is far from trivial. Here we provide R functions for generating spatially realistic null models to use in species distribution modelling as well as other spatially explicit fields such as landscape genetics.

Differences in Gut Microbes Across Age and Sex Linked to Metabolism and Microbial Stability in a Hibernating Mammal

ABSTRACTThe gut microbiome has a well‐documented relationship with host fitness, physiology, and behavior. However, most of what is known comes from captive animals where diets and environments are more homogeneous or controlled. Studies in wild populations that experience dynamic environments and have natural life history variation are less common but are key to understanding the drivers of variation in the gut microbiome. Here we examine a wild population of yellow‐bellied marmots (Marmota flaviventer), an obligate winter hibernator, to quantify multivariate associations between host‐associated factors (e.g., age, sex, environmental harshness, and social behavior) and gut microbial composition. Across 5 years and 143 individuals, we found that males had a higher relative abundance of microbes associated with mass gain and cellulose digestion, which suggests a metabolic investment in mass gain (such as phylum Firmicutes and family Lachnospiraceae). By contrast, females had higher relative abundances of microbes associated with inflammation and metabolism (from microbial groups such as Tenericutes and Ruminococcus), possibly reflecting the importance of lactation and offspring investment. Post hoc analyses of lactating females showed a negative relationship with the abundance of microbes associated with mass gain but a positive relationship with microbes associated with metabolic energy, suggesting a trade‐off between investment in pups and maternal mass gain. Older animals also had reduced Proteobacteria relative abundance, a phylum associated with reduced inflammation. Results demonstrate that sex and age‐based traits, not sociality or environmental harshness, are associated with microbe‐mediated metabolism and inflammation in a wild, hibernating mammal.

Using social-network analysis to map institutional actors’ links with vulnerable municipalities under climate change in Honduras’ dry corridor. Pathways towards improved cooperation and territorial interventions

The Honduras dry corridor, located in Central America’s Pacific region, has high natural climate variability. Nearly half of the Honduran population depends on socio-economic activities linked to agriculture, making climate-change adaptation crucial for the agricultural sector to ensure food and nutrition security. This research analyzes how institutional structures function and interact as a network to investigate the spatial coherence and relevance of public- and private-sector interventions related to agriculture, climate change, and food security in 153 municipalities of Honduras’ dry corridor. We employed a Social Network Analysis (SNA) approach to examine these interactions over the territories, revealing two network patterns: the first favors a single municipality, observed only in the Central District where Honduras’ capital is located; the second is an egocentric network, favoring a single institution, observed in four cases, particularly in municipalities bordering with El Salvador and Guatemala. The SNA results reveal a spatial misalignment, where only 9% of interventions linked to climate-change adaptation are conducted in the highly vulnerable, outlying zones located farthest from the capital. The study highlights the need for improved coordination and strategic prioritization of interventions in the most vulnerable municipalities within the Honduras dry corridor, specifically improvement in collaborative actions, use of resources, and setting strategic priorities in regions where future demand will require progressively mobilizing institutional capabilities. By identifying the current gaps and misalignments in institutional actions, this research provides valuable insights for policymakers and stakeholders to enhance collaborative efforts to ensure that climate-change adaptation measures effectively target the most vulnerable areas.