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Understanding how both the mean (location) and variance (scale) of traits differ among species and lineages is fundamental to unveiling macroevolutionary patterns. Yet, traditional phylogenetic comparative methods primarily focus on modelling mean trait values, often overlooking variability and heteroscedasticity that can provide critical insights into evolutionary dynamics. Here, we introduce phylogenetic location–scale models (PLSMs), a novel framework that jointly analyses the evolution of trait means and variances. This dual approach captures heteroscedasticity and evolutionary changes in trait variability, allowing for the detection of clades with differing variances and revealing patterns of adaptation, diversification, and evolutionary constraints. Extending PLSMs to a multivariate context enables simultaneous analysis of multiple traits and their covariances, facilitating the testing of hypotheses about evolutionary trade‐offs, pleiotropy and phenotypic integration. By modelling covariances between phylogenetic effects in both the location and scale parts, we can discern whether changes in one trait's mean or variance are associated with changes in another's, thereby offering deeper insights into the mechanisms driving trait co‐evolution and co‐divergence or ‘contra‐divergence’. We also describe how an extended version of PLSMs incorporating within‐species variability can enhance our understanding of trait convergence and divergence arising from ecological and environmental factors. Our framework provides a powerful tool for exploring macroevolutionary patterns and can be used to reassess previously published comparative data, offering new insights into the mechanisms driving the diversity of life.

Issue Title: Special Issue: Approach/Avoidance Approach motivation is the energization of behavior by, or the direction of behavior toward, positive stimuli (objects, events, possibilities), whereas avoidance motivation is the energization of behavior by, or the direction of behavior away from, negative stimuli (objects, events, possibilities). In this article, I provide a brief overview of this distinction between approach and avoidance motivation. In addition, I provide a brief overview of a model of motivation in which this approach-avoidance distinction plays an integral role--the hierarchical model of approach-avoidance motivation.[PUBLICATION ABSTRACT]

PurposeThere are notable geographic variations in incidence rates of suicide both in Japan and globally. Previous studies have found that rurality/urbanity shapes intra-regional differences in suicide mortality, and suicide risk associated with rurality can vary significantly by gender and age. This study aimed to examine spatial patterning of and rural–urban differences in suicide mortality by gender and age group across 1887 municipalities in Japan between 2009 and 2017.MethodsSuicide data were obtained from suicide statistics of the Ministry of Health, Labour and Welfare in Japan. We estimated smoothed standardized mortality ratios for suicide for each of the municipalities and investigated associations with level of rurality/urbanity using Bayesian hierarchical models before and after adjusting for socioeconomic characteristics.ResultsThe results of the multivariate analyses showed that, for males aged 0–39 and 40–59 years, rural residents tended to have a higher suicide risk compared to urban ones. For males aged 60+ years, a distinct rural–urban gradient in suicide risk was not observed. For females aged 0–39 years, a significant association between suicide risk and rurality was not observed, while for females aged 40–59 years and females aged 60 years or above, the association was a U-shaped curve.ConclusionOur results showed that geographical distribution of and rural–urban differences in suicide mortality in Japan differed substantially by gender and age. These findings suggest that it is important to take demographic factors into consideration when municipalities allocate resources for suicide prevention.

1. Savanna ecosystems are defined largely by tree-grass mixtures, and tree establishment is a key driver of community structure and ecosystem function in these systems. The factors controlling savanna tree establishment are understudied, but likely involve some combination of seed, microsite and predator/fire limitation. In African savannas, suppression and killing of adult trees by large mammals like elephants (Loxodonta africana Blumenbach, 1797) and giraffes (Giraffa camelopardalis Linnaeus, 1758) can maintain tree-grass co-dominance, although the impacts of even these conspicuous herbivores on tree establishment also are poorly understood. 2. We combined seed addition and predator exclusion experiments with a large-scale, long-term field manipulation of large herbivores to investigate the relative importance of seeds, microsites and predators in limiting establishment of a monodominant tree (Acacia drepanolobium Sjostedt) in a Kenyan savanna. 3. Both wild and domestic (i.e. cattle; Bos taurus Linnaeus, 1758) large herbivores facilitated tree establishment by suppressing abundances of rodents, the most important seed and seedling predators. However, this indirect, positive effect of wild herbivores was negated by wild herbivores' suppression of seed production. Cattle did not have this direct, negative impact; rather, they further assisted tree establishment by reducing cover of understorey grasses. Thus, the impacts of both groups of large herbivores on tree establishment were largely routed through other taxa, with a negligible net effect of wild herbivores and a positive net effect of cattle on tree establishment. 4. The distinction between the (positive) net effect of cattle and (neutral) net effect of wild herbivores is due to the inclusion of browsers and mixed feeders within the assemblage of wild herbivores. Browsing by wild herbivores limited seed production, which reduced tree recruitment; grazing by cattle was more pronounced than that by wild herbivores, and thus promoted germination and subsequent establishment of small trees. 5. Our study is the first to link seed fates to tree establishment in savanna ecosystems in experimentally-manipulated herbivore communities. Further, our results highlight how large herbivores can modify a suite of independent factors -seed production, competition with understorey species, and seed and seedling predation -to collectively drive tree establishment.

Evidence of climate-change-drivenshifts in plant and animal phenology haveraised concerns that certain trophic interactions may be increasingly mismatched in time,resultingin declines in reproductive success. Given the constraints imposed by extreme seasonalityat high latitudes and the rapid shifts in phenology seen in the Arctic, we would also expectAntarctic species to be highly vulnerable to climate-change-drivenphenological mismatcheswith their environment. However, few studies have assessed the impacts of phenological changein Antarctica. Using the largest database of phytoplankton phenology, sea-icephenology, andAdélie Penguin breeding phenology and breeding success assembled to date, we find that, whilea temporal match between Penguin breeding phenology and optimal environmental conditionssets an upper limit on breeding success, only a weak relationship to the mean exists. Despiteprevious work suggesting that divergent trends in Adélie Penguin breeding phenology areapparentacross the Antarctic continent, we find no such trends. Furthermore, we find no trendin the magnitude of phenological mismatch, suggesting that mismatch is driven by interannualvariability in environmental conditions rather than climate-change-driventrends, as observed inother systems. We propose several criteria necessary for a species to experience a strong climate-change-drivenphenological mismatch, of which several may be violated by this system

Predicting biotic responses to environmental change requires understanding the joint effects of abiotic conditions and biotic interactions on community dynamics. One major challenge is to separate the potentially confounding effects of abiotic environmental variation and local biotic interactions on individual performance. The stress gradient hypothesis (SGH) addresses this issue directly by predicting that the effects of biotic interactions on performance become more positive as the abiotic environment becomes more stressful. It is unclear, however, how the predictions of the SGH apply to plants of differing functional strategies in diverse communities. We asked (1) how the effect of crowding on performance (growth and survival) of trees varies across a precipitation gradient, and (2) how functional strategies (as measured by two key traits: wood density and leaf mass per area, LMA) mediate average demographic rates and responses to crowding across the gradient. We built trait-based neighborhood models of growth and survival across a regional precipitation gradient where increasing precipitation is associated with reduced abiotic stress. In total, our dataset comprised ∼170,000 individual trees belonging to 252 species. The effect of crowding on tree performance varied across the gradient; crowding negatively affected growth across plots and positively affected survival in the wettest plot. Functional traits mediated average demographic rates across the gradient, but we did not find clear evidence that the strength of these responses depends on species’ traits. Our study lends support to the SGH and demonstrates how a trait-based perspective can advance these concepts by linking the diversity of species interactions with functional variation across abiotic gradients.

The present work aims to compare results in aircraft joints, focusing on spar and skin regions, considering two levels of detail to understand the differences in the structural response using different types of modeling (numerical and semi-amalytical Rutman approach). Several studies were already performed to obtain the correct understanding of how actual loads are distributed through the joints. Finite Element Analysis modeling made using Nastran software were performed here. The study has shown the differences between the models analyzed by comparing the stiffness of the fasteners at the specific region analyzed. Results indicate good agreement between models for translational stiffness and more significant differences for rotational stiffness. The finite elements model with high level of detail presents larger rotational stiffness when compared with the Rutman approach.

Occupancy estimation is an effective analytic framework, but requires repeated surveys of a sample unit to estimate the probability of detection. Detection rates can be estimated from spatially replicated rather than temporally replicated surveys, but this may violate the closure assumption and result in biased estimates of occupancy. We present a new application of a multi-scale occupancy model that permits the simultaneous use of presence–absence data collected at 2 spatial scales and uses a removal design to estimate the probability of detection. Occupancy at the small scale corresponds to local territory occupancy, whereas occupancy at the large scale corresponds to regional occupancy of the sample units. Small-scale occupancy also corresponds to a spatial availability or coverage parameter where a species may be unavailable for sampling at a fraction of the survey stations. We applied the multi-scale occupancy model to a hierarchical sample design for 2 bird species in the Black Hills National Forest: brown creeper (Certhia americana) and lark sparrow (Chondestes grammacus). Our application of the multi-scale occupancy model is particularly well suited for hierarchical sample designs, such as spatially replicated survey stations within sample units that are typical of avian monitoring programs. The model appropriately accounts for the non-independence of the spatially replicated survey stations, addresses the closure assumption for the spatially replicated survey stations, and is useful for decomposing the observation process into detection and availability parameters. This analytic approach is likely to be useful for monitoring at local and regional scales, modeling multi-scale habitat relationships, and estimating population state variables for rare species of conservation concern.

Background The analysis of correlated binary data is commonly addressed through the use of conditional models with random effects included in the systematic component as opposed to generalized estimating equations (GEE) models that addressed the random component. Since the joint distribution of the observations is usually unknown, the conditional distribution is a natural approach. Our objective was to compare the fit of different binary models for correlated data in Tabaco use. We advocate that the joint modeling of the mean and dispersion may be at times just as adequate. We assessed the ability of these models to account for the intraclass correlation. In so doing, we concentrated on fitting logistic regression models to address smoking behaviors. Methods Frequentist and Bayes’ hierarchical models were used to predict conditional probabilities, and the joint modeling (GLM and GAM) models were used to predict marginal probabilities. These models were fitted to National Longitudinal Study of Adolescent to Adult Health (Add Health) data for Tabaco use. Results We found that people were less likely to smoke if they had higher income, high school or higher education and religious. Individuals were more likely to smoke if they had abused drug or alcohol, spent more time on TV and video games, and been arrested. Moreover, individuals who drank alcohol early in life were more likely to be a regular smoker. Children who experienced mistreatment from their parents were more likely to use Tabaco regularly. Conclusions The joint modeling of the mean and dispersion models offered a flexible and meaningful method of addressing the intraclass correlation. They do not require one to identify random effects nor distinguish from one level of the hierarchy to the other. Moreover, once one can identify the significant random effects, one can obtain similar results to the random coefficient models. We found that the set of marginal models accounting for extravariation through the additional dispersion submodel produced similar results with regards to inferences and predictions. Moreover, both marginal and conditional models demonstrated similar predictive power.

Despite increasing demand of application specific requirements in wireless sensor networks, lots of research is still going on under assumption of general requirement without considering specific traffic model as well as several constraints. To address this issue, we have already introduced a new real-time application with ( m , k )-firm model and developed communication protocols for multimedia sensor networks. But, scalability problem and lack of architecture for ( m , k )-firm stream are major research challenges that remain unsolved. Based on corresponding demands, in this paper, we propose a new integrated architecture for ( m , k )-firm stream in wireless sensor networks with following functions, that is, flow aggregation based on compositional hierarchical model, velocity based routing protocol, hybrid medium access control protocol, and congestion control scheme. Simulation results are given to prove the suitability of the architecture and performance improvement under several scenarios.