Careyibsen8025

Our work highlights the multi-causality of dispersal and that some dispersal costs can only be understood by considering extrinsic and intrinsic factors and their interaction across the entire dispersal process.With some taxa, a reduction in the mean size of individuals may reflect over-harvesting and/or trophy hunting. However, we show that in sea turtles, a reduction in the mean size of breeding individuals may be part of the good news story of an expanding population. We describe a 70-fold increase in annual nest numbers on the island of Sal (Cape Verde, North Atlantic) between 2008 and 2020 (from 506 to 35 507 nests), making this now one of the largest loggerhead (Caretta caretta) nesting aggregations in the world. We use 20 128 measurements of the size of nesting turtles to show that their mean annual size has decreased by about 2.4 cm, from 83.2 to 80.8 cm. This decrease in the mean size of nesting turtles was not caused by the removal of larger turtles, for example by selective harvesting. Rather we develop a theoretical model to show than this decrease in mean size can be explained by an influx of first-time nesters, combined with a decrease in the size of those first-time nesters over time. A reduction in mean size of nesting turtles has been reported across the Atlantic, Pacific and Indian Oceans, and may be a common feature of population recoveries in sea turtles.Dispersal is a key driver of spatial population dynamics. Dispersal behaviour may be shaped by many factors, such as mate-finding, the spatial distribution of resources, or wind and currents, yet most models of spatial dynamics assume random dispersal. We examined the spatial dynamics of a day-flying moth species (Arctia virginalis) that forms mating aggregations on hilltops (hilltopping) based on long-term adult and larval population censuses. Using time-series models, we compared spatial population dynamics resulting from empirically founded hilltop-based connectivity indices and modelled the interactive effects of temperature, precipitation and density dependence. Model comparisons supported hilltop-based connectivity metrics including hilltop elevation over random connectivity, suggesting an effect of hilltopping behaviour on dynamics. We also found strong interactive effects of temperature and precipitation on dynamics. Simulations based on fitted time-series models showed lower patch occupancy and regional synchrony, and higher colonization and extinction rates when hilltopping was included, with potential implications for the probability of persistence of the patch network. Apocynin Overall, our results show the potential for dispersal behaviour to have important effects on spatial population dynamics and persistence, and we advocate the inclusion of such non-random dispersal in metapopulation models.The accumulation of trehalose has been suggested as a mechanism underlying insect cross-tolerance to cold/freezing and drought. Here we show that exposing diapausing larvae of the drosophilid fly, Chymomyza costata to dry conditions significantly stimulates their freeze tolerance. It does not, however, improve their tolerance to desiccation, nor does it significantly affect trehalose concentrations. Next, we use metabolomics to compare the complex alterations to intermediary metabolism pathways in response to three environmental factors with different ecological meanings environmental drought (an environmental stressor causing mortality), decreasing ambient temperatures (an acclimation stimulus for improvement of cold hardiness), and short days (an environmental signal inducing diapause). We show that all three factors trigger qualitatively similar metabolic rearrangement and a similar phenotypic outcome-improved larval freeze tolerance. The similarities in metabolic response include (but are not restricted to) the accumulation of typical compatible solutes and the accumulation of energy-rich molecules (phosphagens). Based on these results, we suggest that transition to metabolic suppression (a state in which chemical energy demand is relatively low but need for stabilization of macromolecules is high) represents a common axis of metabolic pathway reorganization towards accumulation of non-toxic cytoprotective compounds, which in turn stimulates larval freeze tolerance.Inland fisheries feed greater than 150 million people globally, yet their status is rarely assessed due to their socio-ecological complexity and pervasive lack of data. Here, we leverage an unprecedented landings time series from the Amazon, Earth's largest river basin, together with theoretical food web models to examine (i) taxonomic and trait-based signatures of exploitation in inland fish landings and (ii) implications of changing biodiversity for fisheries resilience. In both landings time series and theory, we find that multi-species exploitation of diverse inland fisheries results in a hump-shaped landings evenness curve. Along this trajectory, abundant and large species are sequentially replaced with faster growing and smaller species. Further theoretical analysis indicates that harvests can be maintained for a period of time but that continued biodiversity depletion reduces the pool of compensating species and consequently diminishes fisheries resilience. Critically, higher fisheries biodiversity can delay fishery collapse. Although existing landings data provide an incomplete snapshot of long-term dynamics, our results suggest that multi-species exploitation is affecting freshwater biodiversity and eroding fisheries resilience in the Amazon. More broadly, we conclude that trends in landings evenness could characterize multi-species fisheries development and aid in assessing their sustainability.The nymphalid butterfly genus Junonia has remarkable dispersal abilities. Occurring on every continent except Europe and Antarctica, Junonia are often among the only butterflies on remote oceanic islands. The biogeography of Junonia has been controversial, plagued by taxonomic disputes, small phylogenetic datasets, incomplete taxon sampling, and shared interspecific mitochondrial haplotypes. Junonia originated in Africa but its route into the New World remains unknown. Presented here is, to our knowledge, the most comprehensive Junonia phylogeny to date, using full mitogenomes and nuclear ribosomal RNA repeats from 40 of 47 described species. Junonia is monophyletic and the genus Salamis is its probable sister clade. Genetic exchange between Indo-Pacific Junonia villida and New World Junonia vestina is evident, suggesting a trans-Pacific route into the New World. However, in both phylogenies, the sister clades to most New World Junonia contain both African and Asian species. Multiple trans-Atlantic or trans-Pacificinvasions could have contributed to New World diversification. Hybridization and lateral transfer of mitogenomes, already well-documented in New World Junonia, also occurs in at least two Old World lineages (Junonia orithya/Junonia hierta and Junonia iphita/Junonia hedonia). Variation associated with reticulate evolution creates challenges for phylogenetic reconstruction, but also may have contributed to patterns of speciation and diversification in this genus.Treehoppers of the insect family Membracidae have evolved enlarged and elaborate pronotal structures, which is hypothesized to involve co-opted expression of genes that are shared with the wings. Here, we investigate the similarity between the pronotum and wings in relation to growth. Our study reveals that the ontogenetic allometry of the pronotum is similar to that of wings in Membracidae, but not the outgroup. Using transcriptomics, we identify genes related to translation and protein synthesis, which are mutually upregulated. These genes are implicated in the eIF2, eIF4/p70S6K and mTOR pathways, and have known roles in regulating cell growth and proliferation. We find that species-specific differential growth patterning of the pronotum begins as early as the third instar, which suggests that expression of appendage patterning genes occurs long before the metamorphic molt. We propose that a network related to growth and size determination is the more likely mechanism shared with wings. However, regulators upstream of the shared genes in pronotum and wings need to be elucidated to substantiate whether co-option has occurred. Finally, we believe it will be helpful to distinguish the mechanisms leading to pronotal size from those regulating pronotal shape as we make sense of this spectacular evolutionary innovation.Gaussian processes (GPs), implemented through multivariate Gaussian distributions for a finite collection of data, are the most popular approach in small-area spatial statistical modelling. In this context, they are used to encode correlation structures over space and can generalize well in interpolation tasks. Despite their flexibility, off-the-shelf GPs present serious computational challenges which limit their scalability and practical usefulness in applied settings. Here, we propose a novel, deep generative modelling approach to tackle this challenge, termed PriorVAE for a particular spatial setting, we approximate a class of GP priors through prior sampling and subsequent fitting of a variational autoencoder (VAE). Given a trained VAE, the resultant decoder allows spatial inference to become incredibly efficient due to the low dimensional, independently distributed latent Gaussian space representation of the VAE. Once trained, inference using the VAE decoder replaces the GP within a Bayesian sampling framework. This approach provides tractable and easy-to-implement means of approximately encoding spatial priors and facilitates efficient statistical inference. We demonstrate the utility of our VAE two-stage approach on Bayesian, small-area estimation tasks.Computational modelling of the lungs is an active field of study that integrates computational advances with lung biophysics, biomechanics, physiology and medical imaging to promote individualized diagnosis, prognosis and therapy evaluation in lung diseases. The complex and hierarchical architecture of the lung offers a rich, but also challenging, research area demanding a cross-scale understanding of lung mechanics and advanced computational tools to effectively model lung biomechanics in both health and disease. Various approaches have been proposed to study different aspects of respiration, ranging from compartmental to discrete micromechanical and continuum representations of the lungs. This article reviews several developments in computational lung modelling and how they are integrated with preclinical and clinical data. We begin with a description of lung anatomy and how different tissue components across multiple length scales affect lung mechanics at the organ level. We then review common physiological and imaging data acquisition methods used to inform modelling efforts. Building on these reviews, we next present a selection of model-based paradigms that integrate data acquisitions with modelling to understand, simulate and predict lung dynamics in health and disease. Finally, we highlight possible future directions where computational modelling can improve our understanding of the structure-function relationship in the lung.