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  • The genus Corbicula consists of estuarine or freshwater clams native to temperate/tropical regions of Asia, Africa, and Australia that collectively encompass both sexual species and clonal (androgenetic) lineages. The latter have become globally invasive in freshwater systems and they represent some of the most successful aquatic invasive lineages. Previous studies have documented four invasive clonal lineages, Forms A, B, C, and Rlc, with varying known distributions. Form A (R in Europe) occurs globally, Form B is found solely in North America, mainly the western United States, Form C (S in Europe) occurs both in European watersheds and in South America, and Rlc is known from Europe. A putative fifth invasive morph, Form D, was recently described in the New World from the Illinois River (Great Lakes watershed), where it occurs in sympatry with Forms A and B. An initial study showed Form D to be conchologically distinct: possessing rust-colored rays and white nacre with purple teeth. However, its genetic distinctiveness using standard molecular markers (mitochondrial cytochrome c oxidase subunit I and nuclear ribosomal 28S RNA) was ambiguous. To resolve this issue, we performed a phylogenomic analysis using 1,699-30,027 nuclear genomic loci collected via the next generation double digested restriction-site associated DNA sequencing method. Our results confirmed Form D to be a distinct invasive New World lineage with a population genomic profile consistent with clonality. A majority (7/9) of the phylogenomic analyses recovered the four New World invasive Corbicula lineages (Forms A, B, C, and D) as members of a clonal clade, sister to the non-clonal Lake Biwa (Japan) endemic, C. sandai. The age of the clonal clade was estimated at 1.49 million years (my; ± 0.401– 2.955 my) whereas the estimated ages of the four invasive lineage crown clades ranged from 0.27-0.44 my. We recovered no evidence of nuclear genomic admixture among the four invasive lineages in our study populations. In contrast, 2/6 C. sandai individuals displayed partial nuclear genomic Structure assignments with multiple invasive clonal lineages. These results provide new insights into the origin and maintenance of clonality in this complex system.
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  • Fish spawning aggregations (FSA) act as biological hotspots that concentrate food and nutrients across a broad trophic spectrum. In Pohnpei (Federated States of Micronesia), 20 female grey reef sharks (Carcharhinus amblyrhynchos) were acoustically tagged at two multi-species grouper (Epinephelidae) FSA to examine the likelihood that these mesopredators utilize FSA as a seasonal food source. Both FSA sites are within small-scale MPAs, thus providing a secondary opportunity to examine their conservation potential during these ephemeral events. Shark movement and residency was gauged against known spatial and temporal grouper reproductive patterns using an array of 15 and 50 acoustic receivers at Ant Atoll and Pohnpei (Island), respectively. Activity space was investigated using Kernel Density estimates of individual sharks, and residency indices (RI) were analyzed based on daily and monthly occurrence at the array. Three distinct residency patterns were identified: transient, semi-transient, or resident (Daily RI 0.400.80, respectively). Generalized linear mixed models (GLMMs) were used to identify biological and environmental factors influencing shark activity space, including month, temperature, shark size, spawning month, and residency pattern. Findings revealed significant changes in average monthly residency indices and kernel densities during spawning months in support of an opportunistic foraging strategy around FSA. Monthly residency was higher during spawning months among semi-resident and transient sharks, while average monthly activity space was concentrated around FSA. Best-fit models for the GLMM indicated that activity spaces were most influenced by month and grouper spawning month. Seven of 20 sharks demonstrated inter-island movement and wide variations in individual movement and spatial requirements were shown. The concentration of sharks and groupers at unprotected FSA sites increases their vulnerability to fishing and supports the need for combined area and non-area management measures to effectively protect these species.
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  • Many vertebrates exhibit cranial kinesis, or movement between bones of the skull other than at the jaw joint. Many kinetic species possess a particular suite of features to accomplish this movement, including flexible cranial joints and protractor musculature. Whereas the skeletal anatomy of these kinetic systems is well understood, how these joints are biomechanically loaded, how different soft tissues affect joint loading and kinetic capacity, and how the protractor musculature loads the skull remain poorly understood. Here we developed a Finite Element Model of the savannah monitor, Varanus exanthematicus, a modestly kinetic lizard, to better elucidate the roles of soft tissue in mobile joints and protractor musculature on cranial loading. We described the 3D resultants of jaw muscles and histology of palatobasal, otic and jaw joints. We tested the effects of joint tissue types, bite point, and muscle loads to evaluate the biomechanical role of muscles have on the palate and braincase. We found the jaw muscles have significant mediolateral components and resultants that can impart stability across palatocranial joints. We found articular tissues affect the magnitude of strains experienced across the palatobasal and otic joints. We found that without protractor muscle loading, the palate, quadrate and braincase experience higher strains suggesting this muscle helps insulate the braincase and palatoquadrate from high loads. Finally, we found the cross-sectional properties of the bones of Varanus exanthematicus is well suited for performing under torsional loads. These findings suggest that torsion may be a significant driver in the evolution of cranial kinesis in lepidosaurs.
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  • Learning is a widespread ability among animals and, like physical traits, is subject to evolution. But how did learning first arise? What selection pressures and phenotypic preconditions fostered its evolution? Neither the fossil record nor phylogenetic comparative studies provide answers to these questions. Here, we take a novel approach by studying digital organisms in environments that promote the evolution of navigation and associative learning. Starting with a non-learning, sessile ancestor, we evolve multiple populations in four different environments, each consisting of nutrient trails with various layouts. Trail nutrients cue organisms on which direction to follow, provided they evolve to acquire and use those cues. Thus, each organism is tested on how well it navigates a randomly selected trail before reproducing. We find that behavior evolves modularly and in a predictable sequence, where simpler behaviors are necessary precursors for more complex ones. Associative learning is only one of many successful behaviors to evolve, and its origin depends on the environment possessing certain information patterns that organisms can exploit. Environmental patterns that are stable across generations foster the evolution of reflexive behavior, while environmental patterns that vary across generations, but remain consistent for periods within an organism’s lifetime, foster the evolution of learning behavior. Both types of environmental patterns are necessary, since the prior evolution of simple reflexive behaviors provides the building blocks for learning to arise. Finally, we observe that an intrinsic value system evolves alongside behavior and supports associative learning by providing reinforcement for behavior conditioning.
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  • Background: Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of behaviour recognition, even though accelerometers have been used extensively, magnetometers have recently been shown to detect specific behaviours that accelerometers miss. The prevalent constraint of limited training data necessitates the importance of identifying behaviours with high robustness to data from new individuals, and may require fusing data from both these sensors. However, no study yet has developed an end-to-end approach to recognise common animal behaviours such as foraging, locomotion, and resting from magnetometer data in a common classification framework capable of accommodating and comparing data from both sensors. Methods: We address this by first leveraging magnetometers’ similarity to accelerometers to develop biomechanical descriptors of movement: we use the static component given by sensor tilt with respect to Earth’s local magnetic field to estimate posture, and the dynamic component given by change in sensor tilt with time to characterise movement intensity and periodicity. We use these descriptors within an existing hybrid scheme that combines biomechanics and machine learning to recognise behaviour. We showcase the utility of our method on triaxial magnetometer data collected on ten wild Kalahari meerkats (Suricata suricatta), with annotated video recordings of each individual serving as groundtruth. Finally, we compare our results with accelerometer-based behaviour recognition. Results: The overall recognition accuracy of >94% obtained with magnetometer data was found to be comparable to that achieved using accelerometer data. Interestingly, higher robustness to inter-individual variability in dynamic behaviour was achieved with the magnetometer, while the accelerometer was better at estimating posture. Conclusions: Magnetometers were found to accurately identify common behaviours, and were particularly robust to dynamic behaviour recognition. The use of biomechanical considerations to summarise magnetometer data makes the hybrid scheme capable of accommodating data from either or both sensors within the same framework according to each sensor’s strengths. This provides future studies with a method to assess the added benefit of using magnetometers for behaviour recognition.
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  • Many birds vocalize in flight. Since wingbeat and respiratory cycles are often linked in flying vertebrates, birds in these cases must satisfy the respiratory demands of vocal production within the physiological limits imposed by flight. Using acoustic triangulation and high-speed video, we found that avian vocal production in flight exhibits a largely phasic and kinematic relationship with the power stroke. However, the sample of species showed considerable flexibility, especially those from lineages known for vocal plasticity (songbirds, parrots and hummingbirds), prompting a broader phylogenetic analysis. We thus collected data from 150 species across 12 avian orders and examined the links between wingbeat period, flight call duration and body mass. Overall, shorter wingbeat periods, controlling for ancestry and body mass, were correlated with shorter flight call durations. However, species from vocal learner lineages produced flight signals that, on average, exceeded multiple phases of their wingbeat cycle, while vocal non-learners had signal periods that were, on average, closer to the duration of their power stroke. These results raise an additional question: is partial emancipation from respiratory constraints a necessary step in the evolution of vocal learning or an epiphenomenon? Our current study cannot provide the answer, but it does suggest several avenues for future research.
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  • Aims: Phylogenies are increasingly used in community ecology, biogeography and macroecology. However, sourcing a phylogeny comprising the entire species pool for a focal region can be difficult. Typically, a bespoke phylogeny must be created requiring considerable data manipulation and the use of many standalone software. Here we present a suite of methodological tools within the popular R environment that help to build molecular phylogenies appropriate for ecological studies with a regional focus. Innovation: Our R package regPhylo provides a pipeline to construct a Bayesian posterior distribution of time-calibrated trees suitable to address ecological questions. The novel contributions of regPhylo include options to: use prior phylogenetic knowledge through flexible topological constraints; include spatial metadata in sourcing DNA sequences; and include taxa without DNA sequences and then infer consequent phylogenetic uncertainty. Specifically, regPhylo helps researchers: retrieve DNA sequences; enhance available metadata; select DNA sequences based on their length or spatial proximity to the region of study; align sequences; and perform quality control. Output from the pipeline is a file ready to run in the Bayesian tree reconstruction software BEAST2, appropriate for estimating time-calibrated trees and including phylogenetic uncertainty for downstream analyses. Main conclusions: Overall, regPhylo improves the integration of popular standalone phylogenetic software into the flexible R environment. It provides a novel approach to include topological constraints based on prior knowledge, include taxa without DNA sequences, and select spatially appropriate DNA sequences. When coupled with a Bayesian tree-building process, our approach provides estimates of uncertainty in both topology and branch-lengths. We demonstrate the utility of the package by constructing a posterior distribution of time-calibrated phylogenies for the New Zealand marine ray-finned fishes (Actinopterygii) providing the unprecedented opportunity to include phylogenetic information in downstream ecological analyses for marine fishes in this region.
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  • How can we explain morphological variations in a holobiont? The genetic determinism of phenotypes is not always obvious and could be circumstantial in complex organisms. In symbiotic cnidarians, it is known that morphology or colour can misrepresent a complex genetic and symbiotic diversity. Anemonia viridis is a symbiotic sea anemone from temperate seas. This species displays different colour morphs based on pigment content and lives in a wide geographical range. Here, we investigated whether colour morph differentiation correlated with host genetic diversity or associated symbiotic genetic diversity by using RAD-sequencing and symbiotic dinoflagellate typing of 140 sea anemones from the English Channel and the Mediterranean Sea. We did not observe genetic differentiation among colour morphs of A. viridis at the animal host or symbiont level, rejecting the hypothesis that A. viridis colour morphs correspond to species level differences. Interestingly, we however identified at least four independent animal host genetic lineages in A. viridis that differed in their associated symbiont populations. In conclusion, although the functional role of the different morphotypes of A. viridis remains to be determined, our approach provides new insights on the existence of cryptic species within A. viridis.
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  • 1. Co-infections with multiple parasite taxa are ubiquitous in nature and have the potential to impact the co-evolutionary dynamics between host and parasite, though patterns of phylogenetic community structure of co-infecting parasites and the processes that generate these patterns have rarely been studied across diverse host-parasite communities. 2. Here, we tested for the roles of host and parasite evolutionary history as well as environmental variables as drivers of phylogenetic community structure among co-infecting haemosporidian (malaria) parasites and their avian hosts in the North American boreal forest, a region characterized by an extraordinarily high blood parasite co-infection rate. 3. We used multiple methods to identify non-random patterns of co-infection among parasite species and determined whether these patterns were influenced more by co-evolutionary host associations or environmental variables. We used model-based approaches to test whether parasites that occurred together in a single host individual exhibited phylogenetic clustering or overdispersion. Lastly, we tested whether the observed phylogenetic community structure could be explained by parasites having convergently evolved similar patterns of host associations. 4. We found that haemosporidian parasite co-infections occurred at a high frequency in the boreal forest system, and that parasite taxa co-occurred in significantly non-random patterns within host individuals and among host species. Parasite taxa that occurred in co-infections tended to be phylogenetically overdispersed. We show that this pattern of phylogenetic overdispersion can be attributed largely to the effect of evolutionarily labile, convergent host associations that have resulted in the pool of parasites that have the potential to infect a given host consisting nearly exclusively of distantly related lineages. 5. Our findings illustrate that environmental filtering of convergent traits can produce phylogenetically overdispersed communities, even at the level of co-infecting parasites within an individual host organism. Broadly, this analysis illustrates how co-evolutionary history can have a strong influence on the modern phylogenetic community assembly of diverse host-symbiont communities.
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  • Complex ethological behaviors could be constructed from finite modules that are reproducible functional units of behavior. Here, we test this idea for foraging and develop methods to dissect rich behavior patterns in mice. We uncover discrete modules of foraging behavior reproducible across different strains and ages, as well as nonmodular behavioral sequences. Modules differ in terms of form, expression frequency, and expression timing and are expressed in a probabilistically determined order. Modules shape economic patterns of feeding, exposure, activity, and perseveration responses. The modular architecture of foraging changes developmentally, and different developmental, genetic, and parental effects are found to shape the expression of specific modules. Dissecting modules from complex patterns is powerful for phenotype analysis. We discover that both parental alleles of the imprinted Prader-Willi syndrome gene Magel2 are functional in mice but regulate different modules. Our study found that complex economic patterns are built from finite, genetically controlled modules.
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