Evolution of Camouflage Drives Rapid Ecological Change in an Insect Community

SummaryBackgroundEvolutionary change in individual species has been hypothesized to have far-reaching consequences for entire ecological communities [1–3], and such coupling of ecological and evolutionary dynamics (“eco-evolutionary dynamics”) has been demonstrated for a variety systems [4–7]. However, the general importance of evolutionary dynamics for ecological dynamics remains unclear. Here, we investigate how spatial patterns of local adaptation in the stick insect Timema cristinae, driven by the interaction between multiple evolutionary processes, structure metapopulations, communities, and multitrophic interactions.ResultsObservations of a wild T. cristinae metapopulation show that locally imperfect camouflage reduces population size and that the effect of such maladaptation is comparable to the effects of more traditional ecological factors, including habitat patch size and host-plant species identity. Field manipulations of local adaptation and bird predation support the hypothesis that maladaptation reduces population size through an increase in bird predation. Furthermore, these field experiments show that maladaptation in T. cristinae and consequent increase in bird predation reduce the pooled abundance and species richness of the co-occurring arthropod community, and ultimately cascade to decrease herbivory on host plants. An eco-evolutionary model of the observational data demonstrates that the demographic cost of maladaptation decreases habitat patch occupancy by T. cristinae but enhances metapopulation-level adaptation.ConclusionsThe results demonstrate a pervasive effect of ongoing evolution in a spatial context on population and community dynamics. The eco-evolutionary model makes testable predictions about the influence of the spatial configuration of the patch network on metapopulation size and the spatial scale of adaptation

Observational evidence that maladaptive gene flow reduces patch occupancy in a wild insect metapopulation: BRIEF COMMUNICATION

Theory predicts that dispersal throughout metapopulations has a variety of consequences for the abundance and distribution of species. Immigration is predicted to increase abundance and habitat patch occupancy, but gene flow can have both positive and negative demographic consequences. Here, we address the eco-evolutionary effects of dispersal in a wild metapopulation of the stick insect Timema cristinae, which exhibits variable degrees of local adaptation throughout a heterogeneous habitat patch network of two host-plant species. To disentangle the ecological and evolutionary contributions of dispersal to habitat patch occupancy and abundance, we contrasted the effects of connectivity to populations inhabiting conspecific host plants and those inhabiting the alternate host plant. Both types of connectivity should increase patch occupancy and abundance through increased immigration and sharing of beneficial alleles through gene flow. However, connectivity to populations inhabiting the alternate host-plant species may uniquely cause maladaptive gene flow that counters the positive demographic effects of immigration. Supporting these predictions, we find the relationship between patch occupancy and alternate-host connectivity to be significantly smaller in slope than the relationship between patch occupancy and conspecific-host connectivity. Our findings illustrate the ecological and evolutionary roles of dispersal in driving the distribution and abundance of species

Local mechanical stimuli correlate with tissue growth in axolotl salamander joint morphogenesis

Movement-induced forces are critical to correct joint formation, but it is unclear how cells sense and respond to these mechanical cues. To study the role of mechanical stimuli in the shaping of the joint, we combined experiments on regenerating axolotl (Ambystoma mexicanum) forelimbs with a poroelastic model of bone rudiment growth. Animals either regrew forelimbs normally (control) or were injected with a transient receptor potential vanilloid 4 (TRPV4) agonist during joint morphogenesis. We quantified growth and shape in regrown humeri from whole-mount light sheet fluorescence images of the regenerated limbs. Results revealed significant differences in morphology and cell proliferation between groups, indicating that TRPV4 desensitization has an effect on joint shape. To link TRPV4 desensitization with impaired mechanosensitivity, we developed a finite element model of a regenerating humerus. Local tissue growth was the sum of a biological contribution proportional to chondrocyte density, which was constant, and a mechanical contribution proportional to fluid pressure. Computational predictions of growth agreed with experimental outcomes of joint shape, suggesting that interstitial pressure driven from cyclic mechanical stimuli promotes local tissue growth. Predictive computational models informed by experimental findings allow us to explore potential physical mechanisms involved in tissue growth to advance our understanding of the mechanobiology of joint morphogenesis.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 841047 and the National Science Foundation under grant no. 1727518. J.J.M. has been also funded by the Spanish Ministry of Science and Innovation under grant no. DPI2016-74929-R, and by the local government Generalitat de Catalunya under grant no. 2017 SGR 1278. K.L. was supported by a Northeastern University Undergraduate Research and Fellowships PEAK Experiences Award.Peer ReviewedPostprint (published version

Shifts in Plant Functional Composition Following Long-term Drought in Grasslands

1. Plant traits can provide unique insights into plant performance at the community scale. Functional composition, defined by both functional diversity and community-weighted trait means (CWMs), can affect the stability of above-ground net primary production (ANPP) in response to climate extremes. Further complexity arises, however, when functional composition itself responds to environmental change. The duration of climate extremes, such as drought, is expected to increase with rising global temperatures; thus, understanding the impacts of long-term drought on functional composition and the corresponding effect that has on ecosystem function could improve predictions of ecosystem sensitivity to climate change. 2. We experimentally reduced growing season precipitation by 66% across six temperate grasslands for 4 years and measured changes in three indices of functional diversity (functional dispersion, richness and evenness), community-weighted trait means and phylogenetic diversity (PD). Specific leaf area (SLA), leaf nitrogen content (LNC) and (at most sites) leaf turgor loss point (pi(TLP)) were measured for species cumulatively representing similar to 90% plant cover at each site. 3. Long-term drought led to increased community functional dispersion in three sites, with negligible effects on the remaining sites. Species re-ordering following the mortality/senescence of dominant species was the main driver of increased functional dispersion. The response of functional diversity was not consistently matched by changes in phylogenetic diversity. Community-level drought strategies (assessed as CWMs) largely shifted from drought tolerance to drought avoidance and/or escape strategies, as evidenced by higher community-weighted pi(TLP), SLA and LNC. Lastly, ecosystem drought sensitivity (i.e. relative reduction in ANPP in drought plots) was positively correlated with community-weighted SLA and negatively correlated with functional diversity. 4. Synthesis. Increased functional diversity following long-term drought may stabilize ecosystem functioning in response to future drought. However, shifts in community-scale drought strategies may increase ecosystem drought sensitivity, depending on the nature and timing of drought. Thus, our results highlight the importance of considering both functional diversity and abundance-weighted traits means of plant communities as their collective effect may either stabilize or enhance ecosystem sensitivity to drought

What Does It Take? California County Funding Requests for Recovery-Oriented Full Service Partnerships Under the Mental Health Services Act

The need to move mental health systems toward more recovery-oriented treatment modes is well established. Progress has been made to define needed changes but evidence is lacking about the resources required to implement them. The Mental Health Services Act (MHSA) in California was designed to implement more recovery-oriented treatment modes. We use data from county funding requests and annual updates to examine how counties budgeted for recovery-oriented programs targeted to different age groups under MHSA. Findings indicate that initial per-client budgeting for Full Services Partnerships under MHSA was maintained in future cycles and counties budgeted less per client for children. With this analysis, we begin to benchmark resource allocation for programs that are intended to be recovery-oriented, which should be evaluated against appropriate outcome measures in the future to determine the degree of recovery-orientation

Genome-Wide Association Mapping of Phenotypic Traits Subject to a Range of Intensities of Natural Selection in Timema cristinae*

abstract: The genetic architecture of adaptive traits can reflect the evolutionary history of populations and also shape divergence among populations. Despite this central role in evolution, relatively little is known regarding the genetic architecture of adaptive traits in nature, particularly for traits subject to known selection intensities. Here we quantitatively describe the genetic architecture of traits that are subject to known intensities of differential selection between host plant species in Timema cristinae stick insects. Specifically, we used phenotypic measurements of 10 traits and 211,004 single-nucleotide polymorphisms (SNPs) to conduct multilocus genome-wide association mapping. We identified a modest number of SNPs that were associated with traits and sometimes explained a large proportion of trait variation. These SNPs varied in their strength of association with traits, and both major and minor effect loci were discovered. However, we found no relationship between variation in levels of divergence among traits in nature and variation in parameters describing the genetic architecture of those same traits. Our results provide a first step toward identifying loci underlying adaptation in T. cristinae. Future studies will examine the genomic location, population differentiation, and response to selection of the trait-associated SNPs described here

Detecting modification of biomedical events using a deep parsing approach

<p>Abstract</p> <p>Background</p> <p>This work describes a system for identifying event mentions in bio-molecular research abstracts that are either speculative (e.g. <it>analysis of IkappaBalpha phosphorylation</it>, where it is not specified whether phosphorylation did or did not occur) or negated (e.g. <it>inhibition of IkappaBalpha phosphorylation</it>, where phosphorylation did <it>not </it>occur). The data comes from a standard dataset created for the BioNLP 2009 Shared Task. The system uses a machine-learning approach, where the features used for classification are a combination of shallow features derived from the words of the sentences and more complex features based on the semantic outputs produced by a deep parser.</p> <p>Method</p> <p>To detect event modification, we use a Maximum Entropy learner with features extracted from the data relative to the trigger words of the events. The shallow features are bag-of-words features based on a small sliding context window of 3-4 tokens on either side of the trigger word. The deep parser features are derived from parses produced by the English Resource Grammar and the <it>RASP </it>parser. The outputs of these parsers are converted into the Minimal Recursion Semantics formalism, and from this, we extract features motivated by linguistics and the data itself. All of these features are combined to create training or test data for the machine learning algorithm.</p> <p>Results</p> <p>Over the test data, our methods produce approximately a 4% absolute increase in F-score for detection of event modification compared to a baseline based only on the shallow bag-of-words features.</p> <p>Conclusions</p> <p>Our results indicate that grammar-based techniques can enhance the accuracy of methods for detecting event modification.</p

Treatment effect of switching from intravenous to subcutaneous C1-inhibitor for prevention of hereditary angioedema attacks: COMPACT subgroup findings

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Taxonomy of the order Mononegavirales : update 2016

In 2016, the order Mononegavirales was emended through the addition of two new families (Mymonaviridae and Sunviridae), the elevation of the paramyxoviral subfamily Pneumovirinae to family status (Pneumoviridae), the addition of five free-floating genera (Anphevirus, Arlivirus, Chengtivirus, Crustavirus, and Wastrivirus), and several other changes at the genus and species levels. This article presents the updated taxonomy of the order Mononegavirales as now accepted by the International Committee on Taxonomy of Viruses (ICTV)

Multimodal surface-based morphometry reveals diffuse cortical atrophy in traumatic brain injury.

<p>Abstract</p> <p>Background</p> <p>Patients with traumatic brain injury (TBI) often present with significant cognitive deficits without corresponding evidence of cortical damage on neuroradiological examinations. One explanation for this puzzling observation is that the diffuse cortical abnormalities that characterize TBI are difficult to detect with standard imaging procedures. Here we investigated a patient with severe TBI-related cognitive impairments whose scan was interpreted as normal by a board-certified radiologist in order to determine if quantitative neuroimaging could detect cortical abnormalities not evident with standard neuroimaging procedures.</p> <p>Methods</p> <p>Cortical abnormalities were quantified using multimodal surfaced-based morphometry (MSBM) that statistically combined information from high-resolution structural MRI and diffusion tensor imaging (DTI). Normal values of cortical anatomy and cortical and pericortical DTI properties were quantified in a population of 43 healthy control subjects. Corresponding measures from the patient were obtained in two independent imaging sessions. These data were quantified using both the average values for each lobe and the measurements from each point on the cortical surface. The results were statistically analyzed as z-scores from the mean with a p < 0.05 criterion, corrected for multiple comparisons. False positive rates were verified by comparing the data from each control subject with the data from the remaining control population using identical statistical procedures.</p> <p>Results</p> <p>The TBI patient showed significant regional abnormalities in cortical thickness, gray matter diffusivity and pericortical white matter integrity that replicated across imaging sessions. Consistent with the patient's impaired performance on neuropsychological tests of executive function, cortical abnormalities were most pronounced in the frontal lobes.</p> <p>Conclusions</p> <p>MSBM is a promising tool for detecting subtle cortical abnormalities with high sensitivity and selectivity. MSBM may be particularly useful in evaluating cortical structure in TBI and other neurological conditions that produce diffuse abnormalities in both cortical structure and tissue properties.</p