Evolutionary change in continuous reaction norms

Abstract Understanding the evolution of reaction norms remains a major challenge in ecology and evolution. Investigating evolutionary divergence in reaction norm shapes between populations and closely related species is one approach to providing insights. Here we use a meta-analytic approach to compare divergence in reaction norms of closely related species or populations of animals and plants across types of traits and environments. We quantified mean-standardized differences in overall trait means (Offset) and reaction norm shape (including both Slope and Curvature). These analyses revealed that differences in shape (Slope and Curvature together) were generally greater than differences in Offset. Additionally, differences in Curvature were generally greater than differences in Slope. The type of taxon contrast (species vs. population), trait, organism, and the type and novelty of environments all contributed to the best-fitting models, especially for Offset, Curvature, and the total differences (Total) between reaction norms. Congeneric species had greater differences in reaction norms than populations, and novel environmental conditions increased the differences in reaction norms between populations or species. These results show that evolutionary divergence of curvature is common and should be considered an important aspect of plasticity, together with slope. Biological details about traits and environments, including cryptic variation expressed in novel environmental conditions, may be critical to understanding how reaction norms evolve in novel and rapidly changing environments

Undergraduates Phenotyping Arabidopsis Knockouts in a Course-Based Undergraduate Research Experience: Exploring Plant Fitness and Vigor Using Quantitative Phenotyping Methods †

We present a curriculum description, an initial student outcome investigation, and sample scientific results for a representative Course-Based Undergraduate Research Experience (CURE) that is part of the &ldquo;Undergraduates Phenotyping Arabidopsis Knockouts&rdquo; (unPAK) network. CUREs in the unPAK network characterize quantitative phenotypes of the model plant Arabidopsis from across environments to uncover connections between genotype and phenotype. Students in unPAK CUREs grow plants in a replicated block design and make quantitative measurements throughout the semester. This CURE enables students to answer plant science questions that draw from fields such as environmental science, genetics, ecology, and evolution. Findings indicate that this experience provides students with opportunities to make relevant scientific discoveries. Eighty percent of student datasets produced from the CURE met criteria for inclusion in the project database, indicative of student learning in data collection and analysis of quantitative plant traits. Student datasets uncovered novel effects of mutation on plant form. In addition, students&rsquo; science self-efficacy increased as a result of course participation, and faculty feedback on course implementation was positive. We present unPAK as a new network that supports CUREs and research experiences focused on collecting biological data made publicly available to the scientific community. The unPAK CUREs can be tailored to address instructor interests or pedagogical needs while involving students in research investigating quantitative plant phenotypes.</p

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Developmental phenotypic plasticity: where ecology and evolution meet molecular biology

An exploration of the nexus between ecology, evolutionary biology and molecular biology, via the concept of phenotypic plasticity

Appendix B. Pearson product-moment correlation coefficients for all traits measured in the greenhouse experiments.

Pearson product-moment correlation coefficients for all traits measured in the greenhouse experiments

Seasonal patterns of native plant cover and leaf trait variation on New York City green roofs: Data

These data include all plant trait data, percent green cover, and plant community data used in Yee et al. 2022. Files also include R-ready code and dataframes used to analyze these data. Article abstract: Plants make important contributions to green roof ecosystem service provision through evapotranspiration, canopy shading, and water retention. Because these plant communities are a critical component of green roof design and function, both seasonal and interspecific variation of these plant communities are important factors in evaluating green roof performance. This study examines variation in both species abundance and 9 leaf traits throughout the 2015 growing season of four New York City green roofs. While community composition varied significantly between each month (pANOSIM = 0.036), three major plant families (Asteraceae, Lamiaceae, and Poaceae) consistently had the greatest green cover and were present during the entirety of the growing season. For leaf traits, period of the growing season had a significant impact on most of the traits measured. Leaf thickness, leaf relative water content (RWC) and saturated water content (SWC) decreased as the growing season progressed, while leaf dry matter content (LDMC) and stomatal density increased, likely due to a seasonal decrease in rainfall as species-level variance in these water traits is low (7.40% and 0.88%, respectively). We also ranked planted and spontaneous species in accordance to both cover and functional trait values, and identified 11 species suitable for green roofs in NYC: Pycnanthemum tenuifolium (Lamiaceae), Symphiotrichum leave, Symphiotrichum pilosum, Rudbeckia hirta, Solidago odora (Asteraceae), Panicum virgatum, Sorghastrum nutrans, Schizachyrium scoparium, Dichanthelium clandestinum, Deschampsia flexuosa (Poaceae), and Oenothera biennis (Onagraceae). Understanding the temporal responses of plant communities and their constituent species is critical in optimizing green roof ecosystem services

Evolutionary Change in Continuous Reaction Norms

Understanding the evolution of reaction norms remains a major challenge in ecology and evolution. Investigating evolutionary divergence in reaction norm shapes between populations and closely related species is one approach to providing insights. Here w

Data from: Evolutionary change in continuous reaction norms

Understanding the evolution of reaction norms remains a major challenge in ecology and evolution. Investigating evolutionary divergence in reaction norm shapes between populations and closely related species is one approach to provide insights. Here we use a meta-analytic approach to compare divergence in reaction norms of closely related species or populations of animals and plants, across types of traits and environments. We quantified mean-standardized differences in overall trait means (Offset) and reaction norm shape (including both Slope and Curvature). These analyses revealed that differences in shape (Slope and Curvature together) were generally greater than differences in Offset. Additionally, differences in Curvature were generally greater than differences in Slope. The type of taxon contrast (species vs. population), trait, organism, and the type and novelty of environments all contributed to the best fitting models, especially for Offset, Curvature and the total differences (Total) between reaction norms. Congeneric species had greater differences in reaction norms than populations, and novel environmental conditions increased the differences in reaction norms between populations or species. These results show that evolutionary divergence of curvature is common and should be considered an important aspect of plasticity together with slope. Biological details about traits and environments, including cryptic variation expressed in novel environmental conditions, may be critical to understanding how reaction norms may evolve in novel and rapidly changing environments

Constraints on the evolution of phenotypic plasticity:Limits and costs of phenotype and plasticity

Phenotypic plasticity is ubiquitous and generally regarded as a key mechanism for enabling organisms to survive in the face of environmental change. Because no organism is infinitely or ideally plastic, theory suggests that there must be limits (for example, the lack of ability to produce an optimal trait) to the evolution of phenotypic plasticity, or that plasticity may have inherent significant costs. Yet numerous experimental studies have not detected widespread costs. Explicitly differentiating plasticity costs from phenotype costs, we re-evaluate fundamental questions of the limits to the evolution of plasticity and of generalists vs specialists. We advocate for the view that relaxed selection and variable selection intensities are likely more important constraints to the evolution of plasticity than the costs of plasticity. Some forms of plasticity, such as learning, may be inherently costly. In addition, we examine opportunities to offset costs of phenotypes through ontogeny, amelioration of phenotypic costs across environments, and the condition-dependent hypothesis. We propose avenues of further inquiry in the limits of plasticity using new and classic methods of ecological parameterization, phylogenetics and omics in the context of answering questions on the constraints of plasticity. Given plasticity's key role in coping with environmental change, approaches spanning the spectrum from applied to basic will greatly enrich our understanding of the evolution of plasticity and resolve our understanding of limits

Murren_et_al_AS_UPLOADED_DRYAD

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