The environment could alter growth and resistance tradeoffs in plants by affecting the ratio of resource allocation to various competing traits. Yet, how and why functional tradeoffs change over time and space is poorly understood particularly in long-lived conifer species. By establishing four common-garden test sites for five lodgepole pine populations in western Canada, combined with genomic sequencing, we revealed the decoupling pattern and genetic underpinnings of tradeoffs between height growth, drought resistance based on δ13C and dendrochronology, and metrics of pest resistance based on pest suitability ratings. Height and δ13C correlation displayed a gradient change in magnitude and/or direction along warm-to-cold test sites. All cold test sites across populations showed a positive height and δ13C relationship. However, we did not observe such a clinal correlation pattern between height or δ13C and pest suitability. Further, we found that the study populations exhibiting functional tradeoffs or synergies to various degrees in test sites were driven by non-adaptive evolutionary processes rather than adaptive evolution or plasticity. Finally, we found positive genetic relationships between height and drought or pest resistance metrics and probed five loci showing potential genetic tradeoffs between northernmost and the other populations. Our findings have implications for deciphering the ecological, evolutionary, and genetic bases of the decoupling of functional tradeoffs due to environmental change.
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http://dx.doi.org/10.1093/evolut/qpad004 | DOI Listing |
Comput Struct Biotechnol J
December 2024
Department of Medicinal Chemistry, Institute of Pharmacy, Martin-Luther-University of Halle-Wittenberg, Halle (Saale) 06120, Germany.
Reliable in silico prediction of fragment binding modes remains a challenge in current drug design research. Due to their small size and generally low binding affinity, fragments can potentially interact with their target proteins in different ways. In the current study, we propose a workflow aimed at predicting favorable fragment binding sites and binding poses through multiple short molecular dynamics simulations.
View Article and Find Full Text PDFFront Parasitol
January 2024
Department of Biology, McGill University, Montreal, QC, Canada.
With climate and land use changes, tick-borne pathogens are expected to become more widely distributed in Canada. Pathogen spread and transmission in this region is modulated by changes in the abundance and distribution of tick and host populations. Here, we assessed the relationships between pathogens detected in and mammal hosts at sites of different levels of disease risk using data from summer field surveys in Ontario and Quebec, Canada.
View Article and Find Full Text PDFFront Child Adolesc Psychiatry
June 2024
IM Franchise Department, Les Laboratoires SERVIER, Global Value, Access & Pricing, Suresnes, France.
Introduction: Autism spectrum disorder (ASD) is characterised by difficulty with social communication and restricted, repetitive patterns of behaviour. This study aimed to improve understanding of the ASD patient experience with the treatment (bumetanide) regarding the changes in core symptoms and to assess changes considered as meaningful. To achieve this, qualitative interviews were conducted with caregivers of patients in two phase 3 clinical trials (NCT03715153; NCT03715166) of a novel ASD treatment.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
School of Ocean Sciences, Bangor University, Menai Bridge, Anglesey LL59 5AB, U.K.
Accurate prediction of chlorophyll- (Chl-) concentrations, a key indicator of eutrophication, is essential for the sustainable management of lake ecosystems. This study evaluated the performance of Kolmogorov-Arnold Networks (KANs) along with three neural network models (MLP-NN, LSTM, and GRU) and three traditional machine learning tools (RF, SVR, and GPR) for predicting time-series Chl- concentrations in large lakes. Monthly remote-sensed Chl- data derived from Aqua-MODIS spanning September 2002 to April 2024 were used.
View Article and Find Full Text PDFAdv Mater
January 2025
School of Chemical and Biomolecular Engineering, The University of Sydney, Darlington, New South Wales, 2006, Australia.
Oxygen evolution reaction (OER) is a cornerstone of various electrochemical energy conversion and storage systems, including water splitting, CO/N reduction, reversible fuel cells, and rechargeable metal-air batteries. OER typically proceeds through three primary mechanisms: adsorbate evolution mechanism (AEM), lattice oxygen oxidation mechanism (LOM), and oxide path mechanism (OPM). Unlike AEM and LOM, the OPM proceeds via direct oxygen-oxygen radical coupling that can bypass linear scaling relationships of reaction intermediates in AEM and avoid catalyst structural collapse in LOM, thereby enabling enhanced catalytic activity and stability.
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