Background And Aims: In habitat mosaics, plant populations face environmental heterogeneity over short geographical distances. Such steep environmental gradients can induce ecological divergence. Lowland rainforests of the Guiana Shield are characterized by sharp, short-distance environmental variations related to topography and soil characteristics (from waterlogged bottomlands on hydromorphic soils to well-drained terra firme on ferralitic soils). Continuous plant populations distributed along such gradients are an interesting system to study intrapopulation divergence at highly local scales. This study tested (1) whether conspecific populations growing in different habitats diverge at functional traits, and (2) whether they diverge in the same way as congeneric species having different habitat preferences.
Methods: Phenotypic differentiation was studied within continuous populations occupying different habitats for two congeneric, sympatric, and ecologically divergent tree species (Eperua falcata and E. grandiflora, Fabaceae). Over 3000 seeds collected from three habitats were germinated and grown in a common garden experiment, and 23 morphological, biomass, resource allocation and physiological traits were measured.
Key Results: In both species, seedling populations native of different habitats displayed phenotypic divergence for several traits (including seedling growth, biomass allocation, leaf chemistry, photosynthesis and carbon isotope composition). This may occur through heritable genetic variation or other maternally inherited effects. For a sub-set of traits, the intraspecific divergence associated with environmental variation coincided with interspecific divergence.
Conclusions: The results indicate that mother trees from different habitats transmit divergent trait values to their progeny, and suggest that local environmental variation selects for different trait optima even at a very local spatial scale. Traits for which differentiation within species follows the same pattern as differentiation between species indicate that the same ecological processes underlie intra- and interspecific variation.
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http://dx.doi.org/10.1093/aob/mct176 | DOI Listing |
Sci Rep
December 2024
Department of Computer Science, Birzeit University, P.O. Box 14, Birzeit, West Bank, Palestine.
Accurate classification of logos is a challenging task in image recognition due to variations in logo size, orientation, and background complexity. Deep learning models, such as VGG16, have demonstrated promising results in handling such tasks. However, their performance is highly dependent on optimal hyperparameter settings, whose fine-tuning is both labor-intensive and time-consuming.
View Article and Find Full Text PDFNat Commun
December 2024
Department of Electronics and Information Convergence Engineering, Kyung Hee University, Yongin-si, Republic of Korea.
Self-assembled configurations are versatile for applications in which liquid-mediated phenomena are employed to ensure that static or mild physical interactions between assembling blocks take advantage of local energy minima. For granular materials, however, a particle's momentum in air leads to random collisions and the formation of disordered phases, eventually producing jammed configurations when densely packed. Therefore, unlike fluidic self-assembly, the self-assembly of dry particles typically lacks programmability based on density and ordering symmetry and has thus been limited in applications.
View Article and Find Full Text PDFEcol Lett
January 2025
Asian School of the Environment, Nanyang Technological University, Singapore, Singapore.
Insects represent most of terrestrial animal biodiversity, and multiple reports suggest that their populations are declining globally due to anthropogenic impacts. Yet, a high proportion of insect species remain undescribed and limited data on their population dynamics hamper insect conservation efforts. This is particularly critical in tropical biodiversity hotspots such as Southeast Asia.
View Article and Find Full Text PDFBrief Bioinform
November 2024
In-Service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, 250 Wuxing Street, 110, Taipei, Taiwan.
Accurate prediction of RNA modifications holds profound implications for elucidating RNA function and mechanism, with potential applications in drug development. Here, the RNA-ModX presents a highly precise predictive model designed to forecast post-transcriptional RNA modifications, complemented by a user-friendly web application tailored for seamless utilization by future researchers. To achieve exceptional accuracy, the RNA-ModX systematically explored a range of machine learning models, including Long Short-Term Memory (LSTM), Gated Recurrent Unit, and Transformer-based architectures.
View Article and Find Full Text PDFOpen Vet J
November 2024
Department of Pathology and Poultry Disease, College of Veterinary Medicine, University of Diyala, Baqubah, Iraq.
Background: Pollution of aquatic environments with heavy metals causes severe adverse effects on fish, invertebrates, and human. The importance of this study lies in the fact that long-term ingestion of heavy metal-contaminated fish can result in the accumulation of harmful metals in numerous organs and pose a major risk to human health.
Aim: The current study was designed to investigate the concentrations of toxic arsenic (As), lead (Pb), and mercury (Hg) in the liver, gills, and muscles of highly consumed aqua cultured common carp ( L.
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