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The impacts of climate change have re-energized interest in understanding the role of climate in setting species geographic range edges. Despite the strong focus on species' distributions in ecology and evolution, defining a species range edge is theoretically and empirically difficult. The challenge of determining a range edge and its relationship to climate is in part driven by the nested nature of geography and the multidimensionality of climate, which together generate complex patterns of both climate and biotic distributions across landscapes. Because range-limiting processes occur in both geographic and climate space, the relationship between these two spaces plays a critical role in setting range limits. With both conceptual and empirical support, we argue that three factors-climate heterogeneity, collinearity among climate variables, and spatial scale-interact to shape the spatial structure of range edges along climate gradients, and we discuss several ways that these factors influence the stability of species range edges with a changing climate. We demonstrate that geographic and climate edges are often not concordant across species ranges. Furthermore, high climate heterogeneity and low climate collinearity across landscapes increase the spectrum of possible relationships between geographic and climatic space, suggesting that geographic range edges and climatic niche limits correspond less frequently than we may expect. More empirical explorations of how the complexity of real landscapes shapes the ecological and evolutionary processes that determine species range edges will advance the development of range limit theory and its applications to biodiversity conservation in the context of changing climate.
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http://dx.doi.org/10.1111/gcb.14897 | DOI Listing |
Biomed Phys Eng Express
September 2025
College of Computer Science and Technology, China University of Petroleum East China - Qingdao Campus, College of Computer Science and Technology, China University of Petroleum (East China), Qingdao 266580, China, Qingdao, Shandong, 266580, CHINA.
Purpose: Cerebrovascular segmentation is crucial for the diagnosis and treatment of cerebrovascular diseases. However, accurately extracting cerebral vessels from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) remains challenging due to the topological complexity and anatomical variability.
Methods: This paper presents a novel Y-shaped segmentation network with fast Fourier convolution and Mamba, termed F-Mamba-YNet.
Mar Life Sci Technol
August 2025
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48103 USA.
Unlabelled: Habitat fragmentation is a major cause of biodiversity loss. Fragmentation can alter thermal conditions on the remaining patches, especially at habitat edges, but few studies have examined variations in thermal tolerance of species in fragmented habitats. Ants are sensitive to both habitat fragmentation and temperature changes, and are an ideal taxon for studying these impacts.
View Article and Find Full Text PDFCureus
August 2025
Department of Radiology, Aichi Medical University, Nagakute, JPN.
Purpose This planning study aimed to clarify the significance of inverse planning with variable dose rate (VDR) and the segment shape optimization (SSO) in the quality and efficiency of dynamic conformal arcs (DCA) using the high-definition dynamic radiosurgery (HDRS) platform for stereotactic radiosurgery (SRS) of single brain metastases (BMs). Materials and methods Twenty clinical BMs were included, with the gross tumor volume (GTV) ranging from 0.33 cc to 48.
View Article and Find Full Text PDFSci Adv
September 2025
Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
Advances in brain stimulation have made it possible to target smaller and smaller regions for electromagnetic stimulation, in the hopes of producing increasingly focal neural effects. However, the brain is extensively interconnected, and the neurons comprising those connections may themselves be particularly susceptible to neurostimulation. Here, we test this hypothesis by identifying long-range projections in single-unit recordings from nonhuman primates receiving transcranial alternating current stimulation.
View Article and Find Full Text PDFJ Acoust Soc Am
September 2025
Centre de Vision Numérique, CentraleSupélec, Université Paris-Saclay, Inria, Gif-Sur-Yvette, France.
Conventional techniques for underwater source localization have traditionally relied on optimization methods, matched-field processing, beamforming, and, more recently, deep learning. However, these methods often fall short to fully exploit the data correlation crucial for accurate source localization. This correlation can be effectively captured using graphs, which consider the spatial relationship among data points through edges.
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