Stressors such as antibiotics, herbicides, and pollutants are becoming increasingly common in the environment. The effects of stressors on populations are typically studied in homogeneous, nonspatial settings. However, most populations in nature are spatially distributed over environmentally heterogeneous landscapes with spatially restricted dispersal. Little is known about the effects of stressors in these more realistic settings. Here, we combine laboratory experiments with novel mathematical theory to rigorously investigate how a stressor's physiological effect and spatial distribution interact with dispersal to influence population dynamics. We prove mathematically that if a stressor increases the death rate and/or simultaneously decreases the population growth rate and yield, a homogeneous distribution of the stressor leads to a lower total population size than if the same amount of the stressor was heterogeneously distributed. We experimentally test this prediction on spatially distributed populations of budding yeast (). We find that the antibiotic cycloheximide increases the yeast death rate but reduces the growth rate and yield. Consistent with our mathematical predictions, we observe that a homogeneous spatial distribution of cycloheximide minimizes the total equilibrium size of experimental metapopulations, with the magnitude of the effect depending predictably on the dispersal rate and the geographic pattern of antibiotic heterogeneity. Our study has implications for assessing the population risk posed by pollutants, antibiotics, and global change and for the rational design of strategies for employing toxins to control pathogens and pests.
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http://dx.doi.org/10.1086/709293 | DOI Listing |
Atten Percept Psychophys
January 2025
Department of Psychology, Senshu University, Kawasaki, Japan.
Sci Rep
January 2025
School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, 454003, China.
Owing to China's massive area and vastly differing regional variations in the types and efficiency of energy, the spatiotemporal distributions of regional carbon emissions (CE) vary widely. Regional CE study is becoming more crucial for determining the future course of sustainable development worldwide. In this work, two types of nighttime light data were integrated to expand the study's temporal coverage.
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January 2025
College of Engineering, Ocean University of China, Qingdao, 266404, China.
Although deterministic analysis can provide initial insights into slope stability, there is no way to reflect the true distribution of soil properties within a slope. To further investigate the effects of the spatial variability of soil properties on the stability and failure mechanism of slope under different foundation types, this study develops a framework combining simple limit equilibrium method (LEM), Monte Carlo Simulation (MCS), and random field to incorporate these factors into slope probabilistic stability analysis. The slope models of two typical foundations (e.
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January 2025
Business School, Hebei University of Economics and Business, Shijiazhuang, 050062, China.
The development and implementation of county carbon control action plans in the Yellow River Basin (YRB) are crucial for realizing the "dual carbon" goals and modernizing national governance. Utilizing remote sensing data from 2001 to 2020, this study constructs a light-carbon conversion model and a carbon footprint model to simulate the carbon footprint of county energy consumption in the YRB. Employing spatial autocorrelation and spatial Durbin models, the study examines the temporal-spatial evolution characteristics and spatial effect mechanism.
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January 2025
Department of Biology, University of Ottawa, Ottawa, ON K1N 6N5, Canada.
Axons in the mammalian brain show significant diversity in myelination motifs, displaying spatial heterogeneity in sheathing along individual axons and across brain regions. However, its impact on neural signaling and susceptibility to injury remains poorly understood. To address this, we leveraged cable theory and developed model axons replicating the myelin sheath distributions observed experimentally in different regions of the mouse central nervous system.
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