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2 results

  • 8 - Biodiversity Scaling on a Continuous Plane: Geometric Underpinnings of the Nested Species–Area Relationship

  • from Part III - Theoretical Advances in Species–Area Relationship Research
  • Edited by Thomas J. Matthews, University of Birmingham, Kostas A. Triantis, Robert J. Whittaker, University of Oxford
  • Book:
    The Species–Area Relationship
    Published online:
    11 March 2021
    Print publication:
    18 March 2021, pp 185-210

  • Summary

    The slope and shape of the nested species–area relationship (SAR) can be derived using geometrical considerations. The local slope of the nested SAR is determined by mean species occupancy at a given scale. Thus, any factor that affects the scale dependent occupancy patterns of individual species will affect the overall shape of the nested SAR. Using only geometric considerations, we can derive not only the formula relating mean occupancy to the overall nested SAR slope, but also the overall triphasic shape of the nested SAR. The relatively shallow slope of the nested SAR at intermediate spatial scales, which can be well approximated by a power law, can be attributed to the scale independent (approximately fractal) spatial distribution of individual species. The shape and slope of the nested SAR are linked to beta diversity patterns as well as to the species abundance distribution (SAD), although we argue that the SAD is in fact a derived pattern which cannot be used to construct the nested SAR. In general, geometrical considerations provide a first-order explanation of the nested SAR, while biological factors affect the basic parameters of species distributions and thus act to determine the specific nested SAR in any given case.

  • Analysis of spatial-temporal distribution and influencing factors of pulmonary tuberculosis in China, during 2008–2015

  • Y. Zhang, X. L. Wang, T. Feng, C. Z. Fang
  • Journal:
    Epidemiology & Infection / Volume 147 / 2019
    Published online by Cambridge University Press:
    10 October 2018, e25
    • Article
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  • At present, the number of people with tuberculosis in China is second only to India and ranks second in the world. Under such a severe case of tuberculosis in China, prevention and control of pulmonary tuberculosis are urgently needed. This study aimed to study the temporal and geographical relevance of the pathogenesis of pulmonary tuberculosis and the factors affecting the incidence of tuberculosis. Spatial autocorrelation model was used to study the spatial distribution characteristics of pulmonary tuberculosis from a quantitative level. The research results showed that the overall incidence of pulmonary tuberculosis (IPT) in China was low in the east, high in the west and had certain seasonal characteristics. We use Spatial Lag Model to explore influencing factors of pulmonary tuberculosis. It indicates that the IPT is high in areas with underdeveloped economics, poor social services and low average smoking ages. Additionally, the IPT is high in areas with high AIDS prevalence. Also, compared with Classical Regression Model and Spatial Error Model, our model has smaller values of Akaike information criterion and Schwarz criterion. Besides, our model has bigger values of coefficient of determination (R2) and log-likelihood (log L) than the other two models. Apart from that, it is more significant than Spatial Error Models in the spatial dependence test for the IPT.