A Review of “War,Violence, and Population: Making the Body Count”

An understanding of the contemporary biogeography of a region must be predicated not only on the current environmental conditions that influence species distributions but also on historical factors including anthropogenic disturbance regimes. Increasingly, researchers are using historical data, such as the Public Land Survey System (PLSS) records, to create baselines from which subsequent biogeographic changes can be gauged. The present-day state of Oklahoma is unique in that two separate PLSS surveys were conducted in the state during a relatively short time span. We compare these two historical data sets, from the 1870s and 1890s, respectively, to quantify changes in landscape structure and woody plant assemblages corresponding to rapid demographic changes occurring within the Arbuckle Mountains in Oklahoma. During this period, the PLSS data show a landscape that became increasingly fragmented, as well as differences in stand composition and density. The documentation of these important historical anthropogenic changes occurring on the western fringes of the eastern deciduous forest could serve as a valuable guide for conservation and restoration initiatives.     

Ethnic Restructuring in Rural America: Migration and the Changing Faces of Rural Communities in the Great Plains

Scholars have long documented widespread aging and depopulation of rural communities in the Great Plains. Paralleling these trends is the emergence, growth, and spatial dispersion of new and longtime non-white populations across the region. The dual processes of population loss in many counties combined with the growth of new, non-white population groups suggest that the ethnic structure of the population is changing. In this article we utilize choropleth maps, Hoover and Simpson indexes, and cluster analysis to assess whether the emergence and growth of ethnic minority groups in the Great Plains between 1970 and 2008 is a localized phenomenon or region-wide shift in the ethnic composition of the population. Results suggest that as depopulation is occurring in many counties of this region, the growth of non-white populations, both immigrant and native born, is changing or restructuring the ethnic composition of the Great Plains.     

Migration,Sources of Income,and Community Change in the Nonmetropolitan Northwest

During the late 1980s and the first half of the 1990s, the nonmetropolitan Northwest grew quite rapidly, narrowing the gap between the growth rates of the metropolitan Northwest, and oupacing national rates. This growth was largely the result of in-migration from regional and national metropolitan areas. Traditional economic base theory does not explain the recent growth, as employment levels in in the region's basic industries continue to stagnate and decline, and the sources of income for these in-migrants remain a mystery. This paper utilizes data from the 1990 Public Use Microdata Sample (PUMS) to determine the extent to which metropolitan-origin migrants are measurably different from oldtime nonmetropolitan residents on certain socioeconomic variables, in an attempt to understand the ways in which the newcomers survive financially. Analysis of variance (ANOVA) shows that newcomers are younger, earn less in wages and salary, receive more nonearnings income, and reside in more valuable housing compared with the resident population. Discriminant analysis shows that differences in the earned income measures are largely explained by age differences, while the nonearnings income and value of residence remainsignificantly higher for the metropolitan origin migrants even when age and earned income are controlled. While the analysis indicates that measurable socioeconomic differences do exist between the two populations, it appears that the current wave of growth and change in the nonmetropolitan Northwest is much more complicated than a simple newcomer-oldtimer dichotomy.     

The Hoover Index of Population Concentration: A Correction and Update

Geographers have made extensive use of the Hoover index to measure the evenness with which population is distributed across territorial units. This paper corrects an error in the original county-based series for the United States, presented by Duncan et al. In Statistical Geography (1961) and often reproduced. We extend the series backward and forward in time to show population deconcentration at the county level from at least 1890 until 1910 (as low-density areas grew rapidly), a second round of deconcentration corresponding to the nonmetropolitan turnaround of the 1970s, and a third, much weaker round beginning around 1990 along with a modest resurgence of nonmetropolitan population growth. When states are used as the basis for computing the index, deconcentration has been a consistent pattern, except for 1940 to 1970, and for this exception we offer an explanation. We attempt to put these findings in the context of long- and short-term patterns of metropolitanization.     

A MEASURE OF DISPARITY

The Thornthwaite method for computing evapotranspiration has been employed in a variety of climatic realms. Recently, the equation for computing potential evapotranspiration has been shown to underestimate measured moisture losses in dry environments. This study presents monthly calibration equations that enhance the reliability of the Thornthwaite estimates of evapotranspiration for California stations. Six years of calibrated monthly potential evapotranspiration are compared with lysimetermeasured evapotranspiration at Davis and with other estimates of evapotranspiration for this site.     

甘肃敦煌西湖荒漠-湿地生态系统优势植物种群分布格局及种间关联性

基于25个样地、375个样方和150条样线的调查资料,采用扩散系数(C)、负二项参数(K)、平均拥挤度(m*)、丛生指标(D、聚块性指标(PI)、Green指数(GI)、Cassie指标(GA)和Moristia指数(Ⅰδ)等8个指标以及方差比率(VR)法,对甘肃敦煌西湖荒漠-湿地生态系统优势植物种群的空间分布格局、聚集强度和种间总体关联性进行了研究.结果表明:①研究区8种优势种群均为聚集分布(p＜0.01).其中,多枝柽柳群落、多枝柽柳沙包群落和胡杨群落均具有较高聚集程度,而疏叶骆驼刺群落和芦苇群落均具有较低聚集程度.②研究区优势种群中灌(乔)木层均为聚集分布(p＜0.05).③研究区优势种群在各海拔梯度上均为聚集分布(p＜0.05).随海拔梯度的增加,种群聚集强度增加,且种群聚集程度变化较为平缓.④研究区植物群落中,灌(乔)木层主要种群的种间联结表现为显著的正关联,乔灌草和草本层的主要种群的种间联结表现为显著的负关联.应用2×2联列表x2统计量、联结系数(AC)和共同出现百分率(PC)等方法,综合分析了敦煌西湖主要种群的种间联结显著性和关联强度.结果表明:研究区大多数种群种间关联程度不显著(p＞0.05),不关联的种对数明显要多于显著关联种对数,显著负关联的种对数多于正关,说明种群对生境和资源要求不一样,与总体种间相关性检验的方差比率VR值的结果一致,群落中优势物种处于不稳定阶段.     

基于聚落演变的岩溶山区小尺度人口数推算方法——以普定后寨河地区为例

运用高分辨率遥感数据源,从聚落入手,采用聚落调查法和GIS空间分析方法,在小尺度上建立基于研究区普定后寨河地区的总体情况、地形地貌差异、聚落等级的岩溶山区乡村聚落空间规模与人口数之间的相关关系,并在此基础上对其4个时期独立聚落人口动态数量进行回归模拟。步骤为:1)建立研究区已获取人口数的聚落空间分布规模(面积)与人口数的一元线性相关关系,对研究区聚落与人口进行回归分析,推算出研究区各时期无法获取准确数据的独立聚落人口数;2)建立各地貌区聚落空间规模与人口的线性关系,推算基于地貌类型无法获取准确数据的聚落人口数;3)考虑聚落空间规模的等级效应,将研究区各时期聚落按空间分布规模划分为高、中、低3个规模等级,计算不同等级内已获取人口数聚落的人均聚落面积,然后推算未知人口数聚落的人口数;4)在上述三种推算方式的基础上,使用平均法计算各时期每个独立聚落人口数。通过对比县志、人口资料和实地调查,证明通过聚落与人口数之间的相关关系推算聚落人口数是基本有效的、准确的。     

基于散度和旋度纵横波分离方法的改进

纵、横波的分离是多波多分量地震资料处理中很重要的一步,其分离结果直接影响到后续数据处理的质量.各向同性介质中纵波为无旋场,横波为无散场,因此可以在频率-波数域利用散度和旋度算子对地震记录进行纵、横波分离,但是此处理过程必须知道地表处的纵、横波速度.本文给出了一种估算地表纵、横波速度的方法,可以在纵、横波速度值未知的情况下,将其估算出来.针对弹性波场进行散度和旋度运算时,纵、横波的相位和振幅比发生改变的问题,本文给出了相位和纵、横波振幅比的校正方法.     

Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009

ABSTRACT

Large-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates. Such temporal projections do not include any subnational variation in population distribution trends and ignore changes in geographical covariates such as urban land cover changes. Improved predictions of population distribution changes over time require the use of a limited number of covariates that are time-invariant or temporally explicit. Here we make use of recently released multi-temporal high-resolution global settlement layers, historical census data and latest developments in population distribution modelling methods to reconstruct population distribution changes over 30 years across the Kenyan Coast. We explore the methodological challenges associated with the production of gridded population distribution time-series in data-scarce countries and show that trade-offs have to be found between spatial and temporal resolutions when selecting the best modelling approach. Strategies used to fill data gaps may vary according to the local context and the objective of the study. This work will hopefully serve as a benchmark for future developments of population distribution time-series that are increasingly required for population-at-risk estimations and spatial modelling in various fields.