Spatial pattern analysis of pre- and post-hurricane forest canopy structure in North Carolina,USA

Existing spatial patterns of a forest are in part a product of its disturbance history. Using laser altimetry and field measures of canopy top height to represent pre- and post-hurricane canopy topography, respectively, we measured changes in spatial patterns of stand structure of a United States southern mixed coniferous-deciduous for est. Autocorrelative and fractal properties were measured in this opportunistic study to quantify changes in canopy architecture along twelve, 190-250 m transects that were subjected to moderate to high levels of wind disturbance. Prior to the hurricane, canopy heights were autocorrelated at scales <40 m with an average fractal dimension of 1.71. After the disturbance, autocorrelation disappeared; the average fractal dimension rose to 1.94. This shift towards spatial randomness illustrates part of the cyclical nature of ecosystem development. It shows how a catastrophic collapse of biomass accumulation corresponds to a decrease in ecosystem organization across a landscape. This revised version was published online in July 2006 with corrections to the Cover Date.     

Spatio-temporal modelling of broad scale heterogeneity in soil moisture content: a basis for an ecologically meaningful classification of soil landscapes

We describe the classification of landscapes characterised bymineral soil using a model that calculates soil moisture availability on amonthly basis. Scotland is used as a case study area. The model uses potentialsoil moisture deficit, estimated using broad scale (40 × 40 km)climate patterns, in conjunction with meteorological station measurements toobtain finer scale values of climatic soil moisture deficit. Point estimates ofsoil available water are obtained for soil characteristics using appropriatepedotransfer functions, and geostatistical techniques are used to upscale theresults and interpolate to a 1-km grid. Known heterogeneityin soil physical characteristics is used to provide local corrections to thepotential soil moisture deficit, estimated using the climatic variables above.Temporal profiles of monthly water content are modelled for each1-km location and classified into six classes usingunsupervised cluster analysis. The spatial distribution of these classesreflects regional variations in the availability of moisture and energy, onwhich finer-grained topographic patterns are superimposed. In the case study,the broad scale spatial heterogeneity of heathlands and grasslands on mineralsoils in Scotland is shown to be strongly related to the soil moistureclassification. The results can be used in studies investigating the patternsofdistribution of communities at the landscape and regional scale.This revised version was published online in May 2005 with corrections to the Cover Date.     

非线性、分形与期锌市场价格

从非线性角度研究期锌市场，运用R/S分析法对期锌市场进行分析，发现期锌市场的Hurst指数为0.6183,其价格收益率序列是分维时间序列，具有分形结构，维数为1.6174。期锌市场的平均周期长度为176天，具有强持续性和相关性。关联系数为19.47%，远远大于国外相关市场。在风险方面，期锌市场的风险比期铜市场的要小，而比股票市场的风险要大。     

Why viewing nature is more fascinating and restorative than viewing buildings: A closer look at perceived complexity

The present paper addresses the question which visual features trigger people’s often more positive affective responses to natural compared to built scenes. Building on notions about visual complexity and fractal geometry, we propose that perceived complexity of magnified scene parts can predict the greater fascinating and restorative qualities of natural versus built scenes. This prediction was tested in an experiment in which 40 participants viewed and rated 40 images of unspectacular natural and built scenes in their original size, and at 400% and 1600% magnification levels. Results showed that the original, unmagnified natural scenes were viewed longer and rated more restorative than built scenes, and that these differences were statistically mediated by the greater perceived complexity of magnified parts of natural scenes. These findings fit with the idea that fractal-like, recursive complexity is an important visual cue underlying the restorative potential of natural and built environments.     

Object‐Based Mapping of Karst Rocky Desertification using a Support Vector Machine

Accurate and cost‐effective mapping of karst rocky desertification (KRD) is still a challenge at the regional and national scale. Visual interpretation has been utilised in the majority of studies, while an automated method based on pixel data has been investigated repeatedly. An object‐based method coupling with support vector machine (SVM) was developed and tested using Enhanced Thematic Mapper Plus (ETM+) images from three selected counties (Liujiang, Changshun and Zhenyuan) with different karst landscapes in SW China. The method supports a strategy of defining a mapping unit. It combined ETM+ images and ancillary data including elevation, slope and Normalized Difference Vegetation Index images. A sequence of scale parameters estimation, image segmentation, training data sampling, SVM parameters tuning and object classification was performed to achieve the mapping. A quantitative and semi‐automated approach was used to estimate scale parameters for segmenting an object at an optimal scale. We calculated the sum of area‐weighted standard deviation (WS), rate of change for WS, local variance (LV) and rate of change for LV at each scale level, and the threshold of the aforementioned index that indicated the optimal segment level and merge level. The KRD classification results had overall accuracies of 85·50, 84·00 and 84·86 per cent for Liujiang, Changshun and Zhenyuan, respectively, and kappa coefficients are up to 0·8062, 0·7917 and 0·8083, respectively. This approach mapped six classes of KRD and offered a visually appealing presentation. Moreover, it proposed a conceptual and size‐variable object from the classification standard of KRD. The results demonstrate that the application of our method provides an efficient approach for the mapping of KRD. Copyright © 2012 John Wiley & Sons, Ltd.     

黑龙港流域参考作物蒸散量的时序变化和分形特征

利用位于黑龙港流域的武强、深泽、饶阳、晋州、献县5站1957-2009年日最高气温、日平均气温、日最低气温、日平均相对湿度、日平均风速、日照时数资料,采用Penman-Monteith算法,计算各站不同时间尺度ET0,采用线性趋势分析法分析其趋势倾向,并应用滑动R/S分析方法研究该流域不同时间尺度ET0时间序列的分形特征。线性趋势分析显示,各站历史上自1957年以来的ET0年总值的气候倾向率在-33.81-10.79mm.10a^-1,即均呈下降趋势,但变化倾向率不同;各月ET0倾向率在-11.27-2.02mm.10a^-1,大多数为负值,其中5、6月份各站的下降趋势最大;春、夏、秋、冬季ET0倾向率为-15.87-1.30mm.10a^-1,且夏季各站之间的差异较大,尤以饶阳站与其他4站间的差异最大。气候要素倾向率的对比分析表明,5站参考作物蒸散量总体下降趋势的基本特征主要是由于风速下降、日照时数减少、日最高最低气温上升造成的;5、6月份下降趋势明显则主要是由于风速下降、日照时数减少、日平均气温上升减缓、相对湿度上升明显造成的;饶阳站与其他4站差异较大的主要原因在于2、3、11、12月风速下降和日照时数减少以及日最高最低气温上升趋势减缓、相对湿度和气压下降明显,以致这些月份的ET0倾向率大于0,形成秋季和冬季ET0倾向率大于0,年尺度ET0年际变化下降趋势不明显。R/S分析结果显示,5站全年和各季ET0时间序列的Hurst指数均大于0.5,相关系数均在0.98以上,分维数均小于1.5,说明各站全年和各季节ET0时间序列变化趋势在未来一段时间内具有持续性,即ET0在未来将呈较明显的下降趋势,这种趋势在除饶阳外的其他站月均有不同程度的表现。     

神府煤田土壤颗粒分形及降雨对径流产沙的影响

神府煤田在开发建设过程中造成的扰动地面、弃土体、弃渣体产生了严重的人为水土流失。采用野外人工模拟降雨试验方法,研究了土壤分形维数及降雨强度对未扰动地面、扰动地面、弃土体及弃渣体径流产沙的影响。结果表明,(1)弃土体、弃渣体随产流历时呈现突增—下降—稳定的过程,扰动地面和未扰动地面则经历上升—稳定的产流过程,各下垫面径流率均随着雨强的增大而增大。(2)各下垫面土壤颗粒分形维数的大小为D1(弃渣体)D2(弃土体)D3(扰动地面)D4(未扰动地面),次降雨径流量与降雨强度、分形维数分别呈显著的线性、幂函数关系,且D1~D2及D3~D4之间存在用以区分下垫面类型的临界分形维数值。(3)弃渣体侵蚀过程线呈先波动后稳定趋势,弃土体则呈多峰多谷特点,扰动地面和未扰动地面在1.0~2.5 mm min-1雨强下侵蚀速率均先增大后逐渐稳定,3.0 mm min-1时二者侵蚀速率则波动剧烈。四种下垫面平均侵蚀速率均随着雨强的增大而增大。(4)次降雨产沙量与降雨强度、分形维数均呈显著的幂函数关系。(5)径流量、产沙量与雨强和分形维数分别呈显著的线性、指数函数关系。分形维数对矿区土壤侵蚀模型的建立有重要的科学意义。     

荒漠-绿洲边缘区生态过渡带的土壤颗粒分形特征

通过实地采样和实验室分析,测定了黑河中游荒漠绿洲边缘区生态过渡带的土壤粒级分布、有机碳(SOC)、全氮(TN)、全磷(TP)、速效氮(AN)和速效磷(AP)的含量,并采用1993年杨培岭等提出的用粒径的重量分布代替数量分布的土壤分形模型,计算了土壤颗粒分形维数;最后利用统计分析法,研究了颗粒分形维数与土壤粒级分布及各养分指标的关系.结果表明:从荒漠边缘向绿洲延伸的过渡带,土壤中砂粒含量占绝对优势,粉粒居中,黏粒最少,采样区土壤质地较粗;土壤颗粒分形维数在2.105～2.609之间变动,处于极低水平,与土壤各养分指标具有相似的变化趋势,除靠近绿洲区存在一个"生态裂谷"外,整体呈上升趋势;利用相关分析法得出,土壤颗粒分形维数与砂粒含量呈显著负相关,与黏粉粒及各养分指标均呈显著的正相关;利用回归分析法进行定量分析,砂粒含量每增加1g/kg,颗粒分形维数D降低0.0019个单位;粉粒和黏粒含量每增加1g/kg,颗粒分形维数D分别增加0.002和0,023个单位,对土壤颗粒分形维数变化幅度的影响依次为黏粒>粉粒>砂粒,分形维数对黏粒含量的变化最为敏感.因此,可以将土壤颗粒分形维数作为衡量荒漠-绿洲边缘区土壤养分变化状况的指标之一,用于反映荒漠绿洲区土壤的退化状况.     

The concept of habitat specificity revisited

Habitat specificity indices reflect richness (α) and/or distinctiveness (β) components of diversity. The latter may be defined by α and γ (landscape) diversity in two alternative ways: multiplicatively () and additively (). We demonstrate that the original habitat specificity concept of Wagner and Edwards (Landscape Ecol 16:121–131, 2001) consists of three independent components: core habitat specificity (uniqueness of the species composition), patch area and patch species richness. We describe habitat specificity as a family of indices that may include either area or richness components, or none or both, and open for use of different types of mean in calculation of core habitat specificity. Core habitat specificity is a beta diversity measure: the effective number of completely distinct communities in the landscape. Habitat specificity weighted by species number is a gamma diversity measure: the effective number of species that a patch contributes to landscape richness. We compared 12 habitat specificity indices by theoretical reasoning and by use of field data (vascular plant species in SE Norwegian agricultural landscapes). Habitat specificity indices are strongly influenced by weights for patch area and patch species richness, and the relative contribution of rare vs. common species (type of mean). The relevance of properties emphasized by each habitat specificity index for evaluation of patches in a biodiversity context is discussed. Core habitat specificity is emphasized as an ecologically interpretable measure that specifically addresses patch uniqueness while habitat specificity weighted by species number combines species richness and species composition in ways relevant for conservation biological assessment. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Effects of landscape structure on nest predation in roadsides of a midwestern agroecosystem: a multiscale analysis

Nest predation is an important cause of mortality for many bird species, especially in grassland ecosystems where generalist predators have responded positively to human disturbance and landscape fragmentation. Our study evaluated the influence of the composition and configuration of the surrounding landscape on nest predation. Transects consisting of 10 artificial ground nests each were set up in 136 roadsides in six watersheds in south-central Iowa. Nest predation on individual roadside transects ranged from 0 to 100% and averaged 23%. The relationship of landscape structure within spatially-nested landscapes surrounding each roadside transect (within 200, 400, 800, 1200, and 1600 m of the transect line) to nest predation was evaluated by using multiple regression and canonical correlation analyses. The results of this multiscale landscape analysis demonstrated that predation on ground nests was affected by the surrounding landscape mosaic and that nest predators with different-sized home ranges and habitat affinities responded to landscapes in different ways. In general, wooded habitats were associated with greater nest predation, whereas herbaceous habitats (except alfalfa/pasture) either were associated with less nest predation or were not important. Different landscape variables were important at different spatial scales. Whereas some block-cover habitats such as woodland were important at all scales, others such as rowcrops and alfalfa/pasture were important at large scales. Some strip-cover habitats such as gravel roads and paved roads were important at small scales, but others such as wooded roadsides were important at all all scales. Most landscape metrics (e.g., mean patch size and edge density) were important at large scales. Our study demonstrated that the relationships between landscape structure and predator assemblages are complex, thus making efforts to enhance avian productivity in agricultural landscapes a difficult management goal.