上海宝山区农业用地土壤重金属空间分异规律及分布特征研究

利用地理信息系统(GIS)和地统计分析方法对宝山区农业用地土壤重金属(As,Cd,Cr,Hg,Pb)空间分异规律和分布特征进行研究.结果表明,区内农业用地土壤中5种重金属均表现为中等空间变异性;在全局趋势上,Cd为一次全局趋势,其余重金属元素都表现为二次趋势;5种元素在空间上均存在明显的方向效应;Cr,Hg和Pb具有强烈的空间相关性,As和Cd具有中等强度的空间相关性;5种重金属的空间变程由大到小分别为Hg,Pb,Cr,As和Cd.土壤重金属As,Cd,Cr,Hg和Pb平均含量分别为7.31mg.kg-1、0.24 mg.kg-1、107.89 mg.kg-1、0.15 mg.kg-1和38.54 mg.kg-1,分别是上海土壤背景值的0.80,1.81,1.44,1.43和1.51倍.宝山区南部农业用地土壤重金属污染程度普遍高于北部.从宝山区各镇农业用地土壤重金属污染看,Cr和Pb普遍污染严重,而基本不存在As污染.同期降尘污染调查表明,降尘重金属是本区土壤重金属污染的最重要来源.     

北京市典型有机设施蔬菜基地重金属污染特征及风险评估

为研究北京市典型有机设施蔬菜基地重金属污染状况,采用野外调查及室内分析法,选取北京市5个有机设施蔬菜基地中125个土壤样品和77个蔬菜样品进行了Pb、Cd、Cr、As和Hg含量的检测、统计分析与评价,对土壤重金属含量与土壤理化指标进行了相关分析,研究了重金属在蔬菜中的迁移规律,并结合美国环保署(US EPA)推荐采用的健康风险评价模型,评价由于蔬菜摄入导致的成人和儿童的健康风险。结果表明,5个设施蔬菜基地中有极少数土壤样本Cd含量超标,有极少数叶菜样本Cr含量超标,其他重金属含量均未超标。污染指数评价表明5个基地土壤重金属污染排序为:基地5基地1基地3基地2基地4,主要由土壤Cd累积所致。土壤重金属与理化性质相关性表明,5种重金属含量都受土壤的理化性质影响较大。总体上,5种重金属在土壤-蔬菜中迁移能力排序为:CdHgAsCrPb,在不同类蔬菜中的富集系数排序为:叶菜类茄果类瓜果类豆菜类。5种重金属造成的目标危害系数大小依次为:CdPbAsHgCr,不同类蔬菜的综合重金属目标危害系数值排序为:叶菜类茄果类瓜果类豆菜类,所有蔬菜单一重金属目标危害系数和复合危害系数都远小于1,说明单一重金属和复合重金属污染对成人和儿童都没有明显的负面健康影响。     

太原市土壤重金属污染空间分布及评价

以太原市土壤作为研究对象,系统研究了太原市城市土壤及工业区土壤中Cr、Ni、Cu、Zn、As、Cd、Pb的污染水平和分布,并对污染状况进行了评价.研究表明,太原市土壤中重金属的含量分别为Cr:35.35—848.80mg·kg-1,Ni:4.00—99.57 mg·kg-1,Cu:4.89—266.99 mg·kg-1,Zn:45.16—677.01 mg·kg-1,As:0.66—35.46 mg·kg-1,Cd:nd—1.00 mg·kg-1,Pb:15.61—1240.41 mg·kg-1.其中城市土壤重金属含量较低,工业区土壤重金属含量较高,受到多种重金属的复合污染.以土壤环境质量国家二级标准值作为评价标准,用单项污染指数和综合污染指数对太原市土壤重金属污染进行评价,结果显示太原市大部分城市土壤未受7种重金属污染,只有6.7%的地区处于轻污染水平;工业区土壤污染严重,污染程度从高至低为化工厂(重污染)热电厂(重污染)化肥厂(重污染)第一电厂(中度污染)建筑工地(中度污染)焦化厂(轻污染).7种重金属在太原市土壤中的空间分布规律不同,且均与工业区分布相关,工业区是太原城市土壤重金属污染的重要来源.     

澜沧江下游景观破碎化时空动态及成因分析

景观破碎化深刻影响着景观格局和过程。以澜沧江下游城市——景洪市为研究区域,选取2000、2005和2010年的景观类型数据与对应的SPOT-NDVI遥感数据,对比了移动窗口法和空间自相关法在指示景观破碎化时的精确性和可应用性。采用300 m的移动窗口边长,选取蔓延度指数(CONTAG)、景观形状指数(LSI)、斑块密度(PD)、边缘密度(ED)、最大斑块指数(LPI)和香农多样性指数(SHDI),利用移动窗口法将景观指数空间可视化以指示景观破碎化特征。研究表明,不同景观类型的NDVI值均在0.6以上;2000年、2005年和2010年,Moran’s I值均在0.78以上;进一步分析了NDVI的局部空间自相关指数Moran’s I,结果表明NDVI呈"高—高"自相关的地区大多为常绿阔叶林地带,而NDVI呈"低—低"自相关的地区大多为建筑用地和耕地分布广泛的区域。统计各景观类型的景观指数和空间自相关指数后发现,对于常绿阔叶林和未利用地等景观类型,局部自相关指数高的区域,CONTAG值也高,而LSI值较低,这表明该类景观类型斑块较少且完整,破碎化不明显。通过比较不同景观类型的景观指数和空间自相关系数,发现两种方法在指示景观破碎化上具有良好的可比性。同时,提取了海拔、坡度、坡向、地形起伏度和地面粗糙度等地形因子,分析了NDVI和地形因子之间的局部空间自相关指数Moran’s I,结果表明研究区植被分布在一定的程度上由海拔、坡度、地形起伏度和地面粗糙度所决定。本研究为综合景观指数与空间统计分析揭示景观格局变化和空间异质性提供了参考,并通过景观格局与地形因子的相关性分析进一步解释了景观格局变化与环境变化的生态意义。     

大邑铅锌矿区土壤和蔬菜重金属污染现状及评价

研究了四川省大邑县铅锌矿区附近土壤和蔬菜中Pb、Zn、Cr和Cd含量,采用单因子污染指数法和综合污染指数法评价铅锌矿区附近土壤重金属污染状况。结果表明,铅锌矿矿口以及选矿厂周边土壤重金属富集因子均超过1,距选矿厂距离≤20 m的3个土壤样点Pb、Zn和Cd的单因子污染指数和综合污染指数较高,土壤污染程度为重污染,选矿厂周边土壤重金属污染在水平层次的空间分布上表现出异质性。选矿厂周边蔬菜地下部分重金属含量普遍高于地上部分,不同重金属在蔬菜可食用部分的转移因子总体由大到小依次为Cd、Zn、Pb和Cr。选矿厂周边蔬菜地土壤与蔬菜中Pb、Zn、Cd和Cr含量之间无显著相关性,但土壤中Pb、Zn和Cd含量3者之间在α=0.01水平上显著相关。     

矿业城市煤矸石山周边土壤重金属分布特征与影响因素研究

以阜新海州井工矿煤矸石山为研究对象,在矸石山东南、东北、西南和西北4个方向50 m范围内共采集表层土壤样品32个,研究煤矸石堆放对周边土壤重金属污染的危害程度,分析土壤中重金属的生物有效性,评价土壤中重金属的污染程度及影响其分布的因素。结果表明:研究区域土壤中5种重金属Zn、Pb、Cu、Cr和Ni中,Pb、Cu、Cr和Ni含量的平均值均高于土壤背景值,其中Ni和Cu的含量分别为土壤环境质量Ⅱ级(GB15618—1995)标准值的1.49倍和1.76倍。土壤中重金属含量基本呈现出随着距煤矸石堆距离的增加而下降的趋势。单因子污染指数和内梅罗综合污染指数法评价结果为重金属Ni单项污染水平最高,有28.1%的样本处于轻度污染水平,研究区域土壤中5种重金属综合污染指数大于1,土壤处于轻度污染。BCR顺序提取法对研究区域土壤中重金属形态的分析结果显示,5种重金属都以残渣态为主要存在形态,弱酸溶态含量仅占总量的2.09%~10.8%。统计分析结果显示,研究区域32个土壤样品中重金属的形态分布未呈随土壤pH值变化而变化趋势,土壤有机质与相应土壤中重金属形态分布相关性分析数据表明,土壤有机质不是影响研究区域土壤中重金属分布的主要因素。     

湖南省某矿遗址周围农业土壤重金属污染及风险评价

为了进一步了解湖南省某矿遗址周围农田土壤重金属的风险,在该矿遗址附近两个区域(Ⅰ区、Ⅱ区)采集125个农业土壤样品,分析其中重金属(As、Cd、Cr、Cu、Pb)的含量,运用综合污染评价法、潜在生态指数法和地积累指数法对其开展风险评估.结果表明,Ⅰ区农田土壤中As和Cd的含量比国家风险管控标准值高,属于中度污染土壤,存在着极高的潜在生态风险;地积累指数进一步指出Ⅰ区土壤中As污染属于二级污染、Cd污染属于四级污染.Ⅱ区农田土壤,除Cd的含量相对较高外,其它重金属含量均很低,该区域土壤重金属的综合污染评价值低于1.0.但是由于Ⅱ区土壤中Cd的地积累指数为1.92,表明Ⅱ区土壤受到Cd的轻度污染,存在一定的潜在风险.     

锡林郭勒露天煤矿矿区草原土壤重金属分布特征

在内蒙古典型草原上,以锡林郭勒胜利煤田西一号和西二号露天矿为研究对象,采用野外样带取样和室内分析相结合的方法,研究了露天煤矿区土壤重金属含量(Cr、Cu、Mn、Ni、Zn和Pb元素)的空间分布特征,并探讨土壤重金属来源,旨在为典型草原露天矿区土壤重金属防治和草原生态系统可持续发展提供科学理论依据。结果表明:研究区土壤重金属Cr、Cu、Mn、Ni、Zn和Pb的平均质量分数分别为27.53、16.17、353.49、14.78、44.65和3.44 mg·kg~(-1),低于国家土壤环境质量二级标准,仅Cu含量高于内蒙古背景值;矿区东北方向样带,所有采样点的土壤重金属含量高于内蒙古背景值;露天矿开采对周围土壤重金属空间分布有显著影响,土壤重金属元素含量在矿区中心处最高,并向四周逐渐降低;矿区周围0.5 km范围内土壤重金属含量均超过内蒙古自治区背景值。统计分析(相关分析、主成分分析和聚类分析)结果显示,土壤重金属Cr、Cu、Mn、Ni和Zn来源可划归为一类,Pb单独为一类。     

贵州草海流域不同土地利用方式土壤重金属潜在生态风险评价

为揭示草海流域不同土地利用方式下土壤重金属的污染特征及分布规律,采集了草海流域耕地、林地、灌草地和城镇用地4种土地利用类型的75个表层土壤样品,测定了Hg、Cd、As、Cu、Pb、Ni、Cr和Zn共8种重金属的全量,利用潜在生态风险指数(RI)评价了重金属的污染水平,运用反距离权重插值法(IDW)分析了重金属的全量和潜在生态风险的空间分布特征。结果表明:(1) Hg、Cd、As、Cu、Pb、Ni、Cr和Zn的含量平均值分别为0.13、2.71、19.39、39.87、62.71、45.16、91.67和169.23 mg·kg~(-1)。其中,Cd在4种土地利用类型土壤中均呈重度污染,Pb在城镇用地和林地中呈中度污染,Zn在城镇用地中呈中度污染,其余情况均属于轻度污染或无污染。(2) 4种不同土地利用方式仅对Cd和Zn含量有显著影响(P 0.05),而对Hg、As、Cu、Pb、Ni和Cr含量无显著影响(P0.05)。与耕地、林地和灌草地相比,城镇用地可显著提高Cd和Zn的含量。(3)流域土壤重金属的RI平均值为204.59,属于中度风险水平。4种不同土地利用类型土壤重金属的RI平均值有所差异,由大到小依次为城镇用地(243.66)、耕地(209.71)、林地(192.50)和灌草地(153.53)最低。(4) Pb、Ni、Cr、Zn、Cd和RI的高值主要分布在流域西南部和流域东部中段区域,与研究区"土法炼锌"遗址吻合。Cu的高值积聚在东北部的城镇用地和灌草地。Hg和As在流域内均匀分布,其高值呈零星分布模式。上述研究结果能为草海流域土壤重金属污染防治提供参考依据。     

禹州市煤矿区周边土壤和农作物重金属污染状况及健康风险评价

为全面了解河南省禹州市煤矿周边土壤和农作物中的重金属污染现状.对禹州市的某3个典型矿区(下文称为A、B和C矿区)周围土壤和主要谷类农作物(玉米和小麦)进行了调研和采样分析,并采用电感耦合等离子体质谱仪(ICP-MS)测定其重金属含量,同时通过单因子指数法和内梅罗综合指数法评价了煤矿周围土壤的污染状况,并利用MMSOILS风险评价模型评价了食用当地谷类农作物对成人和儿童造成的重金属健康风险.结果表明:研究区土壤受到了重金属不同程度的污染,污染程度排序:小麦地玉米地,且就单个重金属污染程度来说, Cd Cu Co Ni Zn Cr;内梅罗综合污染指数分析结果表明,玉米地的污染程度为安全,小麦地的污染程度为重污染,均以Cd对污染指数P_(综合)值的贡献最大;研究区农作物玉米籽粒中Cr、Co、Ni、Cu、Zn和Cd的平均含量分别为25.03、0.54、2.87、21.52、118.68、1.97 mg·kg~(-1);小麦籽粒中Cr、Co、Ni、Cu、Zn和Cd的平均含量分别为1.04、0.11、1.17、9.55、61.51、0.06 mg·kg~(-1).Cr、Co、Ni、Cu、Zn和Cd富集系数大小的顺序均为玉米小麦;健康风险评价表明,研究区农作物籽粒中存在高重金属污染风险,尤其以Cd最为明显,食用当地谷类农作物对人体造成健康风险的顺序依次为Co Cd Cu Zn Ni Cr,其中Co、Cd对成人风险较高,Co、Cu、Zn、Cd对儿童风险较高,对儿童造成的健康风险要明显高于成人;土壤重金属含量与谷类农作物可食部分重金属含量间无明显相关性.     

Scale-dependent interaction of fire and grazing on community heterogeneity in tallgrass prairie

Natural disturbances affect spatial and temporal heterogeneity in plant communities, but effects vary depending on type of disturbance and scale of analysis. In this study, we examined the effects of fire frequency (1-, 4-, and 20-yr intervals) and grazing by bison on spatial and temporal heterogeneity in species composition in tallgrass prairie plant communities. Compositional heterogeneity was estimated at 10-, 50-, and 200-m2 scales. For each measurement scale, we used the average Euclidean Distance (ED) between samples within a year (2000) to measure spatial heterogeneity and between all time steps (1993-2000) for each sample to measure temporal heterogeneity. The main effects of fire and grazing were scale independent. Spatial and temporal heterogeneity were lowest on annually burned sites and highest on infrequently burned (20-yr) sites at all scales. Grazing reduced spatial heterogeneity and increased temporal heterogeneity at all scales. The rate of community change over time decreased as fire frequency increased at all scales, whereas grazing had no effect on rate of community change over time at any spatial scale. The interactive effects of fire and grazing on spatial and temporal heterogeneity differed with scale. At the 10-m2 scale, grazing increased spatial heterogeneity in annually burned grassland but decreased heterogeneity in less frequently burned areas. At the 50-m2 scale, grazing decreased spatial heterogeneity on 4-yr burns but had no effect at other fire frequencies. At the 10-m scale, grazing increased temporal heterogeneity only on 1- and 20-yr burn sites. Our results show that the individual effects of fire and grazing on spatial and temporal heterogeneity in mesic prairie are scale independent, but the interactive effects of these disturbances on community heterogeneity change with scale of measurement. These patterns reflect the homogenizing impact of fire at all spatial scales, and the different frequency, intensity, and scale of patch grazing by bison in frequently burned vs. infrequently burned areas.     

Hierarchical analysis of species distributions and abundance across environmental gradients

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes interact across scales. Traditional statistical models that ignore autocorrelation and spatial hierarchies can result in misidentification of important ecological covariates. Here, we demonstrate the utility of a hierarchical modeling framework for testing hypotheses about the importance of abiotic factors at different spatial scales and local spatial autocorrelation for shaping species distributions and abundances. For the two orchid species studied, understory light availability and soil moisture helped to explain patterns of presence and abundance at a microsite scale (<4 m2), while soil organic content was important at a population scale (<400 m2). The inclusion of spatial autocorrelation is shown to alter the magnitude and certainty of estimated relationships between abundance and abiotic variables, and we suggest that such analysis be used more often to explore the relationships between species life histories and distributions. The hierarchical modeling framework is shown to have great potential for elucidating ecological relationships involving abiotic and biotic processes simultaneously at multiple scales.     

Scale dependency of conservation outcomes in a forest-offsetting scheme

Offset schemes help avoid or revert habitat loss through protection of existing habitat (avoided deforestation), through the restoration of degraded areas (natural regrowth), or both. The spatial scale of an offset scheme may influence which of these 2 outcomes is favored and is an important aspect of the scheme's design. However, how spatial scale influences the trade-offs between the preservation of existing habitat and restoration of degraded areas is poorly understood. We used the largest forest offset scheme in the world, which is part of the Brazilian Forest Code, to explore how implementation at different spatial scales may affect the outcome in terms of the area of avoided deforestation and area of regrowth. We employed a numerical simulation of trade between buyers (i.e., those who need to offset past deforestation) and sellers (i.e., landowners with exceeding native vegetation) in the Brazilian Amazon to estimate potential avoided deforestation and regrowth at different spatial scales of implementation. Allowing offsets over large spatial scales led to an area of avoided deforestation 12 times greater than regrowth, whereas restricting offsets to small spatial scales led to an area of regrowth twice as large as avoided deforestation. The greatest total area (avoided deforestation and regrowth combined) was conserved when the spatial scale of the scheme was small, especially in locations that were highly deforested. To maximize conservation gains from avoided deforestation and regrowth, the design of the Brazilian forest-offset scheme should focus on restricting the spatial scale in which offsets occur. Such a strategy could help ensure conservation benefits are localized and promote the recovery of degraded areas in the most threatened forest landscapes.     

Scale-Dependent Effects of Habitat Disturbance on Species Richness in Tropical Forests

Abstract: Despite growing concern, no consensus has emerged over the effects of habitat modification on species diversity in tropical forests. Even for comparatively well-studied taxa such as Lepidoptera, disturbance has been reported to increase and decrease diversity with approximately equal frequency. Species diversity within landscapes depends on the spatial scale at which communities are sampled, and the effects of disturbance in tropical forests have been studied at a wide range of spatial scales. Yet the question of how disturbance affects diversity at different spatial scales has not been addressed. We reanalyzed data from previous studies to examine the relationship between spatial scale and effects of disturbance on tropical-forest Lepidoptera. Disturbance had opposite effects on diversity at large and small scales: as scale decreased, the probability of a positive effect of disturbance on diversity increased. We also explicitly examined the relationship between spatial scale and the diversity of butterflies in selectively logged and unlogged forest in Maluku Province, Indonesia. Species richness increased with spatial scale in both logged and unlogged forest, but at a significantly faster rate in unlogged forest, whereas species evenness increased with scale in unlogged forest but did not increase with scale in logged forest. These data indicate that the effects of habitat modification on species diversity are heavily scale-dependent. As a result, recorded effects of disturbance were strongly influenced by the spatial scale at which species assemblages were sampled. Future studies need to account for this by explicitly examining the effects of disturbance at a number of different spatial scales. A further problem arises because the relationship between scale and diversity is likely to differ among taxa in relation to mobility. This may explain to some extent why the measured effects of disturbance have differed between relatively mobile and immobile taxa.     

Variation at local scales need not impede tests for broader scale patterns

Ecologists are not always mindful of the constraints imposed by their scale of observation and sometimes prematurely attempt broad generalisations or become mesmerised by local details depending on their predilections. We specifically chose a character that is known for its local and unpredictable variation (morphology of kelp) to test the effect of scale on our ability to determine spatial patterns. We compared the morphology of Ecklonia radiata between monospecific and mixed stands of canopy-forming algae across temperate Australia (>5,100 km coastal distance) within a hierarchy of several spatial scales. While E. radiata specimens were generally larger in monospecific than in mixed stands, we failed to observe differences in morphology between stands at many sites and locations. Despite substantial local variation, differences between stands became increasingly clear at broader scales. The frequency of inconsistent differences between stands was greatest at local scales (sites separated by kms), intermediate at intermediate scales (locations separated by 100s of kms) and least at regional scales (regions separated by 1,000s of kms). These observations support the idea that large scale patterns can emerge from apparent stochasticity at small scales, and that unaccountable variation at local scales need not impede tests for similar patterns at broader scales. Most ecologists work at scales where complexity tends to be greatest (i.e. local) and is likely to be explained by special and unique events. It is encouraging, therefore, to observe that patterns can emerge from complexity at local scales to provide new opportunities to answer some of the more interesting questions about the relative importance of processes across the vast parts of the worlds coast.Communicated by M.S. Johnson, Crawley     

Variations in mortality of a coral-reef fish: links with predator abundance

The mortality rates of a pomacentrid Acanthochromis polyacanthus were examined in relation to the abundance of large predatory fish (>200 mm total length, TL) at two spatial scales. Survivorship was negatively related to patterns of predator abundance at a large spatial scale (hundreds of metres) over 3 yr, but not at a small spatial scale (tens of metres) over 2 yr. On the large scale, mortality was consistently greater (14 to 30%) in locations where there were greater numbers of predators, and lower in locations where predators occurred in smaller numbers. Among these locations, spatial differences in rank abundance of surviving juveniles were primarily due to mortality, whereas temporal differences in rank abundance were primarily due to initial juvenile abundance. These data suggest that impacts of large predatory fish were likely to have been greater in space than time and at the large spatial scale than the small spatial scale.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.     

Linking chronic wasting disease to mule deer movement scales: a hierarchical Bayesian approach.

Observed spatial patterns in natural systems may result from processes acting across multiple spatial and temporal scales. Although spatially explicit data on processes that generate ecological patterns, such as the distribution of disease over a landscape, are frequently unavailable, information about the scales over which processes operate can be used to understand the link between pattern and process. Our goal was to identify scales of mule deer (Odocoileus hemionus) movement and mixing that exerted the greatest influence on the spatial pattern of chronic wasting disease (CWD) in northcentral Colorado, USA. We hypothesized that three scales of mixing (individual, winter subpopulation, or summer subpopulation) might control spatial variation in disease prevalence. We developed a fully Bayesian hierarchical model to compare the strength of evidence for each mixing scale. We found strong evidence that the finest mixing scale corresponded best to the spatial distribution of CWD infection. There was also evidence that land ownership and habitat use play a role in exacerbating the disease, along with the known effects of sex and age. Our analysis demonstrates how information on the scales of spatial processes that generate observed patterns can be used to gain insight when process data are sparse or unavailable.     

Productivity alters the scale dependence of the diversity-invasibility relationship

At small scales, areas with high native diversity are often resistant to invasion, while at large scales, areas with more native species harbor more exotic species, suggesting that different processes control the relationship between native and exotic species diversity at different spatial scales. Although the small-scale negative relationship between native and exotic diversity has a satisfactory explanation, we lack a mechanistic explanation for the change in relationship to positive at large scales. We investigated the native-exotic diversity relationship at three scales (range: 1-4000 km2) in California serpentine, a system with a wide range in the productivity of sites from harsh to lush. Native and exotic diversity were positively correlated at all three scales; it is rarer to detect a positive relationship at the small scales within which interactions between individuals occur. However, although positively correlated on average, the small-scale relationship between native and exotic diversity was positive at low-productivity sites and negative at high-productivity sites. Thus, the change in the relationship between native and exotic diversity does not depend on spatial scale per se, but occurs whenever environmental conditions change to promote species coexistence rather than competitive exclusion. This occurred within a single spatial scale when the environment shifted from being locally unproductive to productive.     

Beta diversity at different spatial scales: plant communities in organic and conventional agriculture.

Biodiversity studies that guide agricultural subsidy policy have generally compared farming systems at a single spatial scale: the field. However, diversity patterns vary across spatial scales. Here, we examined the effects of farming system (organic vs. conventional) and position in the field (edge vs. center) on plant species richness in wheat fields at three spatial scales. We quantified alpha-, beta-, and gamma-diversity at the microscale in 800 plots, at the mesoscale in 40 fields, and at the macroscale in three regions using the additive partitioning approach, and evaluated the relative contribution of beta-diversity at each spatial scale to total observed species richness. We found that alpha-, beta-, and gamma-diversity were higher in organic than conventional fields and higher at the field edge than in the field center at all spatial scales. In both farming systems, beta-diversity at the meso- and macroscale explained most of the overall species richness (up to 37% and 25%, respectively), indicating considerable differences in community composition among fields and regions due to environmental heterogeneity. The spatial scale at which beta-diversity contributed the most to overall species richness differed between rare and common species. Total richness of rare species (present in < or = 5% of total samples) was mainly explained by differences in community composition at the meso- and macroscale (up to 27% and 48%, respectively), but only in organic fields. Total richness of common species (present in > or = 25% of total samples) was explained by differences in community composition at the micro- and mesoscale (up to 29% and 47%, respectively), i.e., among plots and fields, independent of farming system. Our results show that organic farming made the greatest contribution to total species richness at the meso (among fields) and macro (among regions) scale due to environmental heterogeneity. Hence, agri-environment schemes should exploit this large-scale contribution of beta-diversity by tailoring schemes at regional scales to maximize dissimilarity between conservation areas using geographic information systems rather than focusing entirely at the classical local-field scale, which is the current practice.