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。     

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.     

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。     

基于地理探测器的土壤重金属影响因子分析及其污染风险评价

地理探测器能快速定量化揭示驱动重金属含量影响因素的强度,这对于重金属空间预测模型构建变量的确定和土壤污染修复措施的精准实施具有重要意义。利用地理探测器模型,对5种土壤重金属元素Cu、Zn、Pb、Cr、Ni的空间分布和11种环境因子的交互作用进行定量评估,通过单因子指数法进行重庆市土壤重金属污染风险评价。结果表明:研究区内土壤Cu、Zn、Cr和Pb的平均含量是重庆市土壤背景值的1.3—1.4倍,Ni含量低于背景值;其中Cu、Pb达到重度污染水平,其余3种重金属为中度或轻度污染水平。5种重金属元素中Cu和Pb为高度变异(变异系数为0.57、0.4),Zn、Cr和Ni为中等变异(变异系数为0.22—0.29),且各重金属元素之间呈显著正相关性,表明研究区重金属富集受人为干扰影响较大,且污染具有复合性或同源性。地理探测器的因子探测发现高程、坡度和土壤类型对5种土壤重金属含量的解释力最显著,说明地势和土壤类型是土壤重金属含量分布差异的最主要影响因素。交互作用探测发现,高程与其他因子交互作用是重金属空间分异的主导因素,气候条件和土壤类型也是重要影响因子。土壤重金属空间分布是多种因素共同作用的结果,而高程、坡度和土壤类型具有较强的解释力,这些因子可作为土壤重金属含量空间预测模型的辅助变量,也可促进重金属污染治理措施的靶向实施。     

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.     

宁东基地不同燃煤电厂周边土壤5种重金属元素污染特征及生态风险

为了解宁东基地不同燃煤电厂周边土壤重金属污染特征,采集并测定了表层土壤样品的Cr、Cd、Pb、As和Hg等5种重金属含量,分析了土壤重金属元素的含量特征、不同风向上重金属含量的分布规律,采用单因子污染指数和综合污染指数对研究区域土壤重金属污染程度进行分析,并利用潜在生态风险指数法对其生态风险进行评价。结果表明:研究区域表层土壤中上述5种重金属元素质量分数的平均值分别为52.19~63.35、0.52~0.57、22.18~26.16、5.57~10.68和0.12~0.18 mg?kg~(-1),均没有超过《国家土壤环境质量标准》(GB15618—1995)二级标准(p H7.5)和《展览会用地土壤环境质量评价标准(暂行)》(HJ350—2007)A级标准限值,但Cd、Pb和Hg的平均值超过了宁夏土壤背景值,其中Pb含量略高于背景值,Cd和Hg含量明显超出背景值,分别是背景值的4.6~5.1和6.0~9.0倍;Cr、Cd、Pb和As含量在不同燃煤电厂不同风向上的变化无明显规律,而Hg含量呈现西北风向最小,东南风向最大的分布规律,明显受主导风向影响;经单因子污染指数和综合污染指数评价,不同燃煤电厂周边表层土壤重金属的单项和综合污染指数均小于0.7,污染水平属于"清洁"。潜在生态风险指数评价结果进一步表明,电厂周边表层土壤呈轻微生态风险。尽管不同燃煤电厂周边表层土壤受重金属污染影响较小,但Cd和Hg含量在当地积累明显,这2种重金属元素的防治应受到重点关注。该研究可为宁东基地不同燃煤电厂周边土壤重金属污染防治和管理提供理论依据     

重庆某废弃电镀工业园农田土壤重金属污染调查与生态风险评价

以重庆市某废弃电镀工业园周边农田土壤(0—20 cm)为研究对象,分析了土壤中Cr、Ni、Cu、Zn及Cd含量,评估了农田土壤重金属污染程度以及潜在生态风险.结果表明,废弃电镀工业园周边农田土壤均受到了不同程度的重金属污染,其中Cr、Ni、Cu、Zn、Cd的含量平均值分别为重庆土壤环境背景值的6.77、2.02、4.05、4.29、3.14倍,土壤总体表现为以Cr、Zn为主的多种重金属富集.单因子污染指数评价显示,该区域农田土壤5种重金属的污染程度依次为CrZnCuCdNi;综合污染指数评价和综合潜在生态风险评价表明,该区域整体呈现重度污染,轻度潜在生态风险水平.     

宁东基地不同工业园区周边土壤重金属污染特征及其评价

为了解宁东基地不同工业园区周边土壤重金属污染特征,采集并测定了土壤样品的重金属含量(Cr、Cd、Pb、As和Hg),进一步采用Tessier连续提取法对Cr、Cd、Pb和Hg含量超出背景值的土壤样品进行了重金属形态分析。采用单因子污染指数和综合污染指数对研究区土壤重金属污染程度进行分析,并利用潜在生态风险指数法对其进行生态风险评价,旨在为宁东基地土壤环境保护及生态系统维护提供科学理论依据。结果表明:研究区土壤中上述5种重金属含量的平均值分别为63.26、0.13、21.11、8.77和0.17 mg?kg~(-1),均没有超过《国家土壤环境质量标准》(GB15618—1995)二级标准(p H7.5)和《展览会用地土壤环境质量评价标准(暂行)》(HJ350—2007)A级标准限值,但Cr、Cd和Pb和Hg的平均值超过了宁夏土壤背景值,其中Cr、Cd和Pb的平均值与对应背景值相差不大,Hg的平均值是背景值的8.5倍。重金属形态分析表明,Cr和Hg主要以稳定的残余态形式存在,Cd和Pb主要以非残余态(可交换态、碳酸盐结合态、铁锰氧化物结合态和有机结合态)形式存在,分别占对应总量的65.09%和66.05%。经单因子污染指数和综合污染指数评价,各重金属元素的污染等级均为清洁(安全)水平,研究区土壤表现为无重金属污染状态。潜在生态风险指数评价结果进一步表明,研究区土壤整体呈轻微生态风险。尽管宁东基地不同工业园区周边土壤目前受重金属污染影响较小,但Hg积累明显,Cd和Pb的非残余态含量和比例较高,这3种元素对土壤环境的影响应予以关注。     

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。     

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.