第一届全国生物多样性监测研讨会第一轮通知

<正>生物多样性监测是对生物多样性组成和变化进行的有计划的观察和记录,对生物多样性进行监测是生态学研究、物种保护管理和资源可持续利用的核心环节,是评估生物多样性保护进展的最有效途径。为了中国生物多样性实施全面长期监测,在全国范围内组建生物多样性专业监测和研究队伍,建立全国生物多样性监测信息数据共享平台,定期发布生物多样性动态变化数据和综合分析研究成果,中国科学院科技促进发展局、国际生物多样性计划中国委员会、中国科学院生物多样性委     

基于黑土农田生物多样性监测样地的地表大型节肢动物群落特征

农田生态系统是陆地生态系统的重要组成部分,是全球生态与环境研究的关键区之一.为了研究农田生物群落构建过程,探索其多样性维持机理,本研究于2015年在东北典型黑土区建立了16 hm²的农田生物多样性监测样地,按照作物生长期,于玉米生长大喇叭口期(8月初)、抽穗期(9月初)和成熟期(10月初)对陷阱法获取的地表大型节肢动物进行了统计分析.结果表明: 3次调查共获得地表大型节肢动物5284只,隶属于节肢动物门3纲12目32科47种.调查中优势类群3类,常见类群11类.节肢动物营养功能群中植食性和杂食性节肢动物所占比重较大.地表大型节肢动物物种数量和个体数量随作物生长期有显著变化.9月初节肢动物的Shannon多样性指数、Margalef丰富度指数、Pielou均匀度指数相对较高,8月初Simpson优势度指数较高.从不同物种的变异系数(CV)及群落空间插值可以看出,节肢动物群落在水平方向上存在异质性.在与土壤环境因子关系上,双变量相关分析表明,不同月份地表大型节肢动物总个体数与土壤pH值、有机质、全氮、含水量的相关性均未达到显著性水平;典范对应分析(CCA)进一步表明,优势类群和常见类群对环境因子具有较强的适应能力,在研究区内分布广泛.农田生物多样性监测样地内地表节肢动物物种组成丰富,在作物不同生长时期地表节肢动物群落组成及空间分布格局具有明显的变化过程.农田生物多样性监测样地通过大尺度、长时间对样地内土壤动物空间过程进行监测,可以为解决群落生物多样性形成和维持机制提供重要手段.     

欧洲蝴蝶监测的历史、现状与我国的发展对策

蝴蝶是进行生物多样性监测、评估及生态环境影响评价的重要指示生物.欧洲对蝴蝶的种类组成、种群动态与分布的长期监测已有数十年的历史,先后实施了许多具有国际性影响的长期监测计划.这些计划的目标是评估区域及国家范围的蝴蝶物种丰富度的变化趋势,分析其与栖境和气候变化等环境因素的相关性,为研究、保护和利用蝴蝶资源及预测环境变化提供基础数据,并在蝴蝶受威胁等级的划分、保护措施的制定、生态环境保护与管理等方面发挥了重要作用.本文在总结欧洲蝴蝶监测历史及现状的基础上,着重介绍英国蝴蝶监测计划(The UK Butterfly Monitoring Scheme, UKBMS)、德国及欧盟等重要的蝴蝶监测计划,同时提出了开展我国蝴蝶监测工作的具体建议.     

物种谱系不确定性对群落谱系格局指标的影响

物种谱系关系常被用于衡量群落谱系格局及推断格局背后的生态过程,但多数研究往往忽视谱系关系的不确定性及其可能对群落谱系格局造成的影响.为此,本文以浙江天童20 hm^2样地内150个树种为研究对象,采用这些物种叶绿体DNA的rbcL和matK碱基序列构建1棵一致系统发育树和反映谱系不确定性的999棵系统发育树,然后结合样地物种分布数据计算标准化净亲缘指数(NRI)和最近亲缘指数(NTI),最后运用独立置换零模型衡量样地群落谱系格局.结果表明:物种系统发育树在拓扑结构和物种谱系分支节点年龄上均存在较大的不确定性,谱系不确定性随着谱系分支节点年龄的减小而增大,也随物种间平均谱系距离的增加而增加;在样方尺度上,物种谱系的不确定性增加了标准化NRI和NTI指数的变异,但对两个指数的影响几乎独立;其对两指数的空间分布影响不同,且程度不一,其中标准化NRI受到的影响相对更大;在群落尺度上,物种谱系的不确定性增加了标准化NRI和NTI的变异,平均变异系数分别为0.37和0.077,表明群落水平的标准化NRI更易受到谱系不确定性的影响.这说明物种谱系不确定性会传递到常用的群落谱系格局指标中,且不同指标受影响的程度不同,进而影响对群落谱系格局的衡量及相关生态过程的推断.该结论也暗示以往不考虑谱系不确定性的研究中,非随机的群落谱系格局比例可能被高估.     

喀斯特常绿落叶阔叶混交林木本植物组成特征

喀斯特常绿落叶阔叶混交林是我国西南喀斯特地区分布的典型森林植被类型之一,由于富钙偏碱的地球化学背景及多样性的生境类型,该森林具有群落结构多样、树种组成丰富、优势物种突出等特点,基于大型动态监测样地的群落特征分析是揭示其生物多样性维持机制的基础。该研究在木论国家自然保护区建立了25 hm2的样地,依照CTFS全球森林生物多样性监测规范,定位并调查了样地内每一棵胸径≥1 cm的木本植物。结果表明：(1)样地内有监测树种254种,隶属于64科161属;独立个体总数为110370株(含分枝为144679株),平均胸径为4.14 cm。(2)个体数最多的15个树种的个体数之和占到总个体数的78.46％,稀有种有100种,占总树种数的39.37％。(3)群落结构稳定且更新良好,木本植物整体径级结构呈倒“J”形。(4)样地内重要值≥1的树种有26种,占总树种数量10.24％;重要值排名前三的物种分别是小果厚壳桂、栀子皮和香叶树。(5)样地中共有萌生木本植物204种34309株,分属于127属51科,分别占样地总物种、个体数量、属及科数的80.32％、14.42％、78.88％和79.69％。此结果表明木论喀斯特常绿落叶阔叶混交林物种组成丰富、群落成熟稳定、更新良好,反映了亚热带非地带性喀斯特顶极群落常绿落叶阔叶混交林的典型特征。     

浙江天童20ha常绿阔叶林动态监测样地的群落特征

常绿阔叶林是我国东部低海拔地区的典型植被,基于大型动态监测样地的群落特征分析是揭示其生物多样性维持机制的基础.作者在天章国家森林公园建立了20 ha的样地,并完成了第一次群落学特征调查和分析.结果显示,样地内共有胸径≥1 cm的木本植物152种94,603株,隶属51科94属.重要值最大的前3个科依次是山茶科、樟科和壳斗科.属水平上热带区系成分占总属数的52.1%,温带区系成分占42.6%.常绿物种在样地内占绝对优势,占总重要值的80.3%.重要值最大的3个种依次是细枝柃(Eurya loquaiana)、黄丹木姜子(Litsea elongata)和南酸枣(Choerospondias axiliaris);稀有种共计55种,占总物种数的36.2%.木本植物整体径级结构呈逆"J"字型.萌枝分枝 情况表明,常绿物种的萌、分枝能力强于落叶物种.此结果表明天童常绿阔叶林物种组成丰富,群落成熟稳定,更新良好,反映了亚热带东部常绿阔叶林的典型特征.     

中国农田土壤动物长期监测样地科学调查监测的实施方法

我国农田土壤动物面临严峻的多样性丧失问题, 建设监测样地并开展长期监测是解决该问题的重要途径, 但至今国内外仍缺乏农田土壤动物长期监测样地科学调查监测的实施方法。依据BCI 50 ha大型固定样地建设规范, 参照我国已建成的森林和农田土壤动物大型固定样地监测经验, 本文提出了农田土壤动物长期监测样地科学调查监测的实施方法。首先, 需要明确科学问题, 确定科学调查监测应遵守的基本原则。其次, 需要规范长期调查监测涉及的专业术语, 依据研究目的和实际情况选择地点和样地, 参照建设规范和农田特征建立农田土壤动物大型固定样地。第三, 以研究农田土壤动物多样性为核心, 揭示土壤动物在农田生态系统健康和功能中的作用, 有选择性地开展4类27项科学指标的长期监测工作, 要求按照统一的、规范化的工作流程开展野外调查和室内实验。最后, 要科学规范地完成标本的鉴定描述和保存保管, 研发体现农田土壤动物特征的数据库和管理信息系统。希望本文的研究结果能推动我国乃至世界范围的规范化样地建设和标准化网络监测, 为我国农田土壤动物评估与保护提供长期可靠的数据支撑。     

中国海物种多样性研究进展

中国海的生物多样性研究是中国科学院青岛海洋生物研究室1950年成立后开始大规模系统进行的.经过半个多世纪的努力,迄今已有千篇论文和约200部专著出版.主要专著《中国动物志》“无脊椎动物”已出版47卷,其中27卷为海洋生物,5年计划编写中17卷;《中国动物志》“脊椎动物”鱼类11卷,哺乳类1卷;《中国海藻志》8卷,待出版4卷,编写中3卷.另外,《海洋科学集刊》已出版的50卷中有22卷是海洋生物的专刊;另有《西沙群岛生物考察专辑》6卷.其中有代表性的著作《中国海洋生物种类与分布》(黄宗国,1994)集成国内外文献,记载物种20,278种(内有化石种及异名应除去).2008年出版的《中国海洋生物名录》(刘瑞玉主编)记录22,629现生种,比1994年相同门类多5,118种,仅次于澳大利亚和日本,居世界第三位.主要进展是取得了中国海翔实可靠的物种鉴定、编目和分布数据.此外还参加了国际“物种2000”计划项目,交出的“中国生物名录”比2008年名录显著增多.全部物种正进行“世界海洋物种登录,”(WoRMS),可供与世界不同海域和生境的种类多样性作比较研究.完成国家标准《海洋生物分类代码》(国家质量技术监督局1999发布)的修订,纠正了种名和分类系统的错误,增补了物种,保证了作为国家标准的高水平,待付印.完成全国濒危物种评估,负责编写《中国物种红色名录》1、3、2卷海洋无脊椎动物部分;结果发现濒危物种显著增多.1997-2000年“专属经济区大陆架环境资源调查”的结果进一步显示陆架海域生物多样性和主要资源衰退,还提出了应采取的措施.中国参加了国际重大项目“海洋生物普查计划”,进行了浮游动物普查,提交了中国国家汇总报告——中国海生物多样性研究,交PLoS ONE出版.全面加强了多样性和濒危种的保护,全国已建立国家级海洋自然保护区33个,特别保护区21个.论文在肯定中国海生物多样性研究进展和成绩的同时,指出了存在的主要不足是调查采集和研究的生境主要在陆架浅海,深海大洋特殊生境刚刚起步;多样性调查缺少全国统一计划行动,缺全面的多样性“背景值”资料.而监测、采集、研究不够;评估、保护亟待加强.文终提出了几点涉及学科发展和多样性监测、评估、保护的关键性建议.     

鱼类多样性监测的理论方法及中国内陆 水体鱼类多样性监测

近年来, 生物多样性监测网络的建设得到广泛重视, 全球、地区或国家生物多样性观测网不断组建。生物多样性观测的理论框架得到发展, 提出了生物多样性核心监测指标(Essential Biodiversity Variables, EBV)。鱼类多样性监测的理论框架包含于生物多样性核心监测指标之内, 在遗传、物种、生态系统等多层次进行。基于鱼类监测提出的生物完整性指数(index of biotic integrity, IBI)强调不同物种的生态功能, 可以综合反映群落结构和功能的变化, 得到广泛应用。鱼类多样性的监测方法是传统网具和现代水声学等方法的结合。监测结果的分析可以进行简单的指数比较, 也可以进行长期的趋势分析, 寻找关键节点, 探讨宏观生态格局的变化。中国内陆水体鱼类多样性监测网隶属于中国生物多样性监测与研究网络, 拟选取长江、黄河、黑龙江、珠江、澜沧江、怒江、塔里木河及青海湖8大流域, 对25个重要区域和24个重点物种(类群)进行监测, 从重要区域鱼类群落结构、重点物种(类群)种群动态和个体生物学特征、遗传多样性、早期资源等不同层次, 全面监测我国内陆水体鱼类生物多样性状况。     

中国森林生物多样性监测网络: 二十年群落构建机制探索的回顾与展望

中国森林生物多样性监测网络(CForBio)目前已经沿纬度梯度从寒温带到热带布设23个大型森林动态样地, 监测1,893种木本植物, 代表我国木本植物种类的近1/6。CForBio的主要目标之一是研究森林群落的构建机制。本文综述了近20年来CForBio在群落构建机制探索方面取得的进展, 包括生物多样性时空格局、生境过滤、生物相互作用、局域扩散和区域因素以及利用新技术取得的新认知等。CForBio研究发现: (1)生境过滤和扩散限制共同决定种-面积关系及β多样性等多样性格局, 但二者的相对作用在不同样地及不同尺度存在差异; (2)生境过滤对局域群落构建的作用广泛存在, 但很难量化其对群落构建的重要性; (3)同种负密度制约在不同气候带样地普遍存在, 负密度制约的强度主要由植物菌根类型介导, 并随植物生活史类型、功能性状及环境变化而变化; (4)扩散限制在局域群落构建中发挥关键作用, 而区域因素如区域地质历史、区域物种库大小等塑造不同生物地理区群落之间的生物多样性差异; (5)宏观和微观两个方面的新技术促进群落构建机制的研究。在宏观方面, 遥感技术以低成本使大范围、多尺度的连续群落生物多样性监测和时空比较研究成为可能; 另一方面, 叶绿体基因技术和代谢组学等微观技术能促进推导群落构建的分子机制。同时, 本文还总结了以往研究的不足, 并展望了基于森林动态样地开展群落构建机制研究的未来发展, 特别强调了: (1)关注群落构建研究中的尺度问题; (2)深入开展多维度(物种、功能和系统发育)、多营养级生物互作相关的研究; (3)拓展全球变化对群落构建影响的研究; (4)融合观测-实验-模型多种手段开展群落构建机制的研究; (5)连结“群落构建理论研究”和“森林管理实践”。总之, 中国森林生物多样性监测网络的长期监测和联网研究是森林群落构建机制研究的重要基础, 也是推动群落构建理论、解决森林管理难题的重要平台。     

Estimating acridid densities in grassland habitats: a comparison between presence-absence and abundance sampling designs

Sampling methods to estimate acridid density per surface area unit in grassland habitats were compared using presence-absence data and count data. Sampling plans based on 6 yr of surveys were devised to estimate the density of Chorthippus spp., Euchorthippus spp., and Calliptamus italicus L. These acridids represented >90% of species in the study area. Sampling plans based on count data provided a reasonable tool when densities were >1/m(2) and when the level of precision was 0.20-0.30. A binomial sampling plan can be used to estimate C. italicus density with a level of precision >or=0.28. Sampling characteristics, i.e., estimated mean, actual precision, and sample size, were established on validation data sets with bootstrapping analysis. Sampling costs were also calculated according to density-dependent functions. Comparison between binomial sampling and enumerative sampling of C. italicus showed that binomial sampling required less time than enumerative sampling when densities were 0.35. Plot area had no significant effect on sample variances of counts.     

Strategies and Decision-Support Tools for Optimizing Long-Term Groundwater Monitoring Plans—MAROS 2.0

Existing long-term groundwater monitoring programs can be optimized to increase their effectiveness/efficiency with the potential to generate considerable cost savings. The optimization can be achieved through an overall evaluation of conditions of the contaminant plume and the monitoring network, focused spatial and temporal sampling analyses, and automated and efficient management of data, analyses, and reporting. Version 2.0 of the Monitoring and Remediation Optimization System (MAROS) software, by integrating long-term monitoring analysis strategies and innovative optimization methods with a data management, processing, and reporting system, allows site managers to quickly and readily develop cost-effective long-term groundwater monitoring plans. The MAROS optimization strategy consists of a hierarchical combination of analysis methods essential to the decision-making process. Analyses are performed in three phases: 1) evaluating site information and historical monitoring data to obtain local concentration trends and an overview of the plume status; 2) developing optimal sampling plans for future monitoring at the site with innovative optimization methods; and 3) assessing the statistical sufficiency of the sampling plans to provide insights into the future performance of the monitoring program. Two case studies are presented to demonstrate the usefulness of the developed techniques and the rigor of the software.     

Strategies and Decision-Support Tools for Optimizing Long-Term Groundwater Monitoring Plans—MAROS 2.0

Existing long-term groundwater monitoring programs can be optimized to increase their effectiveness/efficiency with the potential to generate considerable cost savings. The optimization can be achieved through an overall evaluation of conditions of the contaminant plume and the monitoring network, focused spatial and temporal sampling analyses, and automated and efficient management of data, analyses, and reporting. Version 2.0 of the Monitoring and Remediation Optimization System (MAROS) software, by integrating long-term monitoring analysis strategies and innovative optimization methods with a data management, processing, and reporting system, allows site managers to quickly and readily develop cost-effective long-term groundwater monitoring plans. The MAROS optimization strategy consists of a hierarchical combination of analysis methods essential to the decision-making process. Analyses are performed in three phases: 1) evaluating site information and historical monitoring data to obtain local concentration trends and an overview of the plume status; 2) developing optimal sampling plans for future monitoring at the site with innovative optimization methods; and 3) assessing the statistical sufficiency of the sampling plans to provide insights into the future performance of the monitoring program. Two case studies are presented to demonstrate the usefulness of the developed techniques and the rigor of the software.     

Some new approaches to conservation monitoring of British breeding birds

It is important to monitor bird populations both in their own right and as indicators of the general health of wildlife habitats. The objectives of the British Trust for Ornithology's Integrated Population Monitoring programme relate to breeding bird populations in Britain and Ireland and involve the estimation of demographic parameters as well as assessment of numbers. Current programmes for monitoring bird numbers cover the majority of British species; it would be feasible to monitor most of the rest. A new Breeding Bird Survey has been developed to provide effective coverage of all regions and all major habitats in Britain through random sampling, allowing for the marked geographical variation in volunteer observer density. The final choice of a random sample stratified by observer density (with some professional support in regions with few volunteer observers) was based on comparison with alternative stratifications, using data from a 2-year pilot study to assess the number of species adequately covered under various alternatives. A method of assessing whether or not targets are being achieved at any time has been developed: it involves looking back through the data at intervals of 1-year, 4-year, 16-year and longer spans. It will be possible to refine this by incorporating environmental and density-dependent effects into predictive models. The method is illustrated here using Common Birds Census data. We discuss associated problems of statistical inference and of taking decisions under uncertainty. The data provide evidence for large declines in some species, particularly in farmland; the value of birds as general indicators of habitat health is clear. The results of monitoring can be used to illuminate possible causes of problems and to guide both practical steps to ameliorate the problems and research aimed at better understanding the causes. Examples of such research are discussed.     

Monitoring an Arizona Ponderosa Pine Restoration: Sampling Efficiency and Multivariate Analysis of Understory Vegetation

As monitoring plans for the restoration of Pinus ponderosa forests in the southwestern United States evolve toward examining multifactor ecosystem responses to ecological restoration, designing efficient sampling procedures for understory vegetation will become increasingly important. The objective of this study was to compare understory composition and diversity among thin/burn and control treatments in a P. ponderosa restoration, while simultaneously examining the effects of sampling design and multivariate analyses on which conclusions were based. Using multi‐response permutation procedures (MRPP), we tested the null hypothesis of no difference in understory species composition among treatments using different data matrices (e.g., frequency and cover) for two different sampling methods. Treatment differences were subtle and were detected by an intensive 50, 1‐m² subplot sampling method for all data matrices but were not detected by a less intensive point‐intercept sampling method for any matrix. Sampling methods examined in this study controlled results of multivariate analyses more than the data matrices used to summarize data generated by a sampling method. We partitioned data into plant life form and native/exotic species categories for MRPP, and this partitioning isolated plant groups most responsible for treatment differences. We also examined the effects of number of 1‐m² subplots sampled on mean‐species‐richness/m² estimates and found that estimates based on 10 subplots and based on 50 subplots were highly correlated (r = 0.99). Species–area curves indicated that the 50, 1‐m² subplot sampling method detected the common species of sites but failed to detect the majority of rare species. Additional sampling‐design studies are needed to develop single sampling designs that produce multifactor data on plant composition, diversity, and spatial patterns amenable to multivariate analyses as part of monitoring plans of vegetation responses to ecological restoration.     

Simulations inform design of regional occupancy‐based monitoring for a sparsely distributed,territorial species

Sparsely distributed species attract conservation concern, but insufficient information on population trends challenges conservation and funding prioritization. Occupancy‐based monitoring is attractive for these species, but appropriate sampling design and inference depend on particulars of the study system. We employed spatially explicit simulations to identify minimum levels of sampling effort for a regional occupancy monitoring study design, using white‐headed woodpeckers (Picoides albolvartus), a sparsely distributed, territorial species threatened by habitat decline and degradation, as a case study. We compared the original design with commonly proposed alternatives with varying targets of inference (i.e., species range, space use, or abundance) and spatial extent of sampling. Sampling effort needed to achieve adequate power to observe a long‐term population trend (≥80% chance to observe a 2% yearly decline over 20 years) with the previously used study design consisted of annually monitoring ≥120 transects using a single‐survey approach or ≥90 transects surveyed twice per year using a repeat‐survey approach. Designs that shifted inference toward finer‐resolution trends in abundance and extended the spatial extent of sampling by shortening transects, employing a single‐survey approach to monitoring, and incorporating a panel design (33% of units surveyed per year) improved power and reduced error in estimating abundance trends. In contrast, efforts to monitor coarse‐scale trends in species range or space use with repeat surveys provided extremely limited statistical power. Synthesis and applications. Sampling resolutions that approximate home range size, spatially extensive sampling, and designs that target inference of abundance trends rather than range dynamics are probably best suited and most feasible for broad‐scale occupancy‐based monitoring of sparsely distributed territorial animal species.     

Bird Conservation: The Science and the Action Report on the BOU Joint Conference, 6–10 April 1994

• 1 Birds are hugely popular and the public demands their conservation.
• 2 Ornithology has made a major contribution to nature conservation by virtue of this popular support. The value of birds as environmental indicators has been greatly enhanced by voluntary data collection on a wide scale over many years.
• 3 Habitat loss and degradation are the main causes of species decline, even though other factors may contribute to extinction. More research should address the causes of decline at an early stage, while the chance of recovery is highest.
• 4 The geographical ranges of native bird species should be maintained, both to avoid the risk of local or wider extinction and to enable people to enjoy them as part of their normal experience.
• 5 To maintain species ranges. conservation must be incorporated in policies affecting the wider countryside and the sea. This is as important as managing protected areas.
• 6 The management of protected areas can only be successful in the context of sympathetic management of the surrounding countryside.
• 7 The Biodiversity Convention requires countries to produce national conservation plans and strategies. This offers ornithologists an unprecedented opportunity to contribute to conservation by developing explicit objectives and specific targets for the maintenance (or restoration) of numbers and distributions of species, and of extent and quality of habitats. Targets should be ambitious but realistic and be sufficiently precise as to be testable.
• 8 Predictive models have the potential to support conservation advice, but traditional natural history studies have proved vital in the past and theory could not replace them.
• 9 Detailed ecological research with long data runs is the ideal basis for conservation action. But urgency demands shorter studies, informed by ecological intuition and knowledge, and reaching specific recommendations for action.
• 10 Conservation actions should be treated as experiments so that techniques can be improved progressively. This applies both to the management of nature reserves and to habitat management stemming from broader policy measures, for example in Environmentally Sensitive Areas.
• 11 Monitoring across a wide species base is essential because the threats to wildlife are unpredictable. Birds have proven to be successful indicators because they are highly visible: are enthusiastically counted by volunteers: and respond to a wide variety of environmental impacts.
• 12 Threshold levels, indicating the normal upper and lower levels of variation (for instance in numbers or breeding success), are needed in order to trigger prompt remedial action.
• 13 Monitoring, research and consenration action must be taken forward internationally. Integrated and common approaches enable exchange of data and inforniation. and reinforce national actions across the range.
• 14 Fxisting data need to be made more accessible by greater collaboration and openness, and by the use of computerization.
• 15 Ornithologists need to build stronger partnerships, both with other biologists and with decision-makers across the range of land-use and economic policy. This will be helped by better communication built on clear but simple messages for non-biologists.
• 16 The training of future ecologists should take account of the wide range of skills required by the expanding discipline of conservation.

     

Development and economic evaluation of spatial sampling plans for corn rootworm Diabrotica spp. (Col., Chrysomelidae) adults

Abstract  To develop spatial sampling plans for corn rootworm ( Diabrotica spp.) adults, their spatial distributions were characterized and economics of sampling plans were evaluated by comparing sampling costs between spatial and conventional (non-spatial) sampling plans. Semivariogram modelling and spatial by with distance indices showed that corn rootworm adults were significantly (P < 0.05) aggregated at peak population densities and any two samples were spatially correlated within approximately 45 m, with 39–90% of the variability explained by spatial dependence. Sampling costs for spatial sampling plans linearly increased as the sampling distance decreased and exponentially increased as the field size increased. Although sampling costs for non-spatial sampling plans were generally lower, spatial sampling plans could be more economical when the mean insect density became lower and the field size became smaller. This study demonstrated that spatial sampling plans could be optimized to minimize the sampling costs and maximize the spatial resolution.     

Using higher taxa as surrogates of species-level data in three Portuguese protected areas: a case study on Spheciformes (Hymenoptera)

Protected areas are the focus of most conservation efforts worldwide. Despite vast amount of investment in protected areas, biodiversity loss continues. This has led to increasing efforts to develop measures to assess the effectiveness of protected areas. The reliability of these measures depends on the quality of the information collected. However, because the resources available for the collection of information are limited, several strategies have been developed to reduce the resources necessary. In this study the combination of two resource reduction approaches—bioindicator and higher-taxa—is proposed. Spheciformes have been found to be useful as biodiversity, ecological and environmental indicators. Identification to the species level is usually very costly, but the use of genus-level information has been suggested. Tribe- and genus-level data for Spheciformes were assessed for their ability to predict the number of species independently of other variables—sampling area, geographic location, vegetation type, disturbance regime, and sampling effort—at three Portuguese protected areas. Tribe and genus-level data were found to be good indicators, with genus being the more reliable taxonomic level. Sampling effort was the only external variable that affected the relationship between species and higher-taxa richness. Genus-level data were also found to be useful for ranking sites according to richness or composition, and for determining richness-based and rarity-based complementary sets of sites for conservation. Using genus richness as a surrogate for species richness seems a promising approach for monitoring and contributing to the establishment of protected areas in Portugal and the entire Mediterranean region.     

Iwao’s patchiness regression through the origin: biological importance and efficiency of sampling applications

Iwao’s mean crowding-mean density relation can be treated both as a linear function describing the biological characteristics of a species at a population level, or a regression model fitted to empirical data (Iwao’s patchiness regression). In this latter form its parameters are commonly used to construct sampling plans for insect pests, which are characteristically patchily distributed or overdispersed. It is shown in this paper that modifying both the linear function and statistical model to force the intercept or lower functional limit through the origin results in more intuitive biological interpretation of parameters and better sampling economy. Firstly, forcing the function through the origin has the effect of ensuring that zero crowding occurs when zero individuals occupy a patch. Secondly, it ensures that negative values of the intercept, which do not yield an intuitive biological interpretation, will not arise. It is shown analytically that sequential sampling plans based on regression through the origin should be more efficient compared to plans based on conventional regression. For two overdispersed data sets, through-origin based plans collected a significantly lower sample size during validation than plans based on conventional regression, but the improvement in sampling efficiency was not large enough to be of practical benefit. No difference in sample size was observed when through-origin and conventional regression based plans were validated using underdispersed data. A field researcher wishing to adopt a through-origin form of Iwao’s regression for the biological reasons outlined above can therefore be confident that their sampling strategies will not be affected by doing so.