基于MODIS数据的河南省冬小麦产量遥感估算模型

小麦是世界上最重要的粮食作物,小麦生产对中国的粮食保障起着十分重要的作用,及时、准确、大范围对小麦产量进行监测预报,对于农学经济发展和粮食政策制定具有极为重要的现实意义。对作物产量进行遥感监测的原理是建立在其遥感特征基础之上的,通过建立作物长势指标与遥感信息的定量关系,可实现对作物产量的监测预报。文章基于2009年MODIS遥感数据和气象数据,利用Arcgis和ENVI提取纯小麦像元,并提取纯小麦像元对应的NDVI、NPP和LAI,获取分县NDVI、NPP和LAI均值,利用统计软件对产量数据和分县遥感参数均值进行数据整理和分析,建立了河南省冬小麦产量估算模型。以往研究多采用遥感图像上某像元和地面调查点进行研究,具有很大的不确定性,文章以县为单位,对冬小麦平均单产和县域内冬小麦种植像元遥感参数的均值进行相关研究,提高了模型模拟精度。同时文章选用多种遥感参数和多项气象因子建立估产模型,避免了针对一个参数进行估产的局限性。在最佳时相的选择上,根据冯美辰（2010）以往的研究结果,从4月以后,5月8日和4月20Et植被指数和产量相关性最大,4月份之前冬小麦处于返青到拔节期,对产量来说还有很多不确定闪素,因此文章选用5月8El和4月20日进行冬小麦估产研究。结果表明,5月8日的估产模型优于4月20日,加入气象冈子的遥感气象估产模型优于只采用遥感参数进行估产的遥感模型。利用2010年产量数据对模型精度进行检验,遥感气象模型预测精度在70．2％N99．7％之间,平均精度为90．7％;遥感模型预测精度在68．1％到95．5％之间,平均精度为83．9％。表明遥感气象模型模拟精度更高,其精度可以满足大面积估产要求,可以对产量预报提供科学参考。     

Empirical realised niche models for British coastal plant species

Coastal environments host plant taxa adapted to a wide range of salinity conditions. Salinity, along with other abiotic variables, constrains the distribution of coastal plants in predictable ways, with relatively few taxa adapted to the most saline conditions. However, few attempts have been made to quantify these relationships to create niche models for coastal plants. Quantification of the effects of salinity, and other abiotic variables, on coastal plants is essential to predict the responses of coastal ecosystems to external drivers such as sea level rise. We constructed niche models for 132 coastal plant taxa in Great Britain based on eight abiotic variables. Paired measurements of vegetation composition and abiotic variables are rare in coastal habitats so four of the variables were defined using community mean values for Ellenberg indicators, i.e. scores assigned according to the typical alkalinity, fertility, moisture availability and salinity of sites where a species occurs. The remaining variables were the canopy height, annual precipitation, and maximum and minimum temperatures. Salinity and moisture indicator scores were significant terms in over 80 % of models, suggesting the distributions of most coastal species are at least partly determined by these variables. When the models were used to predict species occurrence against an independent dataset 64 % of models gave moderate to good predictions of species occurrence. This indicates that most models had successfully captured the key determinants of the niche. The models could potentially be applied to predict changes to habitats and species-dependent ecosystem services in response to rising sea levels.     

Use of Community‐Composition Data to Predict the Fecundity and Abundance of Species

Abstract: Species distribution models are critical tools for the prediction of invasive species spread and conservation of biodiversity. The majority of species distribution models have been built with environmental data. Community ecology theory suggests that species co‐occurrence data could also be used to predict current and potential distributions of species. Species assemblages are the products of biotic and environmental constraints on the distribution of individual species and as a result may contain valuable information for niche modeling. We compared the predictive ability of distribution models of annual grassland plants derived from either environmental or community‐composition data. Composition‐based models were built with the presence or absence of species at a site as predictors of site quality, whereas environment‐based models were built with soil chemistry, moisture content, above‐ground biomass, and solar radiation as predictors. The reproductive output of experimentally seeded individuals of 4 species and the abundance of 100 species were used to evaluate the resulting models. Community‐composition data were the best predictors of both the site‐specific reproductive output of sown individuals and the site‐specific abundance of existing populations. Successful community‐based models were robust to omission of data on the occurrence of rare species, which suggests that even very basic survey data on the occurrence of common species may be adequate for generating such models. Our results highlight the need for increased public availability of ecological survey data to facilitate community‐based modeling at scales relevant to conservation.     

Evaluating the efficacy of restoration plantings through DNA barcoding of frugivorous bird diets

Frugivores are critical components of restoration programs because they are seed dispersers. Thus, knowledge about bird–plant trophic relationships is essential in the evaluation of the efficacy of restoration processes. Traditionally, the diet of frugivores is characterized by microscopically identifying plant residues in droppings, which is time‐consuming, requires botanical knowledge, and cannot be used for fragments lacking detectable morphological characteristics (e.g., fragmented seeds and skins). We examined whether DNA barcoding can be used as a universal tool to rapidly characterize the diet of a frugivorous bird, Eurasian blackcap (Sylvia atricapilla). We used the DNA barcoding results to assess restoration efforts and monitor the diversity of potentially dispersed plants in a protected area in northern Italy. We collected 642 Eurasian Blackcap droppings at the restored site during the autumn migration over 3 years. Intact seeds and fragmented plant material were analyzed at 2 plastidial barcode loci (rbcL and trnH‐psbA), and the resulting plant identifications were validated by comparison with a reference molecular data set of local flora. At least 17 plant species, including 7 of the 11 newly transplanted taxa, were found. Our results demonstrate the potential for DNA barcoding to be used to monitor the effectiveness of restoration plantings and to obtain information about fruit consumption and dispersal of invasive or unexpected plant species. Such an approach provides valuable information that could be used to study local plant biodiversity and to survey its evolution over time.     

地表臭氧浓度升高对冬小麦和大豆生长和产量的影响

我国近地层臭氧污染日趋严重,其不断增加的浓度对农作物的生长造成了严重威胁。以冬小麦和大豆为研究对象,基于大田开顶式气室(OTC)试验,分别设置对照(CK)、100 n L·L~(-1)和150 n L·L~(-1)这3个O3浓度处理组,对2种作物生长指标和产量等参数连续观测,结果表明:O3浓度增加对冬小麦和大豆的株高、叶面积和生物量产生影响,并且对大豆的影响更为明显。与此同时,O3浓度增加使得冬小麦的穗重、穗粒数以及大豆的单株荚数、单株粒数、单株粒重都呈现大幅度下降状态,进而导致其产量降低。在100 n L·L~(-1)臭氧处理下,冬小麦产量较CK降低了12.89%,而大豆产量下降了23.76%。在150 n L·L~(-1)的臭氧处理下,冬小麦产量较对照组降低了29.23%,大豆则比对照组下降了41.57%,与CK相比,大豆产量下降更为明显。上述研究表明,臭氧污染对农作物的生长具有显著影响,且大豆对O3的反应比冬小麦敏感。     

Testing ecological models: the meaning of validation

The ecological literature reveals considerable confusion about the meaning of validation in the context of simulation models. The confusion arises as much from semantic and philosophical considerations as from the selection of validation procedures. Validation is not a procedure for testing scientific theory or for certifying the ‘truth’ of current scientific understanding, nor is it a required activity of every modelling project. Validation means that a model is acceptable for its intended use because it meets specified performance requirements.Before validation is undertaken, (1) the purpose of the model, (2) the performance criteria, and (3) the model context must be specified. The validation process can be decomposed into several components: (1) operation, (2) theory, and (3) data. Important concepts needed to understand the model evaluation process are verification, calibration, validation, credibility, and qualification. These terms are defined in a limited technical sense applicable to the evaluation of simulation models, and not as general philosophical concepts. Different tests and standards are applied to the operational, theoretical, and data components. The operational and data components can be validated; the theoretical component cannot.The most common problem with ecological and environmental models is failure to state what the validation criteria are. Criteria must be explicitly stated because there are no universal standards for selecting what test procedures or criteria to use for validation. A test based on comparison of simulated versus observed data is generally included whenever possible. Because the objective and subjective components of validation are not mutually exclusive, disagreements over the meaning of validation can only be resolved by establishing a convention.     

Niche complementarity due to plasticity in resource use: plant partitioning of chemical N forms

Niche complementarity, in which coexisting species use different forms of a resource, has been widely invoked to explain some of the most debated patterns in ecology, including maintenance of diversity and relationships between diversity and ecosystem function. However, classical models assume resource specialization in the form of distinct niches, which does not obviously apply to the broadly overlapping resource use in plant communities. Here we utilize an experimental framework based on competition theory to test whether plants partition resources via classical niche differentiation or via plasticity in resource use. We explore two alternatives: niche preemption, in which individuals respond to a superior competitor by switching to an alternative, less-used resource, and dominant plasticity, in which superior competitors exhibit high resource use plasticity and shift resource use depending on the competitive environment. We determined competitive ability by measuring growth responses with and without neighbors over a growing season and then used 15N tracer techniques to measure uptake of different nitrogen (N) forms in a field setting. We show that four alpine plant species of differing competitive abilities have statistically indistinguishable uptake patterns (nitrate > ammonium > glycine) in their fundamental niche (without competitors) but differ in whether they shift these uptake patterns in their realized niche (with competitors). Competitively superior species increased their uptake of the most available N form, ammonium, when in competition with the rarer, competitively inferior species. In contrast, the competitively inferior species did not alter its N uptake pattern in competition. The existence of plasticity in resource use among the dominant species provides a mechanism that helps to explain the manner by which plant species with broadly overlapping resource use might coexist.     

开花前后变水条件对春小麦的补偿效应

在防雨棚内的盆栽实验条件下，研究了4种梯度的10种不分组合对红芒麦和宁春10号产量及耗水量等的影响。结果表明，试验期间充分灌水，轻度，中度，重度干旱处理，随着干旱程度的加剧，株高，干物质积累，产量，耗水量都逐渐减少；红芒麦灌浆期不同程度的,匀有利于产量的形成，促进物质运输，提高千粒重，同时减少水分消耗，提高WUE；孕穗期干旱处理后，灌浆期复水，会造成减产，和灌浆期相比，孕穗期是水分的敏感的时期，而灌浆期对水分亏缺不敏感，两种小麦相比较，宁春10号耗水量大，产量低，抗旱性较强，图2表2参7     

The ecological niche of Daphnia magna characterized using population growth rate

The concept of an organism's niche is central to ecological theory, but an operational definition is needed that allows both its experimental delineation and interpretation of field distributions of the species. Here we use population growth rate (hereafter, pgr) to define the niche as the set of points in niche space where pgr > 0. If there are just two axes to the niche space, their relationship to pgr can be pictured as a contour map in which pgr varies along the axes in the same way that the height of land above sea level varies with latitude and longitude. In laboratory experiments we measured the pgr of Daphnia magna over a grid of values of pH and Ca2+, and so defined its "laboratory niche" in pH-Ca2+ space. The position of the laboratory niche boundary suggests that population persistence is only possible above 0.5 mg Ca2+/L and between pH 5.75 and pH 9, though more Ca2+ is needed at lower pH values. To see how well the measured niche predicts the field distribution of D. magna, we examined relevant field data from 422 sites in England and Wales. Of the 58 colonized water bodies, 56 lay within the laboratory niche. Very few of the sites near the niche boundary were colonized, probably because pgr there is so low that populations are vulnerable to extinction by other factors. Our study shows how the niche can be quantified and used to predict field distributions successfully.     

Evidence of Local Adaptation in the Demographic Response of American Ginseng to Interannual Temperature Variation

Abstract: Bioclimatic envelope models of species’ responses to climate change are used to predict how species will respond to increasing temperatures. These models are frequently based on the assumption that the northern and southern boundaries of a species’ range define its thermal niche. However, this assumption may be violated if populations are adapted to local temperature regimes and have evolved population‐specific thermal optima. Considering the prevalence of local adaptation, the assumption of a species‐wide thermal optimum may be violated for many species. We used spatially and temporally extensive demographic data for American ginseng (Panax quinquefolius L.) to examine range‐wide variation in response of population growth rate (λ) to climatic factors. Our results suggest adaptation to local temperature, but not precipitation. For each population, λ was maximized when annual temperatures were similar to site‐specific, long‐term mean temperatures. Populations from disparate climatic zones responded differently to temperature variation, and there was a linear relation between population‐level thermal optima and the 30‐year mean temperature at each site. For species that are locally adapted to temperature, bioclimatic envelope models may underestimate the extent to which increasing temperatures will decrease population growth rate. Because any directional change from long‐term mean temperatures will decrease population growth rates, all populations throughout a species’ range will be adversely affected by temperature increase, not just populations at southern and low‐elevation boundaries. Additionally, when a species’ local thermal niche is narrower than its range‐wide thermal niche, a smaller temperature increase than would be predicted by bioclimatic envelope approaches may be sufficient to decrease population growth.     

Integrated Monitoring and Information Systems for Managing Aquatic Invasive Species in a Changing Climate

Abstract:  Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change.     

秀丽线虫转基因品系在环境暴露评价与毒理学研究中的应用

目前,模式动物秀丽线虫已被广泛应用于环境暴露评价和环境毒理学研究中.在系统介绍了各种秀丽线虫转基因品系在环境暴露与毒性评价以及环境毒理研究中的应用进展基础上,分析了秀丽线虫转基因品系在环境暴露与毒性评价研究中的灵敏性与直观性的特点.最后,讨论了秀丽线虫转基因品系在环境暴露与毒性评价以及环境毒理研究中尚存在的问题和可能的...     

山西工矿区土壤二氧化硫与多环芳烃复合污染对小麦种子萌发和幼苗生长的影响

以小麦为供试植物,山西工矿区生黄土为供试土壤,进行了土壤中二氧化硫(SO2)与多环芳烃(PAHs)单一及复合污染对小麦种子萌发率及小麦幼苗株高、根伸长和地下生物量影响的研究,以期考察复合污染的生态毒性效应。结果表明,小麦种子萌发对SO2与PAHs单一及复合污染均不敏感;SO2和PAHs单一污染时,小麦幼苗的株高与根伸长均受到一定程度的影响,低浓度SO2或PAHs处理对小麦生长起促进作用,高浓度则为抑制作用;小麦幼苗株高与SO2浓度呈显著负相关(r=-0.954,P<0.05),但与PAHs浓度的相关性不显著;SO2与PAHs复合污染条件下,对小麦幼苗株高或根伸长的联合作用多体现为协同作用,在低浓度情况下(SO2<500mg·kg-1)表现为协同促进;当SO2达到500～1000mg·kg-1时,对小麦幼苗株高或根伸长的联合作用均体现为协同抑制。SO2和PAHs单一污染时,小麦幼苗地下生物量与SO2、PAHs浓度均为显著负相关(rPAHs=-0.953,rSO2=-0.916,P<0.05);复合污染条件下,在SO2浓度为10mg·kg-1时,对地下生物量的联合作用多体现协同促进作用;而在SO2浓度为1000mg·kg-1,PAHs为50～100mg·kg-1时,对地下生物量的联合作用均体现为协同抑制作用。多元逐步回归分析进一步表明,SO2与PAHs复合污染条件下,小麦幼苗株高、根伸长都受到了SO2及PAHs的共同影响,而SO2是影响小麦幼苗地下生物量的主要因素。     

论全球生态经济系统的不可持续性——基于农业生态系统承载力视角

运用3种方法预测的作物产量潜力分别为：（1）利用作物历年单产回归拟合后进行趋势外推,得出多数作物的未来产量潜力极限大约将是现在单产的2～3倍;（2）运用＂国际应用系统研究所＂（IIASA）与＂联合国粮农组织＂（FAO）共同开发的＂农业生态区划＂（AEZ）模型计算我国主要粮油作物的区域单产最高潜力,得出水稻、小麦、玉米、马铃薯、油菜和大豆的单产潜力分别是它们2005年全国平均单产的1.2、2.2、2.2、2.9、2.0、1.9倍;（3）运用自然界中植物的最大光能利用率计算世界主要粮油作物单产的光合潜力,得出水稻、小麦、玉米、马铃薯、油菜、大豆产量的最大光合生产潜力大约分别是目前高产地区单产的1.4、2.5、1.2、1.8、1.9、2.2倍。据此：从作物产量潜力极限出发,阐述了农业生态系统的承载力;再从＂封闭＂系统特性出发,论述了全球生态经济系统的不可持续性。人类所能做的是尽力延缓＂终点＂的出现：行动越早,效果越好。     

Genetic variability in triticale x bread wheat derivatives under normal and phosphorus stress regimes

Twenty six hexaploid triticale (X Triticosecale Wittmack) X bread wheat (Triticum aestivum L. em Thell) derivatives, along with 2 bread wheat and 2 triticale checks, were grown in normal and P-stress environments. Spikes/plant and grain yield/plant, followed by peduncle length, Were the most sensitive to phosphorus deficiency, which also caused a delay in heading and maturity. The heritability and genetic advance for grain yield/plant were high in the stress environment, reflecting the effectiveness of direct selection. The 1000-grain weight, grains/spike and plant height were the important traits for phenotypic selections in both the environments.     

Species distribution models and ecological theory: A critical assessment and some possible new approaches

Given the importance of knowledge of species distribution for conservation and climate change management, continuous and progressive evaluation of the statistical models predicting species distributions is necessary. Current models are evaluated in terms of ecological theory used, the data model accepted and the statistical methods applied. Focus is restricted to Generalised Linear Models (GLM) and Generalised Additive Models (GAM). Certain currently unused regression methods are reviewed for their possible application to species modelling.A review of recent papers suggests that ecological theory is rarely explicitly considered. Current theory and results support species responses to environmental variables to be unimodal and often skewed though process-based theory is often lacking. Many studies fail to test for unimodal or skewed responses and straight-line relationships are often fitted without justification.Data resolution (size of sampling unit) determines the nature of the environmental niche models that can be fitted. A synthesis of differing ecophysiological ideas and the use of biophysical processes models could improve the selection of predictor variables. A better conceptual framework is needed for selecting variables.Comparison of statistical methods is difficult. Predictive success is insufficient and a test of ecological realism is also needed. Evaluation of methods needs artificial data, as there is no knowledge about the true relationships between variables for field data. However, use of artificial data is limited by lack of comprehensive theory.Three potentially new methods are reviewed. Quantile regression (QR) has potential and a strong theoretical justification in Liebig's law of the minimum. Structural equation modelling (SEM) has an appealing conceptual framework for testing causality but has problems with curvilinear relationships. Geographically weighted regression (GWR) intended to examine spatial non-stationarity of ecological processes requires further evaluation before being used.Synthesis and applications: explicit theory needs to be incorporated into species response models used in conservation. For example, testing for unimodal skewed responses should be a routine procedure. Clear statements of the ecological theory used, the nature of the data model and sufficient details of the statistical method are needed for current models to be evaluated. New statistical methods need to be evaluated for compatibility with ecological theory before use in applied ecology. Some recent work with artificial data suggests the combination of ecological knowledge and statistical skill is more important than the precise statistical method used. The potential exists for a synthesis of current species modelling approaches based on their differing ecological insights not their methodology.     

Does the choice of climate baseline matter in ecological niche modelling?

Ecological niche models (ENMs) have multiple applications in ecology, evolution and conservation planning. They relate the known locations of a species to characteristics of its environment (usually climate) over its geographical range. Most ENMs are trained using standard 30-year (1961-1990) or 50-year (1951-2000) baselines to represent current climate conditions. Species occurrence records used as input to the models, however, are frequently collected from time periods that differ from those from which the climate is derived. Since climate variability can be significant within and outside baselines, and the distributions of some plants and animals (e.g., annual plants, insects) can adjust to environmental conditions on much shorter time scales, this mismatch between collection records and climatic baselines may affect the utility and accuracy of model outputs. We investigated how the choice of baseline periods influenced modelling efforts, anticipating that climate baselines derived from the same temporal period as the species records would yield improved ENMs. Ten simulated species’ distributions were modelled using an ENM (Maxent) for (a) occurrences and climates within the same temporal period, based on eighteen 10-year baselines within the 20th century and (b) all available samples and climate baselines from 1951-2000 and 1961-1990. Each model was projected onto all the available 10-year climate scenarios and compared to the models trained on the corresponding scenario. We show that temporal mismatches of species occurrences and climate baselines can result in significantly poorer distribution models. Such temporal mismatch may be unavoidable for many studies, but we emphasize here the need to match the time range of samples and climate data whenever possible.     

全氟辛烷磺酸短期暴露对不同作物苗期生长的影响

全氟辛烷磺酸(PFOS)作为一种新型持久性有机污染物,目前国内外对其生态毒性研究主要集中在水环境领域,而高等植物的生态毒性数据尚不完善。因此,本研究采用内培养方式,选取小麦、大麦、小白菜、三叶草、绿豆作为供试植物,利用根伸长、芽伸长、地上部分生物量等评价指标,研究了PFOS短期暴露对不同供试作物苗期生长的影响,建立了PFOS和作物苗期生长的剂量-效应关系,并对不同的评价指标进行相关性分析,筛选出表征PFOS生态毒性的敏感植物。结果表明,不同供试作物培育3 d后,PFOS对其于不同毒性终点的最小EC₅₀值为：小麦352 mg·kg^-1(根伸长)、大麦434 mg·kg^-1(根伸长)、三叶草794 mg·kg^-1(地上部分生物量鲜重)、小白菜829 mg·kg^-1(地上部分生物量鲜重)、绿豆>1 000 mg·kg^-1,因此敏感程度依次为：小麦>大麦>三叶草>小白菜>绿豆。须根系作物小麦、大麦较直根系作物三叶草、小白菜和绿豆敏感,而须根系作物各评价指标的敏感程度依次为：根伸长>地上部分生物量鲜重>芽伸长>地上部分生物量干重,可见小麦的根伸长对PFOS污染最为敏感。各评价指标间均呈正相关关系,表明PFOS对同种植物的不同评价指标影响趋势一致。