养分管理与农田杂草生物多样性和遗传进化的关系研究进展

施肥被看作是一项潜在降低农田杂草对作物干扰的有效农作管理措施。不同施肥处理可形成具有不同养分状况的土壤条件,而土壤条件的差异是导致杂草生物多样性的重要因素。论证养分管理可显著改变农田杂草发生状况和杂草生物多样性,强调了深入开展不同养分管理模式对农田杂草生物多样性和遗传进化影响研究的重要性,提出了如何利用养分管理措施调节农田杂草,在控制杂草对农业危害的同时,保持一定农田可控杂草生物多样性的科学问题。长期N、P和K平衡配施,可维持杂草群落和杂草种子库的生物多样性与稳定性,兼顾杂草控制和杂草多样性保护,实现平衡施肥的经济效应与生态效应的统一。同时,农业生态系统中不同养分管理措施条件下的地表光辐射变化特征、不同光辐射变化对杂草种群种子萌发及植株建立的影响、优势杂草种群的确定及其生理生态和遗传进化规律是今后研究的重点和难点。     

Spatial structure, sampling design and abundance estimates in sandy beach macroinfauna: some warnings and new perspectives

We discuss methodological aspects directed to quantify the across-shore population structure and abundance of sandy beach macroinfauna. The reliability of estimates derived from design-based (stratified random sampling) and model-based (geostatistics, kriging) approaches is discussed. Our analysis also addresses potential biases arising from environmentally driven designs that consider a priori fixed strata for sampling macroinfauna, as opposed to species-driven sampling designs, in which the entire range of across-shore distribution is covered. Model-based approaches showed, spatially, highly autocorrelated and persistent structures in two intertidal populations of the Uruguayan coast: the isopod Excirolana armata and the yellow clam Mesodesma mactroides. Both populations presented zonation patterns that ranged from the base of the dunes to upper levels of the subtidal. The Gaussian model consistently explained the spatial distribution of species and population components (clam recruits and adults), with a minor contribution (Е%) of unresolved, small-scale variability. The consistent structure of spatial dependence in annual data strongly suggests an across-shore-structured process covering close to 35 m. Kriging predictions through cross-validation corroborated the appropriateness of the models fitted through variographic analysis, and the derived abundance estimates were very similar (maximum difference=7%) to those obtained from linear interpolation. Monthly analysis of E. armata data showed marked variations in its zonation and an unstable spatial structure according to the Gaussian model. The clear spatial structure resulting from species-driven sampling was not observed when data was truncated to simulate an environmentally driven sampling design. In this case, the linear semivariogram indicated a spatial gradient, suggesting that sampling was not performed at the appropriate spatial scale. Further, the cross-validation procedure was not significant, and both density and total abundance were underestimated. We conclude that: (1) geostatistics provides useful additional information about population structure and aids in direct abundance estimation; thus we suggest it as a powerful tool for further applications in the study of sandy beach macroinfauna; and that (2) environmentally driven sampling strategies fail to provide conclusive results about population structure and abundance, and should be avoided in studies of sandy beach populations. This is especially true for microtidal beaches, where unpredictable swash strength precludes a priori stratification through environmental reference points. The need to use adaptive sampling designs and avoid snapshot sampling is also stressed. Methodological implications for the detection of macroecological patterns in sandy beach macroinfauna are also discussed.     

Changes in distribution patterns of weed species richness in agricultural lands on Qinghai-Tibet Plateau under climate change北大核心CSCD

农田杂草是阻碍农业生产的主要因素之一.明确农田杂草丰富度分布格局对农业生产管理具有重要意义.以青藏高原农田杂草为研究对象,利用物种分布模型探讨基于县域尺度的农田杂草物种丰富度分布格局及其未来(2050s)的变化,利用逐步回归筛选影响物种丰富度的环境因子,基于传统最小二乘法(OLS)和地理加权回归模型(GWR)分析环境因子对农田杂草物种丰富度的影响,并对两种分析方法进行比较.结果显示:(1)分布在青藏高原的农田主要杂草有51科284种,其中59种单子叶杂草、222种双子叶杂草、135种一年生杂草和149种多年生杂草.青藏高原农田杂草物种丰富度呈由西向东递增的变化规律,物种丰富度中心(丰富度值为167-194)主要集中在一江两河、河湟谷地和川西北等地区;(2)全球气候变化背景下,未来(2050s)青藏高原农田杂草物种丰富度整体呈由东南向西北方向增加的趋势,其中SSP1-2.6情境下最多增加43种,SSP5-8.5情境下最多增加49种;(3)GWR模型优于OLS,其结果表明青藏高原农田杂草物种丰富度的主要驱动因子是最冷季平均温、太阳辐射和最干月降水量,上述变量对杂草丰富度的影响存在明显的空间差异性,其中最冷季平均温由南向北逐渐从负向影响转变为正向影响.太阳辐射整体在青藏高原东部边缘等地区对农田杂草丰富度起正向的影响,在藏东南、青藏高原北部边缘等地区起负向的影响.最干月降水量对整个研究区域起负向影响,并表现出影响力由南向北逐步递增的趋势.上述结果表明青藏高原农田杂草物种丰富度调查不足,实际观测到的丰富度值明显低于当前气候下潜在的丰富度值,存在低估现象.当前气候背景下的农田杂草物种丰富度中心分布地区在未来仍是重点监管对象,且未来青藏高原部分地区作物可能面临新的杂草入侵风险.建议未来研究应注重于青藏高原粮食主产区农田杂草群落结构和功能调查、杂草和作物种间关系、耕地尺度上丰富度驱动因子分析等方面,为区域杂草管理和防治提供充分科学依据.(图6表2参53)     

Evaluation of sampling methods for the estimation of structural indices in forest stands

The paper is about the accurate (i.e. unbiased and precise) and efficient estimation of structural indices in forest stands. We present SIAFOR, a computer programme for the calculation of four nearest-neighbour indices, which describe the spatial arrangement of tree positions, the distribution pattern of species, and the size differentiation between trees. The study uses SIAFOR as a sampling simulator in eight completely stem-mapped forest stands of varying area and structural complexity. We statistically evaluate two sample types (distance and plot sampling), comparing sampling error, bias and minimum sample size for index estimation. We introduce the concepts of measurement expansion factor (MEF) and design expansion factor (DEF) for the technical evaluation of sample type efficiency (optimal sample type). Results indicate that sampling error can reach high levels and that minimum sample sizes for index estimation often amply exceed the limit of 20% of tree density or 20 trees per species per hectare, that we set as the highest feasible sample size in normal situations. We found clear feasibility limits (in terms of minimal tree densities and reachable accuracy levels) for the estimation of all investigated indices. Generally, equal or higher sample sizes are needed for plot sampling than for distance sampling to reach equal accuracy levels. Nevertheless, plot sampling resulted more efficient for the estimation of tree size differentiation at low to medium accuracy levels. For all other investigated indices distance sampling resulted more efficient than plot sampling. Minimum sample size increases with accuracy and is negatively correlated with tree density. At a given accuracy level minimum sample size is highest for the estimation of relative mingling and lowest for tree size differentiation; furthermore it is generally lower in large stands than in small ones. Because of the consistency of our conclusions in all of the investigated stands, we think they apply in most stands of similar area (between 1 and 10 ha) and species diversity (not more than four species).     

Using CA model to obtain insight into mechanism of plant population spread in a controllable system: annual weeds as an example

Using cellular automata (CA) model, in this article, a mechanistic approach has been conducted to help to insight into spread process of plant population such as annual weed population. A controllable CA model with 25 neighbourhood cells has been built, in which seed dispersal, as a key process of annual weed population dynamics, has been described by Gaussian distribution. The hypothesis that initial configurations affect annual weed population dynamics and control strategies has been tested by simulating. And the results support strongly the hypothesis. Patch, pattern and configuration are important concepts in weed patch management, which have been mathematically defined in this article. The aggregation effects have been found out while simulating, which is subject to patch size, patch density and distribution function of seed dispersal. Perhaps it could partly explain the reason why weeds often distribute in patch. Accordingly, true-patch and generalised patch have been distinguished from each other, which would be practically applicable to weed patch management. Based on this approach to the particular weed-crop system, a new hypothesis has been proposed: in a real controllable weed-crop system, the mean law might hold. If so, algorithm of patch control for long-term weed management could be simplified to control a true-patch only according to its mean density, it is unnecessary to control it according to the density in its each cell.     

Using Niche-Based Models to Improve the Sampling of Rare Species

Abstract:  Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.     

Application of adaptive cluster sampling to low-density populations of freshwater mussels

Freshwater mussels appear to be promising candidates for adaptive cluster sampling because they are benthic macroinvertebrates that cluster spatially and are frequently found at low densities. We applied adaptive cluster sampling to estimate density of freshwater mussels at 24 sites along the Cacapon River, WV, where a preliminary timed search indicated that mussels were present at low density. Adaptive cluster sampling increased yield of individual mussels and detection of uncommon species; however, it did not improve precision of density estimates. Because finding uncommon species, collecting individuals of those species, and estimating their densities are important conservation activities, additional research is warranted on application of adaptive cluster sampling to freshwater mussels. However, at this time we do not recommend routine application of adaptive cluster sampling to freshwater mussel populations. The ultimate, and currently unanswered, question is how to tell when adaptive cluster sampling should be used, i.e., when is a population sufficiently rare and clustered for adaptive cluster sampling to be efficient and practical? A cost-effective procedure needs to be developed to identify biological populations for which adaptive cluster sampling is appropriate.     

Invasion dynamics of the European shore crab,<Emphasis Type="Italic"> Carcinus maenas</Emphasis>, in Australia

In Australia and most other invaded locations, rates of range expansion by the European shore crab, Carcinus maenas, are typically only a few kilometres per year, despite a planktonic duration upwards of 50 days and off-shore larval development. This relatively static distribution is punctuated by rare episodes of long-distance and large-scale spread, some of which appear to be related to unusual oceanographic conditions and some of which are likely to be human assisted. These observations suggest, first, that long planktonic duration and off-shore development in a marine invertebrate does not preclude very localised recruitment, and, second, that this recruitment norm may be punctuated by brief episodes of wide scale mixing of propagules. Punctuated dispersal has previously been suggested to account for large-scale biogeographic patterns of distribution and speciation, but may also have implications for the processes that stabilise structured spatial metapopulations.     

北京山区典型流域不同海拔椴树种群的空间点格局分析

采用点格局分析法对不同海拔的椴树（Tilia miqueliana Maxim.）种群进行分布格局及其种间关系进行了研究。结果表明：整体上群落内以中龄树个体数为最多,小树次之,成年树个体最少。随着海拔的增加可以看出：小树（d≤5 cm）随着海拔的增加而减少,中树（5 cm20 cm）的规律不明显;椴树种群的空间分布格局与空间尺度（25 m内）有密切关系,在较小的空间尺度上倾向于非随机分布,具有明显的空间相关性;在〉15 m或25m的某临界尺度时却倾向于随机分布,同时空间关联变得微弱。随着海拔的增加,各物种聚集分布的尺度有逐渐减小的趋势。种间关系随着海拔的增加,物种间的正相关尺度有增加的趋势。     

Deconstructing adaptive management: criteria for applications to environmental management.

The concept of adaptive management has, for many ecologists, become a foundation of effective environmental management for initiatives characterized by high levels of ecological uncertainty. Yet problems associated with its application are legendary, and many of the initiatives promoted as examples of adaptive management appear to lack essential characteristics of the approach. In this paper we propose explicit criteria for helping managers and decision makers to determine the appropriateness of either passive or active adaptive-management strategies as a response to ecological uncertainty in environmental management. Four categories of criteria--dealing with spatial and temporal scale, dimensions of uncertainty, the evaluation of costs and benefits, and institutional and stakeholder support--are defined and applied using hypothetical yet realistic case-study scenarios that illustrate a range of environmental management problems. We conclude that many of the issues facing adaptive management may have less to do with the approach itself than with the indiscriminate choice of contexts within which it is now applied.     

Variance estimation in the EMAP strategy for sampling discrete ecological resources

The United States Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) is designed to describe status, trends and spatial pattern of indicators of condition of the nation's ecological resources. The proposed sampling design for EMAP is based on a triangular systematic grid and employs both variable probability and double sampling. The Horvitz-Thompson estimator provides the foundation of the design-based estimation strategy used in EMAP. However, special features of EMAP designed to accommodate the complexity of sampling environmental resources on a national scale require modifications of standard variance estimation procedures as well as development of new techniques. An overview of variance estimation methods proposed for application to EMAP's sampling strategy for discrete resources is presented.     

Cross-combined composite sampling designs for identification of elevated regions

Analyzing soils for contaminants can be costly. Generally, discrete samples are gathered from within a study area, analyzed by a laboratory and the results are used in a site-specific statistical analysis. Because of the heterogeneities that exist in soil samples within study areas, a large amount of variability and skewness may be present in the sample population. This necessitates collecting a large number of samples to obtain reliable inference on the mean contaminant concentration and to understand the spatial patterns for future remediation. Composite, or Incremental, sampling is a commonly applied method for gathering multiple discrete samples and physically combining them, such that each combination of discrete samples requires a single laboratory analysis, which reduces cost and can improve the estimates of the mean concentration. While incremental sampling can reduce cost and improve mean estimates, current implementations do not readily facilitate the characterization of spatial patterns or the detection of elevated constituent regions within study areas. The methods we present in this work provide efficient estimation and inference for the mean contaminant concentration over the entire spatial area and enable the identification of high contaminant regions within the area of interest. We develop sample design methodologies that explicitly define the characteristics of these designs (such as sample grid layout) and quantify the number of incremental samples that must be obtained under a design criteria to control false positive and false negative (Type I and II) decision errors. We present the sample design theory and specifications as well as results on simulated and real data.     

Kernel density estimators of home range: smoothing and the autocorrelation red herring

Two oft-cited drawbacks of kernel density estimators (KDEs) of home range are their sensitivity to the choice of smoothing parameter(s) and their need for independent data. Several simulation studies have been conducted to compare the performance of objective, data-based methods of choosing optimal smoothing parameters in the context of home range and utilization distribution (UD) estimation. Lost in this discussion of choice of smoothing parameters is the general role of smoothing in data analysis, namely, that smoothing serves to increase precision at the cost of increased bias. A primary goal of this paper is to illustrate this bias-variance trade-off by applying KDEs to sampled locations from simulated movement paths. These simulations will also be used to explore the role of autocorrelation in estimating UDs. Autocorrelation can be reduced (1) by increasing study duration (for a fixed sample size) or (2) by decreasing the sampling rate. While the first option will often be reasonable, for a fixed study duration higher sampling rates should always result in improved estimates of space use. Further, KDEs with typical data-based methods of choosing smoothing parameters should provide competitive estimates of space use for fixed study periods unless autocorrelation substantially alters the optimal level of smoothing.     

物种敏感度分布的非参数核密度估计模型

针对目前物种敏感度分布参数方法建模所存在的缺点,首次提出基于非参数核密度估计方法的物种敏感度分布模型,并提出相应的最优窗宽和检验方法。选用无机汞作为案例研究对象,利用非参数核密度估计方法和3种传统参数模型分别推导了保护我国水生生物的无机汞的急性水质基准值。结果表明,非参数核密度估计方法在推导无机汞水质基准中的稳健性和精确度都大大优于传统参数模型,能够更好地构建物种敏感度分布曲线。该方法的提出丰富了水质基准的理论方法学,为更好地保护水生生物提供了有力的支撑。     

Resampling methods for estimating dispersion indices in random and adaptive designs

In many surveys in environmental and natural phenomena the aim is to evaluate the heterogeneity, and the skewness of the distribution of the number point-objects in the study area opportunely partitioned in sub-regions. For this purpose, in this paper the estimation of dispersion indices is considered by using simple random sampling and adaptive sampling with initial simple random sampling selected with replacement or without replacement. The jackknife and the bootstrap procedures are proposed in both cases for reducing bias. Finally, both a simulation study and a case study on biological population referred to a Oidium tuckeri contamination in a growing vineyard is performed to assess the accuracy of the proposed estimators.     

Optimization model for a wolf-ungulate system

Public outcries against predator control create a need to devise management policies that optimally balance the cost (managerial and environmental) of predator control against the benefit of ungulate harvesting. To address this problem, an optimization procedure utilizing stochastic dynamic programming is described. Through this approach, optimal feedback strategies for a wolf-ungulate system in Alaska are estimated. The dynamic predator-prey model used in the analysis is based on parameter estimates from data collected over an eight-year period in Denali (Mt. McKinley) National Park. Stability analysis of the system revealed that stability properties depend on predator search efficiency. The effects of random fluctuations in winter severity and alternative objective functions are considered in the estimation of optimal feedback strategies. Optimal moose harvesting strategies appear to be dependent on wolf control costs. If no wolf control cost is assessed, optimal moose harvest is independent of wolf density. Optimal wolf control strategies are completely insensitive to moose density. The strategies are compared to current and simplified management policies.     

Adaptive two-stage one-per-stratum sampling

We briefly describe adaptive cluster sampling designs in which the initial sample is taken according to a Markov chain one-per-stratum design (Breidt, 1995) and one or more secondary samples are taken within strata if units in the initial sample satisfy a given condition C. An empirical study of the behavior of the estimation procedure is conducted for three small artificial populations for which adaptive sampling is appropriate. The specific sampling strategy used in the empirical study was a single random-start systematic sample with predefined systematic samples within strata when the initially sampled unit in that stratum satisfies C. The bias of the Horvitz-Thompson estimator for this design is usually very small when adaptive sampling is conducted in a population for which it is suited. In addition, we compare the behavior of several alternative estimators of the standard error of the Horvitz-Thompson estimator of the population total. The best estimator of the standard error is population-dependent but it is not unreasonable to use the Horvitz-Thompson estimator of the variance. Unfortunately, the distribution of the estimator is highly skewed hence the usual approach of constructing confidence intervals assuming normality cannot be used here.     

Optical characterization of primary productivity across a coastal front

Methods for the remote estimation of phytoplankton biomass and production rates using multiplatform sampling strategies are essential for the better understanding of oceanic bio-geochemical cycles. Recent advances in remote sensing of ocean color have made synoptic estimation of phytoplankton biomass attainable. While considerable success has been achieved in the estimation of plant biomass, the synoptic estimation of phytoplankton rates of production has been inadequate. Rapid shipboard estimates of the vertical distribution of primary productivity, on mesoscale spatial scales and event-time scales, are needed to provide both surface validation and data for the development of bio-optical models linking production to the optical characteristics of the water column. This study details the primary productivity and optical properties of a frontal region in July 1985 along 35°50N in the Southern California Bight which is shown to be consistent with the concurrent high-performance liquid-chromatography pigment-analysis. We describe here a quasi-synoptic shipboard bio-optical sampling strategy across a frontal region as an example of time-corrected data for assessing phytoplankton production in highly variable ocean regions.     

施肥模式对砂姜黑土区土壤种子库影响的研究

通过对砂浆黑土区小麦-大豆轮作制地不同施肥模式的杂草土壤种子库（0～15 cm）进行调查,分析种子库的大小、组成、多样性等特征,探讨施肥模式与群落演替速率之间的关系。结果表明,施肥模式显著影响着土壤种子库的大小、组成、多样性、群落演替速率。土壤样品中共检出杂草种子18种,隶属于11科,且各处理优势种组成差异明显。种子库密度按NPK〉NP〉NK〉CK〉PK顺序依次递减且差异极显著（P〈0.01）。各处理物种组成不同,种数按CK〉NPK〉PK=NK〉NP顺序依次递减,群落均匀度指数按NP〉CK〉NK〉PK〉NPK顺序依次递减且差异显著（P〈0.05）,物种多样性指数按CK〉NP〉NK〉PK〉NPK顺序依次递减,群落优势度指数按NPK〉PK=NK〉CK〉NP顺序依次递减。我们初步认为适应与竞争机制影响土壤种子库的物种组成、密度的差异;施肥模式间土壤种子库的优势种变化尤为突出,引起均匀度的改变,导致施肥模式下土壤种子库多样性的差异。Whittaker指数按CK〈NPK〈PK=NK〈NP顺序依次增大,表明土壤种子库的群落演替速率依次加快,说明长期平衡施肥模式（NPK）对土壤种子库群落的影响明显小于PK、NP、NK施肥处理,群落结构较PK、NP、NK施肥处理更稳定。气候、取样时间、除草剂等因素导致年际间、种植季间的杂草土壤种子库特征差异明显。本研究认为长期平衡施肥既有利于作物的优质高产,也有利于农田土壤种子库群落的稳定,是建立合理、高效、稳定的农业生态系统以及取得良好的经济效益和生态效益的重要施肥方式。     

Geostatistical analysis of spatial distribution of Liocarcinus depurator,Macropipus tuberculatus and Polybius henslowii (Crustacea: Brachyura) over the Galician continental shelf (NW Spain)

Geostatistics was used to analyze the spatial structure and distribution of three species of brachyurans, Liocarcinus depurator, Macropipus tuberculatus and Polybius henslowii, from sets of data collected during three survey cruises (1983 and 1984) over the Galician continental shelf. The present study investigates the feasibility of using geostatistics with data collected according to traditional methods and of thereby improving the sampling methodology. In order to investigate the spatial structure of the species studied, experimental variograms were calculated and fitted to a spherical model. The spatial structure model was used to estimate and map abundance and distribution of the populations studied using the so-called Kriging technique. Geostatistical analysis enabled the determination of spatial density gradients as well as patch size (14 to 22 km, L. depurator; 10 to 28 km, M. tuberculatus; 7.5 to 28 km, P. henslowii) along the continental shelf. Depth was revealed as a limiting factor, restricting the distribution of L. depurator and M. tuberculatus on a large scale, whereas upwelling processes and nutrient-rich waters from the rías affected the spatial structure on a smaller scale, especially in the case of P. henslowii. A spatial segregation in the distribution of the three species also emerged; this probably arose from differences in physical and biological factors that result in different habitat-exploitation patterns. The study demonstrates the existence of spatial covariance and that the variograms vary as a function of population density and geographical area. This information will be useful in improving the design of future sampling cruises.