竞争和景观格局相互作用对外来入侵物种传播影响的动态模拟

通过中性景观模型和元胞自动机模型模拟了不同景观格局、不同竞争力和关键种群特征的外来入侵物种的传播动态,模拟结果表明:(1)竞争力强的外来入侵物种,可利用生境面积越大,集聚度越高,越有利于其入侵和传播,而对竞争力弱的外来入侵物种来说,可利用生境面积越小,越分散,越有利于其生存。竞争力强可以有效利用整块的高集聚度的资源,而弱竞争力的外来入侵物种为了逃避土著种的竞争往往趋向于分布在分散的小生境中;(2)可利用生境面积大于50%时,景观格局集聚度越小,竞争力弱的外来入侵物种适应环境的弛豫时间越长;(3)外来入侵物种的传播与种子产量呈正相关关系,与繁殖年龄呈负相关关系,拟合关系因景观格局和竞争而异;(4)平均迁移距离对外来入侵物种传播的影响最大,在管理过程中应根据不同的目标,不同的景观格局、竞争力和种群特征选择合适的管理措施。     

景观遗传学原理及其在生境片断化遗传效应研究中的应用

景观遗传学是近年来在景观生态学和种群遗传学之间形成的一个交叉领域,强调景观的组成、空间构型和环境梯度对基因流、种群遗传空间结构和局域种群适应的影响。景观遗传学尚未成为一门独立的学科,其理论基础主要来自分子遗传学、种群生物学和景观生态学。现代分子遗传标记技术、遥感和GIS支持下的景观分析和空间统计方法的综合运用是景观遗传学主要研究途径。系统介绍了景观遗传学的基础概念,关键科学问题,基本理论框架,及其与相邻研究领域的关系,综述了景观遗传学最为关注的现实课题——景观碎裂化的种群遗传效应的研究进展,主要涉及生境片断化的遗传效应、不同属性的物种响应、以及生境片断化过程的选择作用等方面。通过采取一种跨尺度的视角,景观遗传学研究显著深化了关于景观碎裂化对生物多样性影响的理解。     

《基于三种营养水平的进化生态学》评介

Author:Warren G.Abrahamson and Arthur E.Weis 索书号：58.181/a159 1997 本书通过对一支黄花、虫瘿及其天敌三种营养水平互相作用的研究,建立了田地生态和进化生态互作的系统模型。在系统上阐明了包括在物种相互作用关系内的多种手段。 本书包括的基本内容 (1)进化生态学和植物与昆虫的相互关系;(2)茎杆上虫瘿制造者的天敌和黄花：三种营养水平互作的系统模型;(3)虫瘿对黄花的影响;(4)寄主植物对虫瘿侵袭的抵抗力：植物上虫瘿遭遇——植物能力;(5)寄主植物的选择;(6)虫瘿是Eurosta扩张的表现;(7)寄主特性和食草动物的物种形成;(8)三级营养水平是选择的动力;(9)生物环境的变化和变化选择;10.表现型的可塑性与假进化;(11)侵袭与防御的等级制度的选择;(12)黄花、虫瘿与植物-昆虫互作的进化生态学。 本书适于进化生态学、系统学、生理学、遗传学、分子生物学、发育生物学、行为学及生物学等研究人员参考。 联系人：刘丽华武汉大学外国教材中心邮编：430072 027-87682740-847 E-mail:LiuLh@mail.lib.whu.edu.cn     

整合电路理论的生态廊道及其重要性识别

景观连接度被认为是影响诸多生态过程的一个重要因素.基于最小累积阻力模型的最小成本路径识别方法可以有效识别异质性景观中的功能连接,已被广泛应用到景观的功能连接评价与生态廊道模拟的研究中.基于电路理论的连接度模型用电阻代替了图论中的边、用电阻距离代替成本距离,来衡量异质性景观的功能连接.本文以SIMMAP 2.0软件生成的模拟景观为对象,借助于Linkage Mapper工具和Circuitscape软件,探讨如何将最小累积阻力模型与基于电路理论的连接度模型相结合来识别生态廊道及其景观要素的相对重要性.结果表明: 两种模型在应用中各有优势,互为补充.最小成本路径方法可以有效识别栖息地之间的最小成本廊道,基于电路理论的连接度模型通过电流密度的计算可以有效识别对景观连接性有重要影响的景观要素和“夹点”地区,并且“夹点”的位置不受廊道宽度的影响,在廊道重要性识别研究中具有明显优势.该方法可为区域生态保护规划和生态廊道设计提供科学依据.     

植物景观遗传学研究进展

植物景观遗传学是新兴的景观遗传学交叉学科的一个重要研究方向。目前植物景观遗传学的研究虽落后于动物,但其在生物多样性保护方面具有的巨大潜力不可忽视。从景观特征对遗传结构、环境因素对适应性遗传变异影响两个方面,系统综述了近十年来国际上植物景观遗传学的研究焦点和研究进展,比较了植物景观遗传学与动物景观遗传学研究在研究设计和研究方法上的异同,并基于将来植物景观遗传学由对空间遗传结构的描述发展为对景观遗传效应的量化分析及预测的发展框架,具体针对目前景观特征与遗传结构研究设计的系统性差、遗传结构与景观格局在时间上的误配、适应性位点与环境变量的模糊匹配、中性遗传变异与适应性遗传变异研究的分隔、景观与遗传关系分析方法的局限等五个方面提出了研究对策。     

中国芦苇沼泽植物物种丰富度分布格局及其驱动因素

明确大尺度物种丰富度的分布格局及其影响因素一直是生态学及生物地理学领域的核心议题之一,其对于预测全球环境变化背景下生物多样性的响应和制定减少生物多样性丧失的保护方案有着重要意义。本文基于全国芦苇(Phragmites australis)沼泽野外调查数据,结合气候、地理、土壤等环境因子,探讨了中国芦苇沼泽植物物种丰富度的分布格局及其驱动机制。结果表明:(1)中国的芦苇沼泽植物物种丰富度总体表现为亚热带湿润区和温带湿润半湿润区较高,青藏高原区、温带干旱半干旱区和滨海区较低的特点;(2)芦苇沼泽植物物种丰富度与年降水、土壤有机碳、土壤总氮、纬度均呈显著正相关,而与年均温、最冷月最低温、土壤pH值、海拔之间表现为显著负相关;(3)土壤因子特别是土壤pH值是影响芦苇沼泽植物物种丰富度的最主要因素,其次分别为淹水状况、气候因子和地理因子;(4)结构方程模型结果表明土壤因子、淹水状况和气候因子直接影响植物物种丰富度,而地理因子通过调控土壤因子、淹水状况与气候因子间接影响植物物种丰富度。总体而言,中国芦苇沼泽植物物种丰富度具有空间异质性,其分布格局受到多种因素的共同影响,土壤因子是影响植物物种丰富度...     

数字植物标本在科学研究中的应用: 进展及挑战

全球自然历史博物馆中保存着约3.9亿份植物标本,这些标本为科学研究提供了重要支撑。近20年来,随着标本数字化的发展,数字植物标本在科学研究中的应用日益广泛。数字植物标本不仅为标本传统的用途提供了便利,而且衍生出了新的研究主题和方向。鉴于目前中文文献中缺乏数字植物标本在科学研究中的应用概述及所面临挑战的分析,该文概述了全球植物标本数字化的现状,并对数字标本在生物地理学、入侵生物学、气候变化和保护生物学等领域中的应用情况进行了综述。主要集中在以下5个方面:(1)生物地理学研究中物种分布格局及其成因;(2)编制入侵植物名录、重建入侵历史和预测入侵风险;(3)气候变化情景下植物分布格局的变迁机制;(4)生物多样性编目和保护区规划;(5)其他相关应用(如农业和民族药物学等)。最后,针对数字植物标本应用中存在的问题进行了讨论,并提出了应对策略,同时提出开发将数字标本与其他学科大数据进行整合分析的新理论、新方法和新工具,为植物学及相关学科提供参考。     

高黎贡山种子植物物种丰富度沿海拔梯度的变化

物种丰富度沿海拔梯度的分布格局成为生物多样性研究的热点。为探讨中尺度区域物种丰富度沿海拔梯度的分布,本文以高黎贡山为研究对象,利用该地区的地方植物志资料,结合通过GIS生成的区域数字高程模型(DEM)数据,分析了该区域全部种子植物和乔木、灌木、草本三种生活型种子植物物种丰富度的垂直分布格局以及物种密度沿海拔梯度的变化特征。结果表明：(1)全部种子植物和不同生活型植物物种丰富度随着海拔的升高呈现先增加后减小的趋势,最大值出现在海拔1500—2000m的范围;(2)物种密度与海拔也呈现单峰曲线关系;(3)物种丰富度和物种密度分布格局的形成主要受海拔所反映的水、热状况组合以及物种分布的边界影响。     

第十八届国际拟南芥研究大会

第十八届国际拟南芥研究大会(18thInternationalConferenceonArabidopsisResearch)将于2007年6月19日至24日在北京九华山庄举行。本次会议由中国科学院植物研究所、中国科学院遗传与发育生物学研究所、北京大学、北京生命科学研究所和中国农业大学联合主办。北京生命科学研究所邓兴旺教授担任大会主席。本次会议主题是拟南芥的植物生物学全方位功能研究及其在农业生产中的开发应用。大会将分为以下各专题:(1)植物发育;(2)植物信号转导;(3)遗传学;(4)基因组学;(5)植物对环境的应答;(6)植物与微生物的反应;(7)植物细胞生物学;(8)代谢和生物…     

湛江市城市森林树种结构分析

调查湛江市道路、公园和附属三类绿地159个单位的100 452株乔木,比较其物种多样性特征、物种组成特性、相对多度、物种重要值。结果表明:(1)湛江城市森林有52科204种乔木,物种多样性较丰富,树种结构受绿地类型、生境与人文等因素影响;(2)物种组成反映出热带季雨林地带性特色,外来种有96种,应用丰富,但乡土植物开发不足;(3)在调查的植株中,少数优势种占很大比例,其中,道路绿地前25种植物相对多度高达89.66,公园有最多的非常见种;(4)物种重要值SI>1的有26种,7种基调树种反映了湛江城市森林的基本特色。     

MigClim: Predicting plant distribution and dispersal in a changing climate

Aim Many studies have forecasted the possible impact of climate change on plant distributions using models based on ecological niche theory, but most of them have ignored dispersal‐limitations, assuming dispersal to be either unlimited or null. Depending on the rate of climatic change, the landscape fragmentation and the dispersal capabilities of individual species, these assumptions are likely to prove inaccurate, leading to under‐ or overestimation of future species distributions and yielding large uncertainty between these two extremes. As a result, the concepts of ‘potentially suitable’ and ‘potentially colonizable’ habitat are expected to differ significantly. To quantify to what extent these two concepts can differ, we developed Mig Clim, a model simulating plant dispersal under climate change and landscape fragmentation scenarios. Mig Clim implements various parameters, such as dispersal distance, increase in reproductive potential over time, landscape fragmentation or long‐distance dispersal. Location Western Swiss Alps. Methods Using our Mig Clim model, several simulations were run for two virtual species by varying dispersal distance and other parameters. Each simulation covered the 100‐year period 2001–2100 and three different IPCC‐based temperature warming scenarios were considered. Results of dispersal‐limited projections were compared with unlimited and no‐dispersal projections. Results Our simulations indicate that: (1) using realistic parameter values, the future potential distributions generated using Mig Clim can differ significantly (up to more than 95% difference in colonized surface) from those that ignore dispersal; (2) this divergence increases under more extreme climate warming scenarios and over longer time periods; and (3) the uncertainty associated with the warming scenario can be as large as the one related to dispersal parameters. Main conclusions Accounting for dispersal, even roughly, can importantly reduce uncertainty in projections of species distribution under climate change scenarios.     

Do landscape processes predict phylogeographic patterns in the wood frog?

Understanding factors that influence population connectivity and the spatial distribution of genetic variation is a major goal in molecular ecology. Improvements in the availability of high-resolution geographic data have made it increasingly possible to quantify the effects of landscape features on dispersal and genetic structure. However, most studies examining such landscape effects have been conducted at very fine (e.g. landscape genetics) or broad (e.g. phylogeography) spatial scales. Thus, the extent to which processes operating at fine spatial scales are linked to patterns at larger scales remains unclear. Here, we test whether factors impacting wood frog dispersal at fine spatial scales are correlated with genetic structure at regional scales. Using recently developed methods borrowed from electrical circuit theory, we generated landscape resistance matrices among wood frog populations in eastern North America based on slope, a wetness index, land cover and absolute barriers to wood frog dispersal. We then determined whether these matrices are correlated with genetic structure based on six microsatellite markers and whether such correlations outperform a landscape-free model of isolation by resistance. We observed significant genetic structure at regional spatial scales. However, topography and landscape variables associated with the intervening habitat between sites provide little explanation for patterns of genetic structure. Instead, absolute dispersal barriers appear to be the best predictor of regional genetic structure in this species. Our results suggest that landscape variables that influence dispersal, microhabitat selection and population structure at fine spatial scales do not necessarily explain patterns of genetic structure at broader scales.     

Effects of the landscape on boreal toad gene flow: does the pattern–process relationship hold true across distinct landscapes at the northern range margin?

Understanding the impact of natural and anthropogenic landscape features on population connectivity is a major goal in evolutionary ecology and conservation. Discovery of dispersal barriers is important for predicting population responses to landscape and environmental changes, particularly for populations at geographic range margins. We used a landscape genetics approach to quantify the effects of landscape features on gene flow and connectivity of boreal toad (Bufo boreas) populations from two distinct landscapes in south-east Alaska (Admiralty Island, ANM, and the Chilkat River Valley, CRV). We used two common methodologies for calculating resistance distances in landscape genetics studies (resistance based on least-cost paths and circuit theory). We found a strong effect of saltwater on genetic distance of CRV populations, but no landscape effects were found for the ANM populations. Our discordant results show the importance of examining multiple landscapes that differ in the variability of their features, to maximize detectability of underlying processes and allow results to be broadly applicable across regions. Saltwater serves as a physiological barrier to boreal toad gene flow and affects populations on a small geographic scale, yet there appear to be few other barriers to toad dispersal in this intact northern region.     

Functional connectivity in replicated urban landscapes in the land snail (Cornu aspersum)

Urban areas are highly fragmented and thereby exert strong constraints on individual dispersal. Despite this, some species manage to persist in urban areas, such as the garden snail, Cornu aspersum, which is common in cityscapes despite its low mobility. Using landscape genetic approaches, we combined study area replication and multiscale analysis to determine how landscape composition, configuration and connectivity influence snail dispersal across urban areas. At the overall landscape scale, areas with a high percentage of roads decreased genetic differentiation between populations. At the population scale, genetic differentiation was positively linked with building surface, the proportion of borders where wooded patches and roads appeared side by side and the proportion of borders combining wooded patches and other impervious areas. Analyses based on pairwise genetic distances validated the isolation‐by‐distance and isolation‐by‐resistance models for this land snail, with an equal fit to least‐cost paths and circuit‐theory‐based models. Each of the 12 landscapes analysed separately yielded specific relations to environmental features, whereas analyses integrating all replicates highlighted general common effects. Our results suggest that urban transport infrastructures facilitate passive snail dispersal. At a local scale, corresponding to active dispersal, unfavourable habitats (wooded and impervious areas) isolate populations. This work upholds the use of replicated landscapes to increase the generalizability of landscape genetics results and shows how multiscale analyses provide insight into scale‐dependent processes.     

Potential impacts of climate and landscape fragmentation changes on plant distributions: Coupling multi-temporal satellite imagery with GIS-based cellular automata model

Climate change and landscape fragmentation are considered to be the main treats to biodiversity. In this study, probable alteration of future species distribution was tested based on the association of landscape fragmentation and climate change scenarios compared to the classical approach that assumed an unchanged landscape. Also, projected range shifts including realistic dispersal scenarios were compared with classical models, in which no or full dispersal has been supposed.A GIS-based cellular automata model, MigClim, was implemented to projection of future distribution over the 21st century for three plant species in a study area of the central Germany. For each species, simulations were run for four dispersal scenarios (full dispersal, no dispersal, realistic dispersal, and realistic dispersal with long-distance dispersal events), two landscape fragmentation (static and dynamic change) and two climate change (RCP4.5 and RCP8.5) scenarios. In this research, temporal satellite data were utilized to simulate landscape changes by the use of a hybrid (CA-Markov) model for the years 2020, 2040, 2060 and 2080.A significant difference appears to be between the simulations of realistic dispersal limitations and those considering full or no dispersal for projected future distributions. Although simulations accounting for dispersal limitations produced, for our study area, results that were closer to no dispersal than to full dispersal. Additionally, our results revealed that change in landscape fragmentation is more effective than the climate change impacts on species distributions in this study.     

A plea for simultaneously considering matrix quality and local environmental conditions when analysing landscape impacts on effective dispersal

Landscape genetics has tremendous potential for enhancing our understanding about landscape effects on effective dispersal and resulting genetic structures. However, the vast majority of landscape genetic studies focus on effects of the landscape among sampling locations on dispersal (i.e. matrix quality), while effects of local environmental conditions are rather neglected. Such local environmental conditions include patch size, habitat type or resource availability and are commonly used in (meta‐) population ecology and population genetics. In our opinion, landscape genetic studies would greatly benefit from simultaneously incorporating both matrix quality and local environmental conditions when assessing landscape effects on effective dispersal. To illustrate this point, we first outline the various ways in which environmental heterogeneity can influence different stages of the dispersal process. We then propose a three‐step approach for assessing local and matrix effects on effective dispersal and review how both types of effects can be considered in landscape genetic analyses. Using simulated data, we show that it is possible to correctly disentangle the relative importance of matrix quality vs. local environmental conditions for effective dispersal. We argue that differentiating local and matrix effects in such a way is crucial for predicting future species distribution and persistence, and for optimal conservation decisions that are based on landscape genetics. In sum, we think it is timely to move beyond purely statistical, pattern‐oriented analyses in landscape genetics and towards process‐oriented approaches that consider the full range of possible landscape effects on dispersal behaviour and resulting gene flow.     

A conceptual framework for the spatial analysis of landscape genetic data

Understanding how landscape heterogeneity constrains gene flow and the spread of adaptive genetic variation is important for biological conservation given current global change. However, the integration of population genetics, landscape ecology and spatial statistics remains an interdisciplinary challenge at the levels of concepts and methods. We present a conceptual framework to relate the spatial distribution of genetic variation to the processes of gene flow and adaptation as regulated by spatial heterogeneity of the environment, while explicitly considering the spatial and temporal dynamics of landscapes, organisms and their genes. When selecting the appropriate analytical methods, it is necessary to consider the effects of multiple processes and the nature of population genetic data. Our framework relates key landscape genetics questions to four levels of analysis: (i) node-based methods, which model the spatial distribution of alleles at sampling locations (nodes) from local site characteristics; these methods are suitable for modeling adaptive genetic variation while accounting for the presence of spatial autocorrelation. (ii) Link-based methods, which model the probability of gene flow between two patches (link) and relate neutral molecular marker data to landscape heterogeneity; these methods are suitable for modeling neutral genetic variation but are subject to inferential problems, which may be alleviated by reducing links based on a network model of the population. (iii) Neighborhood-based methods, which model the connectivity of a focal patch with all other patches in its local neighborhood; these methods provide a link to metapopulation theory and landscape connectivity modeling and may allow the integration of node- and link-based information, but applications in landscape genetics are still limited. (iv) Boundary-based methods, which delineate genetically homogeneous populations and infer the location of genetic boundaries; these methods are suitable for testing for barrier effects of landscape features in a hypothesis-testing framework. We conclude that the power to detect the effect of landscape heterogeneity on the spatial distribution of genetic variation can be increased by explicit consideration of underlying assumptions and choice of an appropriate analytical approach depending on the research question.     

cdpop: A spatially explicit cost distance population genetics program

Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (cdpop). The model implements individual-based population modelling with Mendelian inheritance and k-allele mutation on a resistant landscape. The model simulates changes in population and genotypes through time as functions of individual based movement, reproduction, mortality and dispersal on a continuous cost surface. This model will be a valuable tool for the study of landscape genetics by increasing our understanding about the effects of life history, vagility and differential models of landscape resistance on the genetic structure of populations in complex landscapes.     

Applying a continua landscape approach to evaluate plant response to fragmentation: Primula vulgaris in the Cantabrian mountains

Question: Continua landscape approaches conceptualize the effects of habitat fragmentation on the biota by considering fragmented landscapes as continuous gradients, departing from the view of habitat as either suitable (fragment) or unsuitable (matrix). They also consider the ecological gradients or the ‘Umwelt’ (species‐specific perception of the landscape) to represent the processes that ultimately limit organisms' ability to colonize and persist within habitat remnants. Are these approaches suitable for evaluating the response of plant species to fragmentation? Location: Fragmented mid‐elevation temperate forests, Cantabrian range, Spain. Methods: The presence, abundance and demographic structure of populations of the perennial herb Primula vulgaris were sampled across a continuous extent of 100 ha, subdivided into 400 50 m × 50 m sampling units. These variables were related to forest availability, forest subdivision and edge density, topography and the spatial clumpiness of populations (a measure of plant dispersal constraints and, hence, a major surrogate of plant Umwelt). Results: Fragmentation processes, especially habitat loss, negatively affect P. vulgaris, with a stronger effect on presence than on abundance and demography. Despite the importance of habitat availability, P. vulgaris does not occupy all potentially suitable forest habitat, mostly owing to dispersal constraints. A positive effect of slope on plant presence also suggests some effect of habitat quality in determining establishment and occupancy of forest landscape. Conclusions: Within‐habitat dispersal constraints are as important as forest fragmentation in determining the landscape‐scale distribution of P. vulgaris. By assessing the relative role of the diverse fragmentation processes, and of the species' landscape perception, a continua landscape approach proves to be a valuable tool for predicting plant response to landscape change.