北京城市与西北远郊地表臭氧浓度梯度移动监测研究

北京城市与区域臭氧浓度逐年升高,对自然生态系统已经构成影响。但地表臭氧在北京城市与远郊梯度空间上的连续递变特征机制尚不清楚。采用移动监测车,搭载臭氧分析仪,选择夏季典型臭氧污染天气,以北京教学植物园为对照点,从北京城市中心向西北远郊方向,多点位连续测定地表臭氧浓度。通过分析臭氧浓度和采样点周围归一化植被指数(NDVI)的关系以及典型臭氧污染情况下的天气形势和气团轨迹,探讨北京城市和区域臭氧浓度连续空间变化特征及机制。结果表明:(1)北京西北山区森林区域臭氧浓度显著高于"城市区域",约为城市区域的2.00倍。十三陵是地表臭氧浓度的分界点,从十三陵开始臭氧浓度陡然升高,在西北山区方向保持在高水平。空间上从高到低的顺序是西北山区(254.68μg/m~3)对照点教学植物园(220.89μg/m~3)城市支路(162.84μg/m~3)城市快速路和高速路(103.24μg/m~3);(2)植被分布影响臭氧空间格局。在相同时间范围内,臭氧浓度和NDVI正相关,随NDVI增加臭氧浓度呈Logistic增长;(3)西北山区地表臭氧空间变异系数为0.11,城市支路上平均为0.28,城市快速路上为0.26,高速公路上为0.36。山区地表臭氧浓度的空间变异系数最小,高速公路最大,城市快速路、城市支路空间变异较大;(4)大范围均压场、高压后部、低压前部等稳定型天气型易造成南向弱气流,能够把空气污染物输送到西北远郊,但本研究中监测到的西北山区高浓度臭氧并非当天从城区输送而来。北京城市与区域臭氧格局与植被的关系及成因需要深入研究。     

内蒙古多伦县土地沙漠化景观格局变化特征

利用景观分析软件Fragstats 3.3和内蒙古多伦县1960、1975、1987、1995、2000、2005年6期遥感影像解译结果,分析了1960—2005年间土地沙漠化景观格局变化.结果表明:1960—1995年间研究区土地沙漠化面积呈先增后减趋势,总沙漠化面积增加212.70km2,沙漠化斑块数先增多后减少,景观多样性和均匀性上升,轻度、中度、重度沙漠化斑块形状趋向简单;1995—2005年间研究区沙漠化斑块数大幅增加,景观多样性和均匀性下降,轻度、中度、重度沙漠化斑块形状趋向复杂;严重沙漠化斑块形状在1960年以后一直趋向复杂化.整个景观在研究期间表现为完整-破碎-完整-破碎的趋势,由轻度到严重沙漠化,其景观类型的破碎化程度逐渐降低.     

Wildlife habitat analysis – a multidimensional habitat management model

In intensively cultivated landscapes, the effects of land use – changing habitat quality and habitat availability - on wildlife populations are of major importance for wildlife management. Populations of some species reach high densities, grow rapidly, and can therefore cause damage to tree regeneration in forests; chamois (Rupicapra rupicapra) is an example. Other species, like capercaillie (Tetrao urogallus), suffer from substantial habitat loss resulting in a population decline. Consequently, the number of individuals and the quality of habitat are of crucial relevance for the development of wildlife management concepts. It is critical to know, which areas provide suitable habitat conditions for a species, and what quantity and quality of habitat is required to achieve a certain population size.

In order to evaluate habitat quality and to link wildlife research to practical habitat management, an integrated habitat management model has been designed. The model is based on a multi-dimensional habitat analysis which employs different methodological levels, which were defined according to different spatial scales. On a country scale (level 1), the wildlife ecological landscape type (WELT) is introduced. For this study the federal state of Baden-Wuerttemberg is divided into units which represent distinct regions with similar landscape ecological habitat conditions for wildlife species. On an eco-regional scale (level 2), the landscape ecological habitat potential (LEHP) was developed. It is based on the evaluation of species-related landscape parameters within an exemplary eco-region and provides information about the potential habitat available to a population. On two local scales (level 3: forest district, level 4: forest stand), a habitat structure analysis was conducted, which serves as a foundation for habitat improvement and the monitoring of habitat conditions. The three methodological elements WELT, LEHP and habitat structure analysis were integrated into a habitat management model. The model uses chamois and capercaillie as examples, but can be equally applied to other species and wildlife management regimes.     

Future eating and country keeping: what role has environmental history in the management of biodiversity?

In order to understand and moderate the effects of the accelerating rate of global environmental change land managers and ecologists must not only think beyond their local environment but also put their problems into a historical context. It is intuitively obvious that historians should be natural allies of ecologists and land managers as they struggle to maintain biodiversity and landscape health. Indeed, ‘environmental history’ is an emerging field where the previously disparate intellectual traditions of ecology and history intersect to create a new and fundamentally interdisciplinary field of inquiry. Environmental history is rapidly becoming an important field displacing many older environmentally focused academic disciplines as well as capturing the public imagination. By drawing on Australian experience I explore the role of ‘environmental history’ in managing biodiversity. First I consider some of the similarities and differences of the ecological and historical approaches to the history of the environment. Then I review two central questions in Australian environment history: landscape‐scale changes in woody vegetation cover since European settlement and the extinction of the marsupials in both historical and pre‐historical time. These case studies demonstrate that environmental historians can reach conflicting interpretations despite using essentially the same data. The popular success of some environmental histories hinges on the fact that they narrate a compelling story concerning human relationships and human value judgements about landscape change. Ecologists must learn to harness the power of environmental history narratives to bolster land management practices designed to conserve biological heritage. They can do this by using various currently popular environmental histories as a point of departure for future research, for instance by testing the veracity of competing interpretations of landscape‐scale change in woody vegetation cover. They also need to learn how to write parables that communicate their research findings to land managers and the general public. However, no matter how sociologically or psychologically satisfying a particular environmental historical narrative might be, it must be willing to be superseded with new stories that incorporate the latest research discoveries and that reflects changing social values of nature. It is contrary to a rational and publicly acceptable approach to land management to read a particular story as revealing the absolute truth.     

Spatiotemporally explicit demographic modelling supports a joint effect of historical barriers to dispersal and contemporary landscape composition on structuring genomic variation in a red‐listed grasshopper

Inferring the processes underlying spatial patterns of genomic variation is fundamental to understand how organisms interact with landscape heterogeneity and to identify the factors determining species distributional shifts. Here, we use genomic data (restriction site‐associated DNA sequencing) to test biologically informed models representing historical and contemporary demographic scenarios of population connectivity for the Iberian cross‐backed grasshopper Dociostaurus hispanicus, a species with a narrow distribution that currently forms highly fragmented populations. All models incorporated biological aspects of the focal taxon that could hypothetically impact its geographical patterns of genomic variation, including (a) spatial configuration of impassable barriers to dispersal defined by topographic landscapes not occupied by the species; (b) distributional shifts resulting from the interaction between the species bioclimatic envelope and Pleistocene glacial cycles; and (c) contemporary distribution of suitable habitats after extensive land clearing for agriculture. Spatiotemporally explicit simulations under different scenarios considering these aspects and statistical evaluation of competing models within an Approximate Bayesian Computation framework supported spatial configuration of topographic barriers to dispersal and human‐driven habitat fragmentation as the main factors explaining the geographical distribution of genomic variation in the species, with no apparent impact of hypothetical distributional shifts linked to Pleistocene climatic oscillations. Collectively, this study supports that both historical (i.e., topographic barriers) and contemporary (i.e., anthropogenic habitat fragmentation) aspects of landscape composition have shaped major axes of genomic variation in the studied species and emphasizes the potential of model‐based approaches to gain insights into the temporal scale at which different processes impact the demography of natural populations.     

流溪河流域景观空间特征与河流水质的关联分析

人类活动影响或改变流域景观空间结构,并有可能对河流水质产生不同程度的影响,以流溪河流域为研究区,分析流域景观空间格局特征与水质指数之间的相关关系。将流域划分为27个子流域,采集水样分析水质状况,所选用的水质指标有氨氮(NH3-N)、硝态氮-亚硝态氮(NO3-N+NO2-N)、总磷(TP)、化学需氧量(CODCr)。结果表明:1)该流域土地利用结构与水质具有显著相关性,其中居住用地对水质的影响作用最强,林地对河流水质具有净化功能,与水质指标之间的关系表现为负相关,园地与水质指标关系具有不确定性;2)流域景观特征从上游到下游之间表现为城市化增强的梯度,水质状况响应这个梯度变化表现为上游优于下游,人类活动及城市化发展引起的土地利用变化及土地管理方式对水质变化有显著影响;(3)景观破碎度与水质呈现显著正相关性,是影响水质的重要指标,景观聚集程度和斑块形状复杂程度与水质有负相关关系;子流域尺度和河岸带尺度景观空间特征对水质的影响差异不明显。     

农村高血压患者协调性和连续性服务的利用现状研究

目的 分析高血压患者在农村医疗服务网络接受协调性和连续性服务的提供状况,为改进患者的整合服务利用提供决策参考。方法 根据国内外文献,以自行编制服务协调性和连续性提供的问卷为工具,调查数据采用描述性统计分析。结果 49.6%的患者伴有1种及以上疾病,约73.0%在乡镇卫生院有就医经历,到过2家及以上机构就医的占51.3%;在乡村两级治疗效果不佳的患者,能够获取村医和乡镇医生推荐转诊机构的比重最大,分别为28.4%和68.7%;上级医生能够根据下级机构相关诊疗信息连续诊疗的不到43.0%,下级医生能够根据前期诊疗信息继续诊疗的比例刚超4成;“上转容易、下转难”现象同样存在。 结论 农村慢性病患者的患病特点增加了在农村纵向医疗机构就诊的几率,但该网络提供连续性和协调性服务的程度却不高,应加强农村三级医疗机构间的全面整合。     

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。     

Source-sink landscape theory and its ecological significance

Exploring the relatiouships between landscape pattern and ecological processes is the key topic of landscape ecology,for which,a large number of indices as well as landscape pattern analysis model were developed.However,one problem faced by landscape ecologists is that it is hard to link the landscape indices with a specific ecological process.Linking landscape pattern and ecological processes has become a challenge for landscape ecologists."Source" and "sink" are common concepts used in air pollution research,by which the movement direction and pattern of different pollutants in air can be clearly identified.In fact,for any ecological process,the research can be considered as a balance between the source and the sink in space.Thus,the concepts of "source" and "sink" could be implemented to the research of landscape pattern and ecological processes.In this paper,a theory of sourcesink landscape was proposed,which include:(1) In the research of landscape pattern and ecological process,all landscape types can be divided into two groups,"source"landscape and "sink" landscape."Source" landscape contributes positively to the ecological process,while "sink" landscape is unhelpful to the ecological process.(2) Both landscapes are recognized with regard to the specific ecological process."Source" landscape in a target ecological process may change into a "sink"landscape as in another ecological process.Therefore,the ecological process should be determined before "source"or "sink" landscape were defined.(3) The key point to distinguish "source" landscape from "sink" landscape is to quantify the effect of landscape on ecological process.The positive effect is made by "source" landscape,and the negative effect by "sink" landscape.(4) For the same ecological process,the contribution of "source" landscapes may vary,and it is the same to the "sink"landscapes.It is required to determine the weight of each landscape type on ecological processes.(5) The sourcesink principle can be applied to non-point source pollution control,biologic diversity protection,urban heat island effect mitigation,etc.However,the landscape evaluation models need to be calibrated respectively,because different ecological processes correspond with different source-sink landscapes and evaluation models for the different study areas.This theory is helpful to further study landscape pattern and ecological process,and offers a basis for new landscape index design.     

A comparison of individual‐based genetic distance metrics for landscape genetics

A major aim of landscape genetics is to understand how landscapes resist gene flow and thereby influence population genetic structure. An empirical understanding of this process provides a wealth of information that can be used to guide conservation and management of species in fragmented landscapes and also to predict how landscape change may affect population viability. Statistical approaches to infer the true model among competing alternatives are based on the strength of the relationship between pairwise genetic distances and landscape distances among sampled individuals in a population. A variety of methods have been devised to quantify individual genetic distances, but no study has yet compared their relative performance when used for model selection in landscape genetics. In this study, we used population genetic simulations to assess the accuracy of 16 individual‐based genetic distance metrics under varying sample sizes and degree of population genetic structure. We found most metrics performed well when sample size and genetic structure was high. However, it was much more challenging to infer the true model when sample size and genetic structure was low. Under these conditions, we found genetic distance metrics based on principal components analysis were the most accurate (although several other metrics performed similarly), but only when they were derived from multiple principal components axes (the optimal number varied depending on the degree of population genetic structure). Our results provide guidance for which genetic distance metrics maximize model selection accuracy and thereby better inform conservation and management decisions based upon landscape genetic analysis.