论西部大开发中张掖市生态环境建设问题

张掖市长期受干旱、大风及沙尘暴影响,生态环境极为恶劣,制约着西部大开发建设进程。其存在的重要问题是:水资源匮乏,植被破坏严重,覆盖率低等;针对具体情况提出:改善水资源条件和恢复植被是张掖地区生态环境建设的重点。     

菌根与植被恢复

菌根不仅可促进植物的营养吸收、生长发育、抗病、抗逆,而且在保持良好的土壤结构、控制水土流失方面具有直接的作用。在我国西北许多地区,菌根菌与植物间的共生关系已被中断,要恢复该地区的植被,治本的方法应是重建植物与菌根菌的共生关系,形成健康的生态系统。文中还提出了菌根技术在植被恢复中的应用策略。     

阜康绿洲土壤盐渍化特征及其与肥力的相关性分析

本文以电导、可溶性总盐含量和pH作为指标,将阜康绿洲的盐渍化类型划分为9种,其中以强盐渍土和盐土为主,在纬度梯度上从南至北,即从洪积扇下部到沙漠按照中盐渍土-强盐渍土-盐土-强盐渍土-盐土-非盐渍土的顺序依次分布。而土壤含水率却是从洪积下部至扇缘溢出带逐渐升高,在细土平原地区差异较大,在沙漠中又迅速降低。通过土壤剖面中有机质、全量N、P、K和速效N、P、K的分析,结果表明阜康荒漠自然状态下土壤肥力很低,各养分含量在空间上呈现规律性的变化,在纬度梯度上逐渐升高又在沙漠中降低。通过水盐与土壤肥力的相关性分析,结果表明:有机质、全N、P和速P与含水率、电导、总盐均具有显著和极显著正相关,而与pH成负相关,但相关性不显著。由于盐生植物的多样性,在盐渍土和盐土土壤肥力并无显著降低,只是土壤溶液的高盐浓度限制了植物对养分的吸收,因此防止和治理土壤盐渍化是发挥土地生产潜力的重要手段。     

河西走廊典型绿洲景观格局比较研究--以张掖、临泽、高台、酒泉为例

以地处河西走廊的张掖、临泽、高台和酒泉等县 /市级行政区为景观单元 ,利用LandsetTM影像资料的目视解译 ,在ArcView 3.1和景观格局分析软件FRAGSTATS的支持下 ,计算各绿洲景观格局指标。结果表明 :荒漠类型在四个绿洲景观组分中占绝对优势 ,其次为水浇地 ,但不同绿洲水浇地所占比例相差较大 ,酒泉最高 ,张掖其次 ,高台最低 ;斑块数、斑块密度、边缘密度和平均斑块面积的差异表明 ,张掖绿洲景观类型最多且斑块粒径小 ,而高台则完全相反 ,体现出单调而粒径粗大的荒漠绿洲特征。     

景观格局分布特征的区域差异分析--以鄂尔多斯高原伊金霍洛旗为例

以内蒙古鄂尔多斯高原伊金霍洛旗为研究区域 ,以TM遥感影像解译的 1998年土地利用图为基础资料 ,将伊金霍洛旗划分为毛乌素沙地亚区、乌审凹地亚区和黄土丘陵亚区。从区域尺度 ,利用多样性、优势度、均匀度、分维数、平均斑块形状指数、平均斑块大小、斑块密度指数和斑块体平均斑块边缘等指数 ,对不同景观亚区的景观格局进行了数量分析。结果表明 ,在景观亚区这一尺度上 ,毛乌素沙地亚区一方面对该旗景观格局起控制作用 ,另一方面该亚区所承受的人类活动强度最大 ,景观的破碎化程度最深。而乌审凹地亚区的景观破碎化程度最小 ,人类活动强度最弱。从景观要素来看 ,无论哪一亚区均以天然草地为景观基质 ;不同类型斑块总的格局特点是 ,受人类影响程度愈深的斑块 ,其破碎化程度愈深 ,斑块的复杂性降低。总体而言 ,天然类型的斑块体 ,其斑块复杂性以乌审凹地亚区最为复杂 ,斑块的破碎化程度则以毛乌素沙地亚区最深 ;而人工斑块类型的变化规律在不同斑块类型之间稍有不同。     

基于不同尺度的干旱区城市景观生态研究--以陕西榆林市为例

从区域与城市两个尺度水平 ,对毛乌素沙漠南缘的榆林市城市景观进行研究认为 :在大尺度水平上 ,区域景观生态特征对城市景观特征具有一定的控制作用 ,而城市景观强大的功能流对区域景观产生干扰作用。城市景观的空间扩展与演化 ,既受区域景观特征的影响 ,也是区域景观演化的一个有机构成部分 ;在小尺度空间上 ,景观功能区、景观斑块与廊道的格局与功能 ,对城市景观格局动态以及维持城市景观多样的生态功能具有重要意义。在不同的利益追求下形成的景观文化 ,将深刻地影响到区域与城市景观演化的方向与过程。     

Predicting the spatial distribution of ground flora on large domains using a hierarchical Bayesian model

Accomodation of important sources of uncertainty in ecological models is essential to realistically predicting ecological processes. The purpose of this project is to develop a robust methodology for modeling natural processes on a landscape while accounting for the variability in a process by utilizing environmental and spatial random effects. A hierarchical Bayesian framework has allowed the simultaneous integration of these effects. This framework naturally assumes variables to be random and the posterior distribution of the model provides probabilistic information about the process. Two species in the genus Desmodium were used as examples to illustrate the utility of the model in Southeast Missouri, USA. In addition, two validation techniques were applied to evaluate the qualitative and quantitative characteristics of the predictions.This revised version was published online in May 2005 with corrections to the Cover Date.     

额尔齐斯河流域生态系统格局及变化

本文首先对额尔齐斯河流域气候，地貌，水文等环境因子特征进行了评述，进而阐述了流域生态系统的特征和格局以及在自然和人为干扰作用下的变化。分析结果表明在自然干扰作用下流域生态系统的格局与流域水文情势变化相适应，处于准稳定变化状态，而在人为对流域水文情势扰动下，流域生态系统的格局间接地受到影响。从而产生新的格局，其作用的强度，持久性和生态系统的格局变化程度过错大于大于自然干扰作用下的变化。引额调水工程对额尔齐斯河流域河谷生态系统内部单元格局变化具有重要影响。     

A leakiness index for assessing landscape function using remote sensing

The cover, number, size, shape, spatial arrangement and orientation of vegetation patches are attributes that have been used to indicate how well landscapes function to retain, not ‘leak’, vital system resources such as rainwater and soil. We derived and tested a directional leakiness index (DLI) for this resource retention function. We used simulated landscape maps where resource flows over map surfaces were directional and where landscape patch attributes were known. Although DLI was most strongly related to patch cover, it also logically related to patch number, size, shape, arrangement and orientation. If the direction of resource flow is multi-directional, a variant of DLI, the multi-directional leakiness index (MDLI) can be used. The utility of DLI and MDLI was demonstrated by applying these indices to three Australian savanna landscapes differing in their remotely sensed vegetation patch attributes. These leakiness indices clearly positioned these three landscapes along a function-dysfunction continuum, where dysfunctional landscapes are leaky (poorly retain resources). This revised version was published online in July 2006 with corrections to the Cover Date.     

Modelling Plant Disease Epidemics

An epidemic is the progress of disease in time and space. Each epidemic has a structure whose temporal dynamics and spatial patterns are jointly determined by the pathosystem characteristics and environmental conditions. One of the important objectives in epidemiology is to understand such spatio-temporal dynamics via mathematical and statistical modelling. In this paper, we outline common methodologies that are used to quantify and model spatio-temporal dynamics of plant diseases, with emphasis on developing temporal forecast models and on quantifying spatial patterns. Several examples of epidemiological models in cereal crops are described, including one for Fusarium head blight.