Climate change and lakeshore conservation: a model and review of management techniques

Climate change is expected to cause significant changes to the hydrology of lakes, reservoirs and other wetlands. In particular, there will be an increase in the level of disturbance produced by water-level fluctuations. This may have adverse consequences for biodiversity, water quality and human uses. Strategies to cope with these climate change impacts are currently poorly developed. This article proposes the use of Grime’s CSR theory as a framework to understand the potential impacts of climate change on shoreline vegetation. It is also used to recommend a series of practical management techniques that will contribute to the adaptation capacity of shoreline ecosystems. Four key areas are highlighted: hydrological controls, substrate conditions, shoreline topography and vegetation establishment.     

Naturally recruited herbaceous vegetation in abandoned Belgian limestone quarries: towards habitats of conservation interest analogues?

We examined if naturally recruited herbaceous vegetation in abandoned Belgian limestone quarries tend towards plant communities analogous to semi-natural habitats of conservation interest. We studied taxon-based assemblages (using two-dimensional non-metric multidimensional scaling ordination) and functional patterns (relative to Grime’s competitor, stress tolerator and ruderal plant strategies (CSR) classification) of plant communities (n = 360 plots) among three different time periods after quarry abandonment (< 3 y, 3–20 y, >?20 y). We compared those successional assemblages with those of habitat of conservation interest plant communities (n = 53 plots): lowland hay meadows and rupicolous, xerophilous and mesophilous calcareous grasslands. Our results indicate that naturally recruited herbaceous vegetation compositionally resembled mesophilous grassland, even though initial substrate conditions were more similar to rupicolous or xerophilous grasslands. The specific successional pathway we found in CSR state-space differs from Grime's predictions because there was a functional shift in plant assemblages from dominance by ruderals to dominance by stress-tolerant species. The differences in successional trajectories we found on different types of rock substrate suggest that conservation management should adopt a site-specific approach, recognizing that the highest probabilities of success on hard limestone will be restoration to calcareous grassland analogues.     

地形对植被生物量遥感反演的影响——以广州市为例

目前植被生物量遥感反演研究中的地形校正主要是校正地形变化对地表反射率的影响,较少考虑地形起伏引起的像元面积与实际地表面积的差异,而这种差异将导致植被生物量估算结果的偏差.在生物量遥感反演的基础上,结合地表面积计算模型和物质守恒定律,建立了生物量地形校正模型,定量分析和讨论了地形起伏对广州市植被类型面积提取和生物量准确估算的影响.结果表明:地形校正前后全市针叶林、阔叶林、草地、灌木林和园地面积分别增加6.18％、3.70％、2.86％、1.92％和1.29％;在综合分析区域生物量遥感反演中的各种不确定性的基础上,建立的各植被类型的生物量模型均具有较高精度,相关系数均接近或者超过0.9,可以满足生物量反演的要求;全市植被生物量呈现出东、北高,西、南低的分布格局,像元实际代表的林地(阔叶林和针叶林)平均生物量为61.86t/hm2,高于珠三角区域生物量平均值,但与亚热带林的顶级群落生物量水平有较大差距,林地生物量还有较大的增长空间;经过校正地形变化引起的像元面积和实际地表面积差异对生物量提取结果的影响后,植被总生物量比校正前增加了5.82％,5种植被类型的总生物量有不同程度的增加,阔叶林、针叶林、草地、灌木林和园地分别增加了7.74％,4.76％、3.34％、2.50％和1.58％.与其它的表面积计算模型相比,利用的像元地表面积模型具有较高的精度,可以满足生物量遥感估算中地形校正的需要.     

Timing of snowmelt affects species composition via plant strategy filtering

Plant strategy schemes aim to classify plants according to measurable traits and group species according to their shared evolutionary responses to selective pressures. In this way, it becomes possible to make meaningful comparisons among ecosystems and communities and to predict how plant communities might respond to changes in their environment. Here, we classified common alpine plants which occur in snowpatches (Early and Late snowmelt sites) and in adjacent vegetation (Snow-free sites which melt early in the growing season) using Grime’s CSR plant strategy scheme. Alpine plant communities are largely driven by environmental filters associated with a relatively constant gradient of snowmelt timing. Since snow persistence influences the abiotic environment and plant assemblages alike, we hypothesised that these patterns would be reflected in community CSR scores. Weighted community CSR scores were clustered towards the stress-tolerator (S) corner of the triangular CSR space, and Snow-free communities were significantly more stress-tolerant than Early and Late snowmelt communities. This suggests that snowpatch communities are functionally distinct from surrounding vegetation when considering the major axes of plant variation identified by CSR theory. These results lend further support to the importance of the timing of snowmelt as a key filter, influencing how species and plant strategy types distribute themselves across the alpine landscape.     

Remote sensing of biodiversity: what to measure and monitor from space to species?

Global biodiversity monitoring systems through remote sensing can support consistent assessment, monitoring, modelling and reporting on biodiversity which are key activities intended for sustainable management. This work presents an overview of biodiversity monitoring components, i.e. biodiversity levels, essential biodiversity variables, biodiversity indicators, scale, biodiversity inventory, biodiversity models, habitat, ecosystem services, vegetation health and biogeochemical heterogeneity and discusses what remote sensing through Earth Observations has contributed to the study of biodiversity. The technological advancements in remote sensing have enabled information-rich data on biodiversity. Remote sensing data are making a strong contribution in providing unique information relevant to various biodiversity research and conservation applications. The extensive use of Earth observation data are not yet realized in biodiversity assessment, monitoring and conservation. The development of direct remote sensing approaches and the techniques for quantifying biodiversity at the community to species level is likely to be a great challenge for comprehensive earth observation-based monitoring strategy.

     

Vegetation Colonization in a Restoring Tidal Marsh: A Remote Sensing Approach

Although remote sensing offers the ability to monitor wetland restoration, few have tested automated methods for quantifying vegetation change. We implemented a semiautomated technique using color infrared aerial photography and a common vegetation index, Normalized Difference Vegetation Index (NDVI), to document vegetation colonization in a restoring salt marsh. Change in vegetation over a period of 10 years was analyzed using a postclassification comparison technique where each image year was classified individually into vegetated and nonvegetated areas using NDVI thresholds and then differenced between years to identify areas of vegetation change. Vegetated and nonvegetated areas were identified using this technique, as were areas and time periods of vegetation change. By comparing classified NDVI imagery, we calculated that 90% of our study site was vegetated 10 years after restoration. This study demonstrated that high-resolution remotely sensed data can be analyzed with common geospatial software to monitor change in a rapidly vegetating wetland and that long time frames with yearly image acquisition are needed to quantify plant colonization rates. This method was effective at detecting change in vegetation over time in a variable tidal marsh environment using imagery that had inconsistent specifications and quality across years. Inconsistencies included interannual climate variation, phenology, and presence of algae, as well as differences in pixel size and image brightness. Our findings indicate that remote sensing is useful for postrestoration monitoring of tidal marsh ecosystems.     

基于植被信息季节变换的植被覆盖度变化——以福建省连江县为例

基于植被覆盖度的植被信息遥感变化检测已成为研究植被及其相关生态系统变化的主要途径,但由于云覆盖等天气条件的影响,很难获得不同年份同一季节覆盖整个研究区的光学遥感影像来进行植被变化检测,而采用季节差异的影像必然会影响植被变化检测的结果.为此,本研究利用中高分辨率遥感数据的空间分辨率优势和MODIS遥感数据的时间分辨率优势,基于二者关系的拟合,提出一种植被信息季节变换的方法,将不同季节影像的植被覆盖度变换到研究所需的季节上.结果表明: 将该方法应用到福建敖江流域连江片区发现,植被信息变换的效果较好,经过将覆盖研究区的2007年冬季和2013年春季的中高分辨率影像的植被信息统一变换到夏季后,2007年的植被覆盖度由66.5%上升到79.7%,2013年由58.6%上升到77.9%,有效消除了因季节差异而对植被覆盖度估算产生的误差,提高了结果的准确性.     

Comparing and Combining Landsat Satellite Imagery and Participatory Data to Assess Land-Use and Land-Cover Changes in a Coastal Village in Papua New Guinea

In regions lacking socio-economic data, pairing satellite imagery with participatory information is essential for accurate land-use/cover (LULC) change assessments. At the village scale in Papua New Guinea we compare swidden LULC classifications using remote sensing analyses alone and analyses that combine participatory information and remotely sensed data. These participatory remote sensing (PRS) methods include participatory land-use mapping, household surveys, and validation of image analysis in combination with remotely sensed data. The classifications of the swidden area made using only remote sensing analysis show swidden areas are, on average, two and a half times larger than land managers reported for 1999 and 2011. Classifications made using only remote sensing analysis are homogeneous and lack discrimination among swidden plots, fallow land, and non-swidden vegetation. The information derived from PRS methods allows us to amend the remote sensing analysis and as a result swidden areas are more similar to actual swidden area found when ground-truthing. We conclude that PRS methods are needed to understand swidden system LULC complexities.     

遥感在生物多样性研究中的应用进展

随着人口的持续增长, 人类经济活动对自然资源的利用强度不断升级以及全球气候变暖, 全球物种正以前所未有的速度丧失, 生物多样性成为了全球关注的热点问题。传统生物多样性研究以地面调查方法为主, 重点关注物种或样地水平, 但无法满足景观尺度、区域尺度以及全球尺度的生物多样性保护和评估需求。遥感作为获取生物多样性信息的另一种手段, 近年来在生物多样性领域发展迅速, 其覆盖广、序列性以及可重复性等特点使之在大尺度生物多样性监测和制图以及评估方面具有极大优势。本文主要通过文献收集整理, 从观测手段、研究尺度、观测对象和生物多样性关注点等方面综述了遥感在生物多样性研究中的应用现状, 重点分析不同遥感平台的技术优势和局限性, 并探讨了未来遥感在生物多样性研究的应用趋势。遥感平台按观测高度可分为近地面遥感、航空遥感和卫星遥感, 能够获取样地-景观-区域-洲际-全球尺度的生物多样性信息。星载平台在生物多样性研究中应用最多, 航空遥感的应用研究偏少主要受飞行成本限制。近地面遥感作为一个新兴平台, 能够直接观测到物种的个体, 获取生物多样性关注的物种和种群信息, 是未来遥感在生物多样性应用中的发展方向。虽然遥感技术在生物多样性研究中的应用存在一定的局限性, 未来随着传感器发展和多源数据融合技术的完善, 遥感能更好地从多个尺度、全方位地服务于生物多样性保护和评估。     

Vegetation maps based on remote sensing are informative predictors of habitat selection of grassland birds across a wetness gradient

Vegetation is a major environmental factor influencing habitat selection in bird species. High resolution mapping of vegetation cover is essential to model the distribution of populations and improve the management of breeding habitats. However, the task is challenging for grassland birds because microhabitat variations relevant at the territory scale cannot be measured continuously over large areas to delineate areas of higher suitability. Remote sensing may help to circumvent this problem. We addressed this issue by using SPOT 5 imagery and phytosociological data. We mapped grassland vegetation in a floodplain using two methods. We (i) mapped the continuous Ellenberg index of moisture and (ii) identified 5 vegetation classes distributed across the wetness gradient. These two methods produced consistent output maps, but they also provided complementary results. Ellenberg index is a valuable proxy for soil moisture while the class approach provided more information about vegetation structure, and possibly trophic resources. In spite of the apparent uniformity of meadows, our data show that birds do not settle randomly along the moisture and vegetation gradients. Overall birds tend to avoid the driest vegetation classes, i.e. the highest grounds. Thus, vegetation maps based on remote sensing could be valuable tools to study habitat selection and niche partition in grassland bird communities. It is also a valuable tool for conservation and habitat management.     

Applying remote sensing techniques to monitor shifting wetland vegetation: A case study of Danshui River estuary mangrove communities,Taiwan

The purpose of this study is to apply different remote sensing techniques to monitor shifting mangrove vegetation in the Danshui River estuary in Taipei, Taiwan, in order to evaluate a long-term wetland conservation strategy compromising between comprehensive wetland ecosystem management and urban development. In the Danshui estuary, mangrove dominated by Kandelia candel is the major vegetation, and a large area of marsh with freshwater grasses has been protected in three reserves along the river shore. This study applied satellite imagery from different remote sensors of various resolutions for spectral analysis in order to compare shifting wetland vegetation communities at different times. A two-stage analytical process was used for extracting vegetation area and types. In the first-stage, a normalized difference vegetation index (NDVI) was adopted to analyze SPOT, Landsat, and QuickBird imagery to obtain the spatial distribution of vegetation covers. In the second stage, a maximum likelihood classification (MLC) program was used to classify mangrove and non-mangrove areas. The results indicated that the spatial distribution of mangroves expanded 15.18 and 40 ha in two monitoring sites in 10 years, demonstrating the success of establishing reserves for protecting mangrove habitats. The analytical results also indicated that satellite imagery can easily discern the difference in characteristics between imagery of mangrove and other vegetation types, and that the logistical disadvantages of monitoring long-term vegetation community changes as well as evaluating an inaccessible area may be overcome by applying remote sensing techniques.     

天津市彩色红外相片在研究植被与大气污染关系中的应用

利用彩色红外相片来研究城市植被与大气污染的关系,这是遥感技术应用于环境动态研究中的一个重要课题。在研究过程中,使用了中国科学院遥感所提供的天津市1／5000和1／10000比例尺彩色红外相片。我们首先将显示在相片上的植被与大气污染的遥感信息进行了解译,然后取样分析该地植物体中污染物质的含量,最后再到实地验证。结果表明,彩色红外相片记录了当时植被与大气污染的真实状况,具有丰富的信息,植被信息特征能够反映大气污染的基本情况。同时还可发现一些抗性强、吸毒能力大的绿化效应好的树种和绿化结构,可为城市建设、城市环境质量评价提供科学依据。     

RS和GIS在植被生态学中的应用及其前景

近年来,随着遥感和计算机软、硬件技术的发展与完善,利用遥感数据所进行的生态学研究已经深入到生态学的许多领域,取得了丰富的研究成果,并将继续在区域和全球尺度上的生态学研究中起着极为重要的作用。利用遥感所进行的生态学研究主要是基于植物的反射光谱特征来实现的。植物的反射光谱曲线具有显著特征。在可见光谱段,绿色植物的平均光谱反射率低于干土,而高于或接近于水体。在近红外谱段,植物的平均光谱反射率比土壤或水体高,以水体为最低。在中红外谱段,植物的平均光谱反射率比水体略高（或相近）,但明显高于干土。在０．３５…     

竞争-耐胁迫-杂草型植物对策理论及其应用研究进展

竞争-耐胁迫-杂草型植物(CSR)对策理论主要研究植物对环境胁迫和干扰的适应性特化。从功能生态学角度讲,CSR理论是通过解释各种功能性状协同变异的主导维度来反映植物的生态对策。而物种所采取的生态对策将决定其在群落中的生态位,并最终会影响生态系统过程与功能。自1974年Grime首次提出CSR对策的概念以来,CSR对策思想就受到了生态学家很大的关注,经过近半个世纪的发展,目前已经形成了比较完整的理论和研究方法体系。试图在回顾CSR理论及其研究方法发展的基础上,阐述其基本内涵,并重点从功能性状变异空间、植物适应性、群落过程和生态系统特性等4个方面概述CSR理论及其分析模型的验证及应用,梳理其最新研究进展。CSR理论已经得到了很多研究的广泛验证并应用于多种尺度上的植物生态学研究,但仍有一些方面值得进一步发展完善,如第四区缺失问题、功能性状变异主轴以外的变异、CSR对策与功能性状种内变异和谱系关系的联系等方面需要深入研究。     

时间信息熵及其在植被覆盖时空变化遥感检测中的应用

基于遥感影像的变化检测是当前的研究热点,可为区域生态环境保育、资源管理与发展规划等提供决策支撑。目前遥感影像的变化检测多基于两个时相,不能充分地反映植被在时间维的连续变化特征。通过引入信息论,提出了利用时间信息熵来综合表征植被长时间序列的变化特征。研究以延河流域为试验区,基于MODIS/NDVI数据,应用时间信息熵方法来计算了2000—2010年该区域的植被覆盖变化信息,厘清了时空变化特征。研究结果表明,近10年延河流域的植被覆盖的变化以增加为主,占流域面积的80.7%;植被覆盖明显增加的区域占流域面积13.9%,主要分布在流域的东北部和东南部;植被覆盖减少的区域占比2.4%,主要分布在流域的西部和西北部;严重减少的区域占比1.1%,主要分布在流域的中部和西南部,是需要重点的生态恢复与治理区域。时间信息熵方法与回归分析法相比,能够更为客观地表征长时间序列植被覆盖的连续变化强度和变化趋势,可为区域生态环境的保护和管理提供更为科学的理论依据。     

基于不同光谱指数的植被物候期遥感监测差异

植被物候是陆地生态系统响应气候和环境变化的一项综合性指标.遥感光谱已经被广泛用于提取植被物候期,但遥感提取的物候期与站点观测差别很大,其物理意义尚不明确.本文选取中国东北部的一景MODIS数据(2000—2014年),分析了基于红波段和近红外波段的归一化差值植被指数(NDVI)和简单比植被指数(SR)提取的植被生长季起始期(SOS)和结束期(EOS)的差异.结果表明:两者的物候期存在显著差别,基于NDVI提取的SOS比SR提取的SOS平均早18.9 d,基于NDVI提取的EOS比SR提取的EOS平均晚19.0 d,NDVI得到的生长季长度更长.基于NDVI和SR提取的物候期的年际变化也存在显著差别,超过20%的像元SOS和EOS甚至表现出相反的年际变化趋势.上述差异与两种植被指数自身的季节曲线特征和抗噪性差异有关.NDVI与SR观测数据来源完全一致,仅数学表达形式不同,提取的物候期结果却存在显著差异.说明遥感监测的植被物候期高度依赖于植被指数的数学表达形式,如何建立可靠的植被物候期遥感提取方法仍需进一步研究.     

Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review

Wetland vegetation plays a key role in the ecological functions of wetland environments. Remote sensing techniques offer timely, up-to-date, and relatively accurate information for sustainable and effective management of wetland vegetation. This article provides an overview on the status of remote sensing applications in discriminating and mapping wetland vegetation, and estimating some of the biochemical and biophysical parameters of wetland vegetation. Research needs for successful applications of remote sensing in wetland vegetation mapping and the major challenges are also discussed. The review focuses on providing fundamental information relating to the spectral characteristics of wetland vegetation, discriminating wetland vegetation using broad- and narrow-bands, as well as estimating water content, biomass, and leaf area index. It can be concluded that the remote sensing of wetland vegetation has some particular challenges that require careful consideration in order to obtain successful results. These include an in-depth understanding of the factors affecting the interaction between electromagnetic radiation and wetland vegetation in a particular environment, selecting appropriate spatial and spectral resolution as well as suitable processing techniques for extracting spectral information of wetland vegetation.     

城市不透水面与相关城市生态要素关系的定量分析

城市空间的快速扩展已使得原来以植被为主的自然景观逐渐被人工不透水建筑物所取代,并对区域乃至全球的生态系统造成了明显的影响.因此,准确了解城市不透水面及其与植被、水体、城市热环境的相关关系对于城市的科学规划和城市生态系统的修复具有重要的意义.以福州市为例,采用遥感空间信息技术,获得了城市不透水面、地表温度、植被和水体的信息,并对它们的关系进行了定量分析.发现了城市不透水面与地表温度之间的关系并不是一种简单的线性关系,而是一种很显著的指数函数关系,说明高不透水面比例地区的升温效应要明显高于低不透水面比例地区.多元统计分析表明不透水面是引发城市热岛的最重要因子.     

Differentiating geological fertility derived vegetation zones in Kruger National Park,South Africa,using Landsat and MODIS imagery

Spatial technologies present possibilities for producing frequently updated and accurate habitat maps, which are important in biodiversity conservation. Assemblages of vegetation are equivalent to habitats. This study examined the use of satellite imagery in vegetation differentiation in South Africa's Kruger National Park (KNP). A vegetation classification scheme based on dominant tree species but also related to the park's geology was tested, the geology generally consisting of high and low fertility lithology. Currently available multispectral satellite imagery is broadly either of high spatial but low temporal resolution or low spatial but high temporal resolution. Landsat TM/ETM+ and MODIS images were used to represent these broad categories. Rain season dates were selected as the period when discrimination between key habitats in KNP is most likely to be successful. Principal Component Analysis enhanced vegetated areas on the Landsat images, while NDVI vegetation enhancement was employed on the MODIS image. The images were classified into six field sampling derived classes depicting a vegetation density and phenology gradient, with high (about 89%) indicative classification accuracy. The results indicate that, using image processing procedures that enhance vegetation density, image classification can be used to map the park's vegetation at the high versus low geological fertility zone level, to accuracies above 80% on high spatial resolution imagery and slightly lower accuracy on lower spatial resolution imagery. Rainfall just prior to the image date influences herbaceous vegetation and, therefore, success at image scene vegetation mapping, while cloud cover limits image availability. Small scale habitat differentiation using multispectral satellite imagery for large protected savanna areas appears feasible, indicating the potential for use of remote sensing in savanna habitat monitoring. However, factors affecting successful habitat mapping need to be considered. Therefore, adoption of remote sensing in vegetation mapping and monitoring for large protected savanna areas merits consideration by conservation agencies.