森林生态系统生物多样性的遥感评估

目前的评估由于方法的原因,常常会遗留下一些含糊不清的地方。遥感则可以作一种观察生态系统多样性和单个生态系统中各种结构侧面的重要工具。它提供了一种能够跨越几个不同空间尺度实施评估的手段,并且对于评估生态系统格局随时间的变化也是必不可少。现在许多不同的遥感技术已经被应用在生态学研究中。大多数工作所用的数据主要是来自机载和星载平台提供的摄影和数字光学图像,目前则越来越强调激光扫描和合成孔径雷达数据的应用。这些技术手段为从景观到林分规模的不同现象的评估提供了机会。遥感提供了可用于确定森林生态系统中生物多样性景观尺度的元素最有效的工具。例如基质和斑块的相对百分比以及它们的配置。在中间尺度,遥感为评价廊道的存在和边界的特性提供了理想的工具。在林分尺度,遥感技术可用来获取关于森林分结构属性的信息,例如冠层表面的特性,是否存在冠内分层等等。随着的发展,遥感将更广泛地应用于生态学研究。     

Applying geographic information systems and remote sensing for water quality assessment of mangrove forest

The study of environmental conditions is one of the most important measures in the field of reforestation. The present study was undertaken to assess the environmental status of the mangrove forest of Alibaug, Maharashtra, India with respect to different sixteen physicochemical parameters of water using Geographical information system (GIS) for rehabilitation, conservation and development of the destructed area of the mangrove forest. The Base map of study area was prepared using topographic map and the remote sensing data of Landsat 7 ETM + for spatial analysis. The distributions of water pollutants were assigned using a GIS approach of Inverse Distance Weighted (IDW). The results showed that the amounts of EC, COD, hardness, O&G, Cl^?, Na⁺, Ca^2 +, Mg^2 +, NO₃^? and PO₄^3? are higher than the normal ranges in mangrove forest due to natural processes and human activity, industrial and domestic wastewater disposal, oil spillage and agricultural runoff which all eventually affect the water quality of mangrove forest of Alibaug. To identify the areas within the normal ranges of 16 studied parameter, suitability map of water was prepared through an integration of 16 suitability maps of the studied parameters. The suitability map of water classified the water to six classes of suitability in order of moderate > moderate to high > low to moderate > high > low suitable. The areas with classes of 1 and 2 were suitable for the protective measures. Classes 3 and 4 were suitable for replantation and restoration of native mangrove species as well as local communities' cooperation in the participatory protection measures. The areas of classes 5 and 0 need to be designed an urgent management and mitigation plan to reduce impact of human activities. The result of the study also proves the use of GIS as a powerful tool in addressing assessment and monitoring programs of the water quality in the mangrove ecosystems.     

基于TM遥感影像的森林资源线性规划与优化配置研究

山东黄河流域是黄河入海的最后区域,也是水土流失最为严重的地区之一,基于遥感影像和数学方法优化配置森林资源对区域尺度的水土保持具有重要意义。选取2000年、2006年时相相近的TM遥感影像作为数据源,采用监督分类法、专家分类法以及GPS、GIS等技术对森林资源进行分类、统计、验证和分析。在层次分析法确定森林资源、森林景观、环境和社会经济等指标因子权重的基础上,利用线性规划法对森林资源的空间格局进行优化。结果表明,区域森林资源空间分布极不均匀,且主要集中于鲁中南山地及丘陵地区。6a间,森林资源增长相对缓慢,宜林荒山荒地的面积增加了8.2%,到2006年,其面积高达238955.7 hm2。对宜林荒山荒地进行线性优化后,森林类型和结构得到明显改善,土地利用结构信息墒降低了8.4%,森林资源和土地利用空间结构有序度明显提高。最后,对立地条件不同的地区采取了相应的树种配置措施。     

Integrating demography,dispersal and interspecific interactions into bird distribution models

Species’ ranges are primarily limited by the physiological (abiotic) tolerance of the species, described by their fundamental niche. Additionally, demographic processes, dispersal, and interspecific interactions with other species are shaping species distributions, resulting in the realised niche. Understanding the complex interplay between these drivers is vital for making robust biodiversity predictions to novel environments. Correlative species distribution models have been widely used to predict biodiversity response but also remain criticised, as they are not able to properly disentangle the abiotic and biotic drivers shaping species’ niches. Recent developments have thus focussed on 1) integrating demography and dispersal into species distribution models, and on 2) integrating interspecific interactions. Here, I review recent demographic and multi‐species modelling approaches and discuss critical aspects of these models that remain underexplored in general and in respect to birds, for example, the complex life histories of birds and other animals as well as the scale dependence of interspecific interactions. I conclude by formulating modelling guidelines for integrating the abiotic and biotic processes that limit species’ ranges, which will help to disentangle the complex roles of demography, dispersal and interspecific interactions in shaping species niches. Throughout, I pinpoint complexities of avian life cycles that are critical for consideration in the models and identify data requirements for operationalizing the different modelling steps.     

Integrating GIS and remote sensing for vegetation analysis and modeling: methodological issues

Abstract. GIS and remote sensing have emerged as distinct spatial data handling technologies with their own methods of data representation and analysis. Combining them as tools to support vegetation analysis and modeling thus presents a number of challenges. The paper begins by describing the major data sources, applications, and software characteristics of each technology, and then compares them within a consistent terminological framework that emphasizes the digital representation of continuously varying spatial data. Because the spatial continuum can be discretized in many different ways, and because each can only approximate the truth, both GIS and remote sensing are subject to error and uncertainty. Integration, and subsequent analysis and modeling, require that explicit attention be directed to uncertainty. The paper reviews the models of error that have been developed in recent years for spatial data and examines their use in the interface between GIS and remote sensing. The paper looks at the functional requirements of modeling, and includes discussion of error propagation.     

Integrating approaches leads to more effective conservation of biodiversity

Recent debates have discussed whether a species-approach or an ecosystem-approach is better for protecting biodiversity. Rather than perpetuate this debate, we argue that critical new scientific and conservation insights arise from combining and integrating approaches along a continuum. We present a suite of case studies and other examples, which highlight the value and synergies derived from an integrated approach for developing management-relevant understanding aimed at protecting biodiversity. Attempts to conserve biodiversity should therefore be multi-faceted in approach and thinking. They also should be long-term as well as driven by well-developed questions focused on closing key knowledge gaps.     

森林生物量遥感降尺度研究

森林生物量是评价全球碳氧平衡、气候变化的重要指标。目前已有基于星载激光雷达数据的全球森林生物量产品,但空间分辨率较低,不能很好地满足小区域森林调查和动态监测的需要。针对这一现状,以美国马里兰州两个森林分布状况不同的区域为研究区,基于CMS(Carbon Monitoring System)30 m分辨率和GEOCARBON 1 km分辨率森林地上生物量产品以及TM等数据源,通过升尺度模拟低分辨率生物量数据和直接使用低分辨率产品两种方式,分别尝试建立了多光谱地表参数和低分辨率森林地上生物量之间的统计关系,以此作为降尺度模型实现了森林地上生物量空间分辨率从1 km到30 m的转换,并对降尺度结果进行精度评价和误差分析。结果表明:模拟数据降尺度后的30 m分辨率森林地上生物量空间分布和CMS森林地上生物量分布状况大致相同,RMSE=59.2—65.5 Mg/hm~2,相关系数约为0.7;其降尺度结果优于GEOCARBON产品直接降尺度结果RMSE=75.3—79.9 Mg/hm~2;相较于线性模型,非线性模型能更好地呈现森林地上生物量和地表参数间的关系;总体上,降尺度生物量呈现高值区低估,低值区高估的现象。     

Toward a forest biomass reference measurement system for remote sensing applications

Forests contribute to climate change mitigation through carbon storage and uptake, but the extent to which this carbon pool varies in space and time is still poorly known. Several Earth Observation missions have been specifically designed to address this issue, for example, NASA's GEDI, NASA-ISRO's NISAR and ESA's BIOMASS. Yet, all these missions' products require independent and consistent validation. A permanent, global, in situ, site-based forest biomass reference measurement system relying on ground data of the highest possible quality is therefore needed. Here, we have assembled a list of almost 200 high-quality sites through an in-depth review of the literature and expert knowledge. In this study, we explore how representative these sites are in terms of their coverage of environmental conditions, geographical space and biomass-related forest structure, compared to those experienced by forests worldwide. This work also aims at identifying which sites are the most representative, and where to invest to improve the representativeness of the proposed system. We show that the environmental coverage of the system does not seem to improve after at least the 175 most representative sites are included, but geographical and structural coverages continue to improve as more sites are added. We highlight the areas of poor environmental, geographical, or structural coverage, including, but not limited to, Canada, the western half of the USA, Mexico, Patagonia, Angola, Zambia, eastern Russia, and tropical and subtropical highlands (e.g. in Colombia, the Himalayas, Borneo, Papua). For the proposed system to succeed, we stress that (1) data must be collected and processed applying the same standards across all countries and continents; (2) system establishment and management must be inclusive and equitable, with careful consideration of working conditions; and (3) training and site partner involvement in downstream activities should be mandatory.     

Allometric equations for integrating remote sensing imagery into forest monitoring programmes

Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able – for the first time – to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed – specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large‐scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.     

遥感在森林地上生物量估算中的应用

生物量是地表C循环研究的重要组成部分,生物量研究有助于深入认识区域乃至全球的C平衡。森林作为地球最重要的陆地生态系统,区域乃至全球尺度的森林地上生物量估算一直是生态学研究的难点之一。在大的空间尺度上,遥感技术是估算森林地上生物量的有效手段。TM、AVHRR、SAR等数据以及多源数据的融合在森林生物量估算方面广泛应用,并取得了显著效果。运用遥感技术进行森林生物量估算时,所采用的数据源不同,分析方法也不相同,主要分析方法有:相关分析、多元回归分析、神经网络和数学模型模拟等。随着测定不同空间、时间和波谱分辨率的各种传感器的广泛使用,以及生物量遥感估算模型的进一步发展和完善,大尺度森林生物量的遥感估算研究必将向前迈进一大步。     

Integrating remote sensing and local ecological knowledge to monitor rangeland dynamics

Rangelands are among the most extensive anthropogenic landscapes on earth, supporting nearly 500 million people. Disagreements over the extent and severity of rangeland degradation affect pastoralist livelihoods, especially when impacts of drought and over-grazing are confounded. While vegetation indices (such as NDVI, or Normalized Difference Vegetation Index) derived from remotely sensed imagery are often used to monitor rangelands, their strategic integration with local ecological knowledge (LEK) is under-appreciated. Here, we explore these complementary approaches in Kyrgyzstan’s pasture-rich province of Naryn, where disagreements regarding pasture degradation could greatly benefit from additional information. We examine a time series of MODIS satellite imagery (2000–2015) to characterize browning trends in vegetation as well as to distinguish between climate- and grazing-induced trends. We also compare and contrast measured trends with LEK perceptions of pasture degradation. To do so, we first examine statistical trends in NDVI as well as in NDVI residuals after de-trending with meteorological data. Second, we use participatory mapping to identify areas local pasture managers believe are overgrazed, a particularly useful approach in lieu of reliable historical stocking rates for livestock in this region. Lastly, we compare the strengths and weaknesses of LEK and remote sensing for landscape monitoring.Browning trends were widespread as declining trends in NDVI (and NDVI residuals) covered 24% (and 9%) of the landscape, respectively. Local managers’ perceptions of pasture degradation better reflected trends seen in NDVI than in climate-controlled NDVI residuals, suggesting patterns in the latter are less apparent to managers. Our approach demonstrated great potential for the integration of two inexpensive and effective methods of rangeland monitoring well-suited to the country’s needs. Despite limitations due to terrain, our approach was most successful within the semi-arid steppe where pasture degradation is believed to be most severe. In many parts of the world, sources of long-term spatially extensive data are rare or even non-existent. Thus, paired LEK and remote sensing can contribute to comprehensive and informative assessments of land degradation, especially where contentious management issues intersect with sparse data availability. LEK is a valuable source of complementary information to remote sensing and should be integrated more routinely and formally into landscape monitoring. To aid this endeavor, we synthesize advice for linking LEK and remote sensing across diverse landscape situations.     

Towards more effective integration of tropical forest restoration and conservation

Conservation and restoration interventions can be mutually reinforcing and are converging through an increased focus on social dimensions. This paper examines how to more effectively integrate the complementary goals of conservation and restoration of tropical forests. Forest conservation and restoration interventions are integral components of a broad approach to forest ecosystem and landscape management that aims to maintain and restore key ecological processes and enhance human well‐being, while minimizing biodiversity loss. The forest transition model provides a useful framework for understanding the relative importance of forest conservation and restoration interventions in different regions. Harmonizing conservation and restoration presents serious challenges for forest policy in tropical countries, particularly regarding the use and management of secondary forests, fallow vegetation, and forests degraded by logging and fire. Research to implement restoration more effectively in tropical regions can be stimulated by transforming questions that initially focused on conservation issues. Examination of papers published in Biotropica from 2000–2018 shows that most studies relevant to tropical forest conservation do not address forest restoration issues. Forest restoration studies, on the other hand, show a consistent association with conservation issues. There is much scope for further integration of conservation and restoration in research, practice, and policy. Securing a sustainable future for tropical forests requires developing and applying integrated approaches to landscape management that effectively combine knowledge and tools from multiple disciplines with practical experience and engagement of local stakeholders. Abstract in Portuguese is available with online material.     

基于遥感降尺度估算中国森林生物量的空间分布

森林生物量是陆地生态系统重要的碳库,其大小与空间分布特征直接影响森林的碳汇潜力。基于空间降尺度技术,以中国第六次国家森林资源清查资料为基础,同时结合1∶100万植被分布图及同期的基于MODIS反演的NPP空间分布,定量估算了1 km分辨率下我国森林生物量的空间分布。结果表明:(1)降尺度技术能有效结合遥感数据的空间特征与地面详查资料的统计特征,从而较好地解决当前生物量估算的区域尺度转化问题;(2)我国森林生物量存在明显的空间分布规律,与水热条件的空间分布格局基本一致,表现为西部较低东部较高,大型山脉分布处较高;(3)我国森林生物量总量11.0 Pg,平均生物量74.8 Mg/hm2,其中高值区主要集中在东北大小兴安岭和长白山地区、新疆山区、西南横断山脉地区以及东南武夷山地区。     

Integrating demography and distribution modeling for the iconic Leontopodium alpinum Colm. in the Romanian Carpathians

1. Both climate change and human exploitation are major threats to plant life in mountain environments. One species that may be particularly sensitive to both of these stressors is the iconic alpine flower edelweiss (Leontopodium alpinum Colm.). Its populations have declined across Europe due to over‐collection for its highly prized flowers. Edelweiss is still subject to harvesting across the Romanian Carpathians, but no study has measured to what extent populations are vulnerable to anthropogenic change.
2. Here, we estimated the effects of climate and human disturbance on the fitness of edelweiss. We combined demographic measurements with predictions of future range distribution under climate change to assess the viability of populations across Romania.
3. We found that per capita and per‐area seed number and seed mass were similarly promoted by both favorable environmental conditions, represented by rugged landscapes with relatively cold winters and wet summers, and reduced exposure to harvesting, represented by the distance of plants from hiking trails. Modeling these responses under future climate scenarios suggested a slight increase in per‐area fitness. However, we found plant ranges contracted by between 14% and 35% by 2050, with plants pushed into high elevation sites.
4. Synthesis. Both total seed number and seed mass are expected to decline across Romania despite individual edelweiss fitness benefiting from a warmer and wetter climate. More generally, our approach of coupling species distribution models with demographic measurements may better inform conservation strategies of ways to protect alpine life in a changing world.

     

不同林分郁闭度与遥感数据的相关性

林分郁闭度与遥感数据的相关性分析是郁闭度遥感估算的基础,郁闭度遥感是林业遥感的重要方向。以四川省石棉县为例,就不同林分探讨了其郁闭度与陆地资源卫星专题制图仪LANDSAT Thematic Mapper(TM,包括其波段1至7,分别表示为TM1、TM2、TM3、TM4、TM5、TM6和TM7)数据之间的相关性及其受地形校正的影响。建立了地形数据库和基于1994年调查数据的森林资源数据库;对1994年6月26日成像的LANDSAT TM数据进行了几何校正,并与森林资源数据库配准;分别利用Lambert Cosine Correction(LCC)模型和Sun Canopy Sensor(SCS)模型对TM数据进行地形校正,生成TM-LCC和TM-SCS数据;将TM、TM-LCC和TM-SCS各波段数据分别与森林资源数据叠加统计,得到各小班TM、TM-LCC和TM-SCS各波段数据的均值和标准差,并将其添入数据库中,选取标准差较小的小班共1194个作为样本。按优势树种将样本层化为8个林分层,分别计算其郁闭度与TM、TM-LCC和TM-SCS各波段数据间的相关系数,并分析其在不同林分不同波段上的差异及其受地形校正的影响。研究表明:铁杉、冷杉和云杉等林分郁闭度与TM部分波段数据的相关性在0.01的水平上均为显著;而桦木、栎类、桤木、软阔类和云南松等林分郁闭度与TM数据的相关性在0.05的水平上均不显著;TM的LCC校正提高了冷杉、铁杉和软阔等林分郁闭度与TM4和TM5的相关性,TM的LCC校正还提高了软阔类林分郁闭度与TM7的相关性,TM的SCS校正提高了冷杉林分郁闭度与TM4和TM5的相关性,且在0.01的水平上均为显著。TM的LCC和SCS校正未能明显提高桦木、栎类、桤木、云南松和云杉等林分郁闭度与TM数据的相关性。该研究对林分郁闭度遥感具有一定的科学意义和应用价值。     

地形校正对森林生物量遥感估测的影响

基于常用的4种地形校正模型（Cosine模型、C模型、C+SCS模型、Minnaert模型）,以IDL语言为二次开发平台,对黑龙江省帽儿山地区2007年7月21日TM图像进行地形校正,从视觉差异、图像的定量统计特征两方面评价了4种地形校正模型的修正效果,并比较了地形校正后几种遥感因子与森林生物量的相关性,建立了森林生物量的遥感反演模型,分析了不同地形校正模型对森林生物量反演的影响.结果表明：由于K-T变换采用线性变换方式,地形校正后遥感数据与森林生物量的相关性出现了较大波动,应根据地表信息调整变换参数,因此该变换方式不适合与地形校正结合使用;植被指数的信息量在地形校正后明显提高,其与森林生物量的相关性显著增强;4种地形校正模型中,Cosine校正过度,不宜采用,C模型和C+SCS模型通过引入半经验参数,较好地消除了地形效应,Minnaert模型校正后降低了森林生物量估测的误差,有效地提高了遥感反演模型的精度.     

林地叶面积指数遥感估算方法适用分析

叶面积指数是与森林冠层能量和CO2交换密切相关的一个重要植被结构参数,为了探讨估算林地叶面积指数LAI的遥感适用方法和提高精度的途径,利用TRAC仪器测定北京城区森林样地的LAI,从Landsat TM遥感图像计算NDVI、SR、RSR、SAVI植被指数,分别建立估算LAI的单植被指数统计模型、多植被指数组合的改进BP神经网络,获取最有效描述LAI与植被指数非线性关系的方法并应用到TM图像估算北京城区LAI。结果表明,单植被指数非线性统计模型估算LAI的精度高于线性统计模型;多植被指数组合神经网络中,以NDVI、RSR、SAVI组合估算LAI的精度最高,估算值与观测值线性回归方程的R2最高,为0.827,而RMSE最低,为0.189,神经网络解决了多植被指数组合统计模型非线性回归方程的系数较多、较难确定的问题,可较为有效的应用于遥感图像林地LAI的估算。