Past and present forest vegetation in NE Slovenia derived from old maps

Abstract. Using old military and cadastral maps and modern vegetation maps, the changes in land use over the past 230 yr were followed. The following maps were used: the military map from the second half of the 18th century, the cadastral map of the ‘Economic cadastral survey for regulation of land taxes’ from the first half of the 19th century, and a field map made in the 1980s. A vegetation map of the area was made on the basis of satellite images. We used basic classification techniques combined with extensive field inspections and aerial photographs. The output of this procedure was verified in the field. Additionally, a comparison of statistical data about land use categories is presented. It was established that the last remaining areas of inundated riverine forest disappeared 200 yr ago, and since then only minor changes in land use have occurred.     

Regression Tree Analysis of satellite and terrain data to guide vegetation sampling and surveys

Abstract. Monitoring of regional vegetation and surface biophysical properties is tightly constrained by both the quantity and quality of ground data. Stratified sampling is often used to increase sampling efficiency, but its effectiveness hinges on appropriate classification of the land surface. A good classification must be sufficiently detailed to include the important sources of spatial variability, but at the same time it should be as parsimonious as possible to conserve scarce and expensive degrees of freedom in ground data. As part of the First ISLSCP (International Satellite Land Surface Climatology Program) Field Experiment (FIFE), we used Regression Tree Analysis to derive an ecological classification of a tall grass prairie landscape. The classification is derived from digital terrain, land use, and land cover data and is based on their association with spectral vegetation indices calculated from single-date and multi-temporal satellite imagery. The regression tree analysis produced a site stratification that is similar to the a priori scheme actually used in FIFE, but is simpler and considerably more effective in reducing sample variance in surface measurements of variables such as biomass, soil moisture and Bowen Ratio. More generally, regression tree analysis is a useful technique for identifying and estimating complex hierarchical relationships in multivariate data sets.     

Spectral reflectance of coral

Spectral reflectance (R) of corals is a fundamental parameter to coral reef remote sensing. We explore general trends as well as geographic and taxonomic variabilities of coral R using a data set consisting of 5,199 Rs measured in situ at depths of up to 15 m for 195 coral colonies at 11 sites worldwide. Coral R ranges in magnitude from ~0.5% at 400 nm to near 100% at 700 nm; mean coral R rises from ~2.5% at 400–500 nm to ~8% between 550 and 650 nm. All corals measured in this study exhibit one of two basic shapes of R, which we label the brown and blue modes. We postulate that brown-mode R is determined by pigment absorption solely by zooxanthellae, while blue-mode R arises through expression of a non-fluorescing coral-host pigment. Taxonomic and geographic variabilities are approximately equal to global variability, both in magnitude and shape, indicating that coral R is independent of taxonomic or geographic differences. We reason that this is to be expected, since R is determined by pigments that are conservative across geographic and taxonomic boundaries.     

Responses of the infrared sensilla of Melanophila acuminata (Coleoptera: Buprestidae) to monochromatic infrared stimulation

The pit organs of the beetle Melanophilaacuminata were stimulated with monochromatic infrared radiation using a continuous wave CO overtone infrared laser. Best sensitivity was in the wavelength range 2.8–3.5 μm. In this range a stimulus intensity of 14.7 mW cm⁻² was sufficient to generate single action potentials. At a wavelength of 5 μm receptor performance significantly decreased. An increase in stimulus intensity caused a decrease in response latency and an increase in the number of action potentials elicited. At a given wavelength (3.4 μm) the dynamic amplitude range of action potential responses covered 12 dB. At high stimulus intensities (94.2 mW cm⁻²) a stimulus duration of 4 ms was sufficient to generate one to two action potentials and a stimulus duration of 60 ms already caused response saturation (with up to nine action potentials). In a repetitive stimulus regime distinct receptor potentials were visible up to a frequency of 600 Hz. Accepted: 18 March 2000     

利用GIS和RS确定长白山自然保护区森林景观分布的环境范围

在对遥感数据进行景观分类和对环境因子进行空间表达基础上,在地理信息系统的支持下,确定长白山自然保护区森林景观分布的环境(包括年均温、年降水量、坡度和坡向)范围．结果表明。从苔原、岳桦、云冷杉到阔叶红松林,最适海拔高度范围依次为1780-2212、1705-1956、1042-1625、823-1184m;最适温度范围分别为-4．75～-2．40℃、-3．42～-2．07℃、-1．49-1．39℃、0．71-2．37℃;最适降水范围分别为1034～1110、1014-1060、883-1017、824-925mm;长白山自然保护区的森林景观主要分布在平、缓坡地上,并与坡向关系密切。苔原在各个坡向上均有分布。且在各个坡向上分布面积的变化不大;岳样、云冷杉林、阔叶红松林、山杨白样林主要呈现北、西北向分布,其次为东北、西向分布;落叶松林主要为东北向分布。其次为东和北向分布;疏林主要为西向分布,其次为西南、西北和南向分布;风倒区主要为西、西南、西北向分布。     

利用GIS对吉林针阔混交林TM遥感图像分类方法的初探

为提高林区TM遥感图像自动分类识别精度,在GIS技术辅助下,以吉林省汪清林业局针阔混交林TM遥感图像为例,对研究区DEM、坡向等地理因子和土壤类型等环境因子与森林植被分布之间的内在规律进行了定量分析,并结合对遥感图像预分类的定性分析,形成分类知识库,建立了适用于针阔混交林的自动分类识别专家系统.分类试验证明,该系统能比较明显地削弱混合像元和地形阴影的影响,分类精度较无监督分类法提高了14.22%,Kappa指数为0.7556,达到区别森林类型的分类目的.将GIS数据引入专家系统,应用先验知识建立推理机制,可以解决遥感图像中云区和云阴影区由于不能接收到正确的光谱值而无法进行分类的问题.     

The integration of Artificial Night-Time Lights in landscape ecology: A remote sensing approach

High-biodiversity landscapes around the globe are under immense pressure due to the expansion of human activities. To ensure effective monitoring and management of such landscapes, it is necessary to integrate landscape composition and the associated socio-economic processes in the conservation schemes. Artificial Night-Time Light (ANTL) pollution is a recent but striking environmental alteration due to human interventions. It is a major threat for species and communities which co-evolved with invariant natural light patterns over geological times. In spite of its potential key role in re-shaping natural systems, ANTL is seldom considered in macroecology. Remote sensing provides a unique set of tools to integrate ANTL in macroecological studies. In this work, we used remote sensing data of night-time lights along with Enhanced Vegetation Index (EVI) to study the effects and extent of ANTL in the night-time landscape (nightscape) of two protected areas in Italy. Our results showed that a considerable number of semi-natural vegetated patches suffer from ANTL pollution with varying magnitude. We observed a decline in highly suitable patches for biodiversity while the remaining patches were found concentrated in the innermost part of the parks. By simulating an exponential decrease in ANTL we showed that a moderate reduction in ANTL pollution would result in regaining a substantial amount of highly suitable patches for biodiversity. The decline in homogeneous dark patches in vegetated landscapes has negative impacts on biodiversity as well as on the ecosystem services it provides. Therefore, it is high time that the scientific community and the policy-makers increase their efforts to monitor and mitigate the ecological impacts of ANTL on ecosystems. The integration of light pollution in landscape ecology could combine remote sensing with other aspects of light pollution like indirect propagation and spectral composition.     

Vertical migration of Karenia brevis in the northeastern Gulf of Mexico observed from glider measurements

The toxic marine dinoflagellate, Karenia brevis (the species responsible for most of red tides or harmful algal blooms in the Gulf of Mexico), is known to be able to swim vertically to adapt to the light and nutrient environments, nearly all such observations have been made through controlled experiments using cultures. Here, using continuous 3-dimensional measurements by an ocean glider across a K. brevis bloom in the northeastern Gulf of Mexico between 1 and 8 August 2014, we show the vertical migration behavior of K. brevis. Within the bloom where K. brevis concentration is between 100,000 and 1,000,000 cells L⁻¹, the stratified water shows a two-layer system with the depth of pycnocline ranging between 14–20 m and salinity and temperature in the surface layer being <34.8 and >28 °C, respectively. The bottom layer shows the salinity of >36 and temperature of <26 °C. The low salinity is apparently due to coastal runoff, as the top layer also shows high amount of colored dissolved organic matter (CDOM). Within the top layer, chlorophyll-a fluorescence shows clear diel changes in the vertical structure, an indication of K. brevis vertical migration at a mean speed of 0.5–1 m h⁻¹. The upward migration appears to start at sunrise at a depth of 8–10 m, while the downward migration appears to start at sunset (or when surface light approaches 0) at a depth of ∼2 m. These vertical migrations are believed to be a result of the need of K. brevis cells for light and nutrients in a stable, stratified, and CDOM-rich environment.