基于机载激光雷达的中亚热带常绿阔叶林林窗特征

机载激光雷达(LiDAR)是一种新型主动式遥感技术,能直接获取多尺度高精度的冠层三维结构信息,将其推广到森林干扰生态学领域,可为林窗研究提供应用支撑.以湖南中亚热带常绿阔叶林为研究对象,利用小光斑LiDAR数据进行林窗识别和几何特征估测.选择合适的分辨率和内插方法生成冠层高程模型,采用计算机图形学方法估测林窗面积、边界木高度和形状指数,并进行野外观测验证.结果表明: 林窗识别率为94.8%,主要影响因素是林窗面积和林窗形成木类型;估测的林窗面积和边界木高与野外观测值呈较强线性相关,R²值分别为0.962和0.878,其中估测的林窗面积平均比野外观测值高19.9%,估测的林窗边界木高度平均比野外观测值低9.9%;区域内林窗密度为12.8个·hm^-2,占森林面积13.3%;林窗面积、边界木高和形状指数的平均值分别为85.06 m²、15.33 m和1.71,区域内多为较小面积、边缘效应不太显著的林窗.
     

斑块边缘效应的定量评价及其生态学意义

边缘效应是生态系统 (斑块 )边缘和生态过渡区所呈现出的生态效应。但由于景观性质、研究目标和斑块形状的变化 ,边缘效应影响的范围和程度差异较大。核心斑块与周边景观之间的相似性既可以增强边缘效应 ,也可以减弱边缘效应。正确理解和确定边缘效应的影响范围和程度直接关系到对野外环境观测数据的科学使用。许多情况下 ,由于未能正确认识一个生态系统(斑块 )的边缘效应 ,时常会将在边缘效应地区获得的数据与系统内部核心区的观测数据混淆使用 ,得出一些不科学的结论。边缘效应的定量评价对于进行科学的野外环境观测 ,及其在自然保护区功能区设计和生物多样性保护中具有重要意义。但如何定量评价生态系统 (斑块 )的边缘效应目前还缺乏科学有效的方法。从分析边缘效应的概念和影响因子出发 ,结合地理信息系统 ,提出了开展定量评价斑块边缘效应的方法 ,并探讨了定量研究边缘效应的生态学意义。     

Modelling relationships between birds and vegetation structure using airborne LiDAR data: a review with case studies from agricultural and woodland environments

Airborne LiDAR (Light Detection and Ranging) is a remote sensing technology that offers the ability to collect high horizontal sampling densities of high vertical resolution vegetation height data, over larger spatial extents than could be obtained by field survey. The influence of vegetation structure on the bird is a key mechanism underlying bird–habitat models. However, manual survey of vegetation structure becomes prohibitive in terms of time and cost if sampling needs to be of sufficient density to incorporate fine-grained heterogeneity at a landscape extent. We show that LiDAR data can help bridge the gap between grain and extent in organism–habitat models. Two examples are provided of bird–habitat models that use structural habitat information derived from airborne LiDAR data. First, it is shown that data on crop and field boundary height can be derived from LiDAR data, and so have the potential to predict the distribution of breeding Sky Larks in a farmed landscape. Secondly, LiDAR-retrieved canopy height and structural data are used to predict the breeding success of Great Tits and Blue Tits in broad-leaved woodland. LiDAR thus offers great potential for parameterizing predictive bird–habitat association models. This could be enhanced by the combination of LiDAR data with multispectral remote sensing data, which enables a wider range of habitat information to be derived, including both structural and compositional characteristics.     

Root distribution at various distances from clove trees growing in Indonesia

Efficient fertilizer application requires an understanding of the distribution of roots and soil nutrients in the soil profile. Cultural practices for clove trees in Indonesia has resulted in phosphorus (P) fertilizer being applied at the canopy edge; however, in these high P fixing soils efficient P fertilizer application should occur with the highest root densities. The objective of this study, therefore, was to determine the rooting distribution at various distances from the tree and soil depths for clove (Eugenia aromatica OK; variety Zanzibar) trees growing on an Andosol soil at Modoinding, Indonesia. Root distributions were determined to a 100-cm soil depth using soil cores at 0.5, 1.0 and 1.5 times the canopy radius for five 10-year-old clove trees grown on either level terrain or 23% slopes. Clove root length and weight densities decreased with soil depth and distance from the tree base. Fine clove roots (1 mm dia) comprised 72% of the total root length and was three to five times higher underneath the canopy than that outside the canopy. Roots were concentrated in the upper soil horizons; however, up to 36% of the total root length was found at a depth of 50–100 cm. Clove roots for trees growing at the level landscape position had the highest root length densities. Intercropped species root length densities were higher than clove root length densities at 1.5 times the canopy radius whereas intercropped root weight densities were higher than that for clove roots at both 1.5 and 1 times the canopy radius. Results suggest that fertilizer applications should be placed closer to the tree trunk rather than at the canopy edge to maximize P uptake by clove roots.     

Photosynthetic acclimation to elevated CO2 in a sunflower canopy

Sunflower canopies were grown in mesocosom gas exchange chambers at ambient and elevated CO2 concentrations (360 and 700 ppm) and leaf photosynthetic capacities measured at several depths within each canopy. Elevated [CO2] had little effect on whole-canopy photosynthetic capacity and total leaf area, but had marked effects on the distribution of photosynthetic capacity and leaf area within the canopy. Elevated [CO2] did not significantly reduce the photosynthetic capacities per unit leaf area of young leaves at the top of the canopy, but it did reduce the photosynthetic capacities of older leaves by as much as 40%. This effect was not dependent on the canopy light environment since elevated [CO2] also reduced the photosynthetic capacities of older leaves exposed to full sun on the south edge of the canopy. In addition to the effects on leaf photosynthetic capacity, elevated [CO2] shifted the distribution of leaf area within the canopy so that more leaf area was concentrated near the top of the canopy. This change resulted in as much as a 50% reduction in photon flux density in the upper portions of the elevated [CO2] canopy relative to the ambient [CO2] canopy, even though there was no significant difference in the total canopy leaf area. This reduction in PFD appeared to account for leaf carbohydrate contents that were actually lower for many of the shaded leaves in the elevated as opposed to the ambient [CO2] canopy. Photosynthetic capacities were not significantly correlated with any of the individual leaf carbohydrate contents. However, there was a strong negative correlation between photosynthetic capacity and the ratio of hexose sugars to sucrose, consistent with the hypothesis that sucrose cycling is a component of the biochemical signalling pathway controlling photosynthetic acclimation to elevated [CO2].     

基于无人机激光雷达遥感的亚热带常绿阔叶林群落垂直结构分析

森林植被高度与树木分布格局是植物群落重要结构特征,也是计算森林生物量分布的重要参数。传统的森林群落调查方法耗费大量人力物力难以进行较大尺度的群落结构测量,而一般的遥感影像也难以获得精确的地形信息及垂直结构。近年来激光雷达(Light Detection and Ranging,LiDAR)技术快速发展,能够较好的进行植被三维特征的提取并被广泛应用于森林生态系统检测模拟。且随着无人机低空摄影技术的发展催生的无人机激光雷达(UAV-Lidar)更增加了激光雷达的灵活性以及获取较大范围植被冠层信息的能力。而受限于激光的穿透性以及不同植被类型郁闭度的影响,该技术的应用多局限于在针叶林群落的垂直结构研究,而在常绿阔叶林的研究中应用较少。为探究现有无人机激光雷达设备及垂直结构提取分析技术应用于常绿阔叶林的可行性,利用无人机载激光雷达遥感技术对哀牢山中山湿性常绿阔叶林3块面积1hm~2的样地进行基于数字表面模型以及数字地表高程模型做差得到树冠高度模型测量的植被冠层高度、基于局部最大值法进行单木位置提取并使用Clark-Evans最近邻体分析方法进行样地内高大乔木分布格局的计算。分析结果显示,植被高度提取精度平均大于95%,与地表实测的植被高度值拟合度较高,相关系数R~2介于0.833—0.927之间;3个样地冠层高度平均值分别为18.79、19.08、17.03 m,标准差分别为8.10、7.34、7.17 m。单木探测百分比平均86.3%,用户精度以及生产者精度平均分别为75.69%和65.15%。实测得出三个样地全部高大乔木空间分布格局均为聚集分布,而激光雷达测量结果显示为随机分布或均匀分布。实验显示基于无人机激光雷达技术能够很好地提取植被冠层高度信息并能够较好地获取树木位置,但对于树木空间分布格局判定的准确性有待于进一步探索。未来研究应从多角度对激光雷达测量造成的误差原因予以分析(如环境因素),并进一步研究更为精确的单木提取以及植被高度提取方法,为通过无人机激光雷达测算森林生物量及各种生态过程提供更加精准的指标数据。     

Investigation of Spatial Distribution of Radiocesium in a Paddy Field as a Potential Sink

Surface soils, under various land uses, were contaminated by radionuclides that were released by the Fukushima Daiichi Nuclear Power Plant accident. Because paddy fields are one of the main land uses in Japan, we investigated the spatial distribution of radiocesium and the influence of irrigation water in a paddy field during cultivation. Soil core samples collected at a paddy field in Fukushima showed that plowing had disturbed the original depth distribution of radiocesium. The horizontal distribution of radiocesium did not show any evidence for significant influence of radiocesium from irrigation water, and its accumulation within the paddy field, since the original amount of radiocesium was much larger than was added into the paddy field by irrigation water. However, it is possible that rainfall significantly increases the loading of radiocesium.     

Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2 mission) with the goal of improving wildlife modeling for more locations across the globe.     

Comparing canopy metrics derived from terrestrial and airborne laser scanning in a Douglas-fir dominated forest stand

Accurate estimates of vegetation structure are important for a large number of applications including ecological modeling and carbon budgets. Light detection and ranging (LiDAR) measures the three-dimensional structure of vegetation using laser beams. Most LiDAR applications today rely on airborne platforms for data acquisitions, which typically record between 1 and 5 “discrete” returns for each outgoing laser pulse. Although airborne LiDAR allows sampling of canopy characteristics at stand and landscape level scales, this method is largely insensitive to below canopy biomass, such as understorey and trunk volumes, as these elements are often occluded by the upper parts of the crown, especially in denser canopies. As a supplement to airborne laser scanning (ALS), a number of recent studies used terrestrial laser scanning (TLS) for the biomass estimation in spatially confined areas. One such instrument is the Echidna^® Validation Instrument (EVI), which is configured to fully digitize the returned energy of an emitted laser pulse to establish a complete profile of the observed vegetation elements. In this study we assess and compare a number of canopy metrics derived from airborne and TLS. Three different experiments were conducted using discrete return ALS data and discrete and full waveform observations derived from the EVI. Although considerable differences were found in the return distribution of both systems, ALS and TLS were both able to accurately determine canopy height (Δ height < 2.5 m) and the vertical distribution of foliage and leaf area (0.86 > r ² > 0.90, p < 0.01). When using more spatially explicit approaches for modeling the biomass and volume throughout the stands, the differences between ALS and TLS observations were more distinct; however, predictable patterns exist based on sensor position and configuration.     

Willow Warbler Phylloscopus trochilus habitat in woods with different structure and management in southern England

Capsule Use of Light Detection and Ranging (LiDAR) data identified suitable Willow Warbler habitat based on mean vegetation height. This habitat model provided maps of distribution and occupation of suitable habitat.

Aims To identify habitat associations in woods with different vegetation structure and management systems during a period of low Willow Warbler populations.

Methods Locations of all Willow Warblers were mapped during the breeding season in three woods of contrasting management; recent low intervention, actively coppiced woodland and high forest with clear‐fells. Height profile models of each wood were derived from airborne LiDAR. The mean vegetation height at locations with Willow Warblers and a sample from the rest of the wood were used to produce models of optimum habitat and breadth of habitat occupied in each wood. The habitat model was then used to produce maps of suitable habitat.

Results The habitat models did not differ between woods, with highest probability of Willow Warbler occurrence in mean vegetation heights of 3.7–5.3 m. Habitat of heights 6–11 m appeared less suitable, being only partly occupied. Habitat maps showed that habitat of suitable height was only occupied when it occurred as large patches; smaller patches (mostly <0.5 ha) and edges along rides and fields were not used.

Conclusion The use of LiDAR derived measures of vegetation height identified areas of suitable habitat for Willow Warblers. Willow Warblers occupied areas of low mean vegetation height either as early successional or open canopy woodland in all woods. Height‐based habitat maps can identify areas of suitable habitat within larger expanses of heterogeneous woodland and are a potentially useful tool in assessing changes in extent of what are often temporary patches of habitat.     

The effects of larval abundance, settlement and juvenile mortality on the depth distribution of a colonial ascidian

The colonial ascidian Didemnum candidum (Savigny) is more abundant at shallow depths on floating docks than at greater depths along pilings in Pearl Harbor, Oahu, Hawaii. To compare the effects of selective settlement and postsettlement mortality on adult distribution, I determined if settlement was nonrandom relative to depth, if differences in adult abundance were responsible for the depth distribution of settlement, and if juvenile mortality varied with depth. A plankton pump was used to measure variation in larval abundance with depth. Acrylic settling plates were suspended at different depths and sampled nondestructively to measure settlement intensity and juvenile mortality. Settlement and mortality of the didemnid ascidians Diplosoma listerianum Milne-Edwards and Diplosoma sp. were also measured in the field and compared to that of D. candidum. Settlement of D. candidum was indeed nonrandom over depth. Both planktonic larvae and settled juvenils were more numerous at 0.5 than 3 or m. Settlement intensity on vertical plates was greatest within 1–2 cm of the water surface in the laboratory and within 2–3 cm in the field. Directly adjacent to the floating dock, where adults were equally abundant, settlement on horizontal plates was greater at shallow depths, suggesting directed movement of larvae upward. However, the ratio of settled juveniles to planktonic larvae (number of settlers: number of larvae) did not significantly differ with depth, suggesting that larvae were not more likely to settle at a particular depth. Settlement of the Diplosoma species was also heaviest near the surface. Juvenile mortality was greater at 0.5 than at 3 or 6 m for both D. candidum and the Diplosoma species. Experimental settlement showed that mortality, per se, of D. candidum was independent of depth. Rather, mortality was density-dependent, and the higher mortality near the surface was due to the greater number of larvae settling there. At this location, nonrandom settlement appears to determine the adult distribution of D. candidum, despite greater juvenile mortality at shallow depths. The pattern of settlement over depth is largely determined by adult proximity, rather than active larval behavior.     

Quantifying Tropical Dry Forest Type and Succession: Substantial Improvement with LiDAR

Improved technologies are needed to advance our knowledge of the biophysical and human factors influencing tropical dry forests, one of the world's most threatened ecosystems. We evaluated the use of light detection and ranging (LiDAR) data to address two major needs in remote sensing of tropical dry forests, i.e., classification of forest types and delineation of forest successional status. We evaluated LiDAR‐derived measures of three‐dimensional canopy structure and subcanopy topography using classification‐tree techniques to separate different dry forest types and successional stages in the Guánica Biosphere Reserve in Puerto Rico. We compared the LiDAR‐based results with classifications made from commonly used remote sensing data, including Landsat satellite imagery and radar‐based topographic data. The accuracy of the LiDAR‐based forest type classification (including native‐ and exotic‐dominated forest classes) was substantially higher than those from previously available data (kappa = 0.90 and 0.63, respectively). The best result was obtained when combining LiDAR‐derived metrics of canopy structure and topography, and adding Landsat spectral data did not improve the classification. For the second objective, we observed that LiDAR‐derived variables of vegetation structure were better predictors of forest successional status (i.e., mid‐secondary, late‐secondary, and primary forests) than was spectral information from Landsat. Importantly, the key LiDAR predictors identified within each classification‐tree model agreed with previous ecological knowledge of these forests. Our study highlights the value of LiDAR remote sensing for assessing tropical dry forests, reinforcing the potential for this novel technology to advance research and management of tropical forests in general.     

Assessing maximum depth distribution,vegetated area,and production of submerged macrophytes in shallow,turbid coastal lagoons of the southern Baltic Sea

Submerged macrophytes improve water quality in shallow coastal lagoons but eutrophication often resulted in a degradation of macrophytes. Management measures that protect and restore macrophyte stands require knowledge on what limits macrophyte distribution. Information on macrophyte production and distribution in the Darss-Zingst Bodden Chain (southern Baltic Sea) is lacking since an almost complete loss of submerged vegetation in the 1980s. Nutrient input was reduced in the 1990s and macrophytes seem to recover, although turbidity is high and light conditions are still poor. However, this recovery raised hope that returning macrophytes could stabilize sediments and improve water clarity. In this study, seasonal changes in photosynthesis–irradiance curves of selected macrophyte species were used to calculate potential primary production in different depths and turbidity situations. Bathymetry of the area is then used to assess depth distribution and vegetated area. Since the so-calculated depth limits correspond well with the actual depth distribution in the field, macrophyte depth distribution is concluded to be mostly determined by light conditions. Most macrophytes grow in very shallow areas up to 50 cm depth where also 70% of potential primary production takes place. Present light conditions do not support a further expansion of macrophyte distribution in the DZBC.     

What do ecologists miss by not digging deep enough? Insights and methodological guidelines for assessing soil fertility status in ecological studies

Soil fertility is one of the major drivers of ecological processes and is therefore frequently investigated in ecological research. Although often referred to in studies, soil fertility is not well quantified. Consequently some studies have resorted to classifying site soil fertility according to the potential fertility associated with underlying geology, ignoring the soil nutrient status of the rootzone. A common protocol is for ecologists to sample the upper soil layers only (<20 cm). Unfortunately these surface layers are those most likely to be altered by the vegetation itself and may not necessarily reflect the influence of the geological substrate. Using examples, we attempt to provide some practical guidelines on how to determine the intrinsic nutrient status of soils. Soil data from five sites in southern African savannas were used to demonstrate: a) when deeper soil sampling may not be needed, b) how to determine which nutrients may be limiting at a site, c) the importance of bulk density measurements and d) the effect of three different sampling methods. Our data illustrate that the effects of fine scale landscape variability on soil nutrients were evident to variable soil depths. Frequent fires affected soils only to depths of <5 cm, the presence of tree canopies affected soils up to 50 cm, while topographic position affected soil nutrients to a depth of 90 cm. Bulk density did not differ between depths nor between treatments within sites, but differed amongst sites. None of the alternative methods used to collect soil samples (i.e. augering vs. digging soil pits and sampling by depth or horizon) resulted in significant differences in nutrient measures. Standardised sampling from at least three depths together with bulk density measurements allow for calculation of nutrient stocks as a measure of intrinsic soil nutrient status, while also providing insights into nutrient distributions with depth, thereby allowing meaningful cross-site comparisons.     

Using airborne laser scanning to model potential abundance and assemblages of forest passerines

Modelling and forecasting of the distribution and abundance of organisms using environmental variables is a major focus of applied ecological research. High-resolution airborne laser scanning is a recently developed remote-sensing method that provides data that can be used as surrogates for the vertical structure of the vegetation. These data can be used for modelling the occurrence and abundance of species or species assemblages. Until now, few studies evaluated the potential of these data for use in such models, or compared the suitability of data obtained by airborne systems with data gained by alternative methods. To fill part of this gap, we used forest passerine bird species to evaluate airborne laser scanning data for statistical modelling of potential bird abundances and composition of assemblages. Birds were counted in a mixed montane forest, on 223 1-ha plots along four transects. In the same period, these areas were scanned using Light Detection And Ranging (LiDAR) to characterise canopy structure. Additionally, we used visual interpretations of aerial photographs and field measurements on the same plots to derive habitat variables for comparison. We found clear correlations between the LiDAR variables and the other two variable sets using canonical correlation analysis. With a few exceptions, predictive power of the LiDAR data set for modelling abundances of single species, with up to 40% explained variance, was superior to that of the other two data sets. Models agreed with existing ecological knowledge for these species. For modelling of species composition with redundancy analysis, LiDAR was also superior to the other two data sets with more than 20% unique contribution to the explained variance. Our results clearly showed that LiDAR provides valuable data for describing and modelling single species as well as assemblages of forest organisms.     

Canopy closure estimation in a temperate forest using airborne LiDAR and LANDSAT ETM+ data

Aims　Forest canopy closure is one of the essential factors in forest survey, and plays an important role in forest ecosystem management. It is of great significance to study how to apply LiDAR (light detection and ranging) data efficiently in remote sensing estimation of forest canopy closure. LiDAR can be used to obtain data fast and accurately and therefore be used as training and validation data to estimate forest canopy closure in large spatial scale. It can compensate for the insufficiency (e.g. labor-intensive, time-consuming) of conventional ground survey, and provide foundations to forest inventory.Methods　In this study, we estimated canopy closure of a temperate forest in Genhe forest of Da Hinggan Ling area, Nei Mongol, China, using LiDAR and LANDSAT ETM+ data. Firstly, we calculated the canopy closure from ALS (Airborne Laser Scanning) high density point cloud data. Then, the estimated canopy closure from ALS data was used as training and validation data to modeling and inversion from eight vegetation indices computed from LANDSAT ETM+ data. Three approaches, multi-variable stepwise regression (MSR), random forest (RF) and Cubist, were developed and tested to estimate canopy closure from these vegetation indices, respectively.Important findings The validation results showed that the Cubist model yielded the highest accuracy compared to the other two models (determination coefficient (R²) = 0.722, root mean square error (RMSE) = 0.126, relative root mean square error (rRMSE) = 0.209, estimation accuracy (EA) = 79.883%). The combination of LiDAR data and LANDSAT ETM+ showed great potential to accurately estimate the canopy closure of the temperate forest. However, the model prediction capability needs to be further improved in order to be applied in larger spatial scale. More independent variables from other remotely sensed datasets, e.g. topographic data, texture information from high-resolution imagery, should be added into the model. These variables can help to reduce the influence of optical image, vegetation indices, terrain and shadow and so on. Moreover, the accuracy of the LiDAR-derived canopy closure needs to be further validated in future studies.     

Edge-mediated effects on stand dynamic processes in forest interiors: a coupled field and simulation approach

Researchers studying forest edge effects in fragmented landscapes have begun to move beyond merely documenting changes along the edge itself to examining the dynamic influences that edges may have on processes in adjacent areas. One such "edge-mediated effect" is the influence that edges may have on canopy gap replacement processes within the forest interior by acting as seed sources for shade-intolerant plant species. In this paper, we coupled analyses of woody species composition in gap and non-gap areas within the interior of an Ohio hardwood forest with a simple cellular automata model of forest dynamics. Non-gap composition was primarily correlated with disturbance history and site conditions (topographic position and slope) while a comparable analysis using a 24-year time series of composition in gaps showed that gap composition was related most strongly to the proximity of edge communities for the first 10–15 years. However, after 15–20 years of gap succession, composition was correlated with essentially the same variables and to the same degree as non-gap vegetation, suggesting that the influence of edge proximity on interior stand dynamic processes was transient. These results were used to develop a simple mathematical model of stand dynamics that showed that losses of interior forest area may be much greater than typically predicted by core-area models, which do not consider dynamic, edge-mediated effects. Further, our findings suggest the importance of considering disturbance interval in mediating edge-interior relationships, particularly as it may interact with forest size and shape.     

Effects of within-lake gradients on the distribution of fossil chironomids from maar lakes in western Alaska: implications for environmental reconstructions

We examined fossil chironomids (Diptera: Chironomidae) in the surface sediments of four maar lakes in western Alaska to determine chironomid distribution patterns with respect to within-lake gradients of water depth, LOI (loss-on-ignition), and bottom-water temperature. Linear and non-linear regressions were undertaken to test whether the within-lake distributions of fossil chironomids were uniform. Additionally, water depths where abrupt changes or breakpoints in the assemblages occur were identified using piecewise regression. Direct gradient analysis was then used to examine variation in the assemblages explained by the environmental data. For the shallowest lake, chironomid abundances of individual taxa and inferred temperatures varied little within the lake. For the three deep lakes, seven of the sixteen commonest fossil taxa varied significantly with water depth, although some lake-specific patterns were evident. Water depth was generally identified as the principal environmental variable in explaining variation in the assemblages, although sediment organic matter content and bottom-water temperature were also important. Abrupt changes in assemblages occurred at different water depths in each lake, and at only one lake did the breakpoint occur within the range of water depths defining the thermocline. Chironomid-inferred temperature trends from the lakes also showed depth-related patterns: the warmest inferred temperatures were generally from both the shallowest and deepest water depths, whereas intermediate depths yielded temperature inferences about 0.5 to 1.0°C cooler than the average within-lake value. Nevertheless, we conclude that these patterns had only a slight impact on temperature reconstructions relative to the prediction error of the model. A greater understanding of taphonomic processes is needed to determine their influence on environmental reconstructions based on chironomids. Handling editor: J. Saros     

六盘山华山松(Pinus armandii)林降雨再分配及其空间变异特征

利用2004和2005年生长季(6～9月份)六盘山自然保护区的香水河小流域内华山松天然林的穿透降雨、树干径流和冠层截留量观测资料,通过对华山松林降雨再分配特征和穿透降雨空间变异及其影响因素的综合分析,所得结果表明华山松天然林的穿透降雨量、树干径流量和冠层截留量,分别占大气降雨量的84.34%、0.72%和14.94%.穿透降雨在林内具有较大的空间变异,其变异程度随降雨量的增加而减小,冠层对穿透降雨具有一定的聚集效应,降雨量越高时效应越明显; 华山松冠层结构特征是影响穿透降雨的重要因素, 叶面积指数、冠层覆盖度、冠层厚度及距树干的距离等都会影响穿透降雨的空间分布,其中以叶面积指数的影响最大.由分析结果可知,冠层结构特征是决定大气降雨再分配和空间变异的重要生态因素之一.