Effects of visitor pressure on understory vegetation in Warsaw forested parks (Poland)

Visitor’s access to understorey vegetation in park forest stands results in the impoverishment of plant species composition and a reduction in habitat quality. The phenomenon of biotic homogenisation is typical in urban landscapes, but it can proceed differently depending on the scale, a detail that has not been observed in previous studies. This research was carried out in seven Warsaw parks (both public and restricted access). Thirty-four forested areas were randomly selected, some subjected to strong visitors’ pressure and some within restricted access areas, free of such impacts. The latter category included woodlands growing in old forest and secondary habitats. Public access to the study areas contributed to the disappearance of some forest species and their replacement by cosmopolitan non-forest species, leading to loss of floristic biodiversity in areas of high ecological importance at the city scale. Some human-induced factors, including soil compaction and changes in soil pH, moisture and capillary volume, were found to cause habitat changes that favoured native non-forest plants. Despite changes in species composition, the taxonomic similarity of understorey vegetation in both categories—public access and restricted access—was comparable. In a distance gradient of measurements taken around selected individual trees, there was found to be significant variation (in light, soil pH and compaction) affecting the quality and quantity of understorey vegetation (including rare species). In conclusion, the protection of rare forest species could be achieved by limiting access to forested areas, particularly in old forest fragments, and we highly recommend its consideration in the proposal of future park restoration plans.     

2001—2021年黑龙江省森林植被生态质量变化分析

通过统计分析及空间插值等方法,使用气象和遥感数据,分析2001—2021年黑龙江省林区主要植被生长季的气候条件及植被生态质量变化特征。结果表明：2001—2021年黑龙江省林区生长季降水量、平均气温和日照时数分别呈增加、增加和减少趋势。在水分、热量整体逐步增加的背景下,气候条件有利于改善植被生态质量。2021年生长季大部分林区植被生态质量为优和良等级;与多年平均比较,85%以上的林区呈偏好趋势,尤其是中部、东南部部分林区呈很好趋势。植被生态质量指数平均每10 a增大43,99%以上的林区呈提高趋势,特别是北部、东南部及中部部分林区改善明显。     

两种应用场景下NDVI时间序列数据拟合方法研究

植被覆盖指数（NDVI）时间序列数据集包含地表植被的长势、生长周期、时空变化等信息,其拟合重建结果可应用于物候信息提取、生态质量评价、人类活动扰动识别、覆被变化动态监测等方面。基于TIMESAT软件,选取物候参数提取和扰动识别2个应用场景,结合地面站点数据和Jacknife法模拟数据,对比分析非对称高斯函数拟合法（AG法）、双Logistic函数拟合法（D-L法）和Savitzky-Golay滤波法（S-G法）3种方法的拟合效果。结果表明：（1）3种方法拟合重建后提取的生长开始时间（SOS）、生长结束时间（EOS）、生长周期（LOS）等物候参数接近站点数据,AG法和D-L法保持NDVI时序曲线整体变化特征的能力较强,提取的SOS和EOS更接近站点数据;（2）人类活动扰动识别应用场景中,S-G法在滤波时能够最大限度地保留时序曲线细节变化,恢复速率相关系数达到0.618,回归估计标准差低于AG法和D-L法,因此识别精度最优。     

野外无人值守森林实时监控与报警系统研究

随着中国森林的过度砍伐，森林面积急剧减少，对植被的保护刻不容缓。但由于人力物力有限，无法对大量的野生植被进行实时巡视，造成大量野生植被的滥砍滥伐。采用数字摄像头作为采集终端，利用太阳能电池作为可移动电源，结合 GPS 和 GSM的智能控制板，实现植被状况的前端智能判断与实时监控。     

Mapping the spatio-temporal distribution of key vegetation cover properties in lowland river reaches,using digital photography

The presence of vegetation in stream ecosystems is highly dynamic in both space and time. A digital photography technique is developed to map aquatic vegetation cover at species level, which has a very high spatial and a flexible temporal resolution. A digital single-lens reflex (DSLR) camera mounted on a handheld telescopic pole is used. The low-altitude (5 m) orthogonal aerial images have a low spectral resolution (red-green-blue), high spatial resolution (～1.9 pixels cm^?2, ～1.3 cm length) and flexible temporal resolution (monthly). The method is successfully applied in two lowland rivers to quantify four key properties of vegetated rivers: vegetation cover, patch size distribution, biomass and hydraulic resistance. The main advantages are that the method is (i) suitable for continuous and discontinuous vegetation covers, (ii) of very high spatial and flexible temporal resolution, (iii) relatively fast compared to conventional ground survey methods, (iv) non-destructive and (v) relatively cheap and easy to use, and (vi) the software is widely available and similar open source alternatives exist. The study area should be less than 10 m wide, and the prevailing light conditions and water turbidity levels should be sufficient to look into the water. Further improvements of the image processing are expected in the automatic delineation and classification of the vegetation patches.     

European Farmland Bird Distribution Explained by Remotely Sensed Phenological Indices

Birds are important components of biodiversity conservation since they are capable of indicating changes in the general status of wildlife and of the countryside. The Pan-European Common Bird Monitoring Scheme (PECBM) has been launched by the BirdLife Partnership in Europe, where the European Bird Census Council has been collecting data from 20 independent breeding bird survey programs across Europe over the last 25 years. These data show dramatic declines in European farmland birds. We suggest that seasonal characteristics of vegetation cover derived from high temporal resolution remote sensing images could facilitate the monitoring the suitability of farmland bird habitats, and that these indicators may be a better choice for monitoring than climate data. We used redundancy analysis to link the PECBM data of the estimated number of farmland birds in Europe to a set of phenological and climatic indicators and to the biogeographic regions of Europe. Variance partitioning was used to account for the variation explained by the phenological and climate variables and by the area of the environmental strata individually, to define the pure effect of the variables, and to extract the total explained variance. The analysis revealed high statistical significance (p < 0.001) of the correlations between species and environment. Phenological indices explained 38% of the variance in community composition of the 23 farmland bird species, whereas climate explained 30% of the variance. After partitioning the other variables as covariables, the pure effect of phenology, climate, and environmental strata were 16%, 8%, and 16%, respectively. Based on the probability results, we suggest that phenological indicators derived from remote sensing may supply better indicators for continental scale biodiversity studies than climate only. In addition, these indicators are cost and time effective, are on continuous scale, and are readily repeatable on a large spatial coverage while supplying standardized results.     

Can tree species diversity be assessed with Landsat data in a temperate forest?

The diversity of forest trees as an indicator of ecosystem health can be assessed using the spectral characteristics of plant communities through remote sensing data. The objectives of this study were to investigate alpha and beta tree diversity using Landsat data for six dates in the Gönen dam watershed of Turkey. We used richness and the Shannon and Simpson diversity indices to calculate tree alpha diversity. We also represented the relationship between beta diversity and remotely sensed data using species composition similarity and spectral distance similarity of sampling plots via quantile regression. A total of 99 sampling units, each 20 m × 20 m, were selected using geographically stratified random sampling method. Within each plot, the tree species were identified, and all of the trees with a diameter at breast height (dbh) larger than 7 cm were measured. Presence/absence and abundance data (tree species number and tree species basal area) of tree species were used to determine the relationship between richness and the Shannon and Simpson diversity indices, which were computed with ground field data, and spectral variables derived (2 × 2 pixels and 3 × 3 pixels) from Landsat 8 OLI data. The Shannon-Weiner index had the highest correlation. For all six dates, NDVI (normalized difference vegetation index) was the spectral variable most strongly correlated with the Shannon index and the tree diversity variables. The Ratio of green to red (VI) was the spectral variable least correlated with the tree diversity variables and the Shannon basal area. In both beta diversity curves, the slope of the OLS regression was low, while in the upper quantile, it was approximately twice the lower quantiles. The Jaccard index is closed to one with little difference in both two beta diversity approaches. This result is due to increasing the similarity between the sampling plots when they are located close to each other. The intercept differences between two investigated beta diversity were strongly related to the development stage of a number of sampling plots in the tree species basal area method. To obtain beta diversity, the tree basal area method indicates better result than the tree species number method at representing similarity of regions which are located close together. In conclusion, NDVI is helpful for estimating the alpha diversity of trees over large areas when the vegetation is at the maximum growing season. Beta diversity could be obtained with the spectral heterogeneity of Landsat data. Future tree diversity studies using remote sensing data should select data sets when vegetation is at the maximum growing season. Also, forest tree diversity investigations can be identified by using higher-resolution remote sensing data such as ESA Sentinel 2 data which is freely available since June 2015.     

Cover estimation versus density counting in species-rich pasture under different grazing intensities

Two methods for monitoring of grassland vegetation were compared: visual estimation of plant cover (C) and plant densities counting (D). C and D were performed in monthly intervals for three vegetation growing seasons after imposing different grazing regimes on abandoned grassland in 1998. Species scores obtained from paired redundancy analyses (RDA) of C and D data were compared and Spearman's rank correlations were used to show if the two methods give comparable results. Results of C and D were highly correlated in the first two growing seasons only. In the third season, correlation was substantially lower as the sward structure was more heterogeneous due to creation of differently defoliated patches especially under extensive grazing. Presence of the same plant species with different habit in frequently and in infrequently grazed patches, reduced significance of Spearman's rank correlations. Cover estimation can fully substitute plant density counting in grassland with lower proportion of frequently and infrequently grazed patches only, but caution should be used when comparing different management regimes in long term analyses.     

1982—2022年黄土高原归一化植被指数变化的时空特征

长时间地表植被指数变化序列构建与分析是生态环境监测领域的重要内容。以我国生态工程建设重点地区——黄土高原为研究区，采用时间序列的方差匹配方法，融合了2套卫星遥感的归一化植被指数(NDVI)数据产品(GIMMS 3g和MODIS),建立了覆盖1982—2022年的黄土高原暖季(5—9月)NDVI数据集，揭示了其间黄土高原植被覆盖变化的时空特征。研究发现：黄土高原暖季NDVI呈现“先慢后快”的增加趋势，转折点大致出现在2002年，1982—2002年暖季NDVI增速仅为0.01/(10 a),2003—2022年增速高达0.06/(10 a),其中十八大以来增速尤为显著；暖季NDVI快速增加区域主要位于黄土高原中部，并向东北、西南方向延展，与“退耕还林(草)”重点区域范围基本一致；在黄土高原南部、东部和青海省东部一带，暖季NDVI呈缓慢下降趋势。过去40年间黄土高原NDVI增加与生态工程建设关系密切。     

Plants as bioindicators for archaeological prospection: a case of study from Domitian’s Stadium in the Palatine (Rome, Italy)

In this study, we analyzed the relationship between buried archaeological remains (masonries, pavements, and ancient ruins) and spontaneous vegetation growing above them. We carried out several vegetation surveys in the Domitian’s Stadium at the archaeological site of the Palatine (Rome). Vegetation data were collected using the Braun-Blanquet approach and elaborated using statistical analyses (cluster analysis) to assess the similarity among surveys. Structural, chorological, and ecological features of the plant communities were analyzed. Results showed that the vegetation responds significantly to the presence of sub-emerging ancient remains. The plant bioindication of this phenomenon occurs through the following floristic-vegetation variations: phenological alterations in single individuals (reduction in height, displacement of flowering/fruiting period), increase of annual species and decrease of perennial ones, decrease of total plant coverage, reduction of maturity level of the vegetation which remains blocked at a pioneer evolutive stage. The presence of sub-surfacing ruins manifests itself through the dominant occurrence of xerophilous and not-nitrophilous species (e.g., Hypochaeris achyrophorus L., Aira elegantissima Schur, Trifolium scabrum L. ssp. scabrum, Trifolium stellatum L., Plantago lagopus L., Medicago minima (L.) L., and Catapodium rigidum (L.) C.E. Hubb. ex Dony ssp. rigidum) and in a rarefaction of more mesophilous and nitrophilous species (e.g., Plantago lanceolata L., Trifolium pratense L. ssp. pratense, Trifolium repens L. ssp. repens, and Poa trivialis L.). Therefore, the vegetation can be used as bioindicator for the detection of buried ruins, contributing in the archaeological prospection for a general, fast, and inexpensive interpretation of the underground.     

Integrating in-situ, Landsat, and MODIS data for mapping in Southern African savannas: experiences of LCCS-based land-cover mapping in the Kalahari in Namibia

Integrated ecosystem assessment initiatives are important steps towards a global biodiversity observing system. Reliable earth observation data are key information for tracking biodiversity change on various scales. Regarding the establishment of standardized environmental observation systems, a key question is: What can be observed on each scale and how can land cover information be transferred? In this study, a land cover map from a dry semi-arid savanna ecosystem in Namibia was obtained based on the UN LCCS, in-situ data, and MODIS and Landsat satellite imagery. In situ botanical relevé samples were used as baseline data for the definition of a standardized LCCS legend. A standard LCCS code for savanna vegetation types is introduced. An object-oriented segmentation of Landsat imagery was used as intermediate stage for downscaling in-situ training data on a coarse MODIS resolution. MODIS time series metrics of the growing season 2004/2005 were used to classify Kalahari vegetation types using a tree-based ensemble classifier (Random Forest). The prevailing Kalahari vegetation types based on LCCS was open broadleaved deciduous shrubland with an herbaceous layer which differs from the class assignments of the global and regional land-cover maps. The separability analysis based on Bhattacharya distance measurements applied on two LCCS levels indicated a relationship of spectral mapping dependencies of annual MODIS time series features due to the thematic detail of the classification scheme. The analysis of LCCS classifiers showed an increased significance of life-form composition and soil conditions to the mapping accuracy. An overall accuracy of 92.48% was achieved. Woody plant associations proved to be most stable due to small omission and commission errors. The case study comprised a first suitability assessment of the LCCS classifier approach for a southern African savanna ecosystem.     

Growing stock and woody biomass assessment in Asola-Bhatti Wildlife Sanctuary,Delhi, India

Biomass is an important entity to understand the capacity of an ecosystem to sequester and accumulate carbon over time. The present study, done in collaboration with the Delhi Forest Department, focused on the estimation of growing stock and the woody biomass in the so-called lungs of Delhi—the Asola-Bhatti Wildlife Sanctuary in northern Aravalli hills. The satellite-derived vegetation strata were field-inventoried using stratified random sampling procedure. Growing stock was calculated for the individual sample plots using field data and species-specific volume equations. Biomass was estimated from the growing stock and the specific gravity of the wood. Among the four vegetation types, viz. Prosopis juliflora, Anogeissus pendula, forest plantation and the scrub, the P. juliflora was found to be the dominant vegetation in the area, covering 23.43 km² of the total area. The study revealed that P. juliflora forest with moderate density had the highest (10.7 m³/ha) while A. pendula forest with moderate density had the lowest (3.6 m³/ha) mean volume. The mean woody biomass was also found to be maximum in P. juliflora forest with moderate density (10.3 t/ha) and lowest in A. pendula forest with moderate density (3.48 t/ha). The total growing stock was estimated to be 20,772.95 m³ while total biomass worked out to be 19,366.83 t. A strong correlation was noticed between the normalized difference vegetation index (NDVI) and the growing stock (R ²?=?0.84)/biomass (R ²?=?0.88). The study demonstrated that growing stock and the biomass of the woody vegetation in Asola-Bhatti Wildlife Sanctuary could be estimated with high accuracy using optical remote sensing data.     

An automated (novel) algorithm for estimating green vegetation cover fraction from digital image: UIP-MGMEP

Green vegetation cover fraction (VCF) is an important indicator of vegetation status in ecology and agronomy. Digital image analysis (DIA) has been widely accepted as a new VCF measurement technique. In this study, we present a novel fully automatic threshold segmentation algorithm for VCF measurements, which is named as upper inflection point plus mean gradient magnitude of edge pixels (UIP-MGMEP). The algorithm performs VCF estimation upon the vegetation index Excess Green (EXG). UIP-MGMEP optimizes the EXG threshold by searching the upper inflection point (UIP) of the M-Et curve (mean gradient magnitude of edge pixels (MGMEP) vs. EXG threshold), based on the assumption that EXG variance of the boundary pixels between vegetation and background is larger than the variance of the background. Five typical sample images are used to illustrate how ground complexity reduces the distinctness of the UIP. Three controlled experiments are illustrated to test the robustness of UIP-MGMEP to resolution, exposure, and ground complexity. The results show that UIP-MGMEP is a promising algorithm for automatic VCF estimation upon digital images. Compared to broad-leaved grass, narrow-leaved grass is more sensitive to resolution and exposure. To reduce ground complexity, smaller footprint size while more images to cover the same area may be better than one image with large footprint size. UIP-MGMEP is fully automatic, making it promising for batch processing of VCF measurements that is very difficult in any wide-range field survey in the past. UIP-MGMEP algorithm can only extract green vegetation and is not suitable for non-green (even grayish-green) vegetation, due to the limits of vegetation index EXG. In addition, UIP-MGMEP is not recommended for images with VCF less than 0.5% or greater than 99.5%.     

Assessment of heavy metal toxicants in the roadside soil along the N-5, National Highway, Pakistan

The assessment of the toxicants in roadside soil on regular basis has become extremely essential with the increase in awareness for the metal toxicity in the environment. The present study investigates the presence of toxic metals along National Highway (N-5), Pakistan. Averages of about 1.3 million per month of automobile vehicles ply on this route. Lead (Pb), zinc (Zn), copper (Cu), nickel (Ni), cadmium (Cd), cobalt (Co), manganese (Mn), mercury (Hg), and iron (Fe) were analyzed by atomic absorption spectrophotometry in roadside soil at the nine selected locations along the highway. Strong Pearson correlations (α = 0.05) were found between Pb and Zn (r(2)?= 0.887), Fe and Mn (r(2)?= 0.880), Hg and Cd (0.864), Cu and Zn (0.838), and Cu and Pb (0.814). The correlation between the elemental compositions of the main automobile components revealed vehicular traffic as the main non-point source of roadside soil pollution. Extremely high level of mercury, 144.05 mg kg(-1), was found at S5. It was revealed that the unregulated incineration and dumping sites of hazardous waste material along N-5 were also responsible for these contaminations. Multivariate analysis on the obtained data also disclosed the same interpretation. Cluster analysis of the data grouped Pb, Zn, and Cu at 85.23% similarity, whereas, Cd, Hg, and Ni were grouped at 78.75% similarity basis. The findings need swift action against the root cause of soil pollution.     

Monitoring and validating the temporal dynamics of interday streamflow from two upland head micro-watersheds with different vegetative conditions during dry periods of the growing season in the Bohemian Massif,Czech Republic

At present, dynamic land use, climate change, and growing needs for fresh water are increasing the demand on the ecosystem effects of forest vegetation. Mountainous areas are at the forefront of scientific interest in European forest ecology and forest hydrology. Although uplands cover a significant area of the Czech Republic and other countries and are often covered with forest formations, they do not receive an appropriate amount of attention. Therefore, two experimental upland head micro-watersheds in the Bohemian Massif were selected for study because they display similar natural conditions, but different vegetative conditions (forest versus meadow). During the 2011 growing season, short-term streamflow measurements were carried out at the discharge profiles of both catchments and were evaluated in relation to climatic data (rainfall and temperature). The basic premise was that the streamflow in a forested catchment must exhibit different temporal dynamics compared to that in treeless areas and that these differences can be attributed to the effects of woody vegetation. These conclusions were drawn from measurements performed during dry periods lasting several days. A decreasing streamflow trend during the day part of the day (0900–1900 hours) was observed in both localities. The decrease reached approx. 44 % of the initial morning streamflow (0.24 dm³ s^?1 day^?1) in the treeless catchment and approx. 20 % (0.19 dm³ s^?1 day^?1) in the forested catchment. At night (1900–0900 hours), the streamflow in the forested catchment increased back to its initial level, whereas the streamflow in the treeless catchment stagnated or slowly decreased. We attribute these differences to the ecosystem effects of woody vegetation and its capacity to control water loss during the day. This type of vegetation can also function as a water source for the hydrographic network during the night.     

Vegetation Mapping for Change Detection on an Arid-Zone River

A vegetation mapping system for change detection was tested at the Havasu National Wildlife Refuge (HNWR) on the Lower Colorado River. A low-cost, aerial photomosaic of the 4200 ha, study area was constructed utilizing an automated digital camera system, supplemented with oblique photographs to aid in determining species composition and plant heights. Ground-truth plots showed high accuracy in distinguishing native cottonwood (Populus fremontii) and willow (Salix gooddingii) trees from other vegetation on aerial photos. Marsh vegetation (mainly cattails, Typha domengensis) was also easily identified. However, shrubby terrestrial vegetation, consisting of saltcedar (Tamarix ramosissima), arrowweed (Pluchea sericea), and mesquite trees (Prosopis spp.), could not be accurately distinguished from each other and were combined into a single shrub layer on the final vegetation map. The final map took the form of a base, shrub and marsh layer, which was displayed as a Normalized Difference Vegetation Index map from a Landsat Enhanced Thematic Mapper (ETM+) image to show vegetation intensity. Native willow and cottonwood trees were digitized manually on the photomosaic and overlain on the shrub layer in a GIS. By contrast to present, qualitative mapping systems used on the Lower Colorado River, this mapping system provides quantitative information that can be used for accurate change detection. However, better methods to distinguish between saltcedar, mesquite, and arrowweed are needed to map the shrub layer.     

Spatial pattern and heterogeneity of soil organic carbon and nitrogen in sand dunes related to vegetation change and geomorphic position in Horqin Sandy Land, Northern China

To assesses the effect of geomorphology, topography, and vegetation changes on spatial pattern of soil organic carbon (C) and total nitrogen (N) in sand dunes, we used the quantitative methods to examine the spatial heterogeneity of vegetation cover, soil organic C, and total N in an 11-year naturally restored mobile dune (RMD11) and a 20-year naturally restored mobile dune (RMD20) that had been fenced to exclude grazing in Horqin Sandy Land, northern China. Our results showed that the vegetation cover, plant density, species number and diversity, soil organic C, and total N increased from RMD11 to RMD20 and increased from the 50 × 50-m plot (crest) to the 100 × 100-m plot (slope) in each dune. Geostatistical analysis showed that the spatial structural variance accounted for the largest proportion of the total sample variance in vegetation cover, soil organic C, and total N in each dune plot. Calculated spatial autocorrelation ranges of vegetation cover, soil organic C, and total N increased from RMD11 to RMD20, indicating that longer time since vegetation restoration results in a more homogeneous distribution of vegetation cover, soil organic C, and total N in sand dunes. In addition, the spatial continuity of vegetation cover, soil organic C, and total N decreased from the 50 × 50-m plot (crest) to the 100 × 100-m plot (slope) in each dune. These results suggest that the spatial distribution of soil organic C and total N in sand dunes is associated closely with geomorphic position related to the dune crest and slope, relative elevation of sampling site, and vegetation cover. Understanding the principles of this relationship between them may guide strategies for the conservation and management of semiarid dune ecosystems.     

Evaluating the difference between the normalized difference vegetation index and net primary productivity as the indicators of vegetation vigor assessment at landscape scale

Both the net primary productivity (NPP) and the normalized difference vegetation index (NDVI) are commonly used as indicators to characterize vegetation vigor, and NDVI has been used as a surrogate estimator of NPP in some cases. To evaluate the reliability of such surrogation, here we examined the quantitative difference between NPP and NDVI in their outcomes of vegetation vigor assessment at a landscape scale. Using Landsat ETM+ data and a process model, the Boreal Ecosystem Productivity Simulator, NPP distribution was mapped at a resolution of 90 m, and total NDVI during the growing season was calculated in Heihe River Basin, Northwest China in 2002. The results from a comparison between the NPP and NDVI classification maps show that there existed a substantial difference in terms of both area and spatial distribution between the assessment outcomes of these two indicators, despite that they are strongly correlated. The degree of difference can be influenced by assessment schemes, as well as the type of vegetation and ecozone. Overall, NDVI is not a good surrogate of NPP as the indicators of vegetation vigor assessment in the study area. Nonetheless, NDVI could serve as a fairish surrogate indicator under the condition that the target region has low vegetation cover and the assessment has relatively coarse classification schemes (i.e., the class number is small). It is suggested that the use of NPP and NDVI should be carefully selected in landscape assessment. Their differences need to be further evaluated across geographic areas and biomes.     

Using photographic image analysis to assess ground cover: a case study of forest road cutbanks

Road prisms, including cutbanks, road surfaces, and fillslopes, can be important contributors of sediment to streams in forested watersheds. Following road construction, cutbanks and fillslopes are often seeded, mulched, and sometimes fertilized to limit erosion and sedimentation. Assessing the success of vegetation establishment on cutbanks and fillslopes is a common task of forested land managers. This study developed and applied a photographic image analysis method to assess percent ground cover along an entire cutbank of a cut-and-fill haul road in the Monongahela National Forest in Tucker County, West Virginia. Variable-sized sections were employed to quantify the vegetative cover. Measurements obtained by this technique were similar to more commonly applied fixed-area plots, and it proved to be a useful tool for land managers who require a more repeatable quantification of ground cover than is possible through visual assessments. Cutbank slope and aspect also were analyzed to determine their potential impact on cutbank vegetation establishment. Slope was not a significant variable in explaining differences in vegetation cover; however, aspect did affect vegetation establishment. South-facing aspects had significantly lower percent vegetation cover than northeast, east, northwest, and north northwest aspects after the first year following seeding and throughout the entire study. Mean percent cover on the south-facing cutbanks was 32% over all time periods, compared to 60% to 73% for the other represented aspects. This result was expected since south-facing slopes generally are drier in the growing season and are subject to more freeze–thaw cycles in the winter. Timber felled onto the cutbank also decreased vegetative cover in the short term on north and north northwest aspects, but vegetation quickly became reestablished on these aspects with their favorable growing conditions.     

太湖湖滨带浮游植物群落特征及指示种筛选

针对太湖湖滨带,均匀布设49个点位,分别于2009年12月、2010年4、8月开展浮游植物及水质监测。结果显示,湖滨带浮游植物群落多样性整体较低,优势种从枯水期到丰水期呈"鱼腥藻-鱼腥藻-微囊藻"的演变趋势;西北部湖区(竺山湖、梅梁湾、西部沿岸)浮游植物密度明显高于东南部湖区(东部沿岸、东太湖、南部沿岸);湖滨带浮游植物群落结构与湖体相似,密度比湖体高1个数量级;RDA排序筛选出在显著水平上解释浮游植物分布的最小变量组合为TN、CODMn、SS、p H、SD,且方差分解指出TN是相对最重要的变量;当物种适合度为50%~100%时,与TN具有较好梯度响应关系的是四尾栅藻及弓型藻,并且这2个种与TN、TP及综合营养状态指数的组合变量也有较好的梯度响应关系,具备指示太湖湖滨带富营养化的可能,但定量指示意义尚待进一步研究。