An evaluation of the analysis system of video transects used to sample subtidal epibiota

Two popular methods of benthic cover estimation (the point intercept technique with two sets of position points, and digital interactive color segmentation) were compared with an alternative method of digital cover estimation using Bezier curves as a tool for outlining the objects on an images and AutoCAD® software for the final evaluation of abundance. The comparison was done using still video images obtained from two 10-m transects on subtidal rocks off the Rimsky-Korsakov islands in the Sea of Japan (Russia). Ten rectangular sectors (1×0.4 m each) selected randomly within both video transects were analyzed. One-way ANOVA for repeated measurements was used to test the differences between methods. The point intercept technique differed significantly from both methods of digital estimation and had an essential positive bias. The Tukey multiple comparison test revealed the differences among digital estimation methods in the species, which have the complicated color with many contrast spots. The proposed approach using Bezier curves has an advantage over the interactive color segmentation if the objects under selection are lit at different levels or have a contrast coloration or are hidden by canopy organisms. Besides, estimation of cover in the field of AutoCAD® software is more precise and takes less time than that obtained using a scaled grid, available for automatically segmented species. The results showed that digital cover estimation using Bezier curves and AutoCAD® software is a convenient method for analyzing benthic samples at large spatial scales.     

景观生态学中的尺度分析方法

多尺度空间分析法是发现和识别景观特征尺度的主要方法.当前这类方法很多,缺乏归类和对比分析评价.基于空间类型变量和数值变量,对多尺度空间分析方法进行了重新梳理.同时对当前常用的尺度分析方法:半方差分析、尺度方差分析、小波分析和孔隙度指数分析,以中国三北防护林为例,对比了各种尺度分析方法的特点和优劣.结果表明,在特征尺度的识别上:小波方差方法清晰明了;半方差分析法灵活简捷,结果明显;尺度方差分析法和孔隙度指数法在本研究中的判识结果不甚明显.在计算速度上:半方差分析法计算量最大、耗时最长,尺度方差次之,小波方差速度最快,孔隙度指数法计算速度快于前两种,慢于小波方差分析方法.半方差分析方法简单灵活,而且相关理论方法成熟,但缺乏对大尺度格局的整体把握,而小波分析恰恰能很好的弥补这一不足.最后提出,半方差分析和小波变换相结合将会是最优的尺度分析方法.     

流域尺度土地利用与土壤类型空间分布的相关性研究

随着人类活动日益加强,土地利用变化及其驱动力研究已经成为国际地理学界研究的热点。但目前更多的工作侧重于研究人为因子,如人口增长、政策变化等因子对土地利用变化的影响,其实土地利用在宏观尺度上的变化一定程度上取决于自然环境背景,因此研究土地利用变化的自然环境背景特征对于进一步探讨土地利用变化的自然驱动力具有重要意义。土壤类型的空间分布在一定程度将影响土地利用的空间分布格局和变化过程。本文利用遥感、地理信息系统,通过选取景观格局指标,以于桥水库流域为例,研究了土地利用与土壤类型空间分布之间的相互关系。结果表明：(1)受人类活动干扰较弱的土地利用类型,如有林地、稀疏林地、灌木林地、其他林地和草地,主要分布在淋溶褐土、褐土性土以及棕壤地区;而与人类活动密切的土地利用类型,如山区旱耕地、丘陵区水田、丘陵区旱耕地和平原区旱耕地主要分布在淋溶褐土、褐土性土和潮土地区;(2)同类地区土地利用的多样性指数要比土壤的低。并且土地利用和土壤类型多样性均表现出明显的地形梯度效应,从中低山区、低山丘陵区、丘陵平原区到山间盆地区,土壤多样性指数从小到大有规律地变化。而土地利用类型多样性变化较为复杂,反映出人类活动对土地利用格局的影响较强,而对土壤类型的影响相对较小;(3)随着平均斑块面积的增加,流域多样性指数将呈下降趋势。土地利用多样性指数与流域总面积之间的相关性较差,但土壤多样性指数与流域总面积表现出的相关性较好;(4)土地利用类型与土壤类型之间,平均斑块面积上没有明显的相关关系,但在多样性指数之间存在着较好的相关性。土壤类型丰富多样的地区,土地利用的多样性指数也相对较高。     

土壤侵蚀定量评价的空间尺度效应

土壤侵蚀的空间尺度效应使得小尺度上观测到的大量数据无法得到有效的利用,给多空间尺度土壤侵蚀定量评价带来了困难和问题。对土壤侵蚀定量评价研究中的空间尺度效应及其机理和空间尺度转换方法进行了综述。分离、搬运和堆积子系统之间的协同效应与大尺度土壤侵蚀背景条件之间的协同效应是土壤侵蚀空间尺度效应产生的根本原因。在土壤侵蚀定量评价中,基本侵蚀单元地表参数的定量描述是建立土壤侵蚀空间尺度转换模型的基础。     

Spatial scale dependence of the species diversityin Tianmu Mountain and its relationship with spatial patterns by using multifractal analysis

This study took the Tianmu Mountain National Natural Preservation Area in western Zhejiang Province as an example 1) to quantify the species diversity with selected species indices including Shannon-Wiener index (H), Margalef index (K) and Evenness index (E) at different spatial scales, 2) to analyze the spatial distribution patterns of the species diversity by multifractal parameters such as the singularity index α, its fractal dimension f(α), the f(α)–α spectrum range (SR) and its symmetry (Dist) using the multifractal theory, and 3) to determine their relationships. Results of nonlinear regression analysis with power functions showed that increasing spatial scale resulted in increasing H but decreasing E and K, indicating that the scale dependence of species diversity existed. By using the multifractal method, it was indicated that species spatial distribution had multifractal features. Moreover, strong linear relationships of the diversity indices H, E and K with α_min and clear nonlinear associations of the diversity indices H, E and K with power functions for SR and Dist were found. Since interactions of the species diversity and the spatial characteristics are very complex, the above mentioned relationships need further validation along with precise explanations of any correlations among their ecological processes.     

Spatial scale dependence of the species diversityin Tianmu Mountain and its relationship with spatial patterns by using multifractal analysis

This study took the Tianmu Mountain National Natural Preservation Area in western Zhejiang Province as an example 1) to quantify the species diversity with selected species indices including Shannon-Wiener index (H), Margalef index (K) and Evenness index (E) at different spatial scales, 2) to analyze the spatial distribution patterns of the species diversity by multifractal parameters such as the singularity index α, its fractal dimension f(α), the f(α)–α spectrum range (SR) and its symmetry (Dist) using the multifractal theory, and 3) to determine their relationships. Results of nonlinear regression analysis with power functions showed that increasing spatial scale resulted in increasing H but decreasing E and K, indicating that the scale dependence of species diversity existed. By using the multifractal method, it was indicated that species spatial distribution had multifractal features. Moreover, strong linear relationships of the diversity indices H, E and K with α_min and clear nonlinear associations of the diversity indices H, E and K with power functions for SR and Dist were found. Since interactions of the species diversity and the spatial characteristics are very complex, the above mentioned relationships need further validation along with precise explanations of any correlations among their ecological processes.     

Automated measurement of root length with a three-dimensional high-resolution scanner and image analysis

For measuring the length of root samples, the use of a three-dimensional (3D) scanner is proposed to address the problem of a too low resolution. The scanner's high resolution (up to 354 pixels per cm) enables in the resulting grey-value image very thin roots (diameter 100 m) to be segmented from the background by a simple thresholding operation. After skeletonizing, total length of the roots is calculated by multiplying the number of skeleton pixels by a correction factor. A comparison with the modified Newman Line-Intersect Method showed a correlation of r=0.98. Besides its superior resolution, an advantage of this type of scanner is its focusing depth, which allows root samples to be recorded on the scanbed similarly to a camera-oriented system.     

空间幅度变化对景观格局分析的影响

景观格局指数是量化描述景观格局特征的主要方法之一,各种格局指数的尺度依赖性使比较分析景观格局特征和尺度推绎复杂化,分析不同指数随空间幅度变化的一般行为有助于景观格局分析结果的解释和降低空间尺度推绎的复杂性。研究以2种真实景观和27种模拟景观为分析对象,考查了16种常用的景观水平格局指数随空间幅度变化行为。根据这些指数因幅度变化行为可预测性把它们分为两类：第1类随幅度变化可预测性强,指数与幅度之间的关系可用简单的函数关系来表达;这类指数包括缀块数、边界总长、景观形状指数和缀块丰度密度;前两者随幅度增加呈幂函数形式增加,而缀块丰度密度随幅度增加呈幂函数下降,景观形状指数随幅度增加呈直线增加。第2类指数随幅度变化的可预测性较差,指数随幅度的变化存在多种可能(不同形式的增加、减小或保持不变),不可用一种或多种简单的函数关系来描述所有的情况。这类指数包括缀块丰度、缀块密度、边界密度、最大缀块指数、平均缀块面积、缀块面积标准差、缀块面积变异系数、平均缀块形状指数、面积加权平均缀块形状指数、双对数回归分维数、聚集度指数与Shannon多样性指数。第2类指数随幅度的变化行为受景观格局特征和指数本身算法的影响。总体上来说,第2类格局指数随幅度变化呈折线增加或减小;但当景观的缀块类型较多、各类型优势度比较均等、空间分布格局比较随机时,它们随幅度变化形为的可预测性增加,随幅度增加的函数关系主要有3种：幂函数减小、对数函数增加或直线增加,因指数和格局特征不同而异。研究的结果在揭示了常用景观指数随幅度变化的一般关系外,也启示我们在进行景观格局的比较分析,比较景观的幅度应相同或采用尺度效应图(scalograms)更有效。     

温带落叶阔叶林地表鞘翅目成虫小尺度空间格局动态分析

土壤动物空间格局是格局—过程以及生物多样性维持机制研究的重要基础,目前小尺度空间土壤动物空间格局动态特征仍不清楚。基于地统计空间分析方法,以鞘翅目成虫为研究对象,研究帽儿山温带落叶阔叶林小尺度空间(5m)地表鞘翅目成虫群落及类群的空间格局动态特征。结果表明:4次调查共捕获鞘翅目成虫11科、29类、1021只个体,调查月份鞘翅目成虫群落具有较强的时空变异性;Moran'sⅠ系数表明鞘翅目成虫群落和类群具有复杂的正的空间自相关性,其空间异质性可用球状、指数、高斯和线性模型进行拟合。这种空间异质性具有一定的时间变化特征,且这种空间分异是由随机性因素单一调控或结构性因素和随机性因素共同调控的结果;类群之间在多种尺度上表现为复杂的以负相关居多的空间关联性,这种空间关联性的形成主要是结构性因素或随机性因素单一调控的结果。本实验表明地表鞘翅目成虫群落在小尺度空间具有明显的空间异质性特征,这种空间异质性时间变异性较明显。     

遥感反演植被理化参数的光谱和空间尺度效应

植被理化参数是生态系统中碳和养分等物质循环与能量交换的重要指标,利用遥感技术反演是获取区域及全球植被理化参数的重要手段,但光谱和空间尺度效应的存在,限制了源自不同遥感传感器植被理化参数产品的统一应用。阐述了遥感反演植被理化参数光谱尺度效应的概念及其产生原因,主要从光谱波段位置和波段宽度两方面对国内外相关研究进行了介绍和评述。同时,从遥感反演植被理化参数的空间尺度效应产生原因、空间异质性描述方法和空间尺度转换方法等方面对其国内外研究现状进行了归纳和评述。最后,总结了遥感反演植被理化参数光谱和空间尺度效应研究的不足之处和发展趋势,并指出光谱和空间耦合效应的研究将是一大趋势,而在生态学等领域形成的尺度效应研究的理论和方法也值得借鉴参考。     

生态学中的尺度问题：内涵与分析方法

尺度问题已成为现代生态学的核心问题之一.尺度问题主要涉及3个方面：尺度概念、尺度分析和尺度推绎.主要评述前两个方面.生态学尺度有三重概念：维数、种类和组分,其中每重概念又包含了多个定义,有必要进行澄清、分类和统一.尺度分析涉及尺度效应分析和多尺度空间格局分析.格局、过程及它们之间的关系,以及某些景观特性均表现出尺度效应,因此多尺度研究非常必要和重要.多尺度空间格局分析（尤其是特征尺度的识别）是进行尺度效应分析和跨尺度推绎的基础.多尺度分析需要特定的方法,景观指数法是最常用和最简单的方法,但也常产生误导;空间统计学方法（如半方差分析法、尺度方差分析法、空隙度指数法和小波分析法等）和分维分析法在最近十几年发展起来,并逐渐应用于生态学,在尺度分析上具有很大的应用潜力.各种方法在尺度分析上各有优势和不足,有必要同时使用两种或两种以上方法进行比较和评估.总之,有关尺度分析的研究需要进一步加强,从而为下一步的尺度推绎提供可靠的依据.     

The influence of spatial scale on cross-taxon congruence patterns and prediction accuracy of species richness

A comparison of species richness patterns of butterflies and birds was made using data from two grids of squares (small squares 137.5 km on a side and large squares 275 km on a side) covering western North America. Using geostatistical procedures, we found that the spatial patterns of species richness of these two taxa were related. The influence of grain size on the strength of this relationship was investigated by analysing the two data sets. For both data sets, the number of butterfly species in a square was a statistically significant predictor of the corresponding number of bird species. However, cross-validation techniques showed that the marginal improvement in prediction accuracy due to including butterflies as a predictor was greater in the large-square data. We explored the effect of areal extent on cross-taxon congruencies by investigating species richness patterns in four subsets of the small-square data. In regions with smaller areal extent, the cross-taxon congruence patterns were not substantially different from the pattern found in the full data set. Finally, using data-splitting techniques, we explored the relationships between prediction accuracy of species richness, sample size, areal extent of the sample, and grain size.     

Use of time‐lapse photography and digital image analysis to estimate breeding success of a cliff‐nesting seabird

Development of new methods for obtaining basic demographic data from difficult‐to‐access breeding colonies and easily disturbed species is an important challenge in studies of seabirds. We describe a method that can generate data concerning annual breeding success of cliff‐nesting seabirds or other colonial birds with open nests. Our method requires only a single visit to a colony every second or third year, and is based on the use of automated time‐lapse photography. To test our method, we used time‐lapse photos to examine the breeding success of Thick‐billed Murres (Uria lomvia) in two breeding colonies in Greenland during the years 2011, 2012, and 2014. Based on the analysis of time‐lapse photos, we found that hatching success during the 3 yr of our study ranged from 60% to 81%, fledging success from 89% to 95%, and breeding success from 53% to 74% (Table 1). Use of digital image analysis made it possible to differentiate between breeding and non‐breeding birds and determine if and when breeding attempts failed or succeeded. The key to making our method a realistic long‐term monitoring technique is the use of an automated, formal image analysis to process the thousands of photos from the time‐lapse cameras and, more specifically, to reduce a large number of photos to a manageable number. Using our method, we needed 12–22 h per study plot, depending on the number of breeding sites per plot (range = 47–127) and whether it was the first or the second time the plot was analyzed, to obtain our estimates of hatching, fledging, and breeding success. This included time for data preparation, image analyses, visual inspections, and summarizing data in a spreadsheet. We found that our estimates of breeding success were comparable to those obtained by direct observation in the field. An important aspect of using time‐lapse technology is to foresee potential reasons why time‐lapse cameras might stop taking pictures, for example, equipment failure (camera, timer, or battery) or interference by visitors (e.g., vandalism or theft). As such, thorough testing of time‐lapse systems and selecting camera locations less likely to be disturbed are most important. We believe that use of time‐lapse photography in combination with digital image analysis to estimate breeding success can be useful for determining the breeding success of other cliff‐nesting seabirds and, more generally, other birds that breed in colonies, especially those located in remote areas and where direct observation may disturb birds.     

Using spatial analysis to monitor tree diversity at a large scale: a case study in Northeast China Transect

Aims Monitoring and assessing diversity change at a large scale is important for any meaningful biodiversity conservation and management. Spatial analysis techniques can provide information about different aspects of diversity distribution including change. We applied some common spatial analysis methods and additive partitioning of species diversity in the Northeast China Transect as a case study to show how to characterize the distribution and change of tree diversity in this area from different perspectives.Methods The field data were collected from the permanent plots conducted every 4 km. The additive partitioning of species diversity was used to characterize the diversity of tree species at different scales. Moran's I was used for identifying the spatial scale of autocorrelation, lacunarity was studied for diversity patch contagion and dispersion and spectral entropy was used for assessing the overall spatial distribution.Important findings Data collected from 1986 to 1994 indicate that the change of α diversity was not significant in the study area, but the change of β diversity was significant. The percentage of α diversity in total diversity (γ) increased from 14.2 to 17.2%, and the percentage of β diversity decreased from 85.8 to 82.8%. For both α and β diversities, the scale of spatial autocorrelation decreased at the scale of 25–40 km and increased around 15–20 and 200 km. The lacunarity of α diversity decreased significantly and there was a sudden change at the scale of 56–68 km, but the lacunarity of β diversity increased across scales. The spectral entropy decreased slightly in α diversity and remained similar for β diversity. By using spatial analysis, we can monitor the diversity change over a large area and also assess the effectiveness of the current conservation strategies.     

Plants on small islands revisited: the effects of spatial scale and habitat quality on the species–area relationship

Understanding how species diversity is related to sampling area and spatial scale is central to ecology and biogeography. Small islands and small sampling units support fewer species than larger ones. However, the factors influencing species richness may not be consistent across scales. Richness at local scales is primarily affected by small‐scale environmental factors, stochasticity and the richness at the island scale. Richness at whole‐island scale, however, is usually strongly related to island area, isolation and habitat diversity. Despite these contrasting drivers at local and island scales, island species–area relationships (SARs) are often constructed based on richness sampled at the local scale. Whether local scale samples adequately predict richness at the island scale and how local scale samples influence the island SAR remains poorly understood. We investigated the effects of different sampling scales on the SAR of trees on 60 small islands in the Raja Ampat archipelago (Indonesia) using standardised transects and a hierarchically nested sampling design. We compared species richness at different grain sizes ranging from single (sub)transects to whole islands and tested whether the shape of the SAR changed with sampling scale. We then determined the importance of island area, isolation, shape and habitat quality at each scale on species richness. We found strong support for scale dependency of the SAR. The SAR changed from exponential shape at local sampling scales to sigmoidal shape at the island scale indicating variation of species richness independent of area for small islands and hence the presence of a small‐island effect. Island area was the most important variable explaining species richness at all scales, but habitat quality was also important at local scales. We conclude that the SAR and drivers of species richness are influenced by sampling scale, and that the sampling design for assessing the island SARs therefore requires careful consideration.     

不同空间尺度景观特征对南流江水质的影响差异

流域景观特征决定了非点源污染物来源与地表景观削减消纳能力,但尚缺乏全流域不同空间尺度对二者关联性的认识。以广西北部湾南流江为例,分别在子流域、河岸缓冲带以及监测点圆形缓冲区三种尺度上,基于2020年Landsat 8 OLI遥感影像解译的土地利用类型特征,结合水质监测数据,运用数理统计和GIS空间分析方法,探讨了流域景观特征在不同空间尺度上对河流水质的影响。结果表明：(1)在子流域尺度,土地利用类型以林地为主,而在河岸缓冲带与监测点圆形缓冲区均以耕地为主;(2)水质指标高锰酸盐指数、生化需氧量与景观特征相关性最为显著,耕地、建设用地、其他用地和园地与其呈正相关,是南流江水质污染负荷的重要来源区;景观格局指数中,斑块密度、蔓延度指数、多样性指数、均匀度指数是引起河流水质指标变化的主要景观因子;(3)受流域内或不同子流域间景观特征差异,景观组成面积占比和景观格局指数均在河岸缓冲带尺度对水质状况影响最大,分别可解释57.0%和64.7%的水质指标变化;子流域尺度次之,圆形缓冲区尺度最小,且景观格局指数对水质状况的影响大于景观组成面积占比。建议在河岸带50 m范围内严格控制耕地面积,建设河岸缓...