Evaluating the effectiveness of landscape metrics in quantifying spatial patterns

The effectiveness of landscape metrics in quantifying spatial patterns is fundamental to metrics assessment. Setting 36 simulated landscapes as sample space and focusing on 23 widely used landscape metrics, their effectiveness in quantifying the complexity of such spatial pattern components as number of patch types, area ratio of patch types and patch aggregation level, were analyzed with the application of the multivariate linear regression analysis method. The results showed that all the metrics were effective in quantifying a certain component of spatial patterns, and proved that what the metrics quantified were not a single component but the complexity of several components of spatial patterns. The study also showed a distinct inconsistency between the performances of landscape metrics in simulated landscapes and the real urban landscape of Shenzhen, China. It was suggested that the inconsistency resulted from the difference of the correlation among spatial pattern components between simulated and real landscapes. After considering the very difference, the changes of all 23 landscape metrics against changing of number of patch types in simulated landscapes were consistent with those in the real landscape. The phenomenon was deduced as the sign effect of spatial pattern components on landscape metrics, which was of great significance to the proper use of landscape metrics.     

Coccinellid response to landscape composition and configuration

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On using landscape metrics for landscape similarity search

Landscape similarity search involves finding landscapes from among a large collection that are similar to a query landscape. An example of such collection is a large land cover map subdivided into a grid of smaller local landscapes, a query is a local landscape of interest, and the task is to find other local landscapes within a map which are perceptually similar to the query. Landscape search and the related task of pattern-based regionalization, requires a measure of similarity – a function which quantifies the level of likeness between two landscapes. The standard approach is to use the Euclidean distance between vectors of landscape metrics derived from the two landscapes, but no in-depth analysis of this approach has been conducted. In this paper we investigate the performance of different implementations of the standard similarity measure. Five different implementations are tested against each other and against a control similarity measure based on histograms of class co-occurrence features and the Jensen–Shannon divergence. Testing consists of a series of numerical experiments combined with visual assessments on a set of 400 3 km-scale landscapes. Based on the cases where visual assessment provides definitive answer, we have determined that the standard similarity measure is sensitive to the way landscape metrics are normalized and, additionally, to whether weights aimed at controlling the relative contribution of landscape composition vs. configuration are used. The standard measure achieves the best performance when metrics are normalized using their extreme values extracted from all possible landscapes, not just the landscapes in the given collection, and when weights are assigned so the combined influence of composition metrics on the similarity value equals the combined influence of configuration metrics. We have also determined that the control similarity measure outperforms all implementations of the standard measure.     

Seeking parsimony in landscape metrics

Numerous metrics describing landscape patterns have been used to explain landscape-scale habitat selection by birds. The myriad metrics, their complexity, and inconsistent responses to them by birds have led to a lack of clear recommendations for managing land for desired species. The amount of a target land cover type in the landscape (percentage cover) often has been a useful indicator of the likelihood of species occurrence or of habitat selection; is it also a more adequate and parsimonious measure for explaining species distributions than patch size or more complex measures of landscape configuration? We examined responses of 6 woodland-interior bird species to the percentage tree cover within prescribed areas and to patch size, edge density, and other metrics. We examined responses in 2 landscapes: a mixed woodland-savanna and an eastern deciduous forest. For these 6 species, percentage tree cover explained bird occurrence as well as or better than other measures in both study areas. We then repeated the analysis on a larger group of woodland species, including those associated with woodland edges. The bird species we studied had varied responses to landscape metrics, but percentage tree cover was the strongest explanatory variable overall. Although percentage cover estimated from remotely sensed data is an inexact representation of habitat in the landscape, it does appear to be reliable and easy to conceptualize, relative to other measures. We suggest that, at least for woodland habitat, percentage cover is a broadly useful measure that can be helpful in pragmatic questions of explaining responses to landscapes or in anticipating responses to landscape change. © 2011 The Wildlife Society.     

Evaluating the effects of landscape configuration on site occupancy and movement dynamics of odonates in Iowa

Odonates contribute highly to global biodiversity and are considered good indicators of environmental quality, but they are under-studied and quantitative information on their habitat associations is lacking. Our objective was to examine the effects of landscape configuration on site occupancy and movement dynamics of four odonate species in Iowa: Tramea onusta, Epitheca princeps, Pantala flavescens, and Calopteryx maculata. We conducted standardized visual encounter surveys for odonates at 233 public properties in Iowa from 2007 to 2011 and computed landscape variables within a 200, 600 m, and 1 km radius of each surveyed site. Using a robust design occupancy model in Program MARK, we estimated detection probability and site occupancy, site extinction, and site colonization probabilities for each species. We found few significant effects of landscape variables on site occupancy, extinction, or colonization, although landscape variables at 600 m were included in the best model for all species. Detection probability (SE) ranged from 0.30 (0.04) for Pantala flavescens to 0.49 (0.04) for Calopteryx maculata. Our study provides information to aid habitat restoration and management efforts on sites having suitable characteristics in the surrounding landscape and ultimately help conserve odonates.     

The effect of landscape composition and configuration on the spatial distribution of temperate demersal fish

In contrast to the terrestrial environment, where the use of landscape analyses has been clearly demonstrated, the influence of landscape composition and configuration on the abundance and spatial distribution of marine organisms remains poorly understood. Development of this area of marine research has been limited by the lack of accurate benthic habitat maps, particularly for marine environments deeper than can be penetrated by optical remote sensing (<10 m). However, the recent availability of detailed (1:25 000) and accurate habitat maps derived from hydroacoustic surveys of deeper marine waters has redressed this situation. The aim of this research was to establish the strength and significance of derived landscape composition and configuration indices on the demersal fish assemblage structure and spatial distribution. A combination of depth and 6 landscape measures were found to explain 34.8% of the variation in the fish assemblage. Depth contributed the highest percentage of the variance explained, accounting for 23.7%. Distance to reef was the most important landscape index explaining 7.1% of the variability, followed by total length of edge environment (the interface between different benthic substrates) explaining 1.5%. Species responsible for driving the structure of the fish assemblage were also examined and found to respond not only to the proximity of reef but also to the configuration of the reef. For example, Parika scaber and Pseudolabrus psittaculus characterised more heterogeneous landscapes offering clusters of small interconnected patches of reef with a lot of edge environment, whilst juvenile Trachyurus novaezelandiae and Platycephalus caeruleopunctatus preferred more homogeneous landscapes offering little reef or edge environment. This research demonstrated that a broad scale landscape analysis, employing indices of landscape composition and configuration, is important for understanding demersal fish assemblage structure and spatial distribution.     

景观格局指数相关性的幅度效应

以TM遥感图像为数据源,选择江苏盐城大丰地区一块1764km2的研究区,运用地理信息系统技术处理得到该研究区的景观类型图,选取景观水平上4种类型的32个景观指数进行计算,分析了不同幅度对景观指数间相关关系的影响。结果表明:随着研究幅度由0.5km到14km的逐渐增加,同类型景观指数间相关性幅度效应最为显著的为面积、周长、密度指数,其次是蔓延度、指数和形状指数,最后是多样性指数;不同类型景观指数间相关关系的幅度效应中,面积、周长、密度指数与其他类型指数间的相关关系较好,形状指数与多样性指数间的相关性则较差;且大部分景观指数间相关关系发生质变的空间幅度为3km×3km后,且随着研究幅度的增加,大部分发生质变的指数逐渐表现出不相关。该研究为不同幅度下景观指数的选取提供了参考。     

景观指数之间的相关分析

应用辽宁省1997~1998年的TM 5影像数据,编制了景观类型图,以78个县市区为单位,分割成78个景观,共计算39个景观格局指数,对它们进行了相关分析。总面积是最基本的景观指数,它决定景观总边界长度、斑块数、类型密度等基本指数,同时与多个指数有显著的相关关系(相关系数绝对值大于0.75)。形状指数的独立性强,极少数指数与其它指数有显著的相关关系;多样性指数和蔓延度指数之间信息重复量最多,都表示景观的异质性,但多样性指数以面积百分比表示景观异质性,而蔓延度指数以类型之间相邻边界的百分比表示景观异质性。研究发现,如果两个指数之间存在显著的相关关系,而由它们两个构成的指数与它们之间没有显著的相关关系。如果指数平均值之间存在显著的相关关系,则它们的变异系数之间不存在显著的相关关系。景观指数间的相关系数不仅与景观格局本身有关,还与空间尺度,分类系统、计算公式及其参数、计算单元和生态学意义关系密切。指数之间影响因子的相同之处越多,它们之间存在显著相关关系的概率越大。     

城市热岛效应与景观格局的关联:从城市规模、景观组分到空间构型

景观格局的改变被视为城市热岛形成的直接原因,但景观格局指标与热岛效应的关联机理仍未厘清。城市规模、景观组分、空间构型作为景观格局的重要表征指标,对热岛效应的影响体现了从整体到局部、从数量到空间的递进关系。其中,城市规模与热岛效应的关联存在地带性规律;景观组分与热岛效应的相关性受昼夜、季节控制;显著驱动热岛效应的关键空间构型指标仍有待遴选。景观格局与热岛效应的非线性关联可能存在拐点,拐点前后对应不一致的因子驱动强度。科学界定城市规模、景观组分、空间构型等景观格局要素显著影响热岛效应的阈值区间,有助于明晰缓解城市热岛效应的关键景观生态途径。     

景观指数耦合景观格局与土壤侵蚀的有效性

景观格局分析是景观生态学中揭示景观变化及其生态效应的主要方法,而景观指数是景观格局分析中广泛使用的工具。土壤侵蚀是土壤物质在景观中的迁移和再分配过程,受地形、植被和人类活动及其空间格局的调控。运用景观格局分析揭示景观格局变化特别是土地利用/覆被格局变化对土壤侵蚀的影响是土壤侵蚀研究中应用景观生态学原理和方法的典型。在当前的研究中,斑块-廊道-基质范式下建立的景观指数对侵蚀过程的解释能力不断受到质疑,建立筛选适用的景观指数的原则和方法十分必要。以延河流域碾庄沟小流域为例,利用WATEM/SEDEM模型模拟多个年份流域侵蚀产沙和输沙量;基于土地利用/覆被数据,利用Fragstat4.2软件,计算了相应年份流域斑块、边界密度、形状、集聚与分散和斑块类型多样性4个方面的代表性景观指数。在此基础上,分析了景观指数与流域侵蚀产沙和输沙之间的关系,讨论了景观指数在土壤侵蚀研究中的有效性,在景观和斑块类型水平上分析了景观指数表达"源"、"汇"两大类景观类型的空间格局与侵蚀产沙和输沙之间的关系的一致性。结果表明:斑块-廊道-基底范式下发展的景观指数在指示景观格局的土壤侵蚀效应时存在局限。相对而言,斑块类型尺度的景观指数更能有效表达景观格局与土壤侵蚀的关系。基于景观类型在土壤侵蚀过程中的"源"、"汇"功能,提出了在土壤侵蚀研究中筛选适用的景观指数的原则:(1)对"源"、"汇"两类景观类型,景观指数与土壤侵蚀状况表征变量的相关系数符号相反;(2)对同为"源"或"汇"景观类型的多个景观类型,景观指数与土壤侵蚀表征变量的相关系数应具有符号一致性。尽管景观指数在斑块类型水平上具有一定的有效性,但用其预测景观格局变化的侵蚀效应有很大的不确定性。因此,基于土壤侵蚀过程与景观格局的作用机制发展新型的景观指数是增强景观格局分析预测土壤侵蚀过程的能力的途径。     

The role of landscape configuration in plant composition of floodplain forests across different physiographic areas

Questions: What is the relative importance of landscape variables compared to habitat quality variables in determining species composition in floodplain forests across different physiographic areas? How do species composition and species traits relate to effects of particular landscape variables? Do lowland and mountain areas differ in effects of landscape variables on species composition? Location: Southern Czech Republic. Methods: A total of 240 vegetation relevés of floodplain forests with measured site conditions were recorded across six physiographic areas. I tested how physiographic area, habitat quality variables and landscape variables such as current land‐cover categories, forest continuity, forest size and urbanization influenced plant species composition. I also compared how mountain and lowland areas differ in terms of the relative importance of these variables. To determine how landscape configuration affects the distribution of species traits, relationships of traits and species affinity with landscape variables were tested. Results: Among landscape variables, forest continuity, landscape forest cover and distance to nearest settlement altered the vegetation. These variables also influenced the distributions of species traits, i.e. life forms, life strategies, affinity to forest, dispersal modes, seed characteristics, flooding tolerance and Ellenberg indicator values for nitrogen, light, moisture and soil reaction. Nevertheless, physiographic area and habitat quality variables explained more variation in species composition. Landscape variables were more important in lowland areas. Forest continuity affected species composition only in lowlands. Conclusions: Although habitat quality and physiographic area explained more vegetation variability, landscape configuration was also a key factor influencing species composition and distribution of species traits. However, the results are dependent on forest geographical location, with lowland forests being more influenced by landscape variables compared to mountain forests.     

景观格局指标对不同景观格局的反应

探讨了在人为控制不同因子变量的条件下各景观格局指标对由中性随机模型产生的不同景观格局系列的反应 ,以评价一些常用指标的实用性和局限性。研究结果表明 ,大部分指标所指示的格局特征往往是不全面的 ,即它们只对格局系列中个别因子的变化敏感 ,而对另一些因子的变化反应迟钝。比较值得推荐的指标有 :总斑块数目 ,平均斑块大小 ,总边界密度 ,分维数 ,蔓延度 ,聚集度。但即使是这些指标 ,也各有其局限性 ,且存在冗余。由此提醒读者在运用景观格局指标时应在了解其实际意义的基础上 ,结合生态学过程慎重选择和解释 ,避免陷于数字游戏。     

Evaluating the use of pairwise dissimilarity metrics in paleoanthropology

Questions of alpha taxonomy are best addressed by comparing unknown specimens to samples of the taxa to which they might belong. However, analysis of the hominin fossil record is riddled with methods that claim to evaluate whether pairs of individual fossils belong to the same species. Two such methods, log se_m and the related STET method, have been introduced and used in studies of fossil hominins. Both methods attempt to quantify morphological dissimilarity for a pair of fossils and then evaluate a null hypothesis of conspecificity using the assumption that pairs of fossils that fall beneath a predefined dissimilarity threshold are likely to belong to the same species, whereas pairs of fossils above that threshold are likely to belong to different species. In this contribution, we address (1) whether these particular methods do what they claim to do, and (2) whether such approaches can ever reliably address the question of conspecificity. We show that log se_m and STET do not reliably measure deviations from shape similarity, and that values of these measures for any pair of fossils are highly dependent upon the number of variables compared. To address these issues we develop a measure of shape dissimilarity, the Standard Deviation of Logged Ratios (s_LR). We suggest that while pairwise dissimilarity metrics that accurately measure deviations from isometry (e.g., s_LR) may be useful for addressing some questions that relate to morphological variation, no pairwise method can reliably answer the question of whether two fossils are conspecific.     

Evaluating the effectiveness of road mitigation measures

The last 20 years have seen a dramatic increase in efforts to mitigate the negative effects of roads and traffic on wildlife, including fencing to prevent wildlife-vehicle collisions and wildlife crossing structures to facilitate landscape connectivity. While not necessarily explicitly articulated, the fundamental drivers behind road mitigation are human safety, animal welfare, and/or wildlife conservation. Concomitant with the increased effort to mitigate has been a focus on evaluating road mitigation. So far, research has mainly focussed on assessing the use of wildlife crossing structures, demonstrating that a broad range of species use them. However, this research has done little to address the question of the effectiveness of crossing structures, because use of a wildlife crossing structure does not necessarily equate to its effectiveness. The paucity of studies directly examining the effectiveness of crossing structures is exacerbated by the fact that such studies are often poorly designed, which limits the level of inference that can be made. Without well performed evaluations of the effectiveness of road mitigation measures, we may endanger the viability of wildlife populations and inefficiently use financial resources by installing structures that are not as effective as we think they are. In this paper we outline the essential elements of a good experimental design for such assessments and prioritize the parameters to be measured. The framework we propose will facilitate collaboration between road agencies and scientists to undertake research programs that fully evaluate effectiveness of road mitigation measures. We discuss the added value of road mitigation evaluations for policy makers and transportation agencies and provide recommendations on how to incorporate such evaluations in road planning practices.     

Spatial metrics for detecting ecosystem degradation in the ridge-slough patterned landscape

Indicators of landscape condition should be selected based on their sensitivity to environmental changes and their capacity to provide early warning detection of those changes. We assessed the performance of a suite of spatial-pattern metrics selected to quantify the condition of the ridge-slough landscape in the Everglades (South Florida, USA). Spatial pattern metrics (n = 14) that describe landscape composition, geometry and hydrologic connectivity were enumerated from vegetation maps of twenty-five 2 × 2 km primary sampling units (PSUs) that span a gradient of hydrologic and ecological condition across the greater Everglades ecosystem. Metrics were assessed in comparison with field measurements from each PSU of landscape condition obtained from regional surveys of soil elevation, which have previously been shown to capture dramatic differences between conserved and degraded locations. Elevation-based measures of landscape condition included soil elevation bi-modality (BI_SE), a binary measure of landscape condition, and also the standard deviation of soil elevation (SD_SE), a continuous measure of condition. Metric performance was assessed based on the strength (sensitivity) and shape (leading vs. lagging) of the relationship between spatial pattern metrics and these elevation-based measures. We observed significant logistic regression slopes with BI_SE for only 4 metrics (slough width, ridge density, directional connectivity index – DCI, and least flow cost – LFC). More significant relationships (n = 8 metrics) were observed with SD_SE, with the strongest associations for slough density, mean ridge width, and the average length of straight flow, as well as for a suite of hydrologic connectivity metrics (DCI, LFC and landscape discharge competence – LDC). Leading vs. lagging performance, inferred from the curvature of the association obtained from the exponent of fitted power functions, suggest that only DCI was a leading metric of the loss of soil elevation variation; most metrics were indeterminate, though some were clearly lagging. Our findings support the contention that soil elevation changes from altered peat accretion dynamics precede changes in landscape pattern, and offer insights that will enable efficient monitoring of the ridge-slough landscape as part of the ongoing Everglades restoration effort.     

Validating Landsat-based landscape metrics with fine-grained land cover data

ContextModerate-grained data may not always represent landscape structure in adequate detail which could cause misleading results. Certain metrics have been shown to be predictable with changes in scale; however, no studies have verified such predictions using independent fine-grained data.ObjectivesOur objective was to use independently derived land cover datasets to assess relationships between metrics based on fine- and moderate-grained data for a range of analysis extents. We focus on metrics that previous literature has shown to have predictable relationships across scales.MethodsThe study area was located in eastern Connecticut. We compared a 1 m land cover dataset to a 30 m resampled dataset, derived from the 1 m data, as well as two Landsat-based datasets. We examined 11 metrics which included cover areas and patch metrics. Metrics were analyzed using analysis extents ranging from 100 to 1400 m in radius.ResultsThe resampled data had very strong linear relationships to the 1 m data, from which it was derived, for all metrics regardless of the analysis extent size. Landsat-based data had strong correlations for most cover area metrics but had little or no correlation for patch metrics. Increasing analysis areas improved correlations.ConclusionsRelationships between coarse- and fine-grained data tend to be much weaker when comparing independent land cover datasets. Thus, trends across scales that are found by resampling land cover are likely to be unsuitable for predicting the effects of finer-scale elements in the landscape. Nevertheless, coarser data shows promise in predicting fine-grained for cover area metrics provided the analysis area used is sufficiently large.