Evaluating empirical scaling relations of pattern metrics with simulated landscapes

Landscape patterns demonstrate scale-dependent properties that have been parsimoniously described by empirical scaling functions. These functions, derived from multiple-scale analysis of real landscapes, are evaluated here for their generality and robustness via a series of simulated landscapes with known landscape patterns. A factorial design was used to generate these landscapes, varying the number of classes, class abundance distribution, and patch dispersion. The results confirm that the three types of scaling relations were both general and robust. Type I metrics were predictable with simple scaling functions (e.g. power laws or linear functions); Type II metrics showed stair-case like response patterns and were essentially not predictable; Type III metrics exhibited erratic response patterns that were unpredictable in most cases. However, significant differences were found between real and simulated landscapes when landscape extent was increased. Systematic changes in grain size show that the predictability of scaling relations increases with the number of classes, the evenness of class abundance distribution, and the aggregation of patch dispersion. However, random patch dispersion seemed to enhance the predictability of scaling relations when changing spatial extent.     

Using connectivity metrics in conservation planning – when does habitat quality matter?

Aim The objective of conservation planning is often to prioritize patches based on their estimated contribution to metapopulation or metacommunity viability. The contribution that an individual patch makes will depend on its intrinsic characteristics, such as habitat quality, as well as its location relative to other patches, its connectivity. Here we systematically evaluate five patch value metrics to determine the importance of including an estimate of habitat quality into the metrics. Location We tested the metrics in landscapes designed to represent different degrees of variability in patch quality and different levels of patch aggregation. Methods In each landscape, we simulated population dynamics using a spatially explicit, continuous time metapopulation model linked to within patch logistic growth models. We tested five metrics that are used to estimate the contribution that a patch makes to metapopulation viability: two versions of the probability of connectivity index, two versions of patch centrality (a graph theory metric) and the metapopulation capacity metric. Results All metrics performed best in environments where patch quality was very variable and high quality patches were aggregated. Metrics that incorporated some measure of patch quality did better in all environments, but did particularly well in environments with high variance of patch quality and spatial aggregation of good quality patches. Main conclusions Including an estimate of patch quality significantly increased the ability of a given connectivity metric to rank correctly habitat patches according to their contribution to metapopulation viability. Incorporating patch quality is particularly important in landscapes where habitat quality is highly variable and good quality patches are spatially aggregated. However, caution should be used when applying patch metrics to homogeneous landscapes, even if good estimates of patch quality are available. Our results demonstrate that landscape structure and the degree of variability in patch quality need to be assessed prior to selecting a suitable method for estimating patch value.     

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.     

Scale dependence of landscape metrics and their indicatory value for nutrient and organic matter losses from catchments

We investigated scale dependence of landscape metrics and the relationship between land use parameters and FRAGSTATS-based landscape metrics (edge density (ED), patch density (PD), mean shape index (SHAPE_MN), mean euclidean nearest neighbor index (ENN_MN), contagion (CONTAG), patch richness density (PRD), and Shannon's diversity index (SHDI)) and nutrient/organic-matter-based water quality indicators (BOD₇ and COD_KMnO4 values, total-N and total-P concentrations in water) in 24 catchments with various land use patterns in Estonia. We used the Basic Map of Estonia (1:10,000), the Base Map of Estonia (1:50,000) and the CORINE Land Cover Map (1:100,000). In scale analysis, we calculated landscape metrics on artificial and real landscapes. Scale analysis showed that responses of landscape metrics to changing grain size vary among landscapes and metrics. Analysis of artificial landscapes showed that mean euclidean nearest neighbor distance and contagion are directly dependent on grain size and should therefore be used carefully. When finding relationships between landscape metrics and water quality indicators, significant differences between the relationships derived from the Base Map and the CORINE Land Cover Map were found. In the case of the Base Map, landscape metrics correlated strongly with land use and showed no expected relationships with water quality data. This underlines the importance of land use classification in such kind of analysis. Correlation between the landscape metrics calculated on the basis of the CORINE Land Cover Map and water quality data was stronger than in the case of the Base Map. The COD_KMnO4 value significantly correlated with all land use types. For instance, the COD_KMnO4 values are higher when fens and natural areas form a higher proportion of the catchments’ land use. Except for the BOD₇ value, all the water quality indicators showed significant correlation with urban land use proportions. Strong relationship between the patch density and the COD_KMnO4 value is most likely caused by the fact that both parameters were significantly correlated with the proportion of natural areas. As the landscape metrics depend on pixel size, topographic scale, and land use classification, and as the effect of land use on water quality in catchments is the most significant of the factors, it was impossible to separate the influence of land use pattern from the influence of FRAGSTATS-based landscape metrics.     

Habitat quality of source patches and connectivity in fragmented landscapes

Because spatial connectivity is critical to dispersal success and persistence of species in highly fragmented landscapes, the way that we envision and measure connectivity is consequential for biodiversity conservation. Connectivity metrics used for predictive modeling of spatial turnover and patch occupancy for metapopulations, such as with Incidence Function Models (IFM), incorporate distances to and sizes of possible source populations. Here, our focus is on whether habitat quality of source patches also is considered in these connectivity metrics. We propose that effective areas (weighted by habitat quality) of source patches should be better surrogates for population size and dispersal potential compared to unadjusted patch areas. Our review of a representative sample of the literature revealed that only 12.5% of studies incorporated habitat quality of source patches into IFM-type connectivity metrics. Quality of source patches generally was not taken into account in studies even if habitat quality of focal patches was included in analyses. We provide an empirical example for a metapopulation of a rare wetland species, the round-tailed muskrat (Neofiber alleni), demonstrating that a connectivity metric based on effective areas of source patches better predicts patch colonization and occupancy than a metric that used simple patch areas. The ongoing integration of landscape ecology and metapopulation dynamics could be hastened by incorporating habitat quality of source patches into spatial connectivity metrics applied to species conservation in fragmented landscapes.     

不同干扰背景下景观指数与物种多样性的多尺度效应——以巩义市为例

以黄河中下游山地丘陵区的巩义市为研究区,采用典型样地法对灌草丛、人工林和农田边缘3种不同干扰背景下的自然、半自然生境内的植物进行调查。基于景观生态学原理,在地理信息系统技术支持下,借助于Fragstatta3.3软件,以调查样地为中心,计算了150、250、500、750、1000、1250、1500m不同半径缓冲区内表征景观形状(Edge and patch shape)、边缘对照(Edge contrast)、相似度和邻近度(Proximity and similarity)、景观多样性(Diversity)、基质(Texture)、斑块大小和密度(Patch size and patch density)共6类52个指数,运用冗余分析(RDA)筛选出不同尺度下对该区农业景观中植物多样性有显著影响的景观指数。结果表明:不同尺度,景观指数对物种多样性的影响变化显著。灌草丛生境,在500—750m范围内,SHAPE_AM指数和PARA_AM指数能够很好的解释物种多样性,解释量为33.6%;人工林生境,SHAPE_AM指数、AREA_CV指数、SIMI指数和PAFRAC指数在1000—1250m范围内对物种多样性的解释量达到48.1%;农田边缘生境,GYRATE_CV指数、ENN_CV指数、PARA_MN指数和FRAC_AM指数在750—1250m范围内对物种多样性影响显著,解释量为32%。其中,辛普森多样性指数(SIDI)与灌草丛物种多样性在750—1250m范围内作用显著,ENN_CV指数仅对农田边缘物种多样性影响较大。景观指数对物种多样性的影响具有尺度依赖性,未来应全面综合探讨这些指数的尺度效应及在景观生态学中的应用。     

基于理想生态系统模式与三维景观指数的徽派村落空间特征解析——以呈坎为例

徽派村落是中国传统村落的典型代表,蕴含了丰富的地域文化和生态内涵,是中国古代人与自然和谐相处的典范,其研究与保护在生态学、地理学、建筑学和美学等领域具有重要的科学价值.本文以呈坎村为例,综合风水理论、心理场理论等,从生态学视角提出理想人居环境的理想生态系统模式,并引入三维景观指数,对徽派村落空间结构进行解析,定量分析村落理想生态系统各景观要素组合结构的生态功能体现.结果表明: 呈坎村立体结构为“山-林-屋-水-林”的景观空间组合模式,形成了以人为中心、自然景观立体环绕的圈层结构,符合理想人居模式.传统基于投影距离的方法造成了景观指数偏差(如对面积与边长的低估).平均斑块面积三维指数比二维指数高6.7%;林地的面积比重三维指数比二维指数高1.0%,其他景观类型的面积比重均有所下降,其中建设用地和耕地等人工斑块的面积比重下降最多.面积与周长指标被低估,形状指标和多样性指标被高估,导致景观格局分析中自然斑块的优势度被低估、人工斑块的优势度被高估.三维景观指数表明,呈坎村落生态系统中各自然要素及组合体现出了较好的生态功能,关键要素和景观生态系统具有较高的稳定性、连接度和聚集性;定量印证了以呈坎为代表的徽派村落是理想的生态系统.     

Entropy increase of fragmented habitats: A sign of human impact?

Analysis of a recently validated fragmentation index, named ‘coherence’, shows a direct relationship with the Simpson and Shannon indices. Since these diversity metrics are also denoted as ‘entropy metrics’, it can be accepted that patch size heterogeneity can adequately be described by an entropy metric. Since both indices are used to determine the entropy of a sample, the Brillouin index should be applied instead to correctly determine the entropy of a landscape pattern, this because this latter index is developed for fully censused data sets, such as landscapes when a complete coverage by cartographic data or imagery is available. Calculation of the Brillouin entropy index for three specific sites located in Cadiz Township (USA), the Poole Basin (Dorset, UK) and Sao Paulo State (Brazil), respectively, and using long-term data of patch size diversity, reveals increasing entropy levels associated with anthropogenic land cover dynamics (fragmentation). The observed entropy trends defy the laws of thermodynamics and signal the impact of human action on landscape integrity.     

Evaluating the effectiveness of landscape configuration metrics from landscape composition metrics

Although landscape configuration and landscape composition metrics are correlated theoretically and empirically, the effectiveness of configuration metrics from composition metrics has not been explicitly investigated. This study explored to what extent substantial information of configuration metrics increases from certain easily calculated and extensively used composition metrics and how strongly the effectiveness is influenced by different factors. The effectiveness of 12 landscape configuration metrics from the percentage of landscape (PLAND) of each land-use class and patch density (PD) was evaluated through the coefficient of determination (R ²) of multivariate stepwise linear regression analysis of 150 town-based landscape samples from three regions. The different landscape configuration metrics from PLAND and PD presented significantly different performances in terms of effectiveness [the contagion index and aggregation index possess minimal information, and the effective mesh size (MESH) and area-weighted mean patch fractal dimension possess abundant information]. Furthermore, the effectiveness of configuration metrics showed different responses to changing cell sizes and different land-use categorization in different regions (interspersion and juxtaposition index, patch cohesion index, and MESH exhibited large variations in R ² among the different regions). No single, uniform, consistent characteristic of effectiveness was determined across different factors. This new approach to understanding the effectiveness of configuration metrics helps clarify landscape metrics and is fundamental to landscape metric assessment.     

黄土丘陵小流域景观格局指数的粒度效应

采用基于GIS的景观格局分析法,研究了1975-2007年黄土丘陵沟壑区大南沟小流域景观格局指数在1～50 m粒度范围内的粒度效应.结果表明：研究区小流域景观格局指数的粒度效应明显,不同年份之间的差异显著;该区景观格局指数的粒度效应可分为5种类型,即稳定不变型、平稳降低型、波动降低型、波幅增强型和不规则变化型.研究区景观的斑块丰富度属于稳定不变型,即随着粒度增大保持不变;边界长度、边界密度、景观形状指数、聚合度指数和蔓延度指数属于平衡降低型,即随着粒度增大呈显著的线性降低趋势;分维数随粒度增大呈波动递减趋势,属于波动降低型粒度效应;景观总面积、Shannon多样性指数和Shannon均匀度指数的波幅呈显著增大趋势,属于波幅增强型粒度效应;不规则变化型粒度效应的景观格局指数包括斑块数、斑块密度、平均斑块面积、最大斑块指数、破碎度指数和景观分离度指数.1975年研究区上述景观格局指数的粒度效应与其他年份之间的差异显著,甚至截然相反.     

不同斑块类型的景观指数粒度效应响应——以无锡市为例

斑块类型与景观格局粒度效应响应关系密切。以无锡市为研究区域,针对地区社会经济活动频繁、人为干扰强烈和生态脆弱等特性,以土地利用类型、热力等级和生态贡献为斑块类型划分依据,构建出对应的3种不同景观格局。在相同粒度变化情况下,选用了19个景观水平指数和Moran's I指数,分析了不同景观格局粒度效应的响应情况。结果表明,随粒度变粗:1)土地利用类型、热力等级和生态贡献斑块的部分景观指数响应曲线变化剧烈程度依次减弱;2)3类斑块的Moran's I指数均存在尺度效应。其中,土地利用类型和生态贡献斑块的Moran's I指数存在负相关,热力等级斑块没有。生态贡献斑块响应曲线在正相关区域内变化相对平缓,土地利用类型与热力等级斑块响应曲线变化趋势相反;3)指数反映的第一临界粒度基本一致,但景观指数响应曲线的临界现象更为明显。总体上,不同类型斑块在同一研究区构成的景观格局、指数响应曲线变化趋势和第一临界粒度都较为相似;斑块类型对景观指数粒度效应响应存在影响,但还有待深入探讨。     

中性景观模型与真实景观的一致性

采用RULE和SimMap中性景观模型,使其形成模拟景观的图幅大小、景观内各类型数目以及各类型之间的比例等项与真实景观相同,通过不同景观指标对中性模型系列的反应,看其在多大程度上代替真实景观．研究发现,中性景观模型在斑块数、斑块周长、聚集度、蔓延度以及孔隙度等指标所反映的格局特征方面,能很好地代替真实景观,而在校正斑块周长面积比、分维数以及边界分布均匀度等指标所反映的格局特征方面,并不能很好地代替真实景观,说明中性景观模型只能在一定的范围内可以代替真实景观。而不能完全取而代之.     

Towards a core set of landscape metrics for biodiversity assessments: A case study from Dadia National Park,Greece

Spatial heterogeneity has an important influence on a wide range of ecological patterns and processes, and many landscape metrics in GIS environment are used to facilitate the investigation of the relation between landscape structure and biodiversity. Data reduction analyses have been applied to tackle the problem of highly correlated indices, but valid landscape predictors for fine scale Mediterranean forest-mosaics are still missing. Therefore, we analyzed the landscape structure of Dadia National Park, Greece, a Mediterranean forest landscape of high biodiversity, characterized by pine, oak and mixed woodland. By distinguishing nine land cover classes, 119 variables were computed and factor analysis was applied to detect the statistical dimensions of landscape structure and to define a core set of representative metrics. At landscape level, diversity of habitats, fragmentation and patch shape and at class level dominance of mixed forest and the gradient from one pure forest type to another turned out to be the crucial factors across three different scales. Mapping the encountered dimensions and the representative metrics, we detected that the pattern of landscape structure in Dadia National Park was related to dominating habitat types, land use, and level of protection. The evaluated set of metrics will be useful in establishing a landscape monitoring program, to detect the local drivers of biodiversity, and to improve management decisions in Dadia NP and similar mosaic-landscapes.     

The Relationship between Habitat Loss and Fragmentation during Urbanization: An Empirical Evaluation from 16 World Cities

Urbanization results in habitat loss and habitat fragmentation concurrently, both influencing biodiversity and ecological processes. To evaluate these impacts, it is important to understand the relationships between habitat loss and habitat fragmentation per se (HLHF) during urbanization. The objectives of this study were two-fold: 1) to quantify the different forms of the HLHF relationship during urbanization using multiple landscape metrics, and 2) to test the validity of the HLHF relations reported in the literature. Our analysis was based on a long-term urbanization dataset (1800–2000) of 16 large cities from around the world. Habitat area was represented as the percentage of non-built-up area in the landscape, while habitat fragmentation was measured using several landscape metrics. Our results show that the relationship between habitat loss and habitat fragmentation during urbanization is commonly monotonic—linear, exponential, or logarithmic, indicating that the degree of habitat fragmentation per se increases with habitat loss in general. We compared our results with 14 hypothesized HLHF relationships based on simulated landscapes found in the literature, and found that four of them were consistent with those of urbanization, whereas the other ten were not. Also, we identified six new HLHF relationships when fragmentation was measured by total core area, normalized total core area, patch density, edge density and landscape shape index, respectively. In addition, our study demonstrated that the “space-for-time” approach, frequently used in ecology and geography, generated specious HLHF relationships, suggesting that this approach is largely inappropriate for analyses of urban landscapes that are highly heterogeneous in space and unusually contingent in dynamics. Our results show both generalities and idiosyncrasies of the HLHF relationship, providing new insights for assessing ecological effects of urbanization.     

A comparison of spatially explicit landscape representation methods and their relationship to stream condition

1. Biodiversity, water quality and ecosystem processes in streams are known to be influenced by the terrestrial landscape over a range of spatial and temporal scales. Lumped attributes (i.e. per cent land use) are often used to characterise the condition of the catchment; however, they are not spatially explicit and do not account for the disproportionate influence of land located near the stream or connected by overland flow. 2. We compared seven landscape representation metrics to determine whether accounting for the spatial proximity and hydrological effects of land use can be used to account for additional variability in indicators of stream ecosystem health. The landscape metrics included the following: a lumped metric, four inverse‐distance‐weighted (IDW) metrics based on distance to the stream or survey site and two modified IDW metrics that also accounted for the level of hydrologic activity (HA‐IDW). Ecosystem health data were obtained from the Ecological Health Monitoring Programme in Southeast Queensland, Australia and included measures of fish, invertebrates, physicochemistry and nutrients collected during two seasons over 4 years. Linear models were fitted to the stream indicators and landscape metrics, by season, and compared using an information‐theoretic approach. 3. Although no single metric was most suitable for modelling all stream indicators, lumped metrics rarely performed as well as other metric types. Metrics based on proximity to the stream (IDW and HA‐IDW) were more suitable for modelling fish indicators, while the HA‐IDW metric based on proximity to the survey site generally outperformed others for invertebrates, irrespective of season. There was consistent support for metrics based on proximity to the survey site (IDW or HA‐IDW) for all physicochemical indicators during the dry season, while a HA‐IDW metric based on proximity to the stream was suitable for five of the six physicochemical indicators in the post‐wet season. Only one nutrient indicator was tested and results showed that catchment area had a significant effect on the relationship between land use metrics and algal stable isotope ratios in both seasons. 4. Spatially explicit methods of landscape representation can clearly improve the predictive ability of many empirical models currently used to study the relationship between landscape, habitat and stream condition. A comparison of different metrics may provide clues about causal pathways and mechanistic processes behind correlative relationships and could be used to target restoration efforts strategically.     

Impacts of land use patterns on river water quality: the case of Dongjiang Lake Basin,China

Landscape pattern can regulate water quality, but determining the thresholds at which landscape metrics impact water quality remains a key issue. Thus, in this study, we investigated landscape metrics that affect the water quality of the rivers flowing into Dongjiang Lake, China, and their spatial and seasonal differences, were investigated using redundancy and partial redundancy analyses. Further, a raw water quality parameter-landscape metric data set was constructed. Threshold values of landscape metrics that induced sudden changes in water quality were analyzed using the bootstrap method applied to 1000 random samples extracted from data set. Finally, mechanisms of landscape patterns that affected river water quality were quantitively explored. The following results were obtained: (1) The key area of landscape that impacted water quality in the Dongjiang Lake Basin was the 400 m buffer zone; (2) Seasonal differences were observed in water quality changes, which better explained by landscape metrics in the dry season than in the wet season. Moreover, water quality was most influenced by landscape configuration metrics. The influence of landscape topographic metrics was greater than that of composition metrics in the dry season, whereas the opposite was true in the wet season; and (3) In this watershed, the largest patch index of grassland and landscape shape index of built-up land were the key metrics at the sub-basin and 400 m buffer zone, respectively. If the largest patch index of grassland was below 8.5% or the landscape shape index of built-up land exceeded 1.5, the water quality of the rivers flowing into the lake was prone to a risk of significant decline, which has an important guiding significance to the optimization of land use pattern.     

Multifaceted Analysis of Patch-Level Plant Diversity in Response to Landscape Spatial Pattern and History on Mediterranean Dunes

Landscape structure is known to critically affect biodiversity. However, although the multi-facetted character of biodiversity is widely recognized, few studies have linked landscape spatial pattern and history simultaneously to multiple facets (taxonomic, functional, and phylogenetic) and spatial components (α, β, and γ) of plant diversity. We set out to reveal whether landscape parameters have specific effects on the separate diversity facets and components of plant diversity at a patch scale on coastal dune landscapes of Central Italy. For each landscape patch, we computed a set of patch-based metrics relying on multi-temporal land-cover maps. Based on a database of plant community plots, on functional traits from field measurements and on a dated phylogenetic tree, we calculated taxonomic (TD), functional (FD), and phylogenetic diversity (PD) within each patch at α, β, and γ level. Diversity measures were then related to the landscape metrics via linear mixed-effect models. Landscape pattern and transformations affected TD only moderately in coastal dune ecosystems. We found much stronger and contrasted effects on FD and PD. FD increased in patches surrounded by human-dominated habitats; PD was higher in fragmented patches, particularly in the Mediterranean macchia. Moreover, landscape pattern affected differently the single communities, the turnover among communities and the pool of species within the patch (α, β, and γ components). Our results call for the combined inclusion of FD and PD and their partitions into ecological analyses, being TD too crude to capture the comprehensive and contrasted response of plant diversity to landscape spatial pattern.     

Interactions between landcover pattern and geospatial processing methods: Effects on landscape metrics and classification accuracy

Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric “number of patches” than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty.