Landscape Fractal Dimension Research Articles

Satellite Imagery-Based Identification of High-Risk Areas of Schistosome Intermediate Snail Hosts Spread after Flood

Snail intermediate host monitoring and control are essential for interrupting the parasitic disease schistosomiasis. Identifying large-scale high-risk areas of snail spread after floods has been greatly facilitated by remote sensing imagery. However, previous studies have usually assumed that all inundation areas carry snails and may have overestimated snail spread areas. Furthermore, these studies only used a single environmental factor to estimate the snail survival risk probability, failing to analyze multiple variables, to accurately distinguish the snail survival risk in the snail spread areas. This paper proposes a systematic framework for early monitoring of snail diffusion to accurately map snail spread areas from remote sensing imagery and enhance snail survival risk probability estimation based on the snail spread map. In particular, the flooded areas are extracted using the Sentinel-1 Dual-Polarized Water Index based on synthetic aperture radar images to map all-weather flooding areas. These flood maps are used to extract snail spread areas, based on the assumption that only inundation areas that spatially interacted with (i.e., are close to) the previous snail distribution regions before flooding are identified as snail spread areas, in order to reduce the misclassification in snail spread area identification. A multiple logistic regression model is built to analyze how various types of snail-related environmental factors, including the normalized difference vegetation index (NDVI), wetness, river and channel density, and landscape fractal dimension impact snail survival, and estimate its risk probabilities in snail spread area. An experiment was conducted in Jianghan Plain, China, where snails are predominantly linearly distributed along the tributaries and water channels of the middle and lower reaches of the Yangtze River. The proposed method could accurately map floods under clouds, and a total area of 231.5 km2 was identified as the snail spread area. The snail survival risk probabilities were thus estimated. The proposed method showed a more refined snail spread area and a more reliable degree of snail survival risk compared with those of previous studies. Thus, it is an efficient way to accurately map all-weather snail spread and survival risk probabilities, which is helpful for schistosomiasis interruption.

From Hutchinsonian ratios to spatial scaling theory: the interplay among limiting similarity, body size and landscape structure

Spatial scaling theory (SST) relates the physical structure of the environment to species coexistence and community assembly. Although SST is a recognized theory in ecology, few studies have evaluated its predictions, producing contradictory results and frequently failing to meet its assumptions. In addition, the ‘risk predictions’ of SST regarding an increase in species similarity with body size and the dependence of this pattern on the landscape and food fractal dimensions have not been evaluated. This study attempted to account for previous limitations, analyzing these predictions in coleopteran guilds that inhabit 18 temporary ponds. This metacommunity covers a large gradient of environmental variables, including food density, the landscape fractal dimension, the food fractal dimensions and other indicators of pond heterogeneity. Average similarity in carnivorous and herbivorous body sizes systematically increased with guild richness, fulfilling classical predictions of niche theory. Species similarity was associated with body size, but the association reverts from negative to positive as the landscape fractal dimension and heterogeneity increases, a pattern further supported by null model analyses. Several nonexclusive mechanisms may account for this pattern: 1) the body size‐dependent landscape perception, through which small animals detect more heterogeneity than larger animals; 2) the reaching of landscape limits by larger species, which prevents them from accessing novel largest clusters; 3) the large differences between the landscape and food fractal dimensions; and 4) the homogenization of the landscape when an integer fractal dimension is reached. These mechanisms may dictate that smaller organisms are more able to capitalize on heterogeneity or available resources than larger organisms, thus promoting increased similarity among smaller species. The presented results support the connection between landscape spatial structure and biodiversity and a mechanistic understanding of this connection from the SST.

Remote sensing and evaluation of the wetland ecological degradation process of the Zoige Plateau Wetland in China

Abstract The Zoige Plateau Wetland is the largest high-altitude swamp wetland in China. It plays a key role in ecological balance and the global change. Climate change and improper utilization have consequently resulted in decreased wetland area, disrupted ecosystem structure, and wetland function degradation and function loss. The Zoige Plateau Wetland thus faces severe ecological degradation problems. In this study, selecting the Zoige Plateau Wetland as the study area, remote sensing was used to track the ecological degradation process during 2000–2015 from three aspects (area degradation, structure degradation and function degradation) and at three administrative levels (study area, county and key township). To assess the wetland degradation quantitatively, an analytic hierarchy process (AHP) was used to construct a composite wetland degradation index based on five indicators: wetland area change rate, landscape fractal dimension, landscape fragmentation, vegetation biomass and vegetation coverage. The results showed the following. (1) In terms of area change rate, the total wetland area had continuously decreased during 2000–2015 compared to that in the 1990s, and 2010 was the most significant. The frequency of negative change in the wetland area reached 87.5% in all four counties and across four time periods (2000, 2005, 2010 and 2015), and 85% at the township level. At the spatial scale, Hongyuan County had the smallest wetland area change rate. (2) In terms of structure change, the variations in landscape fractal dimension and landscape fragmentation generally exhibited similar trends at different levels. Specifically, the ecosystem structure was seriously affected in 2000, then gradually recovered in 2005 and 2010, and was again under aggravated interference in 2015. (3) In terms of function change, the above-ground biomass yield in the northeastern region was higher than that in the southern region. A low value was detected in 2000, and then the value increased and remained essentially the same in 2005 and 2010. However, the value decreased in 2015, indicating deteriorated vegetation condition. The vegetation coverage in the study area remained steady, without deterioration in a particular year. (4) In terms of the whole study area, the wetland degradation grades in the four periods were mild (2000), moderate (2005), mild (2010) and mild (2015). In brief, the wetland degradation was the most severe in 2005. Over the 2000–2015 period, the spatial degradation pattern of the Zoige Plateau Wetland progressed from the northeast to the southwest. The model built in this study could be widely applicable. And this study has also some reference value for monitoring and management of wetland degradation by remote sensing.

Evolution of Urban Landscape Pattern in Suzhou City during 1987-2009

The urban landscape pattern evolution and driving forces in SuZhou City in the past two decades were explored based on the landscape ecology theory and the ENVI 4.7 & Fragstats 3.3 technology, using the multi-source interpreted data of Landsat TM images in 1987,2005 and 2009, and Landsat ETM+ image in 2000. The indices chosen are the urban landscape overall constitution, average patch area, patch number, patch density, fractal dimension, contagion index, isolation index, fragment index, landscape diversity and evenness index. Taking the remote sensing as a platform to integrate and analyze the data, the driving forces are summarized together with the development of SuZhou City. This will supply the theory foundation and scientific basis for the land resources of reasonable planning and using, management, sustainable utilization, and the landscape pattern optimization configuration in SuZhou City. The results show that, the landscape pattern in Suzhou City changed greatly from 1987 to 2009. The construction land area increased, while the cultivated land, wood land and water body area decreased. The urban landscape contagion index and landscape fractal dimension were all increased, while the urban landscape diversity and evenness index were all decreased. The isolation index and fragment index of the construction land and cultivated land were small, this shows that the landscape pattern changed mainly by human factors. The population and economy growth together with industrialization and urbanization were main forces for the urban landscape pattern evolution in SuZhou City. The results can provide scientific evidence for ecological landscape design and urban development planning in other regions.

Seagrass landscape-scale changes in response to disturbance created by the dynamics of barrier-islands: A case study from Ria Formosa (Southern Portugal)

This study documents long-term changes of a Zostera noltii landscape induced by a natural cyclic event in a coastal lagoon. The barrier-islands forming this system are very dynamic with drifting movements controlling ecological patterns and processes occurring in this area. Changes in the areal extent of the Z. noltii meadows were assessed using historical aerial photographs from 1940, 1980, 1989, 1996 and 1998. Landscape indices such as total patch area (TA), mean patch size (MPS), number of patches (NP), mean shape coefficient of variation (CV) and landscape fractal dimension (D) were calculated for each year and related to an index of disturbance intensity. The spatial distribution of the Z. noltii meadows varied greatly during the studied period and changes observed were related to the disturbance created by the barrier-islands' spatial dynamics. After an artificial inlet relocation the Z. noltii area, number of patches, patch mean size and coefficient of variation decreased. The fractal dimension of the Z. noltii landscape increased by 50% showing that besides a decrease in total area, number of patches, and patch mean area, patch fragmentation was an important consequence of this anthropogenic disturbance. Seagrass natural distribution patterns changed in response to natural and human-induced activities. This study emphasizes the importance of the landscape approach and the historical perspective when studying seagrass changes and the importance of taking into consideration long-term changes in seagrass landscapes to avoid confusion between man-induced effects with natural cyclic events.

Multiscale Analysis of Landscape Heterogeneity: Scale Variance and Pattern Metrics

A major goal of landscape ecology is to understand the formation, dynamics, and maintenance of spatial heterogeneity. Spatial heterogeneity is the most fundamental characteristic of all landscapes, and scale multiplicity is inherent in spatial heterogeneity. Thus, multiscale analysis is imperative for understanding the structure, function and dynamics of landscapes. Although a number of methods have been used for multiscale analysis in landscape ecology since the 1980s, the effectiveness of many of them, including some commonly used ones, is not clear or questionable. In this paper, we discuss two approaches to multiscale analysis of landscape heterogeneity: the direct and indirect approaches. We will focus on scale variance and semivariance methods in the first approach and 17 landscape metrics in the second. The results show that scale variance is potentially a powerful method to detect and describe multiple-scale structures of landscapes, while semivariance analysis may often fail to do so especially if landscape variability is dominant at broad scales over fine scales. Landscape metrics respond to changing grain size rather differently, and these changes are reflective of the modifiable areal unit problem as well as multiple-scale structures in landscape pattern. Interestingly, some metrics (e.g., the number of patches, patch density, total edge, edge density, mean patch size, patch size coefficient of variation) exhibit consistent, predictable patterns over a wide range of grain sizes, whereas others (e.g., patch diversity, contagion, landscape fractal dimension) have nonlinear response curves. The two approaches to multiple-scale analysis are complementary, and their pros and cons still need to be further investigated systematically.

Tectonic, climatic and lithologic influences on landscape fractal dimension and hypsometry: implications for landscape evolution in the San Gabriel Mountains, California

East-west variation in tectonic activity and strong north-south climatic gradients provide a unique opportunity to study tectonic, climatic and lithologic influences on landscape evolution in the San Gabriel Mountains, California. The competing tendencies of constructive tectonic and degradational climatic effects act against lithologic resistance to influence fluvial systems, and thus the nature of adjacent and nested drainage basins. Landscape fractal dimension ( D), a measure of surface roughness over a variety of scales, and the hypsometric integral ( I), a measure of the distribution of landmass volume above a reference plane are useful measures of altitudinal variation with scale. As such, they may provide clues as to the relative influences of tectonism, climate and rock type. Topographic analyses of the San Gabriel Mountains clearly indicate that tectonism strongly influences D at range-wavelength scales, while rock-type variation apparently influences D and I at smaller scales. Tectonism is also shown to influence I across the mountain-piedmont junction at all scales investigated. Tectonic activity shows strong negative correlation with both I and D because tectonically active portions of the mountain front do not allow time for much landscape dissection by lower-order streams. Three-dimensional topographic modeling suggests climatic parameters exert a stronger influence on D than does tectonism. This modeling also suggests an inverse correlation between range-scale D and I with varying climate and uplift rate; a positive correlation is observed in the San Gabriel Mountains. We suggest this difference results from (1) differences in uplift style between the San Gabriel Mountains and the models, and/or (2) variation in rock-type erodibility present in the San Gabriel Mountains but which was not modeled. We postulate that the interaction of tectonic, climatic and lithologic parameters influences the stable I and D to which a landscape evolves. Key questions remaining include: (1) the time required to reach a stable I or D after a climatic or tectonic change; (2) what does the fractal nature of topography tell us about the scaling characteristics of major landforming processes; (3) how does climate influence range-scale I and both range- and small-scale D; and (4) what are the effects on I and D of range-scale lithologic variation, both in the models and in real landscapes?

The Coexistence of Species in Fractal Landscapes

The degree of spatial dependence in a landscape can be modeled by varying the landscape's fractal dimension, D. I simulated landscapes in which D varied independently of environmental variability. Individuals of 10 species with modes placed evenly along the dominant environmental gradient were randomly placed on these landscapes and were allowed to reproduce, disperse, and compete. The results demonstrate that the effect of a landscape's environmental variability on species coexistence is affected by the degree of spatial dependence in a complex manner. Increasing the fractal dimension (decreasing spatial dependence) allows more species to exist per microsite and per landscape. However, extremely high fractal dimensions cause fewer species to coexist on the landscape scale. Observed habitat breadths are increased (and beta diversity is decreased) as a function of D. I suggest that these patterns can be explained by habitat area, the mass effect, ecological equivalency, and global biological constraints.