A multiscale analysis of ecosystem services supply in the NW Iberian Peninsula from a functional perspective

In recent years, the assessment of ecosystem services (ES) supply has been based on the use of Land Use/Land Cover (LULC) data as proxies for spatial representation of ecosystems. Nevertheless, some shortcomings of this method, such as uncertainties derived from generalization of the ecosystem types and assumptions of invariance across spatial scales, indicate the need for new approaches. Such approaches could be aimed at improving knowledge of the relationships between ecosystem services and landscape structure and the spatial characteristics of ES patterns. In this study, we propose an integrative approach that involves the generation and analysis of continuous maps representing the supply of five ES potentially related to the amount of biomass. Five remote sensing images of the Northwestern Iberian Peninsula, obtained with Landsat-5 TM, were used to generate a proxy for net primary production by combining the normalized difference vegetation index (NDVI) of each image to calculate a ΣNDVI index that could act as a potential indicator of some ecosystem services. This information was combined with three variables – terrain slope, population density and occurrence of protected areas – to produce spatial models for the five ES and eventually a series of five supply maps. Food, materials and energy provision services showed a clustered pattern, with high supply values in flat zones and areas with high population densities. In contrast, mass flow and climate regulation services were more widely distributed throughout the study area. The five ecosystem service patterns were analyzed at different scales by two methods: lacunarity and four term local quadrat variance (4TLQV) analysis. These methods revealed differences in the spatial pattern: lacunarity analysis was useful for detection of scale thresholds at the local level, whereas 4TLQV was more sensitive to scale thresholds at larger spatial levels. Thus, the variance analysis yielded higher values for larger windows sizes, particularly for provisioning services. The results demonstrated the suitability of the proposed approach for the spatially explicit modeling of ecosystem services, avoiding the uncertainty of other assessments such as those based on LULC data, and for the exploratory analysis of ES supply from a spatial point of view.     

Gypsy moth response to landscape structure differs from neutral model predictions: implications for invasion monitoring

Simulations of dispersal across computer-generated neutral landscapes have generated testable predictions about the relationship between dispersal success and landscape structure. Models predict a threshold response in dispersal success with increasing habitat fragmentation. A threshold is defined as an abrupt, disproportionate decline in dispersal success at a certain proportion of habitat in the landscape. To identify potential empirical threshold responses in invasion success to landscape structure, we quantified the relationship between progression of the gypsy moth (Lymantria dispar) invasion wavefront across Michigan (1985–1996) and the structure of the Michigan landscape using two indices of invasion success and six landscape metrics. We also examined the effect of scale of analysis and choice of land cover characterization on our results by repeating our analysis at three scales using two different land cover maps. Contrary to simulation model predictions, thresholds in invasion success did not correspond closely with thresholds in landscape structure metrics. Increased variation in invasion success indices at smaller scales of analysis also suggested that invasion success should be studied at larger spatial extents (≥75 km²) than would be appropriate for characterizing individual dispersal events. The predictions of individual dispersal models across neutral landscapes may have limited applications for the monitoring and management of vagile species with excellent dispersal capabilities such as the gypsy moth.     

Light distribution in mesic grasslands: Spatial patterns and temporal dynamics

Abstract. Spatial patterns and temporal dynamics of light distribution were investigated using lacunarity analysis, a multi‐scale measure of spatial heterogeneity, in three mesic grasslands with different disturbance regimes. Frequency distributions of relative light intensity (RLI) were similar for the two non‐disturbed grasslands, despite different composition (forbs vs. caespitose grass) resulting from different historical disturbance regimes prior to 1985, and different from the annually disturbed grassland. Spatial heterogeneity of light distribution was greater at all scales in the native, annually disturbed grassland than in the two non‐disturbed grasslands. The disturbance regime affected temporal dynamics of the spatial patterns of light distribution in each grassland. The annually disturbed grassland exhibited a dramatic decrease in lacunarity (heterogeneity) from early to late April, likely the result of considerable growth of a cool‐season grass. A general decrease in lacunarity occurred in the native, non‐disturbed grassland, although the magnitude was much less than in the annually disturbed grassland. The reverted, non‐disturbed grassland did not exhibit an appreciable change in lacunarity until later in the growing season, and then only at smaller scales. Combining the frequency distribution of RLI and the lacunarity curves provided an effective approach to assess relationships between the dynamics of spatial pattern of light distribution and ecological processes as influenced by different disturbance regimes. Integrating lacunarity analysis with more traditional measurements of grassland ecosystems (plant spatial distribution and arrangement and plant species composition and architecture) may be an effective way to assess functional consequences of structural changes in grassland ecosystems.     

Adapting lacunarity techniques for gradient-based analyses of landscape surfaces

Typically, landscapes are modeled in the form of categorical map patterns, i.e. as mosaics made up of basic elements which are presumed to possess sharp and well-defined boundary lines. Many landscape ecological concepts are based upon this perception. In reality, however, the spatial value progressions of environmental parameters tend to be “gradual” rather than “abrupt”. Therefore, gradient approaches have shifted to the forefront of scientific interest recently. Appropriate methods are needed for the implementation of such approaches. Lacunarity analysis may provide a suitable starting point in this context. We propose adapted versions of standard lacunarity techniques for analyzing ecological gradients in general and the heterogeneity of physical landscape surfaces in particular. A simple way of customizing lacunarity analysis for quantifying the heterogeneity of digital elevation models is to use the value range for defining the box mass used in the calculation process. Furthermore, we demonstrate how lacunarity analysis can be combined with metrics derived from surface metrology, such as the “Average Surface Roughness”. Finally, the “classical” lacunarity approach is used in combination with simple landform indices. The methods are tested using different data sets, including high-resolution digital elevation models. In summary, lacunarity analysis is adopted in order to establish a gradient-based approach for terrain analysis and proves to be a valuable concept for comparing three-dimensional surface patterns in terms of their degree of “heterogeneity”. The proposed developments are meant to serve as a stimulus for making increased use of this simple but effective technique in landscape ecology. They offer a large potential for expanding the methodical spectrum of landscape structure analysis towards gradient-based approaches. Methods like lacunarity analysis are promising, since they do not rely on predefined landscape units or patches and thus enable ecologists to effectively deal with the complexity of natural systems.     

Lacunarity as a novel measure of cancer cells behavior

An important goal in many branches of science, especially in molecular biology and medicine is the quantitative analysis of the structures and their morphology. The morphology can be analyzed in many ways, in particular by the fractal analysis. Apart from the fractal dimension, an important part of the fractal analysis is the lacunarity measurement which, roughly speaking, characterizes the distribution of gaps in the fractal: a fractal with high lacunarity has large gaps. In this paper, we present an extension of the lacunarity measure to objects with nonregular shapes that enables us to provide a successful discrimination of cancer cell lines. The cell lines differ in the shape of vacuole (the gaps in their body) which is perfectly suited for the lacunarity analysis.     

Indirect effects of cattle grazing on shrub spatial pattern in a mediterranean scrub community

Identifying the mechanisms and interactions that influence the spatial structure of vegetation is important for both scientific and practical purposes. Grazing is one of the most fundamental interactions in ecology but so far its effect on vegetation spatial pattern received little attention. In this study we propose a conceptual model that can be used to predict the effect of grazing on shrub spatial pattern in water-limited ecosystems where shrubs grow within a matrix of annual vegetation. According to the model, grazing may increase or decrease clumping in shrub distribution, depending on (1) the relative palatability of shrubs vs. annual plants to the herbivores, and (2) the manner (negative or positive) by which adult shrubs and annual plants affect the establishment of shrub seedlings. We tested our model in a Mediterranean scrub ecosystem by analyzing the development of shrub spatial pattern over a period of 40 years in plots characterized by contrasting intensities of cattle grazing. As predicted by the model, all plots showed a clumped pattern of shrub distribution in the absence of cattle grazing while intense cattle grazing reduced the clumpiness of the vegetation and generated a more random pattern of shrub distribution. Interestingly, plots representing the two grazing regimes did not differ significantly in their shrub cover, suggesting that shrub spatial pattern may be more sensitive to grazing than overall shrub cover.