153 research outputs found

    Interpreting multiscale domains of tree cover disturbance patterns in North America

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    Spatial patterns at multiple observation scales provide a framework to improve understanding of pattern-related phenomena. However, the metrics that are most sensitive to local patterns are least likely to exhibit consistent scaling relations with increasing extent (observation scale). A conceptual framework based on multiscale domains (i.e., geographic locations exhibiting similar scaling relations) allows the use of sensitive pattern metrics, but more work is needed to understand the actual patterns represented by multiscale domains. The objective of this study was to improve the interpretation of scale-dependent patterns represented by multiscale domains. Using maps of tree cover disturbance covering North American forest biomes from 2000 to 2012, each 0.09-ha location was described by the proportion and contagion of disturbance in its neighborhood, for 10 neighborhood extents from 0.81 ha to 180 km2. A k-means analysis identified 13 disturbance profiles based on the similarity of disturbance proportion and contagion across neighborhood extent. A wall to wall map of multiscale domains was produced by assigning each location (disturbed and undisturbed) to its nearest disturbance profile in multiscale pattern space. The multiscale domains were interpreted as representing two aspects of local patterns – the proximity of a location to disturbance, and the interior-exterior relationship of a location relative to nearby disturbed areas.Ye

    “Body goals”: Exposure to idealized, popular media images can affect body satisfaction ratings

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    College students are exposed to media many times throughout their day. Studies have shown that there are many negative correlations between students and their comparison of their bodies to others. In this study, it was tested to see if viewing mass media images for a while can affect the way people rate their body satisfaction and whether or not they would change their body. There were 20 people tested in this study. There were 10 people in the control group, and 10 people in the experimental group. The experimental group was required to watch a slideshow with 4 different pictures of health magazine covers then take a short body satisfaction survey, whereas the control group just completed the survey. It was found that there was no significance between the two groups and their group means were basically the same. Lack of significance could be caused by the small sample size or lack of time spent looking at the media images. This study can be built on in the future to add more people and expand to a more diverse sampling. In general, this study has not compared to other studies on the same topic but the method can be used to form a different study

    Patterns of disturbance at multiple scales in real and simulated landscapes

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    We describe a framework to characterize and interpret the spatial patterns of disturbances at multiple scales in socio-ecological systems. Domains of scale are defined in pattern metric space and mapped in geographic space, which can help to understand how anthropogenic disturbances might impact biodiversity through habitat modification. The approach identifies typical disturbance ’profiles’ based on the similarity of trajectories in a pattern metric space over a range of spatial scales. When different profiles are coherent in pattern metric space, they describe a regional spatial pattern. The divergence of a profile indicates a scale-dependent transition to a local spatial pattern, which can be examined for correspondence to different regions of geographic space. We illustrate the conceptual model with simulated maps and real disturbance maps from satellite imagery in south Italy. The results suggest that management of disturbances in the study region depend less on local drivers of disturbance and more on broader-scale drivers within the socio-ecological framework

    Disturbance patterns in a socio-ecological system at multiple scales

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    Ecological systems with hierarchical organization and non-equilibrium dynamics require multiple-scale analyses to comprehend how a system is structured and to formulate hypotheses about regulatory mechanisms. Characteristic scales in real landscapes are determined by, or at least reflect, the spatial patterns and scales of constraining human interactions with the biophysical environment. If the patterns or scales of human actions change, then the constraints change, and the structure and dynamics of the entire socioecological system (SES) can change accordingly. Understanding biodiversity in a SES requires understanding how the actions of humans as a keystone species shape the environment across a range of scales. We address this problem by investigating the spatial patterns of human disturbances at multiple scales in a SES in southern Italy. We describe an operational framework to identify multi-scale profiles of short-term anthropogenic disturbances using a moving window algorithm to measure the amount and configuration of disturbance as detected by satellite imagery. Prevailing land uses were found to contribute in different ways to the disturbance gradient at multiple scales, as land uses resulted from other types of biophysical and social controls shaping the region. The resulting profiles were then interpreted with respect to defining critical support regions and scale-dependent models for the assessment and management of disturbances, and for indicating system fragility and resilience of socio-ecological systems in the region. The results suggest support regions and scale intervals where past disturbance has been most likely and clumped - i.e. where fragility is highest and resilience is lowest. We discuss the potential for planning and managing landscape disturbances with a predictable effect on ecological processes. (c) 2006 Elsevier B.V. All rights reserved

    Forest fragmentation in Massachusetts, USA: a town-level assessment using Morphological spatial pattern analysis and affinity propagation

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    Forest fragmentation has been studied extensively with respect to biodiversity loss, disruption of ecosystem services, and edge effects although the relationship between forest fragmentation and human activities is still not well understood. We classified the pattern of forests in Massachusetts using fragmentation indicators to address these objectives: 1) characterize the spatial pattern of forest fragmentation in Massachusetts towns using Morphological Spatial Pattern Analysis (MSPA); and (2) identify regional trends using archetypal towns in relation to town history, geography and socioeconomic characteristics. Six fragmentation indicators were calculated using MSPA for each town to represent patterns and processes of fragmentation. We then used these indicators and the proportion of forested land to group towns across Massachusetts with similar patterns of fragmentation. Six representative towns typify different types of forest fragmentation, and illustrate the commonalities and differences between different fragmentation types. The objective selection of representative towns suggests that they might be used as the target of future studies, both in retrospective studies that seek to explain current patterns and in analyses that predict future fragmentation trends

    Representative Landscapes in the Forested Area of Canada

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    Canada is a large nation with forested ecosystems that occupy over 60% of the national land base, and knowledge of the patterns of Canada’s land cover is important to proper environmental management of this vast resource. To this end, a circa 2000 Landsat-derived land cover map of the forested ecosystems of Canada has created a new window into understanding the composition and configuration of land cover patterns in forested Canada. Strategies for summarizing such large expanses of land cover are increasingly important, as land managers work to study and preserve distinctive areas, as well as to identify representative examples of current land-cover and land-use assemblages. Meanwhile, the development of extremely efficient clustering algorithms has become increasingly important in the world of computer science, in which billions of pieces of information on the internet are continually sifted for meaning for a vast variety of applications. One recently developed clustering algorithm quickly groups large numbers of items of any type in a given data set while simultaneously selecting a representative—or “exemplar”—from each cluster. In this context, the availability of both advanced data processing methods and a nationally available set of landscape metrics presents an opportunity to identify sets of representative landscapes to better understand landscape pattern, variation, and distribution across the forested area of Canada. In this research, we first identify and provide context for a small, interpretable set of exemplar landscapes that objectively represent land cover in each of Canada’s ten forested ecozones. Then, we demonstrate how this approach can be used to identify flagship and satellite long-term study areas inside and outside protected areas in the province of Ontario. These applications aid our understanding of Canada’s forest while augmenting its management toolbox, and may signal a broad range of applications for this versatile approach
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