The majority of landscape pattern studies are based on the patch-mosaic paradigm, in which habitat patches are the basic unit of the analysis. While many patch-based landscape indices successfully relate spatial patterns to ecological processes, it is also desirable to use finer grained analyses for understanding species presence, abundance, and movement patterns across the landscape and to describe spatial context by measuring habitat change across scales. Here, we introduce two multi-scale pixel-based approaches for spatial pattern analysis, which quantify the spatial context of each pixel in the landscape. Both approaches summarize the proportion of habitat at increasing window sizes around each pixel in a scalogram. In the first regressionbased approach, a third-order polynomial is fitted to the scalogram of each pixel, and the four polynomial coefficients are used as descriptors of spatial context of each pixel within the landscape mosaic. In the second shape-based approach, the scalogram mean and standard deviation, and the mean slope between forest cover at the smallest window size and each of the larger window sizes are calculated. The values emerging from these two approaches are assigned to each focal pixel and can be used as predictive variables, for example, in species presence and abundance studies. We tested the performance of these approaches on 18 random landscapes and nine actual landscapes with varying forest habitat cover. Results show that both methods were able to differentiate between several spatial contexts. We thus suggest that these approaches could serve as a complement or an alternative to existing methods for landscape pattern analysis and possibly add further insight into pattern-species relations.
File: BarMassada_LE_2010.pdf
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Housing growth has been widely shown to be negatively correlated with wildlife populations, avian richness, anadromous fish, and exotic invasion. Zoning is the most frequently used public policy to manage housing development and is often motivated by a desire to protect the environment. Zoning is also pervasive, taking place in all 50 states. One relevant question that has received little research concerns the effectiveness of zoning to meet ecological goals. In this paper, we examined whether minimum frontage zoning policies have made a positive impact on the lakes they were aimed to protect in Vilas County, Wisconsin, USA. We used an economic model that estimated when a given lot will be subdivided and how many new lots will be created as a function of zoning. Using the economic model, we simulated the effects of multiple zoning scenarios on lakeshore development. The simulated development patterns were then input to ecological models that predicted the amount of coarse woody debris (CWD) and the growth rate of bluegills as a function of residential density. Comparison of the ecological outcomes under different simulated zoning scenarios quantified the effect of zoning policies on residential density, CWD, and bluegill growth rates. Our results showed that zoning significantly affected residential density, CWD counts, and bluegill growth rates across our study area, although the effect was less clear at the scale of individual lake. Our results suggest that homogeneous zoning (i.e., for a county) is likely to have mixed results when applied to a heterogeneous landscape. Further, our results suggest that zoning regimes with a higher minimum shoreline frontage are likely to have larger ecological effects when applied to lakes that are less developed.
File: Butsic_etal_2010.pdf
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Glossy privet (Ligustrum lucidum) is a tree native to China that successfully invades forests of central Argentina. To fully understand glossy privet's ecological effects on native forest, it is necessary to accurately map the distribution of glossy privet stands and the changes in biodiversity and forest structure of the invaded areas. The objectives of this paper were (1) to map the distribution of glossy privet stands in an area representative of the Sierras Chicas (Co'rdoba, Argentina) and (2) compare composition, structure and regeneration between glossy privet invaded stands and native forest stands. Using four Landsat TM images (October 2005, March, May and July 2006) we mapped the distribution of a glossy privet-dominated stand using a support vector machine, a non-parametric classifier. We recorded forest structure variables and tree diversity on 105 field plots. Glossy privet-dominated stands occupied 3,407 ha of the total forested land in the study area (27,758 ha), had an average of 33 glossy privet trees (dbh[2.5 cm) per plot and the cover of their shrub and herb strata was substantially reduced compared with native forest. Forest regeneration was dominated by glossy privet in native forest stands adjacent to glossy privet-dominated stands. We conclude that in the Sierras Chicas glossy privet has become a widespread invader, changing the patterns of vertical structure, diversity, and regeneration in native forests.
File: Hoyos_etal_BiologicalInvasions2010.pdf
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Housing growth is a primary form of landscape change that is occurring throughout the world. Because of the ecological impacts of housing growth, understanding the patterns of growth over time is imperative in order to better inform land use planning, natural resource management, and conservation. Our primary goal was to quantify hotspots of housing growth in the North Central United States over a 60-year time frame (1940-2000) using a spatial statistical approach. Specifically, our objectives were to: (1) determine where housing growth hotspots exist; (2) determine if hotspots are changing in space and over time; and, (3) investigate if hotspots differ based upon the type of measurement and scale of analysis. Our approach was based on a spatial statistical framework (Getis-Ord G* statistic) that compared local housing growth patterns with regional growth rates. Over the 60-year period the number and mean area of hotspots, measured both as absolute and percent growth, remained largely constant. However, total area of all hotspots increased significantly over time as measured by absolute growth. Spatially, the hotspots shifted over time and exhibited different patterns based upon the measurement. Absolute growth hotspots exhibited patterns of expanding sets of rings around urban centers, whereas percent growth hotspots exhibited both expanding rings and shifting locations throughout rural locations. When increasing the neighborhood size used to discern hotspots from 5 to 50 km, the number of hotspots decreased while their size increased. Regardless of neighborhood size, ~95 and ~88% of the landscape, as measured by absolute and percent growth, respectively, never contained a hotspot. Overall our results indicate that housing growth is occurring at distinct locations on the landscape, which change in space and time, and are influenced by the scale of analysis and type of measure. In general these results provide useful information for the natural resource, planning, and policy communities.
File: Lepczyk et al 2007 Landscape Ecology.pdf
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File: Radeloff_etal_Oikos2000.pdf
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Measures of image texture derived from remotely sensed imagery have proven useful in many applications. However, when using multitemporal imagery or multiple images to cover a large study area, it is important to understand how image texture measures are affected by surface phenology. Our goal was to characterize the robustness to phenological variation of common first- and second-order texture measures of satellite imagery. Three North American study sites were chosen to represent different biomes. At each site, a suite of image textures were calculated for three to four dates across the growing season. Texture measures were compared among dates to quantify their stability, and the stability of measures was also compared between biomes. Interseasonal variability of texture measures was high overall indicating that care must be taken when using measures of texture at different phenological stages. Certain texture measures, such as first-order mean and entropy, as well as second-order homogeneity, entropy, and dissimilarity, were more robust to phenological change than other measures
File: Culbert_etal_IEEE_JSTARS_2010_0.pdf
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Natural resource amenities may be an attractor as people decide where they will live and invest in property. In the American Midwest these amenities range from lakes to forests to pastoral landscapes, depending on the ecological province. We used simple linear regression models to test the hypotheses that physiographic, land cover (composition and spatial pattern), forest characteristics, land use on undeveloped land, public ownership, soil productivity and proximity to urban centers predict changes in population, housing, and seasonal housing densities over a 10-year interval (1980-1990). We then generated multiple-regression models to predict population, total and seasonal housing density change in the most recent decade (1990- 2000) based on ownership and ecological conditions in 1990 and tested them by comparing the predictions to actual change measured by the US Census Bureau. Our results indicate that the independent variables explained between 25 and 40% of the variability in population density change, 42-67% of the variability of total housing density change, and 13-32% of the variability in seasonal housing density change in the 1980s, depending on the province. The strength of the relationships between independent and dependent variables varied by province, and in some cases the sign varied as well. Topographic relief was significantly related to population growth in all provinces, and land cover composition and the presence of water was significantly related to total housing growth in all provinces. There was a surprisingly limited association of any of the independent variables to seasonal housing growth in the northern province, which is commonly perceived to attract seasonal use because of ecological amenities. Proximity to urban centers is related to population and housing density change, but not seasonal housing density change. Our tests indicated that models for population density change showed some utility, but the models for total and seasonal housing density generally performed poorly. Ecologic variables were consistently poor at predicting seasonal housing density change. Our results show that environmental characteristics appear to have some influence on the spatial distribution of population and housing change in the Midwest, although other factors that were not modeled are clearly dominant.
File: Gustafson_etal_LE_2005.pdf
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Eastern Europe provides unique opportunities to study changes in land use patterns, because much farmland became parcelized in the post-socialist period (i.e. large fields were broken up into smaller ones). Classification-based remote sensing approaches, however, do not capture such land cover modifications and new approaches based on continuous indicators are needed. Our goal is to develop a novel method to map farmland field size based on image texture.We fitted linear regression models to relate field size to Landsat-based image texture for a study area in the border region of Poland, Slovakia and Ukraine. Texture explained up to 93% of the variability in field size. Our field size map revealed marked differences among countries and these differences appear to be related to socialist land-ownership patterns and post-socialist land reform strategies. Image texture has great potential for mapping land use patterns and may contribute to a better understanding of land cover modifications in Eastern Europe and elsewhere.
File: Kuemmerle-etal_2009_JLUS_2.pdf
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In the present study,we examine housing growth in California, Oregon, andWashington in the wildland-urban interface (WUI), the area where homes and other structures abut or intermingle with wildland vegetation. We combine housing density information from the 1990 and 2000 USA censuses with land cover information from the 1992/93 National Land Cover Dataset to demarcate the location and extent of the WUI and its growth, both in terms of area and number of housing units during the 1990s.We overlay the WUI with coarse-scale fire regime condition class information to evaluate implications for wildland fire management. During the 1990s, WUI area in the three-state region increased by 5218 km2 (10.9%) to nearly 53 000 km2 and the number of housing units in the WUI increased over 1 million units (17.6%) and in 2000 encompassed 6.9 million units, 43% of all housing in the region. Over a million new homes were constructed in the WUI, comprising 61% of the new homes constructed in the region. By 2000, there was far more intermixWUI (75% of the WUI area and 64% of the WUI housing units) than interface WUI. Expansion of the WUI accounted for only 13% of WUI housing unit growth and WUI that existed in 1990 encompassed 98% of WUI housing units in 2000. In 2000, there were nearly 1.5 million WUI housing units in areas with 0-35-year fire return intervals and 3.4 million in areas with 35-100+ year fire return intervals. In both these fire regimes, the majority of WUI housing units (66% and 90% respectively) are in areas with a current condition outside the historic range of variability. Housing growth patterns in this three-state region are exacerbating wildland fire problems in the WUI. Any long-term solution to wildland fire issues in the western United States will have to address housing growth patterns. Using a consistent, nationally applicable assessment protocol, the present study reveals the vast extent of WUI in the west coast states and its growth in the 1990s, and provides a foundation for consistent monitoring efforts.
File: Hammer_etal_IJWF_2007.pdf
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Finding a balance between strict protection and multiple use requires data on wildlife survival in human-managed ecosystems. We examined the habitat use and species composition of mammals = 2 kg in size inhabiting an agroforest ecosystem neighboring a park in the Peruvian Amazon. First, we recorded wildlife presence in fields, fallows, and forests within one settlement over a 9-month period. Then we monitored wildlife presence over 21 months in 42 fields across a 65-km transect, including remote and highly disturbed sites. We tested for correlations between the size and number of mammal species visiting fields and human activities measured at different scales. Hunting intensity more powerfully predicted the average biomass and species diversity observed in fields than did vegetation disturbance. The number of commercial hunters in the surrounding community had a stronger impact than did the individual field owner's hunting intensity. Large-bodied species appeared only in remote farms neighboring uninhabited areas in the reserve, indicating that undisturbed forests act as sources for wildlife dispersing into agricultural regions. Farmers in these remote areas experience greater crop and livestock losses to wildlife, but by hunting large game they are able to offset losses with bushmeat gains. In more disturbed areas, crop losses exceeded bushmeat gains, although both occurred at negligible levels. Our case study suggests that large herbivores, large carnivores, and most primates are unlikely to persist in multiple-use zones in Amazonian forests unless hunting is effectively restricted. Even highly disturbed agroforests are not empty of wildlife, however, but are inhabited by a suite of adaptable, fast-reproducing species able to withstand human activity (e.g., brown agoutis [ Dasyprocta variegata ], armadillos [ Dasypus novemcinetus ], and red brocket deer [ Mazama gauazoubira ]). These weedy species may not be of immediate concern to conservation biologists, and they will not attract tourists. But they have both economic and ecological value and deserve to be taken into account in management decisions.
File: Naughton_etal_ConsBio2003.pdf
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