Spatiotemporal pattern of urbanization in Shanghai, China between 1989 and 2005

Quantifying the spatiotemporal pattern of urbanization is necessary to understand urban morphology and its impacts on biodiversity and ecological processes, and thus can provide essential information for improving landscape and urban planning. Recent studies have suggested that, as cities evolve, certain general patterns emerge along the urban–rural gradient although individual cities always differ in details. To help better understand these generalities and idiosyncrasies in urbanization patterns, we analyzed the spatiotemporal dynamics of the Shanghai metropolitan area from 1989 to 2005, based on landscape metrics and remote sensing data. Specifically, the main objectives of our study were to quantitatively characterize the spatiotemporal patterns of urbanization in Shanghai in recent decades, identify possible spatial signatures of different land use types, and test the diffusion coalescence hypotheses of urban growth. We found that, similar to numerous cities around the world reported in previous studies, urbanization increased the diversity, fragmentation, and configurational complexity of the urban landscape of Shanghai. In the same time, however, the urban–rural patterns of several land use types in Shanghai seem unique—quite different from previously reported patterns. For most land use types, each showed a distinctive spatial pattern along a rural–urban transect, as indicated by landscape metrics. Furthermore, the urban expansion of Shanghai exhibited an outward wave-like pattern. Our results suggest that the urbanization of Shanghai followed a complex diffusion–coalescence pattern along the rural–urban transect and in time.     

Riparian influences on stream fish assemblage structure in urbanizing streams

We assessed the influence of land cover at multiple spatial extents on fish assemblage integrity, and the degree to which riparian forests can mitigate the negative effects of catchment urbanization on stream fish assemblages. Riparian cover (urban, forest, and agriculture) was determined within 30 m buffers at longitudinal distances of 200 m, 1 km, and the entire network upstream of 59 non-nested fish sampling locations. Catchment and riparian land cover within the upstream network were highly correlated, so we were unable to distinguish between those variables. Most fish assemblage variables were related to % forest and % urban land cover, with the strongest relations at the largest spatial extent of land cover (catchment), followed by riparian land cover in the 1-km and 200-m reach, respectively. For fish variables related to urban land cover in the catchment, we asked whether the influence of riparian land cover on fish assemblages was dependent on the amount of urban development in the catchment. Several fish assemblage metrics (endemic richness, endemic:cosmopolitan abundance, insectivorous cyprinid richness and abundance, and fluvial specialist richness) were all best predicted by single variable models with % urban land cover. However, endemic:cosmopolitan richness, cosmopolitan abundance, and lentic tolerant abundance were related to % forest cover in the 1-km stream reach, but only in streams that had <15% catchment urban land cover. In these cases, catchment urbanization overwhelmed the potential mitigating effects of riparian forests on stream fishes. Together, these results suggest that catchment land cover is an important driver of fish assemblages in urbanizing catchments, and riparian forests are important but not sufficient for protecting stream ecosystems from the impacts of high levels of urbanization.     

Improved methods for quantifying potential nutrient interception by riparian buffers

Efforts to quantify the effects of riparian buffers on watershed nutrient discharges have been confounded by a commonly used analysis, which estimates buffer potential as the percentage of forest or wetland within a fixed distance of streams. Effective landscape metrics must instead be developed based on a clear conceptual model and quantified at the appropriate spatial scale. We develop new metrics for riparian buffers in two stages of increasing functional specificity to ask: (1) Which riparian metrics are more distinct from measures of whole watershed land cover? (2) Do functional riparian metrics provide different information than fixed-distance metrics? (3) How do these patterns vary within and among different physiographic settings? Using publicly available geographic data, we studied 503 watersheds in four different physiographic provinces of the Chesapeake Bay Drainage. In addition to traditional fixed-distance measures, we calculated mean buffer width, gap frequency, and measures of variation in buffer width using both “unconstrained” metrics and “flow-path” metrics constrained by surface topography. There were distinct patterns of relationship between watershed and near-stream land cover in each physiographic province and strong correlations with watershed land cover confounded fixed-distance metrics. Flow-path metrics were more independent of watershed land cover than either fixed-distance or unconstrained measures, but both functional metrics provided greater detail, interpretability, and flexibility than the fixed-distance approach. Potential applications of the new metrics include exploring the potential for land cover patterns to influence water quality, accounting for buffers in statistical nutrient models, quantifying spatial patterns for process-based modeling, and targeting management actions such as buffer restoration.     

Landscape characteristics affecting streams in urbanizing regions of the Delaware River Basin (New Jersey,New York,and Pennsylvania,U.S.)

Widespread and increasing urbanization has resulted in the need to assess, monitor, and understand its effects on stream water quality. Identifying relations between stream ecological condition and urban intensity indicators such as impervious surface provides important, but insufficient information to effectively address planning and management needs in such areas. In this study we investigate those specific landscape metrics which are functionally linked to indicators of stream ecological condition, and in particular, identify those characteristics that exacerbate or mitigate changes in ecological condition over and above impervious surface. The approach used addresses challenges associated with redundancy of landscape metrics, and links landscape pattern and composition to an indicator of stream ecological condition across a broad area of the eastern United States. Macroinvertebrate samples were collected during 2000–2001 from forty-two sites in the Delaware River Basin, and landscape data of high spatial and thematic resolution were obtained from photointerpretation of 1999 imagery. An ordination-derived ‘biotic score’ was positively correlated with assemblage tolerance, and with urban-related chemical characteristics such as chloride concentration and an index of potential pesticide toxicity. Impervious surface explained 56% of the variation in biotic score, but the variation explained increased to as high as 83% with the incorporation of a second land use, cover, or configuration metric at catchment or riparian scales. These include land use class-specific cover metrics such as percent of urban land with tree cover, forest fragmentation metrics such as aggregation index, riparian metrics such as percent tree cover, and metrics related to urban aggregation. Study results indicate that these metrics will be important to monitor in urbanizing areas in addition to impervious surface.     

Temporal (1958–1993) and spatial patterns of land use changes in Haut-Saint-Laurent (Quebec, Canada) and their relation to landscape physical attributes

In the last few years, landscape researchers have sought to understand temporal and spatial patterns of landscape changes in order to develop comprehensive models of land cover dynamics. To do so, most studies have used similar methods to quantify structural patterns, usually by comparing various landscape structural indices through time. Whereas the necessity for complementary approaches which might provide insights into landscape dynamics at some finer scale relevant to local managers has been expressed, few studies have proposed alternative methodologies. Moreover, the important relationship between the physical constraints of the landscape and land use dynamics has been seldom emphasized. Here we propose a methodological outline which was applied to the study of a rural landscape of Southern Quebec, Canada, to detect spatial and temporal (1958 to 1993) patterns of land cover changes at field, patch and landscape level. We then relate these patterns to the underlying physical structure of landscape elements using GIS and canonical correspondence analyses. We use the different geomorphological deposit types as stable discriminant factors which may constrain land use.Canonical correspondence analyses showed relations of land use and land use changes to the physical attributes of the landscape elements, whereas spatial analyses revealed very dynamic patterns at finer spatial and temporal scales. They highlighted the fact that not only the physical attributes of the landscape elements but also their spatial configuration were important determinants of land use dynamics in this area. Thus more land use changes occurred at the boundary between geomorphological deposit types than in any other locations. This trend is apparent for specific small-size changes (e.g. forest to crop), but not for the large-size ones (e.g. abandoned land to forest). Although land use changes are triggered by socioeconomic forces in this area, these changes are nevertheless constrained by the underlying physical landscape structure. A thorough comprehension of historical changes will enhance our capability to predict future landscape dynamics and devise more effective landscape management strategies.     

Land Use – Land Cover Conversion, Regeneration and Degradation in the High Elevation Bolivian Andes

Regional land-cover change affects biodiversity, hydrology, and biogeochemical cycles at local, watershed, and landscape scales. Developing countries are experiencing rapid land cover change, but assessment is often restricted by limited financial resources, accessibility, and historical data. The assessment of regional land cover patterns is often the first step in developing conservation and management plans. This study used remotely sensed land cover and topographic data (Landsat and Shuttle Radar Topography Mission), supervised classification techniques, and spectral mixture analysis to characterize current landscape patterns and quantify land cover change from 1985 to 2003 in the Altiplano (2535–4671 m) and Intermediate Valley (Mountain) (1491–4623 m) physiographic zones in the Southeastern Bolivian Andes. Current land cover was mapped into six classes with an overall accuracy of 88% using traditional classification techniques and limited field data. The land cover change analysis showed that extensive deforestation, desertification, and agricultural expansion at a regional scale occurred in the last 20 years (17.3% of the Mountain Zone and 7.2% of the Altiplano). Spectral mixture analysis (SMA) indicated that communal rangeland degradation has also occurred, with increases in soil and non-photosynthetic vegetation fractions in most cover classes. SMA also identified local areas with intensive management activities that are changing differently from the overall region (e.g., localized areas of increased green vegetation). This indicates that actions of local communities, governments, and environmental managers can moderate the potentially severe future changes implied by the results of this study.     

Landscape changes and ecological studies in agricultural regions,Québec,Canada

Most landscape definitions in the western world are based on soil, climatic, or physiographic features and do not integrate humans as an integral part of the landscape. We present an approach where landscape types have been delineated in southern Québec, Canada based on current land use where anthropogenic and agricultural activities are concentrated as a practical application of the holistic approach in landscape definition. Landsat-TM satellite images were classified and the 27 habitat classes were regrouped into 5 general land cover classes (cash crop, dairy farming, forest, anthropogenic, wetlands) and overlaid onto soil landscape polygons to characterize natural boundary units. Cluster analyses were used to aggregate these polygons into seven agricultural types of land scape forming a gradient from urban and high-intensity cash crop farming activities to landscapes dominated by a mosaic of agriculture and forested areas. Multivariate analyses of raw data and of socio-economic and farming practices variables were used to describe the defined types of landscape and these were projected over three established land classification systems of southern Québec (Canadian ecoregions, North American Bird Conservation Initiative regions and Corn Heat Unit regions) to compare their similarity in terms of land cover and for planning of future ecological studies. Because agricultural landscapes are highly dynamic, they are bound to undergo changes in the near future. Our landscape delineation may serve as an experimental setup where land scape dynamics and wildlife populations and community structures could be monitored. Because the information we used to delineate and characterize agricultural landscape types is readily available in other countries, our approach could easily be adapted to similar data sources under and a wide variety of landscape types. This revised version was published online in July 2006 with corrections to the Cover Date.     

Impact of data integration technique on historical land-use/land-cover change: Comparing historical maps with remote sensing data in the Belgian Ardennes

Historical reconstructions of land-use/cover change often require comparing maps derived from different sources. The objective of this study was to measure land-use/cover changes over the last 225 years at the scale of a Belgian landscape, Lierneux in Ardennes, on the basis of a heterogeneous time series of land cover data. The comparability between the land-cover maps was increased following a method of data integration by map generalisation. Two types of time series were built by integrating the maps either by reference to the initial map of the time series or by pair of successive maps. Land-cover change detection was performed on the initial time series without data integration and on the two types of integrated time series. Results reveal that land cover and landscape structure have been subject to profound changes in Lierneux since 1775, with an annual rate of change at the landscape level of up to 1.40%. The major land-cover change processes observed are expansion of grasslands-croplands and reforestation with coniferous species, leading to amore fragmented landscape structure. The annual rates of land-cover change estimated from integrated data are significantly different from the annual rates of change estimated without a prior integration of the data. There is a trade-off between going as far back in time as possibleversus performing change detection as accurately as possible. This revised version was published online in July 2006 with corrections to the Cover Date.     

Socioeconomics drive woody invasive plant richness in New England, USA through forest fragmentation

Woody invasive plants are an increasing component of the New England flora. Their success and geographic spread are mediated in part by landscape characteristics. We tested whether woody invasive plant richness was higher in landscapes with many forest edges relative to other forest types and explained land use/land cover and forest fragmentation patterns using socioeconomic and physical variables. Our models demonstrated that woody invasive plant richness was higher in landscapes with more edge forest relative to patch, perforated, and especially core forest types. Using spatially-explicit, hierarchical Bayesian, compositional data models we showed that infrastructure and physical factors, including road length and elevation range, and time-lagged socioeconomic factors, primarily population, help to explain development and forest fragmentation patterns. Our social–ecological approach identified landscape patterns driven by human development and linked them to increased woody plant invasions. Identifying these landscape patterns will aid ongoing efforts to use current distribution patterns to better predict where invasive species may occur in unsampled regions under current and future conditions.     

Modeling scale-dependent landscape pattern,dispersal, and connectivity from the perspective of the organism

Understanding the impacts of habitat fragmentation on dispersal is an important issue in landscape and conservation ecology. Here I examine the effects of fine- to broad-scale patterns in landscape structure on dispersal success of organisms with differing life-history traits. An individual-based model was used to simulate dispersal of amphibian-like species whose movements were driven by land cover and moisture conditions. To systematically control spatial pattern, a landscape model was created by merging simulated land cover maps with synthetic topographic surfaces. Landscapes varied in topographic roughness and spatial contagion in agriculture and urban land cover. Simulations included three different species types that varied in their maximum potential dispersal distances by 1-, 2-, or 4-fold. Two sets of simulations addressed effects of varying aspects of landscape structure on dispersal success. In the first set of simulations, which incorporated variable distances between breeding patches, dispersal success was lowest for all species types when anthropogenic cover was patchily distributed. In the second set, with interpatch distances held constant as landscape composition varied, dispersal success decreased as anthropogenic cover became spatially contagious. Both sets revealed strong main effects of species characteristics, interpatch distances and landscape composition on dispersal success; furthermore, scale-dependent patterns in land cover and moisture gradients had a stronger effect on longer- than shorter-ranging species types. Taken together, these simulations suggest that heuristic conservation strategies could potentially be developed based on important but limited life history information.     

Biodiversity is associated with indicators of soil ecosystem functions over a landscape gradient of agricultural intensification

Agricultural intensification has led to dramatic losses in biodiversity over the past several decades. Many studies have shown the effects of intensification on vegetation or soil communities at field or local scales. However, the functional significance of biodiversity may only appear at larger spatial and temporal scales, due to exchanges among local ecosystems throughout a landscape. To examine how patterns of biodiversity loss are reflected at larger spatial scales, plant and soil biodiversity and associated indicators of ecosystem functions were assessed in riparian areas over a 150 km² agricultural landscape in the Sacramento Valley of California. Publicly-available GIS data were first used to classify and select sites over the range of soils, topography and plant community types. Representative sites from the landscape were sampled for soil physiochemical properties, as well as microbial, nematode, and plant communities. Higher agricultural intensification, based on field and landscape indices, was negatively correlated with richness and diversity of plant and soil taxa, and was related to indicators of ecosystem functions, such as increased soil nitrate and phosphorus loading, decreased riparian health ratings, and lower soil carbon, soil microbial biomass and soil food web structure. Both field- and landscape-scale factors played important roles in the measured losses. The study area was composed of a wide array of soils, vegetation, and land management, indicating that the observed trends transcended site-specific conditions.     

Uncertainties in global-scale reconstructions of historical land use: an illustration using the HYDE data set

Land use and land-use change play an important role in global integrated assessments. However, there are still many uncertainties in the role of current and historical land use in the global carbon cycle as well as in other dimensions of global environmental change. Although databases of historical land use are frequently used in integrated assessments and climate studies, they are subject to considerable uncertainties that often are ignored. This paper examines a number of the most important uncertainties related to the process of reconstructing historical land use. We discuss the origins of different types of uncertainty and the sensitivity of land-use reconstructions to these uncertainties. The results indicate that uncertainties not only arise as result of the large temporal and spatial variation in historical population data, but also relate to assumptions on the relationship between population and land use used in the reconstructions. Improving empirical data to better specify and validate the assumptions about the relationship between population and land use, while accounting for the spatial and temporal variation, could reduce uncertainties in the reconstructions. Such empirical evidence could be derived from local case studies, such as those conducted in landscape ecology, environmental history, archeology and paleoecology.     

Effects of changing landscape pattern and U. S. G. S. land cover data variability on ecoregion discrimination across a forest-agriculture gradient

We examined the use of coarse resolution land cover data (USGS LUDA) to accurately discriminate ecoregions and landscape-scale features important to biodiversity monitoring and management. We used land cover composition and landscape indices, correlation and principal components analysis, and comparison with finer-grained Landsat TM data, to assess how well LUDA data discriminate changing patterns across an agriculture-forest gradient in Minnesota, U.S.A. We found LUDA data to be most accurate at general class levels of agriculture and forest dominance (Anderson Level I), but in consistent and limited in ecotonal areas of the gradient and within forested portions of the study region at finer classes (Anderson Level II). We expected LUDA to over-represent major (matrix) cover types and under-represent minor types, but this was not consistent with all classes. 1) Land cover types respond individualistically across the gradient, changing landscape grain as well as their spatial distribution and abundance. 2) Agriculture is not over-represented where it is the dominant land cover type, but forest is over-represented where it is dominant. 3) Individual forest types are under-represented in an open land matrix. 4) Within forested areas, mixed deciduous-coniferous forest is over-represented by several orders of magnitude and the separate conifer and hardwood types under-represented. Across gradual, transitional agriculture-forest areas, LUDA cover class dominance changes abruptly in a stair-step fashion. In general, rare cover types that are discrete, such as forest in agriculture or wetlands or water in forest, are more accurately represented than cover classes having lower contrast with the matrix. Northward across the gradient, important changes in the proportions of conifer and deciduous forest mixtures occur at scales not discriminated by LUDA data. Results suggest that finer-grained data are needed to map within-state ecoregions and discriminate important landscape characteristics. LUDA data, or similar coarse resolution data sources, should be used with caution and the biases fully understood before being applied in regional landscape management. This revised version was published online in July 2006 with corrections to the Cover Date.     

Land-use and land-cover dynamics in response to changes in climatic,biological and socio-political forces: the case of southwestern Ethiopia

Few studies of land-use/land-cover change provide an integrated assessment of the driving forces and consequences of that change, particularly in Africa. Our objectives were to determine how driving forces at different scales change over time, how these forces affect the dynamics and patterns of land use/land cover, and how land-use/land-cover change affects ecological properties at the landscape scale. To accomplish these objectives, we first developed a way to identify the causes and consequences of change at a landscape scale by integrating tools from ecology and the social sciences and then applied these methods to a case study in Ghibe Valley, southwestern Ethiopia. Maps of land-use/land-cover change were created from aerial photography and Landsat TM imagery for the period, 1957–1993. A method called `ecological time lines' was developed to elicit landscape-scale explanations for changes from long-term residents. Cropland expanded at twice the speed recently (1987–1993) than two decades ago (1957–1973), but also contracted rapidly between 1973–1987. Rapid land-use/land cover change was caused by the combined effects of drought and migration, changes in settlement and land tenure policy, and changes in the severity of the livestock disease, trypanosomosis, which is transmitted by the tsetse fly. The scale of the causes and consequences of land-use/land-cover change varied from local to sub-national (regional) to international and the links between causes and consequences crossed scales. At the landscape scale, each cause affected the location and pattern of land use/land cover differently. The contraction of cropland increased grass biomass and cover, woody plant cover, the frequency and extent of savanna burning, and the abundance of wildlife. With recent control of the tsetse fly, these ecological changes are being reversed. These complex patterns are discussed in the context of scaling issues and current conceptual models of land-use/land-cover change.     

Effects of land use legacies and habitat fragmentation on salamander abundance

Context

Landscape modification is an important driver of biodiversity declines, yet we lack insight into how ongoing landscape change and legacies of historical land use together shape biodiversity.

Objectives

We examined how a history of agricultural land use and current forest fragmentation influence the abundance of red-backed salamanders (Plethodon cinereus). We hypothesized that historical agriculture and fragmentation cause changes in habitat quality and landscape structure that limit abundance.

Methods

We measured salamander abundance at 95 forested sites in New York, USA, and we determined whether sites were agricultural fields within the last five decades. We used a structural equation model to estimate relationships between historical agriculture and salamander abundance mediated by changes in forest vegetation, microclimate, and landscape structure.

Results

Historical agriculture affected salamander abundance by altering forest vegetation at a local scale and forest cover at a landscape scale. Abundance was lowest at post-agricultural sites with low woody vegetation, leaf litter depth, and canopy cover. Post-agricultural sites had limited forest cover in the surrounding landscape historically, and salamander abundance was positively related to historical forest cover, suggesting that connectivity to source populations affects colonization of regenerating forests. Abundance was also negatively related to current forest fragmentation.

Conclusions

Historical land use can have legacy effects on animal abundance on par with effects of ongoing landscape change. We showed that associations between animal abundance and historical land use can be driven by altered site conditions and surrounding habitat area, indicating that restoration efforts should consider local site conditions and landscape context.

     

Assessing landscape functional connectivity in a forest carnivore using path selection functions

Context

Understanding connectivity patterns in relation to habitat fragmentation is essential to landscape management. However, connectivity is often judged from expert opinion or species occurrence patterns, with very few studies considering the actual movements of individuals. Path selection functions provide a promising tool to infer functional connectivity from animal movement data, but its practical application remains scanty.

Objectives

We aimed to describe functional connectivity patterns in a forest carnivore using path-level analysis, and to explore how connectivity is affected by land cover patterns and road networks.

Methods

We radiotracked 22 common genets in a mixed forest-agricultural landscape of southern Portugal. We developed path selection functions discriminating between observed and random paths in relation to landscape variables. These functions were used together with land cover information to map conductance surfaces.

Results

Genets moved preferentially within forest patches and close to riparian habitats. Functional connectivity declined with increasing road density, but increased with the proximity of culverts, viaducts and bridges. Functional connectivity was favoured by large forest patches, and by the presence of riparian areas providing corridors within open agricultural land. Roads reduced connectivity by dissecting forest patches, but had less effect on riparian corridors due to the presence of crossing structures.

Conclusions

Genet movements were jointly affected by the spatial distribution of suitable habitats, and the presence of a road network dissecting such habitats and creating obstacles in areas otherwise permeable to animal movement. Overall, the study showed the value of path-level analysis to assess functional connectivity patterns in human-modified landscapes.

     

Patch-level based vegetation change and environmental drivers in Tarim River drainage area of West China

Information on vegetation-related land cover change and the principle drivers is critical for environmental management and assessment of desertification processes in arid environments. In this study, we investigated patch-level based changes in vegetation and other major land cover types in lower Tarim River drainage area in Xinjiang, West China, and examined the impacts of environmental factors on those changes. Patterns of land cover change were analyzed for the time sequence of 1987–1999–2004 based on satellite-derived land classification maps, and their relationships with environmental factors were determined using Redundancy Analysis (RDA). Environmental variables used in the analysis included altitude, slope, aspect, patch shape index (fractal dimension), patch area, distance to water body, distance to settlements, and distance to main roads. We found that during the study period, 26% of the land experienced cover changes, much of which were the types from the natural riparian and upland vegetation to other land covers. The natural riparian and upland vegetation patches were transformed mostly to desert and some to farmlands, indicating expanding desertification processes of the region. A significant fraction of the natural riparian and upland vegetation experienced a phase of alkalinity before becoming desert, suggesting that drought is not the exclusive environmental driver of desertification in the study area. Overall, only a small proportion of the variance in vegetation-related land cover change is explainable by environmental variables included in this study, especially during 1987–1999, indicating that patch-level based vegetation change in this region is partly attributable to environmental perturbations. The apparent transformation from the natural riparian and upland vegetation to desert indicates an on-going process of desertification in the region.     

Forest recovery in a tropical landscape: what is the relative importance of biophysical,socioeconomic, and landscape variables?

Socioeconomic changes in many areas in the tropics have led to increasing urbanization, abandonment of agriculture, and forest re-growth. Although these patterns are well documented, few studies have examined the drivers leading to landscape-level forest recovery and the resulting spatial structure of secondary forests. Land cover transitions from agricultural lands to secondary forest in the island of Puerto Rico have been ongoing since the 1940s. This study is a glimpse into this landscape level trend from 1991 to 2000. First, we relied on Landsat images to characterize changes in the landscape structure for forest, urban, and agricultural land classes. We found that although forest cover has increased in this period, forest has become increasingly fragmented while the area of urban cover has spread faster and become more clustered. Second, we used logistic regression to assess the relationship between the transition to forest and 21 biophysical, socioeconomic, and landscape variables. We found that the percentage of forest cover within a 100 m radius of a point, distance to primary roads and nature reserves, slope, and aspect are the most important predictors of forest recovery. The resulting model predicts the spatial pattern of forest recovery with accuracy (AUC-ROC = 0.798). Together, our results suggest that forest recovery in Puerto Rico has slowed down and that increasing pressure from urbanization may be critical in determining future landscape level forest recovery. These results are relevant to other areas in the tropics that are undergoing rapid economic development.     

Road Density and Landscape Pattern in Relation to Housing Density,and Ownership,Land Cover,and Soils

Roads are conspicuous components of landscapes and play a substantial role in defining landscape pattern. Previous studies have demonstrated the link between roads and their effects on ecological processes and landscape patterns. Less understood is the placement of roads, and hence the patterns imposed by roads on the landscape in relation to factors describing land use, land cover, and environmental heterogeneity. Our hypothesis was that variation in road density and landscape patterns created by roads can be explained in relation to variables describing land use, land cover, and environmental factors. We examined both road density and landscape patterns created by roads in relation to suitability of soil substrate as road subgrade, land cover, lake area and perimeter, land ownership, and housing density across 19 predominantly forested counties in northern Wisconsin, USA. Generalized least squares regression models showed that housing density and soils with excellent suitability for road subgrade were positively related to road density while wetland area was negatively related. These relationships were consistent across models for different road types. Landscape indices showed greater fragmentation by roads in areas with higher housing density, and agriculture, grassland, and coniferous forest area, but less fragmentation with higher deciduous forest, mixed forest, wetland, and lake area. These relationships provide insight into the complex relationships among social, institutional, and environmental factors that influence where roads occur on the landscape. Our results are important for understanding the impacts of roads on ecosystems and planning for their protection in the face of continued development.     

A comparison of satellite data and landscape variables in predicting bird species occurrences in the Greater Yellowstone Ecosystem,USA

We compare the accuracy of predicting the occurrence of 11 bird species in montane meadows of the Greater Yellowstone National Park ecosystem, in the states of Montana and Wyoming, USA. We used remotely sensed, landscape, and habitat data. The meadow type, as determined from the remotely sensed data, was highly correlated with abundances of six of the 11 bird species. Landscape variables significant in predicting occurrence were selected using a stepwise multiple regression for each bird species. These variables were then used in a multiple regression with the variable meadow type. As expected, the abundances of the generalist species (American Robin, Dark-eyed Junco, White-crowned Sparrow, Brewer's Blackbird, and Chipping Sparrow) were not strongly correlated with landscape variables or meadow type. Conversely, abundances of the Common Snipe, Common Yellowthroat, Lincoln's Sparrow, Savannah Sparrow, Vesper Sparrow, and Yellow Warbler were highly correlated with meadow type and landscape variables such as percent cover of willow (Salix spp.), graminoid, woody vegetation, sagebrush (Artemisia spp.), and graminoid and shrub biomass. The results from our study indicate that remotely sensed data are applicable for estimating potential habitats for bird species in the different types of montane meadows. However, to improve predictions about species in specific sites or areas, we recommend the use of additional landscape metrics and habitat data collected in the field.