978 resultados para Landscape variables


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Effects of roads on wildlife and its habitat have been measured using metrics, such as the nearest road distance, road density, and effective mesh size. In this work we introduce two new indices: (1) Integral Road Effect (IRE), which measured the sum effects of points in a road at a fixed point in the forest; and (2) Average Value of the Infinitesimal Road Effect (AVIRE), which measured the average of the effects of roads at this point. IRE is formally defined as the line integral of a special function (the infinitesimal road effect) along the curves that model the roads, whereas AVIRE is the quotient of IRE by the length of the roads. Combining tools of ArcGIS software with a numerical algorithm, we calculated these and other road and habitat cover indices in a sample of points in a human-modified landscape in the Brazilian Atlantic Forest, where data on the abundance of two groups of small mammals (forest specialists and habitat generalists) were collected in the field. We then compared through the Akaike Information Criterion (AIC) a set of candidate regression models to explain the variation in small mammal abundance, including models with our two new road indices (AVIRE and IRE) or models with other road effect indices (nearest road distance, mesh size, and road density), and reference models (containing only habitat indices, or only the intercept without the effect of any variable). Compared to other road effect indices, AVIRE showed the best performance to explain abundance of forest specialist species, whereas the nearest road distance obtained the best performance to generalist species. AVIRE and habitat together were included in the best model for both small mammal groups, that is, higher abundance of specialist and generalist small mammals occurred where there is lower average road effect (less AVIRE) and more habitat. Moreover, AVIRE was not significantly correlated with habitat cover of specialists and generalists differing from the other road effect indices, except mesh size, which allows for separating the effect of roads from the effect of habitat on small mammal communities. We suggest that the proposed indices and GIS procedures could also be useful to describe other spatial ecological phenomena, such as edge effect in habitat fragments. (C) 2012 Elsevier B.V. All rights reserved.

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The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

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Tsuga canadensis (eastern hemlock) is a highly shade-tolerant, late-successional, and long-lived conifer species found throughout eastern North America. It is most often found in pure or nearly pure stands, because highly acidic and nutrient poor forest floor conditions are thought to favor T. canadensis regeneration while simultaneously limiting the establishment of some hardwood species with greater nutrient requirements. Once a common species, T. canadensis is currently experiencing widescale declines across its range. The hemlock woolly adelgid (Adelges tsugae) is decimating the population across its eastern distribution. Across the Upper Great Lakes region, where the adelgid is currently being held at bay by cold winter temperatures, T. canadensis has been experiencing failures in regeneration attributed, in part, to herbivory by white-tailed deer (Odocoileus virginianus). Deer utilize T. canadensis stands as winter habitat in areas of high snow depth. Tsuga canadensis, once a major component of these forests, currently exists at just a fraction of its pre-settlement abundance due to historic logging and contemporary forest management practices, and what remains is found in small remnant patches surrounded by second- and third-growth deciduous forests. The deer population across the region, however, is likely double that of pre-European settlement times. In this dissertation I explore the relationship between white-tailed deer use of T. canadensis as winter habitat and the effect this use is having on regeneration and forest succession. For this research I quantified stand composition and structure and abiotic variables of elevation and snow depth in 39 randomly selected T. canadensis stands from across the western Upper Peninsula of Michigan. I also quantified composition and the configuration of the landscapes surrounding these stands. I measured relative deer use of T. canadensis stands as pellet group piles deposited in each stand during each of three consecutive winters, 2005-06, 2006-07, and 2007-08. The results of this research suggest that deer use of T. canadensis stands as winter habitat is influenced primarily by snow depth, elevation, and the composition and configuration of the greater landscapes surrounding these stands. Specifically, stands with more heterogeneous landscapes surrounding them (i.e., a patchy mosaic of conifer, deciduous, and open cover) had higher relative deer use than stands surrounded by homogenous deciduous forest cover. Additionally, the intensity of use and the number of stands used was greater in years with higher average snow depth. Tsuga canadensis regeneration in these stands was negatively associated with deer use and Acer saccharum (sugar maple) basal area. Of the 39 stands, 17 and 22 stands had no T. canadensis regeneration in small and large sapling categories, respectively. Acer saccharum was the most common understory tree species, and the importance of A. saccharum in the understory (stems < 10 cm dbh) of the stands was positively associated with overstory A. saccharum dominance. Tsuga canadensis establishment was associated with high-decay coarse woody debris and moss, and deciduous leaf litter inputs in these stands may be limiting access to these important microsites. Furthermore, A. saccharum is more tolerant to the effects of deer herbivory than T. canadensis, giving A. saccharum a competitive advantage in stands being utilized as winter habitat by deer. My research suggests that limited microsite availability, in conjunction with deer herbivory, may be leading to an erosion in T. canadensis patch stability and an altered successional trajectory toward one of A. saccharum dominance, an alternately stable climax species.

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Landscape structure and heterogeneity play a potentially important, but little understood role in predator-prey interactions and behaviourally-mediated habitat selection. For example, habitat complexity may either reduce or enhance the efficiency of a predator's efforts to search, track, capture, kill and consume prey. For prey, structural heterogeneity may affect predator detection, avoidance and defense, escape tactics, and the ability to exploit refuges. This study, investigates whether and how vegetation and topographic structure influence the spatial patterns and distribution of moose (Alces alces) mortality due to predation and malnutrition at the local and landscape levels on Isle Royale National Park. 230 locations where wolves (Canis lupus) killed moose during the winters between 2002 and 2010, and 182 moose starvation death sites for the period 1996-2010, were selected from the extensive Isle Royale Wolf-Moose Project carcass database. A variety of LiDAR-derived metrics were generated and used in an algorithm model (Random Forest) to identify, characterize, and classify three-dimensional variables significant to each of the mortality classes. Furthermore, spatial models to predict and assess the likelihood at the landscape scale of moose mortality were developed. This research found that the patterns of moose mortality by predation and malnutrition across the landscape are non-random, have a high degree of spatial variability, and that both mechanisms operate in contexts of comparable physiographic and vegetation structure. Wolf winter hunting locations on Isle Royale are more likely to be a result of its prey habitat selection, although they seem to prioritize the overall areas with higher moose density in the winter. Furthermore, the findings suggest that the distribution of moose mortality by predation is habitat-specific to moose, and not to wolves. In addition, moose sex, age, and health condition also affect mortality site selection, as revealed by subtle differences between sites in vegetation heights, vegetation density, and topography. Vegetation density in particular appears to differentiate mortality locations for distinct classes of moose. The results also emphasize the significance of fine-scale landscape and habitat features when addressing predator-prey interactions. These finer scale findings would be easily missed if analyses were limited to the broader landscape scale alone.

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The Zagros oak forests in Western Iran are critically important to the sustainability of the region. These forests have undergone dramatic declines in recent decades. We evaluated the utility of the non-parametric Random Forest classification algorithm for land cover classification of Zagros landscapes, and selected the best spatial and spectral predictive variables. The algorithm resulted in high overall classification accuracies (>85%) and also equivalent classification accuracies for the datasets from the three different sensors. We evaluated the associations between trends in forest area and structure with trends in socioeconomic and climatic conditions, to identify the most likely driving forces creating deforestation and landscape structure change. We used available socioeconomic (urban and rural population, and rural income), and climatic (mean annual rainfall and mean annual temperature) data for two provinces in northern Zagros. The most correlated driving force of forest area loss was urban population, and climatic variables to a lesser extent. Landscape structure changes were more closely associated with rural population. We examined the effects of scale changes on the results from spatial pattern analysis. We assessed the impacts of eight years of protection in a protected area in northern Zagros at two different scales (both grain and extent). The effects of protection on the amount and structure of forests was scale dependent. We evaluated the nature and magnitude of changes in forest area and structure over the entire Zagros region from 1972 to 2009. We divided the Zagros region in 167 Landscape Units and developed two measures— Deforestation Sensitivity (DS) and Connectivity Sensitivity (CS) — for each landscape unit as the percent of the time steps that forest area and ECA experienced a decrease of greater than 10% in either measure. A considerable loss in forest area and connectivity was detected, but no sudden (nonlinear) changes were detected at the spatial and temporal scale of the study. Connectivity loss occurred more rapidly than forest loss due to the loss of connecting patches. More connectivity was lost in southern Zagros due to climatic differences and different forms of traditional land use.

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Landscape evolution and surface morphology in mountainous settings are a function of the relative importance between sediment transport processes acting on hillslopes and in channels, modulated by climate variables. The Niesen nappe in the Swiss Penninic Prealps presents a unique setting in which opposite facing flanks host basins underlain by identical lithologies, but contrasting litho-tectonic architectures where lithologies either dip parallel to the topographic slope or in the opposite direction (i.e. dip slope and non-dip slope). The north-western facing Diemtigen flank represents such a dip slope situation and is characterized by a gentle topography, low hillslope gradients, poorly dissected channels, and it hosts large landslides. In contrast, the south-eastern facing Frutigen side can be described as non-dip slope flank with deeply incised bedrock channels, high mean hillslope gradients and high relief topography. Results from morphometric analysis reveal that noticeable differences in morphometric parameters can be related to the contrasts in the relative importance of the internal hillslope-channel system between both valley flanks. While the contrasting dip-orientations of the underlying flysch bedrock has promoted hillslope and channelized processes to contrasting extents and particularly the occurrence of large landslides on the dip slope flank, the flank averaged beryllium-10 (10Be)-derived denudation rates are very similar and range between 0.20 and 0.26 mm yr−1. In addition, our denudation rates offer no direct relationship to basin's slope, area, steepness or concavity index, but reveal a positive correlation to mean basin elevation that we interpret as having been controlled by climatically driven factors such as frost-induced processes and orographic precipitation. Our findings illustrate that while the landscape properties in this part of the northern Alpine border can mainly be related to the tectonic architecture of the underlying bedrock, the denudation rates have a strong orographic control through elevation dependent mean annual temperature and precipitation.

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Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

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The development of topography depends mainly on the interplay between uplift and erosion. These processes are controlled by various factors including climate, glaciers, lithology, seismic activity and short-term variables, such as anthropogenic impact. Many studies in orogens all over the world have shown how these controlling variables may affect the landscape's topography. In particular, it has been hypothesized that lithology exerts a dominant control on erosion rates and landscape morphology. However, clear demonstrations of this influence are rare and difficult to disentangle from the overprint of other signals such as climate or tectonics. In this study we focus on the upper Rhône Basin situated in the Central Swiss Alps in order to explore the relation between topography, possible controlling variables and lithology in particular. The Rhône Basin has been affected by spatially variable uplift, high orographically driven rainfalls and multiple glaciations. Furthermore, lithology and erodibility vary substantially within the basin. Thanks to high-resolution geological, climatic and topographic data, the Rhône Basin is a suitable laboratory to explore these complexities. Elevation, relief, slope and hypsometric data as well as river profile information from digital elevation models are used to characterize the landscape's topography of around 50 tributary basins. Additionally, uplift over different timescales, glacial inheritance, precipitation patterns and erodibility of the underlying bedrock are quantified for each basin. Results show that the chosen topographic and controlling variables vary remarkably between different tributary basins. We investigate the link between observed topographic differences and the possible controlling variables through statistical analyses. Variations of elevation, slope and relief seem to be linked to differences in long-term uplift rate, whereas elevation distributions (hypsometry) and river profile shapes may be related to glacial imprint. This confirms that the landscape of the Rhône Basin has been highly preconditioned by (past) uplift and glaciation. Linear discriminant analyses (LDAs), however, suggest a stronger link between observed topographic variations and differences in erodibility. We therefore conclude that despite evident glacial and tectonic conditioning, a lithologic control is still preserved and measurable in the landscape of the Rhône tributary basins.

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In order to maintain pond-breeding amphibian species richness, it is important to understand how both natural and anthropogenic disturbances affect species assemblages and individual species distributions both at the scale of individual ponds and at a larger landscape scale. The goal of this project was to investigate what characteristics of ponds and the surrounding wetland landscape were most effective in predicting pond-breeding species richness and the individual occurrence of wood frog (Rana sylvatica), bullfrog (Rana catesbeiana) and pickerel frog (Rana palustris) breeding sites in a beaver-modified landscape and how this landscape has changed over time. The wetland landscape of Acadia National Park was historically modified by the natural disturbance cycles of beaver (Castor cazadensis), and since their reintroduction to the island in 1921, beaver have played a large role in creating and maintaining palustrine wetlands. In 2000 and 2001, I studied pond-breeding amphibian assemblages at 71 palustrine wetlands in Acadia National Park, Mount Desert Island, Maine. I determined breeding presence of 7 amphibian species and quantified 15 variables describing local pond conditions and characteristics of the wetland landscape. I developed a priori models to predict sites with high amphibian species and used model selection with Akaike's Information Criterion (AIC) to identify important variables. Single species models were also developed to predict wood frog, bullfrog and pickerel frogs breeding presence. The variables for wetland connectivity by stream corridors and the presence of beaver disturbance were the most effective variables to predict sites with high amphibian richness. Wood frog breeding was best predicted by local scale variables describing temporary, fishless wetlands and the absence of active beaver disturbance. Abandoned beaver sites provided wood frog breeding habitat (70%) in a similar proportion to that found in non beaver-influenced sites (79%). In contrast, bullfrog breeding presence was limited to active beaver wetlands with fish and permanent water, and 80% of breeding sites were large (≥2ha in size). Pickerel frog breeding site selection was predicted best by the connectivity of sites in the landscape by stream corridors. Models including the presence of beaver disturbance, greater wetland perimeter and greater depth were included in the confidence set of pickerel frog models but showed considerably less support. Analysis of historic aerial photographs showed an 89% increase in the total number of ponded wetlands available in the landscape between the years of 1944 and 1997. Beaver colonization generally converted forested wetlands and riparian areas to open water and emergent wetlands. Temporal colonization of beaver wetlands favored large sites low in the watersheds and sites that were impounded later were generally smaller, higher in the watershed, and more likely to be abandoned. These results suggest that beaver have not only increased the number of available breeding sites in the landscape for pond-breeding amphibians, but the resulting mosaic of active and abandoned beaver wetlands also provides suitable breeding habitat for species with differing habitat requirements.

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he inclusion of environmental care data in the decision-making process should be based on the results obtained after scienti?cally evaluating different environmental variables. Herein, a European landscape geographic model is presented. This landscape map would allow the environmental care variable ?visual landscape?, along with other information related to vegetation, geology, soils, cultural variables, etc., to be integrated into the planning process. The methodology used is not new since it has already been tested in Spain by the authors. Nevertheless, the model was adapted to cope with the much more extensive territory of the European Union. This meant dealing with computational dif?culties, and a lack of information. The result of this work is a raster map (100 m cell size) that evaluates landscape quality in Europe by dividing the area into seven visual quality classes. This is a practical tool for territorial development that will facilitate the environmental assessment of plans, such as infrastructure plans, within a strategic pan-European framework.

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The aim of the present study is to identify and evaluate the relationship between Woodpigeon (Columba palumbus, Linnaeus, 1758) density and different environmental gradients (thermotype, ombrotype, continentality and latitudinal), land use and landscape structure, using geographic information systems and multivariate modelling. Transects (n = 396) were developed to estimate the density of Woodpigeon in the Marina Baja (Alicante, Spain) from 2006 to 2008. The highestdensity for Woodpigeon was in September-October (1.28birds/10ha) and the lowest inFebruary-March (0.34birds/10ha). Moreover, there were more Woodpigeons in areas with a mesomediterranean thermotypethan in thermomediterranean or supramediterranean ones. There was greater densityinthe intermediate zones compared to thecoast and interior. The natural or cultural landscape had the highest Woodpigeon density (1.53birds/10ha), with both denseand clear pine forest values standing out. Therefore, it is very important to conserve these traditional landscapes with adequate management strategies in order to maintain, resident and transient Woodpigeon populations. These natural areas are open places where the Woodpigeons find food and detect the presence ofpredators. Thus, this study will enable more precise knowledge of the ecological factors (habitat variables) that intervene in the distribution of Woodpigeon populations and their density.

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Landscape analysis with transects, in the Marina Baja area (province of Alicante, Spain), has contributed to establish the influence of different landscape matrices and some environmental gradients on wild rabbit Oryctolagus cuniculus (Linnaeus, 1758) (Mammalia: Leporidae) abundance (kilometric abundance index, KAI). Transects (n = 396) were developed to estimate the abundance of this species in the study area from 2006 to 2008.Our analysis shows that rabbits have preferences for a specific land use matrix (irrigated: KAI = 3.47 ± 1.14 rabbits/km). They prefer the coastal area (KAI = 3.82 ± 1.71 rabbits/km), which coincides with thermo-Mediterranean (a bioclimatic belt with a tempered winter and a hot and dry summer with high human density), as opposed to areas in the interior (continental climate with lower human occupation). Their preference for the southern area of the region was also noted (KAI = 8.22 ± 3.90 rabbits/km), which coincides with the upper semi-arid area, as opposed to the northern and intermediate areas (the north of the region coinciding with the upper dry and the intermediate area with the lower dry). On the other hand, we found that the number of rabbits increased during the 3-year study period, with the highest abundance (KAI = 2.71 ± 1.30 rabbits/km) inMay. Thus, this study will enable more precise knowledge of the ecological factors (habitat variables) that intervene in the distribution of wild rabbit populations in a poorly studied area.