983 resultados para Landscape variables


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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.

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Traditional water supply systems in semi-arid agrarian ecosystems, mainly irrigation canals, contribute to the diversity of the landscape and influence the composition of species. To evaluate their effect on bird communities in the breeding season, we selected a rural area in southeastern Spain, where an intricate and extensive network of irrigation canals and cultivated areas is located between two wetlands declared as Natural Parks. Birds were counted at representative points distributed throughout the canal network at which we recorded several variables related to the physical features, the vertical and horizontal structure of associated vegetation, reed development (Phragmites australis) and land use in the neighboring areas. We detected 37 bird species, most of which were also breeding in the wetlands nearby. We used Hierarchical Partitioning analyses to identify the variables most strongly related to the probability of the presence of selected species and species richness. Vegetation cover and height close to the canals, together with reed development, were the most important types of variables explaining species presence and richness. We found that current management practices for reeds in canals are not well-suited for biodiversity conservation. We therefore propose alternatives that could be implemented in the area in cooperation with stakeholders.

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Modelling the susceptibility of permafrost slopes to disturbance can identify areas at risk to future disturbance and result in safer infrastructure and resource development in the Arctic. In this study, we use terrain attributes derived from a digital elevation model, an inventory of permafrost slope disturbances known as active-layer detachments (ALDs) and generalised additive modelling to produce a map of permafrost slope disturbance susceptibility for an area on northern Melville Island, in the Canadian High Arctic. By examining terrain variables and their relative importance, we identified factors important for initiating slope disturbance. The model was calibrated and validated using 70 and 30 per cent of a data-set of 760 mapped ALDs, including disturbed and randomised undisturbed samples. The generalised additive model calibrated and validated very well, with areas under the receiver operating characteristic curve of 0.89 and 0.81, respectively, demonstrating its effectiveness at predicting disturbed and undisturbed samples. ALDs were most likely to occur below the marine limit on slope angles between 3 and 10° and in areas with low values of potential incoming solar radiation (north-facing slopes).

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Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric "number of patches" than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty. © 2013 Elsevier B.V.

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Speciation can be understood as a continuum occurring at different levels, from population to species. The recent molecular revolution in population genetics has opened a pathway towards understanding species evolution. At the same time, speciation patterns can be better explained by incorporating a geographic context, through the use of geographic information systems (GIS). Phaedranassa (Amaryllidaceae) is a genus restricted to one of the world’s most biodiverse hotspots, the Northern Andes. I studied seven Phaedranassa species from Ecuador. Six of these species are endemic to the country. The topographic complexity of the Andes, which creates local microhabitats ranging from moist slopes to dry valleys, might explain the patterns of Phaedranassa species differentiation. With a Bayesian individual assignment approach, I assessed the genetic structure of the genus throughout Ecuador using twelve microsatellite loci. I also used bioclimatic variables and species geographic coordinates under a Maximum Entropy algorithm to generate distribution models of the species. My results show that Phaedranassa species are genetically well-differentiated. Furthermore, with the exception of two species, all Phaedranassa showed non-overlapping distributions. Phaedranassa viridiflora and P. glauciflora were the only species in which the model predicted a broad species distribution, but genetic evidence indicates that these findings are likely an artifact of species delimitation issues. Both genetic differentiation and nonoverlapping geographic distribution suggest that allopatric divergence could be the general model of genetic differentiation. Evidence of sympatric speciation was found in two geographically and genetically distinct groups of P. viridiflora. Additionally, I report the first register of natural hybridization for the genus. The findings of this research show that the genetic differentiation of species in an intricate landscape as the Andes does not necessarily show a unique trend. Although allopatric speciation is the most common form of speciation, I found evidence of sympatric speciation and hybridization. These results show that the processes of speciation in the Andes have followed several pathways. The mixture of these processes contributes to the high biodiversity of the region.

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Two protected areas: Royal Bardia National Park (RBNP) and Royal Suklaphanta Wildlife Reserve (RSWR) in the Western Terai, Nepal, are under threats due to present political turmoil, uncontrolled immigration, inefficient land reform policies and unsustainable resource use. I did a stratified random questionnaire survey of 234 households to determine how resource use patterns and problems influence conservation attitudes. Chi-square, Student's t, Mann-Whitney and Kruskal-Wallis tests, and multiple regression were used. There was spatio-temporal variability in resource use patterns and dependency. People were collecting eight and seven types of resources in RBNP and RSWR, respectively. However, people in RBNP were more dependent on resources than RSWR. In both areas, the problem of firewood is serious. The mean attitude score of RBNP (8.4 ± 1.44) was significantly higher than the score of RSWR (7.7 ± 1.66; t = 3.24, p = 0.0007). Conservation attitude was determined by variables such as participation in trainings, wildlife damage, and satisfaction towards user groups.

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Modelling the susceptibility of permafrost slopes to disturbance can identify areas at risk to future disturbance and result in safer infrastructure and resource development in the Arctic. In this study, we use terrain attributes derived from a digital elevation model, an inventory of permafrost slope disturbances known as active-layer detachments (ALDs) and generalised additive modelling to produce a map of permafrost slope disturbance susceptibility for an area on northern Melville Island, in the Canadian High Arctic. By examining terrain variables and their relative importance, we identified factors important for initiating slope disturbance. The model was calibrated and validated using 70 and 30 per cent of a data-set of 760 mapped ALDs, including disturbed and randomised undisturbed samples. The generalised additive model calibrated and validated very well, with areas under the receiver operating characteristic curve of 0.89 and 0.81, respectively, demonstrating its effectiveness at predicting disturbed and undisturbed samples. ALDs were most likely to occur below the marine limit on slope angles between 3 and 10° and in areas with low values of potential incoming solar radiation (north-facing slopes).

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Dependence of some species on landscape structure has been proved in numerous studies. So far, however, little progress has been made in the integration of landscape metrics in the prediction of species associated with coastal features. Specific landscape metrics were tested as predictors of coastal shape using three coastal features of the Iberian Peninsula (beaches, capes and gulfs) at different scales. We used the landscape metrics in combination with environmental variables to model the niche and find suitable habitats for a seagrass species (Cymodocea nodosa) throughout its entire range of distribution. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. We provided the first global model of the factors that can be shaping the environmental niche and distribution of C. nodosa throughout its range. Sea surface temperature and salinity were the most relevant variables. We identified areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. We also present some preliminary results of testing historical biogeographical hypotheses derived from distribution predictions under Last Glacial Maximum conditions and genetic diversity data.

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Intensification of permafrost disturbances such as active layer detachments (ALDs) and retrogressive thaw slumps (RTS) have been observed across the circumpolar Arctic. These features are indicators of unstable conditions stemming from recent climate warming and permafrost degradation. In order to understand the processes interacting to give rise to these features, a multidisciplinary approach is required; i.e., interactions between geomorphology, hydrology, vegetation and ground thermal conditions. The goal of this research is to detect and map permafrost disturbance, predict landscape controls over disturbance and determine approaches for monitoring disturbance, all with the goal of contributing to the mitigation of permafrost hazards. Permafrost disturbance inventories were created by applying semi-automatic change detection techniques to IKONOS satellite imagery collected at the Cape Bounty Arctic Watershed Observatory (CBAWO). These methods provide a means to estimate the spatial distribution of permafrost disturbances for a given area for use as an input in susceptibility modelling. Permafrost disturbance susceptibility models were then developed using generalized additive and generalized linear models (GAM, GLM) fitted to disturbed and undisturbed locations and relevant GIS-derived predictor variables (slope, potential solar radiation, elevation). These models successfully delineated areas across the landscape that were susceptible to disturbances locally and regionally when transferred to an independent validation location. Permafrost disturbance susceptibility models are a first-order assessment of landscape susceptibility and are promising for designing land management strategies for remote permafrost regions. Additionally, geomorphic patterns associated with higher susceptibility provide important knowledge about processes associated with the initiation of disturbances. Permafrost degradation was analyzed at the CBAWO using differential interferometric synthetic aperture radar (DInSAR). Active-layer dynamics were interpreted using inter-seasonal and intra-seasonal displacement measurements and highlight the importance of hydroclimatic factors on active layer change. Collectively, these research approaches contribute to permafrost monitoring and the assessment of landscape-scale vulnerability in order to develop permafrost disturbance mitigation strategies.

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This is an ecological, analytical and retrospective study comprising the 645 municipalities in the State of São Paulo, the scope of which was to determine the relationship between socioeconomic, demographic variables and the model of care in relation to infant mortality rates in the period from 1998 to 2008. The ratio of average annual change for each indicator per stratum coverage was calculated. Infant mortality was analyzed according to the model for repeated measures over time, adjusted for the following correction variables: the city's population, proportion of Family Health Programs (PSFs) deployed, proportion of Growth Acceleration Programs (PACs) deployed, per capita GDP and SPSRI (São Paulo social responsibility index). The analysis was performed by generalized linear models, considering the gamma distribution. Multiple comparisons were performed with the likelihood ratio with chi-square approximate distribution, considering a significance level of 5%. There was a decrease in infant mortality over the years (p < 0.05), with no significant difference from 2004 to 2008 (p > 0.05). The proportion of PSFs deployed (p < 0.0001) and per capita GDP (p < 0.0001) were significant in the model. The decline of infant mortality in this period was influenced by the growth of per capita GDP and PSFs.