53 resultados para Appalachian Trail--Maps.


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From 1978 to 1981, intensive sedimentological investigations were carried out on the Northfrisian intertidal shoals between the small island of Gröde and Nordstrand lsland as a part of an interdisciplinary research projekt. The objective of this sedimentological study was to reveal long and short term tendencies in sedimentation and erosion in the environment. The presented study mainly concentrated on surface mapping in the tidal flats which based on more than 5000 sediment samples. The relative amounts of the grain-size fractions <0.063 mm and >0.125 mm are presented on maps. Predominant sediment typs are well sorted fine sands ("Wattsand") and muddy sands ("Schlicksand"), pure muds covering only small areas. The fine-grained deposits are either found in the lee-side of an island in elongated bays having a low waterdepth during high tide near the shore or near exposed "Klei" outcrops as well as sporadically on the edge of tidal rills. Together with standardized fields observations of biological and physical properties, the maps indicate a slight erosive tendency in large sections of the investigated area.

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This dataset consists of global raster maps indicating the habitat suitability for 7 suborders of cold water octocorals (Octocorallia found deeper than 50m). Maps present a relative habitat suitability index ranging from 0 (unsuitable) to 100 (highly suitable). Two maps are provided for each suborder (Alcyoniina, Calcaxonia, Holaxonia, Scleraxonia, Sessiliflorae, Stolonifera, and Subselliflorae). A publicly accessable low resolution map (grid size 10x10 arc-minutes) and a restricted access high resolution map (grid size 30x30 arc-seconds). Maps are geotiff format incorporating LZW compression to reduce file size. Please contact the corresponding author (Chris Yesson) for access to the high resolution data.

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Reconstructing past landscapes from historical maps requires quantifying the accuracy and completeness of these sources. The accuracy and completeness of two historical maps of the same period covering the same area in Israel were examined: the 1:63,360 British Palestine Exploration Fund map (1871-1877) and the 1:100,000 French Levés en Galilée (LG) map (1870). These maps cover the mountainous area of the Galilee (northern Israel), a region with significant natural and topographical diversity, and a long history of human presence. Land-cover features from both maps, as well as the contours drawn on the LG map, were digitized. The overall correspondence between land-cover features shown on both maps was 59% and we found that the geo-referencing method employed (transformation type and source of control points) did not significantly affect these correspondence measures. Both maps show that in the 1870s, 35% of the Galilee was covered by Mediterranean maquis, with less than 8% of the area used for permanent agricultural cropland (e.g., plantations). This article presents how the reliability of the maps was assessed by using two spatial historical sources, and how land-cover classes that were mapped with lower certainty and completeness are identified. Some of the causes that led to observed differences between the maps, including mapping scale, time of year, and the interests of the surveyors, are also identified.

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In this paper, we present a map describing the main geomorphological features of the coastal and marine area between the towns of Albenga and Savona (Ligurian Sea, NW Mediterranean) corresponding to a coastal stretch of ~40 km. To produce this map, we collated data from the literature, orthophotos, perspective photos, multibeam and side scan sonar data, and undertook direct surveys to ground truth data obtained using indirect techniques. We divided the information into nine thematic layers, including bathymetry, natural coastal types, geomorphological elements, seafloor coverage (both geological and biological), coastal and nearshore dynamics, human influence on coastal and marine environments, coastal occupation and protected areas.

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Wetlands store large amounts of carbon, and depending on their status and type, they release specific amounts of methane gas to the atmosphere. The connection between wetland type and methane emission has been investigated in various studies and utilized in climate change monitoring and modelling. For improved estimation of methane emissions, land surface models require information such as the wetland fraction and its dynamics over large areas. Existing datasets of wetland dynamics present the total amount of wetland (fraction) for each model grid cell, but do not discriminate the different wetland types like permanent lakes, periodically inundated areas or peatlands. Wetland types differently influence methane fluxes and thus their contribution to the total wetland fraction should be quantified. Especially wetlands of permafrost regions are expected to have a strong impact on future climate due to soil thawing. In this study ENIVSAT ASAR Wide Swath data was tested for operational monitoring of the distribution of areas with a long-term SW near 1 (hSW) in northern Russia (SW = degree of saturation with water, 1 = saturated), which is a specific characteristic of peatlands. For the whole northern Russia, areas with hSW were delineated and discriminated from dynamic and open water bodies for the years 2007 and 2008. The area identified with this method amounts to approximately 300,000 km**2 in northern Siberia in 2007. It overlaps with zones of high carbon storage. Comparison with a range of related datasets (static and dynamic) showed that hSW represents not only peatlands but also temporary wetlands associated with post-forest fire conditions in permafrost regions. Annual long-term monitoring of change in boreal and tundra environments is possible with the presented approach. Sentinel-1, the successor of ENVISAT ASAR, will provide data that may allow continuous monitoring of these wetland dynamics in the future complementing global observations of wetland fraction.

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Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.

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Aim: Greater understanding of the processes underlying biological invasions is required to determine and predict invasion risk. Two subspecies of olive (Olea europaea subsp. europaea and Olea europaea subsp. cuspidata) have been introduced into Australia from the Mediterranean Basin and southern Africa during the 19th century. Our aim was to determine to what extent the native environmental niches of these two olive subspecies explain the current spatial segregation of the subspecies in their non-native range. We also assessed whether niche shifts had occurred in the non-native range, and examined whether invasion was associated with increased or decreased occupancy of niche space in the non-native range relative to the native range. Location: South-eastern Australia, Mediterranean Basin and southern Africa. Methods: Ecological niche models (ENMs) were used to quantify the similarity of native and non-native realized niches. Niche shifts were characterized by the relative contribution of niche expansion, stability and contraction based on the relative occupancy of environmental space by the native and non-native populations. Results: Native ENMs indicated that the spatial segregation of the two subspecies in their non-native range was partly determined by differences in their native niches. However, we found that environmentally suitable niches were less occupied in the non-native range relative to the native range, indicating that niche shifts had occurred through a contraction of the native niches after invasion, for both subspecies. Main conclusions: The mapping of environmental factors associated with niche expansion, stability or contraction allowed us to identify areas of greater invasion risk. This study provides an example of successful invasions that are associated with niche shifts, illustrating that introduced plant species are sometimes readily able to establish in novel environments. In these situations the assumption of niche stasis during invasion, which is implicitly assumed by ENMs, may be unreasonable.

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This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.