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300 results for “land change”
NLCD_INEGI: Harmonized US-Mexico Land Cover Change Dataset, 1992/2001/2011
<p>We have taken the Uso del Suelo y Vegetacion land cover classification products for Mexico (courtesy of Mexico's Instituto Nacional de Estadistica y Geografia, or INEGI) for years 1985, 1993, 2002, 2007, and 2011 (INEGI, 2015); harmonized their classes with the classes of the Multi-Resolution Land Characteristics Consortium (MRLC) National Land Cover Database (NLCD) (Homer et al., 2015), and merged the two datasets to form a single land cover product covering the continental US and Mexico, for years 1992/3, 2001/2, and 2011. Details of processing, along with the processing scripts, are archived in GitHub in the <a href="https://github.com/tbohn/NLCD_INEGI/tree/v1.5">NLCD_INEGI</a> project (Bohn, 2019).</p> <p>Output files are ESRI ascii-format raster files, geographic projection, 0.000350884 degree cellsize. Each file contains a 1x1 degree box or "tile", named nlcd_inegi.<em>lat0</em>_<em>lat1</em>n.<em>lon0</em>_<em>lon1</em>w.asc, where <em>lat0</em> and <em>lat1</em> are the south and north boundaries of the box and <em>lon0</em> and <em>lon1</em> are the west and east boundaries (west = positive).</p> <p>This project contains the following g-zipped tar files:</p> <ul> <li>1992.tgz - land cover from 1992 (NLCD) and 1993 (INEGI)</li> <li>2001.tgz - land cover from 2001 (NLCD) and 2002 (INEGI)</li> <li>2011.tgz - land cover from 2011 (both NLCD and INEGI)</li> <li>stable_2001-2011.tgz - land cover from those pixels that had the same class in 2001 and 2011 ("stable" pixels)</li> </ul> <p>On LINUX, the contents of these files can be extracted via "tar":</p> <p>tar -xvzf 1992.tgz >& log.tar.txt</p> <p>On Windows, applications such as "7-zip" can extract the contents.</p> <p>Each of these .tgz files contain a folder with the same name but without the ".tgz". Within each of these folders is a sub-folder called "asc.clip.1deg". This folder contains the 1x1 tiles.</p>
Figure 1 in Impact of Drought and Land - Use Changes on Surface - Water Quality and Quantity: The Sahelian Paradox
Figure 1. - Location of the sampling site (star) of flying gurnard Dactylopterus volitans in the Eastern English Channel.
Figure 3 in Impact of Drought and Land - Use Changes on Surface - Water Quality and Quantity: The Sahelian Paradox
Figure 3. - Specimen of flying gurnard Dactylopterus volitans (MNHN 2013-0612; 47 cm TL) caught in the Eastern English Channel in 2011.
Figure 2 in Impact of Drought and Land - Use Changes on Surface - Water Quality and Quantity: The Sahelian Paradox
Figure 2. - Whole otolith of flying gurnard (Dactylopterus volitans) with annotation of growth rings (red stars).
Figure S4 in Effects of land-use change on herbaceous vegetation in a semi-arid Mopaneveld savanna
Figure S4. Unweighted Pair Group Method with Arithmetic Mean (UPGMA) based on Gower distance measure indicating annual forb plant functional types (PFTs).
Figure S5 in Effects of land-use change on herbaceous vegetation in a semi-arid Mopaneveld savanna
Figure S5. Unweighted Pair Group Method with Arithmetic Mean (UPGMA) based on Gower distance measure indicating perennial forb plant functional types (PFTs).
Figure S3 in Effects of land-use change on herbaceous vegetation in a semi-arid Mopaneveld savanna
Figure S3. Unweighted Pair Group Method with Arithmetic Mean (UPGMA) based on Gower distance measure indicating perennial grass plant functional types (PFTs).
Figure S1 in Effects of land-use change on herbaceous vegetation in a semi-arid Mopaneveld savanna
Figure S1. Principal Co-ordinate Analysis (PCoA) scatter diagram of the species-trait matrix revealing a strong clustering based on life history.
Figure 3 in Effects of land-use change on herbaceous vegetation in a semi-arid Mopaneveld savanna
Figure 3. Herbaceous species (left) and trait (right) diversity measures benchmarked against the mean value calculated for the untransformed (protected) area (----) across transformed land-use types. Vertical bars denote 0.95 confidence intervals. Significant deviations from the protected area (Sidak posthoc pairwise comparison; p<0.05) are denoted by (*).
Figure S2 in Effects of land-use change on herbaceous vegetation in a semi-arid Mopaneveld savanna
Figure S2. Unweighted Pair Group Method with Arithmetic Mean (UPGMA) based on Gower distance measure indicating annual grass plant functional types (PFTs).
Figure 4 in Effects of land-use change on herbaceous vegetation in a semi-arid Mopaneveld savanna
Figure 4. Principal Component Analysis (PCA) ordination of land-use type sampling plots correlated with plant functional types (PFT's). CAF (Communal abandoned fields); CR (Communal rangelands); NRSM (Naturally restored strip mine); RASM (Recently active strip mine); UMV (Untransformed Mopaneveld).
Figure 2 in Effects of land-use change on herbaceous vegetation in a semi-arid Mopaneveld savanna
Figure 2. Multidimensional Scaling (NMDS) ordination of sampling plots representing herbaceous species assemblages across land-use types. Broad groupings are encircled.
Figure 1 in Effects of land-use change on herbaceous vegetation in a semi-arid Mopaneveld savanna
Figure 1. Study area and locality of sampled sites. Strip mines and untransformed Mopaneveld is located at Pompeye (top) and communal areas at Lulekani (bottom).
FIGURE 4 in Land-use changes affect the functional structure of stream fish assemblages in the Brazilian Savanna
FIGURE 4 | Structural equation model diagrams showing the effects of landscape degradation (CDI) on the functional structure of stream fish assemblages from the Araguari River basin. CDI influenced functional diversity mediated by alterations in habitat heterogeneity and stability (A. Model fit: X2 = 32.8, df = 25, p = 0.51). CDI also influenced functional identity, mediated by changes in habitat type (B. Model fit: X2 = 44.9, df = 18, p = 0.13). Arrows indicate positive (black) and negative (gray) significant direct effects (p <0.05; *p <0.10), with thickness proportional to their power (standardized path coefficients along arrows). Biodiversity metrics – FRic: Functional Richness; FDiv: Functional Divergence; FEve: Functional Evennes; FSpe: Functional Specialization; FOri: Functional Originality; CWM1-3: Functional Identity. For physical-habitat codes, calculation and ecological meaning, see Tab. 1.
FIGURE 5 in Land-use changes affect the functional structure of stream fish assemblages in the Brazilian Savanna
FIGURE 5 | Ecomorphological space showing the position of each fish species (36) from the Araguari River basin. Each plot represents two axes of a principal component analysis (PCA), where species are plotted according to their respective trait values. Codes at the ends of the arrows are the most important ecomorphological traits for each PCA axis. For trait and species codes, see Tab. 2 and Tab. S3, respectively).
FIGURE 2 in Land-use changes affect the functional structure of stream fish assemblages in the Brazilian Savanna
FIGURE 2 | Examples of landscape and local-habitat conditions of the streams sampled across a degradation gradient in the Cerrado: A. Streams with a small strip of riparian forests in landscapes dominated by mechanized agriculture; B. Stream with relatively well-preserved local conditions, including forest on both banks; C. Stream surrounded by intermediate riparian cover; and D. Stream running in pasture areas without any forest.
FIGURE 3 in Land-use changes affect the functional structure of stream fish assemblages in the Brazilian Savanna
FIGURE 3 | Predictions tested using structural equation modeling, indicating the expected pathways (arrows) for the effects of catchment degradation (CDI) on stream physical habitat and, consequently, on the functional structure of the fish assemblages. Land use is expected to influence the functional diversity mediated by alterations in habitat heterogeneity and stability (A), and to influence functional identity, mediated by changes in habitat type (B). Arrows indicate expected effects between predictive and response variables, which can be positive (black continuous line), negative (gray continuous line) or non-directional (dashed lines). For physical-habitat codes, calculation and ecological meaning, see Tab. 1.
FIGURE 1 in Land-use changes affect the functional structure of stream fish assemblages in the Brazilian Savanna
FIGURE 1 | Headwater streams (N = 40; black dots) sampled for fish and local physical habitat. All sites drain to Nova Ponte Reservoir in the Araguari River basin, Upper Paraná River, Minas Gerais, Brazil.
Absolute model ages of three craters in the vicinity of the Chang'E-5 landing site and their geologic implications
<p>We used the Crater Size Frequency distribution (CSFD) method to yield the formation ages of Pythagora, Sharp B, and Harpalus crater, and the crater density values (N(1)). Here we provide the crater counting data.</p>
Fig. 3. Land use and land cover data for 2014 in Population trends and conservation status of proboscis monkeys (Nasalis larvatus) in the face of habitat change in the Klias Peninsula, Sabah, Borneo, Malaysia
Fig. 3. Land use and land cover data for 2014/2015 within the 1-km buffer distance from surveyed rivers, overlaid with proboscis monkey sightings from the 2004/2005 and 2014 surveys, Protected Areas, and Production Forest Reserve boundaries.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.