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14 results for “landscape forest cover”
Tree-covered and intact forest landscapes BC1000, 1995, 2000, 2005, 2010, 2013, 2016 at 250 m
<p>Based on the <a href="http://www.unep-wcmc.org/resources-and-data/generalised-original-and-current-forest">UNEP historic forest cover map</a>, ESA land cover time series and <a href="http://www.intactforests.org/data.ifl.html">intact forest landscape (IFL 2000, 2013 and 2016) data</a>. Processing steps are described in detail <strong><a href="https://gitlab.com/openlandmap/global-layers/tree/master/soil/LDN">here</a></strong>. Antartica is not included.</p> <p>To access and visualize maps use: <a href="http://www.openlandmap.org/">OpenLandMap.org</a></p> <p>If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels:</p> <ul> <li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/issues">https://gitlab.com/openlandmap/global-layers/issues</a> </li> <li>General questions and comments: <a href="https://disqus.com/home/forums/landgis/">https://disqus.com/home/forums/landgis/</a></li> </ul> <p>All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention:</p> <ul> <li>ldg = theme: land degradation,</li> <li>forest.cover = variable: forest / tree cover,</li> <li>esacci.ifl = determination method: combination of ESA land cover and IFL maps,</li> <li>c = factor,</li> <li>250m = spatial resolution / block support: 250 m,</li> <li>s0..0cm = vertical reference: land surface,</li> <li>1995 = time reference: year 1995,</li> <li>v0.1 = version number: 0.1,</li> </ul>
Land cover, landscape metrics and typology of European cities for Urban Forest Ecosystem Services (UFES) evaluation
<p>The data refers to the paper "<em>Urban Forests as Regulating Ecosystems: Types and Ranking of European Cities</em>"</p> <p>The datasets provide a typology for 689 European urban areas, the land cover metrics and landscape metrics used to create the typology and the Urban Forest Ecosystem Services (UFES) indexes created from them.</p> <p>The typology of Urban Forest Ecosystem Services (UFES) presents 10 clusters of cities aggregated into 4 groups: Forest cities, Anthropogenic cities, Herbaceous cities and Standard European cities. The data can be used to support urban planning policies at local and regional scales; in urban forestry, urban form and ecosystem services work related at different spatial scales. The metrics used capture the spatial integration of different layers of natural, semi-natural and artificial land within functional urban areas.</p> <p> </p> <p>The datasets are a csv file (<code>Metrics.csv</code>) and a shapefile (<code>UFES.shp</code>) of polygons with attributes.</p> <ul> <li> <p><code>UFES.shp</code> attributes' are the following: FUA codes, country name, main city name, clusters and groups of FUAs resulting from the hierarchical cluster analysis (HCA), the R color codes used in the article, the five UFES budget indexes as well as an aggregated global UFES index for each FUA.</p> </li> <li> <p><code>Metrics.csv</code> contains the FUA codes, the land cover and landscape metrics used in the HCA.</p> </li> </ul> <p> </p>
Data from: Landscape context modulates the effect of local canopy cover on forest multidiversity across elevations
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Data from: Patterns and drivers of recent land cover change on two trailing-edge forest landscapes
<p>Climate change is altering the distribution of woody plants by influencing demographic processes and modifying disturbance regimes. Trailing-edge forests may be particularly vulnerable to these effects because they exist at warm, dry margins of tree distributions. To better understand recent climate-driven changes in trailing-edge forests, we used Landsat time series and 1,558 field reference plots to develop annual land cover maps from 1985 to 2020 in two large, biodiverse landscapes in central Arizona, USA. We then combined annual land cover maps with tree ring records and spatial data describing interannual climate, terrain, bark beetle (Curculionidae: Scolytinae) activity, wildfire, and harvest to quantify drivers of forest change. Throughout the two landscapes, forest extent declined by 0.3% and 0.8% from 1985 to 2020. However, considerable variation occurred within the study period, with abrupt (ca. 1–2 years) declines in forest extent followed by gradual (ca. 10 years) recovery on each landscape. Pinyon-juniper (<em>Pinus</em> <em>edulis</em>, <em>Pinus</em> <em>monophylla</em>, and/or <em>Juniperus</em> spp.) cover increased from 1985 to ca. 2000 but declined after 2000, a period of extreme drought and regional tree die-off. In contrast, pine-oak (<em>Pinus</em> <em>ponderosa</em> and <em>Quercus</em> spp.) cover increased from 2000 to 2020, primarily due to declines in ponderosa pine and mixed conifer cover over the same period. Wildfire was a key driver of transitions from forest to non-forest cover in our study area, with the occurrence of multiple compounded drought years playing an important role in unburned areas. By driving transitions to alternative forest types or non-forest cover, disturbance and drought will increasingly shape forest dynamics and ecosystem transformations throughout the southwestern US.</p>
Tayra (eira barbara) landscape use as a function of cover types, forest protection, and the presence of puma and free-ranging dogs
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Greater landscape-scale forest cover and animal-mediated seed dispersal syndromes associate with faster recovery rates in restoring tropical Andean forests
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Data from: Patterns and drivers of recent land cover change on two trailing-edge forest landscapes
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Torrent frogs have fewer macroparasites but higher rates of chytrid infection in landscapes with smaller forest cover
<p>data set and R script (statistical analysis)</p>
Forest cover at landscape scales increases male and female gametic diversity of palm seedlings
<p>Genetic diversity shapes the evolutionary potential of plant populations. For outcrossing plants, genetic diversity is influenced by effective population size and by dispersal, first of paternal gametes through pollen, and then of paternal and maternal gametes through seeds. Forest loss often reduces genetic diversity, but the degree to which it differentially impacts the paternal and maternal contributions to genetic diversity and the spatial scale at which these impacts are most pronounced are poorly understood. To address these questions, we genotyped 504 seedlings of the animal-dispersed palm <i>Oenocarpus bataua </i>collected from 29 widely distributed sites across Ecuador and decomposed the contribution of paternal and maternal gametes to overall genetic diversity. The amount of forest cover at a landscape scale (> 10 km radius) had an equally significant positive association with both male and female gametic diversity. In addition, there was a significant positive association between forest cover and effective population size. Stronger fine-scale spatial genetic structure for female versus male gametes was observed at sites with low forest cover, but this did not scale up to differences in male vs female gametic diversity. These findings show that reductions in forest cover at spatial scales much larger than those typically evaluated in ecological studies lead to significant, and equivalent, decreases of diversity in both male and female gametes, and that this association between landscape level forest loss and genetic diversity may be driven directly by reductions in effective population size of <i>O. bataua</i>, rather than by indirect disruptions to local dispersal processes. </p>
Data from: Which landscape size best predicts the influence of forest cover on restoration success? – A global meta-analysis on the scale of effect
Landscape context is a strong predictor of species persistence, abundance and distribution, yet its influence on the success of ecological restoration remains unclear. Thus, a primary question arises: which landscape size best predicts the effects of forest cover on restoration success? To answer this question, we conducted a global meta-analysis for biodiversity (mammals, birds, invertebrates, herpetofauna and plants) and measures of vegetation structure (cover, density, height, biomass and litter). Response ratios were calculated for comparisons between reference (e.g. old-growth forest) and disturbed sites (degraded or restored). Using an information-theoretic approach, mean response ratio (restoration success) and response ratio variance (restoration predictability) within each study landscape were regressed against the percentage of overall (summed forest cover) and contiguous (summed pixels of ≥60% forest cover) forest within eight different buffer sizes of radius 5–200 km (at 1-km resolution). We included 247 studies encompassing 196 study landscapes and 4360 quantitative comparisons. The best buffer (landscape) size varied for the following: (i) overall and contiguous forest cover, (ii) biodiversity and vegetation structure and (iii) mean response ratio and response ratio variance. Only plant biodiversity was influenced by overall forest cover (buffer size of 5, 10 and 200 km radii), while plants (10 and 200 km radii), mammals (5, 10 and 50–200 km radii), invertebrates (5 and 10 km radii), cover (5 km radii), height (5 km radii) and litter (100 km radii) were influenced by contiguous forest cover. Overall, mean response ratio and response ratio variance were positively and negatively nonlinearly related with both overall and contiguous forest cover, respectively. We reveal for the first time a clear pattern of increasing restoration success and decreasing uncertainty as contiguous forest cover increases. We also indicate preliminary recommended buffer sizes for investigating landscape restoration effects on biodiversity and vegetation structure. However, the coarse grain and variability in the data mean the optimal landscape size may not have been detected; thus, further research is needed. Synthesis and applications. When setting targets for ecological restoration, policymakers and restoration practitioners should account for the following: (i) the landscape context, particularly the amount of contiguous habitat up to 10 km around a disturbed site, and (ii) the uncertainty in restoration success, as it increases when contiguous forest cover falls below about 50%.
Forest cover at landscape scales increases male and female gametic diversity of palm seedlings
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Data from: Which landscape size best predicts the influence of forest cover on restoration success? – A global meta-analysis on the scale of effect
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Data from: Local tropical forest restoration strategies affect tree recruitment more strongly than does landscape forest cover
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Landscape mosaic map archive for "Forest cover dynamics in the shifting landscape mosaic of the continental United States from 2001 to 2016"
<p>This data archive contains two zipfiles, each containing a raster map of the continental United States showing the landscape mosaic classification at 30-meter resolution as described in the citing publication.</p>
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