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79 results for “conservation value”
Potential forest conservation value rasters for Denmark from Assmann et al. "LiDAR data fusion and machine learning identify temperate forests of high conservation value"
<p>Potential forest conservation value (high / low) rasters for Denmark based on a remote sensing data fusion approach. Please see manuscript (below) for a detailed description of the methods and data products. </p> <p><br>Jakob J. Assmann, Pil B. M. Pedersen, Jesper E. Moeslund, Cornelius Senf, Urs A. Treier, Derek Corcoran, Zsófia Koma, Thomas Nord-Larsen, Signe Normand. In prep. LiDAR data fusion and machine learning identify temperate forests of high conservation value.</p> <p><br>When using the data, please cite the above manuscript. </p> <p><br>Files description:</p> <ul> <li>Compressed and cloud optimised rasters of potential forest conservation value projections for Denmark (10 m res.) in EPSG:3857 <ul> <li>forest_quality_ranger_biowide_10m_cog_epsg3857.tif RandomForest model projections based on BIOWIDE stratification (!! best performing model !!)</li> <li>forest_quality_ranger_sustainscapes_10m_cog_epsg3857.tif RandomForest model projections based on SustainScapes stratification</li> <li>forest_quality_gbm_biowide_10m_cog_epsg3857.tif GBM model projections based on BIOWIDE stratification</li> <li>forest_quality_gbm_sustainscapes_10m_cog_epsg3857.tif GBM model projections based on SustainScapes stratification</li> </ul> </li> </ul> <p> </p> <ul> <li>Aggregated rasters of potential forest conservation value projections for Denmark (100 m res.) in EPSG:25832 <ul> <li>forest_quality_ranger_biowide_100m.tif RandomForest model projections based on BIOWIDE stratification (!! best performing model !!)</li> <li>forest_quality_ranger_sustainscapes_100m.tif RandomForest model projections based on SustainScapes stratification</li> <li>forest_quality_gbm_biowide_100m.tif GBM model projections based on BIOWIDE stratification</li> <li>forest_quality_gbm_sustainscapes_100m.tif GBM model projections based on SustainScapes stratification </li> </ul> </li> </ul> <p> </p> <ul> <li>Uncompressed and tiled rasters of potential forest conservation value projections for Denmark (10 m res.) in EPSG:25832<br>Please note: the archives contain approx. 42k tiles, each 10 x 10 km, as well as a VRT file for covenient loading. <ul> <li>forest_quality_ranger_biowide_10m.zip RandomForest model projections based on BIOWIDE stratification (!! best performing model !!)</li> <li>forest_quality_ranger_sustainscapes_10m.zip RandomForest model projections based on SustainScapes stratification</li> <li>forest_quality_gbm_biowide_10m.zip GBM model projections based on BIOWIDE stratification</li> <li>forest_quality_gbm_sustainscapes_10m.zip GBM model projections based on SustainScapes stratification</li> </ul> </li> </ul>
Conservation outcomes of dietary transitions across different values of nature - model outputs
<p>Archive of output reports produced for the MAgPIE v4.8.2 paper <strong>Conservation outcomes of dietary transitions across different values of nature</strong>.</p> <p><strong>Data</strong></p> <p>The data contain the MAgPIE model and post-processing outputs for all assessed scenarios, including the sensitivity test across the SSP1 and SSP3 scenarios.</p> <ul> <li>The file <em>rev9_healthyLscps_AOH_full_report.Rds </em>contains the outputs of our Area of Habitat (AOH) assessment for all assessed species and across all scenarios. The summary statistics shown in Figure 2 and Figure 3 have been derived from this data set. The data has also been used to create Extended Data Figures<span lang="EN-GB"> 5-</span>7<span lang="EN-GB"> and is shown in the Supplementary Information. </span>However, for Extended Data Figure<span lang="EN-GB"> 7</span> the data was <span lang="EN-GB">used in combination</span> with <span lang="EN-GB">rasterized </span>range polygons obtained from the <span lang="EN-GB">IUCN Red List Database (IUCN 2020).</span></li> <li><span lang="EN-GB">The file <em>rev9_healthyLscps_pollSuff_report_all.Rds </em>reports the global and regional cropland area (Mha) that is subject to insufficient and sufficient pollination supply. This is specified in the column ‘poll_class’, where 1 is insufficient and 2 is sufficient pollination supply. The data is shown in Figure 4, Extended Data Figure 8 and the Supplementary Information.</span></li> <li><span lang="EN-GB">The file <em>rev9_healthyLscps_RUSLE_report_all.Rds</em> reports estimated global and regional soil loss in Pg per year across all modelled scenarios. The data is displayed in Figure 4, Extended Data Figure 9 and the Supplementary Information.</span></li> <li><span lang="EN-GB">The file <em>rev9_healthyLscps_allSSP_report.rds </em>contains regional and global output variables from the MAgPIE model used in this study. The data is shown in Figure 1 and 5, as well as in Extended Data Figures 2-4 and the Supplementary Information.</span></li> <li><span lang="EN-GB">The file <em>rev9_healthyLscps_validation.rds </em>contains validation data for the MAgPIE model output variables.</span></li> </ul> <p> </p> <p><strong><span lang="EN-GB">Model code</span></strong></p> <p>The model code of the MAgPIE and SEALS models can be accessed via:</p> <p><em>MAgPIE model code</em><em>:</em></p> <ul> <li><a href="https://doi.org/10.5281/zenodo.13833444">https://doi.org/10.5281/zenodo.13833444</a> and <a href="https://github.com/magpiemodel/magpie">https://github.com/magpiemodel/magpie</a></li> </ul> <p><em>MAgPIE model documentation</em><em>:</em></p> <ul> <li><a href="https://rse.pik-potsdam.de/doc/magpie/4.3.5/">https://rse.pik-potsdam.de/doc/magpie/4.8.2/</a></li> </ul> <p><em>SEALS model code</em><em>:</em></p> <ul> <li><a href="https://github.com/jandrewjohnson/seals_dev/releases/tag/v1.0.0">https://github.com/jandrewjohnson/seals_dev/releases/tag/v1.0.0</a></li> </ul> <p><em>SEALS mode documentation:</em></p> <ul> <li><a href="https://justinandrewjohnson.com/earth_economy_devstack/seals_overview.html">https://justinandrewjohnson.com/earth_economy_devstack/seals_overview.html</a></li> </ul> <p> </p> <p><strong><span lang="EN-GB">Cited references</span></strong></p> <p><span>IUCN. (2020). <em>The IUCN Red List of Threatened Species. Version 2020-2</em>. https://www.iucnredlist.org.</span><em><span> </span></em><span>Downloaded on 25 November 2020</span></p>
Fig. 2 in A New Measure Of Conservation Value Combining Rarity And Ecological Diversity: A Case Study With Light Trap Collected Caddisflies (Insecta: Trichoptera)
Fig. 2. The Rarity and Ecological Diversity (RED)-index of the different aquatic habitats (aquatic habitats with the same letter are not significantly different at p = 0.05 by non-parametric Tukey-test)
Fig. 1 in A New Measure Of Conservation Value Combining Rarity And Ecological Diversity: A Case Study With Light Trap Collected Caddisflies (Insecta: Trichoptera)
Fig. 1. The map of Hungary with the position of the sampling sites (filled squares show light traps)
Fig. 3 in A New Measure Of Conservation Value Combining Rarity And Ecological Diversity: A Case Study With Light Trap Collected Caddisflies (Insecta: Trichoptera)
Fig. 3. The diversity (A) and RAR-index (B) of the different aquatic habitats (aquatic habitats with the same letter are not significantly different at p = 0.05 by non-parametric Tukey-test)
Figure S2 in Plant diversity and conservation value of wetlands along a rural-urban gradient
Figure S2. MDS ordination indicating the clear separation of the two land use groups based on the urbanisation measures.
Figure 6. A in Plant diversity and conservation value of wetlands along a rural-urban gradient
Figure 6. A, Percentage distribution of alien and indigenous species per site; B, the indigenous (ISR) and alien (ASR) species richness per site; C, the percentage of the total average cover of all alien species per site; D, the associated adjusted Floristic Quality Assessment Index values (adjFQAI) of each site; arranged along a gradient of increasing percentage urban landcover.
Figure S1 in Plant diversity and conservation value of wetlands along a rural-urban gradient
Figure S1. Cluster analysis results based on the urbanisation measures indicating clear grouping between the urban sites 1 and 2 and the rural sites.
Figure 3. A in Plant diversity and conservation value of wetlands along a rural-urban gradient
Figure 3. A, Total number of species per wetland site (alpha diversity); B, the average species richness per transect for each site; C, the size of each wetland; arranged along a gradient of increasing percentage urban landcover.
Figure 4. A in Plant diversity and conservation value of wetlands along a rural-urban gradient
Figure 4. A, Beta diversity between sites (calculated as the average between all the rural sites (R1–R12), the average between the two urban sites and all the rural sites (U1 and U2), and between the two urban sites (U)); B, the SIMPER analysis results of the average similarity of the transects in each wetland site; arranged along a gradient of increasing percentage urban landcover.
Figure 5. A in Plant diversity and conservation value of wetlands along a rural-urban gradient
Figure 5. A, Wetland index values (WIV) of each site; B, the average site cover descriptions; C, the percentage average growth form distribution at each site; D, the average functional diversity per site (upland (U), facultative upland (FU), facultative (F), facultative wetland (FW), obligate wetland (OB)); arranged along a gradient of increasing urban landcover.
Figure 1 in Plant diversity and conservation value of wetlands along a rural-urban gradient
Figure 1. Study area indicating the urban area of Potchefstroom, its rural surroundings and the 14 wetland study sites. Inset map shows the size and location of the urban area and Mooi River within the former Tlokwe Municipal area.
Genotype and genetic diversity data for: Contrasts in riverscape patterns of intraspecific genetic variation in a diverse Neotropical fish community of high conservation value
<p><span>Spatial patterns in genetic variation compared across species provide information about the predictability of genetic diversity of natural populations and areas requiring conservation measures. Due to their remarkable fish diversity, rivers in Neotropical regions are ideal systems to confront theory with observations and would benefit greatly from such approaches given their increasing vulnerability to anthropogenic pressures. We used SNP data from 18 fish species with contrasting life-history traits, co-sampled across 12 sites in the Maroni – a major river system from the Guiana Shield – to compare patterns of intraspecific genetic variation and identify their underlying drivers. Analyses of covariance revealed a decrease in genetic diversity as distance from the river outlet increased for 5 of the 18 species, illustrating a pattern commonly observed in riverscapes for species with low-to-medium dispersal abilities. However, mean within-site genetic diversity was lowest in the two easternmost tributaries of the Upper Maroni and around an urbanized location downstream, indicating the need to address the potential influence of local pressures in these areas, such as goldmining or fishing. Finally, the relative influence of isolation by stream distance, isolation by discontinuous river flow and isolation by spatial heterogeneity in effective size on pairwise genetic differentiation varied across species. Species with similar dispersal and reproductive guilds did not necessarily display shared patterns of population structure. Increasing the knowledge of specific life history traits and ecological requirements of fish species in these remote areas should help further understand factors that influence their current patterns of genetic variation.</span></p>
Tropical dry woodland loss occurs disproportionately in areas of highest conservation value
<p>This data repository contains the data results used to analyse how deforestation dynamics relate to areas of woodland protection and to conservation priorities across the world's tropical dry woodlands. We do this for the period of 2000 to 2020, at 10-km spatial resolution (Coordinate System: WGS_1984_Mollweide, float format) following Buchadas et al. (2022) methods available in https://doi.org/10.1038/s41893-022-00886-9. Datasets used for this analysis are generally publicly available, forest cover and loss data are available at: https://data.globalforestwatch.org/. The data on protected areas is available at https://www.protectedplanet.net/. The global conservation priority layers have been made openly available as part of Jung et al. (2021) at https://doi.org/10.5281/zenodo.5006332. The map of Indigenous Peoples' Lands can be obtained from the authors on reasonable request (Garnett et al. 2018). The data are not publicly available due to privacy or ethical restrictions. Thus we refrain from sharing the primary data that includes it, here.</p> <p>Further details of the datasets can be found in Buchadas et. al. (2023)</p> <p>For further questions or issues with the datasets, please contact Ana Buchadas at ana.buchadas@geo.hu-berlin.de.</p>
Genotype and genetic diversity data for: Contrasts in riverscape patterns of intraspecific genetic variation in a diverse Neotropical fish community of high conservation value
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Data from: Bird diversity and endemism along a land-use gradient in Madagascar: the conservation value of vanilla agroforests
<div> <div> <p>Land-use change is the most important driver of biodiversity loss worldwide and particularly so in the tropics, where natural habitats are transformed into large-scale monocultures or heterogeneous landscape mosaics of largely unknown conservation value. Using birds as an indicator taxon, we evaluated the conservation value of a landscape mosaic in north-eastern Madagascar, a biodiversity hotspot and the center of global vanilla production. We assessed bird species richness and composition by conducting point counts across seven prevalent land-use types (forest- and fallow-derived vanilla agroforests, woody and herbaceous fallow that are part of a shifting cultivation system, rice paddy, forest fragment and contiguous old-growth forest). We find that old-growth forest had the highest species richness, driven by a high share of endemics. Species richness and community composition in forest-derived vanilla agroforest was similar to forest fragment, whereas fallow-derived vanilla agroforest was most comparable to woody fallow. The open land-use types herbaceous fallow and rice paddy had fewest species. Across forest fragment, vanilla agroforests and woody fallow, endemic bird species richness was positively correlated to landscape-scale forest cover. We conclude that both fallow- and forest-derived vanilla agroforests play an important but contrasting role for bird conservation in the landscape: Fallow-derived agroforests are less valuable but take fallow land out of the shifting cultivation cycle, possibly preventing further degradation. Conversely, forest-derived agroforests contribute to forest degradation but may avoid total loss of forest fragments. Considering the land-use history of agroforests may thus be a promising avenue for future research beyond the case of vanilla.</p> </div> </div>
Data from: Low-productivity boreal forests have high conservation value for lichens
1. Land set aside for preservation of biodiversity often has low productivity. As biodiversity generally increases with productivity, due to higher or more diverse availability of resources, this implies that some of the biodiversity may be left unprotected. Due to a lack of knowledge on the species diversity and conservation value of low-productivity habitats, the consequences of the biased allocation of low-productivity land for set-asides are unknown. 2. We examined the conservation value of boreal low-productivity forests (potential tree growth < 1 m3 ha-1 year-1) by comparing assemblages of tree- and deadwood-dwelling lichens and forest stand structure between productive and low-productivity forest stands. We surveyed 84 Scots pine-dominated stands in three regions in Sweden, each including four stand types: two productive (managed and unmanaged) and two low-productivity stands (on mires and on thin, rocky soils). 3. Lichen species richness was highest in low-productivity stands on thin soil, which had similar amounts and diversity of resources (living trees and dead wood) to productive unmanaged stands. Stands in low-productivity mires, which had low abundance of living trees and dead wood, hosted the lowest lichen richness. Lichen species composition differed among stand types, but none of them hosted unique species. The differences in both species richness and composition were more pronounced in northern than in southern Sweden, likely due to shorter history of intensive forestry. 4. Synthesis and applications: Boreal low-productivity forests can have as high conservation value as productive forests, which should be reflected in conservation strategies. However, their value is far from uniform, and conservation planning should acknowledge this variation and not treat all low-productivity forests as a uniform group. Some types of low-productivity forest (e.g. on thin soil) are more valuable than others (e.g. on mires), and should thus be prioritized in conservation. It is also important to consider the landscape context: low-productivity forests may have higher value in landscapes where high-productivity forests are highly influenced by forestry. Finally, although low-productivity forests can be valuable for some taxa, productive forests may still be important for other taxa.
The umbrella value of caribou management strategies for biodiversity conservation in boreal forests under global change
<p><span>Single-species conservation management is often proposed to preserve biodiversity in human-disturbed landscapes. How global change will impact the umbrella value of single-species management strategies remains an open question of critical conservation importance. We assessed the effectiveness of threatened boreal caribou as an umbrella for bird and beetle conservation under global change. We combined mechanistic, spatially explicit models of forest dynamics and predator-prey interactions to forecast the impact of management strategies on the survival of boreal caribou in boreal forest. We then used predictive models of species occupancy to characterize concurrent impacts on bird and beetle diversity. Landscapes were simulated based on three scenarios of climate change and four of forest management. We found that strategies that best mitigate human impact on boreal caribou were an effective umbrella for maintaining bird and beetle assemblages. While we detected a stronger effect of land-use change compared to climate change, the umbrella value of management strategies for caribou habitat conservation were still impacted by the severity of climate change. Our results showed an interplay among changes in forest attributes, boreal caribou mortality, as well as bird and beetle species assemblages. The conservation status of some species mandates the development of recovery strategies, highlighting the importance of our study which shows that single-species conservation can have important umbrella benefits despite global change.</span></p>
Classification and structural analysis of value chain contracts for biodiversity conservation in the European Union
<p><span>The data provided by this dataset are the raw data published in the paper "<strong>Classification and structural analysis of value chain contracts for biodiversity conservation in the European Union</strong>" (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.sftr.2024.100372" target="_blank" rel="noopener"><span><span>https://doi.org/10.1016/j.sftr.2024.100372</span></span></a>). </span></p>
Data from: Deciduous forests hold conservation value for birds within South Andaman Island, India
<p>We assessed the importance of deciduous and evergreen habitats for forest birds (including several endemic and threatened species) within South Andaman Island, India. To this end, we compared the composition and diversity (taxonomic, functional and phylogenetic) of forest birds across the two habitat types, and evaluted species-specific responses to habitat variables within the island.</p> <p>The dataset collected and R codes used in this study are published here. Bird species traits were sourced from Tobias et al. (2022) and Wilman et al. (2014). Phylogenetic trees were sourced from <a href="https://birdtree.org/">birdtree.org</a> (Jetz et al. 2012).</p> <p><br><strong>Taxonomic Coverage: </strong>Birds, 54 species</p> <p><strong>Geographic Coverage:</strong> South Andaman Island, Andaman and Nicobar Islands, India</p> <p><strong>Temporal Coverage:</strong> March-May 2022 and December 2022-April 2023</p> <p> </p> <p><strong>Brief summary of field methods: </strong><br>We conducted line-transect surveys for forest birds across evergreen and deciduous forests in South Andaman Island, India. <br>Twenty-seven transects were sampled either in the morning (between 0515 – 0930 hrs) or in the afternoon (between 1515 – 1730 hrs) from March-May 2022 and December 2022-April 2023. For every bird detected, we noted species identity, group size (if visible), time of detection, and whether the bird(s) was seen or heard. Detections of flying birds and nocturnal species (owls and nightjars) were excluded.<br>For each transect, we measured - <br>a. tree density and basal area (using the point-centered quarter method, or PCQ); <br>b. canopy cover, proportion of deciduous trees, and presence of cane, bamboo runners and clumps of standing bamboo (averaged across PCQ points);<br>c. number of large trees and cut logs (counted within a 20m-wide belt along each transect); and <br>d. distance from nearest settlement/village (using Google Earth Pro).</p> <p>The dataset published here contains eight data files and two R code files, along with a <strong>ReadMe.txt</strong> file that explains each of these files.</p> <p> </p> <p><strong>Funding:</strong></p> <p>Science and Engineering Research Board (Govt. of India) - SRG/2021/001523</p> <p>The Rufford Foundation</p> <p>The Rauf Ali Fellowship</p> <p>Arvind Datar</p> <p>Rohini Nilekani Philanthropies</p> <p> </p> <p><strong>References:</strong></p> <p>Jetz, W., G. H. Thomas, J. B. Joy, K. Hartmann, and A. O. Mooers. 2012. The global diversity of birds in space and time. Nature 491:444–448.<br>Tobias, J. A., C. Sheard, A. L. Pigot, A. J. M. Devenish, J. Yang, et al. 2022. AVONET: morphological, ecological and geographical data for all birds. Ecology Letters 25:581–597.<br>Wilman, H., J. Belmaker, J. Simpson, C. de la Rosa, M. M. Rivadeneira, and W. Jetz. 2014. EltonTraits 1.0: Species-level foraging attributes of the world’s birds and mammals. Ecology 95:2027–2027.</p>
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