Find research datasets worth reusing

opencc-by-4.0Jun 2022View details →

Data for: Improvements in the Land and Crop Modeling over Flooded Rice Fields by Incorporating the Shallow Paddy Water (Submitting to the Journal of Advances in Modeling Earth Systems)

We incorporated the shallow paddy surface water layer into the Noah-MP land surface model to improve its performance of surface heat fluxes over flooded rice paddies. Field measurements from two crop sites, i.e., SAITO (early rice) and SAGA (late rice), were used to initialize and evaluate the modified Noah-MP model (Maruyama, 2021). Additionally, we investigated the roles of some key parameters in the land and crop modeling.  Note that, all numerical experiments in this study were conducted at the field scale using the offline version of Noah-MP (Niu et al., 2011) running within the High-Resolution Land Data Assimilation System (HRLDAS v3.9; Chen et al., 2007). Please refer to the official HRLDAS/Noah-MP unified Github repository (<a href="https://github.com/NCAR/hrldas">https://github.com/NCAR/hrldas-release</a>) for the original model codes. The related model code modifications and model outputs were included in this dataset. Surface observations for the nearest AMeDAS or meteorological observatory stations were obtained from the Japan Meteorological Agency website (<a href="https://www.jma.go.jp/jma/indexe.html">https://www.jma.go.jp/jma/indexe.html</a>), and were also provided in this dataset.   References Chen, F., Manning, K. W., LeMone, M. A., Trier, S. B., Alfieri, J. G., Roberts, R. D., et al. (2007). Description and evaluation of the characteristics of the NCAR high‐resolution land data assimilation system. Journal of Applied Meteorology and Climatology, 46(6), 694-713. <a href="https://doi.org/10.1175/JAM2463.1">https://doi.org/10.1175/JAM2463.1</a> Maruyama, A. (2021). Data for: Coupling land surface and crop models to estimate the effects of changes in the growing season on energy balance and water use of rice paddies (version 2) [Data set]. Mendeley Data. <a href="https://doi.org/10.17632/tv23z95r5g.2">https://doi.org/10.17632/tv23z95r5g.2</a> Niu, G., Yang, Z., Mitchell, K., Chen, F., Ek, M., Barlage, M., et al. (2011). The community Noah land surface model with multiparameterization options (Noah‐MP): 1. Model description and evaluation with local‐scale measurements. Journal of Geophysical Research, 116, D12109. <a href="https://doi.org/10.1029/2010JD015139">https://doi.org/10.1029/2010JD015139</a>

opencc-by-4.0May 2023View details →

land cover interpreted samples for the Amur River Basin in China

7755  training samples were derived by visually interpreting with eight land cover classes using the Landsat images from Google Earth Engine (GEE).

opencc-zeroMay 2023View details →

Habitat differences influence genetic impacts of human land use on the American beech (Fagus grandifolia)

Natural reforestation after regional forest clearance is a globally common land-use sequence. The genetic recovery of tree populations in these recolonized forests may depend on the biogeographic setting of the landscape, for instance whether they are in the core or in the marginal part of the species' range. Using data from 501 individuals genotyped across 7 microsatellites, we investigated whether regional differences in habitat quality affected the recovery of genetic variation in a wind-pollinated tree species, American beech (Fagus grandifolia) in Massachusetts. We compared populations in forests that were recolonized following agricultural abandonment to those in remnant forests that have only been logged in both central inland and marginal coastal regions. Across all populations in our entire study region, recolonized forests showed limited reduction of genetic diversity as only observed heterozygosity was significantly reduced in these forests (H O = 0.520 and 0.590, respectively). Within inland region, this pattern was observed, whereas in the coast, recolonized populations exhibited no reduction in all genetic diversity estimates. However, genetic differentiation among recolonized populations in marginal coastal habitat increased (F st logged = 0.072; F st secondary = 0.249), with populations showing strong genetic structure, in contrast to inland region. These results indicate that the magnitude of recovery of genetic variation in recolonized populations can vary at different habitats.

opencc-by-4.0May 2023View details →

Technical Land-Sea Spaces. Impacts of the Port Clusterization Phenomenon on coasts, cities and architectures [YouTube Video Version]

Beatrice Moretti lectures on the phenomenon of spatial stretching that is imposing a profound evolution, both formal and institutional, in the sphere of contemporary port cities and regions, by giving first insights about the research methodology oriented in this phase to the definition of a indicator systems of the cluster dimension. The presentation questions the spatial impacts introduced by port clusters in the field of architectural design. [YouTube Video Version] <a href="https://www.iccaua.com/page/conference-brochure">6th International Conference of Contemporary Affairs in Architecture and Urbanism - ICCAUA2023</a> Alanya Hamdullah Emin Paşa University, Istanbul (Turkey) Chairman of the Conference: Dr. <a href="https://arch.alanyahep.edu.tr/en/akademik-kadro">Hourakhsh A. Nia</a>, AHEP University, Alanya, Antalya, TR. Special Session "Coastal and Maritime Spaces", proposed by The University IUAV, Venice (IT) Chairs: Paolo De Martino and Fabio Carella (IUAV).

Data from: Conservation of Chinese Theaceae species under future climate and land use changes

Aim: Climate and land use changes are two major pervasive and growing global causes of rapid changes in the distribution patterns of biodiversity, challenging the future effectiveness of protected areas (PAs), which were mainly designed based on a static view of biodiversity. Therefore, evaluating the effectiveness of protected areas for protecting the species threatened by climate and land use change is critical for future biodiversity conservation. Location: China Methods: Here, using distributions of 200 Chinese Theaceae species and ensemble species distribution models, we identified species threatened by future climate and land use change (i.e. species with predicted loss of suitable habitat ≥ 30%) under scenarios incorporating climate change, land use change and dispersal. We then estimate the richness distribution patterns of threatened species and identify priority conservation areas and conservation gaps of the current PA network. Results: Our results suggest that 36.30%-51.85% of Theaceae species will be threatened by future climate and land use conditions, and that although the threatened species are mainly distributed at low latitudes in China under both current and future periods, the mean richness of the threatened species per grid cell will decline by 0.826-3.188 species by the 2070s. Moreover, we found that these priority conservation areas are highly fragmented and that the current PA network only covers 14.21%-20.87% of the 'areas worth exploring' and 6.91%-7.91% of the 'areas worth attention'. Main conclusions: Our findings highlight the necessity of establishing new protected areas and ecological corridors in priority conservation areas to protect the threatened species. Moreover, our findings also highlight the importance of taking into consideration the potential threatened species under future climate and land use conditions when designating priority areas for biodiversity conservation.

Large-scale restoration of species-rich dry grasslands on arable land: Environmental filtering drives successful species establishment over a period of 10 years

Sowing of regionally specific seed mixtures on former arable land is increasingly used to restore species-rich grasslands, but it often faces important obstacles in environmental conditions and colonisation from preserved surrounding grasslands. Long-term landscape scale studies, which explore the processes governing plant establishment from seed mixtures and later colonisation from the surrounding landscape are scarce. We studied the species and functional trait composition of 32 grasslands restored 1–11 years before the first sampling by sowing regional seed mixtures in the White Carpathian Mts (SE Czech Republic). We compared them with 23 well-preserved permanent grasslands in their surroundings. In each grassland we estimated plant species cover in three plots of 25 m2, in restored grasslands in 2009, 2014 and 2019, in permanent grasslands in 2009. The species composition of the restored grasslands converged towards the permanent grasslands due to expansion of dry grassland species and retreat of mesic grassland and weed species. The majority (60–71%) of the vegetation cover of restored grasslands was formed by sown species, while the species number was mainly determined by colonising unsown species (61–63%). The species number of restored grasslands remained lower than that in permanent grasslands. Functional trait composition (Community Weighted Mean) of the sown seed mixtures, permanent grasslands and restored grasslands overlapped in all three samplings. With increasing grassland age, species with resource-retaining traits of low specific leaf area and high leaf dry matter content, lower stature, higher seed mass, and lower capacity for clonal reproduction expanded. Functional trait diversity of the plots was mostly lower than expected by null model randomisations of community, which indicates strong environmental filtering. Comparison of newly colonising species and extinct species indicated that mainly species with traits similar to the rest of the community are able to colonise the grasslands successfully. Synthesis and applications. Sowing of regionally specific seed mixtures was successful and demonstrated to be a fast way of grassland restoration, particularly in terms of functional trait composition. The resulting species diversity depended on the colonisation processes, which are controlled by the functional composition of the local communities.

opencc-by-4.0Jun 2023View details →

Bergbaustandorte im Land Salzburg 1857-1880

Der Datensatz dokumentiert die Standorte der Montanindustrie im Land Salzburg zu den Stichjahren 1857 und 1880. Er umfasst Informationen zur Art und Größe des Betriebes, zu den abgebauten oder verarbeiteten Rohstoffen, zur Anzahl der Beschäftigten und zu leitenden Personen. Die Informationen wurden dem &bdquo;Montan-Handbuch des Österreichischen Kaiserthums für 1857“, bzw. dem &bdquo;Österreichischen Montan-Handbuch für das Jahr 1880“ entnommen, fehlende Daten verweisen auf nicht vorhandene Informationen in der Quelle. Die Standorte sind mit Geodaten identifiziert. Der Datensatz entstand im Rahmen des KO &bdquo;Einführung in die Arbeit mit historischen Geoinformationssystemen. Ressourcenwissen des 19. Jahrhunderts kartieren“ (Leitung Prof. Dr. Sebastian Haumann) im Sommersemester 2023 an der Paris Lodron Universität Salzburg.

APPENDIX 13 in Detangling the effects of patch attributes on bryophyte diversity in fragmented subtropical secondary forests - a case study of land-bridge islands

APPENDIX 13. — Islands with multi-long branched appearance in the Thousand Island Lake, China.

Gray wolf range in the western Great Lakes region under forecasted land use and climate change

Land use and climate alter species distributions worldwide, and detecting and understanding how species ranges shift can facilitate conservation planning and action. Following extirpation from most of the contiguous USA, gray wolves (Canis lupus) have partially recolonized former range in the western Great Lakes region, but it is unknown how land use and climate change may alter amounts of wolf habitat. Using wolf observation data collected during winters 2017–2020 in Minnesota, Wisconsin, and Michigan, we created ensemble models to predict how land use and climate change may affect the amount of wolf habitat within these states. A projection model for the western Great Lakes region suggested three of four scenarios of land use and climate change will lead to 9–35% increases in wolf habitat, while a solely climate-based projection model supported our expectation that changes in climate, in isolation, will have limited effect on current wolf range. Our results support stable or increasing amounts of wolf habitat in the western Great Lakes region during the 21st century, suggesting limited or no adverse effects on the current distribution or further recolonization of wolves. Our findings can inform policy development regarding wolf conservation, and identify areas where recolonization is plausible, thus where promoting human-wolf co-existence is most pertinent.

Data for: Diversity and specialization responses to climate and land use differ between deadwood fungi and bacteria

This dataset contains data from a field study conducted in 2019 and described in the manuscript "Diversity and specialization responses to climate and land use differ between deadwood fungi and bacteria". To test the effects of land use and climate on diversity and community specialization (H2') of deadwood-inhabiting microbes, we exposed branches of four different tree species at 179 study sites, distributed over a spatial extent of 300 km x 300 km and 1000 m in elevation. Study sites were established in four local land-use types: forests, grasslands, arable sites, and settlements, embedded in near-natural, agricultural, or urban landscapes. We used negative-binomial generalized linear models for diversity and calculated community specialization on host trees by using the standardized two-dimensional Shannon entropy (H2') and beta-regression models. Our results show that host identity and hence specialization strongly exceed the effects of climate and land use for fungal but not bacterial communities. This suggests contrasting responses between microbial taxa to climate change and land-use intensification with further consequences on deadwood diversity interactions and hence decomposition processes.

Data from: Multiple facets of biodiversity are threatened by mining-induced land-use change in the Brazilian Amazon

Aim Mining is increasingly pressuring areas of critical importance for biodiversity conservation, such as the Brazilian Amazon. Biodiversity data are limited in the tropics, restricting the scope for risks to be appropriately estimated before mineral licencing decisions are made. As the distributions and range sizes of other taxa differ markedly from those of vertebrates – the common proxy for analysis of risk to biodiversity from mining – whether mining threatens lesser-studied taxonomic groups differentially at a regional scale is unclear. Location Brazilian Amazon Methods We assess risks to several facets of biodiversity from industrial mining by comparing mining areas (within 70km of an active mining lease) and areas unaffected by mining, employing species richness, species endemism, phylogenetic diversity, and phylogenetic endemism metrics calculated for angiosperms, arthropods, and vertebrates. Results Mining areas contained higher densities of species occurrence records than the unaffected landscape, and we accounted for this sampling bias in our analyses. None of the four biodiversity metrics differed between mining and non-mining areas for vertebrates. For arthropods, species endemism was greater in mined areas. Mined areas also had greater angiosperm species richness, phylogenetic diversity, and phylogenetic endemism, although lower species endemism than unmined areas. Main Conclusions Unlike for vertebrates, facets of angiosperm and arthropod diversity are relatively higher in areas of mining activity, underscoring the need to consider multiple taxonomic groups and biodiversity facets when assessing risk and evaluating management options for mining threats. Particularly concerning is the proximity of mining to areas supporting deep evolutionary history, which may be impossible to recover or replace. As pressures to expand mining in the Amazon grow, impact assessments with broader taxonomic reach and metric focus will be vital to conserving biodiversity in mining regions.

opencc-by-4.0Jun 2023View details →

Land cover maps: End-to-end Learning for Land Cover Classification using Irregular and Unaligned SITS by Combining Attention-Based Interpolation with Sparse Variational Gaussian Processes

Land cover maps obtained with mTAN-GP, mTAN-MLP, mTAN-LTAE and raw-LTAE models for the year 2018 with Sentinel-2 acquisitions. For further details see the pre-print article "End-to-end Learning for Land Cover Classification using Irregular and Unaligned SITS by Combining Attention-Based Interpolation with Sparse Variational Gaussian Processes ". This article is available : <a href="https://hal.science/hal-04112115">here</a>.

opencc-by-4.0Jul 2023View details →

Country-level estimates of gross and net carbon fluxes from land use, land-use change and forestry

The datasets contain country-level net and gross CO2 flux data for land use, land-use change and forestry (LULUCF) from various approaches as used in the paper "Country-level estimates of gross and net carbon fluxes from land use, land-use change and forestry" (<a href="https://doi.org/10.5194/essd-16-605-2024">Obermeier et al., 2024, Earth System Science Data</a>).

Validation of C3S SM combined v202212 vs C3S SM combined v202012 vs ERA5-Land v20190904

QA4SM validation: C3S SM combined v202212 vs C3S SM combined v202012 vs ERA5-Land v20190904. URL: https://qa4sm.eu/ui/validation-result/80beb102-f5f4-4b1a-94f4-57008df9e322. Produced on QA4SM (https://qa4sm.eu)

Validation of C3S SM combined v202212 vs C3S SM combined v202012 vs ERA5-Land v20190904

QA4SM validation: C3S SM combined v202212 vs C3S SM combined v202012 vs ERA5-Land v20190904. URL: https://qa4sm.eu/ui/validation-result/aaf66b58-ce30-4754-9349-8c48dcf81595. Produced on QA4SM (https://qa4sm.eu)

Effects of land use and climate change on functional and phylogenetic diversity of terrestrial vertebrates in a Himalayan biodiversity hotspot

Aim: Land use and climate change interact to impact functional and phylogenetic diversity globally, but this pattern is largely unknown in the eastern Himalayas. We aim to discern the response of community diversity and structure of terrestrial mammals and birds to anthropogenic land use and climate change in this hitherto understudied landscape. Location: Himalayan biodiversity hotspot, Bhutan Methods: We used camera trap and point-count transect data to estimate taxonomic, functional, and phylogenetic diversity while accounting for detectability. We calculated the abundance-weighted standardised effect sizes (ses) of mean pairwise distance and mean nearest taxon distance. The ses metrics were regressed against land use (agriculture and forest) and climate (temperature and precipitation) variables using linear mixed effect models. Results: Community diversity declined with agriculture in both groups. Mammal diversity was higher farther from the settlement but birds remained indifferent. Temperature and precipitation were positively associated with mammal diversity, but birds displayed a mixed response: negative with temperature and positive with precipitation. Agriculture had a strong negative effect on the functional structure of birds but not mammals. The functional and phylogenetic structure declined farther from the settlement for mammals but increased for birds. Except for the functional structure, all other metrics increased with temperature and precipitation for mammals. Except for the positive relationship between functional structure and temperature, other metrics showed a mixed response to climate in birds. Main conclusions: Our findings provide evidence that land use rather than climate has an imminent effect in shaping local and regional patterns of terrestrial vertebrate diversity in a Himalayan biodiversity hotspot. Climate effects, although weak, may reduce functional traits and consequently diminish functional roles. Species that can persist in human-modified environments are clustered within a phylogeny, suggesting possible loss of phylogenetic diversity.

opencc-by-4.0Jun 2023View details →

MAgPIE model runs csv for plotting: Climate change-driven global land-use system adaptation under CMIP6-based crop model projections

This .zip file contains the data used to create the figures for the paper. It includes .csv files and .nc files for maps. This version includes additional files like the mapping between countries and MAgPIE're economic regions.

A secure future? Human urban and agricultural land use benefits a flightless island-endemic rail despite climate change

Identifying environmental characteristics that limit species' distributions is important for contemporary conservation and inferring responses to future environmental change. The Tasmanian native hen is an island-endemic flightless rail and a survivor of a prehistoric extirpation event. Little is known about the regional-scale environmental characteristics influencing the distribution of native hens, or how their future distribution might be impacted by environmental shifts (e.g., climate change). Using a combination of local fieldwork and species distribution modelling, we assess environmental factors shaping the contemporary distribution of the native hen, and project future distribution changes under predicted climate change. We find 37.2% of Tasmania is currently suitable for the native hens, owing to low summer precipitation, low elevation, human-modified vegetation, and urban areas. Moreover, in unsuitable regions, urban areas can create 'oases' of habitat, able to support populations with high breeding activity by providing resources and buffering against environmental constraints. Under climate change predictions, native hens were predicted to lose only 5% of their occupied range by 2055. We conclude that the species is resilient to climate change and benefits overall from anthropogenic landscape modifications. As such, this constitutes a rare example of a flightless rail to have adapted to human activity.

openAug 2023View details →

Tropical Andes Land Cover Dataset (TALANDCOVER)

The Tropical Andes Land Cover Dataset (TALANDCOVER) was built for the department of Antioquia Colombia and consists of three folders for the three types of sampling.<ul><li>Random: 5000 images</li><li>Balanced of minimum 50% coverage per class: 1389 images</li><li>Balanced of minimum 70% coverage per class:731 images</li></ul>The coordinate system of each dataset is EPSG:3857 - WGS 84 / Pseudo-Mercator with spatial resolution of 4.77 meters and 128*128px.Example of image and corresponding label name:<ul><li>image_PNICFI_D2019-05_T586-1068_C1_N100.tif</li><li>label_PNICFI_D2019-05_T586-1068_C1_N100.tif</li></ul>Pixel values for label are:0 Bare-degraded lands 1 Grasslands 2 Heterogeneous agricultural areas 3 Dense forest 4 Water bodies 5 Built-up areasThere are multiple keywords intentionally inserted in each image name or label name that enable the split of the name in pieces of information about each image and label metadata.Spliting the image or label name by the keywords, would get 6 items:<ol><li>The item (image/label) describe if the file correspond to a patch image or a patch label.</li><li>The second item (Keyword "_P") gives the name of the product NICFI (<a href="https://assets.planet.com/docs/NICFI_User_Guide_v4_EN.pdf">https://assets.planet.com/docs/NICFI_User_Guide_v4_EN.pdf</a>)</li><li>The third item (keyword "_D") gives a date for the composite</li><li>The fourth (keyword "_T") gives the tile number, as stated in the planet scope visual base map documentation: "The name of each basemap quad within the Basemaps API is designed to represent the x and y position of the quad within the two dimensional grid which makes up the basemap. It is generally {X}-{Y}, where X and Y are the x and y position of the quad in the grid". <a href="https://developers.planet.com/docs/data/visual-basemaps/">https://developers.planet.com/docs/data/visual-basemaps/</a></li><li>The fifth (keyword "_C") when available gives the cover class used by the slidding windows to extract the patch, resulting in at least a minimum of 50% or 70% of the pixels within the image correspond to that specific cover class, depending on the selected sample dataset.</li></ol>Take into account that random samples dont have this keyword since the patches where collected at random from a 2d grid without regard of the cover classes present Article : "Land Cover Classification in the Antioquia Region of the Tropical Andes Using NICFI Satellite Data Program Imagery and Semantic Segmentation Techniques".