This statistic shows the net distribution data center square footage, by data center type, in North America as of year-end 2016. At that time, 13.7 percent of data centers in North America were cloud data centers.

These data are species distribution information assembled for assessing the impacts of land-use barriers, facilitative interactions with other species, and loss of long-distance animal dispersal on predicted species range patterns for four common species in pinyon-juniper woodlands in the western United States. The layers in the data release are initial distribution records of two kinds: point occurrence records and a raster layer for the general vegetation types where the species is a co-dominant, compiled from other sources. Both types of data are the baseline information in species distribution models for the associated publication(see Larger Work Citation).

Projected changes in habitat suitability for 33 marine species on the Northeast US shelf. Changes in habitat suitability are calculated based on species distribution models fit to bottom trawl survey data from the NOAA Northeast Fisheries Science Center. Positive values indicate an increase in habitat suitability by 2040-2050 relative to historical (1963-2005). The spatial resolution of projections is 0.25 x 0.25 degrees. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson acquisition_description=The following methods are excerpted from Rogers et al. (in press):
Bottom trawl data from the NOAA Northeast Fisheries Science Center (NEFSC) fall (1963-2014) surveys were used to characterize the realized thermal niches of species. At each survey station, fish of each species were counted and weighed, and surface and bottom temperature measurements were taken. Correction factors were applied to standardize catch rates for changes in vessel and gear type. A total of 33 species were selected based on their near continuous presence in the survey as well as relative importance to commercial fisheries. For 4 species, data from 1972 onwards were used because observations were irregular prior to that year.

Generalized Additive Models were used to estimate the realized thermal niches of species. We restricted k (number of knots) to 4 or 6 for each of our covariates to ensure biologically meaningful responses. Our response variable was probability of occurrence in a trawl haul, and we used a binomial response with logit transform:

p(occur\u1d67,\u2c7c) ~ logit-1 (s(ST\u1d67,\u2c7c)+s(BT\u1d67,\u2c7c)+s(meanbiomass\u1d67)+s(rugosity\u2c7c))

where ST\u1d67,\u2c7c and BT\u1d67,\u2c7c are sea surface temperature and bottom temperature measured at each haul location j in year y, and meanbiomass\u1d67 is the average annual catch across all hauls to account for interannual changes in abundance due to, e.g., fishing. Rugosity\u1d67 is a measure of benthic habitat roughness, measured as the Terrain Ruggedness Index, using the GEBCO 2014 30-arcsecond bathymetry data (downloaded 4 Feb 2015 from http://www.gebco.net/). The resulting estimated smooth functions describing the relationship between probability of occurrence and temperature can be interpreted as realized thermal niches.

For each species, the change in predicted probability of occurrence under future (2040-2050) projected climate conditions was compared to historical (1963-2005) conditions for each cell within a 0.25\u00b0x0.25\u00b0 spatial grid. Because the modeled probability of occurrence included a component of catchability, values for each species were scaled by dividing by the maximum observed or predicted probability of occurrence across the study area. Positive values for a grid square indicated a projected increase in probability of occurrence, whereas negative values indicated a projected decrease in probability of occurrence.

See related dataset for\u00a0NEFSC bottom trawl data:\u00a0"%5C%22https://www.bco-%0Admo.org/dataset/753142%5C%22">https://www.bco- dmo.org/dataset/753142\u00a0(doi:\u00a010.1575/1912/bco-dmo.753142.1) awards_0_award_nid=559955 awards_0_award_number=OCE-1426891 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1426891 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=Michael E. Sieracki awards_0_program_manager_nid=50446 cdm_data_type=Other comment=Projected changes in habitat suitability PIs: Lauren Rogers & Malin Pinsky Version date: 22-April-2019 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.765386.1 Easternmost_Easting=-64.875 geospatial_lat_max=44.875 geospatial_lat_min=33.625 geospatial_lat_units=degrees_north geospatial_lon_max=-64.875 geospatial_lon_min=-76.875 geospatial_lon_units=degrees_east infoUrl=https://www.bco-dmo.org/dataset/765386 institution=BCO-DMO keywords_vocabulary=GCMD Science Keywords metadata_source=https://www.bco-dmo.org/api/dataset/765386 Northernmost_Northing=44.875 param_mapping={'765386': {'lat': 'master - latitude', 'lon': 'master - longitude'}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/765386/parameters people_0_affiliation=Rutgers University people_0_person_name=Malin Pinsky people_0_person_nid=554708 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=Stanford University people_1_person_name=Lauren Rogers people_1_person_nid=765425 people_1_role=Principal Investigator people_1_role_type=originator people_2_affiliation=Stanford University people_2_person_name=Robert Griffin people_2_person_nid=768380 people_2_role=Co-Principal Investigator people_2_role_type=originator people_3_affiliation=Rutgers University people_3_person_name=Kevin St. Martin people_3_person_nid=559961 people_3_role=Co-Principal Investigator people_3_role_type=originator people_4_affiliation=Princeton University people_4_person_name=Emma Fuller people_4_person_nid=748888 people_4_role=Scientist people_4_role_type=originator people_5_affiliation=Rutgers University people_5_person_name=Talia Young people_5_person_nid=752628 people_5_role=Scientist people_5_role_type=originator people_6_affiliation=National Oceanic and Atmospheric Administration - Alaska Fisheries Science Center people_6_affiliation_acronym=NOAA-AFSC people_6_person_name=Lauren Rogers people_6_person_nid=765425 people_6_role=Contact people_6_role_type=related people_7_affiliation=Woods Hole Oceanographic Institution people_7_affiliation_acronym=WHOI BCO-DMO people_7_person_name=Shannon Rauch people_7_person_nid=51498 people_7_role=BCO-DMO Data Manager people_7_role_type=related project=CC Fishery Adaptations projects_0_acronym=CC Fishery Adaptations projects_0_description=Description from NSF award abstract: Climate change presents a profound challenge to the sustainability of coastal systems. Most research has overlooked the important coupling between human responses to climate effects and the cumulative impacts of these responses on ecosystems. Fisheries are a prime example of this feedback: climate changes cause shifts in species distributions and abundances, and fisheries adapt to these shifts. However, changes in the location and intensity of fishing also have major ecosystem impacts. This project's goal is to understand how climate and fishing interact to affect the long-term sustainability of marine populations and the ecosystem services they support. In addition, the project will explore how to design fisheries management and other institutions that are robust to climate-driven shifts in species distributions. The project focuses on fisheries for summer flounder and hake on the northeast U.S. continental shelf, which target some of the most rapidly shifting species in North America. By focusing on factors affecting the adaptation of fish, fisheries, fishing communities, and management institutions to the impacts of climate change, this project will have direct application to coastal sustainability. The project involves close collaboration with the National Oceanic and Atmospheric Administration, and researchers will conduct regular presentations for and maintain frequent dialogue with the Mid-Atlantic and New England Fisheries Management Councils in charge of the summer flounder and hake fisheries. To enhance undergraduate education, project participants will design a new online laboratory investigation to explore the impacts of climate change on fisheries, complete with visualization tools that allow students to explore inquiry-driven problems and that highlight the benefits of teaching with authentic data. This project is supported as part of the National Science Foundation's Coastal Science, Engineering, and Education for Sustainability program - Coastal SEES. The project will address three questions: 1) How do the interacting impacts of fishing and climate change affect the persistence, abundance, and distribution of marine fishes? 2) How do fishers and fishing communities adapt to species range shifts and related changes in abundance? and 3) Which institutions create incentives that sustain or maximize the value of natural capital and comprehensive social wealth in the face of rapid climate change? An interdisciplinary team of scientists will use dynamic range and statistical models with four decades of geo-referenced data on fisheries catch and fish biogeography to determine how fish populations are affected by the cumulative impacts of fishing, climate, and changing species interactions. The group will then use comprehensive information on changes in fisher behavior to understand how fishers respond to changes in species distribution and abundance. Interviews will explore the social, regulatory, and economic factors that shape these strategies. Finally, a bioeconomic model for summer flounder and hake fisheries will examine how spatial distribution of regulatory authority, social feedbacks within human communities, and uncertainty affect society's ability to maintain natural and social capital. projects_0_end_date=2018-08 projects_0_geolocation=Northeast US Continental Shelf Large Marine Ecosystem projects_0_name=Adaptations of fish and fishing communities to rapid climate change projects_0_project_nid=559948 projects_0_start_date=2014-09 sourceUrl=(local files) Southernmost_Northing=33.625 standard_name_vocabulary=CF Standard Name Table v55 version=1 Westernmost_Easting=-76.875 xml_source=osprey2erddap.update_xml() v1.3

Since 2005, Fisheries and Oceans Canada has been collecting monitoring data for aquatic invasive species (e.g. https://open.canada.ca/data/en/dataset/8d87f574-0661-40a0-822f-e9eabc35780d, https://open.canada.ca/data/en/dataset/503a957e-7d6b-11e9-aef3-f48c505b2a29, https://open.canada.ca/data/en/dataset/8661edcf-f525-4758-a051-cb3fc8c74423). This monitoring data, as well additional occurrence information from online databases and the scientific literature, have been paired with high resolution environmental data and oceanographic models in species distribution models that predict the present-day and future potential distributions of 12 moderate to high risk invasive species on Canada’s east and west coasts. Future distributions were predicted for 2075, under Representative Concentration Pathway 8.5 from the Intergovernmental Panel on Climate Change’s fifth Assessment Report. Present-day and future richness of these species (i.e., hotspots) has also been estimated by summing their occurrence probabilities. This data set includes the occurrence locations of each species, the present-day and future species distribution modeling results for each species, and the estimated species richness. This research has been published in the scientific literature(Lyons et al. 2020). Lyons DA, Lowen JB, Therriault TW, Brickman D, Guo L, Moore AM, Peña MA, Wang Z, DiBacco C. (In Press) Identifying Marine Invasion Hotspots Using Stacked Species Distribution Models. Biological Invasions Cite this data as: Lyons DA., Lowen JB, Therriault TW., Brickman D., Guo L., Moore AM., Peña MA., Wang Z., DiBacco C. Data of: Species distribution models and occurrence data for marine invasive species hotspot identification. Published: November 2020. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/1bbd5131-8b34-4245-b999-3b4c4259d74f

AbundantCenter R Code.txt: R code used for processing data and performing analyses. SppList.csv: List of species in Breeding Bird Survey data. ‘SppID’ is the identification number assigned for our analysis; we combined infraspecific taxa (e.g. great blue heron and the white morph known as great white heron) and did not include taxa that could not be identified to species (these are given ‘NA’ for SppID). ‘Aou’ are the original BBS species indentification numbers. 'Common.Name’ provide the English common name for species without infraspecific taxa names. ‘Common.Name.1’ includes infraspecific taxa names. ‘scinamemap’ is the file name for the BirdLife range map shapefile. SppRelationships.zip: Contains image files (.png) for each species that show geographic and climate abundance maps, and abundance-range position relationships In maps, cell aggregated abundances are depicted from low values in blue to high values in orange; the geographic or climatic area covered by North America is depi...

Forage species such as Pacific sardine, northern anchovy, and market squid are critical ecological links between the planktonic food web and higher trophic levels in the California Current System, as well as supporting valuable fisheries. Environmental variability drives large fluctuations in their abundance and distribution. This dataset includes the outputs of Species Distribution Models (SDMs) for 6 key forage species, combining multiple survey datasets with environmental fields from a high-resolution Regional Ocean Modeling System (ROMS) developed at the University of California - Santa Cruz, and the Copernicus-Globcolour interpolated surface chlorophyll product (https://doi.org/10.48670/moi-00100). The sardine and anchovy SDMs also included predictors indexing stock biomass (MacCall et al. 2016; Kuriyama et al. 2020). As temporally continuous salinity fields are not available from the UCSC ROMS, we included a measure of the distance to the nearest major river (mean > 50,000 CFS discharge) in the herring SDM, to capture to association of this species with estuaries. The 6 species represented are Pacific sardine (Sardinops sagax), northern anchovy (Engraulis mordax), market squid (Doryteuthis opalescens), Pacific herring (Clupea pallasii), Pacific (chub) mackerel (Scomber japonicus), and Jack mackerel (Trachurus symmetricus). Results from two different SDMs are shown: Generalized Additive Models and Boosted Regression Trees, and both models predict the probability of occurrence of each species. We used data from the NOAA Southwest Fisheries Science Center Coastal Pelagic Species and Columbia River Predator (Emmett et al. 2006) trawl surveys to train all SDMs, with the exception of market squid, where juvenile salmon survey data were used instead (see Chasco et al. 2022 for description of these data). More details on preliminary versions of the sardine and anchovy SDMs are available in Muhling et al. (2019). An additional manuscript in preparation will include description of up-to-date data, methods, and model structure. Until this is published, we strongly recommend contacting Barbara Muhling (Barbara.Muhling@noaa.gov) before working with this dataset, to ensure complete understanding of the details and caveats. Funding for this work was provided by NOAA Office of Sustainable Fisheries, and the NOAA Climate and Fisheries Adaptation program. References Chasco, B. E., Hunsicker, M. E., Jacobson, K. C., Welch, O. T., Morgan, C. A., Muhling, B. A., & Harding, J. A. (2022). Evidence of Temperature-Driven Shifts in Market Squid Doryteuthis opalescens Densities and Distribution in the California Current Ecosystem. Marine and Coastal Fisheries, 14(1), e10190. Emmett, R. L., Krutzikowsky, G. K., & Bentley, P. (2006). Abundance and distribution of pelagic piscivorous fishes in the Columbia River plume during spring/early summer 1998-2003: relationship to oceanographic conditions, forage fishes, and juvenile salmonids. Progress in Oceanography, 68(1), 1-26. Kuriyama, P. T., Zwolinski, J. P., Hill, K. T., & Crone, P. R. (2020). Assessment of the Pacific sardine resource in 2020 for US management in 2020-2021. NOAA Technical Memorandum NOAA-TM-NMFS-SWFSC-628 MacCall, A. D., Sydeman, W. J., Davison, P. C., & Thayer, J. A. (2016). Recent collapse of northern anchovy biomass off California. Fisheries Research, 175, 87-94. Muhling, B., Brodie, S., Snodgrass, O., Tommasi, D., Dewar, H., Childers, J., Jacox, M. Edwards, C. A., Xu, Y. & Snyder, S. (2019). Dynamic habitat use of albacore and their primary prey species in the California Current System. CalCOFI Reports 60: 1-15.

This dataset contains the historical Unidata Internet Data Distribution (IDD) Global Observational Data that are derived from real-time Global Telecommunications System (GTS) reports distributed via the Unidata Internet Data Distribution System (IDD). Reports include surface station (SYNOP) reports at 3-hour intervals, upper air (RAOB) reports at 3-hour intervals, surface station (METAR) reports at 1-hour intervals, and marine surface (BUOY) reports at 1-hour intervals. Select variables found in all report types include pressure, temperature, wind speed, and wind direction. Data may be available at mandatory or significant levels from 1000 millibars to 1 millibar, and at surface levels. Online archives are populated daily with reports generated two days prior to the current date.

The three model types compared are logistic model (LM), boosted regression trees (BRT), and MaxEnt models. The descriptions of the rarity types A-H are provided in Table A in S3 File.A table summarizing the Tukey's test [64] after the analysis of variance that evaluated the sources of effects on the performance of species distribution models.

Description: This dataset contains layers of predicted occurrence for 65 groundfish species as well as overall species richness (i.e., the total number of species present) in Canadian Pacific waters, and the median standard error per grid cell across all species. They cover all seafloor habitat depths between 10 and 1400 m that have a mean summer salinity above 28 PSU. Two layers are provided for each species: 1) predicted species occurrence (prob_occur) and 2) the probability that a grid cell is an occurrence hotspot for that species (hotspot_prob; defined as being in the lower of: 1) 0.8, or 2) the 80th percentile of the predicted probability of occurrence values across all grid cells that had a probability of occurrence greater than 0.05.). The first measure provides an overall prediction of the distribution of the species while the second metric identifies areas where that species is most likely to be found, accounting for uncertainty within our model. All layers are provided at a 1 km resolution. Methods: These layers were developed using a species distribution model described in Thompson et al. 2023. This model integrates data from three fisheries-independent surveys: the Fisheries and Oceans Canada (DFO) Groundfish Synoptic Bottom Trawl Surveys (Sinclair et al. 2003; Anderson et al. 2019), the DFO Groundfish Hard Bottom Longline Surveys (Lochead and Yamanaka 2006, 2007; Doherty et al. 2019), and the International Pacific Halibut Commission Fisheries Independent Setline Survey (IPHC 2021). Further details on the methods are found in the metadata PDF available with the dataset. Abstract from Thompson et al. 2023: Predictions of the distribution of groundfish species are needed to support ongoing marine spatial planning initiatives in Canadian Pacific waters. Data to inform species distribution models are available from several fisheries-independent surveys. However, no single survey covers the entire region and different gear types are required to survey the range of habitats that are occupied by groundfish. Bottom trawl gear is used to sample soft bottom habitat, predominantly on the continental shelf and slope, whereas longline gear often focuses on nearshore and hardbottom habitats where trawling is not possible. Because data from these two gear types are not directly comparable, previous species distribution models in this region have been limited to using data from one survey at a time, restricting their spatial extent and usefulness at a regional scale. Here we demonstrate a method for integrating presence-absence data across surveys and gear types that allows us to predict the coastwide distributions of 66 groundfish species in British Columbia. Our model leverages the use of available data from multiple surveys to estimate how species respond to environmental gradients while accounting for differences in catchability by the different surveys. Overall, we find that this integrated method has two main benefits: 1) it increases the accuracy of predictions in data-limited surveys and regions while having negligible impacts on the accuracy when data are already sufficient to make predictions, 2) it reduces uncertainty, resulting in tighter confidence intervals on predicted species occurrences. These benefits are particularly relevant in areas of our coast where our understanding of habitat suitability is limited due to a lack of spatially comprehensive long-term groundfish research surveys. Data Sources: Research data was provided by Pacific Science’s Groundfish Data Unit for research surveys from the GFBio database between 2003 and 2020 for all species which had at least 150 observations, across all gear type and survey datasets available. Uncertainties: These are modeled results based on species observations at sea and their related environmental covariate predictions that may not always accurately reflect real-world groundfish distributions though methods that integrate different data types/sources have been demonstrated to improve model inference by increasing the accuracy of the predictions and reducing uncertainty.

European Union - Distribution of population by household types: Two adults younger than 65 years was 12.00% in December of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for European Union - Distribution of population by household types: Two adults younger than 65 years - last updated from the EUROSTAT on March of 2025. Historically, European Union - Distribution of population by household types: Two adults younger than 65 years reached a record high of 13.10% in December of 2012 and a record low of 12.00% in December of 2023.

This dataset contains a collection of known point locations of humpback whales identified through direct human observation via shipborne and aerial surveys. This can be useful for assessing species abundance, population structure, habitat use, and behavior. This collection is aggregated from multiple data sources and survey periods listed below. Each data point contains attributes for further information about the time and source of the observation. This dataset was compiled by the Pacific Islands Ocean Observing System (PacIOOS) and may be updated in the future if additional data sources are acquired. Cascadia Research Collective (CRC) has been undertaking shipborne surveys for cetaceans in Hawaiian waters since 2000. In addition, Dr. Joseph Mobley of the Marine Mammal Research Consultants (MMRC) led aerial surveys for cetaceans in Hawaiian waters from 1993-2003.

This dataset contains the digitized treatments in Plazi based on the original journal article Grubbs, Scott A., Pessino, Massimo, DeWalt, R. Edward (2012): Michigan Plecoptera (Stoneflies): Distribution Patterns And An Updated Species List. Illiesia 8 (18): 162-173, DOI: http://doi.org/10.5281/zenodo.4753235

Understanding influences of environmental change on biodiversity requires consideration of more than just species richness. Here we present a novel framework for understanding possible changes in species’ abundance structures within communities under climate change. We demonstrate this using comprehensive survey and environmental data from 1,748 woody plant communities across southeast Queensland, Australia, to model rank-abundance distributions (RADs) under current and future climates. Under current conditions, the models predicted RADs consistent with the region’s dominant vegetation types. We demonstrate that under a business as usual climate scenario, total abundance and richness may decline in subtropical rainforest and shrubby heath, and increase in dry sclerophyll forests. Despite these opposing trends, we predicted evenness in the distribution of abundances between species to increase in all vegetation types. By assessing the information rich, multidimensional RAD, we show that ...

Geographic distribution data were collected based on county level occurrences (or converted from point occurrences to county level occurrences) within the five focal states (Minnesota, North Dakota, South Dakota, Nebraska & Iowa) and each U.S. state or Canadian province bordering those focal states (Wisconsin, Illinois, Missouri, Kansas, Wyoming, & Montana in the USA and Saskatchewan, Ontario & Manitoba in Canada).

Preserving native species diversity is fundamental to ecosystem conservation. Selecting appropriate native species for use in restoration is a critical component of project design and may emphasize species attributes such as life history, functional type, pollinator services, and nutritional value for wildlife. Determining which species are likely to establish and persist in a particular environment is a key consideration. Species distribution models (SDMs) characterize relationships between species occurrences and the physical environment (e.g., climate, soil, topographic relief) and provide a mechanism for assessing which species may successfully propagate at a restoration site. In conjunction with information on species attributes, SDMs facilitate holistic ecosystem restoration by enabling practitioners to identify diverse, resilient assemblages of native species. This project develops SDMs for native species of fundamental ecosystem importance in order to guide restoration of Mojave Desert landscapes. The dataset contained herein provides an SDM for Achnatherum hymenoides within its Mojave Desert range based on known occurrences.

Cyprus - Distribution of population by household types: Three or more adults was 14.60% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Cyprus - Distribution of population by household types: Three or more adults - last updated from the EUROSTAT on March of 2025. Historically, Cyprus - Distribution of population by household types: Three or more adults reached a record high of 14.60% in December of 2024 and a record low of 6.20% in December of 2022.

This dataset contains information extracted from 70 studies identified through a systematic review of the peer-reviewed literature (Web of Science and SCOPUS databases both searched on the 13/02/2023) to evaluate the effect of spatial sampling bias correction methods in presence-only species distribution models., Web of Science and SCOPUS databases were searched on the 13/02/2023 using the following search string: ALL=(("species distribution*" OR SDM OR "environmental niche" OR ENM OR "resource selection" OR "habitat selection" OR suitability OR occurrence) AND ("presence-only" OR “presence data†OR "presence-background" OR “pseudo absence†OR opportunistic OR “citizen science†OR preferential OR maxent OR biomod)) After removing duplicates, the search returned 8564 unique studies, and these were further filtered to remove studies that fell outside of the review subject area based on the title and abstract and then the remaining studies were filtered by content based on the criteria that they involved the building of SDMs using PO data (i.e. no absence information, including inferred absences from complete species lists) and that the study included a direct comparison between SDMs that attempted to correct models for SSB and models without this correction. To avoid ambiguity, studies were requir..., The file can be opened with any software capable of reading a .csv file., ---

title: Data for the meta-analysis of the effects of spatial sampling bias correction on presence-only species distribution models. output: pdf_document: default

html_document: default

This dataset contains information extracted from 220 studies identified through a systematic review of the peer-reviewed literature (Web of Science and SCOPUS databases both searched on the 13/02/2023) to evaluate the usage and effect of spatial sampling bias correction methods in presence-only species distribution models.

Description of the Data and file structure

The dataset contains the following columns:

• study_id = Unique number for identifying each study.
• bibtexkey = Author/year key.
• journal = Name of journal publishing the study.
• title = Title of article.
• volume = Volume number of published study.
• year = Year of publication for study.
• doi = doi of study.
• focal_kingdom = Kingdom of focal species (all named, separated by '|').
• f...

Finland - Distribution of population by household types: Single person was 25.80% in December of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Finland - Distribution of population by household types: Single person - last updated from the EUROSTAT on March of 2025. Historically, Finland - Distribution of population by household types: Single person reached a record high of 25.80% in December of 2023 and a record low of 19.00% in December of 2010.

Presences used to model Sphagnum distributions across Europe at resolutions 10, 25, 50, 100 and 200 km. Model projection rasters for the selected models.

This data set was assembled as part of the LIS:Epifauna data compilation (Chief Scientist: Dr. Peter Auster). These data files are of Shapefile format and include Species Distribution and Species Abundance data and were processed after data collection.