RSS 1.0Huettmann, Falk
Recent Submissions
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Data Submission Package for Manuscript 'Model-predicting Matschie's Tree Kangaroo in Papua New Guinea'These are the GIS data used for modeling Matschie's Tree Kangaroo (Huon Tree Kangaroo) in Papua New Guinea PNG; for details please see metadata. THe manuscript is currently in revision phase.
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Metadata of six NCEAS data sets in Elith et al. 2020The publication by Elith et al. 2020 publishes data from Elith et al. 2006 and consists of six data set; metadata descriptions provided here. Data are found in OSF and as an R package; details provided in Elith et al. 2020 and/or with authors.
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Data (Appendix) for Book Chapter 43: Citizen Science Experience in Lumbini/Nepali for Sarus Cranes and Lesser Adjudants (Storks) with Regmi and Huettmann 2020 Hindu Kush Himalaya: Watersheds Downhill, SpringerThis dataset consist of an appendix of citizen science data for the Sarus Crane and Adjudant storks in Lumbini and Jagdishpur Reservoir, Nepal. It's a plain MS Excel sheet.
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Data (Appendix) for Book Chapter 33: Persistent Langur (Semnopithecus) decline in Nepal with Regmi and Huettmann 2020 Hindu Kush Himalaya: Watersheds Downhill, SpringerThis dataset consists of an appendix of a GIS map of langur sp information in Nepal. The datasets are locations, presences and absences from a value-added GBIF.org query, transect data by the authors and literature data Details are specified in the book chapter by Ale et al in Regmi and Huettmann 2020. This is the first and best compiled data for this species in Nepal and shows national declines with large conservation management implications.
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Data (Appendix) for Book Chapter 25: Museum Data holdings and Libraries in Nepal and Hindu Kush Himalaya region with Regmi and Huettmann 2020 Hindu Kush Himalaya: Watersheds Downhill, SpringerThis compiled dataset consists of a value-added analysed GBIF data set in the wider Hindu Kush-Himalaya (HKH) region. The original data source is from individual national contributors found in GBIF. Data are used here for research purposes for the wider HKH region watersheds and to show institutional spread and distribution. Some major outside museums internationally are mentioned too. The dataset consists of MS Excel sheets Methods and details are specified in the book chapter by Huettmann in Regmi and Huettmann 2020. This is the first and best compiled data for the study area and is to set a start of such views and investigations towards a better and more fair access to data, as part of a better and more democratic decision-making process.
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Data (Appendix) for Book Chapter 22: Rapid Assessment of Urban Birds and GIS models of Kathmandu and Pokhara, Nepal with Regmi and Huettmann 2020 Hindu Kush Himalaya: Watersheds Downhill, SpringerThis compiled dataset consists of a field data from rapid assessment of common birds found in urban areas of Kathmandu and Pokhara, Nepal, Hindu Kush-Himalaya (HKH) region.The dataset consists of 31 bird and animal species from a detection survey of 2 transects and photos in MS Excel sheets. It is overlaid with Open Street GIS map predictors for the study areas, and model predicted with GIS. We used the following 6 layers:waterways, natural places, shop polygons, land use, roads and highways and computed proximities for each in GIS. Methods and details are specified in the book chapter by Huettmann in Regmi and Huettmann 2020. This is the first and best compiled field and GIS data for the study area and is to set a start of such views and investigations towards a better and more fair access to data, as part of a better and more democratic decision-making process. Here an example is presented using avian species and GIS habitat layers.
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Data (Appendix) for Book Chapter 37: 'Road, Railroad and Airport data for the Hindu Kush Himalaya region' with Regmi and Huettmann 2020 Hindu Kush Himalaya: Watersheds Downhill, SpringerThis compiled dataset consists of an appendix of value-added merged GIS maps for roads, railroads and airports in the wider Hindu Kush-Himalaya (HKH) region. The original data source is from individual national DIVA-GIS files and used here for research purposes for the wider HKH region watersheds. Nations included are: Nepal, India, China, Buthan, Kazachstan, Tajikistan, Kyrgystan, Uzbekistan, Turkmenistan, Afghanistan, Iran, Laos, Myanmar, Thailand, Vietnam, Pakistan, Bangladesh and Cambodia. The dataset consists of 21zip archives of these nations also covering railways and airports. Methods and details are specified in the book chapter by Huettmann in Regmi and Huettmann 2020. This is the first and best compiled data for the study area.
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Data (Appendix) for Book Chapter 28: Sarus Crane GIS Model with Regmi and Huettmann 2020 Hindu Kush-Himalaya: Watersheds Downhill, SpringerThis dataset consist of an appendix of GIS model predictions of Sarus Cranes (GRus antigone Taxonomic Serial Number TSN: 176181) in Nepal. Details are specified in the book chapter by Karmacharya et al in G.R.Regmi and F. Huettmann 2020. This is the first model for this species and shows conservation management implications for the Terai landscape between Nepal and India.
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Rabies data for Canada and Alaska/US for GIS model predictionsThis value-added data set is part of a publication by Huettmann and Hueffer (in prep) and includes the GIS layers for rabies and predictions of Canada, assessed with Alaska locations ((taken from Huettmann et al. 2015). This project compiled the best publically available rabies data for Canada, and models them for the Northern part of the the North American continent (Alaska and Arctic Canada). The environmental data sets are in a common GIS format (ESRI and ASCII grids) and are taken from public Open Access sources. The rabies data sets are point data, as rabies was reported by the Canadian Food Inspection Agency, and processed in the lab. The dataset is 5GB in size and consists of 20 files.
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Camera Trapping Grid Data in Nepal Hindu Kush-Himalaya for regions of Humla 2015 , Manang 2014-2015 and Manang 2016-2017This multi-year, multi-site and multi-species dataset describes Bushnell Camera Trap data from three locations in remote Nepal: Humla 2015, Manang 2014-2015 and Manang 2016-2017. The data from the Hindu Kush-Himalaya region comes from a geo-referenced survey grid and are stored in three MS Excel sheets, also combined and available in CSV consisting of 175658 records and 15 columns with a file size of 19MB. Species covered are Blue Sheep/Bharal (Pseudois nayaur Taxonomic Serial Number TSN 180596 ), Snow Leopard (Panthera unica, Uncia uncia TSN 183811), Beech Marten (Martes foina TSN 621941), Wolf (Canis lupus TSN 180596), birds (Aves Golden Eagle etc.),Pika (Ochotona), Red Fox (Vulpes vulpes TSN 180604), Mountain Weasel (Mustela altaica TSN 621947), Pallas�s Cat (Otocolobus manul, Felis manul TSN 183791), and Golden Jackal (Canis aureus TSN 183817)
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Red squirrel midden model prediction GIS dataThis dataset features the best-available compilation about Red Squirrels (Tamiasciurus hudsonicus, taxonomic serial number 180168 ) GIS model predictions in a study area in Fairbanks,Alaska. This dataset starts in 20016 and ends in 2017. The data are referenced in time and in space (GPS) and it consist of GIS layers for the UAF campus trails, including LIDAR; the geographic projection is UTM 6N in meters. The dara are compiled from sightings and records by the first author. This dataset represents opportunistic as well as complete sightings for a study area at UAF campus. The actual squirrel data are compiled into an MS Excel sheet and all other data layers are in ESRI format: raster or shapefile Tthe size of the overall data package is app. 21 MB.
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Distribution and density of the American Red Squirrel (Tamiasciurus hudsonicus ) in the interior Alaskan old-growth forest for 2019The aim of this project -carried out in July 2019 - was to determine the distribution and density of the American Red Squirrel (Tamiasciurus hudsonicus; taxonomic serial number 180166) in the old-growth forest of interior Alaska; region of Fairbanks. Also the distribution and density of squirrel middens (construction built by the squirrel, which is used for nutrition storing for the winter. Middens also provide as a nest for the squirrel's which can be used as protection from predators. We carried out opportunistic surveys along trails and within forest stands using GPS and notebook. Google Maps were used for navigation and planning help. This work can be used for subsequent model predictions with GIS software and other modelling software programs to obtain the detection rates and the distribution and density of middens in the whole study area (Tanana State Forest).
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Climate (temperature & humidity) data logger data from EasyLogUSB in interior AlaskaThese data are daily climate data (temperature and humidity) collected on transects in interior Alaska throughout the year. Data were collected for the years 2015, 2016 and 2017 by ski, with dogs, by bike and by car. An attached EasyLogUSB data logger was used and usually 10 second interval records were collected during a 1hour data session, or more (daily profiles, some are stationary for 24hours). Temperature is collected as degrees Celsius and humidity as percent; data exist as a txt/ASCII format in columns. These data are referenced to time and locations, and they can be used as cross-profiles for landscape climate and ground-truthing of climate models using GIS and geo-referencing. Data include the �sampling of altitudinal profiles, landscape cover, river crossings and various topographies, including coastal-interior gradients. Data collection is still ongoing.
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Geo-referenced and documented red squirrel (Tamiasciurus hudsonicus) midden sites from 2016 and 2017 in a highly used forest area behind the University of Alaska, FairbanksThis dataset consists out of 29 presence points of red squirrel (Tamiasciurus hudsonicus, Taxonomic Serial No.: 180166) midden sites. Data was collected in a highly human-used forest area behind the University of Alaska, Fairbanks for summer 2016 (n= 29) and winter/spring 2017 (n=20).The data set consists of an ESRI shapefile for each year. Data was collected in two consecutive years (2016-2017). The first set of data points (summer 2016) was collected with a land cruising survey design and recorded with a GPS unit, based on an opportunistic course project work by R. Adams. The second data collection campaign took place in spring 2017 to check whether the squirrel midden sites from 2016 are still in use (data collected by R. Robold). The coordinate system is decimal degree (5 decimals) and with a geographic projection NAD_1983_Alaska_Albers. The excel sheet has five columns (site ID, a short description of the vegetation, latitude, longitude, and one if the middens are still used in 2017); the excel document (midden_data_with_control.xlsx) size is 10 KB (2017). The map is a JPEG-file (Midden_sites_2016-27_RR) with a size of 3MB and the shapefiles have an overall size of ca. 50 KB each. This data set is the basis for ongoing study on squirrels in the boreal forest and urban areas.
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Rapid Assessment Biodiversity Grid Data for Broad Pass 'divide' in Denali Preserve, Alaska, U.S., July 2016This data set consists of a citizen-science type rapid biodiversity assessment at landscape watershed divide in Denali Preserve, Alaska, U.S..The data include 25 plots spaced 100m apart from each other, and 5 additional random points. The geo-referencing was done with a GPS, a geographic datum of WGS84 was used with decimal degrees (5 decimals) of latitude and longitude. The bounding box of this data set is: 63.33421 til 63.33847 Northern latitude, and 149.10451 til 149.11398 Western longitude. The grid was visited three times from July 7th, 8th and 9th in 2016 allowing for occupancy and distance sampling abundance estimates for instance. Point transects were carried out for bird sightings; the vegetation (flowers and trees) and insects (trapping web of 100 cups) were briefly assessed. Three photos were taken for each grid plot, including one sky shot to capture the atmospheric light conditions, e.g. for Remote Sensing work. Noteworthy are the high occurrences of moose browse, as well as savannah and white-crowned sparrows. Despite its esthetic landscape appeal, the grid area was heavily affected by humans, e.g. a highway, local airport and railway and a camp ground are located at the grid. Incidence of hunting and snowmobiling was found. Basic weather data were also collected for 24h during the survey period. This dataset consists of an MS Excel sheet and is less than 1MB in size.
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Rapid Assessment Biodiversity Grid Data for ‘Lueneburger Heide’ (Lueneburg Heathland), Schneverdingen, Germany, August 2015This data set consists of a citizen-science type rapid biodiversity assessment at landscape of ‘Lueneburger Heide’ (Lueneburg Heathland) near Schneverdingen, Germany.The data include 25 plots regularly spaced 100m apart from each other, and 5 additional random points. The geo-referencing was done with a GPS, a geographic datum of WGS84 was used with decimal degrees (5 decimals) of latitude and longitude. The bounding box of this data set is: 53.03996 til 53.10003 Northern latitude, and 9.80769 til 9.81478 Western longitude. The grid was visited three times between August 8th til 12th in 2015 allowing for occupancy and distance sampling abundance estimates for instance. Point transects were carried out for bird sightings. Also, mammalian evidence, the vegetation (flowers and trees) and some insects (primarily ants) were briefly assessed. Three photos were taken for each grid plot, including one sky shot to capture the atmospheric light conditions, e.g. for Remote Sensing work. Noteworthy are the high occurrences of human impacts (biofuel mais and tree plantations, sheep farming “Heidschnucken’, tourism, local train), as well as songbirds. Despite its esthetic and highly managed heath landscape appeal, the grid area is essentially a highly frequented surban nature recreation reserve but avian raptors, common cranes, rare amphibians (moor frog, roe deer, boar and re-introduced wolf can be found! Incidence of hunting occurs (e.g. high stands). This dataset consists of an MS Excel sheet and is less than 1MB in size.
