• GRID survey habitat data for Playa el Coco beach (nesting sea turtles) - Pacific, southwestern Nicaragua July of 2013

      Huettmann, Falk (Maderas Rainforest Conservancy, 2013-07-29)
      This GRID survey was done at the beach of Playa de Coco - near a globally relevant sea turtle nesting beach (La Flor). Playa el Coco (latitude 11.15382, longitude 85.80051, geographic datum WGS84) is situated at the Pacific Ocean in southwestern Nicaragua, approx. 20 km far from San Juan Del Sur and approx. 30 km far from the Costa Rican border, just adjacent to La Flor. We did our grid-based habitat survey on 8th and 9th of July in 2013. The GRID points are geo-referenced by latitude and longitude (decimal degrees, WGS84, +- 10 meters acuracy) and were visited only once (no 3 repeats because it consists of sand and private property) and no species information (mostly empty sand beach). From 25 regular GRID points 9 were inaccessable because of private land holdings or very bushy forests. We took photos for every point (horizontal, vertical, sky), more details can be seen there. This grid can be used for change detection, shoreline location, develeopment, and beach erosion questions over time for turtle nest habitat, for instance. Known sea turtles for this region are predominately Olive`s Ridley turtle (Lepidochelys olivacea, TSN 17384), other species could potentially occur too. On the beach, we also detected Black-throated Magpie-Jay Calocitta colliei 558992, Balck Vulture Coragyps atratus 175272, Groove-billed Ani Crotophaga sulcirostris 177839, Great Kiskadee Pitangus sulphuratus 178301, Magnificent Frigate Bird Fregata magnificens 174763, Black Oystercatcher Haematopus bachman 176475, Sooty Tern Onychoprion fuscatus 824105, Brown Pelican Pelecanus occidentalis 174685, Neotropical Cormorant Phalacrocorax brasilianus 554375 and Banded Wren Thryothorus pleurostictus 563460). This dataset is an MS Excel format and less than 1MB in size.
    • Macro description of public beach attributes that may effect turtle nesting in Playa de Coco, La Flor (Pacific, southwest Nicaragua) and Pacuare and Tortuguero, (Caribbean, Costa Rica), July 2013

      Huettmann, Falk (Maderas Rainforest Conservancy, 2013-07-29)
      We observed several macro beach features of four public sea turtle nesting beaches for Playa Coco (latitude11.15382, longitude 85.80051; geographic datum WGS84) and La Flor (latitude 11.14282, longitude 85.79418) in southwest Nicaragua (Pacific), and Pacuare Reserve (latitude10.20123, longitude, 83.25925) and Tortugero (latitude 10.59583, longitude 83.52520) in Costa Rica (Caribbean). Recorded features included the intensity of tourism, number of different predator species of sea turtle hatchlings, number of tourists, and line transects for density of plastic, wood, metal, and crab burrows. Light and sound disturbances at night were also recorded as well as man-made objects left overnight on the shore of the beaches. This data set is part of a sea turtle class with Maderas Rainforest Conservancy and provides a basic and non-invasive description and a snap shot in time and space for public nesting beaches of relevance for Olive Ridley (Lepidochelys olivacea, TSN 173840), Green (Chelonia mydas TSN 173833), Hawksbill (Eretmochelys imbricata TSN ) and Leatherback (Dermochelys coriacea TSN 173843 ) sea turtles. Some photos were taken for vizualisation purposes.
    • GRID-based habitat plot data for the public nesting sea turtle beach of Pacuare, Caribean Sea, Costa Rica July of 2013

      Huettmann, Falk (Maderas Rainforest Conservancy, 2013-07-29)
      This GRID habitat survey was done at a globally relevant public sea turtle nesting beach: Pacuare (Playa Vigilada). It is situated at the Caribean Sea in Costa Rica ((latitude10.20123 longitude 83.25925; geographic datum WGS84). We did our grid-based habitat survey on 18th of July in 2013. The individual GRID points are geo-referenced by latitude and longitude (decimal degrees, +- 10 meters acuracy) and were visited only once (no 3 repeats because it consists of sand and private property) and no species information was taken (sand beach habitat). From 25 regular GRID points 15 were inaccessable because the nearby jungle and reserve. We took photos for every point (horizontally, ground and sky), more details can be seen there. This grid can for instance be used for change detection, shoreline location, develeopment, and beach erosion questions over time for turtle nest habitat. Known and observed sea turtles to occur for this region are Leatherback sea turtle (Dermochelys coriacea TSN 173843), and presumably Hawksbill sea turtle (Eretmochelys imbricata TSN 208666) and the Green sea turtle (Chelonia mydas TSN 173833). This dataset is in an MS Excel format and is less than 1MB in size.
    • Opportunistic Survey Data of Mew Gull (Larus canus) and other detections in an Urban Environment, downtown Fairbanks, Interior Alaska in mid-June 2013

      Huettmann, Falk (EWHALE lab, University of Alaska-Fairbanks (UAF), 2013-07-31)
      This dataset presents a Mew Gull (Larus canus, Taxonomic Serial Number TSN 176832) survey data set for urban areas and stripmall parking lots (app. 300mx600m), super markets, fast food restaurants, gravel pits, small ponds and the riverside (Chena) in Fairbanks, interior Alaska located app. 120 miles south of the arctic circle. We did geo-referenced 80 point surveys and detections. Data were geo-referenced with a GPS in decimal degrees (latitude and longitude, geographic datum of WGS84) collected 22th of June in 2013 on a Saturday (regular shopping and business times in the U.S.) between 9.30 AM and 5 PM by driving opportunistically on public strip mall parking lots, domestic areas and other locations of relevance for gull presences and absences in the survey area (app. 200m radius). These non-intrusive citizen science car-based surveys result into a virtually unbiased data providing a representative snap shot in space and time. Stripmall parking lots near rivers represent a typical situation of where Mew Gulls are found in an urban habitat during breeding season. We reported basic gull behaviour also. Some other bird species were recorded as well, e.g. Golden Eagle (Aquila chrysaetos 175407), Northern Raven (Corvus corax 179725), Sandhill Crane (Grus canadensis 176177), Bald Eagle (Haliaeetus leucocephalus 175420), Gull sp. (Larus 176803), American Robin (Turdus migratorius 179759). The gull abundance seems to be driven by food items on the parking lot, e.g. provided by an adjacent fast food restaurant and by wetland areas nearby (e.g. Chena river and gravel pits) where the gulls find good conditions for nearby nesting. This survey is unique and contributes to baseline information relevant for gulls, ravens, urban subsidized predators (e.g. eagles) in the interior of Alaska. They are a simple but powerful snapshots in time and space and when put into an overall ecological context, e.g. as done with Geographic Information System (GIS) analysis. Some photos are provided for visual information. The dataset is provided in MS Excel and less than 1MB in size.
    • Vulture and other ornithological survey data in Annapurna and Manaslu Conservation regions

      Karmacharya, Dikpal Krishna; Gyawali, Seejan; Virani, Munir; Huettmann, Falk (2013-10-01)
      This dataset presents geo-referenced summaries of vulture and raptor sightings (from field work as well as from published sources 1977-2013), as well as general avian species lists and their detected abundances, for the Annapurna (ACA) and Manaslu Conservation Areas (MCA). In addition, compiled 'presence only' data of vultures are provided for Nepal and Northern India as well. The bounding box (decimal degrees) of the data coverage is 77.4966 til 87.0667 latitude and 26.3666 til 28.58333 longitude, and Altitude covers 100m til 7969m. The data consist of MS Excel and include 6 worksheets (all bird list, number of bird sighting and counting, descending number of individuals, vulture survey in ACA, raptors in Manaslu, and compiled presence only sightings of vultures for Nepal and Northern India). While this data set is reatively small, it includes a large and complex set of information for a vast and globally relevant region. The following raptor species are primarily covered in this data set: Upland Buzzard (Buteo hemilasius, TSN 175385), Himalayan Griffon (Gyps fulvus, 175487), Golden Eagler (Aquila chrysaetos, 175407), Himalayan Vulture (Gyps himalayensis,175488), Bearded Vulture (Gypaetus barbatus,175483), Egyptian Vulture (Neophron percnopterus, 175481) and White-Rumped Vulture (Gyps bengalensis, 175485). Smaller predators like Common Kestrel (Falco tinnunculus, 175620), Peregrine Falcon (Falco peregrinus,175604), Shikra (Accipiter badius, 55890), Bonelli's Eagle (Aquila fasciata, 175565), Black Kite (Milvus migrans,175469), Mountain Hawk Eagle (Spizaetus nipalensis, 175580), Spotted Owlet (Athene brama, 555472), Western Osprey (Pandion haliaetus, 175590) and Crested Serpent Eagle (Spilornis cheela, 175506) were also reported, In addition, overall app. 763 sighting locations of 143 species of birds are also featured in the data (english names as well as scientific names). Naturalists, bird watchers, modelers as well as investigators of raptors and other birds in the Nepal and Northern Indian regions will find great value in this data set.
    • Opportunistic Survey Data of Common Gull (Larus canus) and other detections in an Urban Environment, downtown Fairbanks, Interior Alaska during mid-May 2014

      Huettmann, Falk; Spangler, Mark (2014-05-17)
      This dataset presents a Common Gull (Mew Gull, Larus canus, Taxonomic Serial Number TSN 176832) survey data set for urban areas and stripmall parking lots (app. 300mx600m), super markets, fast food restaurants, gravel pits, small ponds and the riverside (Chena) in Fairbanks, interior Alaska located app. 120 miles south of the arctic circle. We did geo-referenced 50 point surveys and detections in a rapid assessment fashion. Some opportunistic data were also taken when cruising. Gull data included detection width to obtain correction factors. Data were geo-referenced with a GPS in decimal degrees (latitude and longitude, geographic datum of WGS84) collected in early breeding season, 17th of May in 2014 on a Saturday (regular shopping and business times in the U.S.) between 8.15 AM and 5 PM by driving opportunistically on public strip mall parking lots, domestic areas and other locations of relevance for gull presences and absences in the survey area (app. 200m radius). These non-intrusive citizen science car-based surveys result into a virtually unbiased data providing a representative snap shot in space and time for the study area. Stripmall parking lots near rivers represent a typical situation of where Common Gulls are found in an urban habitat during breeding season. We reported basic gull behaviour also. Some other bird species were recorded as well but not in great detail, e.g. American Wigeon, Lesser Scaup, Pigeon, White Crowned Sparrow, Swallow sp, Shorebirds sp, Mallard, Lesser Yellowleg, American Robin, Scaups sp., Common Raven, Bunting sp., Grassland birds, Northern Shoveler, Grebe sp., Dark-eyed Junco, Herring Gull, Grouse sp. Noteworthy are the higher abundances of planes and helicopters. The gull abundance seems to be driven by food items on the parking lot, e.g. provided by an adjacent fast food restaurant and by wetland areas nearby (e.g. Chena river and gravel pits) where the gulls find good conditions for nearby nesting. Gulls seem to be quite colonial. This survey is unique and contributes to multi-year baseline information relevant for gulls, ravens, urban subsidized predators (e.g. raptors) in the interior of Alaska. They are a simple but powerful snapshots in time and space and when put into an overall ecological context, e.g. as done with Geographic Information System (GIS) analysis. Some photos exist for visual information. The dataset is provided in MS Excel, consists of 144 rows and is less than 1MB in size.
    • Compiled Rabies and Trichinosis (presence only) outbreak data for Alaska

      Waltuch, Rebekah (2014-09-01)
      These are two data sets that were compiled during a UAF student research project, Landscape Ecology class 469/669 (eLearning). They represent a value-added data set and can easily be mapped in a Geographic Information System (GIS) etc. For rabies in Alaska, 237 confirmed cases were found of which 158 had complete information (year, coordinates and vector). The rabies cases in this database are from 1914 til 2013; vectors include Dog, Wolf, Red Fox, Coyote, Arctic Fox, Cat, Caribou, Little Brown Bat, Keen's Myotic Bat and Wolverine. The Alaskan trichinosis data cover 1976-2012 and with various details. Species covered are: Walrus Black Bear, Brown Bear, Bear (unspecified) and Polar Bear. These are student project data compiled from various accessible sources (e.g. the State of Alaska Epidiology website <http://www.epi.hss.state.ak.us> and references cited in the Methods), and they are incomplete. However, they can be used for predictive modeling and similar studies and investigations.
    • Marine surveys (at sea and 16 ports) of Atlantic seabirds, passerines and marine mammals during Semester at Sea cruise fall 2014

      Huettmann, Falk (2014-12-08)
      This data set was collected during the Fall 2014 cruise with Semester at Sea (SAS). It covers 2 MS Excel files of marine species surveys (three worksheets: opportunistic 5 minutes, and Distance Sampling 10 minutes, Individual Sightings) as well as harbour species surveys (one file with one worksheet). The SAS cruise of fall 2014 took place in the Atlantic, southern Baltic, the Mediterrean and Caribbean Seas and has the following bounding box coordinates (decimal degrees of latitude and longitude WGS 1984): Highest latitude 59.88929 North, lowest latitude -22.28687 South, most western longitude -81.80984, most eastern longitude -40.91894. The following 16 ports were covered: Southampton (UK), St. Petersburg (Russia), Gdansk (Poland), Rostock (Germany), Antwerp (Belgium), Le Havre (France), Dublin (Ireland), Lisbon (Portugal), Cadiz (Spain), Casablanca (Morocco), Citivecchia (Italy), Barcelona (Spain), Rio De Janeiro (Brazil), Salvador (Brazil), Bridgetown (Barbados), Havanna (Cuba) and Fort Lauderdale (Florida US). The starting date was August 21st and the ending date was Dec 7th 2014. The cruise included app. 632 students and 380 staff and crew (including professors). This dataset includes data from opportunistic 5 minute surveys ('presence only'), as well as 10minute long Distance Sampling surveys (abundances) done 2-3 times per day. All data are geo-referenced. In addition, many additional individual sigthings by the shipboard community and local excursion (terrestrial) data are also included, photos were collected whenever possible. Additional data like state of the ocean, plastic pollution, vessels in view, and weather were also collected. This data set can serve as a basic quantitative large-scale snapshot for the Atlantic region and its ecosystem in fall 2014. The 5 minute-long opportunistic at-sea surveys featured app 102 species; more species were detected in the other surveys. Most of these species are seabirds, with a few mamrine mammals, squid, fish sightings etc. Noteworthy are the high ocurrences of passerines at sea! This dataset has maximum 29 columns, and 314 rows (5 minute Opportunistic Survey), 146 rows (10min abundance surveys) and 271 rows (Individual Opportunistic Sightings); it is <1MB in size. A few photos exist and can be obtained upon request.
    • Compiled occurrence data of migratory Hooded Cranes in Southeast Asia

      Cai, T.; Guo, Y.; Huettmann, F.; Lee, K. (Beijing Forestry University, Beijing China, 2015-01-01)
      This dataset represents the best available science-based ocurrences (presence only) of Hooded Cranes during fall and spring migration along the flyway in Asia. This dataset consists of 115 geo-referenced sightings with the source/observer in a comma delimited file format. The geo-referencing was done in decimal latitude and longitude with six decimals. Each record carries a source information and is derived from 21 sources. The biggest data sections come from field obervations of the local authors as well as GBIF, satellite telemetry, and Higuchi (1994) and Chang (1999). This data set has four columns and 115 rows with a size of 30KB.
    • Opportunistic Survey Data of Common Gull (Larus canus) and other detections in an Urban Environment, downtown Fairbanks, Interior Alaska during mid-May 2015

      Huettmann, Falk (2015-05-12)
      This dataset presents a Common Gull (Mew Gull, Larus canus, Taxonomic Serial Number TSN 176832) survey data set for urban areas and stripmall parking lots (app. 300mx600m), super markets, fast food restaurants, gravel pits, small ponds and the riverside (Chena) in Fairbanks, interior Alaska located app. 120 miles south of the arctic circle. We did 50 geo-referenced point surveys and detections in a rapid assessment fashion. Some opportunistic data were also taken when cruising. Gull data included presence/absenc. Data were geo-referenced with a GPS in decimal degrees (latitude and longitude, geographic datum of WGS84) collected in early breeding season, 12th of May in 2015 on a Tuesday (regular shopping and business times in the U.S.) between 7 AM and 7 PM by driving opportunistically on public strip mall parking lots, domestic areas and other locations of relevance for gull presences and absences in the survey area (app. 200m radius). Other species were also recorded but received less attention. These non-intrusive citizen science car-based surveys result into a virtually unbiased data providing a representative snap shot in space and time for the study area. Stripmall parking lots near rivers and (gravel) lakes represent a typical situation of where Common Gulls are found in an urban habitat during breeding season. We reported basic gull behaviour also. Some other bird species were recorded as well but not in great detail, e.g. American Wigeon, Pigeon, White-crowned Sparrow, Swallow sp, Shorebirds sp, Mallard, Lesser Yellowleg, American Robin, Common Raven, Grassland birds, Northern Shoveler, Grebe sp., and Dark-eyed Junco. Noteworthy are the very high raven and gull numbers at the city garbage dump. The gull abundance seems to be driven by food items on the parking lot, e.g. provided by an adjacent fast food restaurant and by wetland areas nearby (e.g. Chena river and gravel pits) where the gulls find good conditions for nearby nesting. Gulls seem to be quite colonial. This survey is unique and contributes to multi-year baseline information relevant for gulls, ravens, urban subsidized predators (e.g. raptors) in the interior of Alaska. They are a simple but powerful snapshots in time and space and when put into an overall ecological context, e.g. as done with Geographic Information System (GIS) analysis. Some photos exist for visual information. The dataset is provided in MS Excel, consists of 156 rows and is less than 1MB in size.
    • Rapid Assessment Biodiversity Grid Data for Snow Leopard and Pallas Cat habitats in Manang, Annapurna Conservation Area, Nepal, early June 2015

      Huettmann, Falk; Lama, Rinzin Phunjok; Ghale, Tashi R. (EWHALE Lab, University of Alaska Fairbanks, 2015-06-27)
      This dataset consists of a rapid biodiversity assessment at a Snow Leopard (Panthera uncia) and Pallas Cat (Otocolobus manul) habitat site near Manang village in the Annapurna Conservation Area (ACA), Nepal. 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 decinal degrees (5 decimals) of latitude and longitude. The bounding box of this data set is: 27.691960 to 28.287450 Northern latitude, and 84.004010 to 83.998410 Western longitude. The grid is located on a slope app. on 4200m above sea level and was visited three times on May 30th, May 31st and June 1st in 2015 allowing for occupancy and distance sampling abundance estimates. Point transects were carried out for bird sightings; animal tracks, insects (butterflies) and vegetation (flowers) were briefly assessed. Two photos were taken for each grid plot, and one sky shot to capture the atmospheric light conditions, e.g. for Remote Sensing work.Noteworthy are the high grazing pressures and strong occurrences of yaks, horses, and goats, as well the detection of bharal (blue sheep), Lammergeier, Himalaya Griffon, Golden Eagle, snow cock, cockoo, pipits and wagtails in this mountain high altitude landscape (all scientific names and details are provided in the taxonomic section of the metadata). Small white snails were found too. A snowleopard kill site (blue sheep and yak) was found, as well as tracks and a resting site on a nearby higher cliff site (where Pallas Cat was also observed earlier). This dataset consists of an MS Excel sheet and is less than 1MB in size.
    • Presence points and behavioral data of Sarus Crane in Lumbini-Nepal September and October 2014

      Huettmann, Falk; Karmacharya, Dikpal Krishna; Duwal, Rabita (EWHALE Lab, University of Alaska Fairbanks, 2015-06-27)
      This dataset presents geo-referenced summaries of Sarus Crane (Grus antigone) and their behavioral sightings from field work. The Lumbini region is the hot spot with more than 250 species of birds and included as an Important Bird Area (IBA) of Nepal. It comprises beautiful cultural and religious resources. Hence, it is under the World Heritage Site of UNESCO. The occurrence of Sarus Crane in this region has religious value related with Buddhism. The 'presence only' data of Sarus Crane are provided for low land Nepal covering most of the VDCs of Rupandehi and Kapilbastu districts. The bounding box (decimal degrees) of the data coverage is 27.30015 til 27.576548 latitude (North) and 83.36193 til 82.990292 longitude (East), and an altitude covering 72m til 111m above sea level. Eight human resources including two experts and six local observers compiled the field-based data. The data consist of an MS Excel which includes 19 rows and 74 columns with the the following column headings: Time, Day, Month and Year of sightings, Observers, Latitude, Longitude and Elevation (m) of the sighting points, Geo-referencing method, Geographic datum, Location, District, Country, Male, Female, ClusterTotal, Habitat, Behaviour and Remarks. While this data set is relatively small, it reflects a large and complex set of representative information for the entire lowland of Nepal. Altogether 201 Sarus Cranes individuals weer counted including 104 male and 97 female within three habitats and four behaviours of birds are also described in the data. Naturalists, bird watchers, modelers as well as investigators of cranes and other birds in the region of Nepal and Northern India will find good value in this data set.
    • Rapid Assessment Biodiversity Grid Data for a farming field in Lumbini, Nepal, June 2015

      Huettmann, Falk; Karmacharya, Dikpal; Spangler, Mark (EWHALE Lab, University of Alaska Fairbanks, 2015-06-27)
      This dataset consists of a rapid biodiversity assessment at a farming site near a village in Lumbini, Nepal. 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 decinal degrees (5 decimals) of latitude and longitude. The bounding box of this data set is: 27.481920 to 27.486120 Northern latitude, and 83.261799 to 83.266640 Western longitude. The grid was visited three times from June 7th, 8th and 9th in 2015 allowing for occupancy and distance sampling abundance estimates. Point transects were carried out for bird sightings; the insects and vegetation (flowers) were briefly assessed. Two photos were taken for each grid plot, and one sky shot to capture the atmospheric light conditions, e.g. for Remote Sensing work.Noteworthy are the high occurrences of crows, black kites, myrnas and larks, as well the detection of sarus cranes in this landscape that is dominated by domesticated zebu, water buffalo and goats. The grid area was heavily used by humans, e.g. for walking and sanitary purposes. A high incidence of microplastics was found. At the time of survey a heat wave over up to 47 degree Celsius was measured. This dataset consists of an MS Excel sheet and is less than 1MB in size.
    • Rapid Assessment Biodiversity Grid Data for ‘Lueneburger Heide’ (Lueneburg Heathland), Schneverdingen, Germany, August 2015

      Huettmann, Falk (2015-08)
      This 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.
    • Rapid Assessment Biodiversity Grid Data for Broad Pass 'divide' in Denali Preserve, Alaska, U.S., July 2016

      Huettmann, Falk; Andrew, Phillip (EWHALE lab, Inst of Arctic Biology, Biology & Wildlife Dept., University of Alaska Fairbanks (UAF), 2016-07)
      This 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.
    • Climate (temperature & humidity) data logger data from EasyLogUSB in interior Alaska

      Huettmann, Falk (2017)
      These 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.
    • 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, Fairbanks

      Huettmann, Falk; Robold, Richard; Adams, R. (EWHALE Lab, University of Alaska Fairbanks, 2017)
      This 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.
    • Distribution and density of the American Red Squirrel (Tamiasciurus hudsonicus ) in the interior Alaskan old-growth forest for 2019

      Huettmann, Falk; Steiner, Moriz (2019-07-31)
      The 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).