• EWHALE metadata

      Huettmann, Falk (2012-10-19)
    • 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.
    • GRID habitat plot survey data for the nesting sea turtles beach La Flor beach, Pacific, southwestern Nicaragua July of 2013

      Huettmann, Falk (Maderas Rainforest Conservancy, 2013-07-29)
      This GRID habitat plot survey was done at a globally relevant sea turtle nesting beach: La Flor (latitude 11.14282, longitude 85.79418, geographic datum WGS84). This sand beach is located 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. We did our grid-based habitat survey on the 11th 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 were done because it consists of sand and private/reserve property) and no species information is provided (sand beach). From 25 regular GRID points 13 were inaccessable because of reserve land holdings or dense bush forests. We took three photos (sky, ground vertical view) for every plot, more details can be seen there. This grid can be used for change detection, shoreline location, develeopment questions, and beach erosion questions over time for turtle nest habitat, for instance. Known sea turtles for this region are predominately Olive`s Ridley sea turtle (Lepidochelys olivacea, TSN 173840), but also Hawksbill (Eretmochelys imbricata TSN 208666) and Leatherback sea turtle (Dermochelys coriacea, TSN 173843).
    • 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.
    • 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.
    • 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.
    • Marine boat surveys for the olive ridley sea turtle (Lepidochelys olivacea) off of the coast of La Flor Playa de Coco, Nicaragua, 9th and 13th July 2013

      Huettmann, Falk (2013-07)
      Two marine monitoring boat surveys were conducted off the coasts of La Flor and Playa de Coco, southwest Nicaragua. Single and mating pairs of Olive Ridley sea turtles (Lepidochelys olivacea, TSN 1738400), were observed and activity and geo-referencing recorded with a GPS (decial latitude and longitude, geographic datum WGS84). Single turtles were seen basking and breathing at the surface of the water and subsequently would dive into the water. Mating pairs were also observed. Males held onto the females via a hook on the front flippers, scars were observed but no tumors were detected. Some photos were taken for visualisation.
    • 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.
    • Marine turtle nesting track survey on Playa de Coco, Nicaragua, and Playa Vigilada (Pacuare) and Tortuguero, Costa Rica, July 2013

      Huettmann, Falk (Maderas Rainforest Conservancy, 2013-07)
      Marine turtle tracks were observed on the beaches of Playa de Coco (Pacific, southwest Nicaragua; latitude 11.15382 , longitude 85.80051; WGS 84 ), Playa Vigilada (Pacuare; latitude 10.20123, longitude 83.25925) and Tortuguero (Caribbean, Costa Rica; latitude 10.59583, longitude 83.52520) during the early morning hours. Number of sea turtle tracks were counted along a transect. This was done by walking along the shore every morning to look for specific tracks that matched the tracks of sea turtle species. Maximum number of tracks observed was 8, while the minimum number obsereved was 0. Tracks had distinct features with flipper tracks visible on the edges of the tracts with a single line down the middle were the tail would drag. Tracks were seen to go straight onto the shore while some came up the shore and curved slightly before going back to the ocean. Tracks were observed near resturants and hotels. We observed Olive Ridely sea turtle (Lepidochelys olivacea, TSN 173840) in Playa de Coco, hatchling Leatherback sea turtles (Dermochelys coriacea, TSN 173843), and Green sea turtles (Chelonya mydas, TSN173833) in Playa Vigilada and Tortuguero,
    • Meta-Analysis on the Effects of Global Economic Growth on Birds in the Nations of the Three Poles

      Infante, Cynthia Gabriela Reséndiz (2012-11)
      Economic and population growth as well as global macroeconomic policies are contributing to increasing global greenhouse gas (GHG) emissions. Climate change effects are more pronounced in cold regions such as the ‘Three Poles’ (the Arctic, the Antarctic and the Hindu Kush-Himalaya regions) than anywhere else. The Three Poles are rich in natural resources but the extraction of resources is degrading ecosystems and processes, and affecting species. In the Three Poles, many species depend on ice and snow habitats, but these species are competing with human activities for space and resources on a finite globe. Local and global pressures cause bird species populations to decline. In this study I investigated how bird populations are affected by economic growth and subsequent effects on the environment in the Three Poles regions. Data mining based on machine learning algorithms was used to perform the analyses. TreeNet (based on regression trees), included in the software Salford Predictive Modeler Builder® v.6.6 was used to develop the models. An additional Random Forests analysis (classification trees) was used to analyze the datasets. Two response variables were chosen based on bird distribution maps provided by BirdLife and the IUCN RedList categories, including those that have risk of extinction or are in the Least Concern category but with declining populations. Data from the WDI Data Catalog of The World Bank (World Development Indicators) were used as predictors. The results include a total of 24 models, classified by pole and type of country according to their direct (primary countries) or indirect (secondary countries) link to the Three Poles regions. A combind model was also run (primary and secondary countries). Models were evaluated according to the response curves and gains charts. Models confirm that global demand for, and consumtion of, resources is affecting the Three Poles. Food production, rural population, CO2 emissions, Gross Domestic Product (GDP) and agricultural land were the top ranked predictors to explain the number of birds classified as threatened or with populations decreasing. This finding supports that the global demand for resources such as oil, gas and fish that were exploited from the Three Poles, added to global warming from anthropogenic causes are significantly affecting bird species populations. However, further research has to be carried out in order to obtain sound information on what the best management and governance is for a sustainable outlook for the Three Poles and beyond.
    • Metadata of six NCEAS data sets in Elith et al. 2020

      Elith, J.; Graham, C.H.; Valavi, R.; Abegg, M.; Bruce, C.; Ford, A.; Guisan, A.; Hijmans, R.J.; Huettmann, F.; Lohmann, L.G.; et al. (7/29/2020)
      The 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.
    • Micro-habitat description of sea turtle nests on three public nesting beaches in LaFlor (Pacific) southeast Nicaragua, and Pacuare Reserve and Tortuguero (Caribbean) Costa Rica during July 2013

      Huettmann, Falk (Maderas Rainforest Conservancy, 2013-07)
      Descriptions of the micro habitat of sea turtle nests were recorded on three public beaches: La Flor (latitude 11.14282, longitude 85.79418, Pacific) in southwest Nicaragua, and Pacuar Reserve (latitude10.20123 longitude 83.25925), and Tourtuguero (latitude 10.59583, longitude 83.52520) at the Caribbean coast of Costa Rica. Species covered are the Olive Ridley sea turtle (Lepidochelys olivacea, TSN 173840), 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). After a nest was identified during night and the turtle left successfully, next day the following micro-habitat attributes were collected with dates: distance from waterline, distance from treeline, slope of beach, nearest known nest, and tree height. The presence of egg shells, tree canopy cover, vegatation type, occurence of plastic and driftwood were also recorded, as well as a description of the sand. Geo-referencing of nests was done with a GPS using decimal latitude and longitude (geographic datum of WGS84). This dataset consists of an MS Excel sheet and is <1MB in size. Some photos are also provided for visual purposes.
    • Model-predicting the Effect of Freshwater Inflow on Saltwater Layers, Migration and Life History of Zooplankton in the Arctic Ocean: Towards Scenarios and Future Trends

      Schmid, Moritz (2012-04)
      The Arctic Ocean is warming up and an increasing freshwater inflow is triggering major changes in ocean layers. This model study aims at creating a baseline, and analyzing the effect of freshwater content changes, subsequent freshwater sealing as well as related parameters in the Arctic Ocean on migration and life history of zooplankton such as copepods and euphausiids. Copepods and euphausiids make for a major part of the zooplankton biomass in the Arctic Ocean, and are an important part of the food chain. Analyses are carried out using an ecosystem-based, spatial modeling approach with machine learning algorithms (Salford Systems TreeNet®, Random Forests® and R implementations). The underlying data consists of over 100 predictors including a globally unique data set of physical oceanography. Raw data that was used in this project is available as metadata from the Core Science Metadata Clearinghouse (former National Biological Information Infrastructure) and available at http://mercury.ornl.gov/clearinghouse/ and on servers from the University of Alaska Fairbanks. The Canadian Earth System Model 2 (CanESM2) was utilized to model the effect of changing climate on zooplankton for the next 100 years and for a low emission (RCP26) and a high emission scenario (RCP85). The results consist of spatially explicit (where every point in the layer is geo referenced) and predicted layers for Geographic Information Systems (GIS) that show predicted plankton presence/random absence as well as the relative index of depth and life stage distribution where the zooplankton is most likely to occur. The models show a clear trend towards an increasing relative index of depth where zooplankton is most likely to be found for the year 2100. Moreover, a trend towards a diminishing ecological niche for adult life stages of zooplankton was observed. These changes add stress to the life of zooplankton, especially regarding the diel vertical migration of mostly adult life stages. If zooplankton has to migrate a longer way, this will most likely increase energy expenditure and predation risk which ultimately decreases fitness. When accounting for other man-made impacts on the ocean such as ocean acidification and increasing shipping in the Arctic and taking the big picture into account, the outlook and conditions for zooplankton in 2100 are negative.
    • Nest and attribute data for 24 Hooded Cranes (Grus monacha) and control plots from field surveys in Northeast China 1993-2010

      Huettmann, Falk (Yu Guo, S. Jiao and colleagues, 2013-05-31)
      This dataset conists of 24 nests and their environmental attributes for the Hooded Crane (Grus monarcha, taxonomic serial number TSN 176186, Avibase ID38F36091DBC85095) in China. It is a legacy dataset, presents the best available information, and covers 9 years of survey work (time window 1993-2010). The Hooded Crane is a vulnerable (VU) species according to the IUCN Red list. The estimated world population of this species is just 10,160 individuals, of which more than 8,000 winter in Izumi, Japan. The Hooded Crane breeds in landscapes of Eastern Russia and Northeastern China. It generally nests in forest swamps, mostly within the permafrost zone. This data set can be used for nest preference studies and is available as an Open Office, ASCII or MS Excel format data sheet. The following environmental attributes have been collected for nests as well as for 81 control plots: elevation (in Meters), aspect (in Degrees), slope position (in degrees), distance to the nearest tree (Meters), distance to the nearest road (meters), distance to the nearest human settlement (Meters), distance to the nearest feeding site (Meters), distance to the nearest skidding road (Meters), water surface area around the nest (Square Meters), average water depth around the nest (Centimeter), canopy coverage (Percent), shrub coverage (Percent), grass coverage (Percent). number of trees (Count).
    • Non-invasive nocturnal surveys of sea turtle nesting beaches at La Flor (Pacific) Nicaragua, and Pacuare Reserve and Tortuguero (Caribbean) Costa Rica, July 2013

      Huettmann, Falk (Maderas Rainforest Conservancy, 2013-07)
      Marine turtles on the nesting beaches of La Flor public beach (latitude11.14282, longitude 11.14282, geographic datum WGS84), Pacific Nicaragua, and Pacuare Reserve public beach (latitude 10.20123, longitude 83.25925) and Tortuguero (latitude 10.59583, longitude 83.52520) , Caribbean, Costa Rica were observed during late hours after sunset. Observations where noninvasive, geo-referenced and observers stayed three meters away from the sea turtles, according to the national requirements (no light, and some limited red light was used for field clarifications). Many surrounding attributes were taken into consideration and measured including date, time, species, location, observed cysts present in the facial region, visually estimated carapace length, other disturbances present on the beach, number of people/tourists and dogs present, plastic encountered, and if applicable, start and end time of specific activities of nesting (such as start of nest time, start of egg laying and start of Ridley dance.) These data are part of a citizen science project and from a sea turtle fieldclass with Maderas Rainforest Conservancy. This dataset consists of an MS Excel sheet and is less than 1MB in size. Some photoes were taken to present the beaches and procedures.
    • 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.
    • 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.
    • 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.