NPSMANDATORY for Data Store: NPS Alpha Unit Code (ACAD)MANDATORY for Data Store: NPS Unit Type (National Park, National Monument, etc)Falk Huettmann - Laszlo Koever20130703NARapid Biodiversity Assessment GRID Sampling (citizen science) in the White Mountains, northern Alaska, USA, June 2013 dSPACE repository Uni of Alaska-Fairbanks (UAF) USGS Metadata Clearinghouse databaseThis data set consists of a Rapid Biodiversity Sampling from a non-intrusive citizen science GRID (5*5 geo-referenced sampling + 5 random plots = 30 plots overall). It includes raw count data for 305 bird observations of 14 identified bird species, and plants from the 25+5 survey sampling plots (3m radius), as well as insects from four trapping webs (3m radius, 25 traps each, 3 repeats; mostly spiders were detected). The survey was done between 25th of June and 27th of June in 2013 at the White Mountains (north to the NorthForkBirch and Twelvemile Creeks - near the Steese Hgw 6) in Alaska USA (decimal degrees latitude 65.39590, longitude -145.72890, geographic datum of WGS84) . Plots are located near the public road in the rolling hills, subartic tundra on some slope, and some are located. All plot locations were photographed (sky, ground and habitat shots) and for a visual assessment. All bird detections (visual and oral) carry a radial distance 360 degrees from the observer, and were collected according to DISTANCE Sampling point transect protocols. Respectively, a DISTANCE Sampling trapping web protocol, with a 3m radius and allowing for detectability correction in abundance estimates, was applied for ground-living insects. Generally, these data do not cover high detailed taxonomic information (and usually just follow basic but accurate descriptions). Each plot was visited three times according to the PRESENCE software requirements to obtain occupancy estimates. All of these data can be data-mined using for instance freely available RandomForest, Distance Sampling and PRESENCE software packages. Comparable Biodiversity GRID data so far is available for over 11 other regions (e.g. Nicaragua, Central Alaska, Costa Rica, Papua New-Guinea, Northern & Interior Alaska, Northeastern China and Russian Far East). Data from the other study sites are also available online. For more details please contact authors. The fllowing species were identified: dwarf birch (Betula nana Taxonomic Serial Number TSN by ITIS.org 19479), Black crowberry (Empetrum nigrum 23743), Cottongrass (Eriophorum 40079), marsh Labrador tea (Rhododendron tomentosum 894434), Alaska blue berry (Vaccinium ovalifolium 23607), Bird vetch (Vicia cracca 26335), Ant (Formica 154211), Bohemian Waxwing (Bombycilla garrulus 178529), Fox Sparrow (Carduelis flammea 179230), Gray Jay (Perisoreus canadensis 179667), Swainson`s Thrush (Catharus ustulatus 179788), Raven (Corvus corax 179725), Yellow-rumped Warbler (Dendroica coronata 178891), Savannah Sparow (Passerculus sandwichensis 179314), Fox Sparrow (Passerella iliaca 179464), Grouse (Phasianidae 175861), Woodpecker (Picidae 178148), American Robin (Turdus migratorius 179759), Wilson Warbler (Wilsonia pusilla 178973), White-crowned Sparrow (Zonotrichia leucophrys 179455), Common Redpoll (Carduelis flammea 179230).These non-intrusive citizen science GRID data were collected in order to develop low-cost rapid biodiversity assessment methods corrected for detectability. Data from this site are compatible with other GRID locations worldwide, where the same data were collected following an identical protocol. Findings from this study should allow to learn more about the global state of biodiversity and multiple-species monitoring worldwide. This data will prove specifically valuable for repeats in the future, as well as for quantitative analysis referenced in space and time. 201306current145.71718145.7289065.3941565.39906640.000682.000A square grid of 5 times 5 plots (100m spaced apart; 400m2 + 5 random plots), located at White Mountains (North to the NorthForkBirch and Twelvemile Creeks - near the public Steese Hgw 6) in Alaska, USA.NoneBiodiversity MonitoringGRID SamplingDISTANCE SamplingPRESENCEOccupancyData MiningPredictive ModelingMultiple-Species SurveyBiodiversitySubarcticMountainsWhite MountainsFairbanksUSAbirdsplantssprucelandscapedwarf birch (Betula nana 19479),Black crowberry (Empetrum nigrum 23743),Cottongrass (Eriophorum 40079),marsh Labrador tea (Rhododendron tomentosum 894434),Alaska blue berry (Vaccinium ovalifolium 23607),Bird vetch (Vicia cracca 26335)Ant (Formica 154211),Bohemian Waxwing (Bombycilla garrulus 178529),Fox Sparrow (Carduelis flammea 179230),Gray Jay (Perisoreus canadensis 179667),Swainson`s Thrush (Catharus ustulatus 179788),Raven (Corvus corax 179725),Yellow-rumped Warbler (Dendroica coronata 178891),Savannah Sparow (Passerculus sandwichensis 179314),Fox Sparrow (Passerella iliaca 179464),Grouse (Phasianidae 175861),Woodpecker (Picidae 178148),American Robin (Turdus migratorius 179759),Wilson Warbler (Wilsonia pusilla 178973),White-crowned Sparrow (Zonotrichia leucophrys 179455),Common Redpoll (Carduelis flammea 179230)National Park Service Theme Category ThesaurusISO 19115 Topic CategoryNoneWhite MontainsNorthForkBirch CreekTwelvemile Creeknear the Steese Hgw 6Steese HighwayAlaskaUSASubarcticBLMBureau of Land ManagementNational Park System Unit Name ThesaurusNational Park System Unit Code ThesaurusThe authors and EWHALE/UAF remain the owners of this dataset. However, this data is open access and can be distributed or utilized by interested parties.The authors and EWHALE/UAF remain the owners of this dataset. This data is open access and can be distributed or utilized by interested parties. However, it is important to interprete the data and findings in the context of the overall study and the methods outlined. Please refer to Citation for directions on how to cite when using the data. See also other BiodiversityGRIDs by the author and the M.Sc. thesis by Dirk Nemitz.Falk HuettmannUAFAssociate Professor907 474 7882fhuettmann@alaska.eduphotoscamera photosJPEGother grids done by the author and online.UnknownNonecollectionmultiple speciessingle speciesinvertebratesplantsvegetationvertebratesspidersmosslichendwarf birch (Betula nana 19479),Black crowberry (Empetrum nigrum 23743),Cottongrass (Eriophorum 40079)marsh Labrador tea (Rhododendron tomentosum 894434),Alaska blue berry (Vaccinium ovalifolium 23607),Bird vetch (Vicia cracca 26335)Ant (Formica 154211),Bohemian Waxwing (Bombycilla garrulus 178529),Fox Sparrow (Carduelis flammea 179230),Gray Jay (Perisoreus canadensis 179667),Swainson`s Thrush (Catharus ustulatus 179788),Raven (Corvus corax 179725),Yellow-rumped Warbler (Dendroica coronata 178891),Savannah Sparow (Passerculus sandwichensis 179314),Fox Sparrow (Passerella iliaca 179464),Grouse (Phasianidae 175861),Woodpecker (Picidae 178148),American Robin (Turdus migratorius 179759),Wilson Warbler (Wilsonia pusilla 178973),White-crowned Sparrow (Zonotrichia leucophrys 179455),Common Redpoll (Carduelis flammea 179230)KingdomAnimaliaPhylumArthropodaSubphylumHexapodaClassInsectaSubclassPterygotaInfraclassNeopteraOrderHymenopteraSuborderApocritaInfraorderAculeataSuperfamilyVespoideaFamilyFormicidaeSubfamilyFormicinaeTribeFormiciniGenusFormicaPhylumChordataSubphylumVertebrataClassAvesOrderGalliformesFamilyPhasianidaePartridgesTurkeysGrousePheasantsQuailcaillesfaisansOrderPasseriformesFamilyBombycillidaeGenusBombycillaSpeciesBombycilla garrulusBohemian Waxwingjaseur boréalFamilyCorvidaeGenusCorvusSpeciesCorvus coraxCuervo comúnCommon Ravengrand corbeauNorthern RavenGenusPerisoreusSpeciesPerisoreus canadensisGray Jaymésangeai du CanadaGrey JayFamilyEmberizidaeGenusPasserculusSpeciesPasserculus sandwichensisSavannah SparrowGorrión sabanerobruant des présGenusPasserellaSpeciesPasserella iliacaFox Sparrowbruant fauveGorrión rascadorGenusZonotrichiaSpeciesZonotrichia leucophrysWhite-crowned Sparrowbruant à couronne blancheGorrión corona blancaFamilyFringillidaeSubfamilyCarduelinaeGenusCarduelisSpeciesCarduelis flammeaCommon Redpollsizerin flamméFamilyParulidaeGenusDendroicaSpeciesDendroica coronataChipe coronadoYellow-rumped Warblerparuline à croupion jauneGenusWilsoniaSpeciesWilsonia pusillaChipe corona negraWilson's Warblerparuline à calotte noireFamilyTurdidaeGenusCatharusSpeciesCatharus ustulatusZorzal de SwainsonSwainson's Thrushgrive à dos oliveGenusTurdusSpeciesTurdus migratoriusMirlo primaveraAmerican Robinmerle d'AmériqueOrderPiciformesFamilyPicidaeWoodpeckersWrynecksfourmilierspic-boisKingdomPlantaeSubkingdomViridaeplantaeInfrakingdomStreptophytaDivisionTracheophytaSubdivisionSpermatophytinaInfradivisionAngiospermaeClassMagnoliopsidaSuperorderAsteranaeOrderEricalesFamilyEricaceaeGenusEmpetrumSpeciesEmpetrum nigrumblack crowberryGenusRhododendronSpeciesRhododendron tomentosummarsh Labrador teaGenusVacciniumSpeciesVaccinium ovalifoliumoval-leaf blueberryAlaska blueberrySuperorderLilianaeOrderPoalesFamilyCyperaceaeGenusEriophorumcottongrassSuperorderRosanaeOrderFabalesFamilyFabaceaeGenusViciaSpeciesVicia craccabird vetchtufted vetchcow vetchOrderFagalesFamilyBetulaceaeGenusBetulaSpeciesBetula nanashrub birchbog birchdwarf birchFalk Huettmann and Laszlo KoeverNoneUnclassifiedNoneexcel sheet and notebookDirk Nemitz did an analysis of such data for his M.Sc. thesis, based on data mining, Random Forest and PRESENCE and DISTANCE Sampling software, Details are available from the authors (or see cross reference for citation).see other GRIDs by author and onlineOnline_Linkage: see with NBII and eBIRD for more references and some dataPC IBM basedData were collected according to the GRID protocols, and as outlined in Nemitz (2008).All data should be high-quality. Insect, plant and tree data are basic but reliable.see aboveConsistent methods were used, see GRID protocol in Nemitz (2008)The GPSwas used for location (latitude and longitude). It is assumed it is accurate to +- 10m.Field and LabBIODIVERSITY GRID For efficiency reasons a systematic sampling approach was chosen. First of all an equally spaced GRID was implemented: 25 points were arranged in five rows and five columns in order to cover a consistent area but also to have a known spatial neighbor relationship among all plots. The distance between plots was 100 m, resulting in a total GRID size of 400 m x 400 m. While the final GRID system ideally covers the globe systematically without intentional placement, for these initial studies the GRIDs were placed in a way that roughly half to two thirds of the plots fell inside a forested area, the remaining plots at the forest edge or inside the cultural landscape. This survey setup enables other studies on the same data set to make realistic and representative statements about fragmentation effects. The only exception is GRID in Barrow in northern Alaska, where naturally only one habitat type, arctic tundra, occurs. Additionally, five points were randomly placed within the GRID to be able to model the influence of random patterns on the results and their spatial relations (Figure 8). The coordinates of each plot were obtained from a regular hand-held GPS receiver and re-visited by using the Go to function. All plots as well as the path between them were marked with decomposing flagging tape to make recognition in the field easier. A simple schematic map was drawn by hand for each field work participant to ensure that plots are found when the GPS does not receive signals, as was often the case in dense forest settings. BUDGET CONSTRAINTS The biodiversity GRID is meant as a method for cost-efficient rapid biodiversity assessment that allows for an analysis of spatial relations as well. All methods involved have to work in relatively short time, with low costs and little demand of technological equipment. There is no objection to include more sophisticated methods in add-on protocols, but they are discouraged for the main protocol to keep the inhibition threshold for decision makers low. Trained taxonomists were not available, as they rarely are for many ecosystems. All notes regarding the observed species were made as precisely as possible, although most of the observers were not trained especially in tropical ornithology or entomology. Data collection followed the motto the more detail the better, but it was not intended to refuse data because of lacking taxonomic details. If the observer did not readily know the correct scientific name of a specimen, a common name or, in lack of knowledge of a common name, a short description was noted. This original field note is referred to as the narrative name of an observation respectively of a species. Such process is common when dealing with large numbers of species and in largely unexplored environments, where huge fractions of the biodiversity remains still unknown, or where appropriate taxonomic guide books are missing. This resulted in good abundance and occupancy estimates, but in less detailed taxonomic data. Such is the characteristic in rapid biodiversity assessments on shoestring budgets, which allow for a first impression and provide detailed information for deeper investigation if desired. This type of rapid assessment additionally serves as a pilot study for further assessments. In the present study the focus lies on spatial global coverage, instead of local detail. ANIMAL SPECIES DATA COLLECTION In the ideal case, the protocol should result not only in information about the presence or absence of species, but also in an estimate of population size. The DISTANCE sampling approach uses the concept of a detection function based on distance of the observed object from the observer to estimate population density. It plays a central role in this study and is used in a number of ways. At each of the 30 plots (25 systematic and 5 random), five minute point transect DISTANCE sampling counts for birds were conducted within 360 degrees. A short settle-in period of one minute was granted prior to counting to allow for the snapshot character of DISTANCE sampling, especially meeting the assumption that presence of the observer does not introduce bias by causing responsive movements of animals. Following common practice the point counts took place only in the morning between 5:30 and 10 am. Birds are known to show higher activity at this time, which generally increases detectability and maximizes inventory accuracy. Each bird seen or heard was noted, including an estimate of the radial distance from the observer. Double counts were avoided by the observers attention and the relatively short counting period. Observers decided to make two adjustments: - in study area on Sakhalin Island, Russia seabird observations were excluded from plot A1; - in study area in Barrow, Alaska the survey time was reduced from five to four minutes. The second method of DISTANCE sampling used was a trapping web. 17 pitfall traps with a diameter of 9 cm each were arranged in a DISTANCE sampling trapping web design to estimate ground-living insects. This sampling method is very labor-intensive and could not be implemented at all 30 plots given the short time period available. Thus, four of the plots were systematically selected to capture the general patterns of species and abundances within the GRID: B2, D2, B4 and D4 (underlined in Figure 8) to gather at least some information about ground-living insects. Trapping webs were usually checked every 24 hours; and records were taken every 48 hours. In between check dates the cups were emptied without recording to avoid correlation in time between trapping events, and obtain spatially independent results. Because of the low number of traps and more available work force it was decided to add a third circle of traps at 3 m from the centre in study areas in Russia, Papua New Guinea and Barrow, Alaska. This increased the total number of pitfall traps in these areas to 25. The third application of DISTANCE sampling was an add-on sampling protocol using DISTANCE sampling line transects, conducted at each of the 30 plots. Transects with a length of 10 m and traversing the plot at its centre were surveyed to estimate numbers of butterflies, amphibians and reptiles. DISTANCE sampling point counts for birds and trapping webs for ground living insects were repeated three times. These repetitive visits further allow for an analysis with the software PRESENCE, which gives an estimate of general occurrence of a species in the area in a point-based sense. PRESENCE generates a detection function based on multiple visits under the assumption that the population is closed, meaning that no animals leave or enter the area of interest between several visits. Repetitions were not realized for the add-on protocol for DISTANCE sampling line transects. VEGETATION & ENVIRONMENT Additionally, basic data about the plot environment was collected. If at all possible, the GPS coordinates were noted. A plot picture and a canopy picture were taken with a digital camera to give a general impression of the area and also allow for an analysis of light conditions in other studies on the same data set, e.g. remote sensing investigations. All pictures are available from the authors. A short description of the ecosystem was noted as well (for example: pasture, forest interior, forest edge). Height and diameter at breast height were recorded for all trees within 5 m of plot centre. Estimates were noted regarding canopy cover percentage, understory cover percentage, shrub cover percentage (at 1.35 m height), bare soil percentage, duff coverage percentage, leaf browsing percentage, and number of flowers visible. The thickness of epiphytes, hemi-epiphytes, mosses and lichen was noted in categories (none, low, medium, high). Presence/absence of identified plant species or plant families was noted, as well as remarkable animal tracks (e.g. land crab holes, large mammal tracks, etc). Those are referred to as Covariates 1 to 32 in all six study areas, but the actual meaning is different in each. Detailed lists and the full protocol are available from the authors. The covariates can have one of four effects: 1. affecting habitat quality (presence/ absence of a species) 2. affecting detectability (detection/ non-detection of a species that is present) 3. affecting both of the above 4. affecting none of the above.Buckland et al2001Title: Introduction to DISTANCE samplingMacKenzie et al.2005Occupancy estimates and modelingBreiman2001Statistical modelling: the two culturesHuettmann & NemitzUnknownBiodiversity GRID Sampling ProtocolNo process steps have been described for this data setUnknownWhite mountains, Steese HighwayPoint0.0010.001Decimal degreesWorld Geodetic System of 1984World Geodetic System of 19846378137298.25722210088North American Vertical Datum of 1988metersAttribute valuesBird_surveybird detecion information for each plotauthorsdayday of surveyauthorsmonthmonth of surveyauthorsdatedate of surveyauthorsobserverspeople who done the surveyauthorslocationlocation where the survey doneauthorsstatestate where the survey doneauthorscountrycountry where the survey doneauthorsGeoProjused geo systemauthorsinstitutioninstitution carried out the surveyauthorsSurveytypemethod of surveyauthorsSurveylengthtime of survey duration at a pointauthorsweatherdescription of the weatherauthorsplotnamename of pointauthorlatitudelatitude of pointauthorslongitudelongitude of pointauthorssessionnumber of repeatauthorsstarttimetime of survey startingauthorsdetectiontimetime of the bird detectionauthorsspeciesname of the detected birdauthorsnumbernumber of the detected individualauthorsdistancemdistance from the detected bird speciesauthorsdetectiontypetype of the bird detectionauthorsbehaviourdescription of the bird`s behaviourauthorscommentscommentsauthorsyearyear of surveyauthorsVegetationVegetation for each plotauthorsplotnamename of pointauthorlatitudelatitude of pointauthorslongitudelongitude of pointauthorsaltitudealtitude of pointauthorsGeoProjused geo systemauthorslocationlocation where the survey doneauthorsstatestate where the survey doneauthorscountrycountry where the survey doneauthorsdayday of surveyauthorsmonthmonth of surveyauthorsyearyear of surveyauthorsdatedate of surveyauthorstimetime of surveyauthorsobserverspeople who done the surveyauthorsPhotostakenphotos about the pointauthorsNumbofWhiteSprucenumber of White Spruce of the pointauthorHeightofSpruceheight of white spuce at we observed at the pointauthorsotherplantsname of the plants that we observed at pointauthorsidentificationreferencesperson who determined the speciesauthorsnotesnote about the pointauthorsTrappingWebDistance Sampling Trapping Web for insectsauthorsplotnamename of pointauthorlatitudelatitude of pointauthorslongitudelongitude of pointauthorsaltitudealtitude of pointauthorsGeoProjused geo systemauthorslocationlocation where the survey doneauthorsstatestate where the survey doneauthorscountrycountry where the survey doneauthorssetdayday when we set up the trapauthorssetmonthmonth when we set up the trapauthorssetyearyear when we set up the trapauthorssetDatedate when we set up the trapauthorssettimetime when we set up the trapauthorsobserverspeople who done the surveyauthorscheckdayday when we checked the trapauthorscheckmonthmonth when we checked the trapauthorscheckyearyear when we checked the trapauthorscheckdatedate when we checked the trapauthorschecktimetime when we checked the trapauthorssessionrepeatnumber of repeatauthorstrapnamename of the trapauthorsdistfromcenternmdistance from the center in meterauthorsspeciesspecies that we found in the trapauthorsnumbernumber of the detected individualauthorsnotesnote about the pointauthorsExplanationsome basic explanation about the GRID surveyauthorssee authorsnoneNonePC IBM MS Excel or Open Office sheetregular office, phone or email2003110620031114Falk Huettmann and Laszlo KoeverUAF and University of DebrecenAssociate Professor and Ph.D. student907 474 7882fhuettmann@alaska.eduFGDC Biological Data Profile of the Content Standard for Digital Geospatial MetadataFGDC-STD-001.1-1999http://nrdata.nps.gov/profiles/NPS_Profile.xmlNPS NR and GIS Metadata Profile20031106local timeNANANANANA