Rapid Biodiversity Assessment GRID Sampling at Krasny Kamen (Yamalo-Nenetsky administrative region; c. 200 km from Vorkuta), Polar Ural foot hills, Russia, July 2011

Metadata also available as

Metadata:


Identification_Information:
Citation:
Citation_Information:
Originator:
Falk Huettmann, and Ekaterina Matsyna, 2011. EWHALE lab, Biology and Wildlife Dept. Institute of Arctic Biology, University of Alaska Fairbanks. University, USA.
Publication_Date: 20110722
Title:
Rapid Biodiversity Assessment GRID Sampling at Krasny Kamen (Yamalo-Nenetsky administrative region; c. 200 km from Vorkuta), Polar Ural foot hills, Russia, July 2011
Edition: 1
Geospatial_Data_Presentation_Form: database
Publication_Information:
Publication_Place: EWHALE lab
Publisher: University of Alaska-Fairbanks (UAF)
Other_Citation_Details: NA
Online_Linkage: NA
Description:
Abstract:
This data set contains Rapid Biodiversity Sampling data from a GRID (5*5 geo-referenced sampling + 5 random plots). It includes raw count data for 259 bird observations of 16 identified bird species, and plants from the 30 sampling plots (3m radius), and basic insect ocurrence from four trapping webs (3m radius, 25 traps each; mostly spiders), done July 15th til 20th 2011 at the Ural mountains foothills, railway141km, Yamalo-Nenetsky administrative okrug, c. 200km from Vorkuta town (app. +66.90592 latitude North, and +65.74022 longitude West; altitude 92-152 m above sea level). The study area is located north of the Arctic circle, and near a former Gulag camp site adjacent to mountains and near a railway. Plots are located in the boreal forest on some slope, and some are located near the railway. All plot locations were photographed (sky, ground and habitat shots). All bird detections (visual and oral) carry a radial distance from the observer, a time reference 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 and compatible descriptions) but are described with the Integrated Taxonomic Information System (itis.org). 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 in R and similar. A more detailed biological analysis is coming forward, and will be published elsewhere. 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) and for a wider, global analysis. Data from the other study sites are also available online. For more details please contact authors.
Purpose:
These 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.
Supplemental_Information:
The sampling sites are geo-referenced. DISTANCE Sampling abundance estimates, PRESENCE occupancy estimates and Random Forests predictive modeling for such types of GRIDs were done for a master thesis (Nemitz 2008).For details, please contact authors.

Book references for the study area: Ryzhanovsky V.N. (1997) Ecology of postbreeding period of subarctice passerine life. Ural University, Russian Academy of Science, Ekaterinburg, Russia. 288 pages.

Golovatin M, Paskhalny (2005). Birds of the Polar Ural. Ural University, Russian Academy of Science, Ekaterinburg, Russia. 560 pages.

Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20110715
Ending_Date: 20110724
Currentness_Reference: Current for 2009
Status:
Progress:
Maintenance_and_Update_Frequency: None planned for this dataset
Spatial_Domain:
Description_of_Geographic_Extent:
A squared grid of 5 times 5 plots (100m spaced apart; 400m2), located at Krasny Kamein (Red Rock), Polar Urals, Russia (railway km 141; near Harp village) in the Yamalo-Nenetsky administrative region (okrug), (c. 200 km from Vorkuta town).
Bounding_Coordinates:
West_Bounding_Coordinate: 65.742630
East_Bounding_Coordinate: 65.752640
North_Bounding_Coordinate: 66.909070
South_Bounding_Coordinate: 66.905160
Bounding_Altitudes:
Altitude_Minimum: 90
Altitude_Maximum: 152
Altitude_Distance_Units: meters
Keywords:
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: Biodiversity Monitoring
Theme_Keyword: GRID Sampling
Theme_Keyword: DISTANCE Sampling
Theme_Keyword: PRESENCE
Theme_Keyword: Occupancy
Theme_Keyword: Data Mining
Theme_Keyword: Predictive Modeling
Theme_Keyword: Multiple-Species Survey
Theme_Keyword: Biodiversity
Theme_Keyword: Mountains
Theme_Keyword: Polar Ural
Theme_Keyword: Ural
Theme_Keyword: Sob river
Theme_Keyword: Russia
Theme_Keyword: Arctic
Theme_Keyword: Birds
Theme_Keyword: Plants
Theme_Keyword: Trees
Theme_Keyword: Landscape
Theme_Keyword: Russian Railway
Theme_Keyword: Krasny Kamein (Red Rock)
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Russia
Place_Keyword: Ural
Place_Keyword: Polar Ural
Place_Keyword: Ural mountains
Place_Keyword: Foothills
Place_Keyword: Sob river
Place_Keyword: Vorkuta region
Place_Keyword: Harp village
Place_Keyword: 141 km railway station
Place_Keyword: Krasny Kamen (Red Rock)
Place_Keyword: Arctic
Place_Keyword: Russian Arctic
Taxonomy:
Keywords/Taxon:
Taxonomic_Keyword_Thesaurus: None
Taxonomic_Keywords: collection
Taxonomic_Keywords: multiple species
Taxonomic_Keywords: single species
Taxonomic_Keywords: invertebrates
Taxonomic_Keywords: plants
Taxonomic_Keywords: vegetation
Taxonomic_Keywords: vertebrates
Taxonomic_Keywords: Phylloscopus borealis
Taxonomic_Keywords: Anthus sp
Taxonomic_Keywords: Phylloscopus trochilus
Taxonomic_Keywords: Pica pica
Taxonomic_Keywords: Carduelis flammea
Taxonomic_Keywords: Larus sp
Taxonomic_Keywords: Poecile (Parus) cincta
Taxonomic_Keywords: Fringilla montifringilla
Taxonomic_Keywords: Sitta europea
Taxonomic_Keywords: Turdus
Taxonomic_Keywords: Corvus corone
Taxonomic_Keywords: Aves
Taxonomic_Keywords: Ficedula parva
Taxonomic_Keywords: Turdus atrogularis
Taxonomic_Keywords: Turdus pilaris
Taxonomic_Keywords: Turdus iliacus
Taxonomic_Keywords: Emberiza pusilla
Taxonomic_Keywords: Muscicapa striata
Taxonomic_Keywords: Vaccinium uliginosum
Taxonomic_Keywords: Rubus chamaemorus
Taxonomic_Keywords: Betula nana
Taxonomic_Keywords: Vaccinium myrtillus
Taxonomic_Keywords: Sphagnum
Taxonomic_Keywords: Empetrum nigrum
Taxonomic_Keywords: Ledum palustre
Taxonomic_Keywords: Carex sp
Taxonomic_Keywords: vaccinium vitis-idea
Taxonomic_Keywords: Equisetum sp
Taxonomic_Keywords: Larix sibirica
Taxonomic_Keywords: Alnus sp
Taxonomic_Keywords: Salix sp
Taxonomic_Keywords: Aconitum sp
Taxonomic_Keywords: Lycopodium clavatum
Taxonomic_Keywords: Rubus arcticus
Taxonomic_Keywords: Veratrum labelianum
Taxonomic_Keywords: Pteridium aquillinum (likely)
Taxonomic_Keywords: Anthriscus sylvestris
Taxonomic_Keywords: Geranium sylvaticum
Taxonomic_Keywords: Sorbus sp
Taxonomic_Keywords: Festuca sp
Taxonomic_Keywords: Solidaro virgaurea
Taxonomic_Keywords: Lynnea borealis
Taxonomic_Keywords: Caprifoliacae
Taxonomic_Keywords: Lycopodium clavatum
Taxonomic_Keywords: Rosa myalis
Taxonomic_Keywords: Lonicera caerulea
Taxonomic_Keywords: Dentaria quinquefolia
Taxonomic_Keywords: Trientalis europaea
Taxonomic_System:
Classification_System/Authority:
Classification_System_Citation:
Citation_Information:
Originator: ITIS (nonmatches do not show in the phylogeny)
Publication_Date: Unknown
Title:
Geospatial_Data_Presentation_Form:
Classification_System_Modifications: Some (Arctic and endemic) species do not show in ITIS yet.
Identification_Reference:
Citation_Information:
Originator: Local reference was used in Russian and by EM.
Originator: For plants, see:
Originator:
1. Alecseev Yu. E., Balandin S.A., Vakhrameeva M. G. 2003. Encyclopedia of plants in
Originator: Russia. Tundra plants. Moscow, Classic-Style, 208 p.
Originator:
2. Novikov V.S., Gubanov I.A. 1985. School Atlas is the determinant of higher
Originator: plants. Moscow, Prosvesheniye. 240
Publication_Date: Unknown
Title:
Geospatial_Data_Presentation_Form: atlas
Other_Citation_Details: see references mentioned within
Identifier:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Falk Huettmann, Ekaterina Matsyna
Contact_Organization: EWHALE lab
Contact_Address:
Address_Type: mailing and physical
Address: 419 Irving I
City: Fairbanks
State_or_Province: Alaska
Postal_Code: 99775
Country: USA
Contact_Voice_Telephone: 907 474 7882
Contact_Electronic_Mail_Address: fhuettmann@alaska.edu
Taxonomic_Procedures:
Birds were identified visually (or orally), and confirmed by binocular by FH and KM; local bird guides were used. Plants were mostly idenitied by KM and Anna Gaginskaya and with the help of a local plant book. See Linneage for citations and literature details; contact authors for questions.
Taxonomic_Completeness:
complete for birds in the grid, incomplete for insects and plants (photos were taken). Other birds that are found in the wider area but not encountered in the grid; Luscinia svecica - Bluethroat, Motacilla flava - Wagtail, Larus canus - Common Gull, Falco subbuteo Hobby, Carpodacus erithryna Rose Finch, Merganser, Hen Harrier Circus cyaneus, Hazelgrouse Bonasia bonasia
General_Taxonomic_Coverage: Birds, plants and insects of the Urals and Russian subarctic.
Taxonomic_Classification:
Taxon_Rank_Name: Kingdom
Taxon_Rank_Value: Animalia
Taxonomic_Classification:
Taxon_Rank_Name: Phylum
Taxon_Rank_Value: Chordata
Taxonomic_Classification:
Taxon_Rank_Name: Subphylum
Taxon_Rank_Value: Vertebrata
Taxonomic_Classification:
Taxon_Rank_Name: Class
Taxon_Rank_Value: Aves
Applicable_Common_Name: Birds
Applicable_Common_Name: oiseaux
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Ciconiiformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Laridae
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Larinae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Larus
Applicable_Common_Name: Gulls
Applicable_Common_Name: Ivory Gulls
Applicable_Common_Name: Kittiwakes
Applicable_Common_Name: Ross' Gulls
Applicable_Common_Name: Sabine's Gulls
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Passeriformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Corvidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Corvus
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Corvus corone
Applicable_Common_Name: Carrion Crow
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Pica
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Pica pica
Applicable_Common_Name: Black-billed Magpie
Applicable_Common_Name: pie bavarde
Applicable_Common_Name: Eurasian Magpie
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Emberizidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Emberiza
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Emberiza pusilla
Applicable_Common_Name: Little Bunting
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Fringillidae
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Carduelinae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Carduelis
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Carduelis flammea
Applicable_Common_Name: Common Redpoll
Applicable_Common_Name: sizerin flammé
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Fringillinae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Fringilla
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Fringilla montifringilla
Applicable_Common_Name: Brambling
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Motacillidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Anthus
Applicable_Common_Name: Pipits
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Muscicapidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Ficedula
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Ficedula parva
Applicable_Common_Name: Red-breasted Flycatcher
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Paridae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Poecile
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Poecile cincta
Applicable_Common_Name: Gray-headed Chickadee
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Sylviidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Phylloscopus
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Phylloscopus trochilus
Applicable_Common_Name: Willow Warbler
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Turdidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Turdus
Applicable_Common_Name: Robins
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Turdus iliacus
Applicable_Common_Name: Redwing
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Turdus pilaris
Applicable_Common_Name: Fieldfare
Applicable_Common_Name: grive litorne
Access_Constraints:
The 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.
Use_Constraints:
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.
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Falk Huettmann
Contact_Organization:
EWHALE lab- Biology and Wildlife Dept., Institute of Arctic Biology, University of Alaska Fairbanks
Contact_Address:
Address_Type:
Address: 419 IRVING I
City: Fairbanks
State_or_Province: Alaska
Postal_Code: 99775-7000
Country: USA
Contact_Voice_Telephone: 001 907 474 7882
Contact_Electronic_Mail_Address: fffh@uaf.edu
Data_Set_Credit: Falk Huettmann and Ekaterina Matsyna
Security_Information:
Security_Classification_System: NA
Security_Classification: Unclassified
Security_Handling_Description: NA
Native_Data_Set_Environment: Excel sheet and notebook
Cross_Reference:
Citation_Information:
Originator: Dirk Nemitz
Publication_Date: 2008
Title:
An assessment of sampling detectability for global bioidversity monitoring: results from sampling GRIDs in different climatic regions, Master thesis 5 Dec 2008 (unpublished)
Edition: 1
Geospatial_Data_Presentation_Form: document
Publication_Information:
Publication_Place: Goettingen
Publisher: University of Goettingen, MINC project
Other_Citation_Details:
This work was co-supervised between University of Goettingen and University of Alaska-Fairbanks
Online_Linkage: See also other BioDiversity GRIDS with NBII and by the author.
Analytical_Tool:
Analytical_Tool_Description:
Dirk Nemitz did an analysis of such data for his M.Sc. thesis, based on data mining, Random Forest and PRESENCE software, Details are available from the authors (or see cross reference for citation).
Tool_Access_Information:
Online_Linkage: see with NBII and eBIRD for more references and some data
Tool_Access_Instructions:

Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
Data were collected according to the GRID protocols, and as outlined in Nemitz (2008).
Quantitative_Attribute_Accuracy_Assessment:
Attribute_Accuracy_Value:
All data should be high-quality. Insect, plant and tree data are basic but reliable.
Attribute_Accuracy_Explanation: see above
Logical_Consistency_Report:
Consistent methods were used, see GRID protocol in Nemitz (2008)
Completeness_Report:
Dataset is complete for July 2011; raw data are not corrected for detectability but are collected in a research design that allow for unbiased estimates after processing. Some plant identifications should be evaluated.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
The GPSwas used for location (latitude and longitude). It is assumed it is accurate to +- 10m.
Lineage:
Methodology:
Methodology_Type: Field & Lab
Methodology_Identifier:
Methodology_Keyword_Thesaurus: None
Methodology_Keyword: DISTANCE Sampling
Methodology_Keyword: PRESENCE / Occupancy
Methodology_Description:
This text is taken from Nemitz M.Sc. (cited earlier)

BIODIVERSITY 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.

Methodology_Citation:
Citation_Information:
Originator: Buckland et al
Publication_Date: 2001
Title: Introduction to DISTANCE sampling
Geospatial_Data_Presentation_Form:
Methodology_Citation:
Citation_Information:
Originator: MacKenzie et a.
Publication_Date: 2005
Title: Occupancy estimates and modeling
Geospatial_Data_Presentation_Form:
Methodology_Citation:
Citation_Information:
Originator: Breiman
Publication_Date: 2001
Title: Statistical modelling: the two cultures
Geospatial_Data_Presentation_Form:
Methodology_Citation:
Citation_Information:
Originator: Huettmann & Nemitz
Publication_Date: Unknown
Title: Biodiversity GRID Sampling Protocol
Geospatial_Data_Presentation_Form:
Process_Step:
Process_Description: No process steps have been described for this data set
Process_Date: Unknown

Spatial_Data_Organization_Information:
Indirect_Spatial_Reference: Please socation names
Direct_Spatial_Reference_Method: Point

Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Geographic:
Latitude_Resolution: 0.001
Longitude_Resolution: 0.001
Geographic_Coordinate_Units: Decimal degrees
Geodetic_Model:
Horizontal_Datum_Name: World Geodetic System of 1984
Ellipsoid_Name: World Geodetic System of 1984
Semi-major_Axis: 6378137
Denominator_of_Flattening_Ratio: 298.25722210088
Vertical_Coordinate_System_Definition:
Altitude_System_Definition:
Altitude_Datum_Name: North American Vertical Datum of 1988
Altitude_Distance_Units: meters
Altitude_Encoding_Method:
Explicit elevation coordinate included with horizontal coordinates
Depth_System_Definition:
Depth_Datum_Name: Local surface
Depth_Distance_Units:
Depth_Encoding_Method:

Entity_and_Attribute_Information:
Detailed_Description:
Entity_Type:
Entity_Type_Label: Vegetation
Entity_Type_Definition: Vegetation for each plot
Entity_Type_Definition_Source: Falk Huettmann, EWHALE lab
Detailed_Description:
Entity_Type:
Entity_Type_Label: Birds
Entity_Type_Definition: Bird detection information for each plot
Entity_Type_Definition_Source: Falk Huettmann, EWHALE lab
Detailed_Description:
Entity_Type:
Entity_Type_Label: Trapping Webs
Entity_Type_Definition: Distance Sampling Trapping Web for insects
Entity_Type_Definition_Source: Falk Huettmann, EWHALE lab
Detailed_Description:
Entity_Type:
Entity_Type_Label: DistanceTransectCrossProfile
Entity_Type_Definition: Distance Sampling Cross Profile of the study area
Entity_Type_Definition_Source: Falk Huettmann, EWHALE lab
Detailed_Description:
Entity_Type:
Entity_Type_Label: Explanation
Entity_Type_Definition: Short details of the data and Excel sheet
Entity_Type_Definition_Source: Falk Huettmann, EWHALE lab

Distribution_Information:
Distributor:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Falk Huettmann
Contact_Organization:
EWHALE lab- Biology and Wildlife Dept., Institute of Arctic Biology, University of Alaska Fairbanks
Contact_Position: Associate Professor
Contact_Address:
Address_Type:
Address: 419 IRVING I
City: Fairbanks
State_or_Province: Alaska
Postal_Code: 99775-7000
Country: USA
Contact_Voice_Telephone: +1 907 474 7882
Contact_TDD/TTY_Telephone: +1 907 474 7959
Contact_Electronic_Mail_Address: fhuettmann@alaska.edu
Distribution_Liability:
The authors and the hosting institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics (i.e. GIF or JPG format files) are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The data are not better than the original sources from which they were derived. It is the responsibility of the data user to use the data appropriately and consistent within the limitations of geospatial data in general and these data in particular. The related graphics are intended to aid the data user in acquiring relevant data; it is not appropriate to use the related graphics as data. The authors give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data. It is strongly recommended that these data are directly acquired from an NPS server and not indirectly through other sources which may have changed the data in some way. Although these data have been processed successfully on computer systems at the University of Alaska, no warranty expressed or implied is made regarding the utility of the data on other systems for general or scientific purposes, nor shall the act of distribution constitute any such warranty. This disclaimer applies both to individual use of the data and aggregate use with other data.
Standard_Order_Process:
Fees: None
Custom_Order_Process: Contact authors, or Maderas Rainforest (online)

Metadata_Reference_Information:
Metadata_Date: 20081008
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Falk Huettmann, Ekatarina Matsyna
Contact_Organization:
EWHALE lab- Biology and Wildlife Dept., Institute of Arctic Biology, University of Alaska Fairbanks
Contact_Address:
Address_Type:
Address: 419 IRVING I
City: Fairbanks
State_or_Province: Alaska
Postal_Code: 99775-7000
Country: USA
Contact_Voice_Telephone: +1 907 474 7882
Contact_Electronic_Mail_Address: fhuettmann@alaska.edu
Metadata_Standard_Name:
FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Access_Constraints: None
Metadata_Use_Constraints: None
Metadata_Security_Information:
Metadata_Security_Classification_System: NA
Metadata_Security_Classification: Unclassified
Metadata_Security_Handling_Description: NA

Generated by mp version 2.8.25 on Mon Jan 30 00:28:53 2012