Rapid Biodiversity Assessment based on GRID Sampling in the Shainjang Wetland Reserve, Fuyan city, Amur river, Northeast China, July 2009

Metadata also available as

Metadata:


Contact_Information:
Contact_Address:
Address: MANDATORY IF APPLICABLE for Data Store

Identification_Information:
Citation:
Citation_Information:
Originator:
Falk Huettmann 1, Aleksey Antonov 2, 2009. 1. EWHALE lab, Biology and Wildlife Dept. Institute of Arctic Biology, University of Alaska Fairbanks. University, USA.
Publication_Date: Unknown
Title:
Rapid Biodiversity Assessment based on GRID Sampling in the Shainjang Wetland Reserve, Fuyan city, Amur river, Northeast China, July 2009
Other_Citation_Details: NA
Online_Linkage: NA
Description:
Abstract:
This data set contains Rapid Biodiversity Sampling data from a GRID. It includes raw count data for 541 bird observations of 38 identified bird species, plants from 30 sampling plots (5*5 100m grid plus 5 random ones lcoated within the grid), and insects from one trapping web, done at the Shainjang Wetland Reserve (RAMSAR Site, and World Heritage Site) at the Amur River, 30km near Fuyan city, Northeastern China (app. 134.57387 longitude and 48.13049 latitude). The site located near the Russian Border. Plots are located in the wetland, with many of them being located on grassland slightly covered by water, and some being located on an access road. All plot locations were photographed (sky and habitat shot). All bird detections (visual and oral) carry a radial distance 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 (only at one plot location due to water coverage elsewhere). Each plot was visited three times according to the PRESENCE software to obtain occupancy. In addition, two cross-profile line transects, app. 200m long each, were carried out in the study area also using DISTANCE SAMPLING. The strongest data set are the birds (species identification and densities), insect identifications are coarse but very good for densities; plant species identifications are coarse, too, but photos exist. They can be used for habitat types and cover percentages, e.g. in Remote Sensing studies nd for groundtruthing. These data can be data-mined using for instance RandomForest, Distance Sampling and PRESENCE. A more detailed biological analysis is coming forward, and will be published elsewhere. Raw data are available as Excel sheets from the authors. Comparable Biodiversity GRID data so far is available for over 5 other regions (e.g. Nicaragua, Central Alaska, Costa Rica, Papua New-Guinea, Northern Alaska). Data from the other study sites are also planned to be available online, and metadata are found online (see with NBII National Biological Information Infrastructure webpage). 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 5 other locations, where the same data were collected following an identical protocol. Findings from this study would allow to learn more about the state of biodiversity and multiple-species monitoring.
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.
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20070806
Ending_Date: 20070824
Currentness_Reference: Current for 2009
Status:
Maintenance_and_Update_Frequency: None planned for this dataset
Spatial_Domain:
Description_of_Geographic_Extent:
Shainjang Wetland Reserve, Fuyan city, Amur river near Russian Border, Northeast China
Bounding_Coordinates:
West_Bounding_Coordinate: 143.69052
East_Bounding_Coordinate: 143.69526
North_Bounding_Coordinate: 50.60234
South_Bounding_Coordinate: 50.59892
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: China
Theme_Keyword: Amur River
Theme_Keyword: RAMSAR site
Theme_Keyword: Wetland
Theme_Keyword: World Heritage Site
Theme:
Theme_Keyword_Thesaurus: National Park Service Theme Category Thesaurus
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: China
Theme_Keyword: Amur River
Theme_Keyword: RAMSAR site
Theme_Keyword: Wetland
Theme_Keyword: World Heritage Site
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
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: China
Theme_Keyword: Amur River
Theme_Keyword: RAMSAR site
Theme_Keyword: Wetland
Theme_Keyword: World Heritage Site
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: China
Place_Keyword: Amur River
Place_Keyword: Russian Border
Place_Keyword: Shainjang Wetland Reserve
Place_Keyword: Fuyan city
Place_Keyword: Northeastern China
Place:
Place_Keyword_Thesaurus: National Park System Unit Name Thesaurus
Place_Keyword: China
Place_Keyword: Amur River
Place_Keyword: Russian Border
Place_Keyword: Shainjang Wetland Reserve
Place_Keyword: Fuyan city
Place_Keyword: Northeastern China
Place:
Place_Keyword_Thesaurus: National Park System Unit Code Thesaurus
Place_Keyword: China
Place_Keyword: Amur River
Place_Keyword: Russian Border
Place_Keyword: Shainjang Wetland Reserve
Place_Keyword: Fuyan city
Place_Keyword: Northeastern China
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: Acrocephalus bistrigiceps
Taxonomic_Keywords: Alcedo atthis
Taxonomic_Keywords: Anas crecca
Taxonomic_Keywords: Anas falcata
Taxonomic_Keywords: Anas platyrhynchos
Taxonomic_Keywords: Anas sp
Taxonomic_Keywords: Anas strepera
Taxonomic_Keywords: Ardea cinerea
Taxonomic_Keywords: Circus melanoleucos
Taxonomic_Keywords: Circus spilonotus
Taxonomic_Keywords: Corvus corone
Taxonomic_Keywords: Cuculus canorus
Taxonomic_Keywords: Domestic Duck
Taxonomic_Keywords: Egretta alba
Taxonomic_Keywords: Emberiza fucata
Taxonomic_Keywords: Emberiza schoeniclus
Taxonomic_Keywords: Emberiza sp
Taxonomic_Keywords: Falco amurensis
Taxonomic_Keywords: Falco subbuteo
Taxonomic_Keywords: Fulica atra
Taxonomic_Keywords: Gallinula chloropus
Taxonomic_Keywords: Hirundo daurica
Taxonomic_Keywords: Hirundo rustica
Taxonomic_Keywords: Hirundo sp
Taxonomic_Keywords: Ixobrychus eurythmos
Taxonomic_Keywords: Lanius cristatus
Taxonomic_Keywords: Larus ridibundus
Taxonomic_Keywords: Locustella certhiola
Taxonomic_Keywords: Motacilla alba
Taxonomic_Keywords: Pandion haliaetus
Taxonomic_Keywords: Passer montanus
Taxonomic_Keywords: Passerines
Taxonomic_Keywords: Phalacrocorax carbo
Taxonomic_Keywords: Phasianus colchicus
Taxonomic_Keywords: Pica pica
Taxonomic_Keywords: Rallus sp
Taxonomic_Keywords: Saxicola torquata
Taxonomic_Keywords: Sterna hirundo
Taxonomic_Keywords: Streptopelia orientalis
Taxonomic_Keywords: Tachybaptus ruficollis
Taxonomic_Keywords: Tringa nebularia
Taxonomic_Keywords: Vanellus vanellus
Taxonomic_Keywords: Carabidae
Taxonomic_System:
Classification_System/Authority:
Classification_System_Citation:
Citation_Information:
Originator: ITIS (nonmatches are listed)
Publication_Date: Unknown
Identifier:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Falk Huettmann and Aleksey Antonov
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: fffh@uaf.edu
Taxonomic_Procedures:
Birds were identified visually (or orally), and confirmed by binocular. The strongest data set are the birds (species identification and densities), insect identifications are coarse but good to be used for densities; plant species identifications are coarse, too, but photos exist. They can be used for habitat types and cover percentages, e.g. in Remote Sensing studies nd for groundtruthing.
Taxonomic_Completeness:
complete for birds, incomplete for insects and plants (photos were taken)
Taxonomic_Classification:
Taxon_Rank_Name: Kingdom
Taxon_Rank_Value: Animalia
Taxonomic_Classification:
Taxon_Rank_Name: Phylum
Taxon_Rank_Value: Arthropoda
Taxonomic_Classification:
Taxon_Rank_Name: Subphylum
Taxon_Rank_Value: Hexapoda
Taxonomic_Classification:
Taxon_Rank_Name: Class
Taxon_Rank_Value: Insecta
Taxonomic_Classification:
Taxon_Rank_Name: Subclass
Taxon_Rank_Value: Pterygota
Taxonomic_Classification:
Taxon_Rank_Name: Infraclass
Taxon_Rank_Value: Neoptera
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Coleoptera
Taxonomic_Classification:
Taxon_Rank_Name: Suborder
Taxon_Rank_Value: Adephaga
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Carabidae
Applicable_Common_Name: carabes
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
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Anseriformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Anatidae
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Anatinae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Anas
Applicable_Common_Name: Dabbling Ducks
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Anas crecca
Applicable_Common_Name: sarcelle d'hiver
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Anas falcata
Applicable_Common_Name: Falcated Teal
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Anas platyrhynchos
Applicable_Common_Name: canard colvert
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Anas strepera
Applicable_Common_Name: canard chipeau
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Ciconiiformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Accipitridae
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Accipitrinae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Circus
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Circus melanoleucos
Applicable_Common_Name: Pied Harrier
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Circus spilonotus
Applicable_Common_Name: Eastern Marsh Harrier
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Pandioninae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Pandion
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Pandion haliaetus
Applicable_Common_Name: balbuzard pêcheur
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Ardeidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Ardea
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Ardea alba
Applicable_Common_Name: Great Egret
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Ardea cinerea
Applicable_Common_Name: Grey Heron
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Ixobrychus
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Ixobrychus eurhythmus
Applicable_Common_Name: Von Schrenck's Bittern
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Charadriidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Vanellus
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Vanellus vanellus
Applicable_Common_Name: vanneau huppé
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Falconidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Falco
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Falco amurensis
Applicable_Common_Name: Amur Falcon
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Falco subbuteo
Applicable_Common_Name: Eurasian Hobby
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
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Larus ridibundus
Applicable_Common_Name: mouette rieuse
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Sterninae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Sterna
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Sterna hirundo
Applicable_Common_Name: sterne pierregarin
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Phalacrocoracidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Phalacrocorax
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Phalacrocorax carbo
Applicable_Common_Name: grand cormoran
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Podicipedidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Tachybaptus
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Tachybaptus ruficollis
Applicable_Common_Name: Little Grebe
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Scolopacidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Tringa
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Tringa nebularia
Applicable_Common_Name: Common Greenshank
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Columbiformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Columbidae
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Columbinae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Streptopelia
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Streptopelia orientalis
Applicable_Common_Name: Oriental Turtle Dove
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Coraciiformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Alcedinidae
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Alcedininae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Alcedo
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Alcedo atthis
Applicable_Common_Name: Common Kingfisher
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Cuculiformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Cuculidae
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Cuculinae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Cuculus
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Cuculus canorus
Applicable_Common_Name: Common Cuckoo
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Galliformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Phasianidae
Taxonomic_Classification:
Taxon_Rank_Name: Subfamily
Taxon_Rank_Value: Phasianinae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Phasianus
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Phasianus colchicus
Applicable_Common_Name: Faisán de collar
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Gruiformes
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Rallidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Fulica
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Fulica atra
Applicable_Common_Name: Eurasian Coot
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Gallinula
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Gallinula chloropus
Applicable_Common_Name: gallinule poule-d'eau
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Rallus
Applicable_Common_Name: Greater Rails
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: Eurasian Magpie
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Emberizidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Emberiza
Applicable_Common_Name: Eurasian Buntings
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Emberiza fucata
Applicable_Common_Name: Chestnut-eared Bunting
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Emberiza schoeniclus
Applicable_Common_Name: Reed Bunting
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Hirundinidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Hirundo
Applicable_Common_Name: Barn Swallows
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Hirundo daurica
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Hirundo rustica
Applicable_Common_Name: hirondelle rustique
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Laniidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Lanius
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Lanius cristatus
Applicable_Common_Name: Brown Shrike
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Motacillidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Motacilla
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Motacilla alba
Applicable_Common_Name: White Wagtail
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Muscicapidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Saxicola
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Saxicola torquatus
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Passeridae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Passer
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Passer montanus
Applicable_Common_Name: Eurasian Tree Sparrow
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Sylviidae
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Acrocephalus
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Acrocephalus bistrigiceps
Applicable_Common_Name: Black-browed Reed Warbler
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Locustella
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Locustella certhiola
Applicable_Common_Name: Pallas's Grasshopper Warbler
Access_Constraints:
The authors and EWHALE/UAF remain the owners of this dataset. However, this data can be distributed or utilized by interested parties.
Use_Constraints:
The authors and EWHALE/UAF remain the owners of this dataset. This data 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.
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: 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
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
Data_Set_Credit: Falk Huettmann and Aleksey Antonov
Security_Information:
Security_Classification_System: na
Security_Classification: Unclassified
Security_Handling_Description: na
Native_Data_Set_Environment: Excel sheet and notebook

Data_Quality_Information:
Logical_Consistency_Report:
Consistent methods were used, see GRID protocol in Nemitz (2008)
Completeness_Report: Dataset is complete for July 2009
Lineage:
Methodology:
Methodology_Type: Field & Lab
Methodology_Identifier:
Methodology_Keyword_Thesaurus: None
Methodology_Keyword: DISTANCE Sampling
Methodology_Keyword: PRESENCE / Occupancy
Methodology_Description:
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 500 m x 500 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
Methodology_Citation:
Citation_Information:
Originator: MacKenzie et a.
Publication_Date: 2005
Title: Occupancy estimates and modeling
Methodology_Citation:
Citation_Information:
Originator: Breiman
Publication_Date: 2001
Title: Statistical modelling: the two cultures
Methodology_Citation:
Citation_Information:
Originator: Huettmann & Nemitz
Publication_Date: Unknown
Title: Biodiversity GRID Sampling Protocol
Process_Step:
Process_Description: No process steps have been described for this data set
Process_Date: Unknown
Attribute_Accuracy:
Attribute_Accuracy_Report:
Data were collected according to the GRID protocols, and as outlined in Nemitz (2008). However, for time and organizational reasons, only ONE (not four as usually done; but with the usual 3 repeats) trapping web was done.

Spatial_Data_Organization_Information:
Indirect_Spatial_Reference: Location 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:
Depth_System_Definition:
Depth_Datum_Name: Local surface

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
Attribute:
Attribute_Label: Excel sheet columns
Attribute_Definition:
The attributes followed the standard Excel sheets of previous GRID studies; see D. Nemitz thesis 2008 (also cited in cross reference section)
Attribute_Definition_Source: Falk Huettmann and Dirk Nemitz
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
Attribute:
Attribute_Label: Excel sheet columns
Attribute_Definition:
The attributes followed the standard Excel sheets of previous GRID studies; see D. Nemitz thesis 2008 (also cited in cross reference section)
Attribute_Definition_Source: Falk Huettmann and Dirk Nemitz
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
Attribute:
Attribute_Label: Excel sheet columns
Attribute_Definition:
The attributes followed the standard Excel sheets of previous GRID studies; see D. Nemitz thesis 2008 (also cited in cross reference section)
Attribute_Definition_Source: Falk Huettmann and Dirk Nemitz
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
Attribute:
Attribute_Label: Excel sheet columns
Attribute_Definition:
The attributes followed the standard Excel sheets of previous GRID studies; see D. Nemitz thesis 2008 (also cited in cross reference section)
Attribute_Definition_Source: Falk Huettmann and Dirk Nemitz
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 PhD, Associate Professor
Contact_Organization:
EWHALE lab- Biology and Wildlife Dept., Institute of Arctic Biology, University of Alaska Fairbanks
Contact_Address:
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
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

Metadata_Reference_Information:
Metadata_Date: 20081008
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Falk Huettmann PhD, Associate Professor
Contact_Organization:
EWHALE lab- Biology and Wildlife Dept., Institute of Arctic Biology, University of Alaska Fairbanks
Contact_Address:
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
Metadata_Standard_Name:
FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Extensions:
Online_Linkage: <http://nrdata.nps.gov/profiles/NPS_Profile.xml>
Profile_Name: NPS NR and GIS Metadata Profile
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

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