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WE035: Multi-locus DNA metabarcoding of western spotted skunk diet in the McKenzie River Ranger District of the Willamette National Forest from 2017-2019

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Status: notPlanned
Period: 2017-08-03 to 2019-01-25
Version: 2
Published: 2022-12-07
EDI Package ID: knb-lter-and.11771.2
Source XML: WE035_2.xml

Notice

"As Is" Basis: All content, including maps and forecasts, is provided without warranties. Users are advised to independently verify critical information.

Citation

Tosa, M.; Levi, T.; Lesmeister, D. 2022. Multi-locus DNA metabarcoding of western spotted skunk diet in the McKenzie River Ranger District of the Willamette National Forest from 2017-2019 Long-Term Ecological Research Andrews Forest LTER Site. [Database]. Available: https://andrewsforest-stage.forestry.oregonstate.edu/data/fsdb-data-catalog/WE035 Accessed 2026-05-10.

Abstract

There are increasing concerns about the declining population trends of small mammalian carnivores around the world. Their conservation and management is often challenging due to limited knowledge about their ecology and natural history. To address one of these deficiencies for western spotted skunks (Spilogale gracilis), we investigated their diet in the Oregon Cascades of the Pacific Northwest during 2017 –2019. We collected 130 spotted skunk scats opportunistically and with detection dog teams and identified prey items using DNA metabarcoding and mechanical sorting. Western spotted skunk diet consisted of invertebrates such as wasps, millipedes, and gastropods, vertebrates such as small mammals, amphibians, and birds, and plants such as Gaultheria, Rubus, and Vaccinium. Diet also consisted of items such as black-tailed deer that were likely scavenged. Comparison in diet by season revealed that spotted skunks consumed more insects during the dry season (June –August), particularly wasps (75% of scats in the dry season), and marginally more mammals during the wet season(September –May). We observed similar diet in areas with no record of human disturbance and areas with a history of logging at most spatial scales, but scats collected in areas with older forest within a skunk’s home range (1 km buffer) were more likely to contain insects. Western spotted skunks provide food web linkages between aquatic, terrestrial, and arboreal systems and serve functional roles of seed dispersal and scavenging. Due to their diverse diet and prey-switching, western spotted skunks may dampen the effects of irruptions of prey, such as wasps during dry springs and summers. By studying the natural history of western spotted skunks in the Pacific Northwest forests while they are still abundant, we provide key information necessary to achieve the conservation goal of keeping this common species common.

Coverage

Temporal coverage: 2017-08-03 to 2019-01-25

Geographic coverage: HJ Andrews Experimental Forest and the surrounding Willamette National Forest (Blue River and Lookout Creek watersheds)

Spatial coverage:

Bounds: W -122.28668350, E -122.12885316, N 44.30425907, S 44.18280497

Purpose
  • To provide a baseline for western spotted skunk diets in the forests of the Pacific Northwest
Project

Title: Long-Term Ecological Research

Personnel
  • Posy Elizabeth Busby - Principal Investigator
    Assistant Professor OSU Botany & Plant Pathology
    Email: busbyp@science.oregonstate.edu, posybusby@gmail.com
    ORCID: http://orcid.org/0000-0002-2837-9820
  • Matthew G Betts - Principal Investigator
    Department of Forest Ecosystems and Society; 201E Richardson Hall; College of Forestry; Oregon State University, Corvallis, OR, 97331
    Phone: (541) 737-3841
    Email: matt.betts@oregonstate.edu
    ORCID: http://orcid.org/0000-0002-7100-2551
  • Brooke E. Penaluna - Principal Investigator
    Email: brooke.penaluna@usda.gov, Brooke.Penaluna@oregonstate.edu
    ORCID: http://orcid.org/0000-0001-7215-770X
  • Catalina Segura - Principal Investigator
    Assistant Professor; Department of Forest Engineering, Resources, and Management; Oregon State University, Corvallis, OR, 97331
    Phone: 541-737-6568
    Email: catalina.segura@oregonstate.edu
    ORCID: http://orcid.org/0000-0002-0924-1172
  • David Bell - Principal Investigator
    Email: david.bell@usda.gov, david.bell@oregonstate.edu
    ORCID: http://orcid.org/0000-0002-2673-5836
Abstract
  • The H.J. Andrews Experimental Forest is a living laboratory that provides unparalleled opportunities for the study of forest and stream ecosystems in the central Cascade Range of Oregon. Since 1980, as a part of the National Science Foundation Long Term Ecological Research (NSF-LTER) program, the Andrews Experimental Forest has become a leader in the analysis of forest and stream ecosystem dynamics.
  • Long-term field experiments and measurement programs have focused on climate dynamics, streamflow, water quality, and vegetation succession. Currently researchers are working to develop concepts and tools needed to predict effects of natural disturbance, land use, and climate change on ecosystem structure, function, and species composition.
  • The Andrews Experimental Forest is administered cooperatively by the USDA Forest Service Pacific Northwest Research Station, Oregon State University and the Willamette National Forest. Funding for the research program comes from the National Science Foundation (NSF), US Forest Service Pacific Northwest Research Station, Oregon State University, and other sources.
Funding

Data were provided by the HJ Andrews Experimental Forest research program, funded by the National Science Foundation's Long-Term Ecological Research Program (DEB 2025755), US Forest Service Pacific Northwest Research Station, and Oregon State University. National Science Foundation: DEB2025755

Awards
Study Area Description
  • Long-Term Ecological Research
    The Andrews Forest is situated in the western Cascade Range of Oregon, and covers the entire 15,800-acre (6400-ha) drainage basin of Lookout Creek. Elevation ranges from 1350 to 5340 feet (410 to 1630 m). Broadly representative of the rugged mountainous landscape of the Pacific Northwest, the Andrews Forest contains excellent examples of the region's conifer forests and associated wildlife and stream ecosystems. These forests are among the tallest and most productive in the world, with tree heights of often greater than 250 ft (75 m). Streams are steep, cold and clean, providing habitat for numerous aquatic organisms.
Associated Party
Contact
  • Information Manager
    Andrews Forest LTER Program, US Forest Service Pacific Northwest Research Station, 3200 SW Jefferson Way, Corvallis, OR, 97331
    Email: hjaweb@lists.oregonstate.edu
  • Marie I Tosa
    104 Nash Hall, Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Corvallis, OR, 97331, USA
    Email: marie.tosa@oregonstate.edu, tosa.marie@gmail.com
Publisher
  • Andrews Forest LTER Site
    Role: Publisher
    Forest Ecosystems and Society Department in Forestry, Oregon State University, 201K Richardson Hall, Corvallis, OR, 97331-5752
    Phone: (541) 737-8480
    Email: lterweb@lists.oregonstate.edu
Study Description

There are increasing concerns about the declining population trends of small mammalian carnivores around the world. Their conservation and management is often challenging due to limited knowledge about their ecology and natural history. To address one of these deficiencies for western spotted skunks (Spilogale gracilis), we investigated their diet in the Oregon Cascades of the Pacific Northwest during 2017 –2019. We collected 130 spotted skunk scats opportunistically and with detection dog teams and identified prey items using DNA metabarcoding and mechanical sorting. Western spotted skunk diet consisted of invertebrates such as wasps, millipedes, and gastropods, vertebrates such as small mammals, amphibians, and birds, and plants such as Gaultheria, Rubus, and Vaccinium. Diet also consisted of items such as black-tailed deer that were likely scavenged. Comparison in diet by season revealed that spotted skunks consumed more insects during the dry season (June –August), particularly wasps (75% of scats in the dry season), and marginally more mammals during the wet season(September –May). We observed similar diet in areas with no record of human disturbance and areas with a history of logging at most spatial scales, but scats collected in areas with older forest within a skunk’s home range (1 km buffer) were more likely to contain insects. Western spotted skunks provide food web linkages between aquatic, terrestrial, and arboreal systems and serve functional roles of seed dispersal and scavenging. Due to their diverse diet and prey-switching, western spotted skunks may dampen the effects of irruptions of prey, such as wasps during dry springs and summers. By studying the natural history of western spotted skunks in the Pacific Northwest forests while they are still abundant, we provide key information necessary to achieve the conservation goal of keeping this common species common. To provide a baseline for western spotted skunk diets in the forests of the Pacific Northwest Field Methods - WE035

Purpose: To provide a baseline for western spotted skunk diets in the forests of the Pacific Northwest

Methods

Method Steps

Field Methods - WE035
  • We collected western spotted skunk scat in multiple ways: 1) during western spotted skunk capture, 2) opportunistically while tracking western spotted skunks with radio-collars and checking trail cameras, and 3) using detection dog teams (summer and fall of 2018). Detection dog teams either surveyed 3 x 3 km grids within the study area for a minimum of 6 hours near camera trap locations where we detected western spotted skunk or focused their surveys around known spotted skunk rest sites. Focused surveys were necessary to increase scat sample sizes and increase spotted skunk scat detection rates. Moreover, western spotted skunk scats were difficult to locate opportunistically because typically, they were deposited after we tracked skunks to their rest sites, were in hard to search locations such as in hollow logs or a short distance from the rest site. We froze all scat samples until we processed them in the laboratory, and processed scats were dried for long-term storage. Detection dog location and collection times where recorded with a handheld GPS. The collection times were originally recorded in local time (Pacific Standard, after 11/4/2018 01:59 AM, or Pacific Daylight, before 11/4/2018 02:00 AM, depending on the date). Pacific Daylight times were converted to Pacific Standard time in the database.
Laboratory Methods - WE035
  • In the lab, we identified the diet of western spotted skunks using DNA metabarcoding (Massey et al. 2021; Eriksson et al. 2019) and mechanical sorting. For DNA metabarcoding, we extracted DNA in a laboratory dedicated to processing degraded DNA using the DNeasy Blood and Tissue kit (Qiagen, Germantown, Maryland) or the QIAamp Fast DNA Stool Mini Kit (Qiagen, Germantown, Maryland). We included an extraction blank with every batch of extractions as a negative control, where we used the same protocol but without a fecal sample (hereafter called extraction blanks). We kept extraction blanks throughout the DNA metabarcoding process. Following DNA extraction, we amplified 3 regions of the mitochondria and chloroplast DNA. First, we amplified a ~100 base-pair DNA segment of the ribosomal mitochondrial 12S gene using universal vertebrate primers (12S-V5-F’: YAGAACAGGCTCCTCTAG and 12S-V5-R: TTAGATACCCCACTATGC) (Kocher et al. 2017; Riaz et al. 2011) and the chloroplast-encoded intron region of the trnL gene using universal plant primers (g-F: GGGCAATCCTGAGCCAA and h-R: CCATYGAGTCTCTGCACCTATC) (Taberlet et al. 2007) in a multiplex polymerase chain reaction (PCR). In a separate singleplex PCR reaction, we amplified the mitochondrial-encoded cytochrome oxidase subunit I (COI) gene using ANML universal arthropod primers (LCO1490-F: GGTCAACAAATCATAAAGATATTGG and CO1-CFMRa-R: GGWACTAATCAATTTCCAAATCC) (Jusino et al. 2019). We performed 3 PCR replicates per sample using the QIAGEN Multiplex PCR kit (Qiagen, Germantown, Maryland) (Appendix S1). To aid in identifying contamination, we performed PCR on a negative control on each plate (hereafter called PCR blanks) in addition to the extraction blanks. Each reaction was amplified with identical 8 base pair tags on the 5’ end of the forward and reverse primer that were unique to each sample to identify individual sample after pooling and to prevent misidentification of prey samples due to tag jumping (Schnell, Bohmann, and Gilbert 2015). We normalized and pooled the PCR products and used NEBNext Ultra II Library Prep Kit (New England BioLabs, Ipswich, Massachusetts) to adapt the library pools into Illumina sequencing libraries (Illumina Inc., San Diego, California). We purified libraries using the Solid Phase Reversible Immobilization beads and sent libraries to the Center for Genome Research and Biocomputing at Oregon State University for 150 base pair paired-end sequencing on the Illumina HiSeq 3000. We paired raw sequence reads using PEAR (Zhang et al. 2014) and demultiplexed samples based on the 8-base pair-index sequences using a custom shell script (Appendix S2). We counted unique reads from each sample replicate and assigned taxonomy using BLAST against the 12S, COI, and trnL sequences in a local database and GenBank (www.ncbi.nlm.nih.gov/blast). Scat amplification was considered successful if DNA sequencing produced over 100 total reads per replicate, and we limited the effects of contamination by retaining only species that consisted of more than 1% of the total reads. Furthermore, we used extraction and PCR negative controls to set additional filtering thresholds for species read counts. Species were only retained in the final species list if it was present in at least 2 of the 3 replicates and if their species distribution maps included our study area or were included on the species lists of the study area (https://andrewsforest.oregonstate.edu/about/species). We identified plants to genus since congeners are difficult to differentiate using these primers. To mechanically sort scats, we placed dried scat contents in a petri dish and separated items using forceps. We identified remains macroscopically to the lowest taxonomic order possible (typically class or order). If we had used all fecal matter for DNA metabarcoding, we relied on notes on identifiable parts from when the scat was collected or processed samples for DNA extraction. Once mechanically sorted, we compared our findings to the DNA metabarcoding results for each scat. If the identified taxon was not included in the DNA metabarcoding results, we augmented the results with the missing taxon. We used mechanical sorting to augment results from DNA metabarcoding because of known biases introduced by mismatches in the universal invertebrate ANML primers we used, which is attributed to a lack of conserved regions across all invertebrates (Deagle et al. 2014). We confirmed scats as defecated by western spotted skunks using the metabarcoding data following criteria: 1) western spotted skunk was the only carnivore (order: Carnivora) identified in the scat, or 2) western spotted skunk was one of the carnivores identified in the scat and the other carnivores consisted of less than 10% of the read count. We confirmed the predator in this way because predators are frequently misidentified through scat morphology (Morin et al. 2016; Lonsinger, Gese, and Waits 2015).

Sampling

Study Extent
  • This study was centered around the H. J. Andrews Experimental Forest (HJA), which is located on the western slope of the Cascade Mountain Range near Blue River, Oregon (Figure 1). The area is surrounded by the McKenzie River Ranger District of the Willamette National Forest. Elevations range from 410 m to 1,630 m. The maritime climate consists of warm, dry summers and mild, wet winters. Mean monthly temperatures range from 1°C in January to 18°C in July. Precipitation falls primarily as rain, is concentrated from November through March, and averages 230 cm at lower elevations and 355 cm at higher elevations (Greenland 1993; Swanson and Jones 2002). During 2018 – 2019, western Oregon experienced an extreme drought (USDM 2022). In Lane County, drought severity was greatest during August 2018 – February 2019, but abnormally dry conditions began as early as January 2018 and moderate drought conditions began as early as June 2018 (Appendix S1: Figure S1). Lower elevation forests are dominated by Douglas-fir (Pseudotsuga menziesii), western hemlock (Tsuga hetemphylla), and western red cedar (Thuja plicata). Upper elevation forests are dominated by noble fir (Abies procera), Pacific silver fir (Abies amabilis), Douglas-fir, and western hemlock. The understory is variable and ranged from open to dense shrubs. Common shrubs included Oregon grape (Mahonia aquifolium), salal (Gaultheria shallon), sword fern (Polystichum munitum), vine maple (Acer circinatum), Pacific rhododendron (Rhododendron macrophyllum), huckleberry (Vaccinium spp.), and blackberry and salmonberry (Rubus spp.). Before timber cutting in 1950, 65% of the HJA was covered in old-growth forest. Approximately 30% of the HJA was clear cut or shelterwood cut to create plantation forests varying in tree composition, stocking level, and age. In 1980, the HJA became a charter member of the Long Term Ecological Research network and no logging has occurred since 1985. The Willamette National Forest immediately surrounding the HJA has a similar logging history, but logging continues to occur. Currently, the HJA consists of a higher percentage of old-growth forest than the surrounding Willamette National Forest (approximately 58% in the HJA vs. 37% in the study area) (Davis et al. In Press). Wildfires are the primary disturbance type, followed by windthrow, landslides, root rot infections, and lateral stream channel erosion. Mean fire return interval of partial or complete stand-replacing fires for this area is 166 years and ranges from 20 years to 400 years (Teensma 1987; Morrison and Swanson 1990).
  • Sampling frequency: irregular
Sampling Description
  • Our western spotted diet study was part of a larger study on their spatial ecology in the temperate rainforest ecosystem of western Oregon that was conducted between April 2017 – September 2019. During this study, we set and maintained 112 baited trail cameras and captured and tracked western spotted skunks (nF = 12, nM = 19) using Tomahawk traps (Model 102 and 103, Tomahawk Live Trap Co., Hazelhurst, WI) and VHF radio-collars (M1545, 16 g; Advanced Telemetry Systems, Isanti, MN). Cameras placed in the HJA were paired with previously established long-term songbird monitoring (Frey, Hadley, and Betts 2016) and small mammal monitoring sites (Weldy et al. 2019). Cameras placed outside of the HJA were stratified based on elevation and old-growth structural index (Spies and Franklin 1988) and chosen randomly within logistical constraints. Both cameras and live traps were baited with a frozen house mouse (Mus musculus), a can of sardines (Culpidae), and/or various carnivore scent lures. We located skunks using radio-telemetry triangulation and homing techniques daily, weather permitting. Homing techniques were mainly used to locate rest site locations during the day whereas triangulation was used to locate skunks during the night when skunks were most active. All animal capture and handling were conducted in accordance with the guidelines set by the American Society of Mammalogists and were approved by the USDA Forest Service Institutional Animal Care and Use Committee (IACUC #2016-015) and the Oregon Department of Fish and Wildlife (Permit #107-17, 059-18, 081-19).
Spatial Sampling Units
  • Andrews Experimental Forest (HJA)
    W -122.26172200, E -122.10084700, N 44.28196400, S 44.19770400
    Altitude: 1631 to 1631 meter
  • WE035 unique location code F15-133 for collected scat sample within detection grid cell 15
    W -122.16929232, E -122.16929232, N 44.28649046, S 44.28649046
    Altitude: 895 to 895 meter
  • WE035 unique location code F15-134 for collected scat sample within detection grid cell 15
    W -122.16929232, E -122.16929232, N 44.28649046, S 44.28649046
    Altitude: 895 to 895 meter
  • WE035 unique location code F15-136 for collected scat sample within detection grid cell 15
    W -122.16929232, E -122.16929232, N 44.28649046, S 44.28649046
    Altitude: 895 to 895 meter
  • WE035 unique location code F15-137 for collected scat sample within detection grid cell 15
    W -122.16929232, E -122.16929232, N 44.28649046, S 44.28649046
    Altitude: 895 to 895 meter
  • WE035 unique location code F15-50 for collected scat sample within detection grid cell 15
    W -122.16941117, E -122.16941117, N 44.28695048, S 44.28695048
    Altitude: 870 to 870 meter
  • WE035 unique location code F22-101 for collected scat sample within detection grid cell 22
    W -122.19017339, E -122.19017339, N 44.26911148, S 44.26911148
    Altitude: 783 to 783 meter
  • WE035 unique location code F22-143 for collected scat sample within detection grid cell 22
    W -122.18905702, E -122.18905702, N 44.26555636, S 44.26555636
    Altitude: 829 to 829 meter
  • WE035 unique location code F22-18 for collected scat sample within detection grid cell 22
    W -122.19456280, E -122.19456280, N 44.26422685, S 44.26422685
    Altitude: 869 to 869 meter
  • WE035 unique location code F22-196 for collected scat sample within detection grid cell 22
    W -122.18267018, E -122.18267018, N 44.25901962, S 44.25901962
    Altitude: 847 to 847 meter
  • WE035 unique location code F22-197 for collected scat sample within detection grid cell 22
    W -122.18267018, E -122.18267018, N 44.25901962, S 44.25901962
    Altitude: 847 to 847 meter
  • WE035 unique location code F22-198 for collected scat sample within detection grid cell 22
    W -122.18267018, E -122.18267018, N 44.25901962, S 44.25901962
    Altitude: 847 to 847 meter
  • WE035 unique location code F22-199 for collected scat sample within detection grid cell 22
    W -122.18267018, E -122.18267018, N 44.25901962, S 44.25901962
    Altitude: 847 to 847 meter
  • WE035 unique location code F22-22 for collected scat sample within detection grid cell 22
    W -122.19521791, E -122.19521791, N 44.26487969, S 44.26487969
    Altitude: 849 to 849 meter
  • WE035 unique location code F22-224 for collected scat sample within detection grid cell 22
    W -122.18248075, E -122.18248075, N 44.27178461, S 44.27178461
    Altitude: 784 to 784 meter
  • WE035 unique location code F22-226 for collected scat sample within detection grid cell 22
    W -122.18300666, E -122.18300666, N 44.27090608, S 44.27090608
    Altitude: 817 to 817 meter
  • WE035 unique location code F22-300 for collected scat sample within detection grid cell 22
    W -122.18267018, E -122.18267018, N 44.25901962, S 44.25901962
    Altitude: 847 to 847 meter
  • WE035 unique location code F22-301 for collected scat sample within detection grid cell 22
    W -122.18267018, E -122.18267018, N 44.25901962, S 44.25901962
    Altitude: 847 to 847 meter
  • WE035 unique location code F22-302 for collected scat sample within detection grid cell 22
    W -122.18267018, E -122.18267018, N 44.25901962, S 44.25901962
    Altitude: 847 to 847 meter
  • WE035 unique location code F22-303 for collected scat sample within detection grid cell 22
    W -122.18267018, E -122.18267018, N 44.25901962, S 44.25901962
    Altitude: 847 to 847 meter
  • WE035 unique location code F22-307 for collected scat sample within detection grid cell 22
    W -122.17943017, E -122.17943017, N 44.26049090, S 44.26049090
    Altitude: 850 to 850 meter
  • WE035 unique location code F22-70 for collected scat sample within detection grid cell 22
    W -122.19015426, E -122.19015426, N 44.26867920, S 44.26867920
    Altitude: 787 to 787 meter
  • WE035 unique location code F29-71 for collected scat sample within detection grid cell 29
    W -122.23042825, E -122.23042825, N 44.22609390, S 44.22609390
    Altitude: 567 to 567 meter
  • WE035 unique location code F29-73 for collected scat sample within detection grid cell 29
    W -122.23042825, E -122.23042825, N 44.22609390, S 44.22609390
    Altitude: 567 to 567 meter
  • WE035 unique location code F29-74 for collected scat sample within detection grid cell 29
    W -122.23042825, E -122.23042825, N 44.22609390, S 44.22609390
    Altitude: 567 to 567 meter
  • WE035 unique location code F29-75 for collected scat sample within detection grid cell 29
    W -122.23042825, E -122.23042825, N 44.22609390, S 44.22609390
    Altitude: 567 to 567 meter
  • WE035 unique location code F29-76 for collected scat sample within detection grid cell 29
    W -122.23042825, E -122.23042825, N 44.22609390, S 44.22609390
    Altitude: 567 to 567 meter
  • WE035 unique location code F30-112 for collected scat sample within detection grid cell 30
    W -122.20769595, E -122.20769595, N 44.22853139, S 44.22853139
    Altitude: 644 to 644 meter
  • WE035 unique location code F30-113 for collected scat sample within detection grid cell 30
    W -122.20769595, E -122.20769595, N 44.22853139, S 44.22853139
    Altitude: 644 to 644 meter
  • WE035 unique location code F30-114 for collected scat sample within detection grid cell 30
    W -122.20769595, E -122.20769595, N 44.22853139, S 44.22853139
    Altitude: 644 to 644 meter
  • WE035 unique location code F30-115 for collected scat sample within detection grid cell 30
    W -122.20769088, E -122.20769088, N 44.22890949, S 44.22890949
    Altitude: 629 to 629 meter
  • WE035 unique location code F30-116 for collected scat sample within detection grid cell 30
    W -122.20769088, E -122.20769088, N 44.22890949, S 44.22890949
    Altitude: 629 to 629 meter
  • WE035 unique location code F30-117 for collected scat sample within detection grid cell 30
    W -122.20769088, E -122.20769088, N 44.22890949, S 44.22890949
    Altitude: 629 to 629 meter
  • WE035 unique location code F30-118 for collected scat sample within detection grid cell 30
    W -122.20776516, E -122.20776516, N 44.22897302, S 44.22897302
    Altitude: 627 to 627 meter
  • WE035 unique location code F30-119 for collected scat sample within detection grid cell 30
    W -122.20776516, E -122.20776516, N 44.22897302, S 44.22897302
    Altitude: 627 to 627 meter
  • WE035 unique location code F30-120 for collected scat sample within detection grid cell 30
    W -122.20776516, E -122.20776516, N 44.22897302, S 44.22897302
    Altitude: 627 to 627 meter
  • WE035 unique location code F30-121 for collected scat sample within detection grid cell 30
    W -122.20767848, E -122.20767848, N 44.22890040, S 44.22890040
    Altitude: 629 to 629 meter
  • WE035 unique location code F30-123 for collected scat sample within detection grid cell 30
    W -122.20756931, E -122.20756931, N 44.22863855, S 44.22863855
    Altitude: 638 to 638 meter
  • WE035 unique location code F30-138 for collected scat sample within detection grid cell 30
    W -122.20770763, E -122.20770763, N 44.22859449, S 44.22859449
    Altitude: 640 to 640 meter
  • WE035 unique location code F30-140 for collected scat sample within detection grid cell 30
    W -122.20724130, E -122.20724130, N 44.22788901, S 44.22788901
    Altitude: 692 to 692 meter
  • WE035 unique location code F30-142 for collected scat sample within detection grid cell 30
    W -122.20959558, E -122.20959558, N 44.22973296, S 44.22973296
    Altitude: 619 to 619 meter
  • WE035 unique location code F30-39 for collected scat sample within detection grid cell 30
    W -122.21079597, E -122.21079597, N 44.23266728, S 44.23266728
    Altitude: 547 to 547 meter
  • WE035 unique location code F36-173 for collected scat sample within detection grid cell 36
    W -122.25597653, E -122.25597653, N 44.20967037, S 44.20967037
    Altitude: 438 to 438 meter
  • WE035 unique location code F37-150 for collected scat sample within detection grid cell 37
    W -122.24035799, E -122.24035799, N 44.21920094, S 44.21920094
    Altitude: 547 to 547 meter
  • WE035 unique location code F37-151 for collected scat sample within detection grid cell 37
    W -122.24035799, E -122.24035799, N 44.21920094, S 44.21920094
    Altitude: 547 to 547 meter
  • WE035 unique location code F37-152 for collected scat sample within detection grid cell 37
    W -122.24035799, E -122.24035799, N 44.21920094, S 44.21920094
    Altitude: 547 to 547 meter
  • WE035 unique location code F37-153 for collected scat sample within detection grid cell 37
    W -122.24035799, E -122.24035799, N 44.21920094, S 44.21920094
    Altitude: 547 to 547 meter
  • WE035 unique location code F37-154 for collected scat sample within detection grid cell 37
    W -122.24035799, E -122.24035799, N 44.21920094, S 44.21920094
    Altitude: 547 to 547 meter
  • WE035 unique location code F37-155 for collected scat sample within detection grid cell 37
    W -122.24035799, E -122.24035799, N 44.21920094, S 44.21920094
    Altitude: 547 to 547 meter
  • WE035 unique location code F37-156 for collected scat sample within detection grid cell 37
    W -122.24035799, E -122.24035799, N 44.21920094, S 44.21920094
    Altitude: 547 to 547 meter
  • WE035 unique location code F37-158 for collected scat sample within detection grid cell 37
    W -122.24035799, E -122.24035799, N 44.21920094, S 44.21920094
    Altitude: 547 to 547 meter
  • WE035 unique location code F37-159 for collected scat sample within detection grid cell 37
    W -122.24035799, E -122.24035799, N 44.21920094, S 44.21920094
    Altitude: 547 to 547 meter
  • WE035 unique location code F37-162 for collected scat sample within detection grid cell 37
    W -122.24035799, E -122.24035799, N 44.21920094, S 44.21920094
    Altitude: 547 to 547 meter
  • WE035 unique location code F37-192 for collected scat sample within detection grid cell 37
    W -122.19493611, E -122.19493611, N 44.21114715, S 44.21114715
    Altitude: 1353 to 1353 meter
  • WE035 unique location code F37-194 for collected scat sample within detection grid cell 37
    W -122.24582457, E -122.24582457, N 44.21560890, S 44.21560890
    Altitude: 474 to 474 meter
  • WE035 unique location code F37-241 for collected scat sample within detection grid cell 37
    W -122.24038065, E -122.24038065, N 44.21646414, S 44.21646414
    Altitude: 603 to 603 meter
  • WE035 unique location code F37-242 for collected scat sample within detection grid cell 37
    W -122.24038065, E -122.24038065, N 44.21646414, S 44.21646414
    Altitude: 603 to 603 meter
  • WE035 unique location code F37-243 for collected scat sample within detection grid cell 37
    W -122.24038065, E -122.24038065, N 44.21646414, S 44.21646414
    Altitude: 603 to 603 meter
  • WE035 unique location code F37-51 for collected scat sample within detection grid cell 37
    W -122.21642513, E -122.21642513, N 44.20477829, S 44.20477829
    Altitude: 894 to 894 meter
  • WE035 unique location code F37-6 for collected scat sample within detection grid cell 37
    W -122.21949025, E -122.21949025, N 44.20677097, S 44.20677097
    Altitude: 863 to 863 meter
  • WE035 unique location code F38-46 for collected scat sample within detection grid cell 38
    W -122.20748209, E -122.20748209, N 44.21927469, S 44.21927469
    Altitude: 908 to 908 meter
  • WE035 unique location code F38-47 for collected scat sample within detection grid cell 38
    W -122.20748209, E -122.20748209, N 44.21927469, S 44.21927469
    Altitude: 908 to 908 meter
  • WE035 unique location code MT284 for manually collected scat samples
    W -122.24193911, E -122.24193911, N 44.22281270, S 44.22281270
    Altitude: 475 to 475 meter
  • WE035 unique location code MT285 for manually collected scat samples
    W -122.21309371, E -122.21309371, N 44.22656101, S 44.22656101
    Altitude: 647 to 647 meter
  • WE035 unique location code MT287 for manually collected scat samples
    W -122.22294543, E -122.22294543, N 44.21338483, S 44.21338483
    Altitude: 892 to 892 meter
  • WE035 unique location code MT288 for manually collected scat samples
    W -122.22804588, E -122.22804588, N 44.21390558, S 44.21390558
    Altitude: 846 to 846 meter
  • WE035 unique location code MT289 for manually collected scat samples
    W -122.22294543, E -122.22294543, N 44.21338483, S 44.21338483
    Altitude: 892 to 892 meter
  • WE035 unique location code MT296 for manually collected scat samples
    W -122.19388760, E -122.19388760, N 44.27237886, S 44.27237886
    Altitude: 616 to 616 meter
  • WE035 unique location code MT315 for manually collected scat samples
    W -122.25488921, E -122.25488921, N 44.21251728, S 44.21251728
    Altitude: 438 to 438 meter
  • WE035 unique location code MT37 for manually collected scat samples
    W -122.24229626, E -122.24229626, N 44.22327423, S 44.22327423
    Altitude: 482 to 482 meter
  • WE035 unique location code MT383 for manually collected scat samples
    W -122.25542787, E -122.25542787, N 44.20950474, S 44.20950474
    Altitude: 455 to 455 meter
  • WE035 unique location code MT408 for manually collected scat samples
    W -122.24345023, E -122.24345023, N 44.22212948, S 44.22212948
    Altitude: 470 to 470 meter
  • WE035 unique location code MT431 for manually collected scat samples
    W -122.19637883, E -122.19637883, N 44.26703059, S 44.26703059
    Altitude: 737 to 737 meter
  • WE035 unique location code MT432 for manually collected scat samples
    W -122.19637883, E -122.19637883, N 44.26703059, S 44.26703059
    Altitude: 737 to 737 meter
  • WE035 unique location code MT433 for manually collected scat samples
    W -122.19637883, E -122.19637883, N 44.26703059, S 44.26703059
    Altitude: 737 to 737 meter
  • WE035 unique location code MT906 for manually collected scat samples
    W -122.19384726, E -122.19384726, N 44.27899581, S 44.27899581
    Altitude: 709 to 709 meter
  • WE035 unique location code MT907 for manually collected scat samples
    W -122.24566942, E -122.24566942, N 44.21599501, S 44.21599501
    Altitude: 467 to 467 meter
  • WE035 unique location code MT908 for manually collected scat samples
    W -122.18626173, E -122.18626173, N 44.25112255, S 44.25112255
    Altitude: 747 to 747 meter
  • WE035 unique location code MT909 for manually collected scat samples
    W -122.24566942, E -122.24566942, N 44.21599501, S 44.21599501
    Altitude: 467 to 467 meter
  • WE035 unique location code MT916 for manually collected scat samples
    W -122.23519462, E -122.23519462, N 44.20318589, S 44.20318589
    Altitude: 832 to 832 meter
  • WE035 unique location code MT918 for manually collected scat samples
    W -122.12885316, E -122.12885316, N 44.20803339, S 44.20803339
    Altitude: 1499 to 1499 meter
  • WE035 unique location code MT927 for manually collected scat samples
    W -122.21989675, E -122.21989675, N 44.21674923, S 44.21674923
    Altitude: 797 to 797 meter
  • WE035 unique location code S22-117 for collected scat sample within detection grid cell 22
    W -122.19641359, E -122.19641359, N 44.26723790, S 44.26723790
    Altitude: 723 to 723 meter
  • WE035 unique location code S22-118 for collected scat sample within detection grid cell 22
    W -122.19637883, E -122.19637883, N 44.26703059, S 44.26703059
    Altitude: 737 to 737 meter
  • WE035 unique location code S22-119 for collected scat sample within detection grid cell 22
    W -122.19637883, E -122.19637883, N 44.26703059, S 44.26703059
    Altitude: 737 to 737 meter
  • WE035 unique location code S22-154 for collected scat sample within detection grid cell 22
    W -122.18937024, E -122.18937024, N 44.27011413, S 44.27011413
    Altitude: 739 to 739 meter
  • WE035 unique location code S22-155 for collected scat sample within detection grid cell 22
    W -122.18937024, E -122.18937024, N 44.27011413, S 44.27011413
    Altitude: 739 to 739 meter
  • WE035 unique location code S22-156 for collected scat sample within detection grid cell 22
    W -122.18937024, E -122.18937024, N 44.27011413, S 44.27011413
    Altitude: 739 to 739 meter
  • WE035 unique location code S22-157 for collected scat sample within detection grid cell 22
    W -122.18937024, E -122.18937024, N 44.27011413, S 44.27011413
    Altitude: 739 to 739 meter
  • WE035 unique location code S22-158 for collected scat sample within detection grid cell 22
    W -122.18937024, E -122.18937024, N 44.27011413, S 44.27011413
    Altitude: 739 to 739 meter
  • WE035 unique location code S22-159 for collected scat sample within detection grid cell 22
    W -122.18937024, E -122.18937024, N 44.27011413, S 44.27011413
    Altitude: 739 to 739 meter
  • WE035 unique location code S22-160 for collected scat sample within detection grid cell 22
    W -122.18937024, E -122.18937024, N 44.27011413, S 44.27011413
    Altitude: 739 to 739 meter
  • WE035 unique location code S22-161 for collected scat sample within detection grid cell 22
    W -122.18891065, E -122.18891065, N 44.26982277, S 44.26982277
    Altitude: 750 to 750 meter
  • WE035 unique location code S22-4 for collected scat sample within detection grid cell 22
    W -122.19391266, E -122.19391266, N 44.27237903, S 44.27237903
    Altitude: 616 to 616 meter
  • WE035 unique location code S22-5 for collected scat sample within detection grid cell 22
    W -122.19150652, E -122.19150652, N 44.26966111, S 44.26966111
    Altitude: 726 to 726 meter
  • WE035 unique location code S22-6 for collected scat sample within detection grid cell 22
    W -122.19019436, E -122.19019436, N 44.26940873, S 44.26940873
    Altitude: 777 to 777 meter
  • WE035 unique location code S22-74 for collected scat sample within detection grid cell 22
    W -122.18235830, E -122.18235830, N 44.25711774, S 44.25711774
    Altitude: 820 to 820 meter
  • WE035 unique location code S30-106 for collected scat sample within detection grid cell 30
    W -122.20936627, E -122.20936627, N 44.22815583, S 44.22815583
    Altitude: 637 to 637 meter
  • WE035 unique location code S30-107 for collected scat sample within detection grid cell 30
    W -122.20936627, E -122.20936627, N 44.22815583, S 44.22815583
    Altitude: 637 to 637 meter
  • WE035 unique location code S30-108 for collected scat sample within detection grid cell 30
    W -122.20925130, E -122.20925130, N 44.22832609, S 44.22832609
    Altitude: 636 to 636 meter
  • WE035 unique location code S30-109 for collected scat sample within detection grid cell 30
    W -122.20925130, E -122.20925130, N 44.22832609, S 44.22832609
    Altitude: 636 to 636 meter
  • WE035 unique location code S30-54 for collected scat sample within detection grid cell 30
    W -122.24562805, E -122.24562805, N 44.21825452, S 44.21825452
    Altitude: 458 to 458 meter
  • WE035 unique location code S30-69 for collected scat sample within detection grid cell 30
    W -122.20935255, E -122.20935255, N 44.22824577, S 44.22824577
    Altitude: 636 to 636 meter
  • WE035 unique location code S30-71 for collected scat sample within detection grid cell 30
    W -122.20935255, E -122.20935255, N 44.22824577, S 44.22824577
    Altitude: 636 to 636 meter
  • WE035 unique location code S30-72 for collected scat sample within detection grid cell 30
    W -122.20957381, E -122.20957381, N 44.22855340, S 44.22855340
    Altitude: 627 to 627 meter
  • WE035 unique location code S36-55 for collected scat sample within detection grid cell 36
    W -122.24582638, E -122.24582638, N 44.21840889, S 44.21840889
    Altitude: 469 to 469 meter
  • WE035 unique location code S36-56 for collected scat sample within detection grid cell 36
    W -122.24577735, E -122.24577735, N 44.21832753, S 44.21832753
    Altitude: 462 to 462 meter
  • WE035 unique location code S36-57 for collected scat sample within detection grid cell 36
    W -122.24562805, E -122.24562805, N 44.21825452, S 44.21825452
    Altitude: 458 to 458 meter
  • WE035 unique location code S37-1 for collected scat sample within detection grid cell 37
    W -122.24400770, E -122.24400770, N 44.21965730, S 44.21965730
    Altitude: 477 to 477 meter
  • WE035 unique location code S37-75 for collected scat sample within detection grid cell 37
    W -122.22652877, E -122.22652877, N 44.22365472, S 44.22365472
    Altitude: 607 to 607 meter
  • WE035 unique location code S37-76 for collected scat sample within detection grid cell 37
    W -122.22704428, E -122.22704428, N 44.22348715, S 44.22348715
    Altitude: 601 to 601 meter
  • WE035 unique location code S37-77 for collected scat sample within detection grid cell 37
    W -122.22704428, E -122.22704428, N 44.22348715, S 44.22348715
    Altitude: 601 to 601 meter
  • WE035 unique location code S37-78 for collected scat sample within detection grid cell 37
    W -122.22704428, E -122.22704428, N 44.22348715, S 44.22348715
    Altitude: 601 to 601 meter
  • WE035 unique location code S44-100 for collected scat sample within detection grid cell 44
    W -122.25262100, E -122.25262100, N 44.18301707, S 44.18301707
    Altitude: 615 to 615 meter
  • WE035 unique location code S44-101 for collected scat sample within detection grid cell 44
    W -122.25262100, E -122.25262100, N 44.18301707, S 44.18301707
    Altitude: 615 to 615 meter
  • WE035 unique location code S44-16 for collected scat sample within detection grid cell 44
    W -122.25598922, E -122.25598922, N 44.18280497, S 44.18280497
    Altitude: 695 to 695 meter
  • WE035 unique location code S44-17 for collected scat sample within detection grid cell 44
    W -122.25598922, E -122.25598922, N 44.18280497, S 44.18280497
    Altitude: 695 to 695 meter
  • WE035 unique location code S44-18 for collected scat sample within detection grid cell 44
    W -122.25598922, E -122.25598922, N 44.18280497, S 44.18280497
    Altitude: 695 to 695 meter
  • WE035 unique location code S44-97 for collected scat sample within detection grid cell 44
    W -122.25262100, E -122.25262100, N 44.18301707, S 44.18301707
    Altitude: 615 to 615 meter
  • WE035 unique location code S44-98 for collected scat sample within detection grid cell 44
    W -122.25262100, E -122.25262100, N 44.18301707, S 44.18301707
    Altitude: 615 to 615 meter
  • WE035 unique location code S45-126 for collected scat sample within detection grid cell 45
    W -122.23260400, E -122.23260400, N 44.19257179, S 44.19257179
    Altitude: 627 to 627 meter
  • WE035 unique location code S45-127 for collected scat sample within detection grid cell 45
    W -122.23260400, E -122.23260400, N 44.19257179, S 44.19257179
    Altitude: 627 to 627 meter
  • WE035 unique location code S45-128 for collected scat sample within detection grid cell 45
    W -122.23260400, E -122.23260400, N 44.19257179, S 44.19257179
    Altitude: 627 to 627 meter
  • WE035 unique location code S45-129 for collected scat sample within detection grid cell 45
    W -122.23260400, E -122.23260400, N 44.19257179, S 44.19257179
    Altitude: 627 to 627 meter
  • WE035 unique location code S45-130 for collected scat sample within detection grid cell 45
    W -122.23260400, E -122.23260400, N 44.19257179, S 44.19257179
    Altitude: 627 to 627 meter
  • WE035 unique location code S45-132 for collected scat sample within detection grid cell 45
    W -122.23260400, E -122.23260400, N 44.19257179, S 44.19257179
    Altitude: 627 to 627 meter
  • WE035 unique location code S45-133 for collected scat sample within detection grid cell 45
    W -122.23260400, E -122.23260400, N 44.19257179, S 44.19257179
    Altitude: 627 to 627 meter
  • WE035 unique location code S45-134 for collected scat sample within detection grid cell 45
    W -122.23260400, E -122.23260400, N 44.19257179, S 44.19257179
    Altitude: 627 to 627 meter
  • WE035 unique location code S45-135 for collected scat sample within detection grid cell 45
    W -122.23250059, E -122.23250059, N 44.18896982, S 44.18896982
    Altitude: 583 to 583 meter
  • WE035 scat detection grid cell number 15; see scat detection map
    W -122.17255214, E -122.13534138, N 44.30425907, S 44.27697438
    Altitude: 895 to 895 meter
  • WE035 scat detection grid cell number 22; see scat detection map
    W -122.21052166, E -122.17330983, N 44.27751874, S 44.25024628
    Altitude: 869 to 869 meter
  • WE035 scat detection grid cell number 29; see scat detection map
    W -122.24845675, E -122.21124391, N 44.25076542, S 44.22350519
    Altitude: 567 to 567 meter
  • WE035 scat detection grid cell number 30; see scat detection map
    W -122.21088304, E -122.17368788, N 44.25051203, S 44.22323969
    Altitude: 692 to 692 meter
  • WE035 scat detection grid cell number 36; see scat detection map
    W -122.28635745, E -122.21160428, N 44.22399914, S 44.19649822
    Altitude: 469 to 469 meter
  • WE035 scat detection grid cell number 37; see scat detection map
    W -122.24880044, E -122.21160428, N 44.22375834, S 44.19649822
    Altitude: 1354 to 1354 meter
  • WE035 scat detection grid cell number 38; see scat detection map
    W -122.21124391, E -122.17406540, N 44.22350519, S 44.19623297
    Altitude: 909 to 909 meter
  • WE035 scat detection grid cell number 44; see scat detection map
    W -122.28668351, E -122.21196414, N 44.19699171, S 44.16949112
    Altitude: 695 to 695 meter
  • WE035 scat detection grid cell number 45; see scat detection map
    W -122.21160428, E -122.17444240, N 44.19649822, S 44.16922612
    Altitude: 628 to 628 meter
  • WE035 manual, opportunistic scat collection within study area
    W -122.28668351, E -122.13534138, N 44.30425907, S 44.16922612
    Altitude: 1500 to 1500 meter
Software

No software entries listed in this EML file.

Keywords
  • LTER controlled vocabulary: food webs (theme), predators (theme), genetics (theme), predation (theme), forest disturbance (theme), timber harvest (theme), terrestrial ecosystems (theme), forest ecosystems (theme), animals (theme), invertebrates (theme), vertebrates (theme), salamanders (theme), birds (theme), mammals (theme), plants (theme)
  • Andrews Experimental Forest site thesaurus: H. J. Andrews Experimental Forest (AND) (theme)
Taxonomic Hierarchy
  • All Organisms: All Organisms
  • Highest common category (ca. kingdom): Plantae
  • Division or Phylum: Polypodiophyta
  • Class: Filicopsida
  • Order: Polypodiales
  • Family: Dryopteridaceae
  • Genus: Athyrium
  • Species: Athyrium brevifrons
  • Genus: Dryopteris
  • Genus: Polystichum
  • Species: Polystichum vestitum
  • Species: Polystichum weimingii
  • Family: Blechnaceae
  • Genus: Blechnum
  • Family: Athyriaceae
  • Division or Phylum: Coniferophyta
  • Class: Pinopsida
  • Order: Pinales
  • Family: Pinaceae
  • Genus: Tsuga
  • Species: Tsuga heterophylla
  • Genus: Pseudotsuga
  • Species: Pseudotsuga menziesii
  • Division or Phylum: Streptophyta
  • Subphylum: Streptophytina
  • Class: Polypodiopsida
  • Division or Phylum: Magnoliophyta
  • Class: Magnoliopsida
  • Order: Poales
  • Family: Poaceae
  • Genus: Festuca
  • Species: Festuca altissima
  • Genus: Avena
  • Species: Avena nuda
  • Order: Boraginales
  • Subclass: Magnoliidae
  • Order: Ranunculales
  • Family: Berberidaceae
  • Genus: Berberis
  • Species: Berberis wallichiana
  • Family: Ranunculaceae
  • Genus: Coptis
  • Species: Coptis quinquesecta
  • Subclass: Rosidae
  • Order: Rhamnales
  • Family: Rhamnaceae
  • Genus: Frangula
  • Species: Frangula purshiana
  • Genus: Ceanothus
  • Species: Ceanothus pumilus
  • Species: Ceanothus americanus
  • Order: Geraniales
  • Family: Oxalidaceae
  • Genus: Oxalis
  • Species: Oxalis tuberosa
  • Order: Fabales
  • Family: Fabaceae
  • Genus: Glycine
  • Genus: Arachis
  • Species: Arachis hypogaea
  • Genus: Cytisus
  • Species: Cytisus striatus
  • Order: Cornales
  • Family: Cornaceae
  • Genus: Cornus
  • Species: Cornus canadensis
  • Species: Cornus kousa
  • Order: Sapindales
  • Family: Aceraceae
  • Genus: Acer
  • Family: Sapindaceae
  • Order: Apiales
  • Family: Araliaceae
  • Genus: Aralia
  • Species: Aralia californica
  • Order: Rosales
  • Family: Rosaceae
  • Genus: Spiraea
  • Species: Spiraea pubescens
  • Genus: Rubus
  • Species: Rubus saxatilis
  • Species: Rubus occidentalis
  • Genus: Fragaria
  • Species: Fragaria vesca
  • Genus: Oemleria
  • Species: Oemleria cerasiformis
  • Genus: Prunus
  • Species: Prunus spinosa
  • Genus: Sorbus
  • Family: Saxifragaceae
  • Genus: Tolmiea
  • Species: Tolmiea menziesii
  • Subclass: Hamamelididae
  • Order: Fagales
  • Family: Betulaceae
  • Genus: Alnus
  • Species: Alnus alnobetula
  • Species: Alnus incana
  • Genus: Corylus
  • Species: Corylus cornuta
  • Family: Fagaceae
  • Genus: Quercus
  • Species: Quercus pubescens
  • Subclass: Dilleniidae
  • Order: Salicales
  • Family: Salicaceae
  • Genus: Populus
  • Species: Populus suaveolens
  • Species: Populus mexicana
  • Genus: Salix
  • Species: Salix zygostemon
  • Order: Ericales
  • Family: Ericaceae
  • Genus: Vaccinium
  • Genus: Gaultheria
  • Genus: Arctostaphylos
  • Genus: Rhododendron
  • Species: Rhododendron aureum
  • Species: Rhododendron ungernii
  • Family: Pyrolaceae
  • Genus: Pyrola
  • Species: Pyrola aphylla
  • Order: Malvales
  • Family: Malvaceae
  • Order: Oxalidales
  • Order: Saxifragales
  • Order: Malpighiales
  • Class: Liliopsida
  • Subclass: Asteridae
  • Order: Dipsacales
  • Family: Adoxaceae
  • Family: Caprifoliaceae
  • Genus: Linnaea
  • Species: Linnaea borealis
  • Genus: Sambucus
  • Species: Sambucus williamsii
  • Order: Asterales
  • Family: Asteraceae
  • Genus: Taraxacum
  • Species: Taraxacum officinale
  • Genus: Erigeron
  • Species: Erigeron cascadensis
  • Order: Solanales
  • Family: Solanaceae
  • Genus: Capsicum
  • Species: Capsicum pubescens
  • Family: Hydrophyllaceae
  • Genus: Hydrophyllum
  • Species: Hydrophyllum canadense
  • Family: Convolvulaceae
  • Genus: Convolvulus
  • Highest common category (ca. kingdom): Animalia
  • Division or Phylum: Mollusca
  • Class: Gastrapoda
  • Order: Stylommatophora
  • Family: Polygyridae
  • Genus: Vespericola
  • Family: Arionidae
  • Genus: Prophysaon
  • Species: Prophysaon obscurum
  • Family: Haplotrematidae
  • Genus: Haplotrema
  • Class: Mammalia
  • Order: Artiodactyla
  • Family: Cervidae
  • Family: Bovidae
  • Genus: Bos
  • Species: Bos taurus
  • Genus: Spilogale
  • Species: Spilogale gracilis
  • Order: Rodentia
  • Family: Sciuridae
  • Genus: Neotamias
  • Species: Neotamias townsendii
  • Family: Cricetidae
  • Genus: Myodes
  • Genus: Sorex
  • Species: Sorex trowbridgii
  • Genus: Scapanus
  • Species: Scapanus orarius
  • Genus: Odocoileus
  • Species: Odocoileus hemionus
  • Genus: Neurotrichus
  • Species: Neurotrichus gibbsii
  • Genus: Microtus
  • Species: Microtus oregoni
  • Genus: Lepus
  • Species: Lepus americanus
  • Genus: Glaucomys
  • Species: Glaucomys oregonensis
  • Order: Lagomorpha
  • Family: Leporidae
  • Order: Eulipotyphla
  • Family: Soricidae
  • Family: Talpidae
  • Class: Amphibia
  • Genus: Rhyacotriton
  • Species: Rhyacotriton cascadae
  • Genus: Plethodon
  • Species: Plethodon dunni
  • Genus: Aneides
  • Species: Aneides ferreus
  • Genus: Ambystoma
  • Genus: Taricha
  • Species: Taricha granulosa
  • Family: Plethodontidae
  • Order: Anura
  • Family: Hylidae
  • Genus: Pseudacris
  • Species: Pseudacris regilla
  • Order: Caudata
  • Family: Salamandridae
  • Family: Ambystomatidae
  • Family: Rhyacotritonidae
  • Division or Phylum: Chordata
  • Subphylum: Craniata
  • Class: Reptilia
  • Order: Squamata
  • Division or Phylum: Arthropoda
  • Class: Insecta
  • Order: Diptera
  • Family: Psilidae
  • Family: Cecidomyiidae
  • Order: Orthoptera
  • Family: Gryllacrididae
  • Genus: Pristoceuthophilus
  • Species: Pristoceuthophilus cercalis
  • Family: Rhaphidophoridae
  • Order: Lepidoptera
  • Family: Lasiocampidae
  • Genus: Tolype
  • Species: Tolype dayi
  • Order: Hemiptera
  • Suborder: Homoptera
  • Family: Cicadellidae
  • Genus: Macropsis
  • Order: Coleoptera
  • Family: Staphylinidae
  • Genus: Deinopteroloma
  • Species: Deinopteroloma subcostatum
  • Order: Hymenoptera
  • Family: Vespidae
  • Genus: Vespula
  • Species: Vespula consobrina
  • Family: Ichneumonidae
  • Family: Chrysididae
  • Genus: Ceratochrysis
  • Class: Diplopoda
  • Subphylum: Chelicerata
  • Subphylum: Myriapoda
  • Subphylum: Hexapoda
  • Class: Arachnida
  • Subclass: Araneae
  • Family: Theridiidae
  • Genus: Steatoda
  • Species: Steatoda bipunctata
  • Family: Araneidae
  • Genus: Araneus
  • Species: Araneus saevus
  • Class: Gastropoda
  • Class: Chilopoda
  • Order: Scolopendromorpha
  • Family: Cryptopidae
  • Genus: Scolopocryptops
  • Species: Scolopocryptops capillipedatus
  • Class: Aves
  • Order: Accipitriformes
  • Order: Falconiformes
  • Family: Cathartidae
  • Genus: Cathartes
  • Species: Cathartes aura
  • Order: Galliformes
  • Family: Phasianidae
  • Genus: Bonasa
  • Species: Bonasa umbellus
  • Order: Apodiformes
  • Family: Trochilidae
  • Genus: Selasphorus
  • Species: Selasphorus rufus
  • Order: Piciformes
  • Family: Picidae
  • Genus: Dryobates
  • Species: Dryobates pubescens
  • Order: Passeriformes
  • Family: Emberizidae
  • Genus: Junco
  • Species: Junco hyemalis
  • Family: Bombycillidae
  • Genus: Bombycilla
  • Species: Bombycilla cedrorum
  • Family: Turdidae
  • Genus: Catharus
  • Species: Catharus ustulatus
  • Genus: Turdus
  • Species: Turdus migratorius
  • Family: Motacillidae
  • Genus: Anthus
  • Species: Anthus rubescens
  • Family: Thraupidae
  • Genus: Piranga
  • Species: Piranga ludoviciana
  • Family: Passerellidae
  • Division or Phylum: Rotifera
  • Class: Bdelloidea
  • Class: Eurotatoria
  • Order: Adinetida
  • Family: Adinetidae
  • Genus: Adineta
  • Species: Adineta vaga
  • Species: Adineta gracilis
  • Highest common category (ca. kingdom): Fungi
  • Division or Phylum: Ascomycota
  • Subphylum: Pezizomycotina
  • Class: Sordariomycetes
  • Order: Hypocreales
  • Family: Nectriaceae
  • Genus: Neonectria
  • Species: Neonectria ditissima
Data Entities
# Entity Metadata Data
1 WE03501
Prey information for each scat
within scat information; results from DNA metabarcoding and manual sorting
 METADATA DATA
2 WE03502
Summarized information about prey composition for each scat
scat-level information summarizing results from DNA metabarcoding and manual sorting by taxonomic class
 METADATA DATA
3 WE03503
Location information for each scat
associated environmental attributes of the location where the scat was collected
 METADATA DATA
Metadata
WE03501 - Prey information for each scat

Object name: WE03501_v1.csv

Records: 467

Attributes: 26

Temporal coverage: 2017-08-03 to 2019-01-25

File size: 115184 byte

Checksum (MD5): e259ff6b81f8d207150d87c32f0afdc0

Format: headers=1, recordDelimiter=\r\n, fieldDelimiter=,, quoteCharacter=", orientation=column

Constraints (2)
  • primaryKey: PRIMARY
    WE03501.COLLECTION_DATETIME, WE03501.COLLECTION_TYPE, WE03501.SCAT_NUMBER, WE03501.PREY_SUPERKINGDOM, WE03501.GRID_NUMBER
  • notNullConstraint: NOTNULL
    WE03501.CARNIVORE, WE03501.COLLECTION_DATETIME, WE03501.COLLECTION_TYPE, WE03501.DBCODE, WE03501.ENTITY, WE03501.LOCUS, WE03501.SCAT_ID, WE03501.SCAT_NUMBER, WE03501.PREY_SUPERKINGDOM, WE03501.GRID_NUMBER
Attributes (26)
DBCODE - char(5) (nominal)

ID: WE03501.DBCODE

FSDB Database Code

Type system: Microsoft SQL Server 2019

Code definitions (1)
  • WE035
    FSDB Database Study Code WE035
ENTITY - numeric(2,0) (ratio)

ID: WE03501.ENTITY

Entity number

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=natural, min=1.0000 (exclusive=false), max=1.0000 (exclusive=false)

SCAT_ID - char(7) (ordinal)

ID: WE03501.SCAT_ID

Unique sample code representing collection_type, grid_number, scat_number and its location

Type system: Microsoft SQL Server 2019

Code definitions (128)
  • F15-133
    WE035 unique location code F15-133 for collected scat sample within detection grid cell 15
  • F15-134
    WE035 unique location code F15-134 for collected scat sample within detection grid cell 15
  • F15-136
    WE035 unique location code F15-136 for collected scat sample within detection grid cell 15
  • F15-137
    WE035 unique location code F15-137 for collected scat sample within detection grid cell 15
  • F15-50
    WE035 unique location code F15-50 for collected scat sample within detection grid cell 15
  • F22-101
    WE035 unique location code F22-101 for collected scat sample within detection grid cell 22
  • F22-143
    WE035 unique location code F22-143 for collected scat sample within detection grid cell 22
  • F22-18
    WE035 unique location code F22-18 for collected scat sample within detection grid cell 22
  • F22-196
    WE035 unique location code F22-196 for collected scat sample within detection grid cell 22
  • F22-197
    WE035 unique location code F22-197 for collected scat sample within detection grid cell 22
  • F22-198
    WE035 unique location code F22-198 for collected scat sample within detection grid cell 22
  • F22-199
    WE035 unique location code F22-199 for collected scat sample within detection grid cell 22
  • F22-22
    WE035 unique location code F22-22 for collected scat sample within detection grid cell 22
  • F22-224
    WE035 unique location code F22-224 for collected scat sample within detection grid cell 22
  • F22-226
    WE035 unique location code F22-226 for collected scat sample within detection grid cell 22
  • F22-300
    WE035 unique location code F22-300 for collected scat sample within detection grid cell 22
  • F22-301
    WE035 unique location code F22-301 for collected scat sample within detection grid cell 22
  • F22-302
    WE035 unique location code F22-302 for collected scat sample within detection grid cell 22
  • F22-303
    WE035 unique location code F22-303 for collected scat sample within detection grid cell 22
  • F22-307
    WE035 unique location code F22-307 for collected scat sample within detection grid cell 22
  • F22-70
    WE035 unique location code F22-70 for collected scat sample within detection grid cell 22
  • F29-71
    WE035 unique location code F29-71 for collected scat sample within detection grid cell 29
  • F29-73
    WE035 unique location code F29-73 for collected scat sample within detection grid cell 29
  • F29-74
    WE035 unique location code F29-74 for collected scat sample within detection grid cell 29
  • F29-75
    WE035 unique location code F29-75 for collected scat sample within detection grid cell 29
  • F29-76
    WE035 unique location code F29-76 for collected scat sample within detection grid cell 29
  • F30-112
    WE035 unique location code F30-112 for collected scat sample within detection grid cell 30
  • F30-113
    WE035 unique location code F30-113 for collected scat sample within detection grid cell 30
  • F30-114
    WE035 unique location code F30-114 for collected scat sample within detection grid cell 30
  • F30-115
    WE035 unique location code F30-115 for collected scat sample within detection grid cell 30
  • F30-116
    WE035 unique location code F30-116 for collected scat sample within detection grid cell 30
  • F30-117
    WE035 unique location code F30-117 for collected scat sample within detection grid cell 30
  • F30-118
    WE035 unique location code F30-118 for collected scat sample within detection grid cell 30
  • F30-119
    WE035 unique location code F30-119 for collected scat sample within detection grid cell 30
  • F30-120
    WE035 unique location code F30-120 for collected scat sample within detection grid cell 30
  • F30-121
    WE035 unique location code F30-121 for collected scat sample within detection grid cell 30
  • F30-123
    WE035 unique location code F30-123 for collected scat sample within detection grid cell 30
  • F30-138
    WE035 unique location code F30-138 for collected scat sample within detection grid cell 30
  • F30-140
    WE035 unique location code F30-140 for collected scat sample within detection grid cell 30
  • F30-142
    WE035 unique location code F30-142 for collected scat sample within detection grid cell 30
  • F30-39
    WE035 unique location code F30-39 for collected scat sample within detection grid cell 30
  • F36-173
    WE035 unique location code F36-173 for collected scat sample within detection grid cell 36
  • F37-150
    WE035 unique location code F37-150 for collected scat sample within detection grid cell 37
  • F37-151
    WE035 unique location code F37-151 for collected scat sample within detection grid cell 37
  • F37-152
    WE035 unique location code F37-152 for collected scat sample within detection grid cell 37
  • F37-153
    WE035 unique location code F37-153 for collected scat sample within detection grid cell 37
  • F37-154
    WE035 unique location code F37-154 for collected scat sample within detection grid cell 37
  • F37-155
    WE035 unique location code F37-155 for collected scat sample within detection grid cell 37
  • F37-156
    WE035 unique location code F37-156 for collected scat sample within detection grid cell 37
  • F37-158
    WE035 unique location code F37-158 for collected scat sample within detection grid cell 37
  • F37-159
    WE035 unique location code F37-159 for collected scat sample within detection grid cell 37
  • F37-162
    WE035 unique location code F37-162 for collected scat sample within detection grid cell 37
  • F37-192
    WE035 unique location code F37-192 for collected scat sample within detection grid cell 37
  • F37-194
    WE035 unique location code F37-194 for collected scat sample within detection grid cell 37
  • F37-241
    WE035 unique location code F37-241 for collected scat sample within detection grid cell 37
  • F37-242
    WE035 unique location code F37-242 for collected scat sample within detection grid cell 37
  • F37-243
    WE035 unique location code F37-243 for collected scat sample within detection grid cell 37
  • F37-51
    WE035 unique location code F37-51 for collected scat sample within detection grid cell 37
  • F37-6
    WE035 unique location code F37-6 for collected scat sample within detection grid cell 37
  • F38-46
    WE035 unique location code F38-46 for collected scat sample within detection grid cell 38
  • F38-47
    WE035 unique location code F38-47 for collected scat sample within detection grid cell 38
  • MT284
    WE035 unique location code MT284 for manually collected scat samples
  • MT285
    WE035 unique location code MT285 for manually collected scat samples
  • MT287
    WE035 unique location code MT287 for manually collected scat samples
  • MT288
    WE035 unique location code MT288 for manually collected scat samples
  • MT289
    WE035 unique location code MT289 for manually collected scat samples
  • MT296
    WE035 unique location code MT296 for manually collected scat samples
  • MT315
    WE035 unique location code MT315 for manually collected scat samples
  • MT37
    WE035 unique location code MT37 for manually collected scat samples
  • MT383
    WE035 unique location code MT383 for manually collected scat samples
  • MT408
    WE035 unique location code MT408 for manually collected scat samples
  • MT431
    WE035 unique location code MT431 for manually collected scat samples
  • MT432
    WE035 unique location code MT432 for manually collected scat samples
  • MT433
    WE035 unique location code MT433 for manually collected scat samples
  • MT906
    WE035 unique location code MT906 for manually collected scat samples
  • MT907
    WE035 unique location code MT907 for manually collected scat samples
  • MT908
    WE035 unique location code MT908 for manually collected scat samples
  • MT909
    WE035 unique location code MT909 for manually collected scat samples
  • MT916
    WE035 unique location code MT916 for manually collected scat samples
  • MT918
    WE035 unique location code MT918 for manually collected scat samples
  • MT927
    WE035 unique location code MT927 for manually collected scat samples
  • S22-117
    WE035 unique location code S22-117 for collected scat sample within detection grid cell 22
  • S22-118
    WE035 unique location code S22-118 for collected scat sample within detection grid cell 22
  • S22-119
    WE035 unique location code S22-119 for collected scat sample within detection grid cell 22
  • S22-154
    WE035 unique location code S22-154 for collected scat sample within detection grid cell 22
  • S22-155
    WE035 unique location code S22-155 for collected scat sample within detection grid cell 22
  • S22-156
    WE035 unique location code S22-156 for collected scat sample within detection grid cell 22
  • S22-157
    WE035 unique location code S22-157 for collected scat sample within detection grid cell 22
  • S22-158
    WE035 unique location code S22-158 for collected scat sample within detection grid cell 22
  • S22-159
    WE035 unique location code S22-159 for collected scat sample within detection grid cell 22
  • S22-160
    WE035 unique location code S22-160 for collected scat sample within detection grid cell 22
  • S22-161
    WE035 unique location code S22-161 for collected scat sample within detection grid cell 22
  • S22-4
    WE035 unique location code S22-4 for collected scat sample within detection grid cell 22
  • S22-5
    WE035 unique location code S22-5 for collected scat sample within detection grid cell 22
  • S22-6
    WE035 unique location code S22-6 for collected scat sample within detection grid cell 22
  • S22-74
    WE035 unique location code S22-74 for collected scat sample within detection grid cell 22
  • S30-106
    WE035 unique location code S30-106 for collected scat sample within detection grid cell 30
  • S30-107
    WE035 unique location code S30-107 for collected scat sample within detection grid cell 30
  • S30-108
    WE035 unique location code S30-108 for collected scat sample within detection grid cell 30
  • S30-109
    WE035 unique location code S30-109 for collected scat sample within detection grid cell 30
  • S30-54
    WE035 unique location code S30-54 for collected scat sample within detection grid cell 30
  • S30-69
    WE035 unique location code S30-69 for collected scat sample within detection grid cell 30
  • S30-71
    WE035 unique location code S30-71 for collected scat sample within detection grid cell 30
  • S30-72
    WE035 unique location code S30-72 for collected scat sample within detection grid cell 30
  • S36-55
    WE035 unique location code S36-55 for collected scat sample within detection grid cell 36
  • S36-56
    WE035 unique location code S36-56 for collected scat sample within detection grid cell 36
  • S36-57
    WE035 unique location code S36-57 for collected scat sample within detection grid cell 36
  • S37-1
    WE035 unique location code S37-1 for collected scat sample within detection grid cell 37
  • S37-75
    WE035 unique location code S37-75 for collected scat sample within detection grid cell 37
  • S37-76
    WE035 unique location code S37-76 for collected scat sample within detection grid cell 37
  • S37-77
    WE035 unique location code S37-77 for collected scat sample within detection grid cell 37
  • S37-78
    WE035 unique location code S37-78 for collected scat sample within detection grid cell 37
  • S44-100
    WE035 unique location code S44-100 for collected scat sample within detection grid cell 44
  • S44-101
    WE035 unique location code S44-101 for collected scat sample within detection grid cell 44
  • S44-16
    WE035 unique location code S44-16 for collected scat sample within detection grid cell 44
  • S44-17
    WE035 unique location code S44-17 for collected scat sample within detection grid cell 44
  • S44-18
    WE035 unique location code S44-18 for collected scat sample within detection grid cell 44
  • S44-97
    WE035 unique location code S44-97 for collected scat sample within detection grid cell 44
  • S44-98
    WE035 unique location code S44-98 for collected scat sample within detection grid cell 44
  • S45-126
    WE035 unique location code S45-126 for collected scat sample within detection grid cell 45
  • S45-127
    WE035 unique location code S45-127 for collected scat sample within detection grid cell 45
  • S45-128
    WE035 unique location code S45-128 for collected scat sample within detection grid cell 45
  • S45-129
    WE035 unique location code S45-129 for collected scat sample within detection grid cell 45
  • S45-130
    WE035 unique location code S45-130 for collected scat sample within detection grid cell 45
  • S45-132
    WE035 unique location code S45-132 for collected scat sample within detection grid cell 45
  • S45-133
    WE035 unique location code S45-133 for collected scat sample within detection grid cell 45
  • S45-134
    WE035 unique location code S45-134 for collected scat sample within detection grid cell 45
  • S45-135
    WE035 unique location code S45-135 for collected scat sample within detection grid cell 45
GRID_NUMBER - char(2) (nominal)

ID: WE03501.GRID_NUMBER

Sampling grid (3Km x 3Km) cell number

Type system: Microsoft SQL Server 2019

Code definitions (10)
  • 15
    WE035 scat detection grid cell number 15; see scat detection map
  • 22
    WE035 scat detection grid cell number 22; see scat detection map
  • 29
    WE035 scat detection grid cell number 29; see scat detection map
  • 30
    WE035 scat detection grid cell number 30; see scat detection map
  • 36
    WE035 scat detection grid cell number 36; see scat detection map
  • 37
    WE035 scat detection grid cell number 37; see scat detection map
  • 38
    WE035 scat detection grid cell number 38; see scat detection map
  • 44
    WE035 scat detection grid cell number 44; see scat detection map
  • 45
    WE035 scat detection grid cell number 45; see scat detection map
  • MT
    WE035 manual, opportunistic scat collection within study area
SCAT_NUMBER - numeric(3,0) (ratio)

ID: WE03501.SCAT_NUMBER

Scat number within collection type

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=natural, min=1.0000 (exclusive=false), max=927.0000 (exclusive=false)

COLLECTION_TYPE - char(2) (nominal)

ID: WE03501.COLLECTION_TYPE

Defines collection method and time frame

Type system: Microsoft SQL Server 2019

Code definitions (3)
  • S
    samples collected by Conservation K9s during summer 2018 (June-August)
  • F
    samples collected by Conservation K9s during fall 2018 (October-November)
  • MT
    samples collected opportunistically during field work from 2017-2019
COLLECTION_DATETIME - datetime (dateTime)

ID: WE03501.COLLECTION_DATETIME

Date and time scat was collected (time was not recorded for collection_tpe=MT); in Pacific Standard Time (PST)

Type system: Microsoft SQL Server 2019

Date format: YYYY-MM-DD hh:mm:ss

LOCUS - char(6) (nominal)

ID: WE03501.LOCUS

Region of genome used to barcode potential prey items: COI, 12s, manual, trnL

Type system: Microsoft SQL Server 2019

Code definitions (4)
  • COI
    COI locus of mitochondrial DNA that was used to barcode potential invertebrate prey items
  • 12s
    12s locus of mitochondrial DNA that was used to barcode potential vertebrate prey items
  • manual
    scats that were manually sorted for coarse identification of prey items
  • trnL
    trnL locus of chloroplast DNA that was used to barcode potential plant diet items
PREY_SUPERKINGDOM - char(15) (ordinal)

ID: WE03501.PREY_SUPERKINGDOM

Superkingdom of prey item detected within the scat

Type system: Microsoft SQL Server 2019

Code definitions (1)
  • Eukaryota
    All Organisms
PREY_KINGDOM - varchar(20) (ordinal)

ID: WE03501.PREY_KINGDOM

Kingdom of prey item detected within the scat

Type system: Microsoft SQL Server 2019

Code definitions (3)
  • Metazoa
    Animalia
  • Viridiplantae
    Plantae
  • Fungi
    Fungi
PREY_PHYLUM - varchar(20) (ordinal)

ID: WE03501.PREY_PHYLUM

Phylum of prey item detected within the scat

Type system: Microsoft SQL Server 2019

Code definitions (6)
  • Arthropoda
    Arthropoda
  • Streptophyta
    Streptophyta
  • Ascomycota
    Ascomycota
  • Chordata
    Chordata
  • Mollusca
    Mollusca
  • Rotifera
    Rotifera
PREY_SUBPHYLUM - varchar(20) (ordinal)

ID: WE03501.PREY_SUBPHYLUM

Subphylum of prey item detected within the scat

Type system: Microsoft SQL Server 2019

Code definitions (6)
  • Streptophytina
    Streptophytina
  • Pezizomycotina
    Pezizomycotina
  • Craniata
    Craniata
  • Myriapoda
    Myriapoda
  • Hexapoda
    Hexapoda
  • Chelicerata
    Chelicerata
PREY_CLASS - varchar(30) (ordinal)

ID: WE03501.PREY_CLASS

Class of prey item detected within the scat

Type system: Microsoft SQL Server 2019

Code definitions (15)
  • Magnoliopsida
    Magnoliopsida
  • Pinopsida
    Pinopsida
  • Polypodiopsida
    Polypodiopsida
  • Sordariomycetes
    Sordariomycetes
  • Amphibia
    Amphibia
  • Aves
    Aves
  • Mammalia
    Mammalia
  • Arachnida
    Arachnida
  • Gastropoda
    Gastropoda
  • Diplopoda
    Diplopoda
  • Chilopoda
    Chilopoda
  • Insecta
    Insecta
  • Bdelloidea
    Bdelloidea
  • Eurotatoria
    Eurotatoria
  • Reptilia
    Reptilia
PREY_ORDER - varchar(30) (ordinal)

ID: WE03501.PREY_ORDER

Order of prey item detected within the scat

Type system: Microsoft SQL Server 2019

Code definitions (42)
  • Sapindales
    Sapindales
  • Apiales
    Apiales
  • Polypodiales
    Polypodiales
  • Asterales
    Asterales
  • Ranunculales
    Ranunculales
  • Fagales
    Fagales
  • Dipsacales
    Dipsacales
  • Solanales
    Solanales
  • Cornales
    Cornales
  • Rosales
    Rosales
  • Pinales
    Pinales
  • Ericales
    Ericales
  • Fabales
    Fabales
  • Malvales
    Malvales
  • Boraginales
    Boraginales
  • Oxalidales
    Oxalidales
  • Poales
    Poales
  • Saxifragales
    Saxifragales
  • Malpighiales
    Malpighiales
  • Hypocreales
    Hypocreales
  • Anura
    Anura
  • Caudata
    Caudata
  • Galliformes
    Galliformes
  • Apodiformes
    Apodiformes
  • Piciformes
    Piciformes
  • Passeriformes
    Passeriformes
  • Accipitriformes
    Accipitriformes
  • Rodentia
    Rodentia
  • Lagomorpha
    Lagomorpha
  • Artiodactyla
    Artiodactyla
  • Eulipotyphla
    Eulipotyphla
  • Araneae
    Araneae
  • Scolopendromorpha
    Scolopendromorpha
  • Coleoptera
    Coleoptera
  • Hemiptera
    Hemiptera
  • Hymenoptera
    Hymenoptera
  • Lepidoptera
    Lepidoptera
  • Orthoptera
    Orthoptera
  • Diptera
    Diptera
  • Stylommatophora
    Stylommatophora
  • Adinetida
    Adinetida
  • Squamata
    Squamata
PREY_FAMILY - varchar(30) (ordinal)

ID: WE03501.PREY_FAMILY

Family of prey item detected within the scat

Type system: Microsoft SQL Server 2019

Code definitions (64)
  • Araliaceae
    Araliaceae
  • Asteraceae
    Asteraceae
  • Berberidaceae
    Berberidaceae
  • Betulaceae
    Betulaceae
  • Blechnaceae
    Blechnaceae
  • Caprifoliaceae
    Caprifoliaceae
  • Convolvulaceae
    Convolvulaceae
  • Cornaceae
    Cornaceae
  • Dryopteridaceae
    Dryopteridaceae
  • Ericaceae
    Ericaceae
  • Fabaceae
    Fabaceae
  • Fagaceae
    Fagaceae
  • Hydrophyllaceae
    Hydrophyllaceae
  • Malvaceae
    Malvaceae
  • Oxalidaceae
    Oxalidaceae
  • Pinaceae
    Pinaceae
  • Poaceae
    Poaceae
  • Ranunculaceae
    Ranunculaceae
  • Rhamnaceae
    Rhamnaceae
  • Rosaceae
    Rosaceae
  • Salicaceae
    Salicaceae
  • Saxifragaceae
    Saxifragaceae
  • Solanaceae
    Solanaceae
  • Sapindaceae
    Sapindaceae
  • Adoxaceae
    Adoxaceae
  • Athyriaceae
    Athyriaceae
  • Nectriaceae
    Nectriaceae
  • Plethodontidae
    Plethodontidae
  • Hylidae
    Hylidae
  • Ambystomatidae
    Ambystomatidae
  • Rhyacotritonidae
    Rhyacotritonidae
  • Salamandridae
    Salamandridae
  • Cathartidae
    Cathartidae
  • Phasianidae
    Phasianidae
  • Trochilidae
    Trochilidae
  • Picidae
    Picidae
  • Turdidae
    Turdidae
  • Motacillidae
    Motacillidae
  • Bombycillidae
    Bombycillidae
  • Thraupidae
    Thraupidae
  • Passerellidae
    Passerellidae
  • Sciuridae
    Sciuridae
  • Bovidae
    Bovidae
  • Cervidae
    Cervidae
  • Soricidae
    Soricidae
  • Cricetidae
    Cricetidae
  • Leporidae
    Leporidae
  • Talpidae
    Talpidae
  • Araneidae
    Araneidae
  • Theridiidae
    Theridiidae
  • Cryptopidae
    Cryptopidae
  • Rhaphidophoridae
    Rhaphidophoridae
  • Cecidomyiidae
    Cecidomyiidae
  • Chrysididae
    Chrysididae
  • Cicadellidae
    Cicadellidae
  • Ichneumonidae
    Ichneumonidae
  • Lasiocampidae
    Lasiocampidae
  • Psilidae
    Psilidae
  • Staphylinidae
    Staphylinidae
  • Vespidae
    Vespidae
  • Arionidae
    Arionidae
  • Haplotrematidae
    Haplotrematidae
  • Polygyridae
    Polygyridae
  • Adinetidae
    Adinetidae
PREY_GENUS - varchar(30) (ordinal)

ID: WE03501.PREY_GENUS

Genus of prey item detected within the scat

Type system: Microsoft SQL Server 2019

Code definitions (83)
  • Acer
    Acer
  • Alnus
    Alnus
  • Arachis
    Arachis
  • Aralia
    Aralia
  • Arctostaphylos
    Arctostaphylos
  • Athyrium
    Athyrium
  • Avena
    Avena
  • Berberis
    Berberis
  • Blechnum
    Blechnum
  • Ceanothus
    Ceanothus
  • Convolvulus
    Convolvulus
  • Coptis
    Coptis
  • Cornus
    Cornus
  • Corylus
    Corylus
  • Cytisus
    Cytisus
  • Dryopteris
    Dryopteris
  • Erigeron
    Erigeron
  • Festuca
    Festuca
  • Fragaria
    Fragaria
  • Frangula
    Frangula
  • Gaultheria
    Gaultheria
  • Hydrophyllum
    Hydrophyllum
  • Linnaea
    Linnaea
  • Oemleria
    Oemleria
  • Oxalis
    Oxalis
  • Polystichum
    Polystichum
  • Populus
    Populus
  • Prunus
    Prunus
  • Pseudotsuga
    Pseudotsuga
  • Pyrola
    Pyrola
  • Quercus
    Quercus
  • Rhododendron
    Rhododendron
  • Rubus
    Rubus
  • Salix
    Salix
  • Sambucus
    Sambucus
  • Sorbus
    Sorbus
  • Spiraea
    Spiraea
  • Taraxacum
    Taraxacum
  • Tolmiea
    Tolmiea
  • Tsuga
    Tsuga
  • Vaccinium
    Vaccinium
  • Capsicum
    Capsicum
  • Glycine
    Glycine
  • Neonectria
    Neonectria
  • Ambystoma
    Ambystoma
  • Aneides
    Aneides
  • Plethodon
    Plethodon
  • Rhyacotriton
    Rhyacotriton
  • Taricha
    Taricha
  • Pseudacris
    Pseudacris
  • Cathartes
    Cathartes
  • Bonasa
    Bonasa
  • Selasphorus
    Selasphorus
  • Catharus
    Catharus
  • Turdus
    Turdus
  • Anthus
    Anthus
  • Bombycilla
    Bombycilla
  • Piranga
    Piranga
  • Junco
    Junco
  • Dryobates
    Dryobates
  • Glaucomys
    Glaucomys
  • Lepus
    Lepus
  • Microtus
    Microtus
  • Neurotrichus
    Neurotrichus
  • Odocoileus
    Odocoileus
  • Scapanus
    Scapanus
  • Sorex
    Sorex
  • Bos
    Bos
  • Myodes
    Myodes
  • Neotamias
    Neotamias
  • Araneus
    Araneus
  • Steatoda
    Steatoda
  • Scolopocryptops
    Scolopocryptops
  • Macropsis
    Macropsis
  • Pristoceuthophilus
    Pristoceuthophilus
  • Tolype
    Tolype
  • Vespula
    Vespula
  • Ceratochrysis
    Ceratochrysis
  • Deinopteroloma
    Deinopteroloma
  • Prophysaon
    Prophysaon
  • Haplotrema
    Haplotrema
  • Vespericola
    Vespericola
  • Adineta
    Adineta
PREY_SPECIES - varchar(50) (ordinal)

ID: WE03501.PREY_SPECIES

Species of prey item detected within the scat

Type system: Microsoft SQL Server 2019

Code definitions (76)
  • Alnus alnobetula
    Alnus alnobetula
  • Alnus incana
    Alnus incana
  • Arachis hypogaea
    Arachis hypogaea
  • Aralia californica
    Aralia californica
  • Athyrium brevifrons
    Athyrium brevifrons
  • Avena nuda
    Avena nuda
  • Berberis wallichiana
    Berberis wallichiana
  • Ceanothus americanus
    Ceanothus americanus
  • Ceanothus pumilus
    Ceanothus pumilus
  • Coptis quinquesecta
    Coptis quinquesecta
  • Cornus kousa
    Cornus kousa
  • Cornus canadensis
    Cornus canadensis
  • Corylus cornuta
    Corylus cornuta
  • Cytisus striatus
    Cytisus striatus
  • Erigeron cascadensis
    Erigeron cascadensis
  • Festuca altissima
    Festuca altissima
  • Fragaria vesca
    Fragaria vesca
  • Frangula purshiana
    Frangula purshiana
  • Hydrophyllum canadense
    Hydrophyllum canadense
  • Linnaea borealis
    Linnaea borealis
  • Oemleria cerasiformis
    Oemleria cerasiformis
  • Oxalis tuberosa
    Oxalis tuberosa
  • Polystichum vestitum
    Polystichum vestitum
  • Polystichum weimingii
    Polystichum weimingii
  • Populus mexicana
    Populus mexicana
  • Populus suaveolens
    Populus suaveolens
  • Prunus spinosa
    Prunus spinosa
  • Pseudotsuga menziesii
    Pseudotsuga menziesii
  • Pyrola aphylla
    Pyrola aphylla
  • Quercus pubescens
    Quercus pubescens
  • Rhododendron aureum
    Rhododendron aureum
  • Rhododendron ungernii
    Rhododendron ungernii
  • Rubus occidentalis
    Rubus occidentalis
  • Rubus saxatilis
    Rubus saxatilis
  • Salix zygostemon
    Salix zygostemon
  • Sambucus williamsii
    Sambucus williamsii
  • Spiraea pubescens
    Spiraea pubescens
  • Taraxacum officinale
    Taraxacum officinale
  • Tolmiea menziesii
    Tolmiea menziesii
  • Tsuga heterophylla
    Tsuga heterophylla
  • Capsicum pubescens
    Capsicum pubescens
  • Neonectria ditissima
    Neonectria ditissima
  • Aneides ferreus
    Aneides ferreus
  • Plethodon dunni
    Plethodon dunni
  • Taricha granulosa
    Taricha granulosa
  • Rhyacotriton cascadae
    Rhyacotriton cascadae
  • Pseudacris regilla
    Pseudacris regilla
  • Cathartes aura
    Cathartes aura
  • Bonasa umbellus
    Bonasa umbellus
  • Selasphorus rufus
    Selasphorus rufus
  • Catharus ustulatus
    Catharus ustulatus
  • Turdus migratorius
    Turdus migratorius
  • Anthus rubescens
    Anthus rubescens
  • Bombycilla cedrorum
    Bombycilla cedrorum
  • Piranga ludoviciana
    Piranga ludoviciana
  • Junco hyemalis
    Junco hyemalis
  • Dryobates pubescens
    Dryobates pubescens
  • Lepus americanus
    Lepus americanus
  • Microtus oregoni
    Microtus oregoni
  • Neurotrichus gibbsii
    Neurotrichus gibbsii
  • Odocoileus hemionus
    Odocoileus hemionus
  • Scapanus orarius
    Scapanus orarius
  • Sorex trowbridgii
    Sorex trowbridgii
  • Bos taurus
    Bos taurus
  • Neotamias townsendii
    Neotamias townsendii
  • Glaucomys oregonensis
    Glaucomys oregonensis
  • Araneus saevus
    Araneus saevus
  • Steatoda bipunctata
    Steatoda bipunctata
  • Scolopocryptops capillipedatus
    Scolopocryptops capillipedatus
  • Pristoceuthophilus cercalis
    Pristoceuthophilus cercalis
  • Tolype dayi
    Tolype dayi
  • Vespula consobrina
    Vespula consobrina
  • Deinopteroloma subcostatum
    Deinopteroloma subcostatum
  • Prophysaon obscurum
    Prophysaon obscurum
  • Adineta gracilis
    Adineta gracilis
  • Adineta vaga
    Adineta vaga
CARNIVORE - varchar(50) (ordinal)

ID: WE03501.CARNIVORE

assignment of scat defecator based on DNA metabarcoding

Type system: Microsoft SQL Server 2019

Code definitions (1)
  • Spilogale gracilis
    Spilogale gracilis
SEQ - varchar(254) (nominal)

ID: WE03501.SEQ

DNA barcode sequence used to identify species.

Type system: Microsoft SQL Server 2019

NUMREPS - numeric(1,0) (ratio)

ID: WE03501.NUMREPS

Number of replicates that returned the same sequence (all samples run in triplicate)

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=natural, min=2.0000 (exclusive=false), max=9.0000 (exclusive=false)

NUMREADS - numeric(8,1) (ratio)

ID: WE03501.NUMREADS

Number of reads of unique sequences in each sample. Mean number of reads calculated for sequences that were in multiple replicates.

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=real, min=7.0000 (exclusive=false), max=455460.3000 (exclusive=false)

TOTALREADS - numeric(8,1) (ratio)

ID: WE03501.TOTALREADS

Sum of all numreads for a sample

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=real, min=34.7000 (exclusive=false), max=551050.0000 (exclusive=false)

RRA - numeric(6,4) (ratio)

ID: WE03501.RRA

Relative read abundance: calculated by dividing the numreads by totalreads per sample

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=real, min=0.0088 (exclusive=false), max=1.0000 (exclusive=false)

PIDMATCH - numeric(6,2) (ratio)

ID: WE03501.PIDMATCH

Percent match of sequence with sequence in the GenBank database

Type system: Microsoft SQL Server 2019

Unit: percent

Precision: 1

Numeric domain: type=real, min=82.3300 (exclusive=false), max=99.5400 (exclusive=false)

QCOVER - numeric(6,2) (ratio)

ID: WE03501.QCOVER

Query coverage: percentage of the query sequence (your specimen) that overlaps the reference sequence

Type system: Microsoft SQL Server 2019

Unit: percent

Precision: 1

Numeric domain: type=real, min=18.0000 (exclusive=false), max=100.0000 (exclusive=false)

BITSCORE - numeric(6,2) (ratio)

ID: WE03501.BITSCORE

Bit score: measures sequence similarity independent of query sequence length and database size and is normalized based on the rawpairwise alignment score

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=real, min=56.2800 (exclusive=false), max=330.2500 (exclusive=false)

WE03502 - Summarized information about prey composition for each scat

Object name: WE03502_v1.csv

Records: 128

Attributes: 17

Temporal coverage: 2017-08-03 to 2019-01-25

File size: 9032 byte

Checksum (MD5): 7c681cae62cb54b313c23acc52d77966

Format: headers=1, recordDelimiter=\r\n, fieldDelimiter=,, quoteCharacter=", orientation=column

Constraints (2)
  • primaryKey: PRIMARY
    WE03502.COLLECTION_DATETIME, WE03502.COLLECTION_TYPE, WE03502.SCAT_NUMBER, WE03502.GRID_NUMBER
  • notNullConstraint: NOTNULL
    WE03502.AMPHIBIA, WE03502.ARACHNIDA, WE03502.AVES, WE03502.COLLECTION_DATETIME, WE03502.COLLECTION_TYPE, WE03502.DBCODE, WE03502.ENTITY, WE03502.GASTROPODA, WE03502.INSECTA, WE03502.MAMMALIA, WE03502.MYRIAPODA, WE03502.REPTILIA, WE03502.SCAT_ID, WE03502.SCAT_NUMBER, WE03502.SEASON, WE03502.STREPTOPHYTA, WE03502.GRID_NUMBER
Attributes (17)
DBCODE - char(5) (nominal)

ID: WE03502.DBCODE

FSDB Database Code

Type system: Microsoft SQL Server 2019

Code definitions (1)
  • WE035
    FSDB Database Study Code WE035
ENTITY - numeric(2,0) (ratio)

ID: WE03502.ENTITY

Entity number

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=natural, min=2.0000 (exclusive=false), max=2.0000 (exclusive=false)

SCAT_ID - char(7) (ordinal)

ID: WE03502.SCAT_ID

Unique sample code representing collection_type, grid_number, scat_number and its location

Type system: Microsoft SQL Server 2019

Code definitions (128)
  • F15-133
    WE035 unique location code F15-133 for collected scat sample within detection grid cell 15
  • F15-134
    WE035 unique location code F15-134 for collected scat sample within detection grid cell 15
  • F15-136
    WE035 unique location code F15-136 for collected scat sample within detection grid cell 15
  • F15-137
    WE035 unique location code F15-137 for collected scat sample within detection grid cell 15
  • F15-50
    WE035 unique location code F15-50 for collected scat sample within detection grid cell 15
  • F22-101
    WE035 unique location code F22-101 for collected scat sample within detection grid cell 22
  • F22-143
    WE035 unique location code F22-143 for collected scat sample within detection grid cell 22
  • F22-18
    WE035 unique location code F22-18 for collected scat sample within detection grid cell 22
  • F22-196
    WE035 unique location code F22-196 for collected scat sample within detection grid cell 22
  • F22-197
    WE035 unique location code F22-197 for collected scat sample within detection grid cell 22
  • F22-198
    WE035 unique location code F22-198 for collected scat sample within detection grid cell 22
  • F22-199
    WE035 unique location code F22-199 for collected scat sample within detection grid cell 22
  • F22-22
    WE035 unique location code F22-22 for collected scat sample within detection grid cell 22
  • F22-224
    WE035 unique location code F22-224 for collected scat sample within detection grid cell 22
  • F22-226
    WE035 unique location code F22-226 for collected scat sample within detection grid cell 22
  • F22-300
    WE035 unique location code F22-300 for collected scat sample within detection grid cell 22
  • F22-301
    WE035 unique location code F22-301 for collected scat sample within detection grid cell 22
  • F22-302
    WE035 unique location code F22-302 for collected scat sample within detection grid cell 22
  • F22-303
    WE035 unique location code F22-303 for collected scat sample within detection grid cell 22
  • F22-307
    WE035 unique location code F22-307 for collected scat sample within detection grid cell 22
  • F22-70
    WE035 unique location code F22-70 for collected scat sample within detection grid cell 22
  • F29-71
    WE035 unique location code F29-71 for collected scat sample within detection grid cell 29
  • F29-73
    WE035 unique location code F29-73 for collected scat sample within detection grid cell 29
  • F29-74
    WE035 unique location code F29-74 for collected scat sample within detection grid cell 29
  • F29-75
    WE035 unique location code F29-75 for collected scat sample within detection grid cell 29
  • F29-76
    WE035 unique location code F29-76 for collected scat sample within detection grid cell 29
  • F30-112
    WE035 unique location code F30-112 for collected scat sample within detection grid cell 30
  • F30-113
    WE035 unique location code F30-113 for collected scat sample within detection grid cell 30
  • F30-114
    WE035 unique location code F30-114 for collected scat sample within detection grid cell 30
  • F30-115
    WE035 unique location code F30-115 for collected scat sample within detection grid cell 30
  • F30-116
    WE035 unique location code F30-116 for collected scat sample within detection grid cell 30
  • F30-117
    WE035 unique location code F30-117 for collected scat sample within detection grid cell 30
  • F30-118
    WE035 unique location code F30-118 for collected scat sample within detection grid cell 30
  • F30-119
    WE035 unique location code F30-119 for collected scat sample within detection grid cell 30
  • F30-120
    WE035 unique location code F30-120 for collected scat sample within detection grid cell 30
  • F30-121
    WE035 unique location code F30-121 for collected scat sample within detection grid cell 30
  • F30-123
    WE035 unique location code F30-123 for collected scat sample within detection grid cell 30
  • F30-138
    WE035 unique location code F30-138 for collected scat sample within detection grid cell 30
  • F30-140
    WE035 unique location code F30-140 for collected scat sample within detection grid cell 30
  • F30-142
    WE035 unique location code F30-142 for collected scat sample within detection grid cell 30
  • F30-39
    WE035 unique location code F30-39 for collected scat sample within detection grid cell 30
  • F36-173
    WE035 unique location code F36-173 for collected scat sample within detection grid cell 36
  • F37-150
    WE035 unique location code F37-150 for collected scat sample within detection grid cell 37
  • F37-151
    WE035 unique location code F37-151 for collected scat sample within detection grid cell 37
  • F37-152
    WE035 unique location code F37-152 for collected scat sample within detection grid cell 37
  • F37-153
    WE035 unique location code F37-153 for collected scat sample within detection grid cell 37
  • F37-154
    WE035 unique location code F37-154 for collected scat sample within detection grid cell 37
  • F37-155
    WE035 unique location code F37-155 for collected scat sample within detection grid cell 37
  • F37-156
    WE035 unique location code F37-156 for collected scat sample within detection grid cell 37
  • F37-158
    WE035 unique location code F37-158 for collected scat sample within detection grid cell 37
  • F37-159
    WE035 unique location code F37-159 for collected scat sample within detection grid cell 37
  • F37-162
    WE035 unique location code F37-162 for collected scat sample within detection grid cell 37
  • F37-192
    WE035 unique location code F37-192 for collected scat sample within detection grid cell 37
  • F37-194
    WE035 unique location code F37-194 for collected scat sample within detection grid cell 37
  • F37-241
    WE035 unique location code F37-241 for collected scat sample within detection grid cell 37
  • F37-242
    WE035 unique location code F37-242 for collected scat sample within detection grid cell 37
  • F37-243
    WE035 unique location code F37-243 for collected scat sample within detection grid cell 37
  • F37-51
    WE035 unique location code F37-51 for collected scat sample within detection grid cell 37
  • F37-6
    WE035 unique location code F37-6 for collected scat sample within detection grid cell 37
  • F38-46
    WE035 unique location code F38-46 for collected scat sample within detection grid cell 38
  • F38-47
    WE035 unique location code F38-47 for collected scat sample within detection grid cell 38
  • MT284
    WE035 unique location code MT284 for manually collected scat samples
  • MT285
    WE035 unique location code MT285 for manually collected scat samples
  • MT287
    WE035 unique location code MT287 for manually collected scat samples
  • MT288
    WE035 unique location code MT288 for manually collected scat samples
  • MT289
    WE035 unique location code MT289 for manually collected scat samples
  • MT296
    WE035 unique location code MT296 for manually collected scat samples
  • MT315
    WE035 unique location code MT315 for manually collected scat samples
  • MT37
    WE035 unique location code MT37 for manually collected scat samples
  • MT383
    WE035 unique location code MT383 for manually collected scat samples
  • MT408
    WE035 unique location code MT408 for manually collected scat samples
  • MT431
    WE035 unique location code MT431 for manually collected scat samples
  • MT432
    WE035 unique location code MT432 for manually collected scat samples
  • MT433
    WE035 unique location code MT433 for manually collected scat samples
  • MT906
    WE035 unique location code MT906 for manually collected scat samples
  • MT907
    WE035 unique location code MT907 for manually collected scat samples
  • MT908
    WE035 unique location code MT908 for manually collected scat samples
  • MT909
    WE035 unique location code MT909 for manually collected scat samples
  • MT916
    WE035 unique location code MT916 for manually collected scat samples
  • MT918
    WE035 unique location code MT918 for manually collected scat samples
  • MT927
    WE035 unique location code MT927 for manually collected scat samples
  • S22-117
    WE035 unique location code S22-117 for collected scat sample within detection grid cell 22
  • S22-118
    WE035 unique location code S22-118 for collected scat sample within detection grid cell 22
  • S22-119
    WE035 unique location code S22-119 for collected scat sample within detection grid cell 22
  • S22-154
    WE035 unique location code S22-154 for collected scat sample within detection grid cell 22
  • S22-155
    WE035 unique location code S22-155 for collected scat sample within detection grid cell 22
  • S22-156
    WE035 unique location code S22-156 for collected scat sample within detection grid cell 22
  • S22-157
    WE035 unique location code S22-157 for collected scat sample within detection grid cell 22
  • S22-158
    WE035 unique location code S22-158 for collected scat sample within detection grid cell 22
  • S22-159
    WE035 unique location code S22-159 for collected scat sample within detection grid cell 22
  • S22-160
    WE035 unique location code S22-160 for collected scat sample within detection grid cell 22
  • S22-161
    WE035 unique location code S22-161 for collected scat sample within detection grid cell 22
  • S22-4
    WE035 unique location code S22-4 for collected scat sample within detection grid cell 22
  • S22-5
    WE035 unique location code S22-5 for collected scat sample within detection grid cell 22
  • S22-6
    WE035 unique location code S22-6 for collected scat sample within detection grid cell 22
  • S22-74
    WE035 unique location code S22-74 for collected scat sample within detection grid cell 22
  • S30-106
    WE035 unique location code S30-106 for collected scat sample within detection grid cell 30
  • S30-107
    WE035 unique location code S30-107 for collected scat sample within detection grid cell 30
  • S30-108
    WE035 unique location code S30-108 for collected scat sample within detection grid cell 30
  • S30-109
    WE035 unique location code S30-109 for collected scat sample within detection grid cell 30
  • S30-54
    WE035 unique location code S30-54 for collected scat sample within detection grid cell 30
  • S30-69
    WE035 unique location code S30-69 for collected scat sample within detection grid cell 30
  • S30-71
    WE035 unique location code S30-71 for collected scat sample within detection grid cell 30
  • S30-72
    WE035 unique location code S30-72 for collected scat sample within detection grid cell 30
  • S36-55
    WE035 unique location code S36-55 for collected scat sample within detection grid cell 36
  • S36-56
    WE035 unique location code S36-56 for collected scat sample within detection grid cell 36
  • S36-57
    WE035 unique location code S36-57 for collected scat sample within detection grid cell 36
  • S37-1
    WE035 unique location code S37-1 for collected scat sample within detection grid cell 37
  • S37-75
    WE035 unique location code S37-75 for collected scat sample within detection grid cell 37
  • S37-76
    WE035 unique location code S37-76 for collected scat sample within detection grid cell 37
  • S37-77
    WE035 unique location code S37-77 for collected scat sample within detection grid cell 37
  • S37-78
    WE035 unique location code S37-78 for collected scat sample within detection grid cell 37
  • S44-100
    WE035 unique location code S44-100 for collected scat sample within detection grid cell 44
  • S44-101
    WE035 unique location code S44-101 for collected scat sample within detection grid cell 44
  • S44-16
    WE035 unique location code S44-16 for collected scat sample within detection grid cell 44
  • S44-17
    WE035 unique location code S44-17 for collected scat sample within detection grid cell 44
  • S44-18
    WE035 unique location code S44-18 for collected scat sample within detection grid cell 44
  • S44-97
    WE035 unique location code S44-97 for collected scat sample within detection grid cell 44
  • S44-98
    WE035 unique location code S44-98 for collected scat sample within detection grid cell 44
  • S45-126
    WE035 unique location code S45-126 for collected scat sample within detection grid cell 45
  • S45-127
    WE035 unique location code S45-127 for collected scat sample within detection grid cell 45
  • S45-128
    WE035 unique location code S45-128 for collected scat sample within detection grid cell 45
  • S45-129
    WE035 unique location code S45-129 for collected scat sample within detection grid cell 45
  • S45-130
    WE035 unique location code S45-130 for collected scat sample within detection grid cell 45
  • S45-132
    WE035 unique location code S45-132 for collected scat sample within detection grid cell 45
  • S45-133
    WE035 unique location code S45-133 for collected scat sample within detection grid cell 45
  • S45-134
    WE035 unique location code S45-134 for collected scat sample within detection grid cell 45
  • S45-135
    WE035 unique location code S45-135 for collected scat sample within detection grid cell 45
GRID_NUMBER - char(2) (nominal)

ID: WE03502.GRID_NUMBER

Sampling grid (3Km x 3Km) cell number

Type system: Microsoft SQL Server 2019

Code definitions (10)
  • 15
    WE035 scat detection grid cell number 15; see scat detection map
  • 22
    WE035 scat detection grid cell number 22; see scat detection map
  • 29
    WE035 scat detection grid cell number 29; see scat detection map
  • 30
    WE035 scat detection grid cell number 30; see scat detection map
  • 36
    WE035 scat detection grid cell number 36; see scat detection map
  • 37
    WE035 scat detection grid cell number 37; see scat detection map
  • 38
    WE035 scat detection grid cell number 38; see scat detection map
  • 44
    WE035 scat detection grid cell number 44; see scat detection map
  • 45
    WE035 scat detection grid cell number 45; see scat detection map
  • MT
    WE035 manual, opportunistic scat collection within study area
SCAT_NUMBER - numeric(3,0) (ratio)

ID: WE03502.SCAT_NUMBER

Scat number within collection type

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=natural, min=1.0000 (exclusive=false), max=927.0000 (exclusive=false)

COLLECTION_TYPE - char(2) (nominal)

ID: WE03502.COLLECTION_TYPE

Defines collection method and time frame

Type system: Microsoft SQL Server 2019

Code definitions (3)
  • S
    samples collected by Conservation K9s during summer 2018 (June-August)
  • F
    samples collected by Conservation K9s during fall 2018 (October-November)
  • MT
    samples collected opportunistically during field work from 2017-2019
COLLECTION_DATETIME - datetime (dateTime)

ID: WE03502.COLLECTION_DATETIME

Date and time scat was collected (time was not recorded for collection_tpe=MT); in Pacific Standard Time (PST)

Type system: Microsoft SQL Server 2019

Date format: YYYY-MM-DD hh:mm:ss

SEASON - char(3) (nominal)

ID: WE03502.SEASON

Season when sample collected

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • wet
    scat samples collected during the wet season (September - May)
  • dry
    scat samples collected during the dry season (June - August)
AMPHIBIA - char(1) (nominal)

ID: WE03502.AMPHIBIA

indicates whether or not the taxonomic class Amphibia was detected in scat sample

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    taxonomic class Amphibia were not detected in scat sample
  • 1
    taxonomic class Amphibia were detected in scat sample
AVES - char(1) (nominal)

ID: WE03502.AVES

indicates whether or not the taxonomic class Aves was detected in scat sample

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    taxonomic class Aves were not detected in scat sample
  • 1
    taxonomic class Aves were detected in scat sample
MAMMALIA - char(1) (nominal)

ID: WE03502.MAMMALIA

indicates whether or not the taxonomic class Mammalia was detected in scat sample

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    taxonomic class Mammalia were not detected in scat sample
  • 1
    taxonomic class Mammalia were detected in scat sample
REPTILIA - char(1) (nominal)

ID: WE03502.REPTILIA

indicates whether or not the taxonomic class Reptilia was detected in scat sample

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    taxonomic class Reptilia were not detected in scat sample
  • 1
    taxonomic class Reptilia were detected in scat sample
GASTROPODA - char(1) (nominal)

ID: WE03502.GASTROPODA

indicates whether or not the taxonomic class Gastropoda was detected in scat sample

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    taxonomic class Gastropoda were not detected in scat sample
  • 1
    taxonomic class Gastropoda were detected in scat sample
ARACHNIDA - char(1) (nominal)

ID: WE03502.ARACHNIDA

indicates whether or not the taxonomic class Arachnida was detected in scat sample

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    taxonomic class Arachnida were not detected in scat sample
  • 1
    taxonomic class Arachnida were detected in scat sample
MYRIAPODA - char(1) (nominal)

ID: WE03502.MYRIAPODA

indicates whether or not the taxonomic class Myriapoda was detected in scat sample

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    taxonomic class Myriapoda were not detected in scat sample
  • 1
    taxonomic class Myriapoda were detected in scat sample
INSECTA - char(1) (nominal)

ID: WE03502.INSECTA

indicates whether or not the taxonomic class Insecta was detected in scat sample

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    taxonomic class Insecta were not detected in scat sample
  • 1
    taxonomic class Insecta were detected in scat sample
STREPTOPHYTA - char(1) (nominal)

ID: WE03502.STREPTOPHYTA

indicates whether or not the taxonomic class Streptophyta was detected in scat sample

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    taxonomic class Streptophyta were not detected in scat sample
  • 1
    taxonomic class Streptophyta were detected in scat sample
WE03503 - Location information for each scat

Object name: WE03503_v1.csv

Records: 128

Attributes: 24

Temporal coverage: 2017-08-03 to 2019-01-25

File size: 17385 byte

Checksum (MD5): 9360a7965625d60e0adad62cf43c6ccf

Format: headers=1, recordDelimiter=\r\n, fieldDelimiter=,, quoteCharacter=", orientation=column

Constraints (2)
  • primaryKey: PRIMARY
    WE03503.COLLECTION_DATETIME, WE03503.COLLECTION_TYPE, WE03503.SCAT_NUMBER, WE03503.GRID_NUMBER
  • notNullConstraint: NOTNULL
    WE03503.CLASS, WE03503.COLLECTION_DATETIME, WE03503.COLLECTION_TYPE, WE03503.DBCODE, WE03503.EASTING, WE03503.ELEVATION, WE03503.ENTITY, WE03503.HJA, WE03503.LOGGED, WE03503.NORTHING, WE03503.PERCENTAGE_INSIDE_R100, WE03503.PERCENTAGE_INSIDE_R1000, WE03503.PERCENTAGE_INSIDE_R500, WE03503.PERCENTAGE_INSIDE_R5000, WE03503.SCAT_ID, WE03503.SCAT_NUMBER, WE03503.TREATMENT, WE03503.YRSSINCEDI, WE03503.GRID_NUMBER
Attributes (24)
DBCODE - char(5) (nominal)

ID: WE03503.DBCODE

FSDB Database Code

Type system: Microsoft SQL Server 2019

Code definitions (1)
  • WE035
    FSDB Database Study Code WE035
ENTITY - numeric(2,0) (ratio)

ID: WE03503.ENTITY

Entity number

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=natural, min=3.0000 (exclusive=false), max=3.0000 (exclusive=false)

SCAT_ID - char(7) (ordinal)

ID: WE03503.SCAT_ID

Unique sample code representing collection_type, grid_number, scat_number and its location

Type system: Microsoft SQL Server 2019

Code definitions (128)
  • F15-133
    WE035 unique location code F15-133 for collected scat sample within detection grid cell 15
  • F15-134
    WE035 unique location code F15-134 for collected scat sample within detection grid cell 15
  • F15-136
    WE035 unique location code F15-136 for collected scat sample within detection grid cell 15
  • F15-137
    WE035 unique location code F15-137 for collected scat sample within detection grid cell 15
  • F15-50
    WE035 unique location code F15-50 for collected scat sample within detection grid cell 15
  • F22-101
    WE035 unique location code F22-101 for collected scat sample within detection grid cell 22
  • F22-143
    WE035 unique location code F22-143 for collected scat sample within detection grid cell 22
  • F22-18
    WE035 unique location code F22-18 for collected scat sample within detection grid cell 22
  • F22-196
    WE035 unique location code F22-196 for collected scat sample within detection grid cell 22
  • F22-197
    WE035 unique location code F22-197 for collected scat sample within detection grid cell 22
  • F22-198
    WE035 unique location code F22-198 for collected scat sample within detection grid cell 22
  • F22-199
    WE035 unique location code F22-199 for collected scat sample within detection grid cell 22
  • F22-22
    WE035 unique location code F22-22 for collected scat sample within detection grid cell 22
  • F22-224
    WE035 unique location code F22-224 for collected scat sample within detection grid cell 22
  • F22-226
    WE035 unique location code F22-226 for collected scat sample within detection grid cell 22
  • F22-300
    WE035 unique location code F22-300 for collected scat sample within detection grid cell 22
  • F22-301
    WE035 unique location code F22-301 for collected scat sample within detection grid cell 22
  • F22-302
    WE035 unique location code F22-302 for collected scat sample within detection grid cell 22
  • F22-303
    WE035 unique location code F22-303 for collected scat sample within detection grid cell 22
  • F22-307
    WE035 unique location code F22-307 for collected scat sample within detection grid cell 22
  • F22-70
    WE035 unique location code F22-70 for collected scat sample within detection grid cell 22
  • F29-71
    WE035 unique location code F29-71 for collected scat sample within detection grid cell 29
  • F29-73
    WE035 unique location code F29-73 for collected scat sample within detection grid cell 29
  • F29-74
    WE035 unique location code F29-74 for collected scat sample within detection grid cell 29
  • F29-75
    WE035 unique location code F29-75 for collected scat sample within detection grid cell 29
  • F29-76
    WE035 unique location code F29-76 for collected scat sample within detection grid cell 29
  • F30-112
    WE035 unique location code F30-112 for collected scat sample within detection grid cell 30
  • F30-113
    WE035 unique location code F30-113 for collected scat sample within detection grid cell 30
  • F30-114
    WE035 unique location code F30-114 for collected scat sample within detection grid cell 30
  • F30-115
    WE035 unique location code F30-115 for collected scat sample within detection grid cell 30
  • F30-116
    WE035 unique location code F30-116 for collected scat sample within detection grid cell 30
  • F30-117
    WE035 unique location code F30-117 for collected scat sample within detection grid cell 30
  • F30-118
    WE035 unique location code F30-118 for collected scat sample within detection grid cell 30
  • F30-119
    WE035 unique location code F30-119 for collected scat sample within detection grid cell 30
  • F30-120
    WE035 unique location code F30-120 for collected scat sample within detection grid cell 30
  • F30-121
    WE035 unique location code F30-121 for collected scat sample within detection grid cell 30
  • F30-123
    WE035 unique location code F30-123 for collected scat sample within detection grid cell 30
  • F30-138
    WE035 unique location code F30-138 for collected scat sample within detection grid cell 30
  • F30-140
    WE035 unique location code F30-140 for collected scat sample within detection grid cell 30
  • F30-142
    WE035 unique location code F30-142 for collected scat sample within detection grid cell 30
  • F30-39
    WE035 unique location code F30-39 for collected scat sample within detection grid cell 30
  • F36-173
    WE035 unique location code F36-173 for collected scat sample within detection grid cell 36
  • F37-150
    WE035 unique location code F37-150 for collected scat sample within detection grid cell 37
  • F37-151
    WE035 unique location code F37-151 for collected scat sample within detection grid cell 37
  • F37-152
    WE035 unique location code F37-152 for collected scat sample within detection grid cell 37
  • F37-153
    WE035 unique location code F37-153 for collected scat sample within detection grid cell 37
  • F37-154
    WE035 unique location code F37-154 for collected scat sample within detection grid cell 37
  • F37-155
    WE035 unique location code F37-155 for collected scat sample within detection grid cell 37
  • F37-156
    WE035 unique location code F37-156 for collected scat sample within detection grid cell 37
  • F37-158
    WE035 unique location code F37-158 for collected scat sample within detection grid cell 37
  • F37-159
    WE035 unique location code F37-159 for collected scat sample within detection grid cell 37
  • F37-162
    WE035 unique location code F37-162 for collected scat sample within detection grid cell 37
  • F37-192
    WE035 unique location code F37-192 for collected scat sample within detection grid cell 37
  • F37-194
    WE035 unique location code F37-194 for collected scat sample within detection grid cell 37
  • F37-241
    WE035 unique location code F37-241 for collected scat sample within detection grid cell 37
  • F37-242
    WE035 unique location code F37-242 for collected scat sample within detection grid cell 37
  • F37-243
    WE035 unique location code F37-243 for collected scat sample within detection grid cell 37
  • F37-51
    WE035 unique location code F37-51 for collected scat sample within detection grid cell 37
  • F37-6
    WE035 unique location code F37-6 for collected scat sample within detection grid cell 37
  • F38-46
    WE035 unique location code F38-46 for collected scat sample within detection grid cell 38
  • F38-47
    WE035 unique location code F38-47 for collected scat sample within detection grid cell 38
  • MT284
    WE035 unique location code MT284 for manually collected scat samples
  • MT285
    WE035 unique location code MT285 for manually collected scat samples
  • MT287
    WE035 unique location code MT287 for manually collected scat samples
  • MT288
    WE035 unique location code MT288 for manually collected scat samples
  • MT289
    WE035 unique location code MT289 for manually collected scat samples
  • MT296
    WE035 unique location code MT296 for manually collected scat samples
  • MT315
    WE035 unique location code MT315 for manually collected scat samples
  • MT37
    WE035 unique location code MT37 for manually collected scat samples
  • MT383
    WE035 unique location code MT383 for manually collected scat samples
  • MT408
    WE035 unique location code MT408 for manually collected scat samples
  • MT431
    WE035 unique location code MT431 for manually collected scat samples
  • MT432
    WE035 unique location code MT432 for manually collected scat samples
  • MT433
    WE035 unique location code MT433 for manually collected scat samples
  • MT906
    WE035 unique location code MT906 for manually collected scat samples
  • MT907
    WE035 unique location code MT907 for manually collected scat samples
  • MT908
    WE035 unique location code MT908 for manually collected scat samples
  • MT909
    WE035 unique location code MT909 for manually collected scat samples
  • MT916
    WE035 unique location code MT916 for manually collected scat samples
  • MT918
    WE035 unique location code MT918 for manually collected scat samples
  • MT927
    WE035 unique location code MT927 for manually collected scat samples
  • S22-117
    WE035 unique location code S22-117 for collected scat sample within detection grid cell 22
  • S22-118
    WE035 unique location code S22-118 for collected scat sample within detection grid cell 22
  • S22-119
    WE035 unique location code S22-119 for collected scat sample within detection grid cell 22
  • S22-154
    WE035 unique location code S22-154 for collected scat sample within detection grid cell 22
  • S22-155
    WE035 unique location code S22-155 for collected scat sample within detection grid cell 22
  • S22-156
    WE035 unique location code S22-156 for collected scat sample within detection grid cell 22
  • S22-157
    WE035 unique location code S22-157 for collected scat sample within detection grid cell 22
  • S22-158
    WE035 unique location code S22-158 for collected scat sample within detection grid cell 22
  • S22-159
    WE035 unique location code S22-159 for collected scat sample within detection grid cell 22
  • S22-160
    WE035 unique location code S22-160 for collected scat sample within detection grid cell 22
  • S22-161
    WE035 unique location code S22-161 for collected scat sample within detection grid cell 22
  • S22-4
    WE035 unique location code S22-4 for collected scat sample within detection grid cell 22
  • S22-5
    WE035 unique location code S22-5 for collected scat sample within detection grid cell 22
  • S22-6
    WE035 unique location code S22-6 for collected scat sample within detection grid cell 22
  • S22-74
    WE035 unique location code S22-74 for collected scat sample within detection grid cell 22
  • S30-106
    WE035 unique location code S30-106 for collected scat sample within detection grid cell 30
  • S30-107
    WE035 unique location code S30-107 for collected scat sample within detection grid cell 30
  • S30-108
    WE035 unique location code S30-108 for collected scat sample within detection grid cell 30
  • S30-109
    WE035 unique location code S30-109 for collected scat sample within detection grid cell 30
  • S30-54
    WE035 unique location code S30-54 for collected scat sample within detection grid cell 30
  • S30-69
    WE035 unique location code S30-69 for collected scat sample within detection grid cell 30
  • S30-71
    WE035 unique location code S30-71 for collected scat sample within detection grid cell 30
  • S30-72
    WE035 unique location code S30-72 for collected scat sample within detection grid cell 30
  • S36-55
    WE035 unique location code S36-55 for collected scat sample within detection grid cell 36
  • S36-56
    WE035 unique location code S36-56 for collected scat sample within detection grid cell 36
  • S36-57
    WE035 unique location code S36-57 for collected scat sample within detection grid cell 36
  • S37-1
    WE035 unique location code S37-1 for collected scat sample within detection grid cell 37
  • S37-75
    WE035 unique location code S37-75 for collected scat sample within detection grid cell 37
  • S37-76
    WE035 unique location code S37-76 for collected scat sample within detection grid cell 37
  • S37-77
    WE035 unique location code S37-77 for collected scat sample within detection grid cell 37
  • S37-78
    WE035 unique location code S37-78 for collected scat sample within detection grid cell 37
  • S44-100
    WE035 unique location code S44-100 for collected scat sample within detection grid cell 44
  • S44-101
    WE035 unique location code S44-101 for collected scat sample within detection grid cell 44
  • S44-16
    WE035 unique location code S44-16 for collected scat sample within detection grid cell 44
  • S44-17
    WE035 unique location code S44-17 for collected scat sample within detection grid cell 44
  • S44-18
    WE035 unique location code S44-18 for collected scat sample within detection grid cell 44
  • S44-97
    WE035 unique location code S44-97 for collected scat sample within detection grid cell 44
  • S44-98
    WE035 unique location code S44-98 for collected scat sample within detection grid cell 44
  • S45-126
    WE035 unique location code S45-126 for collected scat sample within detection grid cell 45
  • S45-127
    WE035 unique location code S45-127 for collected scat sample within detection grid cell 45
  • S45-128
    WE035 unique location code S45-128 for collected scat sample within detection grid cell 45
  • S45-129
    WE035 unique location code S45-129 for collected scat sample within detection grid cell 45
  • S45-130
    WE035 unique location code S45-130 for collected scat sample within detection grid cell 45
  • S45-132
    WE035 unique location code S45-132 for collected scat sample within detection grid cell 45
  • S45-133
    WE035 unique location code S45-133 for collected scat sample within detection grid cell 45
  • S45-134
    WE035 unique location code S45-134 for collected scat sample within detection grid cell 45
  • S45-135
    WE035 unique location code S45-135 for collected scat sample within detection grid cell 45
GRID_NUMBER - char(2) (nominal)

ID: WE03503.GRID_NUMBER

Sampling grid (3Km x 3Km) cell number

Type system: Microsoft SQL Server 2019

Code definitions (10)
  • 15
    WE035 scat detection grid cell number 15; see scat detection map
  • 22
    WE035 scat detection grid cell number 22; see scat detection map
  • 29
    WE035 scat detection grid cell number 29; see scat detection map
  • 30
    WE035 scat detection grid cell number 30; see scat detection map
  • 36
    WE035 scat detection grid cell number 36; see scat detection map
  • 37
    WE035 scat detection grid cell number 37; see scat detection map
  • 38
    WE035 scat detection grid cell number 38; see scat detection map
  • 44
    WE035 scat detection grid cell number 44; see scat detection map
  • 45
    WE035 scat detection grid cell number 45; see scat detection map
  • MT
    WE035 manual, opportunistic scat collection within study area
SCAT_NUMBER - numeric(3,0) (ratio)

ID: WE03503.SCAT_NUMBER

Scat number within collection type

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=natural, min=1.0000 (exclusive=false), max=927.0000 (exclusive=false)

COLLECTION_TYPE - char(2) (nominal)

ID: WE03503.COLLECTION_TYPE

Defines collection method and time frame

Type system: Microsoft SQL Server 2019

Code definitions (3)
  • S
    samples collected by Conservation K9s during summer 2018 (June-August)
  • F
    samples collected by Conservation K9s during fall 2018 (October-November)
  • MT
    samples collected opportunistically during field work from 2017-2019
COLLECTION_DATETIME - datetime (dateTime)

ID: WE03503.COLLECTION_DATETIME

Date and time scat was collected (time was not recorded for collection_tpe=MT); in Pacific Standard Time (PST)

Type system: Microsoft SQL Server 2019

Date format: YYYY-MM-DD hh:mm:ss

EASTING - numeric(6,0) (ratio)

ID: WE03503.EASTING

Easting in NAD 83 UTM Zone 10

Type system: Microsoft SQL Server 2019

Unit: meters

Precision: 1

Numeric domain: type=natural, min=559441.0000 (exclusive=false), max=569599.0000 (exclusive=false)

NORTHING - numeric(7,0) (ratio)

ID: WE03503.NORTHING

Northing in NAD 83 UTM Zone 10

Type system: Microsoft SQL Server 2019

Unit: meters

Precision: 1

Numeric domain: type=natural, min=4892446.0000 (exclusive=false), max=4904080.0000 (exclusive=false)

ELEVATION - numeric(6,1) (ratio)

ID: WE03503.ELEVATION

elevation of collection site above sea level; derived from DEM using LiDAR, converted from feet

Type system: Microsoft SQL Server 2019

Unit: meters

Precision: 1

Numeric domain: type=real, min=438.4000 (exclusive=false), max=1499.9000 (exclusive=false)

YR_LOGGED - numeric(4,0) (interval)

ID: WE03503.YR_LOGGED

year stand was logged (if logged) from historical records

Type system: Microsoft SQL Server 2019

Unit: year (yyyy)

Precision: 1

Numeric domain: type=whole, min=1946.0000 (exclusive=false), max=1990.0000 (exclusive=false)

YRSSINCEDI - numeric(3,0) (ratio)

ID: WE03503.YRSSINCEDI

years since stand disturbance via logging; stands with no logging record were assigned 200 years.

Type system: Microsoft SQL Server 2019

Unit: number

Precision: 1

Numeric domain: type=natural, min=28.0000 (exclusive=false), max=200.0000 (exclusive=false)

TREATMENT - char(2) (nominal)

ID: WE03503.TREATMENT

type of logging that occurred on stand from historical records

Type system: Microsoft SQL Server 2019

Code definitions (3)
  • CT
    Commercial Thinning
  • CC
    Clearcut
  • NA
    No known logging occurred within the last 100 years
CLASS - char(1) (nominal)

ID: WE03503.CLASS

time since logging classified into 3 groups

Type system: Microsoft SQL Server 2019

Code definitions (3)
  • 1
    stand logged 0-40 years ago
  • 2
    stand logged 41-80 years ago> 100 years
  • 3
    stand logged > 100 years ago
HJA - char(1) (nominal)

ID: WE03503.HJA

indicates whether the site is within or outside of the HJ Andrews Experimental Forest boundary

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    site is outside of the HJ Andrews Experimental Forest boundary
  • 1
    site is within the HJ Andrews Experimental Forest boundary
LOGGED - char(1) (nominal)

ID: WE03503.LOGGED

indicates whether the location of scat collected was within or outside of a logged area

Type system: Microsoft SQL Server 2019

Code definitions (2)
  • code
    location of scat collected was not within a logged area
  • 1
    location of scat collected was within a logged area
VALUE_R100 - numeric(4,2) (ratio)

ID: WE03503.VALUE_R100

area within 100 m of the scat location that was logged

Type system: Microsoft SQL Server 2019

Unit: hectares

Precision: 1

Numeric domain: type=real, min=0.2700 (exclusive=false), max=3.3300 (exclusive=false)

PERCENTAGE_INSIDE_R100 - numeric(6,2) (ratio)

ID: WE03503.PERCENTAGE_INSIDE_R100

percent area within 100 m of the scat location that was logged

Type system: Microsoft SQL Server 2019

Unit: percent

Precision: 1

Numeric domain: type=real, min=8.6000 (exclusive=false), max=106.0700 (exclusive=false)

VALUE_R500 - numeric(5,2) (ratio)

ID: WE03503.VALUE_R500

area within 500 m of the scat location that was logged

Type system: Microsoft SQL Server 2019

Unit: hectares

Precision: 1

Numeric domain: type=real, min=7.9200 (exclusive=false), max=70.7400 (exclusive=false)

PERCENTAGE_INSIDE_R500 - numeric(6,2) (ratio)

ID: WE03503.PERCENTAGE_INSIDE_R500

percent area within 500 m of the scat location that was logged

Type system: Microsoft SQL Server 2019

Unit: percent

Precision: 1

Numeric domain: type=real, min=10.0900 (exclusive=false), max=90.1300 (exclusive=false)

VALUE_R1000 - numeric(6,2) (ratio)

ID: WE03503.VALUE_R1000

area within 1 km of the scat location that was logged

Type system: Microsoft SQL Server 2019

Unit: hectares

Precision: 1

Numeric domain: type=real, min=26.5500 (exclusive=false), max=253.8900 (exclusive=false)

PERCENTAGE_INSIDE_R1000 - numeric(6,2) (ratio)

ID: WE03503.PERCENTAGE_INSIDE_R1000

perent area within 1 km of the scat location that was logged

Type system: Microsoft SQL Server 2019

Unit: percent

Precision: 1

Numeric domain: type=real, min=8.4600 (exclusive=false), max=80.8700 (exclusive=false)

VALUE_R5000 - numeric(7,2) (ratio)

ID: WE03503.VALUE_R5000

area within 5 km of the scat location that was logged

Type system: Microsoft SQL Server 2019

Unit: hectares

Precision: 1

Numeric domain: type=real, min=1191.2400 (exclusive=false), max=2945.8800 (exclusive=false)

PERCENTAGE_INSIDE_R5000 - numeric(6,2) (ratio)

ID: WE03503.PERCENTAGE_INSIDE_R5000

percent area within 5 km of the scat location that was logged

Type system: Microsoft SQL Server 2019

Unit: percent

Precision: 1

Numeric domain: type=real, min=15.1800 (exclusive=false), max=37.5300 (exclusive=false)

Units
meters m length meter meter 1 meter; SI unit of length
percent % dimensionless number dimensionless 100 percent; a number
hectares ha area hectare meterSquared 10000 hectares; 1 hectare is 10^4 square meters
number number dimensionless number dimensionless 1 dimensionless number, i.e., ratio, count
year (yyyy) YYYY datetime YYYY YYYY-MM-DDThh:mm:ss N/A year (4 character) portion of date
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Intellectual Rights

Data Use Agreement:

The re-use of scientific data has the potential to greatly increase communication, collaboration and synthesis within and among disciplines, and thus is fostered, supported and encouraged. This Data Set is released under the Creative Commons license CC BY "Attribution" (see: https://creativecommons.org/licenses/by/4.0/). Creative Commons license CC BY - Attribution is a license that allows others to distribute, remix, tweak, and build upon your work (even commercially), as long as you are credited for the original creation. This license accommodates maximum dissemination and use of licensed materials.

It is considered professional conduct and an ethical obligation to acknowledge the work of other scientists. The Data User is asked to provide attribution of the original work if this data package is shared in whole or by individual parts or used in the derivation of other products. A recommended citation is provided for each Data Set in the Andrews LTER data catalog (see: http://andlter.forestry.oregonstate.edu/data/catalog/datacatalog.aspx). A generic citation is also provided for this Data Set on the website https://portal.edirepository.org in the summary metadata page. Data Users are thus strongly encouraged to consider consultation, collaboration and/or co-authorship with the Data Set Creator.

While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed and all data are made available "as is." The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data.

General acknowledgement: Data were provided by the HJ Andrews Experimental Forest research program, funded by the National Science Foundation's Long-Term Ecological Research Program (DEB 2025755), US Forest Service Pacific Northwest Research Station, and Oregon State University.

Licensed

License: Creative Commons Attribution 4.0 International Public License

Identifier: CC-BY-4.0

URL: https://creativecommons.org/licenses/by/4.0/

Maintenance

Maintenance update frequency: notPlanned

Description

  • An update history is logged and maintained with each new version of every dataset.

Change History

  • Version1 (2018-03-22)
    Study code and preliminary metadata established
  • Version2 (2022-12-07)
    Original creation of entities from Excel entity_attribute table using move_xls program. Ran QC. Uploaded to SQL.