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9 results for “iDNA”
Measuring protected-area effectiveness using vertebrate distributions from leech iDNA
<p>Protected areas are key to meeting biodiversity conservation goals, but direct measures of effectiveness have proven difficult to obtain. We address this challenge by using environmental DNA from leech-ingested bloodmeals to estimate spatially-resolved vertebrate occupancies across the 677 km<sup>2</sup> Ailaoshan reserve in Yunnan, China. From 30,468 leeches collected by 163 park rangers across 172 patrol areas, we identify 86 vertebrate species, including amphibians, mammals, birds and squamates. Multi-species occupancy modelling shows that species richness increases with elevation and distance to reserve edge. Most large mammals (e.g. sambar, black bear, serow, tufted deer) follow this pattern; the exceptions are the three domestic mammal species (cows, sheep, goats) and muntjak deer, which are more common at lower elevations. Vertebrate occupancies are a direct measure of conservation outcomes that can help guide protected-area management and improve the contributions that protected areas make towards global biodiversity goals. Here, we show the feasibility of using invertebrate-derived DNA to estimate spatially-resolved vertebrate occupancies across entire protected areas.</p>
Measuring protected-area effectiveness using vertebrate distributions from leech iDNA
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Mosquito iDNA reveals landscape patterns of birds and mammals
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Leech-derived iDNA complements traditional surveying methods, enhancing species detections for rapid biodiversity sampling in the tropics
<p>Deforestation, exploitation, and other drivers of biodiversity loss in Madagascar leave its highly endangered and predominantly endemic wildlife at risk of extinction. Decreasing biodiversity threatens to compromise ecosystem functions and vital services provided to people. New, economical, and diverse methods of biodiversity monitoring can help to establish reliable baseline and long-term records of species richness. Metabarcoding with invertebrate-derived DNA (iDNA) has emerged as a promising new biosurveillance tool. An unexpected wet forest fragment tucked in the dry cliffs of Madagascar's southcentral plateau, the Ivohibory Protected Area (IPA), hosts a unique mosaic of species diversity, featuring both dry and wet forest species. Recently elevated to protected status, the IPA has been surveyed for flora and fauna with a range of inventory methods over three years and six expeditions (2016, 2017, & 2019). We collected 1,451 leeches over 12 days from the IPA to supplement known species richness and to compare results against current records. With iDNA, we pooled tissues, and isolated, and amplified bloodmeal DNA with five sets of primers. We detected 20 species of which four are species of frogs previously undetected and three of which are previously unknown to exist in this region. iDNA surveys can provide complementary data to traditional surveying methods like camera traps, line transects, and bioacoustic methods.</p>
Mammal mitogenomics from invertebrate-derived DNA (iDNA)
<p>Mitogenomic capture of Non-human Primates from invertebrate derived DNA using hybridisation capture. </p> <p>Files are in fastq format and sequenced with illumina Mi-Seq using the Mi-Seq Reagent Kit v3 (2 x 250bp; illumina) .</p>
Leech-derived iDNA complements traditional surveying methods, enhancing species detections for rapid biodiversity sampling in the tropics
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Data from: Shifting up a gear with iDNA: from mammal detection events to standardized surveys
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Leech blood-meal iDNA reveals differences in Bornean mammal diversity across habitats
<b>Description: </b><p>This data set includes the data used in Drinkwater et al. (2020) Leech blood-meal iDNA reveals differences in Bornean mammal diversity across habitats, submitted to Molecular Ecology. There are three sets of data based on the biomonitoring of mammals using iDNA extracted from leeches collected across the SAFE project (and DVCA) in 2016. At each site in the SAFE landscape 20 minute handsearches took place within the boundaries of fixed 25m2 vegetation plots. For these analyses we only used Haemadipsa picta individuals, as previous studies have revealed species differences between H. picta and H. zeylanica in the SAFE area. With metabarcoding techniques, first we extracted and amplified the 16S rRNA region of mammal DNA, from site-matched pools of leeches using PCR and specific mammal primers. NGS sequencing was used and the short fragments were then identified using in silico PCR with ecoPCR and OBITOOLS (metabarcoding packages) to assign taxonomy to the unknown sequences. We then analysed diversity in different habitats across the landscape and included microclimate data, from LiDAR scans of the landscape as variables which could impact the detection of mammals. </p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/10"><b>The effects of rainforest fragmentation on mammal community assemblages using leech blood-meal analysis</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC (Standard grant , NE/K016148/1)</li><li>NERC (Independent research grant, NE/S01537X/1)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Council (Research licence JKM/MBS.1000 2/2 (34))</li><li>Sabah Biodiversity Council (Research licence JKM/MBS.1000 2/3 JLD.2 (107))</li><li>Sabah Biodiversity Council (Export licence JKM/MBS.1000 2/3 JLD.3 (44))</li><li>Danum Valley Conservation Area (Research licence YS/DVMC/2016/253)</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=4095374">here</a></p><p><b>Files: </b>This consists of 1 file: Drinkwater2020-iDNA_diversity3.xlsx</p><p><b>Drinkwater2020-iDNA_diversity3.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>UNFILTERED Taxonomic assignment of iDNA sequences</b> (described in worksheet ecoTAG_output_raw)</p><p>Description: UNFILTERED This dataset is the raw output of the in silico PCR using the programs ecoPCR and the OBITOOLS package. The exact primers are matched against all mammal sequences in GenBank (NCBI) using a minimum of three mismatches between primer and query sequence and a quality filter of a minimum identity of 0.95. This dataset was subsequently filtered for contaminant, geographically implausible mammals and collapsed by haplotype per pool</p><p>Number of fields: 15</p><p>Number of data rows: 3454</p><p>Fields: </p><ul><li><b>id</b>: Unique sequence ID within leech pool (Field type: id)</li><li><b>site</b>: The site at the SAFE project from which the pool of leeches was collected (Field type: id)</li><li><b>hab</b>: The habitat type of the site at the SAFE project from which the pool of leeches was collected (Field type: id)</li><li><b>count</b>: Count of the times this sequence was found - UNFILTERED (Field type: numeric)</li><li><b>best_identity</b>: Percent identity match between query and database sequence - UNFILTERED (Field type: numeric)</li><li><b>family</b>: Family taxid - following GenBank (Field type: id)</li><li><b>family_name</b>: Family name (Field type: id)</li><li><b>genus</b>: Genus taxid - following GenBank (Field type: id)</li><li><b>genus_name</b>: Genus name (Field type: id)</li><li><b>order</b>: Order taxid - following GenBank (Field type: id)</li><li><b>order_name</b>: Order name (Field type: id)</li><li><b>species</b>: Species taxid - following GenBank (Field type: id)</li><li><b>species_name</b>: Species name (Field type: id)</li><li><b>Assigned_name</b>: Assigned taxonomic name (Field type: id)</li><li><b>sequence</b>: Query sequence (Field type: id)</li></ul></li><li><p><b>Mammal detections recorded in each pool </b> (described in worksheet detections)</p><p>Description: From the taxonomic assignment list, the unique sequences identfied in each pool are are recorded as detections. The value is a count of the numebr of time the unique sequence for that taxon was recorded in the pool. Geographically implausible mammals have been removed and taxa which agree per site have been collapsed. This give a detections by pool matrix. For analyses these counts were converted into presence/absence data. </p><p>Number of fields: 19</p><p>Number of data rows: 57</p><p>Fields: </p><ul><li><b>pool</b>: This is the pool name given to the leech pool for sequencing (Field type: id)</li><li><b>site</b>: The site at the SAFE project from which the pool of leeches was collected (Field type: id)</li><li><b>leeches</b>: This is the number of individual leeches which make up the pool (Field type: numeric)</li><li><b>habitat</b>: Habitat type - classification used in the paper to describe the quality of forest in the sites where the leeches were collected (Field type: id)</li><li><b>Arctogalidia</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Elephas</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Felidae</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Helarctos</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Hemigalus</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Hystrix</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Macaca</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Manis</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Muntiacus</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Rusa</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Sus</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Paguma</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Tragulus</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Trichys</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li><li><b>Viverra</b>: Occurrence of detections of this taxon in a leech pool, as determined from leech-based iDNA (Field type: abundance)</li></ul></li><li><p><b>Microclimate variables</b> (described in worksheet microclimate)</p><p>Description: Mean and maximum temperature and mean and maximum VPD extracted at each of the second order points used in the study. These values were extracted from microclimate surfaces generated in Jucker et al., (2018), using the coordinates from the centre of each of the 25m2 plots. For the values in Danum Valley Conservation Area (DVCA), these were extracted from the nearest river point (coordinates given).</p><p>Number of fields: 6</p><p>Number of data rows: 92</p><p>Fields: </p><ul><li><b>Code</b>: SAFE second order points including LOMBOK points at RLFE and three river sites at DVCA (Field type: location)</li><li><b>site</b>: The site at the SAFE project from which the pool of leeches was collected (Field type: id)</li><li><b>T_max_raster</b>: The maximum daily temperature at each second order point (Field type: numeric)</li><li><b>T_mean_raster</b>: The mean daily temperature at each second order point (Field type: numeric)</li><li><b>VPD_max_raster</b>: The maximum daily vapour pressure deficit (VPD) at each second order point (Field type: numeric)</li><li><b>VPD_mean_raster</b>: The mean daily vapour pressure deficit (VPD) at each second order point (Field type: numeric)</li></ul></li></ol><p><b>Date range: </b>2016-01-01 to 2016-12-31</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Mammalia <br> -  -  -  -  Rodentia <br> -  -  -  -  -  Hystricidae <br> -  -  -  -  -  -  <i>Hystrix</i> <br> -  -  -  -  -  -  <i>Trichys</i> <br> -  -  -  -  -  -  -  <i>Trichys fasciculata</i> <br> -  -  -  -  Proboscidea <br> -  -  -  -  -  Elephantidae <br> -  -  -  -  -  -  <i>Elephas</i> <br> -  -  -  -  -  -  -  <i>Elephas maximus</i> <br> -  -  -  -  Primates <br> -  -  -  -  -  Cercopithecidae <br> -  -  -  -  -  -  <i>Macaca</i> <br> -  -  -  -  Carnivora <br> -  -  -  -  -  Felidae <br> -  -  -  -  -  Viverridae <br> -  -  -  -  -  -  <i>Viverra</i> <br> -  -  -  -  -  -  -  <i>Viverra tangalunga</i> <br> -  -  -  -  -  -  <i>Paguma</i> <br> -  -  -  -  -  -  -  <i>Paguma larvata</i> <br> -  -  -  -  -  -  <i>Arctogalidia</i> <br> -  -  -  -  -  -  -  <i>Arctogalidia trivirgata</i> <br> -  -  -  -  -  -  <i>Hemigalus</i> <br> -  -  -  -  -  -  -  <i>Hemigalus derbyanus</i> <br> -  -  -  -  -  Ursidae <br> -  -  -  -  -  -  <i>Helarctos</i> <br> -  -  -  -  -  -  -  <i>Helarctos malayanus</i> <br> -  -  -  -  Pholidota <br> -  -  -  -  -  Manidae <br> -  -  -  -  -  -  <i>Manis</i> <br> -  -  -  -  -  -  -  <i>Manis javanica</i> <br> -  -  -  -  Artiodactyla <br> -  -  -  -  -  Suidae <br> -  -  -  -  -  -  <i>Sus</i> <br> -  -  -  -  -  -  -  <i>Sus barbatus</i> <br> -  -  -  -  -  Tragulidae <br> -  -  -  -  -  -  <i>Tragulus</i> <br> -  -  -  -  -  Cervidae <br> -  -  -  -  -  -  <i>Muntiacus</i> <br> -  -  -  -  -  -  <i>Rusa</i> <br> -  -  -  -  -  -  -  <i>Rusa unicolor</i> <br></div><p></p>
Network analysis with either Illumina or MinION reveals that detecting vertebrate species requires metabarcoding of iDNA from a diverse fly community
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