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Sones, Jayme E; Perez, Kate H; Sobel, Crystal N; Young, Monica R; Hebert, Paul DN; deWaard, Jeremy R
Genome, 11/2017, Letnik: 60, Številka: 11Journal Article
Background: The ability to rapidly measure the health of an ecosystem is becoming increasingly important with respect to effects of global climate change and human activity on the environment. Invertebrate diversity assessments facilitated by genetic analysis show promise as a rapid and effective approach to measure baseline data and subsequently monitor changes in local communities over time. However, many methods of capturing this diversity prior to genetic analysis are available, which can vary greatly in the amount of time, effort, and cost required. In this study, we assess the effectiveness of three collecting strategies (a 24 h bioblitz, a week of standardized sampling, and 20 weeks of Malaise trapping) employed within the Rouge National Urban Park in the summer of 2013. Results: In total, 43 924 individual specimens were sequenced for the barcode region of COI. Of these records, 38 145 met minimum sequence quality criteria, representing 4422 putative species or Barcode Index Numbers (BINs). Despite temporal and spatial overlap between the three approaches, only 183 BINs were found using all three methods. One week of standardized sampling resulted in the highest capture abundance (21 443) and second-highest BIN richness (2091) but required the maximum collecting effort (612 min). Conversely, the maximum richness (2225) and similar capture abundance (18 118) was detected with just 60 min of effort using 20 weeks of Malaise trapping. In comparison, 610 min of collector effort was employed during the 24 h bioblitz but resulted in the lowest capture abundance (4363) and BIN richness detection (1215). Significance: Our results indicate that while each DNA barcode-based biotic survey approach captured unique diversity of the invertebrate community, Malaise trapping presents the most valuable method for invertebrate surveys with potential for long-term site monitoring.
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Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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