Abstract
Pollinators serve key ecological functions, ensuring stable ecosystems and high agricultural yields. Hence, assessing ecosystem health and effects of agricultural management would benefit from understanding and monitoring pollination networks, which involves identifications of pollinators and pollinated plants. Classic approaches of morphology-based identification of plants and pollinators can be time-consuming, labor-intensive and costly, and require highly specialized taxonomic expertise. In comparison, DNA barcoding and high-throughput sequencing technologies can provide efficient and accurate identifications of plants and their pollinators, which may facilitate construction of pollination networks. Here we propose using sequencing technologies with a PCR-free genome-skimming work frame, using “super DNA barcode” as a new method to assess plant-pollinator networks. We expect this technique to improve resolution and accuracy of taxonomic identification to help gain quantitative information for bulk samples of pollinators or pollens. Al-though there are technical challenges to be resolved, the robustness of the new methodology has been validated in relevant biodiversity studies, suggesting promise in constructing pollination networks.
| Original language | English |
|---|---|
| Pages (from-to) | 445-456 |
| Number of pages | 12 |
| Journal | Biodiversity Science |
| Volume | 26 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 20 May 2018 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
Keywords
- Chloroplast
- Metabarcoding
- Metagenome
- Mitochondria
- PCR-free
- Pollen
- Quantify
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