Foraminifera are a diverse clade of mostly shell-building single-celled organisms. Estimation of foraminiferal diversity is critical for understanding past and present climatic conditions, as they are highly sensitive to environmental perturbations. Biodiversity estimates of foraminifera began with the counting of test (i.e., shell) microfossils composed of calcium carbonate, as they are well preserved in sediment samples. However, this view has changed with molecular biodiversity estimates, which suggest that early-diverging single-chamber (i.e., "monothalamid") species that lack preservation ability are more diverse than anticipated. Although biodiversity estimates of foraminifera at the molecular level have changed our perceptions, they possess various challenges, especially with metabarcoding approaches. The metabarcoding approach is challenging in foraminifera because small subunit ribosomal (SSU) rRNA gene does not PCR amplify "universal" eukaryotic primers due to the presence of large insertions. Therefore, studies of foraminiferal diversity require targeted primers. Similarly, the pair-wise sequence similarity approach to taxonomic resolution can be problematic for Foraminifera, as fewer matching reference database exists for “monothalamids”- this requires the use of a more robust phylogeny-informed taxonomy, which provides a taxonomic identification for each sequence. Also, the appropriateness of recently developed metabarcoding tools still needs validation and comparison with clustering approaches for foraminiferal biodiversity estimation. This chapter introduces the current state of knowledge of foraminiferal biodiversity while also describing the knowledge gaps addressed in this thesis.
Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:masters_theses_2-2322 |
Date | 05 April 2023 |
Creators | Thakur, Rabindra |
Publisher | ScholarWorks@UMass Amherst |
Source Sets | University of Massachusetts, Amherst |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Masters Theses |
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