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      Ancient and modern scats record broken ecological interactions and a decline in dietary breadth of the critically endangered kākāpō parrot (Strigops habroptilus)

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      Frontiers in Ecology and Evolution
      Frontiers Media SA

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          Abstract

          Threatened animal taxa are often absent from most of their original habitats, meaning their ecological niche cannot be fully captured by contemporary data alone. Although DNA metabarcoding of scats and coprolites (palaeofaeces) can identify the past and present species interactions of their depositors, the usefulness of coprolites in conservation biology is untested as few endangered taxa have known coprolite records. Here, we perform multilocus metabarcoding sequencing and palynological analysis of dietary plants of >100 coprolites (estimated to date from c. 400–1900 A.D.) and > 100 frozen scats (dating c. 1950 A.D. to present) of the critically endangered, flightless, herbivorous kākāpō ( Strigops habroptilus), a species that disappeared from its natural range in Aotearoa-New Zealand (NZ) after the 13th C. A.D. We identify 24 orders, 56 families and 67 native plant genera unrecorded in modern kākāpō diets (increases of 69, 108 and 75% respectively). We found that southern beeches (Nothofagaceae), which are important canopy-forming trees and not an important kākāpō food today, dominated kākāpō diets in upland (c. >900 m elevation) habitats. We also found that kākāpō frequently consumed hemiparasitic mistletoes (Loranthaceae) and the holoparasitic wood rose ( Dactylanthus taylorii), taxa which are nutrient rich, and now threatened by mammalian herbivory and a paucity of dispersers and pollinators. No single dataset or gene identified all taxa in our dataset, demonstrating the value of multiproxy or multigene datasets in studies of animal diets. Our results highlight how contemporary data may considerably underestimate the full dietary breadth of threatened species and demonstrate the potential value of coprolite analysis in conservation biology.

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          BLAST+: architecture and applications

          Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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            Search and clustering orders of magnitude faster than BLAST.

            Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.
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              Bayesian Analysis of Radiocarbon Dates

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                Author and article information

                Journal
                Frontiers in Ecology and Evolution
                Front. Ecol. Evol.
                Frontiers Media SA
                2296-701X
                March 28 2023
                March 28 2023
                : 11
                Article
                10.3389/fevo.2023.1058130
                4f3ed009-3d48-4813-b6b4-8a0643d24689
                © 2023

                Free to read

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

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