Species data used in Random Forest modelling to determine predictors of extinction.
2023
- 109Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage109
- Views87
- Downloads22
Dataset Description
Plant species information extracted from the South African National Red List (http://redlist.sanbi.org/index.php). The list of species includes taxa as categorised by the Red List as Extinct, Critically Endangered Possibly Extinct, and a sample of extant taxa (Critically Endangered, Endangered, Vulnerable, Near Threatened, Least Concern) totaling 946 taxa. The information included are Genspec (UniqueID), Group (Extinct, Threatened or not-Threatened), Life form (LF), Growth form (GF), Fam (taxonomic family), South African biome that the taxa occur in, national Red List status, Range size in km2, threats impacting the species as identified during Red List assessment indicated using binary coding (Yes/No) for Habitat loss, Habitat degradation, Invasive alien species (IAS), Other, Over-exploitation, Pollution, Unknown. This dataset was used to classify taxa as EX, threatened or not-threatened to identify which predictors are the most important for classifying taxa as extinct using Rando...
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