feat: support verbatimScientificName as species label in existing dataset tools

[mihow]

Context

load_dwca_data() in src/dataset_tools/utils.py:20 hardcodes the columns it selects from the DwC-A occurrence data, and verbatimScientificName is not among them. This means all downstream CLI commands (clean-dataset, verify-images, split-dataset, etc.) cannot natively use verbatimScientificName as a label column.

Currently, this is worked around by scripts/build_species_list.py, which reads the DwC-A independently and joins the name column onto the annotations CSV after the clean-dataset step. This works but adds an extra step to the pipeline.

Proposed Changes

1. Add an extra_columns parameter (or a name_column option) to load_dwca_data() in src/dataset_tools/utils.py:20 so that additional DwC-A columns can be carried through the pipeline.

2. Update the CLI decorators/options in src/dataset_tools/cli.py to expose this option on relevant commands (clean-dataset, split-dataset, etc.).

3. Once supported natively, the build_species_list.py bridge script could be simplified or removed.

Related

• PR feat: add species classifier training pipeline #69 (species classifier pipeline) uses the workaround