Botanical databases in EIA: opportunities and challenges

Abstract

Botanical databases are useful in environmental impact assessment (EIA), but they present significant concerns. These databases compile botanical literature, digitized herbaria and citizen science data, offering extensive data but varying in quality and precision. Scientific databases, though reliable in identification, often suffer from location inaccuracies, and new data entry is limited. Conversely, citizen science databases provide well-located records with a constant input of new data, but identification accuracy is inconsistent, particularly in complex species; AI-assisted plant identifications, frequently used, currently pose many reliability issues. Global databases aggregate data from multiple sources, combining accuracy concerns; while the quantity of data constantly increasing the quality control is insufficient. Limitations related to positional, attribute or temporal accuracy, or to data set completeness, may compromise decision-making. Other concerns include automatic mapping and GIS integration, which can obscure data inaccuracies. Recommendations for improving database quality include stricter data validation, excluding low-quality citizen science records, and ensuring that AI machine learning involves expert oversight. For EIA practitioners, critical assessment of data, especially regarding threatened species, is essential to avoid erroneous conclusions and ensure reliable decision-making.