Freshwater diversity and biosecurity data re-packaged
We collect a range of ecological data as part of our day-to-day research and services. This data is stored in various databases, for example, NIWA's Freshwater Biodata Information System (FBIS). FBIS contains fish, algae, aquatic plant (macrophyte) and invertebrate data gathered from New Zealand's freshwater streams, rivers and lakes.
This freshwater biodata includes over 2000 collated records on water weeds and over 900 submerged vegetation surveys, from more than 350 lakes. This data can be viewed via NIWA's Freshwater Biodata Information System (FBIS) web-portal.
Using this data NIWA has produced a series of fact sheets on weed and other alien species. The fact sheets 'Freshwater Pest Species in New Zealand' include descriptions of pest presence and maps of distribution for territorial regions. Re-packaging data in this way provides a resource to aid inventory, surveillance and monitoring of pest species.
In further examples of data re-use, a panel of experts appointed by the Department of Conservation used FBIS biodata to reassess the threat status of New Zealand's aquatic plants (see accompanying article: Threatened aquatic and wetland plants). Historical and current records helped determine the level of concern over dwindling species distributions or abundance, and assign an appropriate conservation status.
Additionally, lake vegetation survey data from FBIS has been re-assessed by the recently developed monitoring method, LakeSPI (Lake Submerged Plant Indicators). LakeSPI provides a measure of ecological condition based on the presence, extent and composition of submerged plants, see About Lake Submerged Plant Indicators. Biodata from FBIS has been used to generate historic LakeSPI scores to compare with current assessments and help identify the magnitude of impacts from water weed invasion or water quality deterioration over time.
NIWA's continuing investment in data management and retrieval systems means that data is secure and reusable and maximum benefit can be made of past data collection efforts.