Open Collections

Mapping Species at Risk and of Cultural Value in Campbell River Regional District, British Columbia

Zhang, Zechen

In the face of rapidly declining biodiversity and the increasing fragmentation of habitats, identifying and prioritizing conservation areas have become crucial challenges for environmental sustainability. This study seeks to address these challenges by leveraging the power of citizen science data from iNaturalist and integrating it with GIS technology to assess conservation priorities in Campbell River, British Columbia. By integrating species occurrence data, conservation status, and cultural value, we have used GIS tools to assess conservation priority land parcels visually. Species occurrence data from iNaturalist Meticulous collection and validation of data emphasizes research-grade observations to reduce identification errors and ensure reliability. We integrated species conservation status from CDC-iMap and cultural value from IMPRESS and applied a tiered scoring system to quantify Species Importance Scores (IV). Through GIS analysis, the spatial visualization of species distribution can be realized and the corresponding land parcel Importance Score (LPIS) calculation can be obtained by summing up each land parcel based on IV. The results demonstrate significant differences in species importance across land cover types, identify several higher-value conservation land parcels in the Campbell River region, and highlight key conservation values that emphasize certain types of land cover habitat. The results showed that the riparian area along the Elk Falls Provincial Park and nearby urban and coastal areas of Campbell River tend to contain the highest conservation value. We also discussed potential limitations, mainly caused by the species occurrence data selectivity bias, and species identification accuracy. This approach would guide species and biodiversity conservation and land management planning in the Campbell River region.

Campbell River; British Columbia

2024-04-11

CC-BY 4.0

https://doi.org/10.5683/SP3/UTZMMC

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

Dataverse