Non-native invasive plants are a major challenge to biodiversity. Protecting and restoring native communities under invasive plant pressure requires species-specific approaches to invasive species management, including attention to timing of plant life cycles. Mapping invasive species populations is essential to adaptive management prioritization but staffing for field observation is often in short supply. Volunteers can provide important support to land management organizations but may lack advanced skill in plant identification necessary to assist with invasive species mapping. To test whether volunteers could produce actionable information if provided with optimal observation times based on highly visible key identifying features, we used community science data from iNaturalist and expert botanical knowledge to develop a calendar of 'phenobvious' traits (seasonally identifying life cycle events, e.g. early spring leaf-out of Rosa multiflora) for more than 100 invasive species of the U.S. Mid-Atlantic region (North Carolina to New York), developed a mapping application for use on smart phones, and created and implemented tutorials.
Volunteers were able to rapidly identify focal invasive species using phenological cues. Review of initial mapping revealed a tendency for volunteers to map either broadly (designating a large area as containing a species) or granularly (mapping individual plants). To reduce this variability, we categorized species according to management priority by invasion phase and specified mapping granularity based on priority phase (e.g., mapping all individuals of species with small populations that might be eradicated from the site, versus mapping population boundaries of widespread species). Once creation of the key feature phenology table and tutorials was complete, staff time investment decreased to occasional maintenance of the table and weekly communication with volunteers. Mapped populations are now being integrated with management planning and used in concert with a complementary project identifying optimal treatment phenology to focus invasive species management effort.
Co-Authors: Kristie Lane Anderson and Evan Horne
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