Search Results (3)

Arctomecon humilis (dwarf bear poppy) is an endangered gypsophile restricted to the St. George area in southern Utah, USA. Extirpation of the rare oligolectic bee Perdita meconis and decline of other native pollinators within the last 20 years has been largely attributed to the advent of invasive Africanized honeybees (AHBs), which have become the predominant pollinator for A. humilis. A three-year study was carried out to determine if reliance on AHBs had a negative effect on reproductive output. In the first year, pollen addition experiments were carried out in a small, isolated population to determine if pollinator scarcity or genetic factors affected reproductive output. In the subsequent two years, reproductive output studies were conducted across four populations. In all years, fruit set across study sites was exceptionally high. There was no consistent effect from flower number or interplant distance, which have historically been shown to have a significant impact on reproductive output prior to AHB arrival. The consequences and sustainability of this relatively young relationship between A. humilis and the AHB remain unclear. However, high reproductive success shows that the AHB is currently capable of adequately fulfilling pollinator services for A. humilis. Full article

A census of endangered plant populations is critical to determining their size, spatial distribution, and geographical extent. Traditional, on-the-ground methods for collecting census data are labor-intensive, time-consuming, and expensive. Use of drone imagery coupled with application of rapidly advancing deep learning technology could greatly reduce the effort and cost of collecting and analyzing population-level data across relatively large areas. We used a customization of the YOLOv5 object detection model to identify and count individual dwarf bear poppy (Arctomecon humilis) plants in drone imagery obtained at 40 m altitude. We compared human-based and model-based detection at 40 m on n = 11 test plots for two areas that differed in image quality. The model out-performed human visual poppy detection for precision and recall, and was 1100× faster at inference/evaluation on the test plots. Model inference precision was 0.83, and recall was 0.74, while human evaluation resulted in precision of 0.67, and recall of 0.71. Both model and human performance were better in the area with higher-quality imagery, suggesting that image quality is a primary factor limiting model performance. Evaluation of drone-based census imagery from the 255 ha Webb Hill population with our customized YOLOv5 model was completed in <3 h and provided a reasonable estimate of population size (7414 poppies) with minimal investment of on-the-ground resources. Full article

Accurate census is essential for endangered plant management, yet lack of resources may make complete on-the-ground census difficult to achieve. Accessibility, especially for species in fragile habitats, is an added constraint. We examined the feasibility of using UAV (unmanned aerial vehicle, drone)-based imagery for census of an endangered plant species, Arctomecon humilis (dwarf bear-poppy), an herbaceous perennial gypsophile endemic of the Mojave Desert, USA. Using UAV technology, we captured imagery at both 50-m altitude (census) and 15-m altitude (validation) at two populations, White Dome (325 ha) and Red Bluffs (166 ha). The imagery was processed into orthomosaics that averaged 2.32 cm ground sampling distance (GSD) for 50-m imagery and 0.73 cm GSD for 15-m imagery. Putative poppy plants were marked in the 50-m imagery according to predefined criteria. We then used the 15-m imagery from each area to verify the identification accuracy of marked plants. Visual evaluation of the 50-m imagery resulted in errors of both commission and omission, mainly caused by failure to accurately identify or detect small poppies (<10 cm diameter). Higher-resolution 30-m altitude imagery (1.19 cm GSD) greatly reduced errors of commission. Habitat classification demonstrated that poppy density variation was closely tied to soil surface color. This study showed that drone imagery can potentially be used to census rare plant species with distinctive morphology in open habitats and understand their spatial distribution. Full article