Aerobiological data as an indicator for invasive plants monitoring
Year: 2025
Type: article
Abstract: The relationship between airborne pollen of the invasive species Acacia dealbata Link, climate factors, and its ground expansion is studied using aerobiological data and aerial photography to test if pollen data can be used as a tool to detect changes in the surface area of invasive species.Airborne pollen monitoring was performed over a 31 years period (1994-2024). Additionally eight years within this interval were selected for Acacia area measurement with high-resolution aerial imagery, based on the availability of phorgraphs. Measurements for the years 2020 and 2024 was used to validate the proposed model.Aerial pollen recorded correlated significantly with maximum temperatures during the pre-peak period, stabilizing the correlation in the time series after 23 years. Additionally, the pollen integral showed an increasing trend that was not climate dependent. Mapped Acacia areas expanded from 261.3 ha in 2003 to 365.4 ha in 2017, a 39.6 % increase reflected in the increase of pollen levels, reaching a 4.8-fold rise.Acacia stabilizes and even reduces its surface during the last years of study. The interaction of pollen recorded in pre-peak period and maximum temperature explains 82% of the invasion of Acacia surface variation, with an estimated area error in the validation years (2020 and 2024) of 3.4% and 0.23%, respectively. It is concluded that Acacia pollen serves as a new indicator to monitor acacia surface and reconstruct its cover in the absence of high-resolution aerial images. Monitoring pollen concentrations in the atmosphere constitutes a useful tool for the management of invasive species.
Source: Ecological Indicators
Institution: Universidade de Vigo
Language: English
Subfield: Nature and Landscape Conservation
Field: Environmental Science
Domain: Physical Sciences
SDGs: Life on land, Climate action
Open Access status: gold
Estimated APC paid: $3,650
Funder: Ministerio de Universidades
Award: G1881690991
OpenAlex ID: W4409588645
