Forests (Jan 2024)

Characterization of Chinese Tallow Invasion in the Southern United States

  • Mohammad M. Bataineh,
  • Jacob S. Fraser,
  • Lauren S. Pile Knapp

DOI
https://doi.org/10.3390/f15010202
Journal volume & issue
Vol. 15, no. 1
p. 202

Abstract

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Chinese tallow is a non-native invasive tree expanding in range and abundance throughout the southern United States. Several biogeographical studies mapping tallow distribution and examining key underlying environmental factors relied on the U.S. Forest Service Forest Inventory and Analysis (FIA) data, representing forestlands at scales of ~2400 ha. However, given that most invasive trees, like tallow, are cosmopolitan and dynamic in nature, FIA data fails to capture the extent and severity of the invasion especially outside areas classified as forestlands. To develop tallow maps that more adequately depict its distribution at finer spatial scales and to capture observations in non-forestlands, we combined verified citizen science observations with FIA data. Further, we described spatiotemporal patterns and compared citizen science to FIA and other previously published distribution maps. From our work, although tallow is prevalent in the south, Louisiana, Texas, and Mississippi were the most invaded states. Tallow was associated with flatwoods and prairie grasslands of the Gulf Coast. Annual extreme minimum temperatures of less than −12.2 °C (10 °F) represented the northern limit of naturalized tallow populations. Tallow’s northward and inland expansion was captured in citizen science and FIA data, indicating a tallow spread rate ranging from 5 to 20 km annually over the last decade. Systematic sampling, such as FIA, and citizen science data both have their own unique pitfalls. However, the use of citizen science data can complement invasive plant distribution mapping, especially when combined with data from established systematic monitoring networks. This approach provides for a more complete understanding of invasive tree extent and spatiotemporal dynamics across large landscapes.

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