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Dryad

Data from: Spatial modeling improves understanding patterns of invasive species defoliation by a biocontrol herbivore

Cite this dataset

Henry, Annie L. et al. (2019). Data from: Spatial modeling improves understanding patterns of invasive species defoliation by a biocontrol herbivore [Dataset]. Dryad. https://doi.org/10.5061/dryad.2ts54jj

Abstract

Spatial modeling has proven to be useful in understanding the drivers of plant populations in the field of ecology, but has yet to be applied to understanding variation in biocontrol impact. In this study, we employ multi-scale analysis (Moran’s Eigenvector Maps) to better understand the variation in tree canopy exposed to defoliation by a biocontrol beetle (Diorhabda spp.). The control of the exotic tree Tamarix in riparian areas has long been a priority for land managers and ecologists in the American southwest. Diorhabda spp. was introduced as a bio-control agent beginning in 2001 and has since become an inseparable part of Tamarix-dominated river systems in the southwest. Between 2013 and 2016 tamarisk dieback was assessed at 79 sites across Grand County, Utah, arguably the epicenter of Diorhabda impact in the U.S. Canopy cover of Tamarix was between 73%-81% at these sites, with the percent that was live cover fluctuating by year with a minimum of 42%. Using a traditional general linear model, we found that readily and commonly measured environmental factors could explain only up to 26% of the variation in Tamarix live canopy each year, including that number of defoliations was correlated with an increase rather than a decrease in percent live canopy, suggesting compensatory growth. Spatial structure alone explained 22-40% of variation. We found fine scale spatial structure at less than 10 km and broad scale spatial structure from 10-30 km. Combining both traditional and novel spatial statistical methods we increased that percentage to 43-63%, depending on year. These results suggest that scientists and land managers must look beyond commonly measured environmental variables to explain non-random biocontrol impact in this system. In particular, this study points to the potential for biotic interactions and variation in flood cycles for further exploration of the identified spatial structure.

Usage notes

Location

United States
Utah