P. A. Townsend

Mapping oak wilt disease using phenological observations from space

This paper maps oak wilt disease using land surface phenology metrics from satellite data to distinguish tree health conditions with high accuracy.

Variability in Forest Plant Traits along the Western Ghats of India and Their Environmental Drivers at Different Resolutions

The paper maps plant trait variability across different spatial resolutions in the Western Ghats using imaging spectroscopy and identifies environmental drivers of trait variation.

Remotely detected plant function in two midwestern prairie grassland experiments reveals belowground processes

The paper uses imaging spectroscopy to link aboveground vegetation properties with belowground soil processes in two grassland experiments, finding contrasting relationships based on ecosystem productivity and diversity.

Plastic mulches reduce adult and larval populations of Drosophila suzukii in fall-bearing raspberry

This study evaluates the effectiveness of plastic mulches in reducing Drosophila suzukii populations in raspberry crops and assesses their impact on microclimate factors.

Canopy spectral reflectance detects oak wilt at the landscape scale using phylogenetic discrimination

This study uses canopy spectral reflectance and phylogenetic analysis to detect oak wilt disease in forests with high accuracy.

Integrating remote sensing and jurisdictional observation networks to improve the resolution of ecological management

This paper presents a jurisdictional observation network integrating satellite remote sensing and volunteer-based trail cameras to improve wildlife monitoring and management.

Coupling spectral and resource-use complementarity in experimental grassland and forest communities

The paper links plant spectral variation to ecosystem productivity by analyzing spectral and resource-use complementarity in grassland and forest communities.

A generalized observation confirmation model to account for false positive error in species detection-nondetection data

The paper introduces a generalized observation confirmation model to address false positive error in species detection-nondetection data, showing it reduces bias in abundance and arrival time estimates.