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Title: Landowner functional types to characterize response to invasive forest insects
Abstract

Invasive forest insects can induce tree mortality in two ways: (a) by directly harming trees; or (b) by influencing forest owners to pre‐emptively harvest threatened trees. This study investigates forest owners’ intentions to harvest trees threatened by invasive insects.

Our first objective is to identify and characterize agent functional types (AFTs) of family forest owners in the northeastern United States using a set of contingent behaviour questions contained in a mail survey. We establish AFTs as a form of dimension reduction, effectively casting landowners into a typology in which each type (AFT) has distinct probabilities of tree harvesting in response to forest insects. Our analysis identifies three functional types of landowners: ‘Cutters’ (46% of respondents; high intent to harvest trees impacted by invasive forest insects), ‘Responsive Cutters’ (42% of respondents; intent sensitive to insect impact severity), and ‘Non‐cutters’ (12% of respondents; low intent to cut).

Our second objective is to model AFT membership to predict the distribution of AFTs across the landscape. Predictors are chosen from a set of survey, geographic and demographic features. Our best AFT‐prediction model has three predictor variables: parcel size (hectares of forest), geographical region, and town‐level forested fraction. Application of the model provides a high‐resolution probability distribution of AFTs across the landscape.

By coupling human and insect behaviour, our results allow for holistic assessments of how invasive forest insects disturb forests, inclusive of the management response to these pests.

A freePlain Language Summarycan be found within the Supporting Information of this article.

 
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Award ID(s):
1832210
NSF-PAR ID:
10456718
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
People and Nature
Volume:
2
Issue:
1
ISSN:
2575-8314
Page Range / eLocation ID:
p. 204-216
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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