Keywords
Functional types; Land use; Mixture model; Forest management
Start Date
25-6-2018 3:40 PM
End Date
25-6-2018 5:20 PM
Abstract
Family forest owners (FFO’s) play an important role in the complex interactions between development decisions and ecosystems. Determining the conditions of FFO engagement with natural systems will facilitate projections of future decision-making and subsequent ecosystem responses. We establish agent functional types (AFT’s) of landowners as a form of dimension reduction, effectively assigning individual FFO’s to a particular decision-making class, each with unique behavior rules. The objectives of this study are to (1) characterize AFT’s of New England FFO’s and (2) model AFT membership as a function of demographic and geographic data. Accomplishing (1) will establish differences in social, economic, and biophysical values between different classes of landowners. Fulfilling (2) allows for a high-resolution probability surface of AFT’s across the landscape, which can provide key input for simulation models of forest and land cover change. To characterize AFT’s we leverage a survey which was administered to New England FFO’s. The survey includes a choice experiment in which respondents indicate their willingness to cut their trees under various insect infestation scenarios. We use landowner responses to the choice experiment, as well as stated demographics and motivations, to construct 4 fundamental AFT’s in the form of a mixture model. Parcel- and town-level demographic and geographic data are then used to develop an AFT classification model. Preliminary results suggest that NLCD land-cover types, road densities, and population education metrics are predictive of landowner typology. The modeling framework presented here provides a representation of the geographical, sociological, economic, and ecological drivers of human-land interaction in New England.
Predicting Family Forest Owner Decision-Making
Family forest owners (FFO’s) play an important role in the complex interactions between development decisions and ecosystems. Determining the conditions of FFO engagement with natural systems will facilitate projections of future decision-making and subsequent ecosystem responses. We establish agent functional types (AFT’s) of landowners as a form of dimension reduction, effectively assigning individual FFO’s to a particular decision-making class, each with unique behavior rules. The objectives of this study are to (1) characterize AFT’s of New England FFO’s and (2) model AFT membership as a function of demographic and geographic data. Accomplishing (1) will establish differences in social, economic, and biophysical values between different classes of landowners. Fulfilling (2) allows for a high-resolution probability surface of AFT’s across the landscape, which can provide key input for simulation models of forest and land cover change. To characterize AFT’s we leverage a survey which was administered to New England FFO’s. The survey includes a choice experiment in which respondents indicate their willingness to cut their trees under various insect infestation scenarios. We use landowner responses to the choice experiment, as well as stated demographics and motivations, to construct 4 fundamental AFT’s in the form of a mixture model. Parcel- and town-level demographic and geographic data are then used to develop an AFT classification model. Preliminary results suggest that NLCD land-cover types, road densities, and population education metrics are predictive of landowner typology. The modeling framework presented here provides a representation of the geographical, sociological, economic, and ecological drivers of human-land interaction in New England.
Stream and Session
C6: Ecosystem Services Values and Quantification: A Negotiation between Engineers, Economists, and Ecologists