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Exploring the relationship between parcelization metrics and natural resource managers’ perceptions of forest land parcelization intensity
Highlights Parcelization can adversely impact many forest-derived goods and services. Resource managers ranked forest ownership patterns for their impacts. Certain ownership patterns are seen as having greater adverse impacts than others. Some metrics are strongly correlated with rankings of parcelization impact.
Abstract A major challenge associated with forest land parcelization, defined as the subdivision of forest land holdings into smaller ownership parcels, is that little information exists on how to measure its severity and judge its impacts across forest landscapes. To address this information gap, an on-line survey presented field-based public natural resource managers in the Lake States of Minnesota, Wisconsin, and Michigan with four private forest ownership patterns, each containing the same total forest area, number of parcels, and average parcel size. Survey respondents ranked each landscape from most to least parcelized based on the degree to which each ownership pattern was perceived to adversely impact three forest-based goods and services: timber production, recreational access, and wildlife habitat. Using an exploded logit model, respondents’ rankings of parcelization impact were found to be consistent, regardless of the forest good or service evaluated. Rankings were also not influenced by the respondent’s professional discipline, location, length of professional experience, or employer. Of the four parcelization metrics evaluated, the Gini Coefficient and Adjusted Mean metrics appear to best capture the forest land ownership patterns that natural resource professionals are most concerned about, suggesting those metrics may be useful indicators by which to assess parcelization impact.
Exploring the relationship between parcelization metrics and natural resource managers’ perceptions of forest land parcelization intensity
Highlights Parcelization can adversely impact many forest-derived goods and services. Resource managers ranked forest ownership patterns for their impacts. Certain ownership patterns are seen as having greater adverse impacts than others. Some metrics are strongly correlated with rankings of parcelization impact.
Abstract A major challenge associated with forest land parcelization, defined as the subdivision of forest land holdings into smaller ownership parcels, is that little information exists on how to measure its severity and judge its impacts across forest landscapes. To address this information gap, an on-line survey presented field-based public natural resource managers in the Lake States of Minnesota, Wisconsin, and Michigan with four private forest ownership patterns, each containing the same total forest area, number of parcels, and average parcel size. Survey respondents ranked each landscape from most to least parcelized based on the degree to which each ownership pattern was perceived to adversely impact three forest-based goods and services: timber production, recreational access, and wildlife habitat. Using an exploded logit model, respondents’ rankings of parcelization impact were found to be consistent, regardless of the forest good or service evaluated. Rankings were also not influenced by the respondent’s professional discipline, location, length of professional experience, or employer. Of the four parcelization metrics evaluated, the Gini Coefficient and Adjusted Mean metrics appear to best capture the forest land ownership patterns that natural resource professionals are most concerned about, suggesting those metrics may be useful indicators by which to assess parcelization impact.
Exploring the relationship between parcelization metrics and natural resource managers’ perceptions of forest land parcelization intensity
Kilgore, Michael A. (author) / Snyder, Stephanie A. (author)
Landscape and Urban Planning ; 149 ; 43-48
2016-02-03
6 pages
Article (Journal)
Electronic Resource
English
Factors that influence working forest conservation and parcelization
| Elsevier | 2017
Factors that influence working forest conservation and parcelization
| Elsevier | 2017