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Using multiple research methods to understand family forest ownersAuthor(s): John Schelhas
Source: In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 16-19.
Publication Series: Paper (invited, offered, keynote)
Station: Northern Research Station
PDF: View PDF (294.62 KB)
DescriptionApplied research on family forest owners ensures that we understand who they are, what they do, and why they do it. This information enables us to develop policy, management, and outreach approaches that can optimize the social, economic, cultural, and environmental benefits of private forests at the landowner, community, and national levels. The three principal scientific sources of information are National Woodland Owner Survey (NWOS) data, Forest Inventory and Analysis (FIA) data, and individual research efforts focused on specific geographical areas. NWOS and FIA data aim to be geographically comprehensive and are collected in intervals to provide time series data but are also less responsive to change in order to provide time series data. Individual research studies are tailored to specific questions, but their place specificity makes generalization difficult. We need to identify key management questions, use multiple research methods and data sources, and work collaboratively to maximize the effectiveness of our research.
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CitationSchelhas, John. 2012. Using multiple research methods to understand family forest owners. In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 16-19.
Keywordsstatistics, estimation, sampling, modeling, remote sensing, forest health, data integrity, environmental monitoring, cover estimation, international forest monitoring
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