2011
DOI: 10.2139/ssrn.2816144
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Unexpected Co-Benefits: Forest Connectivity and Property Tax Incentives

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Cited by 2 publications
(2 citation statements)
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“…In our case, a similar change in the behaviour of the recipients was confirmed only indirectly by the interviews. Moreover, as Giertliova et al ( 2019) stated, the biggest advantage of land tax reductios are their transparency and long-term functioning, thus can be combined with other policy instruments to prevent forest conversion to development (Locke & Rissman 2012). If such support did not exist, forest owners and enterprises would try to get their increased costs or reduced earnings into market prices, especially in wood prices, and thus distort the market (Giertliová et al 2019).…”
Section: Discussionmentioning
confidence: 99%
“…In our case, a similar change in the behaviour of the recipients was confirmed only indirectly by the interviews. Moreover, as Giertliova et al ( 2019) stated, the biggest advantage of land tax reductios are their transparency and long-term functioning, thus can be combined with other policy instruments to prevent forest conversion to development (Locke & Rissman 2012). If such support did not exist, forest owners and enterprises would try to get their increased costs or reduced earnings into market prices, especially in wood prices, and thus distort the market (Giertliová et al 2019).…”
Section: Discussionmentioning
confidence: 99%
“…We obtained these forest morphology classes for the forest present in both 2000 and 2012 by applying the eight neighbor rule, in which a forest cell is connected if any of its sides or corners is in contact with another forest cell, and a one-pixel edge (30 m). This neighbor rule and edge width have been used previously to calculate forest patches and their connectivity (Sorte et al 2004, Locke and Rissman 2012, Rogan et al 2016. We also calculated the number of forest patches, the mean area of the forest patch, the number of forest loss patches, and the largest area of forest loss using the R package SDMTools (VanDerWal et al 2014; Table 2).…”
Section: Forest Composition and Configurationmentioning
confidence: 99%