Effects of preference heterogeneity among landowners on spatial conservation prioritization

Abstract

The participation of private landowners in conservation is crucial to efficient biodiversity conservation. This is especially the case in settings where the share of private ownership is large and the economic costs associated with land acquisition are high. We used probit regression analysis and historical participation data to examine the likelihood of participation of Danish forest owners in a voluntary conservation program. We used the results to spatially predict the likelihood of participation of all forest owners in Denmark. We merged spatial data on the presence of forest, cadastral information on participation contracts, and individual-level socioeconomic information about the forest owners and their households. We included predicted participation in a probability model for species survival. Uninformed and informed (included land owner characteristics) models were then incorporated into a spatial prioritization for conservation of unmanaged forests. The choice models are based on sociodemographic data on the entire population of Danish forest owners and historical data on their participation in conservation schemes. Inclusion in the model of information on private landowners' willingness to supply land for conservation yielded at intermediate budget levels up to 30% more expected species coverage than the uninformed prioritization scheme. Our landowner-choice model provides an example of moving toward more implementable conservation planning.

Microtargeting for conservation

“…; Nielsen et al. ). Adapting microtargeting to this particular challenge presents a novel opportunity to prioritize conservation investments by spatially coupling fine‐grain social and ecological data across large extents.…”

“…In these contexts, the management of valued resources is directly tied to individual landowner decisions. Previous studies have sought coupled social-ecological landscape prioritizations, recognizing that the likelihood of conservation success is a function of biophysical as well as human dimensions and dynamics (Game et al 2011;Guerrero et al 2013;Karimi et al 2017;Nielsen et al 2017). Adapting microtargeting to this particular challenge presents a novel opportunity to prioritize conservation investments by spatially coupling fine-grain social and ecological data across large extents.…”

“…), and one study by Nielsen et al. () coupled cadastral and forest‐cover data to a national registry of conservation‐program participation, the latter being a data set unique to Denmark and unavailable elsewhere.…”

“…A few studies have coupled social and biophysical variables to prioritize landscapes, either by summarizing social receptivity based on qualitative data (Game et al 2011) or by using coarse-resolution data over wide extents (Guerrero & Wilson 2017;Karimi et al 2017). Some have used agentbased modeling to represent the complexity of social and ecological interrelationships (Miyasaka et al 2017), and one study by Nielsen et al (2017) coupled cadastral and forest-cover data to a national registry of conservation-program participation, the latter being a data set unique to Denmark and unavailable elsewhere.…”

Preference heterogeneity among landowners and spatial conservation prioritization: response to Eyvindson et al. 2017

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Eyvindson et al (2017) comment on our recent paper, Nielsen et al (2017), in which we examined the revealed participation choice of Danish forest owners in a voluntary conservation program. We used the results to predict spatially the likelihood of all Danish forest owners participating in such programs and assessed the value of such information.Eyvindson et al acknowledge that the issues we address are important.

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