Microtargeting for conservation

Abstract

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting-predictive analytics of big data-to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social-ecological systems.

Keywords: 保护营销学; asignación de recursos; conservation marketing; land-use planning; mercadotecnia de la conservación; planeación del uso de suelo; planeación espacial; planeación sistemática de la conservación; private lands; protocolo de intervención; resource allocation; retorno de la inversión; return on investment; spatial planning; systematic conservation planning; tierras privadas; triage; 优先等级分类; 土地利用规划; 投资收益; 私有土地; 空间规划; 系统保护规划; 资源分配.

Figure 1

Conceptual conservation‐priority space defined by conservation value and social propensity for conservation action (prime prospects, areas where conservation value and social propensity are both high; premium, areas of high value where social propensity is low; trivial, areas with lower conservation value despite likely conservation action; sinks, areas where conservation value and social propensity for action are both low).

Figure 2

Examples of microtargeting use of consumer data to (i) identify likely participants in conservation programs from lists of past known participants and (ii) identify likely members of population segments based on known market segments.

Figure 3

Properties with riparian gaps (i.e., nonforest and nonshrub areas within 11 m of streams) jointly ranked by gap size and owner's score for propensity to participate in conservation (jittered deciles). Properties with gaps >3.50 ha are clustered at 3.50 ha in the figure for clarity.

Figure 4

Percentage of known buffer‐restoration program participants in the training and validation data sets by score for propensity to participate in restoration.