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.

Integrated spatial analysis for human–wildlife coexistence in the American West

“…New analysis techniques, or those from other fields, offer promise for more robust integration of social dimensions into spatial analysis for wildlife conservation planning. Microtargeting, for example, allows conservationists to borrow tools from marketing and political sciences to understand conservation propensity at the individual level (Metcalf et al 2019). Coupled with increasing access to spatially explicit data on land ownership, these techniques could allow wildlife conservationists to identify prime corridor areas based on habitat quality and social receptivity.…”

Identifying and prioritizing human behaviors that benefit biodiversity

“…The audience targeted in this study was broad. Ideally, future work would consider more specific audience segmentation for each of the behaviors selected and their potential interventions (Metcalf et al, 2019). Effective audience segmentation and targeting involves different interventions or messaging strategies for each audience segment (Kidd et al, 2019), as individuals have different motivations and barriers to participation (Asah & Blahna, 2012).…”

Using spatially explicit, time‐dependent analysis to understand how social factors influence conservation outcomes

“…Their findings can inform conservation planning by identifying the types of landowners who or communities that are not achieving desired conservation outcomes; managers may then target outreach toward these specific groups (e.g., Metcalf et al. ).…”