Microtargeting for conservation
| Autor: | Cassandra Pallai, Ben Yuhas, Michael T. Norton, Allyson Muth, Conor N. Phelan, James C. Finley, Alexander L. Metcalf |
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| Rok vydání: | 2019 |
| Předmět: |
0106 biological sciences
Conservation of Natural Resources Geospatial analysis return on investment asignación de recursos resource allocation planeación sistemática de la conservación computer.software_genre 010603 evolutionary biology 01 natural sciences retorno de la inversión tierras privadas 空间规划 Return on investment mercadotecnia de la conservación planeación del uso de suelo 优先等级分类 私有土地 land‐use planning Contributed Papers planeación espacial Environmental planning Ecosystem Ecology Evolution Behavior and Systematics Spatial planning Nature and Landscape Conservation Pace Ecology business.industry 010604 marine biology & hydrobiology 保护营销学 Land-use planning Biodiversity 投资收益 资源分配 Contributed Paper protocolo de intervención Outreach Analytics Scale (social sciences) conservation marketing private lands 土地利用规划 spatial planning systematic conservation planning triage business computer 系统保护规划 |
| Zdroj: | Conservation Biology |
| ISSN: | 1523-1739 0888-8892 |
| DOI: | 10.1111/cobi.13315 |
| Popis: | 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. Article impact statement: Microtargeting boosts conservation impact by finding willing partners and individualizing behavior‐change interventions. |
| Databáze: | OpenAIRE |
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