Understanding behavioral intention of landowners to promote wildlife richness and biodiversity in the Southern Great Plains

JOURNAL OF ENVIRONMENTAL MANAGEMENT(2024)

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摘要
Ranchers have been conducting traditional management practices such as mono-species grazing and limited burning that focus on stocking rate maximization. This has resulted in negative environmental consequences such as woody plant encroachment, land use change, and species diversity loss. Recently, there has been a growing appreciation for alternative range management that simultaneously promotes biodiversity and agricultural productivity through fire and grazing interactions. The purpose of the study was to investigate the influence of landowner values, attitudes, and norms on their behavioral intention to adopt best management practices (BMPs) that enhance wildlife abundance in the southern Great Plains. The required data was generated through a mail survey following the Tailored Design method. We utilized the structural equation path model to construct two latent variables for norms and attitudes and analyzed the relationship of the latent variables with value orientations and behavioral intentions. The study results indicated that the attitudes had a significant positive relationship with biocentric (beta = 0.15, p-value<0.05) and a negative relationship with anthropocentric (beta = -0.259, p-value<0.05) value orientations, however, the relationship of value orientations was statistically insignificant with norms. Further, the results indicated that both norms (beta = 0.404, p-value<0.05) and attitudes (beta = 0.508, p-value<0.05) had a positive and statistically significant relation with ranchers' intentions to increase wildlife abundance on their land. Study results emphasize the need for innovative communication and non-traditional outreach methods to educate rangeland owners on the importance of patch-burn grazing and other best management practices.
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关键词
Rangelands,Wildlife abundance,Cognitive hierarchy theory,Biocentric value,Anthropocentric value,Structural equation path model
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