Carroll Sarah L, Vogel Susanne M, Taek Purity Nititi, Tumuti Clevers, Vasudev Divya, Goswami Varun R, Wall Jake, Mwiu Stephen, Reid Robin S, Salerno Jonathan
Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, USA.
Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, Colorado, USA.
Conserv Biol. 2025 Feb;39(1):e14408. doi: 10.1111/cobi.14408. Epub 2024 Oct 22.
Conservation plans that explicitly account for the social landscape where people and wildlife co-occur can yield more effective and equitable conservation practices and outcomes. Yet, social data remain underutilized, often because social data are treated as aspatial or are analyzed with approaches that do not quantify uncertainty or address bias in self-reported data. We conducted a survey (questionnaires) of 177 households in a multiuse landscape in the Kenya-Tanzania borderlands. In a mixed-methods approach, we used Bayesian hierarchical models to quantify and map local attitudes toward African elephant (Loxodonta africana) conservation while accounting for response bias and then combined inference from attitude models with thematic analysis of open-ended responses and cointerpretation of results with local communities to gain deeper understanding of what explains attitudes of people living with wildlife. Model estimates showed that believing elephants have sociocultural value increased the probability of respondents holding positive attitudes toward elephant conservation in general (mean increase = 0.31 [95% credible interval, CrI, 0.02-0.67]), but experiencing negative impacts from any wildlife species lowered the probability of respondents holding a positive attitude toward local elephant conservation (mean decrease = -0.20 [95% CrI -0.42 to 0.03]). Qualitative data revealed that safety and well-being concerns related to the perceived threats that elephants pose to human lives and livelihoods, and limited incentives to support conservation on community and private lands lowered positive local attitude probabilities and contributed to negative perceptions of human-elephant coexistence. Our spatially explicit modeling approach revealed fine-scale variation in drivers of conservation attitudes that can inform targeted conservation planning. Our results suggest that approaches focused on sustaining existing sociocultural values and relationships with wildlife, investing in well-being, and implementing species-agnostic approaches to wildlife impact mitigation could improve conservation outcomes in shared landscapes.
明确考虑人类与野生动物共存的社会环境的保护计划，能够产生更有效、更公平的保护措施和成果。然而，社会数据仍未得到充分利用，这通常是因为社会数据被视为非空间数据，或者在分析时采用的方法无法量化不确定性，也无法解决自我报告数据中的偏差问题。我们对肯尼亚-坦桑尼亚边境地区一个多用途地区的177户家庭进行了一项调查（问卷调查）。采用混合方法，我们使用贝叶斯层次模型来量化和绘制当地对非洲象（Loxodonta africana）保护的态度，同时考虑回应偏差，然后将态度模型的推断与对开放式回答的主题分析以及与当地社区共同解读结果相结合，以更深入地了解是什么因素影响了与野生动物共存的人们的态度。模型估计表明，认为大象具有社会文化价值会增加受访者总体上对大象保护持积极态度的可能性（平均增加0.31 [95%可信区间，CrI，0.02 - 0.67]），但经历过任何野生动物物种带来的负面影响会降低受访者对当地大象保护持积极态度的可能性（平均降低 -0.20 [95% CrI -0.42至0.03]）。定性数据显示，与大象对人类生命和生计构成的感知威胁相关的安全和福祉担忧，以及在社区和私人土地上支持保护的激励措施有限，降低了当地积极态度的可能性，并导致了对人象共存的负面看法。我们的空间明确建模方法揭示了保护态度驱动因素的精细尺度变化，可为有针对性的保护规划提供信息。我们的结果表明，专注于维持现有的社会文化价值和与野生动物的关系、投资于福祉以及实施与物种无关的减轻野生动物影响的方法，可以改善共享景观中的保护成果。
