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The Effect of Wildlife Conservation on Local Perceptions of Risk and Behavioral Response

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Abstract

In this study, we examine the effect of Tarangire National Park (TNP) on local perceptions of risk and how these perceptions may influence behavioral responses. Data were collected during 2004–2005 through household surveys and participatory risk mapping (PRM) in eight villages east of TNP. By identifying and rank-ordering respondents’ perceived risks, PRM enhances understanding of the nature and variation of risks faced within a population by distinguishing between the incidence and severity of subjective risk perceptions. Results indicate that proximity to the park has a strong effect on the type and severity of perceived risks. Within villages close to the park, however, behavioral response to perceived risks varies considerably. This study contributes to an appreciation of how behavioral response to environmental and socioeconomic factors is mediated by human perception.

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Notes

  1. The term “contextual environment” is used here to refer to the social, economic, political, and ecological environment which provides the context in which households make decisions.

  2. While a few widowed women were interviewed, household heads were generally men and therefore the sample reflects a strong gender bias.

  3. In the case of a small sample, non-random sampling (esp. controlled sampling) may be better than random sampling at including small groups within the larger population - groups than may be lost with a strictly random sample (Bilsborrow RE, 2009, personal communication).

  4. Originally Smith and et al. (2000) set highest severity equal to 1 and lowest severity equal to 2. We rescaled this from 0 to 1 according to their follow-up paper (Smith et al. 2001). We did this to orient the risk maps in a more intuitive way and to facilitate logistic regression analyses.

  5. For example, if a respondent ranked one or more of the four park related risks (see Table 2) as either no. 1 or no. 2 on his ranking of perceived risks, he was coded 1 for the first set of models. If not, he was coded 0. This same logic applies for non-park related risks in the second set of models.

  6. Several measures of wealth were examined here including total herd size, land holdings, agricultural yields (including per capita measures of these), source of income, and total household size (see McCabe 2004). Only the composite measure of wealth described above yielded any significant results.

  7. To improve clarity on the risk maps, some very low incidence points are deliberately omitted. In this analysis we focus on high incidence risks.

  8. With this arrangement, local Maasai retain tenure privileges for all the land (which amount to 100 year leases from the government) and sharecroppers, having already provided payment in the form of tractor services, retain all the proceeds from the sale of their harvest.

  9. We might expect perceived wildlife-related risks in the villages near the park even if the park was not there as these are the areas where wildlife would normally congregate.

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Baird, T.D., Leslie, P.W. & McCabe, J.T. The Effect of Wildlife Conservation on Local Perceptions of Risk and Behavioral Response. Hum Ecol 37, 463–474 (2009). https://doi.org/10.1007/s10745-009-9264-z

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