University of Illinois Urbana-Champaign

Mapping the funding landscape for biodiversity conservation in Peru

Nakamura Lam, Katia Sofia

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NAKAMURALAM-THESIS-2017.pdf

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https://hdl.handle.net/2142/98419

Description

Title
Mapping the funding landscape for biodiversity conservation in Peru
Author(s)
Nakamura Lam, Katia Sofia
Issue Date
2017-07-19
Director of Research (if dissertation) or Advisor (if thesis)
Miller, Daniel C.
Committee Member(s)
  • Brazee, Richard
  • Waldron, Anthony
Department of Study
Natural Res & Env Sci
Discipline
Natural Res & Env Sciences
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2017-09-29T17:57:02Z
Keyword(s)
  • Biodiversity
  • Funding
  • Peru
  • Allocation
Abstract
Financial resources are crucial to effective biodiversity conservation. Globally, research shows that conservation-related expenditures are directed towards countries of high biodiversity importance, even as funding flows are well below estimates of financial need. The absence of sufficient funding makes the effective and efficient use of the available resources even more imperative. Empirical evidence on previous funding flows is necessary to develop a baseline for comparison, identification of funding gaps, and assessment of ultimate impacts. To date, however, knowledge of the distribution of funding within countries remains very limited. This study, therefore, analyzes the conservation funding landscape in Peru, a mega-diverse country, to shed light on the nature and trends of support for biodiversity and the factors shaping funding allocation at the sub-national level. I carried out desk-based and field research to collect as much data as possible on conservation finance in Peru from 2009, the year the Peruvian Ministry of the Environment was founded, to 2015, the last year for which full data were available. Information collected covered a range of public and private, domestic and international sources. Overall, I found that 19% of the funding for conservation in Peru derived from domestic sources and 81% from international ones during the study period. Descriptive results indicate that domestic funding was more likely to support strict, biodiversity-focused projects, while international funders exhibited a preference for mixed projects that included both biodiversity and development objectives. I analyzed a subset of the data focused on funding for terrestrial protected areas using remote sensing and econometric methods for the years 2009-2013 with a two-part regression model: ordinary least squares and a logistic regression. The multiple linear regression results show that higher deforestation, higher population density around the PA, higher number of visits, the absence of mining, and a larger PA area were the predictors driving overall funding allocation within the national protected area system. When analyzing domestic funders alone, the presence of more threatened species, more visitors, and a larger area were significantly associated with higher funding. Analysis of international sources showed that more deforestation around a PA, more visitors, and no mining concessions surrounding a PA were the main drivers of funding. Results from logit regression analysis of the decision to fund or not fund PAs in Peru indicates that PAs with larger numbers of threatened species and more deforestation were more likely to receive international funding. These findings provide much-need evidence for scholars, policymakers, and practitioners alike regarding the conservation funding landscape in Peru, including the preferences of different funders and allocation patterns. The evidence and analysis presented in this thesis can inform future research on conservation finance in Peru and beyond as well as more targeted decision-making relating to funding allocation to achieve biodiversity conservation priorities.
Graduation Semester
2017-08
Type of Resource
text
Permalink
http://hdl.handle.net/2142/98419
Copyright and License Information
Copyright 2017 Katia Nakamura Lam

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