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Tag: deforestation

Protected Areas’ Impacts on Brazilian Amazon Deforestation: examining conservation – development interactions to inform planning

Alexander Pfaff, Juan Robalino, Diego Herrera, Catalina Sandoval
PLOS ONE 2015 (forthcoming) DOI:10.1371/journal.pone.0129460

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Protected areas are the leading forest conservation policy for species and ecoservices goals and they may feature in climate policy if countries with tropical forest rely on familiar tools. For Brazil’s Legal Amazon, we estimate the average impact of protection upon deforestation and show how protected areas’ forest impacts vary significantly with development pressure.We use matching, i.e., comparisons that are apples-to-apples in observed land characteristics, to address the fact that protected areas (PAs) tend to be located on lands facing less pressure. Correcting for that location bias lowers our estimates of PAs’ forest impacts by roughly half. Further, it reveals significant variation in PA impacts along development-related dimensions: for example, the PAs that are closer to roads and the PAs closer to cities have higher impact. Planners have multiple conservation and development goals, and are constrained by cost, yet still conservation planning should reflect what our results imply about future impacts of PAs.

 

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Estimating the Impacts of Local Policy Innovation: the synthetic control method applied to tropical deforestation

Erin O. Sills, Diego Herrera, A. Justin Kirkpatrick, Amintas Brandao Jr., Rebecca Dickson, Simon Hall, Subhrendu Pattanayak, David Shoch, Mariana Vedoveto, Luisa Young, Alexander Pfaff
PLOS ONE 2015 (forthcoming) DOI:10.1371/journal.pone.0132590

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Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts’ selection of best case comparisons. The synthetic control method (SCM) offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal “blacklist” that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual) scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012). This demonstrates that SCM can yield  helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and permutations on policies that are implemented in just a few locations.

 

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Evaluating Interactions of Forest Conservation Policies on Avoided Deforestation

Juan Robalino, Catalina Sandoval, David N. Barton, Adriana Chacon, Alexander Pfaff
PLoS ONE 10(4):e0124910 (2015) doi:10.1371/journal.pone.0124910

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We estimate the effects on deforestation that have resulted from policy interactions between parks and payments and between park buffers and payments in Costa Rica between 2000 and 2005. We show that the characteristics of the areas where protected and unprotected lands are located differ significantly. Additionally, we find that land characteristics of each of the policies and of the places where they interact also differ significantly. To adequately estimate the effects of the policies and their interactions, we use matching methods. Matching is implemented not only to define adequate control groups, as in previous research, but also to define those groups of locations under the influence of policies that are comparable to each other. We find that it is more effective to locate parks and payments away from each other, rather than in the same location or near each other. The high levels of enforcement inside both parks and lands with payments, and the presence of conservation spillovers that reduce deforestation near parks, significantly reduce the potential impact of combining these two policies.

 

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Paper Park Performance: Mexico’s Natural Protected Areas in the 1990s

Allen Blackman, Alexander Pfaff, Juan Robalino
Global Environmental Change 31 (2015) pp50-61

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Although developing countries have established scores of new protected areas over the past three decades, they often amount to little more than ‘‘paper parks’’ that are chronically short of the financial, human, and technical resources needed for effective management. It is not clear whether and how severely under-resourced parks affect deforestation. In principle, they could either stem it by, for example, creating an expectation of future enforcement, or they could spur it by, for example, creating open access regimes. We examine the effect of Mexico’s natural protected areas (NPAs) on deforestation from 1993 to 2000, a period when forest clearing was rampant and the vast majority of protected areas had negligible resources or management. We use high-resolution satellite data to measure deforestation and (covariate and propensity score) matching to control for NPAs’ nonrandom siting and for spillovers. Our broad finding is that Mexico’s paper parks had heterogeneous effects both inside and outside their borders. More specifically, at the national-level, we cannot reject the null hypothesis that NPAs had zero average effect on clearing inside their borders, nor can we reject a similar hypothesis for spillover clearing outside their borders. However, we can detect statistically and economically significant inside- and outside-NPA effects for certain geographic regions. Moreover, these effects have different signs depending on the region. Finally, we find that NPAs with certain characteristics were more effective at stemming deforestation inside their borders, namely, those that were large, new, mixed use, and relatively well-funded. Taken together, these results suggest that paper parks have the potential to either reduce or exacerbate tropical deforestation and highlight the need for further research on the conditions that lead to each outcome.

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Evolving Protected-Areas Impacts in Panama: impact shifts show that plans require anticipation

Akiko Haruna, Alexander Pfaff, Sander van den Ende, Lucas Joppa
Environmental Research Letters 9 (2014)

PDF link iconProtected areas (PAs) are the leading forest conservation policy, so accurate evaluation of future PA impact is critical in conservation planning. Yet by necessity impact evaluations use past data. Here we argue that forwardlooking plans should blend such evaluations with anticipation of shifts in threats. Applying improved methods to evaluate past impact, we provide rigorous support for that conceptual approach by showing that PAs’ impacts on deforestation shifted with land use. We study the Republic of Panama, where species-dense tropical forest faces real pressure. Facing variation in deforestation pressure, the PAs’ impacts varied across space and time. Thus, if shifts in pressure levels and patterns could be anticipated, that could raise impact.

 

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Realistic REDD: Improving the Forest Impacts of Domestic Policies in Different Settings

Alexander Pfaff, Gregory S. Amacher, Erin O. Sills
Review of Environmental Economics and Policy, volume 7, issue 1, winter 2013, pp. 114–135 doi:10.1093/reep/res023

PDF link iconThis article, which is part of a symposium on the economics of REDD, identifies three common settings for forest loss involving different types of decision-making agents that operate under different markets and institutions. That suggests using different theoretical frameworks for these three settings, which in turn generates different predictions concerning policies’ impacts. The first model, “producer profit maximization given market integration,” has been applied to many private decisions about the best locations for profitable land uses, such as agriculture and forest. Its predictions have been widely studied empirically, beginning no later than von Thunen (1826). The second model, “rural household optimization given incomplete markets and household heterogeneity,” has been applied to more isolated settings featuring high transactions costs that yield incomplete integration of households in input and output markets. Its policy impact predictions have been tested with surveys at household and village levels. In the third model, “public optimization given production and corruption responses by private firms,” a public agency determines public forest access by balancing public goods, public revenue needs, and private rents to award concessions. There is potential for corruption, and the decisions may be affected by decentralization. This model’s predictions can be tested using observed policies. We find that past policies rarely addressed the incentives driving forest loss effectively. This helps to explain the limited impact of past policies on deforestation and forest degradation. It also suggests directions for the design of future policies. In sum, the theory and the evidence suggest that REDD success requires an understanding of all the incentives that drive forest loss, so that domestic policy can be tailored to specific settings (i.e., relevant agents and institutions).

 

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