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Entry Points for Considering Ecosystem Services within Infrastructure Planning: how to integrate conservation with development in order to aid them both

Lisa Mandle, Benjamin P. Bryant, Mary Ruckelshaus, Davide Geneletti, Joseph M. Kiesecker, Alexander Pfaff
Conservation Letters 2015 (online 9/28, doi 10.1111/conl.12201)

PDF link iconNew infrastructure is needed globally to support economic development and improve human well-being. Investments that do not consider ecosystem services (ES) can eliminate these important societal benefits from nature, undermining the development benefits infrastructure is intended to provide. Such tradeoffs are acknowledged conceptually but in practice have rarely been considered in infrastructure planning. Taking road investments as one important case, here we examine where and what forms of ES information have the potential to meaningfully influence decisions by multilateral development banks (MDBs). Across the stages of a typical road development process, we identify where and how ES information could be integrated, likely barriers to the use of available ES information, and key opportunities to shift incentives and thereby practice. We believe inclusion of ES information is likely to provide the greatest development benefit in early stages of infrastructure decisions. Those strategic planning stages are typically guided by in-country processes, with MDBs playing a supporting role, making it critical to express the ES consequences of infrastructure development using metrics relevant to government decision makers. This approach requires additional evidence of the in-country benefits of cross-sector strategic planning and more tools to lower barriers to quantifying these benefits and facilitating ES inclusion.


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).


Protecting forests, biodiversity, and the climate: predicting policy impact to improve policy choice

Alexander Pfaff, Juan Robalino
Oxford Review of Economic Policy, Volume 28, Number 1, 2012, pp. 164–179

PDF link iconPolicies must balance forest conservation’s local costs with its benefits—local to global—in terms of biodiversity, the mitigation of climate change, and other eco-services such as water quality. The trade-offs with development vary across forest locations. We argue that considering location in three ways helps to predict policy impact and improve policy choice: (i) policy impacts vary by location because baseline deforestation varies with characteristics (market distances, slopes, soils, etc.) of locations in a landscape; (ii) different mixes of political-economic pressures drive the location of different policies; and (iii) policies can trigger ‘second-order’ or ‘spillover’ effects likely to differ by location. We provide empirical evidence that suggests the importance of all three considerations, by reviewing highquality evaluations of the impact of conservation and development on forest. Impacts of well-enforced conservation rise with private clearing pressure, supporting (i). Protection types (e.g. federal/state) differ in locations and thus in impacts, supporting (ii). Differences in development process explain different signs for spillovers, supporting (iii).


Policy Impacts on Deforestation: Lessons Learned from Past Experiences to Inform New Initiatives

Alexander Pfaff, Erin O. Sills, Gregory S. Amacher, Michael J. Coren, Kathleen Lawlor, Charlotte Streck
Report from the Nicholas Institute for Environmental Policy Solutions, Duke University (with the support of the Packard Foundation)

PDF link iconNational and international efforts within the last few decades to reduce forest loss, while having some impact, have failed to substantially slow the loss of the world’s forests. Forest loss, i.e., deforestation and forest degradation, is widespread and accounts for 12%–17% of the world’s greenhouse gas (GHG) emissions. Global concern about climate change and the realization that reduced emissions from deforestation and degradation (REDD) can play a role in climate change mitigation make it critical to learn from our past experiences with policies to reduce forest loss. Within the UN Framework Convention on Climate Change (UNFCCC), negotiators are actively considering ways to include incentives for REDD and other forest carbon activities in any post-2012 treaty. In parallel, the U.S. Congress is developing proposals for a long-term climate policy that includes incentives for REDD, and possibly other international forest carbon activities. Such policies may mobilize new funds for forest conservation, including for addressing drivers of deforestation and forest degradation in developing countries. Climate-related incentives for REDD are likely to be performance-based, i.e., to emphasize the measurement, reporting, and verification of all results. The implementation of this emphasis, alongside the introduction of new financial incentives, could increase such policies’ impacts on forest loss relative to the past. Policy effectiveness, efficiency, and equity can increase if we learn lessons from the past about what drives and what inhibits deforestation and degradation. It is in the interest of any REDD program to understand what has worked in reducing deforestation and degradation and what has not, as well as the reasons for observed differences in outcomes. Investments and policies can then more effectively embrace and extend success while reducing risks of further failures. This report aims to provide lessons to inform U.S. and international policymakers by analyzing dominant influences on deforestation and degradation. We study not only forest-focused policies, but also other policies that directly or indirectly influence forest loss, all in light of relevant nonpolicy factors such as trends in commodity prices. We provide examples of previous policies to draw lessons from successes and failures, then link those observations about the past to the decisions current policymakers must soon make within ongoing climate policy deliberations.


Global protected area impacts

Lucas N. Joppa, Alexander Pfaff
Proceedings of the Royal Society B 2010 doi:10.1098/rspb.2010.1713

PDF link iconProtected areas (PAs) dominate conservation efforts. They will probably play a role in future climate policies too, as global payments may reward local reductions of loss of natural land cover. We estimate the impact of PAs on natural land cover within each of 147 countries by comparing outcomes inside PAs with outcomes outside. We use ‘matching’ (or ‘apples to apples’) for land characteristics to control for the fact that PAs very often are non-randomly distributed across their national landscapes. Protection tends towards land that, if unprotected, is less likely than average to be cleared. For 75 per cent of countries, we find protection does reduce conversion of natural land cover. However, for approximately 80 per cent of countries, our global results also confirm (following smaller-scale studies) that controlling for land characteristics reduces estimated impact by half or more. This shows the importance of  controlling for at least a few key land characteristics. Further, we show that impacts vary considerably within a country (i.e. across a landscape): protection achieves less on lands far from roads, far from cities and on steeper slopes. Thus, while planners are, of course, constrained by other conservation priorities and costs, they could target higher impacts to earn more global payments for reduced deforestation.


Indigenous Lands, Protected Areas, and Slowing Climate Change

Taylor H. Ricketts, Britaldo Soares-Filho, Gustavo A.B. da Fonseca, Daniel Nepstad, Alexander Pfaff, Annie Petsonk, Anthony Anderson, Doug Boucher, Andrea Cattaneo, Marc Conte, Ken Creighton, Lawrence Linden, Claudio Maretti, Paulo Moutinho, Roger Ullman, Ray Victurine
PLoS Biol 2010 8(3): e1000331. doi:10.1371/journal.pbio.1000331

PDF link iconForest clearing and degradation account for roughly 15% of global greenhouse gas emissions, more than all the cars, trains, planes, ships, and trucks on earth. This is simply too big a piece of the problem to ignore; fail to reduce it and we will fail to stabilize our climate. Although the recent climate summit in Copenhagen failed to produce a legally binding treaty, the importance of forest conservation in mitigating climate change was a rare point of agreement between developed and developing countries and is emphasized in the resulting Copenhagen Accord. Language from the meeting calls for developing countries to reduce emissions from deforestation and degradation (nicknamed REDD), and for wealthy nations to compensate them for doing so. For REDD to succeed, forest nations must develop policies and institutions to reduce and eventually eliminate forest clearing and degradation. One of the most straightforward components of such a program is also one of the oldest and most reliable tricks in the conservation book: protected areas. Indigenous lands and other protected areas (hereafter ILPAs)— created to safeguard land rights, indigenous livelihoods, biodiversity, and other values— contain more than 312 billion tons of carbon (GtC). Crucially, and paradoxically, this ‘‘protected carbon’’ is not entirely protected. While ILPAs typically reduce rates of deforestation compared to surrounding areas, deforestation (with resulting greenhouse gas [GHG] emissions) often continues within them, especially inside those that lack sufficient funding, management capacity, or political backing. These facts suggest an attractive but overlooked opportunity to reduce GHG emissions: creating new ILPAs and strengthening existing ones. Here, we evaluate the case for this potential REDD strategy. We focus on the Amazon basin given its importance for global biodiversity, its enormous carbon stocks, and its advanced network of indigenous lands and other protected areas.

Reassessing the forest impacts of protection: The challenge of nonrandom location and a corrective method

Lucas Joppa, Alexander Pfaff
Ann. N.Y. Acad. Sci. 1185 (2010) 135–149

PDF link iconProtected areas are leading tools in efforts to slow global species loss and appear also to have a role in climate change policy. Understanding their impacts on deforestation informs environmental policies. We review several approaches to evaluating protection’s impact on deforestation, given three hurdles to empirical evaluation, and note that “matching” techniques fromeconomic impact evaluation address those hurdles. The central hurdle derives from the fact that protected areas are distributed nonrandomly across landscapes.Nonrandom location can be intentional, and for good reasons, including biological and political ones. Yet even so, when protected areas are biased in their locations toward less-threatened areas, many methods for impact evaluationwill overestimate protection’s effect. The use ofmatching techniques allows one to control for known landscape biases when inferring the impact of protection. Applications of matching have revealed considerably lower impact estimates of forest protection than produced by other methods. A reduction in the estimated impact from existing parks does not suggest, however, that protection is unable to lower clearing. Rather, it indicates the importance of variation across locations in how much impact protection could possibly have on rates of deforestation.Matching, then, bundles improved estimates of the average impact of protection with guidance on where new parks’ impacts will be highest.While many factors will determine where new protected areas will be sited in the future, we claim that the variation across space in protection’s impact on deforestation rates should inform site choice.


High and Far: Biases in the Location of Protected Areas

Lucas N. Joppa, Alexander Pfaff
PLoS ONE 2009 4(12): e8273. doi:10.1371/journal.pone.0008273

PDF link iconBackground: About an eighth of the earth’s land surface is in protected areas (hereafter ‘‘PAs’’), most created during the 20th century. Natural landscapes are critical for species persistence and PAs can play a major role in conservation and in climate policy. Such contributions may be harder than expected to implement if new PAs are constrained to the same kinds of locations that PAs currently occupy.

Methodology/Principal Findings: Quantitatively extending the perception that PAs occupy ‘‘rock and ice’’, we show that across 147 nations PA networks are biased towards places that are unlikely to face land conversion pressures even in the absence of protection. We test each country’s PA network for bias in elevation, slope, distances to roads and cities, and suitability for agriculture. Further, within each country’s set of PAs, we also ask if the level of protection is biased in these ways. We find that the significant majority of national PA networks are biased to higher elevations, steeper slopes and greater distances to roads and cities. Also, within a country, PAs with higher protection status are more biased than are the PAs with lower protection statuses.

Conclusions/Significance: In sum, PAs are biased towards where they can least prevent land conversion (even if they offer perfect protection). These globally comprehensive results extend findings from nation-level analyses. They imply that siting rules such as the Convention on Biological Diversity’s 2010 Target [to protect 10% of all ecoregions] might raise PA impacts if applied at the country level. In light of the potential for global carbon-based payments for avoided deforestation or REDD, these results suggest that attention to threat could improve outcomes from the creation and management of PAs.


Behavior, Environment, and Health in Developing Countries: evaluation and valuation

Subhrendu Pattanayak, Alexander Pfaff
Annual Review of Resource Economics (2009) 1:183–217

PDF link iconWe consider health and environmental quality in developing countries, where limited resources constrain behaviors that combat enormously burdensome health challenges. We focus on four huge challenges that are preventable (i.e., are resolved in rich countries). We distinguish them as special cases in a general model of household behavior, which is critical and depends on risk information. Simply informing households may achieve a lot in the simplest challenge (groundwater arsenic); yet, for the three infectious situations discussed (respiratory, diarrhea, and malaria), community coordination and public provision may also be necessary. More generally, social interactions may justify additional policies. For each situation, we discuss the valuation of private spillovers (i.e., externalities) and evaluation of public policies to reduce environmental risks and spillovers. Finally, we reflect on open questions in our model and knowledge gaps in the empirical literature including the challenges of scaling up and climate change.