Alexander Pfaff

Measuring the effectiveness of protected area networks in reducing deforestation.

Global efforts to reduce tropical deforestation rely heavily on the establishment of protected areas. Measuring the effectiveness of these areas is difficult because the amount of deforestation that would have occurred in the absence of legal protection cannot be directly observed. Conventional methods of evaluating the effectiveness of protected areas can be biased because protection is not randomly assigned and because protection can induce deforestation spillovers (displacement) to neighboring forests. We demonstrate that estimates of effectiveness can be substantially improved by controlling for biases along dimensions that are observable, measuring spatial spillovers, and testing the sensitivity of estimates to potential hidden biases. We apply matching methods to evaluate the impact on deforestation of Costa Ricas renowned protected-area system between 1960 and 1997. We find that protection reduced deforestation: approximately 10% of the protected forests would have been deforested had they not been protected. Conventional approaches to evaluating conservation impact, which fail to control for observable covariates correlated with both protection and deforestation, substantially overestimate avoided deforestation (by over 65%, based on our estimates). We also find that deforestation spillovers from protected to unprotected forests are negligible. Our conclusions are robust to potential hidden bias, as well as to changes in modeling assumptions. Our results show that, with appropriate empirical methods, conservation scientists and policy makers can better understand the relationships between human and natural systems and can use this to guide their attempts to protect critical ecosystem services.

High and far: biases in the location of protected areas.

Background About an eighth of the earths 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 countrys PA network for bias in elevation, slope, distances to roads and cities, and suitability for agriculture. Further, within each countrys 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 Diversitys 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.

Global protected area impacts

Protected 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.

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

Protected 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 protections impact on deforestation, given three hurdles to empirical evaluation, and note that “matching” techniques from economic 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 evaluation will overestimate protections effect. The use of matching 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 protections impact on deforestation rates should inform site choice.

Road Investments, Spatial Spillovers, And Deforestation In The Brazilian Amazon

Understanding the impact of road investments on deforestation is part of a complete evaluation of the expansion of infrastructure for development. We find evidence of spatial spillovers from roads in the Brazilian Amazon: deforestation rises in the census tracts that lack roads but are in the same county as and within 100 km of a tract with a new paved or unpaved road. At greater distances from the new roads the evidence is mixed, including negative coefficients of inconsistent significance between 100 and 300 km, and if anything, higher neighbor deforestation at distances over 300 km.

CARBON DYNAMICS AND LAND-USE CHOICES: BUILDING A REGIONAL-SCALE MULTIDISCIPLINARY MODEL

Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over 50 years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.

Indigenous Lands, Protected Areas, and Slowing Climate Change

Recent climate talks in Copenhagen reaffirmed the crucial role of reducing emissions from deforestation and degradation (REDD). Creating and strengthening indigenous lands and other protected areas represents an effective, practical, and immediate REDD strategy that addresses both biodiversity and climate crises at once.

Effective and Equitable Dissemination of Seasonal-to-Interannual Climate Forecasts: policy implications from the Peruvian fishery during El Niño 1997-98

The development of seasonal-to-interannual climate predictions has spurred widespread claims that the dissemination of such forecasts will yield benefits for society. Based on the use as well as non-use of forecasts in the Peruvian fishery during the 1997–98 El Niño event, weidentify: (1) potential constraints on the realization of benefits, such aslimited access to and understanding of information, and unintended reactions; (2) theneed for an appropriately detailed definition of societal benefit, considering whose welfare counts as a benefit among groups such as labor, industry, consumers, citizens of different regions, and future generations.We argue that consideration of who benefits, and an understanding of potential socioeconomic constraints and how they might be addressed, should be brought to bear on forecast dissemination choices. We conclude with examples of relevant dissemination choices made using this process.

The Kyoto protocol and payments for tropical forest: an interdisciplinary method for estimating carbon-offset supply and increasing the feasibility of a carbon market under the CDM.

Abstract Protecting tropical forests under the Clean Development Mechanism (CDM) could reduce the cost of emissions limitations set in Kyoto. However, while society must soon decide whether or not to use tropical forest-based offsets, evidence regarding tropical carbon sinks is sparse. This paper presents a general method for constructing an integrated model (based on detailed historical, remote sensing and field data) that can produce land-use and carbon baselines, predict carbon sequestration supply to a carbon-offsets market and also help to evaluate optimal market rules. Creating such integrated models requires close collaboration between social and natural scientists. Our project combines varied disciplinary expertise (in economics, ecology and geography) with local knowledge in order to create high-quality, empirically grounded, integrated models for Costa Rica.

Reduction in Urinary Arsenic Levels in Response to Arsenic Mitigation Efforts in Araihazar, Bangladesh

Background There is a need to identify and evaluate an effective mitigation program for arsenic exposure from drinking water in Bangladesh. Objective We evaluated the effectiveness of a multifaceted mitigation program to reduce As exposure among 11,746 individuals in a prospective cohort study initiated in 2000 in Araihazar, Bangladesh, by interviewing participants and measuring changes in urinary As levels. Methods The interventions included a) person-to-person reporting of well test results and health education; b) well labeling and village-level health education; and c) installations of 50 deep, low-As community wells in villages with the highest As exposure. Results Two years after these interventions, 58% of the 6,512 participants with unsafe wells (As ≥50 μg) at baseline had responded by switching to other wells. Well labeling and village-level health education was positively related to switching to safe wells (As < 50 μg/L) among participants with unsafe wells [rate ratio (RR) = 1.84; 95% confidence interval (CI), 1.60–2.11] and inversely related to any well switching among those with safe wells (RR = 0.80; 95% CI, 0.66–0.98). The urinary As level in participants who switched to a well identified as safe (< 50 μg As/L) dropped from an average of 375 μg As/g creatinine to 200 μg As/g creatinine, a 46% reduction toward the average urinary As content of 136 μg As/g creatinine for participants that used safe wells throughout. Urinary As reduction was positively related to educational attainment, body mass index, never-smoking, absence of skin lesions, and time since switching (p for trend < 0.05). Conclusions Our study shows that testing of wells and informing households of the consequences of As exposure, combined with installation of deep community wells where most needed, can effectively address the continuing public health emergency from arsenic in drinking water in Bangladesh.