Peer-reviewed publications

Community-based natural resource management (CBNRM) is a major global strategy for enhancing conservation outcomes while also seeking to improve rural livelihoods; however, little evidence of socioeconomic outcomes exists. We present a national-level analysis that empirically estimates socioeconomic impacts of CBNRM across Tanzania, while systematically controlling for potential sources of bias. Specifically, we apply a difference-in-differences model to national-scale, cross-sectional data to estimate the impact of three different CBNRM governance regimes on wealth, food security and child health, considering differential impacts of CBNRM on wealthy and poor populations. We also explore whether or not longer-standing CBNRM efforts provide more benefits than recently-established CBNRM areas. Our results show significant improvements in household food security in CBNRM areas compared with non-CBNRM areas, but household wealth and health outcomes in children are generally not significantly different. No one CBNRM governance regime demonstrates consistently different welfare outcomes than the others. Wealthy households benefit more from CBNRM than poor households and CBNRM benefits appear to increase with longer periods of implementation. Perhaps evidence of CBNRM benefits is limited because CBNRM hasn’t been around long enough to yield demonstrable outcomes. Nonetheless, achieving demonstrable benefits to rural populations will be crucial for CBNRM’s future success in Tanzania.

The US Endangered Species Act (ESA) regulates what landowners and land managers can do on lands occupied by listed species. The act does this in part through the designation of habitat areas considered critical to the recovery of listed species. Critics have argued that the designation of critical habitat (CH) has substantial economic impacts on landowners above and beyond the costs associated with listing in general. Here we examine the effects of CH designation on land cover change from 1992 to 2011 in areas subject to ESA regulations. We find that, on average, the rate of change in developed land (urban and residential) and agricultural land is not significantly affected by CH designation. In addition, our estimate of the effects of CH designation is not strongly correlated with the costs of CH as predicted by economic analyses published in the Federal Register. While CH designation, on average, does not affect the overall rates of land cover change, CH designation does appear to modify the impact of land cover change drivers. Generally, land prices had more impact (statistically) on land cover decisions within CH areas than in areas subject to ESA regulations but with no CH designation. Land cover decisions in these latter areas tended to be driven more by clustering and land availability concerns. These trends suggest that CH designation has increased landowner uncertainty and that conversion to developed and agricultural use in CH areas, on average, requires a return premium. Overall, however, this different reaction to land prices in and outside of CH areas has not been strong enough to differentiate the average rates of developed or agricultural land change in CH areas versus areas subject to ESA regulations but with no CH designation.

The recent report from the Secretariat of the Convention on Biological Diversity [(2010) Global Biodiversity Outlook 3] acknowledges that ongoing biodiversity loss necessitates swift, radical action. Protecting undisturbed lands, although vital, is clearly insufficient, and the key role of unprotected, private land owned is being increasingly recognized. Seeking to avoid common assumptions of a social planner backed by government interventions, the present work focuses on the incentives of the individual landowner. We use detailed data to show that successful conservation on private land depends on three factors: conservation effectiveness (impact on target species), private costs (especially reductions in production), and private benefits (the extent to which conservation activities provide compensation, for example, by enhancing the value of remaining production). By examining the high-profile issue of palm-oil production in a major tropical biodiversity hotspot, we show that the levels of both conservation effectiveness and private costs are inherently spatial; varying the location of conservation activities can radically change both their effectiveness and private cost implications. We also use an economic choice experiment to show that consumers' willingness to pay for conservation-grade palm-oil products has the potential to incentivize private producers sufficiently to engage in conservation activities, supporting vulnerable International Union for Conservation of Nature Red Listed species. However, these incentives vary according to the scale and efficiency of production and the extent to which conservation is targeted to optimize its cost-effectiveness. Our integrated, interdisciplinary approach shows how strategies to harness the power of the market can usefully complement existing—and to-date insufficient—approaches to conservation.

The central challenge of the 21st century is to develop economic, social, and governance systems capable of ending poverty and achieving sustainable levels of population and consumption while securing the life-support systems underpinning current and future human well-being. Essential to meeting this challenge is the incorporation of natural capital and the ecosystem services it provides into decision-making. We explore progress and crucial gaps at this frontier, reflecting upon the 10 y since the Millennium Ecosystem Assessment. We focus on three key dimensions of progress and ongoing challenges: raising awareness of the interdependence of ecosystems and human well-being, advancing the fundamental interdisciplinary science of ecosystem services, and implementing this science in decisions to restore natural capital and use it sustainably. Awareness of human dependence on nature is at an all-time high, the science of ecosystem services is rapidly advancing, and talk of natural capital is now common from governments to corporate boardrooms. However, successful implementation is still in early stages. We explore why ecosystem service information has yet to fundamentally change decision-making and suggest a path forward that emphasizes: (i) developing solid evidence linking decisions to impacts on natural capital and ecosystem services, and then to human well-being; (ii) working closely with leaders in government, business, and civil society to develop the knowledge, tools, and practices necessary to integrate natural capital and ecosystem services into everyday decision-making; and (iii) reforming institutions to change policy and practices to better align private short-term goals with societal long-term goals.

Biodiversity conservation, as an environmental goal, is increasingly recognized to be connected to the socioeconomic well-being of local communities. The development of a widespread community-based natural resource management (CBNRM) program in Namibia makes it an ideal location to analyze the connection between conservation and socioeconomic well-being of local communities. Namibia’s CBNRM program involves the formation of communal conservancies within rural communities and previous studies have found it to be successful on both ecological and economic fronts. In order to broaden the understanding of the program’s impact to include social factors, we have conducted a comparative analysis to determine the effects of this program on household welfare outcomes. Data from two rounds of the Namibia Demographic and Health Surveys (2000 and 2006/07) and quasi-experimental statistical methods were used to evaluate changes in various health, education and wealth outcomes of those living in conservancies, relative to non-conservancy comparison groups. Regression results indicate mixed effects of the conservancy program at the household level. The program had positive effects on some health outcome variables, including bednet ownership, which was twice as likely to increase over time in conservancy compared to non-conservancy households. Program impacts were negative for education outcomes, with the proportion of school attendance of conservancy children being 45% less likely to increase over time than non-conservancy children. Wealth outcome results were inconclusive. Our findings highlight the importance of analyzing community conservation programs at a variety of scales when evaluating overall impact, as community-level benefits may not necessarily extend down to the household level (and vice versa).

How often do people visit the world’s protected areas (PAs)? Despite PAs covering one-eighth of the land and being a major focus of nature-based recreation and tourism, we don’t know. To address this, we compiled a globally-representative database of visits to PAs and built region-specific models predicting visit rates from PA size, local population size, remoteness, natural attractiveness, and national income. Applying these models to all but the very smallest of the world’s terrestrial PAs suggests that together they receive roughly 8 billion (8 x 109) visits/y—of which more than 80% are in Europe and North America. Linking our region-specific visit estimates to valuation studies indicates that these visits generate approximately US $600 billion/y in direct in-country expenditure and US $250 billion/y in consumer surplus. These figures dwarf current, typically inadequate spending on conserving PAs. Thus, even without considering the many other ecosystem services that PAs provide to people, our findings underscore calls for greatly increased investment in their conservation.

The Sunda Banda Seascape (SBS), located in the center of the Coral Triangle, is a global center of marine biodiversity and a conservation priority. We proposed the first biophysical environmental delineation of the SBS using globally available satellite remote sensing and model-assimilated data to categorize this area into unique and meaningful biophysical classes. Specifically, the SBS was partitioned into eight biophysical classes characterized by similar sea surface temperature, chlorophyll a concentration, currents, and salinity patterns. Areas within each class were expected to have similar habitat types and ecosystem functions. Our work supplemented prevailing global marine management schemes by focusing in on a regional scale with finer spatial resolution. It also provided a baseline for academic research, ecological assessments and will facilitate marine spatial planning and conservation activities in the area. In addition, the framework and methods of delineating biophysical environments we presented can be expanded throughout the whole Coral Triangle to support research and conservation activities in this important region.

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.

To implement the REDD+ mechanism (Reducing Emissions for Deforestation and Forest Degradation, countries need to prioritize areas to combat future deforestation CO2 emissions, identify the drivers of deforestation around which to develop mitigation actions, and quantify and value carbon for financial mechanisms. Each comes with its own methodological challenges, and existing approaches and tools to do so can be costly to implement or require considerable technical knowledge and skill. Here, we present an approach utilizing a machine learning technique known as Maximum Entropy Modeling (Maxent) to identify areas at high deforestation risk in the study area in Madre de Dios, Peru under a business-as-usual scenario in which historic deforestation rates continue. We link deforestation risk area to carbon density values to estimate future carbon emissions. We quantified area deforested and carbon emissions between 2000 and 2009 as the basis of the scenario.

Ecosystem Service Assessments (ESAs) have become a popular tool for science-based policy. Yet, there are few guidelines for developing an ESA to inform a decision-making process. This is an important area of inquiry since the process of conducting an ESA is likely to affect the quality of results and their influence on decisions. Drawing on the lessons of conducting ESAs around the world, we propose a set of enabling conditions and a framework for carrying out ESAs that foster high-quality results and drive action. Our framework includes an emphasis on iterative stakeholder engagement, advancing science to address policy needs, and capacity-building through six general steps: (1) scope the process, (2) collect and compile data, (3) develop scenarios, (4) analyze ecosystem services, (5) synthesize results, and (6) communicate knowledge. Our experience indicates that using this framework to conduct an ESA can generate policy-relevant science and enhance uptake of information about nature’s benefits in decisions.