Assessing and planning for the climate and biodiversity outcomes of avoided deforestation

Tropical forests are the oldest and most ecologically complex of the planet’s terrestrial ecosystems (Myers 1984). Unsustainable logging, conversion to agriculture and anthropogenic fires caused these biological storehouses to shrink by 5-12 million hectares per year since 1980 (DeFries et al. 2002; FAO 2006, 2010). Unchecked, tropical deforestation could be this century’s biggest driver of biodiversity loss (Laurance 2007a; Pimm & Raven 2000; Whitmore & Sayer 1992). Simultaneously, the degradation and conversion of tropical forests is causing 12-25% of anthropogenic carbon emissions (IPCC 2007; van der Werf et al. 2009). In 2005, at the United Nations climate talks in Montreal, the concept of creating a funding mechanism to provide incentives for reducing emissions from deforestation and forest degradation (REDD) was born. Since then, REDD has grown into one of the most widely supported initiatives within UN climate negotiations (UNFCCC 2009). With global carbon markets forecast to trade US$600 billion by 2013 (SBI 2009), REDD is widely viewed as the best chance to secure a future for tropical forests (Laurance 2008). This thesis draws on decision science, first to assess the capacity for REDD to conserve imperilled biodiversity and second to develop approaches for making smart decisions for REDD implementation. Environmentally harmful subsidies are estimated at $1 trillion annually (van Beers & de Moor 1999), forestry exports from developing countries are worth $39 billion annually (FAO 2007) and a single agricultural commodity, palm oil, from a single country, Indonesia, is worth $4 billion annually (FAO 2007). Can REDD really provide incentives great enough to protect forests from such large and profitable industries? In Chapter 2, I use cost-benefit analyses to determine the financial viability of REDD in 808 agricultural leases slated for conversion to industrial oil palm plantations in Kalimantan, Indonesia. I discover that REDD can compete with oil palm plantations if averted carbon emissions are valued at current market prices. The results demonstrate that REDD is a financially viable land use, even when facing an agricultural crop as profitable as palm oil. Without specific provisions for biodiversity, REDD is likely to protect forests that are most cost-effective for reducing carbon emissions. In Chapter 3, I use a dynamic decision science approach to critically assess how well such forest protection will protect biodiversity at the global scale. I demonstrate spatial trade-offs in allocating funds to protect forests for carbon and biodiversity, and show that cost-effective spending for REDD would protect relatively few species. However, because trade-offs are non-linear, I discover that minor adjustments to the allocation of funds could double the biodiversity protected by REDD, with negligible compromise to carbon outcomes. This chapter demonstrates that though REDD might be well funded, it will not be a silver bullet for biodiversity without some extra effort. As REDD scales up from site based projects to larger landscape-scales, and even national scale programs, making smart decisions about which strategies to implement and where to implement them becomes increasingly difficult. In Chapter 4, I present the first spatially explicit approach to prioritize systematically REDD strategies and locations. I discover that if agricultural expansion is prioritized alongside efforts to reduce emissions, land which is slated for conversion to agriculture can play a much larger role in reducing emissions. Moreover, meeting REDD targets becomes cheaper and agricultural production becomes more efficient. I demonstrate that the decision approach is robust to data quality and that efficient outcomes could be expected even in the situation where only freely available data are used. The approach presents a transparent and defensible method for developing cost-efficient solutions for obtaining the targets set forth by large-scale REDD programs. Actors, such as non-governmental organizations, working to conserve imperilled biodiversity have for several decades served as an integral part of the response to the tropical forest crisis. But, with the emergence of REDD, the tropical forest landscape is rapidly changing. How should biodiversity and REDD actors interact? In Chapter 5, I critically assess for the first time the expected outcomes of three contrasting scenarios of engagement between a biodiversity actor and a REDD actor working in the same region. I discover that if a biodiversity actor acts in ignorance of REDD, meeting their targets is substantially more expensive than necessary. Meeting biodiversity and carbon targets is always cheaper if actors collaborate. However, if the REDD actor has a relatively large budget, the biodiversity actor could benefit even more by free-riding off the REDD actor, which involves shifting biodiversity investments to areas not sufficiently represented by the REDD actor’s conservation network. While good for biodiversity, free-riding leads to a conservation network that costs more overall than one selected collaboratively