Xishuangbanna has been largely transformed from biodiverse natural forests and mixed-use farms into monoculture rubber plantations in just twenty years. This conversion has expanded into forests previously protected by the community and onto marginal sites at high-elevation. Market-based ecosystem payments, especially carbon financing, are potential tools to prevent further forest loss in China. Here, we compare rubber net present value (NPV), carbon sequestration, and seed-plant species diversity for Xishuangbanna given three land-use scenarios: Business-As-Usual (BAU), Economic Oriented Scenario (EOS) and Conservation Oriented Scenario (COS) using a previously published spatial map of rubber profitability. The EOS achieved the greatest rubber profit but caused substantial reductions in natural forest area, biodiversity and carbon stocks. The EOS also requires substantial immigration of workers into a remote and ecologically important region with little social infrastructure for basic security, food security, health-care and education, causing frequently ignored costs. As expected, the COS will maintain the highest levels of natural forest area, sequester 57% more carbon, and 71% more biodiversity than EOS. Given the conservation value of the carbon stores and rich biodiversity residing in Xishuangbanna's natural forests, reducing rubber NPV only marginally would probably cost less than attempting to recover these resources. We recommend that rubber plantations be limited to established, productive lowland areas whilst protecting intact high-elevation forest and reforesting low-productivity plantations. These actions will enhance carbon sequestration and biodiversity conservation. Management policies focused solely on profits, like the EOS scenario, will fail to sustain the entire range of natural resources and ecosystem services. The prices in the carbon market would have to be considerably larger than they are currently to compete with the profitability of rubber. (C) 2014 Elsevier Ltd. All rights reserved.
1.Chinese Acad Sci, Kunming Inst Bot, Key Lab Plant Biodivers & Biogeog East Asia KLPB, Kunming 650201, Yunnan, Peoples R China 2.Chinese Acad Sci, Xishuangbanna Trop Bot Garden, Key Lab Trop Forest Ecol, Mengla 666303, Peoples R China 3.East Asia Off, World Agroforestry Ctr, Kunming 650201, Yunnan, Peoples R China 4.Ctr Int Forestry Res CIFOR, Forest & Livelihoods Programme, Bogor 16000, Indonesia 5.Texas Tech Univ, Dept Biol Sci, Lubbock, TX 79409 USA 6.Univ Gottingen, Fac Forest Sci & Forest Ecol, Chair Forest Inventory & Remote Sensing, D-37077 Gottingen, Germany 7.Staffordshire Univ, Dept Geog, Stoke On Trent ST4 2DF, Staffs, England
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