In pursuit of socioeconomic development, many countries are expanding oil and mineral extraction into tropical forests. These activities seed access to remote, biologically rich areas, thereby endangering global biodiversity. We examined how protection of biodiversity and economic revenues can be balanced in biologically valuable regions. Using spatial data on oil profits and predicted species and ecosystem extents, we optimized the protection of 741 terrestrial species and 20 ecosystems of the Ecuadorian Amazon across a range of opportunity costs (i.e., sacrifices of extractive profit). We also applied spatial statistics to remotely sensed, historic deforestation data to focus the optimization on areas most threatened by imminent forest loss. Giving up 5% of a year's oil profits (US$221 million) allowed for a protected area network that retained an average of 65% of the extent of each species and ecosystem. This performance far exceeded that of the network produced by simple optimization for land area (which required a sacrifice of approximately 40% of annual oil profits [US$1.7 billion]) and used only marginally less land to achieve equivalent levels of ecological protection. We identified what we call emergency conservation targets: regions that are essential components of a cost-effective conservation reserve network but at imminent risk of destruction, thus requiring urgent and effective protection. Governments can use our methods when evaluating extractive-led development options to responsibly manage the associated ecological and economic trade-offs and protect natural capital.