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Governments across the globe are exploring ways to reduce the environmental and human health impacts created by shale energy production. In active areas, environmental regulations tend to be limited. We apply established instruments to empirically estimated environmental impact abatement cost curves for the development of 56 sites in Pennsylvania, USA. We compare the cost to industry of setting a cap on environmental impacts from land-clearing and building of surface infrastructure under two regulations: cap and trade versus a uniform, inflexible regulation. Greatest differences in cost are achieved when firm-level permits are allocated to reduce market-wide potential impacts by 36%. Cap and trade achieved this cap at a cost of 0.05% of not developing and allowed all development to proceed. The uniform, inflexible regulation cost 32% of not developing for a similar outcome and prevented 18% of firms from developing. Cap and trade's performance depended on the regulator's ability to accurately allocate firm-level permits that reflect developers' options. In extreme cases, inaccurate allocations made cap and trade perform worse than other the approach. We conclude that, where developers differ in their ability and cost of minimizing impacts, cap and trade should be explored as an inexpensive alternative to traditional approaches. [ABSTRACT FROM AUTHOR]

Growing energy demand has increased the need to manage conflicts between energy production and the environment. As an example, shale-gas extraction requires substantial surface infrastructure, which fragments habitats, erodes soils, degrades freshwater systems, and displaces rare species. Strategic planning of shale-gas infrastructure can reduce trade-offs between economic and environmental objectives, but the specific nature of these trade-offs is not known. We estimated the cost of avoiding impacts from land-use change on forests, wetlands, rare species, and streams from shale-energy development within leaseholds. We created software for optimally siting shale-gas surface infrastructure to minimize its environmental impacts at reasonable construction cost. We visually assessed sites before infrastructure optimization to test whether such inspection could be used to predict whether impacts could be avoided at the site. On average, up to 38% of aggregate environmental impacts of infrastructure could be avoided for 20% greater development costs by spatially optimizing infrastructure. However, we found trade-offs between environmental impacts and costs among sites. In visual inspections, we often distinguished between sites that could be developed to avoid impacts at relatively low cost (29%) and those that could not (20%). Reductions in a metric of aggregate environmental impact could be largely attributed to potential displacement of rare species, sedimentation, and forest fragmentation. Planners and regulators can estimate and use heterogeneous trade-offs among development sites to create industry-wide improvements in environmental performance and do so at reasonable costs by, for example, leveraging low-cost avoidance of impacts at some sites to offset others. This could require substantial effort, but the results and software we provide can facilitate the process. [ABSTRACT FROM AUTHOR]

Observations of species occurrences are often used to inform spatial prioritizations for the effective use of limited conservation resources. Additional species observations have the potential to change where a conservation group plans to invest. But by how much? How different would conservation priorities be if planners updated current observations with the information they will have next year?, We sought to address these questions using a 111-year data set that reflects commonly used collection and prioritization practices. We quantify changes in the ranking of Tennessee watersheds brought on by annual additions of species observations made between 1900 and 2010. We ranked watersheds by their complementary contribution to overall species richness. We examine the sensitivity of our results to the number of watersheds prioritized., We expected the effect of new observations to diminish as the data set grew, and we found this to be the case. Importantly, however, additional observations may continue to significantly change conservation priorities in the future if current data collection trends continue., We found that, overall, additional observations can greatly affect priorities and that this result is sensitive to the number of watersheds ranked. Thus, the extent of planning activities moderates the effect of including additional data., Synthesis and applications. Long-term, opportunistically collected data of species locations are commonly used in conservation planning. We find that when using such data, additional species observations significantly affect subsequent priorities. This effect is most pronounced when data are sparse. As such, data collection should be a focus of very early conservation actions in new areas. Even in well-studied areas, however, additional observations may continue to change spatial priorities into the future, and so while data collection can decrease in well-studied areas, it should continue at a lower intensity. Our methods could also be used to determine the balance of data collection and conservation action in a new location. [ABSTRACT FROM AUTHOR]