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The environmental benefits and costs of conservation policies often vary over space and through time. Accounting for this spatial and temporal heterogeneity has important implications for the potential cost effectiveness of different payment program designs. In this study, we examine the cost efficiency gain from spatial and temporal targeting in payment designs for forest carbon storage in the Central and Southern Appalachian Mountains in the Eastern United States. We run a forest land change model and a carbon simulation model utilizing a panel data on forest land and its competing uses, economic returns, and spatial characteristics for each 1 km2 grid cells in 1992, 2001, 2006 and 2011. A time- and space-specific carbon cost for each individual 1 km2 grid cell is calculated that captures the spatial and temporal heterogeneity in carbon cost efficiency. From there, we compare carbon cost efficiency levels of various payment designs that allow for different degrees of spatial and temporal flexibility. We find that 1) spatial targeting improves carbon cost efficiency, and this efficiency gain is larger as payments become more narrowly targeted, 2) this carbon efficiency gain is present in all market conditions, but is largest in a moderately growing market and smallest in a downturn market, 3) accounting for temporal heterogeneity results in even larger carbon efficiency gains, almost double those from spatial targeting. Just as policies that enable spatial targeting (e.g., auctions) increase cost efficiency savings, so too will policy mechanisms that emphasize budget flexibility through time. These could include utilizing loans or flexible conservation financing, or allowing movement across budgeting categories within a given time period. • Spatial targeting improves the cost efficiency of forest carbon payments. • The narrower the spatial targeting, the larger the efficiency gain. • Efficiency gain is largest in a moderately growing and smallest in a downturn market. • Accounting for temporal heterogeneity double efficiency gains than from spatial targeting. [ABSTRACT FROM AUTHOR]

To help conserve biodiversity in coming decades, protected areas need to be located in places that will be important for species as their ranges shift to track suitable climatic conditions. Had past protected areas been optimally targeted to cover today's biodiversity, then we would expect future coverage to decline. However, past protected area siting was often biased towards higher elevations and, with upslope movements of many species predicted under climate change projections, perhaps future coverage may improve as a result. We examine present and future coverage of species potential ranges by protected areas in the Appalachian Mountains, a critical climate refuge and corridor for the biodiversity of the eastern United States. We parameterize climate niche models using the Maxent algorithm with occurrence records for 258 amphibian, bird, mammal, and reptile species of conservation policy concern that depend on forested habitat. We forecast future range shifts by integrating climate projections from six global circulation models and two representative concentration pathways while making contrasting assumptions about species dispersal. We then examine coverage of the estimated present and future ranges of species by existing protected areas. Most of these policy relevant species (93%) have less than 15% of their present estimated range in the region covered by protected areas. We found that species ranked as high conservation priority would be poorly protected under future climate scenarios. We predicted amphibian and mammal coverages by protected areas would worsen whereas coverages of birds and reptiles improve if species are able to disperse freely to future climatically suitable habitat. If species movements are more restricted, then we predict marked losses of species from protected areas, particularly amphibians and mammals. Our results identify obvious candidate locations for adding new protected areas in places that are currently under-protected and that harbor a high diversity of species across all future climate scenarios we consider. [ABSTRACT FROM AUTHOR]