Incorporating opportunity costs in conservation design.

Targeted conservation practices, involving deliberate management decisions applied strategically and efficiently within the landscape to allow maximum environmental benefits, are the prevailing conservation paradigm.  Federally incentivized agricultural conservation programs provide financial incentives for producers to voluntarily alter crop production to foster multiple environmental services.  Explicitly linking programmatic goals, geographic eligibility and practice availability to objectives of national conservation initiatives increases the likelihood of achieving environmental outcomes at regional and national scales. Sophisticated empirically-based decision support tools that incorporate bio-physical processes such as sediment transport, nutrient transport, connectivity, colonization, critical habitat area, biodiversity, population viability, and geneflow are increasingly used to inform conservation design.  These data-informed approaches to practice placement will enhance the efficacy and cost-effectiveness of programs, but leave out the adoption-decision element.  Even well-designed conservation programs can fail to achieve desired outcomes if producer adoption is low.  Conservation adoption is multidimensional, influenced predominantly by time management, profit, and yields. Producers incur opportunity costs of practice adoption, yet these costs are rarely quantified and programmatic incentives are rarely structured around true costs.  McConnell and Burger (2011) described a geospatial decision support tool to guide producers and resource planners in making adoption decisions informed by profitability.  Recent advances in precision agriculture technologies allow more sophisticated spatially-explicit profit determination to accurately characterize opportunity costs, better informing adoption decisions and structuring of practice incentives.   Combining outcomes from nutrient/sediment transport, wildlife habitat value, and profitability in a multiple criteria decision support context would more fully realize the potential of conservation delivery in working landscapes.