Over the last 100 years, agriculture has made many strides in the development of more sustainable production practices both in the United States and worldwide, but there are still great needs and opportunities for further progress. Current production methods externalize environmental costs to the detriment of the natural resource base that sustains agricultural systems. These externalities also increase the costs of production. Agriculture must increase productive capacity to provide rapidly escalating societal needs for food, feed, fuel, and fiber while simultaneously adapting to the impacts of climate change, population growth, dwindling freshwater resources, impaired soil health, greater demand for meat products in the developing world, and increasing land degradation. To achieve these goals, we need a dynamic analysis approach to conservation planning that allows us to more realistically evaluate management practices, understanding that adaptation will necessarily be a continuous process. Here, the word “dynamic” is used in the sense of “constant change,” with an additional nod to the complexity and nonlinearity of many of the physical and agroecological processes involved. This book offers tools that will facilitate such a dynamic approach to conservation planning, detailing a number of useful observational, computational, modeling, and analysis approaches on the “physical” side of the problem. These can then be linked with comparable tools from the “living” side of the problem, incorporating considerations such as the importance of microbial contributions to soil function, competitive plant pressures, and pest adaptations under a changing climate to develop more robust management tools. Each use of such a dynamic system would employ the relevant components for a given location and conservation planning application. But first, the physical aspects, the “bones” of the system under analysis, need to be well defined and represented, covering hydrology, soils, elevation, extant erosion, land use, and other fundamental aspects of the agroecosystem. The addition of wildlife surveys, land use, and agricultural production histories, along with social and economic analysis tools, literally “lays the groundwork.”