A classic example of microbiome function is its role in nutrient assimilation in both plants and animals, but other less obvious roles are becoming more apparent, particularly in terms of driving infectious and non-infectious disease outcomes and influencing host behaviour. However, numerous biotic and abiotic factors influence the composition of these communities, and host microbiomes can be susceptible to environmental change. How microbial communities will be altered by, and mitigate, the rapid environmental change we can expect in the next few decades remain to be seen. That said, given the enormous range of functional diversity conferred by microbes, there is currently something of a revolution in microbial bioengineering and biotechnology in order to address real-world problems including human and wildlife disease and crop and biofuel production. All of these concepts are explored in further detail throughout the book.

Host-associated microbiomes are ubiquitous in nature, but highly variable in both space and time, and shaped by a diverse range of biotic and abiotic factors. This chapter summarises the numerous drivers of variation in microbiome structure and function across both plants and animals. Plants harbour distinct microbial communities in their rhizosphere, phyllosphere and endosphere. These communities interact with hosts in a different way, and in turn are shaped by a unique set of environmental factors. For example, the rhizosphere supports a particularly diverse microbial community shaped by plant exudates and signalling molecules to facilitate nutrient transfer to the host. Similarly, variation in animal microbiomes is driven by host genetic, life-history and environmental traits, including phylogeny, diet, age, metabolism and sociality. Several of these factors are also given more detailed treatment in later chapters. Particular attention is given to our current state of knowledge concerning initial colonisation and subsequent succession in microbial community composition in juveniles, the consequences of which remain one of the major outstanding questions in microbiome research.

If you are like me, whenever a new planning method or tool is described, you wonder how it relates to those planning methods or tools with which you are already familiar. Usually, the description of the method or tool does little to answer questions of this type. To find out how it relates to other methods or tools (and whether or not it is any good), you must wait, instead, for a review of the method by a planning maven.

A similar, but more awkward, situation occurs if you have been told to evaluate a new method and/or tool for its usefulness in your planning situation. If you cannot find a review of the method/tool, you must either wait for an expert review or you must make the comparisons yourself.

Partly because of the way in which Assumption-Based Planning (ABP) was developed, we have already done that work. ABP started out as the solution to a specific U.S. Army planning problem. When the Army asked us to reapply and document the “method” two years later, we searched through the literature to see how it related to other methods/tools.

Over the years, we have kept up that comparison effort, primarily as due diligence in understanding the literature and, secondarily, as a means of honing our own definitions. As anyone who has looked can attest, there is little standardization of terms and concepts in the large and varied literature on planning.

We cannot know the future perfectly, but we can imagine the future and make plans for it by making some assumptions—or judgments— about what that future could be like. Some of the assumptions we make are pretty likely to come true; others are more vulnerable to uncontrollable and unforeseen events; still others seem quite unlikely. Some of the assumptions are likely to be very important to the success of the plan; others will be more peripheral. Assumption-Based Planning (ABP) is a tool designed for improving the robustness and adaptability of plans—for reducing the number of avoidable surprises in any plan or planning. It is primarily a “post-planning” tool (recognizing that planning is an iterative process) that concentrates on the assumptions in an already-developed plan that are most important to the plan's success and that are most uncertain. Specifically, ABP works to decrease the risks that assumptions represent.

Over the years, we have come to appreciate how much art there is to any kind of planning. Mintzberg (1994b) argues convincingly that creativity is at the heart of planning and, further, that any attempt to force planning into a rigid framework is likely to squelch that creativity. Creativity is that burst of insight—that “aha!”—that jumps from a thorny problem to its solution. Creativity can be nurtured but not taught. While agreeing with Mintzberg's arguments, I would add that there is an art to planning that is separate from the creativity that he talks about. There is an art to the conducting of planning.

Anyone who has done planning has had good and bad experiences. Largely unrelated to the details of the plan, those experiences had more to do with the people involved, or the circumstances in which the planning was done, or the time of the day, week, or year, etc. As you do more planning, the better you begin to understand what is likely to make for good or bad experiences—and how to turn a bad experience into a good one. Art is something that improves with experience, and it can be taught.

This chapter presents some of the major lessons we have learned about the art of conducting ABP. The major lessons break down into four categories:

• Creating the general setup

• Identifying load-bearing, vulnerable assumptions

• Agreeing on signposts

• Introducing scenarios.

Assumption-Based Planning (ABP) started out in 1987 as an approach Morlie Hammer Levin and I developed to solve a U.S. Army strategic planning problem. Thanks to the fall of the Berlin Wall two years later, that early ABP work initiated an ongoing conversation with the Army about how to do planning in the Army's newly and differently uncertain times. The use of ABP was first described in James A. Dewar and Morlie H. Levin, Assumption-Based Planning for Army 21, Santa Monica, Calif.: RAND, R-4172-A, 1992, and ABP itself was first documented in James A. Dewar, Carl H. Builder, William M. Hix, and Morlie H. Levin, Assumption-Based Planning: A Planning Tool for Very Uncertain Times, Santa Monica, Calif.: RAND, MR-114-A, 1993. As ABP evolved through various Army and other applications, it turned into a planning tool—a self-contained process with a specific planning purpose—that is applicable to any kind of plan or planning process. ABP continues to evolve, but its fundamentals have changed little in its last several applications. For that reason, it seemed appropriate to document formally what we have learned about it.

The careful reader will already have noticed that I use both the singular and plural first-person pronouns in talking about ABP. My coauthors on the original ABP documentation were intimately involved in both the intellectual development of ABP and in the learning process that accompanied its application to real planning problems.

A primary aim of Assumption-Based Planning is to identify certain types of assumptions underlying a plan: those that are load-bearing and vulnerable. This suggests that there are different kinds of assumptions. Indeed, we have found it useful to distinguish among several different types. In addition to making clear exactly what we mean in general by assumption, it is also important to make the distinctions among the different types of assumptions clear.

Webster's New World Dictionary defines assumption as “the supposition that something is true” or “a fact or statement taken for granted.” (The 1998 version defines assumption as “an assuming that something is true.”) The assumptions we are interested in fit these definitions, but they are more restricted. We are interested only in planning assumptions. For ease of discussion, we drop the planning, but it is implicit in what we have come to mean by “assumption” in Assumption- Based Planning:

All planning requires some judgments about, or evaluations of, the future. The more uncertain the future, the more likely it is that the planner will have to make judgments or “guesstimates” to help narrow the range and number of uncertainties about the future into a manageable few before progress can be made.