Critical Infrastructure for Ocean Research and Societal Needs in 2030 (2011)

The infrastructure and research investments required to address most of the compelling scientific questions are substantial. The development and maintenance of Earth ob­serving systems have been a significant challenge for decades and major elements of the observing system are actually in decline (NRC, 2007b). Consequently, the competition for resources to develop and maintain the infrastructure needed to support scientific investigations is growing. A list of infra­structure requirements, matched to scientific questions and societal needs, is by itself insufficient guidance to ensure appropriate investment for infrastructure that will facilitate ocean research in 2030. Instead, it needs to be accompanied by mechanisms or criteria for prioritization.

A National Research Council review of Charting the Course of Ocean Science in the United States for the Next Decade: An Ocean Research Priorities Plan and Imple­mentation Strategy (NRC, 2007a) proposed the following questions to identify the most compelling research priorities for ocean research:

• Is the proposed research transformational (e.g., will the proposed research enable significant advances in insight and application, even with potentially high risk for its success; would success provide dramatic benefits for the nation)?

• Does the proposed research impact many societal theme areas?

• Does the research address high-priority needs of resource managers?

• Would the research provide understanding of high value to the broader scientific community?

• Will the research promote partnerships to expand the nation’s capabilities (e.g., contributions from other partners, including communities outside of ocean science, such as health science; unique timing of activities)?

• Does the research serve to contribute to or enhance the leadership of the United States in ocean science?

• Does the research contribute to a greater understand­ing of ocean issues at a global scale?

• Does the research address mandates of governing entities (federal agencies; state, tribal, and local governments)?

This committee expands upon these proposed ques­tions on the basis that ocean research infrastructure will increasingly be judged on its importance to society. Public investment in the research enterprise exists as part of a social contract, first articulated by Vannevar Bush in his seminal document, Science the Endless Frontier (Bush, 1945). It describes a framework in which investment in the basic sciences is motivated by benefits that are realized by the public (e.g., improvement in the standard of living, higher productivity, increased jobs, national security). Gov­ernment research investments today are often connected to the societal benefits that might accrue, providing greater linkage between basic research and application than was implied in Bush’s brief report. In this chapter, the commit­tee describes a framework in which ocean infrastructure investments are prioritized by their potential societal con­tributions within an economic valuation. It is important to note that societal contributions for the public good can come in many forms, including the value of job creation or avoidance or mitigation of natural disasters. As the 20th century saw enormous investments in research motivated by the Cold War, the 21st century may see investments motivated by a wish to avoid or lessen the impact of envi­ronmental catastrophes.

Research infrastructure in place in 2030 will shape both the nature and quality of ocean science that is undertaken, as well as the value that this science will generate for inform­ing policy and management decisions. As noted throughout the report, the degree to which ocean research infrastructure is of compelling importance to society can be judged based on potential contributions toward enabling stewardship of the environment, protecting life and property, promoting

sustainable economic vitality, and increasing fundamental scientific understanding.

Each piece of infrastructure enables or supports a set of data collection and/or modeling activities, and therefore supports the production of information, which has value. The same piece of infrastructure also has a cost associated with it (e.g., building and maintaining a ship or computer model, training and supporting a technician, archiving and making accessible a data set). The task of prioritizing ocean research infrastructure investments can be interpreted as maximizing net benefits over time by choosing the best combination of infrastructure investments needed to address the science within budget constraints. The committee concedes that there may be other legitimate considerations beyond those spelled out in this report, but most likely these could all be incorporated into an economic optimization framework.

The bottom-up linkage from infrastructure to societal benefits shown in Figure 1.1 provides a useful approach to thinking about infrastructure priorities. An important feature of this prioritization is economy of scale and scope, as a given piece of infrastructure may support multiple research activities, models, and science questions. For example, a particular mooring may support multiple sensors, each sensor can supply data that feed into several models, and each model can contribute information to one or more societal objectives. In addition, a system of coordinated sensors can provide information that is more valuable than their individual contributions. An approach of this kind requires knowledge about the value (benefit) generated by specific information about the ocean and its contribution to achieving societal objectives; linkages between each piece of infrastructure and this specific information; and the cost of each piece of infrastructure.

The value of information (Howard, 1966; McCall, 1982; Nordhaus, 1986) relevant to societal objectives is determined by the degree to which the information allows decision makers to achieve an economically better outcome. The role of information is to reduce the uncertainty under which these decisions are made. For example, the societal objective of managing the nation’s commercial marine fish stocks for maximum sustainable yield can be advanced by improving the quality of information represented by stock assessments and forecasts of fish stock abundance under different levels of fishing effort, environmental conditions, and ecological interactions. When information (e.g., stock assessments, forecasts, interactions between species within and across tropic levels) is less than perfect, fisheries managers must make decisions with greater uncertainty. Uncertainty can be addressed by either reducing the fish catch below the theoretical sustainable yield or by accepting an increased risk that the stock will be overexploited. If these assessments and forecasts were perfect, fisheries managers could allow fishing closer to maximum sustainable yield without risking overexploitation or other adverse ecological consequences. By increasing yield without reducing sustainability, the economic value of the fish stock to the nation could be maximized. The difference in economic outcomes with and without the information is its value.

Although infrastructure costs can usually be determined with considerable accuracy, the value of information in most cases can only be estimated (e.g., Adams et al., 1995; Nordhaus and Popp, 1997; Teisberg and Weiher, 2000; Williamson et al., 2002). Certainty about the value of information from research investments decreases the further it is removed from helping to answer specific applied questions; this uncertainty is greatest for basic science investments, where the nature of the answers and their applications are by definition not well identified in advance. Uncertainty about the expected value of information from infrastructure investments arises from several sources, including uncertainty about the performance of new technologies, the nature of information generated by new technologies or research activities, and the value that the information will in fact generate. Uncertainty can lead to missed opportunities in commercial market assessments, when comparing a well-known market with an arguably better but less well defined market (e.g., the Innovator’s Dilemma [Christensen, 1997]). Deep-mapping autonomous underwater vehicles (AUVs) provide an ocean technology market example. They are an example of a disruptive new technology introduced to the established seafloor survey market, which had relied upon deep towed systems prior to AUV use. Due to the established companies’ hesitancy in adopting a new technology or because of their already significant investment in the existing technology, smaller survey companies using AUVs were able to quickly gain a strong market.

It is not necessary to have perfectly accurate estimates of the value of information in order to make reasonable prioritization decisions. It is necessary, however, to employ a rigorous and harmonized approach that will need to be undertaken at a national level—one that is consistent across and between all relevant agencies, and one that treats uncertainty about returns from investments in a systematic way. Uncertainty in making ocean research infrastructure choices can be addressed in part through mechanisms for the treatment of uncertainty in investment decisions (Dixit and Pindyck, 2010), and the emerging theory and practice of strategic decision making about real options in research and development (Trigeorgis, 1996). Much of this work is focused on investment in research and development by firms seeking to maximize profits from future technology improvements (Bowman and Moskowitz, 2001; Huchzermeier and Loch, 2001; Weeds, 2002; Gunther-McGrath and Nerkar, 2004; Wang and Hwang, 2007), but these problems are structurally analogous to the challenge facing government agencies as they seek to maximize return from research infrastructure investments.

Economic value estimations begin with mapping research questions to infrastructure requirements. In Chapter 4, the committee takes a first step in assembling the infor­mation needed to map infrastructure components to relevant ocean research questions for 2030. More detailed mapping of linkages between future infrastructure and information pro­duced may require formal or informal simulation exercises (e.g., Observing System Simulation Experiments). As with the estimation of future economic benefits, there are limits to the precision with which this kind of mapping can be car­ried out; development of a framework, however approximate, can indicate trends useful for prioritization. The challenge of prioritizing ocean research infrastructure investments is best approached by estimating the economic costs and benefits of each potential infrastructure investment, and funding those investments (subject to budget constraints) that collectively produce the largest expected net benefit over time. Indeed, the net societal benefit from investment in ocean science infrastructure is likely to be high. The pro­cess of prioritization needs to incorporate uncertainty in the value of information from future ocean science, including uncertainty about the economics of the societal interests, and uncertainty about the ability of future science to produce information relevant to those interests.

As mentioned throughout this report, the science research questions were selected based on their potential to contribute to four major societal objectives: enabling stew­ardship of the environment, protecting life and property, promoting sustainable economic vitality, and increasing fundamental scientific understanding.

The infrastructure needs required to address the broad range of ocean research questions can be priori­tized using an economic framework that includes consid­eration of important criteria, such as:

1. Ability to address the science

2. Affordability, efficiency, and longevity

3. Ability to serve other missions or applications

Each of these major considerations, which are listed in the order in which they should be applied, encompasses a variety of other factors and questions that contribute to the determination of the value of ocean science and, by impli­cation, the value of the infrastructure necessary to support that science.

• How important is the infrastructure in addressing and resolving one or more science questions?

• How dependent is an area of research on the specific infrastructure?

• Does the infrastructure provide the appropriate level and quality of data? Are the measurements and analy­ses provided sufficient to support science and reduce uncertainty for decision making?

• What is the potential for quantum leaps in under­standing or capability?

• Is there an appropriate infrastructure portfolio to manage uncertainty?

• Does the infrastructure have design flexibility to take advantage of future trends in technology (e.g., through upgrades, component swap-out)?

• Does the infrastructure portfolio avoid redundan­cy with investments by non-ocean industries or agencies?

• What is the unit cost of observation (cost per unique observation) provided by this infrastructure, and how does the cost compare to that of other forms of measurement for the same information?

• Is there an appropriate infrastructure portfolio to manage a combination of sustained, episodic, and event-driven requirements?

• Is the infrastructure broadly accessible to the ocean research community? Does it promote or leverage community talents or capabilities?

• Does the infrastructure leverage other sources of support (e.g., from states, international partnerships, public-private partnerships, or the private sector)?

• What is the balance between risk and potential bene­fits? Is risk managed appropriately (e.g., by spreading investment in technology development over several competing groups)?

• Is the infrastructure technologically mature, or are there limiting technological (or other) challenges?

• Does the infrastructure serve multiple science ques­tions or applications that yield multiple benefits, es­pecially across more than one domain or discipline?

• Does the infrastructure improve or enhance collaborations?

• Does the infrastructure serve other issues of national strategic importance (e.g., leadership in ocean sci­ence and technology, resource development, national security, education)?

• What is the potential for serving applications or mis­sions in multiple agencies?

These considerations can assist in the process of determining costs and benefits to prioritize ocean research infrastructure

investment decisions; such a process would optimistically result in a well-supported economic argument for a particular set of infrastructure investment priorities encompassing all federal agencies with a role in ocean research. In the process to optimize investments in ocean research infrastructure outlined above, decision makers (e.g., federal, state, and local governments) will naturally take into account subsidiary considerations that help define the net benefits associated with development, maintenance, and eventual replacement of specific infrastructure. Developing the detailed structure of that process and its application is beyond the scope of this report.

Recommendation: Development, maintenance, or replacement of ocean research infrastructure assets should be prioritized based on (1) usefulness for addressing important science questions; (2) affordability, efficiency, and longevity; and (3) ability to contribute to other missions or applications. Such prioritization will maximize societal benefit for the nation.