Joint Force Quarterly 119 (4th Quarter 2025)
By NDU Press | March 16, 2026

U.S. Navy SEAL secures deck of ship and conducts board, search, and seizure training with British Royal Marine Commandos and Ukrainian special forces in Odesa, Ukraine, June 21, 2021 (U.S. Army/Patrik Orcutt)
Cover of JFQ 119
Cover of JFQ 119. U.S. Navy SEAL secures deck of ship and conducts board, search, and seizure training with British Royal Marine Commandos and Ukrainian special forces in Odesa, Ukraine, June 21, 2021 (U.S. Army/Patrik Orcutt)
Photo By: Cover of JFQ 119
VIRIN: 260316-D-HL629-0283

Read JFQ 119 (PDF)

Read JFQ 119 (Web version)

While not all readers of this journal read my Executive Summary, they do read the results of my team’s work. From acquisition to publication and distribution, the authors’ efforts are transformed from simple files of words and occasional graphics into the journal you are reading. At 32 years and now 119 issues, Joint Force Quarterly has had over 40 people involved in making the magic happen. As great as JFQ has become, two significant events will undoubtably change how this journal is produced and delivered.

Primarily because of changes in the media environment at large and the budgetary pressures across government, National Defense University (NDU) Press will be significantly reducing the available print copies of JFQ beginning with the next edition, JFQ 120, due after the New Year. A small quantity of copies will be published and provided primarily to the joint force community—specifically, the joint professional military education schoolhouses, the Joint Staff, and the Combatant Command staffs. Our budget and my proper stewardship of the limited funds available, along with the dramatic expansion and use of digital means to disseminate content, are the key drivers for this change. For locations other than those I have mentioned, JFQ 119 will be the last print edition delivered, both for individual subscriptions and for bulk deliveries. Effective October 1, 2025, NDU Press will no longer accept requests for print copies of JFQ, except for copies of previous editions. A small number of copies will continue to be available here on NDU’s North Campus at Fort McNair. Those who wish to continue receiving individual copies can do so through the Government Publishing Office’s U.S. Government Bookstore for a fee.

To me personally, another significant change will also influence future editions—the retirement of our longtime Executive Editor, Dr. Jeffrey Smotherman. Jeff has served at NDU Press for over 25 years and has done so brilliantly. Every page, every word, and even the very style of the current JFQ has his personal touch, dating back to JFQ 35 in the fall of 2000. Jeff was involved with some 84 of the now 119 editions, totaling some 1,732 articles from at least 2,400 authors and nearly 11,000 pages of the Chairman’s Journal. No other member of the NDU Press team past or present has served as long or as well for this special mission as Jeff.

In addition to his work on JFQ, Jeff has stewarded NDU Press’s production of 20 major books—always his preferred work assignment—and hundreds of research monographs and case studies. He has been the first person called upon when a document for NDU leadership use needed a perfectionist’s eye. Warriors talk of having a teammate to get them through the good times and the trials of combat. While Jeff Smotherman has not served in the military, he has been every bit a battle buddy to his NDU teammates and especially me. We wish Jeff a healthy, happy, and well-deserved retirement.

In Forum this time, we have four very current and significant articles on deterrence, support to the force, decision support from artificial intelligence (AI), and current U.S. munitions production. Robert Hinck continues our long discussion on integrated deterrence with his suggestions on how a network strategy can help the U.S. influence friend and foe alike. Every unit will want to consider Aubry Eaton and Dustin Thomas’s suggestions on how to build combat capability on the front lines. None of us can stop talking about AI, but Michael Silver, Kellen Sick, Matthew Snyder, and Justin Farnell offer us ways to use it for organizational design and decisionmaking in warfighting. Another hot topic is the U.S. defense industrial base, and Bryce Loidolt—my teammate from NDU’s Institute for National Strategic Studies— will bring you up to speed on the issues involved in getting the right materiel to the front lines of Ukraine.

Our JPME Today section returns with two important discussions, one old and another very new. Often it seems everyone has a good idea on how to reshape professional military education (PME), but serious change comes from just understanding this enterprise we are involved in. Ryan Wadle and Heather Venable offer their views on the right balance between breadth and depth of the content and courses in PME, as well as outlining the battle lines inside the halls of our colleges and higher headquarters. JFQ alum Kevin D. Stringer and his research partner, Taisiia Vivdych, bring us their insights on how the Ukrainian special forces are achieving success.

Commentary from two new JFQ voices helps extend the discussions we have had in recent issues on two key topics: cyber and nuclear weapons. Jorge Kravetz wades into the debate over the use of cyber for deterrence through intelligence special operations. Michaela Dodge brings us her Larry D. Welch Award–winning essay on the value of intercontinental ballistic missiles—an enduring part of our nuclear triad, despite calls not too long ago to abandon them.

One can easily see the strategic connections between the three articles we have for you in Features this time. Alexander Goodno discusses his ideas on how to combat Chinese influence and China’s illegal fishing in the waters of South America. Seeing an opportunity to learn lessons from past combat support efforts, Jonathan Pederson describes how the joint force might improve casualty evacuation in large-scale combat operations. Addressing what many believe is the next big theater of operations, Samuel Krakower and Troy Bouffard suggest how the United States can best position our military to fight when needed in the Bering Region of the Arctic.

Closing out this edition of JFQ, we have three excellent book reviews.

To my teammate who was a constant companion to us here at NDU, who has suffered through all my stories and never-ending tortured analogies, I wish Jeff Smotherman fair winds and following seas, with a reminder to always check your six! JFQ

—William T. Eliason, Editor in Chief

Click here to read JFQ 119 →


Strategic Assessment 2025: Evolving Great Power Competition at Mid-Decade
By Thomas F. Lynch III | Feb. 25, 2026

Download Full PDF

The geostrategic framework of international relations at mid-decade remains heavily conditioned and shaped by Great Power Competition (GPC) between three rivalrous, globally dominant states: the United States, China and Russia. After more than two decades of mainly cooperation and collaboration, these Great Powers drifted into de-facto rivalrous competition at the end of the 2000s. By the middle of the twenty-tens, their undeclared but obvious rivalry intensified, and their major interactions shifted from those of cooperation and collaboration to competition, confrontation and preparation for potential armed clash. Fully acknowledged GPC arrived in late 2017 — after a decade of de-facto GPC contested by China and Russia but poorly understood in Washington — when the United States published a dramatically new National Security Strategy and declared a formal end to the 25-year era of United States-led globalization and pro-active, world-wide American democratization initiatives.

Some elements of legacy collaboration between the Great Powers persist in selected international organizations, agencies and activities, but serious disagreements about strategic goals and legitimate means to achieve them underpin a structure that features intensifying competition and greater confrontation than witnessed for decades. By 2018, the U.S., China and Russia were engaged in fully-acknowledged, global Great Power rivalry.

In October 2022, the Biden Administration published its NSS. The 2022 update did not reject the Trump NSS diagnosis of a new geostrategic era of Great Power competition. Instead, the October 2022 NSS accepted it. However, the Biden Administration did end the Trump Administration’s “American First” policy approach toward GPC that it believed too often resulted in “America alone” impacts. The Biden approach that came to be known in many quarters as “Strategic Competition.” Under Biden, Strategic Competition featured a vigorous program of security, economic, information, and diplomatic competition with China and Russia, working closely with allies and partners against these rivals, and with specific attention to reinvigorating both American domestic economic competitiveness and the attractiveness of American strategic partnership. The Biden administration approach believed that the United States would succeed in competition with China over time by enhancing its domestic competitiveness while working more closely with friends and partners and avoiding the strategic error of posing stark, binary choices to would-be partners and friends.

From 2021 through 2024, the debates about GPC’s relevance to the international geostrategic framework subsided. They were replaced by debates about what America could do to succeed in this strategic competition between large, rivalrous powers. The second Trump administration entered office with a different view about the best path forward in GPC.  The Trump 2.0 approach was only emerging in 2025, but nascent administration activities suggest that significant change will occur. The new administration indicates that it will expand and evolve an “America First 2.0” agenda with less reliance on American global alliances and partnerships, more focus on defending the American homeland, and a greater willingness to broker arrangements that afford today’s Great Power strategic rivals with primacy in their immediate geographic regions. One January 2025 analysis forecast that American strategy in the late 2020s may turn toward one where the U.S., “…is to be ruthlessly pragmatic about values, tough with allies and open to deals with opponents…”

Strategic Assessment 2025 will explore the evolution of this fully acknowledged strategic competition among and between the Great Powers at mid-decade. Its chapters feature primary analysis amplifying the reciprocal and dynamic interaction of the policies, strategies, capabilities, and influence of the mid-decade's three great powers: the United States, China and Russia.  Strategic Assessment 2025 will project the trajectory of major trends in this strategic competition for the remainder of the decade — through 2030.  Its authors — subject matter experts all — will explore the most salient features of strategic Great Power competition over the course of fifteen original chapters. In addition to this introductory chapter, one chapter focuses on historical analysis of past trends in multi-state global Great Power competition, two frame the global strategies and power capabilities of today’s Great Powers, five focus on today’s Great Power competitive posture and power capabilities in critical functional areas and activities, another five focus on evolving Great Power competition in critical geostrategic regions, and a concluding chapter draws together major insights for the future of Great Power competition for the remainder of the decade. 


Understanding Space Frontier Areas
By Todd Pennington | Feb. 12, 2026

Download PDF

Executive Summary

Distant reaches of space loom as a strategic horizon. The vast majority of space operations have, so far, been limited to a few families of near-Earth orbits. However, space beyond geostationary Earth orbit, or xGEO, is likely to become important for strategic purposes in the near future. This is especially true of cislunar space, that region of space in which the gravity of Earth’s moon is significant. This paper refers to xGEO and cislunar space as Space Frontier Areas, since missions there have not yet reached sufficient scale to cluster into patterns of use.

Current strategic thought on activities in Space Frontier Areas is largely bipolar, with some experts emphasizing their near-term security implications and others emphasizing much longer term economic potential. This bipolarity tends to suggest a zero-sum choice between imminent security needs or long-term economic opportunity, constraining policymakers’ ability to identify trade-offs and make nuanced choices about risk and priorities in space operations.

This paper proposes an analytical framework for improving the coherence of strategic thought about Space Frontier Areas. It postulates four strategic purposes served by activities in Space Frontier Areas (prestige, governance, security, and resources), and a framework in which each purpose can be weighted by its importance and immediacy in a given time frame. Relying on data derived from research interviews with several experts in space operations, it demonstrates that this framework can produce more coherent strategic perspectives about activities in Space Frontier Areas.

Reducing bipolarity in strategic thought about Space Frontier Area improves the realism and nuance of the context in which leaders must make decisions about time, attention, and resources to be devoted to space operations.

 


Cognitive Warfare and Organizational Design: Leveraging AI to Reshape Military Decisionmaking
By Michael S. Silver, Kellen D. Sick, Matthew A. Snyder, and Justin E. Farnell | Jan. 9, 2026

Download PDF

Soldier fights in tandem with various robotics in Human-Machine Integrated Formations during Project Convergence Capstone 5 experiment, March 15, 2025, at Fort Irwin, California (U.S. Army/Patrick Hunter)
Captain Michael S. Silver, USN, is an MH-60 pilot and the prospective Executive Officer of the USS Theodore Roosevelt. Colonel Kellen D. Sick, USAF, is an F-15 Pilot serving on the Joint Staff J7 as a Joint Force Development Strategist. Major Matthew A. Snyder, USA, is a Special Forces Officer serving at Special Operations Command South as Deputy J3. Major Justin E. Farnell, USMC, is a Marine Corps MV-22 Osprey Pilot currently serving on the Joint Staff in the J6 Joint Assessment Division.

In 2002, the Oakland Athletics faced formidable challenges. With a payroll less than a third of the New York Yankees’ $125.9 million and the departure of key players, the Oakland A’s were projected to struggle. Yet they won the American League West division, besting their star-studded 2001 run. Immortalized in the film inspired by Michael Lewis’s book Moneyball, the team’s 2002 season is a case study in leveraging data-driven decisionmaking to challenge and overturn a failing status quo. By prioritizing undervalued metrics, the Oakland A’s constructed a team that tied the Yankees for the most wins in the league for a fraction of the cost. In 2004, the Boston Red Sox adopted this approach to break their 86-year championship drought, demonstrating the competitive edge that data-centric analysis provides in decisionmaking. Just as the 2002 Oakland A’s leveraged data to challenge conventional approaches, modern warfare requires a shift from intuitionbased decisionmaking to artificial intelligence/machine learning (AI/ ML)–enabled decisionmaking. The joint force, like baseball two decades ago, faces an urgent challenge: integrate AI/ML or risk being outmaneuvered by more agile adversaries.

The military and economic dominance of the United States in the post-Soviet era compelled adversaries to shift their strategies away from largescale conventional warfare. Instead, they have increasingly focused on contesting American decisionmaking through cognitive warfare, leveraging psychological, informational, and technological domains to erode strategic advantage. Unlike traditional warfare, cognitive warfare shapes how individuals and organizations perceive reality, evaluate choices, and act on information.1 Russia’s interference in the 2016 U.S. Presidential election and the United Kingdom’s Brexit vote, as well as China’s 2024 use of TikTok to influence Taiwan’s presidential election, demonstrate the profound impact cognitive warfare has had on recent history.2 Moreover, China is aggressively pursuing a future battlefield dominated by autonomy, outpacing adversaries with AI/ ML tools that compress decisionmaking from seconds to milliseconds.3

The proliferation of tools such as China-based DeepSeek AI and U.S.-based ChatGPT has revolutionized private and commercial sectors by accelerating decision cycles.4 These tools can analyze vast and complex data sets in seconds, producing insights that once required entire teams of analysts working over extended periods. For example, JPMorgan Chase uses AI tools to detect fraud and assess credit risk across millions of accounts in near-real time, while the U.S. National Weather Service employs ML models to rapidly process satellite imagery and atmospheric data, generating earlier and more accurate storm forecasts.5 These systems reduce the human cognitive load and enable faster, higher-quality decisions at scale. In the national security domain, where the stakes far exceed those of finance or public safety, a competitive edge in the speed and accuracy of decisionmaking is more critical than ever. In this type of contest, those who can shape narratives, manipulate information, and make superior decisions faster than their competitors achieve victory.6

Despite widespread investment and experimentation in AI/ML, most organizations struggle to increase performance with this technology. Only one-quarter of companies experimenting with AI have generated real value, and less than 5 percent have built AI capabilities at scale.7 Even large companies like Microsoft believe they are transforming, but they are merely using AI to speed up processes rather than fundamentally reshaping operations to optimize performance.8 As evidenced by initiatives detailed on ai.mil, the Department of Defense—now the Department of War (DOW)—has invested billions of dollars into AI/ML capabilities. Still, mere access to this technology has proved insufficient for widescale integration. The struggle is not only technological; it is behavioral. True AI integration requires more than technology; it requires adoption. Understanding why these AI challenges persist is critical to identifying viable solutions and preventing the erosion of strategic advantage. With three-quarters of all organizations yet to see tangible AI benefits, the challenge to adoption lies in amending structures, processes, and people to unlock the full potential of AI/ML.9 DOW must take note and move beyond the status quo, accelerating AI/ML adoption to enhance decisionmaking. At a February 2025 AI Action Summit in Paris, North Atlantic Treaty Organization (NATO) Supreme Allied Commander Transformation, Admiral Pierre Vandier, clearly articulated this imperative: “Artificial intelligence is massively accelerating military decisionmaking, and armed forces that do not keep up risk being outmatched.”10 Using the conflict in Ukraine as an example, he highlighted that the stakes of maintaining the status quo are stark: “If you do not adapt at speed and at scale, you die.”11 Admiral Vandier’s mandate for AI training among officers in Allied Command Transformation underscores the critical insight that adoption, not capability, is the limiting factor for integration.

In this article, we seek to analyze organizational design factors affecting the widescale adoption of AI/ML tools into DOW decisionmaking. We do not address offensive and defensive applications of cognitive warfare; ethical considerations for using AI/ML tools; trust and transparency requirements; or vulnerabilities that using AI/ML tools might present to adversarial actors. These areas represent future research opportunities.

Approach to Analyzing Organizational Design

When an organization reaches an inflection point and assesses that the status quo will ultimately lead to its stagnation or decline, it must adapt its organizational design. Jay Galbraith’s Star Model, first introduced in 1977 as a strategic approach to organizational design, provides a useful framework for such adaptation.12 In this article, we modify Galbraith’s Star Model to analyze organizational design factors affecting the widescale adoption of AI/ML tools into DOW decisionmaking. These factors can be applied across tactical, operational, and strategic organizations for warfighting, resourcing, and administrative purposes. The modified Star Model, illustrated in figure 1, includes five organizational design factors: people, structure, processes, incentives, and leadership and management.

The term people refers to the mindset, skill sets, and talents required of the individual workforce to achieve an organization’s goals.13 Structure refers to the location of decisionmaking power. It defines the shape of an organization, reflecting the hierarchy of authority and distribution of power through the lens of what and where decisions are made.14 The term processes refers to the information flows that feed into decisionmaking.15 Incentives are the motivational tools that drive people to exercise processes within a specified structure to achieve organizational objectives.16 Incentives reflect a combination of extrinsic and intrinsic motivators. Leadership and management reflect the role that joint leaders play in establishing strategic direction and priorities for their organizations. They wield considerable influence over the other organizational design factors.17

These five factors operate as interdependent nodes of organizational design, reinforcing or weakening the overall strength of the organization. How these factors interact drives the organization’s performance and cultural outputs. When mission or environmental changes influence one node in the modified Star Model to change, organizations should evolve and adapt to reoptimize the design factors.18 Failure to do so risks organizational impotence or, worse, obsolescence.

Figure 1. Modified Star Model for the Joint Force.

Modified Star Model for the Joint Force diagram, derived from Jay R. Galbraith's Star Model

Analyzing Organizational Design Factors

People. The physiology of the human brain as well as the mindset and skill set of people in an organization are critical factors affecting AI/ML adoption. Decisionmaking relies on interconnected cognitive processes shaped by experience and repetition. Over time, familiar workflows become deeply ingrained, leading individuals to rely on default patterns even when new tools become available.19 This is evident in the joint force, where decades of Internet use have conditioned personnel to develop a “search-engine mindset.”20 This habituated approach relies on generating results through indexed, static, keyword-driven interaction. In contrast, AI/ML tools generate dynamic, context-sensitive responses that improve with iteration.

Effective AI/ML adoption necessitates a fundamental shift in human cognitive habits. Just as military planners use multiple iterations to refine initial concepts prior to execution, AI-generated outputs require a similar process to achieve optimal results. However, many users unknowingly limit the effectiveness of AI/ML by treating it as a static query system rather than an interactive tool. Reliance on traditional search-engine workflows has reinforced behaviors that are at odds with AI/ML’s adaptive nature. Users approaching AI/ML with a conventional search-and-response model struggle when the technology requires a different form of interaction. Frustration grows when responses appear incomplete or contain “hallucination” errors that often prompt users to disengage from the technology.21 As Conor Grennan, chief AI architect at New York University’s Stern School of Business, notes, “It’s not that our brain doesn’t know how to use it—it’s more nefarious than that. It’s that our brain thinks it knows how to use it, but it’s wrong.”22 The challenge is not simply learning a new tool; it is retraining deeply ingrained cognitive habits.

Like any weapon system, AI/ML is a purpose-built tool that complements, rather than replaces, existing capabilities. To unlock its full potential, personnel must shift away from treating AI/ML like a search engine to actively shaping AI/ML-generated outputs. For example, a Google query for “develop an operations plan for a joint force mission” yields static templates and archived operations orders (OPORDs). While useful, these resources require hours of manual adjustment to meet dynamic mission requirements. In contrast, a user iterating with a generative AI/ML model can rapidly create a fully customized OPORD tailored to mission-specific inputs. When provided with these inputs, AI/ML can analyze real-time intelligence to identify enemy force positions, vulnerabilities, and likely courses of action (COAs). It can incorporate weather forecasts to assess operational impacts and recommend troop movements, logistics, and contingencies. This iterative process has the potential to significantly accelerate the planning process, reducing planning timelines from days to hours and enabling faster, more informed decisions.

Marine Corps Lance Corporal Eric Granados, intelligence specialist with 3rd Battalion, 5th Marine Regiment, 1st Marine Division, I Marine Expeditionary Force, launches RQ-20 Puma during artificial intelligence–enabled system Dead Center as part of small unmanned aircraft system training on Marine Corps Base Camp Pendleton, California, August 20, 2025 (U.S. Marine Corps/Trent A. Henry)

Developing new cognitive habits is only part of the challenge. Effective AI/ ML adoption requires structured training to develop the requisite skills.23 A recent study found that untrained users underperformed when applying AI beyond its intended capabilities, often because they treated it like a search engine. In contrast, trained AI users demonstrated significant gains in both productivity and quality. For individuals normally below the average performance threshold, performance increased 43 percent with effective AI augmentation. Individuals already performing above the average performance threshold still experienced a 17-percent improvement with effective AI augmentation. Additionally, trained AI users completed 12 percent more tasks and worked 25 percent faster than those without AI augmentation.24 These findings highlight the necessity of deliberate AI/ML training to maximize operational effectiveness.

AI/ML training extends beyond technical proficiency in key skill sets such as prompt engineering, iteration and chaining, role-based interaction, and conversational engagement. It must also account for cognitive and behavioral mechanisms that drive adaptation. Training should reinforce positive feedback loops, where improved performance encourages continued use, ultimately leading to the formation of new habits. Achieving this shift requires deliberate implementation efforts to correct the lack of structured reinforcement strategies found in legacy methods. Behavioral change demands a combination of hands-on training, iterative learning, and leadership-driven adoption initiatives. While training programs are essential, adoption also depends on aligning AI/ ML tools with organizational structure.

Structure. Organizational structure determines what decisions are made and where they occur, directly shaping AI/ ML adoption. While mission and environment drive structural design, different structures affect the speed, efficiency, and effectiveness of using AI/ML tools for decisionmaking. Understanding the types of decisions an organization makes reveals how to use AI/ML tools. Identifying where decisions occur reveals where to apply them.

Decisions vary significantly in nature and complexity.25 Administrative tasks like summarizing and disseminating meeting transcripts differ substantially from dynamic battlefield assessments based on emerging targeting information and force posture. Different types of decisions require different AI/ML integration models. Tasks with high variability and unpredictability require a more collaborative approach. In contrast, structured, repeatable decisions allow for greater automation. Common models include full delegation, interaction, and aggregation.26 In full delegation, AI/ ML tools make decisions without human intervention. In interaction, human and AI/ML tools sequentially make decisions such that the output of one decisionmaker provides the input to the other. Project Maven’s augmentation of the targeting cycle is an example of this interaction model. The model can be further subdivided into the “Centaur” and “Cyborg” approaches. The Centaur approach drives human and AI task division based on relative strengths. The Cyborg approach fuses human-AI decisionmaking in real time, leveraging AI for continuous analysis and adaptation while maintaining human oversight for context-driven judgments.27 In aggregation, human- and AI-based decisions are made independently, delegated based on strengths, and then aggregated into a collective decision. In this model, the AI/ML tool becomes a voting member in the decisionmaking process, often weighted based on various criteria. Each model reflects a different balance between human and AI/ML capabilities, tailored to the specific decision type.28

In addition to the type of decision being made, the distribution of decisionmaking power—where decisions occur—determines the optimal placement of AI/ML tools. Mission and environment typically drive this distribution across several structural types. Organizations emphasizing standardization tend toward professional or machine bureaucracies with centralized decisionmaking. Those requiring standardized output across semiautonomous units develop “divisionalized” structures. When project-based adaptive output is essential, organizations benefit from adhocracies—fluid structures with flatter decentralized authority.29 In all cases, AI/ ML tools should be integrated where decisionmaking occurs. Where mission and environment allow structural flexibility, decentralized decisionmaking can enhance AI’s impact by enabling faster and more adaptive responses at lower levels. For example, Ukraine recently embedded Palantir engineers with AI/ML tools into its frontline units to enable rapid decisionmaking on the battlefield.30

AI/ML tools perform best when accessing broad interconnected data sources. Consequently, AI/ML integration is particularly effective in rapidly composable and decomposable crossfunctional teams that synthesize diverse inputs across disciplines. For example, in the convergence between electronic warfare and cyberspace, AI-enhanced threat detection becomes most effective when cybersecurity, signals intelligence, and operations personnel collaborate closely rather than operating in isolated silos.

Conversely, highly centralized structures may limit AI/ML tools to merely advisory roles instead of active components in real-time operations. Formalized hierarchies may also impede the development of the organizational competencies needed for effective adoption.31 Even so, command-structured hierarchies like DOW can still benefit from increasing the vertical or horizontal decentralization of their decisionmaking wherever possible. Organizations face a fundamental tension between maintaining internal coherence for efficiency and adapting to environmental changes. Bureaucracies often struggle with rapid adaptation despite their efficiency at standardization.32 These organizational structures are slow to evolve, often failing to keep pace with changing environments that demand adaptation. Organizations must balance structural adaptation with internal consistency, implementing AI/ML tools according to the type of decision and aligning AI/ML tools to where they most effectively enhance speed, insight, and decision superiority.33

Processes. Adopting AI/ML tools into decisionmaking depends not only on what and where decisions occur, but also on how they are made. Processes are the interconnected activities that shape information flow up, down, and across an organization.34 They facilitate collaboration, coordination, and organizational decisionmaking and affect how AI/ML tools enhance these information flows. Processes apply to both hierarchical and decentralized structures when any level of collaboration between internal boundaries is required to accomplish the mission.35 For the joint force, informal and formal processes must operate seamlessly under conditions of uncertainty, time constraints, and adversary countermeasures.

Figure 2. Joint Planning Process Opportunities for AI/ML Tool Adoption

Joint Planning Process Opportunities for AI/ML Tool Adoption

Decisionmaking, while complex, is a cycle of linked information flows.36 John Boyd’s OODA loop—observe, orient, decide, and act—provides a helpful simplification. Born out of the needs of aerial combat, the OODA loop asserts cycling faster than an opponent through this loop would produce advantages in combat. Conceptually, Boyd’s ideas hold weight for using AI/ML tools in cognitive warfare. In the observe and orient steps, actors gather and perceive information and build mental models of the environment, threats, opportunities, and risks. An implied step is generating decision alternatives and comparing those alternatives before selecting one (the decide step) and then executing it (the act step).37 Given this simplified framework, AI/ML tools are well suited for adoption in observe-orient processes and in generating and comparing decision alternatives. Using the Joint Planning Process (JPP) as a representative military decisionmaking process highlights these opportunities (see figure 2).

In its most distilled form, the JPP is a series of information flows executed across several functions to produce products and staff actions leading to commander decisions. Doctrinally, the JPP facilitates planning interactions among the commander, planning staff, and lower echelons.38 This framework is a recursive, assessment-informed process in which issues that planners discover in later steps drive adjustments to earlier steps, and commanders have the flexibility to truncate, modify, or concurrently execute its seven steps depending on the situation or available time.39

To initiate planning, the commander must have a means by which to recognize, monitor, and react to changing trends in the environment. If the commander centralizes this function, he or she risks missing salient trends. However, disaggregating this function increases the requirement for processes. Previously, the larger the organization and the more disaggregated the processes, the more manpower was required to make decisions, resulting in slower decision cycles. AI/ML tools can accelerate decisionmaking processes by providing faster pattern recognition and sensing insights from a wider data set, enabling proactive rather than reactive planning.40 For example, AI/ML tools can rapidly analyze raw intelligence data and highlight changes that exceed human-defined thresholds, reducing the need for manual data analysis and allowing humans to focus on critical and creative thinking.41

Once planning is initiated, AI/ML accelerates data-intensive mission analysis by fusing intelligence sources and force readiness reporting into a unified operational picture. This is critical for framing the problem and guiding COA development. Previously, these inputs were processed and visualized separately and with direct staff intervention, making it difficult for commanders to develop a comprehensive picture of the operating environment and the military problems they must solve. Instead, planners can use AI/ML tools to process terabytes of data, rapidly displaying information according to human-defined parameters. They can also use AI/ML tools to provide multiple visualization options for decisionmakers to consider.42

Unmanned combat aerial vehicle YFQ-42A Collaborative Combat Aircraft, developed in partnership with General Atomics, conducts flight testing in California, August 27, 2025 (Courtesy General Atomics)

After this step, planners must develop decision alternatives for commander approval. In the JPP, this involves COA development, COA analysis and wargaming, and COA comparison. At this stage, planning shifts from critical to creative thinking. Still, planners currently generate solutions using manual methods of iteration, limited by the expertise and experience of their teams, and present the results using antiquated visualization tools like PowerPoint. AI/ML tools allow aggregation of large amounts of data across disparate functions and sources to generate multiple COAs faster and from a wider range of perspectives, reducing reliance on individual expertise and manual iteration.

Planners can use AI/ML tools to assume a unique persona when assessing potential adversary, neutral, and friendly reactions. With proper inputs, AI/ML tools can also role-play the “red team,” speeding up the iterative play of war games. These tools facilitate the background analysis needed to identify a COA’s strengths, weaknesses, and risks. Planners can also use AI/ML tools to assess multiple COAs based on the commander’s priorities, constraints, and restraints.43 These opportunities for AI/ ML tool integration allow planners to compare, refine, and evaluate COAs, deepening the analysis supporting their COA recommendations to the commander. While AI-generated COAs are powerful, planners must resist overreliance on them and ensure that machine-generated options are filtered through human judgment, operational context, and commander’s intent. As previously noted, AI/ ML tools should augment, not replace, the iterative cognitive processes that underpin military decisionmaking.

Once the commander selects a COA, planners can use AI/ML tools to draft and disseminate the plan and orders on behalf of the commander. AI/ML tools can craft outputs from a wide range of inputs based on specified formats. Currently, the process of generating plans and orders involves the manually intensive task of transcribing the analysis and decisions made during planning to generate products like OPORDs.

Integrating AI/ML tools into the JPP illustrates just one of many opportunities where AI/ML-enabled processes enhance the effectiveness of information flow at machine speeds. AI/ML tools enhance a decisionmaker’s ability to observe and orient and then develop a wide range of decision alternatives for refinement, comparison, and evaluation before selecting the optimal choice. For other processes, the adoption challenge lies in recognizing which information flows AI/ML tools are primed to support and then optimizing their use. Predictable and repeatable processes such as intelligence synthesis and aggregation, as well as force readiness assessment, lend themselves to more automated decisions using AI/ML tools. Ambiguous, iterative, or creative processes like mission analysis, adversary modeling, and COA development lend themselves to interaction models like the Centaur or Cyborg approaches discussed earlier. Processes related to the evaluation of decision alternatives, such as COA comparison, lend themselves to the aggregated use of AI/ML tools.

Incentives. Incentives drive behavioral change, aligning individual and organizational goals to ensure mission effectiveness. If DOW is to pursue the broadscale adoption of AI/ML tools into decisionmaking, its leaders must carefully evaluate the impact of incentives and disincentives on organizational performance, particularly regarding the acceptance of change. The status quo acts as an adversary to change, manifesting in deeply rooted organizational habits that create resistance to the changes needed for progress.44

Resistance can be individual or organizational. Individual resistance is either malicious or nonmalicious. Malicious resistors actively create obstacles to preserve self-value, often driven by fears of emerging technology displacing their position in the organization. Nonmalicious resistors, by contrast, may simply lack understanding of the change, making them reluctant to venture beyond familiar practices.45

Autonomous low-profile vessel sails on Del Mar Boat Basin to test its capabilities as part of Project Convergence Capstone 4, February 23, 2024, at Camp Pendleton, California (U.S. Marine Corps/Kevin Ray J. Salvador)

Organizational resistance may manifest in several ways. First, social and cultural resistance may stem from generational preferences for traditional methods. This could be due to a lack of AI/ML tool literacy or misunderstandings about the technology’s potential application. This resistance is more pronounced in hierarchical structures like DOW, where time-in-service promotion systems concentrate decisionmaking authority within a single generation. Second, ethical and moral criticism creates organizational resistance that centers on concerns about trustworthiness, authenticity, and potential plagiarism of using AI-generated content. “AI shaming”—the criticism of using AI/ML tools based on ethical concerns, perceptions of laziness, or trust issues—can manifest both horizontally and vertically within an organization.46 Third, perceptions of the impact that AI/ ML tools have on individual skill requirements, job security, and authority may contribute to this resistance.47

Within each category of resistance, there is likely a champion of the status quo whose behavior joint leaders must influence by providing appropriate incentives for change. For example, this could be the senior warrant officer preferring traditional tools, a noncommissioned officer concerned about security implications, a staff officer fearing job obsolescence, or a general officer who does not trust AI-produced products, demanding intensive staff labor no matter the impact on efficiency.

Overcoming this resistance requires a balanced approach to incentives. While structural and process changes can address tangible obstacles, overcoming entrenched habits requires careful attention to incentives. Incentives can be extrinsic (for example, compensation, promotions, and recognition) or intrinsic (job satisfaction, challenging work, and personal fulfillment).48 While extrinsic incentives may help jump-start the early adoption of AI/ML tools, intrinsic incentives ultimately shape the organizational culture needed for longterm transformation.

Intrinsic incentives offer several opportunities for individual and organizational growth and development. For instance, AI/ML tools may enhance individual and group research efficiency across various disciplines, subsequently streamlining product-generation timelines. Additionally, human-machine collaboration allows organizations to leverage the creative and computational strengths of both, facilitating rapid data analysis and creative problem-solving. Finally, mitigating self-biases through education and training develops a growth-minded culture within the organization. This type of culture unlocks additional innovation, normalizes change, and increases intrinsic incentives that drive individuals and organizations toward aligned goals.

The combination of extrinsic and intrinsic incentives should be tailored to the type of resistance the organization experiences. However, organizations may be constrained by what incentive levers they can affect to motivate desirable behaviors. This leaves joint leaders with the challenge of identifying the right influence tools to promote the growth and transformation within their organizations to achieve widescale adoption of AI/ML tools.

Leadership and Management. An organization’s leadership and management greatly influence organizational design factors affecting the adoption of AI/ML tools into decisionmaking. However, joint leaders must first address their own AI/ML literacy before they can effectively adapt the other organizational design factors for AI/ML tool adoption. Without understanding AI/ML capabilities and limitations, leaders risk either over-relying on these tools or under-utilizing them because of skepticism.49 For example, using AI/ML-enabled decision aids can enhance battlefield effectiveness, but only if commanders know how to interpret their suggestions and trust their outputs.

Beyond developing personal AI/ML literacy, joint leaders must articulate a compelling vision for change and a clear path to pursue it.50 This communication is particularly important for addressing nonmalicious resistance, which often stems from a lack of understanding rather than active opposition. Leaders must recognize that resistance to AI/ML adoption will manifest differently across their organizations and tailor incentives to overcome the specific type of resistance they encounter. Leaders who create a growth-minded organizational culture create a powerful complement to more direct incentives. Such cultures become self-reinforcing as improved results demonstrate the value of AI/ML tools, normalizing their adoption.51

Joint leaders must systematically assess how organizational design factors affect AI/ML adoption in their units. For people, this means driving the training initiatives to shift mindsets from “search-engine thinking” to understanding the interactive use of AI/ML tools. It also means driving the training initiatives to develop new skill sets like prompt engineering and iteration techniques to optimize human-AI collaboration. Where mission and environment allow flexibility, joint leaders should consider structural choices that better enable AI/ML adoption to accomplish their mission through faster and wider-informed decisionmaking. This generally involves pushing decisionmaking down and to the edges of an organization, flattening the structure to facilitate cross-functional collaboration, iteration, and parallel use of AI/ ML tools. To do this, joint leaders must assess what decisions are made in an organization and where decisions are made, restructuring to optimize the use of AI/ML tools. When necessary, command relationships drive hierarchical structure, and joint leaders should still identify vertical and horizontal decentralization opportunities to maximize AI/ML tool effectiveness. In processes, joint leaders must guide the adoption of AI/ML tools into the information flows that feed their decision cycles, identifying which flows benefit from fully automated or hybrid approaches. Ultimately, joint leaders must recognize that the adoption of AI/ML tools requires synchronized adaptation across all organizational design factors.

Leadership and management play an outsized role in shaping organizational design factors. The combination of these factors drives an organization’s performance and culture. Joint leaders who fail to proactively adapt their organizations for AI/ML adoption risk leaving the joint force anchored to legacy decisionmaking models that compromise strategic advantage.

Conclusion

In modern warfare, decision dominance is highly correlated with victory. AI/ML tools are reshaping the battlespace by enhancing the speed and precision of decisions. For DOW, failure to meaningfully adopt these tools carries severe consequences, including slower operational tempo, increased cognitive overload, a higher probability of intelligence blind spots, and reduced force readiness.52

This analysis reveals that widescale integration of AI/ML tools hinges not only on technological capability and access but also on organizational design factors affecting the adoption of AI/ML tools. To break from a status quo deeply rooted in outdated habits of human cognition, institutional resistance, and legacy decisionmaking processes, DOW must adapt its people, structure, processes, incentives, and leadership and management.

The imperative is clear. DOW must accelerate the adoption of AI/ML tools into its decisionmaking. Failure to do so risks the joint force being outpaced by adversaries who weaponize AI/ ML tools to operate more effectively. As these tools move further left in the decision continuum, they will increasingly shape how problems are framed, options generated, and actions selected. Human judgment still plays a role, and must evolve in parallel, but it must not become a brake on progress. In short, failure to adopt AI/ML at speed invites obsolescence, an untenable option for U.S. national security.53 JFQ

Notes

1 Marie Morelle et al., “Towards a Definition of Cognitive Warfare,” HAL Open Science, December 7, 2023, Conference on Artificial Intelligence for Defense, DGA Maîtrise de l’Information, November 2023, Rennes, France, https://hal.science/hal04328461v1/document.

2 Patrick Tucker, “How China Used TikTok, AI, and Big Data to Target Taiwan’s Elections,” Defense One, April 8, 2024,
https://www.defenseone.com/technology/2024/04/how-china-usedtiktok-ai-and-big-data-target-taiwanselections/395569/.

3 Kevin Pollpeter and Amanda Kerrigan, The PLA and Intelligent Warfare: A Preliminary Analysis, with Andrew Ilachinski (Arlington, VA: CNA, October 2021), https://www.cna.org/reports/2021/10/The-PLA-and-Intelligent-Warfare-A-Preliminary-Analysis.pdf.

4 Sam Ransbotham et al., “Achieving Individual—and Organizational—Value With AI,” MIT Sloan Management Review, October 31, 2022,
https://sloanreview.mit.edu/projects/achieving-individual-and-organizational-value-with-ai/.

5 “Payments Unbound,” n.d., accessed August 5, 2025, https://www.jpmorgan.com/payments/payments-unbound/volume-3/smart-money; Theo Stein, “NOAA Research Develops an AI-Powered Sibling to Its Flagship Weather Model,” NOAA Research, July 22, 2025,
https://research.noaa.gov/noaa-research-develops-an-ai-powered-sibling-to-its-flagship-weather-model/.

6 Kathy Cao et al., “Countering Cognitive Warfare: Awareness and Resilience,” NATO Review, May 20, 2021,
https://web.archive.org/web/20250402203501/https://www.nato.int/docu/review/articles/2021/05/20/countering-cognitive-warfare-awareness-and-resilience/index.html.

7 Nicolas de Bellefonds et al., Where’s the Value in AI? (Boston: Boston Consulting Group, October 2024),
https://www.bcg.com/publications/2024/wheres-value-in-ai.

8 Connor Grennan, “Connon Grennan on Moving Beyond the ‘Search Engine Mindset,’” interview by Molly Wood, Microsoft WorkLab, January 7, 2025, podcast audio, 26:50, https://www.microsoft.com/en-us/worklab/podcast/conor-grennan-on-moving-beyondthe-search-engine-mindset.

9 Bellefonds et al., Where’s the Value in AI?

10 Rudy Ruitenberg, “Survival of the Quickest: Military Leaders Aim to Unleash, Control AI,” Defense News, February 13, 2025,
https://www.defensenews.com/global/europe/2025/02/13/survival-of-the-quickestmilitary-leaders-aim-to-unleash-control-ai/.

11 Ruitenberg, “Survival of the Quickest.”

12 Jay R. Galbraith, “Organization Design Challenges Resulting from Big Data,” Journal of Organization Design 3, no. 1 (2014), 2–13,
http://dx.doi.org/10.7146/jod.8856.

13 Jay R. Galbraith, Designing Organizations: Strategy, Structure, and Process at the Business Unit and Enterprise Levels, 3rd ed. (Hoboken, NJ: Jossey-Bass, 2014), 52–3.

14 Galbraith, Designing Organizations, 22–3.

15 Galbraith, Designing Organizations, 37–8.

16 Galbraith, Designing Organizations, 44.

17 Galbraith, Designing Organizations, 22–3.

18 Jay R. Galbraith, “The Star Model,” n.d., 4–5, https://jaygalbraith.com/services/star-model/.

19 Casey Henley, Foundations of Neuroscience (East Lansing: Michigan State University Libraries, 2021), 349–53,
https://openbooks.lib.msu.edu/neuroscience/.

20 Conor Grennan uses the term searchengine mindset in his course. See “Generative AI for Professionals: A Strategic Framework to Give You an Edge,” AI Mindset, https://www.ai-mindset.ai/gen-ai-for-professionals. See also Connor Grennan, “Connon Grennan on Moving Beyond the ‘Search Engine Mindset,’” interview by Molly Wood.

21 Fabrizio Dell’Acqua et al., “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality,” SSRN Scholarly Paper no. 4573321 (Social Science Research Network, September 15, 2023),
https://doi.org/10.2139/ssrn.4573321.

22 “Generative AI for Professionals.”

23 “AI Rapid Capabilities Cell,” DOD Chief Digital and Artificial Intelligence Office, accessed February 20, 2025,
https://www.ai.mil/Initiatives/AI-Rapid-Capabilities-Cell/.

24 Non-AI users relied solely on conventional, human-driven workflows, resulting in lower productivity. AI with nontrained users achieved productivity improvements but were prone to increased errors due to reliance on AI for unsuitable tasks. AI with trained users leveraged iterative prompting to refine outputs, optimizing task performance by balancing AI capabilities and human intuition. See Dell’Acqua et al., “Navigating the Jagged Technological Frontier.”

25 Decision complexity varies based on the breadth of information considered, output interpretation requirements, option generation, time constraints, and repeatability needs. See Yash Raj Shrestha et al., “Organizational Decision-Making Structures in the Age of Artificial Intelligence,” California Management Review 61, no. 4 (2019), 1, https://doi.org/10.1177/0008125619862257.

26 Shrestha et al., “Organizational DecisionMaking Structures in the Age of Artificial Intelligence,” 5, 9–10.

27 Dell’Acqua et al., “Navigating the Jagged Technological Frontier.”

28 Shrestha et al., “Organizational DecisionMaking Structures in the Age of Artificial Intelligence,” 12.

29 Henry Mintzberg, “Organization Design: Fashion or Fit?” Harvard Business Review, January 1, 1981,
https://hbr.org/1981/01/organization-design-fashion-or-fit.

30 Richard Farnell and Kira Coffey, “AI’s New Frontier in War Planning: How AI Agents Can Revolutionize Military Decision-Making,” Harvard Kennedy School Belfer Center for Science and International Affairs, October 11, 2024,
https://www.belfercenter.org/research-analysis/ais-new-frontier-war-planning-how-ai-agents-can-revolutionize-military-decision.

31 Mathieu Bérubé et al., “Barriers to the Implementation of AI in Organizations: Findings from a Delphi Study,” paper presented at Hawaii International Conference on System Sciences, 2021, https://doi.org/10.24251/HICSS.2021.805.

32 Mintzberg, “Organization Design.”

33 Mintzberg, “Organization Design.”

34 Amy Kates and Jay R. Galbraith, Designing Your Organization: Using the STAR Model to Solve 5 Critical Design Challenges (Hoboken, NJ: Jossey-Bass, 2007), 17, http://ebookcentral.proquest.com/lib/nationaldefense-ebooks/detail.action?docID=315230.

35 Kates and Galbraith, Designing Your Organization, 37.

36 Kates and Galbraith, Designing Your Organization, 4.

37 “John Boyd and the OODA Loop,” Psych Safety, n.d., accessed February 20, 2025, https://psychsafety.com/john-boyd-and-the-ooda-loop/.

38 Joint Publication 5-0, Joint Planning (Washington, DC: The Joint Staff, July 1, 2024), III–10.

39 The seven steps of the JPP are planning initiation; mission analysis; course of action (COA) development; COA analysis and wargaming; COA comparison; COA approval; and plan or order development.

40 Thomas W. Spahr, “Raven Sentry: Employing AI for Indications and Warnings in Afghanistan,” Parameters 54, no. 2 (2024),
https://press.armywarcollege.edu/parameters/vol54/iss2/9/.

41 Justin Doubleday, “Pentagon Shifting Project Maven, Marquee Artificial Intelligence Initiative, to NGA,” April 26, 2022,
https://federalnewsnetwork.com/intelligence-community/2022/04/pentagon-shifting-project-maven-marquee-artificial-intelligence-initiative-to-nga/.

42 International Committee of the Red Cross (ICRC) and Geneva Academy of International Humanitarian Law and Human Rights, Artificial Intelligence and Related Technologies In Military Decision-Making on the Use of Force in Armed Conflicts (Geneva: ICRC, March 2024),
https://www.icrc.org/en/publication/expert-consultation-report-artificial-intelligence-and-related-technologies-military.

43 Farnell and Coffey, “AI’s New Frontier in War Planning.”

44 Tom Galvin, Leading Change in Military Organizations: Primer for Senior Leaders (Carlisle, PA: U.S. Army War College, 2018), 97,
https://apps.dtic.mil/sti/citations/AD1124769.

45 Galvin, Leading Change in Military Organizations, 97.

46 Louie Giray, “AI Shaming: The Silent Stigma among Academic Writers and Researchers,” Annals of Biomedical Engineering 52, no. 9 (2024), 2319, https://doi.org/10.1007/s10439-024-03582-1.

47 Giray, “AI Shaming,” 2320–21.

48 Galbraith, Designing Organizations, 44.

49 Bérubé et al., “Barriers to the Implementation of AI in Organizations.”

50 Galvin, Leading Change in Military Organizations, 98.

51 Edgar H. Schein, Organizational Culture and Leadership, 4th ed. (Hoboken, NJ: JosseyBass, 2010).

52 David Vergun, “AI to Give U.S. Battlefield Advantages, General Says,” U.S. Department of Defense, September 24, 2019,
https://www.defense.gov/News/NewsStories/Article/Article/1969575/ai-to-giveus-battlefield-advantages-general-says/.

53 During the preparation of this work, the research team used ChatGPT 4.0, Claude, and Perplexity to assist with outlining, structure, and proofreading. Subsequently, the research team thoroughly reviewed and edited the content as necessary.


Combating IUU Fishing in the South American Pacific: An Opportunity to Counter Chinese Influence Closer to Home
By Alexander Goodno | Jan. 9, 2026

Download PDF

Coastguardsmen from USCGC James conduct boarding of fishing vessel in Eastern Pacific, August 3, 2022 (U.S. Coast Guard)
Colonel Alexander Goodno, USMC, is Commanding Officer of Marine Aircraft Group 13.

In August 2022, USCGC James took evasive action to avoid a Chinese-flagged vessel that was attempting to ram the cutter in the Pacific Ocean.1 While most confrontations between the United States and China center around Taiwan or the South China Sea, this event took place off the coast of South America—nearly 10,000 miles (16,000 kilometers) from mainland China. The incident had little to do with Chinese territorial expansion. Instead, it focused on illicit fishing activity, the Chinese vessel being a member of China’s distant water fishing (DWF) fleet, the largest in the world.2

For many in the United States, news of this encounter was the first time they had heard of China’s fishing activities in the Western Hemisphere; however, highstakes encounters between Chinese fishing vessels and South American authorities have been common over the past decade. In 2016, an Argentine coast guard vessel sank the Lu Yan Yuan Yu 010, and in 2019, it fired on the Hua Xiang 801; both were Chinese DWF vessels caught fishing inside Argentina’s exclusive economic zone (EEZ).3 Similarly, the Ecuadorean navy confiscated the Fu Yuan Yu Leng 999 in 2017 for fishing inside the Galápagos Maritime Reserve.4

With China’s expanding presence in South America, these at-sea confrontations have tarnished the positive image China has tried to convey. They have also created an opportunity that the United States could exploit. By establishing itself at the forefront in combating illegal, unregulated, and unreported (IUU) fishing activities off the Pacific coast of South America, the United States could strengthen its role as a leader in the Western Hemisphere and counter growing Chinese influence in South America. To achieve this end, the United States must adopt a uniform approach to curbing IUU fishing, encourage the South Pacific Regional Fisheries Management Organisation (SPRFMO)—an international treaty-based organization—to implement unambiguous regulations that nations could easily enforce, and strengthen counter–IUU fishing operations with South American partner countries as well as with China.

China’s Growing Influence in South America

China’s presence in the Southern Hemisphere is not new, but its reach and ambitions on the South American continent have expanded significantly over the past 15 years. At the turn of the millennium, as China’s mineral resources depleted domestically, Beijing began significantly increasing trade with South America, importing its untapped raw materials.5 A decade later, China expanded the scope of its Latin American interests, incorporating South America into its Belt and Road Initiative (BRI) and encouraging increased investment on the continent.6 These Chinese investments have largely focused on infrastructure, such as China’s plan for the Twin-Ocean Railway, which would connect Brazil’s Atlantic coast to Peru’s Pacific coast, or its newly completed megaport in Chancay, Peru.7 China has similarly encouraged companies to invest in South American utilities. Huawei, China’s premier telecom company, was awarded separate contracts to build out a national 5G network in Ecuador, Chile, and Peru, and in 2024, China finalized its purchase of equity stakes in two of Peru’s largest power suppliers.8

While many of these projects appear primarily focused on economic opportunities, they also support Beijing’s goal of increasing its influence and cooperation on the South American continent. China has been open about these objectives. In the 2010s, Beijing established the China–Comunidad de Estados Latinoamericano y Caribeños (CCF), outlining a desire to bolster Sino–Latin American cooperation across multiple endeavors: space technology, disaster prevention, and climate change, among others.9

Their plan for expanded collaboration and partnership on the South American continent has had success. Consider China’s relationship with Chile. At the start of the 21st century, China’s relationship with Chile primarily focused on copper exports; today, their relationship is much more intertwined. During the COVID-19 pandemic, the two countries partnered in developing a coronavirus vaccine.10 More recent, the two countries have been moving forward on a joint venture to build a 10-square-mile (26-square-kilometer) astronomical park in the Chilean Ventarrones Mountains that will house over 100 telescopes, including a 12-meter telescope.11 While China’s initial forays in South America may have been transactional, its future on the continent appears politically much broader in scope.

China’s increasing presence in South America has not gone unnoticed. Although Beijing claims that its motive behind BRI investments and CCF collaborations is to bolster developing nations, Western policymakers believe otherwise. As an example, analysts at the International Institute for Strategic Studies and Asian–Latin American professors collectively suggest that specific infrastructure projects, like a South American transcontinental railway, could be a means for China to bypass the Panama Canal or provide a gateway for future naval logistics bases, similar to China’s foreign military base in Djibouti.12 Similarly, U.S. investigative journalists have highlighted that the proposed Chilean Ventarrones observatory could also serve as a military node, monitoring U.S. satellites and space operations, and complete China’s network of five global sites needed for it to scan the entire northern and southern hemispheric skies every 30 minutes.13

In concert with Washington’s apprehension, skepticism is percolating through the South American populace over Chinese intentions on their continent. South American manufacturing laborers, whose factories began closing due to low-cost imports, strongly oppose increased trade with China.14 Additionally, Peruvian military leaders and business officials have argued that economic dependency on China and near-total Chinese control over Peruvian utilities create a national security liability in the region.15 Something Fishy on the High Seas In parallel with South American concern over China’s impact on the continent, discord over China’s fishing operations is also garnering increased attention. China’s South American DWF fleet—which began as a relatively small enterprise three decades ago, responding to dwindling Chinese squid fisheries—has grown exponentially and now numbers more than 500 vessels.16 In an industrial-like operation, the at-sea fishing vessels rely on refrigerated mother ships to store their catch, transport fish to ports, and sustain the vessels with food and fuel. The fleet operates for months on end and can resemble an island city-state, covering swaths of the ocean nearly 200 miles (300 kilometers) long, equivalent to the length of the entire coastline of South Carolina.

The imposing presence of Chinese DWF creates a growing problem for the Pacific coastal nations of South America. Though China’s DWF vessels claim to operate outside each country’s EEZ, their practices are questionable: turning off their automatic identification systems to traverse into EEZs unnoticed, casting expansive fishing nets underwater into an EEZ while keeping the ship outside of the EEZ’s boundary, or fishing for protected or regulated species.17 As an example, in 2017, the Ecuadorean navy discovered 7,639 unreported sharks aboard the Fu Yuan Yu Leng 999, a Chinese vessel registered to catch squid.18 More concerning is the impact that industrial-scale fishing has had on the ecosystem, disrupting migratory patterns of fish along the South American coast and depleting species necessary to support local artisanal fisheries.19 For countries like Ecuador, the seventh-largest tuna-fishing nation in the world, or Chile, where fish is its largest export after copper, the impact is tremendous.20 In 2020, IUU fishing accounted for a nearly $2.3 billion drain on South America’s economy, with $600 million of these losses coming from individual incomes.21 Left unchecked, the situation in the southern Pacific could gut the South American fishing industry, to say nothing of the ripple effects it will have across global fish stocks.

South America’s Pacific countries are not standing idly by. As the problem has grown, many of these nations have begun strengthening their capacities to surveil and patrol their EEZs. Already a regional leader in surveillance, Chile has invested significantly in unmanned aerial vehicles and satellite technology to further increase its ability to monitor maritime protected areas farther offshore.22 Like its neighbor to the south, Ecuador has expanded its surveillance capabilities. Leveraging technology used by Canada’s Department of Fisheries and Oceans, Quito has begun using satellites and artificial intelligence to find and track “dark vessels”—that is, ships that turn their transponders off to evade detection when crossing into an EEZ unauthorized.23

At the same time as they seek to find offending fishing vessels from the sky, these countries are also expanding their naval capacity to patrol the oceanic commons. In April 2024, Peru signed a deal with South Korea’s Honda Heavy Industries to build one multirole and one offshore patrol vessel. Lima hopes to add these to the eight Peruvian-built patrol boats it recently purchased, which have been successful in aiding Peru’s efforts against IUU fishing.24 Columbia and Ecuador are also expanding their navies, adopting similar plans to increase the number of multipurpose and offshore patrol vessels within their fleets.25

Nevertheless, despite these noteworthy efforts, large-scale IUU fishing in the South American Pacific persists. Part of the problem is a lack of adequately trained personnel. Multiple reports highlight that Ecuador lacks the necessary staffing to monitor its offshore waters properly and that its existing maritime enforcement personnel do not fully understand available legal tools against IUU fishing.26 Chile is in a similar predicament. Consider that while Santiago invests more in its navy than nearly every other Central and South American country, its ratio of navy personnel to square mile of coastline is lower than half of these same countries.27 Chile simply does not have the resources to cover its vast territorial waters.

The South American Pacific’s demonstrated desire to curb IUU fishing, combined with its existing resource shortfall, presents a window of opportunity for Washington. To date, many of the U.S. efforts to counter China’s global influence have focused on the Western Pacific. In the South American Pacific, Washington could both challenge Beijing’s behaviors on this side of the globe while also strengthening relations with its partner countries to the south. In short, combating IUU fishing in the region requires deliberate action: South American countries cannot do it alone, it serves U.S. interests, and it is an effort that the United States can take the lead in delivering on.

During Asia-Pacific Economic Cooperation Peru 2024 Forum, China’s President Xi Jinping meets with Peru’s President Dina Boluarte in Lima to strengthen their strategic partnership and celebrate inauguration of Chancay megaport, November 14, 2024 (Fotoholica Press Agency/Alamy Live News)

Leading the Effort to Combat IUU Fishing

To succeed as a leader in countering IUU fishing in South America, Washington should focus on three lines of effort—each tailored to combat IUU fishing and build trust among its southern peers. These lines of effort include consistent messaging, regional fisheries management organization (RFMO) measures, and inclusive multinational training and operations.

1. Consistent Messaging. Adopting an even-handed approach will be essential for the United States to assert itself as a leader in South America’s campaign against IUU fishing. In the past, Washington’s attempts to enforce international policy have been inconsistent, holding one nation accountable while disregarding another. To avoid this perception in the Latin American South Pacific, consistency in America’s messaging and enforcement will help legitimize its cause.28

Regarding messaging, the United States must implement a precise information operations campaign to voice concerns over all forms of IUU fishing. All too often, countries and spokespeople reduce the term IUU fishing to illegal fishing. The concept is much broader than that. The Food and Agriculture Organization (FAO) of the United Nations defines IUU fishing as illegal—fishing in sovereign waters without permission, unreported—not fully explaining in which type of fishing a vessel is engaging or misreporting the number of fish caught, and unregulated—failing to abide by national or international regulations and responsibilities focused on preserving maritime life.29 Careless language creates ambiguity and provides a scapegoat for governments whose vessels are the offenders. This is particularly the case on the high seas (the oceanic area outside of an EEZ), where most infractions are not necessarily illegal—since vessels are not fishing within sovereign waters—but rather violate reporting or regulation requirements laid out by RMFOs, the United Nations, or other international fishing agreements.

The United States also needs to focus on combating all IUU fishing. While the introduction of this article highlights multiple standoffs with China’s DWF fleet, China is not the only offender. China accounts for roughly half the DWF activity off the coast of South America, with DWF fleets from South Korea, Taiwan, and Spain making up the other half.30 While Chinese fleets may be making the most headlines, coast guards and navies should not focus solely on Chinese DWF fleets but also on regulating all DWF activity. Beyond DWF activities, U.S. efforts should also consider those infractions by traditional small-scale fishing fleets closer to shore, especially since such infractions may be a more pressing concern to a local population than DWF violations hundreds of miles away. For example, Peru has voiced as much concern about Ecuadorean fishing vessels within its EEZ as it has over Chinese DWF.31 The key throughout must be consistency, not just in messaging but also in enforcement.

2. Strengthening RFMO Regulations. As has been previously touched on, successfully enforcing fishing practices on the high seas depends on the regulatory measures of the relevant RFMOs, which are international organizations that provide regulations governing fishing practices on the high seas in a specific area.32 Their membership includes nations located near the maritime region or with a vested fishing interest in the region.33 The high-seas area off the western coast of South America falls within SPRFMO’s jurisdiction, and the organization includes the United States, China, Taiwan, and the European Union among its nonlocal members.34 The problem with RFMOs is that regulations can be ambiguous, and since the responsibility for taking punitive action against an offending fishing vessel falls on the flagged nation of that vessel, how these countries interpret the regulations and impose penalties can vary. For example, in certain instances, Beijing has been reluctant to impose penalties on Chinese DWF vessels, citing a lack of sufficient evidence to meet its threshold for violating SPRFMO’s regulations protecting fish stocks.35 As an SPRFMO member, the United States should lead efforts with fellow member nations to enact regulatory measures that achieve the organization’s conservation aspirations but are less subjective in interpretation.

Inspiration to better direct SPRFMO’s future conservation measures is available among its fellow member states. The West and Central Pacific Fisheries Commission (WCPFC) and the North Pacific Regional Fisheries Commission (NPFC), two historically strong RFMOs, are good examples.36 Six years ago, the WCPFC enacted a comprehensive measure restricting the overfishing of bluefin tuna and has since seen bluefin tuna populations rebound dramatically, surpassing the WCPFC’s initial 5-year target within its first year.37 SPRFMO could enact similarly stringent fishing conservation measures targeting specific species.

Other measures from peer RFMOs have targeted more transparent illicit activity associated with DWF. For example, by targeting human labor abuse at sea, a crime with strong ties to IUU fishing, governments have been able to curb IUU fishing in certain parts of the globe. Consider that, under pressure from the European Union, Thailand enacted a series of stricter labor laws for its fishing industry in the 2010s, indirectly reducing the number of Thai fishermen engaging in IUU fishing.38 SPRFMO attempted such an indirect approach in 2024; however, its regulation only encourages nations to comply with international labor standards.39 Instead, it should follow the WCPFC’s lead by enacting regulations that establish a legal requirement for minimum labor standards on board fishing vessels within its waters.40 In addition to looking at regulations regarding human labor rights, SPRFMO might also consider examining the NPFC’s regulations combating pollution caused by DWF, or focusing on drug trafficking, an illicit activity that the Ecuadorean navy has regularly observed aboard IUU fishing vessels in the South American Pacific.41

Beyond arguing for the United States to leverage SPRFMO as a force enabler, Washington will need to overcome enforcement challenges inherent in the structure of RFMOs. For example, adding new conservation measures typically requires approval from a supermajority of RFMO members, making it challenging to pass measures with teeth.42 SPRFMO faced this roadblock in 2021, when numerous South American countries proposed various measures, all of which China vetoed.43 At impasses such as these, the United States must take the lead and work with China to find common-ground measures that can still effect change. Proposing fishing moratoriums, a regulation China openly supports, backed by scientific inputs from SPRFMO members, is a start.44 The United States can also leverage China’s global status and membership in numerous other RFMOs to identify proven measures to which China is already a party or has already approved elsewhere. China’s membership in the WCPFC and NPFC means that some of the examples highlighted in the preceding discussion could be suitable options. Some critics also cite RFMOs’ inability to enforce regulations.45 However, SPRFMO’s recent passage of a measure authorizing high-seas boarding inspections could be a game-changer.46 Although still gaining acceptance in RFMOs worldwide, these inspections have proved highly effective in fostering a culture of compliance.47 In short, with dedicated effort, SPRFMO has the potential to be an effective partner for U.S. operations against IUU fishing on the high seas.

3. A Multinational Approach. Whether enforcing SPRFMO regulations or South American national law, identifying IUU fishing violators and holding them accountable must be a multinational effort. Given its vast resources, the United States has a distinct opportunity to emerge as a leader in providing this capacity at sea. South American nations have routinely demonstrated a willingness to conduct boardings within their EEZ; however, they are less inclined to do so on the high seas.48 Part of the problem is due to the limited number of Latin American naval vessels that can travel beyond the EEZ, and as highlighted previously, another part is due to a lack of personnel trained in countering IUU fishing.49

The United States can assist with the former by dedicating more of its vessels to counter–IUU fishing operations in South America. The desire within recent White House administrations to draw down in the Middle East and refocus on the Pacific could provide this opportunity, diverting U.S. Coast Guard cutter deployments from U.S. Central Command (USCENTCOM) to U.S. Southern Command (USSOUTHCOM). Perhaps more feasibly and with far-reaching impact, the United States can help the latter through increased training efforts and shiprider agreements. Unfortunately, despite the Maritime Security and Fisheries Enforcement Act of 2019 (16 U.S.C. § 8001–8041) directing the increase of bilateral agreements to make shipriding a reality, little action has been taken toward this effort.50 The U.S. Department of State must be more aggressive in establishing mechanisms for these invaluable cross-training opportunities.

In contrast to the inaction on bilateral shipriding agreements, USSOUTHCOM and the USCG have been aggressive in building robust programs to address needed multinational training on countering IUU fishing. Leveraging its U.S. Pacific Regional Fisheries Training Center, the USCG has established a mobile training course designed for partner nations.51 The course trains foreign sailors and coastguardsmen on boarding procedures, evidence collecting, authorities, case studies, and mock boardings.52

In tandem with these training initiatives, the United States should also increase opportunities to conduct counter–IUU fishing drills within multinational military exercises and operations in Latin America. Participation not only would achieve the goal of training more South American partners in counter–IUU fishing operations but also could provide a temporary infusion of U.S. counter–IUU fishing assets in the South American Pacific. Consider USSOUTHCOM-sponsored exercise Resolute Sentinel. Started in 2021, this U.S.–South American exercise, which includes all four South American Pacific countries, focuses on joint military training and readiness in humanitarian assistance and disaster response, cybersecurity, space domain awareness, and counterthreat training.53 Though combating IUU fishing is not among these listed lines of effort, in 2023, the U.S. Coast Guard embedded its IUU fishing mobile training course within the exercise’s construct.54 Leveraging exercise assets, the U.S.-led multinational training course included a capstone event, where students and instructors flew onboard a U.S. C-130 over the Peruvian EEZ and high seas to put their training into practice.55 USSOUTHCOM has since maintained counter–IUU fishing training within Resolute Sentinel’s framework, adding USCG-led counter–IUU fishing ship boardings during its 2024 exercise.56

Ecuador’s exercise Galapex, a 2-week effort focused entirely on combating IUU fishing near the Galàpagos, holds even greater promise in demonstrating U.S. commitment to multinational training on countering IUU fishing. Comprising 14 countries, this exercise places significant emphasis on a partnered approach to decreasing IUU fishing within the South American South Pacific. USSOUTHCOM has been an active participant since the exercise’s inception. However, during the exercise’s 2024 edition, the United States conducted only one shipriding partnership, between the USCGC Benjamin Bottoms and the Ecuadorean navy. USSOUTHCOM should further expand such opportunities by including additional maritime assets to expose even more nations to U.S. tactics, techniques, and procedures.57

The United States should not limit collaborative multinational efforts to exercises alone; instead, it should include partner nations in limited enforcement operations. Consider the USCG’s Operation Southern Shield, which focused on countering IUU fishing and took place in October 2023. The operation had SPRFMO’s backing, involved multinational partners in its intelligence and coordination, and included partner nations in its after-action distribution; however, it fell short of including partnernation vessels at sea alongside USCG vessels.58 The United States should avoid unilateral patrols to the maximum extent possible. Demonstrating multinational resolve through actual enforcement will make it much easier for SPRFMO nations to hold one another accountable and ensure that the United States does not project an overbearing image.

A Multinational Approach Should Include China

Besides working alongside South American naval forces, Washington should also consider partnering with China to combat IUU fishing. Desiring to be a maritime leader, China has openly stated it has “zero tolerance for illegal fishing” and has enacted stiff penalties on its DWF vessels that turn off their automatic identification systems, fail to comply with inspectors, or commit other violations.59 With this being the case, the United States must use this rare opportunity to reach across the table and work together.

Collaborative efforts may initially involve inspection training as previously described, participation in a future counter–IUU fishing exercise, and possibly limited shiprider opportunities. Over time, the United States might also encourage Chinese coast guard vessels to participate actively in regulatory operations in the South American Pacific, either alone or alongside the USCG.

Given the current political climate between the two nations, such collaboration may prove complex. However, it has precedent. During the height of the Cold War, the United States and Soviet Union set aside their political differences to establish an agreement that permitted Soviet DWF vessels access to U.S. ports in exchange for limiting the number of fish that Soviet vessels caught on the high seas off the U.S. Pacific Northwest.60 In a more recent example specific to Sino-U.S. relations, China and the United States partnered in the multinational effort to crack down on piracy in the Gulf of Aden. Even during President Barack Obama’s strategic reprioritization to limit Chinese geopolitical influence, the two countries successfully collaborated on the African coast, sharing limited intelligence on piracy operations, agreeing to emergency landing rights for Chinese helicopters on U.S. Navy vessels, and achieving success as a team.61

To be clear, such a partnership will not be easy. Relations between the two countries have only regressed further in the decade since Obama’s Presidency. To succeed, both countries will have to overcome growing mistrust and build on small gains, such as confining intelligence sharing to open-source information, like monitoring of automatic identification systems. These impediments, however, are constraints, not barriers. As demonstrated by the 2023 statement at Sunnylands, California, in which the United States and China reaffirmed their commitment to jointly work toward addressing climate change, even amid increased saber-rattling, these two countries are willing to work together to address specific transnational issues.62

Thus, proposing a collaborative effort in the South American Pacific should not be dismissed for its audacity. If anything, by including a nation whose DWF vessels have routinely come under question, Washington would further legitimize efforts to police IUU fishing, be better positioned to ensure that China’s proclamations against IUU fishing are not empty rhetoric, and perhaps even create an avenue by which to ease political tensions between the two global powers.

A Partner That South America Can Rely On

To ensure that lines of effort directed toward combating IUU fishing have the secondary effect of strengthening the United States as a leader within the Western Hemisphere, they must emphasize fully integrated multilateral efforts. Undoubtedly, reducing IUU fishing boosts the economics of all affected nations: protecting local artisanal fishermen, national fishing exports, and wildlife tourism (such as in the Galápagos). However, a key enabler in establishing trust between nations occurs when foreign militaries work closely together.63 Studies have shown that when militaries work together in collaborative efforts—specifically exchanging tactics and doctrine—it creates linkages among participants that extend military familiarity to political cooperation.64 By directly assisting in a cause through mutual partnerships with Western Hemisphere nations, these secondary and tertiary effects can double U.S. positive return across the region.

The United States should also remain measured in its approach. Washington has had a complex and shifting relationship with its southern neighbors, who might argue against the United States assuming an active leadership role in combating IUU fishing off their respective Pacific coasts. Such concerns are not unfounded. U.S. fishing vessels have been the subject of IUU fishing activity in South American fisheries since the 1950s, continuing up to as recently as 2001.65 Throughout that period, Peru, Chile, and Ecuador regularly confronted the United States over these incursions, resulting in multiple signed agreements and a loss of faith in U.S. adherence to maritime law.66 These infractions will certainly give South Americans pause about a renewed U.S. interest in fishing along their Pacific Coast.

Nonetheless, active interest in countering IUU fishing might allow Washington to repair previous grievances, mainly since its enforcement is focused on international rules and not on protecting U.S. fishing fleets. If anything, failure to assist might project an image of indifference to those impacted by these fishing violations, or, worse, demonstrate tacit approval to those nations that allow IUU fishing to go unchecked. So long as the United States enforces equitably against all offenders, it has more to gain from actively assisting and leading efforts to combat IUU fishing in South America than from otherwise abstaining.

Coastguardsmen from USCGC James conduct boarding of fishing vessel in Eastern Pacific, August 4, 2022 (U.S. Coast Guard/Justin Upshaw)

Conclusion

This article highlights three broad lines of effort to curb IUU fishing in the South American Pacific: consistent messaging, strengthening RFMO regulations, and pursuing greater multinational collaboration. While some of these lines of effort, such as strengthening RFMO regulations, may take time to develop or receive foreign endorsement, there are specific actions that the United States can take now. First, increase U.S. participation in South American exercises with a focus on IUU fishing. Exercise Galapex 2024 included only one maritime vessel, the USCG Benjamin Bottoms. The current U.S. force posture may not have the capacity to sustain extensive patrols against IUU fishing patrols in the South American Pacific, but it should have the ability to commit more maritime assets temporarily toward counter–IUU fishing training in future South American exercises. Second, increase opportunities for South American maritime enforcement personnel to receive counter–IUU fishing training in the United States. Schoolhouses, such as those offered by the National Oceanic and Atmospheric Administration and the USCG, provide an affordable option by leveraging existing training facilities and curricula. Last, increase public awareness of this issue. Most Americans remain unaware of DWF fleet actions off the South American Pacific coast. As U.S. leaders have done to increase public awareness of China’s role in feeding the fentanyl pipeline through Central America, they have an opportunity to bring greater awareness of the role of China’s DWF fleet in IUU fishing on this side of the Pacific.

Though these actions are achievable, there will also be limitations on Washington’s ability to execute the proposed lines of effort. As already highlighted, cooperating with China to counter IUU fishing in the South American Pacific will be foremost, likely requiring a graduated approach toward an eventual military partnership. Competing global demands and finite U.S. military resources are another limit. After two decades in the Middle East, the United States has voiced a desire to draw down its presence in the region. However, as current Israeli conflicts have shown, the U.S. military may not be able to withdraw from USCENTCOM as quickly as its strategists desire, hampering the U.S. ability to direct those assets toward areas of irregular competition with China.

Today, no single nation can combat every problem at sea. Doing so requires a collective effort.67 Contesting IUU fishing activity in the South American Pacific, exacerbated in recent years by China’s DWF fleet, is no different. It will require multinational collaboration in which the United States should play a key role. Furthermore, IUU fishing enforcement in the Southern Hemisphere presents the United States with a unique opportunity, particularly when viewed through the lens of America’s global competition with China. Here, the United States can not only create greater security for South American fisheries, strengthen relationships with South American countries, and assert its leadership role in the Western Hemisphere but also hedge against further Chinese influence in the region. JFQ

Notes

1 John Goodman, “China Fishing Fleet Defied U.S. in Standoff on High Seas,” Associated Press, November 1, 2022,
https://apnews.com/article/taiwan-fish-pacific-oceanoceans-china-810be144e62b695da2c6c0da65e9f051/.

2 Goodman, “China Fishing Fleet Defied U.S. in Standoff on High Seas.”

3 Isabella Montecalvo et al., “Ocean Predators: Squids, Chinese Fleets, and the Geopolitics of High Seas Fishing,” Marine Policy 152 (June 2023), 4, https://doi.org/10.1016/j.marpol.2023.105584.

4 Montecalvo, “Ocean Predators,” 4; Oscar Barrionuevo, Ecuadorean navy commander, interview by author, September 12, 2023.

5 Carol Wise and Victoria Chonn Ching, “Conceptualizing China–Latin America Relations in the Twenty-First Century: The Boom, the Bust, and the Aftermath,” Pacific Review 31, no. 5 (2017), 554, https://doi.org/10.1080/09512748.2017.1408675.

6 Gustavo de L.T. Oliveira and Margaret Myers, “The Tenuous Co-Production of China’s Belt and Road Initiative in Brazil and Latin America,” Journal of Contemporary China 30, no. 129 (2021), 486–7, https://doi.org/10.1080/10670564.2020.1827358.

7 Wise and Ching, “Conceptualizing China–Latin America Relations in the TwentyFirst Century,” 560; Mario Caceres Solis, “Belt and Road” Initiative in Peru: Impact, Opportunities, and Challenges (Lima: Centro de Estudios Estratégicos del Ejército del Perú [Peruvian Army Center for Strategic Studies], January 25, 2022), 6, https://ceeep.mil.pe/wp-content/uploads/2022/01/5.-Belt-and-Road-Initiative-in-Peru-Impact-Opportunities-and-Challenges-for-PDF-251600ene.pdf.

8 Diana Roy, “China’s Growing Influence in Latin America,” Council on Foreign Relations, June 6, 2025, https://www.cfr.org/backgrounders/china-influence-latin-america-argentina-brazil-venezuela-security-energy-bri; Leslie Moreno Custodio, “China’s Role in Peru’s Grids Stirs Debates,” Dialogue Earth, April 7, 2025, https://dialogue.earth/en/energy/chinas-role-in-perus-grids-stirs-debates/.

9 David Beszeditz, “Chinese Cooperation in Latin America: Implication for United States Space Security” (Master’s thesis, Naval Postgraduate School, 2021), 5, https://calhoun.nps.edu/server/api/core/bitstreams/8acb4e97-b55b-4858-b7ca-cafdf3b80a2c/content.

10 “Latin America,” Strategic Survey 122, no. 1 (2022), 390, https://doi.org/10.1080/04597230.2022.2145096.

11 Didi Kirsten Tatlow, “China’s Quest for Supremacy Moves into Space,” Newsweek, December 18, 2024,
https://www.newsweek.com/china-space-infrastructure-us-latin-america-chile-argentina-1999644; “Astronomy: China to Install Megaproject in Chile,” InvestChile, March 18, 2019, https://blog.investchile.gob.cl/astronomy-china-to-install-megaproject-in-chile.

12 Oliveira and Myers, “The Tenuous CoProduction of China’s Belt and Road Initiative in Brazil and Latin America,” 498; “Latin America,” 389.

13 Tatlow, “China’s Quest for Supremacy Moves into Space.”

14 Katja Levy and Caroline Rose, “Are China and Japan Rivals in Latin America? A Rivalry Perception Analysis,” Pacific Review 32, no. 5 (2019), 904, https://doi.org/10.1080/09512748.2019.1570316.

15 Solis, “Belt and Road” Initiative in Peru, 8–9; Custodio, “China’s Role in Peru’s Grids Stirs Debates.”

16 Montecalvo et al., “Ocean Predators,” 1; Goodman, “China Fishing Fleet Defied U.S. in Standoff on High Seas.”

17 Barrionuevo, interview.

18 Montecalvo et al., “Ocean Predators,” 4.

19 Barrionuevo, interview.

20 Raiana McKinney et al., Netting Billions 2020: A Global Tuna Valuation (Philadelphia: Pew Charitable Trusts, October 6, 2020),
https://www.pew.org/en/research-and-analysis/reports/2020/10/netting-billions-2020-a-global-tuna-valuation; “Chile,” Observatory of Economic Complexity, n.d., https://oec.world/en/profile/country/chl; Carmen Piedrahita-Rook, “Rights of the Sea: Toward a Global Understanding,” American Studies International 41, no. 3 (2003), 86, https://www.jstor.org/stable/41279988.

21 A.J. Manuzzi, “Latin America–Caribbean: Illicit Fishing is Environmental Security Challenge,” AULABLOG, July 21, 2022,
https://aulablog.net/2022/07/21/latin-america-caribbean-illicit-fishing-is-environmental-security-challenge/.

22 Matthew Taylor et al., IUU Fishing Crimes in Latin America and the Caribbean, CLALS Working Paper Series No. 39 (Washington, DC: American University Center for Latino American and Latino Studies and Insight Crime, August 2022), 42,
https://insightcrime.org/wp-content/uploads/2022/09/SSRN-IUU-Fishing-Crimes-in-Latin-America-and-the-Caribbean-American-university-InSight-Crime-2022.pdf.

23 Daniela Andrade Tamayo, “Combatting Illegal, Unreported and Unregulated (IUU) Fishing in Ecuador: The Maritime Authority Approach for the Exercise of Coastal State Rights” (Master’s thesis, World Maritime University, October 28, 2023), 45,
https://commons.wmu.se/cgi/viewcontent.cgi?article=3265&context=all_dissertations.

24 Wilder Alejandro Sánchez, How Latin American Navies Combat Illegal, Unreported, or Unregulated Fishing (Washington, DC: Center for Strategic International Studies, May 22, 2024), https://www.csis.org/analysis/how-latin-american-navies-combat-illegal-unreported-or-unregulated-fishing.

25 Arnab Chakrabarty, “Illegal, Unreported, and Unregulated Fishing in Latin American Waters by China’s Distant Water Fleet—Concerns,” Indian Council of World Affairs, January 7, 2025, https://www.icwa.in/show_content.php?lang=1&level=3&ls_id=12229&lid=7461.

26 Taylor et al., IUU Fishing Crimes in Latin America and the Caribbean, 35; Tamayo, “Combatting Illegal, Unreported and Unregulated (IUU) Fishing in Ecuador,” 44.

27 Taylor et al., IUU Fishing Crimes in Latin America and the Caribbean, 30, 32.

28 Ivan T. Luke, “Legitimacy in the Use of Seapower” (Master’s thesis, U.S. Naval War College, 2020), 4.

29 “What Is IUU Fishing?” Illegal, Unreported and Unregulated (IUU) Fishing, Food and Agriculture Organization of the United Nations, n.d.,
https://www.fao.org/iuu-fishing/background/what-is-iuu-fishing/en/.

30 Gonzalo Torrico, “South America Plans Regional Response to Squid Overfishing,” Dialogue Earth, January 13, 2021,
https://dialogue.earth/en/ocean/15979-squid-overfishing-south-america-plans-regional-response/.

31 Santiago Vascones, Peruvian navy lieutenant commander, interview by the author, September 13, 2023.

32 Government Accountability Office (GAO), Combating Illegal Fishing: Clear Authority Could Enhance U.S. Efforts to Partner With Other Nations at Sea, GAO-22-104234 (Washington, DC: GAO, 2021), 5, https://www.gao.gov/assets/720/717435.pdf.

33 GAO, Combating Illegal Fishing, 5.

34 “Participation,” South Pacific Regional Fisheries Management Organization, n.d., https://www.sprfmo.int/about/participation/.

35 Montecalvo et al., “Ocean Predators,” 8.

36 Patricia Bennet, U.S. Coast Guard Chief of Fisheries Enforcement Policy, telephone interview by author, September 7, 2023.

37 “International Actions Pay Off for Pacific Bluefin Tuna as Species Rebounds at Accelerating Rate,” NOAA Fisheries, August 15, 2022, last updated October 7, 2022, https://www.fisheries.noaa.gov/feature-story/international-actions-pay-pacific-bluefin-tuna-species-rebounds-accelerating-rate.

38 Alin Kadfak and Sebastian Linke, “More Than Just a Carding System: Labour Implications of the EU’s Illegal, Unreported, and Unregulated (IUU) Fishing Policy in Thailand,” Marine Policy 127 (May 2021), 6, https://doi.org/10.1016/j.marpol.2021.104445.

39 South Pacific Regional Fisheries Management Organization, Decision 18-2024, “Labour Standards on Fishing Vessels in the SPRFMO Convention Area,” April 5, 2024, https://www.sprfmo.int/assets/Basic-Documents/Convention-and-Final-Act/Article-16-Decisions/Decision-18-2024-Labour-Standards-in-SPRFMO-1Mar2024.pdf.

40 A.N. Honniball, “WCPFC: Adopts Legally Binding Conservation & Management Measure on Fishing Labour Conditions,” De Maribus, January 1, 2025, https://demaribus.net/2025/01/10/wcpfc-adopts-legally-binding-conservation-management-measure-on-fishing-labour-conditions/.

41 Barrionuevo, interview.

42 Jessica F. Green and Bryce Rudyak, “Closing the High Seas to Fishing: A Club Approach,” Marine Policy 115 (May 2020), 2,
https://doi.org/10.1016/j.marpol.2020.103855.

43 Montecalvo et al., “Ocean Predators,” 7.

44 Daniel Peñalosa Martinell et al., “Closing the High Seas to Fisheries: Possible Impacts on Aquaculture,” Marine Policy 115 (May 2020), 2,
https://doi.org/10.1016/j.marpol.2020.103854; Montecalvo et al., “Ocean Predators,” 6.

45 Sally Yozell and Amanda Shaver, Shining a Light: The Need for Transparency Across Distant Water Fishing, Resources and Climate Report (Washington, DC: Stimson Center, November 2019), 4, www.stimson.org/2019/shining-light-need-transparency-across-distant-water-fishing/.

46 South Pacific Regional Fisheries Management Organization, CMM 11-2023, Conservation and Management Measure for High Seas Boarding and Inspection Procedures for the South Pacific Regional Fisheries Management Organization, 1–8,
https://www.sprfmo.int/fisheries/conservation-and-management-measures/cmm-11-boarding-and-inspection.

47 Huihui Shen and Shuolin Huang, “China’s Policies and Practice on Combatting IUU in Distant Water Fisheries,” Aquaculture and Fisheries 6, no. 1 (2021), 33, https://doi.org/10.1016/j.aaf.2020.03.002.

48 James M. O’Mara, U.S. Coast Guard Chief of Enforcement, District 11, email message to author, September 14, 2023.

49 Vascones, interview; Barrionuevo, interview.

50 Combating Illegal Fishing, 13; Janet Coit and Richard Spinrad, National 5-Year Strategy for Combating Illegal, Unreported, and Unregulated Fishing 2022–2026, Report to Congress (Washington, DC: U.S. Interagency Working Group on IUU Fishing, 2022), 15,
https://media.fisheries.noaa.gov/2022-10/2022_NationalStrategyReport_USIWGonIUUfishing.pdf.

51 O’Mara, email.

52 Jeffrey Platt, U.S. Coast Guard commander; Flor Joseph, U.S Coast Guard lieutenant; and Colin Clyne, U.S. Coast Guard lieutenant, “Exercise Resolute Sentinel 2023 IUUF Training Syllabus,” email to author, September 16, 2023.

53 U.S. Southern Command, “Resolute Sentinel 2024,” 2024, https://www.southcom.mil/Media/Special-Coverage/Resolute-Sentinel-2024/.

54 O’Mara, email.

55 O’Mara, email; Michael J. Kurey, Enhanced Domain Awareness program manager at U.S. Southern Command J2, email message to author, September 16, 2023.

56 Jessica Smith McMahan, “Resolute Sentinel 24 Concludes, Strengthens Global Partnerships,” Defense Visual Information Distribution Service, June 15, 2024, https://www.dvidshub.net/news/474204/resolute-sentinel-24-concludes-strengthens-global-partnerships.

57 “Coast Guard Participates in Multinational Exercise Near Galapagos Islands,” U.S. Coast Guard, August 6, 2024,
https://www.news.uscg.mil/Press-Releases/Article/3863639/coast-guard-participates-in-multinational-exercise-near-galapagos-islands/.

58 O’Mara, email.

59 Goodman, “China Fishing Fleet Defied U.S. in Standoff on High Seas”; Shen and Huang, “China’s Policies and Practice on Combatting IUU in Distant Water Fisheries,” 30; Montecalvo et al, “Ocean Predators,” 9.

60 Theodore Shabad, “U.S. and Soviet [sic] Sign Accords Controlling Fishing Off West Coast,” New York Times, February 22, 1973,
https://www.nytimes.com/1973/02/22/archives/u-s-and-soviet-sign-accords-controlling-fishing-off-west-coast-aide.html.

61 Cindy Cheng, China and U.S. AntiPiracy Engagement in the Gulf of Aden and Western Indian Ocean Region, Africa–U.S.–China Trilateral Cooperation Research Series No. 5 (Atlanta: Carter Center, 2017), https://www.cartercenter.org/resources/pdfs/peace/china/trs-05-anti-piracy-engagement.pdf.

62 “Sunnylands Statement on Enhancing Cooperation to Address the Climate Crisis,” Department of State, November 14, 2023,
https://2021-2025.state.gov/sunnylands-statement-on-enhancing-cooperation-to-address-the-climate-crisis/.

63 Derrick V. Frazier and J. Wesley Hutto, “The Socialization of Military Power: Security Cooperation and Doctrine Development Through Multinational Military Exercises,” Defence Studies 17, no. 4 (2017), 388, https://doi.org/10.1080/14702436.2017.1377050.

64 Frazier and Hutto, “The Socialization of Military Power,” 383, 392.

65 Piedrahita-Rook, “Rights of the Sea,” 86.

66 Piedrahita-Rook, “Rights of the Sea,” 88. 67 Geoffrey Till, Seapower (London: Routledge, 2018), 55