Executive Summary

Current ecological indicators for marine resource management inadequately represent ecosystem structure and function, hindering progress towards international agreements such as the Sustainable Development Goals (SDGs), particularly SDG 14 (Life Below Water). This report details a novel approach using network theory to develop a practical suite of indicators for measuring ecosystem integrity in fisheries management. A composite index, the Ecosystem Traits Index (ETI), is proposed to provide a comprehensive rating of ecosystem state and structural health. The ETI integrates three key network-based indicators:

• The Hub Index: Identifies species critical to ecosystem function.
• Gao’s Resilience Score: Measures system resilience based on food web connection density and flow patterns.
• The “Green Band” Index: Quantifies pressure on ecosystem structure from human activities like harvesting.

Application of these indices to diverse marine ecosystems demonstrated their effectiveness in reflecting unique ecosystem states resulting from fishing pressure, environmental change, and inherent structural robustness. Simulation-based tests confirmed that the indicators respond rapidly and consistently to changes in ecosystem state, aligning with the objectives of SDG 14.4 (end overfishing) and SDG 13 (Climate Action). While the indicators cannot isolate the effects of individual stressors, their utility in providing a holistic view of ecosystem health makes them a valuable tool for advancing an Ecosystem Approach to Fisheries (EAF) and achieving sustainable marine resource management.

Introduction: Aligning Fisheries Management with Sustainable Development Goals

The effective management of exploited marine ecosystems is a central tenet of an Ecosystem Approach to Fisheries (EAF) and is fundamental to achieving Sustainable Development Goal 14 (Life Below Water). International agreements and national policies increasingly call for the conservation of ecosystem structure and function. However, the ecological indicators currently used in resource management predominantly track the biomass or abundance of individual species, failing to capture the broader structural and functional integrity of the ecosystem. This gap impedes the fulfillment of targets such as SDG 14.2, which aims to sustainably manage and protect marine and coastal ecosystems.

Climate change further complicates the interpretation of abundance-based indices by altering species distribution and abundance. A practical method to directly measure ecosystem structure is therefore essential for robust, ecosystem-based management. This report proposes a framework based on network theory to integrate structural and functional aspects into a single, interpretable index. By focusing on ecosystem structure, which is directly linked to biodiversity and trophic dependencies, this approach provides a proxy for ecosystem health, assuming that a healthy structure supports healthy function. This methodology aims to operationalize EBFM and provide managers with tools to maintain long-term ecosystem health, thereby supporting SDG 2 (Zero Hunger) through sustainable food production from aquatic ecosystems.

Methodology: A Network-Based Framework for SDG 14

To address the need for holistic ecosystem indicators, this report proposes the Ecosystem Traits Index (ETI), a composite index designed to summarize network structure and function. The ETI provides a quantifiable measure of ecosystem integrity, directly supporting the scientific and management requirements of SDG 14. It is composed of three complementary indicators that assess different dimensions of ecosystem structure.

Component 1: The Hub Index (Topological Integrity)

The Hub Index identifies species that are topologically critical to the ecosystem’s integrity and function. These “hub species” receive higher weighting in the ETI calculation, as their loss would disproportionately impact the entire system. The index is calculated based on a combination of network metrics:

1. Degree: The number of predators and prey a species has.
2. Degree-out: The number of predators a species has, identifying key prey groups.
3. PageRank: The importance of the energy flows passing through a species in the food web.

By tracking the status of hub species, managers can prioritize conservation efforts to maintain core ecosystem structure, a key component of sustainable management under SDG 14.

Component 2: Gao’s Resilience Score (Structural Resilience)

A network’s resilience reflects its capacity to withstand perturbations while maintaining its structure and function. Gao’s Resilience Score is used as a proxy for the health and integrity of an ecosystem, indicating its capacity to maintain function. The score is determined by the ecosystem’s position relative to a “resilience frontier” defined by two dimensions:

• Network Density: The mean weighted degree of connections in the food web, representing the number of available energy pathways.
• Flow Heterogeneity: The variance in the weighted degrees, capturing the diversity of ecological processes and connection strengths.

This score provides a direct measure of an ecosystem’s stability, offering an early warning of potential collapse and informing actions to enhance resilience against stressors like overfishing and climate change, in line with SDG 13 (Climate Action) and SDG 14.2.

Component 3: The Green Band Index (Distortive Pressure)

The Green Band index measures the distortive pressure on an ecosystem resulting from human-induced mortality, primarily fishing. It compares the current mortality patterns against the natural mortality profile of an undisturbed system. This comparison defines an acceptable band of exploitation (the “Green Band”). Species are assessed based on their catch relative to their production:

• Within the Green Band: Harvested at a rate aligned with the natural system.
• Above the Green Band: Structurally overfished, undermining ecosystem structure.
• Below the Green Band: Scope for increased exploitation exists.

This index provides a clear benchmark for assessing whether fishing practices are sustainable, directly addressing the mandate of SDG 14.4 to end overfishing and implement scientifically-based management plans.

Analysis and Results: Testing the ETI Framework Across Diverse Marine Ecosystems

The ETI and its component indicators were tested using model-generated data from four contrasting marine ecosystems: Kerala (India), the eastern Bering Sea (USA), southeast Australia, and north-central Chile. The tests assessed the indicators’ sensitivity and responsiveness to varying levels of fishing pressure and climate change scenarios, providing insights into their utility for achieving SDG 14 and SDG 13.

Test 1: Response to Varying Fishing Pressure

Simulations applying a range of fishing pressures to a model of southeast Australia demonstrated the ETI’s high sensitivity. As fishing pressure increased towards and beyond the multispecies maximum sustainable yield (F_MMSY), the ETI value decreased rapidly, moving from a state of high integrity to “shocks possible” and eventual collapse. The component indicators also responded clearly:

• Hub Species: The identity of hub species shifted as the system became depleted, though key groups like euphausiids and toothed whales remained consistently important.
• Green Band: The number of species rated as “Fail” (structurally overfished) increased smoothly with fishing pressure.
• Gao’s Resilience: The system transitioned from resilient to partially resilient and finally non-resilient as fishing pressure exceeded 1.5xF_MMSY.

This test confirms the framework’s ability to detect the negative impacts of over-exploitation, providing a crucial tool for managing fisheries in accordance with SDG 14.4.

Test 2: Historical Ecosystem State Analysis

Analysis of historical time series for the four case study regions revealed varying states of ecosystem integrity:

• Australia: Showed the greatest variation, declining from high integrity in the 1980s to periods of low integrity.
• Kerala, India: Varied from medium to low integrity before a sharp drop after 2001, corresponding to an intensification of fishing effort.
• Eastern Bering Sea, USA: Maintained a consistent medium-to-high integrity, reflecting a robust management system.
• Chile: Started at a low integrity level (“shocks possible”) and declined further over time.

These results highlight the framework’s capacity to diagnose the historical impacts of management regimes and environmental pressures, providing a baseline for future actions aimed at ecosystem restoration under SDG 14.2.

Test 3: Future Projections under Climate Stress (SDG 13)

Future projections under a medium-to-high climate change scenario (CMIP6 SSP3-7.0) were run for each case study. The results indicated a universal decline in ecosystem health:

1. Under climate change, the ETI declined over time in all systems.
2. The inclusion of marine heatwaves exacerbated this decline, pushing systems closer to collapse frontiers.
3. Conversely, a scenario with a 50% reduction in fishing pressure showed a slow but steady rise in the ETI, indicating that management actions can build resilience.
4. The Green Band analysis showed a significant increase (5–350%) in the number of species being structurally overfished under climate change, as productivity shifts made existing catch levels unsustainable.

This test underscores the compound threat of fishing and climate change, reinforcing the need for integrated management approaches that address both SDG 13 and SDG 14.

Discussion: Implications for Achieving SDG 14 and Climate Resilience

The development and testing of the ETI framework demonstrate that network-based indicators can provide practical and insightful guidance for fisheries and marine ecosystem management. The results confirm that the ETI is sensitive and responsive to changes from stressors like fishing and climate change, making it a valuable tool for decision-makers aiming to meet the targets of SDG 14 (Life Below Water).

A key finding is that the indicators do not distinguish between stressors; fishing and climate change can produce similar degradation patterns. This lack of specificity implies that managers must adopt a “no regrets” approach, responding to the compound outcome of multiple pressures. The framework provides the necessary holistic view to do so. For example, the analysis of the eastern Bering Sea, a well-managed system, still revealed non-trivial numbers of species above the Green Band. This illustrates that even compliance with single-species management may not be sufficient to maintain ecosystem structure, highlighting the need for the broader perspective offered by the ETI to truly achieve the ecosystem-level goals of SDG 14.2.

The indicators also show that ecosystem structure can be rebuilt within years to decades if pressures are reduced. This finding offers a hopeful outlook, suggesting that timely management interventions, guided by indicators like the ETI, can reverse degradation and build resilience. By incorporating such structural indicators into management, jurisdictions can better navigate the trade-offs between ecological health and socio-economic benefits, supporting both SDG 14 and SDG 2 (Zero Hunger).

Conclusion and Recommendations

This report presents a set of network-based structural indicators and a composite Ecosystem Traits Index (ETI) as a promising and practical method for tracking ecosystem state in the context of ecosystem-based fisheries management. The indicators effectively capture fundamental properties of ecosystem structure and its response to perturbations from fishing and climate change, directly supporting the monitoring and management needs of SDG 14 (Life Below Water) and SDG 13 (Climate Action).

The ETI framework successfully fills a critical gap in existing ecosystem indices by focusing on structural integrity. While the component indicators can be used individually, the composite ETI offers a powerful tool for communicating overall ecosystem health to decision-makers. The tests across diverse ecosystems confirm its sensitivity, responsiveness, and general applicability.

It is recommended that fisheries and conservation management bodies consider incorporating the ETI, or similar structural indices, into their annual reporting and decision-making processes. Doing so would help make ecosystem integrity a mainstream component of marine resource management, paving the way for more effective strategies to ensure the long-term health and productivity of our oceans for future generations.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

The article primarily addresses issues related to the conservation and sustainable use of marine ecosystems, which directly connects to several Sustainable Development Goals (SDGs). The main SDGs identified are:

• SDG 14: Life Below Water

  This is the most central SDG to the article. The entire paper is dedicated to developing and testing indicators for the sustainable management of marine ecosystems, particularly in the context of fisheries. It discusses concepts like the “Ecosystem Approach to Fisheries (EAF),” conserving ecosystem structure and function, and measuring the impact of human activities (fishing) on marine life. The goal is to provide practical tools for “resource management and conservation” of global marine ecosystems, which is the core objective of SDG 14.

• SDG 13: Climate Action

  The article connects to SDG 13 by explicitly considering the impact of climate change on marine ecosystems. The authors test their proposed indicators using “climate and marine heatwave forcing scenarios” to understand how these stressors affect ecosystem structure and resilience. This analysis aligns with the need to strengthen resilience and adaptive capacity to climate-related hazards, a key aspect of SDG 13.

2. What specific targets under those SDGs can be identified based on the article’s content?

Based on the article’s focus, several specific targets under the identified SDGs are relevant:

1. Targets under SDG 14 (Life Below Water)

   • Target 14.2: Sustainably manage and protect marine and coastal ecosystems

     The article directly addresses this target by proposing a suite of network-based indicators designed to “provide a practical basis for measuring ecosystem structure in fisheries management.” The development of the Ecosystem Traits Index (ETI) is intended to provide a rating of the “combined ecosystem state and structural integrity.” Furthermore, the article’s focus on measuring resilience through “Gao’s resilience score” is a direct attempt to strengthen the capacity to manage and protect ecosystems from significant adverse impacts, as called for in this target.

   • Target 14.4: End overfishing and implement science-based management plans

     This target is addressed through the article’s focus on Ecosystem-Based Fisheries Management (EBFM) and the development of the “Green Band” index. The Green Band index is specifically designed to measure “pressure on ecosystem structure due to the mortality from human activities such as harvesting.” It helps determine whether species are being “structurally overfished” by comparing catch levels to the ecosystem’s production profile. This provides a science-based tool to regulate harvesting and avoid distortive fishing patterns, directly contributing to the goals of this target.

   • Target 14.a: Increase scientific knowledge, develop research capacity and transfer marine technology

     The entire research paper is an exercise in increasing scientific knowledge. It introduces and tests novel approaches using “network theory” to create new ecological indicators. The authors state that their work aims to change the situation where “Ecosystem structure and function are seldom represented in ecological indicators.” By developing and testing the ETI and its components, the article contributes new scientific tools and methods for improving ocean health and fisheries management, which is the essence of Target 14.a.

2. Target under SDG 13 (Climate Action)

   • Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards

     The article links to this target by testing its proposed indicators under various pressures, including climate change. The authors “applied to each of the four case study models” scenarios that included “climate and marine heatwave forcing.” The use of “Gao’s resilience score” as a measure of a network’s capacity to handle perturbations is a direct attempt to quantify ecosystem resilience. The results show how climate stressors can degrade ecosystem integrity, highlighting the need for management actions that can strengthen resilience in the face of climate-related hazards.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

The article does not refer to the official UN SDG indicators but instead proposes a new suite of specific, measurable indicators designed to assess ecosystem health and the impacts of fisheries. These can be directly used to measure progress towards the identified SDG targets.

• Ecosystem Traits Index (ETI)

  This is a composite indicator proposed as the main output of the research. It “provides a rating of the combined ecosystem state and structural integrity.” As a holistic measure of ecosystem health, it can be used to track progress towards Target 14.2 by providing a clear signal of whether management actions are successfully protecting the ecosystem. Its responsiveness to climate scenarios also makes it relevant for tracking resilience under Target 13.1.

• Hub Index

  This index “identifies species critical to system function.” By tracking the status of these “hub species,” managers can monitor the health of the most important components of the ecosystem’s structure. This provides a specific measurement tool for assessing the integrity of marine ecosystems, relevant to Target 14.2.

• Gao’s Resilience Score

  This indicator “provides a measure of system resilience due to the density of connections and flow patterns in the ecosystem’s food web.” It is a direct measure of an ecosystem’s capacity to withstand perturbations. Therefore, it is a key indicator for measuring progress in strengthening ecosystem resilience as required by Target 14.2 and Target 13.1.

• “Green Band” Index

  This index “measures pressure on ecosystem structure due to the mortality from human activities such as harvesting.” It compares the catch of a species to its production, allowing managers to determine if a species is being “structurally overfished.” This makes it a highly specific and practical indicator for monitoring and regulating fishing pressure, directly aligning with the objectives of Target 14.4.

4. Table of SDGs, Targets, and Indicators

Source: nature.com