Course: EAS 472  

Dr. Karin Block 

An Approach for Equitably Prioritizing Ocean Mapping Efforts 

Introduction 

The world’s coasts are home to more than 40% of the global human population. (Reimannn et al, 2023) Sensitive to climate change, coastal environments are vital habitat to aquatic life as well as crucial to human economics, food systems, infrastructure, and climate goals. (Ayilu et al, 2022, Hoerling et al, 2004) The role of comprehensive bathymetric data to the management of these coastal environments is key to strategies meant to address these many needs, as detailed in the following Sustainable Development Goals (SDGs): No Poverty; Zero Hunger; Affordable and Clean Energy; Industry, Innovation, and Infrastructure; Climate Action; and Life Below Water. While bathymetric data has far-reaching applications within the context of each of these goals, its different uses require data of varying resolutions and quality. As publicly available bathymetric data is currently not comprehensive in its coverage of coastal environments, global needs to meet these SDGs are not supported. 

The Indian Ocean is home to many coastal communities in developing nations whose livelihoods, infrastructure, and emerging /developing economies rely upon marine resources. (Celliers et al, 2022, Nimit, 2021) The “Blue Economy” is a concept most recently introduced to describe the matrix of economic and conservation activities within the ocean. (Voyer et al, 2018) The term is often utilized by small island developing states (SIDS) and other developing nations to discuss the complex interactions between their local economies, the ocean’s natural resources, and global and regional responses to climate change within the ocean. (Voyer et al, 2018, Blythe et al, 2021) These developing states inform their economic and conservation practices and policies both within their exclusive economic zones (EEZs) and beyond each country’s respective national jurisdiction through international collaborative bodies, such as the Indian Ocean Tuna Commission and the Indian Ocean Commission. (Blythe et al, 2021, Nishida et al, 2001) 

Due to the population density of the coastal areas of the Indian Ocean and the increased risk and vulnerability to climate change experienced by these coastal communities, this paper focuses on states bordering the Indian Ocean. (Rabbani et al, 2010, Celliers et al, 2022) In areas where local populations are most vulnerable to climate change and in most need for support in reaching the outlined SDGs, this data is most urgently needed. Bathymetric data is fundamental to planning, modeling, and active needs across sectors of the blue economy, marine security, and environmental sustainability. (Bennett et al, 2021) This paper identifies the current data, the accessibility of the data, the resolutions at which they are available, and the area of data coverage relative to densely populated coastal areas, exclusive economic zones, and previously identified sites for development (AIS, Wind Farms, and Oil & Gas). Taken together, these factors identify vulnerable populations and the support they need to develop in an economically, ecologically, and politically sustainable manner.  

No Poverty (SDG 1): 

The goal of “No Poverty” encompasses a multifaceted approach, addressing various aspects of the issue, including equal rights to natural resources and the adoption of “appropriate new technology.” (United Nations, 2023a) It also seeks to reduce the vulnerability of communities, especially those in poverty, to “climate-related extreme events …and other…environmental shocks and disasters.” (United Nation, 2023a) Furthermore, the SDG emphasizes the imperative of mobilizing significant resources through enhanced development cooperation to implement programs and policies aimed at eradicating poverty in all its dimensions (United Nations, 2023a). While climate change presents imminent disaster for many impoverished communities, the economic constraints imposed by climate-sensitive policy often undercuts the more pressing economic concerns of these communities. (Fischer, 2018). While climate change is often highlighted as a primary stressor for coastal communities, the economic factors that contribute to vulnerability, such as social, economic, local institutional, geopolitical, demographic (race, age, gender, class, etc.), livelihood, and other environmental changes, also must be addressed in comprehensive policy aimed at ameliorating poverty. (Bennett et al, 2015) These factors create a matrix of domestic and international relationships that must inform vulnerability to climate change and policy aimed at addressing poverty holistically. Underdeveloped and Small Island Developing States (SIDS) often experience inadequate infrastructure, poor management of water and land resources, suboptimal urban planning, as well as complex dynamics of international politics that perpetuate poverty (Kremlin, 2014). To achieve “No Poverty” within these coastal communities, the data infrastructure needed to complete comprehensive surveys of their natural resources are essential to modeling, management, and planning in the face of climate change and these other stressors must be bolstered, in part, by comprehensive bathymetric data (Kelman, 2014; Novaglio, 2022; and Ayilu et al. 2022)  

Bathymetry is an important aspect of economic activity for SIDS and other coastal communities, as the Blue Economy plays a significant role in their overall economic behavior. (Bennett et al, 2015, Celliers et al, 2022) Bathymetric data informs planning for marine habitat management, which informs vital shipping and fishing industries; for infrastructure such as piers, ports, coastal defense systems, and industrial institutions; for off-shore wind; and other critical pieces of the blue economy, all of which can support autonomous and equitable economic activity to reach the goal of eradicating poverty.  

Zero Hunger (SDG 2): 

One of the target indicators of the Zero Hunger SDG is to “ensure sustainable food production systems… that help maintain ecosystems, that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding and other disasters…”(United Nations 2023b) As previously mentioned, bathymetric data is part of the information needed to create maps and models of marine environments to support fisheries. (Nishida et al 2001) Not only do coastal populations, especially of those in low- and middle-income countries, currently rely greatly upon seafood for their food and nutrition security, but also for their livelihoods. (Jensen et al, 2023, Ayilu et al, 2022). As human populations increase, there is acute need for increased food production from ocean resources in these same countries (Jensen et al, 2023) This effort will require the bolstering of every level of this sector of the blue economy. While large industrial fisheries produce more of the global fish and have greater resources allocated to marine management for market stability, small-scale fisheries are an important part of the market. (Ayilu et al, 2022) Small-scale fisheries employ 44% of people “directly engaged in fishing” and supply ~25% of the globally available fish for consumption. (Ayilu et al, 2022) However, these resources needed to support these fisheries are insufficient and blue economic policy within the Indian ocean region has largely privileged larger fisheries, making them better equipped to face the challenges of climate change and economic development within the ocean (Ayilu et al., 2022) Small-scale fisheries are a cornerstone of many coastal economies in the Indian Ocean region, playing a vital role in sustaining local communities and ensuring food security. However, resource Variability due to climate change-induced shifts in ocean temperatures and currents affect the distribution and availability of fish stocks (Jensen et al. 2023) This variability poses challenges for small-scale fishers who rely on consistent access to these resources. These small-scale fishers are working to adapt to changing environmental conditions by adjusting their fishing practices, such as altering fishing locations, using different gear, or diversifying their catch. (Jensen et al., 2023) However, these adaptations often require external support to be effective. Equitable management of these ocean resources requires data infrastructure to support both their knowledge of and access to appropriate fishing grounds. That data infrastructure includes comprehensive, high-resolution bathymetric data for marine habitat mapping. (Rabbani et al., 2010) 

An important case study of intergovernmental cooperation around a marine resource is the Indian Ocean Tuna Commission (IOTC). Tuna is an especially important good for African (West Indian Ocean) and other Indian Ocean states’ export economies; often referred to as “blue gold,” Tuna generates US$2 billion yearly. (Kull & Andriamahefazafy, 2019) Tuna distribution and abundance within the Indian Ocean are impacted by sea surface temperature, sea level pressure, and wind actions, which are all in flux because of climate change (Kumar et al., 2014) This commission references explicitly the blue economy as a framework to guide policy that concerns both the environment and the economy. The IOTC has put parameters around what resources a country is allowed to harvest within their EEZs, how to manage access with regard to conservation efforts, how “surplus” is managed, and a data infrastructure, including mapping as a socio-natural issue. (Kull & Andriamahefazafy, 2019) Access to maps and the ability to map itself is not equitably distributed, and this issue is unresolved within the IOTC’s regulatory framework, which presents problems most especially for small fisheries. As mentioned, this issue of food security can only be addressed with active and fair involvement of all stakeholders within the blue economy engaged in fishing activity. The significant market share of small-scale artisanal fishers is undercut by the difficulty they face attaining the various permits needed to both fish and sell their goods and the information they need to plan accordingly. (Kull & Andriamahefazafy, 2019) Bathymetric maps are prime resources for equitable planning for marine food resources, however resolution needs are varied in different approaches taken to analyze marine ecosystems and needs for specific species and fisheries. (Nishida et al., 2001, Marsak et al., 2020) However, high resolution bathymetric data is explicitly cited as an urgent need for planning for food security. (Temple et al., 2017) 

[Figure 1. A map of the Indian Ocean region that includes the EEZs, the resolutions above and below 100m (low and high respectively), also the vulnerability of these countries’ economies and political situations due to climate change, as presented by the state department. (National Intelligence Council, 2021)] 

Affordable and Clean Energy (SDG 7):

Affordable and clean energy are key to the economic development of SIDS and developing nations. Among the targets of SDG 7 are increasing renewable energy, creating, and maintaining access to affordable energy, and “[enhancing] international cooperation to facilitate access to clean energy research and technology” (United Nations, 2023c) To power the future, many of these aforementioned states are looking for ways to develop their clean energy infrastructure, which includes offshore wind farms. The blue economy traditionally eschews the inclusion of fossil fuel extraction, which undercuts the goals of environmental sustainability and addressing climate change, as fossil fuel consumption is the major contributor to climate change and deep-sea mining and oceanic fossil fuel extraction can lead to contamination of marine habitats through souls, which often occur. Several countries along the Indian Ocean have developing or partially developed clean energy sectors interested in offshore wind farms, such as India, Kenya, Madagascar, and Thailand, among others. (Kazimierczuk, 2019, Arun Kumar et al, 2020, Ranthodsang  et al, 2020, Elsner, 2019) In the case of these nations, significant resources have already been allocated to exploration and there are corporate entities looking to explore.  

Offshore wind farms rely primarily upon specific wind and Bathymetric conditions. For offshore wind farms with standing turbines the conditions are as follows: 7+m/s and 50≥m (Choti & Xydis, 2022, Arun Kumar et al, 2020)  

[Figure 2. insert map of Indian Ocean with coastal states included. This map has population density, EEZs, the general potential area of oil/gas exploration, as well as a calculated area of the 50≥m depths and 7+m/s winds in the Indian Ocean. AIS information may or may not be included, depending on how visually busy it becomes. This will exhibit areas which should not be prioritized for international mapping projects that emphasize equity in bathymetric data (like SeaBed 2030), as they will already be prioritized by the respective nations due to their immediate economic and energy infrastructure priority.] 

Industry, Innovation, and Infrastructure (SDG 9): 

The interplay between marine ecosystems and the developed coastline with densely populated urban areas is a complex matrix of ecological, economic, and infrastructural concerns. SDG 9 seeks, in part, to “facilitate sustainable and resilient infrastructure development in …African countries, least developed countries…and [SIDS].” (United Nations, 2023d) Coastal infrastructure encompasses the physical and organizational structures needed to facilitate society and business, such as ports, piers, and security. Tsunamis are a global natural hazard that is primarily caused by tectonic activity, causing damage primarily in areas near the source. (Kious, 1996) The 2004 Indian Ocean Tsunami, initiated near Indonesia, caused considerable damage to the human health, economies, infrastructure, and property in 17 countries in the region. (US Department of Commerce, 2018) While tsunamis of this magnitude are not frequent, there is a clear need for preparedness methods that include tsunami risk modeling that relies upon high-quality, high-fidelity bathymetric data. The Indian Ocean Tsunami Warning and Mitigation System (IOTWMS) is a successful program developed in response to the 2004 tsunami and foundationally relies upon gridded bathymetric data to model wave behaviors and flooding patterns. (Hettiarachchi, 2018) While other tsunami risk models exist, this is a comprehensive system overseen by the Intergovernmental Oceanographic Commission (IOC) that relies upon coastal bathymetry of politically disparate nations to allow for domestic coastal security for each of the participating nations. In this instance, reliable bathymetric data is needed across nations for management of coastal vulnerability to natural hazards beyond the scope of resource management for economically and environmentally extractive purposes.   
 

Climate Action (SDG 13) & Life Below Water (SDG 14): 

The world’s vast oceans are vulnerable to climate change, which has greatly impacted marine ecosystems on nearly every trophic level. SDG 13, “Climate Action,” is a global call to take urgent action to combat climate change and its impacts, especially within SIDS and developing countries. (United Nations, 2023e). The effects of climate change are felt most acutely in coastal regions, making this goal particularly relevant to the Indian Ocean area. (Fisher, 2018) According to the Food and Agriculture Organization (FAO), only 65.8% of global fish stocks are within biologically sustainable levels. (2020) This statistic highlights the need for improved fisheries management to achieve SDG 13’s goal of sustainably using marine resources in ways responsive to climate change. SDG 14, “Life Below Water,” emphasizes the urgent need to conserve and sustainably use the oceans, seas, and marine resources for sustainable development, especially within SIDS and least developed countries. (United Nations, 2023f) SDG 14 emphasizes the critical role of marine ecosystems in supporting life on Earth and calls for the protection of these valuable resources; methods of which require mapping and monitoring for which bathymetric data is essential. In the face of climate change, marine protected areas (MPAs) that are well-managed through equitable approaches that are data-driven are effective at conserving marine biodiversity, reporting 21% more fish biomass and larger fish, on average, as compared to unprotected areas, supporting the importance of selecting areas for conservation in line with SDG 14. A scientific, data-driven approach to address climate change within the oceans, sensitive “life below water” can only be achieved through a high-quality, high-fidelity, and (often) high resolution bathymetry data set necessary for understanding the complex interactions between ocean currents, sea surface temperature, sea level rise, nutrient cycling, and climate change. (Bennett et al., 2021, FAO, 2020, Marsac et al., 2020, Kumar et al., 2014) Altogether, comprehensive climate action is only possible with sensitivity to life below the water, which is subject to conditions provided by the underlying bathymetry of marine habitats, the comprehensive data of which must be accessible to countries with vulnerable marine habitats and human populations to understand and prepare for the effects of climate change in coastal areas and implement sustainable solutions. 

Conclusion:  

Coastal regions represent a significant portion of both the human population and marine biodiversity. Climate change has presented many challenges to these regions with sea level rise, increased coastal flood risk, and marine heatwaves. While all countries with both large coastal populations and great ecological challenges are vulnerable, SIDS and other developing economies, especially those of the Indian Ocean, are particularly subject to economic, political, and ecological difficulties with increased climate change. Bathymetric maps are crucial to many marine activities encompassed within the blue economy, like marine habitat characterization and protection and risk modeling climate change impact, which is at the heart of many SDGs. There is an acute need to expand available bathymetric data that prioritizes regions vulnerable to climate change which face economic disparities that prevent domestic or local data infrastructure from fully meeting the actual regional needs. This approach may encompass diverse approaches to meet these needs, such as SDB and CSB being applied to supplement more expensive modes of data collection that are cost prohibitive and less available to these nations. As the GEBCO Nippon Foundation Seabed 2030 Project seeks to continue to develop its openly accessible map of the world ocean by 2030, it must emphasize seek to identify and promote high-priority areas for new mapping efforts.  Equity must be highlighted within the approach taking in the factors of previously identified local priorities (e.g. AIS routes, potential off-shore wind sites, etc.), technology needed to collect the relevant data, the economic needs of country whose EEZ intersects with the area of interest, and the regional sensitivities to climate change and the reverberating effects to be felt throughout the environment and economy. This is an emergent framework that needs further investigation into the data that has been collected but not published or made publicly available to prevent re-mapping; global collaboration between variably owned research vessels, local officials and scientists within the region, and bathymetric data processing centers; and the relevant data formats and resolutions for different applications of the data for each stakeholder within the blue economy. 

Works Cited

Arun Kumar, S. V. V., Nagababu, G., Sharma, R., & Kumar, R. (2020). Synergetic use of multiple scatterometers for offshore wind energy potential assessment. Ocean Engineering, 196, 106745. https://doi.org/10.1016/j.oceaneng.2019.106745 

Ayilu, R. K., Fabinyi, M., & Barclay, K. (2022). Small-scale fisheries in the blue economy: Review of Scholarly Papers and multilateral documents. Ocean & Coastal Management, 216, 105982. https://doi.org/10.1016/j.ocecoaman.2021.105982 

Bennett, N. J., Blythe, J., White, C. S., & Campero, C. (2021). Blue Growth and blue justice: Ten risks and solutions for the ocean economy. Marine Policy, 125, 104387. https://doi.org/10.1016/j.marpol.2020.104387  

Bennett, N. J., Dearden, P., & Peredo, A. M. (2015). Vulnerability to multiple stressors in coastal communities: a study of the Andaman Coast of Thailand. Climate and Development, 7(2), 124-141. 

Celliers, L., Rosendo, S., Rölfer, L., Manez Costa, M., Snow, B., & Rivers, N. (2022). Sans frontières-ocean and coastal sustainability of the Western Indian Ocean. In Transition to a Sustainable Western Indian Ocean Blue Economy: Addressing the Challenges and Seizing the Opportunities. United Nations Nairobi Convention.  

Choti, J., & Xydis, G. (2022). Harnessing Offshore Wind Energy in East Africa: The next big move to lighting up the continent. Proceedings of the Institution of Civil Engineers – Civil Engineering, 175(6), 31–38. https://doi.org/10.1680/jcien.21.00253 

Elsner, P. (2019). Continental-scale assessment of the African Offshore Wind Energy Potential: Spatial analysis of an under-appreciated Renewable Energy Resource. Renewable and Sustainable Energy Reviews, 104, 394–407. https://doi.org/10.1016/j.rser.2019.01.034 

FAO. (2020). The State of World Fisheries and Aquaculture 2020. Sustainability in action. Rome. https://doi.org/10.4060/ca9229en 

Fischer, A. P. (2018). Pathways of adaptation to external stressors in coastal natural-resource-dependent communities: Implications for climate change. World Development, 108, 235–248. https://doi.org/10.1016/j.worlddev.2017.12.007  

Hettiarachchi, S. (2018). Establishing the indian ocean tsunami warning and mitigation system for human and environmental security. Procedia Engineering, 212, 1339–1346. https://doi.org/10.1016/j.proeng.2018.01.173 

Hoerling, M. P., Hurrell, J. W., Xu, T., Bates, G. T., & Phillips, A. S. (2004). Twentieth Century North Atlantic Climate Change. part II: Understanding the effect of Indian Ocean Warming. Climate Dynamics, 23(3–4), 391–405. https://doi.org/10.1007/s00382-004-0433-x  

Jensen, I.-J., Bodin, N., Govinden, R., & Elvevoll, E. O. (2023). Marine capture fisheries from Western Indian Ocean: An excellent source of proteins and essential amino acids. Foods, 12(5), 1015. https://doi.org/10.3390/foods12051015 

Kazimierczuk, A. H. (2019). Wind energy in Kenya: A status and Policy Framework Review. Renewable and Sustainable Energy Reviews, 107, 434–445. https://doi.org/10.1016/j.rser.2018.12.061 

Kelman, I. (2014). No change from climate change: vulnerability and small island developing states. The Geographical Journal, 180(2), 120–129. http://www.jstor.org/stable/43868597  

Kious, W. J., & Tilling, R. I. (1996). This dynamic earth: The story of plate tectonics. General Interest Publication. https://doi.org/10.3133/7000097  

Kull, C., & Andriamahefazafy, M. (2019). Materializing the blue economy: Tuna fisheries and the theory of access in the western Indian Ocean. Journal of Political Ecology, 26(1). https://doi.org/10.2458/v26i1.23040 

Kumar, P. S., Pillai, G. N., & Manjusha, U. (2014). El Nino Southern Oscillation (ENSO) impact on tuna fisheries in Indian Ocean. SpringerPlus, 3(1). https://doi.org/10.1186/2193-1801-3-591 

Marsac, F., Galletti, F., Ternon, J.-F., Romanov, E. V., Demarcq, H., Corbari, L., Bouchet, P., Roest, W. R., Jorry, S. J., Olu, K., Loncke, L., Roberts, M. J., & Ménard, F. (2020). Seamounts, plateaus and governance issues in the southwestern Indian Ocean, with emphasis on fisheries management and marine conservation, using the Walters Shoal as a case study for implementing a protection framework. Deep Sea Research Part II: Topical Studies in Oceanography, 176, 104715. https://doi.org/10.1016/j.dsr2.2019.104715 

National Intelligence Council. (2021). National Intelligence Estimate: Climate Change and International Responses Increasing Challenges to US National Security Through 2040. (NIC-NIE-2021-10030-A, p.12). Sep 1, 2023 

Nishida, T., Mohri, M., Itoh, K., & Nakagome, J. (2001). Study of bathymetry effects on the nominal hooking rates of yellowfin tuna (Thunnus albacares) and bigeye tuna (Thunnus obesus) exploited by the Japanese tuna longline fisheries in the Indian Ocean. In IOTC Proceedings (Vol. 4, No. 4, pp. 191-206). 

Nimit, K. (2021). Ideas and perspectives: Ushering the Indian Ocean into the UN Decade of ocean science for sustainable development (UNDOSSD) through Marine Ecosystem Research and Operational Services – an early career’s take. Biogeosciences, 18(12), 3631–3635. https://doi.org/10.5194/bg-18-3631-2021  

Novaglio, C., Bax, N., Boschetti, F. et al. Deep aspirations: towards a sustainable offshore Blue Economy. Rev Fish Biol Fisheries 32, 209–230 (2022). https://doi.org/10.1007/s11160-020-09628-6  

Rabbani, M. G., Rahman, A. A., Islam, N., Michel, D., & Pandya, A. (2010). Climate change and sea level rise: issues and challenges for coastal communities in the Indian Ocean region. Coastal zones and climate change, 17-29. 

Ranthodsang, M., Waewsak, J., Kongruang, C., & Gagnon, Y. (2020). Offshore wind power assessment on the western coast of Thailand. Energy Reports, 6, 1135–1146. https://doi.org/10.1016/j.egyr.2020.04.036 

Reimann, L., Vafeidis, A., & Honsel, L. (2023). Population development as a driver of coastal risk: Current trends and future pathways. Cambridge Prisms: Coastal Futures, 1, E14. doi:10.1017/cft.2023.3  

Sala, E., Costello, C., Dougherty, D., Heal, G., Kelleher, K., Murray, J. H., … & Sumaila, U. R. (2021). Protecting the global ocean for biodiversity, food, and climate. Nature, 592(7856), 397-402. 

Temple, A. J., Kiszka, J. J., Stead, S. M., Wambiji, N., Brito, A., Poonian, C. N., Amir, O. A., Jiddawi, N., Fennessy, S. T., Pérez-Jorge, S., & Berggren, P. (2017). Marine megafauna interactions with small-scale fisheries in the southwestern Indian Ocean: A review of Status and challenges for research and Management. Reviews in Fish Biology and Fisheries, 28(1), 89–115. https://doi.org/10.1007/s11160-017-9494-x 

United Nations. (2023a). Goal 1 | Department of Economic and Social Affairs. United Nations. https://sdgs.un.org/goals/goal1#targets_and_indicators  

United Nations. (2023b). Goal 2 | Department of Economic and Social Affairs. United Nations. https://sdgs.un.org/goals/goal2#targets_and_indicators  

United Nations. (2023c). Goal 7 | Department of Economic and Social Affairs. United Nations. https://sdgs.un.org/goals/goal7#targets_and_indicators  

United Nations. (2023d). Goal 9 | Department of Economic and Social Affairs. United Nations. https://sdgs.un.org/goals/goal9#targets_and_indicators 

United Nations. (2023e). Goal 13 | Department of Economic and Social Affairs. United Nations. https://sdgs.un.org/goals/goal13#targets_and_indicators 

United Nations. (2023f). Goal 14 | Department of Economic and Social Affairs. United Nations. https://sdgs.un.org/goals/goal14#targets_and_indicators 

US Department of Commerce. (2018, October 1). Tsunamis | National Oceanic and Atmospheric Administration. National Oceanic and Atmospheric Administration. https://www.noaa.gov/education/resource-collections/ocean-coasts/tsunamis 

Voyer, M., Quirk, G., McIlgorm, A., & Azmi, K. (2018). Shades of Blue: What do competing interpretations of the Blue Economy Mean for oceans governance? Journal of Environmental Policy & Planning, 20(5), 595–616. https://doi.org/10.1080/1523908x.2018.1473153  

Wright, G., Schmidt, S., Rochette, J., Shackeroff, J., Unger, S., Waweru, Y., Müller, A., ‘Partnering for a Sustainable Ocean: The Role of Regional Ocean Governance in Implementing SDG14’, PROG: IDDRI, IASS, TMG & UN Environment, 2017