One-year high-frequency environmental and behavioral data from ALAN experience in a French coastal area – Nature

Report on the Impact of Artificial Light at Night (ALAN) on Coastal Ecosystems in Alignment with Sustainable Development Goals

Introduction: Addressing Light Pollution to Advance Global Sustainability

The proliferation of Artificial Light at Night (ALAN) is a significant anthropogenic stressor with poorly understood effects on coastal ecosystems. This issue directly challenges the achievement of several Sustainable Development Goals (SDGs). The disruption of natural light cycles threatens marine biodiversity, undermining SDG 14 (Life Below Water). Furthermore, as ALAN is a byproduct of urbanization, it highlights the need for more environmentally conscious urban development in line with SDG 11 (Sustainable Cities and Communities). This report details a one-year in situ study conducted to generate high-quality data on ALAN’s impacts, providing a scientific basis for policies that promote sustainable coastal management and responsible production.

Background and Project Objectives

The Critical Role of Coastal Ecosystems and the Threat of ALAN

Coastal zones are critical for global sustainability, providing essential ecosystem services that support biodiversity and economic activities. They are central to achieving SDG 14 by hosting biodiversity hotspots and to SDG 12 (Responsible Consumption and Production) through industries like aquaculture and tourism. However, these areas are increasingly vulnerable to anthropogenic pressures. Currently, ALAN affects 22% of the world’s coasts, disrupting the biological timings, species interactions, and overall health of marine organisms. This light pollution represents a significant barrier to the conservation and sustainable use of marine resources.

The LUCIOLE Project: A Framework for Sustainable Solutions

The LUCIOLE project (2023–2026) was initiated to address the knowledge gap regarding ALAN’s impact on coastal environments. The project focuses on Arcachon Bay, France, a designated marine protected area that also supports intensive oyster farming—an economic cornerstone for the region. This site serves as a crucial case study for balancing conservation efforts with sustainable economic development, directly addressing the interconnected goals of SDG 14 and SDG 12. The project’s research is organized into four interconnected work packages:

1. Characterize and map ALAN in Arcachon Bay using remote sensing.
2. Assess ALAN impacts on sentinel oyster species through in-situ biomonitoring.
3. Characterize ALAN impacts on biological timing in controlled laboratory experiments.
4. Assess the physiological and pathological consequences of biological timing disruption.

This report focuses on the data generated from the second work package.

Research Methodology

Study Site and Experimental Design

The experiment was conducted from December 2023 to November 2024 at “Ile aux Oiseaux” in Arcachon Bay, a location selected for its minimal exposure to existing anthropogenic light. The experimental setup consisted of two underwater oyster tables:

• Control Condition: Exposed only to natural light cycles.
• ALAN Condition: Exposed to a skyglow ALAN intensity using underwater LEDs during the night.

This semi-controlled design ensured that both groups were exposed to identical environmental conditions, isolating ALAN as the primary experimental variable to produce reliable data for policy-making.

Technological Innovation for Environmental Monitoring (SDG 9)

The study utilized advanced and sustainable technologies, aligning with SDG 9 (Industry, Innovation, and Infrastructure). The monitoring platform was designed for long-term, autonomous operation.

• Biosensors: High-frequency non-invasive (HFNI) valvometers continuously recorded the valve behavior of sentinel oysters.
• Environmental Sensors: A suite of sensors measured light irradiance, temperature, water level, salinity, turbidity, conductivity, and low-frequency sound.
• Sustainable Infrastructure: The entire platform was powered by a solar panel and lithium batteries, demonstrating a commitment to sustainable research practices.

Sentinel Species and Parameters Measured

Two oyster species were selected as sentinel organisms to assess the impacts of ALAN, reflecting a dual focus on economic and ecological sustainability.

• Crassostrea gigas: An economically vital species for global aquaculture, relevant to SDG 12.
• Ostrea edulis: A native and endangered species, highlighting the study’s contribution to biodiversity conservation under SDG 14.

The continuous data collected on oyster behavior and the surrounding physicochemical environment were used to analyze disruptions to daily, lunar, and annual biological rhythms.

Data Records and Validation

Open-Access Data for Global Collaboration (SDG 17)

In support of SDG 17 (Partnerships for the Goals), all quality-controlled data from this experiment are freely available on the PANGAEA data repository. This open-access approach ensures that the findings can be utilized by scientists, public agencies, and industries to develop evidence-based strategies for mitigating light pollution. The bundled data records include five specific datasets:

• Hourly valve opening data of oysters Crassostrea gigas.
• Hourly valve opening data of oysters Ostrea edulis.
• Hourly underwater irradiance data.
• Hourly underwater sound pressure magnitude data.
• Hourly underwater physicochemical parameters.

Technical Validation and Quality Assurance

A rigorous validation process was implemented to ensure data integrity. After removing technical artifacts and data from deceased individuals, 1,915,157 data points were validated for analysis. Intercalibration of sensors confirmed that environmental parameters such as temperature (r² = 0.999) and water pressure (r² = 0.983) were highly comparable between the control and ALAN conditions, validating the experimental design. The sensors were regularly cleaned and calibrated according to manufacturer protocols to prevent biofouling and ensure measurement accuracy.

Implications for Sustainable Development

Informing Policy for Sustainable Cities and Communities (SDG 11)

The findings from this research provide critical evidence for local governments and urban planners to develop sustainable public lighting policies. By quantifying the ecological impact of ALAN, this study helps guide the adoption of lighting strategies that minimize harm to coastal ecosystems, contributing to the development of more sustainable and resilient cities.

Enhancing Responsible Production in Aquaculture (SDG 12)

The data on ALAN’s effects on oyster physiology, growth, and behavior can be used to optimize aquaculture practices. By modifying the lighting on oyster farms and advocating for reduced coastal light pollution, this research supports the long-term economic viability and environmental sustainability of the aquaculture industry, promoting responsible production and consumption patterns.

Conserving Life Below Water (SDG 14)

This study makes a direct and significant contribution to SDG 14 by generating high-frequency, long-term data on the impact of a pervasive pollutant on marine life. The results offer a scientific foundation for implementing targeted conservation measures, improving the management of marine protected areas, and mitigating a key threat to coastal biodiversity.

Analysis of Sustainable Development Goals in the Article

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

The article on the impact of Artificial Light at Night (ALAN) on coastal ecosystems connects to several Sustainable Development Goals (SDGs) by addressing environmental protection, sustainable economic activity, and scientific innovation.

• SDG 14: Life Below Water

  This is the most directly relevant SDG. The entire study focuses on understanding and mitigating the impacts of a pollutant (ALAN) on a coastal marine ecosystem (Arcachon Bay). It examines the health of marine species (oysters Crassostrea gigas and Ostrea edulis), the functioning of a marine protected area, and aims to provide data to preserve local biodiversity and ensure the health of coastal waters.

• SDG 11: Sustainable Cities and Communities

  The article links the problem of ALAN directly to anthropogenic stressors from urban areas. It states that Arcachon Bay is “bordered by ten coastal towns whose human population is constantly growing” and that the research aims to inform “local public lighting management policy strategies.” This connects the study to the goal of reducing the adverse environmental impact of cities on surrounding ecosystems.

• SDG 8: Decent Work and Economic Growth

  The research is situated in a region where oyster farming is a “primary source of regional economic and tourist activities.” A key objective of the study is to “improve oyster farming and economic benefits” by understanding how ALAN affects oyster health and growth. This aligns with promoting sustainable economic activities that depend on healthy ecosystems.

• SDG 9: Industry, Innovation, and Infrastructure

  The study is an example of scientific research and innovation aimed at solving an environmental challenge. It employs advanced technology, such as “high-frequency non-invasive valvometer biosensors” and a sophisticated experimental platform, to generate “high-quality environmental data.” This data is intended to inform both public policy and industrial practices (aquaculture), contributing to the development of sustainable infrastructure and industries.

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

Based on the article’s focus, several specific SDG targets can be identified:

1. Under SDG 14 (Life Below Water):

   • Target 14.1: “By 2025, prevent and significantly reduce marine pollution of all kinds, in particular from land-based activities…” The article directly addresses this by studying ALAN, which it identifies as a form of pollution originating from land-based “anthropogenic activities” and “urbanization” that affects “22% of the world’s coasts.”
   • Target 14.2: “By 2020, sustainably manage and protect marine and coastal ecosystems to avoid significant adverse impacts…” The study is conducted within the Arcachon Bay, a “marine protected area,” with the explicit goal of assessing ALAN’s impacts to develop “ad-hoc management approaches” and maintain “coastlines health.”
   • Target 14.a: “Increase scientific knowledge, develop research capacity and transfer marine technology… in order to improve ocean health…” The LUCIOLE project is designed to fill “fundamental gaps in the understanding of coastal ecosystems’ responses to ALAN” by generating a “quality-controlled, free-accessible dataset” to “better inform science, public policies, and oyster-farm management.”

2. Under SDG 11 (Sustainable Cities and Communities):

   • Target 11.6: “By 2030, reduce the adverse per capita environmental impact of cities…” The research aims to provide data that can be used in “local public lighting management policy strategies.” This directly contributes to reducing a specific adverse environmental impact—light pollution—generated by the “ten coastal towns” surrounding the bay.

3. Under SDG 8 (Decent Work and Economic Growth):

   • Target 8.4: “Improve progressively, through 2030, global resource efficiency in consumption and production and endeavour to decouple economic growth from environmental degradation…” The study’s goal to “improve oyster farming and economic benefits” by mitigating a form of environmental degradation (ALAN) directly supports the principle of making economic activities more sustainable and less harmful to the environment.

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

Yes, the article mentions and implies several specific, measurable indicators that can be used to track progress.

• Indicators for SDG 14 Targets:

  • For Target 14.1 (Reduce Marine Pollution): The primary indicator is the measurement of underwater light irradiance. This data provides a direct measure of the intensity of ALAN pollution in the marine environment, allowing for a baseline to be established and the effectiveness of mitigation strategies to be tracked.
  • For Target 14.2 (Protect Ecosystems): The article uses oysters as “sentinel organisms,” and their health serves as a proxy indicator for ecosystem health. Specific indicators mentioned are:
    • Oyster valve behavior: Measured by Valve Opening Amplitude (VOA) and Valve Opening Duration (VOD).
    • Oyster growth rate: The article mentions analyzing “daily shell growth at the annual scale.”
    • Oyster physiology and pathology: The study assesses the “consequences of biological timing disruption by ALAN on the physiology and pathology of the oysters.”
  • For Target 14.a (Increase Scientific Knowledge): The key indicator is the creation and accessibility of the scientific dataset. The article explicitly states that a “quality-controlled, free-accessible dataset” is available on the PANGAEA website, complete with specific DOIs for different data types (e.g., valve opening, irradiance, physicochemical parameters).

• Indicator for SDG 11 Target:

  • For Target 11.6 (Reduce Environmental Impact of Cities): An implied indicator is the adoption of evidence-based public lighting management policies by local municipalities. The success of the research can be measured by whether the “ten coastal towns” modify their lighting strategies based on the study’s findings to reduce ALAN.

4. Table of SDGs, Targets, and Indicators

Source: nature.com