Airborne DNA reveals decades of biodiversity loss – Earth.com

Long-Term Biodiversity Decline Revealed Through Airborne DNA Analysis in Northern Sweden

Introduction

A recent study conducted near Kiruna, northern Sweden, has uncovered a significant long-term decline in biodiversity over 34 years by analyzing genetic traces captured from archived air samples. This research highlights critical insights related to the Sustainable Development Goals (SDGs), particularly SDG 15 (Life on Land), SDG 13 (Climate Action), and SDG 12 (Responsible Consumption and Production).

Methodology: Utilizing Airborne Environmental DNA (eDNA)

Collection of Air Samples

1. Weekly replacement of air filters at a monitoring station outside Kiruna over several decades.
2. Filters trapped airborne particles including pollen, spores, and skin cells, preserving DNA fragments.
3. Archived filters stored in controlled environments for long-term analysis.

DNA Extraction and Sequencing

• DNA fragments were extracted by washing the filters.
• Advanced DNA sequencing techniques decoded genetic material.
• Machine learning algorithms assigned DNA fragments to approximately 2,700 organism groups, including plants, fungi, insects, birds, fish, and large mammals such as moose and reindeer.

Airflow Modeling

Air-flow and weather data were modeled to trace the origins of airborne DNA, distinguishing local biodiversity signals from distant sources. This step is crucial for accurate interpretation of ecosystem changes.

Validation and Complementary Approaches

Traditional field surveys were used to validate airborne DNA findings. While field surveys may miss elusive species or short-lived blooms, airborne DNA sampling can detect genetic traces even during adverse conditions such as storms or darkness. Combining both methods enhances biodiversity monitoring accuracy.

Key Findings: Biodiversity Decline and Ecosystem Changes

Observed Decline

• A marked decline in biodiversity was detected from the 1970s to the early 2000s.
• Significant reductions in birch populations, wood-associated lichens, and fungi were observed.
• Parallel shifts in microbes and insects indicate ecosystem-wide changes affecting multiple food web levels.

Drivers of Biodiversity Loss

1. Forest and land use changes, particularly logging and road construction, identified as primary pressures.
2. Selective cutting and even-aged planting practices reduce habitat complexity, negatively impacting specialist species.
3. Climate records did not fully explain the decline, emphasizing the role of human land management.

Limitations and Challenges of Airborne DNA Monitoring

• Inability to determine exact population sizes due to variable DNA shedding rates among species.
• Environmental factors such as temperature, sunlight, and microbial activity accelerate DNA degradation, complicating long-term comparisons.
• Incomplete reference databases for many insects and fungi limit precise taxonomic identification.

Global Implications and Future Applications

Expanding Airborne DNA Networks

Many air-monitoring stations worldwide archive filters that could be analyzed to reveal biodiversity trends in other regions, supporting SDG 15 by promoting ecosystem conservation globally.

Cost-Effective Biodiversity Monitoring

This method leverages existing air-quality infrastructure, reducing costs and environmental impact compared to establishing new survey systems, aligning with SDG 12 on sustainable resource use.

Early Warning System for Ecosystem Health

• Airborne DNA monitoring can detect genetic variation and invasive species early, aiding in pest and disease management (SDG 3: Good Health and Well-being).
• Provides baseline data for land managers to guide restoration and sustainable harvesting.
• Potential for open data sharing to facilitate regional and global biodiversity assessments while protecting sensitive species information.

Conclusion

The study, led by Associate Professor Per Stenberg of Umeå University and published in Nature Communications, demonstrates the power of airborne DNA analysis as a tool for long-term biodiversity monitoring. This innovative approach supports multiple Sustainable Development Goals by enhancing understanding of ecosystem changes, informing sustainable land use, and enabling proactive conservation efforts.

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1. Sustainable Development Goals (SDGs) Addressed

1. SDG 13: Climate Action
   • The article discusses climate pressures affecting northern ecosystems and the importance of monitoring environmental changes.
2. SDG 15: Life on Land
   • The core focus is on biodiversity decline, forest and land use changes, and ecosystem monitoring in northern Sweden.
3. SDG 3: Good Health and Well-being
   • Early warning systems for invasive species and disease tracking are mentioned, linking to ecosystem health and human well-being.
4. SDG 9: Industry, Innovation and Infrastructure
   • Use of advanced DNA sequencing, machine learning, and air monitoring infrastructure highlights innovation in environmental monitoring.

2. Specific Targets Under the Identified SDGs

1. SDG 13: Climate Action
   • Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters.
   • Target 13.3: Improve education, awareness-raising and human and institutional capacity on climate change mitigation, adaptation, impact reduction, and early warning.
2. SDG 15: Life on Land
   • Target 15.1: Ensure the conservation, restoration and sustainable use of terrestrial and inland freshwater ecosystems and their services.
   • Target 15.5: Take urgent and significant action to reduce the degradation of natural habitats, halt the loss of biodiversity.
   • Target 15.2: Promote the implementation of sustainable management of all types of forests.
3. SDG 3: Good Health and Well-being
   • Target 3.d: Strengthen the capacity of all countries for early warning, risk reduction and management of national and global health risks.
4. SDG 9: Industry, Innovation and Infrastructure
   • Target 9.5: Enhance scientific research, upgrade technological capabilities and encourage innovation.

3. Indicators Mentioned or Implied in the Article

1. Biodiversity Indicators
   • Long-term biodiversity decline measured through DNA fragments from airborne samples over 34 years.
   • Tracking changes in species groups such as plants, fungi, insects, birds, fish, and mammals.
   • Changes in forest structure indicated by decline in birch, lichens, and fungi.
2. Environmental Monitoring Indicators
   • Airborne environmental DNA (eDNA) as a proxy for species presence and ecosystem health.
   • Air-flow modeling and weather data to trace DNA source locations.
3. Early Warning System Indicators
   • Detection of invasive species and genetic variation through airborne DNA.
   • Timelines of ecosystem changes to guide restoration and management.
4. Technological and Research Indicators
   • Use of DNA sequencing, machine learning, and archived air filter data as innovative methods to monitor biodiversity.

4. Table of SDGs, Targets and Indicators

Source: earth.com