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Integrating Carbon Sequestration and Biodiversity Impacts in Forest Ecosystems: Concepts, Case Studies, and Policy Strategies

Year: 2025
Type: conference-paper
Abstract: The challenges of climate change, biodiversity loss, and land use are deeply interconnected, requiring integrated solutions. This paper (Alam et al. 2023) summarizes findings from 11 contributions in a special issue of AMBIO, where the authors, as guest editors, led discussions on topics such as integrated modelling, spatial prioritization, mass-balance studies, Earth Observation (EO) methods, research infrastructure, and the assessment of policy measures and economic compensation schemes. The studies cover various spatial scales, from site-specific analyses to broader European contexts. We present an overview of key conclusions, highlight general insights, and suggest areas for future research and methodological advancement. The papers in this special issue aim to address the following questions: How can areas important for both carbon (C) and biodiversity be identified in forests, and are there synergies or trade-offs between them? Can climate and biodiversity policy goals be met with current land-use trends and climate impacts? How do spatial, temporal, and resolution uncertainties, along with ecosystem interactions, affect evaluation outcomes? How should measurement systems and ecosystem research infrastructures be optimally developed? How can EO and deep learning techniques help develop indicators and detect landscape changes? How should economic instruments support integrated C and biodiversity policies? How are forest policy coherence and knowledge production linked? How can areas important for both carbon (C) and biodiversity be identified in forests, and are there synergies or trade-offs between them? Can climate and biodiversity policy goals be met with current land-use trends and climate impacts? How do spatial, temporal, and resolution uncertainties, along with ecosystem interactions, affect evaluation outcomes? How should measurement systems and ecosystem research infrastructures be optimally developed? How can EO and deep learning techniques help develop indicators and detect landscape changes? How should economic instruments support integrated C and biodiversity policies? How are forest policy coherence and knowledge production linked? We identify three key interconnected themes based on the individual contributions. First, we analyse the evaluation and modelling of C and greenhouse gas (GHG) processes in forested landscapes. Studies show that achieving C neutrality at national and regional levels requires both reducing anthropogenic GHG emissions and maintaining C sinks through moderate forest harvesting policies. Mitigation potential and land-use strategies vary by region, and the C neutrality gap can be quantified using the techniques developed in these papers (Forsius et al. 2023, Holmberg et al. 2023, Junttila et al. 2023, Mäkelä et al. 2023, Rankinen et al. 2023). Second, we conclude by discussing the integration of C and biodiversity processes and their landscape-level impacts. The papers in this special issue offer methods and databases for designing optimal solutions for co-managing climate and biodiversity. Using various approaches,Mäkelä et al. (2023) and Kujala et al. (2023) demonstrate that reducing harvesting levels benefits both C storage and biodiversity. While biodiversity conservation is increasingly linked to climate mitigation goals, it should remain the primary focus when prioritizing areas for protection. Finally, we discuss the implementation of economic instruments and policy measures. Kangas and Ollikainen (2023) highlight that adding a C payment to a biodiversity conservation program, with a corresponding increase in the conservation budget, boosts site availability and promotes synergy between biodiversity and C goals. Kujala et al. (2023) show that biodiversity values and stand age correlate more with C storage than with potential C sinks, which should be considered when designing Payments for Ecosystem Services (PES) schemes.
Language: English
Open Access status: diamond
OpenAlex ID: W4410826240
FWCI:
Cites: 8
Cited by:
Related to: 10