Fragmentation and Degradation in Tropical Forests: Quantifying Impacts and Responses Under Global Change

Degraded and fragmented tropical forest landscapes are increasingly widespread and exposed to interacting pressures from climate change, recurrent disturbance, and land-use intensification. These landscapes remain critically important for biodiversity conservation, ecosystem functioning, carbon storage, and the provision of ecosystem services, yet their recovery potential varies substantially across regions and disturbance histories. Their protection and restoration are now explicitly embedded in international policy commitments, including the Paris Agreement and its Nationally Determined Contributions (NDCs), the UN Sustainable Development Goals (notably SDGs 13 and 15), the Kunming-Montreal Global

Biodiversity Framework, and the UN Decade on Ecosystem Restoration (2021–2030). Meeting these commitments depends on robust, comparable, and transferable scientific evidence to set targets and track progress across degraded and fragmented landscapes. Advances in forest mensuration, long-term field inventories, and airborne and satellite remote sensing have significantly improved the capacity to detect structural change and monitor forest condition. However, major uncertainties remain regarding how degradation and fragmentation jointly shape vegetation structure and biomass, species composition, functional attributes, and belowground processes in tropical forest landscapes, and how this knowledge can support restoration, connectivity, and adaptive forest management under global change.
This Research Topic examines the interacting effects of fragmentation, degradation, and climate-driven disturbances on tropical forest structure, biodiversity, carbon dynamics, and recovery potential. Although degraded and fragmented tropical forests are increasingly recognized as central to biodiversity persistence, climate mitigation, and restoration agendas, current evidence remains uneven across tropical regions, spatial scales, and methodological approaches. Much of the available literature is still based on localized case studies or focused on a limited set of response variables, especially aboveground biomass or carbon, with less integration of vegetation composition and structure, community dynamics, functional traits, belowground processes, and species interactions. At the same time, rapidly expanding tools—including multi-sensor remote sensing (eg., orbital, multispectral, hyperspectral, LiDAR, and SAR), artificial intelligence, ecological modelling and permanent plot networks, —can be combined to explain variation in forest trajectories across tropical landscapes. This Research Topic aims to address this gap by bringing together studies that quantify and compare how degraded and/or fragmented tropical forest landscapes respond under climate disturbance.
This Research Topic will prioritise studies covering tropical forest mesoscales and biome-level assessments, while also considering well-designed regional studies that offer a robust spatiotemporal approach and methodological relevance. We welcome interdisciplinary contributions integrating field inventories, remote sensing, artificial intelligence, and ecological modelling to enhance the understanding of tropical forest condition, and management in the face of global changes, including but not limited to the following:

• quantifying forest condition, fragmentation, degradation, and regeneration in tropical forest landscapes;
• modelling resilience and recovery across scales, including biodiversity, functional attributes, biomass and carbon, belowground processes, and species interactions;
• applications to restoration, connectivity, landscape planning, and adaptive forest management.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review
• Technology and Code

Keywords: AI, Planning, Conservation, Models, Management

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.