Christian A. Kull’s research while affiliated with University of Lausanne and other places

Globally, forest landscape restoration (FLR) is gaining ground, alongside other forms of restoration under the UN Decade on Ecosystem Restoration. In most cases, projects and initiatives fail to consider human dimensions that influence the processes and outcomes of the restoration effort. These dimensions refer to how and why humans value natural resources; how humans want resources to be managed; and how humans affect or are affected by natural resource management decisions. Using the model of the forest transition curve that shows the trajectory from loss of forests to restored forests, we discuss how FLR intersects in different ways with this transition curve. We conclude that: 1) definitions and their implications are a fundamental challenge for FLR; 2) there is an intrinsic interdependence between people and forests that varies across spatial and temporal scales and that is mediated by institutions; 3) power differentials among stakeholders create imbalances in restoration; 4) conflicts around restoration result from differing interests, power and values. Equitable and durable restoration requires a much greater inclusion of human dimensions along all steps of the process.

The concept of a forest transition – a regional shift from deforestation to forest recovery – tends to equate forest area expansion with sustainability, assuming that more forest is good for people and the environment. To promote debate and more just and ecologically sustainable outcomes during this period of intense focus on forests (such as the United Nations’ Decade on Ecological Restoration, the Trillion Trees initiative and at the United Nations’ Climate Change Conferences), we synthesize recent nuanced and integrated research to inform forest management and restoration in the future. Our results reveal nine pitfalls to assuming forest transitions and sustainability are automatically linked. The pitfalls are as follows: (1) fixating on forest quantity instead of quality; (2) masking local diversity with large-scale trends; (3) expecting U-shaped temporal trends of forest change; (4) failing to account for irreversibility; (5) framing categories and concepts as universal/neutral; (6) diverting attention from the simplification of forestlands into single-purpose conservation forests or intensive production lands; (7) neglecting social power transitions and dispossessions; (8) neglecting productivism as the hidden driving force; and (9) ignoring local agency and sentiments. We develop and illustrate these pitfalls with local- and national-level evidence from Southeast Asia and outline forward-looking recommendations for research and policy to address them. Forest transition research that neglects these pitfalls risks legitimizing unsustainable and unjust policies and programmes of forest restoration or tree planting.

Madagascar is one of the most burned regions in the world, to the point that it has been called the ‘Isle of fire’ or the ‘Burning Island’. An accurate characterization of the burned area (BA) is crucial for understanding the true situation and impacts of fires on this island, where there is an active scientific debate on how fire affects multiple environmental and socioeconomic aspects, and how fire regimes should be in a complex context with differing interests. Despite this, recent advances have revealed that BA in Madagascar is poorly characterised by the currently available global BA products. In this work, we present, validate, and explore a BA database at 20 m spatial resolution for Madagascar covering the period 2016-2022. The database was built based on 75,010 Sentinel-2 images using a two-phase BA detection algorithm. The validation with independent long-term reference units showed Dice coefficients ≥79%, omission errors ≤24%, commission errors ≤18%, and a relative bias ≥-8%. An intercomparison with other available global BA products (GABAM, FireCCI51, C3SBA11, or MCD64) demonstrated that our product (i) exhibits temporal consistency, (ii) represents a significant accuracy improvement, as it reduces BA underestimations by about eightfold, (iii) yields BA estimates four times higher, and (iv) shows enhanced capability in detecting fires of all sizes. The observed BA spatial patterns were heterogeneous across the island, with 32% of the grasslands burning annually, in contrast to other land cover types such as the dense tropical forest where less than 2% burned every year. We conclude that the BA characterization in Madagascar must be addressed using imagery at spatial resolution higher than MODIS or Sentinel-3 (≥250 m), and temporal resolution higher than Landsat (16 days) to deal with cloudiness, the rapid attenuation of burn scars signals, and small fire patches.

Madagascar is one of the most burned regions in the world, to the point that it has been called the ‘Isle of fire’ or the ‘Burning Island’. An accurate characterization of the burned area (BA) is crucial for understanding the true situation and impacts of fires on this island, where there is an active scientific debate on how fire affects multiple environmental and socioeconomic aspects, and how fire regimes should be in a complex context with differing interests. Despite this, recent advances have revealed that BA in Madagascar is poorly characterised by the currently available global BA products. In this work, we present, validate, and explore a BA database at 20 m spatial resolution for Madagascar covering the period 2016–2022. The database was built based on 75,010 Sentinel-2 images using a two-phase BA detection algorithm. The validation with independent long-term reference units showed Dice coefficients ≥79 %, omission errors ≤24 %, commission errors ≤18 %, and a relative bias ≥ − 8 %. An intercomparison with other available global BA products (GABAM, FireCCI51, C3SBA11, or MCD64) demonstrated that our product (i) exhibits temporal consistency, (ii) represents a significant accuracy improvement, as it reduces BA underestimations by about eightfold, (iii) yields BA estimates four times higher, and (iv) shows enhanced capability in detecting fires of all sizes. The observed BA spatial patterns were heterogeneous across the island, with 32 % of the grasslands burning annually, in contrast to other land cover types such as the dense tropical forest where <2 % burned every year. We conclude that the BA characterization in Madagascar must be addressed using imagery at spatial resolution higher than MODIS or Sentinel-3 (≥250 m), and temporal resolution higher than Landsat (16 days) to deal with cloudiness, the rapid attenuation of burn scars signals, and small fire patches.