Periodic Reporting for period 1 - FAIR (Forest transitions in the Anthropocene and their Implications for Restoration values – a global assessment based on remote sensing)
Período documentado: 2020-07-01 hasta 2022-06-30
Forest degradation and biodiversity losses caused by land conversion and over-use have strongly increased since the mid-20th century. Today, only 22% of the global forest area remains as intact forest with little human activity or habitat fragmentation. Despite their exceptional value for global biodiversity conservation, ecosystem services and human well-being, only 12% of the intact forests are protected, and many intact forests risk degradation from climate change and increasing human pressures, e.g. conversion to agriculture, extractive harvesting, and fragmentation. However, forest transitions - shift from net deforestation to net reforestation - have occurred widely and rapidly in recent decades. These net increases in forest area are due to active afforestation, reforestation, and spontaneous reforestation following land abandonment. In addition to increases in forest area, reversals from forest degradation to net gains in tree cover and forest quality are also reported from degraded forests. Recent studies highlight that global forest restoration provides us with an important opportunity for climate change mitigation. However, the restoration of biodiversity and ecosystem processes often fails, e.g. when monocultures are planted, if the landscape is fragmented, or due to social, political, and economic pressures. The need to develop strategies for shaping forest transitions has been increasingly highlighted, with active restoration becoming a global priority with billions of dollars invested. The overall objective of FAIR is to link the trajectories of global forest transitions dynamic (i.e. de- to reforestation shifts and analogous shifts in intactness) to societal and climate change. FAIR relies strongly on remote sensing remote sensing satellite data, which has tremendous potential to map, quantify, and monitor forest change at global scale. We found that: 1) remotely sensed tree-cover heterogeneity can easily distinguish tree plantations from primary and secondary forests. 2) that human factors are the second-most important driver of forest structure after climate - both globally and regionally. It even had dominant influence on forest structure in protected areas and intact forest landscapes. 3) greater influence of climate, human activities, and fire on the structure of naturally regrown forests compared to planted forests globally, particularly in areas with low human development, indicating that naturally regrown forests are at particularly high risk from anthropogenic pressures and climate stress.
1) Global mapping of forest transition types
We first explored the spatial patterns in global forest transition types (primary, secondary, planted) in different biomes. We then investigated the underlying relationship between tree cover and its heterogeneity at landscape scale for different forest transition types across the globe. Finally, nine possible combinations of variation trends in tree cover and its heterogeneity were used to generate a new map of forest dynamics categories. Our results showed that monotonic changes in tree cover are not necessarily associated with changes in tree cover heterogeneity. This suggested that simply using variation trends of tree cover without considering the context of local spatial heterogeneity does not fully capture forest dynamics. We showed that remotely sensed tree cover heterogeneity can easily distinguish tree plantations from primary and secondary forests and that temporal change in tree cover heterogeneity is sensitive to spatial heterogeneity of open forest landscapes.
2) Quantification of forest transitions in structure and composition
We used a massive dataset from the GEDI LiDAR and MODIS satellites for the year 2020 to develop and map forest structural density at a near-global scale. We found: 1) distinct latitudinal patterns of multidimensional forest structure, and 2) that forests in protected areas and so-called intact forest landscapes have an overall higher structural density than other forests across different biomes. We quantified the multidimensional canopy structure of secondary forests (naturally regrown as well as planted) at a near-global scale and link it to the preceding 19-year tree cover dynamics using satellite remote sensing. We found that naturally regrown forests are structurally more like primary forests than planted forests but suffer higher rates of tree cover re-clearance than planted forests globally.
3) Analysis of societal and climate change drivers and modulators
We investigated how global forest structural density related to climatic, anthropogenic, soil, and topographic factors at both global and regional scale using a linear mixed-effects regression model and a geographically weighted regression model, respectively. We found that human factors are the second-most important driver of forest structure after climate both globally and regionally and had dominant influence on forest structure in protected areas and intact forest landscapes. Effects of preceding re-clearance on secondary forest structure were evaluated along the year of tree cover loss, differentiating naturally regrown and planted forests. Finally, we investigated how secondary forest structural density and heterogeneity were linked to climate, human activities, and fire, and assessed how these relations vary with socioeconomic conditions. We found greater influence of climate, human activities, and fire on the structure of naturally regrown forests than planted forests, particularly in areas with low human development, indicating that naturally regrown forests are at particularly high risk from anthropogenic pressures and climate stress globally.
We first explored the spatial patterns in global forest transition types (primary, secondary, planted) in different biomes. We then investigated the underlying relationship between tree cover and its heterogeneity at landscape scale for different forest transition types across the globe. Finally, nine possible combinations of variation trends in tree cover and its heterogeneity were used to generate a new map of forest dynamics categories. Our results showed that monotonic changes in tree cover are not necessarily associated with changes in tree cover heterogeneity. This suggested that simply using variation trends of tree cover without considering the context of local spatial heterogeneity does not fully capture forest dynamics. We showed that remotely sensed tree cover heterogeneity can easily distinguish tree plantations from primary and secondary forests and that temporal change in tree cover heterogeneity is sensitive to spatial heterogeneity of open forest landscapes.
2) Quantification of forest transitions in structure and composition
We used a massive dataset from the GEDI LiDAR and MODIS satellites for the year 2020 to develop and map forest structural density at a near-global scale. We found: 1) distinct latitudinal patterns of multidimensional forest structure, and 2) that forests in protected areas and so-called intact forest landscapes have an overall higher structural density than other forests across different biomes. We quantified the multidimensional canopy structure of secondary forests (naturally regrown as well as planted) at a near-global scale and link it to the preceding 19-year tree cover dynamics using satellite remote sensing. We found that naturally regrown forests are structurally more like primary forests than planted forests but suffer higher rates of tree cover re-clearance than planted forests globally.
3) Analysis of societal and climate change drivers and modulators
We investigated how global forest structural density related to climatic, anthropogenic, soil, and topographic factors at both global and regional scale using a linear mixed-effects regression model and a geographically weighted regression model, respectively. We found that human factors are the second-most important driver of forest structure after climate both globally and regionally and had dominant influence on forest structure in protected areas and intact forest landscapes. Effects of preceding re-clearance on secondary forest structure were evaluated along the year of tree cover loss, differentiating naturally regrown and planted forests. Finally, we investigated how secondary forest structural density and heterogeneity were linked to climate, human activities, and fire, and assessed how these relations vary with socioeconomic conditions. We found greater influence of climate, human activities, and fire on the structure of naturally regrown forests than planted forests, particularly in areas with low human development, indicating that naturally regrown forests are at particularly high risk from anthropogenic pressures and climate stress globally.
The results obtained in this project contribute with important corrections to popular beliefs about forest degradation drivers and uncovers the extent of human impacts on the natural environment. Such knowledge should be taken into consideration in planning and sustainable management of protected areas and intact forest landscapes. The worrying re-degradation risks of naturally regrown forests found in this project point to underestimated challenges for achieving climate change mitigation, biodiversity conservation, and the sustainable development goals (SDG13 & 15). FAIR outputs emphasize the importance to ensure the persistence of natural forest regeneration via enforced land-use policies globally. It is urgently needed to realize and upscale the potential of global naturally regrown forests in ecosystem restoration and sustainable development.
The grant managed to add valuable aspects to the experienced researcher’s academic career and helped him mature as a researcher with a deeper understanding of the societal impacts of his research subject. The skillset the experienced researcher obtained enabled him to become a very competitive scientist in environmental resource monitoring and protection, which is a big demand in his home country China.
The grant managed to add valuable aspects to the experienced researcher’s academic career and helped him mature as a researcher with a deeper understanding of the societal impacts of his research subject. The skillset the experienced researcher obtained enabled him to become a very competitive scientist in environmental resource monitoring and protection, which is a big demand in his home country China.