Abstract The global forest carbon stocks represent the amount of carbon stored in woody vegetation and are important for quantifying the ability of the global forests to sequester atmospheric CO2and to provide ecosystem services (e.g., timber) under climate change. The forest ecosystem carbon pool estimates are highly variable and poorly quantified in areas lacking forest inventory estimates. Here, we compare and analyze aboveground biomass (AGB) estimates from five satellite‐based global data sets and nine dynamic global vegetation models (DVGMs). We find that across the data sets, mean AGB exhibits the largest variability around the tropical area. In addition, AGB shows a similar latitudinal trend but large variability among the data sets. Satellite‐based AGB estimates are lower than those simulated by DVGMs. The divergence among the satellite‐based AGB estimates can be driven by the methodology, input satellite products, and the forested areas used to estimate AGB. The modeled NPP, autotrophic respiration, and carbon allocation mostly drive the variability of AGB simulated by DGVMs. The future availability of a high‐quality global forest area map is anticipated to improve AGB estimate accuracy and to reduce the discrepancies among different satellite‐ and model‐based AGB estimates. We suggest the carbon‐modeling community reexamine the methodology used to estimate AGB and forested areas for a more robust global forest carbon stock estimation. 
                        more » 
                        « less   
                    This content will become publicly available on July 1, 2026
                            
                            Anthromes and forest carbon responses to global change
                        
                    
    
            Societal Impact StatementForest ecosystems absorb and store about 25% of global carbon dioxide emissions annually and are increasingly shaped by human land use and management. Climate change interacts with land use and forest dynamics to influence observed carbon stocks and the strength of the land carbon sink. We show that climate change effects on modeled forest land carbon stocks are strongest in tropical wildlands that have limited human influence. Global forest carbon stocks and carbon sink strength may decline as climate change and anthropogenic influences intensify, with wildland tropical forests, especially in Amazonia, likely being especially vulnerable. SummaryHuman effects on ecosystems date back thousands of years, and anthropogenic biomes—anthromes—broadly incorporate the effects of human population density and land use on ecosystems. Forests are integral to the global carbon cycle, containing large biomass carbon stocks, yet their responses to land use and climate change are uncertain but critical to informing climate change mitigation strategies, ecosystem management, and Earth system modeling.Using an anthromes perspective and the site locations from the Global Forest Carbon (ForC) Database, we compare intensively used, cultured, and wildland forest lands in tropical and extratropical regions. We summarize recent past (1900‐present) patterns of land use intensification, and we use a feedback analysis of Earth system models from the Coupled Model Intercomparison Project Phase 6 to estimate the sensitivity of forest carbon stocks to CO2and temperature change for different anthromes among regions.Modeled global forest carbon stock responses are positive for CO2increase but neutral to negative for temperature increase. Across anthromes (intensively used, cultured, and wildland forest areas), modeled forest carbon stock responses of temperate and boreal forests are less variable than those of tropical forests. Tropical wildland forest areas appear especially sensitive to CO2and temperature change, with the negative temperature response highlighting the potential vulnerability of the globally significant carbon stock in tropical forests.The net effect of anthropogenic activities—including land‐use intensification and environmental change and their interactions with natural forest dynamics—will shape future forest carbon stock changes. These interactive effects will likely be strongest in tropical wildlands. 
        more » 
        « less   
        
    
                            - Award ID(s):
- 2306198
- PAR ID:
- 10613831
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- PLANTS, PEOPLE, PLANET
- Volume:
- 7
- Issue:
- 4
- ISSN:
- 2572-2611
- Page Range / eLocation ID:
- 1027 to 1042
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
- 
            
- 
            Summary The mortality rates of large trees are critical to determining carbon stocks in tropical forests, but the mechanisms of tropical tree mortality remain poorly understood. Lightning strikes thousands of tropical trees every day, but is commonly assumed to be a minor agent of tree mortality in most tropical forests.We use the first systematic quantification of lightning‐caused mortality to show that lightning is a major cause of death for the largest trees in an old‐growth lowland forest in Panama. A novel lightning strike location system together with field surveys of strike sites revealed that, on average, each strike directly kills 3.5 trees (> 10 cm diameter) and damages 11.4 more.Given lightning frequency data from the Earth Networks Total Lightning Network and historical total tree mortality rates for this site, we conclude that lightning accounts for 40.5% of the mortality of large trees (> 60 cm diameter) in the short term and probably contributes to an additional 9.0% of large tree deaths over the long term.Any changes in cloud‐to‐ground lightning frequency due to climatic change will alter tree mortality rates; projected 25–50% increases in lightning frequency would increase large tree mortality rates in this forest by 9–18%. The results of this study indicate that lightning plays a critical and previously underestimated role in tropical forest dynamics and carbon cycling.more » « less
- 
            Climate change increases fire-favorable weather in forests, but fire trends are also affected by multiple other controlling factors that are difficult to untangle. We use machine learning to systematically group forest ecoregions into 12 global forest pyromes, with each showing distinct sensitivities to climatic, human, and vegetation controls. This delineation revealed that rapidly increasing forest fire emissions in extratropical pyromes, linked to climate change, offset declining emissions in tropical pyromes during 2001 to 2023. Annual emissions tripled in one extratropical pyrome due to increases in fire-favorable weather, compounded by increased forest cover and productivity. This contributed to a 60% increase in forest fire carbon emissions from forest ecoregions globally. Our results highlight the increasing vulnerability of forests and their carbon stocks to fire disturbance under climate change.more » « less
- 
            Abstract Tropical forests are increasingly threatened by deforestation and degradation, impacting carbon storage, climate regulations and biodiversity. Restoring these ecosystems is crucial for environmental sustainability, yet monitoring these efforts poses significant challenges. Secondary forests are in a constant state of flux, with growth depending on multiple factors.Remote sensing technologies offer cost‐effective, scalable and transferable solutions, advancing forest restoration monitoring towards more accurate, efficient and real‐time data analysis and interpretation. This review provides a comprehensive evaluation of the current state and advancements in remote sensing technologies applied to monitoring tropical forest restoration.Synthesis and applications: This review brings together the state of the art of remote sensing technologies, such as very‐high‐resolution RGB imagery, multi‐ and hyperspectral imaging, lidar, radar and thermal‐infrared technologies and their applicability in monitoring forest restoration. In conclusion, this review emphasizes the potential of remote sensing technologies, coupled with advanced computational techniques, to enhance global efforts towards effective and sustainable forest restoration monitoring.more » « less
- 
            Abstract As we increasingly understand the impact that land management intensification has on local and global climate, the call for nature-based solutions (NbS) in agroecosystems has expanded. Moreover, the pressing need to determine when and where NbS should be used raises challenges to socioecological data integration as we overcome spatiotemporal resolutions. Natural and working lands is an effort promoting NbS, particularly emissions reduction and carbon stock maintenance in forests. To overcome the spatiotemporal limitation, we integrated life cycle assessments (LCA), an ecological carbon stock model, and a land cover land use change model to synthesize rates of global warming potential (GWP) within a fine-scale geographic area (30 m). We scaled National Agricultural Statistic Survey land management data to National Land Cover Data cropland extents to assess GWP of cropland management over time and among management units (i.e. counties and production systems). We found that cropland extent alone was not indicative of GWP emissions; rather, rates of management intensity, such as energy and fertilizer use, are greater indicators of anthropogenic GWP. We found production processes for fuel and fertilizers contributed 51.93% of GWP, where 33.58% GWP was estimated from N2O emissions after fertilization, and only 13.31% GWP was due to energy consumption by field equipment. This demonstrates that upstream processes in LCA should be considered in NbS with the relative contribution of fertilization to GWP. Additionally, while land cover change had minimal GWP effect, urbanization will replace croplands and forests where NbS are implemented. Fine-scale landscape variations are essential for NbS to identify, as they accumulate within regional and global estimates. As such, this study demonstrates the capability to harness both LCA and fine-resolution imagery for applications in spatiotemporal and socioecological research towards identifying and monitoring NbS.more » « less
 An official website of the United States government
An official website of the United States government 
				
			 
					 
					
