Forests, as part of their ecosystem services, serve as the world’s largest terrestrial sink of carbon (C) by storing it in biomass and soil (1–3). This C cycles through the ecosystem via biogeochemical processes causing it to move between different pools, (i.e., aboveground and belowground biomass, dead wood, litter, organic soil, and harvested wood products) or back to the atmosphere depending on the ecosystem’s dynamics and disturbances. These processes include photosynthesis, respiration, decomposition, and natural and anthropogenic disturbances (4). Studies of C stocks in forests are key to informing changes in greenhouse gas emission and removal accounts under climate change scenarios (3) and can be estimated at different scales.
When quantifying C at a large geographic scale, land use and land cover change and disturbance history are essential components to consider (3, 5, 6). In this matter, land use dynamics (2, 6–8) including land use legacies (7, 9), are major factors affecting terrestrial C fluxes. For example, C accumulation in forests of the eastern United States has been credited to historical changes in land use, especially to forest regrowth after agricultural abandonment (9). However, when quantifying C at a stand-level scale, land use change is rarely incorporated (10), creating uncertainties in C accounting.
Carbon emissions due to land use change can be quantified by separating the different C fluxes into its individual components. The Intergovernmental Panel on Climate Change (IPCC) provides guidelines for the estimation of national greenhouse gas (GHG) inventories (11), including C, which are consistent with reporting requirements in the United Nations Framework Convention on Climate Change (UNFCCC). These guidelines specifically include operational models to estimate fluxes (emissions and removals) using a process for each C pool. The fluxes are estimated for each land use category and differentiate the categories remaining the same from those that were converted to another land use.
However, much uncertainty exists when quantifying how much land use and land cover change actually contributes to C flux (2, 12), due, in part, to a lack of confidence in separating these fluxes into individual components (12). In addition, C dioxide emissions or transfers resulting from land use change may be underestimated as some processes (e.g., tree harvesting and land clearing from shifting cultivation) are not considered (9, 12–14) or data is limited. Similarly, there are too few global-scale observational constraints to exclusively estimate anthropogenic land use and land cover C emissions (12). Different methods have been used to estimate changes in C density caused by land use change. Three of the most common approaches include: inventory-based estimates, satellite-based estimates, and process-based vegetation models (14). In the US, estimates of GHG emissions and removals are estimated with data from the Forest Inventory and Analysis (FIA) program, which is in charge of conducting the US national forest inventory (4).
One of the common measures used in land use change research is land cover change, though this does not always accurately reflect actual land use change (15). A crucial difference between these two concepts is that tree cover loss (in case of forest cover) does not always show the activities that actually happen on the ground. Different drivers affect land use and land cover change. On the one hand, global drivers of tree cover loss include deforestation (mostly in Southeast Asia and Latin America), shifting agriculture (Africa and Latin America), forestry (Europe, North America, Russia/China/Southeast Asia, and Australia/Oceania), wildlife (Russia/China/Southeast Asia, Australia/Oceania, and North America), and urbanization (North America) (16). On the other hand, land use change is caused by both human and climate drivers. Decisions on land use are often based on short-term economic factors and are influenced by globalization, technological innovation, and policies at different levels (i.e. local, state or national) (17). For forest lands, the risk of conversion to other land uses is correlated with environmental, political, social, cultural, and economic factors (10, 17). Key drivers of this conversion include changes in demographic variables (3), urban expansion (18), distance to the nearest road (10), and deforestation for commodity production (16). Therefore, understanding the trends and long-term demographic context for population change could aid land managers and other stakeholders in mitigating the effects of residential development, especially near public lands, and anticipate future human population changes (19).
While global projections on carbon are bleak, the current situation in the US shows a better picture. Land use change at a global level is projected to contribute between 11 and 110 billion metric tons of carbon to the atmosphere by 2050 due to economic, social, and demographic trends (8). For forest land, global trends indicate a loss in the tropics and an increase in Europe, China, and North America (14). Specifically in the US, this trend is due to better forest management practices, reforestation, and an improvement in natural resources management, which have contributed to 11–13% of the global ecosystem carbon removal (8). However, even though these forests are expected to continue sequestering carbon, they would do so at declining rates mainly due to aging forests and land use dynamics (20).
The US’s future in C emissions might change according to land use change projections. Some studies show that even though current estimates for the eastern US (2001 to 2012) indicate that forest land use has changed (positive or negative) less than 5%, large changes in land use are likely in the coming decades in a business-as-usual scenario (3). For this study, recent trends indicated increasing forest areas in the southern Plains and Great Lakes’ states and losses in forest areas in the central and south-central states. Additional areas with high probability of conversion to non-forest include the Great Plains, especially in poorly stocked areas and/or sites with small diameter trees (10). Other studies estimate as high as 36% of the land area in the conterminous United States to change in land use between 2001 and 2051 in a business-as-usual scenario (21). According to this study, urban and forest land use in the US are predicted to increase by 79% and 7%, respectively. On the other hand, cropland and pasture land use are expected to decline by 16% and 13%, respectively (21).
Overall, the study of land use change is critical in forest C dynamics and better land use planning is needed to secure ecosystem services provided by forests. Even though some C stocks are increasing due to forest regrowth, especially from agricultural abandonment (22, 23), it is critical that we address the issue of forest conversion due to its significant contribution on the C budget. For example, in the US, forest lands, harvested wood products, and urban trees together offset more than 11% of the total annual GHG emissions (24). Here, C uptake estimates for forests remaining forests were − 564.5 MMT CO2 equivalent (eq.) in 2018. On the other hand, C emission estimates for forests which transitioned to other land uses during the same year were 127.4 MMT CO2-Eq. (24). To help address these issues, our research focuses on modeling the relationships among disturbances, land use change, and aboveground C stocks in six US states over an 18-year period. The research objectives are to (1) model the probability of forest conversion and C stock’s dynamics using USDA Forest Service Forest Inventory and Analysis (FIA) data and (2) create wall-to-wall maps showing estimates of the risk of areas to convert from forest to non-forest. This research will allow us to better understand the impacts of land use change on the forest C cycle and be able to more effectively determine priority areas for management and land use planning.