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Multiple climate-driven stressors, including warming and increased nutrient delivery, are exacerbating hypoxia in coastal marine environments. Within coastal watersheds, environmental managers are particularly interested in climate impacts on terrestrial processes, which may undermine the efficacy of management actions designed to reduce eutrophication and consequent low-oxygen conditions in receiving coastal waters. However, substantial uncertainty accompanies the application of Earth System Model (ESM) projections to a regional modeling framework when quantifying future changes to estuarine hypoxia due to climate change. In this study, two downscaling methods are applied to multiple ESMs and used to force two independent watershed models for Chesapeake Bay, a large coastal-plain estuary of the eastern United States. The projected watershed changes are then used to force a coupled 3-D hydrodynamic-biogeochemical estuarine model to project climate impacts on hypoxia, with particular emphasis on projection uncertainties. Results indicate that all three factors (ESM, downscaling method, and watershed model) are found to contribute significantly to the uncertainty associated with future hypoxia, with the choice of ESM being the largest contributor. Overall, in the absence of management actions, there is a high likelihood that climate change impacts on the watershed will expand low-oxygen conditions by 2050, relative to a 1990s baseline period; however, the projected increase in hypoxia is quite small (4 %) because only climate-induced changes in watershed inputs are considered and not those on the estuary itself. Results also demonstrate that the attainment of established nutrient reduction targets will reduce annual hypoxia by about 50 % compared to the 1990s. Given these estimates, it is virtually certain that fully implemented management actions reducing excess nutrient loadings will outweigh hypoxia increases driven by climate-induced changes in terrestrial runoff.

Satellite data reveal widespread changes in Earth's vegetation cover. Regions intensively attended to by humans are mostly greening due to land management. Natural vegetation, on the other hand, is exhibiting patterns of both greening and browning in all continents. Factors linked to anthropogenic carbon emissions, such as CO2 fertilization, climate change, and consequent disturbances such as fires and droughts, are hypothesized to be key drivers of changes in natural vegetation. A rigorous regional attribution at the biome level that can be scaled to a global picture of what is behind the observed changes is currently lacking. Here we analyze different datasets of decades-long satellite observations of global leaf area index (LAI, 1981–2017) as well as other proxies for vegetation changes and identify several clusters of significant long-term changes. Using process-based model simulations (Earth system and land surface models), we disentangle the effects of anthropogenic carbon emissions on LAI in a probabilistic setting applying causal counterfactual theory. The analysis prominently indicates the effects of climate change on many biomes – warming in northern ecosystems (greening) and rainfall anomalies in tropical biomes (browning). The probabilistic attribution method clearly identifies the CO2 fertilization effect as the dominant driver in only two biomes, the temperate forests and cool grasslands, challenging the view of a dominant global-scale effect. Altogether, our analysis reveals a slowing down of greening and strengthening of browning trends, particularly in the last 2 decades. Most models substantially underestimate the emerging vegetation browning, especially in the tropical rainforests. Leaf area loss in these productive ecosystems could be an early indicator of a slowdown in the terrestrial carbon sink. Models need to account for this effect to realize plausible climate projections of the 21st century.

The Chesapeake Bay is a large coastal-plain estuary that has experienced considerable anthropogenic change over the past century. At the regional scale, land-use change has doubled the nutrient input from rivers and led to an increase in riverine carbon and alkalinity. The bay has also experienced global changes, including the rise of atmospheric temperature and CO2. Here we seek to understand the relative impact of these changes on the inorganic carbon balance of the bay between the early 1900s and the early 2000s. We use a linked land–estuarine–ocean modeling system that includes both inorganic and organic carbon and nitrogen cycling. Sensitivity experiments are performed to isolate the effect of changes in (1) atmospheric CO2, (2) temperature, (3) riverine nitrogen loading and (4) riverine carbon and alkalinity loading. Specifically, we find that over the past century global changes have increased ingassing by roughly the same amount (∼30 Gg-C yr−1) as has the increased riverine loadings. While the former is due primarily to increases in atmospheric CO2, the latter results from increased net ecosystem production that enhances ingassing. Interestingly, these increases in ingassing are partially mitigated by increased temperatures and increased riverine carbon and alkalinity inputs, both of which enhance outgassing. Overall, the bay has evolved over the century to take up more atmospheric CO2 and produce more organic carbon. These results suggest that over the past century, changes in riverine nutrient loads have played an important role in altering coastal carbon budgets, but that ongoing global changes have also substantially affected coastal carbonate chemistry.

A three-dimensional coupled physical–biogeochemical model was used to simulate and examine temporal and spatial variability of sea surface pCO2 in the Gulf of Mexico (GoM). The model was driven by realistic atmospheric forcing, open boundary conditions from a data-assimilative global ocean circulation model, and observed freshwater and terrestrial nutrient and carbon input from major rivers. A 7-year model hindcast (2004–2010) was performed and validated against ship measurements. Model results revealed clear seasonality in surface pCO2 and were used to estimate carbon budgets in the Gulf. Based on the average of model simulations, the GoM was a net CO2 sink with a flux of 1.11 ± 0.84 × 1012 mol C yr−1, which, together with the enormous fluvial inorganic carbon input, was comparable to the inorganic carbon export through the Loop Current. Two model sensitivity experiments were performed: one without biological sources and sinks and the other using river input from the 1904–1910 period as simulated by the Dynamic Land Ecosystem Model (DLEM). It was found that biological uptake was the primary driver making GoM an overall CO2 sink and that the carbon flux in the northern GoM was very susceptible to changes in river forcing. Large uncertainties in model simulations warrant further process-based investigations.

Over the past 4 decades, a number of numerical models have been developed to quantify the magnitude, investigate the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH4) fluxes within terrestrial ecosystems. These CH4 models are also used for integrating multi-scale CH4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls, and (3) significant data–model and model–model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Three areas for future improvements and applications of terrestrial CH4 models are that (1) CH4 models should more explicitly represent the mechanisms underlying land–atmosphere CH4 exchange, with an emphasis on improving and validating individual CH4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. These improvements in CH4 models would be beneficial for the Earth system models and further simulation of climate–carbon cycle feedbacks.

As urban land expands rapidly across the globe, much concern has been raised that urbanization may alter the terrestrial carbon cycle. Urbanization involves complex changes in land structure and multiple environmental factors. Little is known about the relative contribution of these individual factors and their interactions to the terrestrial carbon dynamics, however, which is essential for assessing the effectiveness of carbon sequestration policies focusing on urban development. This study developed a comprehensive analysis framework for quantifying relative contribution of individual factors (and their interactions) to terrestrial carbon dynamics in urbanized areas. We identified 15 factors belonging to five categories, and we applied a newly developed factorial analysis scheme to the southern United States (SUS), a rapidly urbanizing region. In all, 24 numeric experiments were designed to systematically isolate and quantify the relative contribution of individual factors. We found that the impact of land conversion was far larger than other factors. Urban managements and the overall interactive effects among major factors, however, created a carbon sink that compensated for 42% of the carbon loss in land conversion. Our findings provide valuable information for regional carbon management in the SUS: (1) it is preferable to preserve pre-urban carbon pools than to rely on the carbon sinks in urban ecosystems to compensate for the carbon loss in land conversion. (2) In forested areas, it is recommendable to improve landscape design (e.g., by arranging green spaces close to the city center) to maximize the urbanization-induced environmental change effect on carbon sequestration. Urbanization-induced environmental change will be less effective in shrubland regions. (3) Urban carbon sequestration can be significantly improved through changes in management practices, such as increased irrigation and fertilizer and targeted use of vehicles and machinery with least-associated carbon emissions.

Nitrous oxide (N2O) is a potent greenhouse gas which also contributes to the depletion of stratospheric ozone (O3). However, the magnitude and underlying mechanisms for the spatiotemporal variations in the terrestrial sources of N2O are still far from certain. Using a process-based ecosystem model (DLEM – the Dynamic Land Ecosystem Model) driven by multiple global change factors, including climate variability, nitrogen (N) deposition, rising atmospheric carbon dioxide (CO2), tropospheric O3 pollution, N fertilizer application, and land conversion, this study examined the spatial and temporal variations in terrestrial N2O flux over North America and further attributed these variations to various driving factors. From 1979 to 2010, the North America cumulatively emitted 53.9 ± 0.9 Tg N2O-N (1 Tg = 1012 g), of which global change factors contributed 2.4 ± 0.9 Tg N2O-N, and baseline emission contributed 51.5 ± 0.6 Tg N2O-N. Climate variability, N deposition, O3 pollution, N fertilizer application, and land conversion increased N2O emission while the elevated atmospheric CO2 posed opposite effect at continental level; the interactive effect among multiple factors enhanced N2O emission over the past 32 yr. N input, including N fertilizer application in cropland and N deposition, and multi-factor interaction dominated the increases in N2O emission at continental level. At country level, N fertilizer application and multi-factor interaction made large contribution to N2O emission increase in the United States of America (USA). The climate variability dominated the increase in N2O emission from Canada. N inputs and multiple factors interaction made large contribution to the increases in N2O emission from Mexico. Central and southeastern parts of the North America – including central Canada, central USA, southeastern USA, and all of Mexico – experienced increases in N2O emission from 1979 to 2010. The fact that climate variability and multi-factor interaction largely controlled the inter-annual variations in terrestrial N2O emission at both continental and country levels indicate that projected changes in the global climate system may substantially alter the regime of N2O emission from terrestrial ecosystems during the 21st century. Our study also showed that the interactive effect among global change factors may significantly affect N2O flux, and more field experiments involving multiple factors are urgently needed.

The attribution of spatial and temporal variations in terrestrial methane (CH4) flux is essential for assessing and mitigating CH4 emission from terrestrial ecosystems. In this study, we used a process-based model, the Dynamic Land Ecosystem Model (DLEM), in conjunction with spatial data of six major environmental factors to attribute the spatial and temporal variations in the terrestrial methane (CH4) flux over North America from 1979 to 2008 to six individual driving factors and their interaction. Over the past three decades, our simulations indicate that global change factors accumulatively contributed 23.51 ± 9.61 T g CH4-C (1 Tg = 1012 g) emission over North America, among which ozone (O3) pollution led to a reduced CH4 emission by 2.30 ± 0.49 T g CH4-C. All other factors including climate variability, nitrogen (N) deposition, elevated atmospheric carbon dioxide (CO2), N fertilizer application, and land conversion enhanced terrestrial CH4 emissions by 19.80 ± 12.42 T g CH4-C, 0.09 ± 0.02 T g CH4-C, 6.80 ± 0.86 T g CH4-C, 0.01 ± 0.001 T g CH4-C, and 3.95 ± 0.38 T g CH4-C, respectively, and interaction between/among these global change factors led to a decline of CH4 emission by 4.84 ± 7.74 T g CH4-C. Climate variability and O3 pollution suppressed, while other factors stimulated CH4 emission over the USA; climate variability significantly enhanced, while all the other factors exerted minor effects, positive or negative, on CH4 emission in Canada; Mexico functioned as a sink for atmospheric CH4 with a major contribution from climate change. Climatic variability dominated the inter-annual variations in terrestrial CH4 flux at both continental and country levels. Precipitation played an important role in the climate-induced changes in terrestrial CH4 flux at both continental and country-levels. The relative importance of each environmental factor in determining the magnitude of CH4 flux showed substantially spatial variation across North America. This factorial attribution of CH4 flux in North America might benefit policy makers who would like to curb climate warming by reducing CH4 emission.