Long-term moderate warming shifts soil carbon cycling but maintains carbon sinks in a subtropical forest

The primary objective of the proposed research was to quantify and explain the effects of a sustained in situ 5oC soil temperature increase on net carbon (C) storage in a northeastern deciduous forest ecosystem. The research was done at an established soil warming experiment at the Harvard Forest in central Massachusetts – Barre Woods site established in 2001. In the field, a series of plant and soil measurements were made to quantify changes in C storage in the ecosystem and to provide insights into the possible relationships between C-storage changes and nitrogen (N) cycling changes in the warmed plots. Field measurements included: 1) annual woody increment; 2) litterfall; 3) carbon dioxide (CO2) efflux from the soil surface; 4) root biomass and respiration; 5) microbial biomass; and 6) net N mineralization and net nitrification rates. This research was designed to increase our understanding of how global warming will affect the capacity of temperate forest ecosystems to store C. The work explored how soil warming changes the interactions between the C and N cycles, and how these changes affect land-atmosphere feedbacks. This core research question framed the project – What are the effects of a sustained in situ 5oC soil temperature increase on net carbon (C) storage in a northeastern deciduous forest ecosystem? A second critical question was addressed in this research – What are the effects of a sustained in situ 5{degrees}C soil temperature increase on nitrogen (N) cycling in a northeastern deciduous forest ecosystem?

Fine roots and extramatrical mycelia regulate the composition of soil organic carbon and nitrogen in a subtropical montane forest

Context.The long-term carbonate silicate cycle plays an important role in the evolution of Earth’s climate and, therefore, may also be an important mechanism in the evolution of the climates of Earth-like exoplanets. However, given the large diversity in the possible interiors for Earth-like exoplanets, the ensuing evolution of the atmospheric CO2pressure may be widely different.Aims.We assess the role of the thermal evolution of the planetary interior on the long-term carbon cycle of Earth-like exoplanets. In particular, we investigate the effects of radiogenic mantle heating, core size, and planetary mass on the atmospheric partial CO2pressure, and the ability of a long-term carbon cycle driven by plate tectonics to control the atmospheric CO2pressure.Methods.We developed a box-model which connects carbon cycling to parametrized mantle convection. Processes considered in the carbon cycle are temperature-dependent continental weathering, seafloor weathering, subduction, and degassing through ridge and arc volcanism. The carbon cycle was coupled to the thermal evolution via the plate speed, which was parametrized in terms of the global Rayleigh number.Results.We find decreasing atmospheric CO2pressure with time, up to an order of magnitude over the entire main sequence lifetime of a solar-type star. High abundances of radioactive isotopes allow for more efficient mantle degassing, resulting in higher CO2pressures. Within the spread of abundances found in solar-type stars, atmospheric CO2pressures at 4.5 Gyr were found to vary from 14 Pa to 134 Pa. We find a decreasing Rayleigh number and plate speed toward planets with larger core mass fractionsfc, which leads to reduced degassing and lower atmospheric CO2pressure. In particular forfc≳ 0.8, a rapid decrease of these quantities is found. Variations in planet mass have more moderate effects. However, more massive planets may favor the development of more CO2rich atmospheres due to hotter interiors.Conclusions.The dependence of plate tectonics on mantle cooling has a significant effect on the long-term evolution of the atmospheric CO2pressure. Carbon cycling mediated by plate tectonics is efficient in regulating planetary climates for a wide range of mantle radioactive isotope abundances, planet masses and core sizes. More efficient carbon cycling on planets with a high mantle abundance of thorium or uranium highlights the importance of mapping the abundances of these elements in host stars of potentially habitable exoplanets. Inefficient carbon recycling on planets with a large core mass fraction (≳0.8) emphasizes the importance of precise mass-radius measurements of Earth-sized exoplanets.

The Indian Ocean, a crucial component of the global thermohaline circulation with a carbonate saturation state intermediate between the Atlantic and Pacific oceans, plays a vital role in climate variability. It serves as a major sink for atmospheric carbon dioxide (CO₂), sequestering approximately 20% of the world's anthropogenic carbon. However, a major gap exists in understanding the deep carbon cycle of the Indian Ocean because the evolution of deep-sea carbonate carbon reservoirs, as a key contributor to the long-term global carbon cycle, remains unknown across this ocean over the Cenozoic. Here, we present new regional carbonate compensation depth (CCD) reconstructions incorporating dynamic topography and eustasy impacts to quantify the storage and fluxes of carbonate carbon to the Indian seafloor since the early Cenozoic. The CCD is defined as the water depth at which carbonate supply from the surface is balanced with its dissolution, leading to the absence of carbonate components below the CCD. Due to the complexity of carbonate distribution across the Indian Ocean, we model the Cenozoic CCD across six regions: western North Indian, western and eastern equatorial Indian, western and eastern South Indian, and the Indian sector of the Southern Ocean. Utilizing updated age models and backtracking with lithology-specific decompaction from 118 deep-sea drill sites (DSDP, ODP, and IODP expeditions), we compute the CCD through a linear reduced major-axis regression of the carbonate accumulation rate (CAR) versus paleo-water depth. The regression analysis is carried out in 0.5 My time intervals. Our results illustrate distinct CCD patterns across the Indian Ocean, fluctuating regionally by ~1.5–2.5 km over the Cenozoic. The western equatorial Indian shows a long-term deepening trend from ~2.7 km at 44 Ma to ~4.9 at present, while the eastern equatorial maintains a deep CCD fluctuating between ~4.2 km and ~4.8 km since 19 Ma. The relatively shallow CCD of the Indian sector of the Southern Ocean, between ~2–4 km since 43 Ma, experiences pronounced variability across the Indian Ocean, indicating significant oceanographic changes and the complexity of diverse factors influencing the carbonate system in this high-latitude region. The highly variable CCDs across the Indian Ocean result in substantial regional heterogeneity in carbonate carbon flux corresponding to distinct oceanography characteristics such as deep-water carbonate chemistry and gradients of carbonate rain rate. The regional CCD models for the Indian Ocean are utilized to estimate the evolution of deep-sea carbonate carbon reservoir across the entire Indian during the Cenozoic in the context of the long-term global carbon cycle.

<p>Throughout the Anthropocene, the conversion of land to agriculture and atmospheric deposition of nitrogen have resulted in significant changes to biogeochemical cycling, including soil carbon stocks. Quantifying these changes is complex due to a number of influential factors (including climate, land use management, soil type) and their interactions. As the largest terrestrial store of carbon, soils are a key component in climate regulation. In addition, soil carbon storage contributes to numerous ecosystem services including food provision. It is therefore imperative that we understand changes to soil carbon stocks, and provide effective strategies for their future management.</p><p>Modelling soil systems provides a means to estimate changes to soil carbon stocks. Due to linkages between the carbon cycle and other major nutrient cycles (notably nitrogen and phosphorus which often limit the productivity of ecosystems), models of integrated nutrient cycling are required to understand the response of the carbon cycle to global pressures. Simulating the impacts of land use changes requires capacity to model both semi-natural and intensive agricultural systems.</p><p>In this study, we have developed an integrated carbon-nitrogen-phosphorus model of semi-natural systems to include representation of both arable and grassland systems, and a range of agricultural management practices. The model is applicable to large spatial scales, as it uses readily available input data and does not require site-specific calibration.  After being validated both spatially and temporally using data from long-term experimental sites across Northern-Europe, the model was applied at a national scale throughout the United Kingdom to assess the impacts of land use change and management practices during the last two centuries. Results indicate a decrease in soil carbon in areas of agricultural expansion, yet in areas of semi-natural land use, atmospheric deposition of nitrogen has resulted in increased net primary productivity and subsequently soil carbon. The results demonstrate anthropogenic impacts on long-term nutrient cycling and soil carbon storage, and the importance of integrated nutrient cycling within models.</p>

Depth-dependent response of particulate and mineral-associated organic carbon to long-term throughfall reduction in a subtropical natural forest

<strong class="journal-contentHeaderColor">Abstract.</strong> Models of the carbon cycle and climate on geologic (&gt;10⁴ year) timescales have improved tremendously in the last 50 years due to parallel advances in our understanding of the Earth system and the increase in computing power to simulate its key processes. Despite these advances, balancing the Earth System's vast complexity with a model's computational expense is a primary challenge in model development. Running longer simulations spanning hundreds of thousands of years or more generally requires reducing the complexity of the modeled climate system. However, simpler model frameworks often leave out certain features of the climate system, such as radiative feedbacks, shifts in atmospheric circulation, and the expansion and decay of ice sheets, which can have profound effects on the long-term carbon cycle. Here, we present a model for climate and the long-term carbon cycle that captures many fundamental features of global climate while retaining the computational efficiency needed to simulate millions of years of time. The Carbon-<em>H₂O</em> Coupled HydrOlOgical model with Terrestrial Runoff And INsolation, or CH2O-CHOO TRAIN, couples a one-dimensional (latitudinal) moist static energy balance model of climate with a model for rock weathering and the long-term carbon cycle. The key advantages of this framework are (1) it simulates fundamental climate forcings and feedbacks; (2) it accounts for geographic configuration; and (3) it is highly customizable, equipped to easily add features, change the strength of feedbacks, and prescribe conditions that are often hard-coded or emergent properties of more complex models, such as climate sensitivity and the strength of meridional heat transport. The CH2O-CHOO TRAIN is capable of running million-year-long simulations in about thirty minutes on a laptop PC. This paper outlines the model equations, presents a sensitivity analysis of the climate responses to varied climatic and carbon cycle perturbations, and discusses potential applications and next stops for the CH2O-CHOO TRAIN.

<strong class="journal-contentHeaderColor">Abstract.</strong> Models of the carbon cycle and climate on geologic (&gt;10⁴ year) timescales have improved tremendously in the last 50 years due to parallel advances in our understanding of the Earth system and the increase in computing power to simulate its key processes. Despite these advances, balancing the Earth System's vast complexity with a model's computational expense is a primary challenge in model development. Running longer simulations spanning hundreds of thousands of years or more generally requires reducing the complexity of the modeled climate system. However, simpler model frameworks often leave out certain features of the climate system, such as radiative feedbacks, shifts in atmospheric circulation, and the expansion and decay of ice sheets, which can have profound effects on the long-term carbon cycle. Here, we present a model for climate and the long-term carbon cycle that captures many fundamental features of global climate while retaining the computational efficiency needed to simulate millions of years of time. The Carbon-<em>H₂O</em> Coupled HydrOlOgical model with Terrestrial Runoff And INsolation, or CH2O-CHOO TRAIN, couples a one-dimensional (latitudinal) moist static energy balance model of climate with a model for rock weathering and the long-term carbon cycle. The key advantages of this framework are (1) it simulates fundamental climate forcings and feedbacks; (2) it accounts for geographic configuration; and (3) it is highly customizable, equipped to easily add features, change the strength of feedbacks, and prescribe conditions that are often hard-coded or emergent properties of more complex models, such as climate sensitivity and the strength of meridional heat transport. The CH2O-CHOO TRAIN is capable of running million-year-long simulations in about thirty minutes on a laptop PC. This paper outlines the model equations, presents a sensitivity analysis of the climate responses to varied climatic and carbon cycle perturbations, and discusses potential applications and next stops for the CH2O-CHOO TRAIN.

Abstract. Models of the carbon cycle and climate on geologic (&gt;104-year) timescales have improved tremendously in the last 50 years due to parallel advances in our understanding of the Earth system and the increase in computing power to simulate its key processes. Still, balancing the Earth system's complexity with a model's computational expense is a primary challenge in model development. Simulations spanning hundreds of thousands of years or more generally require a reduction in the complexity of the climate system, omitting features such as radiative feedbacks, shifts in atmospheric circulation, and the expansion and decay of ice sheets, which can have profound effects on the long-term carbon cycle. Here, we present a model for climate and the long-term carbon cycle that captures many fundamental features of global climate while retaining the computational efficiency needed to simulate millions of years of time. The Carbon–H2O Coupled HydrOlOgical model with Terrestrial Runoff And INsolation, or CH2O-CHOO TRAIN, couples a one-dimensional (latitudinal) moist static energy balance model of climate with a model for rock weathering and the long-term carbon cycle. The CH2O-CHOO TRAIN is capable of running million-year-long simulations in about 30 min on a laptop PC. The key advantages of this framework are (1) it simulates fundamental climate forcings and feedbacks; (2) it accounts for geographic configuration; and (3) it is flexible, equipped to easily add features, change the strength of feedbacks, and prescribe conditions that are often hard-coded or emergent properties of more complex models, such as climate sensitivity and the strength of meridional heat transport. We show how climate variables governing temperature and the water cycle can impact long-term carbon cycling and climate, and we discuss how the magnitude and direction of this impact can depend on boundary conditions like continental geography. This paper outlines the model equations, presents a sensitivity analysis of the climate responses to varied climatic and carbon cycle perturbations, and discusses potential applications and next stops for the CH2O-CHOO TRAIN.

<strong class="journal-contentHeaderColor">Abstract.</strong> Models of the carbon cycle and climate on geologic (&gt;10⁴ year) timescales have improved tremendously in the last 50 years due to parallel advances in our understanding of the Earth system and the increase in computing power to simulate its key processes. Despite these advances, balancing the Earth System's vast complexity with a model's computational expense is a primary challenge in model development. Running longer simulations spanning hundreds of thousands of years or more generally requires reducing the complexity of the modeled climate system. However, simpler model frameworks often leave out certain features of the climate system, such as radiative feedbacks, shifts in atmospheric circulation, and the expansion and decay of ice sheets, which can have profound effects on the long-term carbon cycle. Here, we present a model for climate and the long-term carbon cycle that captures many fundamental features of global climate while retaining the computational efficiency needed to simulate millions of years of time. The Carbon-<em>H₂O</em> Coupled HydrOlOgical model with Terrestrial Runoff And INsolation, or CH2O-CHOO TRAIN, couples a one-dimensional (latitudinal) moist static energy balance model of climate with a model for rock weathering and the long-term carbon cycle. The key advantages of this framework are (1) it simulates fundamental climate forcings and feedbacks; (2) it accounts for geographic configuration; and (3) it is highly customizable, equipped to easily add features, change the strength of feedbacks, and prescribe conditions that are often hard-coded or emergent properties of more complex models, such as climate sensitivity and the strength of meridional heat transport. The CH2O-CHOO TRAIN is capable of running million-year-long simulations in about thirty minutes on a laptop PC. This paper outlines the model equations, presents a sensitivity analysis of the climate responses to varied climatic and carbon cycle perturbations, and discusses potential applications and next stops for the CH2O-CHOO TRAIN.

<strong class="journal-contentHeaderColor">Abstract.</strong> Models of the carbon cycle and climate on geologic (&gt;10⁴ year) timescales have improved tremendously in the last 50 years due to parallel advances in our understanding of the Earth system and the increase in computing power to simulate its key processes. Despite these advances, balancing the Earth System's vast complexity with a model's computational expense is a primary challenge in model development. Running longer simulations spanning hundreds of thousands of years or more generally requires reducing the complexity of the modeled climate system. However, simpler model frameworks often leave out certain features of the climate system, such as radiative feedbacks, shifts in atmospheric circulation, and the expansion and decay of ice sheets, which can have profound effects on the long-term carbon cycle. Here, we present a model for climate and the long-term carbon cycle that captures many fundamental features of global climate while retaining the computational efficiency needed to simulate millions of years of time. The Carbon-<em>H₂O</em> Coupled HydrOlOgical model with Terrestrial Runoff And INsolation, or CH2O-CHOO TRAIN, couples a one-dimensional (latitudinal) moist static energy balance model of climate with a model for rock weathering and the long-term carbon cycle. The key advantages of this framework are (1) it simulates fundamental climate forcings and feedbacks; (2) it accounts for geographic configuration; and (3) it is highly customizable, equipped to easily add features, change the strength of feedbacks, and prescribe conditions that are often hard-coded or emergent properties of more complex models, such as climate sensitivity and the strength of meridional heat transport. The CH2O-CHOO TRAIN is capable of running million-year-long simulations in about thirty minutes on a laptop PC. This paper outlines the model equations, presents a sensitivity analysis of the climate responses to varied climatic and carbon cycle perturbations, and discusses potential applications and next stops for the CH2O-CHOO TRAIN.

<strong class="journal-contentHeaderColor">Abstract.</strong> Models of the carbon cycle and climate on geologic (&gt;10⁴ year) timescales have improved tremendously in the last 50 years due to parallel advances in our understanding of the Earth system and the increase in computing power to simulate its key processes. Despite these advances, balancing the Earth System's vast complexity with a model's computational expense is a primary challenge in model development. Running longer simulations spanning hundreds of thousands of years or more generally requires reducing the complexity of the modeled climate system. However, simpler model frameworks often leave out certain features of the climate system, such as radiative feedbacks, shifts in atmospheric circulation, and the expansion and decay of ice sheets, which can have profound effects on the long-term carbon cycle. Here, we present a model for climate and the long-term carbon cycle that captures many fundamental features of global climate while retaining the computational efficiency needed to simulate millions of years of time. The Carbon-<em>H₂O</em> Coupled HydrOlOgical model with Terrestrial Runoff And INsolation, or CH2O-CHOO TRAIN, couples a one-dimensional (latitudinal) moist static energy balance model of climate with a model for rock weathering and the long-term carbon cycle. The key advantages of this framework are (1) it simulates fundamental climate forcings and feedbacks; (2) it accounts for geographic configuration; and (3) it is highly customizable, equipped to easily add features, change the strength of feedbacks, and prescribe conditions that are often hard-coded or emergent properties of more complex models, such as climate sensitivity and the strength of meridional heat transport. The CH2O-CHOO TRAIN is capable of running million-year-long simulations in about thirty minutes on a laptop PC. This paper outlines the model equations, presents a sensitivity analysis of the climate responses to varied climatic and carbon cycle perturbations, and discusses potential applications and next stops for the CH2O-CHOO TRAIN.

(1) The late Paleocene to the early Eocene (� 58-52 Ma) was marked by significant changes in global climate and carbon cycling. The evidence for these changes includes stable isotope records that reveal prominent decreases in i 18 Oa ndi 13 C, suggesting a rise in Earth's surface temperature (� 4 i C) and a drop in net carbon output from the ocean and atmosphere. Concurrently, deep-sea carbonate records at several sites indicate a deepening of the calcite compensation depth (CCD). Here we investigate possible causes (e.g., increased volcanic degassing or decreased net organic burial) for these observations, but from a new perspective. The basic model employed is a modified version of GEOCARB III. However, we have coupled this well-known geochemical model to LOSCAR (Long-term Ocean-atmosphere Sediment CArbon cycle Reservoir model), which enables simulation of seawater carbonate chemistry, the CCD, and ocean i 13 C. We have also added a capacitor, in this case represented by gas hydrates, that can store and release 13 C-depleted carbon to and from the shallow geosphere over millions of years. We further consider accurate input data (e.g., i 13 C of carbonate) on a currently accepted timescale that spans an interval much longer than the perturbation. Several different scenarios are investigated with the goal of consistency amongst inferred changes in temperature, the CCD, and surface ocean and deep ocean i 13 C. The results strongly suggest that a decrease in net organic carbon burial drove carbon cycle changes during the late Paleocene and early Eocene, although an increase in volcanic activity might have contributed. Importantly, a drop in net organic carbon burial may represent increased oxidation of previously deposited organic carbon, such as stored in peat or gas hydrates. The model successfully recreates trends in Earth surface warming, as inferred from i 18 O records, the CCD, and i 13 C. At the moment, however, our coupled modeling effort cannot reproduce the magnitude of change in all these records collectively. Similar problems have arisen in simulations of short-term hyperthermal events during the early Paleogene (Paleocene-Eocene Thermal Maximum), suggesting one or more basic issues with data interpretation or geochemical modeling remain.

Seasonal and inter-annual variations in net ecosystem exchange of two old-growth forests in southern China

Deep-sea carbonates constitute the primary deep carbon reservoir, playing a critical role in regulating the long-term global carbon cycle. Reconstructing the temporal evolution of carbonate flux to the seafloor requires estimating the changes in carbonate compensation depth (CCD), a key proxy, revealing the depth where the rate of calcium carbonate supply from biogenic ooze equals the rate of dissolution. However, regional CCD estimates across the Pacific, the deepest and largest ocean basin, remain poorly constrained, except for the eastern equatorial region. Here, we present six new regional reconstructions of the CCD across the Pacific Ocean, using a linear reduced major-axis regression of the carbonate accumulation rate (CAR) versus paleo-water depth, that include the effects of dynamic topography and eustasy. The CCDs show significant fluctuations of ∼1–1.2 km across the Pacific over the Neogene. Regional CCD models since the early Miocene suggest the influence of climate perturbations, Antarctic ice-sheet growth, and Pacific gateway reorganization on Pacific deep-water circulation and carbonate production. The western Pacific CCD shows a distinct deepening after ∼24 Ma, not seen in the eastern tropical Pacific, which we interpret as a delayed consequence of changes in deep water circulation in response to the expansion of the West Antarctic ice sheet into the marine realm at ∼26 Ma. Our models also reveal two significant late Miocene events, the carbonate crash and biogenic bloom, across both the western and eastern equatorial Pacific. However, a ∼1 Ma lag is noted for both events in the western tropical CCD, likely attributed to the successive effects of Panama Gateway constriction and shifts in the Western Pacific Warm Pool, respectively. The absence of the carbonate crash event from the western North Pacific reflects the regional nature of this event, predominantly influencing the Pacific equatorial region. Our analysis offers new insights into regional CCD variability across the Pacific Ocean and can be used to evaluate the evolution of deep-sea carbonate carbon reservoirs in the context of the long-term carbon cycle.