Crop-climate feedbacks boost U.S. maize and soy yields

U.S. maize and soy production have increased rapidly since the mid-20th century. While global warming has raised temperatures in most regions over this time period, trends in extreme heat have been smaller over U.S. croplands, reducing crop-damaging high temperatures and benefiting maize and soy yields. Here we show that agricultural intensification has created a crop-climate feedback in which increased crop production cools local climate, further raising crop yields. We find that maize and soy production trends have driven cooling effects approximately as large as greenhouse gas induced warming trends in extreme heat over the central U.S. and substantially reduce them over the southern U.S., benefiting crops in all regions. This reduced warming has boosted maize and soy yields by 3.3 (2.7 – 3.9; 13.7 – 20.0%) and 0.6 (0.4 – 0.7; 7.5 – 13.7%) bu/ac/decade, respectively, between 1981 and 2019. Our results suggest that if maize and soy production growth were to stagnate, the ability of the crop-climate feedback to mask warming would fade, exposing U.S. crops to more harmful heat extremes.

Soil carbon loss in warmed subarctic grasslands is rapid and restricted to topsoil

Global warming may lead to carbon transfers from soils to the atmosphere, yet this positive feedback to the cli- mate system remains highly uncertain, especially in subsoils (Ilyina and Friedlingstein, 2016; Shi et al., 2018). Using natural geothermal soil warming gradients of up to +6.4 °C in subarctic grasslands (Sigurdsson et al., 2016), we show that soil organic carbon (SOC) stocks decline strongly and linearly with warming (−2.8 ton ha−1 °C−1). Comparison of SOC stock changes following medium-term (5 and 10 years) and long-term (> 50 years) warming revealed that all SOC loss occurred within the first five years of warming, after which continued warming no longer reduced SOC stocks. This rapid equilibration of SOC observed in Andosol suggests a critical role for ecosystem adaptations to warming and could imply short-lived soil carbon-climate feedbacks. Our data further revealed that the soil C loss occurred in all aggregate size fractions, and that SOC losses only occurred in topsoil (0–10 cm). SOC stocks in subsoil (10–30 cm), where plant roots were absent, remained unaltered, even after > 50 years of warming. The observed depth-dependent warming responses indicate that explicit vertical resolution is a prerequisite for global models to accurately project future SOC stocks for this soil type and should be investigated for soils with other mineralogies.

Utilization of Hyperspectral Remote Sensing Imagery for Improving Burnt Area Mapping Accuracy

Wildfires pose a direct threat when occurring close to populated areas. Additionally, their significant carbon and climate feedbacks represent an indirect threat on a global, long-term scale. Monitoring and analyzing wildfires is therefore a crucial task to increase the understanding of interconnections between fire and ecosystems, in order to improve wildfire management activities. This study investigates the suitability of 232 different red/near-infrared band combinations based on hyperspectral imagery of the DESIS sensor with regard to burnt area detection accuracy. It is shown that the selection of wavelengths greatly influences the detection quality, and that especially the utilization of lower near-infrared wavelengths increases the yielded accuracy. For burnt area analysis based on the Normalized Difference Vegetation Index (NDVI), the optimal wavelength range has been found to be 660–670 nm and 810–835 nm for the red band and near-infrared band, respectively.

Soluble Iodine Speciation in Marine Aerosols Across the Indian and Pacific Ocean Basins

Iodine affects the radiative budget and the oxidative capacity of the atmosphere and is consequently involved in important climate feedbacks. A fraction of the iodine emitted by oceans ends up in aerosols, where complex halogen chemistry regulates the recycling of iodine to the gas-phase where it effectively destroys ozone. The iodine speciation and major ion composition of aerosol samples collected during four cruises in the East and West Pacific and Indian Oceans was studied to understand the influences on iodine’s gas-aerosol phase recycling. A significant inverse relationship exists between iodide (I–) and iodate (IO3–) proportions in both fine and coarse mode aerosols, with a relatively constant soluble organic iodine (SOI) fraction of 19.8% (median) for fine and coarse mode samples of all cruises combined. Consistent with previous work on the Atlantic Ocean, this work further provides observational support that IO3– reduction is attributed to aerosol acidity, which is associated to smaller aerosol particles and air masses that have been influenced by anthropogenic emissions. Significant correlations are found between SOI and I–, which supports hypotheses that SOI may be a source for I–. This data contributes to a growing observational dataset on aerosol iodine speciation and provides evidence for relatively constant proportions of iodine species in unpolluted marine aerosols. Future development in our understanding of iodine speciation depends on aerosol pH measurements and unravelling the complex composition of SOI in aerosols.

Dispersal and fire limit Arctic shrub expansion

Arctic shrub expansion has been widely reported in recent decades, with large impacts on carbon budgets, albedo, and warming rates in high latitudes. However, predicting shrub expansion across regions remains challenging because the underlying controls remain unclear. Observational studies and models typically use relationships between observed shrub presence and current environmental suitability (climate and topography) to predict shrub expansion, but such approaches omit potentially important biotic-abiotic interactions and non-stationary relationships. Here, we use long-term high-resolution satellite imagery across Alaska and western Canada to show that observed shrub expansion has not been controlled by environmental suitability during 1984-2014, but rather can only be explained by accounting for seed dispersal and fire. These findings provide the impetus for better observations of recruitment and for incorporating currently underrepresented processes of seed dispersal and fire in land models to project shrub expansion and future climate feedbacks. Integrating these dynamic processes with projected fire extent and climate, we estimate that shrubs will expand into 25% of the non-shrub tundra by 2100, in contrast to 39% predicted using a relationship with increasing suitability alone. Thus, using environmental suitability alone likely overestimates and misrepresents the spatial pattern of shrub expansion and its associated carbon sink.

Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NOx emissions. Second, the response of O3 to decreased NOx emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

Key predictors of soil organic matter vulnerability to mineralization differ with depth at a continental scale

Soil organic matter (SOM) is the largest terrestrial pool of organic carbon, and potential carbon-climate feedbacks involving SOM decomposition could exacerbate anthropogenic climate change. However, our understanding of the controls on SOM mineralization is still incomplete, and as such, our ability to predict carbon-climate feedbacks is limited. To improve our understanding of controls on SOM decomposition, A and upper B horizon soil samples from 26 National Ecological Observatory Network (NEON) sites spanning the conterminous U.S. were incubated for 52 weeks under conditions representing site-specific mean summer temperature and sample-specific field capacity (−33 kPa) water potential. Cumulative carbon dioxide respired was periodically measured and normalized by soil organic C content to calculate cumulative specific respiration (CSR), a metric of SOM vulnerability to mineralization. The Boruta algorithm, a feature selection algorithm, was used to select important predictors of CSR from 159 variables. A diverse suite of predictors was selected (12 for A horizons, 7 for B horizons) with predictors falling into three categories corresponding to SOM chemistry, reactive Fe and Al phases, and site moisture availability. The relationship between SOM chemistry predictors and CSR was complex, while sites that had greater concentrations of reactive Fe and Al phases or were wetter had lower CSR. Only three predictors were selected for both horizon types, suggesting dominant controls on SOM decomposition differ by horizon. Our findings contribute to the emerging consensus that a broad array of controls regulates SOM decomposition at large scales and highlight the need to consider changing controls with depth.

ESD Ideas: A Global Warming Scaling Law

In this study, we highlight a component of global warming variability, a scaling law that is based purely on fundamental physical properties of the climate system. We suggest that three similarity parameters define the system response to external forcing, and an argument of physical similarity with observed climate responses in the past can be made when all three parameters are identical for the current and historical climates. We determined that the scaling law of global warming is the (𝜆 + 1 + m) – power of time, where 𝜆 is prescribed by external forcing and m is defined by climate system internal dynamics. When the climate system develops in the direction of intensified positive feedbacks, the power m changes from m = −1 (negative feedbacks dominate) to m ≥ 1 (positive feedbacks dominate). We also establish that a “hothouse” climate with dominant positive feedbacks will be preceded by a climate having a property of incomplete similarity in feedbacks similarity parameters. It implies that the same future scenario may be produced by climate feedbacks of different magnitudes as long as their positive-to-negative ratio is the same.

Circum-Arctic Map of the Yedoma Permafrost Domain

Ice-rich permafrost in the circum-Arctic and sub-Arctic (hereafter pan-Arctic), such as late Pleistocene Yedoma, are especially prone to degradation due to climate change or human activity. When Yedoma deposits thaw, large amounts of frozen organic matter and biogeochemically relevant elements return into current biogeochemical cycles. This mobilization of elements has local and global implications: increased thaw in thermokarst or thermal erosion settings enhances greenhouse gas fluxes from permafrost regions. In addition, this ice-rich ground is of special concern for infrastructure stability as the terrain surface settles along with thawing. Finally, understanding the distribution of the Yedoma domain area provides a window into the Pleistocene past and allows reconstruction of Ice Age environmental conditions and past mammoth-steppe landscapes. Therefore, a detailed assessment of the current pan-Arctic Yedoma coverage is of importance to estimate its potential contribution to permafrost-climate feedbacks, assess infrastructure vulnerabilities, and understand past environmental and permafrost dynamics. Building on previous mapping efforts, the objective of this paper is to compile the first digital pan-Arctic Yedoma map and spatial database of Yedoma coverage. Therefore, we 1) synthesized, analyzed, and digitized geological and stratigraphical maps allowing identification of Yedoma occurrence at all available scales, and 2) compiled field data and expert knowledge for creating Yedoma map confidence classes. We used GIS-techniques to vectorize maps and harmonize site information based on expert knowledge. We included a range of attributes for Yedoma areas based on lithological and stratigraphic information from the source maps and assigned three different confidence levels of the presence of Yedoma (confirmed, likely, or uncertain). Using a spatial buffer of 20 km around mapped Yedoma occurrences, we derived an extent of the Yedoma domain. Our result is a vector-based map of the current pan-Arctic Yedoma domain that covers approximately 2,587,000 km2, whereas Yedoma deposits are found within 480,000 km2 of this region. We estimate that 35% of the total Yedoma area today is located in the tundra zone, and 65% in the taiga zone. With this Yedoma mapping, we outlined the substantial spatial extent of late Pleistocene Yedoma deposits and created a unique pan-Arctic dataset including confidence estimates.

Model simulations of arctic biogeochemistry and permafrost extent are highly sensitive to the implemented snow scheme in LPJ-GUESS

The Arctic is warming rapidly, especially in winter, which is causing large-scale reductions in snow cover. Snow is one of the main controls on soil thermodynamics, and changes in its thickness and extent affect both permafrost thaw and soil biogeochemistry. Since soil respiration during the cold season potentially offsets carbon uptake during the growing season, it is essential to achieve a realistic simulation of the effect of snow cover on soil conditions to more accurately project the direction of arctic carbon–climate feedbacks under continued winter warming. The Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model has used – up until now – a single layer snow scheme, which underestimated the insulation effect of snow, leading to a cold bias in soil temperature. To address this shortcoming, we developed and integrated a dynamic, multi-layer snow scheme in LPJ-GUESS. The new snow scheme performs well in simulating the insulation of snow at hundreds of locations across Russia compared to observations. We show that improving this single physical factor enhanced simulations of permafrost extent compared to an advanced permafrost product, where the overestimation of permafrost cover decreased from 10 % to 5 % using the new snow scheme. Besides soil thermodynamics, the new snow scheme resulted in a doubled winter respiration and an overall higher vegetation carbon content. This study highlights the importance of a correct representation of snow in ecosystem models to project biogeochemical processes that govern climate feedbacks. The new dynamic snow scheme is an essential improvement in the simulation of cold season processes, which reduces the uncertainty of model projections. These developments contribute to a more realistic simulation of arctic carbon–climate feedbacks.