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Carbon dioxide removal technologies such as bioenergy with carbon capture and storage (BECCS) are required if the effects of climate change are to be reversed over the next century. However, BECCS demands extensive land use change that may create positive or negative radiative forcing impacts upstream of the BECCS facility through changes to in situ greenhouse gas fluxes and land surface albedo. When quantifying these upstream climate impacts, even at a single site, different methods can give different estimates. Here we show how three common methods for estimating the net ecosystem carbon balance of bioenergy crops established on former grassland or former cropland can differ in their central estimates and uncertainty. We place these net ecosystem carbon balance forcings in the context of associated radiative forcings from changes to soil N2O and CH4 fluxes, land surface albedo, embedded fossil fuel use, and geologically stored carbon. Results from long term eddy covariance measurements, a soil and plant carbon inventory, and the MEMS 2 process-based ecosystem model all agree that establishing perennials such as switchgrass or mixed prairie on former cropland resulted in net negative radiative forcing (i.e., global cooling) of -26.5 to -39.6 fW m-2 over 100 years. Establishing these perennials on former grassland sites had similar climate mitigation impacts of -19.3 to -42.5 fW m-2. However, the largest climate mitigation came from establishing corn for BECCS on former cropland or grassland, with radiative forcings from -38.4 to -50.5 fW m-2, due to its higher plant productivity and therefore more geologically stored carbon. Our results highlight the strengths and limitations of each method for quantifying the field scale climate impacts of BECCS and show that utilizing multiple methods can increase confidence in the final radiative forcing estimates. 

The relationship between precipitation and evapotranspiration (ET) is critical to understanding water cycle related dynamics in ecosystems, including crops. Existing studies of bioenergy crops have primarily focused on annual or seasonal ET rates, with less attention given to the immediate ET response following precipitation events. This study examines the variation in ET rates in the days subsequent to precipitation events across various bioenergy crops—corn, switchgrass, and prairies—utilizing 13 years (2010–2022) of growing season data. Meteorological and eddy covariance flux data were collected from seven eddy covariance flux towers as part of the GLBRC scale-up experiment at the Kellogg Biological Station Long Term Ecological Research sites. The analysis revealed that average ET peaked the day after precipitation and declined linearly over the following days, with a statistically significant relationship (p-value = 0.00027, R²= 0.96). Neither the type of biofuel vegetation nor the historical land use significantly influenced ET post-precipitation events (p-values = 0.53 and 0.153, respectively). Key predictors of ET following precipitation events include shortwave radiation, season, day of the year, ambient temperature, vapor pressure deficit (VPD), long-wave radiation, precipitation amount, soil moisture, and annual variability. These findings enhance our comprehension of ET responses in bioenergy crop systems, with implications for water management in sustainable agriculture. 

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. 

Abstract Radiative forcing (RF) resulting from changes in surface albedo is increasingly recognized as a significant driver of global climate change but has not been adequately estimated, including by Intergovernmental Panel on Climate Change (IPCC) assessment reports, compared with other warming agents. Here, we first present the physical foundation for modeling albedo-induced RF and the consequent global warming impact (GWI_Δα). We then highlight the shortcomings of available current databases and methodologies for calculating GWI_Δαat multiple temporal scales. There is a clear lack of comprehensivein situmeasurements of albedo due to sparse geographic coverage of ground-based stations, whereas estimates from satellites suffer from biases due to the limited frequency of image collection, and estimates from earth system models (ESMs) suffer from very coarse spatial resolution land cover maps and associated albedo values in pre-determined lookup tables. Field measurements of albedo show large differences by ecosystem type and large diurnal and seasonal changes. As indicated from our findings in southwest Michigan, GWI_Δαis substantial, exceeding the RF_Δαvalues of IPCC reports. Inclusion of GWI_Δαto landowners and carbon credit markets for specific management practices are needed in future policies. We further identify four pressing research priorities: developing a comprehensive albedo database, pinpointing accurate reference sites within managed landscapes, refining algorithms for remote sensing of albedo by integrating geostationary and other orbital satellites, and integrating the GWI_Δαcomponent into future ESMs. 

Abstract Changes in land surface albedo can alter ecosystem energy balance and potentially influence climate. We examined the albedo of six bioenergy cropping systems in southwest Michigan USA: monocultures of energy sorghum (Sorghum bicolor), switchgrass (Panicum virgatumL.), and giant miscanthus (Miscanthus×giganteus), and polycultures of native grasses, early successional vegetation, and restored prairie. Direct field measurements of surface albedo (α_s) from May 2018 through December 2020 at half‐hourly intervals in each system quantified the magnitudes and seasonal differences in albedo (∆_α) and albedo‐induced radiative forcing (RF_∆α). We used a nearby forest as a historical native cover type to estimate reference albedo and RF_∆αchange upon original land use conversion, and a continuous no‐till maize (Zea mays L.) system as a contemporary reference to estimate change upon conversion from annual row crops. Annually,α_sdiffered significantly (p < 0.05) among crops in the order: early successional (0.288 ± 0.012SE) >> miscanthus (0.271 ± 0.009) ≈ energy sorghum (0.270 ± 0.010) ≥ switchgrass (0.265 ± 0.009) ≈ restored prairie (0.264 ± 0.012) > native grasses (0.259 ± 0.010) > maize (0.247 ± 0.010). Reference forest had the lowest annualα_s(0.134 ± 0.003). Albedo differences among crops during the growing season were also statistically significant, with growing seasonα_sin perennial crops and energy sorghum on average ~20% higher (0.206 ± 0.003) than in no‐till maize (0.184 ± 0.002). Average non‐growing season (NGS)α_s(0.370 ± 0.020) was much higher than growing seasonα_s(0.203 ± 0.003) but these NGS differences were not significant. Overall, the original conversion of reference forest and maize landscapes to perennials provided a cooling effect on the local climate (RF_αMAIZE: −3.83 ± 1.00 W m⁻²; RF_αFOREST: −16.75 ± 3.01 W m⁻²). Significant differences among cropping systems suggest an additional management intervention for maximizing the positive climate benefit of bioenergy crops, with cellulosic crops on average ~9.1% more reflective than no‐till maize, which itself was about twice as reflective as the reference forest. 

Abstract Surface albedo can affect the energy budget and subsequently cause localized warming or cooling of the climate. When we convert a substantial portion of lands to agriculture, land surface properties are consequently altered, including albedo. Through crop selection and management, one can increase crop albedo to obtain higher levels of localized cooling effects to mitigate global warming. Still, there is little understanding about how distinctive features of a cropping system may be responsible for elevated albedo and consequently for the cooling potential of cultivated lands. To address this pressing issue, we conducted seasonal measurements of surface reflectivity during five growing seasons on annual crops of corn-soybean–winter wheat (Zea mays L.- Glycine max L.Merrill—Triticum aestivum L.; CSW) rotations at three agronomic intensities, a monoculture of perennial switchgrass, and perennial polycultures of early successional and restored prairie grasslands. We found that crop-species, agronomic intensity, seasonality, and plant phenology had significant effects on albedo. The mean ± SD of albedo was highest in perennial crops of switchgrass (Panicum virgatum; 0.179 ± 0.04), intermediate in early successional crops (0.170 ± 0.04), and lowest in a reduced input corn systems with cover crops (0.154 ± 0.02). Thestrongest cooling potentials were found in soybean (−0.450 kg CO₂e m⁻²yr⁻¹) and switchgrass (−0.367 kg CO₂e m⁻²yr⁻¹), with up to −0.265 kg CO₂e m⁻²yr⁻¹of localized climate cooling annually provided by different agroecosystems. We also demonstrated how diverse ecosystems, leaf canopy, and agronomic practices can affect surface reflectivity and provide another potential nature-based solution for reducing global warming at localized scales. 

The stable isotopic composition of soil-formed carbonate, and bulk geochemistry of preserved soil matrix, can provide regionally constrained records of hydroclimatic change throughout deep-time. The SK cores, spanning over 10 km of sediment drilled from the Songliao Basin in Northeast China, represent near continuous terrestrial deposition across the late Jurassic to early Paleogene. In this study we analyze SK-1n paleosol core samples spanning late Maastrichtian to early Danian to interpret the regional hydroclimate response to global climate change, concurrent with Deccan Traps volcanism and the Chicxulub impact. Building on numerous paleosol carbonate datasets from the Sifangtai and Mingshui formations, we present ~40 new carbonate clumped isotope measurements at ca. 10 – 20 kyr resolution between 66.3 to 65.5 Ma. We produce a new kernel-smoothed temperature record and estimate the δ18O of soil porewater (δ18Opw), and δ13C of soil CO2 (δ13Cs) from new and previously published datasets. Molecular weathering ratios, derived from bulk geochemistry, are used to reconstruct weathering (CIA-K), clay formation (Al/Si), soil drainage (Ba/Sr), and calculate mean annual precipitation (MAP) via established transfer functions. Preliminary results suggest elevated K-Pg boundary temperatures, averaging ~30 °C, that decline by ~10 °C over the following 500 kyr. Post-impact cooling may contribute to a negative δ18Ocarb excursion (-2.5‰) at ~65.8 Ma. Further, stable subhumid MAP (~1100 mm/yr) across the dataset suggests negligible amount effect influence. Mean δ18Opw (-6.9‰) is largely stable, and does not reflect regional monsoon seasonality. Instead, stable δ18Opw indicates a consistent moisture source, a potential persistent seasonal bias in carbonate formation. Binning all compiled δ18Opw by soil profile depth reveals statistically significant enrichment in the upper 60 cm of soil profiles, and accounts for variability in the δ18Opw (σ = 1.16‰). Soil respiration, modeled from δ13Cs, increases from ca. 700 to 2000 gC/m2/year across the K-Pg boundary, indicating increased productivity despite declining pCO2 and available phosphorus. Future work will expand the temporal range of isotopic measurements (~72 to 65 Ma) and contextualize our latest Cretaceous results within a spatial framework across Asia. 

Abstract Global warming increases ecosystem respiration (ER), creating a positive carbon-climate feedback. Thermal acclimation, the direct responses of biological communities to reduce the effects of temperature changes on respiration rates, is a critical mechanism that compensates for warming-induced ER increases and dampens this positive feedback. However, the extent and effects of this mechanism across diverse ecosystems remain unclear. By analyzing CO2 flux data from 93 eddy covariance sites worldwide, we observed thermal acclimation at 84 % of the sites. If sustained, thermal acclimation could reduce projected warming-induced nighttime ER increases by at least 25 % across most climate zones by 2041-2060. Strong thermal acclimation is particularly evident in ecosystems at high elevation, with low-carbon-content soils, and within tundra, semi-arid, and warm-summer Mediterranean climates, supporting the hypothesis that extreme environments favor the evolution of greater acclimation potential. Moreover, ecosystems with dense vegetation and high productivity such as humid tropical and subtropical forests generally exhibit strong thermal acclimation, suggesting that regions with substantial CO2 uptake may continue to serve as strong carbon sinks. Conversely, some ecosystems in cold continental climates show signs of enhancing thermal responses, the opposite of thermal acclimation, which could exacerbate carbon losses as climate warms. Our study underscores the widespread yet climate-specific patterns of thermal acclimation in global terrestrial ER, emphasizing the need to incorporate these patterns into Earth System Models for more accurate carbon-climate feedback projections.