Although substantial advances in predicting the ecological impacts of global change have been made, predictions of the evolutionary impacts have lagged behind. In soil ecosystems, microbes act as the primary energetic drivers of carbon cycling; however, microbes are also capable of evolving on timescales comparable to rates of global change. Given the importance of soil ecosystems in global carbon cycling, we assess the potential impact of microbial evolution on carbon-climate feedbacks in this system. We begin by reviewing the current state of knowledge concerning microbial evolution in response to global change and its specific effect on soil carbon dynamics. Through this integration, we synthesize a roadmap detailing how to integrate microbial evolution into ecosystem biogeochemical models. Specifically, we highlight the importance of microscale mechanistic soil carbon models, including choosing an appropriate evolutionary model (e.g., adaptive dynamics, quantitative genetics), validating model predictions with ‘omics’ and experimental data, scaling microbial adaptations to ecosystem level processes, and validating with ecosystem-scale measurements. The proposed steps will require significant investment of scientific resources and might require 10–20 years to be fully implemented. However, through the application of multi-scale integrated approaches, we will advance the integration of microbial evolution into predictive understanding of ecosystems, providing clarity on its role and impact within the broader context of environmental change.

The Miocene (23.03-5.33 Ma) is recognized as a period with close to modern-day paleogeography, yet a much warmer climate. With large uncertainties in future hydroclimate projections, Miocene conditions illustrate a potential future analog for the Earth system. A recent opportunistic Miocene Model Intercomparison Project 1 (MioMIP1) focused on synthesizing published Miocene climate simulations and comparing them with available temperature reconstructions. Here, we build on this effort by analyzing the hydrological cycle response to Miocene forcings across early-to-middle (E2MMIO; 20.03-11.6 Ma) and middle-to-late Miocene (M2LMIO; 11.5-5.33 Ma) simulations with CO2 concentrations ranging from 200 to 850 ppm and providing a model-data comparison against available precipitation reconstructions. We find global precipitation increases by similar to 2.1 and 2.3% per degree of warming for E2MMIO and M2LMIO simulations, respectively. Models generally agree on a wetter than modern-day tropics; mid and high-latitude, however, do not agree on the sign of subtropical precipitation changes with warming. Global monsoon analysis suggests most monsoon regions, except the North American Monsoon, experience higher precipitation rates under warmer conditions. Model-data comparison shows that mean annual precipitation is underestimated by the models regardless of CO2 concentration, particularly in the mid- to high-latitudes. This suggests that the models may not be (a) resolving key processes driving the hydrological cycle response to Miocene boundary conditions and/or (b) other boundary conditions or processes not considered here are critical to reproducing Miocene hydroclimate. This study highlights the challenges in modeling and reconstructing the Miocene hydrological cycle and serves as a baseline for future coordinated MioMIP efforts. This study looks at Earth's hydrological cycle during the Miocene (23-5 million years ago). During this period, the Earth's climate was 3-7 degrees C warmer than today, with carbon dioxide (CO2) estimates ranging between 400 and 850 ppm. Understanding how the hydrological cycle responded during warmer climate conditions can give us insight into what might happen as the Earth gets warmer. We analyzed a suite of Miocene paleoclimate simulations with different CO2 concentrations in the atmosphere and compared them against fossil plant data, which gives an estimate of the average annual rainfall during the period. We found that during the Miocene global rainfall increased by about 2.1%-2.3% for each degree of warming. The models agree that the tropics, mid- and high-latitude, became wetter than they are today but have lower agreement on whether subtropical areas got wetter or drier as they warmed. Compared to proxies, models consistently underestimated how much rain fell in a year, especially in the mid- to high-latitude. This illustrates the challenges in reconstructing the Miocene's hydrological cycle and suggests that the models might not fully capture the range of uncertainties associated with changes in the hydrological cycle due to warming or other factors that differentiated the Miocene. A multi-model comparison of the hydrological cycle in early-to-middle and middle-to-late Miocene simulations is conductedModels generally agree on wetter than modern tropics, middle and high latitudes, but not on the sign of subtropical precipitation changesModel-data comparison shows mean annual precipitation is underestimated by the models, particularly in the mid- to high-latitudes

The Arctic region is warming about four times faster than the rest of the globe, and thus it is important to understand the processes driving climate change in this region. Aerosols are a significant component of the Arctic climate system as they form ice crystals and liquid droplets that control the dynamics of clouds and also directly interact with solar radiation, depending on the compositions and mixing states of individual particles. Here, we report on the characteristics of submicron-sized aerosol particles using transmission electron microscopy obtained at two high Arctic sites, northeast Greenland (Villum Research Station) and Svalbard (Zeppelin Observatory), during spring 2018. The results showed that a dominant compound in the submicron-sized spring aerosols was sulfate, followed by sea salt particles. Both model simulations and observations at the Zeppelin Observatory showed that sea salt particles became more prevalent when low-pressure systems passed by the station. Model simulations indicate that both sampling sites were affected by diffused and diluted long-range transport of anthropogenic aerosols from lower latitudes with negligible influences of biomass burning emissions during the observation period. Overall, the composition of measured aerosol particles from the two Arctic sites was generally similar and showed no apparent variation except for the sea salt fractions. This study shows a general picture of high Arctic aerosol particles influenced by marine sources and diffused long-range transport of anthropogenic sources during the Arctic spring period. These results will contribute to a better knowledge of the aerosol composition and mixing state during the Arctic spring, which helps to understand the contributions of aerosols to the Arctic climate.

Whale watching is considered a form of green tourism, but can affect marine ecosystems, impacting cetaceans’ behavior and potentially increasing acoustic pollution. A more sustainable whale-watching practice should employ a comprehensive approach involving all stakeholders, but whale-watching operators are rarely involved. We propose a method to assess whale–watching operators’ perceptions regarding the possible effects of their activity on marine fauna and preferred mitigation solutions, by means of online questionnaires and website communication strategies. Results from Canadian whale-watching operators show that they observe regulations regarding distance to whales but only partially perceive general vessels’ impacts on fauna. Three recognized whale-watching experts identify the need for continuous training targeted at operators, which should include the impacts on marine ecosystems. A continuous training framework is proposed that targets whale-watching operators in addition to tourists, and involves scientists in several steps of the approach. This study serves as a starting point to involve operators’ in order to advance towards a sustainable whale-watching tourism.

Nanocellulose with specific surface chemistry exhibits divergent effects on bacterial growth. Here, we report the interaction between different nanocelluloses and Escherichia coli (E. coli). When E. coli is exposed to lignin-containing cellulose nanocrystals (L-CNCs) and TEMPO-oxidized cellulose nanofibers (T-CNFs), the growth rate is reduced, but not the viability of bacterial cells in liquid media, with L-CNCs having the most prominent effect. In situ, PeakForce quantitative nanomechanical mapping (PFQNM) revealed that the surface roughness and stiffness of E. coli were affected when in direct contact with the nanocellulose during incubation, except for the cells attached to CNCs, which promote strong adhesion and even the embedding of E. coli. Thus, nanocelluloses with certain surface chemistries, such as T-CNFs and L-CNCs, could be used as complements or alternatives to antimicrobial drugs for controlling and limiting bacterial growth in liquid media and further biofilm formation on surfaces.

The hydrological cycle is expected to intensify in a warming climate. However, observational evidence of such changes in the Southern Ocean is difficult to obtain due to sparse measurements and a complex superposition of changes in precipitation, sea ice, and glacial meltwater. Here we disentangle these signals using a dataset of salinity and seawater oxygen isotope observations collected in the Indian sector of the Southern Ocean. Our results show that the atmospheric water cycle has intensified in this region between 1993 and 2021, increasing the salinity in subtropical surface waters by 0.06 ± 0.07 g kg⁻¹ per decade, and decreasing the salinity in subpolar surface waters by -0.02 ± 0.01 g kg⁻¹ per decade. The oxygen isotope data allow to discriminate the different freshwater processes showing that in the subpolar region, the freshening is largely driven by the increase in net precipitation (by a factor two) while the decrease in sea ice melt is largely balanced by the contribution of glacial meltwater at these latitudes. These changes extend the growing evidence for an acceleration of the hydrological cycle and a melting cryosphere that can be expected from global warming.

The Arctic has warmed more than twice the rate of the entire globe. To quantify possible climate change effects, we calculate wind energy potentials from a multi-model ensemble of Arctic-CORDEX. For this, we analyze future changes of wind power density (WPD) using an eleven-member multi-model ensemble. Impacts are estimated for two periods (2020-2049 and 2070-2099) of the 21st century under a high emission scenario (RCP8.5). The multi-model mean reveals an increase of seasonal WPD over the Arctic in the future decades. WPD variability across a range of temporal scales is projected to increase over the Arctic. The signal amplifies by the end of 21st century. Future changes in the frequency of wind speeds at 100 m not useable for wind energy production (wind speeds below 4 m/s or above 25 m/s) has been analyzed. The RCM ensemble simulates a more frequent occurrence of 100 m non-usable wind speeds for the wind-turbines over Scandinavia and selected land areas in Alaska, northern Russia and Canada. In contrast, non-usable wind speeds decrease over large parts of Eastern Siberia and in northern Alaska. Thus, our results indicate increased potential of the Arctic for the development and production of wind energy. Bias corrected and not corrected near-surface wind speed and WPD changes have been compared with each other. It has been found that both show the same sign of future change, but differ in magnitude of these changes. The role of sea-ice retreat and vegetation expansion in the Arctic in future on near-surface wind speed variability has been also assessed. Surface roughness through sea-ice and vegetation changes may significantly impact on WPD variability in the Arctic.

A sufficient supply of ecosystem services (ESs) in agriculture provides the basis for human sustainable development. Intensified large-scale farming has changed wetland ecosystems extensively by reducing both the resilience and capacity to support production of many ESs. Small-scale farming may also affect the generation of ESs where the impact often reflects the differences in farming practices. This paper explores the supply and demand of the ESs between management practices, irrigated and rainfed, of smallholder farmers in Kilombero wetland, Tanzania. We conducted interviews involving 30 households and two focus groups with five discussants for each practice, rainfed and irrigation. Generally, we found that the need for ES, especially food, water and flood control, in both farming practices, were exceeding the capacity to supply. In general, irrigation farming compared to rainfed farming was associated with higher levels of food production, increasing flood regulation and erosion control. However, the ES delivery and need were not uniform depending on the river discharge. The differences in supply and demand of ESs between farming practices suggest that society would benefit from investing in irrigation and regulatory infrastructures to minimize flooding risk and to build up the ecosystem’s natural capacity to produce services. Such practical policy-relevant measures could balance the gap between supply and demand of ESs in smallholder farming systems in Tanzanian wetland. 

Pistachio is an important economic crop in arid and semi-arid regions of Iran. A major problem leading to a reduction in crop quality and reduced marketability is extreme air temperature in summer, which causes sunburn of pistachio leaves and fruit. A solution proposed to deal with the negative effects of high temperatures and increase water consumption efficiency in pistachio orchards is use of light-reflecting compounds. This study investigated the effect of foliar application of gypsum, sulfur, and NAX-95 (calcium-based suspension coating) to trees in a pistachio orchard (150 ha) in central Iran. The effect of these foliar products is assessed at plot scale, using control plots sprayed with calcium sulfate, based on temperature and evapotranspiration changes analyzed through remote sensing. Landsat 8 sensor images and RGB images collected by UAVs (spatial resolution of 30 m and 20 cm, respectively), on the same dates, before and after foliar spray application, were merged using the PCA method and bilinear interpolation re-sampling. Land surface temperature (LST) was then estimated using the split-window algorithm, and daily evapotranspiration using the surface energy balance algorithm for land (SEBAL) algorithm. A land use map was prepared and used to isolate pistachio trees in the field and assess weed cover, whose effect was not accounted. The results showed that temperature remained constant in the control plot between the spraying dates, indicating no environmental changes. In the main plots, gypsum had the greatest effect in reducing the temperature of pistachio trees. The plots with foliar spraying with gypsum displayed a mean tree temperature (47–48 °C) decrease of 3.3 °C in comparison with the control plots (>49 °C), leading to an average decline in evapotranspiration of 0.18 mm/day. NAX-95 and sulfur reduced tree temperature by on average 1.3 °C and 0.6 °C, respectively. Thus, gypsum is the most suitable foliar-spraying compound to lower the temperature of pistachio trees, reduce the water requirement, and increase crop productivity.

The partitioning of precipitation water input on land between green (evapotranspiration) and blue (runoff) water fluxes distributes the annually renewable freshwater resource among sectors and ecosystems. The patterns and main drivers of this partitioning are not fully understood around the global land area. We decipher the worldwide patterns and key determinants of this water flux partitioning and investigate its predictability based on a global machine learning model. Available data for 3,614 hydrological catchments and model application to the global land area agree in showing mostly larger green than blue water flux. Possible expansion/intensification of irrigated and/or rainfed agriculture to feed a growing human population, along with climate warming, will tend to increase this flux partitioning asymmetry, jeopardizing blue water security. The developed machine learning model presents a promising predictive tool for future blue and green water availability under various forthcoming climate and land-use change scenarios around the world.

Despite having approximately 100,000 lakes, Sweden has limited continuous gauged lake water level data. Although satellite radar altimetry (RA) has emerged as a popular alternative to measure water levels in inland water bodies, it has not yet been used to understand the large-scale changes in Swedish lakes. Here, we quantify the changes in water levels in 144 lakes using RA data and in situ gauged measurements to examine the effects of flow regulation and hydroclimatic variability. We use data from several RA missions, including ERS-2, ENVISAT, JASON-1,2,3, SARAL, and Sentinel-3A/B. We found that during 1995–2022, around 52% of the lakes exhibited an increasing trend and 43% a decreasing trend. Most lakes exhibiting an increasing trend were in the north of Sweden, while most lakes showing a decreasing trend were in the south. Regarding the potential effects of regulation, we found that unregulated lakes had smaller trends in water level and dynamic storage than regulated ones. While the seasonal patterns of water levels in the lakes in the north are similar in regulated and unregulated lakes, in the south, they differ substantially. This study highlights the need to continuously monitor lake water levels for adaptation strategies in the face of climate change and understand the downstream effects of water regulatory schemes.

Lakes are important sources of freshwater for human activities and provide critical ecosystem services. However, despite having approximately 100,000 lakes, Sweden has limited continuous gauged water level data. Although satellite radar altimetry has emerged as a popular alternative to measure water levels in inland water bodies, it is yet to be exploited to understand large-scale changes in inland water bodies in Sweden. Here, we quantify the changes in water levels of 144 lakes using satellite altimetry data and in-situ gauged measurements and examine the effects of flow regulation and hydroclimatic variability. Data from multiple altimetry missions, including ERS-2, ENVISAT, JASON-1,2,3, SARAL, and Sentinel-3A/B, are employed to estimate the variability and yearly and seasonal trends of water levels in two periods, 1995-2022 and 2013-2022. Our study finds that water levels significantly increased in 52% of the lakes during 1995-2022. The increasing trends primarily occurred in northern Sweden and are potentially attributed to earlier snowmelt. On the other hand, 43% of the lakes exhibited a significant decreasing trend, which was mostly concentrated in Southern Sweden. Dividing the set of lakes into regulated and unregulated groups shows how lake regulation in Sweden can partly explain the spatial patterns of water levels and their variability. This study highlights the need to continuously monitor lake water levels for adaptation strategies in the face of climate change and understand the downstream effects of water regulatory schemes.

It is essential to track lake water level fluctuations, however, the number of conventional gauging stations is declining worldwide due to impractical installation and maintenance procedures. Satellite altimetry is a substitute for traditional gauges. Nevertheless, altimetry sensors cannot identify small lakes owing to poor spatial coverage. Their application is limited to lakes falling exactly below the path of the altimeter. Differential Interferometric Synthetic Aperture Radar (D-InSAR) is commonly used to track land deformation and water surface changes, with the latter being comparatively limited and focused mainly on wetlands. We here explore the potential of D-InSAR to track water level changes in two Swedish lakes, focusing on the shoreline in search of potential double-bounce backscattering and analyzing pixel phase changes and coherence. We use Sentinel-1A and Sentinel-1B data from 2019, generate six-day interferograms, and exclude those when corresponding to in-situ water level changes exceeding one phase cycle. We find that D-InSAR is sensitive to minor water level changes, obtaining Lin's correlations of up to 0.63 and 0.89 (RMSE = 9 & 4 mm, respectively). These results evidence the potential of future L-band SAR missions with larger wavelengths, such as NISAR, to track water level changes in lakes and aid water tracking missions such as the SWOT.

Monitoring lake water level fluctuations is critical for managing water resources, predicting the impacts of climatic change, and preserving ecosystem services lakes provide. However, traditional gauging stations are insufficient to monitor all lakes worldwide due to the large number of existing lakes, the challenges of installation and maintenance, and the remote locations of some. Although satellite altimetry is an alternative for measuring water levels, it cannot monitor small lakes effectively. This study evaluates the potential of Differential Interferometric Synthetic Aperture Radar (D-InSAR) for tracking minor water level changes in small lakes, a method more typically used in wetland studies. We investigate two Swedish lakes using Sentinel-1A and Sentinel-1B data from 2019, generating six-day interferograms and filtering out those with in situ water level changes exceeding one phase cycle. Our results show that D-InSAR can detect small water level changes with Lin’s correlations up to 0.63 and 0.89 and RMSE values of approximately 9 and 4 mm, respectively. These results evidence the potential of future L-band SAR missions with larger wavelengths, such as the NASA-ISRO SAR (NISAR) of the National Aeronautics and Space Administration (NASA) and the Indian Space Research Organisation (ISRO), to track water level changes in lakes and aid water tracking missions such as the SWOT (Surface Water and Ocean Topography).

Lakes are valuable water resources that support aquatic and terrestrial ecosystems and supply fresh water for the agricultural, industrial, and urban sectors worldwide. Although water levels should be tracked to monitor these services, conventional gauging is unfeasible in most lakes. This study explores the potential, advantages, and limitations of using Differential Interferometric Synthetic Aperture Radar (D-InSAR) to estimate small water level changes in lakes (i.e., less than the full cycle of the SAR signal) and overall long-term direction of change. We validated the method across the shores of 30 Swedish lakes with gauged observations during 2019. We used Sentinel-1A/B images with a six-day temporal separation to construct consecutive interferograms and accumulated the phase changes in pixels of high coherence to build time series of water levels. We find that the accumulated phase change replicates the magnitude of water levels in seven lakes in Southern Sweden, where water level changes seldom exceed a complete SAR phase (i.e., 1.8 cm in the vertical direction), evident from the Concordance Correlation Coefficients (0.30 < CCC < 0.55). Furthermore, D-InSAR can estimate the long-term direction of water level change (i.e., increase or decrease) in all 30 lakes. We elaborate on the possible explanation for this last finding. The novel methodology could be used to validate future altimetry missions such as SWOT in lakes worldwide and can be improved with upcoming SAR missions with longer wavelengths.

Lakes are valuable water resources that support aquatic and terrestrial ecosystems and supply fresh water for the agricultural, industrial, and urban sectors worldwide. Although water levels should be tracked to monitor these services, conventional gauging is unfeasible in most lakes. This study applies Differential Interferometric Synthetic Aperture Radar (D-InSAR) to estimate small water level changes, less than 2 cm, in Swedish lakes over 6-day intervals. We validated the method across the shores of 30 Swedish lakes with gauged observations in 2019. We used Sentinel-1A/B images with a 6-day temporal separation to construct consecutive interferograms and accumulated the phase changes in pixels of high coherence to build a time series of water levels. We find that the accumulated phase change obtained by D-InSAR replicates the magnitude of water levels in seven lakes in Southern Sweden, where water levels change slowly, less than 2 cm per 6-day period, as validated by in-situ gauges. In addition, this study demonstrates the application of D-InSAR to estimate the long-term direction of water level change (i.e., increase or decrease) in all 30 lakes. This work reveals the utility of high temporal resolution water level observations in support of other satellite water level instruments such as conventional altimeters and the recently launched Surface Water and Ocean Topography Mission.

Lakes provide societies and natural ecosystems with valuable services such as freshwater supply and flood control. Water level changes in lakes reflect their natural responses to climatic and anthropogenic stressors; however, their monitoring is costly due to installation and maintenance requirements. With its advanced hardware and computational capabilities, altimetry has become a popular alternative to conventional in-situ gauging, although subject to the temporal availability of altimetric observations. To further improve the temporal resolution of altimetric measurements, we here combine radar altimetry data with Differential Interferometric Synthetic Aperture Radar (D-InSAR), using ten lakes in Sweden as a testing platform. First, we use Sentinel-1A and Sentinel-1B SAR images to generate consecutive six-day baseline interferograms across 2019. Then, we accumulate the phase change of coherent pixels to construct the time series of InSAR-derived water level anomalies. Finally, we retrieve altimetric observations from Sentinel-3, estimate their mean and standard deviation, and apply them to the D-InSAR standardized anomalies. In this way, we build a water-level time series with more temporal observations. In general, we find a strong agreement between water level estimates from the combination of D-InSAR and Satellite Altimetry (DInSAlt) and in-situ observations in eight lakes (Concordance Correlation Coefficient - CCC >0.8) and moderate agreement in two lakes (CCC >0.57). The applicability of DInSAlt is limited to lakes with suitable conditions for double-bounce scattering, such as the presence of trees or marshes. The accuracy of the water level estimates depends on the quality of the altimetry observations and the lake's width. These findings are important considering the recently launched Surface Water and Ocean Topography (SWOT) satellite, whose capabilities could expand our methodology's geographical applicability and reduce its reliance on ground measurements.

The Anthropocene is characterized by the strengthening of planetary-scale interactions between the biophysical Earth system (ES) and human societies. This increasing social-ecological entanglement poses new challenges for studying possible future World-Earth system (WES) trajectories and World-Earth resilience defined as the capacity of the system to absorb and regenerate from anthropogenic stresses such as greenhouse gas emissions and land-use changes. The WES is currently in a non-equilibrium transitional regime of the early Anthropocene with arguably no plausible possibilities of remaining in Holocene-like conditions while sheltering up to 10 billion humans without risk of undermining the resilience of the ES. We develop a framework within which to conceptualize World-Earth resilience to examine this risk. Because conventional ball-and-cup type notions of resilience are hampered by the rapid and open-ended social, cultural, economic and technological evolution of human societies, we focus on the notion of 'pathway resilience', i.e. the relative number of paths that allow the WES to move from the currently occupied transitional states towards a safe and just operating space in the Anthropocene. We formalize this conceptualization mathematically and provide a foundation to explore how interactions between ES resilience (biophysical processes) and World system (WS) resilience (social processes) impact pathway resilience. Our analysis shows the critical importance of building ES resilience to reach a safe and just operating space. We also illustrate the importance of WS dynamics by showing how perceptions of fairness coupled with regional inequality affects pathway resilience. The framework provides a starting point for the analysis of World-Earth resilience that can be extended to more complex model settings as well as the development of quantitative planetary-scale resilience indicators to guide sustainable development in a stabilized ES.

The boron isotope (δ¹¹B) proxy for seawater pH is a tried and tested means to reconstruct atmospheric CO₂ in the geologic past, but uncertainty remains over how to treat species-specific calibrations that link foraminiferal δ¹¹B to pH estimates prior to 22 My. In addition, no δ¹¹B-based reconstructions of atmospheric CO₂ exist for wide swaths of the Oligocene (33–23 Ma), and large variability in CO₂ reconstructions during this epoch based on other proxy evidence leaves climate evolution during this period relatively unconstrained. To add to our understanding of Oligocene and early Miocene climate, we generated new atmospheric CO₂ estimates from new δ¹¹B data from fossil shells of surface-dwelling planktic foraminifera from the mid-Oligocene to early Miocene (∼28–18 Ma). We estimate atmospheric CO₂ of ∼680 ppm for the mid-Oligocene, which then evolves to fluctuate between ∼500–570 ppm during the late Oligocene and between ∼420–700 ppm in the early Miocene. These estimates tend to trend higher than Oligo-Miocene CO₂ estimates from other proxies, although we observe good proxy agreement in the late Oligocene. Reconstructions of CO₂ fall lower than estimates from paleoclimate model simulations in the early Miocene and mid Oligocene, which indicates that more proxy and/or model refinement is needed for these periods. Our species cross-calibrations, assessing δ¹¹B, Mg/Ca, δ¹⁸O, and δ¹³C, are able to pinpoint and evaluate small differences in the geochemistry of surface-dwelling planktic foraminifera, lending confidence to paleoceanographers applying this approach even further back in time.

As new to the Swedish research system, one is faced with a series of questions, about what applies to qualifications, what the networks look like, but also practical issues. To make things easier, YAS has developed a guide for international researchers, to help navigate Swedish academia and remove time-consuming obstacles.

We present a reconstruction of the surface climate of the mid-Pliocene Warm Period (mPWP), specifically Marine Isotope Stage (MIS) KM5c or 3.205 Ma. We combine the ensemble of climate model simulations, which contributed to the Pliocene Model Intercomparison Project (PlioMIP), with compilations of proxy data analyses of sea surface temperature (SST). The different data sets we considered are all sparse with high uncertainty, and the best estimate of annual global mean surface air temperature (SAT) anomaly varies from 2.1 up to 4.8 °C depending on the data source. We argue that the latest PlioVAR analysis of alkenone data is likely more reliable than other data sets we consider, and using this data set yields an SAT anomaly of 3.9±1.1 °C, with a value of 2.8±0.9 °C for SST (all uncertainties are quoted at 1 standard deviation). However, depending on the application, it may be advisable to consider the broader range arising from the various data sets to account for structural uncertainty. The regional-scale information in the reconstruction may not be reliable as it is largely based on the patterns simulated by the models.

The remoteness and low population in the Arctic allow us to study global environmental processes, where the analysis of indicators can provide useful information about local and distant pollution sources. Fresh snow represents a convenient indicator of regional and transboundary atmospheric contamination sources, entrapping aerosols, and particulates like a natural autosampler of the environment. Lead stable isotopes are widely used to trace and monitor local and distant pollution sources. However, the behavior of Pb within different snow components is still not thoroughly studied, and its significance could be underestimated if only larger particulates are accounted for. We collected snow and samples from potential sources (fuel, rocks, coal) in three Arctic localities: Nuuk (Greenland), Reykjavik (Iceland), and Longyearbyen (Svalbard). We separated the filtrate from the filter residue through 0.45 mu m nitrocellulose membranes to isolate the low-diameter particles associated with long-range transport from larger particles of mostly local natural origin.

Filtrates yielded higher EFs (enrichment factor as the Pb/Al ratio relative to the upper crust) than filtration residues (80 +/- 104 and 2.1 +/- 1.1, respectively), and Pb isotope signals similar to fuel and coal (206Pb/207Pb are 1.199 +/- 0.028 in coal, 1.168 +/- 0.029 in filtrates, 1.163 +/- 0.013 in fuel, 1.137 +/- 0.045 in residues, and 0.985 +/- 0.020 in rocks). In contrast to filtrates, the filter residues present wider ranges of Pb isotope compositions and crustal contributions and lower EFs, so we suggest that filtrate contains Pb from fuel combustion more selectively, while the residue carries a more considerable contribution of local mineral dust that can mask the contribution of other anthropogenic or distant natural sources. These findings add weight to the notion that filtrates are a more selective measure of metal deposition from long-range anthropogenic emissions compared to analyzing bulk melted snow or only filter residues.

The impact of moisture transport and sources on precipitation stable isotopes (d(18)O and d-excess) in the central Himalayas are crucial to understanding the climatic archives. However, this is still unclear due to the lack of in-situ observations. Here we present measurements of stable isotopes in precipitation at two stations (Yadong and Pali) in the central Himalayas during 2014-2015. Combined with simulations from the dispersion model FLEXPART, we investigate effects on precipitation stable isotopes related to changes in moisture sources and convections in the region, and possible influence by El Nino. Our results suggest that the moisture supplies related to evaporation over northeastern India and moisture losses related to convective activities over the Bay of Bengal (BoB) and Bangladesh region play important roles in changes in d(18)O and d-excess in precipitation in the Yadong Valley. Outgoing longwave radiation and moisture flux divergence analysis further confirm that the contribution from continental evaporation dominates the moisture supply in the central Himalayas with a lesser contribution from convection over the BoB during the 2015 monsoon season compared with 2014. A change in the altitude effect is observed in 2015, which is more significant than the temperature and precipitation amount effect during the observation period. These findings provide valuable insights into climatic interpretations of paleo-isotopic archives with an isotopic response to changes in moisture transport to the central Himalayas.

Aquatic networks contribute greenhouse gases and lateral carbon (C) export from catchments. The magnitudes of these fluxes exceed the global land C sink but are uncertain. Resolving this uncertainty is important for understanding climate feedbacks. We quantified vertical methane (CH₄) and carbon dioxide (CO₂) emissions from lakes and streams, and lateral export of dissolved inorganic and organic carbon from a hemiboreal catchment for 3 yr. Lateral C fluxes dominated the total aquatic C flux. All aquatic C fluxes were disproportionately contributed from spatially restricted areas and/or short-term events. Hence, consideration of local and episodic variability is vital. Temperature and runoff were the main temporal drivers for lake and stream C emissions, respectively. Whole-catchment aquatic C emissions scaled linearly with these drivers within timeframes of stable land-cover. Hence, temperature and runoff increase across Northern Hemisphere humid areas from climate change may yield proportional increases in aquatic C fluxes. 

Deep convective clouds can redistribute gaseous species and particulate matter among different layers of the troposphere with important implications for atmospheric chemistry and climate. The large number of atmospheric trace gases of different volatility makes it challenging to predict their partitioning between hydrometeors and gas phase inside highly dynamic deep convective clouds. In this study, we use an ensemble of 51,200 trajectories simulated with a cloud-resolving model to characterize up- and downdrafts within Amazonian deep convective clouds. We also estimate the transport of a set of hypothetical non-reactive gases of different volatility, within the up- and downdrafts. We find that convective air parcels originating from the boundary layer (i.e., originating at 0.5 km altitude), can transport up to 25% of an intermediate volatility gas species (e.g., methyl hydrogen peroxide) and up to 60% of high volatility gas species (e.g., n-butane) to the cloud outflow above 10 km through the mean convective updraft. At the same time, the same type of gases can be transported to the boundary layer from the middle troposphere (i.e., originating at 5 km) within the mean convective downdraft with an efficiency close to 100%. Low volatility gases (e.g., nitric acid) are not efficiently transported, neither by the updrafts nor downdrafts, if the gas is assumed to be fully retained in a droplet upon freezing. The derived properties of the mean up- and downdraft can be used in future studies for investigating convective transport of a larger set of reactive trace gases.

Mass loss at the Greenland Ice Sheet is influenced by atmospheric processes controlling its surface mass balance, and by submarine melt and calving where glaciers terminate in fjords. There, an ice mélange - a composite matrix of calved ice bergs and sea ice - may provide a buttressing force on a glacier terminus and control terminus dynamics. Kangerlussuaq Glacier is a major outlet of the Greenland Ice Sheet, for which recent major retreat events in 2004/2005 and 2016-2018 coincided with the absence of an ice mélange in Kangerlussuaq Fjord. To better understand the response of Kangerlussuaq Glacier to climatic and oceanic drivers, a 2D flowline model is employed. Results indicate that an ice mélange buttressing force exerts a major control on calving frequency and rapid retreat. When an ice mélange forms in Kangerlussuaq Fjord, it provides stabilising forces and conditions favourable for winter terminus re-advance. When it fails to form during consecutive years, model results indicate that Kangerlussuaq Glacier is primed to retreat into the large overdeepenings in Kangerlussuaq Fjord, and to terminus positions more than 30 km farther inland, implying that excessive mass loss from Kangerlussuaq Glacier by the year 2065 cannot be excluded.

This paper provides an update on the 2017 status of Arctic protected areas. It provides an overview of the status and trends of the extent of protected areas in the Arctic and an overview of area-based conservation measures including World Heritage Sites and wetlands. This paper uses the International Union for Conservation of Nature (IUCN) definition for protected areas which includes a wide range of Management Categories – from strict nature reserve to protection with sustainable use. Consequently, the level of protection and governance of these areas varies throughout the circumpolar region. As of 2021, 20.77 per cent of the Arctic’s terrestrial area and 5.24 per cent of its marine areas are protected. Protected area coverage of the Arctic’s terrestrial ecosystems exceeded Aichi Biodiversity Target 11 which aimed for at least 17 per cent of terrestrial and inland water to be protected by 2020. The protected area coverage of marine areas fell short of the Aichi Target for 10 per cent of coastal and marine areas to be protected.

Land cover heterogeneity information considering soil wetness across the entire Arctic tundra is of interest for a wide range of applications targeting climate change impacts and ecological research questions. Patterns are potentially linked to permafrost degradation and affect carbon fluxes. First, a land cover unit retrieval scheme which provides unprecedented detail by fusion of satellite data using Sentinel-1 (synthetic aperture radar) and Sentinel-2 (multispectral) was adapted. Patterns of lakes, wetlands, general soil moisture conditions and vegetation physiognomy are interpreted at 10 m nominal resolution. Units with similar patterns were identified with a k-means approach and documented through statistics derived from comprehensive in situ records for soils and vegetation (more than 3500 samples). The result goes beyond the capability of existing land cover maps which have deficiencies in spatial resolution, thematic content and accuracy, although landscape heterogeneity related to moisture gradients cannot be fully resolved at 10 m. Wetness gradients were assessed, and measures for landscape heterogeneity were derived north of the treeline. About 40 % of the area north of the treeline falls into three units of dry types with limited shrub growth. Wetter regions have higher land cover diversity than drier regions. An area of 66 % of the analysed Arctic landscape is highly heterogeneous with respect to wetness at a 1 km scale (representative scale of frequently used regional land cover and permafrost modelling products). Wetland areas cover 9 % and moist tundra types 32 %, which is of relevance for methane flux upscaling.

Biomass burning plumes are frequently transported over the southeast Atlantic (SEA) stratocumulus deck during the southern African fire season (June-October). The plumes bring large amounts of absorbing aerosols and enhanced moisture, which can trigger a rich set of aerosol-cloud-radiation interactions with climatic consequences that are still poorly understood. We use large-eddy simulation (LES) to explore and disentangle the individual impacts of aerosols and moisture on the underlying stratocumulus clouds, the marine boundary layer (MBL) evolution, and the stratocumulus-to-cumulus transition (SCT) for three different meteorological situations over the southeast Atlantic during August 2017. For all three cases, our LES shows that the SCT is driven by increased sea surface temperatures and cloud-top entrainment as the air is advected towards the Equator. In the LES model, aerosol indirect effects, including impacts on drizzle production, have a small influence on the modeled cloud evolution and SCT, even when aerosol concentrations are lowered to background concentrations. In contrast, local semi-direct effects, i.e., aerosol absorption of solar radiation in the MBL, cause a reduction in cloud cover that can lead to a speed-up of the SCT, in particular during the daytime and during broken cloud conditions, especially in highly polluted situations. The largest impact on the radiative budget comes from aerosol impacts on cloud albedo: the plume with absorbing aerosols produces a total average 3 d of simulations. We find that the moisture accompanying the aerosol plume produces an additional cooling effect that is about as large as the total aerosol radiative effect. Overall, there is still a large uncertainty associated with the radiative and cloud evolution effects of biomass burning aerosols. A comparison between different models in a common framework, combined with constraints from in situ observations, could help to reduce the uncertainty.

Plant responses to water stress influence water and carbon cycles and can lead to feedbacks on climate yet characterizing these responses at ecosystem levels remains uncertain. Quantifying ecosystem-level water use strategies is complex due to challenges of upscaling plant traits and disentangling confounding environmental factors, ultimately limiting our ability to understand and anticipate global change in ecosystem dynamics and ecohydrological fluxes. We reduce the dimensionality of this problem and quantify plant water use strategies by combining plant traits with soil and climate variables into parameter groups that synthesize key eco-physiological tradeoffs. Using a parsimonious soil water balance framework, we explore variations in plant water uptake capacity, water stress responses, and water use performance via these non-dimensional parameter groups. The group characterizing the synchronization of plant water transport and atmospheric water demand emerges as the primary axis of variation in water use strategies and interacts with the group representing plant hydraulic risk tolerance, especially in arid conditions when plant water transport is limiting. Next, we show that specific plant water use strategies maximize plant water uptake (leading to carbon gain benefits) weighted by risks of water stress (leading to higher costs of water use). A model-data comparison demonstrates that these ecohydrologically optimal parameter groups capture observed soil moisture variability in 40 ecosystems and beyond aridity, rainfall frequency is an important environmental control for plant water use strategies. The emerging parsimonious link between ecohydrological performance and non-dimensional parameters provides a tractable representation of plant water use strategies, relevant to parameterize global models while accounting for ecological and evolutionary constraints on the water cycle.

Thank you to the 1396 reviewers who provided 2328 reviews during 2023 to ensure the quality and integrity of JGR-Oceans manuscripts.

The Arctic is sensitive to cloud radiative forcing. Due to the limited number of aerosols present throughout much of the year, cloud formation is susceptible to the presence of cloud condensation nuclei and ice nucleating particles (INPs). Primary biological aerosol particles (PBAP) contribute to INPs and can impact cloud phase, lifetime, and radiative properties. We present yearlong observations of hyperfluorescent aerosols (HFA), tracers for PBAP, conducted with a Wideband Integrated Bioaerosol Sensor, New Electronics Option during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (October 2019–September 2020) in the central Arctic. We investigate the influence of potential anthropogenic and natural sources on the characteristics of the HFA and relate our measurements to INP observations during MOSAiC. Anthropogenic sources influenced HFA during the Arctic haze period. But surprisingly, we also found sporadic “bursts” of HFA with the characteristics of PBAP during this time, albeit with unclear origin. The characteristics of HFA between May and August 2020 and in October 2019 indicate a strong contribution of PBAP to HFA. Notably from May to August, PBAP coincided with the presence of INPs nucleating at elevated temperatures, that is, >−9°C, suggesting that HFA contributed to the “warm INP” concentration. The air mass residence time and area between May and August and in October were dominated by the open ocean and sea ice, pointing toward PBAP sources from within the Arctic Ocean. As the central Arctic changes drastically due to climate warming with expected implications on aerosol–cloud interactions, we recommend targeted observations of PBAP that reveal their nature (e.g., bacteria, diatoms, fungal spores) in the atmosphere and in relevant surface sources, such as the sea ice, snow on sea ice, melt ponds, leads, and open water, to gain further insights into the relevant source processes and how they might change in the future.

Thawing of ice-rich permafrost soils in sloped terrain can lead to activation of retrogressive thaw slumps (RTSs) which make organic matter available for decomposition that has been frozen for centuries to millennia. Recent studies show that the area affected by RTSs increased in the last two decades across the pan-Arctic. Combining a model of soil carbon dynamics with remotely sensed spatial details of thaw slump area and a soil carbon database, we show that RTSs in Siberia turned a previous quasi-neutral ecosystem into a strong source of carbon dioxide of 367 ± 213 gC m-1 a-1. On a global scale, recent CO₂ emissions from Siberian thaw slumps of 0.42 ± 0.22 Tg carbon per year are negligible so far. However, depending on the future evolution of permafrost thaw and hence thaw slump-affected area, such hillslope processes can transition permafrost landscapes to become a major source of additional CO₂ release into the atmosphere.

Aerosol effects on cloud properties are notoriously difficult to disentangle from variations driven by meteorological factors. Here, a machine learning model is trained on reanalysis data and satellite retrievals to predict cloud microphysical properties, as a way to illustrate the relative importance of meteorology and aerosol, respectively, on cloud properties. It is found that cloud droplet effective radius can be predicted with some skill from only meteorological information, including estimated air mass origin and cloud top height. For ten geographical regions the mean coefficient of determination is 0.41 and normalised root-mean square error 24%. The machine learning model thereby performs better than a reference linear regression model, and a model predicting the climatological mean. A gradient boosting regression performs on par with a neural network regression model. Adding aerosol information as input to the model improves its skill somewhat, but the difference is small and the direction of the influence of changing aerosol burden on cloud droplet effective radius is not consistent across regions, and thereby also not always consistent with what is expected from cloud brightening.

New antibacterial compounds are urgently needed, especially for infections caused by the top-priority Gram-negative bacteria that are increasingly difficult to treat. Lipid A is a key component of the Gram-negative outer membrane and the LpxH enzyme plays an important role in its biosynthesis, making it a promising antibacterial target. Inspired by previously reported ortho-N-methyl-sulfonamidobenzamide-based LpxH inhibitors, novel benzamide substitutions were explored in this work to assess their in vitro activity. Our findings reveal that maintaining wild-type antibacterial activity necessitates removal of the N-methyl group when shifting the ortho-N-methyl-sulfonamide to the meta-position. This discovery led to the synthesis of meta-sulfonamidobenzamide analogs with potent antibacterial activity and enzyme inhibition. Moreover, we demonstrate that modifying the benzamide scaffold can alter blocking of the cardiac voltage-gated potassium ion channel hERG. Furthermore, two LpxH-bound X-ray structures show how the enzyme-ligand interactions of the meta-sulfonamidobenzamide analogs differ from those of the previously reported ortho analogs. Overall, our study has identified meta-sulfonamidobenzamide derivatives as promising LpxH inhibitors with the potential for optimization in future antibacterial hit-to-lead programs.

Sustainable groundwater use relies on adequate rates of groundwater recharge, which are expected to change with climate change. However, climate impacts on recharge remain uncertain due to a paucity of measurements of recharge trends globally. Here we leverage the relationship between climatic aridity and long-term recharge measurements at 5,237 locations globally to identify regions where recharge is most sensitive to changes in climatic aridity. Recharge is most sensitive to climate changes in regions where potential evapotranspiration slightly exceeds precipitation, meaning even modest aridification can substantially decrease groundwater recharge. Future climate-induced recharge changes are expected to be dominated by precipitation changes, whereby changes in groundwater recharge will be amplified relative to precipitation changes. Recharge is more sensitive to changes in aridity than global hydrological models suggest. Consequently, the effects of climatic changes on groundwater replenishment and their impacts on the sustainability of groundwater use by humans and ecosystems probably exceed previous predictions.

Proxy records have shown that the Mid-Holocene was a period of humid conditions across West Africa, with an enhanced West African Monsoon (WAM) and vegetated conditions in areas currently characterized by desert, often referred to as the Green Sahara. However, General Circulation Models regularly struggle with recreating this strengthened Mid-Holocene monsoon in West Africa. Vegetation feedbacks has long been viewed as an essential process modulating the monsoon variability in West Africa, and simulations using prescribed vegetation to recreate a Green Sahara have shown a strengthened WAM and increased rainfall. However, simulations with prescribed vegetation in Sahara represent an idealized vegetation cover and do not take any environmental heterogeneity into account. Furthermore, this only represents a one-directional forcing by the vegetation on the climate rather than the full vegetation feedback. To address this, we have simulated the Mid-Holocene (similar to 6 ka) climate using the Earth System Model EC-Earth3-Veg. The results show that coupled dynamic vegetation reproduces an apparent enhancement of the WAM, with the summer rainfall in the Sahel region increasing by 15% compared to simulations with a prescribed modern vegetation cover. Vegetation feedbacks enhance the warming of the Sahara region, deepens the Sahara Heat Low, results in increased rainfall and strengthens monsoonal flow across West Africa. However, the enhancement is still below what can be viewed in proxy reconstructions, highlighting the role of model limitation and biases and the importance of investigating other processes, such as the interactive aerosol-albedo feedback.

Sustainability-focused research networks and communities of practice have emerged as a key response and strategy to build capacity and knowledge to support transformation towards more sustainable, just and equitable futures. This paper synthesises insights from the development of a community of practice on social-ecological systems (SES) research in southern Africa over the past decade, linked to the international Programme on Ecosystem Change and Society (PECS). This community consists of a network of researchers who carry out place-based SES research in the southern African region. They interact through various cross-cutting working groups and also host a variety of public colloquia and student and practitioner training events. Known as the Southern African Program on Ecosystem Change and Society (SAPECS), its core objectives are to: (1) derive new approaches and empirical insights on SES dynamics in the southern African context; (2) have a tangible impact by mainstreaming knowledge into policy and practice; and (3) grow the community of practice engaged in SES research and governance, including researchers, students and practitioners. This paper reflects on experiences in building the SAPECS community, with the aim of supporting the development of similar networks elsewhere in the world, particularly in the Global South.