ALBERT

Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hand, K., Phillips, C., Murray, A., Garvin, J., Maize, E., Gibbs, R., Reeves, G., San Martin, A., Tan-Wang, G., Krajewski, J., Hurst, K., Crum, R., Kennedy, B., McElrath, T., Gallon, J., Sabahi, D., Thurman, S., Goldstein, B., Estabrook, P., Lee, S. W., Dooley, J. A., Brinckerhoff, W. B., Edgett, K. S., German, C. R., Hoehler, T. M., Hörst, S. M., Lunine, J. I., Paranicas, C., Nealson, K., Smith, D. E., Templeton, A. S., Russell, M. J., Schmidt, B., Christner, B., Ehlmann, B., Hayes, A., Rhoden, A., Willis, P., Yingst, R. A., Craft, K., Cameron, M. E., Nordheim, T., Pitesky, J., Scully, J., Hofgartner, J., Sell, S. W., Barltrop, K. J., Izraelevitz, J., Brandon, E. J., Seong, J., Jones, J.-P., Pasalic, J., Billings, K. J., Ruiz, J. P., Bugga, R. V., Graham, D., Arenas, L. A., Takeyama, D., Drummond, M., Aghazarian, H., Andersen, A. J., Andersen, K. B., Anderson, E. W., Babuscia, A., Backes, P. G., Bailey, E. S., Balentine, D., Ballard, C. G., Berisford, D. F., Bhandari, P., Blackwood, K., Bolotin, G. S., Bovre, E. A., Bowkett, J., Boykins, K. T., Bramble, M. S., Brice, T. M., Briggs, P., Brinkman, A. P., Brooks, S. M., Buffington, B. B., Burns, B., Cable, M. L., Campagnola, S., Cangahuala, L. A., Carr, G. A., Casani, J. R., Chahat, N. E., Chamberlain-Simon, B. K., Cheng, Y., Chien, S. A., Cook, B. T., Cooper, M., DiNicola, M., Clement, B., Dean, Z., Cullimore, E. A., Curtis, A. G., Croix, J-P. de la, Pasquale, P. Di, Dodd, E. M., Dubord, L. A., Edlund, J. A., Ellyin, R., Emanuel, B., Foster, J. T., Ganino, A. J., Garner, G. J., Gibson, M. T., Gildner, M., Glazebrook, K. J., Greco, M. E., Green, W. M., Hatch, S. J., Hetzel, M. M., Hoey, W. A., Hofmann, A. E., Ionasescu, R., Jain, A., Jasper, J. D., Johannesen, J. R., Johnson, G. K., Jun, I., Katake, A. B., Kim-Castet, S. Y., Kim, D. I., Kim, W., Klonicki, E. F., Kobeissi, B., Kobie, B. D., Kochocki, J., Kokorowski, M., Kosberg, J. A., Kriechbaum, K., Kulkarni, T. P., Lam, R. L., Landau, D. F., Lattimore, M. A., Laubach, S. L., Lawler, C. R., Lim, G., Lin, J. Y., Litwin, T. E., Lo, M. W., Logan, C. A., Maghasoudi, E., Mandrake, L., Marchetti, Y., Marteau, E., Maxwell, K. A., Namee, J. B. Mc, Mcintyre, O., Meacham, M., Melko, J. P., Mueller, J., Muliere, D. A., Mysore, A., Nash, J., Ono, H., Parker, J. M., Perkins, R. C., Petropoulos, A. E., Gaut, A., Gomez, M. Y. Piette, Casillas, R. P., Preudhomme, M., Pyrzak, G., Rapinchuk, J., Ratliff, J. M., Ray, T. L., Roberts, E. T., Roffo, K., Roth, D. C., Russino, J. A., Schmidt, T. M., Schoppers, M. J., Senent, J. S., Serricchio, F., Sheldon, D. J., Shiraishi, L. R., Shirvanian, J., Siegel, K. J., Singh, G., Sirota, A. R., Skulsky, E. D., Stehly, J. S., Strange, N. J., Stevens, S. U., Sunada, E. T., Tepsuporn, S. P., Tosi, L. P. C., Trawny, N., Uchenik, I., Verma, V., Volpe, R. A., Wagner, C. T., Wang, D., Willson, R. G., Wolff, J. L., Wong, A. T., Zimmer, A. K., Sukhatme, K. G., Bago, K. A., Chen, Y., Deardorff, A. M., Kuch, R. S., Lim, C., Syvertson, M. L., Arakaki, G. A., Avila, A., DeBruin, K. J., Frick, A., Harris, J. R., Heverly, M. C., Kawata, J. M., Kim, S.-K., Kipp, D. M., Murphy, J., Smith, M. W., Spaulding, M. D., Thakker, R., Warner, N. Z., Yahnker, C. R., Young, M. E., Magner, T., Adams, D., Bedini, P., Mehr, L., Sheldon, C., Vernon, S., Bailey, V., Briere, M., Butler, M., Davis, A., Ensor, S., Gannon, M., Haapala-Chalk, A., Hartka, T., Holdridge, M., Hong, A., Hunt, J., Iskow, J., Kahler, F., Murray, K., Napolillo, D., Norkus, M., Pfisterer, R., Porter, J., Roth, D., Schwartz, P., Wolfarth, L., Cardiff, E. H., Davis, A., Grob, E. W., Adam, J. R., Betts, E., Norwood, J., Heller, M. M., Voskuilen, T., Sakievich, P., Gray, L., Hansen, D. J., Irick, K. W., Hewson, J. C., Lamb, J., Stacy, S. C., Brotherton, C. M., Tappan, A. S., Benally, D., Thigpen, H., Ortiz, E., Sandoval, D., Ison, A. M., Warren, M., Stromberg, P. G., Thelen, P. M., Blasy, B., Nandy, P., Haddad, A. W., Trujillo, L. B., Wiseley, T. H., Bell, S. A., Teske, N. P., Post, C., Torres-Castro, L., Grosso, C. Wasiolek, M. Science goals and mission architecture of the Europa Lander mission concept. The Planetary Science Journal, 3(1), (2022): 22, https://doi.org/10.3847/psj/ac4493.

Description: Europa is a premier target for advancing both planetary science and astrobiology, as well as for opening a new window into the burgeoning field of comparative oceanography. The potentially habitable subsurface ocean of Europa may harbor life, and the globally young and comparatively thin ice shell of Europa may contain biosignatures that are readily accessible to a surface lander. Europa's icy shell also offers the opportunity to study tectonics and geologic cycles across a range of mechanisms and compositions. Here we detail the goals and mission architecture of the Europa Lander mission concept, as developed from 2015 through 2020. The science was developed by the 2016 Europa Lander Science Definition Team (SDT), and the mission architecture was developed by the preproject engineering team, in close collaboration with the SDT. In 2017 and 2018, the mission concept passed its mission concept review and delta-mission concept review, respectively. Since that time, the preproject has been advancing the technologies, and developing the hardware and software, needed to retire risks associated with technology, science, cost, and schedule.

Description: K.P.H., C.B.P., E.M., and all authors affiliated with the Jet Propulsion Laboratory carried out this research at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (grant No. 80NM0018D0004). J.I.L. was the David Baltimore Distinguished Visiting Scientist during the preparation of the SDT report. JPL/Caltech2021.

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ward, N. D., Megonigal, J. P., Bond-Lamberty, B., Bailey, V. L., Butman, D., Canuel, E. A., Diefenderfer, H., Ganju, N. K., Goni, M. A., Graham, E. B., Hopkinson, C. S., Khangaonkar, T., Langley, J. A., McDowell, N. G., Myers-Pigg, A. N., Neumann, R. B., Osburn, C. L., Price, R. M., Rowland, J., Sengupta, A., Simard, M., Thornton, P. E., Tzortziou, M., Vargas, R., Weisenhorn, P. B., & Windham-Myers, L. Representing the function and sensitivity of coastal interfaces in earth system models. Nature Communications, 11(1), (2020): 2458, doi:10.1038/s41467-020-16236-2.

Description: Between the land and ocean, diverse coastal ecosystems transform, store, and transport material. Across these interfaces, the dynamic exchange of energy and matter is driven by hydrological and hydrodynamic processes such as river and groundwater discharge, tides, waves, and storms. These dynamics regulate ecosystem functions and Earth’s climate, yet global models lack representation of coastal processes and related feedbacks, impeding their predictions of coastal and global responses to change. Here, we assess existing coastal monitoring networks and regional models, existing challenges in these efforts, and recommend a path towards development of global models that more robustly reflect the coastal interface.

Description: Funding for this work was provided by Pacific Northwest National Laboratory (PNNL) Laboratory Directed Research & Development (LDRD) as part of the Predicting Ecosystem Resilience through Multiscale Integrative Science (PREMIS) Initiative. PNNL is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830. Additional support to J.P.M. was provided by the NSF-LTREB program (DEB-0950080, DEB-1457100, DEB-1557009), DOE-TES Program (DE-SC0008339), and the Smithsonian Institution. This manuscript was motivated by discussions held by co-authors during a three-day workshop at PNNL in Richland, WA: The System for Terrestrial Aquatic Research (STAR) Workshop: Terrestrial-Aquatic Research in Coastal Systems. The authors thank PNNL artist Nathan Johnson for preparing the figures in this manuscript and Terry Clark, Dr. Charlette Geffen, and Dr. Nancy Hess for their aid in organizing the STAR workshop. The authors thank all workshop participants not listed as authors for their valuable insight: Lihini Aluwihare (contributed to biogeochemistry discussions and development of concept for Fig. 3), Gautam Bisht (contributed to modeling discussion), Emmett Duffy (contributed to observational network discussions), Yilin Fang (contributed to modeling discussion), Jeremy Jones (contributed to biogeochemistry discussions), Roser Matamala (contributed to biogeochemistry discussions), James Morris (contributed to biogeochemistry discussions), Robert Twilley (contributed to biogeochemistry discussions), and Jesse Vance (contributed to observational network discussions). A full report on the workshop discussions can be found at https://www.pnnl.gov/publications/star-workshop-terrestrial-aquatic-research-coastal-systems.

Description: Background Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. Interpretation Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios.

Description: Sustainable intensification (SI) of agriculture is a promising strategy for boosting the capacity of the agricultural sector to meet the growing demands for food and non-food products and services in a sustainable manner. Assessing and quantifying the options for SI remains a challenge due to its multiple dimensions and potential associated trade-offs. We contribute to overcoming this challenge by proposing an approach for the ex-ante evaluation of SI options and trade-offs to facilitate decision making in relation to SI. This approach is based on the utilization of a newly developed SI metrics framework (SIMeF) combined with agricultural systems modelling. We present SIMeF and its operationalization approach with modelling and evaluate the approach’s feasibility by assessing to what extent the SIMeF metrics can be quantified by representative agricultural systems models. SIMeF is based on the integration of academic and policy indicator frameworks, expert opinions, as well as the Sustainable Development Goals. Structured along seven SI domains and consisting of 37 themes, 142 sub-themes and 1128 metrics, it offers a holistic, generic, and policy-relevant dashboard for selecting the SI metrics to be quantified for the assessment of SI options in diverse contexts. The use of SIMeF with agricultural systems modelling allows the ex-ante assessment of SI options with respect to their productivity, resource use efficiency, environmental sustainability and, to a large extent, economic sustainability. However, we identify limitations to the use of modelling to represent several SI aspects related to social sustainability, certain ecological functions, the multi-functionality of agriculture, the management of losses and waste, and security and resilience. We suggest advancements in agricultural systems models and greater interdisciplinary and transdisciplinary integration to improve the ability to quantify SI metrics and to assess trade-offs across the various dimensions of SI.

Description: The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985–2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world's forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth.

Description: A total of 45 165 171 deaths were analysed in the 406 cities. On average, a 10 µg/m3 increase in ozone during the current and previous day was associated with an overall relative risk of mortality of 1.0018 (95% confidence interval 1.0012 to 1.0024). Some heterogeneity was found across countries, with estimates ranging from greater than 1.0020 in the United Kingdom, South Africa, Estonia, and Canada to less than 1.0008 in Mexico and Spain. Short term excess mortality in association with exposure to ozone higher than maximum background levels (70 µg/m3) was 0.26% (95% confidence interval 0.24% to 0.28%), corresponding to 8203 annual excess deaths (95% confidence interval 3525 to 12 840) across the 406 cities studied. The excess remained at 0.20% (0.18% to 0.22%) when restricting to days above the WHO guideline (100 µg/m3), corresponding to 6262 annual excess deaths (1413 to 11 065). Above more lenient thresholds for air quality standards in Europe, America, and China, excess mortality was 0.14%, 0.09%, and 0.05%, respectively. Conclusions: Results suggest that ozone related mortality could be potentially reduced under stricter air quality standards. These findings have relevance for the implementation of efficient clean air interventions and mitigation strategies designed within national and international climate policies.

Description: Characterizing the temporal uncertainty in palaeoclimate records is crucial for analysing past climate change, correlating climate events between records, assessing climate periodicities, identifying potential triggers and evaluating climate model simulations. The first global compilation of speleothem isotope records by the SISAL (Speleothem Isotope Synthesis and Analysis) working group showed that age model uncertainties are not systematically reported in the published literature, and these are only available for a limited number of records (ca. 15 %, n=107/691). To improve the usefulness of the SISAL database, we have (i) improved the database's spatio-temporal coverage and (ii) created new chronologies using seven different approaches for age–depth modelling. We have applied these alternative chronologies to the records from the first version of the SISAL database (SISALv1) and to new records compiled since the release of SISALv1. This paper documents the necessary changes in the structure of the SISAL database to accommodate the inclusion of the new age models and their uncertainties as well as the expansion of the database to include new records and the quality-control measures applied. This paper also documents the age–depth model approaches used to calculate the new chronologies. The updated version of the SISAL database (SISALv2) contains isotopic data from 691 speleothem records from 294 cave sites and new age–depth models, including age–depth temporal uncertainties for 512 speleothems. SISALv2 is available at https://doi.org/10.17864/1947.256 (Comas-Bru et al., 2020a).

Description: 〈p〉〈em〉Land use and landcover (LULC) change has become a critical component of current methods for not just urban planning but also managing a region's natural resources. The focus of this research is to evaluate the LULC scenario that occurred in Yellanuru Mandal of Anantapur district, AP, India between 2010 and 2020 using Remote Sensing (RS) and Geographical Information Systems (GIS). This study was conducted by gathering Landsat data over a decade, from 2010 to 2020, using ERDAS Imagine 2014 and Arc GIS software, and generating a LULC map using a supervised classification approach. The research region's LULC is divided into five types: vegetation, fallow land, agricultural land, developed land, and water bodies/river. Our findings suggest that satellite data are well adapted to classifying land use/land cover at the subpixel level, where land use categories are linked with homogenous land cover.〈/em〉〈/p〉

Description: In den 10 Must-Knows aus der Biodiversitätsforschung legen 45 Wissenschaftlerinnen und Wissenschaftler fundiert und allgemein verständlich Fakten zur biologischen Vielfalt dar. Sie analysieren die komplexen Systeme der Erde, indem sie zehn Schlüsselbereiche hervorheben, von denen wiederum jeder untrennbar mit allen anderen verbunden ist. Sie zeigen Wege auf, um einen weiteren Verlust an Artenvielfalt und Ökosystemen zu stoppen und die biologische Vielfalt zu fördern. Ihr Ziel ist, für Politik und Gesellschaft wissenschaftlich gesicherte Bewertungen der aktuellen Erkenntnisse für bessere politische Entscheidungen und Maßnahmen auf lokaler, regionaler, nationaler und globaler Ebene zur Verfügung zu stellen, um die Vielfalt des Lebens – die Biodiversität – zu erhalten. Dies sind die 10MustKnows 2022: 1. Klima- und Biodiversitätsschutz zusammen verwirklichen 2. Planetare Gesundheit stärken 3. Unsichtbare Biodiversität beachten 4. Biokulturelle Lebensräume fördern 5. Wald nachhaltig nutzen 6. Landwirtschaft umbauen 7. Land und Ressourcen schützen 8. Transnationale Infrastrukturen und Bildung für Nachhaltigkeit 9. Zugang und offene Nutzung von Forschungsdaten sichern 10. Biodiversitätsfreundliche Anreize setzen