Collapse

Abstract

Globally, glaciers and icefields contribute significantly to sea level rise. Here we show that ice loss from Juneau Icefield, a plateau icefield in Alaska, accelerated after 2005 AD. Rates of area shrinkage were 5 times faster from 2015–2019 than from 1979–1990. Glacier volume loss remained fairly consistent (0.65–1.01 km3 a−1) from 1770–1979 AD, rising to 3.08–3.72 km3 a−1 from 1979–2010, and then doubling after 2010 AD, reaching 5.91 ± 0.80 km3 a−1 (2010–2020). Thinning has become pervasive across the icefield plateau since 2005, accompanied by glacier recession and fragmentation. Rising equilibrium line altitudes and increasing ablation across the plateau has driven a series of hypsometrically controlled melt-accelerating feedbacks and resulted in the observed acceleration in mass loss. As glacier thinning on the plateau continues, a mass balance-elevation feedback is likely to inhibit future glacier regrowth, potentially pushing glaciers beyond a dynamic tipping point.

Abstract

As the climate warms, the consequent moistening of the atmosphere increases extreme precipitation. Precipitation variability should also increase, producing larger wet-dry swings, but that is yet to be confirmed observationally. Here we show that precipitation variability has already grown globally (over 75% of land area) over the past century, as a result of accumulated anthropogenic warming. The increased variability is seen across daily to intraseasonal timescales, with daily variability increased by 1.2% per 10 years globally, and is particularly prominent over Europe, Australia, and eastern North America. Increased precipitation variability is driven mainly by thermodynamics linked to atmospheric moistening, modulated at decadal timescales by circulation changes. Amplified precipitation variability poses new challenges for weather and climate predictions, as well as for resilience and adaptation by societies and ecosystems.

Highlights

• When lakes dry up, their exposed lake beds become sources of greenhouse gases
• Many lakes, such as Great Salt Lake (United States), are drying up because of human actions
• High emissions from such lake beds should be assessed with regional carbon budgets

Science for society

Great Salt Lake (Utah, United States) illustrates the many impacts of lake drying, including regional air quality impacts and losses of migratory bird habitat. Here, we show that Great Salt Lake’s drying has exposed lake-bed sediments that are also a major source of greenhouse gas emissions. By comparing these emissions to estimates of the lake’s aquatic emissions, we show that they are likely a new source of greenhouse gases to the atmosphere. The emissions from this and likely many other saline lake beds around the world are anthropogenic, being the direct result of the human activities responsible for their drying, including agriculture, mining, and urban consumption. The emissions are high enough to be accounted for in regional carbon budgets and warrant efforts to halt and reverse the loss of saline lakes around the world.

Summary

Saline lake desiccation is widespread and typically caused by anthropogenic withdrawals for agricultural, industrial, and municipal uses, but its impact on greenhouse gas (GHG) emissions is unknown. While dry-flux studies have shown that desiccating waterbodies emit carbon dioxide (CO2) and methane (CH4) from exposed sediments, these studies are often seasonal and for freshwater systems, limiting their application to chronically desiccating saline lakes. We measured CO2 and CH4 emissions (April to November, 2020) from the exposed sediments of Great Salt Lake (Utah, United States), and compared them with aquatic emissions estimates to determine the anthropogenic emissions associated with desiccation. In 2020, the lake bed emitted 4.1 million tons of CO2eq to the atmosphere, primarily (94%) as CO2, constituting a ∼7% increase to Utah’s anthropogenic GHG emissions. As climate change exacerbates drought in arid regions, anthropogenic desiccation and associated climate feedbacks should be considered in assessments of global GHG trajectories as well as local GHG emissions reduction efforts.

Abstract

The deep ocean, a vast thermal reservoir, absorbs excess heat under greenhouse warming, which ultimately regulates the Earth’s surface climate. Even if CO2 emissions are successfully reduced, the stored heat will gradually be released, resulting in a particular pattern of ocean warming. Here, we show that deep ocean warming will lead to El Niño-like ocean warming and resultant increased precipitation in the tropical eastern Pacific with southward shift of the intertropical convergence zone. Consequently, the El Niño-Southern Oscillation shifts eastward, intensifying Eastern Pacific El Niño events. In particular, the deep ocean warming could increase convective extreme El Niño events by 40 to 80% relative to the current climate. Our findings suggest that anthropogenic greenhouse warming will have a prolonged impact on El Niño variability through delayed deep ocean warming, even if CO2 stabilization is achieved.

Significance

Mammals include some of the best-known species of animals, and are icons of conservation efforts. Despite their status, there is no rigorous estimate available for their overall global biomass. We quantified absolute wild mammalian biomass and its distribution across different taxa and continents. Such data can serve as a holistic benchmark to analyze temporal trends. This quantitative global view of wildlife, when contrasted for example to the mass of humanity and its livestock, can help dispel notions about the seemingly endless ubiquity of wildlife and provide a quantitative argument for the urgency of nature conservation efforts.

Abstract

Wild mammals are icons of conservation efforts, yet there is no rigorous estimate available for their overall global biomass. Biomass as a metric allows us to compare species with very different body sizes, and can serve as an indicator of wild mammal presence, trends, and impacts, on a global scale. Here, we compiled estimates of the total abundance (i.e., the number of individuals) of several hundred mammal species from the available data, and used these to build a model that infers the total biomass of terrestrial mammal species for which the global abundance is unknown. We present a detailed assessment, arriving at a total wet biomass of ≈20 million tonnes (Mt) for all terrestrial wild mammals (95% CI 13-38 Mt), i.e., ≈3 kg per person on earth. The primary contributors to the biomass of wild land mammals are large herbivores such as the white-tailed deer, wild boar, and African elephant. We find that even-hoofed mammals (artiodactyls, such as deer and boars) represent about half of the combined mass of terrestrial wild mammals. In addition, we estimated the total biomass of wild marine mammals at ≈40 Mt (95% CI 20-80 Mt), with baleen whales comprising more than half of this mass. In order to put wild mammal biomass into perspective, we additionally estimate the biomass of the remaining members of the class Mammalia. The total mammal biomass is overwhelmingly dominated by livestock (≈630 Mt) and humans (≈390 Mt). This work is a provisional census of wild mammal biomass on Earth and can serve as a benchmark for human impacts.

Abstract

Interannual sea surface temperature (SST) variations in the subtropical-midlatitude Southern Hemisphere are often associated with a circumpolar wavenumber-4 (W4) pattern. This study is the first attempt to successfully simulate the SST-W4 pattern using a state-of-the-art coupled model called SINTEX-F2 and clarify the underlying physical processes. It is found that the SST variability in the southwestern subtropical Pacific (SWSP) plays a key role in triggering atmospheric variability and generating the SST-W4 pattern during austral summer (December-February). In contrast, the tropical SST variability has a very limited effect. The anomalous convection and associated divergence over the SWSP induce atmospheric Rossby waves confined in the westerly jet. Then, the synoptic disturbances circumnavigate the subtropical Southern Hemisphere, establishing an atmospheric W4 pattern. The atmospheric W4 pattern has an equivalent barotropic structure in the troposphere, and it interacts with the upper ocean, causing variations in mixed layer depth due to latent heat flux (LHF) anomalies. As incoming climatological solar radiation goes into a thinner (thicker) mixed layer, the shallower (deeper) mixed layer promotes surface warming (cooling). This leads to positive (negative) SST anomalies, developing the SST-W4 pattern during austral summer. Subsequently, anomalous entrainment due to the temperature difference between the mixed layer and the water below the mixed layer, anomalous LHF, and disappearance of the overlying atmospheric W4 pattern cause the decay of the SST-W4 pattern during austral autumn. These results indicate that accurate simulation of the atmospheric forcing and the associated atmosphere-ocean interaction is essential to capture the SST-W4 pattern in coupled models.

Key Points

First attempt to successfully simulate the wavenumber-4 (W4) pattern of Southern Ocean sea surface temperature (SST) using a coupled model, uncovering the underlying physical processes

Southwestern subtropical Pacific SST plays a crucial role in generating SST W4 pattern via circumpolar atmospheric variability

The ocean mixed layer and upper ocean processes are found to be important for the growth and decay of the SST pattern

Plain Language Summary

In the subtropical-midlatitude Southern Hemisphere, we often observe year-to-year fluctuations in sea surface temperature (SST) linked to a specific pattern known as wavenumber-4 (W4). This study represents the first successful attempt to simulate this temperature pattern using a climate emulator called SINTEX-F2, allowing us to uncover its physical processes. Our research reveals that SST variations in the southwestern subtropical Pacific (SWSP) play a pivotal role in generating the W4 pattern in the atmosphere, subsequently influencing SST during austral summer. Interestingly, this pattern is almost independent of tropical SST variability. The process starts with heating in the SWSP, causing atmospheric disturbances. This leads to an undulation in mid-latitude atmospheric flow, evolving into a well-established global Rossby wave with four positive (negative) loading centers, forming a W4 pattern. This atmospheric wave interacts with the ocean's surface, leading to heat exchange between the atmosphere and the upper ocean. In turn, it influences the depth of the mixed layer in the upper ocean, which receives solar energy. When solar energy penetrates into a shallower (deeper) mixed layer, it warms (cools) the mixed layer effectively, resulting in higher (lower) SSTs. Afterwards, the energy exchange between the mixed layer and the deep ocean contributes to the decay of the SST pattern.

Abstract

In the period between 5,300 and 4,900 calibrated years before present (cal. bp), populations across large parts of Europe underwent a period of demographic decline1,2. However, the cause of this so-called Neolithic decline is still debated. Some argue for an agricultural crisis resulting in the decline3, others for the spread of an early form of plague4. Here we use population-scale ancient genomics to infer ancestry, social structure and pathogen infection in 108 Scandinavian Neolithic individuals from eight megalithic graves and a stone cist. We find that the Neolithic plague was widespread, detected in at least 17% of the sampled population and across large geographical distances. We demonstrate that the disease spread within the Neolithic community in three distinct infection events within a period of around 120 years. Variant graph-based pan-genomics shows that the Neolithic plague genomes retained ancestral genomic variation present in Yersinia pseudotuberculosis, including virulence factors associated with disease outcomes. In addition, we reconstruct four multigeneration pedigrees, the largest of which consists of 38 individuals spanning six generations, showing a patrilineal social organization. Lastly, we document direct genomic evidence for Neolithic female exogamy in a woman buried in a different megalithic tomb than her brothers. Taken together, our findings provide a detailed reconstruction of plague spread within a large patrilineal kinship group and identify multiple plague infections in a population dated to the beginning of the Neolithic decline.

Abstract

This paper presents a conceptual model describing the medium and long term co-evolution of natural and socio-economic subsystems of Earth. An economy is viewed as an out-of-equilibrium dissipative structure that can only be maintained with a flow of energy and matter. The distinctive approach emphasized here consists in capturing the economic impact of natural ecosystems’ depletion by human activities via a pinch of thermodynamic potentials. This viewpoint allows: (i) the full-blown integration of a limited quantity of primary resources into a non-linear macrodynamics that is stock-flow consistent both in terms of matter-energy and economic transactions; (ii) the inclusion of natural and forced recycling; (iii) the inclusion of a friction term which reflects the impossibility to produce (and recycle)goods and services without exuding energy and matter wastes, and (iv) the computation of the anthropically produced entropy as a function of metabolizing intensity and frictions. Analysis and numerical computations confirm the role played by intensity and frictions as key factors for sustainability by contrast with real gdp growth—as well as the interplay between resource scarcity, income inequality, and inflation. A more egalitarian society with moderate inflation turns out to be more sustainable than an unequal society with low inflation. Our approach is flexible enough to allow for various economic models to be embedded into our thermodynamic framework. Finally, we propose the open source EcoDyco software as a first complete realization implementing economic dynamics in a multi-resource environment.

https://archive.is/Hy1fX

In particular, food production has collapsed in the country. Alexis Rodríguez Pérez, a senior official at the Ministry of Agriculture, said the country produced 15,200 tons of beef in the first six months of this year. As a comparison, Cuba produced 172,300 tons of beef in 2022, already down 40% from 289,100 in 1989. Pork production fared even worse. The country produced barely 3,800 tons in the first six months of this year, compared to 149,000 tons in all of 2018.

https://archive.is/Hy1fX

In particular, food production has collapsed in the country. Alexis Rodríguez Pérez, a senior official at the Ministry of Agriculture, said the country produced 15,200 tons of beef in the first six months of this year. As a comparison, Cuba produced 172,300 tons of beef in 2022, already down 40% from 289,100 in 1989. Pork production fared even worse. The country produced barely 3,800 tons in the first six months of this year, compared to 149,000 tons in all of 2018.

Editor’s summary

Net primary productivity (NPP), the storage of carbon within plant tissues resulting from photosynthesis, is a major carbon sink that we rely on for slowing climate change. Global NPP estimates are variable, leading to uncertainty in modeling current and future carbon cycling. Graven et al. updated NPP estimates using radiocarbon data from nuclear bomb testing in the 1960s. This analysis of radiocarbon uptake into vegetation suggested that current models underestimate NPP, likely by underestimating the carbon stored in short-lived, nonwoody tissues. This work suggests that plants store more carbon but for a shorter time frame than is currently recognized. —Bianca Lopez

Abstract

Vegetation and soils are taking up approximately 30% of anthropogenic carbon dioxide emissions because of small imbalances in large gross carbon exchanges from productivity and turnover that are poorly constrained. We combined a new budget of radiocarbon produced by nuclear bomb testing in the 1960s with model simulations to evaluate carbon cycling in terrestrial vegetation. We found that most state-of-the-art vegetation models used in the Coupled Model Intercomparison Project underestimated the radiocarbon accumulation in vegetation biomass. Our findings, combined with constraints on vegetation carbon stocks and productivity trends, imply that net primary productivity is likely at least 80 petagrams of carbon per year presently, compared with the 43 to 76 petagrams per year predicted by current models. Storage of anthropogenic carbon in terrestrial vegetation is likely more short-lived and vulnerable than previously predicted.