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Ancient oceans warmed — and fish thrived as carbon export surged

A recent study finds that during the Paleocene- Eocene Thermal Maximum (PETM, ~55.9 million years ago), pelagic fish productivity and carbon export from the surface ocean both increased widely, especially in the Pacific and North Atlantic, contrary to many short- term modern observations and some model projections of productivity declines under warming.

cGENIE is an Earth system model of intermediate complexity commonly used for paleoclimate and carbon- cycle studies.

Illustration depicting the Paleocene-Eocene Thermal Maximum with an emphasis on ocean conditions 56 million years ago, showing warming ocean, biological carbon pump processes, and the role of phytoplankton and microbes in carbon cycling. — ***AI generated by Grok***

The findings come from a September 2026 open- access paper in Nature Communications (“Coupled increases in pelagic fish productivity and export productivity during the Paleocene- Eocene Thermal Maximum”). The title you referenced matches press coverage of this work (including by science writer David Appell for Phys.org).

Key background and methods

The PETM was a rapid global warming event triggered by a large release of carbon (roughly 3,000- 10,000 Gt C over ~10 kyr), causing a 3–5‰ negative carbon isotope excursion, seawater warming of ~5- 8 °C, ocean acidification, and other stresses. Cumulative carbon release is comparable in scale to high-end future anthropogenic scenarios, though the emission rate was slower, making it a useful long-term analog.

Researchers used:

Ichthyolith accumulation rates (IAR), fossil fish teeth and scales and dermal denticles in deep- sea sediments, as a proxy for mid- trophic pelagic fish productivity (mainly small pelagic fishes and sharks).
Marine barite accumulation rates (BAR) to estimate export productivity (new production, Pnew), because barite forms in association with sinking organic matter.

They examined multiple sediment cores (new data from sites in the North Pacific, Eastern Equatorial Pacific, North Atlantic, South Atlantic, and Southeast Indian Ocean, plus prior data) and compared the proxies spatially and temporally. Earth- system model simulations (cGENIE) under elevated pCO₂ helped interpret mechanisms.

Main results

IAR rose substantially at Pacific and North Atlantic sites during the main carbon isotope excursion interval, with peaks often 5- 11 times background levels (highest in the Eastern Equatorial Pacific). South Atlantic and Indian Ocean sites showed more modest changes.
These IAR increases closely tracked rises in BAR- derived export productivity in both timing and spatial pattern. Global pooled data showed a significant positive correlation between the two.
Model results indicate that under high CO₂, enhanced nutrient supply (e.g., from stronger terrestrial weathering and runoff) can outweigh the productivity-suppressing effects of increased ocean stratification.

The coupled rises suggest that greater carbon export from the surface supplied more food to mid- trophic- level consumers, supporting higher fish productivity. The authors note that higher export in the water column does not automatically mean more organic matter reaches the seafloor.

Implications

Modern satellite and observational data show recent open- ocean productivity declines (especially in low latitudes) linked to stratification and weaker upwelling under warming, and many models project fisheries impacts.

This PETM evidence indicates that the long-term response under sustained greenhouse conditions can differ: productivity and fish production can increase when nutrient inputs rise enough. The authors emphasize that short- term modern trends may not fully capture millennial- to- longer responses once the system equilibrates.

This builds on earlier work showing elevated fish production during early Paleogene warmth (including the Early Eocene Climatic Optimum) and other PETM fish- abundance studies. It adds direct pairing of fish and export-productivity proxies across ocean basins plus modeling support.

In short, the geologic record suggests that ancient ocean warming of this magnitude was associated with surges in both carbon export and pelagic fish productivity, driven in part by nutrient fertilization that overcame stratification effects.

Global maps of soil carbon export under different scenarios of atmospheric CO2 concentration and phosphorus weathering during the PETM transient period, including variations in contributions from elevated pCO2, weathering, and recycling. — Simulated marine particulate organic carbon (POC) export flux at the intermediate water depth (483 m) for the Paleocene-Eocene Thermal Maximum (PETM) under transient sensitivity experiments and isolated contributions of individual processes. Credit: *Nature Communications* (2026). DOI: 10.1038/s41467-026-77863-9

cGENIE is an Earth system model of intermediate complexity commonly used for paleoclimate and carbon- cycle studies.

In this paper, the authors ran a series of transient simulations with it to test possible mechanisms behind the observed rise in export productivity (particulate organic carbon, or POC, flux) during the PETM. They focused on POC export at intermediate depth (~483 m) and compared the results to their barite- derived Pnew proxy records.

Experimental design

They performed sensitivity experiments that isolated three main factors:

Atmospheric $p$ pCO₂ forcing alone (experiment PETM_CP_NER)
- Atmospheric CO₂ was doubled from a pre- PETM baseline of 1112 ppm to 2224 ppm.
CO₂ forcing and temperature- dependent phosphorus (P) weathering (PETM_1×_NER)
- Added enhanced terrestrial weathering of phosphorus driven by warmer temperatures (consistent with independent lithium-isotope evidence of a ~50–60% global weathering increase).
CO₂ forcing and temperature- dependent P weathering and redox- dependent P recycling (PETM_1×_ER)
- Further added internal phosphorus recycling that strengthens under warmer, more deoxygenated conditions.

They also isolated the individual contributions of each process by differencing the experiments (shown in Fig. 4 of the paper).

Key model results

1. CO₂ doubling / warming and stratification alone produce only a tiny net change

Global mean POC export shows an initial transient decline (due to stronger stratification reducing nutrient upwelling), followed by gradual recovery.
At quasi- equilibrium the net increase is only ~0.01 mol m⁻² yr⁻¹, far smaller than the roughly twofold- to- threefold rise inferred from marine barite records.
The result is insensitive to the exact rate of CO₂ increase.
→ Pure greenhouse forcing and the resulting stratification cannot explain the proxy data.

2. Enhanced weathering -derived phosphorus supply is the dominant driver

When temperature- dependent P weathering is enabled, ocean- wide average POC export rises substantially: from ~0.7 to ~1.2 mol m⁻² yr⁻¹.
Stronger weathering enhancements (e.g., 1.9-fold) push the flux even higher (~1.6 mol m⁻² yr⁻¹), matching the magnitude of the global barite-based increase.
Spatially, the largest modeled increases occur in the Eastern Equatorial Pacific, Atlantic, and Tethys, patterns broadly consistent with the proxy spatial variability.
→ External nutrient input from intensified continental weathering outweighs the negative effects of stratification.

3. Redox-dependent phosphorus recycling adds almost nothing extra

Turning on stronger internal P recycling on top of the weathering increase produces only a negligible additional ~0.01 mol m⁻² yr⁻¹.
Reason: in a warmer, more stratified ocean the thermocline deepens and upward nutrient transport weakens, limiting how much recycled phosphorus reaches the surface euphotic zone. This nutrient- transport limitation largely cancels the expected boost from recycling.

4. Regional iron fertilization is a missing amplifier

The global model does not include regional iron inputs (from North Atlantic Igneous Province volcanism, circum- Caribbean eruptions, or enhanced dust).
As a result, simulated POC fluxes are generally lower than the highest proxy $P_{new}$ Pnew values, especially at the Eastern Equatorial Pacific and North Atlantic sites where iron fertilization is thought to have been important.

Overall interpretation from the model

Under elevated $p$ pCO₂, the positive effect of enhanced nutrient supply (mainly via warmer- climate weathering) can outweigh the suppressive effect of ocean stratification on export productivity.

This supports the proxy observation of higher carbon export during the PETM and helps explain why mid- trophic fish productivity also rose. The model also implies that higher export could have acted as negative feedback by increasing organic- carbon burial and helping draw down atmospheric CO₂, although warmer temperatures and acidification may have accelerated organic- matter degradation higher in the water column, so more export does not automatically mean more organic carbon reaches the seafloor.

In short, the cGENIE results show that nutrient fertilization, not just temperature or CO₂, is the key to reconciling increased long- term productivity with a stratified greenhouse ocean.

Coupled increases in pelagic fish productivity and export productivity during the Paleocene-Eocene Thermal Maximum

Abstract (summary)

Ocean productivity is sensitive to climate change. Recent decades show declines, but the long- term response under sustained warming is uncertain. Using paired ichthyolith accumulation rates (IAR; a proxy for pelagic fish productivity) and marine barite accumulation rates (BAR; a proxy for export productivity / new production $P_{new}$ Pnew), the authors examined the Paleocene-Eocene Thermal Maximum (PETM, ~55.9 Ma). They found a widespread increase in pelagic fish productivity (especially Pacific and North Atlantic) that closely tracks export productivity in both trend and spatial pattern. This suggests the fish increase was fueled by enhanced carbon export from the surface ocean. Earth- system model simulations (cGENIE) show that under elevated pCO₂, enhanced nutrient supply can outweigh the negative effects of ocean stratification on export productivity. The long- term response of marine productivity to sustained greenhouse warming may therefore differ from the short- term declines seen in the modern ocean.

Key context

The PETM involved rapid injection of 3,000- 10,000 Gt of isotopically light carbon, a 3- 5‰ negative carbon isotope excursion (CIE), ocean warming of 5-8 °C, acidification, deoxygenation, and biotic turnovers. Cumulative carbon release is comparable to high- end future anthropogenic scenarios (though the rate was slower), making it a useful long- term analog.

Prior proxies and models for PETM productivity have been inconsistent: BAR and some other records suggested increases (linked to terrestrial nutrient input), while certain microfossil assemblages and models pointed to declines from stratification.

Methods and sites

IAR: New data from ODP/IODP Sites 1209 (North Pacific), 1221 (Eastern Equatorial Pacific), U1403 (North Atlantic), U1557 (South Atlantic), and U1514 (Southeast Indian Ocean), plus reanalysis of prior data from Site 1220 (Eastern Equatorial Pacific).
BAR- derived Pnew: Compilation including new measurements and prior data from matching or nearby sites.
Comparison with transient and equilibrated cGENIE model experiments testing CO₂ forcing, temperature- dependent phosphorus weathering, and redox- dependent phosphorus recycling.

Main results

Pronounced IAR increases at Pacific and North Atlantic sites during the main CIE interval (peaks often 5- 11 times as background; highest in Eastern Equatorial Pacific, up to 121 ichthyoliths cm⁻² kyr⁻¹). More modest changes in the South Atlantic and Indian Ocean.
Many sites show two IAR peaks: one at CIE onset and another ~45- 50 kyr later.
IAR rises primarily reflect higher ichthyolith flux (not sedimentation- rate changes). Fish community composition remained relatively stable (mostly small teeth <63 μm; no major morphotypes shifts or excursion fauna).
Pnew also rose, with peaks coinciding with IAR peaks in several regions (e.g., Eastern Equatorial Pacific reaching ~187 g C m⁻² yr⁻¹). Global pooled data show a significant positive correlation between Pnew and IAR (Pearson $r = 0.55$ r=0.55, Spearman $ρ = 0.61$ ρ=0.61).
Spatial patterns match modern export gradients to a degree, with highest values near upwelling or nutrient- source regions.

Mechanisms (from modeling)

CO₂- driven warming/stratification alone produces only a small net change in particulate organic carbon (POC) export after an initial decline.
Enhanced temperature- dependent phosphorus weathering (consistent with lithium- isotope evidence of 50– 60% higher terrestrial weathering) substantially boosts export productivity (roughly matching the observed ~2- 3 times as global rise in some records).
Redox- dependent phosphorus recycling adds little extra effect once stratification is accounted for.
Regional amplifiers (e.g., iron from volcanic ash and dust, especially near the North Atlantic Igneous Province) likely contributed in high- productivity areas but were not fully captured in the global model.

Implications

Elevated export productivity increased food availability for mid- trophic pelagic fish, supporting higher fish productivity. The long- term geologic response under sustained high CO₂ can feature productivity increases when nutrient supply rises enough to overcome stratification, contrasting with many short-term modern observations and some century- scale projections.

The paper is open access; the full text, figures, supplementary data, and methods are available at the link. This is the scientific source behind recent coverage (including pieces such as the Phys.org article referenced earlier).

Title: Coupled increases in pelagic fish productivity and export productivity during the Paleocene-Eocene Thermal Maximum

Journal: Nature Communications, volume 17, Article number: 10030 (2026)

DOI: 10.1038/s41467-026-77863-9

Journal: Nature Communications

Authors: Xiuwen Zhou,
Ruiling Zhang,
Man-Yin Tsang,
Mingsong Li &
Weiqi Yao

Line graph showing the status of the world's fish stocks from 1974 to 2021, indicating the percentage of fish stocks that are biologically sustainable versus overexploited. — Credit: https://ourworldindata.org/fish-and-overfishing#how-much-of-the-world-s-fish-is-managed-sustainably

Tropical Forest Collapse, Not Volcanoes, Kept Earth in a Super- Greenhouse for 5 Million Years

The Permian- Triassic mass extinction (the “Great Dying”), ~251.9- 252 million years ago, was Earth’s most severe extinction event.

New fossil evidence (macrofossils, palynology, and related indicators), combined with climate- biogeochemical modeling, points to a different primary driver for the persistence: the collapse of terrestrial vegetation, especially tropical forests and peat-bforming ecosystems.

Infographic on the impact of tropical forest collapse on Earth's climate, highlighting that forest loss, not volcanic activity, led to a 'super-greenhouse' effect over 5 million years. — AI generated by Grok

The Permian- Triassic mass extinction (the “Great Dying”), ~251.9- 252 million years ago, was Earth’s most severe extinction event.

It eliminated roughly 81- 96% of marine species and about 70% of terrestrial vertebrate species, with major losses among insects, plants, and other groups as well. Recovery of ecosystems took millions of years.

The dominant driver was prolonged, massive eruptions of the Siberian Traps large igneous province in what is now Siberia. These flood- basalt eruptions released enormous volumes of CO₂, sulfur gases, halocarbons, and other volatiles over a geologically short interval (hundreds of thousands of years, with intense pulses). Contact metamorphism of coal- bearing and organic- rich sediments by the intruding magmas amplified greenhouse- gas and toxic- gas release.

The sudden rise in atmospheric greenhouse gases produced rapid global warming (estimates often cite several degrees Celsius on average, with larger extremes in some regions), intensified the hydrological cycle, and drove ocean warming.

Key secondary impacts included:

Ocean acidification from elevated CO₂.
Widespread marine anoxia (oxygen- depleted “dead zones”) and euxinia (hydrogen- sulfide- rich conditions).
Disruption of the carbon cycle, with evidence from large negative carbon- isotope excursions.
Terrestrial effects such as wildfires, soil erosion, and changes in vegetation and weathering patterns.

These stresses acted synergistically, collapsing food webs in the oceans and on land.

The extinction was not a single instantaneous catastrophe but a prolonged crisis with one or more intense pulses coinciding with the main volcanic activity.

The Siberian Traps eruptions acted as a powerful natural catalyst for extreme climate change.

The resulting greenhouse- driven warming, ocean chemistry shifts, and ecosystem collapse is the clearest deep- time analogue for the environmental consequences of a rapid, large- scale injection of greenhouse gases.

Modern anthropogenic CO₂ release is occurring far faster than the volcanic pulses of the end- Permian, but the end-Permian record shows how high greenhouse- gas levels and associated feedback can push the Earth system past tipping points that produce mass extinction.

Other contributing factors sometimes discussed (possible asteroid impact, methane hydrate release, or earlier climatic shifts) are secondary or poorly supported compared with the volcanic– climate cascade.

The event marks the boundary between the Paleozoic and Mesozoic eras and permanently altered the trajectory of life on Earth.

The Siberian Traps form one of Earth’s largest continental Large Igneous Provinces (LIPs), with estimated original volumes commonly in the range of ~2- 5 × 10⁶ km³ (some estimates higher, up to ~7- 15 × 10⁶ km³ including intrusive and eroded material).

Magmatism spanned the Permian- Triassic boundary (~252 Ma) over roughly 1 million years (or less for the main pulse), with intense phases lasting hundreds of thousands of years.

The prevailing model involves a thermochemical mantle plume (hotter by ~100- 300°C and chemically distinct) rising from the core- mantle boundary, possibly combined with lithospheric delamination.

Plume impingement on the base of the thick Siberian Craton lithosphere triggered extensive melting. Early melts often show deeper (garnet -field) origins with stronger pyroxenite contributions; later melts reflect shallower, more extensive melting of predominantly peridotitic mantle (with recycled components).

Alternative or complementary ideas include:

Subduction- related hydration of the mantle transition zone (releasing water that lowers the solidus), consistent with the back- arc tectonic setting and some arc-like geochemical signatures (low Nb, high Pb/Sr/Ba) in low-Ti basalts.
Lithospheric delamination or edge-driven convection (less favored for explaining the full volume and extent).
Extraterrestrial impact (poorly supported).

Seismic data and geochemical progression (high-Ti early suites to low-Ti tholeiitic main phase, with late alkaline activity) support plume- related melting under thinned or eroded lithosphere, especially beneath the West Siberian Basin and Tunguska region.

Magma ascended through the crust and created a complex sub- volcanic plumbing system of dikes and especially extensive sills.

Sills comprise a large fraction of the total volume (estimates ~37- 50%). They preferentially intruded the thick (several km) sedimentary fill of the Tunguska Basin, which includes Cambrian evaporites (halite, anhydrite), carbonates, marls, siliciclastics, and Permian coal- bearing rocks.

Borehole data show abundant thick sills (>100 m common; averages 115- 130 m in evaporites; maximum recorded ~428 m). Evaporites acted as preferred horizons for melt accumulation due to their thermal and mechanical properties. Some individual sills may have exceeded thousands of km³.

Eruptive styles evolved in stages (based on high- precision U- Pb geochronology):

Early phase (pre- extinction): Widespread explosive pyroclastic and phreatomagmatic activity (interaction with groundwater or surface water), producing thick volcaniclastic breccias (up to ~1 km in places), followed by and interspersed with flood- basalt lava effusion. About two-thirds of the lava/pyroclastic volume erupted over ~300 kyr before and during the extinction onset.

Critical intrusive phase (coinciding with extinction ~251.9 Ma): Shift to dominant sill emplacement into volatile- rich sediments. This initial widespread sill pulse is widely regarded as the “deadly” interval because it maximized contact metamorphism of previously untapped sediments.

Later phases: Continued sill intrusion and renewed extrusive activity (including alkaline rocks) for hundreds of kyr after the main extinction.

Phreatomagmatism was important early on, with distributed vents. Flood basalts formed thick, stepwise (“trap”) plateaus of relatively volatile- poor tholeiitic lavas.

Direct magmatic degassing released CO₂, SO₂, H₂O, and halogens from the melts themselves. However, the dominant environmental driver was interaction with sedimentary host rocks:

Contact metamorphism around sills heated organic- rich sediments (coal, shale), carbonates, and evaporites, generating large volumes of thermogenic gases (CO₂, CH₄, SO₂, and halogenated compounds such as CH₃Cl and CH₃Br). Thermal modeling of sill cooling indicates contact aureoles can produce ~52- 80 tonnes of CO₂ per m² (from both marine and terrestrial carbon sources). Scaling suggests that only a small fraction (~0.7- 1.2%) of the sill- affected area in the Tunguska Basin could generate 1,000 Gt CO₂; basin- scale estimates reach on the order of 100,000 Gt CO₂.

Overpressure from gas generation fractured the rocks, forming degassing structures: hydrothermal vents, diatreme pipes, and magnetite- rich pipes (especially rooted in evaporites). These acted as conduits linking deep aureoles to the atmosphere, enabling rapid, explosive gas release. Crater- lake deposits and pipe structures are documented, particularly in southern parts of the basin.

The combination of high magma flux, sill- dominated intrusion into a volatile- fertile sedimentary basin, and efficient venting produced rapid greenhouse- gas loading, sulfur aerosols (short- term cooling pulses), ocean acidification, and other stresses that drove the end- Permian crisis. Mantle- derived and thermogenic carbon both contributed, with the intrusive- metamorphic component especially critical at the extinction onset.

In summary, the Siberian Traps mechanisms center on plume-driven melting, a shift from early explosive/effusive surface volcanism to extensive shallow sill intrusion into carbon- and sulfur- rich sediments, and efficient release of both magmatic and thermogenic volatiles through a network of pipes and vents.

This architecture distinguishes it from purely extrusive flood- basalt provinces and explains its outsized climatic and biotic impact.

_____________________________________________________________________________________

Early Triassic super- greenhouse climate driven by vegetation collapse

For a long time, the prolonged Early Triassic “super- greenhouse” (roughly 5 million years of extreme warmth after the Permian-Triassic mass extinction) was attributed mainly to the lingering effects of Siberian Traps volcanism and associated greenhouse-gas release. Once the main volcanic pulses ended, silicate weathering and organic- carbon burial were expected to draw CO₂ down relatively quickly (on the order of ~100,000 years). The fact that extreme temperatures persisted far longer remained a puzzle.

New fossil evidence (macrofossils, palynology, and related indicators), combined with climate- biogeochemical modeling, points to a different primary driver for the persistence: the collapse of terrestrial vegetation, especially tropical forests and peat-bforming ecosystems.

Nature Communications volume 16, Article number: 5400 (2025). Published 2 July 2025 (with a later author correction).

The Permian- Triassic Mass Extinction (PTME, ~252 Ma) was triggered by intense greenhouse warming from Siberian Traps volcanism (and associated thermogenic gas release). However, extreme “super-greenhouse” conditions persisted for roughly 5 million years into the Early Triassic, long after the main volcanic pulses should have been offset by silicate weathering and organic- carbon burial.

The authors argue that the key reason was the dramatic and prolonged collapse of terrestrial vegetation, especially in the tropics. Loss of plant biomass reduced organic- carbon sequestration and limited chemical weathering, locking the climate- carbon system into a higher- temperature steady state.

Methods and evidence

Compiled a large plant fossil database (macrofossils and palynology) spanning the latest Permian to Middle Triassic.
Produced stage-level spatio- temporal maps of plant productivity and diversity, normalized for fragmentation and sampling bias.
Combined these with lithological climate indicators.
Fed the reconstructed vegetation changes into a linked climate- biogeochemical model.

Results show major loss of low- latitude (tropical) plant productivity at the PTME, coinciding with the well-known multimillion- year “coal gap” (near- absence of peat/coal formation). Tropical peat- forming ecosystems, normally important CO₂ sinks, largely disappeared and recovered only slowly.

Implications

Vegetation collapse created positive feedback:

Reduced organic- carbon burial.
Restricted chemical (silicate) weathering.
Sustained high atmospheric CO₂ and global temperatures for ~5 Myr.

The work supports the existence of thresholds in the climate- carbon system: once warming and vegetation loss cross a critical point, the Earth system can stabilize at a much hotter state until plants gradually recover (which began more substantially in the Middle Triassic).

This mechanism helps explain why temperatures did not return to pre- extinction levels within the expected ~100 kyr window after volcanic degassing ended. It complements earlier ideas about changes in weathering rates or reverse weathering but ties the prolonged hothouse more directly to the timing of terrestrial biotic recovery.

As a result, atmospheric CO₂ stayed elevated and the climate locked into a hotter steady state until vegetation gradually recovered in the Middle Triassic. The study frames this as evidence of a threshold in the climate- carbon system: once warming and vegetation collapse cross a critical point, positive feedback can amplify and prolong the greenhouse conditions far beyond the original volcanic trigger.

In short, the Siberian Traps ignited the crisis, but the near- destruction of tropical forests is what kept the planet in a super- greenhouse state for millions of years afterward. This highlights how tightly the biosphere regulates long- term climate and how its collapse can turn a severe but temporary warming event into a prolonged one.

The study reinforces the tight coupling between the biosphere and long- term climate regulation and illustrates how a mass extinction of plants can amplify and extend the climatic effects of large igneous province eruptions.

Published: Nature Communications volume 16, Article number: 5400 (2025)

DOI: 10.1038/s41467-025-60396-y

Authors: Zhen Xu,
Jianxin Yu,
Hongfu Yin,
Andrew S. Merdith,
Jason Hilton,
Bethany J. Allen,
Khushboo Gurung,
Paul B. Wignall,
Alexander M. Dunhill,
Jun Shen,
David Schwartzman,
Yves Goddéris,
Yannick Donnadieu,
Yuxuan Wang,
Yinggang Zhang,
Simon W. Poulton &
Benjamin J. W. Mills

Abstract

The Permian–Triassic Mass Extinction (PTME), the most severe crisis of the Phanerozoic, has been attributed to intense global warming triggered by Siberian Traps volcanism. However, it remains unclear why super-greenhouse conditions persisted for around five million years after the volcanic episode, with one possibility being that the slow recovery of plants limited carbon sequestration. Here we use fossil occurrences and lithological indicators of climate to reconstruct spatio-temporal maps of plant productivity changes through the PTME and employ climate-biogeochemical modelling to investigate the Early Triassic super-greenhouse. Our reconstructions show that terrestrial vegetation loss during the PTME, especially in tropical regions, resulted in an Earth system with low levels of organic carbon sequestration and restricted chemical weathering, resulting in prolonged high CO₂ levels. These results support the idea that thresholds exist in the climate-carbon system whereby warming can be amplified by vegetation collapse.

Rising CO₂ Supercharges C₄ Grass Growth in African Savannas, Study Finds

C4 grasses have inherently high water use efficiency (WUE) compared to C3 plants, primarily due to their CO₂-concentrating mechanism (CCM), and elevated atmospheric CO₂ further enhances this advantage—especially under water-limited conditions.

Rising atmospheric CO₂ is boosting growth of C₄ grasses in African savannas (especially under dry conditions), according to a 2026 University of Sheffield-led study published in Nature.

The paper (“Increasing CO₂ levels fertilize C₄ grass production”) combines a meta-analysis of 70 CO₂-enrichment experiments on wild C₄ grasses, a 32-year observational record of grass production from 533 sites in South Africa’s Kruger National Park (1989–2021), and modeling with the Community Land Model.

Experimental results: Elevated CO₂ increases aboveground biomass and photosynthesis more strongly under water limitation than under well-watered conditions. Grasses reduce stomatal conductance (limiting water loss) while maintaining or increasing carbon gain, which alleviates drought stress and improves leaf water potential. Root biomass responses were more variable.

Field observations: Grass production in Kruger rose by about 28% over the period (a CO₂-linked increase of roughly 75 g m⁻², or 0.37 tons C ha⁻¹ of annual production). The relative increase was largest in the driest areas. Other factors (rainfall, temperature, grazing, fire, nitrogen deposition, and species shifts) did not fully explain the trend; the pattern aligned best with rising atmospheric CO₂.

Modeling: Simulations indicate CO₂-driven gains in aboveground C₄ grass productivity could continue through the 21st century, though higher temperatures and reduced rainfall may weaken (but not eliminate) the effect.

This challenges the long-standing view that C₄ grasses (which dominate many tropical/subtropical savannas and already use an efficient photosynthetic pathway adapted to hot, high-light conditions) respond little to rising CO₂. The benefit appears largely indirect—via improved water-use efficiency under drought—rather than a strong direct photosynthetic boost under ample water.

Savannas cover ~20% of Earth’s land surface (and about half of Africa) and account for a large share of global plant productivity.

Potential consequences include:

Greater fuel loads and altered fire regimes.
Changes in forage for wildlife and livestock, affecting animal distributions and habitats.
Shifts in plant competition (including with trees) and community composition (taller, more productive grass species became more dominant in Kruger).
Uncertain effects on long-term carbon storage, because much of the extra grass biomass may be consumed by herbivores or burned, releasing carbon rather than sequestering it.

Lead author Dr. Kimberley Simpson (University of Sheffield) noted that the results overturn assumptions about C₄ unresponsiveness under dry conditions.

Co-authors include researchers from Princeton and other institutions; Professor Colin Osborne (Sheffield) highlighted the consistency between experiments and long-term field data.

In short, rising CO₂ is already “supercharging” grass growth in water-limited African savannas via water conservation, with ongoing effects likely as concentrations continue to climb.

This adds nuance to understanding of savanna dynamics, woody encroachment, fire, and the global carbon cycle.

_____________________________________________________________________________________

This is central to their dominance in warm, seasonally dry environments like African savannas and helps explain findings from the recent University of Sheffield-led Nature study on rising CO₂ boosting C4 grass growth.

Water Use Efficiency (WUE) measures how effectively a plant converts water into biomass or fixed carbon.

Common metrics include:

Intrinsic WUE (iWUE): Net CO₂ assimilation rate (A) divided by stomatal conductance (gₛ), reflecting leaf-level efficiency (µmol CO₂ mol⁻¹ H₂O).
Instantaneous or photosynthetic WUE (PWUE): A divided by transpiration rate (E).
Whole-plant or biomass WUE: Biomass produced per unit of water transpired or used (often g dry mass kg⁻¹ H₂O).

Higher WUE means more carbon fixed (or biomass grown) per unit of water lost.

C4 photosynthesis spatially separates initial CO₂ fixation (via PEP carboxylase in mesophyll cells) from the Calvin cycle (in bundle-sheath cells). This CCM elevates CO₂ around Rubisco, nearly eliminating photorespiration.

Key consequences for water use:

C4 leaves saturate photosynthesis at lower intercellular CO₂ concentrations (Cᵢ) than C3 leaves.
They achieve high A at lower gₛ, reducing water vapor loss through stomata.
Typical Cᵢ/Cₐ ratios are ~0.3–0.4 in C4 vs. ~0.6–0.7 in C3 plants, roughly doubling theoretical WUE under similar conditions.

Empirical differences:

Leaf-level iWUE or PWUE is commonly 1.5–3× (or more) higher in C4 than C3 grasses under comparable conditions.
Whole-plant WUE is often ~2× higher.
C4 grasses maintain higher A while operating at lower gₛ and transpiration, especially in hot, high-vapor-pressure-deficit environments.

This efficiency, combined with high temperature optima for photosynthesis, allows C4 grasses to thrive where water is scarce during the growing season (e.g., tropical/subtropical savannas with summer rainfall). Subtypes (NADP-ME, NAD-ME, PCK) show some variation: NAD-ME types often exhibit particularly high WUE under drought.

C4 plants also tend to have hydraulic traits (e.g., higher leaf hydraulic conductivity relative to gₛ) that support efficient water transport while maintaining the low-conductance strategy.

Although the C4 CCM already saturates Rubisco at relatively low Cᵢ, rising atmospheric CO₂ still improves WUE mainly through stomatal responses:

Elevated CO₂ reduces gₛ (partial stomatal closure), lowering transpiration while A is maintained or only modestly increased under well-watered conditions.
Under drought or water limitation, the reduction in water loss improves plant water status (higher leaf water potential), alleviates stress, and allows continued photosynthesis and growth. This indirect fertilization effect is stronger in dry conditions.

The recent Nature study (Simpson et al., 2026) confirmed this across 70 experiments and long-term Kruger National Park data: higher CO₂ helps wild C4 savanna grasses conserve water, reduce drought stress, and increase aboveground production (notably a 28% rise over 1989–2021 in Kruger, greatest in drier sites). Modeling suggests this can continue into the future, though warming and altered rainfall may modulate it.

Meta-analyses and chamber/FACE experiments show:

iWUE often rises proportionally with CO₂ because gₛ declines while A holds steady or increases under stress.
Soil moisture may be conserved in some cases, further benefiting growth.
Benefits are more pronounced for wild (vs. highly selected crop) C4 grasses and under water scarcity.

Note that C4 photosynthesis can still be sensitive to severe drought (limited alternative electron sinks like photorespiration), but the baseline high WUE and CO₂-driven improvements provide resilience.

Ecological and Practical Implications

Savannas and grasslands: High WUE underpins C4 grass dominance in water-limited systems covering ~20% of land area. CO₂-driven WUE gains can increase grass biomass, alter fire regimes (more fuel), forage availability, competition with trees, and carbon cycling.

Crops (maize, sorghum, sugarcane, millet): C4 crops already use water more efficiently; further gains under elevated CO₂ support productivity in aridifying regions, though heat and extreme drought remain challenges. Breeding targets include optimizing stomatal dynamics (faster closure) and hydraulic traits for even higher iWUE.

Climate change context: Rising CO₂ can partially offset drying effects of warming by improving WUE and plant water status, contributing to observed greening in some drylands. However, outcomes depend on interactions with temperature, VPD, nutrients, and competition.

In summary, C4 grasses are water-efficient by design thanks to their CCM, which enables high carbon gain at low stomatal opening.

Elevated CO₂ amplifies this by further reducing water loss, particularly benefiting growth in dry conditions—as demonstrated in African savanna studies. This makes them key players in future grassy ecosystems under global change.

_____________________________________________________________________________________

Increasing CO₂ levels fertilize C₄ grass production

Increasing atmospheric CO₂ levels fertilize C₄ grass production, particularly under dry conditions, according to a 2026 Nature study led by Kimberley Simpson (University of Sheffield) with co-authors including Carla Staver (Princeton University) and Colin Osborne (University of Sheffield).

The paper, titled “Increasing CO₂ levels fertilize C₄ grass production,” combines three independent lines of evidence to challenge the long-held assumption that C₄ grasses (which dominate many tropical and subtropical savannas) respond weakly to rising CO₂ because of their efficient CO₂-concentrating mechanism.

Main Findings

Meta-analysis of 70 CO₂-enrichment experiments on wild C₄ grasses

Elevated CO₂ significantly increased aboveground biomass and photosynthetic rates under water-limited conditions (log response ratio for aboveground biomass ≈ 0.34).
Under well-watered conditions the response was weaker and often non-significant.
Mechanisms: Reduced stomatal conductance limited water loss while carbon gain was maintained or increased; leaf water potential improved under drought; soil water content responses were variable.
Root biomass responses were highly variable. Effects were consistent across C₄ biochemical subtypes, clades, and regions.

Long-term field observations

Analysis of a unique 32-year record (1989–2021) of grass aboveground production from 533 plots in South Africa’s Kruger National Park.
Grass production increased by 28% over the period.
After accounting for rainfall, temperature, grazing, fire, nitrogen deposition, and species composition shifts, the trend was most consistent with the rise in atmospheric CO₂ (~60 ppm over the interval).
The relative increase was greatest at the driest sites, matching experimental patterns.
Part of the biomass gain was linked to a shift toward taller, more productive grass species, but CO₂ remained the dominant explanatory factor.

Modeling with the Community Land Model (CLM)

Simulations indicate that CO₂ fertilization of C₄ grass aboveground productivity is likely to continue through the 21st century.
Higher temperatures and reduced rainfall weaken but do not eliminate the positive effect.

The study estimates a CO₂-driven increase of approximately 75.1 g m⁻² (95% CI 74.5–75.8 g m⁻²), or 0.37 tons C ha⁻¹, of annual aboveground production in the Kruger data.

Savannas cover roughly one-fifth of Earth’s land surface and contribute ~30% of global terrestrial net primary production, so even modest fertilization effects can have large aggregate impacts.

Implications

Ecosystem function: Greater grass biomass can increase fuel loads (altering fire regimes), change forage availability for wildlife and livestock, and shift competitive dynamics with trees.
Carbon cycle: Extra grass production does not automatically translate into long-term carbon sequestration; much of the biomass may be consumed by herbivores or burned, returning carbon to the atmosphere.
Future trajectories: Direct CO₂ effects must be considered alongside changes in temperature and rainfall when forecasting savanna responses. The work highlights that C₄ grasses are more responsive to rising CO₂ than previously assumed, especially via improved water-use efficiency under drought.

In short, rising CO₂ is already fertilizing wild C₄ grass production in water-limited African savannas through enhanced water conservation and sustained photosynthesis, with evidence from controlled experiments, multi-decadal field data, and modeling all converging on the same conclusion.

Published: Nature

DOI: 10.1038/s41586-026-10935-4

Provided: University of Sheffield

Authors: Kimberley J. Simpson,
A. Carla Staver,
James A. King,
William J. Bond,
Corli Coetsee,
Nita C. M. Pallett,
Adam F. A. Pellegrini,
Sarah L. Raubenheimer,
Brad S. Ripley,
Maria Val Martin &
Colin P. Osborne

Abstract

Rising atmospheric CO₂ concentrations are impacting the global terrestrial biosphere through indirect climate effects and direct effects on plant performance^1,2,3. In tropical forests, long-term monitoring indicates a substantial CO₂-driven carbon sink⁴. C₄-grass-dominated tropical and subtropical savannas contribute approximately 30% of terrestrial net primary production⁵, and yet equivalent long-term analyses of CO₂ responses are lacking. Here we show a clear and consistent result across a meta-analysis of 70 CO₂-addition experiments and 32 years of in situ field observations from southern Africa: CO₂ fertilization of wild C₄ grasses is widespread in dry conditions. In experiments, grasses reduced stomatal conductance under higher levels of CO₂, limiting water loss while increasing carbon gain. In the field, improved water use efficiency translated into increased C₄ grass biomass production across three decades of observations. Finally, simulations via the Community Land Model⁶ suggest that CO₂ fertilization of C₄ grass aboveground productivity may continue to increase under future conditions. Together, these results challenge the view that C₄ grasses are unresponsive to increasing levels of CO₂, demonstrating instead that annual aboveground production of grasses in the field in southern Africa has increased by 28% over three decades (a CO₂-driven increase of 75.1 g m⁻² (95% confidence interval of 74.5–75.8 g m⁻²) or 0.37 tons C ha⁻¹ of annual production). Although the fate of this carbon is uncertain (depending on feedbacks with fire, herbivory and woody vegetation), effects on the global carbon cycle may be profound.

Trapped Gases in 2-Billion-Year-Old Rocks Point to Local, Not Global, Carbon Anomaly

Around 2.0–2.3 billion years ago, many sedimentary rocks show a large positive excursion in the carbon-isotope ratio of carbonate minerals (the Lomagundi–Jatuli Event or similar anomalies). The conventional interpretation has been that this reflected a global shift—most often attributed to a massive increase in organic-carbon burial, changes in the carbon cycle, or a response to the Great Oxidation Event—implying a planet-wide perturbation that affected seawater chemistry.

Trapped gases (mainly CO₂ and hydrocarbons) preserved in fluid inclusions within ~2-billion-year-old rocks challenge the long-standing idea that a major global carbon-isotope anomaly at that time was driven by a worldwide environmental or biological event.

Recent work on fluid inclusions (tiny pockets of ancient fluids and gases sealed inside minerals) from rocks of that age indicates that the anomalous carbon signatures can instead be produced or strongly modified by local processes. The trapped gases and fluids record high concentrations of CO₂ and organic compounds whose isotopic composition can generate the observed heavy δ¹³C values through local recycling, metamorphism, or interaction with organic matter, without requiring a uniform global ocean chemistry change.

Key implications:

The anomaly may be heterogeneous or at least partly diagenetic/metamorphic rather than a primary seawater signal everywhere it is recorded.
Global models that treat the excursion as a single, synchronous planetary event need revision; some occurrences could be regional or secondary.
Fluid-inclusion data provide direct samples of the ambient fluids and gases at the time of mineral growth or later alteration, offering a more local “snapshot” than bulk-rock carbonate analyses.

This does not eliminate the possibility of large-scale carbon-cycle changes in the Paleoproterozoic, but it shows that trapped gases and local fluid chemistry can produce or overprint the isotopic signal, weakening the case for a purely global explanation based solely on carbonate δ¹³C. Ongoing work continues to test how widespread these local effects are versus any true global component.

Gathering detailed geological information on the Zaonega Formation.

Zaonega Formation (also called Zaonezhskaya Formation) is a major Paleoproterozoic volcano-sedimentary unit in the Onega Basin (Onega structure/synclinorium), northwestern Russia (Karelia), on the southeastern margin of the Fennoscandian (Baltic) Shield and the Karelian craton.

Location and regional setting

Exposed mainly along the northern shores of Lake Onega (around the Zaonezhye Peninsula and Shunga area).
Part of a ~40,000 km² Paleoproterozoic basin that unconformably overlies Archean granite-gneiss basement.
Formed in a rift-related setting on the continental margin during opening of the Svecofennian Ocean.
The broader Onega succession spans roughly 2.44–1.89 Ga and was deformed into open folds with high-angle faults, then regionally metamorphosed to greenschist facies during the Svecofennian orogeny (~1.89–1.79 Ga).

Age constraints

Deposition is tightly constrained to the mid-Paleoproterozoic (Ludicovian Superhorizon), broadly ~2.0 Ga (commonly cited as ~1.98–2.05 Ga), shortly after or overlapping the end of the Lomagundi–Jatuli Event:

Maximum age: Pb–Pb on underlying Tulomozero Formation dolostones (~2.09 ± 0.07 Ga); possible links to earlier rifting (~2.10–2.14 Ga).
Key internal ages: U–Pb zircon from a tuff in the lower part ~1982 ± 4.5 Ma; Re–Os on organic matter ~2.05 Ga.
Minimum ages: Overlying Suisari (Suisar) Formation volcanics and Konchezero sill (~1.97–1.99 Ga range from Sm–Nd, Re–Os, and recent U–Pb zircon data); cross-cutting dikes/sills ~1.92–1.96 Ga.
Recent work continues to refine the exact limits relative to the Shunga Event (the associated organic-carbon and isotope anomaly).

Thickness and areal extent

Up to ~1,300–1,500 m thick.
Covers several thousand km² within the basin (estimates around 9,000 km² for key exposures).

Lithology and stratigraphy

The formation is a mixed siliciclastic–carbonate–volcanic succession with exceptionally high organic-carbon content (locally up to 60–75 wt% TOC in “shungite” or maksovite intervals—highly carbonaceous rocks).

Main rock types include:

Organic-rich mudstones/shales, siltstones, greywackes, and turbidites.
Dolostones, limestones, and cherts (more abundant in lower and upper parts).
Mafic tuffs, lava flows (basalts), and numerous gabbroic/dolerite sills with peperitic contacts (indicating intrusion into wet, unlithified sediments).
High-silica (chemogenic?) rocks and phosphatic horizons in places.

It is commonly subdivided into members or intervals (e.g., from FAR-DEEP cores 12AB/13A and OnZap cores): lower parts richer in organic mudstones; upward increase in carbonate; interlayered volcanic units throughout. It records the transition from the Lomagundi–Jatuli positive carbonate-carbon isotope excursion into the Shunga Event (strong organic-carbon accumulation and ¹³C-depleted organic matter).

Depositional environment

Predominantly deep-water (below storm-wave base) shelf–slope–basin or restricted-basin setting.
Mixed siliciclastic–carbonate system with hemipelagic mudstones, turbidity currents, and occasional debris flows.
Influenced by hydrothermal vents/seeps and high biological productivity under fluctuating redox conditions (mostly anoxic, with periodic oxygenation).
Evidence for methanotrophy, sulfate reduction, and early phosphogenesis.
Coeval mafic magmatism created local heat, hydrothermal circulation, and thermogenic hydrocarbon generation/migration (one of Earth’s oldest known petroleum systems, sometimes compared to a “supergiant” oil field that is now “petrified”).

Magmatism and alteration

Abundant syn-sedimentary to early post-sedimentary mafic volcanism and intrusive activity (N-MORB-like affinities in places, linked to continental rifting and possible plume influence).
Magmatic heating drove contact metamorphism, oil/gas generation, hydrocarbon migration (including seafloor seeps and asphalt spills), and hydrothermal alteration.
Later regional greenschist-facies metamorphism overprinted the succession.

Significance

The Zaonega Formation is a key archive for post-Great Oxidation Event Earth-system changes, including carbon-cycle perturbations (Shunga–Francevillian anomaly), redox evolution, early petroleum systems, and phosphogenesis.

Recent fluid-inclusion studies of trapped thermogenic hydrocarbons highlight the importance of local basin-scale processes (magma-driven heating + methanotrophy) in generating its distinctive carbon-isotope signals.

Key reference sections come from the FAR-DEEP (International Continental Scientific Drilling Program) cores and later OnZap cores near Shunga.

_____________________________________________________________________________________

Paleoproterozoic thermogenic hydrocarbon generation, Zaonega Formation, Russia

Paper: Paleoproterozoic thermogenic hydrocarbon generation, Zaonega Formation, Russia

DOI: 10.1130/g54338.1

Journal: Geology (Geological Society of America)

Provided: California Institute of Technology

Authors: Nivedita Thiagarajan (Caltech);

Aivo Lepland (Geological Survey of Norway);

Florian Eichinger (Hydroisotop GmbH);

Anthony Prave (University of St. Andrews;

John Eiler (Caltech)

The study examines gases (primarily hydrocarbons such as methane and propane) trapped in microscopic fluid inclusions within pyrobitumen-rich rocks of the ~2.0 Ga Zaonega Formation (Onega Basin, Karelia, Russia)—one of the world’s oldest known fossil oil fields.

These rocks record an unusual carbon-isotope anomaly (part of the Shunga–Francevillian event) that has commonly been interpreted as evidence of a global perturbation of the carbon cycle following the Great Oxidation Event.

Using molecular and isotopic compositions of the trapped gases, the authors reconstruct a local thermogenic hydrocarbon-generation process driven by magmatic heating:

A sheet of magma intruded organic-rich marine sediments.
This created a strong temperature gradient (≈350 °C near the intrusion to ≈72 °C at an ancient seafloor asphalt spill ~300 m higher).
The heating thermally matured organic matter, generating thermogenic hydrocarbons (methane, propane, etc.).
These hydrocarbons migrated upward and fueled methanotrophic microbes near the seafloor, producing biomass with a strongly ¹³C-depleted (light) carbon-isotope signature.

This local geological–biological chain fully accounts for the anomalous carbon-isotope signal recorded at the Zaonega site.

The authors note that the same isotopic and molecular signatures seen in modern oil-and-gas basins are preserved in these 2-billion-year-old samples.

Because the Zaonega Formation is a key reference locality for the Shunga–Francevillian carbon-isotope anomaly, the results challenge the interpretation that the anomaly necessarily records a worldwide environmental or carbon-cycle event.

The data favor a predominantly local (basin-scale) driver, although contributions from other processes cannot be entirely ruled out.

The team plans comparable fluid-inclusion work on correlative rocks from the Francevillian Basin (Gabon) to test whether the same local mechanisms apply there.

This paper directly underpins recent reports that trapped gases in ancient rocks challenge a purely global explanation for the ~2-billion-year-old carbon anomaly.

Bovaer Bovine Stupidity

Late last year, Arla Foods began a trial of Bovaer in 30 farms across the country. At the time, according to BBC Very Iffy, the company claimed the additive could reduce methane emissions from cows by 30-45%. News of the trial caused consternation among some and led to a boycott of some Arla products. The manufacturer of Bovaer, DSM-Firmenich said these people were the subject of mistruths and misinformation and the product was “totally safe” for use.

An animated cartoon depiction of a cow lying on its back with its eyes closed, tongue sticking out, and green gas emissions around it, suggesting a humorous take on cow health and methane emissions.

From The Daily Sceptic

By David Turver

Meanwhile, Bovaer was mandated to use across Denmark in early October this year and there have been many reports that the additive is damaging to livestock, prompting an investigation by the Danish government. By pure coincidence, Arla announced in early November it had stopped the British trial and was evaluating the results.

How did we get into this position of endemic bovine stupidity? Let’s dig in.

Net Zero Emissions

At root, this whole controversy is a story about Net Zero. The climate alarmists are concerned that methane concentrations in the atmosphere measured in parts per billion are having a devastating effect on the climate. This prompted organisations like UK FIRES to call for beef and lamb consumption to fall by 50% by 2030 and be eliminated altogether by 2050.

In its Seventh Carbon Budget the Climate Change Committee (CCC) was less draconian, calling for a 25% reduction in overall meat consumption by 2040 and 35% by 2050 compared to 2019 levels. Within this, it expects a steeper 40% reduction in red meat by 2050. CB7 also calls for a 27% reduction in the number of cattle and sheep by 2040 and a 38% reduction by 2050. It calls for these reductions even while noting that methane emissions “are already 62% lower than they were in 1990”.

Carbon Cycle

The alarmist narrative is driven by a misunderstanding of the carbon cycle. Cows and other ruminants have roamed the earth for thousands of years. For instance, there were about 60 million bison in North America in the 18th century, compared to about 87 million cattle in the US at the beginning of 2024. Somehow these bison did not manage to cause runaway global warming.

This is because of the cattle grazing carbon cycle (see Figure 1).

Illustration of the cattle-grazing carbon cycle, showing the processes of methane degradation, photosynthesis, animal emissions, soil and plant emissions, and carbon sequestration. — Figure 1. Cattle Grazing Methane Carbon Dioxide Cycle

Cows eat grass and methane released from cow belches and rotting manure is released into the atmosphere. The methane oxidises to CO₂ quite quickly and then is reabsorbed by grass through photosynthesis. The grass grows and stores the carbon in its leaves and root systems. The cows then eat the grass and the cycle begins again.

Although methane is emitted during the cycle, it is then reabsorbed, so the net effect on the climate is negligible.

Impact of Methane in the Atmosphere

In addition, the concern about methane in the atmosphere is overblown (see Figure 2).

Diagram illustrating the interaction of solar radiation with the Earth's atmosphere, showing energy intensity, wavelength, and atmospheric absorption components including water vapor, carbon dioxide, oxygen, ozone, methane, and nitrogen oxides. — Figure 2. Methane Absorption Frequencies

As can be seen, the absorption frequencies of methane are almost entirely covered by the absorption frequencies of water vapour. The average concentration of water vapour in the atmosphere is about 0.25%, or about 2,500 parts per million. By contrast, methane concentration is about 1,900 parts per billion, or more than three orders of magnitude lower than water vapour. The idea that a change in methane concentration will have an impact on climate when its absorption frequencies are already saturated by water vapour is absurd.

Bovaer Impact on Cows

Now we turn to the impact of Bovaer on livestock. Back in 2024, the Danish Centre for Food and Agriculture produced a paper setting out the impact of Bovaer on methane emissions and milk productivity.

The paper documented five experiments on Danish cow herds. The reporting of the results is not quite consistent, with some focusing just on methane reduction and others also including the impact on Energy Corrected Milk Yield (ECM) (see Figure 3).

Table summarizing the impact of Bovaer on methane emissions and Energy Corrected Milk Yield from various experiments. — Figure 3. Impact of Bovaer on Methane Emissions and Energy Corrected Milk Yield

Both Johnson experiments showed reductions in methane emissions of about a third, with corresponding reductions in ECM of a similar magnitude. The Kjeldsen experiment reduced methane emissions by nearly a quarter but was silent on the impact on milk yields. The first Maigaard paper showed an 18-23% reduction in methane emissions and simply recorded an unquantified negative impact on milk yields. The second Maigaard paper showed a reduction of between 31% and 34% in methane yield and zero to 5% reduction in ECM depending upon Bovaer dosage. It is noteworthy that none of the experiments got anywhere near the high-end 45% reduction in methane emissions claimed by DSM-Firmenich.

Another meta-study by Pupo et al. concluded that 3-nitrooxypropanol (3-NOP), the active ingredient of Bovaer, reduced methane emissions by 27.9% but a dairy with 1,000 cows would need to be compensated by $128,320 per year to cover the cost of the additive and loss of milk yield.

We can only wonder at the bovine stupidity that would mandate the introduction of an additive that reduces milk yields almost as much as emissions. To get the same output, we would need more cows and have almost the same total emissions, but of course at much greater cost.

Bovaer Safety Data Sheet

The Safety Data Sheet (SDS) for Bovaer leads to additional concerns. It shows Bovaer causes serious eye damage, skin irritation and is suspected of damaging fertility. If the product gets in the eyes, users are recommended to immediately call a Poison Centre and rinse with water for several minutes.

This calls into question DSM-Firmenich’s claim that Bovaer is “totally safe” to use.

The Danish Experience

The Farmers Guardian has reported health issues in Danish cows being fed with Bovaer. The Danish Government made the feeding of Bovaer in herds of over 50 cows compulsory on October 1st 2025. On these farms, Bovaer must be added to the cow’s ration for at least 80 days a year. Farmers have said that their cows have suffered from issues including fever and diarrhoea, fertility performance has been impacted and in some instances farmers have reported cows have collapsed and died. Maybe the suspicion of fertility issues in the SDS can soon be confirmed as fact.

A farmer described Bovaer as a poison, noting an explosion in digital dermatitis and higher somatic cell counts. Higher somatic cell counts indicate lower milk quality and suggest udder infection. When he stopped adding Bovaer to their feed, cow health showed huge signs of improvement and somatic cell count fell by 20% two days later.

Danish farmer Kent Nielsen took to X with a video complaining that since started feeding his cows with Bovaer on October 1st his cows have suffered from diarrhoea, gut paralysis and milk fever. He also reported losing 3kg of milk per cow. He has since stopped administering Bovaer after consulting a vet.

The fifth farmer Kent Davidsen from Denmark, has now come forward and talks about sick and dead cows, due to the use of Bovaerpoison. He urges other farmers to stop using Bovaer and his vet agrees with him.

Please share this and help us stop the madnees🐄🇩🇰

Kent Nielsen 11/8 25 pic.twitter.com/bJEqODurML
— Kent Nielsen Denmark (@Kentfrihedniels) November 8, 2025

Mr Neilsen’s profile on X also documents many instances of what he terms “Bovaerpoison” on other farms, including the death of calves.

Who could have guessed that messing with the digestive processes of cattle would impact their health?

Conclusions

The climate alarmists have made no secret of the fact they want to reduce meat consumption and cull our livestock herds. They have a mistaken belief that methane emissions from cows are damaging the climate, without considering full carbon cycle of ruminant herds.

The mad rush to Net Zero has caused an outbreak of bovine stupidity amongst our ruling classes. They have come up with Bovaer as a dangerous solution that cuts yields as well as emissions to a non-existent problem of cow flatulence. It is hardly surprising that tampering with the digestive processes of cows would harm their health. Some say that the purpose of a system is what it does, so maybe they see the imposition of Bovaer as an easy way to reduce the number of cows on farms. In effect, we must sacrifice the cows to appease the weather gods. We can only hope that Arla does the right thing and decides not to extend the Bovaer trial into the wider farming community.

David Turver writes the Eigen Values Substack page, where this article first appeared.

Guardian: “A climate of unparalleled malevolence”: are we on our way to the sixth major mass extinction?

Apparently, our pitiful atmospheric contribution is comparable to the 2-million-year eruption which drove the Permian–Triassic Extinction, which wiped out most life on Earth.

An eruption of a volcano spewing lava and ash, with a barren landscape and small animals in the foreground.

From Watts Up With That?

Essay by Eric Worrall

A graph depicting atmospheric CO2 levels over geological time, highlighting the transitions between greenhouse and icehouse climates, with models and proxies for carbon dioxide levels. — Fig. 1. Phanerozoic time scale, greenhouse vs. icehouse conditions and three models for atmospheric CO2. Source:
User-friendly carbon-cycle modelling and aspects of Phanerozoic climate change

Apparently, our pitiful atmospheric contribution is comparable to the 2-million-year eruption which drove the Permian–Triassic Extinction, which wiped out most life on Earth.

‘A climate of unparalleled malevolence’: are we on our way to the sixth major mass extinction?

Churning quantities of carbon dioxide into the atmosphere at the rate we are going could lead the planet to another Great Dying

By Peter Brannen
Tue 19 Aug 2025 14.01 AESTLast modified on Tue 19 Aug 2025 14.20 AEST

…

Put enough CO2 into the system all at once, and push the life-sustaining carbon cycle far enough out of equilibrium, and it might escape into a sort of planetary failure mode, where processes intrinsic to the Earth itself take over, acting as positive feedback to release dramatically more carbon into the system. This subsequent release of carbon would send the planet off on a devastating 100-millennia excursion before regaining its composure. And it wouldn’t matter if CO2 were higher or lower than it is today, or whether the Earth was warmer or cooler as a result. It’s the rate of change in CO2 that gets you to Armageddon.

…

Here’s a plausible sequence of events at the end of the Permian. First, and most simply: the excess CO2 trapped more energy from the sun on the surface of our planet – a simple physical process that was worked out by physicists more than 150 years ago. And so the world helplessly warmed – models and proxies both point to about 10C of warming over thousands of years – pushing animal and plant physiology alike to their limits. It’s also a simple physical fact about our world that for every degree it warms, the atmosphere can hold about 7% more water, so, as the temperature climbed and the water cycle accelerated, storms began to take on a menacing, drowning intensity. As the ocean warms as well, it holds less oxygen.

…

Now let’s pull back from the brink. However similar to this era our modern experiment on the planet might first appear, it’s worth acknowledging, even stressing, that the end-Permian climate catastrophe was truly, surpassingly bad. And on a scale unlikely ever to be matched by humans. Upper estimates for how much carbon dioxide the fossil-fuel-burning Siberian Traps erupted, ranging up to 120,000 gigatons, defy belief. Even lower estimates, of say 30,000 gigatons, constitute volumes of CO2 so completely ridiculous that matching it would require humans to not only burn all the fossil fuel reserves in the world, but then keep putting ever more carbon into the atmosphere for thousands of years. Perhaps by burning limestone for fun on an industrial scale for generations, even as the biosphere disintegrates. As it is, industrial civilisation could theoretically generate about 18,000 gigatons of CO2 if the entire world pulled together on a nihilistic, multicentennial, international effort to burn all the accessible fossil fuels on Earth.

…Read more:

https://www.theguardian.com/environment/2025/aug/19/a-climate-of-unparalleled-malevolence-are-we-on-our-way-to-the-sixth-major-mass-extinction

Back in the real world, the Earth is still locked in a brutal Late Cenozoic Ice Age, which started 34 million years ago, yet still threatens to crush our civilisation under mile high walls of ice – so we have plenty of buffer between us and any kind of geologically significant global warming event.

Life has thrived under far higher CO2 levels than today. The graphic at the top of this page came from User-friendly carbon-cycle modelling and aspects of Phanerozoic climate change. During the late Carboniferous for example, CO2 levels were likely far higher than today, but despite elevated CO2 the Earth still experienced icehouse conditions, similar to today’s ice age cycle. So clearly CO2 isn’t the only factor driving climatic conditions.

The ice age of the last 34 million years is a lot of ice age. Clearly something more powerful than CO2 is keeping our planet locked in the ice box. It is likely industrial CO2 emissions will fail to overcome today’s geological ice box forcings, just as much higher CO2 levels failed to overcome the powerful geological ice box forcings which created the Late Paleozoic icehouse during the Carboniferous.

Even if I’m wrong, and substantial warming does occur, we have strong evidence humans would thrive in such conditions. Our monkey ancestors made their debut in the fossil record during much warmer conditions than today. The Palaeocene-Eocene Thermal Maximum, 5-8C hotter than today, was the age of monkeys. Our monkey ancestors thrived on the abundance of the hothouse PETM, and colonised much of the world, only retreating when the cold returned. If a bunch of monkey ancestors with brains the size of matchboxes could thrive in a much world, then we humans certainly could – which gives us at least a 5-8C buffer of safety against any imaginable global warming event.

Fish also did well during the PETM – so it’s not just humans who would thrive in such warm conditions.

Study: Ancient Fish Thrived During PETM Extreme Global Warming

Given the remarkable stability of the Earth’s climate on geological timescales, the fact the Earth is still locked in an ice age, the benign conditions which prevailed in previous much warmer ages, and the existence of previous ice age epochs with far higher CO2 levels than today, those who focus on the carbon cycle alone are overlooking some pretty important evidence. Given all this, I believe we can reasonably conclude claims that industrial emissions are creating a man-made Permian Extinction are an absurd fantasy.

Settled Science Springs a Leak: Rivers Reveal the Carbon Cycle’s Dirty Secret

Let that sink in. Climate models and carbon budgets, paraded as settled science by every bureaucrat, green politician, and eco-apocalyptic influencer on Earth, have been built on the foundational assumption that riverine CO2 is part of a contemporary, short-term biosphere loop. Turns out, they’ve been routing old ghosts through a new story.

From Watts Up With That?

By Charles Rotter

Abstract

Rivers and streams are an important pathway in the global carbon cycle, releasing carbon dioxide (CO₂) and methane (CH₄) from their water surfaces to the atmosphere^1,2. Until now, CO₂ and CH₄ emitted from rivers were thought to be predominantly derived from recent (sub-decadal) biomass production and, thus, part of ecosystem respiration^3,4,5,6. Here we combine new and published measurements to create a global database of the radiocarbon content of river dissolved inorganic carbon (DIC), CO₂ and CH₄. Isotopic mass balance of our database suggests that 59 ± 17% of global river CO₂ emissions are derived from old carbon (millennial or older), the release of which is linked to river catchment lithology and biome. This previously unrecognized release of old, pre-industrial-aged carbon to the atmosphere from long-term soil, sediment and geologic carbon stores through lateral hydrological routing equates to 1.2 ± 0.3 Pg C year⁻¹, similar in magnitude to terrestrial net ecosystem exchange. A consequence of this flux is a greater than expected net loss of carbon from aged organic matter stores on land. This requires a reassessment of the fate of anthropogenic carbon in terrestrial systems and in global carbon cycle budgets and models.

The recent Nature study titled “Old carbon routed from land to the atmosphere by global river systems” is not only a rigorous piece of scientific work—it’s also a spectacular indictment of the so-called “settled science” of climate change. This 2025 paper is a flaming arrow into the heart of carbon cycle certainty, unearthing yet another inconvenient truth: over half of the CO2 emitted from rivers comes from carbon sources that are hundreds to thousands of years old—not from recent fossil fuel emissions or current biological activity.

According to the authors:

“The largest proportion (52 ± 16%) of river CO2 emissions is sourced from millennial-aged carbon…” and “7 ± 1%…from petrogenic carbon” .

That’s right. Over half of these emissions are from old carbon stores—carbon that, until now, was presumed stable, buried, and irrelevant to modern emission tallies. In other words, nature has its own deeply entrenched carbon leaks, and our modern instruments are just now getting around to noticing them.

The implications are vast and devastating—to the credibility of those who have weaponized science to promote radical climate policy. Here are a few of the most laughable consequences of this study for the “settled science” narrative:

1. The Carbon Budget Is a Fantasy

The entire idea of a “carbon budget” depends on the assumption that we can accurately track all natural and anthropogenic carbon sources and sinks. The paper’s authors explicitly state:

“This previously unrecognized release…equates to 1.2 ± 0.3 Pg C yr⁻¹, similar in magnitude to terrestrial net ecosystem exchange”.

Translation: We were missing a carbon leak as big as the net carbon uptake of all land-based ecosystems. That’s like losing a financial ledger entry equivalent to your annual revenue and still claiming your books balance.

2. Climate Models Can’t Model What They Didn’t Know Existed

This isn’t a rounding error. This is a previously invisible carbon flux at a planetary scale—entirely omitted from mainstream Earth system models. The authors even note:

“Current numerical models of river carbon transport and emission also fail to account for inputs from old carbon sources”.

For those of us who have long argued that climate models are glorified curve-fitting exercises based on selectively tuned assumptions, this study is pure vindication. It’s an outright admission that the models are not merely imperfect—they’re structurally blind to major natural processes.

3. Climate Science Is Still in Diapers

If 59% of riverine CO2 emissions come from millennial or older carbon pools, then just how settled can the science be? The authors describe this as a “planetary-scale release” of old carbon and conclude:

“We provide evidence for a previously unrecognized, planetary-scale release of old, pre-industrial-aged carbon from land to the atmosphere through rivers”.

Imagine building a trillion-dollar global policy framework on a dataset that left out half the equation. It would be funny if it weren’t tragic.

4. Anthropogenic Carbon Attribution Is Now a Shell Game

One of the central talking points of climate activists is that CO2 in the atmosphere is traceable and largely caused by human emissions. This study kicks that stool out from under them. After adjusting the models to include this new understanding, the study finds that only:

“41 ± 16% of river CO2 emissions…could contain recent anthropogenic-derived carbon”.

That means nearly 60% of river-based CO2 emissions are from carbon predating modern industrial activity. This calls into question the accuracy of anthropogenic attribution models—models which governments use to justify taxes, regulations, and top-down restructurings of energy and agriculture.

5. So Much for Predicting the Future

The authors admit they don’t know whether the increase in old carbon emissions is from natural variability or anthropogenic disturbance. In their own words:

“Whether or not anthropogenic perturbation has increased the leak of old carbon…remains a notable knowledge gap”.

Yet we’re told with absolute certainty that the Earth will warm by 1.5°C unless we ban gas stoves, eat bugs, and shut down reliable energy. This study exposes just how deeply uncertain and unresolved the feedbacks in the carbon cycle remain.

6. Rivers: Nature’s Carbon Cheaters

The new conceptual model developed in this paper (see Fig. 3b on page 13) is a quiet revolution. It admits that the traditional model of river emissions—where CO2 was thought to be recent and local—is deeply flawed. Instead, rivers act as carbon transport systems, redistributing ancient carbon from soils, rocks, and geologic layers into the atmosphere. That’s not just a different magnitude—it’s an entirely different mechanism.

Existing model in which river CO2 is only derived from young, rapid-cycling carbon (decadal-aged = green); lateral DIC export to the coast is considered a mixture of decadal and petrogenic inputs (grey). By accounting for these river carbon losses, it is estimated that 1.7 Pg C year−1 of anthropogenic carbon emitted to the atmosphere may be accumulating in the rapid-cycling terrestrial carbon pools3; anote that this estimate is based on a lower estimate of vertical river CO2 emissions of 1.51 Pg C year−1. b, revised conceptual model based on the assembled F14C values of river DIC, CO2 and CH4 presented here; millennial carbon inputs are needed from organic matter degradation in soils or river sediments (orange) as well as petrogenic carbon from rock weathering to explain the observed F14C values in our database. This revised conceptual model indicates a loss of carbon from an old (millennial) store on land through vertical river CO2 emissions; a first-order estimate of the impact on the partitioning of carbon in the biosphere and soils is provided (b).

7. Policy Has Left Science Behind

The study’s authors call for a reexamination of the terrestrial carbon sink and the role of rivers, noting:

“This fundamentally changes our inference of where anthropogenic carbon resides within the main Earth system carbon reservoirs”.

But don’t expect the IPCC, Net Zero campaigners, or ESG investors to acknowledge this. Their policy steamrollers are already in motion, powered by inertia and political leverage rather than scientific humility.

This study is a torpedo below the waterline of climate orthodoxy. It makes it painfully clear that we don’t understand the Earth’s carbon system nearly well enough to justify radical economic and societal upheaval. The confidence of climate alarmists—built on the brittle scaffolding of incomplete data and overconfident models—has once again been exposed for what it is: performative certainty.

To call climate science “settled” in the wake of this paper is not just intellectually lazy—it’s laughable. It’s the scientific equivalent of declaring victory halfway through a chess match while ignoring that your queen is missing and half your pawns are spies. The river CO2 study is not a minor correction. It’s a flashing red light that we’re still flying blind.

So, the next time someone tells you the science is settled, ask them if they’ve heard of F¹⁴C. Then sit back and enjoy the silence.

Whose CO₂ is it Anyway? Ocean Fizz or Smokestack Blame

Picture this: it’s a hot day, and you grab a soda can that’s been in the sun. You crack it open—psssht—and CO₂ fizzes out, tickling your nose, maybe spraying your shirt if you’re slow. It’s a tiny chaos, a burst you can’t control. Now imagine that fizz across the ocean’s sun-warmed surface, covering 71% of Earth, bubbling CO₂ into the air we breathe. Wild, right? A bit mad. I reckon it’s a missing piece of the climate puzzle.

From Jennifer Marohasy

By jennifer

The IPCC pins it all on smokestacks—11 billion tonnes of carbon a year from fossil fuels. Even skeptics like the CO₂ Coalition echo this, leaning on guys like Ferdinand Engelbeen who do their maths by the consensus numbers on this issue of CO₂ origins.

But they might have it all back to front and be leaving out ocean chemistry and biology. In fact, I’m convinced they are.

The Keeling Curve—CO₂’s climb from 280 to 420 ppm—carries their blame. But what if the ocean’s fizzing more than they think? Their rock-solid evidence could be mostly myth.

I’ve been digging into this with Ivan Kennedy, my second guest for the webinar series ‘Towards a New Theory of Climate Resilience’. That was back in February and I’m still to process the audio from this discussion.

Instead, my focus has been on writing technical papers. Ivan and I are working through a hypothesis that could perhaps flip the climate script.

Engelbeen claims fossil fuels’ isotopic fingerprint—light ¹²C (isotope C12) dragging the air’s ¹³C-to-¹²C ratio from -6.5‰ (per mille)* to -8.5‰ since 1850—is proof of coal and oil’s guilt. Ocean CO₂, averaging 0‰ from deep waters, should nudge it up—not down. Case closed.

Except. That ¹²C/¹³C tale’s shakier than they admit. What if the ocean’s surface, warmed by the sun, fizzes CO₂ richer in ¹²C than the deep oceans 0‰?

Calcification—limestone forming in seawater—might churn out CO₂ at -10‰ or lower, diluting that delta 13 signal just like fossil fuels. It’s not the deep ocean I’m on about—it’s the top 65 meters, the mixed layer, where sunlight and warmth cause biological action. So much action that it has built the biosphere’s great carbonate deposits, even the White Cliffs of Dover.

Ivan and I talked some of this over—Great Barrier Reef, North Pacific—during our webinar (soon my first podcast—thanks for waiting!). Calcification’s no sleepy trick; it’s a biological buzzsaw—corals, algae, phytoplankton like coccolithophores churning limestone. In summer blooms, they might pump out tonnes of CO₂, light on ¹³C. Our Thermal Acid Calcification (TAC) hypothesis says nature’s pitching in more than you might think.

Ponder this next time you sip a soda: could the ocean be bubbling up a CO₂ twist?

TAC’s perhaps a second plank in my New Theory of Climate Resilience. Subscribe for irregular updates, and to know about next webinars.

In churn and current, me with that silver scuba air tank at the surface above the mixing layer at the Great Barrier Reef. And the top/feature image is of my scuba buddies diving off the edge from Myrmidon Reef that is already at the edge, photographed by underwater photographer, scuba buddy and boat skipper Jenn Mayes.

This is Part 2 of How Climate Works. Part 1 was with Bill Kininmonth. I never properly processed the audio from Part 1, and I accepted the AI summary of our meeting click here.

From a paper by Werner Berner et al. 1980. In Radiocarbon, Vol 22, No.2. pgs. 227-235. Suggesting higher carbon dioxide levels just a few thousand years ago.

************
When we say deep ocean carbon is 0‰ (per mille), we’re talking about its carbon isotope ratio, specifically the δ¹³C value. This is a measure of how much carbon-13 (¹³C) is present relative to carbon-12 (¹²C), compared to a standard reference.

In this case, 0‰ doesn’t mean there’s no carbon-13 in the deep ocean—it means the ratio of ¹³C to ¹²C in deep ocean dissolved inorganic carbon (DIC) is about the same as the standard reference, which is usually the Vienna Pee Dee Belemnite (VPDB). A δ¹³C of 0‰ indicates no enrichment or depletion of ¹³C relative to that standard.

Now, why is deep ocean carbon around 0‰? It’s because the deep ocean is a massive, well-mixed reservoir of carbon that’s been cycled through various processes over long timescales. Surface ocean carbon starts with a δ¹³C of about +1 to +2‰ due to photosynthesis, where phytoplankton preferentially take up ¹²C, leaving the surface water slightly enriched in ¹³C. But as organic matter sinks and decays, it releases carbon back into the deep ocean. This process, along with the mixing of water masses, balances out the isotopic signature. The deep ocean ends up with a δ¹³C close to 0‰ because it reflects a long-term average of all these inputs—biological, physical, and chemical—without much net fractionation.

In terms of carbon-13, this means the deep ocean has a pretty stable and “neutral” amount of ¹³C compared to the global carbon cycle. It’s not heavily skewed like surface waters or organic matter (which can be -20‰ or lower due to that photosynthetic preference for ¹²C). So, a δ¹³C of 0‰ tells us the deep ocean is kind of a baseline, a big pool where carbon isotopes have settled into equilibrium over thousands of years.

New Research Uses Chemistry to Poke Holes in The CO2-Induced Climate Alarm Narrative

Fundamental components of the anthropogenic global warming (AGW) paradigm fail molecular chemistry.

From NoTrickZone

By Kenneth Richard

Fundamental components of the anthropogenic global warming (AGW) paradigm fail molecular chemistry.

According to a new study, the notion that we can and must reduce atmospheric CO2 so as to avoid climate catastrophe (e.g., runaway global warming or ocean acidification) does not withstand probing academic scrutiny.

Carbon Capture and Storage (CCS) is a mitigation strategy proposing to sequester CO2 underground to reduce emissions to “net zero” by 2050. The practice is poised to cost tens of trillions of dollars over the coming decades. New analysis suggests high or ambitious CCS scenarios are presumed to mitigate about half of today’s emissions by 2050. But these economically draconian CCS scenarios are projected to cost US$30 trillion more than those that only mitigate about one-tenth of today’s emissions. Either way, the costs of CCS are astronomical.

But can CCS actually do what is intended and reduce atmospheric CO2 concentrations? Chemistry says no, CCS “will not reduce the atmospheric concentration of CO2 at all.”

“The crux of the issue is that, unlike photosynthesis by plants, perfect sequestration of CO2 will no magically release the O2 that has effectively been ‘sequestered’ in the CO2 and H2O molecules produced by combustion.”

“If the fuel was made of pure carbon, then the net result in the composition of the atmosphere would be a slight reduction in the O2 concentration…and a slight concomitant increase in the CO2 concentration due to the slight shrinking of the denominator.”

Regarding the alarmist “ocean acidification” narrative, the modern trend of rising atmospheric CO2 is assumed to be driving changes in pH levels. However, the chemical basis for this narrative is dubious.

Using the stoichiometric combustion equation, we learn that for every 1 ppm of CO2 increase due to burning fossil fuels, the O2 concentrations decrease by about 2.15 ppm. (For example, over a 20-year period, CO2 increases by 50 ppm as the O2 declines by ~130 ppm.) But this conceptualization engenders fundamental questions for the paradigm that says humans drive changes in the oceans’ pH levels.

“If the reduction in the atmospheric O2 concentration is directly related to the increase of CO2 in the atmosphere, then how can there be enough absorption of CO2 by the oceans to cause ocean acidification, especially since the oceans are highly buffered chemically?”

“If the observed reduction in the atmospheric O2 is accounted for by the observed increase in the atmospheric CO2 concentration, as expected as a result of combustion, then where does the extra CO2 come from that can cause ocean acidification?”

These are just a few of the many other chemistry-based challenges to the AGW narrative described in the paper. It is well worth a read.

Image Source: **Peachey and Maeda, 2024**

Implications of the Linear Carbon Sink Model

An important consequence of the linear sink model needs to be mentioned. When we look again at Figure 1 we clearly see that the large short term variability of the concentration growth is reflected in the sink effect. This variability is removed in the sink model, without changing the trend of the data. Therefore, the reconstructed concentration growth also does not exhibit its original short-term variability; its only “noise” is caused by the anthropogenic emission data.

From Climate Etc.

by Joachim Dengler

This post is the first of two extracts from the paper Improvements and Extension of the Linear Carbon Sink Model.

Introduction – Modelling the Carbon Cycle of the Atmosphere

When a complex system is analyzed, there are two possible approaches. The bottom-up approach investigates the individual components, studies their behavior, creates models of these components, and puts them together, in order to simulate the complex system. The top-down approach looks at the complex system as a whole and studies the way that the system responds to external signals, in the hope to find known patterns that allow conclusions to be drawn about the inner structure.

The relation between anthropogenic carbon emissions, CO₂ concentration, and the carbon cycle has in the past mainly been investigated with the bottom-up approach. The focus of interest are carbon sinks, the processes that reduce the atmospheric CO₂ concentration considerably below the level that would have been reached, if all CO₂ remained in the atmosphere. There are three types of sinks that absorb CO₂ from the atmosphere: physical oceanic absorption, the photosynthesis of land plants, and the photosynthesis of phytoplankton in the oceans. Although the mechanisms of carbon uptake are well understood in principle, there are model assumptions that cause divergent results.

The traditional bottom-up approaches are typically box-models, where the atmosphere, the top layer of the ocean (the mixed layer), the deep ocean, and land vegetation are considered to be boxes of certain sizes and carbon exchange rates between them. These models contain lots of parameters, which characterize the sizes of the boxes and the exchange rate between them. The currently favored model is the Bern box diffusion model, where the deep ocean only communicates by a diffusion process with the mixed layer, slowing down the downwelling carbon sink rate so much, that according to the model 20% of all anthropogenic emissions remain in the atmosphere for more than 1000 years.

I challenge this claim by questioning some of these assumptions. How does the Bern Model explain the high yearly absorption rate of more than 6% of the ¹⁴C from the bomb tests for 30 years after 1963? How does a downwelling diffusion model work, when the CO₂ concentration in the deep ocean is higher than in the top layer? Empirically there is evidence that ocean absorption is still increasing and there is no sign of saturation.

The top-down models in contrast do not typically look at the details of the sink mechanism. On the basis of mass conservation, they measure the actual empirical sink rate as the difference between anthropogenic emissions and the CO₂ concentration growth in the atmosphere, and investigate how this empirical sink rate is related to CO₂ concentration. This is justified with the assumption that all contributing sink effects can be approximated with sufficient accuracy by linear functions of CO₂ concentration.

The Linear Carbon Sink Model

Atmospheric concentration growth is the difference between all emissions and all absorptions – this is the carbon mass balance described by the continuity equation. Emissions are split between known anthropogenic emissions and unknown natural emissions. For simplification, the relatively unknown emissions caused by land use change are included in the unknown natural emissions. This is justified on the basis that the measurement error of land use change emissions is very large anyways, and by transferring a badly known contribution to the unknown contributions, we do not lose important information.

Obviously emissions, absorptions, and concentration must be measured using the same unit. The natural unit for evaluating mass conservation would be Pg (petagram), but atmospheric masses are usually measured as concentration, relative to the total mass of the atmosphere. For emissions and absorption, their masses translate into potential concentration change. Therefore, ppm is used here consequently, where 1 ppm (parts per million) is equivalent to 2.12 PgC (Petagram Carbon).

The difference between the unknown absorptions and the unknown natural emissions is defined as the sink effect during the time interval of typically a year, implying tacitly that the annual net absorptions are larger than the annual net natural emissions. On the other hand, the same sink effect is known from measurements of anthropogenic emissions minus the concentration growth. Together both statements are equivalent to the continuity equation, where annual concentration growth equals all (anthropogenic and natural) annual emissions minus all annual absorptions. This is displayed in Figure 1. The sink effect is modelled linearly with a constant absorption coefficient a expressing the proportionality of the absorptions to CO₂ concentration and a constant n representing the annual natural emissions

Figure 1. The measured yearly sampled time series of anthropogenic emissions and yearly CO2 concentration growth. Both effects are measured in or have been converted to ppm, in order to guarantee comparability. Their difference is the growing carbon sink effect.

The estimated parameters of the least squares fit with annual data from 1959 to 2023 are a=0.0183, n=5.2 ppm. The equilibrium concentration which is reached when anthropogenic emissions are assumed to be zero, is C⁰= n/a = 284 ppm.

When reconstructing or predicting modelled CO2 concentrations, it is carried out by calculating the concentration growth from the mass balance equation and recursively reconstructing the concentration from emissions (equation (6) in the paper).

Figure 2 shows the comparison of the actual measured CO2 concentration with the predicted concentration data 2000–2020, using only data from 1950–1999 for the estimation of the model parameters. This shows the high quality of the prediction based on the linear model, using only data before the prediction time interval for estimating the model parameters. The 95% confidence interval of the prediction error, displayed as the grey shaded area, is extremely small, the actual deviations are much smaller still.

Figure 2. Model estimation with measured data from 1950–1999. The prediction of CO2 concentration is done by using the real emission data and the model. The grey error bar shows the estimated 95% confidence interval based on error propagation of the modelling residual error variance. Direct prediction comparison is possible due to the availability of the actual concentration data from 2000–2020.

Another way of getting a sense for the quality of a model is to compare the model reconstruction with the original data within the range, from which the model was built. Figure 3 displays the comparison of the actual CO2 concentration data with their model reconstruction based on the linear model over the whole time range from 1959 to 2023. Surprisingly, the actual concentration is a bit smaller than the one predicted by the model. This suggests that in the near future no saturation of the sink effect is to be expected.

Figure 3. The measured CO2 concentration (in ppm) is compared with the concentration reconstruction based on the linear model. The parameters of the model are estimated from emission and concentration data of the whole time range from 1959–2023.

Identifying the Inflection Point in the CO₂ Concentration

From a recent publication of the CarbonBrief Project, we know that global emission data have been constant for more than 10 years. For constant emissions the linear sink model implies declining concentration growth, due to increasing sink effect while concentration increases. Figure 4 shows that the measured yearly concentration growth data have an absolute maximum in 2016 and a declining trend afterward. But the concentration growth data, when stripped of short-term effects by means on the linear sink model, have their maximum already in 2013 and are declining since then. This means that the concentration graph has an inflection point in 2013, turning from concave to convex behavior. The effect appears even clearer when emission data are also smoothed. This is a remarkable validation of a model prediction — the fact that atmospheric carbon concentration growth is declining since 2013 has not been published before.

Figure 4. Comparison of the measured atmospheric CO2 concentration growth (in ppm) with the reconstruction of concentration growth by means of the linear sink model from both the original anthropogenic emission data as well as the smoothed anthropogenic emission data.

Figure 4 also explains why the significant Covid-19 related drop in anthropogenic emissions in 2020 did not have any visible effect on concentration growth. The reconstructed “noise-free” concentration growth clearly reflects the drop in emissions. But it so happened that this coincided with a positive spike in the “random” component of the concentration growth originating from natural emissions.

Making Land Use Change Emissions Consistent

When comparing the ex-post prediction in Figure 5 of 2000–2020 concentrations using the linear model with data from 1950–1999, where emissions caused by land use change were included (copied from the previous post), with the new prediction in Figure 2 without explicit land use change emissions, it is obvious that the predictive quality has become considerably better when discarding explicit land use change emission data for estimating the model parameters.

Figure 5. Prediction of 2000–2020 concentration with data from 1950–1999 from previous post. Emissions caused by land use change had been included as anthropogenic emissions. This graph is included for comparison with the better prediction in Figure 2, which does not explicitly include emissions from land use change. The grey area represents the 95% confidence interval of the predicted data.

This does not mean that there are no land use change emissions; it rather means that the best assumption is that they have been constant between 1950 and 2000 and beyond. It is a direct consequence that constant annual land use change emissions are interchangeable with natural emissions, and we are free to interpret a part of the measured natural emissions as land use change emissions.

The most likely annual value of the land use change emissions during this specific time interval can be inferred from the assumption about the equilibrium CO2 concentration by postulating an equilibrium concentration value without land use change emissions, and let land use change account for the difference to the actually measured equilibrium concentration. This obviously assumes that the ocean and land sink mechanisms have remained rather stable over the time of observation.

Let’s postulate that the “real” equilibrium CO2 concentration value should be the same as the preindustrial assumed value of 280 ppm. The estimate of the equilibrium based on anthropogenic emissions is 𝐶⁰=284 ppm. Therefore, we can infer that between 1950 and 2020 the most likely annual value of the Land Use Change emissions LUC is

𝐿𝑈𝐶=((284ppm−280ppm)*0.0183)*2.12 PgC/ppm = 0.15 PgC

The measured data constrain the possible range of the land use change emissions. Increasing their assumed value implies lowering the equilibrium CO2 concentration. With the most likely equilibrium concentration of 280 ppm the best estimate for land use change emissions, they are 0.15 PgC per annum. Obviously changing the assumption of the “real” natural equilibrium value to e.g. 270 ppm, would consequently change the inferred Land Use Change emissions to 0.54 PgC.

The postulated value of land use change emissions may contradict the state-of-the-art literature, depending on the value of the assumed equilibrium concentration. I see, however, no other possibility to reconcile the four constraints of anthropogenic emission measurements, concentration growth measurements, consistent sink coefficient, and equilibrium concentration consistent with preindustrial value of 280 ppm. The satisfied consistency of these constraints is reflected in the quality of prediction, as shown with the ex-post prediction of the 2000–2020 concentration data in Figure 2.

Future Emission Scenarios

To make predictions, assumptions about future CO2 emissions have to be made. Obviously, the standard scenarios of IPCC AR6 are a possible first choice. They have, however, severe handicaps. Originating from the time of exponential emission growth, at least 2 IPCC scenarios (SSP5-8.5 named “Avoid at all costs” and SSP3-7 named “Dangerous”) are so far from reality and even from the availability of fossil fuel resources that it is not meaningful to discuss them. For more than the last 10 years, global emissions have been constant within the range of measurement error. This knowledge is not yet reflected adequately in official emission statistics of the International Energy Agency, but also in these statistics there are no significant global emission changes since 2018.

Therefore, approximately constant emissions are to be considered as the worst-case scenario in the real world. This is slightly above the IPCC scenario SSP2-4.5 named “Middle of the road” during the second half of this century.

At the other end of the scale, the IPCC scenario SSP1-1.9 named “Most optimistic” is equally in denial of reality, because it assumes global emissions will to be cut to zero by 2050. None of the large countries that dominate global emissions has any plans to reduce emissions to zero. Also, SSP1-2.6 named “Next best”, with zero emissions after 2050, ignores industrial transition times, even if there was the political will. Both these scenarios also ignore the stabilizing effect of natural carbon sinks on CO₂ concentration, which is the key message of this post.

Therefore, I want to focus on four scenarios, displayed in Figure 6, which are less restrictive than SSP1-2.6. First, the mentioned worst-case reference scenario with constant future emissions, extrapolating the recent 5 years.

Figure 6. Historical CO2 emissions until 2022 and from 2023 emission scenarios 0%, 0.3%, 1%, and 2% annual emission reductions.

Then, the IEA “Stated Policies” scenario, which is the most likely future emission scenario according to extensive research about existing policy decisions, approximately reducing worldwide carbon emission by 0.3% per annum, strictly speaking after 2040. This, in fact, corresponds closely to the IPCC SSP2-4.5 emission scenario.

A more severe emission reduction scenario would be 1% per annum, reducing worldwide emissions by 50% every 70 years, and finally the most aggressive reduction scenario with 2% reduction per annum, reducing emissions by 50% every 35 years. This comes close to the SSP1-2.6 “Next best” scenario without reducing to zero completely.

The predictions based on the discussed linear carbon sink model for all four scenarios are shown in Figure 7. With the linear carbon sink model, all four emission scenarios will not raise the CO2 concentration beyond 520 ppm, and the three emission reduction scenarios will reach the peak concentration within this century. I do not draw conclusions about consequences for global temperature here, because the difficult question of climate sensitivity is clearly beyond the scope of this post.

Figure 7. Historical CO2 concentration time series until 2022 and from 2023 concentration prediction scenario from linear carbon sink model with 0%, 0.3%, 1%, and 2% annual emission reductions.

For future historians, I include Figure 8, in order to be able to compare the same scenarios with the CO2 concentration predictions after 2022 from the Bern model of the 2013 publication. The IPCC predictions are based on similar models to the Bern model, with comparable outcomes.

Figure 8. Historical CO2 concentration time series, measured in ppm, until 2022 and from 2023 concentration prediction scenario from Bern model with 0%, 0.3%, 1%, and 2% annual emission reductions.

The prediction result of the 1% per annum reduction scenario from the Bern model corresponds to the constant emissions prediction scenario result from the linear sink model, and the 2% per annum reduction scenario from the Bern model corresponds to the 0.3% reduction scenario from the linear sink model. Therefore, the question of which model is correct may greatly affect future policy decisions.

Within the next 10 to 20 years, it will be easier to see which model will come closest to reality.

Conclusions

The linear carbon sink model is primarily a consequence of mass conservation resp. the continuity equation. From measurements we see an increasing sink effect which has been a strict linear function of CO₂ concentration for the last 65 years. When this statistically highly significant model is accepted for the past – where its validity is obvious –, important implications follow.

By removing the “noise” from the CO₂ concentration growth while keeping the trend, the modelled concentration growth data exhibit a clear maximum in 2013 and a declining trend since then. This is fully consistent with the fact that since more than 10 years anthropogenic emissions have been approximately constant. The fact that concentration growth declines when emissions are constant, is a nice validation of the linear carbon sink model.

The linear carbon sink model introduces a strict relation between the measured data, and the model parameter of equilibrium concentration. When the traditional natural equilibrium without anthropogenic emissions of 280 ppm is accepted, then the assumed constant rate of land use change emissions of the last 65 years is restricted to 0.15 PgC per annum.

The linear carbon sink model has proven to be of high predictive value. The concentrations of the years 2000-2020 have been predicted with high accuracy from the 2000-2020 anthropogenic emissions and the model built with the 1950-1999 data.

There is one potential weakness in the linear carbon sink model. The oceanic and photosynthesis sink systems are of finite size, but the model assumes no saturation effect. This contrasts with the box and diffusion models used by other researchers. The Bern model, in particular, claims that the foreseeable capacity of the natural sink systems is effectively only 4 times larger than the atmosphere, with the result, that 20% of all emissions remain in the atmosphere for at least 1000 years. Up to now, not the slightest sign of saturation of the natural sink systems can be detected. We can assume, therefore, that there will be no drastic change of this in the near future.

The simple fact that both models can explain the emission and concentration data of the past very well, makes it necessary to check the deviations in the future. For this purpose, 4 possible emission scenarios have been evaluated by both models, and future researchers and historians will find out which model will have made the better predictions of CO₂ concentrations.

Tag: carbon cycle

Ancient oceans warmed — and fish thrived as carbon export surged

Key background and methods

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Experimental design

Key model results

Overall interpretation from the model

Abstract (summary)

Key context

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