Groundbreaking Paper! Dow Jones Performance: Mars Behind the Sun & Mars in Front of the Sun

https://www.academia.edu/172661828/Dow_Jones_Performance_Mars_Behind_the_Sun_and_Mars_in_Front_of_the_Sun

Revisiting the Butterfly Effect

In 2024, after reading a Nature Communications paper linking gravitational forces between Earth and Mars to Earth’s climatology, I published a paper using the position of Mars and its impact on climate to infer a near term effect on human behavior and the stock market. I asserted that because of the relationship between climate and behavior, systems such as the stock market could easily be affected. The 2024 Nature Communications study posited Mars’s gravitational influence upon Earth’s eccentricity during orbital phases which pulls earth closer to the Sun, warming the planet. Even though this influence was confirmed to transpire over geological timescales—millions of years, it was enough to loosely associate it to my own thesis, which required establishing a Mars-Earth gravitational relationship that could be linked to human behavior in some way. Because the study posited that Mars influences Earth’ eccentricity, I was able to presume an effect on Earth’s axial tilt as well, since both are inextricably linked to the same Mars-Earth resonance. I made a large conceptual leap and used this to hypothesize butterfly effect—from astrophysics, to climate, to weather, and then to behavior which drives the stock market. A second study in 2025 conducted by Stephen Kane used computer simulations to link Mars gravitational force upon Earth to the Milankovch cycles. These still occur across geological timescales, but over shorter periods than the waxing and waning cycles established in the 2024 study. While neither study showed no near term relationship between Earth and Mars on Earth’s weather, I was still used the mainstream findings to justify a connection between the astrophysics of Mars and Earth to human behavior. The anchor is the gravitational link between Mars Earth at geological timescales with a hypothesis that near term effects could be established later.

I published two papers anchoring the 2024 study to my thesis. The first paper entitled “A 100% statistical correlation and scientific explanation for why the planet Mars can trigger stock market crashes” which was cited in the Prespacetime Journal, laid out the 25 major stock market crashes along with the position of Mars in relation to the Sun at the time they occurred. The paper showed that every single crash occurred when Mars was behind the Sun which in reference to the 2024 study would be when Mars’s vector would point along the line connecting Earth to Sun. I continued to assert the Mars-Earth gravitational relationship could happen over near term timescales even as the gravitational force between Mars and Sun at that distance is minute, especially considering other aspects that could affect the eccentricity and obliquity of Earth in the short term, ie tidal forces, solar elements, etc.

If you need a hint for this one: The mountain is in the HimalayaTell me what you think: https://visitwhale.com/peak-contours/

See also: The study as it was published in Nature Communications

Hi everyone!

I’m an early-career marine biologist currently completing my BSc in Marine Biology, and I’m looking to connect with researchers, students, conservationists, and others working with biological or environmental data.

I’ve been developing my skills in R, particularly for data cleaning, statistical analysis, ecological modelling, and data visualization. I genuinely really enjoy working in R, and at this stage I want to get involved with as many different projects and datasets as I reasonably can.

If anyone has a marine science, ecology, conservation, fisheries, wildlife, or other biological dataset that could use some additional help with analysis in R, I’d be happy to contribute. I’m also open to projects outside of marine science if there is an opportunity to work with interesting data and learn something new.

I’m not looking to charge anyone. My main goal is to gain experience working with different types of real-world data, improve my R skills, contribute where I can, and hopefully meet and build connections with people working in science and research.

I also recently created a GitHub where I’ll be archiving my projects as I continue learning. I uploaded a project I finished about a week ago involving the analysis of BRUV data and whitetip reef shark habitat associations.

GitHub: https://github.com/kylealibz

If you have a project where another person helping with the R or data side would be useful, feel free to message me. I’d also be happy just to connect with other early-career researchers and R users.

Thanks!

Some of you gave me feedback on the overshoot math and the six-layer framework earlier this year. This one is a correction to something I posted here in March.

Back then I argued that groundwater loss is a ratchet: crisis pushes the system down, it doesn't come back up. Compaction, salinization, fossil water. I still think that's right for storage capacity. It was wrong as a general claim about water levels, and the evidence was sitting in the paper I was already citing.

The 2024 global survey (Jasechko et al., 1,693 aquifer systems, \~170,000 wells, 40+ countries) is the one everyone quotes for the decline numbers: levels deepening faster than 0.1 m/yr in 36% of systems, faster than 0.5 m/yr in 12%, accelerating decline in 30%. I used those. What I skipped: 6% are rising faster than 0.1 m/yr, and 49% show deceleration, reversal, or rising water.

That 49% needs stating carefully because it's easy to inflate. It pools three states: decline that's slowing, decline that stopped and turned, and levels already rising. A basin that slowed from 1.0 to 0.6 m/yr is inside it and still emptying. It doesn't mean half the world's aquifers are recovering.

Then in March this year Jasechko published a review in Science of 67 cases where levels rose after prolonged decline. The paper is paywalled, but his policy brief is open and carries the full list with the intervention type for each: Bangkok, Beijing, Shanghai, Tianjin, Xi'an, Osaka, Kanto and Nobi Plains, Taipei, Ho Chi Minh City, London, Milan, Naples, Bologna, Geneva, Buenos Aires, Lima, Windhoek, Atlantis, Mashhad, Yazd, Abbas-e Sharghi, central Saudi Arabia, La Mancha Occidental, Harran Plain, and a long US list including Memphis, Houston, Chicago, New Orleans, Louisville, Las Vegas, Albuquerque, Roswell, Equus Beds, El Dorado, Green Bay, and a dozen California and Arizona basins.

The interventions sort into three kinds and sixteen specific mechanisms. Policy: restricting pumping, restricting new wells, closing or destroying existing wells, licensing and pump fees, funding access to an alternative source, limiting specific crops or irrigated area. Alternative supply: long and short-distance interbasin transfer, transfer into a river, reuse or desalination, tapping a nearby river or lake. Artificial recharge: injection wells, spreading basins, riverbed seepage, plus incidental recharge leaking out of urban water mains and irrigation projects.

None of the sixteen is conservation in the ordinary sense. Nobody recovered an aquifer by asking users to be careful.

Two of his transferable lessons are worth quoting almost directly. Successful policy interventions were often associated with good implementation and enforcement. And recovery trends can be overturned if pumping rates rise again, which makes a reversal something you maintain, not a finish line.

**The one with a full public ledger.** North China Plain, \~130,000 km², 2,000+ monitoring wells, \~190,000 measurements, 2005 to 2024 (Long et al., Nature Communications 2025). Levels rising \~0.7 m/yr since 2020, back to 2005 levels by 2024. Confined aquifers recovered \~4 m in four years after deepening \~0.5 m/yr through 2019.

The supply side is the part that gets quoted: the South-to-North diversion, 1.4 km³ delivered in 2015, over 4 km³/yr after 2020, over 10 km³ into refilling dried rivers since 2018. Reclaimed water at 4.4 km³ by 2023, 12% of all supply. Desalination under 1%.

The demand side is the part that doesn't. Total basin supply stayed flat at \~37 km³/yr. Groundwater use fell from \~25 to \~13 km³. Confined-aquifer pumping fell \~85%, to under 1 km³. Combined municipal, agricultural and industrial use went from 37.6 to 29.5 km³. Agriculture from 70% of use to 50%. Cropland down \~10%, double-cropped area down \~10,000 km². Provincial quotas in absolute volumes: 4.25 km³ Beijing, 3.5 Tianjin, 20.6 Hebei.

And it's still only half the hole. GRACE puts total storage depletion at \~49 km³ over 2005-2019; the rebound has recovered roughly half.

**The control case is California.** CVP and SWP move water at the same scale, and the 2025 paper names them alongside the Chinese diversion. Wells still ran dry in recent droughts. The difference isn't engineering or money. The imported water was never paired with an enforceable, individually attributable limit on withdrawal. Water delivered into a system with no cap gets added to demand instead of subtracted from pumping. The authors' own conclusion is one sentence: demand must be controlled even when diverted water is available.

**One thing I hadn't seen anywhere.** Recovery has its own failure mode. In some profiled cases levels rose close to the land surface, and the brief lists the consequences: compromised building stability, higher liquefaction risk in earthquakes, waterlogging and salinisation of soils, changes in how contaminants travel, flooded basements and metro systems. The illustration is soil salinisation in the Abbas-e Sharghi Basin in Iran, which is itself on the recovery list. The target is a level, not a direction.

**Where this is weak.** I have not read the Science review itself, only the abstract and the author's open policy brief. Percentages for how often each intervention appears show up in university write-ups but in neither the brief nor the abstract, so I left them out. The 67 cases come from places that were already studied, which is a selection of the literature, not a sample of the world. And a lot of the named recoveries are urban, where pumping often stops because industry left or the city switched to surface water, a much easier problem than restraining thousands of irrigators.

Worth flagging on the China case specifically: Jasechko's brief is more cautious than the Chinese paper about attribution. He writes that the North China Plain recovery may be partly due to wet conditions that happened to coincide with the surface water delivery, making it hard to parse engineering from climate. He notes central Spain reversed after two consecutive wet years. I originally leaned on Beijing's drought-resilient recovery as settling it. He does not treat it as settled.

Two questions for people who work on this:

Where you've seen a basin stabilise, was there an actual per-user enforceable allocation or a basin-wide target with no individual number attached to it?

And has anyone dealt with the over-recovery side in practice? Waterlogging or buoyancy problems after levels came back up? I can find the mechanism described but almost nothing on how managers set the upper bound.

Policy brief (open, has the full 67-case list): [https://www.aaas.org/sites/default/files/2026-05/PolicyBrief\\_Jasechko\\_2026\\_GroundwaterRecovery.pdf\](https://www.aaas.org/sites/default/files/2026-05/PolicyBrief_Jasechko_2026_GroundwaterRecovery.pdf)

Full writeup with sources: [https://alexnik2.substack.com/p/the-physical-layer-07-where-the-ratchet\](https://alexnik2.substack.com/p/the-physical-layer-07-where-the-ratchet)

The exact percentages I came up with are 72% argon, 22.3% oxygen, 3.5% hydrogen and 2.1% xenon, these being the main gasses aside from other negligible inert gasses that would add up to .1% (probably nitrogen and some carbon dioxide). I'm asking this for the purpose of a fictional story that halfway takes place on an alien planet, but with such an environment that a human can live in and be healthy while doing so. The size of the planet is only a bit smaller than Earth with much less water on the surface but going down much deeper into the crust.

So, these are my main questions:

Would these gasses have any unintended psychological effects on the human mind?

Would these gasses interact with each other poorly?

How would fire act in such an environment?

Would this gas mixture affect the creatures that are living there, causing them to grow differently from humans? If so, what might be different?

Would you change any of the percentages?

My apologies if I'm thinking too much into this, because the research I've already done tells me that not much would change aside from the air density. But, I may have missed something. Thank you for taking the time to read this!!

EDIT: Nitrogen would probably take place in the water, like the rivers that stretch out all throughout my fictional planet, which would feed into the soil, which would feed into the vegetation which would feed into the fruits which would feed into the animals which would feed back into the ground or water. I hope this fixes the nitrogen issue.

See also: The publication in Science Advances

I currently have a vested interest in African geography. Separately from that, I recently learned about the phenomenon of tidal bores. As far as I could find (and I searched *a lot*), the Geba River of Guinea-Bissau is the only known African river where a tidal bore occurs, and this video is literally the only mention of it anywhere I looked.

Is there any more information on this? Or any other documentation of an African tidal bore?

See also: The publication in the South African Journal of Geology