The Gaia Papers: In Search of a Science of Gaia

Description of the Gaia mission spacecraft, instruments, survey and measurement principles Gaia Collaboration, Prusti, T. Gaia Data Release 2: Summary of the contents and survey properties Gaia Collaboration, Brown, A.

• Traitor (Ava Delaney Book 6);
• Submission history.
• To Love, Honor and Cherish!
• Navigation menu!
• Geophysiology, the science of Gaia – James Lovelock.

The astrometric solution Lindegren, L. Processing of the photometric data Riello, M. The photometric content and validation Evans, D. The catalogue of radial velocity standard stars Soubiran, C.

Processing the spectroscopic data Sartoretti, P. Calibration and mitigation of electronic offset effects in Gaia data Hambly, N. Properties and validation of the radial velocities Katz, D. Summary of variability processing and analysis results Holl, B. All-sky classification of high-amplitude pulsating stars Rimoldini, L.

GAIA (journal) - Wikipedia

Rotational modulation in late-type dwarfs Lanzafame, A. The short-timescale variability processing and analysis Roelens, M. First stellar parameters from Apsis Andrae, R. Catalogue validation Arenou, F. Cross-match with external catalogues: Using Gaia parallaxes Luri, X. The media kit with information on the Gaia mission and the contents of Gaia Data Release 2 can be found here.

Astrophysics > Instrumentation and Methods for Astrophysics

You are using an unsupported browser, old browsers can put your security at risk. Please upgrade to a supported browser. OK ESA uses cookies to track visits to our website only, no personal information is collected. By continuing to use the site you are agreeing to our use of cookies. Find out more about our cookie policy. Parallax uncertainties are in the range of up to 0. The corresponding uncertainties in the respective proper motion components are up to 0. The Gaia DR2 parallaxes and proper motions are based only on Gaia data; they do no longer depend on the Tycho-2 Catalogue.

Median radial velocities i. This leads to a full six-parameter solution: The overall precision of the radial velocities at the bright end is in the order of m s -1 while at the faint end the overall precision is approximately 1. An additional set of more than million sources for which a two-parameter solution is available: G magnitudes for more than 1. These passbands are now available for download.

A detailed description is given here. Epoch astrometry for 14, known solar system objects based on more than 1. Subject to limitations see below the effective temperatures T eff for more than million sources brighter than 17 th magnitude with effective temperatures in the range to 10, K. Below an overview of the planned Gaia Data Release 2 in numbers: Percentile All 5-parameter 2-parameter 0.

Gaia source names are therefore constructed as follows: However, the source list for the release is incomplete at the bright end and has an ill-defined faint magnitude limit, which depends on celestial position. The combination of the Gaia scan law coverage and the filtering on data quality done prior to the publication of Gaia DR2 has resulted in regions of the sky with source density fluctuations that reflect the scan law pattern. The completeness near bright sources has improved but is still not perfect. Astrometry Parallax systematics exist depending on celestial position, magnitude, and colour, and are estimated to be below 0.

• La emperatriz de jade (Algaida Literaria - Algaida Narrativa) (Spanish Edition).
• Earth as a superorganism.
• Kyujin Joho Job Offer (Japanese Edition)!
• Alpha - tome 11 - Fucking patriot (French Edition).
• .

The persistence of the disequilibrium, at a steady state, for periods much longer than the residence times of the gases suggests the presence of an active control system regulating atmospheric composition. As we may soon discover, the unregulated injection of methane could be seriously destabilizing. Until the March Chapman Conference on Gaia, Gaia theory had received little or no financial or other support from the scientific establishments. About five scientists worldwide worked on the topic part time.

In such circumstances it was not practical to strive hard to develop tests for the existence or nonexistence of Gaia systems. Inspired by the predictions from the theory, it seemed better to go into the world and collect information. Whether it was right or wrong seemed to matter less than that the quest was objective.

A good example of this was the expedition aboard the research ship Shackleton. Traveling from the United Kingdom to Antarctica and back, the researchers looked for the presence of sulfur and iodine compounds in the ocean and observed how these elements were transferred from the sea to the air and hence back to the land surfaces. This voyage found that the gases dimethyl sulfide, methyl iodide, and carbon disulfide were ubiquitous throughout the ocean environment. It is relevant to note that before the expedition, peer review committees argued that the search for such compounds was pointless.

This was a time when research funds were freely available, yet the expedition was not supported. The fluxes of gases through the present atmosphere compared with the fluxes of the same gases expected for a dead Earth. The vertical scale is in logarithmic decade units of gigamoles per year.

A more practical approach is to make models of Gaia and then see how well these models can be mapped onto the observed systems. But the feedback loops linking life with its environment are so numerous and so intricate that there seems little chance of quantifying or understanding them. Late in it occurred to me to reduce the environment to a single variable temperature and the biota to a single species daisies.

This planet spins like Earth, but its atmosphere has few clouds and a constant low concentration of greenhouse gases. In these circumstances the mean surface temperature is given by the Stefan-Boltzmann expression of the balance between the radiation received from the star and the heat lost by radiation from the planet to space. The albedo of the planet determines its temperature.

Assume that this planet is well seeded with daisies whose growth rate is a simple parabolic function of temperature, that it is well watered, and that nutrients are not limiting. In these circumstances it is easy to predict the area of the planet covered by daisies from a knowledge of the mean surface temperature and equations taken from population biology.

Figure 2a illustrates the evolution of this simple system, according to conventional wisdom, when two differentcolored daisy species are present, one dark and one light. The lower panel illustrates the smooth, monotonic increase of the mean surface temperature as the star increases in luminosity. In Figure 1b the same system is modeled as a closely coupled physiology.

During the first season, dark-colored daisies will be at an advantage, since they will be warmer than the planetary surface. Light-colored daisies will be at a disadvantage, since by reflecting sunlight they will be cooler than the surface. At the end of the season, many more dark daisy seeds will remain in the soil. When the next season begins, dark daisies will be flourishing and soon will be warming not just themselves, but also their locality; as they spread, they warm the region and eventually the whole planet.

The figure illustrates an explosive growth of both temperature and dark daisy population. The spread of dark daisies will eventually be limited by their decline in growth rate at temperatures above As the star evolves, the dark and light daisy populations adjust according to the simple population biology equations of Carter and Prince []. The planetary temperature moves from just above the optimum for daisy growth at low solar luminosity to just below the optimum at high solar luminosity.

Eventually, the output of heat from the star is too great for regulation, and the plants die. Models of the evolution of Daisyworld according a to conventional wisdom and b to geophysiology. The top panels illustrate daisy population in arbitrary units; the bottom panels, temperature in degrees Celsius. Figure 1a illustrates how the physicists and the biologists in complete isolation calculate their view of the evolution of the planet.

According to this conventional wisdom the daisies can only respond or adapt to changes in temperature. When it becomes too hot for comfort, they will die. But in the Gaian Daisyworld Figure 2b the ecosystem can respond by the competitive growth of the dark and light daisies, and it regulates the temperature over a wide range of solar luminosity. The dashed line in the bottom panel in Figure 2a shows how the temperature would rise in a lifeless Daisyworld.

The simple model is a graphic illustration of a geophysiological process. Figure 3 is a model where daisies having a neutral color, that of the bare planetary surface, are included. At low temperatures only dark daisies were fit to grow; at high temperatures only light daisies were fit.

Gaia Data Release 2 (Gaia DR2)

Neutral daisies grew only when there was little need for regulation. An important point here is that Gaia theory and coevolution are not always mutually exclusive. Organisms do not strive ostentatiously to regulate their environment when regulation is not needed. The evolution of the climate on a three-species Daisyworld with dark, neutral, and light daisies present.

By comparison, the dashed line in the bottom panel respresents the temperature evolution in the absence of life. Figure 4 illustrates a model that included 10 different-colored daisy species, their albedos ranging in evenly spaced steps from dark to light. The regulation of the mean surface temperature bottom panel is more accurate than in the two- and three-species models. The middle panel shows the populations of the different-colored daisies, and the top panel indicates the diversity index of the ecosystem as the model evolved. The evolution of the climate on a species Daisyworld. The bottom panel illustrates planetary temperature, where the dashed curve indicates no life present, and the solid curve represents daisies.

The middle panel shows the populations of the 20 different-colored daisies, with the darkest appearing first left and the lightest last right. The top panel illustrates diversity, seen to be maximum when the system temperature is closest to optimum.

The stable coexistence of three or more species in a population biology model is contrary to the experience of modelers in that field of science. Models of the competition of three or more species, like the three-body problem of astrophysics, tend to be unstable and chaotic.

The stability of Daisyworld is even more remarkable, since no attempt was made to linearize the equations used in the model. Not only is the model naturally stable, but it will resist severe perturbations, such as the sudden death of half or more of all the daisies, and then recover homeostasis when the perturbation is removed. The models can include herbivores to graze the daisies and carnivores to cull the grazers, without significant loss of stability. Another scientist like J. Lotka, the father of theoretical ecology. Like Hutton, Lotka saw the science he founded develop in a way that he never expected or intended.

Introduction

The unwise isolation of biology from geology has led population biology into a mathematical cul-de-sac where the phenomena of complex dynamics are investigated, rather than ecology. This fact deserves emphasis. As we proceed we shall see many reasons why we should constantly take in view the evolution, as a whole, of the system organism plus environment. It may appear at first sight as if it should prove a more complicated problem than the consideration of a part only of the system.

But it will become apparent, as we proceed, that the physical laws governing evolution in all probability take on a simpler form when referred to the system as a whole than to any portion thereof. It is not so much the organism or the species that evolves, but the entire system, species plus environment. The two are inseparable. Daisyworld as I have described it is just an invention, a demonstration model used to illustrate how I thought Gaia worked and why foresight and planning need not be invoked to explain automatic regulation.

But as we shall see when the details are fleshed out, it becomes a generality and a theoretical basis for Gaia. I would like to think of it as the kind of model Lotka had in mind but could not develop, because in his day there were no computers to carry out the immense task that the hand calculation of even a simple daisy model requires.

Watson and I [ Watson and Lovelock , ] described the mathematical basis of Daisyworld. But at the time, neither of us realized its unusual properties or the extent to which it is an expression of the general theory of Gaia. The essential mechanism by which homeostasis is maintained is as follows. The Daisyworld thermostat has no set point. Instead, the system always moves to a stable state where the relationships between daisy population and planetary temperature and that between temperature and daisy growth converge. The system seeks the most comfortable state rather like a cat turns and moves before settling.

Inventions often work well but are difficult to explain. Engineers and physiologists have long been aware of the subtleties of feedback. Both positive and negative feedback can lead to stability or instability, depending on the timing of their application.

By contrast, geophysiological models, such as Daisyworld, include feedback, negative and positive, in a coherent manner. As a consequence, the models are robust and stable and will happily accommodate any number of nonlinear equations and still prefer to relate with stable attractors. Figure 5 compares the unstable and chaotic behavior bottom panel of a model of an ecosystem of daisies, rabbits, and foxes according to population biology with the calm stability of the same ecosystem top panel when feedback from the environment is included as in a Daisyworld.

The model in the top diagram included environmental feedback; that in the bottom diagram did not. But what of biogeochemical box models? Are these any more stable? Experience suggests that biogeochemical models are also prone to chaotic behavior and to an unusual sensitivity to the choice of initial conditions. Geophysiology seems to be a way to avoid these distractions. The concluding model is taken from the end of the Archean period when oxygen first began to dominate the chemistry of the atmosphere.

During the long period of the Archean the biosphere was run by bacteria, the primary producers were cyanobacteria, and the oxygen they made was almost entirely used up to oxidize reducing compounds such as ferrous iron and sulfides present in, and continuously released to, the environment. The organic matter of the cyanobacteria was most probably digested by methanogens. In the Archean, cyanobacteria would be like the white daisies of Daisyworld, tending to cool by removing carbon dioxide, and the methanogens would be like the dark daisies, tending to warm by adding methane to the atmosphere.

A geophysiological model constructed this way settles down to a constant climate and bacterial population and sustains an atmosphere where methane is the dominant redox gas and where only traces of oxygen are present. The continuous leak of carbon to the sediments and perhaps also of hydrogen to space would have slowly driven the system toward oxidizing until quite suddenly oxygen would have become the dominant atmospheric gas.

Solid curve The effect of oxygen on the growth of organisms and dashed curve the effect of the presence of organisms on the abundance of oxygen. The point at which the two curves intersect is the level of oxygen at which the system regulates. In this model, as in Daisyworld, a key factor is the function that sets the bounds of the environment for the biota.

The same parabolic relationship between growth and temperature was used as in the daisy models, but in addition, a similar function was introduced for oxygen. Figure 6 shows how the growth of an ecosystem might increase as oxygen rises from zero. Oxygen increases the rate of rock weathering, and hence the supply of nutrients, and also increases the rate of carbon cycling through oxidative metabolism.

Too much oxygen is, however, toxic. The bounds for oxygen in the figure are set by two simple exponential relationships describing nutrition and toxicity. Other bounds, such as those set by the limitations of pH, ionic strength, and the supply of nutrients, could have been included. Hutchinson [] saw the niche as a hypervolume negotiated among the species. In a similar way, I see the physical and chemical bounds to growth form a hypervolume whose surface intersects that of the hypervolume expressing the environmental effects of the species.

The rate of weathering was assumed to be a function of the biomass as well as of the abundance of oxygen and carbon dioxide.