Causal modelIn the philosophy of science, a causal model (or structural causal model) is a conceptual model that describes the causal mechanisms of a system. Several types of causal notation may be used in the development of a causal model. Causal models can improve study designs by providing clear rules for deciding which independent variables need to be included/controlled for. They can allow some questions to be answered from existing observational data without the need for an interventional study such as a randomized controlled trial.
Particulate inorganic carbonParticulate inorganic carbon (PIC) can be contrasted with dissolved inorganic carbon (DIC), the other form of inorganic carbon found in the ocean. These distinctions are important in chemical oceanography. Particulate inorganic carbon is sometimes called suspended inorganic carbon. In operational terms, it is defined as the inorganic carbon in particulate form that is too large to pass through the filter used to separate dissolved inorganic carbon. Most PIC is calcium carbonate, CaCO3, particularly in the form of calcite, but also in the form of aragonite.
Causal inferenceCausal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. The science of why things occur is called etiology, and can be described using the language of scientific causal notation. Causal inference is said to provide the evidence of causality theorized by causal reasoning.
CausalityCausality (also called causation, or cause and effect) is influence by which one event, process, state, or object (a cause) contributes to the production of another event, process, state, or object (an effect) where the cause is partly responsible for the effect, and the effect is partly dependent on the cause. In general, a process has many causes, which are also said to be causal factors for it, and all lie in its past. An effect can in turn be a cause of, or causal factor for, many other effects, which all lie in its future.
Organic chemistryOrganic chemistry is a subdiscipline within chemistry involving the scientific study of the structure, properties, and reactions of organic compounds and organic materials, i.e., matter in its various forms that contain carbon atoms. Study of structure determines their structural formula. Study of properties includes physical and chemical properties, and evaluation of chemical reactivity to understand their behavior.
Dissolved inorganic carbonDissolved inorganic carbon (DIC) is the sum of the aqueous species of inorganic carbon in a solution. Carbon compounds can be distinguished as either organic or inorganic, and as dissolved or particulate, depending on their composition. Organic carbon forms the backbone of key component of organic compounds such as – proteins, lipids, carbohydrates, and nucleic acids. Inorganic carbon is found primarily in simple compounds such as carbon dioxide, carbonic acid, bicarbonate, and carbonate (CO2, H2CO3, HCO3-, CO32- respectively).
Soil carbonSoil carbon is the solid carbon stored in global soils. This includes both soil organic matter and inorganic carbon as carbonate minerals. It is vital to the soil capacity in our ecosystem. Soil carbon is a carbon sink in regard to the global carbon cycle, playing a role in biogeochemistry, climate change mitigation, and constructing global climate models. Natural variation such as organisms and time has affected the management of carbon in the soils. The major influence has been that of human activities which has caused a massive loss of soil organic carbon.
Oceanic carbon cycleThe oceanic carbon cycle (or marine carbon cycle) is composed of processes that exchange carbon between various pools within the ocean as well as between the atmosphere, Earth interior, and the seafloor. The carbon cycle is a result of many interacting forces across multiple time and space scales that circulates carbon around the planet, ensuring that carbon is available globally.
Carbon groupThe carbon group is a periodic table group consisting of carbon (C), silicon (Si), germanium (Ge), tin (Sn), lead (Pb), and flerovium (Fl). It lies within the p-block. In modern IUPAC notation, it is called group 14. In the field of semiconductor physics, it is still universally called group IV. The group is also known as the tetrels (from the Greek word tetra, which means four), stemming from the Roman numeral IV in the group names, or (not coincidentally) from the fact that these elements have four valence electrons (see below).
Linear regressionIn statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.
