Errors and residualsIn statistics and optimization, errors and residuals are two closely related and easily confused measures of the deviation of an observed value of an element of a statistical sample from its "true value" (not necessarily observable). The error of an observation is the deviation of the observed value from the true value of a quantity of interest (for example, a population mean). The residual is the difference between the observed value and the estimated value of the quantity of interest (for example, a sample mean).
Introduced speciesAn introduced species, alien species, exotic species, adventive species, immigrant species, foreign species, non-indigenous species, or non-native species is a species living outside its native distributional range, but which has arrived there by human activity, directly or indirectly, and either deliberately or accidentally. Non-native species can have various effects on the local ecosystem. Introduced species that become established and spread beyond the place of introduction are considered naturalized.
ProtistA protist (ˈproʊtᵻst ) or protoctist is any eukaryotic organism that is not an animal, plant, or fungus. Protists do not form a natural group, or clade, but an artificial grouping of several independent clades that evolved from the last eukaryotic common ancestor. Protists were historically regarded as a separate taxonomic kingdom known as Protista or Protoctista. With the advent of phylogenetic analysis and electron microscopy studies, the use of Protista as a formal taxon was gradually abandoned.
Root-mean-square deviationThe root-mean-square deviation (RMSD) or root-mean-square error (RMSE) is a frequently used measure of the differences between values (sample or population values) predicted by a model or an estimator and the values observed. The RMSD represents the square root of the second sample moment of the differences between predicted values and observed values or the quadratic mean of these differences. These deviations are called residuals when the calculations are performed over the data sample that was used for estimation and are called errors (or prediction errors) when computed out-of-sample.
Mean squared prediction errorIn statistics the mean squared prediction error (MSPE), also known as mean squared error of the predictions, of a smoothing, curve fitting, or regression procedure is the expected value of the squared prediction errors (PE), the square difference between the fitted values implied by the predictive function and the values of the (unobservable) true value g. It is an inverse measure of the explanatory power of and can be used in the process of cross-validation of an estimated model.
Pioneer speciesPioneer species are hardy species that are the first to colonize barren environments or previously biodiverse steady-state ecosystems that have been disrupted, such as by wildfire. Some lichens grow on rocks without soil, so may be among the first of life forms, and break down the rocks into soil for plants. Since some uninhabited land may have thin, poor quality soils with few nutrients, pioneer species are often hardy plants with adaptations such as long roots, root nodes containing nitrogen-fixing bacteria, and leaves that employ transpiration.
Weighted arithmetic meanThe weighted arithmetic mean is similar to an ordinary arithmetic mean (the most common type of average), except that instead of each of the data points contributing equally to the final average, some data points contribute more than others. The notion of weighted mean plays a role in descriptive statistics and also occurs in a more general form in several other areas of mathematics. If all the weights are equal, then the weighted mean is the same as the arithmetic mean.
Invasive speciesAn invasive or alien species is an introduced species to an environment that becomes overpopulated and harms its new environment. Invasive species adversely affect habitats and bioregions, causing ecological, environmental, and/or economic damage. The term can also be used for native species that become harmful to their native environment after human alterations to its food web - for example, the purple sea urchin (Strongylocentrotus purpuratus) which has decimated kelp forests along the northern California coast due to overharvesting of its natural predator, the California sea otter (Enhydra lutris).
Peat swamp forestPeat swamp forests are tropical moist forests where waterlogged soil prevents dead leaves and wood from fully decomposing. Over time, this creates a thick layer of acidic peat. Large areas of these forests are being logged at high rates. Peat swamp forests are typically surrounded by lowland rain forests on better-drained soils, and by brackish or salt-water mangrove forests near the coast. Tropical peatlands, which coexist with swamp forests within the tropical and subtropical moist broadleaf forests biome, store and accumulate vast amounts of carbon as soil organic matter - much more than natural forests contain.
Ordination (statistics)Ordination or gradient analysis, in multivariate analysis, is a method complementary to data clustering, and used mainly in exploratory data analysis (rather than in hypothesis testing). In contrast to cluster analysis, ordination orders quantities in a (usually lower-dimensional) latent space. In the ordination space, quantities that are near each other share attributes (i.e., are similar to some degree), and dissimilar objects are farther from each other.
