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Jargons from Ecology

Some common ecological terms that i frequently run into in ecology papers followed by links to some relative articles or papers about them. The links are usually top google hits and highly relevant to understanding the jargon it follows. In some cases, the links are results of “midnight caffein driven search rashes” that explain the jargons well, and not always on top of google hits.

  • Polynomial Trend Surface Analysis

(link1) : “A variant form of multiple regression can be used to fit a nonlinear model of an explanatory variable x (or several explanatory variables xj) to a response variable y. ”

  • Hellinger transformation

(link1):”The Hellinger transformation is relativization by row (sample unit) totals, followed by taking the square root of each element in the matrix.”

  • Unimodal relationships

(link1):”a function f(x) is a unimodal function if for some value m, it is monotonically increasing for x ≤ m and monotonically decreasing for x ≥ m.”

(link2):” Although heterogeneity among samples was minimized, we observed the often-reported unimodal relationship between richness and biomass in several habitats and treatments “
  • PCNM(principal coordinates of neighbor matrices )

(link1)”The technique represents the spatial configuration of sample points using principal coordinates of a truncated distance matrix amongst points. The resulting PCNM axes with positive eigenvalues are used as spatial components in variation partitioning, with each axis potentially modelling species clustering at different distances amongst sampling units. ”

(link2)”We need statistical methods to model spatial or temporal structures at all scales. ”

  • Spectral decomposition

(link1): “In broad terms the spectral theorem provides conditions under which an operator or a matrix can be diagonalized (that is, represented as a diagonal matrix in some basis)”

  • Canonical Correspondence Analysis

(link1): “The result is that the axes of the final ordination, rather than simply reflecting the dimensions of the greatest variability in the species data, are a linear combination of the environmental variables and the species data.”

“The choice of environmental variables greatly influences the outcome of CCA and other constrained ordinations.”

“The length of the arrow is proportional to the rate of change, so a long pH arrow indicates a large change and indicates that change in pH is strongly correlated with the ordination axes and thus with the community variation shown by the diagram.”

“In any case, you can always remove superfluous variables if they are confusing or difficult to interpret”

  • Contingency Table

(link1):”A contingency table is a tabular representation of categorical data .”

  • Reciprocal Averaging

link1“it starts from assigning arbitrary numerical scores to one variable values”

  • Unconstrained Methods (Ordination)

(link1): “An unconstrained ordination procedure does not use a priori hypotheses in any way, but reduces dimensions on the basis of some general criterion, such as minimizing residual variance (as in PCA) or minimizing a stress function (NMDS) ”

principal component analysis (PCA), correspondence analysis (CA), metric multidimensional scaling (also called principal coordinate analysis or PCO)and nonmetric multidimensional scaling.

  • Chi-Square distance

(link1)” The first premise of this distance function is that it is calculated on relative counts, and not on the original ones, and the second is that it standardizes by the mean and not by the variance. ”

  • Spatial autocorrelation

 (link1)”locations close to each other exhibit more similar values than those further apart”.

  • Direct gradient analysis

(link1)”new techniques were developed to constrain the ordination according to the table E of explanatory environmental variables (‘‘direct compari- son,’’ ‘‘direct gradient analysis’’; ”

“Technically, direct gradient analysis can be viewed as an extension of multiple regression, which has a single response variable, to the case of a multi-species response table: ”

  • Indirect gradient analysis

(link1)“Historically, ecologists have first used indirect ap- proaches for interpreting the structures of species assemblages (structural information extracted by the eigenanalysis of Y) in relation to environmental vari- ability: site scores along the ordination axes, which are composite indices of species abundances contained in Y, were compared a posteriori to environmental variables (‘‘indirect comparison,’’ ‘‘indirect gradient analysis’’)

  • Constrained ordination (or canonical analysis)

(link1)”concentrates on the eigenanalysis of the fitted community table, allowing the direct analysis of the variation in species abundances explained by the environmental variability. ”

 
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Categories: Ecology
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