Economy and environmental problems in the Mexican coastal states.

AutorBeltran Morales, Luis F.

Abstract: A canonical correspondence analysis (CCA) for environmental and economic variables was performed for 17 Mexican coastal states. The ordination method allowed us to identify three groups, namely hydroelectric energy generation (I), pollution (II) and harbours (III), which were associated to different human activities. Furthermore, CCA is efficient to help us generate hypotheses for future research. It is therefore advised that CCA should be used for routine analyses into economics.

Keywords: Coastal States of Mexico, Canonical Correspondence Analysis, Diversity Index, Economic Development, Environmental Variables.

Resumen: Se realizó un análisis de correspondencia canónica sobre variables ambientales y económicas de 17 estados costeros de México. El método de ordenación nos permitió identificar tres grupos llamados generación de energía hidroeléctrica (I), contaminados (II) y portuarios (III), los cuales se asociaron a diferentes actividades humanas. El análisis de correspondencia canónica es una eficiente herramienta para generar hipótesis en investigaciones futuras y puede ser utilizado en análisis de rutina en economía.

Palabras clave: estados costeros, análisis de correspondencia canónica, índices de diversidad, desarrollo ecónomico, variables ambientales.

JEL Classification: 0, 01, 013, 018.

Introduction

The development of canonical correspondence analysis (CCA) by ter Braak (1986) and its implementation in his computer program Canoco (along with other constrained ordination methods such as redundancy analysis (RDA), detrended canonical correspondence analysis and hybrid methods), have revolutionised quantitative community ecology and related subjects such as limnology. These multivariate techniques incorporate regression and ordination into a single extremely powerful method for multivariate direct gradient analysis called canonical or constrained ordination. Besides these direct gradient analysis techniques, Canoco also allows to perform analysis by which the effects of external variables are removed statistically, the statistical testing of the relationship between response variables (usually species) and environmental variables by means of several different types of Monte Carlo permutation tests, the reconstruction of environmental variables (e.g. lake-water pH or salinity) from biological data (e.g. fossil diatoms), statistical analysis of multivariate data from field experiments, etc.

Canoco has been used for data analysis in many topics such as economy (Beltran et al., 2003), paleolimnology (Garcia et al., 2004; Garcia et al., 2002; Smol et al., 1995), biogeography (Hill, 1991; Birks, 1993), conservation (Brown et al., 1993; Dzwonko, 1993), ecology (Allen & Peet, 1990; Adams et al., 1992; Ainley et al., 1993), landscape ecology (Stewart et al., 1993), management (Best, 1993; Dzwonko, 1993), monitoring (Kremen, 1992; Johnson et al., 1993), remote sensing (Frederiksen & Lawesson, 1992), and many others. Therefore, it represents an important tool to extracting information from multivariate data. This is so especially in ecology where hypotheses are often generated and tested with the aid of Canoco (Farrel et al., 1995). The goal of this paper is to perform CCA, by means of Canoco, to a set of economic information (response variables) and environmental variables as well as the calculation of economic diversity, for the Caribbean and Pacific coasts of Mexico.

Methods

The study area is shown in Figure 3. Information about all coastal states of Mexico was taken from the National Institute of Statistics, Geography and Computer Science of Mexico (INEGI, 1999). Selected variables and states are shown in the symbology of figures 1, 2 and 3. The final data base was a 17 states X 11 economic indicators matrix, and a 17 X 12 environmental variables matrix (number of occurrences 163 and 204, respectively).

[FIGURES 1-3 OMITTED]

CCA was performed with the aid of the computer program Canoco (version 3.21) (ter Braak, 1990). A complete explanation of CCA can be found in ter Braak (1986). Briefly, CCA is an extension of correspondence analysis (CA), an ordination technique of common use in ecology that extracts continuous axes of variation from a number of response variables (usually species). Such ordination axes are interpreted with the help of data or knowledge on environmental variables. This is a...

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