Structural equation modeling as a tool to develop conservation strategies using environmental indicators: The case of the forests of the Magdalena river basin in Mexico City

• Published in: Ecological indicators Vol. 54; pp. 124 - 136
• Main Authors: Santibáñez-Andrade, G., Castillo-Argüero, S., Vega-Peña, E.V., Lindig-Cisneros, R., Zavala-Hurtado, J.A.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2015
• Subjects: Biodiversity; Conservation; Conservation status; Ecological monitoring; Ecosystem management; Ecosystems; Environmental indicators; Indicators; Mathematical analysis; Mathematical models; Pressure-state-response model; Strategy; Structural equation modeling; Temperate forests; Mexico; Mexico, Distrito Federal, Mexico City; Pressure-state-response model; Structural equation modeling; Conservation status; Temperate forests; Ecosystem management; Environmental indicators
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2015.02.022

•Environmental indicators provide a more realistic dimension of conservation degree.•The study area, although it is a periurban forest of Mexico City, seems to be well preserved.•Structural equation modeling is a useful tool for environmental planning. A primarily descriptive approach has been used to develop studies in Mexico that use indicators to incorporate information on the conservation state of ecosystems. Consequently, these studies are not well supported by ecological data, or they lack an analysis of socio-ecological integration, making it difficult to implement the strategies derived from these conservation plans. Structural equations models (SEM) help with the understanding of direct and indirect interactions between variables and, consequently, allow the detection of root causes of change. In this study, a method to integrate indicators in relation to a pressure-state-response model was developed and applied to a forest in Mexico City. We developed the model using 21 environmental units, 17 state indicators of biodiversity (evaluating three aspects of the ecosystem: structure, composition and function), 14 environmental indicators (abiotic variables) and 6 anthropogenic pressure indicators. Subsequently, based on multicollinearity tests, redundant indicators were eliminated. A canonical correspondence analysis was carried out to establish the relationship between different indicators and the possible ecological connections of the SEM. With the previous information, an a priori model of the influence of pressure and environmental indicators on the structure, composition and function of the ecosystem was developed. The SEM results enabled us to evaluate the direct and indirect causes of degradation. Some environmental factors, such as the global site factor, humidity, air temperature, organic matter in the soil, slope, and soil pH, had a greater effect on the structure, composition and function indicators registered in the environmental units of the basin than other factors. The pressure factors that most affected the three aspects of the ecosystem were visitors, rubbish, fire incidence, and human activities. Pressure factors affected composition and structure indicators, though the effect on the function indicators was weak. It is possible to conclude that although the ecosystem appears to be changed by some disturbance factors, these factors have not yet altered the functionality of the ecosystem. Finally, from the model, a set of proposals and strategies for management was developed. These strategies can be used to sustain the biodiversity of each environmental unit.