| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 13.8 MB | Adobe PDF |
Authors
Abstract(s)
The evaluation of the environmental status and evolution of an ecosystem is a crucial element to support decision-makers in their management. Such evaluation must incorporate the uncertainty of collected information to allow their objective and binding interpretation. However, up to now, there were no tools for the objective interpretation of environmental monitoring data that consider system heterogeneity and the impact of the sampling strategy in system characterization, making these monitoring inefficient. The main goal of this work was to produce tools, implemented in user-friendly software, for the objective assessment of the status, trends and correlations of relevant parameters of vast environmental areas, to produce biding information for the management of these resources. The Monte Carlo Method simulation of the spatial distribution of studied parameters considering sampling positioning and sample analysis uncertainty, and conservative interpolation of information between sampling points, allowed simulating mean compositional values, trends and correlations with known uncertainty. This tool was applied to study a large estuarine system from the Tagus River and an even larger coastal area from the Portuguese Continental Platform. The developed tool was successfully applied to study nutrients and characteristic oceanographic features in the oceanic area. The tool was developed for areas monitored from up to 100 points using prior information from studied quantities while keeping the studied parameter’s correlation. The application of the developed tools to the above-mentioned systems in different seasonal conditions allowed the objective and metrologically sound evaluation of trends and correlations of studied parameters. This work aims to change the paradigm of probably the most demanding analytical challenge, the monitoring of vast environmental areas, contributing to the objectivity ambitioned for these studies.
Description
Keywords
Sampling uncertainty Monte Carlo simulations Large marine systems Seasonal trends Compositional correlations Incerteza da amostragem Simulações de Monte Carlo Sistemas marinhos vastos Tendências sazonais Correlações composicionais