Abstract
The theory of ecosystem services (ES) needs to be operationalized to contribute to practices leading to sustainable use of ecosystems, which includes solving trade-offs between private and public benefits and incorporating monetary and non-monetary values to help inform decisions. We developed a framework to analyse the impacts of farmers’ management alternatives on Nothofagus antarctica (G. Forst.) Oerst. forest in northern Patagonia, and analysed synergies and trade-offs between private and public benefits based on three conceptual and methodological approaches: a) a state-and-transition model of ecosystem dynamics, and b) indicators of values of ecosystem service benefits based on the cascade model, implemented as c) a decision support tool based on a Bayesian network. We optimized a utility function for short (0-10 yr) and long (70-140 yr) term management decisions (levels of grazing, logging and tree planting) based on monetary and non-monetary indicators of benefits that fulfilled “farmer’s satisfaction” objectives. We then assessed the consequences of these decisions on the fulfilment of public benefits as defined by the National Forest Law when projected into short (0-10 yr), intermediate (10-40 yr) and long (70-140 yr) time horizons. We found that when the short-term decisions are projected into a long-time horizon, they lead to high losses of benefits, mainly linked to “regulating and maintenance” ES. On the other hand, long-term decisions improved the level of benefits in degraded systems but resulted in the degradation of well-preserved forests. The decisions that optimize farmer’s satisfaction did not change with different weights of “farm income” in the utility function, indicating the absence of trade-offs between monetary and non-monetary benefits considered in the utility function. The tool developed helps to show long-term impacts of management, and discloses cause-effect relationships between levels of use and multiple benefits. It can therefore support measures aiming to raise awareness about degradation trends, and improve the functional understanding of the system that can lead to identify solutions for socio-economic and environmental sustainability. https://doi.org/10.25260/EA.17.27.1.1.295
Highlights
Forst.) Oerst. forest in northern Patagonia, and analysed synergies and trade-offs between private and public benefits based on three conceptual and methodological approaches: a) a state-and-transition model of ecosystem dynamics, and b) indicators of values of ecosystem service benefits based on the cascade model, implemented as c) a decision support tool based on a Bayesian network
We assessed the consequences of these decisions on the fulfilment of public benefits as defined by the National Forest Law when projected into short (0-10 yr), intermediate (10-40 yr) and long (70-140 yr) time horizons
We used a systematic approach to identify the most important private and public benefits generated by the system, and their indicators (Table 1, Figure 2) through an expert workshop, following the CICES classification of ecosystem services (ES) (Haines-Young and Potschin 2013)
Summary
We implemented an ID, which provides a graphical representation of the decision problem; it readily allows for Bayesian updating and makes information uncertainty explicit. Following thecascade model’ of ES, the ID was built with nodes representing the structural characteristics of the system (i.e., variables such as herbaceous cover, tree density, mean tree diameter, shrub cover, cane cover, presence of dead wood), which were linked to indicators of ES, and in turn, connected to nodes with indicators. Of benefits (Figures 1 and 2, Table 1, Annex 2). Both economic and non-economic values were attached to benefits. A central element in the ID is the utility function that connects management alternatives to fundamental decision-making objectives, which in our case were based on the value of private (farmer) benefits (Figure 2 and Model parametrization, below). Los valores de las variables de estados se estandarizaron según una escala entre 0 y 1 para poder reportar los resultados en la Tabla 2.
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