Abstract
The national literature on forest ecosystem valuation is scarce and little is known about how important the valuation of forest ecosystem services and their internalization in low density regions of Portugal are. Hence, there is a need for technicians, academics, and researchers to mitigate this knowledge gap through further research in this area. The chapter is a literature review with the objective of systematizing and synthesizing the knowledge produced in the period between 1992 and 2021 with regard to estimates of the economic value of forest ecosystem services in Portugal as well as finding evidence that relates the mechanisms of internalization of externalities in the sustainable development of low-density regions. A meta-regression was estimated, and the results indicate 220 international dollar/hectare/year in 2019 (190 euros/hectare/year) for forest ecosystem services in Portugal. Payment mechanisms for non-market forest ecosystem are still at an embryonic stage, which does not allow an accurate measurement of their real contribution to the sustainability of low-density regions.
TopIntroduction
As the main land use in Portugal, the forest has the potential to tackle the sustainable transition challenge if we take into account the sustainable management of forestry goods and services and the probability of population settlement and valorisation of territories with forestry production. The present book chapter explores the recent research trends and dynamics on the economic valuation of Forest Ecosystem Services (FES) in Portugal to deliver clear guidelines to decision-makers and minimise the knowledge gap identified in previous research related to the scarcity of the national literature on forest ecosystem valuation. Portugal is a country where numerous regions are considered low-density regions, and the valuation of the forest ecosystem can be considered a strategy toward sustainability in these regions. Economic valuation expresses nature’s contribution to monetary value (Farber et al., 2002), appraising both use and non-use values and allowing decision-makers and policymakers to identify, evaluate, and estimate trade-offs with other development goals (Balmford et al., 2002; Christie et al., 2012). The evaluation of FE S can contribute to the conservation and management of forest resources by improve the sustainable use of resources and convincing policymakers about the importance of forest management strategies (Acharya et al., 2019; Aslaksen et al., 2015; Baral et al., 2016; Häyhä et al., 2015). The primary role of economic analysis is to support the decision making of managers and policy makers (Khalfaoui et al., 2020). Therefore, the assessment process offers incentives to managers for sustainable forest management. In this sense, knowledge of the economic value of the multifunctionality of FES is necessary for those who can define, implement and evaluate public policies and public initiatives capable of capturing a favour in sustainable forest management and solving market failures (Bingham et al., 1995; Garcia et al., 2018).
The value of FES reflects the different ways they satisfy human needs (Marta-Pedroso et al., 2014). As highlighted by Costanza et al. (1997), research on the economic valuation of forest ecosystem goods and services is relevant, transdisciplinary and it was carried out in the scope of disciplines such as silviculture, environmental management, natural resources, conservation of biodiversity and the environment, accounting, among others. The national literature on forest ecosystem valuation is scarce, and little is known about how important the valuation of FES is and their internalisation in low-density regions of Portugal. Hence, technicians, academics, and researchers need to narrow this knowledge gap through further research. The present work is a literature review with meta-analysis aiming to systematise and synthesise the knowledge produced between 1992 and 2021 concerning estimates of the economic value of FES in Portugal and finding evidence that relates the mechanisms of internalisation of externalities in the sustainable development of low-density regions.
Key Terms in this Chapter
Low Density Regions: Regions displaying low demographic density (population per square kilometer) as well as weak economic density (GDP per capita, economic developments levels), both below national and European levels. Low density regions often combine these characteristics with physical and relational distance to centers of decision-making.
Ecosystem Services: Direct, indirect, and passive benefits that human populations derive from ecosystems.
Revealed Preference Methods: Draw statistical inferences on values from actual choices people make within markets. Estimation of the values people place on environmental amenities and disamenities proceeds by specifying a theoretical framework and conducting data analyses from purchase decisions (prices paid and quantities purchased) according to this conceptual framework.
Economic Value: Gain or loss in human well-being, when there is an increase or decrease in service provision (Madureira et al., 2013 AU86: The in-text citation "Madureira et al., 2013" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ).
Declared Preference Methods: The declared preference methods apply to situations where the goods or services to be valued do not have a direct relationship with market goods or services. In these cases, these methods consist of placing the consumers of the goods or services to be valued in hypothetical situations in which they would have to exchange expenditure on other goods or services for these. From the respondents' answers, the values of their willingness to pay for the consumption of the good or service to be valued or their willingness to accept compensation to give up this consumption are deducted ( Mendes et al., 2021 ).
Meta-Regression: Is a value function, only estimated based on determinations of the type of value in question made in several contexts and not in a single context. Therefore, the dependent variable is the valuation of the ecosystem service in question and the explanatory variables include characteristics of the situations in which the value of each service was estimated (e.g., geographic area, protected area or not, plant species present in the forest space, relevant characteristics of the population, etc.) and the valuation method that was used in each situation ( Mendes et al., 2021 ).
Economic Valuation of Ecosystem Services: Process of expressing nature's contribution in monetary value (Farber et al., 2002 AU85: The in-text citation "Farber et al., 2002" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ).