Emergy evaluation of benthic ecosystems influenced by upwelling in northern Chile: Contributions of the ecosystems to the regional economy

Ecological Modelling 359 (2017) 146–164

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Emergy evaluation of benthic ecosystems influenced by upwelling in northern Chile: Contributions of the ecosystems to the regional economy Fernando Berrios a,b,∗ , Daniel E. Campbell c , Marco Ortiz b a

Programa de Doctorado en Ciencias Aplicadas, mención Sistemas Marinos Costeros, Universidad de Antofagasta, PO Box 170, Antofagasta, Chile Instituto de Antofagasta (IA), Instituto de Ciencias Naturales AvH, Facultad de Ciencias del Mar y Recursos Biológicos, Universidad de Antofagasta, Chile c USEPA, ORD, NHEERL, AED, Narragansett, RI, USA b

a r t i c l e

i n f o

Article history: Received 26 March 2017 Received in revised form 10 May 2017 Accepted 10 May 2017 Keywords: Benthic ecosystem Ecosystem goods and services Emergy evaluation Upwelling coastal zone La Rinconada Marine Reserve

a b s t r a c t Emergy evaluations of three benthic ecosystem networks found in Mejillones, Antofagasta and Tongoy Bays, located on the coast of northern Chile, were carried out with the intent of documenting the contributions of these coastal ecosystems to the economy. The productivity of these bays is strongly influenced by the Humboldt Current System, as well as by the loss of upwelled flows that occurs during El Nino events. The results of the emergy evaluations were expressed as emdollars (EM$), a combined emergymoney measure that can be used to examine the equity of the emergy exchanges between fishermen and the buyers of the harvested algae and shellfish. In addition, an estimate of the total ecosystem services provided by these coastal ecosystems was made. The emdollar (Em$ y−1 ) and the hypothetical monetary value (US$ y−1 ) of the nitrate nitrogen upwelled constituted the highest inflow of emergy to all three benthic ecosystems. The empower density expressed as Em$ m−2 y−1 was highest in Mejillones Bay; however, the natural capital (biomass) of the ecological components (EM$ m−2 ) was highest in Antofagasta Bay, where La Rinconada Marine Reserve is located. The relationship between the coastal zone system and the regional economic system was assessed using the emergy benefit after exchange, EBE, which showed that there were net gains to the overall welfare of the sellers in two regions, 3,280,000 Em$ to those in Mejillones Bay, and 34,000,000 Em$ to those in Tongoy Bay, but a net loss of 2,000,000 Em$ to the sellers of algae and shellfish harvested from Antofagasta Bay. By supplying a clearer picture of the equity of trade relationships for individual organisms, fisheries and bays, emergy evaluation can help develop and implement management strategies for the conservation and preservation of coastal ecosystems to ensure that they are sustainable in the future. © 2017 Elsevier B.V. All rights reserved.

1. Introduction Ecosystems can be characterized by the processes of transforming available energy, cycling materials, replicating information, and they self-organize into hierarchical networks. These networks support diverse ecological populations, by means of dynamic pulsing, which interacts with economic activities through pathways of power and control (Odum, 2007). Power flows in ecosystems are coupled to the economy through controlling feedbacks manifested in the monetary value assigned to the products and services provided by ecosystems. Obtaining a better understanding of the relationship between the market value of marine ecosystem

∗ Corresponding author. E-mail address: [email protected] (F. Berrios). http://dx.doi.org/10.1016/j.ecolmodel.2017.05.005 0304-3800/© 2017 Elsevier B.V. All rights reserved.

products and the environmental work required for those products is essential for maintaining healthy and maximally sustainable regional systems. Whereas, a comprehensive understanding of the mechanisms of power and control between ecological and economic systems is necessary to establish efficient policies that solve problems related to the sustainable consumption of goods and services generated by ecosystems; in practice, the policies governing fisheries management and conservation of natural resources appear to be moving in the direction favoring economic interests rather than also promoting the environmental and ecological health of ecosystems (Airoldi and Beck, 2007). If the health of ecosystems suffers too much, then the overall health of the entire ecological-economic system is threatened. To counter this trend, we need to find a fair method for quantifying the exchange of real

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wealth1 in transactions where money is exchanged for environmental products (e.g., fish and shellfish) and for estimating the contributions of environmental goods and services that are external to markets (e.g., noncommercial species) to the economy. To address this problem, the real wealth of ecosystem goods and services (i.e., as measured by emergy) can be quantified on an equal basis with the monetary gains by expressing monetary gains in terms of the real wealth (emergy) that can be purchased on the market by the money received for the products of ecosystems. From an economic perspective, the definition of ecosystem goods and services is related to the contributions that they make to our well-being (MEA, 2005), whereas, natural capital yields flows of valuable goods and services from the stock of environmental (land, air, water, sea, etc.) and ecological (biodiversity and ecosystem components) natural capital (Costanza and Daly, 1992; Odum, 1996). In this work, we evaluate the natural capital of the benthic ecosystems in coastal Chile in ecological terms considering the biomass (stock) of the different components that make up the benthic trophic networks and their contributions to the well-being of regional economy. 1.1. The efficacy of the emergy approach

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to perform financial accounting for the environment, economy, and society (Campbell, 2013). Relevant to this analysis, Franzese et al. (2015) and Vassallo et al. (2017) have further developed and elucidated biophysical and trophodynamic accounting methods (e.g., emergy accounting) for the assessment of natural capital in marine protected areas and marine environments; thereby providing the means to quantify the contributions of ecosystem goods and services that arise from marine and estuarine natural capital storages. 1.2. Estimate of the total ecosystem services provided to the regional economy We recognized that our analyses of the commercial and noncommercial products and services provided by the benthic ecosystem fisheries to the regional economy did not give a complete picture of all the ecosystem goods and services provided by the emergy inputs to the coastal benthic ecosystems. A literature search did not reveal any assessments that have valued the total coastal marine environmental inputs to the regional economy of northern Chile in regard to their role (i.e., the work that they are doing) in maintaining the health and integrity of the region. Therefore, we made a first order estimate of the total contributions of the environmental forcing functions of the three bays to the regional economy using the method first proposed by Pulselli et al. (2011) and applied to many countries by Coscieme et al. (2014). In this method, the Ecosystem Emergy to Money Ratio (EEMR) of Pulselli et al. (2011) defined as the geobiosphere emergy baseline divided by the global estimate of the hypothetical2 monetary value of global ecosystem services from Costanza et al. (1997) was used to estimate the economic value of the goods and services provided by the renewable resource inflows of a region or nation of interest.

Neoclassical economic theory does not attempt to quantify the value of all the environmental goods (biomass, food, etc.) and services (evapotranspiration, waste assimilation, etc.) of ecosystems that represent the benefits that humans derive from ecosystem functions. So, natural goods and services without commercial importance (i.e., off-market) often end up being ignored in public and private decisions, compromising the sustainability of ecosystems from a global point of view (Odum and Odum, 2000). To address this problem, various authors have used economic methods (e.g., direct and indirect market pricing, such as contingent valuation, among other methods) and non-economic methods (e.g., based in energy) for economic valuation of ecosystem functions, goods and services (Costanza et al., 1997; Straton, 2006; Costanza et al., 2014; Hutniczak, 2015). Odum (1996, 2007) criticized the use of both money and caloric energy to evaluate the relative importance of each of the components of an ecosystem with regard to its function and value within a system. He argued that: (1) the work of nature is not paid for with money, yet it contributes to the processes valued by society; (2) energy alone does not represent the true value of the contributions of resources from the different elements of an ecosystem to an economic group, because (3) energy sources when expressed in terms of their caloric values are not equivalent in terms of their ability to do work in a system. As a consequence of these observations, he suggested that Emergy evaluation be used to integrate these commonly unquantified processes such as those provided by the environment (e.g., rain, wind, solar radiation) into market evaluations, (Odum, 1996). The application of emergy evaluation, using both analysis (Odum, 1996) and synthesis perspectives (Brown et al., 2000; and subsequent Emergy Synthesis Volumes 2–9 and associated special issues of Ecological Modelling, (Franzese et al., 2014; Brown et al., 2015) has proved to be a useful tool to value the properties of ecological-economic systems at different scales (Odum and Arding, 1991; Campbell et al., 2015; Morandi et al., 2015), ecological services (Campbell and Tilley, 2014; Grönlund et al., 2015), natural and human capital (Campbell and Brown, 2012; Mellino et al., 2015) and

Most of the Chilean coast (18◦ –56◦ S) is strongly influenced by the Humboldt Current System and its importance lies in being one of the most productive marine ecosystems in the world (Strub et al., 1998). In oceanographic terms, this high productivity is supported by the upwelling of sub-surface equatorial waters rich in nutrients and of low oxygen concentration (Strub et al., 1998; Escribano and Hidalgo, 2001). Several studies have analyzed the importance and influence of upwelling areas in northern Chile on the pelagic system, focusing primarily on: (1) the effects on primary and secondary production (Escribano and McLaren, 1999; Daneri et al., 2000); (2) different aspects of population dynamics (Escribano, 1998; Vega et al., 2005); (3) the effect on fisheries (Thiel et al., 2007; Montecino and Lange, 2009); and (4) the EL Nino Southern Oscillation, ENSO, variability (Laudien et al., 2007; Pacheco et al., 2012); among other topics. This area supports both important, artisanal, pelagicbenthic fisheries (i.e., for mollusks, algae, coastal and pelagic fish), as well as scallop aquaculture, with total artisanal landings of about 545,000 t per year (Servicio Nacional de Pesca y Acuicultura SERNAPESCA, 2014. Anuario Estadístico). This environmental setting has contributed to local economic growth of the artisanal fisheries sector, which is focused on benthic resources present in Mejillones, Antofagasta and Tongoy Bays with the majority of landings comprised of the brown alga, Lessonia spp., gastropods Concholepas concholepas and Fisurella spp., the cephalopod, Octopus spp., and the scallop, Argopecten purpuratus. (SERNAPESCA, 2014; Ortiz and Wolff, 2002; Ortiz et al., 2015).

1 Real wealth is the work that an item or flow can do when used in a system for its intended purpose. For example, a car can be driven only so far on a liter of petroleum, regardless of the price paid at the pump. Real wealth is measured by the emergy of an item and not necessarily by its price.

2 The amount of money estimated by Costanza et al. (1997) as the value of global ecosystem services is not really circulating in the gross world product, GWP, because these money flows were, in part, measured by contingent valuation and other methods that give hypothetical dollar values of ecosystem goods and services.

1.3. Environmental setting for the benthic ecosystem evaluations

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Fig. 1. Study areas of Mejillones, Antofagasta and Tongoy Bays in northern Chile, showing the location of La Rinconada Marine Reserve in Antofagasta Bay.

The coastal zones (between 0 and 35 m depth) of Mejillones and Antofagasta Bays are located in the second region of northern Chile where the main economic activity is copper mining and to a lesser degree fishing, i.e., benthic fisheries (Instituto Nacional de Estadística INE, 2015. Banco de Datos). Both Mejillones Bay and to a lesser extent Antofagasta Bays (Fig. 1) are characterized by the development of a concentration of industrial activities related to mining (Valdés et al., 2010). In addition, Antofagasta Bay includes La Rinconada Marine Reserve, which is located at the northern end of this Bay where it covers an area of approximately 270 ha (Fig. 1). The reserve was established to protect the natural populations of the scallop, Argopecten purpuratus (Lamarck, 1819) from overfishing. This marine reserve has also promoted a reduction in the exploitation of other species of commercial interest, such as the bivalves, Tagelus dombeii (Lamarck, 1818) and Aulacomya ater (Molina, 1782), as well as the carnivorous snail, Thais chocolata (Duclos, 1832). However, creating the reserve has caused a socioeconomic conflict with the government authorities on the part of various artisanal fishing organizations, who want to exploit the reserve’s diverse and valuable resources. This desire has resulted ˜ et al., 2017). in an illegal scallop fishery in the reserve (Avendano In the case of Tongoy Bay (Fig. 1), the coastal area between 0 and 35 m depth is located in the central part of Chile (Region 4), which is dominated by mining, agriculture, tourism, fisheries, and aquaculture activities (INE, 2015). The upwelling centers are located

in the southern area of the bays and upwelling appears to be the most important oceanographic process in explaining the physicalchemical properties of the bay waters and the regulation of the filling and emptying of the bays. These physical conditions create a cyclonic gyre in the middle of each bay (Escribano and Hidalgo, 2001; Marín et al., 2003; Moraga-Opazo et al., 2011). 1.4. Objectives of the study We found only one study of a marine fishery system carried out in the coastal areas of northern Chile that used economic methods for valuing ecosystem goods and services and none that used emergy methods. The economic study examined the fishery for the kelps, Lessonia spp. and Macrocystis pyrifera (Váquez et al., 2014). Therefore, one aim of the present study was to provide additional information on the value contributed to the regional economy by the coastal benthic ecosystems of the three bays. Specifically, we wanted to determine the emdollar value of the work accomplished by the ecosystems in supporting the artisanal benthic fisheries for brown and red algae and shellfish harvested from Mejillones, Antofagasta and Tongoy Bays. In addition, we wanted to examine the equity of the exchange of value between fishermen and the buyers of fishery products to determine if the local region is receiving fair value for its resources. Furthermore, we wanted to better understand the role of the individual bays in supporting the ben-

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thic ecosystem productivity found there. Specifically, we wanted to compare and contrast the properties of and the products and services gained from Antofagasta Bay, which contains the La Rinconada Marine Reserve with those obtained from the other two bays that do not have a similar feature. Finally, we had the objective of estimating the total ecosystem services in hypothetical US dollars provided to the regional economy by the three benthic ecosystems and comparing this value to the emdollar value of the fisheries products produced by the same three benthic ecosystems.

2. Methods Emergy evaluation is a methodological procedure to determine the relative value of flows and storages of material, energy, and information within an ecosystem based on the normalization of all types of available energy (i.e., energy with the potential to do work) used in the production of ecosystem and socioeconomic goods or services to emergy, measured in solar equivalent joules that have been used-up in the past to produce the various products and services, i.e., to solar emjoules (sej), the emergy unit. Emergy evaluation offers a quantitative, objective method for measuring the contributions of ecosystem goods and services to the economy. The emergy required for a good or service represents all past use of resources of all kinds required to have those products and services as part of the system. Furthermore, the emergy flows of the environmental contributions to an economy can be related to the GDP of that economy through dividing the emergy flow by the emergy to money ratio (EMR) for the economy to obtain a combined emergymoney measure of value, the emdollar (Em$). This conversion does not change the fundamental underlying relationship between the emdollar flow and the biophysical quantity, emergy, upon which they are based. This procedure redistributes the money flows of the GDP in proportion to the emergy flows supporting the economy; thereby, associating the money flows proportionately with the sources of real wealth hypothesized to be the origin of “buying power” in the economy (Odum, 1996). Emergy methods have been described many times in the literature (Brown and Ulgiati, 2004; Campbell and Ohrt, 2009; Zhang et al., 2013; Campbell et al., 2014; Geng et al., 2017) and specifically in this journal (Falkowski et al., 2015; Campbell and Tilley, 2016), so there is no need to repeat a detailed description of emergy methods in this paper. Instead, we will focus on the specific methods that were necessary to carry out this study. The energy and emergy signatures (Odum, 1996; Campbell, 2000; Campbell et al., 2009) that characterize and drive the coastal ecological systems of each bay were quantified using the inflows of solar radiation, wind, tide, waves and upwelled nutrients. In this work, only nitrates were included in the nutrient component, since one of the main effects of upwelling in terms of its effect on productive processes is to increase nutrients, especially nitrates (Marín et al., 1993; Graco et al., 2007). The emergy base required to support primary production and consumption of a species or functional group in the benthic ecosystem network of each bay was estimated per square meter (i.e., as empower density) using a procedure developed by Campbell (2004) to obtain new estimates for the transformities of available energy flows and components (i.e., natural capital storages) within the benthic ecosystems. The value of commercial and noncommercial species was determined within the benthic ecosystem network from the bottom-up by distributing the emergy inflows in the emergy signature up through the network to obtain the total emergy required for each species, stock, and available energy flow within the system.

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2.1. Quantification of network components and flows The energy flows through the ecological networks were obtained from the flow matrix of steady-state models of the three benthic ecosystems (Ortiz and Wolff, 2002; Ortiz et al., 2015), and the transformities within the networks were determined based on the procedure developed by Li et al. (2010). After obtaining the mass flows of the ecological variables, they were converted to energy using factors to convert from wet weight to dry weight (×0.2) and from dry weight to energy (×5 kcal/g dry weight and ×4183 J/kcal). In this way, the interaction matrix was expressed in joules m−2 y−1 from which the transformities were estimated following the equation that defines emergy as the product of the flow of available energy (J) and the quality of that flow (i.e., its transformity, Tr) where: Emergy sej y−1 = Available Energy J y−1 × Transformity sej J−1 . In the method of Li et al. (2010), the first step to determine the transformities in the network is to structure the equations from the energy systems diagram for each system (Fig. 2a–c) using the energy flows present and considering the rules of emergy algebra described by Odum (1996). The value of the transformity makes a difference in the calculation and it depends on the designation of an energy flow as a co-product or as a split in the ecosystem network. In the case of a co-product, the entire emergy input to the production process is required for each, whereas, in a split the emergy input to the production of a product is divided in proportion to the available energy on each output pathway (Odum, 1996). For example, benthic macrofauna ingest various plant and animal materials and assimilate organic matter into biomass and produce feces (detritus). Filter feeders also produce pseudo feces, which is separated from the food intake, before ingestion. If these products have different properties in the way that they are used in the ecosystem they would be classified as co-products. However, sometimes in such complex systems, there is not enough biologicalecological information to make an accurate determination that a particular flow is a split or a co-product (Campbell, 2004). In this study, we simplified the problem by assuming that there are no coproducts in the benthic ecosystem network, based on the procedure of Brown et al. (2006) and Zarbá and Brown (2015). The transformities calculated were corrected to the new baseline, which is 12E + 24 seJ y−1 (Brown et al., 2016). Note the Brown et al. (2016) explain that the geobiosphere baseline can only be determined by establishing equivalences between the different exergy inputs to the geobiosphere and thus it is expressed in solar equivalent joules (seJ), whereas emergy is determined by a tracking method and is expressed in emjoules (sej) as defined above. The time boundary for making estimates of the flows of available energy was one year. To estimate the biomass turnover time, two methods were used one for exploited species, which considered age-at-capture, and one for unexploited species and functional groups (Schwinghamer et al., 1986), which relates day of the year to the production:biomass ratio (365/(P:B)) extrapolated over a year. The hydrodynamic model of Moraga-Opazo et al. (2011) was used to estimate the volume of upwelled waters entering Tongoy Bay per year, and the models proposed by Escribano and Hidalgo (2001) and Marín et al. (2003) were used to estimate the volume of upwelled waters entering Antofagasta and Mejillones Bays. 2.2. Estimating the emdollar value of ecosystem products and services The emergy-to-money ratio (EMR) for Chile in 2008 was used to determine the emdollar value of the emergy flows in the three benthic networks, the emergy stored in natural capital and the emergy output of harvested algae and shellfish. The first step in determining the emdollar value of a resource is to calculate the nat-

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ural renewable emergy input that maintains a square meter of its ecological flow, its natural capital (biomass) or its output flow (e.g., fisheries yield). The Emdollar value of a given quantity of ecosystem goods or services was estimated by dividing the emergy of the renewable resource flow, ecological flow or quantity of natural capital by the EMR for the Chilean economy in 2008, which was taken from the National Emergy Accounting Database (NEAD, 2017) http://www.cep.ees.ufl.edu/nead/data.php. Values from the NEAD were converted to the new baseline (Brown et al., 2016; Campbell, 2016) to obtain 6.64E + 12 sej/$. The EMR represents how much emergy flow supporting an economy corresponds, on average, to one unit of money flowing in the GDP of that economy (Odum, 1996). The emdollar (Em$ = sej/sej/$) expresses the emergy flow (sej) of a product or service in terms its proportional share (sej/$) of the money flowing in the gross domestic product (GDP) of the economy ($). Thus, expressing quantities in emdollars redistributes the money flow of an economy in proportion to the emergy flows in that economy. This redistribution is thought to better match money flows with the actual purchasing power of money in the economy, which is assumed to be supplied by the emergy of resources available for purchase within the system. Therefore, all emergy flows (including those that are not valued economically) can be assigned a

value expressed in emdollars. For example, by employing emdollars a dollar value related to its emergy flow can be assigned to the nutrients in upwelled waters entering the 3 bays. However, the economy does not pay for the services provided by upwelled nutrients, even though they are essential to providing the products and services of the benthic ecosystems of the three bays. In this study, the following measures were estimated: (1) An emdollar value for the environmental resources input as solar radiation, wind, tide, waves and upwelled nutrients (i.e., nitrate); (2) the empower (emergy flow per unit time) within the benthic ecosystem networks; (3) the empower density (emergy flow per unit time and space) supporting ecological and economic activities; (4) emergy flow within the benthic networks calculated by bottom-up analysis and (5) the natural or ecological capital storages (i.e., the biomass of the exploited species and other components); and (6) the emergy flows in the fisheries output. 2.3. Estimation of the total ecosystem services supporting the regional economy The emergy of the renewable inputs to the three bays was converted to monetary terms (in hypothetical dollars), which allowed

Fig. 2. (a) Energy Systems Language Model of Mejillones Bay showing the emergy base of the benthic network in terms of emdollars (bold underlined numbers on the left) and the benthic ecosystem network with the emdollars flows along the pathways in Em$ m−2 y−1 , which show the relative emdollar values of marketable and nonmarketable flows of energy within the benthic network. Due to the size of networks we only show the natural capital of the exploited species within the tank symbols in Em$ m−2 . Names in bold correspond to commercial fishery resources. (b) Energy Systems Language Model of Antofagasta Bay showing the emergy base of the benthic network in terms of emdollars (bold underlined numbers on the left) and the benthic ecosystem network with the emdollars flows along the pathways in Em$ m−2 y−1 , which show the relative emdollar values of marketable and nonmarketable flows of energy within the benthic network. Due to the size of networks we only show the natural capital of the exploited species within the tank symbols in Em$ m−2 . Names in bold correspond to commercial fishery resources. (c) Energy Systems Language Model of Tongoy Bay showing the emergy base of the benthic network in terms of emdollars (bold underlined numbers on the left) and the benthic ecosystem network with the emdollars flows along the pathways in Em$ m−2 y−1 , which show the relative emdollar values of marketable and nonmarketable flows of energy within the benthic network. Due to the size of networks we only show the natural capital of the exploited species within the tank symbols in Em$ m−2 . Names in bold correspond to commercial fishery resources.

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Fig. 2. (Continued)

us to make an estimate of the economic value of the total ecosystem services provided by the coastal benthic ecosystems of the three bays. In this study, the total support is calculated as the sum of the services from the three bays, since we wanted to compare our estimate of the total value of ecosystem services calculated on a global basis to the ecosystem services provided by the benthic ecosystems and their fisheries. The calculation was performed by dividing the renewable emergy input to the benthic ecosystems of the three bays (without double counting) by the EEMR (Pulselli et al., 2011; Coscieme et al., 2014) defined as the global baseline of Odum (2000) divided by the global monetary estimate of ecosystem services from Costanza et al. (1997). In general, the hypothetical monetary value of ecosystem services in any system can be determined by dividing the EEMR into the emergy value of the primary renewable resource inflows calculated for the region or nation of interest. In this study, the highest value from Coscieme et al. (2014) was converted to the new baseline (Brown et al., 2016; Campbell, 2016) to obtain 5.46E + 11 seJ/$, which is the solar equivalent exergy (SEE)3 per hypothetical dollar of global ecosystem services. The ratio gives an indirect estimate of the relationship between emergy inflows and ecosystem services. This is a relationship between the forcing functions (emergy signature) that supports a system and the possible

3 The primary inputs of exergy (available energy) to the geobiosphere must be expressed as solar equivalent exergy, SEE with the units abbreviated as seJ (Brown et. al., 2016), because the primary inputs solar radiation, Earth’s deep heat and tidal exergy can only be related in terms of their equivalences. Once the solar equivalent baseline of the geobiosphere is established the emergy of all planetary storages and flows can be determined with the standard tracking method giving values in emjoules, abbreviated, sej.

economic benefits (i.e., the value of ecosystem goods and services) that might be obtained from that system (Coscieme et al., 2014). The work of Coscieme et al. (2014) allowed us to make an estimate of the total ecosystem services provided to the coastal region of Chile by the emergy inputs to the benthic ecosystems of the 3 bays. The emdollar values of all species within the fisheries supported by the benthic ecosystem networks and our estimate of the value of total ecosystem services provided by the emergy input to each of the three bays measured in hypothetical dollars were then compared.

2.4. Structure of the economic inputs and analysis of the equity of exchange The relationship between the coastal zone benthic ecosystems and the larger regional economy was quantified through determining the emergy required for the fisheries products compared to the emergy that can be purchased on the regional market with the money received for the fisheries products. The equity of exchange between the fishermen and the buyers of fisheries products in the regional economy was found by determining the emdollar value of the ex-vessel price paid for the harvested algae and shellfish compared to the emergy (emdollars) supplied to the market in the fisheries products of the benthic ecosystems. When this comparison is made as a difference, the Emergy Benefit on Exchange (EBE) is given and when it is expressed as a ratio the relative loss or gain is shown by the Emergy Exchange Ratio (EER). The data needed to evaluate the EBE and the EER were found in reports of the Oficina de Estudios y Políticas Agrarias (ODEPA, 2017). Data on the price per kilogram of red and brown algae or shellfish landed were obtained at the point of extraction (i.e., trade in situ). First,

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Fig. 2. (Continued)

the flows from the stocks of organisms in each benthic ecosystem were determined as available energy flows (J) per year and then converted to emergy through multiplication by the appropriate transformity (sej/J). Then, this emergy flow (sej/y) was converted to an emdollar flow (Em$/y) through dividing it by the EMR for Chile in 2008 (6.64E + 12 sej/$). This allowed us to determine the value derived from the benthic ecosystem contributing to the regional and national socioeconomic output realized from each coastal system or in other words, we determined the relationship between the coastal zone ecosystem and the next larger system of the regional and national economy (i.e., ex-vessel prices are national averages). To determine the contributions of real wealth (Em$) from benthic ecosystems to the regional economy, we used the EBE (Fig. 3), which is defined as the difference between the emergy (YM ) that can be purchased on the national market with the money (MY ) received from buyers purchasing fishery products and the emergy (Y) of the algae and shellfish landed and sold to buyers. This difference structured in this way, represents the net benefit or loss realized by the sellers of ecosystem products as a consequence of trade. In other words, if more emergy leaves the region in nature’s products (Y >YM ) than is received in the buying power of the money paid for those products, the people of the coastal zone will be deprived of a portion of the real wealth (emergy) initially gained from the harvest of their ecosystem products. As a consequence of this exchange, regional wealth will be reduced and those purchasing the fishery’s products will gain more real wealth as a result of the transaction. In addition, we estimated the magnitude of the loss or gain to the sellers using the EBE in a transaction denominated in emdollars (Em$) by first dividing YM by the EMR for Chile in 2008 to determine the

purchasing power of the money received to buy emdollars (emergy) on the national market (Fig. 3) and then comparing this to Y/EMR, which is the emdollar equivalent of the emergy required to produce the ecosystem products, i.e., the kelp, red algae and shellfish sold. The emergy exchange ratio (EER) was used to show the relative magnitude of the advantages realized by the buyers or sellers of particular products (Fig. 3). Advantage to the sellers is shown when this ratio is expressed as the emergy (YM ) that can be purchased by the money received from selling, trading or moving kilograms of fishery product out of the system divided by the emergy (Y) contained in that quantity of product (Odum, 1996). Finally, we also calculated the EER from the perspective of the buyer by reversing the ratio for advantage (or loss) to the seller as shown on Fig. 3.

3. Results The results of this analysis are presented in Fig. 2a–c and in Tables 1–5 with ancillary data and analysis given in the Appendix A. Fig. 2 presents the benthic ecosystem structure for each of the three coastal bays examined, where 2(a) shows Mejillones Bay, 2(b) Antofagasta Bay and 2(c) Tongoy Bay. These models have been evaluated showing the emergy base of the benthic network in terms of Emdollars m−2 y−1 , (underlined numbers). The benthic ecosystem network with the emergy flows along the pathways shown in emdollars (Em$ m−2 y−1 ) gives the relative value of commercial and noncommercial flows of available energy within the benthic network. Due to the size of the networks the natural capital storages (Em$ m−2 ) of the exploited species only are shown within the

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Fig. 3. An Energy Systems Language Diagram of the Emergy Benefit on Exchange (EBE) and the Emergy Exchange Ratio (EER) defined for the benthic ecosystem fisheries of the three bays. In the diagram dashed lines represent the flow of money, dotted lines the flow of information, and solid lines the flows of available energy and emergy.

tank symbols. Names shown on the hexagons in bold correspond to fishery resources.

3.1. The emdollar value of the benthic fisheries and monetary value of total ecosystem services The emdollar (Em$) and hypothetical monetary dollar (US$) values of the environmental renewable energy flows and the ecosystem services provided by these renewable sources, as well as the empower and empower density of the three bays are shown in the Table 1 and supported by the calculations in Appendix A. The emdollar value of the nitrate nitrogen upwelled averaged 1.50E + 07 Em$ y−1 in support of the benthic ecosystem networks and 1.82E + 08 US$ y−1 for the total ecosystem services supporting the coastal region. This was the highest input to the benthic ecosystems in all three bays (Table 1). The emdollar value of the benthic ecosystems in each bay was about 8.2% of the value of the total ecosystem services as measured in hypothetical US dollars. The emdollar value of the empower base of the benthic ecosystem and the hypothetical dollar value of its ecological services was highest in Antofagasta Bay (2.65E + 7 Em$ y−1 , 3.23E + 08 US$ y−1 ) followed by Mejillones Bay (1.25E + 7 Em$ y−1 , 1.52E + 08 US$ y−1 ) and then by Tongoy Bay (8.35E + 6 Em$ y−1 , 1.02E + 8 US$ y−1 ). The total coastal system estimated as the sum of the three bays had an emdollar value of 4.74E + 07 (Em$ y−1 ) for the fishery and a hypothetical dollar value of ecosystem services of 5.76 E + 08 (US$ y−1 ). Emdollar and hypothetical monetary value flows per unit area were highest in Mejillones Bay (0.64 Em$ m−2 y−1 , 7.81 US$ m−2 y−1 ), followed by Antofagasta Bay (0.50 Em$ m−2 y−1 , 6.09 US$ m−2 y−1 ) and then Tongoy Bay (0.31 Em$ m−2 y−1 , 3.72 US$ m−2 y−1 ). All three coastal systems together had an average emdollar value of 0.48 ± 0.14 (Em$ m−2 y−1 ) and the average economic value of the ecosystem services provided was 5.87 ± 1.68 (US$ m−2 y−1 ). The emdollar value of the total empower throughput per unit area of the benthic ecosystem (Table 2) was highest in Mejillones Bay (3.48 Em$ m−2 y−1 ) followed by Antofagasta Bay (2.26 Em$ m−2 y−1 ), and finally, Tongoy Bay (1.29 Em$ m−2 y−1 ).

3.2. Emdollar value of natural capital of the benthic ecosystem networks The Emdollar value of the total natural capital (biomass), which is the sum of all ecological components present in a bay, was highest in the benthic network of Antofagasta Bay, followed by Mejillones and then Tongoy Bay (Table 3). The sea star, Luida magallanica (a top predator that is not marketed) in Tongoy Bay had the lowest emdollar value (0.0002 Em$ m−2 ) of natural capital within the three bays. Whereas, a stock of commercial importance in Antofagasta Bay, the clam, Transennella pannosa, recorded the highest natural capital value (0.62 Em$ m−2 ). The scallop, Argopecten purpuratus (Lamarck 1819), is an important resource that inhabits all three bays and the emdollar density of its stocks and flows (Table 2 and 3) was highest in Mejillones and in Tongoy Bays (biomass: 0.03 Em$ m−2 ; flows: 0.02 Em$ m−2 y−1 ). However, in Antofagasta Bay, Argopecten purpuratus stocks and flows were, respectively, 66% and 80% lower (biomass: 0.01 Em$ m−2 ; flows: 0.004 Em$ m−2 y−1 ), compared to the values observed in Mejillones and Tongoy Bays, which were approximately equal to each other. 3.3. Analysis of power and control loops between benthic ecosystems and the economy The results of calculating the EBE and the EER for the exchange of emergy between the ecosystems and the economy are summarized in Tables 4 and 5. Landings in terms of the emergy harvested were highest for Argopecten purpuratus (4.81E + 11 sej m−2 y−1 ) in Tongoy Bay, followed by the kelp, Lessonia trabeculata (2.58 E + 11 sej m−2 y−1 ) in Antofagasta Bay and then the red alga, Chondracanthus chamissoi (1.11E + 11 sej m−2 y−1 ) also in Tongoy Bay (Table 4). Argopecten purpuratus (1.05E + 11 sej m−2 y−1 ) accounted for the highest emergy flow harvested from Mejillones Bay. The outcomes regarding the EBE indicate that Tongoy Bay realized the highest gain in emergy upon trading on the regional market (2.26E + 20 sej or 34,000,000 Em$), followed by Mejillones Bay (2.18E + 19 sej or 3,280,000 Em$), whereas Antofagasta Bay trades at a disadvantage on the regional market losing more emergy (−1.32E + 19 sej or 1,990,000 Em$) than it gains in the sum of all

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Table 1 Energy, transformity, emergy, emdollar and economic value of ecosystem services in hypothetical US dollars associated with the renewable resource inputs to the three bays. The emergy flow is divided by the EMR of Chile in 2008 (6.64E + 12 sej/$) or the Emergy to Ecosystem Services Ratio for the World in 2008 (5.41E + 11 sej/$), respectively, to obtain the emdollar flows in the benthic ecosystem network and its fisheries, and the total economic value of ecosystem services for each of the bays. The empower and empower density for each of the bays and for the total coastal system along with the emdollar equivalent of these flows and our estimates of the total economic value of ecosystem services that could be provided from the emergy inflows are shown for Mejillones, Antofagasta and Tongoy Bays. The areas of each coastal system are also given. In addition, data source for transformity are shown. Energy (J y−1 )

Transformity (sej J−1 )

Emergy (sej y−1 )

Emdollar (Em$ y−1 )

Hypothetical economic value (US$ y−1 )

(A) Mejillones Bay (1) Solar radiationa (2) Windb (3) Wavec (4) Tided (5) Nitrogen Upwellede

1.18E + 17 1.79E + 15 9.07E + 12 1.05E + 14 3.50E + 12

1.00E + 00 1.23E + 03 3.08E + 04 3.09E + 04 2.28E + 07

1.18E + 17 2.20E + 18 2.79E + 17 3.25E + 18 7.98E + 19

17,771 331,581 42,072 489,499 12,011,092

216,117 4,032,418 511,641 5,952,883 146,068,964

(B) Antofagasta Bay (1) Solar radiationa (2) Windb (3) Wavec (4) Tided (5) Nitrogen Upwellede

3.21E + 17 4.86E + 15 5.26E + 14 2.86E + 14 7.33E + 12

1.00E + 00 1.23E + 03 3.08E + 04 3.09E + 04 2.28E + 07

3.21E + 17 5.97E + 18 1.62E + 19 8.83E + 18 1.67E + 20

48,363 899,652 2,437,602 1,330,434 25,158,392

588,145 10,940,826 29,644,101 16,179,631 305,955,538

(C) Tongoy Bay (1) Solar radiationa (2) Windb (3) Wavec (4) Tided (5) Nitrogen Upwellede

1.48E + 17 2.41E + 15 1.36E + 14 8.09E + 13 2.31E + 12

1.00E + 00 1.23E + 03 3.08E + 04 3.09E + 04 2.28E + 07

1.48E + 17 2.96E + 18 4.20E + 18 2.50E + 18 5.28E + 19

22,328 446,244 632,429 376,316 7,947,928

271,532 5,426,855 7,691,079 4,576,446 96,656,115

Mejillones Bay

Antofagasta Bay

Tongoy Bay

Total coastal system

a) Empower base of benthic productive systems Emergy (sej y−1 ) Emdollar (Em$ y−1 ) Economic value (US$ y−1 )

8.31E + 19 1.25E + 07 1.52E + 08

1.76E + 20 2.65E + 07 3.23E + 08

5.54E + 19 8.35E + 06 1.02E + 08

3.15E + 20 4.74E + 07 5.76E + 08

b) Empower density base of benthic productive systems Emergy (sej m−2 y−1 ) Emdollar (Em$ m−2 y−1 ) Economic value (US$ m−2 y−1 ) Area (m−2 ) Emergy to Money Ratio (EMR) Chile 2008 (sej/$) Emergy to Ecosystem Service Ratio World 2008 (sej/$)

4.26E + 12 0.64 7.81 1.95E + 07 6.64E + 12 5.46E + 11

3.32E + 12 0.50 6.09 5.30E + 07 new base line new base line

2.03E + 12 0.31 3.72 2.73E + 07

3.21E + 12 0.48 5.87

a

By definition. New calculation Campbell and Erban (2016). Transformity of wind energy dissipated in the boundary layer. Number may be slightly different in the final paper 1230 or 1240. c New transformity for the tide from the geobiosphere baseline paper. Brown et al. (2016). d New transformity calculated relative to the new baseline, Campbell and Erban (2016). e New transformity calculated relative to the new baseline, Brown et al. (2016). b

transactions. The EER analysis showed that the highest benefit upon trade, when considering the entire bay was obtained by the sellers from Tongoy Bay (14.84:1), followed by Mejillones Bay (5.14:1) and then Antofagasta Bay (0.58:1). The overall benefit gained by the buyers was highest in Antofagasta Bay (1.74:1) followed by a considerable fall to (0.19:1) in Mejillones Bay. This ratio was even lower (0.07:1) in Tongoy Bay (Table 5). The large surplus obtained by the sellers from Tongoy Bay was driven by the premium price paid for scallops, as well as the general profitability of the other species taken from this bay, especially Chondracanthus chamissoi and the snail, Xanthochorus cassidiformis. In Mejillones Bay, large surpluses were obtained by the sellers only for the clam, Tagelus dombeii and the scallop, Argopecten purpuratus, while the sellers reported losses on the remainder of the resources harvested. The biggest gains to the sellers in Antofagasta Bay came from the sale of Argopecten purpuratus, which was similar to the result found in the other two bays, but the EER for the scallops sold from Antofagasta Bay was only 9.72:1 compared to a 12.36:1 advantage for the sellers in Mejillones Bay and a 17.30:1 ratio in favor of the sellers from Tongoy Bay. In contrast, the greatest profit gained by buyers of benthic ecosystem products from Antofagasta Bay was for the purchase of the kelp, Lessonia trabeculata and the gastropods, Concholepas concholepas and Thais chocolata. In Mejillones Bay advantages to the buyer were realized primarily for the snail, Thais chocolata and

the clam, Aulacomya ater, as well as for Lessonia trabeculata and in Tongoy Bay for the crab, Cancer polyodon. 3.4. Comparison of the three bays: data on possible effects of La Rinconada Marine Reserve The network emdollar (empower) flows are shown in Table 2, where the greatest flow per unit area is through the Mejillones Bay benthic ecosystem (3.48 Em$ m−2 y−1 ) followed by Antofagasta Bay (2.26 Em$ m−2 y−1 ) and then Tongoy Bay (1.29 Em$ m−2 y−1 ). However, Antofagasta Bay has the greatest emdollar flow per unit area (Table 2) for commercially valuable species (0.91 Em$ m−2 y−1 ) and it has the highest species and category richness 25 compared to 24 for Tongoy and 22 for Mejillones Bay. Natural capital stocks (Table 3) for the entire network (2.12 Em$ m−2 ) and for commercially valuable species (1.82 Em$ m−2 ) are greatest in Antofagasta Bay followed by Mejillones Bay (1.63 Em$ m−2 and 1.10 Em$ m−2) and then Tongoy Bay (0.26 Em$ m−2 and 0.06 Em$ m−2 ). The mass flow harvested per unit area (Table 4) from the benthic ecosystems was greatest in Tongoy Bay (231 g m−2 y−1 ) followed by Antofagasta (58.58 g m−2 y−1 ) and then Mejillones Bay (33.39 g m−2 y−1 ).The emergy flow per unit area harvested from the three bays occurred in the same order as mass harvested, but the difference between Antofagasta and Tongoy Bays was much smaller

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Table 2 Energy, transformity, emergy and emdollar value of flows within the benthic networks (both commercial (bold type) and noncommercial flows) of Mejillones, Antofagasta and Tongoy Bays are presented in this table. The emergy flow is divided by the EMR for Chile in 2008 (6.64E + 12 sej $) to obtain emdollar flows. The total network throughput and the flows of marketable species per m−2 are given for each bay. Species/functional groups

Energy (J m−2 yr−1 )

Transformity (sej J−1 )

Emergy (sej m−2 y−1 )

Emdollar (Em$ m−2 y−1 )

(A) Mejillones Bay Phytoplankton Lessonia trabeculata Chlorophyta Rhodophyta Phaeophyta Detritus Zooplankton Argopecten purpuratus Aulacomya Ater Tagelus dombeii Choromytilus chorus Gari solida Tegula spp. Small Epifauna Herbivore (SEH) Sea urchin species (SUS) Other Filter feeders (OFF) Thais chocolata Other Sea Star Species (OSS) Large Epifauna (LE) Small Epifauna Carnivore (SEC) Cancer spp. Luidia magallanica Total currency equivalent flows to market

3.14E + 07 3.12E + 06 8.79E + 05 1.00E + 07 1.38E + 06 9.57E + 06 6.03E + 06 5.46E + 05 8.54E + 05 2.80E + 06 1.27E + 06 1.06E + 06 4.63E + 06 1.08E + 06 1.11E + 04 1.29E + 05 5.33E + 05 6.49E + 02 3.13E + 05 7.10E + 05 2.40E + 05 4.70E + 03

1.36E + 05 3.56E + 05 1.96E + 06 3.56E + 05 2.34E + 05 2.58E + 05 2.86E + 05 2.44E + 05 2.49E + 05 2.36E + 05 3.02E + 05 3.96E + 05 8.82E + 05 7.88E + 05 9.87E + 05 1.58E + 05 2.15E + 05 1.42E + 05 7.48E + 05 8.53E + 05 8.27E + 05 1.35E + 06

4.26E + 12 1.11E + 12 1.73E + 12 3.56E + 12 3.24E + 11 2.47E + 12 1.73E + 12 1.33E + 11 2.13E + 11 6.61E + 11 3.82E + 11 4.21E + 11 4.08E + 12 8.53E + 11 1.09E + 10 2.03E + 10 1.15E + 11 9.24E + 07 2.34E + 11 6.06E + 11 1.98E + 11 6.36E + 09

0.64159 0.16737 0.25989 0.53601 0.04873 0.37138 0.26006 0.02007 0.03201 0.09960 0.05759 0.06335 0.61482 0.12847 0.00164 0.00306 0.01726 0.00001 0.03526 0.09122 0.02982 0.00096 0.46

(B) Antofagasta Bay Phytoplankton Lessonia trabeculata Chlorophyta Rhodophyta Phaeophyta Detritus Zooplankton Argopecten purpuratus Aulacomya Ater Tagelus dombeii Choromytilus chorus Transennella pannosa Protothaca thaca Tegula spp. Small Epifauna Herbivore (SEH) Sea urchin species (SUS) Other Filter feeders (OFF) Other Sea Star Species (OSS) Thais chocolata Large Epifauna (LE) Small Epifauna Carnivore (SEC) Cancer spp. Concholepas concholepas Luidia magallanica Octopus vulgaris Total currency equivalent flows to market

5.23E + 07 1.95E + 06 5.23E + 05 9.21E + 05 9.26E + 05 1.33E + 07 6.03E + 06 2.55E + 05 4.75E + 05 1.36E + 06 3.80E + 05 1.58E + 07 1.90E + 06 5.24E + 05 2.09E + 06 7.72E + 04 3.45E + 05 1.60E + 05 5.90E + 05 3.13E + 04 2.05E + 05 1.35E + 04 7.32E + 04 3.63E + 05 7.83E + 02

6.35E + 04 7.30E + 05 1.21E + 06 9.02E + 05 8.29E + 05 7.03E + 04 1.34E + 05 1.14E + 05 1.41E + 05 1.11E + 05 1.63E + 05 1.05E + 05 1.89E + 05 1.31E + 06 9.64E + 05 1.69E + 06 5.22E + 04 4.79E + 04 3.80E + 05 7.52E + 05 8.45E + 05 8.55E + 05 1.45E + 06 1.54E + 06 1.56E + 06

3.32E + 12 1.42E + 12 6.33E + 11 8.31E + 11 7.68E + 11 9.38E + 11 8.08E + 11 2.91E + 10 6.71E + 10 1.50E + 11 6.21E + 10 1.66E + 12 3.59E + 11 6.87E + 11 2.02E + 12 1.30E + 11 1.80E + 10 7.64E + 09 2.24E + 11 2.35E + 10 1.73E + 11 1.16E + 10 1.06E + 11 5.61E + 11 1.22E + 09

0.50034 0.21443 0.09530 0.12509 0.11573 0.14121 0.12168 0.00438 0.01010 0.02257 0.00935 0.24967 0.05406 0.10347 0.30374 0.01960 0.00272 0.00115 0.03379 0.00354 0.02609 0.00174 0.01600 0.08449 0.00018 0.91

2.93E + 07 6.91E + 05 1.97E + 06 2.53E + 06 1.26E + 06 4.06E + 06 5.43E + 06 9.35E + 05 3.19E + 05 4.33E + 05 6.65E + 05 9.25E + 03 1.84E + 06 4.52E + 05 4.67E + 05 6.58E + 04 7.07E + 03

6.92E + 04 9.40E + 05 2.32E + 05 2.53E + 05 2.32E + 05 5.45E + 05 1.46E + 05 1.44E + 05 1.83E + 05 2.08E + 05 8.02E + 05 8.41E + 05 6.47E + 04 1.90E + 05 1.41E + 05 9.08E + 05 1.34E + 05

2.03E + 12 6.49E + 11 4.57E + 11 6.40E + 11 2.91E + 11 2.21E + 12 7.93E + 11 1.34E + 11 5.85E + 10 9.02E + 10 5.33E + 11 7.78E + 09 1.19E + 11 8.57E + 10 6.60E + 10 5.98E + 10 9.51E + 08

0.30556 0.09778 0.06889 0.09642 0.04383 0.33334 0.11943 0.02020 0.00882 0.01359 0.08032 0.00117 0.01797 0.01291 0.00994 0.00900 0.00014

(C) Tongoy Bay Phytoplankton Heterosostera tasmanica Chondracanthus chamissoi Rodophyta Ulva sp. Detritus Zooplankton Argopecten purpuratus Mulinia sp. Calyptraea trochiformis Tegula sp. Taliepus sp. Infauna Pyura chilensis Small Epifauna (SE) Paraxanthus barbiger Luidia magallanica

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Table 2 (Continued) Species/functional groups

Energy (J m−2 yr−1 )

Transformity (sej J−1 )

Emergy (sej m−2 y−1 )

Emdollar (Em$ m−2 y−1 )

Xanthochorus cassidiformis Megenaster gelatinosus Heliaster helianthus Cancer porteri Cancer polyodon Cancer coronatus Large Epifauna (LE) Total currency equivalent flows to market

2.36E + 04 1.99E + 05 4.88E + 03 2.05E + 04 1.26E + 05 3.87E + 04 7.25E + 04

2.99E + 05 5.91E + 05 8.22E + 05 1.94E + 05 1.07E + 06 2.19E + 05 4.50E + 05

7.05E + 09 1.18E + 11 4.01E + 09 3.98E + 09 1.34E + 11 8.47E + 09 3.26E + 10

0.00106 0.01770 0.00060 0.00060 0.02024 0.00128 0.00491 0.11

Total flows Emdollar (Em$ m−2 y−1 ) Emergy to Money Ratio Chile 2008 (sej/$)

Mejillones Bay 3.48 6.64E + 12

Antofagasta Bay 2.26

Tongoy Bay 1.29

in the case of the empower density harvested 5.88E + 11 sej m−2 y−1 compared to 5.98E + 11 sej m−2 y−1 or a difference of 1.7%, instead of a difference of 75%, which was found in the mass harvested per unit area. The total biomass taken from Tongoy Bay was much greater than that taken from the other two bays, 6306 t compared to 3105 t from Antofagasta Bay and 651 t from Mejillones Bay. The EBE and the EER (Table 5) vary widely according to the species harvested; however, in general, more species are harvested with an advantage to the buyer than with an advantage to the seller (i.e., 9:3 in Antofagasta Bay, 5:2 in Mejillones Bay), but in Tongoy Bay more products are sold with advantage to the sellers (1:3). Only, A. purpuratus, T. dombeii, other filter feeders, OFF, C. chamissoi and X. cassidiformis, yield a positive advantage to the fishermen in a trade. 4. Discussion With a view toward illuminating environmental planning and policies for the coastal zone in northern Chile, the renewable emergy inputs to three coastal bays were compared, and we found that where the nutrients upwelled were higher, the emdollar value of the ecosystem products and our estimate of the hypothetical dollar value of total ecosystem services were also higher. This result illustrates the importance of the upwelling process, where forces such as wind, Coriolis effect, coastline geometry and bottom topography (Strub et al., 1991, 1998) are working together at different spatial and temporal scales to fertilize the coastal zone and support the high productivity of coastal ecosystems. Despite the contributions of renewable emergy sources to the empower base and empower density of the benthic ecosystems examined and the delivery of macroalgae and shellfish from each of the three bays to the regional economy, upwelled nutrients together with the other renewable resource inflows evaluated in this work, usually, are not considered in cost-benefit analyses of the design and implementation of projects related to the thermoelectric and fish processing plants, the port and the sewage plant. (Sistema de Evaluación de Impacto Ambiental SEIA, 2016). 4.1. The importance of and impediments to environmental conservation in the coastal zone The coastal zone of central and northern Chile is influenced by upwelling events that support productive marine ecosystems, fishing and aquaculture. However, these activities co-occur with ports, electric power plants, chemical manufacturing, other industries and tourism, which are also important for a robust regional economy and have relevance to environmental conditions at the local and regional scale. As a consequence, the environmental authorities of Chile are assessing the possibility of declaring several coastal areas in the region as reserves for the preservation and conservation of biodiversity (Ministerio del Medio Ambiente, 2016). However, in the process of setting-up reserves, administrative authorities should consider the experience of managers with clandestine fish-

ing in La Rinconada Marine Reserve and its role in the failure ˜ et al., 2017). Better to effectively manage that system (Avendano fisheries management strategies are needed as a basis for the development and implementation of new targeted conservation policies; especially since, in the case of La Rinconada, the current policies have failed to achieve one of the primary objectives of marine reserves, i.e., the preservation of key species and biodiversity. Past studies by one of us (Campbell, unpublished results) indicate that if the fecundity of heavily exploited populations is protected, those populations tend to be more stable. For example, Maine lobster fishermen protect the larger, highly fecund females by agreement among themselves to v-notch the telson and return these animals to the water and this fishery has been stable for many years. Based ˜ et al. (2017), we believe that if fishing on observations of Avendano were allowed in La Rinconada, under the condition that the scallop divers agree to mark and return the largest scallops to the bed, the breeding stock might be better preserved and the main purpose of the reserve more effectively realized. Lu et al. (2007) suggested that the design and implementation of efficient policies aimed at balancing reasonable levels of exploitation with the conservation and protection of natural resources to achieve economically viable, socially acceptable and ecologically sustainable systems should be the primary objective of environmental management. Therefore, we suggest that these new management strategies for the northern coast of Chile be oriented toward the following aspects of environmental protection: (1) ecosystem protection to ensure the sustainability of fishing activities (e.g., by establishing marine parks, reserves and management areas) and (2) environmental protection of ecosystems from the impacts of industrial activities by eliminating “sacrifice” zones and promoting measures to safeguard the environment within its carrying capacities for various activities. However, both kinds of polices should be evaluated based on a systemic framework that simultaneously integrates the economic and ecological components of marine ecosystems with the overall goal of preserving biodiversity. This study showed that the importance of upwelling ecosystems can be attributed to the benefits that human beings derive from their renewable resources as measured, in part, by the market value of these products (for example, as shown by the anchovy and sardine fisheries, Aliaga et al., 2001; Gatica et al., 2007), but also by other ecosystem functions and services as measured with a variety of ecological indicators, oceanographic conditions, measures of climate change, etc. (Camus and Andrade, 1999; Graco et al., 2007; Sobarzo et al., 2007; Goubanova et al., 2010) and by emergy evaluation, which will be further discussed below. 4.2. Comparison of the properties of the three bays: Possible influence of the La Rinconada Marine Reserve The emergy base of the three benthic ecosystems includes the nitrogen upwelled, the energy of the tides and solar radiation.

F. Berrios et al. / Ecological Modelling 359 (2017) 146–164

157

Table 3 The turnover time, emergy input, energy storage, transformity, biomass emergy stored and emdollar value of the natural capital of commercial (bold type) and noncommercial biomass of Mejillones, Antofagasta and Tongoy Bays. The emergy of the biomass per m−2 is obtained by multiplying the emergy input by the turnover time to give the emergy contained in the biomass m−2 , which is then divided by the available energy contained to give the transformity. Finally, the emergy m−2 is divided by the EMR for Chile in 2008 (6.64E + 12 sej/$) to obtain the emdollar values. The total natural capital and total currency equivalents of market biomass of each bay are shown. Turnover time (y)

Emergy input (sej m−2 y−1 )

Energy (J m−2 )

Transformity (sej J−1 )

Biomass emergy (sej m−2 )

Emdollar (Em$ m−2 )

(A) Mejillones Bay Phytoplankton Lessonia trabeculata Chlorophyta Rhodophyta Phaeophyta Detritus Zooplankton Argopecten purpuratus Aulacomya Ater Tagelus dombeii Choromytilus chorus Gari solida Tegula spp. Small Epifauna Herbivore (SEH) Sea urchin species (SUS) Other Filter feeders (OFF) Thais chocolata Other Sea Star Species (OSS) Large Epifauna (LE) Small Epifauna Carnivore (SEC) Cancer spp. Luidia magallanica Total currency equivalents of market biomass

0.004 2.0 0.20 0.20 0.20 – 0.03 1.70 2.50 2.50 2.50 2.50 0.25 0.91 0.77 0.64 5.6 0.59 0.53 0.50 0.53 2.00

4.26E + 12 1.11E + 12 1.73E + 12 3.56E + 12 3.24E + 11 – 1.73E + 12 1.33E + 11 2.13E + 11 6.61E + 11 3.82E + 11 4.21E + 11 4.08E + 12 8.53E + 11 1.09E + 10 2.03E + 10 1.15E + 11 9.24E + 07 2.34E + 11 6.06E + 11 1.98E + 11 6.36E + 09

1.26E + 05 1.56E + 06 1.76E + 05 2.00E + 06 2.76E + 05 – 8.37E + 04 1.17E + 05 2.26E + 05 7.03E + 05 3.35E + 05 3.68E + 05 5.79E + 05 3.52E + 05 5.86E + 04 5.86E + 04 1.22E + 05 2.09E + 02 8.37E + 04 1.74E + 05 6.30E + 04 4.27E + 03

1.36E + 05 1.43E + 06 1.96E + 06 3.56E + 05 2.34E + 05 – 5.16E + 05 1.94E + 06 2.35E + 06 2.35E + 06 2.85E + 06 2.85E + 06 1.76E + 06 2.21E + 06 1.43E + 05 2.21E + 05 5.27E + 06 2.60E + 05 1.47E + 06 1.74E + 06 1.65E + 06 2.98E + 06

1.70E + 10 2.22E + 12 3.45E + 11 7.12E + 11 6.47E + 10 – 4.32E + 10 2.27E + 11 5.31E + 11 1.65E + 12 9.56E + 11 1.05E + 12 1.02E + 12 7.75E + 11 8.39E + 09 1.29E + 10 6.42E + 11 5.44E + 07 1.23E + 11 3.03E + 11 1.04E + 11 1.27E + 10

0.00257 0.33474 0.05198 0.10720 0.00975 – 0.00650 0.03412 0.08003 0.24899 0.14397 0.15837 0.15371 0.11679 0.00126 0.00195 0.09664 0.00001 0.01856 0.04561 0.01569 0.00192 1.10

(B) Antofagasta Bay Phytoplankton Lessonia trabeculata Chlorophyta Rhodophyta Phaeophyta Detritus Zooplankton Argopecten purpuratus Aulacomya Ater Tagelus dombeii Choromytilus chorus Transennella pannosa Protothaca thaca Tegula spp. Small Epifauna Herbivore (SEH) Sea urchin species (SUS) Other Filter feeders (OFF) Other Sea Star Species (OSS) Thais chocolata Large Epifauna (LE) Small Epifauna Carnivore (SEC) Cancer spp. Concholepas concholepas Luidia magallanica Octopus vulgaris Total currency equivalents of market biomass

0.004 2 0.20 0.20 0.20 – 0.03 1.7 0.56 2.5 2.5 2.5 2.5 0.25 0.91 0.77 0.67 0.59 5 0.53 0.50 0.53 6 2.00 2

3.32E + 12 1.42E + 12 6.33E + 11 8.31E + 11 7.68E + 11 – 8.08E + 11 2.91E + 10 6.71E + 10 1.50E + 11 6.21E + 10 1.66E + 12 3.59E + 11 6.87E + 11 2.02E + 12 1.30E + 11 1.80E + 10 7.64E + 09 2.24E + 11 2.35E + 10 1.73E + 11 1.16E + 10 1.06E + 11 5.61E + 11 1.22E + 09

2.09E + 05 9.75E + 05 1.05E + 05 1.84E + 05 1.85E + 05 – 8.37E + 04 5.44E + 04 1.26E + 05 3.41E + 05 1.00E + 05 3.30E + 06 6.72E + 05 6.55E + 04 6.79E + 05 2.93E + 04 1.38E + 05 5.08E + 04 1.72E + 05 8.37E + 03 5.02E + 04 3.56E + 03 1.53E + 04 3.30E + 05 5.86E + 02

6.35E + 04 2.92E + 06 1.21E + 06 9.02E + 05 8.29E + 05 – 2.41E + 05 9.08E + 05 2.97E + 05 1.10E + 06 1.54E + 06 1.26E + 06 1.34E + 06 2.62E + 06 2.70E + 06 3.42E + 06 8.70E + 04 8.84E + 04 6.54E + 06 1.48E + 06 1.72E + 06 1.71E + 06 4.16E + 07 3.40E + 06 4.17E + 06

1.33E + 10 2.85E + 12 1.27E + 11 1.66E + 11 1.54E + 11 – 2.02E + 10 4.94E + 10 3.73E + 10 3.75E + 11 1.55E + 11 4.14E + 12 8.97E + 11 1.72E + 11 1.83E + 12 1.00E + 11 1.20E + 10 4.49E + 09 1.12E + 12 1.24E + 10 8.66E + 10 6.09E + 09 6.37E + 11 1.12E + 12 2.44E + 09

0.00200 0.42886 0.01906 0.02502 0.02315 – 0.00304 0.00744 0.00561 0.05643 0.02336 0.62418 0.13516 0.02587 0.27612 0.01508 0.00181 0.00068 0.16896 0.00187 0.01305 0.00092 0.09599 0.16897 0.00037 1.82

0.004 0.67 0.17 0.18 0.17 – 0.03 1.7 0.83 1.25 0.45 0.67 0.23 0.31 0.27 0.51 1.43

2.03E + 12 6.49E + 11 4.57E + 11 6.40E + 11 2.91E + 11 – 7.93E + 11 1.34E + 11 5.85E + 10 9.02E + 10 5.33E + 11 7.78E + 09 1.19E + 11 8.57E + 10 6.60E + 10 5.98E + 10 9.51E + 08

1.17E + 05 4.60E + 05 3.29E + 05 4.60E + 05 2.09E + 05 – 7.53E + 04 2.30E + 05 1.00E + 05 9.54E + 03 1.59E + 05 2.72E + 03 2.51E + 05 8.37E + 04 7.53E + 04 1.67E + 04 5.44E + 03

6.92E + 04 9.40E + 05 2.32E + 05 2.53E + 05 2.32E + 05 – 2.63E + 05 9.91E + 05 4.86E + 05 1.18E + 07 1.52E + 06 1.91E + 06 1.08E + 05 3.20E + 05 2.37E + 05 1.83E + 06 2.50E + 05

8.12E + 09 4.33E + 11 7.62E + 10 1.16E + 11 4.85E + 10 – 1.98E + 10 2.28E + 11 4.88E + 10 1.13E + 11 2.42E + 11 5.19E + 09 2.71E + 10 2.68E + 10 1.78E + 10 3.06E + 10 1.36E + 09

0.00122 0.06519 0.01148 0.01753 0.00730 – 0.00299 0.03434 0.00735 0.01699 0.03651 0.00078 0.00408 0.00403 0.00269 0.00461 0.00020

Species/functional groups

(C) Tongoy Bay Phytoplankton Heterosostera tasmanica Chondracanthus chamissoi Rodophyta Ulva sp. Detritus Zooplankton Argopecten purpuratus Mulinia sp. Calyptraea trochiformis Tegula sp. Taliepus sp. Infauna Pyura chilensis Small Epifauna (SE) Paraxanthus barbiger Luidia magallanica

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Table 3 (Continued) Species/functional groups

Turnover time (y)

Emergy input (sej m−2 y−1 )

Energy (J m−2 )

Transformity (sej J−1 )

Biomass emergy (sej m−2 )

Emdollar (Em$ m−2 )

Xanthochorus cassidiformis Megenaster gelatinosus Heliaster helianthus Cancer porteri Cancer polyodon Cancer coronatus Large Epifauna (LE) Total currency equivalents of market biomass

0.67 0.83 1.67 2.00 0.91 0.56 0.80

7.05E + 09 1.18E + 11 4.01E + 09 3.98E + 09 1.34E + 11 8.47E + 09 3.26E + 10

1.00E + 04 9.04E + 04 4.60E + 03 1.47E + 04 4.19E + 04 1.05E + 04 2.30E + 04

4.68E + 05 1.08E + 06 1.45E + 06 5.43E + 05 2.92E + 06 4.50E + 05 1.13E + 06

4.70E + 09 9.79E + 10 6.69E + 09 7.96E + 09 1.22E + 11 4.70E + 09 2.61E + 10

0.00071 0.01475 0.00101 0.00120 0.01840 0.00071 0.00393 0.06

Total value of natural capital Emdollar (Em$ m−2 ) Emergy to Money Ratio Chile 2008 (sej/$)

Mejillones Bay 1.63 6.64E + 12

Antofagasta Bay 2.12

Tongoy Bay 0.26

Table 4 The biomass, biomass emergy, specific emergy, weight of the ecological fishery products harvested, g m−2 y−1 , the emergy harvested, the price per kilogram, the total weight of the ecological fishery products harvested from the bay are shown in this table. The area of each coastal system and the EMR for Chile in 2008 are also given. The biomass emergy per m2 was obtained from Table 3. Specific emergy is obtained from the biomass emergy divided by the energy contained in the biomass and the emergy harvested is obtained by multiplying this transformity by weight of the flow harvested. The weight of the harvest is found by multiplying the area of the coastal system by the flow harvested (yield per m2 per year). Species and functional groups shown for each bay correspond to those taken by artisanal benthic fishing. Biomass (g m−2 )

Biomass Emergy (sej m−2 )

Specific Emergy (sej g−1 )

Flow harvested (g m−2 y−1 )

Emergy harvested (sej m−2 y−1 )

Price/Kg US$

Weight (Kg)

(A) Mejillones Bay Lessonia trabeculata Argopecten purpuratus Aulacomya Ater Tagelus dombeii Choromytilus chorus Gari solida Thais chocolata Total

372.50 27.88 54.00 168.0 80.0 88.00 29.11

2.22E + 12 2.27E + 11 5.31E + 11 1.65E + 12 9.56E + 11 1.05E + 12 6.42E + 11

5.97E + 09 8.13E + 09 9.84E + 09 9.84E + 09 1.19E + 10 1.19E + 10 2.20E + 10

13.61 12.94 0.02 0.01 4.80 1.83 0.19 33.39

8.12E + 10 1.05E + 11 2.44E + 08 7.71E + 07 5.73E + 10 2.18E + 10 4.14E + 09 2.70E + 11

0.50 15.12 0.48 3.02 0.97 1.01 0.40

2.65E + 05 2.52E + 05 4.84E + 02 1.53E + 02 9.35E + 04 3.56E + 04 3.67E + 03 6.51E + 05

(B) Antofagasta Bay Lessonia trabeculata Argopecten purpuratus Tagelus dombeii Choromytilus chorus Transennella pannosa Protothaca thaca SEH OFF Thais chocolata Cancer spp. Concholepas concholepas Octopus vulgaris Total

232.83 13.00 81.38 24.00 787.57 160.51 162.20 33.00 40.99 0.85 3.66 0.14

2.85E + 12 4.94E + 10 3.75E + 11 1.55E + 11 4.14E + 12 8.97E + 11 1.83E + 12 1.20E + 10 1.12E + 12 6.09E + 09 6.37E + 11 2.44E + 09

1.22E + 10 3.80E + 09 4.60E + 09 6.46E + 09 5.26E + 09 5.59E + 09 1.13E + 10 3.64E + 08 2.74E + 10 7.16E + 09 1.74E + 11 1.75E + 10

21.11 5.50 0.02 0.89 11.03 16.05 0.02 0.003 3.60 0.0008 0.32 0.04 58.58

2.58E + 11 2.09E + 10 1.12E + 08 5.73E + 09 5.80E + 10 8.97E + 10 2.26E + 08 1.09E + 06 9.85E + 10 5.73E + 06 5.57E + 10 6.98E + 08 5.88E + 11

0.50 15.12 3.02 0.97 1.61 1.01 2.02 0.99 1.81 1.51 10.08 3.02

1.12E + 06 2.92E + 05 1.29E + 03 4.70E + 04 5.84E + 05 8.51E + 05 1.06E + 03 1.59E + 02 1.91E + 05 4.24E + 01 1.70E + 04 2.12E + 03 3.10E + 06

78.60 55.00 2.28 10.00

7.62E + 10 2.28E + 11 4.70E + 09 1.22E + 11

9.70E + 08 4.15E + 09 2.06E + 09 1.22E + 10

114.00 116.00 0.60 0.40 231.00

1.11E + 11 4.81E + 11 1.24E + 09 4.89E + 09 5.98E + 11

1.01 15.12 1.01 2.02

3.11E + 06 3.17E + 06 1.64E + 04 1.09E + 04 6.31E + 06

Mejillones 1.95E + 07

Antofagasta 5.30E + 07

Tongoy 2.73E + 07

(C) Tongoy Bay Chondracanthus chamissoi Argopecten purpuratus Xanthochorus cassidiformis Cancer polyodon Total Coastal system Area (m−2 )

Wave energy was not included, because the systems examined are deeper than the surf zone. Antofagasta Bay encompasses the largest area followed by Tongoy and then Mejillones Bay, however, the empower base for Mejillones Bay is greater than that of Tongoy Bay. The intermediate value of the empower input to Mejillones Bay combined with the fact that it covers the smallest area causes the empower density of the emergy inputs to be highest in this bay. As a result, a similar pattern is observed for the emdollar and hypothetical dollar density in the three bays. The three bays have very distinct ecological properties and one, Antofagasta Bay, contains a marine reserve; one, Mejillones Bay, is heavily influenced by industrial activities and one, Tongoy Bay, is dominated by its artisanal fisheries. To a first order approximation, we may assume that these dominate characteristics of the three bays should be reflected in their observed properties. Of particular interest in this paper is the role that La Rinconada Marine

Reserve may play in explaining the characteristics of the benthic ecosystems in Antofagasta Bay relative to the other two bays. It is not surprising that the heavily industrialized Mejillones Bay has the largest network empower flow, but Antofagasta Bay with its greater species conservation potential has the largest empower flow of commercially valuable species and the largest species and category richness. La Rinconada’s potential to help preserve species may also be seen in the fact that the benthic ecosystem network there has the highest emergy density of natural capital (Em$ m−2 ) for both the entire network and for commercially valuable species. Tongoy Bay, which had the lowest emergy flow in its benthic network and the lowest values of natural capital, excelled in the mass of commercial species harvested, in part, due to the development of scallop aquaculture in this bay. Despite the large difference in the mass harvested per unit area between Tongoy and Antofagasta Bays, there was little difference (1.7%) in the empower density of

F. Berrios et al. / Ecological Modelling 359 (2017) 146–164

159

Table 5 Emergy harvested from the coastal system (Y) by the benthic artisanal fishery, the money received for the yield (MY ), the emergy that can be purchased with the money received (YM ); the EBE, showing the loss or gain to the sellers in emdollars (Em$) = (Y/EMR − YM /EMR), the EER with advantage to the seller (YM /Y) and with advantage to the buyer (Y/YM ) are given in this table. The emergy that can be purchased by MY is estimated as (MY * EMR), where EMR is for Chile in 2008 (6.64E + 12 sej/$). The EBE is obtained by subtracting Y from YM with a positive number benefiting the sellers. The indices are shown for each commercially harvested species in each bay and as the sum or average as appropriate for the index in each bay. Emergy harvested

Value

Emergy can be

Loss or gain to the

Advantage

Y

My

purchased by MY

EBE

sellers

EER

to buyer

(A) Mejillones Bay Lessonia trabeculata Argopecten purpuratus Aulacomya Ater Tagelus dombeii Choromytilus chorus Gari solida Thais chocolata Total

(sej y−1 ) 1.58E + 18 2.05E + 18 4.76E + 15 1.50E + 15 1.12E + 18 4.25E + 17 8.08E + 16 5.26E + 18

(US$ y−1 ) 1.34E + 05 3.82E + 06 2.34E + 02 4.62E + 02 9.05E + 04 3.59E + 04 1.48E + 03

Ym = (sej y−1 ) 8.88E + 17 2.53E + 19 1.55E + 15 3.07E + 15 6.01E + 17 2.38E + 17 9.82E + 15 2.71E + 19

(sej y−1 ) -6.95E + 17 2.33E + 19 -3.21E + 15 1.56E + 15 -5.17E + 17 -1.87E + 17 -7.10E + 16 2.18E + 19

(EM$) -1.05E + 05 3.51E + 06 -4.83E + 02 2.35E + 02 -7.78E + 04 -2.82E + 04 -1.07E + 04 3.28E + 06

0.56 12.36 0.33 2.04 0.54 0.56 0.12 5.14

1.78:1 0.08:1 3.06:1 0.49:1 1.86:1 1.79:1 8.23:1 0.19:1

(B) Antofagasta Bay Lessonia trabeculata Argopecten purpuratus Tagelus dombeii Choromytilus chorus Transennella pannosa OFF Protothaca thaca SEH Cancer spp. Thais chocolata Concholepas concholepas Octopus vulgaris Total

1.37E + 19 1.11E + 18 5.95E + 15 3.04E + 17 3.08E + 18 5.79E + 13 4.76E + 18 1.20E + 16 3.04E + 14 5.22E + 18 2.95E + 18 3.70E + 16 3.12E + 19

2.07E + 05 1.62E + 06 1.44E + 03 1.67E + 04 3.47E + 05 5.78E + 01 3.15E + 05 7.86E + 02 2.36E + 01 1.27E + 05 6.29E + 04 2.36E + 03

1.38E + 18 1.08E + 19 9.55E + 15 1.11E + 17 2.30E + 18 3.84E + 14 2.09E + 18 5.22E + 15 1.57E + 14 8.46E + 17 4.18E + 17 1.57E + 16 1.79E + 19

-1.23E + 19 9.66E + 18 3.60E + 15 -1.93E + 17 -7.73E + 17 3.26E + 14 -2.66E + 18 -6.76E + 15 -1.47E + 14 -4.38E + 18 -2.54E + 18 -2.13E + 16 -1.32E + 19

-1.85E + 06 1.45E + 06 5.42E + 02 -2.90E + 04 -1.16E + 05 4.91E + 01 -4.01E + 05 -1.02E + 03 -2.21E + 01 -6.59E + 05 -3.82E + 05 -3.21E + 03 -1.99E + 06

0.10 9.72 1.60 0.37 0.75 6.63 0.44 0.44 0.52 0.16 0.14 0.42 0.58

9.93:1 0.10:1 0.62:1 2.73:1 1.34:1 0.15:1 2.27:1 2.29:1 1.94:1 6.17:1 7.07:1 2.36:1 1.74:1

(C) Tongoy Bay Chondracanthus chamissoi Argopecten purpuratus Xanthochorus cassidiformis Cancer polyodon Total Emergy to Money Ratio Chile 2008 (sej/$)

3.02E + 18 1.31E + 19 3.38E + 16 1.33E + 17 1.63E + 19 6.64E + 12

2.24E + 06 3.42E + 07 1.18E + 04 1.57E + 04

1.49E + 19 2.27E + 20 7.83E + 16 1.04E + 17 2.42E + 20

1.19E + 19 2.14E + 20 4.46E + 16 −2.90E + 16 2.26E + 20

1.79E + 06 3.22E + 07 6.71E + 03 −4.37E + 03 3.40E + 07

4.93 17.30 2.32 0.78 14.84

0.20:1 0.06:1 0.43:1 1.28:1 0.07:1

the harvest. This effect is due to the higher network diversity and greater number of species harvested from different positions in the trophic web in Antofagasta Bay. Higher network diversity and a more developed trophic web are associated with effective conservation programs (Libralato et al., 2010; Colléter et al., 2012). Many shellfish in Antofagasta Bay are harvested with an advantage to the buyer and this is true when the total output of the whole bay is considered. Thus, the possible conservation benefits that are described above, apparently, are not being reinforced effectively by the economic exchange of real wealth in its fishery products. In this case, there may be a role for better management to provide the feedback needed to support the benefits to the region gained from the marine reserve. These management measures should regulate the illegal fishermen, who have been greatly favored by the sale of this protected resource on the market. For example, between the 2001 and 2002 about 8.4 million supposedly protected scallops were ˜ and removed from the Marine Reserve by illegal fishing (Avendano Cantillánez, 2005). These illegal landings are not recorded in the official statistics, consequently affecting decision-making. A feed˜ et al. (2017) to improve back mechanism proposed by Avendano reserve management is harvesting regulated by stock dependent fishing quotas implemented through a “co-management” strategy, in which the fishermen and governmental authorities both participate. This system could have a similar result to that found in the Maine lobster fishery, mentioned earlier, but it would only be effective, if the currently illegal fishermen agree to conserve species ˜ et al. (2017) to susfecundity. The plan proposed by Avendano tainably exploit the valuable resources of La Rinconada appears to be a reasonable initiative, but it should be evaluated in a systemic context that includes the ecosystems, socio-economic and

environmental components within an integrated framework. The relevance of our analysis, which was carried out on a larger scale, is that it showed that the current balance of benefits gained through economic exchange lacks a surplus for the bay as a whole that could allow the protection and conservation of the natural systems of Antofagasta Bay. Thus, we conclude that balanced feedback mechanisms from markets to the bay are lacking, which converges with ˜ et al. (2017) for La Rinconada Marine the conclusions of Avendano Reserve made on a smaller scale.

4.3. Comparison of the three bays to other systems Economic activities are known to intervene in the processes of natural systems located in coastal areas (Odum and Arding, 1991; Vassallo et al., 2009). Thus, it is important to know the relative value of natural processes on an equal basis with economic ones. In this regard, a recent study carried out by Campbell et al. (2015) estimated an Em$ value (1.7E07 Em$) for the empower basis of production in Narragansett Bay including rain, waves, tides and rivers, and an empower basis for phytoplankton production 2.3E07 Em$. These results are similar to our results obtained for Mejillones Bay; however, these values were different from those found in Antofagasta and Tongoy Bays. This outcome might be taken to suggest that Mejillones Bay might have certain characteristics in terms of inflow, enrichment, productive processes and oceanographic features similar to Narragansett Bay. For example, both are nutrient enriched with the circulation pattern of Narragansett Bay bringing nutrients from deeper off shore waters, but nutrient input to Narragansett Bay is also enriched by sewage (Nixon, 1997). However, when comparing the three bays, the empower bases of the benthic

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production systems of Antofagasta and Mejillones Bays are greater than that of Tongoy Bay. Also, the highest magnitudes of nonrenewable empower density in coastal watersheds coincide with greater pressure on ecological services and processes (Brandt-Williams et al., 2013) as a consequence of the increased use of the coastal zone by human activities. Since Mejillones and Antofagasta have more developed coastlines and greater production, any adverse effects of economic activities on primary producers and benthic ecosystems are expected to be higher in these two bays compared to Tongoy Bay. The same pattern is repeated for the emergy base per unit area (Em$ m−2 ) required to sustain the benthic ecosystem networks. 4.4. Evaluation of natural capital Our evaluation of the natural capital values of species within the three coastal marine systems showed the importance of commercially important resources, which had high emdollar values, as well as, the relative importance of noncommercial species that currently do not reflect consumer preferences. For example, within Mejillones Bay, we found the L. trabeculata- Tegula spp. complex (a marketed producer and a non-marketed consumer), T. dombeii (a marketed consumer and filter feeder) and G. solida (a marketed consumer and filter feeder) are the key species associations. Within Antofagasta Bay, we found that the T. pannosa – T. chocolata – L. magallanica complex (a marketed consumer and filter feeder, a marketed consumer and a non-marketed consumer) and the L. trabeculata-SEH complex (a marketed producer and marketed consumers) are the key species associations; and within Tongoy we found that H. tasmanica-Tegula sp. (a non-marketed producer and a non-marketed consumer), as well as the scallop A. purpuratus (a marketed consumer and filter feeder) are the key species and associations. These key species associations in each bay are the most important system components, whose temporal trajectories should be followed to monitor the sustainability of the current ecosystem networks. These observations from our analysis on the character of the three bays coincide with ecological indicators that have already been investigated, such as the effect of direct and indirect propagation on species success, ecosystem resilience and the keystone species complexes registered for the three bays (Ortiz and Wolff, 2002; Ortiz et al., 2013; Ortiz et al., 2015). 4.5. Significance of the emergy balance of trade When considering the relationship between the coastal ecosystem and its next larger economic system in Tongoy Bay, we found that the emergy balance of trade favored the sellers after exchange on the regional and national market. On one hand, the trade balance in favor of the fishermen was driven by the premium price paid by the buyers for some species, especially Argopecten purpuratus, where the emergy of the products sold was lower than that of the emergy that could be purchased on the national market with the money paid for the fishery products. In contrast, buyers had a considerable advantage (9.93:1) when purchasing Lessonia trabeculata from Antofagasta Bay sellers, since this species grows abundantly there. Thus, one way that buyers can realize a considerable advantage is when they can acquire certain products that are available in high supply. Buyers can also purchase fishery products at an advantage when the market for the harvested product is not strong. This pattern shows up clearly when the EBEs of all products harvested by the artisanal fishery are examined. This lack of balance in the buying power received in exchange for most shellfish harvested by artisanal fishermen may explain, in part, the current difficulties ˜ et al., 2008; Ortiz and Levins, unpubfacing this industry (Zuniga lished results). Even though overall, Antofagasta Bay sold products at an advantage to the buyers, fishermen also benefited from the

premium price paid for scallops, which are sold at an advantage to the seller of 9.72:1. The Antofagasta Bay region receives the lowest benefits in the emergy balance of trade after exchange on the regional and national markets, due to the large removal of biomass with less remuneration from the market. These results are interesting because Mejillones Bay reported similar behavior to Tongoy Bay in terms of the exchange transactions for fisheries products even though both belong to regions with different economic dynamics (GDP, Banco Central Chile, 2017). However; they are different, because in Tongoy Bay intensive fishing has produced changes in ecosystem structure and functioning over time (Gonzáles et al., 2016). However, the fishermen of Tongoy Bay were stimulated by the high market value of their products and over time established scallop farming to meet the demand, which may explain, in part, the benefit gained by Tongoy fishermen in the balance of market exchange. It is evident that despite the work done in Antofagasta Bay by the ecological services supplied by the coastal system’s emergy signature, and the empower density base of the benthic productive systems required to sustain benthicnetworks that support the landings, the market fails to efficiently allocate value to the fishery and ecological resources of this bay. Measures implemented in Tongoy Bay might help the trade balance between fishermen and the regional economy observed in Antofagasta Bay, if maximizing economic output was a management priority for Antofagasta Bay. In this regard, fisheries authorities could implement measures to promote feedback mechanisms such as repopulation, adaptive cultivation or ecosystem rehabilitation to compensate for the use of these systems and as payment for their contributions as has been suggested by Odum (1996, 2007). However, since a high conservation potential for benthic ecosystem networks and species currently exists in Antofagasta Bay, as shown by the analyses performed in this study, and these beneficial properties are associated with the presence of and may be supported by La Rinconada Marine Reserve, development policies should be implemented with due caution for maintaining the biodiversity of this bay (Lu et al., 2012). An important output to the economy from all three bays is the scallop Argopecten purpuratus (a protected species), which recorded its highest values of network emergy flow and natural capital storage in Tongoy and Mejillones Bays. This is important because building the Port Complex of Mejillones negatively affected a portion of this population and as a protective measure individuals ˜ and were translocated to another sector within the bay (Avendano Cantillánez, 2003). Economic activity grew notably in Mejillones Bay, during the last decade, and thus, the cost in terms of the loss of ecological services was higher compared to the other bays. Another commercially important resource is the kelp, Lessonia trabeculata, which inhabits both Mejillones and Antofagasta Bays and it recorded the highest value contribution to the buyers in Antofagasta Bay delivering more emergy than was available in the buying power of the payment. Also, it was the highest emergy output from Antofagasta Bay with more benefit gained in market exchange by buyers in Antofagasta Bay (9.93:1) compared to Mejillones Bay (1.78:1). 4.6. Limitations and usefulness of the analysis This analysis allowed the estimation of the emdollar value (i.e., the real wealth or emergy) of each flow in the benthic ecosystem network, the empower density of natural capital (i.e., the stored real wealth in the biomass of species and functional groups) and the output of useful fishery products. In addition, the analysis included an estimate of the total value of ecosystems services provided by these benthic ecosystems in hypothetical US dollars. As a result, our analysis captured information on the global properties of the benthic ecosystems in multiple dimensions. Information that is fre-

F. Berrios et al. / Ecological Modelling 359 (2017) 146–164

quently ignored in the classical input-output analysis (Grönlund et al., 2015; Li et al., 2016). The focus on network evaluation in this study is related to the work of Brown et al. (2006) and somewhat different from many past studies that have quantified the emergy and emdollar value of renewable environmental goods and services that are used directly and indirectly in supporting a territorial system or in evaluating economic production processes (Odum and Arding, 1991; Ton et al., 1998; Bardi, 2002; Campbell and Brown, 2012; Campbell and Tilley, 2014; Campbell et al., 2015). Thus, the potential for comparison of our results to other studies is limited. The analysis of the emdollar value of fisheries products presented in this study relied on the assessment of the benthic ecosystem in a narrow band of the coastal zone and as such our results can be reproduced and will be comparable to any similar analyses where the emergy basis of the coastal ecosystem network is quantified and the ex-vessel prices of the fishery products are known along with the necessary supporting data, e.g., the EMR of the relevant economy. Quantifying the ecosystem emergy signature and network of flows in terms of emdollar flows also allows the determination of emdollar values for commercial and noncommercial species that could be of use in economic analyses as an alternative method of establishing the expected prices of natural products when the market is close to an equilibrium based on the supply of products from ecosystems operating at steady state conditions. Campbell and Cai (2007) demonstrated that transformity of products in a value-added chain of US forest products was significantly correlated to the price of the products, except when the biophysically-based supply-demand relationship was perturbed. In addition to the direct contributions of the benthic fisheries ecosystems to the regional economy, we estimated the total ecosystem services provided to the regional economy by the emergy signatures of the three coastal benthic ecosystems. As mentioned above, this estimate was obtained by using the simplified assumption of Pulselli et al. (2011) and Coscieme at al. (2014) that the primary emergy base of the Earth can be directly related to an approximate estimate of the hypothetical value of contributions of the environment to the global economy. Such a complete accounting of the work of the environment in monetary terms is notoriously difficult to obtain (Odum and Odum, 2000; Campbell, 2014), because, in general, these work contributions are complex and external to markets. Economic valuation of environmental goods and services is difficult, because economic methods must rely directly or indirectly on hypothetical values rather than on market value, where money has been exchanged for a product or service. Nevertheless, we decided that an approximate estimate of the total environmental goods and services provided to the regional economy by the three bays would provide useful information, which would be more valuable than having no estimate. In the current contribution, we recognize the following uncertainties and simplifications used in the assessment of emergy and in the calculation of the emergy indices: (1) Total emergy input is strongly related to nutrients and the kinetic energy of upwelling in Antofagasta and Mejillones Bays. There were no studies or hydrodynamic models to be used in describing these phenomena in the two bays. In this study, the hydrodynamic model for Tongoy Bay was used to make first order estimates for Antofagasta and Mejillones Bays. (2) In evaluating the benthic networks the split strategy was applied, assuming that the contribution of possible co-products such as feces, pseudo feces and mortality to detritus would have the same properties, fate and condition. Recently, Vassallo et al. (2017) proposed an emergy assessment method for marine ecosystems that included co-products in the ecosystem network evaluation. In the future, we plan to explore co-product formulations of the network in evaluating the benthic ecosystems of coastal Chile. (3) In addition, only five renewable resources were considered in determining the environmental emergy base for the bays. Despite these

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simplifications and approximations, we believe that emergy analysis provides a useful tool for the valuation of ecosystem networks and their goods and services by integrating information on available energy, material and money flows simultaneously in the analysis. One drawback is that a considerable amount of time and information is required to complete the analysis, and thus simplifications are sometimes necessary. In this study, our intention was to use Energy Systems Theory and emergy analysis to obtain a fair valuation of coastal ecosystem goods and services and as a result provide supporting arguments to guide the implementation of alternative management policies that promote sustainable coastal ecosystems and help develop a better understanding of the possible role of marine reserves in conserving high value ecosystem properties. Also, we showed how the valorization of fisheries and total ecosystem services can be included in an analysis, allowing stakeholders involved in the promotion of different management strategies to assess the possible outcomes of alternative actions. We suggest that monetary resources, such as tax payments for potential environmental damage be set aside to promote the conservation of marine reserves and benthic ecosystem fisheries in the region and that these funds should be assigned solely to rehabilitate the regional coastal ecosystems affected by perturbations and that they not be used for other purposes.

5. Conclusions In this study, we performed emergy evaluations of three coastal bays on the northern coast of Chile that can be used to help understand the effects of existing and proposed conservation policies, e.g., the use of marine reserves, as well as the overall all effects of harnessing ecosystem empower flows (fishery products) and their coupling with the regional economy through market exchanges. This analysis reveals the patterns of the benefit and loss of real wealth (i.e., emergy) that reinforces certain ecosystem patterns and discourages others. We evaluated the contributions of benthic ecosystem-based fisheries and total ecosystem services to the regional economy of northern Chile. Based on our results, the emdollar or emergy flows (EM$ or sej y−1 ) and the flows of ecosystem services (hypothetical US$ y−1 ) associated with upwelled nutrients (i.e., nitrate nitrogen) contributed the most to support the system (average 1.50E + 07 Em$, 1.82E + 08 US$ y−1 ). The characteristics of the benthic ecosystem in Antofagasta Bay, when compared to the other two bays imply that the presence of La Rinconada Marine Reserve may play a role in determining the high species diversity and the greater development of natural capital and trophic network organization found in that bay. Power and control loops between the benthic ecosystems of the three bays and the regional economy indicate that the scallop, Argopecten purpuratus is the key species accounting for most of the net transfer of Em$ (real wealth) to the fishermen and by extension to the region; whereas, the kelp, Lessonia trabeculata is the primary species transferring real wealth to the buyers, who are ostensibly responsible for the removal of real wealth from the region. Fisheries associated with the benthic ecosystems of the coastal zones of the three bays contribute about 8% of the total support value that ecosystem services provide to the regional economy. We showed that trophic network analysis combined with emergy evaluation can be a useful tool in developing conservation and preservation strategies for use in supporting coastal ecosystems. Finally, we demonstrated the usefulness of analyzing the power and control loops between coastal ecosystems and their regional economies using the EBE and the EER to reveal the equity of trade in terms of the exchange of real wealth for whole fishery systems and for individual species.

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Acknowledgments

References

This work was conducted as part of the doctoral thesis of the first author finance by Chilean National Commission for Scientific and Technical Development (CONICYT) and the Programa de Doctorado en Ciencias Aplicadas mención Sistemas Marinos Costeros at the University of Antofagasta, Chile.

Airoldi, L., Beck, M.W., 2007. Loss, status and trends for coastal marine habitats of Europe. Oceanogr. Mar. Biol. 45, 345–405. Aliaga, B.R., Gómez, D.U., Neira, S.A., 2001. Análisis bioeconómico de la pesquería de sardina (Sardinops sagax) y anchoveta (Engraulis ringens) de la zona norte de Chile. Invest. Mar. Valparaíso 29 (2), 15–23. ˜ M., Cantillánez, S., 2003. Population estimates, extraction, and Avendano, translocation of the pectinid Argopecten purpuratus within Mejillones Bay, Chile. Sci. Mar. 67 (3), 285–292. ˜ M., Cantillánez, S., 2005. Growth and population structure of Argopecten Avendano, purpuratus at La Rinconada Marine Reserve, Antofagasta, Chile. Cienc Mar. 31 (3), 491–503.

Appendix A. See Table A1 Table A1 Calculation and data sources of the energy signatures for the three coastal systems. Sources energy

1 Solar radiation Area (m2 ) Radiation solar (J m −2 year−1 ) Albedo Equation: (area × solar radiation × (1-albedo)) Total solar energy inflow (J year−1 ) 2 Wind Area (m2 ) Density (kg m−3 ) Drag coefficient Wind velocity (m s−1 ) Time (seconds year−1 ) Geostrophic wind velocity Equation: (area × density × drag coefficient × (wind velocity)3 × time) Total solar energy inflow (J year−1 ) 3 Wave Shore length (m) Absorption ratio (amplitude is 1/8 height) Density (kg m−3 ) Mean wave height (m) Gravity (m s−2 ) Time (seconds year−1 ) Wave velocity (m s−1 ) Equation: (Shore length × absorption ratio × density × gravity × (height)2 × velocity × seconds year−1 ) Total solar energy inflow (J year−1 ) 4 Tide Area (m2 ) Tides per year (n◦ year−1 ) Height (m) Density (kg m−3 ) Gravity (m s−2 ) Equation: (area × (height)2 × density × 0.5 x (tides year−1 ) × gravity Total solar energy inflow (J year−1 ) 5 Nutrients nitrogen inflowing from upwelled deepwater Concentration difference between AESS and SSW in grams (g m−3 ) Frequency of upwelling events fraction of days with upwelling Volume of upwelled water m3 entering each Bay per year Annual nitrate nitrogen received g NO3-N year−1 Molar weight (g Mol−1 ) Annual influx of NO3 -N in moles Gibb’s free energy of formation HNO3 per mole Equivalence in Joules (J Mol−1 ) Total solar energy inflow (J year−1 )

Bays Mejillones

Antofagasta

Tongoy

1.95E + 07 8.30E + 09 0.27

Data 5.30E + 07 8.30E + 09 0.27

2.73E + 07 7.34E + 09 0.26

1.18E + 17

3.21E + 17

1.48E + 17

1.95E + 07 1.225 0.001 8 3.16E + 07 13.33

5.30E + 07 1.225 0.001 8 3.16E + 07 13.33

2.73E + 07 1.225 0.001 7.9 3.16E + 07 13.17

1.79E + 15

4.86E + 15

2.41E + 15

2.60E + 04 0.13 1.03E + 03 0.19 9.80 3.15E + 07 4.95

5.30E + 04 0.13 1.03E + 03 1.00 9.80 3.15E + 07 4.95

2.20E + 04 0.13 1.03E + 03 0.25 9.80 3.15E + 07 4.95

9.07E + 13

5.26E + 15

1.36E + 14

1.95E + 07 730 1.21 1.03E + 03 9.8

5.30E + 07 730 1.21 1.03E + 03 9.8

2.73E + 07 730 0.9 1.03E + 03 9.8

1.05E + 14

2.86E + 14

8.09E + 13

0.36 0.66 1.16E + 10 4.11E + 09 62.00 4.38E + 07 7.99E + 04 3.50E + 12

0.36 0.9 1.81E + 10 6.43E + 09 62.00 9.33E + 07 7.99E + 04 7.45E + 12

0.36 0.71 7.10E + 09 2.52E + 09 62.00 2.90E + 07 7.99E + 04 2.31E + 12

Data source 1 2 3

1 4 5 6

8

9

10

1 7

11 12 1 13 14

1 This study 2, 3 NASA Surface Meteorology and Solar Energy https://eosweb.larc.nasa.gov/sseRETScreen/. 4, 5 Density of sea level 15◦ celsuis and drag coefficient over water. 6 Dirección Metereólogica de Chile. http://www.164.77.222.61/climatologia/. 7 Servicio Hidrográfico y Oceanográfico de la Armada de Chile. http://www.shoa.cl/ 7, 8 This study 9 http://www.walker.dgf.uchile.cl/explorador/marino 10 This study where velocity is square root of (gravity) × (depth) Odum (1996). These waves can be described by the shallow water wave equation apply to an average depth of 2.5 m. Motion of wave is only effective at moving water to depths equal to one half of the wave length (L/2) apply to the average depths from 2.5 m (from the 5 m isobath to the shore). 11 Concentration difference between Equatorial Subsurface Water (ESSW) and Subtropical Surfacer Water (SSW) given by Cerda et al. (2005). 12 Vásquez et al. (1998). 13,14Molar weight and Gibb×s free energy. http://www.widedchemist.com

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