Revelation of critical gaps in fisheries management of bull kelp Durvillaea antarctica (Chamisso) in the central coast of the Maule Region of Chile through the application of the DPSIR conceptual framework

The brown bull-kelp Durvillaea antarctica (Chamisso) Hariot is an ecosystem engineering species (Peteiro, 2018) that is distributed exclusively along the southern hemisphere coasts of New Zealand, the Subantarctic Islands, and Chile (Graham et al., 2007; Vásquez, 2008; Fraser et al., 2010). In Chile, this alga is an economically important resource, usually known as “Cochayuyo”. Distributed from south of Coquimbo (30°S) to Cape Horn (56°S) (Vásquez, 2008; Velásquez et al., 2020), between the exposed rocky intertidal and subtidal zone where it usually cohabits in the intertidal with another commercially important kelp: Lessonia spicata (Santelices et al., 1980, Santelices, 1990; Westermeier et al., 1994). However, landings of the D. antarctica resource are marginal compared to the brown algae group (Vásquez, 2016). Their use is no less important since it mainly supplies the national market as direct food (Ortiz et al., 2006) and the international market as raw materials for the alginate industry (Peteiro, 2018). In addition, this resource represents a rich source of nutrients (Ortiz et al., 2006) that converts it into healthy food for animals (Quiñones et al., 2021) and human nutrition (Astorga-España and Mansilla, 2014). These properties have led to the development of a variety of products based on the algae, such as hamburgers, cereal bars, and mixtures with flour, among others (Velásquez et al., 2020). Also, D. antarctica is characterized by high alginate yields compared to other kelp (Kelly and Brown, 2000), making it very attractive for this industry. At the national level, Cochayuyo exports have experienced a sharp increase since 2006, exceeding 2000 tonnes in 2013 (SUBPESCA, 2017). This has meant an increase in foreign exchange returns of around 130 million (USD), mainly derived from sales to Taiwan, China, and Norway (SUBPESCA, 2017). As a consequence, landings coming mainly from wild populations in Open Access Areas (OAAs) between the regions of Coquimbo (IV, 30°S) and Los Lagos (X, 41°S), have increased in recent years, exceeding 8000 tonnes in 2021 (SERNAPESCA, 2023). In response to the increase in fishing pressure on the resource, the Subsecretaría de Pesca y Acuicultura (SUBPESCA) (Undersecretary of Fisheries and Aquaculture), the entity responsible for managing fishery resources in Chile, has implemented fishing regulation measures. These consist in setting minimum extraction sizes, the establishment of closed seasons that prohibit fishing, annual catch quotas, and research fishing. It should be noted that this fishery involves, in addition to the artisanal fishermen’ unions, Araucanian “Mapuche” families in the southern coastal area of the Araucanía Province, in the VIII Bio-Bio Region (Castilla and Fernandez, 1998; FIP, 2005). These native groups have traditionally used a self-management strategy, which is replicated in other areas (Gelcich et al., 2006), based on the allocation of rights to sites and rotational use for the exploitation of D. antarctica algae along the coast (outside the legal administrative framework) to eligible members of a community through a lottery system that excludes strangers (Castilla and Fernandez, 1998; Gelcich et al., 2006).

Under this context, it is important to highlight that fishery constitute complex socio-ecological systems (Ortiz & Levins, 2011; 2018; Berrios et al., 2021) and that, therefore, systems-based frameworks seem to be the most appropriate approaches to identify potential critical targets for management and conservation interventions (Binder et al., 2013). In this regard, the Driver-Pressure-State-Impact-Response (DPSIR) conceptual modelling framework (EEA, 1999) is a practical and paramount solution to address a complex problem or a necessity in fishery management. This approach allows linking through the construction of conceptual models of the cause-effect relationships between the drivers that pressure the system which, as a result, change its state and propagate impacts (positive and negative) on society and to which management entities can respond. This conceptual framework has recently been used to describe the fisheries performance of brown algae in response to fishery management measures in northern Chile (Campos et al., 2021; Berrios et al., 2022). In addition, it has been used to examine the responses of different coastal marine systems intervened by aquaculture activities (Serpa and Duarte, 2008; Whitmarsh and Palmieri, 2009; Cranford et al., 2012), fishery activities (Mangi et al., 2007; Gebremedhin et al., 2018; Dzoga et al., 2020), industrial operations (Norpadzlihatun et al., 2012; Liu et al., 2020), and marine pollution (Miranda et al., 2020; Federigi et al., 2022; Skirtun et al., 2022).

In this study, we evaluate the situation of the D. antarctica algae fishery on the coast of the Maule Region in central Chile. This Region is located in the center of the two most important regions in terms of landings: Exploitation is mainly from wild populations in open access areas (OAAs) whose main final destination is human consumption in the domestic market. Moreover, the Maule Region is a high-frequency and intensity tectonic zone, the last one being in 2010 (Jara-Muñoz et al., 2015), which generated a large tsunami (Vargas et al., 2011; Yoshimoto et al., 2016), an event that had negative consequences on the coastal biological communities. In this framework, the present research performs a global assessment of the development of the D. antarctica alga fishery on the coast of the Maule Region, represented by a conceptual DPSIR model. This is in order to i) identify and classify the main factors that drive, pressure, change the state and impact the development of the algae resource fishery, as well as the influence of administrative responses, and ii) a research priority establishment proposal for sustainable fishery management scenarios based on the detection of the information gaps revealed in the construction of the DPSIR conceptual model.