Research

INTRODUCTION

Coastal marine habitats, renowned for their valuable biodiversity, provide important contributions to human well-being (Barbier 2012, Sala et al. 2021). These habitats offer essential benefits such as breeding and reproduction grounds for marine biodiversity (Faria et al. 2021), protection from coastal erosion, flood control, climate change mitigation and adaptation (Smale et al. 2019), and storage of blue carbon (Lovelock and Duarte 2019). Furthermore, they contribute significantly to the provisioning of food from aquaculture and fisheries (Alleway et al. 2019) and offer many cultural benefits such as recreation, scenic beauty, natural heritage, and sense of place (Petrosillo et al. 2007). Many of these contributions are reciprocal because cultural practices are rooted in long-standing customs that reinforce ecosystem resilience (Ojeda et al. 2022).

However, marine ecosystems globally face substantial changes due to escalating human activities, raising concerns about the cumulative impacts of these stressors on biodiversity, ecosystem health, and human well-being (Curren et al. 2022). Human-induced changes such as climate change, overexploitation of marine resources, habitat loss, pollution, and the spread of invasive species pose significant threats to marine biodiversity, which forms the foundation for the numerous benefits that nature provides to societies (IPBES 2019). Moreover, climate change and habitat loss drivers interact, affecting nature’s ability to regulate emissions and protect coasts against extreme weather conditions, affecting coastal livelihoods and their relationships with nature (He and Silliman 2019).

Urgent climate action necessitates adaptation policies that simultaneously address climate change and biodiversity loss (Pörtner et al. 2021). Marine protected areas (MPAs) emerge as effective climate change adaptation strategies, promoting the health and resilience of marine habitats and offering various contributions to human well-being (Roberts et al. 2017, Seddon et al. 2021). In Chilean Patagonia, the marine coastal ecosystems, especially those within MPAs, represent critical climate refugia for marine biodiversity and can play a vital role in adapting to climate change (O’Regan et al. 2021). The region’s high species richness, diverse marine habitats, rate of endemism, and the continuous discovery of new species underscore its significance (Friedlander et al. 2018, 2020, Häussermann et al. 2021, Addamo et al. 2022).

Our study aims to advance the understanding of regional risks in coastal marine habitats, specifically in the context of MPAs in Chilean Patagonia. The objective is to conduct a comprehensive assessment that elucidates the interactions among multiple stressors, including industrial salmon aquaculture, vessel traffic, and climate change. By investigating how these stressors act synergistically, we seek to contribute further to understanding the cumulative effects on both habitats and human well-being in Chilean Patagonia.

Our study focuses on giant kelp (Macrocystis pyrifera) habitats within MPAs, namely Magdalena Island National Park, Guaitecas National Reserve, and Kawésqar National Reserve. Kelp forests are described as “sentinel systems” (Arefeh-Dalmau et al. 2020) acting as early indicators of environmental changes, especially in the face of climate change. This characteristic positions kelp forests as critical models for assessing the impacts of climate change on marine ecosystems. Giant kelp habitats are significant because of their ecological importance in protecting coastlines, providing nursery habitat for fisheries, and acting as carbon sinks (Mora-Soto et al. 2020, 2021). Moreover, these habitats are integral to the livelihoods of coastal communities and are traditionally managed based on customary practices (Fundación Superación Pobreza 2021).

Despite their ecological and socioeconomic importance, protected giant kelp habitats in Chilean Patagonia face direct threats from stressors such as the expansion of salmon farming (Quiñones et al. 2019). Although many of these areas have been granted protection status, they are not free from the presence of salmon farms, highlighting a significant conflict between conservation efforts and industrial interests. The expansion of the intensive salmon farming industry is reported to have devastating effects on the coastal regions of northern Chilean Patagonia and now threatens the delicate coastal fjord ecosystems in the southernmost regions (Häussermann et al. 2013, Friedlander et al. 2018, Quiñones et al. 2019, Buschmann et al. 2021). In response, social and environmental organizations are calling for more stringent legal measures to restrict salmon farming activities in these ecologically sensitive and protected areas. However, the extent and nature of the impacts remain poorly understood, further complicating efforts to develop more effective regulatory frameworks.

Our study bridges the gap between ecological processes and human interactions by examining the interplay between the human-induced stressors of salmon aquaculture, vessel traffic, and climate change, and their multiple impacts on the marine ecosystems of Chilean Patagonia, with specific focus on giant kelp habitats of marine conservation areas. By delving into these interactions, we contribute novel insights into the cumulative effects of these activities on both ecological integrity and human well-being. Through an integral assessment, we seek to inform adaptive management strategies that safeguard the sustainable coexistence of human and natural communities.

METHODS

Study area

The study area covers the coastal protected space in three protected areas of Chilean Patagonia. We consider two types of MPAs: park and reserve. National Parks aim for biodiversity and landscape conservation with restrictions to minimize human impacts. National Reserves also seek conservation, but allow sustainable use of natural resources. Here, we examined the Magdalena Island National Park (MINP), Las Guaitecas National Reserve (GNR), and Kawésqar National Reserve (KNR), which form part of Chile’s National System of Protected Areas (Tecklin et al. 2021). We used the maps available from Tecklin et al. (2021) representing the coastal protected space in Chilean Patagonia. MINP (44°20’S, 73°20’W; 45°29’S, 72°50’W) is in the Cisnes Commune in Aysén Region and has 450 km² of protected marine area and 1563 km² of terrestrial protection. GNR (44°10’S, 75°30’W; 46°30’S, 73°10’W) is located in the Cisnes and Aysén Communes also in Aysén Region, forming part of the large Chonos Archipelago, and has 8270 km² of protected marine area and 10,980 km² of terrestrial protection. KNR (50°10’S, 76°10’W; 54°30’S, 71°10’W) is in Natales and Rio Verde Communes, in the Region of Magallanes and Chilean Antarctica, and has a marine protected surface area of 26,010 km² (Fig. 1).

Habitat risk assessment in protected areas

To assess risks, we applied the “habitat risk assessment” model from InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) version 3.9.0, which is a suite of free, open-source software models used to map ecosystem services (Natural Capital Project 2024). The model considers the spatial distribution of two dimensions of risk, exposure to stressors and their consequences, to assess impacts on marine habitats (Arkema et al. 2014, Wyatt et al. 2017). Exposure is the degree to which the marine habitat experiences a stressor, and the consequence is the habitat-specific response to that exposure. Two types of data are required for running the model: Geographical Information System (GIS) data such as maps representing habitats and stressors, and a table weighting the criteria representing exposure and consequence, which are the two axes of risk.

Weighting risk exposure and consequence criteria

The model calculated exposure, consequences, and risk weights on a continuous raster surface across the study area (Natural Capital Project 2024). Maps were rasterized at 1 km² resolution to assess the effects of stressors considering the geography of the study area’s fjords, islands, and islets. Tables of stressor-habitat interactions also were included, providing all criteria suggested by the model (Natural Capital Project 2024). The criteria for exposure to stressors were the extent of temporal and spatial overlap between stressors, stressor intensity, and the degree to which management strategies mitigate the impact. Consequence criteria were the degree of habitat loss caused by the stressor, change in habitat structure, the ability of habitats to recover, and connectivity. For the criteria, the interaction was scored from 1 to 3, and we applied those proposed in the model (see details in Natural Capital Project 2024).

For the kelp forest habitat, we considered: recruitment rate, age at maturity or recovery time, connectivity, and natural mortality rate of Macrocystis pyrifera. These factors are crucial for assessing the vulnerability of M. pyrifera habitats, capturing essential aspects of kelp forest resilience, including population regeneration, response to stressors, and capacity for recovery. Connectivity is essential for maintaining genetic diversity, whereas stressor overlap highlights exposure risks. These parameters allow for a robust assessment of the ecological health and persistence of kelp forests under anthropogenic pressures (Castorani et al. 2017, Mora-Soto et al. 2021). The model included parameters such as ratings that measure the impact of the criteria on the kelp forest habitat, the data quality of the score, and the weight criteria that were set according to their importance (see details in Appendix 1). The data quality for each criterion’s score was assigned based on the availability of spatial data, with higher certainty applied when spatial data were available (Graham et al. 1997, Rodriguez et al. 2013, Castorani et al. 2017, Mora-Soto et al. 2021).

Giant kelp forest habitat as a conservation feature

A published world map of kelp forest was used as the habitat layer (Mora-Soto et al. 2020; see distribution map in Appendix 2). This map provided the spatial distribution of M. pyrifera, which is one of the dominant species of kelp forests in Patagonia and represents a foundation species that supports diverse communities (Valdivia et al. 2023), constituting a key habitat in this region. It extends approximately 7000 km² along the Patagonian coastline from the southern part of Chiloé Island (Mora-Soto et al. 2020) and remains well conserved in the southernmost portion of Patagonia (Friedlander et al. 2020, 2021, Mora-Soto et al. 2021).

Kelp forests are widely recognized as critical habitats for assessing climate change impacts (Arefeh-Dalmau et al. 2020). Covering approximately 25% of the world’s coastlines (Wernberg et al. 2019), kelp forests provide widespread and representative models for studying coastal ecosystems, facilitating insights applicable across diverse regions, and their loss is highlighted as an emergent global conservation issue (Wernberg et al. 2019). Kelp forests provide a unique three-dimensional structure that serves as a refuge, reproduction area, and food source, playing a fundamental role in trophic dynamics and marine biodiversity by acting as breeding and feeding habitats for numerous organisms from invertebrates to fish, exhibiting a complex interconnection of species that depend directly or indirectly on the forest, and providing ecological, economic, and cultural benefits to people in the region (Steneck et al. 2002, Teagle et al. 2017, Wyatt et al. 2017, Miller et al. 2018, Friedlander et al. 2021, Mora-Soto et al. 2021, Ross et al. 2023).

The distribution of giant kelp (M. pyrifera) forest habitat was determined using a kelp detection algorithm described by Mora-Soto et al. (2020) implemented in Google Earth Engine (see Appendix 2).

Main stressors in the marine protected areas of Chilean Patagonia

The primary stressors affecting marine habitats have been identified as intensive aquaculture, vessel traffic, and climate change (van Leeuwen et al. 2021, Castilla et al. 2024). We compiled available GIS data that could spatially represent these stressors using ArcGis 10.5 software (ESRI 2015; Appendix 2). We produced stressor maps for Patagonia, including (a) aquaculture maps: areas suitable for aquaculture and the number of aquaculture concessions; (b) fishing vessel tracking maps: including aquaculture, industrial, artisanal, and transport fleets; and (c) climate change maps: layers with the differences between present temperatures of benthic and surface and their projection to 2050 according to the Intergovernmental Panel on Climate Change (IPCC). A conceptual model was developed to illustrate the cumulative and interactive impacts of these stressors on kelp forest habitats, showing how each stressor influences the ecosystem both directly and indirectly, and how these combined effects can exacerbate environmental degradation (Fig. 2).

(a) Aquaculture: We collected available aquaculture GIS data from the Chilean Undersecretary of Fisheries and Aquaculture (SUBPESCA 2021a). These maps were the Areas Suitable for Aquaculture and the Aquaculture Concessions.

The Areas Suitable for Aquaculture map represented public beach lands, portions of water, and rock bottom inside and outside Patagonian fjords that are navigable by ships (> 100 tons) and where aquaculture can be carried out if a supreme decree is issued by the Ministry of Defense. These areas are not exclusive, and the decree can be modified through processes of affectation or theoretically misassignment, according to the procedure by which they were established (SUBPESCA 2021a). This represented an extreme scenario because it contained all the potential concessions that could become aquaculture concessions.

The Aquaculture Concessions map was the areas where the Ministry of Defense grants a concession for use, for a renewable period of 25 years, to carry out aquaculture of hydrobiological resources such as mussels, macroalgae, or salmonids (however, concessions granted prior to the reform of aquaculture legislation in 2010 are permanent in duration). These areas must have previously been decreed as suitable areas for aquaculture and free from existing concessions, concession requests under review, and those concessions with an approved resolution (SUBPESCA 2021b). The Aquaculture Concessions map was considered a more realistic scenario because it only considered those concessions granted and those concessions with an approved resolution.

The development of salmon farms introduces sea-cover and sea-use changes, akin to land-cover and land-use changes in terrestrial ecosystems, as natural environments are replaced by aquaculture infrastructure. This alteration in the seascape can have significant consequences for kelp forests. Salmon farms contribute to physical changes in the marine environment and bring an increase in vessel traffic, which also impacts kelp forests. Moreover, these farms introduce chemical substances such as antibiotics and excess nutrients, leading to eutrophication, which negatively affects water quality and kelp forest health. The combined effects of sea-cover and sea-use change, elevated vessel activity, chemical inputs, and nutrient pollution create risks for kelp ecosystems, encompassing factors such as habitat disruption, sedimentation, and altered hydrodynamics and nutrient transport (Schiel and Foster 2015, Wang et al. 2018, Williams et al. 2022).

(b) Vessel tracking maps: Vessel traffic was considered a stressor to biodiversity because it can have several impacts on kelp forests, potentially incurring mechanical damage to kelp, introduction of invasive species, and introduction of nearshore contaminants (Hollarsmith et al. 2022). For example, large vessels can cause physical damage to kelp by directly contacting the submerged structures (Schiel and Foster 2015). Vessel traffic can facilitate the introduction of non-native species, either through ballast water discharge or by transporting invasive species. Also, emissions from vessels can introduce pollutants into the water, affecting water quality, which can influence the health and resilience of kelp forests (Hollarsmith et al. 2022).

To characterize the different fleet activities, we collected and processed vessel tracking maps displaying vessel presence. The Vessel Monitoring System from Global Fishing Watch referred to the systems that transmit the location of a vessel (time, latitude, longitude, course, speed) at established intervals. The Vessel Monitoring System data present four types of fleet: aquaculture fleet, industrial fishing fleet, artisanal fishing fleet, and transport fleet (Verde Arregoitia et al. 2022). The fleets correspond mainly to vessels > 24 m long, which do not engage in pelagic fishing.

We used the spatial outputs reported by Verde-Arregoitia et al. (2022) that processed and classified the Vessel Monitoring System data in raster format representing vessel presence in hours per 1-km² pixel. The sum of hours corresponding to vessel presence for each of the four fleet types were categorized into high, medium, and low intensity based on data distribution quartiles (0.25 and 0.75), derived from the spatial overlap and frequency of vessel presence in each pixel (details in Verde-Arregoitia et al. 2022).

(c) Climate change maps: Rising ocean temperatures due to climate change, both at the surface and on the benthos, are significant stressors to marine biodiversity. These temperature changes affect a wide range of biological processes, including the reproduction, growth, and survival of fish populations, algae, and the broader marine ecosystem (Vergés et al. 2014, Hollarsmith et al. 2020, Friedlander et al. 2021, Mora-Soto et al. 2021). Although M. pyrifera can tolerate higher temperatures compared to some other algae species (Muth et al. 2019), it is increasingly vulnerable to extreme warming events, which are becoming more frequent with ongoing global warming (Oliver et al. 2018, Hollarsmith et al. 2020). The optimal temperature range for M. pyrifera is 12–17°C, with an upper tolerance limit of 18–25°C, depending on local conditions. When temperatures exceed this range, particularly during marine heatwaves, the early life stages of M. pyrifera are severely affected, leading to reduced growth rates and increased mortality. Prolonged exposure to such conditions can have devastating consequences for the persistence of kelp forests (Smale et al. 2019).

We considered two emissions scenarios to model future temperature impacts: one representing moderate changes (RCP4.5) and another reflecting higher greenhouse gas concentrations (RCP8.5). GIS data for these scenarios were sourced from the Bio-ORACLE platform (Tyberghein et al. 2012, Assis et al. 2018), using layers for sea surface temperature and average benthic temperature. The analysis included current data from 2000–2014 and projections for 2040–2050. We calculated temperature differences by subtracting present-day values from future projections for both surface and benthic layers. These differences were then categorized into three impact levels: low, medium, and high. The reclassification was performed using the Natural Breaks (Jenks) method to create three distinct impact classes (see maps and temperature range values in Appendix 2).

Definition of scenarios

The models were developed considering two conditions: with and without projected climate change (Fig. 3). Eight scenarios considered ocean temperatures (scenarios E1–E8), and six scenarios were analyzed without considering this stressor (scenarios E9–E11).

Habitat risk maps

The habitat risk map was the output raster layer resulting from the calculation of the risk model considering exposure, consequences, and risk weights. This output represented the cumulative habitat-specific risk of all stressors on a continuous raster at 1 km² resolution. According to Natural Capital Project (2024), based on the combination of consequence (C) and exposure (E) scores, the Multiplicative Risk (R) to habitat j generated by stressor k in cell l follows the equation:

(1)

The habitat risk map is the sum of the cumulative habitat risk scores, whereas the reclassification map represents the reclassified habitat-specific risk in four values, where 0 = no risk, 1 = low risk, 2 = medium risk, and 3 = high risk. Cells were classified into three risk categories: low (0–33%), medium (34–66%), and high risk (67–100%). Cells with no stressors were classified as no risk. The final maps displayed the distribution of habitat risk across the study area at 1 km² resolution. These qualitative data were presented as frequencies (percentages), representing the distribution and intensity of stressors across the study area.

RESULTS

Fishing vessels and aquaculture: stressors in protected areas

Aquaculture concessions in the marine space of National Protected Areas

A total of 416 aquaculture concessions have been granted within the three studied protected areas. The highest number of concessions is in GNR, with 336 concessions granted (22 km²), followed by KNR, with 73 concessions granted (14.69 km²), and MINP, with 7 concessions granted (0.39 km²). The total surface area of the protected areas occupied by aquaculture concessions granted is 37 km² (Fig. 4). The results reporting the intensity categories (high, medium, and low intensity using the cut-offs at the 0.25 and 0.75 quartiles of the data distribution) that were determined by evaluating the spatial overlap of vessels within protected areas using the Vessel Monitoring System data are presented below.

Fishing vessel presence in the marine space of protected areas

In MINP, high-intensity (236 km², 47% of the protected area) and medium-intensity (250 km², 50% of the protected area) aquaculture fleet activity overlaps with most of the protected area (Fig. 5). The high-intensity artisanal fleet overlaps with 24% of the protected area (123 km²), medium intensity with 26% (132 km²), and low intensity with 15% (75 km²). The high-intensity industrial fleet overlaps with 6% of the marine area (32 km²), with the medium- and low-intensity fleets almost nonexistent. The high- and medium-intensity transport fleets only overlap with 3% of the coastal area (84 km²), with the medium-intensity fleet at 8% (69 km²).

In GNR, the high-intensity aquaculture fleet overlaps with 1219 km² of the coastal protected area (15% of the area), medium intensity with 1813 km² (22% of the area), and low intensity with 295 km² (3%). The high-intensity artisanal fleet overlaps with 8% of the protected area (694 km²), medium intensity with 815 km² (10%), and low intensity with 430 km² (5%). The high-, medium-, and low-intensity industrial fleets overlap with 11% of the protected coastal area (~900 km²). The high-intensity transport fleet overlaps with 8% of the area (639 km²), medium intensity with 5% (447 km²), and low intensity with 2% (130 km²).

In KNR, the medium-intensity aquaculture fleet overlaps with 2230 km² (9% of the protected coastal area), high intensity with 195 km² (1% of the area), and low intensity with 800 km² (3%). The high-intensity artisanal fleet overlaps with 2% of the protected area (533 km²), medium intensity with 700 km² (3%), and low intensity with 466 km² (2%). The medium- and low-intensity industrial fleets overlap with only 2% of the protected coastal area (~400 km²). The high-intensity transport fleet overlaps with 3% of the area (729 km²), medium intensity with 8% of the coastal area (2062 km²), and low intensity with 3% (776 km²).

Habitat risk maps for giant kelp forests in Patagonia

The spatial distribution of risk to kelp forest habitat shows, in all scenarios, that the risk hotspots (i.e., areas that concentrate the highest risk) are in northern Patagonia, specifically in the area of the fjords and channels, with important hotspots also in sectors of southern Patagonia (see risk maps in Appendix 3).

For climate change, the maps of ocean temperature change (Appendix 2) show that the largest changes occur in the fjord zone, increasing northward; the temperature change is smaller moving westward to the open ocean. In these scenarios, changes in surface and benthic temperatures make the largest contribution to risk in the habitat risk models. Table 1 summarizes the relative contribution to risk for the most important stressors for kelp forest habitat in each mapped scenario. For instance, when vessel presence and Areas Suitable for Aquaculture were considered (E1, E5), aquaculture fleets are the second most important stressor. When vessel presence and AC were included (E3, E7), AC becomes the second most significant stressor. Similarly, in scenarios involving ocean temperatures and vessel presence (E4, E8), aquaculture fleets rank as the second most impactful stressor. In summary, climate change has the largest impact on kelp forest habitats across all scenarios, while aquaculture fleets and vessel activities also contribute significantly, depending on the scenario.

Most protected areas show low to medium risk for kelp forests, with high-risk areas concentrated in scenarios involving both climate change and aquaculture. Vessel activities also contribute to medium risk in several scenarios. The majority of the areas are classified under low and medium risk in the climate change scenarios (E1–E8), although high-risk areas emerged in some cases (E2, E3, E6, E7). More than 84% of marine protected area overlaps with low, medium, or high-risk zones in all scenarios, whereas < 16% of protected area is classified as having no risk. High-risk areas are especially prevalent in scenarios that combine climate change with aquaculture stressors, such as E2 and E6. By contrast, scenarios E3 and E7, which combine climate change, aquaculture concessions, and vessel presence, exhibit a higher proportion of medium risk but fewer high-risk areas than E2 and E6. In scenarios E4 and E8, which involve fishing vessel activities, kelp forests are predominantly classified under medium risk. In scenarios E3 and E7, most of the area within the coastal protected areas is categorized as low risk (Fig. 6).

Scenarios without climate change (E9–E11) show lower overall risk, with more areas classified as having no risk. However, aquaculture concessions still pose a significant threat in certain scenarios. In this set of scenarios, because only one stressor was considered, the resulting risk values are confined to one or two categories. For example, in scenarios involving aquaculture concessions (E9, E10), high-risk areas are prominent. In scenarios focused on vessel presence (E11A–D), medium risk predominates. Only scenario E11, which includes all fishing vessel activities, displays two distinct risk classes (medium and high; Fig. 7).

Patterns of risk to kelp forests inside marine protected areas

Magdalena Island National Park

In the climate change scenarios (E1–E8), MINP shows a high proportion of low-risk areas for kelp forests, though medium and high-risk zones are also present. Among the three protected areas, MINP has the highest proportion of high-risk coastal space, especially in scenarios E2 and E6 (Figs. 6 and 8). In scenarios E3 and E7, which include vessel presence, medium and high-risk represent smaller areas. The highest risk hotspots are concentrated in the bays on the western side of the island (Fig. 8, Appendix 3). When climate change is excluded (E9–E11), MINP shows significant high-risk areas from aquaculture, with scenario 11C covering > 51% of the area under medium risk due to vessel presence (Fig. 7).

Las Guaitecas National Reserve

GNR has the highest overall risk for kelp forest, particularly from aquaculture activities, with significant medium and high-risk areas, especially in the narrow fjords and bays in the center of the reserve. In scenarios involving aquaculture (E2 and E6), > 25% of the area is classified as high risk (Fig. 6, Appendix 3). By contrast, in scenarios E3 and E7, < 1% of the area is high risk, though vessel-related scenarios (E1, E4, E5, E8) show > 8% of kelp forests under medium risk. In scenarios without climate change (E9–E11; Fig. 7), aquaculture remains the dominant threat, with the highest coverage of high-risk hotspots (E9 and E10). In the scenarios considering fishing vessel fleets, the medium risk is lower than in MINP, but is much higher in terms of the overlapped area (> 1700 km² of medium-risk hotspots compared to 250 km² of MINP).

Kawésqar National Reserve

KNR has the smallest proportion of high-risk areas and the largest proportion of low-risk kelp forest habitat (> 88%) in all scenarios. Although KNR is the largest protected area, with almost 26,000 km² of coastal space, its high- and medium-risk areas are relatively small compared to MINP and GNR. In scenario E6, aquaculture activities affect ~330 km², which is still a smaller area of risk compared to the other two protected areas. Scenarios involving vessel activities (E2, E8) show < 2% of the area under medium risk. Scenarios related to Areas Suitable for Aquaculture, vessel activities, plus climate change (E1, E5) are associated with greatest areas under low risk to kelp forest (> 90%). In non-climate change scenarios, KNR shows lower overall risk, with < 3% of area under high risk (E9, E10), whereas it reaches 13.5% under medium risk in scenario 11D, with the transport fleet stressor.

DISCUSSION

Spatially assessing the risks posed by multiple anthropogenic stressors affecting marine protected areas in Chilean Patagonia sheds light on the intricate web of stressors influencing these delicate ecosystems and provides crucial information to design actions to abate them and to prioritize actions for conservation (Rojas et al. 2022). However, such an exercise requires delving into the concept of cumulative effects between stressors (Halpern et al. 2019). The habitat risk assessment considering cumulative effects between multiple stressors such as climate change, aquaculture, and fishing vessel presence is a flexible approach to explore possible risk scenarios that could affect the functioning and resilience of kelp forest habitats, which are foundational ecosystems in marine protected areas.

Integration of cumulative effects

The exploration of cumulative effects emerges as a lens through which multiple stressors affecting marine protected habitats in Chilean Patagonia can be more comprehensively understood (Davies at al. 2018, Curren et al. 2022). The expanding diversity and intensity of stressors resulting from human activities is set against the backdrop of natural processes and escalating climate change pressures (He and Silliman 2019). Unraveling the layers of impact brought about by climate change, aquaculture, and vessel presence, we find that the conservation challenge lies in their combined force (Pirotta et al. 2022).

The concept of cumulative effects reveals that the compounding influences amplify the vulnerability of marine ecosystems (Hammar et al. 2020). This integrated perspective allows us to understand spatial patterns of cumulative risk, identify priority areas for targeted management, and envision adaptive strategies that acknowledge multiple stressors. It emphasizes the links between ecological and social dimensions, urging for an approach that engages stakeholders and considers broader implications of our findings (Curren et al. 2022). Focusing on the detailed processes behind the risks can make predictions more accurate, but it can also lead to errors if our assumptions are wrong. Relying only on real-world accessible data reduces this risk, but we need enough data on how all the different factors interact to proceed effectively. In future, the idea of cumulative effects (how multiple stressors combine) should guide the creation of more effective policies and conservation strategies that can better protect these important marine environments.

Identification of habitat risk hotspots

Our findings highlight that areas with the highest risk are concentrated in the fjords of GNR and MINR in northern Patagonia. However, there are local risk hotspots also in sectors of southern Patagonia in the fjords of KNR. It is well documented that temperature changes in marine habitats generated by climate change alter ecological processes such as species extinctions or distributional changes to marine habitats (Rahel et al. 2008, Hoegh-Guldberg and Bruno 2010). An increase in ocean temperatures could cause physiological stress to kelp forests (Mabin et al. 2019), which may modify their dominance, with a range of effects that can trigger structural and cascading effects to giant kelp-associated communities (Mabin et al. 2019).

Intensive salmon aquaculture can also have strong negative effects on marine habitats, including sensitive communities such as animal forests composed of sponges, corals, and other structure-forming organisms. These effects range from salmon escapes and their impacts on the food chain to the consequences of antibiotic use in the water column and nutrient inputs from food waste and feces (Buschmann et al. 2021, Mora-Soto et al. 2021, Naylor et al. 2021). Even though aquaculture centers are not always spatially located above kelp forest habitats, the effects of nutrients and chemical treatments can spread to those habitats. For example, canthaxanthin, an additive in salmon feed, has been traced up to 1 km from salmon cages, demonstrating the far-reaching effects of salmon aquaculture on benthic chemistry (Graydon et al. 2012). In general, salmon industry in protected areas can be expected to have a negative effect on M. pyrifera habitat in Patagonia because the high content of nutrients released from salmon farming can affect marine communities by altering their abundance (positively or negatively), diversity, and trophic composition (Schiel and Foster 2015, Wang et al. 2018, Haugland et al. 2019), ultimately altering community structure, with unknown consequences. Our model outputs showed that > 80% of the coastal protected area of GNR and MINR are under medium and high risk in the scenarios that consider the simultaneous effects of climate change and aquaculture-related stressors. The scenarios that did not include climate change resulted in approximately 30% and 50% of the coastal protected space under medium to high risk in GNR and MINP.

One of the central findings is the identification of risk levels across the three protected areas, which has direct implications for conservation and management. High-risk areas, particularly in GNR and MINP, require urgent intervention to prevent ecosystem collapse. These areas are highly susceptible to degradation due to the effects of climate change and aquaculture. Immediate actions are needed to mitigate further damage, including restricting aquaculture expansion and implementing climate adaptation measures (Buschmann et al. 2021). Medium-risk areas present a critical opportunity for proactive management, as these areas remain vulnerable to stressors such as vessel traffic and nutrient runoff from aquaculture activities. To prevent these areas from escalating into high-risk zones, conservation efforts should focus on implementing monitoring programs, initiating habitat restoration projects, and regulating vessel traffic (Buschmann et al. 2021, Alvarez et al. 2022). By spatially prioritizing such efforts, conservation professionals can protect these ecosystems from further degradation. Low-risk areas in southern Patagonia, particularly in KNR, offer valuable ecological refuges and can serve as benchmarks for marine conservation; strategies in these areas should prioritize maintaining their resilience by protecting them from additional stressors.

Main stressors for the marine habitats of Chilean Patagonia

According to our results, ocean temperature change is the most significant stressor to giant kelp forest habitats. Although M. pyrifera can tolerate higher temperatures, it remains vulnerable to extreme warming events, which are becoming increasingly frequent due to climate change (Muth et al. 2019, Le et al. 2022). These warming events (Oliver et al. 2018) pose a serious threat to the persistence of kelp forests and the overall integrity of these ecosystems (Smale et al. 2019, Hollarsmith et al. 2020).

The risk posed by rising sea temperatures is not confined to specific locations, making it essential to incorporate climate adaptation practices when prioritizing conservation actions (Le et al. 2022). However, the uncertainties in climate models, particularly under emission scenarios 4.5 and 8.5, and the limitations of the available oceanic and benthic surface temperature data for coastal areas, must also be considered. For example, Mora-Soto et al. (2021) observed temperature stability in the southernmost parts of Patagonia over the past three decades, likely due to the cooling influence of glacial meltwater influx. However, as glaciers retreat and the meltwater inflow diminishes, it is expected that water temperatures in fjords will rise. This phenomenon has been documented in other glacial fjord systems, where reduced freshwater inputs have led to warmer conditions, potentially affecting local marine ecosystems (Nilsson et al. 2023, Bao and Moffat 2024).

This temperature stability in southern Patagonia aligns with our findings, showing a lower extent of temperature-related risk along the KNR coast. Similarly, Friedlander et al. (2021) noted that the Humboldt Current has not exhibited signs of tropicalization, suggesting that giant kelp forests in this region may be less affected by climate change in the short term. However, in other parts of its global range, M. pyrifera populations have experienced significant declines, primarily due to elevated sea surface temperatures and reduced water transparency (Tait et al. 2021). This information highlights the importance of cumulative stressors, as warming seas, sedimentation, and nutrient inputs from runoff and coastal development reduce light availability for photosynthesis, limiting kelp recovery and increasing its vulnerability to climate change.

In scenarios incorporating fishing vessel tracking data, the aquaculture fleet emerged as the second most significant stressor. This fleet represents the spatial footprint of aquaculture concessions, driving increased transport activity in key areas like the Moraleda Channel and west of MINP. These regions, where the most at-risk areas are concentrated, also overlap with critical blue whale habitats (Bedriñana-Romano et al. 2021). The increased vessel traffic linked to aquaculture intensifies the stress on marine ecosystems, contributing to the extent and intensity of these stressors. These results highlight the need for better management of aquaculture practices and vessel routes to mitigate the impacts on sensitive ecological zones.

Limitations of the information used

Our study used a global distribution map of giant kelp forests developed over four years of satellite imagery and validated in the Chilean Patagonian fjords (Mora-Soto et al. 2020). While this map provides a high-resolution, broad-scale view of kelp forest distribution and is widely recognized in global habitat risk assessments (Williams et al. 2022), it lacks the fine resolution necessary to capture more localized patterns within fjords. In the absence of specific local data, this map offers valuable, widely recognized data, enabling us to conduct regional-scale risk assessments in Patagonia.

There are some uncertainties regarding the ocean temperature and climate change projections that we used. These projections, which are based on satellite-derived measures, have limitations related to their coarse spatial resolution, particularly when attempting to capture small-scale patterns in coastal environments. Additionally, the IPCC trajectory-based projections carry inherent uncertainties (Tyberghein et al. 2012, Assis et al. 2018). As such, results from this analysis must be interpreted carefully, especially in Patagonian fjords and channels, where the coarser scale of temperature layers may not accurately detect localized effects on kelp forests.

Furthermore, our analysis does not account for key regional dynamics such as the influence of freshwater glaciers on fjords or the potential intensification of the upwelling effect. These factors can alter the salinity, nutrient levels, and temperature of the water column, affecting marine communities in ways that are challenging to integrate into our model due to limited data and the localized impacts of these processes (Drewnik et al. 2016). The small-scale landscape effects of such processes, particularly in the complex environments of fjords, remain difficult to assess with the current data (Drewnik et al. 2016).

Despite these limitations, the data sets used provide accessible global information, enabling us to extract preliminary patterns of risk and habitat stress. These data sets have been widely employed in analogous studies of marine biodiversity and species distribution modeling (Tyberghein et al. 2012, Edgar et al. 2014, Assis et al. 2018, Duarte et al. 2018, Jiménez et al. 2021, Poursanidis et al. 2022). While regional data for finer scale assessments remain limited, our use of global data sets allows for an initial exploration of the cumulative impacts of climate change, aquaculture, and vessel traffic on kelp forest ecosystems. As new regional climate data become available, this analysis can be reviewed and updated to incorporate the latest information.

Implications for conservation planning and protected areas management

In Chilean Patagonia, there is an urgent need for marine spatial planning due to the overlap of various sea uses, including conservation, industrial salmon farming, small-scale fishing, mussel farming, transport, and areas designated for customary Indigenous rights. The presence of salmon farms within protected areas is particularly controversial (Alvarez et al. 2022). Although current legislation mandates environmental impact assessments for aquaculture concessions within and around protected areas, enforcement is often inconsistent. In practice, salmon farming continues in national parks and other conservation zones, despite regulations prohibiting such activities without proper evaluation. It seems incompatible with conservation goals for the Chilean government to grant and maintain aquaculture concessions in areas intended for conservation. For instance, GNR hosts numerous salmon concessions despite lacking the management plan required for productive activities in reserves, reflecting a significant gap in regulatory compliance.

In response to these issues, legislative reforms have been proposed to modify Chile’s General Fisheries and Aquaculture Law (General Law on Fisheries and Aquaculture, Decree 430, 1992). Our findings could support these efforts by identifying high-risk zones where aquaculture and climate change effects overlap, informing prohibitions on new concessions and exit strategies for existing ones. A clearer legal framework is essential to protect areas designated for conservation from activities that compromise their ecological integrity.

Our spatial identification of risk hotspots offers crucial insights into how stressors such as climate change, aquaculture, and vessel traffic contribute to habitat loss and reduce connectivity in giant kelp forests. While these ecosystems are increasingly threatened worldwide, southern Chilean Patagonia remains one of the last areas where kelp forests are largely intact, representing a globally important natural heritage area (Mora-Soto et al. 2021). Our results can help to guide spatial prioritization of conservation actions by targeting areas most affected by overlapping stressors, ensuring that conservation efforts are both efficient and impactful (Salgado-Rojas et al. 2020). High-risk zones, particularly where climate change and aquaculture overlap, should be prioritized for interventions to reduce stressors.

For protected area management, analyzing key stressors is crucial for developing management plans that mitigate negative impacts on kelp forests (Almanza and Buschmann 2013, Hamilton et al. 2022). Of the three stressors analyzed, climate change poses the greatest challenge due to its global scale and levels of uncertainty. However, stressors such as aquaculture and fishing effort can be monitored and managed in a cost-effective manner, serving as performance measures to track conservation progress and adjust strategies in real time.

CONCLUSIONS

The application of the habitat risk assessment for kelp forests in Patagonia emphasizes the importance of considering strategies to abate the multiple stressors that affect seascapes and to advance proactive marine conservation. In Chilean Patagonia, habitat risk was associated with the potential increase in ocean temperature, coupled with the presence of aquaculture and its associated ship fleet. The identification of risk hotspots strongly highlights the incompatibility between conservation efforts for human well-being and some development activities, especially those operating under low environmental standards such as industrial salmon farming. The ability to identify risk hotspots can guide decisions regarding marine spatial planning for multiple sea uses and ultimately meet conservation objectives for dynamic seascapes in Patagonia. There is increasing controversy over the operation of salmon farming within marine protected areas, so our results could provide strong evidence to inform current policy efforts aimed at prohibiting new aquaculture concessions in these areas. Our results highlight the importance and urgent need to take into consideration multiple stressors, not just climate change, as part of informed decisions in conservation planning processes to sustain the necessary social-ecological transformative changes to face a future that seems increasingly uncertain.

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