# Characterization of hypoxic events in Paracas bay (Peru, 13.8°S) through intensity and biological effect indexes

Maricarmen Igarza, Arturo Aguirre-Velarde, Jorge Tam, Rosa Cueto-Vega, Jonathan Flye-Sainte-Marie, Dimitri Gutiérrez, Lander Merma-Mora, François Colas

► To cite this version:

Maricarmen Igarza, Arturo Aguirre-Velarde, Jorge Tam, Rosa Cueto-Vega, Jonathan Flye-Sainte-Marie, et al. Characterization of hypoxic events in Paracas bay (Peru, 13.8°S) through intensity and biological effect indexes. Journal of Marine Systems, 2024, 244, pp.103978. 10.1016/j.jmarsys.2024.103978. hal-04604447

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# Characterization of hypoxic events in PARACAS bay (Peru, 13.8°s) through intensity and biological effect indexes

Igarza Maricarmen <fnref n="1" />, *, Aguirre-Velarde Arturo <fnref n="2" />, Tam Jorge <fnref n="1" />, Cueto-Vega Rosa <fnref n="2" />, Flye Sainte Marie Jonathan <fnref n="3" />, Gutierrez Dimitri <fnref n="1" />, <fnref n="4" />, Merma-Mora Lander <fnref n="4" />, Colas Francois <fnref n="5" />

## Abstract :

Over the past decade, there has been a significant increase in low oxygen conditions within marine coastal areas, profoundly impacting ecosystem processes and living coastal resources. Coastal bays in highly productive upwelling regions, where hypoxia occurs naturally, are special areas affected by both local and adjacent shelf-related processes. Paracas Bay (13.8°S) is a traditional shellfish fishing and intense farming area highly influenced by one of the most active upwelling centers of the Peruvian coast. Despite the small dimensions of the bay (35 km2), a key feature is its complex physical dynamics and high environmental variability. Recently, important efforts have been made in the study of both the spatial and temporal oxygen concentration variability, nevertheless, information regarding the ecological and biological impact of hypoxic events is still lacking. In this study, the spatial and temporal distribution of hypoxic events was analyzed across Paracas bay at different depths by means of high-frequency hourly dissolved oxygen records collected by data-loggers deployed across the bay during the periods September 2012 – February 2013 and March 2015 – February 2017. To study the ecological impact of hypoxic events, we developed a hypoxia intensity index, while the biological impact was studied through the development of a hypoxia biological effect index using as model species the Peruvian scallop (Argopecten purpuratus). Our results showed that hypoxic events have an intrinsic variability across the bay. The deeper areas of the bay, towards the northwest and center, were characterized by long, intense, and lethal events, while the southeast and southwest, shallower areas, were characterized by shorter events of low intensity and either sublethal or innocuous. We propose that the observed variability is not only related to the large-scale environmental context in which the events occurred, but also to small-scale variability linked to local circulation, biological activity, and sediment biogeochemistry. We expect that our research will be useful not only for scientific purposes, but also for coastal resource management and

<footnote n="1">¹ Dirección General de Investigaciones en Oceanografía y Cambio Climático, Instituto del Mar del Perú, Esquina Gamarra y General Valle S/N, Callao 07021, Peru</footnote>

<footnote n="2">² Facultad de Pesquería, Universidad Nacional Agraria La Molina, Av. La Molina S/N, La Molina, Lima 15024, Peru</footnote>

<footnote n="3">³ Université de Bretagne Occidentale, LEMAR (CNRS/UBO/IRD/IFREMER), IUEM, Technopole Brest-Iroise, Plouzané, France</footnote>

<footnote n="4">⁴ Laboratorio de Ciencias del Mar, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano, France</footnote>

<footnote n="5">⁵ Institut de Recherche pour le Développement (IRD), UMR LOCEAN/IRD/SU/CNRS/MNHN, Sorbonne Université, Paris 75252, France</footnote>

<footnote>* Corresponding author : Maricarmen Igarza, email address : maria.igarza.t@upch.pe</footnote>
aquaculture, underlining the importance of developing high-resolution oxygen monitoring systems in
coastal bays.

Highlights

▶ Ecological and biological assessment of hypoxic events across Paracas bay.
▶ Hypoxic events in Paracas bay show high spatial and temporal variability.
▶ Long, intense, and lethal events characterize the deeper areas of the bay.
▶ Low intensity and innocuous events characterize the shallower areas of the bay.

**Keywords** : upwelling bay, hypoxic event, hypoxia intensity index, hypoxia biological effect index
# 1. Introduction

During the last decades, coastal areas and open ocean waters worldwide have been experiencing a decline in oxygen concentrations (Breitburg et al., 2018), thus deoxygenation has become one of the main ocean stressors together with rising sea temperatures, ocean acidification and nutrient enrichment. The occurrence of low oxygen conditions in marine coastal areas can stem from natural phenomena (such as upwelling or restricted circulation) or results from human activities (like eutrophication or global warming) (Middelburg and Levin, 2009). These conditions affect ecosystem processes, thereby influencing coastal resources and impacting the economic livelihood of nearshore populations. In eastern boundary upwelling ecosystems (EBUEs), low oxygen conditions occur naturally due to the upwelling of cold, nutrient-rich and oxygen depleted waters to the surface, which fuels primary production and thus organic matter degradation, promoting the development of oxygen minimum zones (OMZ) (Karstensen et al., 2008). One of the potential scenarios of global warming in EBUEs is the shoaling of the OMZ as a consequence of pycnocline strengthening due to surface ocean warming (Gilly et al., 2013; Stramma, 2008). Therefore, evaluating the impacts of coastal deoxygenation on these complex ecosystems is crucial for the improved management of coastal resources, especially since EBUEs sustain the most important fisheries worldwide.

Coastal bays in EBUEs are characterized by the strong influence of the upwelling in physical, chemical and biological dynamics (Largier, 2020). The morphology of coastal bays allows the retention of upwelled waters, fueling highly productive ecosystems within these bays and thus supporting important economic activities as shellfish fishing and farming, and allowing high fish recruitment due to larvae accumulation (Kämpf and Chapman, 2016). Although upwelling plays a key role in the bay's dynamics, there is also an important influence of shelf-related processes, hence advection of waters from the shelf into the bay during wind relaxation also contributes with the high productivity within these areas (Pitcher et al., 2021; Largier, 2020). Along the Peruvian coast, the area off Pisco - San Juan (13°S – 15°S) is characterized by the presence of islands and an irregular coastline, which contributes to the enhancement of upwelling and productivity in the inner shelf (Kämpf and Chapman, 2016). A prominent feature of the Pisco area is the presence of the Paracas peninsula and Paracas bay, which is considered a case of upwelling bay due to the influence that the Pisco upwelling cell exerts on it (Merma-Mora et al., 2023; Largier, 2020).
Paracas bay (13.8°S) is a semi-enclosed embayment located downstream of Pisco-San Juan upwelling area characterized by high rates of primary production, high nutrient concentrations compared to the surrounding waters and high environmental variability (Aguirre-Velarde et al., 2019, 2016; Maldonado, 1988). Bottom hypoxia and anoxia conditions characterize the bay mainly during austral summer (Aguirre-Velarde et al., 2019; Cabello et al., 2002), though hypoxia has also been registered during winter months (Merma-Mora et al., 2023). Several factors have been proposed to explain oxygen depletion in the bay, including thermohaline stratification, decay of harmful algal blooms (HABs), and advection of oxygen-depleted upwelled waters (Pitcher et al., 2021), the latter influenced by fluctuations in upwelling-favorable and local winds on a synoptic time scale (Merma-Mora et al., 2023). Despite its small dimensions (35 km²), a striking factor of Paracas bay is its complex physical dynamics (Arellano et al., 2022) and the high variability of environmental conditions, as evidenced by hourly variations of temperature and oxygen (Merma-Mora et al., 2023; Aguirre-Velarde et al., 2019). Though important efforts have been made to study the spatial and temporal hypoxia variability (Merma-Mora et al., 2023; Aguirre-Velarde et al., 2019) and its effect on commercial species as the Peruvian scallop (Cueto-Vega et al., 2021; Aguirre-Velarde et al., 2016), information regarding the quantification of hypoxic events throughout the bay and its biological and ecological impact is still lacking. Since the duration and intensity of hypoxic conditions determine its ecological impact, the determination of the intensity and severity of hypoxic events is critical for improvement of coastal resource management (Shields and Weidman, 2008).

The objective of this study is to characterize the spatial and temporal small-scale distribution of hypoxic events along Paracas bay quantified by means of high-frequency dissolved oxygen data, and to propose a hypoxia intensity index and a hypoxia biological effect index to evaluate the impact of these events from a broad ecological and biological perspective. We expect this study serves as a baseline for the assessment of hypoxic events not only locally in upwelling bays along the Humboldt Current System, but also as a tool, through the proposed intensity and biological effect indexes, for environmental risk assessment in sites potentially exposed to limiting oxygen conditions.

## 2. Materials and methods

### 2.1 Study area: Paracas bay

Paracas bay (Peru, 13.8°S) (Figure 1) is a small (35 km²), wide-open and shallow (<15 m depth) coastal embayment located in the central-southern part of the Peruvian coast downstream of Pisco upwelling cell (Figure 1a). Given the proximity of Paracas bay with the Pisco industrial area (Figure 1a), important economic activities as fish and shellfish farming, fish meal manufacturing and fishing take place within the bay and in its surroundings (Kahru et al., 2004), being Atenas beach one of the main aquaculture sites within the bay (Figure 1b – yellow star). Due to the economic importance of Paracas bay, adverse events like HABs, extreme hypoxia and anoxia, and formation of elemental sulphur plumes in the water column (milky-turquoise water events) severely affect the abovementioned activities and thus the economic livelihood of the Pisco
population (Flores et al., 2023; Cuellar-Martinez et al., 2023; 2021; Cueto-Vega et al., 2021; Chauca, 2018; Aguirre-Velarde et al., 2016; Kahru et al., 2004; Ohde et al., 2007; Schunck et al., 2013; Cabello et al., 2002). Due to the orientation of Paracas bay to the prevailing winds and currents, the area is considered an upwelling bay (Merma-Mora et al., 2023; Largier, 2020), thus it plays a key role in food web dynamics by providing sheltered breeding for fish and shellfish (Kämpf and Chapman, 2016).

<figure><img src="image_2.png" /><figcaption>**Figure 1.** (a) Location of Paracas bay (red star) in the central-southern area of the Peruvian upwelling system downstream of the highly productive Pisco - San Juan upwelling center (blue star). The green circle indicates the location of the Pisco industrial area. (b) Location of autonomous data-logger stations in Paracas bay for the collection of hourly records of dissolved oxygen. The yellow star indicates the main scallop farming area in the bay (Atenas beach) located in the southwestern side. Please note that data-logger stations have been named according to its position in the bay. NW: northwest, C: center, SE: southeast, SW1 and SW2: southwest.</figcaption></figure>

Environmental parameters in the bay are highly variable especially during summer months, when upwelling winds typically relax allowing strong stratification inside the bay and the entrance of less saline waters from the Pisco river (Arellano et al., 2022; Pitcher et al., 2021; Aguirre-Velarde et al., 2016). Thus, extreme hypoxic events, HABs and milky-turquoise water events usually occur during summer and early autumn (Flores et al., 2023; Chauca, 2018; Cabello et al., 2002). During winter and early spring, when upwelling winds are stronger, vertical mixing characterizes the bay as well as the intrusion of cold, upwelled waters (Pitcher et al., 2021). Recently, the studies of Merma-Mora et al. (2023) and Arellano et al. (2022) have shown that the main driver
of the bay dynamics is the wind forcing, with even direct consequences in the generation of extreme events as milky-turquoise water events (Flores et al., 2023).

## 2.2 Data collection

Hourly records of bottom dissolved oxygen (DO) and oxygen saturation were collected by means of autonomous data-loggers (MiniDOT PME) deployed 20 cm above the seabed. A total of five data-loggers were deployed at different areas and depths across Paracas bay (Figure 1b) between September 2012 – March 2013 and March 2015 – February 2017 (Table 1). Three data-loggers were located in the northwest (NW – figure 1b), center (C – figure 1b) and southeast (SE – Figure 1b) sides, where variations of bottom dissolved oxygen and organic matter content in sediments have already been reported (Flores, 2016; Merma-Mora, 2016). Two data-loggers were located towards the southwest side of the bay (SW1, SW2 – Figure 1b), close to Atenas beach, the main farming site of Paracas bay. Finally, one data-logger was located towards the southeast side (SE – Figure 1b), very close to the coastal area. Data collection was performed after each data-logger was collected from the bay and the information downloaded, eliminating the data registered when the data-logger was off the water. A high-frequency database of hourly records of bottom DO and oxygen saturation was finally obtained.

<table><caption>**Table 1.** Data-logger stations information according to its position in Paracas bay for different periods. Coordinates (latitude and longitude) of each data-logger station is shown together with the corresponding depth. All data-loggers were deployed 20 cm above the seabed. NW: northwest, C: center, SE: southeast, SW1 and SW2: southwest. Mar: March, Feb: February, Apr: April, Sept: September, Oct: October, Nov: November.</caption><thead><tr><th rowspan="2">Position in the bay</th><th colspan="2">Coordinates</th><th>Depth</th><th rowspan="2">Period of deployment</th></tr><tr><th>Latitude</th><th>Longitude</th><th>(m)</th></tr></thead><tbody><tr><td>NW</td><td>13°48'52"S</td><td>76°17'14"W</td><td>10</td><td>Mar 2015 - Feb 2016; Oct - Nov 2016</td></tr><tr><td>C</td><td>13°49'32"S</td><td>76°16'53"W</td><td>10</td><td>Mar 2015 - Apr 2016; Oct - Nov 2016</td></tr><tr><td>SE</td><td>13°50'35"S</td><td>76°15'59"W</td><td>6</td><td>Mar 2015 - Mar 2016</td></tr><tr><td>SW1</td><td>13°49'35"S</td><td>76°17'43"W</td><td>5</td><td>Sept 2012 - Mar 2013</td></tr><tr><td>SW2</td><td>13°49'28"S</td><td>76°17'58"W</td><td>5</td><td>Mar 2016 - Feb 2017</td></tr></tbody></table>

## 2.3 Data processing

For the purpose of this study, we have differentiated between the hourly records of bottom DO measure by each data-logger, and the hypoxic events, which were quantified based on these hourly records. First, each hourly record of bottom DO was classified as hypoxic if its value was below 2 mg L⁻¹ (Rabalais et al., 2010), which allowed us to calculate the percentage of hypoxic records per study site. Then, to accurately compare the dispersion between the different datasets, the quartile deviation of the bottom DO records was calculated. Afterwards, in order to study the bottom DO daily cycle, a box plot analysis was performed. The daily cycle variability was then assessed by fitting a sinusoidal function to the medians from the box plot analysis, allowing us to
determine and compare the amplitude and phase of the daily cycle between the study sites across
Paracas bay.

After the analysis of the DO daily cycle variability per study site, the DO records were used for the quantification of hypoxic events, which was performed following the minimum interim conceptual model proposed by Shields and Weidman (2008). According to these authors, one or more DO records below a given threshold constitute a hypoxic event. The authors proposed different methods to quantify hypoxic events in which different thresholds were used, showing that, independently of the method or thresholds used to define the events, the frequency patterns of these events were the same. For our study, we have used the threshold of six hours to define our minimum interim. Thus, a hypoxic event can only be defined as such if its duration is not shorter than six consecutive hours. This definition of a hypoxic event avoids the artifact of creating many short events when a low threshold is used, e.g. small variations of DO above 2 mg. L⁻¹. Likewise, since our objective was also to evaluate the impact of hypoxic events from a broad ecological and biological perspective, using a higher threshold is more appropriate since longer hypoxic events will have a greater impact compared to shorter ones. Once the hypoxic events were quantified, the number and frequency of events were compared between the different study sites in Paracas bay.

Although the spatial and temporal distribution of hypoxic events allowed us to characterize the hypoxia pattern across the bay, a simple quantification of events does not distinguish the ecological impact that each one can have on the ecosystem. Thus, in order to assess the ecological impact of each hypoxic event, a hypoxia intensity index (HII) was developed using as main variables duration and DO concentration. Since longer hypoxic events are very likely to have a greater impact at the ecological level, duration was considered as the primary variable and four categories of events from low to severe intensity were established (Table 2a). DO concentrations were divided in three intervals from 0.0 to 2.0 mg L⁻¹, while duration was divided in four intervals according to the observed distribution of the quantified hypoxic events.Although the HII allowed us to categorize each hypoxic event from a broad ecological perspective, the tolerance to hypoxia varies widely among different marine organisms and is intimately related to the duration of hypoxic conditions, which ultimately determines the survival (Middelburg and Levin 2009).

In order to study the impact of the quantified hypoxic events from a biological perspective, we developed a hypoxia biological effect index (HBEI) that can be applied to any species. In this study, we have chosen as a model species the Peruvian scallop (*Argopecten purpuratus*), since it is one of the most historically important resources farmed in Peru and in Paracas bay and is the dominant benthonic species in the area (Kluger et al., 2019). This species also plays a central role at the ecosystem level as prey for various consumer groups and competitor for other filter-feeders (Taylor et al., 2008). The Peruvian scallop has shown a considerable tolerance to hypoxic conditions, changing from oxy-conforming to oxy-regulator at 24% DO saturation, and even surviving at 5% for several days (Cueto-Vega et al., 2021; Aguirre-Velarde et al., 2016). Despite this tolerance, mass mortality events in bottom cultures of this species have been related to anoxia and hypoxia episodes, harmful algal blooms, formation of elemental sulphur plumes, and temperature increase (Cueto-Vega et al., 2021). These events do not only impact the ecosystem but also have a profound economic impact, generating losses to farmer cooperatives and
nearshore populations whose economic livelihood depend upon scallop processing chains (Kluger et al., 2019). For the development of the HBEI, we have used both DO saturation and duration as main variables. Based on the tolerance thresholds of the Peruvian scallop to hypoxia, we assigned three categories to the HBEI from innocuous to lethal (Table 2b).

**Table 2.** Hypoxia intensity index (a) and hypoxia biological effect index (b) developed for each hypoxic event quantified in Paracas bay using duration as the main variable of ecological significance. Four categories were assigned for the hypoxia intensity index and three to the hypoxia biological effect index.

<table><caption>(a) Hypoxia Intensity Index (HII)</caption><thead><tr><th rowspan="2">DO concentration<br>(mg L<sup>-1</sup>)</th><th colspan="4">Hypoxic event duration (hours)</th></tr><tr><th>6 - 20</th><th>21 - 50</th><th>51 - 100</th><th>&gt; 100</th></tr></thead><tbody><tr><td>0 - 0.5</td><td>1</td><td>2</td><td>3</td><td>4</td></tr><tr><td>0.5 - 1.0</td><td>1</td><td>2</td><td>3</td><td>3</td></tr><tr><td>1.0 - 2.0</td><td>1</td><td>1</td><td>1</td><td>1</td></tr></tbody><tfoot><tr><td colspan="5">1: low intensity 3: high intensity</td></tr><tr><td colspan="5">2: moderate intensity 4: severe intensity</td></tr></tfoot></table>

<table><caption>(b) Hypoxia Biological Effect Index (HBEI)</caption><thead><tr><th rowspan="2">DO saturation (%)</th><th colspan="3">Hypoxic event duration (hours)</th></tr><tr><th>6 - 20</th><th>21 - 40</th><th>&gt; 40</th></tr></thead><tbody><tr><td>&gt; 24%</td><td>1</td><td>1</td><td>1</td></tr><tr><td>5 - 24%</td><td>1</td><td>2</td><td>2</td></tr><tr><td>&lt; 5%</td><td>2</td><td>2</td><td>3</td></tr></tbody><tfoot><tr><td colspan="4">1: innocuous 2: sublethal 3: lethal</td></tr></tfoot></table>

The analysis of the daily cycle variability per studied site was performed using the R statistical platform (version 4.0.3) for the boxplot analysis, and the Solver tool from Microsoft Excel for the calculation of the parameters of the sinusoidal function. Quantification of hypoxic events and the respective distribution plots were performed in the R statistical platform using the packages *vegan* (Oksanen et al., 2019), *dplyr* (Wickham et al., 2023) and *ggplot2* (Wickham, 2016). The graphical display of the Pisco - Paracas coastal area map was done using the Ocean Data View software package (version 5.6.2; Schlitzer, 2022).

# 3. Results

## 3.1 Hourly records of bottom dissolved oxygen

The high-frequency hourly records of bottom DO showed different trends across the study areas in Paracas bay. The northwest side and the center of the bay showed the highest percentages of hypoxic records for the studied periods (Table 3), followed by the southeast and the southwest sides, where the lowest percentage corresponded to the data-logger records between March 2016
and February 2017. The quartile deviation showed higher values towards the southeast and the southwest sides compared to the northwest and the center.

<table><caption>**Table 3.** Percentage of hypoxic records and quartile deviation for the five datasets of high-frequency hourly records collected across Paracas bay. NW: northwest, C: center, SE: southeast, SW1 and SW2: southwest. Mar: March, Feb: February, Apr: April, Sept: September, Oct: October, Nov: November.</caption><thead><tr><th>Study site</th><th>Studied period</th><th>Depth (m)</th><th>Total N° of hourly records</th><th>Percentage of hypoxic records (%)</th><th>Quartile deviation</th></tr></thead><tbody><tr><td>NW</td><td>Mar 2015 - Feb 2016; Oct - Nov 2016</td><td>10</td><td>8146</td><td>90.2</td><td>0.4</td></tr><tr><td>C</td><td>Mar 2015 - Apr 2016; Oct - Nov 2016</td><td>10</td><td>9676</td><td>96.2</td><td>0.2</td></tr><tr><td>SE</td><td>Mar 2015 - Mar 2016</td><td>6</td><td>8536</td><td>69.7</td><td>1.2</td></tr><tr><td>SW1</td><td>Sept 2012 - Mar 2013</td><td>5</td><td>1424</td><td>70.9</td><td>0.9</td></tr><tr><td>SW2</td><td>Mar 2016 - Feb 2017</td><td>5</td><td>8680</td><td>15.1</td><td>1.3</td></tr></tbody></table>

## 3.2 Daily cycle analysis

The boxplot analysis performed to study the daily cycle across Paracas bay revealed differences in both the maximum and minimum medians of bottom DO (Figure 2; Table 4). In the northwest side and center of the bay, the maximum medians were below 0.5 mg L⁻¹, while in the southeast and southwest sides the maximum medians were above 2 mg L⁻¹, the hypoxia limit used in the present study. The hour of occurrence of the maximum median also varied across the different sites (Table 4), being the southwest the area where it occurred at the earliest (14:00 – 15:00 hours). With respect to the minimum medians, all the study sites across Paracas bay showed values below 0.1 mg L⁻¹, with the only exception of one data-logger located at the southwest side that recorded information between March 2016 and February 2017, where the minimum median reached was 2.5 mg L⁻¹ (Table 4). The hour of occurrence of the minimum median was consistent across Paracas bay between 05:00 to 07:00 hours.

The differences observed in the daily cycle across Paracas bay were analyzed by fitting a sinusoidal function to the medians, which showed the lower amplitudes in the northwest side and center of the bay, the deepest areas of the bay, compared to the southeast and the southwest sides (Table 4). The maximum amplitude in the daily cycle was obtained for the data-logger located at the southwest side that recorded information between March 2016 – February 2017.
<figure><img src="image_3.png" /><figcaption>**Figure 2.** Boxplots distribution of bottom dissolved oxygen hourly records according to the daily cycle per study site in Paracas bay. Boxplots represent the daily cycle and were prepared using all records available up to 10 mg L⁻¹ from all studied periods per study site. For visual purposes, day records (07:00 – 18:59 hours) are represented by light blue boxes, and night records (19:00 – 06:59 hours) by dark blue boxes. NW: northwest, C: center, SE: southeast, SW1 and SW2: southwest.</figcaption></figure>

<table><caption>**Table 4.** Maximum and minimum medians and hour of occurrence of bottom dissolved oxygen (mg L⁻¹) during the daily cycle per study site in Paracas bay. The parameters amplitude and phase from the sinusoidal functions fitted are also shown. NW: northwest, C: center, SE: southeast, SW1 and SW2: southwest. Mar: March, Feb: February, Apr: April, Sept: September, Oct: October, Nov: November.</caption><thead><tr><th rowspan="2">Study site in Paracas bay</th><th rowspan="2">Depth (m)</th><th colspan="2">Maximum median</th><th colspan="2">Minimum median</th><th colspan="2">Sinusoidal function parameters</th></tr><tr><th>Value</th><th>Hour</th><th>Value</th><th>Hour</th><th>Amplitude</th><th>Phase</th></tr></thead><tbody><tr><td>NW</td><td>10</td><td>0.27</td><td>16:00:00</td><td>0.10</td><td>06:00:00</td><td>0.129</td><td>11.92</td></tr><tr><td>C</td><td>10</td><td>0.24</td><td>17:00:00</td><td>0.09</td><td>05:00 - 09:00</td><td>0.132</td><td>12.61</td></tr><tr><td>SE</td><td>6</td><td>2.42</td><td>18:00:00</td><td>0.18</td><td>07:00:00</td><td>1.910</td><td>12.96</td></tr><tr><td>SW1</td><td>5</td><td>2.31</td><td>14:00:00</td><td>0.32</td><td>05:00:00</td><td>1.668</td><td>11.32</td></tr><tr><td>SW2</td><td>5</td><td>5.48</td><td>15:00:00</td><td>2.51</td><td>06:00:00</td><td>2.695</td><td>11.27</td></tr></tbody></table>

### 3.3 Quantification of hypoxic events

The frequency and duration of the quantified hypoxic events differed across Paracas bay and showed spatial and temporal variability. In the bay, the deeper northwestern and central areas
experienced longer-lasting hypoxic events, in contrast to the southeastern and southwestern sides where such events were shorter but occurred more frequently (Figure 3). In the northwest side and center of the bay, hypoxic events longer than 100 hours (Appendix A - Table S1) occurred throughout the studied periods even during June – September 2015, austral winter months. Hypoxic events longer than 2000 hours occurred only in these two areas of the bay during September – December 2015 (austral spring). The longest hypoxic event occurred in the center of the bay (2622 hours) between December 2015 – April 2016 (austral summer); during this period, none of the other studied areas showed such a long hypoxic event.

In the shallower southeast side of the bay, hypoxic events longer than 100 hours (Appendix A - Table S1) also occurred between June – September 2015 (austral winter). In this area, the longest hypoxic event (1355 hours) occurred between November 2015 - January 2016 (austral spring - beginning of austral summer). Compared to the deeper northwest and center, the southeast side experienced events that were more frequent but shorter in duration, interspersed with occasional longer events (Figure 3 - SE). Finally, the southwest side of the bay was characterized by short and frequent hypoxic events for both the periods between September 2012 – March 2013 (Figure 3 - SW1) and March 2016 – February 2017 (Figure 3 - SW2). In this area, the longest events occurred during February 2013 and February 2017 (austral summer), with a duration of 94 and 117 hours, respectively.

<figure><img src="image_4.png" /><figcaption>**Figure 3.** Distribution of hypoxic events quantified using the high-frequency hourly records of bottom dissolved oxygen collected at different study sites across Paracas bay. The yellow</figcaption></figure>
rectangles inside the plots for the time span between March 2015 – February 2017 indicate
periods were high-frequency data was available (see Table 1). NW: northwest, C: center, SE:
southeast, SW1 and SW2: southwest.

**3.4 Hypoxia Intensity Index (HII)**

The application of the proposed HII showed that hypoxic events of severe intensity occurred in the northwest, center, and the southeast sides of Paracas bay, whilst none of the events quantified in the southwest were of severe intensity for any of the studied periods (Figure 4a). In both the northwest side and center, at least 25% of the quantified hypoxic events were severe, while in the southeast only 3% of events were classified as such. High-intensity hypoxic events were recorded at all study sites in Paracas bay (Figure 4a); however, the deeper northwest and center exhibited the greatest frequency of these high intensity events (28% and 22% of the quantified hypoxic events, respectively). The lowest number of high intensity hypoxic events occurred in the shallower southwest side of the bay during the period March 2016 – February 2017. Regarding hypoxic events of moderate intensity, they occurred throughout Paracas bay except for the northwest side (Figure 4a), where none occurred. Finally, 45% of hypoxic events were of low intensity at the different study sites, being the southwest the area where the highest number of low intensity events (97%) occurred during the period March 2016 – February 2017.

<figure><img src="image_5.png" /></figure>
<figure><img src="image_6.png" /><figcaption>**Figure 4.** (a) Percentage distribution and (b) temporal distribution of the Hypoxia Intensity Index (HII) applied to each hypoxic event quantified using the high-frequency hourly records of bottom dissolved oxygen collected at different study sites across Paracas bay. Colors represent the four categories assigned to the HII using duration as the main variable (Table 2a). The yellow rectangles inside the plots for the time span between March 2015 – February 2017 indicate periods were high-frequency data was available (see Table 1). NW: northwest, C: center, SE: southeast, SW1 and SW2: southwest.</figcaption></figure>

The temporal distribution of the HII (Figure 4b) revealed that the center of Paracas bay was the most affected area, experiencing long-lasting events of severe intensity. In this area, as well as in the northwest and southeast, severe hypoxic events occurred during April – June 2015 (austral autumn). During July – August 2015 (austral winter) only the center and the southeast side showed hypoxic events of severe intensity. Towards September 2015, beginning of austral spring, both the northwest and the center presented a severe hypoxic event, whilst the southeast only registered such an event towards the end of November 2015. In this area, short duration events from low to high severity occurred during January – March 2016 (austral summer). Finally, in the southwest side of Paracas bay, events from low to high severity occurred between September 2012 – March 2013, while during the period between March 2016 to February 2017, most of the recorded events were of low severity.
**3.4 Hypoxia Biological Effect Index (HBEI)**

The application of the proposed HBEI showed that lethal events occurred mainly in the northwest and center of Paracas bay, where they accounted for 20% of the quantified events (Figure 5a). In the southwest, for the period between March 2016 – February 2017, no lethal events occurred. Regarding sublethal hypoxic events, they represented at least 50% of the quantified events and occurred across Paracas bay except for the southwest side for the period March 2016 – February 2017, where they represented only 8% of the hypoxic events. Finally, innocuous hypoxic events represented at least 45% of the events quantified in the southeast and southwest sides, with a clear dominance in the southwest for the period March 2016 – February 2017.

The temporal distribution of the HBEI showed that the majority of lethal events occurred in the center of the bay (Figure 5b). Like the HII (Figure 4b), lethal events occurred in the northwest, center and southeast sides between April – June 2015 (austral autumn). During June – July 2015 (austral winter), a lethal hypoxic event only occurred in the center of the bay, whereas sublethal events occurred in the southwest and southeast. During September 2015 – March 2016 (austral spring and summer), these three areas of Paracas bay presented lethal hypoxic events. Towards the southwest side, a progression of hypoxic events from innocuous to lethal was observed for the study period between September 2012 – March 2013, being austral summer the period were most sublethal events occurred. For the study period between March 2016 – February 2017, sublethal hypoxic events occurred during May – June 2016 (austral autumn) and during February 2017 (austral summer).
<figure><img src="image_7.png" /><figcaption>**Figure 5.** (a) Percentage distribution and (b) temporal distribution of the Hypoxia Biological Effect Index (HBEI) applied to each hypoxic event quantified using the high-frequency hourly records of bottom dissolved oxygen collected at different study sites across Paracas bay. Colors represent the three categories assigned to the HBEI using duration and the tolerance threshold to hypoxia of the Peruvian scallop (*Argopecten purpuratus*) as main variables (Table 2b). The yellow rectangles inside the plots for the time span between March 2015 – February 2017 indicate periods were high-frequency data was available (see Table 1). NW: northwest, C: center, SE: southeast, SW1 and SW2: southwest.</figcaption></figure>
# 4. Discussion

## 4.1 Diurnal fluctuations of dissolved oxygen across Paracas bay

In aquatic environments, the diurnal or daily DO cycle is characterized by an increase in DO concentrations during the day, related mainly to the photosynthetic activity, and a decrease during the night associated to respiration processes, which become the dominant metabolic pathway. Likewise, the daily DO cycle is also influenced by the variation of wind, solar influx and thus stratification. Across Paracas bay, the observed variability in the DO daily cycle could be related to both biological and physical factors. Pariona (2015) reported higher density of both epibenthic fauna and macroalgae towards the southwest side of Paracas bay compared to the southeast, although no seasonal pattern was observed. The observed differences in the daily DO cycle between the shallower southwest and southeast sides of the bay, and the deeper central and northwest areas, could be attributed to the activity of epibenthic organisms and macroalgae in the shallower regions. (Figure 2). Additionally, the average amplitude of the sinusoidal function for the two studied periods in the southwest (2.18, Table 4) was higher compared to the southeast (1.91, Table 4), and the hour of the maximum median also differed between these two areas, evidencing the possible role of biological activity in shaping the DO daily cycle in these areas of Paracas bay. Since benthic activity, especially macrofauna, has shown to mainly occur in shallow areas of the bay (Ibarra, 2015), it is expected that the deeper northwest and center exhibit a DO daily cycle mainly shaped by physical factors.

According to Arellano et al. (2022) the maximum wind speed during the diurnal cycle in Paracas bay is reached at around 16:00 – 18:00 hours, matching the hours of the maximum DO median obtained in this study for the northwest, center and southeast sides, differing only with the southwest, where the maximum median occurred between 14:00 – 15:00 hours (Table 4). The minimum wind speed during the daily cycle occurred between 05:00 – 08:00 hours (Arellano et al., 2022), matching the hours of the minimum DO median for all study sites in Paracas bay (Table 4). The study of Arellano et al. (2022) also showed that around 15:00 hours the maximum heat solar flux is reached in the bay, matching the hour of the maximum DO median in the southwest. Merma-Mora et al. (2023) already reported the synoptic time scale variability of winds as the main driver of bottom-hypoxia in the bay, similarly the present study shows that the DO daily cycle seems to be mainly related to the diurnal variability of wind speed. Nevertheless, the spatial differences observed for the maximum DO median between the southwest and the other study sites could be related to biological factors.

## 4.2 Spatial and temporal variability of hypoxic events across Paracas bay

The studies of Merma-Mora et al. (2023) and Cueto-Vega et al. (2021) already gave great insights into hypoxia variability in Paracas, nevertheless they were both restricted to the northwest and southwest sides of the bay respectively. The present study is, to our knowledge, the first one that characterizes hypoxic events at different study sites of different depths within Paracas bay. Arellano et al. (2022) performed a modelling study in the Pisco - Paracas coastal
area and showed that circulation within Paracas bay was coupled to wind variations. During days of strong wind, the bottom of the bay was characterized by a southward circulation entering the bay and reaching its highest velocities near the eastern side of the bay mouth, which then were reduced towards the center and other areas of the bay, except for the southeast side, where velocities increased (Arellano et al. 2022 – Figure 12e). During days of weak wind, the bottom of the bay was characterized by a northward circulation which was particularly sluggish towards the north and along the eastern shore, specially towards the northeast to the center (Arellano et al. 2022 – Figure 12h). Although a high-resolution observational study on circulation within Paracas bay has not yet been performed, the proposed modelled circulation pattern within the bay could explain the observed spatial variability in the quantified hypoxic events (Figure 3). Bottom sluggish circulation in the northwest and center of the bay, either during strong or weak wind conditions, could promote the development of long and severe hypoxic events. Merma-Mora et al. (2023) already reported that in this area of Paracas bay, severe oxygen depletion can also occur without strong stratification. Towards the southeast, differences in circulation velocities during periods of strong and weak winds could account for the presence of both long and severe hypoxic events and short events of low intensity. Finally, towards the southwest side of the bay, although the modelled circulation proposed by Arellano et al. (2022) do not show an important increase in velocities, the dominance of short hypoxic events of low intensity could be related to the effect of the bottom biological activity, as was already discussed for the DO daily cycle.

Circulation patterns have an important effect on sediment characteristics and thus also affect the preservation or degradation of organic matter. The Pisco - San Juan upwelling area is highly productive almost all year round, with highest chlorophyll-a concentrations occurring during austral spring and austral summer (Gutiérrez et al., 2011, 2016), where phytoplankton blooms usually take place. Aguirre-Velarde et al. (2019) reported high particulate organic matter fluxes (up to 9 g m⁻² day⁻¹) in both bottom and suspended cultures of the Peruvian scallop. Furthermore, being the occurrence of HABs quite common in Paracas bay (Cuellar-Martinez et al., 2021; 2023; Pitcher et al., 2021), it is expected that significant amounts of organic material will reach the sediment due to the bay's shallow depth (<15 m), thereby increasing oxygen consumption and consequently leading to reduced conditions in the sediments. The sedimentological studies performed by Solis et al. (2022) and Velazco and Solis (2000) showed that bottom sediments from the deepest areas of the bay, towards the northwest side and center, were muddy and silty clay, with high content of organic matter. Thus, these geochemical characteristics of bottom sediments could be promoting organic matter accumulation and thus oxygen consumption, contributing to the maintenance of long and severe hypoxic events in the deeper northwest side and center of Paracas bay. In addition, organic pollution from fishmeal plants located at the Pisco industrial area (Figure 1a) could contribute to increase oxygen consumption in the northern side of the bay.

Although the temporal variability of hypoxia in Paracas bay is not the focus of the present study and has already been examined in depth by recent studies (Merma-Mora et al., 2023, Pitcher et al., 2021, Cueto-Vega et al., 2021, Aguirre-Velarde et al., 2019), we did observe a temporal
pattern in the occurrence of certain hypoxic events. Events longer than 100 hours and of severe intensity occurred in both the northwest and center of the bay during end of March and April 2015 (Figure 4b). During austral summer 2015, several elemental sulfur plumes were registered in central Peru, with the largest and most intense one occurring during end of March and beginning of April 2015 (Flores et al., 2023). Sediment geochemical analyses performed during this period across Paracas bay revealed that the northwest side and center were characterized by a positive benthic sulfide flux from the sediments into the water column, revealing strong reduced conditions in surface sediments (Flores et al., 2023). Conversely, in the southeast side of the bay, where no long and/or severe hypoxic events were recorded during this period, no sulfide was detected in bottom sediments (Flores et al., 2023). Towards the end of April 2015 and beginning of May 2015 an “El Niño” event, corresponding to the warm phase of ENSO, began and continued through 2015 until mid-2016 (Cueto-Vega et al., 2021). Despite the low productivity conditions and deepening of the oxycline that characterize “El Niño” events along the Peruvian coast (Espinoza-Morriberón, et al., 2017), long hypoxic events of severe and high intensity occurred during austral winter and spring 2015, and austral summer 2016, in the northwest, center and southeast of the bay (Figure 4b). In the southwest side, the quantified hypoxic events occurred during two contrasting climate conditions, between March 2016 and February 2017, a year presenting a marine heat wave, and between September 2012 and March 2013, when an event “La Niña”, the cold phase of ENSO, developed and persisted through 2013 (Quispe-Ccalluari et al., 2018). Longer events of moderate to high intensity characterized this area of Paracas bay during “La Niña”, especially during January – March 2013 (austral summer), while during March 2016 – February 2017 short hypoxic events of low intensity predominated.

## 4.3 Variability of the Hypoxia Intensity Index (HII) and the Hypoxia Biological Effect Index (HBEI) and its implications for resource management

The quantitative approach used to define hypoxic events in this study allowed us to perform a spatial and temporal comparison among them and to capture its transient nature (Shields and Weidman, 2008). Since deoxygenation has become one of the main ocean stressors (Breitburg et al., 2018), it is of key importance to study the potential ecological impact that hypoxic events have on coastal resources, since they represent the livelihood of nearshore populations. The HBEI developed in this study allowed us to categorize each hypoxic event according to its impact on a specific resource. In our case we selected the Peruvian scallop (*Argopecten purpuratus*), the main of the few resources farmed in coastal Peruvian bays (Mendo et al., 2008). Mass mortality events of this species have been recorded in bottom cultures in Peruvian coastal bays, with mortality causes related to anoxia episodes, HABs and elemental sulfur plumes (Cueto-Vega et al., 2021). In the deeper northwest and center of Paracas bay, hypoxic events of severe intensity (Figure 4b) were also classified as lethal for the Peruvian scallop when the HBEI was applied (Figure 5b). Nevertheless, towards the southeast side, one of the longest events of severe intensity recorded between June – August 2015 (austral winter) (Table S1) was sublethal when the HBEI was applied (Figure 5b). Likewise, most low intensity events quantified in this area were sublethal for the Peruvian scallop. This indicates that assessing the impacts of hypoxic events requires more than a broad ecological perspective, such as that offered by the HII. Instead, specific indexes, as the HBEI, should be developed to accurately evaluate the biological effect of a given event on a specific species. Finally, towards the southwest, the majority of the registered low intensity
events were innocuous for the Peruvian scallop (Figure 5b), especially for the period between March 2016 – February 2017 (marine heatwave event), whereas for the period September 2012 – March 2013 (“La Niña” event), most of the quantified events were sublethal.

The assessment of the biological impact of the hypoxic events identified across Paracas bay provides an important tool for the sustainable management of scallop cultures. In the bay, the Atenas beach (Figure 1b) has been for many years the main farming area of the Peruvian scallop through bottom cultures. According to our findings, the northwest, center, and southeast sides of the bay are lethal areas for bottom cultures even during austral winter months, when hypoxic events of severe intensity can occur. On the contrary, although moderate to high intensity hypoxic events can occur towards the southwest side, they are mainly innocuous for the Peruvian scallop. These results could explain why the farming activity in the northwestern zone has been gradually abandoned, while only moderately active farms remain in the southwestern zone of the bay. Previous studies in both Paracas bay and Sechura bay (Aguirre-Velarde et al., 2019; Kluger et al., 2019) - the latter a coastal embayment situated northward of the Peruvian coast - has highlighted the necessity for site-specific management strategies. This recommendation acknowledges the unique attributes coastal areas, particularly upwelling bays, characterized by complex physical, chemical, and biological dynamics (Largier, 2020).

**5. Conclusions**

This study analyzed the spatial and temporal small-scale distribution of hypoxic events along Paracas bay as well as the variation in the daily DO cycle by means of high-frequency DO data. To our knowledge, this study is the first one to develop a quantitative approach to study hypoxic events in an upwelling bay by giving a definition to them and then exploring its intensity and biological effects through the development of two indexes. While our study does not use physical variables like the coastal upwelling index or wind intensity to define hypoxic events, as has been done in other upwelling areas (Herrera-Becerril et al., 2022), the pattern of hypoxic events distribution across Paracas bay aligns with the findings of previous research on hypoxia dynamics in the area (Merma-Mora et al., 2023; Cueto-Vega et al., 2021). This demonstrates the robustness of our approach.

Overall, the present study shows that bottom hypoxic events have an intrinsic variability within Paracas bay, and are not only affected by the large-scale environmental context in which they occur (i.e. warm/cold phase of ENSO), but also by local processes related to circulation, biological activity and sediment biogeochemistry. Despite the small dimensions of Paracas bay, hypoxic events showed both spatial and temporal variability. The deeper northwest side and center of the bay were characterized by long, intense, and lethal hypoxic events. The southeast area was dominated by hypoxic events of short duration, low intensity, and sublethal to the Peruvian scallop. Finally, the southwest side of the bay showed an overall dominance of short hypoxic events of low intensity and innocuous for the Peruvian scallop. We hope this study is useful not only for scientists studying hypoxic events in other coastal upwelling bays, but also for stakeholders by providing a science-based tool for coastal resources management and aquaculture. Finally, our study pleads for the development of a permanent high resolution oxygen monitoring based on studies of circulation patterns and biogeochemical processes in the bay. This
is a necessary step to understand the high intrinsic variability observed in such a small coastal
embayment and to build an early warning system.

Data availability

Data will be made available on request.

Author contributions

**M. Igarza:** Conceptualization, Methodology, Formal analysis, Investigation, Writing – Original Draft, Visualization. **A. Aguirre-Velarde:** Conceptualization, Methodology, Investigation, Data Curation, Writing – Review and Editing. **J. Tam:** Conceptualization, Methodology, Investigation, Writing – Review and Editing, Funding acquisition. **R. Cueto-Vega:** Data Curation, Writing – Review and Editing. **J. Flye-Sainte-Marie:** Data Curation, Writing – Review and Editing. **D. Gutierrez:** Writing – Review and Editing. **L. Merma-Mora:** Data Curation, Writing – Review and Editing. **F. Colas:** Conceptualization, Methodology, Investigation, Writing – Review and Editing, Supervision, Funding acquisition.

Acknowledgements

M. Igarza acknowledges the financial support of the Project Concytec – World Bank “Characterization and forecast of extreme events in the Peruvian sea using an operational system of oceanic information” (05-2019-FONDECYT-BM), through its executing unit Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (Fondecyt - Prociencia). This work is a contribution to the cooperative agreement between the Instituto del Mar del Perú (IMARPE) and the Institut de Recherche pour le Developpement (IRD) through the IRD international network GDRI DEXICOTROP and the JEAI DYSRUP.
## Appendix A - Supplementary information

<table><caption>**Table S1.** Hypoxic events longer than 100 hours quantified using the high-frequency hourly records of bottom dissolved oxygen collected at different study sites across Paracas bay. Please note that since no hypoxic events longer than 100 hours were recorded in the southwest for the period between September 2012 – March 2013, no information is shown in the table. NW: northwest, C: center, SE: southeast, SW1: southwest.</caption><thead><tr><th rowspan="2">Study site in Paracas bay</th><th rowspan="2">Season</th><th colspan="2">Start of hypoxic event</th><th colspan="2">End of hypoxic event</th><th rowspan="2">Duration (N° hours)</th></tr><tr><th>Date</th><th>Hour</th><th>Date</th><th>Hour</th></tr></thead><tbody><tr><td rowspan="12">NW</td><td rowspan="5">Austral autumm</td><td>2015-03-29</td><td>9:41:00</td><td>2015-04-10</td><td>10:41:00</td><td>289</td></tr><tr><td>2015-04-11</td><td>6:41:00</td><td>2015-04-29</td><td>7:41:00</td><td>433</td></tr><tr><td>2015-04-29</td><td>23:41:00</td><td>2015-05-17</td><td>1:41:00</td><td>410</td></tr><tr><td>2015-05-18</td><td>11:41:00</td><td>2015-05-22</td><td>16:41:00</td><td>101</td></tr><tr><td>2015-05-23</td><td>19:41:00</td><td>2015-06-01</td><td>17:41:00</td><td>214</td></tr><tr><td rowspan="4">Austral winter</td><td>2015-06-28</td><td>18:41:00</td><td>2015-07-07</td><td>3:41:00</td><td>201</td></tr><tr><td>2015-07-09</td><td>16:41:00</td><td>2015-08-06</td><td>7:41:00</td><td>663</td></tr><tr><td>2015-08-16</td><td>3:41:00</td><td>2015-08-21</td><td>9:41:00</td><td>126</td></tr><tr><td>2015-08-22</td><td>20:41:00</td><td>2015-09-20</td><td>12:49:00</td><td>688</td></tr><tr><td>Austral Spring</td><td>2015-09-21</td><td>23:49:00</td><td>2015-12-28</td><td>12:49:00</td><td>2341</td></tr><tr><td rowspan="2">Austral summer</td><td>2015-12-28</td><td>22:49:00</td><td>2016-02-13</td><td>05:00:00</td><td>1106</td></tr><tr><td>2016-02-13</td><td>17:00:00</td><td>2016-02-23</td><td>06:00:00</td><td>229</td></tr><tr><td>Austral Spring</td><td>2016-10-29</td><td>13:00:00</td><td>2016-11-07</td><td>05:00:00</td><td>208</td></tr><tr><td rowspan="12">C</td><td rowspan="4">Austral autumm</td><td>2015-03-29</td><td>9:41:00</td><td>2015-05-07</td><td>4:41:00</td><td>931</td></tr><tr><td>2015-05-07</td><td>12:41:00</td><td>2015-05-26</td><td>20:41:00</td><td>464</td></tr><tr><td>2015-05-27</td><td>9:41:00</td><td>2015-06-01</td><td>13:41:00</td><td>124</td></tr><tr><td>2015-06-07</td><td>22:41:00</td><td>2015-08-09</td><td>11:41:00</td><td>1501</td></tr><tr><td>Austral winter</td><td>2015-08-16</td><td>16:41:00</td><td>2015-09-17</td><td>11:49:00</td><td>763</td></tr><tr><td>Austral Spring</td><td>2015-09-29</td><td>21:49:00</td><td>2015-12-29</td><td>12:49:00</td><td>2175</td></tr><tr><td>Austral summer</td><td>2015-12-30</td><td>0:49:00</td><td>2016-04-17</td><td>11:00:00</td><td>2622</td></tr><tr><td rowspan="2">Austral Spring</td><td>2016-10-29</td><td>12:00:00</td><td>2016-11-07</td><td>19:00:00</td><td>223</td></tr><tr><td>2016-11-12</td><td>0:00:00</td><td>2016-11-16</td><td>17:00:00</td><td>113</td></tr><tr><td rowspan="12">SE</td><td rowspan="4">Austral autumm</td><td>2015-04-15</td><td>20:41:00</td><td>2015-04-21</td><td>13:41:00</td><td>137</td></tr><tr><td>2015-04-22</td><td>0:41:00</td><td>2015-04-26</td><td>14:41:00</td><td>110</td></tr><tr><td>2015-05-07</td><td>8:41:00</td><td>2015-05-22</td><td>14:41:00</td><td>366</td></tr><tr><td>2015-05-26</td><td>3:41:00</td><td>2015-05-30</td><td>12:41:00</td><td>105</td></tr><tr><td>Austral winter</td><td>2015-06-18</td><td>22:41:00</td><td>2015-08-02</td><td>13:41:00</td><td>1071</td></tr><tr><td rowspan="4">Austral Spring</td><td>2015-09-30</td><td>20:49:00</td><td>2015-10-05</td><td>23:49:00</td><td>123</td></tr><tr><td>2015-10-15</td><td>21:49:00</td><td>2015-10-24</td><td>13:49:00</td><td>208</td></tr><tr><td>2015-10-30</td><td>0:49:00</td><td>2015-11-04</td><td>12:49:00</td><td>132</td></tr><tr><td>2015-11-06</td><td>23:49:00</td><td>2015-11-16</td><td>14:49:00</td><td>231</td></tr><tr><td rowspan="2">Austral summer</td><td>2015-11-16</td><td>22:49:00</td><td>2016-01-12</td><td>14:00:00</td><td>1355</td></tr><tr><td>2016-01-30</td><td>4:00:00</td><td>2016-02-03</td><td>14:00:00</td><td>106</td></tr><tr><td rowspan="2">SW2</td><td rowspan="2">Austral summer</td><td>2016-02-08</td><td>23:00:00</td><td>2016-02-13</td><td>11:00:00</td><td>108</td></tr><tr><td>2017-02-21</td><td>18:18:00</td><td>2017-02-26</td><td>10:18:00</td><td>117</td></tr></tbody></table>
## References

Aguirre-Velarde, A., Thouzeau, G., Jean, F., Mendo, J., Cueto-Vega, R., Kawazo-Delgado, M., Vásquez-Spencer, J., Herrera-Sanchez, D., Vega-Espinoza, A., Flye-Sainte-Marie, J., 2019. Chronic and severe hypoxic conditions in Paracas Bay, Pisco, Peru: Consequences on scallop growth, reproduction, and survival. Aquaculture 512, 734259. https://doi.org/10.1016/j.aquaculture.2019.734259.

Aguirre-Velarde, A., Jean, F., Thouzeau, G., Flye-Sainte-Marie, J., 2016. Effects of progressive hypoxia on oxygen uptake in juveniles of the Peruvian scallop, Argopecten purpuratus (Lamarck, 1819). Aquaculture 451, 385-389. https://doi.org/10.1016/j.aquaculture.2015.07.030€

Arellano, C., Echevin, V., Merma-Mora, L., Chamorro, A., Gutierrez, D., Aguirre-Velarde, A., Tam, J., Colas, F., 2022. Circulation and stratification drivers in the upwelling bay of Paracas (Peru): a modelling study. Cont. Shelf Res. 254, 104923. https://doi.org/10.1016/j.csr.2022.104923

Breitburg, D., Levin, L.A., Oschlies, A., Grégoire, M., Chavez, F.P., Conley, D.J., Garçon, V., Gilbert, D., Gutiérrez, D., Isensee, K., Jacinto, G.S., Limburg, K.E., Montes, I., Naqvi, S.W.A., Pitcher, G.C., Rabalais, N.N., Roman, M.R., Rose, K.A., Seibel, B.A., Telszewski, M., Yasuhara, M., Zhang, J., 2018. Declining oxygen in the global ocean and coastal waters. Science (80-. ). 359. https://doi.org/10.1126/science.aam7240

Cabello, R., Tam, J., Jacinto, M.E., 2002. Procesos naturales y antropogénicos asociados al evento de mortalidad de conchas de abanico ocurrido en la bahía de Paracas (Pisco, Perú) en junio de 2000. Rev. peru. biol 9, 94-110.

Chauca, Z., 2018. Caracterización de los eventos de aguas blancas frente a pisco y chincha (entre los 13°-15° S). Master tesis. Universidad Peruana Cayetano Heredia, Lima, 204 pp.

Cuellar-Martinez, T., Huanca Ochoa, A., Sánchez, S., Aguirre-Velarde, A., Martínez, E., Rodriguez, A., Saavedra, R., Colas, F., Tam, J., Gutiérrez, D., 2023. Abundance and distribution of potentially toxic phytoplankton in aquaculture sites along the Peruvian coast. J. Mar. Syst. 240, 103865. https://doi.org/10.1016/j.jmarsys.2023.103865

Cuellar-Martinez, T., Huanca Ochoa, A., Sánchez, S., Aguirre-Velarde, A., Correa, D., Egoavil, K., Luján, H., Ipanaqué, J.M., Colas, F., Tam, J., Gutiérrez, D., 2021. Paralytic shellfish toxins in Peruvian scallops associated with blooms of Alexandrium ostenfeldii (Paulsen) Balech &Ttangen in Paracas Bay, Peru. Mar. Pollut. Bull.

Cueto-Vega, R., Aguirre-velarde, A., Gil-kodaka, P., Cueto-vega, R., Jean, F., Thouzeau, G., 2021. hypoxia Size-based survival of cultured Argopecten purpuratus (L, 1819) under severe hypoxia. https://doi.org/10.1111/jwas.12777

Espinoza-Morriberón, V., Echevin, F., Colas, J., Tam, J., Ledesma, L., Vásquez, A., Graco, M., 2017. Impacts of El Niño events on the Peruvian upwelling system productivity. J. Geophys. Res. 2017-2033. https://doi.org/10.1002/2013JC009262.
Flores, E., Mendoza, U., Callbeck, C.M., Diaz, R., Aguirre-Velarde, A., Bo, M.E., Merma-Mora, L., 2023. Attenuation of wind intensities exacerbates anoxic conditions leading to sulfur plume development off the coast of Peru. PLoS One 1–25. https://doi.org/10.1371/journal.pone.0287914

Flores Rafael, E.E., 2016. Impacto de la variabilidad oceanográfica en la variación de azufre inorgánico en sedimentos de la bahía de Paracas. Master tesis. Universidad Peruana Cayetano Heredia, Lima, 169 pp.

Gilly, W.F., Beman, J.M., Litvin, S.Y., Robison, B.H., 2013. Oceanographic and Biological Effects of Shoaling of the Oxygen Minimum Zone. Ann. Rev. Mar. Sci. 5, 393–420. https://doi.org/10.1146/annurev-marine-120710-100849

Gutiérrez, D., et al., 2011. Coastal cooling and increased productivity in the main upwelling zone off Peru since the mid-twentiesth century. Geophys. Res. Lett. 38 (7), 1–6. https://doi.org/10.1029/2010GL046324.

Gutiérrez, D., Akester, M., Naranjo, L., 2016. Productivity and sustainable management of the Humboldt current large marine ecosystem under climate change. Environ. Dev. 17, 126–144.

Herrera-Becerril, C.A., Sanchez-Cabeza, J.A., Álvarez Sánchez, L.F., Lara-Cera, A.R., Ruiz-Fernández, A.C., Cardoso-Mohedano, J.G., Machain-Castillo, M.L., Colas, F., 2022. Statistical identification of coastal hypoxia events controlled by wind-induced upwelling. Cont. Shelf Res. 233. https://doi.org/10.1016/j.csr.2021.104634

Ibarra, A.A., 2015. Variabilidad temporal en la estructura y composición de la macrofauna bentónica en Playa Atenas, Pisco. Engineer Thesis. Universidad Nacional Agraria La Molina, Lima, 150 pp.

Kahru, M., Mitchell, B.G., Diaz, A., Miura, M., 2004. MODIS detects a devastating algal bloom in Paracas Bay, Peru. Eos (Washington. DC). 85. https://doi.org/10.1029/2004EO450002

Kämpf, J., Chapman, P., 2016. Upwelling Systems of the World, Upwelling Systems of the World: A Scientific Journey to the Most Productive Marine Ecosystems. https://doi.org/10.1007/978-3-319-42524-5

Karstensen, J., Stramma, L., Visbeck, M., 2008. Oxygen minimum zones in the eastern tropical Atlantic and Pacific oceans. Prog. Oceanogr. 77, 331–350. https://doi.org/10.1016/j.pocean.2007.05.009

Kluger, L.C., Taylor, M.H., Wolff, M., Stotz, W., Mendo, J., 2019. From an open-access fishery to a regulated aquaculture business: the case of the most important Latin American bay scallop (Argopecten purpuratus). Rev. Aquac. 11, 187–203. https://doi.org/10.1111/raq.12234

Largier, J.L., 2020. Upwelling Bays: How Coastal Upwelling Controls Circulation, Habitat, and Productivity in Bays. Ann. Rev. Mar. Sci. 12, 415–447. https://doi.org/10.1146/annurev-marine-010419-011020

Maldonado, M., 1988. Condiciones Físico - Químicas y Corrientes de la Bahía Paracas, Perú, Durante Dos Días de Noviembre 1986. Bol. Inst.Mar Peru-Callao.
Mendo, J., Wolff, M., Carbajal, W., Gonzales, I., & Badjeck, M. (2008). Manejo y explotación de los principales bancos naturales de concha de abanico (Argopecten purpuratus) en la costa peruana. In A. Lovatelli, A. Farías, & I. Uriarte (Eds.), Estado actual del cultivo y manejo de moluscos bivalvos y su proyección futura: factores que afectan su sustentabilidad en América Latina. Taller Técnico Regional de la FAO. 20–24 de agosto de 2007, Puerto Montt, Chile. FAO Actas de Pesca y Acuicultura, No. 12 (pp. 101–114). Roma: FAO

Merma-Mora, L., Colas, F., Cardich, J., Sánchez, S., Flores, E., Lorenzo, A., Aguirre-Velarde, A., Correa, D., Gutiérrez, D., 2023. Bottom-water hypoxia in the Paracas Bay (Peru, 13.8°S) associated with seasonal and synoptic time scale variability of winds and water stratification. J. Mar. Syst. 241, 103918. https://doi.org/10.1016/j.jmarsys.2023.103918

Merma-Mora, L., 2016. Foraminíferos bentónicos asociados a condiciones de hipoxia costera y bajo pH en la bahía de Paracas. Master tesis. Universidad Peruana Cayetano Heredia, Lima, 173 pp.

Middelburg, J.J., Levin, L.A., 2009. Coastal hypoxia and sediment biogeochemistry. Biogeosciences 6, 1273–1293. https://doi.org/10.5194/bg-6-1273-2009

Ohde, T., Siegel, H., Reißmann, J., Gerth, M., 2007. Identification and investigation of sulphur plumes along the Namibian coast using the MERIS sensor. Cont. Shelf Res. 27, 744–756. https://doi.org/10.1016/j.csr.2006.11.016

Oksanen, J., Guillaume Blanchet, F., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P., O'Hara, R., Simpson, G., Solymos, P., Henry, M., Stevens, H., Szoecs, E., Wagner, H., 2019. vegan: Community Ecology Package. R package version 2.5-6. https://CRAN.R-project.org/package=vegan

Pariona, E., 2015. Dinámica comunitaria macrobentónica en áreas colonizadas por Caulerpa filiformis (Suhr) Hering (Bryopsidales, Chlorophyta) en bahía Paracas – Perú. Master thesis. Unievrsidad Nacional Agraria La Molina, Lima.

Pitcher, G.C., Aguirre-verlade, A., Breitburg, D., Cardich, J., Carstensen, J., n.d. System controls of coastal and open ocean oxygen depletion 1–166.

Quispe-Ccalluari, C., Tam, J., Demarcq, H., Chamorro, A., Espinoza-Morriberón, D., Romero, C., Dominguez, N., Ramos, J., Oliveros-Ramos, R., 2018. An index of coastal thermal effects of El Niño southern oscillation on the Peruvian upwelling ecosystem. Int. J. Climatol. 38 (7) https://doi.org/10.1002/joc.5493.

Rabalais, N.N., Díaz, R.J., Levin, L.A., Turner, R.E., Gilbert, D., Zhang, J., 2010. Dynamics and distribution of natural and human-caused hypoxia. Biogeosciences 7, 585–619. https://doi.org/10.5194/bg-7-585-2010

Schlitzer, R., 2022. Ocean Data View, https://odv.awi.de

Schunck, H., Lavik, G., Desai, D.K., Großkopf, T., Kalvelage, T., Löscher, C.R., Paulmier, A., Contreras, S., Siegel, H., Holtappels, M., Rosenstiel, P., Schilhabel, M.B., Graco, M., Schmitz, R.A., Kuypers, M.M.M., LaRoche, J., 2013. Giant Hydrogen Sulfide Plume in the Oxygen
Minimum Zone off Peru Supports Chemolithoautotrophy. PLoS One 8.
https://doi.org/10.1371/journal.pone.0068661

Shields, E., Weidman, C., 2008. A Quantitative Approach to Characterizing Hypoxic Events. J. Coast. Res. 10055, 50–58. https://doi.org/10.2112/si55-003.1

Solis, J., Velazco, F., Morón, O., Sánchez, S., Calderón, A., Fernández, E., Luciano, L., Vítor, J., 2022. CARACTERÍSTICAS SEDIMENTOLÓGICAS Y GEOQUÍMICAS DE SEDIMENTOS RECIENTES DE LA BAHÍA DE PARACAS, PISCO DURANTE LOS AÑOS 2013, 2014 y 2015. Boletín del Inst. del Mar del Perú 37.

Stramma, L. et al, 2008. Expanding Oxygen-Minimum Zones in the Tropical Oceans. Science (80). 320, 655–659. https://doi.org/10.1126/science.1153847

Velazco, F., Solis Acosta, J., 2000. Estudio sedimentologico de la bahia de Paracas, Informe progresivo N° 133.

Wickham, H., François, R., Henry, L., Müller, K., Vaughan, D., 2023. dplyr: A Grammar of Data Manipulation. R package version 1.1.2. https://CRAN.R-project.org/package=dplyr

**Declaration of interests**

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

**Highlights**

* Ecological and biological assessment of hypoxic events across Paracas bay

* Hypoxic events in Paracas bay show high spatial and temporal variability

* Long, intense, and lethal events characterize the deeper areas of the bay

* Low intensity and innocuous events characterize the shallower areas of the bay