# Coastal ecosystem services in South Africa's largest natural bay: The role of marine benthic filter feeders in mitigating pollution

Eleonora Puccinelli, Francesca Porri, Katye Altieri, Raquel Flynn, Hazel

Little, Tayla Louw, Paula Pattrick, Conrad Sparks, Mutshutshu Tsanwani,
Sonya de Waardt, et al.

► To cite this version:

Eleonora Puccinelli, Francesca Porri, Katye Altieri, Raquel Flynn, Hazel Little, et al.. Coastal ecosystem services in South Africa's largest natural bay: The role of marine benthic filter feeders in mitigating pollution. Ecological Indicators, 2022, 139, pp. Article number 108899. 10.1016/j.ecolind.2022.108899. hal-04160054

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Original Articles

# Coastal ecosystem services in South Africa's largest natural bay: The role of marine benthic filter feeders in mitigating pollution

Eleonora Puccinelli<sup>a,b,*</sup>, Francesca Porri<sup>c,d</sup>, Katye Altieri<sup>a</sup>, Raquel Flynn<sup>a</sup>, Hazel Little<sup>a</sup>, Tayla Louw<sup>a</sup>, Paula Pattrick<sup>e,f</sup>, Conrad Sparks<sup>g</sup>, Mutshutshu Tsanwani<sup>a,h</sup>, Sonya de Waardt<sup>g</sup>, David Walker<sup>g</sup>, Sarah Fawcett<sup>a,i</sup>

ARTICLE INFO

Keywords:

Water quality

Filter feeders

Coastal circulation

Nutrient loading

Atmospheric deposition

Metal contamination

ABSTRACT

Nearshore water quality can be highly impacted by anthropogenic activities ongoing along the coast, the effects of which on natural environments can be permanent and irreversible, with consequences for ecosystem biodiversity and functioning, as well as for associated services. Benthic filter feeders (e.g., mussels) provide several services for coastal regions, including improving water quality by reducing eutrophication, being a major source of food for humans, and as a habitat-forming species. Here, we seek to understand the role of benthic filter feeders in enhancing water quality in an urban coastal system in order to assess their role as ecosystem service providers and how they should be included in ecosystem-based evaluations. Using as a model False Bay, South Africa's largest natural bay and a socio-economic hotspot, this multidisciplinary study was designed to identify possible pollution sources to a highly-urbanised coastal region, assess their effects on several biological and biogeochemical parameters, and evaluate the role of mussels in mitigating these anthropogenic inputs. We consider several sources of pollution, including nutrient loading from wastewater and river outflows, heavy metals, and aerosol deposition. We find that pollutant inputs are largely attenuated by the circulation of the bay and by the presence of filter feeders that bioaccumulate contaminants, thereby removing them from coastal waters. Our work thus emphasizes the potential for mussels and natural abiotic processes to ameliorate anthropogenic impacts, although these mitigation strategies are not without environmental risk. We recommend that such information should be included in national assessments used to develop appropriate strategies and policies for coastal environmental management and conservation.

# 1. Introduction

Coastal waters are among the most productive systems on Earth, providing a wide variety of services to humans including food, as well as ensuring water quality through filtration and detoxification facilitated by suspension feeders, submerged vegetation, and wetlands (Worm et al., 2006; Barbier, 2019). Over the last few centuries, significant human population growth has disproportionately affected coastal

regions globally (Halpern et al., 2008; Balk et al., 2009; Smith, 2011; Merkens et al., 2016), with the recent exponential increase in coastal urbanisation further impacting natural marine systems through the construction of artificial infrastructures, habitat damage or loss, and degradation of water quality (MAE, 2005; Bulleri and Chapman, 2010; Lai et al., 2015; Marzinelli et al., 2018; Aguilera et al., 2020). Poor water quality results from land- and ocean-based human activities that cause chemical and biological pollution, increased sediment loads, and

<footnote><sup>a</sup> Department of Oceanography, University of Cape Town, Rondebosch 7701, Cape Town, South Africa</footnote>

<footnote><sup>b</sup> University of Brest – UMR 6539 CNRS / UBO / IRD / Ifremer, LEMAR – IUEM – Rue Dumont d’Urville, 29280 Plouzané, France</footnote>

<footnote><sup>c</sup> South African Institute for Aquatic Biodiversity (SAIAB), Somerset Street, 6139 Makhanda, South Africa</footnote>

<footnote><sup>d</sup> Ichthyology and Fisheries Sciences Department, Rhodes University, Makhanda 6139, South Africa</footnote>

<footnote><sup>e</sup> South African Environmental Observation Network (SAEON), Elwandle Coastal Node, Gqeberha 6001, South Africa</footnote>

<footnote><sup>f</sup> ABALOBI, NPO, 1 Westlake Dr, Cape Town 7945, South Africa</footnote>

<footnote><sup>g</sup> Department of Conservation and Marine Sciences, Cape Peninsula University of Technology, Cape Town 8000, South Africa</footnote>

<footnote><sup>h</sup> Oceans and Coasts Research, Department of Environment, Forestry and Fisheries, Cape Town 8001, South Africa</footnote>

<footnote><sup>i</sup> MARIS, University of Cape Town, Rondebosch 7701, Cape Town, South Africa</footnote>

<footnote>* Corresponding author at: Department of Oceanography, University of Cape Town, Rondebosch 7701, Cape Town, South Africa.</footnote>

<footnote>E-mail address: eleonorapuccinelli@gmail.com (E. Puccinelli).</footnote>
eutrophication (Halpern et al., 2008; Huijbers et al., 2013; Johnston
et al., 2016; Ali and Khairy, 2016; Lu et al., 2018).

Shifts in climate can also alter natural ecological processes across a
range of spatial and temporal scales. With climate change, extreme
events such as floods, droughts, and storms are increasing in frequency
and magnitude (Benedetti-Cecchi et al., 2006; Neumann et al., 2015)
and ocean currents are changing in response to alterations in tempera-
ture, rainfall, and wind patterns (Winton et al., 2012; Holliday et al.,
2020). Such changes will alter the land–ocean freshwater flux, with a
higher flux potentially enhancing upper water column stratification,
thus decreasing the vertical nutrient supply and coastal productivity
(MacKenzie and Adamson, 2004; Arellano and Rivas, 2019; Janout
et al., 2020). A large freshwater flux may also lead to terrestrial nutrient
loading, potentially driving harmful algal blooms and eutrophication in
nearshore waters, with an associated decrease in dissolved oxygen
(O’Neil et al., 2012; Lapointe et al., 2017; Tsikoti and Genitsaris, 2021).
Increased eutrophication can also result from a decline in the freshwater
flux as this reduces the dilution effect (Bakun, 1990; Romero et al.,
2013). In synergy with natural and/or anthropogenic disturbances,
climate change is also driving changes in the geographical range,
metabolism, abundance, and diversity of key organisms in coastal eco-
systems, with consequences that extend to food-web dynamics and
ecosystem functioning (Harley et al., 2006; Nagelkerken and Connell,
2015).

Increasing stress on natural systems, either directly through pollu-
tion and/or habitat destruction or indirectly through climate change and
related perturbations, is predicted to drive changes in marine biodi-
versity, with repercussions for ecosystem functioning (Worm et al.,
2005; Doney et al., 2012; Tilman et al., 2014; Hautier et al., 2015). High
species richness and diversity enhance ecosystem productivity and sta-
bility (Stachowicz et al., 2007; Duffy et al., 2017), while a decline in
biodiversity narrows ecosystem functioning with a consequent loss of
services (Balvanera et al., 2006; Worm et al., 2006). Biodiverse com-
munities are thus more likely to withstand anthropogenic stressors
without compromising (or at least, not fully compromising) the func-
tioning and services of the system they inhabit (Worm et al., 2006;
Stachowicz et al., 2007; Teixeira et al., 2019). The impact of biodiversity
loss at a global scale is not yet fully understood (Hooper et al. 2005),
with a lack of information from marine environments identified as a
particular gap (Hendriks et al., 2006; Townsend et al., 2018).

Filter feeders such as bivalves (e.g., mussels) have been extensively
used as environmental tools for the restoration of heavily
anthropogenically-impacted systems (Lorey, 2002; Dumbauld et al.,
2009; La Peyre et al., 2014; McAfee et al., 2016; Puccinelli et al., 2016b;
Pereira et al., 2019). The utility of mussels as sinks for waste is related to
their ability to capture suspended material by filtering water at high
rates (Nakamura and Kerciku 2000). As such, mussels can control
phytoplankton stocks, rates of primary productivity, water clarity,
nutrient cycling, and food web dynamics (Kohata et al., 2003; Higgins
et al., 2011; Vanni, 2021). Additionally, mussels are pivotal as bio-
engineers (Cole and McQuaid, 2010; Lathlean and McQuaid, 2017) and
provide a direct ecosystem service as a food source (Drimie and McLa-
chan, 2013). However, mussels can also accumulate pollutants such as
metals (i.e., “bioaccumulation”; Spada et al., 2013), which may
compromise their ecological resilience and/or utility as a service pro-
vider (Stankovic and Jovic, 2012).

Analyses of carbon (C) and nitrogen (N) stable isotopes (SI) and fatty
acids (FA) have been used extensively to study marine food webs. These
techniques provide time-integrated information on organism diet and
can be used to trace the flux of organic matter from producers to con-
sumers (Peterson and Fry, 1987; Hansson et al., 1997; Dalsgaard et al.,
2003; Kelly and Scheibling, 2012). Additionally, the N isotope ratios (i.
e., δ¹⁵N, in ‰ vs. N₂ in air, = [(¹⁵N/¹⁴N)sample/(¹⁵N/¹⁴N)ref -1] × 1000)
of dissolved inorganic N forms such as nitrate can be used to distinguish
anthropogenic versus natural nutrient inputs to coastal regions, track
pollutant sources through aquatic systems, and evaluate their spatial

and temporal persistence (McClelland and Valiela, 1998; Kendall and
Aravena, 2000; Mayer et al., 2002; Nestler et al., 2011; Qin et al., 2019).
In the case of primary consumers such as bivalves, biomass δ¹⁵N is
indicative of organism trophic level, while biomass δ¹³C (in ‰ vs. VPDB,
= [(¹³C/¹²C)sample/(¹³C/¹²C)ref -1] × 1000) is directly related to or-
ganism food source (DeNiro and Epstein, 1981, 1978), with an estimated
isotopic enrichment between trophic levels of 2.3‰ for δ¹⁵N and 1‰ for
δ¹³C (McCutchan et al., 2003). FA analyses provide insights into the
pathways of FA synthesis, metabolism, and reproduction strategies of
organisms (Iverson et al., 1997; Puccinelli et al., 2016a; Puccinelli et al.,
2017; Ruess and Müller-Navarra, 2019). The majority of FA in aquatic
systems, including the Essential FA (EFA) 20:5n-3 and 22:6n-3, are
largely synthesized by primary producers, yet are also critical for the
health of consumers (Arts et al., 2001; Parrish, 2013). Because primary
consumers and higher trophic organisms must acquire these FA through
their diet (Dalsgaard et al., 2003), it is possible to use FA as trophic
markers (Kelly and Scheibling, 2012; Puccinelli et al., 2016c).

In urbanized coastal regions, metals (e.g., arsenic, cadmium, chromium, copper, lead, zinc) represent a major threat to mussel communities and compromise the quality and safety of this food resource (Dallinger et al., 1987; Yi et al., 2011; Jaishankar et al., 2014). Natural sources of metals include soil erosion and weathering, while anthropogenic processes such as mining, urban and industrial runoff, sewage, and agricultural discharge can also increase ambient metal concentrations (Bradl, 2005; Morais et al., 2012). Metals do not decompose in the environment and can be assimilated by mussels during filter feeding, bioaccumulating in their tissues (Casas and Bacher, 2006; Boudjema et al., 2022) to levels far in excess of those that are safe for higher organism and/or human ingestion (DOH, 1994; Taljaard, 2006).

Using South Africa's largest natural bay, False Bay, as a model for a
rapidly-urbanizing, coastal system, we investigated the role of mussels
in controlling water quality in a near-shore environment subject to
pollutant inputs in order to evaluate their role as an ecosystem service
provider. Our specific objectives included:

Determine the concentration of contaminants – in the form of inorganic N, metals, and anthropogenic aerosols – in coastal waters, evaluate their persistence with distance from the shore, and identify the natural processes that may attenuate them;

Characterize the role of mussels in attenuating inputs of pollution
and thus enhancing water quality;

Characterize the biodiversity of the marine community supported by
mussel populations to assess the possible anthropogenic effects
thereon.

## 2. Study area

False Bay, located near the City of Cape Town (population of >4
million; Stats SA 2016), is southern Africa's largest natural bay (nearly
1000 km²) (Fig. 1). The bay is south-facing and open to the sea, and is
located in the transition zone between the cold west coast and warm-
temperate south coast bioregions of South Africa (Emanuel et al.,
1992). As such, its biological diversity is extremely high (Awad et al.,
2002; Griffiths et al., 2010) and large portions of the bay are denoted
conservation regions, including marine protected areas with restricted
and controlled-use zones (Pfaff et al., 2019). False Bay's intertidal rocky
shore is colonized by benthic filter feeders, predominantly the mussel
*Mytilus galloprovincialis* (Robinson et al., 2005).

Surface water circulation in False Bay, while complex (Dufois and Rouault, 2012), is generally clockwise, with water entering the bay from the west. During summer (November-March), south-easterly winds promote offshore transport and (related) upwelling on the southeast side of the bay, while in winter, north-westerly winds favour onshore transport and enhanced mixing (Grundlingh et al., 1989; Grundlingh and Largier, 1991; Dufois and Rouault, 2012; De Vos, 2014; Jacobson, 2014). False Bay also experiences periodic warm-water intrusions from
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Map of the study area indicating the colour-coded rocky shore sites (black symbols) and onshore-offshore boat stations (blue symbols) sampled in False Bay in May 2018. The contour lines and blue shading show the bathymetry of the bay. The red circle indicates the location of the Cape Point Global Atmosphere Watch station, the site used for aerosol collection. Potential anthropogenic outflow sources to False Bay are also shown: river outflow (light green filled squares), storm water inflow (light green open squares), groundwater input (dark green squares), waste water treatment works (brown open squares). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

the Agulhas Current system to the east (Shannon and Chapman, 1983). In contrast to the large-scale bay circulation, Gordon's Bay to the north-east of False Bay (Fig. 1) hosts a semi-permanent anticyclonic eddy that drives a local anticlockwise circulation pattern (Atkins, 1970; Taljaard et al., 2000b) and increases the residence time of waters in this region (Pfaff et al., 2019).

False Bay hosts three small- to medium-sized harbours (Gordon's Bay, Kalk Bay, and Simons Town) that support limited commercial activities and are instead mainly dedicated to small-scale fisheries and recreational activities (Pfaff et al., 2019). The bay is under increasing anthropogenic pressure, largely due to rising urbanisation, as well as riverine inputs of transported pollutants, the latter mainly affecting the northern shoreline of the bay (Fig. 1; O'Callaghan, 1990; Binning and Baird, 2001; Pfaff et al., 2019). The rivers entering False Bay discharge anthropogenic contaminants from residential and industrial sewage and agriculture by-products (pesticides, fertilizers, farm waste; O'Callaghan 1990, Binning and Baird 2001), and there is also the possibility of atmospheric deposition of pollutants that originate inland (Abiodun et al. 2014).

# 3. Materials and methods

## 3.1. Sample collection

The sampling was conducted at eight rocky shore sites distributed along the False Bay coastline in May 2018 (Fig. 1). Along onshore-offshore transects perpendicular to each intertidal site (except site 7 (Kogel Bay)), samples were also collected between the surface and the seafloor. Sampling was conducted aboard the MA-RE 1 7.3 m Gemini inflatable craft, with each transect including two (transects 3- Muizenberg, 8- Rooi-Els) or three (transects 1- Millers Point, 2- Simons Town, 4- Monwabisi, 5- Strand, 6- Bikini Beach) stations: inshore A, mid-shore B,

and offshore C (Table S.1). At each station, seawater samples were collected from two to four depths using a hand-held 5 L Niskin bottle. Hydrographic data (temperature, salinity, oxygen concentrations) were generated using a Seabird conductivity-temperature-depth (CTD) profiler that was calibrated by the manufacturer a month before our sampling. The depth of the euphotic zone (Zeu) was estimated using a Secchi disk (Idso and Gilbert, 1974; Table S.1).

## 3.2. Biogeochemical parameters

Seawater samples were collected at the rocky shore sites and boat stations (see Table S.1 for sampling depths) for the analysis of nutrient concentrations (nitrate, nitrite, ammonium, phosphate, silicate), dissolved inorganic C (DIC) and total alkalinity (AT), nitrate isotope ratios, chlorophyll a concentrations, phytoplankton taxonomy, SI of particulate organic matter (N and C), and rates of net primary productivity (NPP), N (as nitrate, ammonium, and urea) uptake, and nitrite oxidation (i.e., a measure of nitrification).

### 3.2.1. Nutrients, carbonate system parameters, and nitrate isotopes

Seawater samples for nutrients and nitrate isotopes were collected in duplicate in 50 mL Falcon tubes and high-density polyethylene bottles, respectively, and frozen at -20 °C until analysis. Nitrate + nitrite ($NO_3^-$ + $NO_2^-$) and silicic acid ($Si(OH)_4$) concentrations were measured using a Lachat QuickChem flow injection analysis platform following published auto-analysis protocols (Grasshoff, 1976; Diamond, 1994). The detection limit for both nutrients was 0.1 µM and the precision was ≤0.2 µM. Phosphate ($PO_4^{3-}$) and nitrite ($NO_2^-$) concentrations were measured manually using standard colorimetric methods (Bendschneider and Robinson, 1952; Strickland and Parsons, 1968; Parsons et al., 1984), with a detection limit of 0.05 µM and precision of ≤0.2 µM. $NO_3^-$ concentrations were calculated by subtracting $NO_2^-$ from $NO_3^-$ + $NO_2^-$.
Aliquots of a certified reference material (CRM; JAMSTEC; Lot CG) were analysed during auto-analyser and manual runs to ensure measurement accuracy. The fluorometric method (Holmes et al. 1999) was used to analyse ammonium (NH₄⁺) concentrations, with a detection limit of 0.05 µM and precision of ≤0.2 µM. All NH₄⁺ measurements were corrected for the matrix effect (ME) that results from calibrating seawater samples with Milli-Q water standards (Saxberg and Kowalski, 1979); the ME was always <10%. Urea-N (hereafter, urea) concentrations were measured following the colorimetric method of Revilla et al. (2005) using a Thermo Scientific Genesys 30 Visible spectrophotometer with 5 cm path-length cell. The detection limit was 0.05 µM and the precision was ≤0.5 µM.

Samples for DIC and AT were collected by repeatedly overflowing 1 L glass bottles with seawater, injecting saturated HgCl₂ (1% final concentration), and immediately sealing with gas-tight crimp seals. Samples were analysed using a VINDTA 3C system (Marianda, Inc.) equipped with a CM-5011 carbon coulometer and calibrated using CRMs for oceanic CO₂ (provided by A.G. Dickson from Scripps Institution of Oceanography). The uncertainty associated with DIC and AT was ±6 µM and ±4 µM, respectively. For each sample, using CO2Sys v2.1. (Lewis and Wallace, 1998) and our measurements of temperature, salinity, DIC, AT, PO₄³⁻, and Si(OH)₄, we computed pH, carbonate ion concentration ([CO₃²⁻]ᵣcomputed), and, because mussel shells are composed of both calcite (outer layer) and aragonite (inner layer), the calcite and aragonite saturation state (Ωₐₐ and Ωₐ₄, respectively, where Ω = [CO₃²⁻]ᵣcomputed/[CO₃²⁻]ᵣsaturation). When Ωₐₐ or Ωₐ₄ = 1, seawater is in equilibrium with respect to the mineral phase, while Ωₐₐ or Ωₐ₄ > 1 indicates supersaturation and Ωₐₐ or Ωₐ₄ < 1 indicates undersaturation (Riebesell, et al., 2010). We used the stoichiometric equilibrium constants for carbonic acid of Lueker et al. (2000), for potassium bisulfate of Dickson (1990), and for boron of Lee et al. (2010).

The δ¹⁵N and δ¹⁸O (δ¹⁸O, in ‰ vs. VSMOW, =[(¹⁸O/¹⁶O)sample/ (¹⁸O/¹⁶O)ref -1] × 1000) of seawater nitrate (δ¹⁵NNO₃ and δ¹⁸ONO₃) were measured using the denitrifier method (Sigman et al., 2001; Casciotti et al., 2002; Weigand et al., 2016). Prior to isotopic analysis, samples were treated with sulfamic acid to remove NO₂⁻ since the denitrifier method converts both NO₂⁻ and NO₃⁻ to nitrous oxide gas (N₂O) (Granger and Sigman, 2009). The NO₃⁻ was then quantitatively converted to N₂O by the denitrifying bacteria, *Pseudomonas aureofaciens*, which lacks an N₂O reductase enzyme. The N and O isotope ratios of the resultant N₂O were measured using a Delta V Advantage isotope ratio mass spectrometer (IRMS) with purpose-built online N₂O extraction and purification system. Results were referenced to atmospheric N₂ and VSMOW using the CRMs IAEA-NO-3 (δ¹⁵N = 4.7 ± 0.2‰; Gonfiantini et al., 1995 and δ¹⁸O = 25.6 ± 0.4‰; Böhlke et al., 2003) and USGS-34 (δ¹⁵N = -1.8 ± 0.1‰ and δ¹⁸O = -27.9 ± 0.3‰; Böhlke et al., 2003). The analytical precision for repeat δ¹⁵NNO₃ and δ¹⁸ONO₃ measurements was ≤0.1‰ and ≤0.3‰, respectively.

### 3.2.2. *Chlorophyll a and phytoplankton taxonomy*

At each site and station, seawater (300 mL) was filtered through a 0.3 µm glass fibre filter (GF-75; Sterlitech) for the determination of chlorophyll *a* concentrations. In the laboratory, chlorophyll *a* was extracted in 90% acetone for 24 hr at -20 °C in the dark, after which fluorescence was determined using the non-acidified protocol of Welschmeyer (1994).

For phytoplankton community composition, samples (250 mL) were collected at the rocky shore sites and surface boat stations in amber glass bottles and immediately fixed with Lugol's solution (1% final concentration). Samples were settled overnight in 20 mL Utermöhl chambers (Utermöhl, 1958), then settled phytoplankton were enumerated using an Olympus CKX41 inverted microscope at 200x magnification, with identification to the highest taxonomic level possible. For each sample, minimum of 300 cells was counted.

### 3.2.3. *Particulate organic matter*

Seawater samples (300 mL) were filtered on-site through ashed (450 °C for 5 hr) GF-75 filters to capture particulate organic N (PON) and C (POC) and stored in ashed foil envelopes at -80 °C pending analysis. Filters were oven-dried at 40 °C for 24 hr, trimmed to remove unused perimeter filter, and pelletised in tin capsules. Samples were analysed for PON and POC content and δ¹³C and δ¹⁵N using a Flash Elemental Analyzer 1112 Series coupled to a Delta V Plus IRMS. A protocol blank (unused pre-combusted filter + tin capsule) was run after every 10-20 samples, and laboratory standards calibrated to IAEA reference materials were run after every five samples. The detection limit was 2 µg C and 1 µg N, and analytical precision was < 0.1‰ for δ¹³C and δ¹⁵N.

### 3.2.4. *Rates of NPP, N uptake, and nitrite oxidation*

Simulated *in situ* experiments were conducted to determine the rates of NPP and N (as NO₃⁻, NH₄⁺, and urea) uptake at the boat stations only. Seawater was collected at the surface at each inshore (A) and offshore station (C), pre-filtered (200 µm) to remove large grazers, and transferred to six 1 L clear polycarbonate bottles. Duplicate bottles were amended with ¹⁵urea-N, ¹⁵NH₄Cl, or K¹⁵NO₃ (final ¹⁵N concentration of 0.1 µM, 0.05 µM, or 0.5 µM) and NaH¹³CO₃ was added to four bottles (final ¹³C concentration of 100 µM). Bottles were incubated onboard for 4-6 hr in a custom-built incubator that was cooled via a continuous supply of running seawater and equipped with a neutral density filter to simulate light at ~1 m. Experiments were terminated via filtration onto ashed 0.3 µm GF-75 filters that were stored in cryovials at -80 °C until analysis. Incubation filters were analysed for C and N isotope ratios as described in section 2.3.3 above.

Rates of NPP and NO₃⁻, NH₄⁺, and urea uptake (ρNO₃⁻, ρNH₄⁺, purea; µM hr⁻¹) were calculated using the measured DIC and N-nutrient concentrations following Dugdale and Wilkerson (1986) as:

$$ \rho_x = \left( \frac{(R_{xs})}{((R_{enr}) - (F)) \times T} \right) \times \text{PON or POC} \quad (1) $$

where x is NPP, NO₃⁻, NH₄⁺ or urea; Rxs is the measured sample ¹⁵N or ¹³C atom % minus the natural abundance atom % (F, = 0.366% for ¹⁵N and 1.07% for ¹³C), Renr is the atom % ¹⁵N or ¹³C in the incubation seawater following tracer addition, and T is the incubation length (hr).

For NO₂⁻ oxidation, seawater was collected at stations A and C, from the surface and halfway to seafloor, and transferred to four 250 mL opaque polycarbonate bottles (two per depth). Experiments were initiated via the addition of Na¹⁵NO₂ (final ¹⁵N concentration of 0.4 µM), after which bottles were placed in the incubator for 24 hr. A 50 mL subsample was taken from each incubation bottle at 0 and 24 hr (i.e., T₀ immediately following ¹⁵NO₂ addition and T_f upon termination of the experiment) and frozen at -20 °C pending analysis. In the laboratory, samples were treated with sulfamic acid to remove residual ¹⁵NO₂ (Peng et al., 2015), then analysed using the denitrifier method as described in section 2.3.1 above, with an additional CRM, USGS-32 (δ¹⁵N = 180 ± 0.3‰; Böhlke et al., 1993), included in each run. The rate of NO₂⁻ oxidation (VNO₂⁻; µM/hr) was calculated following Peng et al. (2015) as:

$$ V_{NO_2^-} = \frac{\Delta[ \frac{^{15}NO_3^-}{f_{NO_2^-}^{15}} \times T ]}{f_{NO_2^-}^{15}} \quad (2) $$

where Δ[ ¹⁵NO₃⁻] is the difference in the concentration of ¹⁵NO₃⁻ between the Tfinal and Tinitial samples due to ¹⁵NO₂⁻ oxidation, fNO₂⁻¹⁵ is the fraction of ¹⁵NO₂⁻ at the start of the incubation, and T is the incubation length (hr). The detection limit for VNO₂⁻, calculated following Santoro et al. (2013), ranged from 0.11 to 0.36 nM/day.

### 3.3. Mussel biology

At each rocky shore site except site 5 (Strand) where mussels were absent, *M. galloprovincialis* samples were collected for condition index,
tissue δ¹³C and δ¹⁵N, and FA composition. Sampling was also conducted to assess the biodiversity associated with the mussel beds and to quantify benthic invertebrate settlement and recruitment.

### 3.3.1. Condition index and biodiversity

Twenty-five mussels from each site were collected for assessment of condition index (CI). The shell and soft body tissue of each mussel were separated and dried at 60 °C for 48 hr, after which the CI was calculated following Davenport and Chen (1987):

$$CI = \frac{\text{dry soft tissue weight}}{\text{dry shell weight}} \times 100 \quad (3)$$

The biodiversity of the community associated with the mussel beds was determined through destructive sampling. At each site, six replicate quadrats (15 × 15 cm) with 100% primary mussel cover were collected and stored in 100% ethanol. All organisms >0.5 mm were counted and identified to the highest taxonomic level possible using an Olympus SZX16 stereomicroscope.

### 3.3.2. Stable isotopes

Six mussel replicates of the same size (approximately 5 cm length) were haphazardly collected at each site for samples of adductor muscle. This tissue was chosen because of its long turnover rate (approximately nine months; Hill and McQuaid, 2009), which makes it the preferred indicator of integrated conditions. Mussels were dissected in the laboratory, rinsed with Milli-Q water to remove sediment, shell pieces, and other debris, then placed in 2 mL cryotubes and stored at -20 °C. Samples were subsequently dried at 60 °C for 48 hr, after which 0.5 mg of ground tissue was transferred to a tin capsule and analysed for δ¹³C and δ¹⁵N as described in section 2.3.3.

### 3.3.3. Fatty acids

Mussels were collected in triplicate at each site for samples of adductor muscle that were stored at -80 °C until analysis. Total lipids were extracted and trans-esterified using a modification of the Folch et al. (1957) procedure. Samples were lyophilised for 24 hr, then homogenised in 6 mL of a fresh solution of methanol and chloroform (2/ 1; v/v) and closed under an N₂ atmosphere. The FA methyl esters (FAME) were obtained after acidic transesterification of the sample by the addition of a H₂SO₄/methanol solution (3.4%; v/v) and heating at 100 °C for 10 min. FAME composition was determined using a Varian CP8400 Gas Chromatograph equipped with a ZBWAX column (30 m × 0.25 190 mm ID × 0.2 µm), with hydrogen as the carrier gas. Peaks were identified by comparison with retention times of external standards (Supelco 37 Component FAME Mix, PUFA No.1 and No.3, and Bacterial Acid Methyl Ester Mix; Sigma). FA are reported using the notation A:Bn-x, where A is the number of carbon atoms, B is the number of double bonds, and x indicates the position of the first double bond relative to the terminal methyl group (Puccinelli et al., 2016c).

### 3.3.4. Distribution of benthic invertebrate larvae

To determine the abundance and distribution of early-stage mussels in the water column, duplicate 60–100 L aliquots of seawater were collected adjacent to the rocky shore sites and from the surface boat stations using a submersible pump and filtered through a 75 µm sieve. The sieve contents were then stored in 500 mL bottles in 100% ethanol. Samples were processed for larval identification using a stereoscopic microscope (Leica MZ75, 2.0x magnification).

### 3.4. Potential pollutants

Along with measurements of nutrient concentrations and nitrate isotope ratios, which can provide information on anthropogenic N inputs and background nutrient cycling, samples were collected for the analysis of heavy metals and aerosols, the latter indicative of atmospheric deposition to surface waters (Altieri et al., 2021a).

#### 3.4.1. Metals

Mussels and sediment samples were collected at each rocky shore site for metal concentrations (n = 5 per site). Where possible, sediment samples were also collected from the inshore boat stations using a handheld Van Veen grab (40 × 10 cm, 0.1 m²). Samples were stored in clean plastic jars at -20 °C pending analysis. The entire mussel soft body was analysed, with frozen samples freeze-dried for 48 hr, weighed, and homogenised with a mortar and pestle. Subsamples (~0.5 g) were digested in 7 mL of a 6:1 nitric acid:hydrogen peroxide solution using a MARS microwave digestion system. Metal concentrations were measured using Inductively Coupled Plasma Mass Spectrometry (Agilent 7900) with an Octopole Reaction System. The results were compared to the CRM TORT-3 (CNRC; average uncertainty of ± 1.5 µg/g).

#### 3.4.2. Aerosols

Aerosols were collected daily during the sampling period on pre-combusted glass fibre filters using cyclone size-segregated samplers for fine- (<1 µm) and coarse mode (<10 µm) aerosols at the Cape Point Global Atmosphere Watch (GAW) station (34°21'S, 18°29'E). Filters were stored at -20 °C until aqueous extraction and sample analysis following standard procedures (Chen et al., 2010). Aqueous extracts were analysed for NO₃, NO₂, and NH₄, as well as other anions (Cl⁻ and SO₄²⁻) and cations (Na⁺, K⁺, Ca²⁺, Mg²⁺), using two Dionex Aquion Ion Chromatography Systems (Thermo Scientific) (Altieri et al., 2021b). Aerosol concentrations were converted to dry deposition fluxes following Duce et al. (1991). Aerosol NO₃⁻ was also measured for its δ¹⁵N and δ¹⁸O using the denitrifier method (Sigman et al., 2001; Casciotti et al., 2002; Weigand et al., 2016), amended for atmospheric samples (Hastings et al., 2003; Altieri et al., 2013). Air mass back trajectories were computed for all sample days using the NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The South African Weather Service provided ²²²Rn concentration data for air mass source analysis that was used to further constrain air mass history (Brunke et al., 2004).

### 3.5. Data analysis

#### 3.5.1. Univariate analyses

We tested the effects of the factor Site on the CI, δ¹³C, and δ¹⁵N of mussels using a one-way analysis of variance (ANOVA; factor Site, fixed, n = 7). In the event of significant results, Tukey HSD post hoc tests were conducted. Analyses were performed using R version 3.6.3. (R Core Team, 2020).

Variability among sites for metals in mussels and sediment was evaluated using a Kruskal-Wallis test. In the event of significant results, we performed post hoc pairwise tests adjusted by a Bonferroni correction for multiple tests. Statistical analyses were conducting using SPSS 2019 v26. The efficiency of metal accumulation in mussels was evaluated using a BioSediment Accumulation Factor (BSAF), corresponding to the ratio of metals in mussels versus sediment (Lau et al., 1998). The degree of metal contamination in sediment was determined from the Contamination Factor (CF) and Pollution Load Index (PLI) (El-Sammak and Aboul-Kassim, 1999). CF is the factor by which the metal concentrations exceed previous measurements at the same sites, computed here relative to data from 2001 (Mdzeke 2004). The PLI measures the contamination load as:

$$PLI = \sqrt[4]{(CF_{Zn})(CF_{Cu})(CF_{Cd})(CF_{Pb})} \quad (4)$$

where CFz, CFcu, CFcd, and CFpb are the CFs for zinc, copper, cadmium, and lead, respectively. PLI values > 1.2 imply high sedimentary metal contamination (El-Sammak and Aboul-Kassim, 1999). Metals in mussels and sediment were compared to the permissible legal limits in shellfish for South Africa (DOH, 1994, 2004) and recommended sediment quality guidelines for southern Africa (Taljaard, 2006).
### 3.5.2. Multivariate analyses

A multivariate permutational analysis (PERMANOVA; Anderson 2001) was performed to test for differences among sites (factor *Site*, fixed, n = 7) in the community associated with the mussel beds and the FA composition of the mussels. Variation in the distribution of larvae among sites was investigated using a PERMANOVA two-factor design (factor *Site*, fixed, n = 8; factor *Transect*, fixed, n = 7). Homogeneity of dispersions was tested using PERMDISP (Anderson et al., 2008a). Each term in the PERMANOVA analysis was tested using > 9999 permutations as the relevant permutable units (Anderson and Braak, 2003). In the event of significant results, PERMANOVA pairwise tests were performed.

Principal component analyses (PCA) were used to explore differences in the community associated with the mussel beds, mussel FA composition, and larval distribution in relation to the factors investigated. The combined results of the PCA and similarity percentage analyses (SIMPER) were used to assess the variables responsible for differences among groups of samples. All analyses were based on Bray-Curtis similarities calculated from percentage data after square root transformation. For the community associated with the mussel beds, Shannon (H') and Pielou's (J') indexes were computed to determine species diversity and evenness among sites. The analyses were conducted using the PERMANOVA+ add-on package of PRIMER v6 (Clarke and Gorley, 2006; Anderson et al., 2008).

## 4. Results

Samples were collected at eight rocky shore sites and along seven onshore-offshore transects, each consisting of two or three stations (A, B, C). The term *site* is thus used to denote rocky shore sampling locations (1 to 8), *transect* to indicate the entire onshore-offshore sampling (1 to 8, excluding site 7 (Kogel Bay, where boat sampling was not conducted), and *station* to refer to individual sampling locations along the boat transects (A, B, C).

### 4.1. Physical environment

Vertical profiles of temperature, salinity, and dissolved oxygen concentrations at the boat stations are shown in Fig. 2 and Fig S.1. Generally, the water column was well mixed, with a clear thermocline evident only at the deepest station, 8B (Rooi-Els) (Fig. 2a and Fig S.1 g1). Sea surface temperature ranged between 15.5 and 18.2 °C, and temperature decreased with depth to a minimum of 13.5 °C at station 8B. Salinity was generally higher to the west of the bay and at the offshore stations (except station 5C (Strand) where it reached a minimum), with values ranging between 34.4 and 35.8 (Fig. 2b and Fig S.1e2). Dissolved

oxygen was variable, with concentrations of 180 µM to 312 µM (Fig. 2c). Surface oxygen concentrations were roughly in equilibrium with the atmosphere at stations 3A and 3B (Muizenberg, Fig S.1c3), 4B (Monwabisi, Fig S.1d3), and 6B (Bikini Beach, Fig S.1f3), and undersaturated at the other stations. Stations along transect 5 had the lowest oxygen concentrations, with average surface values equivalent to ~50% saturation.

### 4.2. Biogeochemistry

#### 4.2.1. Nutrients and carbonate system parameters

Nutrient concentrations are summarised in Table 1a, with station averages (i.e., surface to depth at the boat stations) for the N species ($NO_3^-$, $NH_4^+$, urea) shown in Fig. 3a, and depth profiles of $NO_3^-$, $NO_2^-$, Si (OH)$_4$, and $PO_4^{3-}$ shown in Fig S.2. The average $NO_3^-$ concentration across the study region was 5.1 ± 5.1 µM, excluding transects 5 and 6 (Strand and Bikini Beach) where $NO_3^-$ was 14.7 ± 6.3 µM and 7.4 ± 3.2 µM, respectively. At station 5A, surface $NO_3^-$ reached > 20 µM, decreasing offshore. In general, $NO_3^-$ did not vary with depth, except at station 8B (Rooi-Els) where it showed a typical nutrient-like profile, reaching a concentration of 13.0 ± 1.1 µM at 25 m.

The $NO_2^-$ concentrations were generally low, averaging 0.5 ± 0.4 µM, and as per $NO_3^-$, were higher at transect 5 (1.5 ± 0.3 µM). $NH_4^+$ concentrations were higher in shallower waters and at the inshore stations, with the highest concentrations observed at transects 5 and 6 (3.7 ± 0.3 µM versus an average of 1.8 ± 0.4 µM for the other transects). The urea concentrations were generally low, averaging 0.6 ± 0.3 µM for all stations and depths, but reached a maximum of 4.4 µM at 9 m at station 5B.

The $Si(OH)_4$ concentrations averaged 7.0 ± 2.0 µM across the region and increased with depth at site 8B only, reaching 17.0 µM. Rocky shore site 3 (Muizenberg) and station 5B at 6 m were the only other cases where $Si(OH)_4$ exceeded 10 µM. The $PO_4^{3-}$ concentrations were generally low (0.6 ± 0.2 µM) and there was no clear trend among sites or stations, although at stations 4A and B (Monwabisi), $PO_4^{3-}$ exceeded 1 µM.

pH, $\Omega_{Ca}$, and $\Omega_{Ar}$ followed a west-east pattern, with significant higher values to the west of False Bay (transects 1 to 4; $p < 0.05$), regardless of depth or distance from the shore (Table S.2). Specifically, pH in the west ranged from 7.6 to 8.1 (average of 8.0 ± 0.1), while values of 7.6 to 7.9 (average of 7.8 ± 0.1) were computed for the eastern stations. $\Omega_{Ca}$ ranged from 1.9 to 4.5 (average of 3.5 ± 1.0) in the west and from 1.8 to 3.0 (average of 2.3 ± 0.1) in the east, while $\Omega_{Ar}$ ranged from 1.0 to 2.9 (average 2.2 ± 0.6) and from 1.1 to 1.9 (average 1.5 ± 0.2) in the west and east, respectively.

#### 4.2.2. Isotopes of particulate organic matter and nitrate

$\delta^{13}C_{POC}$ did not vary with depth; however, there was a significant

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Vertical profiles of a) temperature, b) salinity, and c) oxygen concentrations from the seven onshore-offshore transects sampled in False Bay in May 2018. The symbol shape indicates the station position (A = triangle (onshore), B = square (mid-shore), C = circle (offshore)) and the colour indicates the transect: 1- Millers Point (yellow), 2- Simons Town (green), 3- Muizenberg (cyan), 4- Monwabisi (blue), 5- Strand (light pink), 6- Bikini Beach (magenta), 8- Rooi-Els (orange). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<caption>Table 1</caption>

a) Concentrations of nutrients (NO₃⁻, Si(OH)₄, PO₄³⁻, NO₂⁻, NH₄⁺, urea) and b) stable isotopic composition of seawater nitrate (δ¹⁵NNO₃ and δ¹⁸ONO₃), suspended particulate organic nitrogen and carbon (δ¹⁵NPOON and δ¹³CPOON), and mussels (δ¹⁵NmusSEL and δ¹³CmusSEL), as well as chlorophyll a (Chl-α) and suspended PON and POC concentrations for samples collected at select intertidal sites and nearshore stations in False Bay in May 2018. Values are reported as mean ± standard error, except for Chl-α where only one sample was collected.

<table><thead><tr><th colspan="11">a)</th></tr><tr><th>Kind of sampling</th><th>Site name & number</th><th>Station</th><th>Depth (m)</th><th>Depth (m)</th><th>[NO3] ± SE<br>(µM)</th><th>[SiO4] ± SE<br>(µM)</th><th>[PO4] ± SE<br>(µM)</th><th>[NO2] ± SE<br>(µM)</th><th>[NH4] ± SE<br>(µM)</th><th>[Urea] ± SE<br>(µM)</th><th>[Chla] (µg/L)</th></tr></thead><tbody><tr><td>Rocky shore</td><td>1- Millers Point</td><td></td><td>surface</td><td></td><td>3.67</td><td>0.02</td><td>7.48</td><td>0.21</td><td>0.50</td><td>0.02</td><td>1.01</td><td>0.02</td><td>0.57</td><td>0.02</td><td>2.46</td></tr><tr><td>Rocky shore</td><td>2- Simons Town</td><td></td><td>surface</td><td></td><td>2.74</td><td>0.01</td><td>8.23</td><td>0.10</td><td>0.28</td><td>0.10</td><td>0.18</td><td>0.01</td><td>2.89</td><td>0.05</td><td>0.59</td><td>0.00</td><td>1.66</td></tr><tr><td>Rocky shore</td><td>3- Muizenberg</td><td></td><td>surface</td><td></td><td>4.04</td><td>0.07</td><td>10.68</td><td>0.05</td><td>0.36</td><td>0.04</td><td>0.30</td><td>0.00</td><td>4.31</td><td>0.06</td><td>0.89</td><td>0.10</td><td>1.11</td></tr><tr><td>Rocky shore</td><td>4- Monwabisi</td><td></td><td>surface</td><td></td><td>6.39</td><td>0.27</td><td>7.67</td><td>0.11</td><td>0.51</td><td>0.02</td><td>0.62</td><td>0.21</td><td>4.19</td><td>1.88</td><td>0.74</td><td>0.20</td><td>1.77</td></tr><tr><td>Rocky shore</td><td>5- Strand</td><td></td><td>surface</td><td></td><td>15.49</td><td>1.03</td><td>6.94</td><td>0.32</td><td>0.94</td><td>0.11</td><td>1.24</td><td>0.06</td><td>2.33</td><td>0.11</td><td>0.78</td><td>0.04</td><td>0.44</td></tr><tr><td>Rocky shore</td><td>6- Bikini Beach</td><td></td><td>surface</td><td></td><td>7.77</td><td></td><td>9.32</td><td></td><td>0.76</td><td>0.30</td><td>0.53</td><td>0.15</td><td>4.23</td><td>0.11</td><td>0.78</td><td>0.04</td><td>0.62</td></tr><tr><td>Rocky shore</td><td>7- Kogel Bay</td><td></td><td>surface</td><td></td><td>7.71</td><td>0.07</td><td>8.17</td><td>0.05</td><td>0.46</td><td>0.05</td><td>0.50</td><td>0.09</td><td>4.48</td><td>2.14</td><td>1.11</td><td>0.02</td><td>1.43</td></tr><tr><td>Rocky shore</td><td>8- Rooi-Els</td><td></td><td>surface</td><td></td><td>7.02</td><td>0.71</td><td>7.90</td><td>0.01</td><td>0.66</td><td>0.31</td><td>1.10</td><td>0.69</td><td>2.61</td><td>0.07</td><td>0.28</td><td>0.04</td><td>0.54</td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>A</td><td>surface</td><td>4</td><td>3.49</td><td>0.39</td><td>5.85</td><td>1.11</td><td>0.84</td><td>0.44</td><td>0.33</td><td>0.02</td><td>2.37</td><td>1.04</td><td>0.54</td><td>0.00</td><td>0.30</td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>A</td><td>4</td><td>4</td><td>6.51</td><td>0.02</td><td>4.71</td><td>0.07</td><td>0.86</td><td>0.01</td><td>1.07</td><td>0.10</td><td>1.24</td><td>0.15</td><td>0.61</td><td>0.21</td><td>0.34</td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>B</td><td>surface</td><td>8</td><td>2.45</td><td>0.03</td><td>8.33</td><td>0.07</td><td>0.51</td><td>0.03</td><td>0.22</td><td>0.01</td><td>2.50</td><td>0.11</td><td>0.66</td><td></td><td>0.31</td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>B</td><td>4</td><td>8</td><td>1.49</td><td>0.06</td><td>6.50</td><td>0.01</td><td>0.24</td><td>0.02</td><td>0.36</td><td>0.06</td><td>1.61</td><td>0.99</td><td>0.76</td><td>0.22</td><td>0.29</td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>B</td><td>8</td><td>8</td><td>1.69</td><td>0.14</td><td>4.66</td><td>0.44</td><td>0.46</td><td>0.02</td><td>0.23</td><td>0.02</td><td>0.14</td><td>0.01</td><td>0.28</td><td>0.04</td><td>0.41</td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>C</td><td>surface</td><td>20</td><td>0.79</td><td>0.04</td><td>5.10</td><td>0.18</td><td>0.27</td><td>0.01</td><td>0.09</td><td>0.01</td><td>2.34</td><td>1.93</td><td>0.44</td><td></td><td>2.15</td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>C</td><td>6</td><td>20</td><td>0.91</td><td>0.02</td><td>6.49</td><td>0.19</td><td>0.20</td><td>0.03</td><td>0.14</td><td>0.02</td><td>2.87</td><td>1.50</td><td>0.52</td><td>0.07</td><td>3.79</td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>C</td><td>13</td><td>20</td><td>0.96</td><td>0.02</td><td>6.84</td><td>0.48</td><td>0.69</td><td>0.14</td><td>0.03</td><td>0.02</td><td>1.34</td><td>0.82</td><td>0.37</td><td>0.01</td><td>4.34</td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>C</td><td>20</td><td>20</td><td>0.80</td><td>0.12</td><td>5.36</td><td>0.18</td><td>0.31</td><td>0.03</td><td>0.07</td><td>0.02</td><td>1.19</td><td>1.07</td><td>0.14</td><td>0.08</td><td>3.56</td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>A</td><td>surface</td><td>4</td><td>1.91</td><td>0.02</td><td>6.95</td><td>0.07</td><td>0.50</td><td>0.01</td><td>0.16</td><td>0.01</td><td>1.78</td><td>0.65</td><td>0.51</td><td>0.01</td><td>0.86</td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>A</td><td>4</td><td>4</td><td>1.18</td><td>0.05</td><td>5.34</td><td>0.16</td><td>0.35</td><td>0.02</td><td>0.10</td><td>0.02</td><td>1.39</td><td>0.01</td><td>0.63</td><td>0.15</td><td>0.93</td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>B</td><td>surface</td><td>9</td><td>1.71</td><td>0.02</td><td>7.12</td><td>0.07</td><td>0.50</td><td>0.02</td><td>0.15</td><td>0.01</td><td>1.02</td><td>0.32</td><td>0.63</td><td>0.03</td><td>0.95</td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>B</td><td>5</td><td>9</td><td>1.61</td><td>0.04</td><td>8.53</td><td>0.07</td><td>0.74</td><td>0.14</td><td>0.26</td><td>0.24</td><td>2.41</td><td>1.08</td><td>0.45</td><td>0.05</td><td>0.98</td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>B</td><td>9</td><td>9</td><td>1.56</td><td>0.18</td><td>7.15</td><td>0.26</td><td>0.43</td><td>0.04</td><td>0.10</td><td>0.00</td><td>1.99</td><td>0.45</td><td>0.39</td><td>0.07</td><td>1.17</td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>C</td><td>surface</td><td>18</td><td>1.61</td><td>0.24</td><td>7.20</td><td>0.73</td><td>0.68</td><td>0.04</td><td>0.11</td><td>0.05</td><td>2.44</td><td>0.05</td><td>0.32</td><td>0.08</td><td>0.88</td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>C</td><td>6</td><td>18</td><td>1.77</td><td>0.09</td><td>7.28</td><td>0.33</td><td>0.33</td><td>0.02</td><td>0.06</td><td>0.02</td><td>2.73</td><td>1.26</td><td>0.30</td><td>0.06</td><td>1.22</td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>C</td><td>12</td><td>18</td><td>1.27</td><td>0.16</td><td>5.67</td><td>0.03</td><td>0.25</td><td>0.01</td><td>0.06</td><td>0.00</td><td>2.56</td><td>2.13</td><td>0.51</td><td>0.21</td><td>1.76</td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>C</td><td>18</td><td>18</td><td>1.16</td><td>0.02</td><td>8.68</td><td>0.04</td><td>0.74</td><td>0.08</td><td>0.06</td><td>0.01</td><td>0.93</td><td>0.35</td><td>0.41</td><td>0.07</td><td>0.76</td></tr><tr><td>Boat</td><td>3- Muizenberg</td><td>A</td><td>surface</td><td>1</td><td>0.89</td><td>0.04</td><td>4.77</td><td>0.07</td><td>0.34</td><td>0.02</td><td>0.10</td><td>0.01</td><td>2.47</td><td>0.07</td><td>0.48</td><td>0.00</td><td>1.65</td></tr><tr><td>Boat</td><td>3- Muizenberg</td><td>B</td><td>surface</td><td>4</td><td>1.20</td><td>0.03</td><td>7.95</td><td>0.13</td><td>0.33</td><td>0.07</td><td>0.15</td><td>0.01</td><td>0.18</td><td>0.02</td><td>0.42</td><td>0.12</td><td>1.05</td></tr><tr><td>Boat</td><td>3- Muizenberg</td><td>B</td><td>4</td><td>4</td><td>1.04</td><td>0.07</td><td>8.12</td><td>0.01</td><td>0.32</td><td>0.02</td><td>0.19</td><td>0.02</td><td>1.13</td><td>0.51</td><td>0.49</td><td>0.00</td><td>1.84</td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>A</td><td>surface</td><td>4</td><td>2.98</td><td>0.25</td><td>2.68</td><td>0.21</td><td>1.00</td><td>0.04</td><td>0.28</td><td>0.05</td><td>1.18</td><td>0.87</td><td>0.41</td><td>0.05</td><td>3.16</td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>A</td><td>4</td><td>4</td><td>3.47</td><td>0.02</td><td>3.09</td><td>0.01</td><td>1.10</td><td>0.01</td><td>0.26</td><td>0.02</td><td>3.45</td><td>1.02</td><td>0.52</td><td>0.02</td><td>3.22</td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>B</td><td>surface</td><td>7</td><td>3.40</td><td>0.93</td><td>7.35</td><td>0.85</td><td>1.10</td><td>0.05</td><td>0.28</td><td>0.01</td><td>1.90</td><td>0.21</td><td>0.70</td><td>0.01</td><td>4.21</td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>B</td><td>4</td><td>7</td><td>2.05</td><td>0.04</td><td>5.41</td><td>0.05</td><td>0.74</td><td>0.10</td><td>0.14</td><td>0.01</td><td>0.13</td><td>0.04</td><td>0.18</td><td>0.08</td><td>1.34</td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>B</td><td>7</td><td>7</td><td>1.24</td><td>0.10</td><td>6.80</td><td>0.29</td><td>0.69</td><td>0.08</td><td>0.11</td><td>0.04</td><td>1.13</td><td>1.04</td><td>0.29</td><td>0.11</td><td>7.23</td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>C</td><td>surface</td><td>14</td><td>3.52</td><td>0.83</td><td>6.57</td><td>0.46</td><td>0.32</td><td>0.09</td><td>0.02</td><td>0.02</td><td>0.07</td><td>0.03</td><td>0.69</td><td>0.05</td><td>1.87</td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>C</td><td>4</td><td>14</td><td>1.11</td><td>0.04</td><td>8.16</td><td>0.08</td><td>0.51</td><td>0.03</td><td>0.06</td><td>0.04</td><td>0.23</td><td>0.10</td><td>0.14</td><td></td><td>2.19</td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>C</td><td>8</td><td>14</td><td>1.20</td><td>0.02</td><td>8.79</td><td>0.06</td><td>0.26</td><td>0.02</td><td>0.02</td><td>0.01</td><td>0.13</td><td>0.07</td><td>0.41</td><td>0.19</td><td>21.76</td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>C</td><td>14</td><td>14</td><td>1.32</td><td>0.03</td><td>4.99</td><td>0.17</td><td>0.83</td><td>0.10</td><td>0.03</td><td>0.00</td><td>0.85</td><td>0.67</td><td>0.31</td><td>0.09</td><td>5.28</td></tr><tr><td>Boat</td><td>5- Strand</td><td>A</td><td>surface</td><td>1</td><td>20.86</td><td>1.42</td><td>9.84</td><td>0.37</td><td>0.83</td><td>0.06</td><td>1.59</td><td>0.18</td><td>3.95</td><td>0.01</td><td>0.97</td><td>0.19</td><td>0.79</td></tr><tr><td>Boat</td><td>5- Strand</td><td>B</td><td>surface</td><td>6</td><td>14.09</td><td>0.37</td><td>8.08</td><td>0.16</td><td>0.76</td><td>0.07</td><td>1.74</td><td>0.17</td><td>4.87</td><td>0.17</td><td>0.69</td><td>0.00</td><td>1.98</td></tr><tr><td>Boat</td><td>5- Strand</td><td>B</td><td>6</td><td>6</td><td>20.00</td><td>0.20</td><td>10.20</td><td>0.02</td><td>0.65</td><td>0.05</td><td>1.59</td><td>0.19</td><td>4.33</td><td>0.07</td><td>4.38</td><td></td><td>4.11</td></tr><tr><td>Boat</td><td>5- Strand</td><td>C</td><td>surface</td><td>9</td><td>12.86</td><td>0.34</td><td>7.99</td><td>0.09</td><td>0.89</td><td>0.16</td><td>1.57</td><td>0.10</td><td>1.49</td><td>0.79</td><td>1.80</td><td>0.76</td><td>1.87</td></tr><tr><td>Boat</td><td>5- Strand</td><td>C</td><td>5</td><td>9</td><td>9.49</td><td>0.48</td><td>8.26</td><td>0.29</td><td>0.87</td><td>0.17</td><td>0.98</td><td>0.06</td><td>4.24</td><td></td><td>1.33</td><td>0.55</td><td>3.52</td></tr><tr><td>Boat</td><td>5- Strand</td><td>C</td><td>9</td><td>9</td><td>8.28</td><td>0.77</td><td>7.93</td><td>0.35</td><td>0.54</td><td>0.05</td><td>1.72</td><td>0.30</td><td>1.24</td><td>0.08</td><td></td><td></td><td>2.26</td></tr></tbody></table>

(continued on next page)
<table><caption>Table 1 (continued)</caption><thead><tr><th colspan="11">a)</th></tr><tr><th>Kind of sampling</th><th>Site name & number</th><th>Station</th><th>Depth (m)</th><th>Depth (m)</th><th>[NO3] ± SE (µM)</th><th>[SiO4] ± SE (µM)</th><th>[PO4] ± SE (µM)</th><th>[NO2] ± SE (µM)</th><th>[NH4] ± SE (µM)</th><th>[Urea] ± SE (µM)</th><th>[Chla] (µg/L)</th></tr></thead><tbody><tr><td>Boat</td><td>6- Bikini Beach</td><td>A</td><td>surface</td><td>1</td><td>8.32</td><td>0.06</td><td>8.28</td><td>0.07</td><td>0.76</td><td>0.03</td><td>0.93</td><td>0.00</td><td>4.77</td><td>0.19</td><td>0.47</td><td>0.31</td><td>0.85</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>B</td><td>surface</td><td>5</td><td>6.52</td><td>0.24</td><td>7.28</td><td>0.13</td><td>0.54</td><td>0.07</td><td>0.91</td><td>0.11</td><td>2.06</td><td>0.04</td><td>0.58</td><td>0.20</td><td>3.31</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>B</td><td>5</td><td>5</td><td>9.27</td><td>0.42</td><td>9.15</td><td>0.26</td><td>0.79</td><td>0.34</td><td>0.66</td><td>0.10</td><td>3.76</td><td></td><td>0.94</td><td>0.10</td><td>1.74</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>C</td><td>surface</td><td>7</td><td>11.11</td><td>0.02</td><td>8.32</td><td>0.04</td><td>0.90</td><td>0.01</td><td>0.00</td><td>0.04</td><td>3.83</td><td>1.25</td><td>0.30</td><td></td><td>2.66</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>C</td><td>4</td><td>7</td><td>7.17</td><td>1.02</td><td>7.14</td><td>0.71</td><td>0.83</td><td>0.14</td><td>0.33</td><td>0.20</td><td>2.37</td><td>0.06</td><td>0.74</td><td>0.04</td><td>14.69</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>C</td><td>7</td><td>7</td><td>6.97</td><td>0.73</td><td>7.40</td><td>0.70</td><td>0.73</td><td>0.18</td><td>0.87</td><td>0.11</td><td>1.72</td><td>0.05</td><td>0.64</td><td>0.24</td><td>5.66</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>A</td><td>surface</td><td>12</td><td>5.13</td><td>0.01</td><td>7.53</td><td>0.02</td><td>0.53</td><td>0.05</td><td>0.44</td><td>0.00</td><td>2.32</td><td>0.73</td><td>0.99</td><td>0.15</td><td>2.64</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>A</td><td>4</td><td>12</td><td>4.45</td><td>0.30</td><td>8.11</td><td>0.32</td><td>0.49</td><td>0.04</td><td>0.49</td><td>0.06</td><td>2.82</td><td>0.13</td><td></td><td></td><td>2.39</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>A</td><td>8</td><td>12</td><td>6.09</td><td>0.21</td><td>7.31</td><td>0.25</td><td>0.75</td><td>0.05</td><td>0.39</td><td>0.04</td><td>2.82</td><td>0.30</td><td>0.89</td><td></td><td>1.29</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>A</td><td>12</td><td>12</td><td>5.48</td><td>0.10</td><td>8.65</td><td>0.08</td><td>0.65</td><td>0.10</td><td>0.41</td><td>0.10</td><td>2.40</td><td>0.84</td><td>0.79</td><td>0.07</td><td>1.01</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>B</td><td>surface</td><td>25</td><td>2.08</td><td>0.08</td><td>7.01</td><td>0.01</td><td>0.29</td><td>0.05</td><td>0.33</td><td>0.06</td><td>0.40</td><td>0.04</td><td>0.79</td><td>0.05</td><td>6.65</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>B</td><td>4</td><td>25</td><td>2.85</td><td>0.12</td><td>6.23</td><td>0.22</td><td>0.66</td><td>0.09</td><td>0.31</td><td>0.01</td><td>1.38</td><td>0.08</td><td>0.55</td><td>0.05</td><td>9.97</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>B</td><td>12</td><td>25</td><td>3.57</td><td>0.08</td><td>8.08</td><td>0.05</td><td>0.30</td><td>0.03</td><td>0.53</td><td>0.07</td><td>1.34</td><td>0.10</td><td>0.72</td><td>0.12</td><td>2.67</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>B</td><td>25</td><td>25</td><td>12.99</td><td>0.11</td><td>17.03</td><td>0.12</td><td>0.76</td><td>0.06</td><td>0.49</td><td>0.00</td><td>2.35</td><td>0.20</td><td>0.49</td><td>0.00</td><td></td></tr></tbody></table>

<table><thead><tr><th colspan="11">b)</th></tr><tr><th>Kind of sampling</th><th>Site name & number</th><th>Station</th><th>Depth (m)</th><th>Bottom depth (m)</th><th>NO3 δ<sup>15</sup>N ± SE (‰)</th><th>NO3 δ<sup>18</sup>O ± SE (‰)</th><th>PON δ<sup>15</sup>N ± SE (‰)</th><th>PON ± SE (µM)</th><th>POC δ<sup>13</sup>C ± SE (‰)</th><th>POC ± SE (µM)</th><th>Mussel δ<sup>15</sup>N ± SE (‰)</th><th>Mussel δ<sup>13</sup>C ± SE (‰)</th></tr></thead><tbody><tr><td>Rocky shore</td><td>1- Millers Point</td><td></td><td>surface</td><td></td><td></td><td>6.24</td><td>1.54</td><td>2.01</td><td>0.27</td><td>-12.61</td><td>0.80</td><td>22.03</td><td>4.82</td><td>7.87</td><td>0.05</td><td>-15.73</td><td>0.51</td></tr><tr><td>Rocky shore</td><td>2- Simons Town</td><td></td><td>surface</td><td></td><td></td><td>4.40</td><td>2.24</td><td>2.44</td><td>0.38</td><td>-14.63</td><td>0.50</td><td>24.29</td><td>6.46</td><td>8.15</td><td>0.04</td><td>-15.52</td><td>0.17</td></tr><tr><td>Rocky shore</td><td>3- Muizenberg</td><td></td><td>surface</td><td></td><td></td><td>6.60</td><td></td><td>2.02</td><td>0.23</td><td>-11.61</td><td></td><td>20.14</td><td>0.76</td><td>9.14</td><td>0.09</td><td>-14.52</td><td>0.04</td></tr><tr><td>Rocky shore</td><td>4- Monwabisi</td><td></td><td>surface</td><td></td><td>8.79</td><td>0.08</td><td>4.99</td><td>0.15</td><td>7.35</td><td>0.14</td><td>3.56</td><td>0.27</td><td>-7.82</td><td>0.56</td><td>62.74</td><td>4.85</td><td>-15.17</td><td>0.39</td></tr><tr><td>Rocky shore</td><td>5- Strand</td><td></td><td>surface</td><td></td><td>7.94</td><td>0.62</td><td>3.76</td><td>0.77</td><td>7.49</td><td>1.49</td><td>2.53</td><td>0.33</td><td>-8.86</td><td>1.06</td><td>38.25</td><td>6.92</td><td></td><td></td></tr><tr><td>Rocky shore</td><td>6- Bikini Beach</td><td></td><td>surface</td><td></td><td>6.61</td><td>0.32</td><td>2.52</td><td>0.35</td><td>7.79</td><td>2.54</td><td>1.97</td><td>0.00</td><td>-9.63</td><td>1.10</td><td>30.51</td><td>1.99</td><td>8.74</td><td>0.07</td></tr><tr><td>Rocky shore</td><td>7- Kogel Bay</td><td></td><td>surface</td><td></td><td>6.84</td><td>0.26</td><td>4.36</td><td>0.35</td><td>6.91</td><td>1.14</td><td>3.34</td><td>0.22</td><td>-10.35</td><td>0.50</td><td>38.34</td><td>3.60</td><td>8.03</td><td>0.08</td></tr><tr><td>Rocky shore</td><td>8- Rooi-Els</td><td></td><td>surface</td><td></td><td>6.82</td><td>0.13</td><td>2.01</td><td>0.15</td><td>11.40</td><td>5.34</td><td>1.56</td><td>0.03</td><td>-13.30</td><td>2.86</td><td>17.83</td><td>1.64</td><td>8.23</td><td>0.06</td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>A</td><td>surface</td><td>4</td><td></td><td></td><td></td><td></td><td>6.18</td><td>0.25</td><td>2.16</td><td>0.79</td><td>-16.49</td><td>0.88</td><td>22.73</td><td>6.87</td><td></td><td></td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>A</td><td>4</td><td>4</td><td>5.83</td><td>0.00</td><td>0.36</td><td>0.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>B</td><td>surface</td><td>8</td><td></td><td></td><td></td><td></td><td>6.28</td><td></td><td>0.72</td><td></td><td>-20.01</td><td></td><td>11.08</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>B</td><td>4</td><td>8</td><td>5.78</td><td>0.00</td><td>1.04</td><td>0.00</td><td>6.78</td><td></td><td>0.74</td><td></td><td>-19.67</td><td></td><td>12.50</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>B</td><td>8</td><td>8</td><td>5.38</td><td>0.00</td><td>1.65</td><td>0.00</td><td>6.16</td><td></td><td>0.52</td><td></td><td>-18.16</td><td></td><td>7.09</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>C</td><td>surface</td><td>20</td><td>7.55</td><td>0.00</td><td>4.37</td><td>0.00</td><td>6.62</td><td></td><td>1.81</td><td></td><td>-19.01</td><td></td><td>19.42</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>C</td><td>6</td><td>20</td><td></td><td></td><td></td><td></td><td>6.87</td><td></td><td>4.05</td><td></td><td>-16.35</td><td></td><td>42.22</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>C</td><td>13</td><td>20</td><td></td><td></td><td></td><td></td><td>7.06</td><td></td><td>2.74</td><td></td><td>-16.51</td><td></td><td>30.66</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>1- Millers Point</td><td>C</td><td>20</td><td>20</td><td></td><td></td><td></td><td></td><td>7.61</td><td></td><td>1.83</td><td></td><td>-16.80</td><td></td><td>22.34</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>A</td><td>surface</td><td>4</td><td></td><td></td><td></td><td></td><td>6.40</td><td></td><td>1.82</td><td>0.59</td><td>-19.25</td><td></td><td>15.57</td><td>3.00</td><td></td><td></td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>A</td><td>4</td><td>4</td><td></td><td></td><td></td><td></td><td>7.35</td><td></td><td>1.28</td><td></td><td>-24.56</td><td></td><td>17.70</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>B</td><td>surface</td><td>9</td><td>7.14</td><td>0.00</td><td>4.64</td><td>0.00</td><td>6.32</td><td></td><td>1.27</td><td></td><td>-18.82</td><td></td><td>11.73</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>B</td><td>5</td><td>9</td><td>6.26</td><td>0.00</td><td>6.00</td><td>0.00</td><td>6.21</td><td></td><td>1.44</td><td></td><td>-19.42</td><td></td><td>14.36</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>B</td><td>9</td><td>9</td><td>6.92</td><td>0.00</td><td>5.71</td><td>0.00</td><td>6.29</td><td></td><td>1.52</td><td></td><td>-17.36</td><td></td><td>15.67</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>C</td><td>surface</td><td>18</td><td>7.15</td><td>0.24</td><td>5.53</td><td>3.29</td><td>6.26</td><td></td><td>1.43</td><td></td><td>-19.58</td><td></td><td>15.40</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>C</td><td>6</td><td>18</td><td>6.45</td><td>0.00</td><td>5.74</td><td>0.00</td><td>6.28</td><td></td><td>1.21</td><td></td><td>-18.19</td><td></td><td>11.76</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>C</td><td>12</td><td>18</td><td>7.09</td><td>0.00</td><td>7.81</td><td>0.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>2- Simons Town</td><td>C</td><td>18</td><td>18</td><td></td><td></td><td></td><td></td><td>7.26</td><td></td><td>0.68</td><td></td><td>-20.63</td><td></td><td>8.45</td><td></td><td></td><td></td></tr><tr><td>Boat</td><td>3- Muizenberg</td><td>A</td><td>surface</td><td>1</td><td>6.78</td><td>0.00</td><td>4.81</td><td>0.00</td><td>5.71</td><td>0.02</td><td>1.90</td><td>0.14</td><td>-15.63</td><td>0.17</td><td>16.17</td><td>0.17</td><td></td><td></td></tr><tr><td>Boat</td><td>3- Muizenberg</td><td>B</td><td>surface</td><td>4</td><td></td><td></td><td></td><td></td><td>5.66</td><td></td><td>1.18</td><td></td><td>-19.12</td><td></td><td>12.25</td><td></td><td></td><td></td></tr></tbody></table>

(continued on next page)
<table><caption>Table 1 (continued)</caption><thead><tr><th>Kind of sampling</th><th>Site name &amp; number</th><th>Station</th><th>Depth (m)</th><th>Bottom depth (m)</th><th>NO3 δ<sup>15</sup>N ± SE (‰)</th><th>NO3 δ<sup>18</sup>O ± SE (‰)</th><th>PON δ<sup>15</sup>N ± SE (‰)</th><th>PON ± SE (μM)</th><th>POC δ<sup>13</sup>C ± SE (‰)</th><th>POC ± SE (μM)</th><th>Mussel δ<sup>15</sup>N ± SE (‰)</th><th>Mussel δ<sup>13</sup>C ± SE (‰)</th></tr></thead><tbody><tr><td>Boat</td><td>3- Muizenberg</td><td>B</td><td>4</td><td>4</td><td></td><td></td><td>6.43</td><td>1.79</td><td>-16.77</td><td>19.36</td><td></td><td></td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>A</td><td>surface</td><td>4</td><td></td><td></td><td>4.45</td><td>2.25</td><td>-11.01</td><td>30.78</td><td>2.95</td><td></td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>A</td><td>4</td><td>4</td><td></td><td></td><td>6.83</td><td>2.39</td><td>-10.23</td><td>33.33</td><td></td><td></td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>B</td><td>surface</td><td>7</td><td></td><td></td><td>4.59</td><td>4.31</td><td>-14.41</td><td>39.11</td><td></td><td></td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>B</td><td>4</td><td>7</td><td></td><td></td><td>7.79</td><td>6.92</td><td>-14.44</td><td>67.62</td><td></td><td></td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>B</td><td>7</td><td>7</td><td>11.37</td><td>0.00</td><td>7.46</td><td>3.94</td><td>-13.06</td><td>47.01</td><td></td><td></td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>C</td><td>surface</td><td>14</td><td></td><td></td><td>7.24</td><td>1.54</td><td>-18.03</td><td>17.43</td><td></td><td></td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>C</td><td>4</td><td>14</td><td></td><td></td><td></td><td>0.00</td><td></td><td>0.00</td><td></td><td></td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>C</td><td>8</td><td>14</td><td></td><td></td><td>7.36</td><td>11.26</td><td>-14.98</td><td>134.56</td><td></td><td></td></tr><tr><td>Boat</td><td>4- Monwabisi</td><td>C</td><td>14</td><td>14</td><td>10.39</td><td>0.00</td><td>7.40</td><td>3.01</td><td>-17.17</td><td>42.29</td><td></td><td></td></tr><tr><td>Boat</td><td>5- Strand</td><td>A</td><td>surface</td><td>1</td><td>8.18</td><td>0.17</td><td>1.75</td><td>0.15</td><td>6.55</td><td>0.26</td><td>-9.61</td><td>1.21</td><td>33.88</td></tr><tr><td>Boat</td><td>5- Strand</td><td>B</td><td>surface</td><td>6</td><td>8.01</td><td>0.42</td><td>3.03</td><td>0.12</td><td>5.69</td><td>1.50</td><td>-14.33</td><td></td><td>19.88</td></tr><tr><td>Boat</td><td>5- Strand</td><td>B</td><td>6</td><td>6</td><td>8.18</td><td>0.18</td><td>1.69</td><td>0.23</td><td>6.02</td><td>5.43</td><td>-9.02</td><td></td><td>86.35</td></tr><tr><td>Boat</td><td>5- Strand</td><td>C</td><td>surface</td><td>9</td><td>7.53</td><td>0.28</td><td>2.94</td><td>0.21</td><td>1.91</td><td>2.33</td><td>-14.00</td><td></td><td>19.05</td></tr><tr><td>Boat</td><td>5- Strand</td><td>C</td><td>5</td><td>9</td><td>7.60</td><td>0.14</td><td>3.03</td><td>0.16</td><td>5.53</td><td>1.53</td><td>-15.23</td><td></td><td>17.25</td></tr><tr><td>Boat</td><td>5- Strand</td><td>C</td><td>9</td><td>9</td><td>7.61</td><td>0.16</td><td>2.25</td><td>0.76</td><td>6.54</td><td>1.21</td><td>-14.49</td><td></td><td>16.62</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>A</td><td>surface</td><td>1</td><td>7.67</td><td>0.48</td><td>3.44</td><td>0.50</td><td>6.36</td><td>0.22</td><td>-16.32</td><td>0.51</td><td>15.63</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>B</td><td>surface</td><td>5</td><td>7.96</td><td>0.07</td><td>2.92</td><td>0.14</td><td>7.07</td><td>2.17</td><td>-19.73</td><td></td><td>20.09</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>B</td><td>5</td><td>5</td><td></td><td></td><td></td><td></td><td>5.61</td><td>1.00</td><td>-14.68</td><td></td><td>12.14</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>C</td><td>surface</td><td>7</td><td></td><td></td><td></td><td></td><td>6.16</td><td>2.56</td><td>-18.17</td><td></td><td>22.02</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>C</td><td>4</td><td>7</td><td></td><td></td><td></td><td></td><td>7.50</td><td>6.26</td><td>-16.03</td><td></td><td>54.72</td></tr><tr><td>Boat</td><td>6- Bikini Beach</td><td>C</td><td>7</td><td>7</td><td></td><td></td><td></td><td></td><td>7.35</td><td>2.07</td><td>-15.11</td><td></td><td>19.49</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>A</td><td>surface</td><td>12</td><td>6.78</td><td>0.13</td><td>1.79</td><td>0.27</td><td>7.54</td><td>1.07</td><td>-17.18</td><td>3.83</td><td>19.24</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>A</td><td>4</td><td>12</td><td></td><td></td><td></td><td></td><td>6.68</td><td>1.14</td><td>-18.13</td><td></td><td>12.19</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>A</td><td>8</td><td>12</td><td>6.81</td><td>0.09</td><td>2.36</td><td>0.49</td><td>7.44</td><td>1.06</td><td>-18.70</td><td></td><td>14.99</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>A</td><td>12</td><td>12</td><td>6.66</td><td>0.00</td><td>1.45</td><td>0.00</td><td>7.18</td><td>1.30</td><td>-19.91</td><td></td><td>17.59</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>B</td><td>surface</td><td>25</td><td></td><td></td><td></td><td></td><td>7.35</td><td>4.10</td><td>-16.30</td><td></td><td>36.54</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>B</td><td>4</td><td>25</td><td></td><td></td><td></td><td></td><td>7.50</td><td>5.64</td><td>-15.94</td><td></td><td>50.26</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>B</td><td>12</td><td>25</td><td></td><td></td><td></td><td></td><td>7.24</td><td>1.37</td><td>-17.51</td><td></td><td>13.67</td></tr><tr><td>Boat</td><td>8- Rooi-Els</td><td>B</td><td>25</td><td>25</td><td>8.56</td><td>0.29</td><td>3.59</td><td>0.82</td><td>7.21</td><td>0.98</td><td>-17.92</td><td></td><td>14.84</td></tr></tbody></table>
difference among stations (p < 0.05; Table 1b). Transects 1 (Millers Point), 2 (Simons Town), 3 (Muizenberg), and 8 (Rooi-Els) had lower average δ¹³C~P~OC (-18.3 ± 1.8‰) than transects 4 (Monwabisi), 5 (Strand), and 6 (Bikini Beach) (-13.8 ± 3.3‰) where the inshore sites and stations were characterized by the highest δ¹³C~P~OC (rocky shore and station A, -10.5 ± 1.2‰). The δ¹³C~P~OC at site 7 (Kogel Bay) was similarly high (-10.4 ± 0.5‰; note that no offshore sampling occurred at this site). We observed a clear onshore-offshore pattern, with δ¹³C~P~OC decreasing with distance from the coast (Table 1b). For example, at transect 4, δ¹³C~P~OC decreased from -7.8 ± 0.6‰ at the rocky shore to -16.8 ± 1.6‰ at station 4C.

δ¹⁵N~P~ON averaged 6.6 ± 1.0‰ across the study region and varied significantly among stations and with depth (p < 0.05), with significant interactions between the two factors (*post-hoc* test, p < 0.05). δ¹⁵N~P~ON increased with depth at stations 4A, 4B, 5C, and 6C, with the largest δ¹⁵N change observed between the surface and 5 m samples (increase of 1.3‰ to 3.6‰; Table 1b, Fig S.3). An onshore-offshore decline in surface δ¹⁵N~P~ON occurred at transects 3, 4, and 5, with the rocky shore sites characterized by a higher δ¹⁵N~P~ON (by 0.9‰ to 2.8‰) than the offshore stations. The opposite pattern was observed for transect 2 where the rocky shore site had a lower δ¹⁵N~P~ON (by 1.9‰) than the offshore stations. The lowest δ¹⁵N~P~ON (1.9‰) was measured in the surface at station 5C.

δ¹⁵N~NO₃~ ranged between 5.4‰ and 11.4‰, with an average across all sites and stations of 7.4 ± 1.2‰ (7.1 ± 0.8‰ without transect 4), and did not vary significantly with depth. The highest average δ¹⁵N~NO₃~ was recorded at transects 4 (average of 10.2 ± 1.3‰) and 5 (average of 7.9 ± 0.3‰), and the lowest at transect 1 (average of 6.1 ± 1.0‰) (Table 1b, Fig S.3). No clear onshore-offshore pattern was evident, except at transect 1 where δ¹⁵N~NO₃~ increased by 1.9‰ between stations A/B and C. By contrast, we observed a clear west-east rise in δ¹⁵N~NO₃~ from an average of 6.6 ± 0.4‰ at sites and stations 1 through 3 to 7.5 ± 0.4‰ at sites and transects 5 through 8. At each site or station, δ¹⁵N~NO₃~ was always similar to or higher than the corresponding δ¹⁵N~PON~, with the exception of rocky shore sites 6 and 8 where δ¹⁵N~PON~ was 1.2‰ and 4.6‰ higher, respectively, than δ¹⁵N~NO₃~ (Table 1b).

δ¹⁸O~NO₃~ ranged from 0.4‰ to 20.1‰, with an average across all sites and stations of 5.3 ± 1.2‰ (3.7 ± 0.6‰ without transect 4 where δ¹⁸O~NO₃~ was extraordinarily high). At transects 5 through 8, δ¹⁸O~NO₃~ generally followed δ¹⁵N~NO₃~, changing in an approximate ratio of 1:1 (Fig S.4). By contrast, at transects 1 through 3, δ¹⁸O~NO₃~ changed by ~4‰ while δ¹⁵N~NO₃~ varied by <1‰. As for δ¹⁵N~NO₃~, the δ¹⁸O~NO₃~ at transect 1 was anomalously low compared to the other stations (1.8 ± 0.8‰).

### 4.2.3. Rates of NPP, N uptake, and nitrite oxidation

Rates of NPP and N uptake were variable and did not follow a west-east gradient (Fig. 3). NPP varied by three orders of magnitude, with the highest rates at inshore station 4A (Monwabisi, 1.7 ± 0.7 µM/hr) and the lowest at station 1A (Millers Point, 0.0 ± 0.0 µM/hr). Stations 6A and C (Bikini Beach) hosted the second highest rates of 0.9 ± 0.2 µM/hr and 0.7 ± 0.1 µM/hr, respectively, and 0.8 ± 0.1 µM/hr was measured at station 3A (Muizenberg). NPP at the other stations was ≤0.4 µM/hr, with an average for all stations of 0.5 ± 0.1 µM/hr (Fig. 3b, Table 2).

As for NPP, N uptake did not show an inshore-offshore pattern, and there was no clear correlation with N-nutrient concentration (Fig S.5). NH₄⁺ was the favoured N substrate, followed by NO₃⁻ and then urea. ρNH₄⁺ ranged from below detection to 0.2 µM/hr (Fig. 3c, pink bars; Table 2), with the highest detectable rates measured at stations 3A (0.2 ± 0.0 µM/hr), 4A (0.1 ± 0.0 µM/hr), and 6C (0.2 ± 0.0 µM/hr), and the lowest at transect 1 (0.5 ± 0.0 µM/hr) where the concentrations of all N species were low. The NO₃⁻ uptake rates ranged from below detection to 0.1 µM/hr (Fig. 3c, blue bars) and were higher on the east side of the bay, with the highest ρNO₃⁻ at stations 4C (0.1 ± 0.03 µM/hr) and 6C (0.03 ± 0.0 µM/hr) where the ambient NO₃⁻ and PON concentrations reached 21 µM and 6.3 µM, respectively (Table 1b). ρurea ranged from below detection to 0.1 µM/hr (Fig. 3c, yellow bars), with the highest rate

measured at site 5C (Strand; 0.1 ± 0.0 µM/hr) where the ambient urea concentration reached a maximum (1.8 ± 0.8 µM).

Rates of NO₂⁻ oxidation could be measured for transects 4, 5, and 6 only, with the rates at or near the methodological detection limit at the other stations (Table 2). The highest NO₂⁻ oxidation rate occurred at 4 m at station 4A (1.2 µM/hr), followed by 9 m at station 5C (0.9 µM/hr) and the surface at station 5A (0.6 µM/hr). At the stations with measurable NO₂⁻ oxidation rates, this flux accounted for >100% of the NO₂⁻ assimilated by phytoplankton.

### 4.2.4. Phytoplankton biomass and community composition

Chlorophyll *a* concentrations were generally low at the rocky shore sites (1.3 ± 0.7 µg/L) and surface stations (2.0 ± 1.5 µg/L) and increased with depth, with maximum values in the mid-depths (4–10 m; average of 3.9 ± 1.2 µg/L; Table 1b). The highest concentration was measured at station 4C (Monwabisi), 21.8 µg/L at 8 m, and the lowest concentration at station 1B, 0.3 µg/L at 8 m.

The POC concentrations followed a similar pattern, reaching a maximum in the subsurface (4–6 m), with the highest concentrations at 6 m at station 5B (Strand, 86.3 µM), followed by 4 m at 4B (67.6 µM), 6C (Bikini Beach, 54.7 µM), and 8B (Rooi-Els, 50.3 µM). The rocky shore sites were characterized by similar POC concentrations to each other (30.8 ± 14.2 µM), except site 4 where POC was considerably higher (62.7 ± 4.8 µM).

Phytoplankton abundance was highest at transects 1 and 8 (up to 435 and 603 cells/mL, respectively) and lowest at transects 3 and 5 (89 and 40 cells/mL) (Fig. 4). Dinoflagellates were the main phytoplankton group at most of the boat stations, accounting for 70.4 ± 35.6% of the community, followed by diatoms (29.2 ± 35.8%) and a small contribution of silicoflagellates (0.4 ± 1.3%), mostly at station 2C (Simons Town) (Table S.3, Fig S.6). The dinoflagellate community was predominantly composed of *Tripos fusus*, which accounted for 52.5 ± 9.9% of the total cells at the boat stations, reaching 89.3 cells/mL (92% of cells) and 100.5 cells/mL (93% of cells) at stations 1C and 8B. By contrast, diatoms were the dominant group at nearly all the rocky shore sites (average of 89.6 ± 16.2% of the phytoplankton community), with 100% presence at sites 1, 3, 5, and 6. *Grammatophora spp.* and *Melosira spp.* dominated at sites 3 and 6, whereas *Navicula spp.* was most abundant at sites 1 and 2.

## 4.3. Mussels

### 4.3.1. Condition index and biodiversity

Mussel CI was significantly higher at sites on the east versus the west side of the bay (p < 0.01; Fig. 5a). A west-east pattern was also evident in the number of species associated with the mussel beds, with sites on the west side of the bay characterized by a higher species richness (Fig. 5b). Sites 1 (Millers Point) and 2 (Simons Town) had the highest biodiversity, with 48 and 53 unique species, while sites 4 (Monwabisi) and 7 (Kogel Bay) had the lowest biodiversity, with 24 and 26 unique species, respectively. Among the organisms found in the mussel beds, only four species were present at all sites: the polychaetes, *Glycera tridactyla* and *Pseudonereis variegata*, and the limpets, *Scutellastra granularis* and *Fissurella mutabilis*, which together accounted for 49% and 46% of the total species at sites 1 and 2, 43% at site 4, and ~20% at the other sites (Table S.4). Other abundant species included the polychaetes, *Syllidae* spp. (22% at site 1), the anemone, *Corynactis annulata* (24% at site 2), the bivalve, *Lasaea adansonii* (18% at site 3 (Muizenberg), 23% at site 4, 16% at site 8 (Rooi-Els)), and the amphipod *Apohyale grandicornis* (44% at site 8). The Shannon Diversity Index (H') and Pielou's Evenness Index (J') differed among sites (p < 0.05), with sites 1 and 8 characterized by the lowest H' and J' (average of 1.3 ± 0.1 and 1.8 ± 0.25 for H' and J', respectively) and site 7 by the highest (2.11 ± 0.1 and 3.1 ± 0.1), while the other four sites were characterized by similar intermediate values (average of 1.8 ± 0.1 and 2.6 ± 0.1, respectively).

The most abundant mussel, *M. galloprovincialis*, was generally longer
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Bar plots of a) nitrate (NO₃⁻, blue bar), ammonium (NH₄⁺, pink bar), and urea (yellow bar) concentrations; b) surface rates of net primary production (NPP) along with the particulate organic carbon (POC) concentrations; and rates of c) NO₃⁻ uptake (ρNO₃⁻), NH₄⁺ uptake (ρNH₄⁺), and urea uptake (ρurea) along with the particulate organic nitrogen (PON) concentration at each site and station. Values are expressed as mean ± standard deviation. Rocky shore sites are highlighted in bold on the x-axes. Uptake experiments were not conducted at the mid-shore stations (B) (although nutrient and POC and PON concentrations were measured; Table 1a and b; Fig S.2). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

**Table 2**

<table><caption>Rates of net primary production (NPP), nitrate uptake (ρNO₃⁻), ammonium uptake (ρNH₄⁺), urea uptake (ρurea), and nitrite oxidation (VNO₃⁻) measured at select stations in nearshore False Bay in May 2018. Values are mean ± standard error. Missing values indicate that samples were not collected, while * indicates that the measured rates were below the calculated detection limit and were thus not significantly higher than zero.</caption><thead><tr><th>Site number</th><th>Site name</th><th>Station</th><th>Sample depth</th><th>NPP (µM/hr)</th><th>ρNO<sub>3</sub> (µM/hr)</th><th>ρNH<sub>4</sub><sup>+</sup> (µM/hr)</th><th>ρUrea (µM/hr)</th><th>VNO<sub>2</sub> (µM/hr)</th></tr></thead><tbody><tr><td>1</td><td>Millers Point</td><td>A</td><td>surface</td><td>0.04 ± 0.01</td><td>0.00 ± 0.00</td><td>0.05 ± 0.00</td><td>0.00 ± 0.00</td><td>*</td></tr><tr><td>1</td><td>Millers Point</td><td>A</td><td>4 m</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>1</td><td>Millers Point</td><td>C</td><td>surface</td><td>0.08 ± 0.00</td><td>0.00 ± 0.00</td><td>0.06 ± 0.00</td><td>0.01 ± 0.00</td><td></td></tr><tr><td>2</td><td>Simons Town</td><td>A</td><td>surface</td><td>0.31 ± 0.04</td><td>0.00 ± 0.00</td><td>0.04 ± 0.00</td><td>0.00 ± 0.00</td><td></td></tr><tr><td>2</td><td>Simon's Town</td><td>A</td><td>4 m</td><td></td><td></td><td></td><td></td><td>*</td></tr><tr><td>2</td><td>Simon's Town</td><td>C</td><td>surface</td><td>0.22 ± 0.03</td><td>0.00 ± 0.00</td><td>0.05 ± 0.00</td><td>0.00 ± 0.00</td><td>*</td></tr><tr><td>2</td><td>Simon's Town</td><td>C</td><td>12 m</td><td></td><td></td><td></td><td></td><td>*</td></tr><tr><td>3</td><td>Muizenberg</td><td>A</td><td>surface</td><td>0.75 ± 0.09</td><td>0.01 ± 0.00</td><td>0.17 ± 0.00</td><td>0.01 ± 0.00</td><td></td></tr><tr><td>4</td><td>Monwabisi</td><td>A</td><td>surface</td><td>1.65 ± 0.72</td><td>0.03 ± 0.02</td><td>0.11 ± 0.00</td><td></td><td>*</td></tr><tr><td>4</td><td>Monwabisi</td><td>A</td><td>4 m</td><td></td><td></td><td></td><td></td><td>*</td></tr><tr><td>4</td><td>Monwabisi</td><td>C</td><td>surface</td><td>0.35 ± 0.08</td><td>0.09 ± 0.03</td><td>0.03 ± 0.00</td><td></td><td>*</td></tr><tr><td>5</td><td>Strand</td><td>A</td><td>surface</td><td>0.18 ± 0.01</td><td>0.01 ± 0.00</td><td>0.04 ± 0.00</td><td>0.01 ± 0.00</td><td>0.61 ± 0.02</td></tr><tr><td>5</td><td>Strand</td><td>C</td><td>surface</td><td>0.26 ± 0.05</td><td>0.01 ± 0.00</td><td>0.02 ± 0.00</td><td>0.06 ± 0.00</td><td>0.13 ± 0.03</td></tr><tr><td>5</td><td>Strand</td><td>C</td><td>9 m</td><td></td><td></td><td></td><td></td><td>0.87 ± 0.23</td></tr><tr><td>6</td><td>Bikini Beach</td><td>A</td><td>surface</td><td>0.87 ± 0.18</td><td>0.01 ± 0.00</td><td>0.07 ± 0.00</td><td>0.01 ± 0.00</td><td>0.28 ± 0.26</td></tr><tr><td>6</td><td>Bikini Beach</td><td>C</td><td>surface</td><td>0.73 ± 0.08</td><td>0.03 ± 0.00</td><td>0.16 ± 0.00</td><td>0.01 ± 0.00</td><td>0.22 ± 0.11</td></tr><tr><td>6</td><td>Bikini Beach</td><td>C</td><td>7 m</td><td></td><td></td><td></td><td></td><td>0.65 ± 0.11</td></tr><tr><td>8</td><td>Rooi-Els</td><td>A</td><td>surface</td><td>0.27 ± 0.15</td><td>0.01 ± 0.00</td><td>0.02 ± 0.00</td><td>0.01 ± 0.00</td><td>*</td></tr><tr><td>8</td><td>Rooi-Els</td><td>A</td><td>8 m</td><td></td><td></td><td></td><td></td><td>0.01</td></tr></tbody></table>

on the east side of the bay (p < 0.05; Fig. 5c), while the lengths of the three other mussel species (*Aulacomya ater*, *Choromytilus meridionalis*, *Perna perna*) varied inconsistently among sites. Mussel recruits (<1 cm) were significantly more abundant on the west side of the bay, with a maximum of over 2000 recruits enumerated at site 2 compared to 180 at site 8 (Fig. 5d).

### 4.3.2. Stable isotopes

The δ¹⁵N and δ¹³C of *M. galloprovincialis* averaged 8.3 ± 0.4‰ and -14.5 ± 0.5‰, respectively (Table 1b). The δ¹³Cₘussel did not vary significantly among rocky shore sites, in contrast to δ¹⁵Nₘussel, which was significantly higher at sites 3 (Muizenberg, 9.1 ± 0.2‰) and 6 (Bikini Beach, 8.7 ± 0.1‰) compared to the other sites (average of 8.1 ± 0.1‰) (p < 0.05).

### 4.3.3. Fatty acids

Mussel FA composition varied significantly among rocky shore sites (PERMANOVA: MS = 102.46, Pseudo-F = 2.55, p < 0.01), with the outcome of the PCA and PERMANOVA identifying two separate groups corresponding to the western (sites 1, 2, 3) and eastern sides (sites 4, 6, 7, 8) of the bay. SIMPER analysis indicates that the eastern specimens were characterised by diatom (16:0, 16:1n-7, 20:5n-3) and dinoflagellate (18:4n-3, 22:6n-3) trophic markers, which together accounted for

48.2 ± 3.6% of the total FA, while BAME, 20:2NMI, 20:4n-6, 22:4n-6, and 22:5n-3 characterized the western sites (40.6 ± 2.3% of total FA) (Table 3, Fig S.7).

### 4.3.4. Benthic invertebrate larvae distribution

Most of the benthic invertebrate larvae collected were *M. galloprovincialis*, followed by barnacle nauplii and D-larvae (the earliest larval phase) from recently fertilised eggs (Fig. 6; Table S.5). The average invertebrate benthic larvae abundance was highest on the east side of the bay, with station 6C (Bikini Beach) characterized by the highest mean values of 10.7 ± 9.3 individual/L. Of these larvae, the majority were *M. galloprovincialis*, which together accounted for 92% of the counts. An onshore-offshore pattern of increasing larvae abundances with distance offshore was evident (p < 0.001), with extremely low numbers of larvae at the rocky shore sites (typically below detection) compared to the offshore stations (average of 0.8 ± 2.5 individual/L).

## 4.4. Potential pollutants

### 4.4.1. Metal concentrations

The concentrations of metals in the mussel tissue were highest at site 6 (Bikini Beach) and lowest at site 8 (Rooi-Els; Table S.6a, Fig S.8). Similarly, the sedimentary metal concentrations were highest at the
<figure><img src="image_6.png" /><figcaption>Fig. 4. Cell counts of the various phytoplankton species identified via light microscopy in False Bay in May 2018. Rocky shore (RS) sites are highlighted in bold on the x-axes. The right-hand y-axis refers to the RS data, while the left-hand y-axis refers to the boat transects (stations A, B, C). Samples were not collected at Monwabisi (transect 4) or Kogel Bay (site 7).</figcaption></figure>

rocky shore and inshore station at site 6 (Table S.6b and c). Sediment samples collected from the inshore stations generally had a similar metal content to the rocky shore sediments, except at site 6 where the rocky shore concentrations were more than double the inshore sediments, with particularly high concentrations of aluminium (Al), barium (Ba), iron (Fe), and lead (Pb). The CF and PLI indexes were below the threshold limit for contamination, except for copper (Cu) at site 6 where the PLI was 2.2 (Table S.6d).

Mussels had significantly higher (p < 0.05) concentrations of arsenic (As), boron (B), cadmium (Cd), Cu, mercury (Hg), selenium (Se), mobility density (Mo), tin (Sn), and zinc (Zn) than the sediments, which had higher concentrations of Al, Ba, Fe, manganese (Mn), and strontium (Sr) (Fig S.8). The concentrations of Cu, Cd, Pb, Sn in mussels from site 6 exceeded the permissible legal limits for shellfish, as did Cd at sites 1 (Millers Point), 7 (Kogel Bay), and 8 (Rooi-Els). Regardless of site, the BSAF factor was highest for antimony (Sb; 105), followed by Hg (38.3), Mo (22.1), and Pb (13.3) (Table S.6a).

### 4.4.2. Aerosols

Three 24-hr size-segregated aerosol samples were collected during the study, on the 14th, 15th, and 16th of May. No rain was recorded during this period, and the atmospheric temperature averaged $16.0 \pm 2.9$ °C. The $^{222}$Rn concentrations were always above the threshold of 500 mBq/m$^3$ for pure marine air and rose over the three days (Fig. 7, right axis), indicative of an increasing continental influence. The air mass back trajectories were consistent with this interpretation and with the observed increase in total aerosol concentration in both the fine and coarse modes over the three days (Fig. 7, left axis). Aerosol $NO_3^-$ concentrations ranged from 6.2 to 44.1 nmol/m$^3$ and $NO_3^-$ was predominantly present in the coarse mode whereas $NH_4^+$ ranged from 0.2 to 11.2 nmol/m$^3$ and was mainly in the fine mode. The aerosol $NO_3^-$ $\delta^{15}$N ranged from 3.1 to 7.0‰ and $\delta^{18}$O ranged from 69 to 74‰ (Table S.7). Averaged over the three sampling days, $NO_3^-$ and $NH_4^+$ dry deposition to False Bay was $67.4 \pm 9.4$ µmol/m$^2$/day and $4.7 \pm 4.2$ µmol/m$^2$/day, respectively.

## 5. Discussion

This multidisciplinary study was designed to evaluate the potential role of benthic filter feeders in mitigating anthropogenic inputs to the coastal waters of a rapidly urbanising area, focusing on False Bay, a socio-economic hotspot in South Africa. Most of the parameters investigated here followed west-east and/or onshore-offshore patterns (Fig. 8), and we detected evidence of nutrient and metal pollution at Strand (site/transect 5) and Bikini Beach (site/transect 6), and atmospheric N deposition in the vicinity of Muizenberg (site/transect 3), in all cases proximate to densely populated stretches of coastline. Below, we discuss potential explanations for the patterns we observed, and consider the socio-economic implications for coastal environments.

### 5.1. Pollution inputs

#### 5.1.1. N-nutrient loading

The concentrations of nutrients, chlorophyll *a*, and metals were low at most locations across nearshore False Bay, except at transects 5 and 6 (Strand and Bikini Beach) where we recorded elevated values, particularly at the stations nearest the coast. Nutrients derived from urban and agricultural wastewater are a major source of pollution to coastal areas (Paerl, 1997; McClelland and Valiela, 1998; Castro et al., 2007). An excess of these nutrients can enhance primary productivity, especially in shallow environments where light does not limit phytoplankton growth (Howarth, 1988; Cloern et al., 2014), such as nearshore False Bay. A high nutrient load can lead to eutrophication, evidenced by organic matter accumulation and excessive oxygen consumption (leading in extreme cases to hypoxia and/or anoxia) (Richardson and Jørgensen, 1996; Paerl, 2006; Gorman et al., 2009). While the oxygen concentrations in False Bay never reached hypoxic levels (defined as $\le 60$ µM, Vaquer-Sunyer and Duarte, 2008), we did measure the lowest oxygen at transect 5 (Fig. 2) along with elevated N-nutrients (particularly $NO_3^-$ and $NH_4^+$) and fairly high POC concentrations (Fig. 2c, Fig. 3a and b; Fig S.1e3 and Fig S.2). These observations suggest enhanced phytoplankton activity and thus biomass accumulation in response to nutrient inputs, and the start of eutrophication due to bacterial decomposition of organic
<figure><img src="image_7.png" /><figcaption>**Fig. 5.** Mussel data for samples collected at seven rocky shore sites in False Bay in May 2018. a) Mussel condition index (n = 25 per site); b) number of unique species found at each site (open bar) and average number of species (filled bar) associated with the mussel beds; c) mussel length; and d) number of mussels present in the quadrats used to sample for the data shown in panels b and c. Information presented in panels b, c, and d was acquired by destructive sampling (6 replicate quadrats per site). Data are expressed as mean ± standard deviation. The letters in panels a and b indicate significant differences among sites. Mussels were not present at site 5 (Strand).</figcaption></figure>

matter.

Eutrophication can have a negative impact on the coastal benthos, causing shifts in community composition (Blumenshine et al., 1997), mass mortality linked to oxygen starvation (Rosenberg and Loo, 1988), a decline in species richness and diversity (Burkholder et al., 2007), and an increase in the abundance and biomass of fast growing algae (Mangialajo et al., 2008). The diversity associated with the mussel beds was generally low on the east side of False Bay, and mussels were entirely absent at site 5 (Strand) (Fig. 5), consistent with an environmental response to an anthropogenic perturbation. Such anthropogenic effects can be exacerbated in semi-enclosed areas such as bays where water circulation and ventilation is limited compared to the open ocean (Le Pape et al., 1996; Wang et al., 1999; Kemp et al., 2005). The semi-permanent anticyclonic eddy near Gordon's Bay, which retains water and dampens mixing to the north-east (Atkins, 1970; Taljaard et al., 2000), likely drove the accumulation of nutrients and other (in)organic compounds at transects 5 and 6 (Bikini Beach) (Pfaff et al., 2019).

The high N-nutrient concentrations measured proximate to Gordon's Bay could have been discharged by the Gordon's Bay waste water treatment works, the Sir Lowry's Pass and/or Lourens Rivers, and/or urban storm water runoff (Taljaard et al., 2000a, 2000b; Giljam, 2002; Pfaff et al., 2019). We assign an allochthonous provenance to these nutrients rather than an autochthonous mechanism of supply such as upwelling because the NO₃⁻ and NH₄⁺ concentrations were highest inshore (at stations 5A and 6A), decreasing offshore. While a similar trend in NO₃⁻ could result from upwelling, the coincident Si(OH)₄ and PO₄³⁻ concentrations were near-constant across all the transect 5 and 6

stations, inconsistent with upwelling, which would supply NO₃⁻, Si(OH)₄, and PO₄³⁻ in a near-constant molar ratio. The idea that nutrient loading occurred near Gordon's Bay is also supported by the low salinity measured at transect 5, which implicates freshwater discharge from a river or outflow. Furthermore, NO₃⁻ concentrations were higher at the surface than at depth at offshore stations 5C and 6C, which can be explained by the mixing of a low-salinity, high-NO₃⁻ terrestrial input with saltier offshore waters.

The δ¹⁵N data further evince N-nutrient loading near Gordon's Bay. The δ¹⁵NNO₃ and δ¹⁵Nmussel were highest at transects 5 and 6, with δ¹⁵NNO₃ rapidly decreasing offshore (Table 1). High values of δ¹⁵NNO₃ can indicate the input of an external N source, such as domestic and/or industrial wastewater (Flipse and Bonner, 1985; McClelland et al., 1997), as might be expected from the outflows at Gordon's Bay. Alternatively, δ¹⁵NNO₃ can increase due to isotopic fractionation associated with NO₃⁻ assimilation by phytoplankton, which raises the δ¹⁵N of the NO₃⁻ pool as its concentration declines (Mariotti et al., 1981). However, δ¹⁵NNO₃ at transect 5 increased shoreward along with an increase in the NO₃⁻ concentration. Additionally, the δ¹⁵NNO₃ at each station was elevated throughout the water column (7.5–8.2‰) relative to the source waters to False Bay (Subantarctic Mode Water (SAMW) and Subtropical Thermocline Water (STW); δ¹⁵NNO₃ < 7‰ (see transect 8; Fig S.3; Flynn et al., 2020)) rather than in the euphotic zone only as would be expected for NO₃⁻ assimilation.

NO₃⁻ is not the only possible source of anthropogenic N to False Bay, with high concentrations of NH₄⁺ commonly present in land-derived inputs to coastal waters. While we have no measurements of NH₄⁺
<caption>**Table 3**</caption>

Total fatty acid composition of the mussel *Mytilus galloprovincialis* collected at seven intertidal sites in False Bay in May 2018. The values are percentages expressed as mean ± standard error (n = 3 per site, except for site 1 where only 1 sample was measured). PUFA = Polyunsaturated Fatty Acids, MUFA = Monounsaturated Fatty Acids, SFA = Saturated Fatty Acids, EFA = Essential Fatty Acids (20:4n-6, 20:5n-3, 22:6n-3), BAME = Bacterial Fatty Acids, and NMI = Non Methylated Fatty Acids. Mussels were not present at site 5 (Strand).

<table><thead><tr><th>Site number</th><th>1- Millers Point</th><th>2- Simons Town</th><th>3- Muizenberg</th><th>4- Monwabisi</th><th>6- Bikini Beach</th><th>7- Kogel Bay</th><th>8- Rooi-Els</th></tr></thead><tbody><tr><td>14:0</td><td>0.69</td><td>0.44 ± 0.63</td><td>0.76 ± 0.19</td><td>1.08 ± 0.34</td><td>0.70 ± 0.28</td><td>0.51 ± 0.16</td><td>0.79 ± 0.06</td></tr><tr><td>16:0</td><td>15.50</td><td>14.50 ± 2.38</td><td>14.90 ± 1.19</td><td>16.87 ± 0.50</td><td>16.39 ± 1.40</td><td>15.19 ± 0.03</td><td>18.53 ± 0.05</td></tr><tr><td>18:0</td><td>5.98</td><td>6.50 ± 1.37</td><td>6.65 ± 0.10</td><td>6.23 ± 0.72</td><td>5.86 ± 0.69</td><td>4.38 ± 0.40</td><td>5.06 ± 0.07</td></tr><tr><td>20:0</td><td>0.84</td><td>0.98 ± 0.04</td><td>0.88 ± 0.05</td><td>0.56 ± 0.52</td><td>0.83 ± 0.06</td><td>0.90 ± 0.41</td><td>0.63 ± 0.06</td></tr><tr><td>16:1n-7</td><td>1.18</td><td>0.90 ± 1.28</td><td>1.15 ± 0.34</td><td>1.66 ± 0.39</td><td>1.03 ± 0.65</td><td>0.66 ± 0.11</td><td>1.28 ± 0.28</td></tr><tr><td>18:1n-7</td><td>1.40</td><td>1.39 ± 0.42</td><td>1.46 ± 0.07</td><td>1.45 ± 0.18</td><td>1.16 ± 0.24</td><td>1.28 ± 0.56</td><td>1.39 ± 0.23</td></tr><tr><td>18:1n-9</td><td>1.53</td><td>0.48 ± 0.68</td><td>0.57 ± 0.15</td><td>0.86 ± 0.11</td><td>0.84 ± 0.38</td><td>1.44 ± 1.32</td><td>1.47 ± 0.17</td></tr><tr><td>20:1n-7</td><td>0.94</td><td>1.16 ± 0.23</td><td>1.06 ± 0.10</td><td>0.97 ± 0.38</td><td>0.96 ± 0.11</td><td>0.73 ± 0.08</td><td>0.79 ± 0.16</td></tr><tr><td>20:1n-9</td><td>4.10</td><td>3.28 ± 0.35</td><td>3.22 ± 0.35</td><td>3.53 ± 0.45</td><td>3.40 ± 0.09</td><td>3.96 ± 1.13</td><td>4.17 ± 0.18</td></tr><tr><td>20:1n-11</td><td>1.00</td><td>1.34 ± 0.11</td><td>1.22 ± 0.08</td><td>1.32 ± 0.44</td><td>1.22 ± 0.08</td><td>0.82 ± 0.37</td><td>0.73 ± 0.12</td></tr><tr><td>16:3n-4</td><td>0.58</td><td>0.25 ± 0.36</td><td>0.41 ± 0.40</td><td>0.46 ± 0.44</td><td>0.88 ± 0.25</td><td>0.76 ± 0.36</td><td>0.81 ± 0.06</td></tr><tr><td>18:2n-6</td><td>0.96</td><td>1.02 ± 0.05</td><td>0.96 ± 0.09</td><td>0.94 ± 0.12</td><td>0.77 ± 0.15</td><td>0.97 ± 0.40</td><td>0.67 ± 0.05</td></tr><tr><td>18:4n-3</td><td>0.70</td><td>0.50 ± 0.70</td><td>0.39 ± 0.37</td><td>0.79 ± 0.14</td><td>0.99 ± 0.64</td><td>0.80 ± 0.00</td><td>1.20 ± 0.14</td></tr><tr><td>20:2NMI</td><td>11.79</td><td>11.96 ± 2.48</td><td>11.37 ± 1.49</td><td>9.60 ± 1.82</td><td>8.93 ± 0.90</td><td>9.58 ± 0.44</td><td>7.66 ± 0.57</td></tr><tr><td>20:4n-6</td><td>6.11</td><td>3.77 ± 0.40</td><td>4.78 ± 0.45</td><td>2.91 ± 0.51</td><td>3.22 ± 0.22</td><td>4.66 ± 2.80</td><td>3.28 ± 0.06</td></tr><tr><td>20:5n-3</td><td>7.92</td><td>8.52 ± 2.18</td><td>9.59 ± 1.64</td><td>8.36 ± 1.82</td><td>9.00 ± 0.93</td><td>7.45 ± 0.54</td><td>8.72 ± 0.03</td></tr><tr><td>22:4n-6</td><td>1.13</td><td>0.73 ± 0.32</td><td>0.99 ± 0.12</td><td>0.57 ± 0.12</td><td>0.52 ± 0.02</td><td>0.77 ± 0.40</td><td>0.39 ± 0.00</td></tr><tr><td>22:5n-3</td><td>1.58</td><td>2.75 ± 1.64</td><td>1.94 ± 0.15</td><td>1.66 ± 0.16</td><td>1.43 ± 0.04</td><td>1.37 ± 0.04</td><td>1.17 ± 0.00</td></tr><tr><td>22:6n-3</td><td>15.97</td><td>15.91 ± 0.50</td><td>15.99 ± 2.07</td><td>20.12 ± 2.05</td><td>21.33 ± 2.30</td><td>19.26 ± 4.84</td><td>22.94 ± 0.57</td></tr><tr><td>22:3NMI</td><td>0.80</td><td>0.84 ± 0.10</td><td>0.79 ± 0.08</td><td>0.79 ± 0.17</td><td>1.01 ± 0.23</td><td>0.71 ± 0.36</td><td>0.48 ± 0.10</td></tr><tr><td>BAME</td><td>19.30</td><td>22.77 ± 3.37</td><td>20.92 ± 3.58</td><td>19.28 ± 1.19</td><td>19.54 ± 2.91</td><td>23.80 ± 0.08</td><td>17.84 ± 1.19</td></tr><tr><td>SFA</td><td>42.31</td><td>45.20 ± 1.69</td><td>44.11 ± 2.39</td><td>44.00 ± 0.48</td><td>43.33 ± 1.28</td><td>44.78 ± 0.85</td><td>42.85 ± 0.95</td></tr><tr><td>MUFA</td><td>10.15</td><td>8.55 ± 2.84</td><td>8.68 ± 0.58</td><td>9.80 ± 1.01</td><td>8.60 ± 1.36</td><td>8.89 ± 2.67</td><td>9.83 ± 0.92</td></tr><tr><td>PUFA</td><td>47.54</td><td>46.25 ± 1.15</td><td>47.21 ± 1.83</td><td>46.20 ± 0.79</td><td>48.07 ± 0.30</td><td>46.33 ± 1.82</td><td>47.32 ± 0.03</td></tr><tr><td>EFA</td><td>30.01</td><td>28.20 ± 2.28</td><td>30.36 ± 1.12</td><td>31.39 ± 1.34</td><td>33.54 ± 1.97</td><td>31.37 ± 1.50</td><td>34.95 ± 0.48</td></tr></tbody></table>

<figure><img src="image_8.png" /><figcaption>**Fig. 6.** Abundance and distribution of invertebrate benthic larvae for samples collected from rocky shore sites and inshore-offshore stations in False Bay in May 2018. Offshore larval sampling was not conducted at transect 7 (Kogel Bay).</figcaption></figure>

δ¹⁵N, which might allow for a diagnosis of NH₄⁺ source(s) (Maeda et al., 2016), δ¹⁵NₚON in marine waters is set by the δ¹⁵N of the N sources assimilated by phytoplankton (Altabet, 1988; Wada, 1980; Fawcett et al., 2011) such that we can use this parameter to evaluate the NH₄⁺ dynamics in coastal False Bay. The δ¹⁵NₚON at the inshore stations of transects 5 and 6 averaged 6.4 ± 0.2‰, ~1‰ lower than the surface δ¹⁵NₐNO₃ (7.5 ± 0.3‰; Fig S.3e, f). The isotope effect associated with NO₃⁻ assimilation by phytoplankton averages ~5‰ (Granger et al., 2004; Fripiat et al., 2019) such that the δ¹⁵NₚON recorded here is considerably

higher than expected for PON produced from the consumption of NO₃⁻ alone (i.e., using the Rayleigh model for kinetic isotope fractionation, where δ¹⁵NₚON is expected to equal δ¹⁵NₐNO₃ minus the isotope effect; Sigman et al., 1999; Altabet and Francois, 2001). This mismatch suggests phytoplankton assimilation of another N source, likely urea or NH₄⁺, a notion that is consistent with the observed rates of ρNH₄⁺, which were far higher than the coincident rates of ρNO₃⁻.

In coastal areas, urea is typically rapidly consumed and its δ¹⁵N is generally low (<1‰; Waser et al., 1998). Urea assimilation would thus
<figure><img src="image_9.png" /><figcaption>**Fig. 7.** Three 24-hour size-segregated aerosol samples collected at the Cape Point Global Atmosphere Watch (GAW) station in May 2018, in both the fine (<1 µm, left bar for each date) and coarse modes (>1 µm, right bar for each date). The stacked bar chart indicates the concentration of each major inorganic ion (left axis; nmol m⁻³): ammonium (NH₄⁺, pink), nitrate (NO₃⁻, blue), non-sea-salt sulphate (nss-SO₄²⁻, orange), calcium (Ca²⁺, cyan), magnesium (Mg²⁺, green), potassium (K⁺, yellow). The connected circle symbols indicate the hourly ²²²Rn concentrations that were measured continuously over the sampling period (right axis; Bq m⁻³), while the dotted horizontal line indicates the ²²²Rn threshold above which air masses are considered to have a continental origin (500 Bq m⁻³). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>**Fig. 8.** Summary of the major patterns of variability observed in False Bay in May 2018, which followed a) west-east, b) onshore-offshore, and/or c) surface-depth gradients. Also shown are d) parameters that were significantly different at sites/transects 5 and 6 compared to the other sites/transects. The colour gradient of the triangles indicates the direction of variation (dark colour = highest value, lighter colour = lowest value). The red bold numbers indicate the site or transect at which the maximum value for a specific parameter was observed. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

act to lower the δ¹⁵NₚON in False Bay and as such, would not yield high-δ¹⁵NₚON. Similarly, marine sources of NH₄⁺ are generally low in δ¹⁵N (~-5 to 0‰; Checkley and Miller, 1989; Montoya et al., 2002; Lehmann et al., 2003). Additionally, the isotope effect associated with NH₄⁺ assimilation is ~3-5‰ at an NH₄⁺ concentration of ~5 µM (as observed at the inshore stations of transects 5 and 6) (Liu et al., 2013). The incomplete assimilation of marine NH₄⁺ would thus act to lower the δ¹⁵NₚON, in contrast to our observations. This scenario may be complicated if nitrification occurs coincident with NH₄⁺ assimilation (i.e., coupled nitrification-NH₄⁺ assimilation). In this case, the nitrifying microorganisms preferentially utilise ¹⁴N-NH₄⁺, leaving ¹⁵N-NH₄⁺ to be consumed by phytoplankton, which would in net raise δ¹⁵NₚON (Mariotti et al., 1984; Waser et al., 1998; Sigman and Fripiat, 2019). While the nitrification rates were highest at the inshore stations of transects 5 and 6, they were insignificant compared to ρNH₄⁺ (e.g., VNO₂⁻ of 0.6 µM/h vs.

ρNH₄⁺ of 200 µM/h at station 5A; Table 2). Thus, coupled nitrification-NH₄⁺ assimilation also cannot explain the elevated δ¹⁵NₚON.

A more likely explanation for the high-δ¹⁵NₚON is that the dominant source of the NH₄⁺ to False Bay at the time of our sampling was anthropogenic rather than marine. The δ¹⁵N of sewage NH₄⁺ can range from 10 to 30‰ (Nikolenko et al., 2018), while the δ¹⁵N of manure NH₄⁺ used in agriculture is typically ~10‰ (Maeda et al., 2016; Nikolenko et al., 2018). The δ¹⁵NₚON produced from the assimilation of NH₄⁺ with a δ¹⁵N of 10-20‰ would be ~5-20‰, depending on the degree of its consumption. Assimilation of anthropogenically-derived, high-δ¹⁵NₚON can thus explain the high-δ¹⁵NₚON measured in False Bay.

As expected, the dynamics described above were reflected in the δ¹⁵Nₘussel at site 6, which averaged 8.7 ± 0.1‰, ~2.3‰ higher than their PON food source (McCutchan et al., 2003). This pattern is consistent with previous studies that have reported high-δ¹⁵N primary
consumers living near anthropogenic N sources (Abreu et al., 2006; Lake et al., 2001; Puccinelli et al., 2016b). N-nutrient loading was particularly evident at transects 5 and 6 due to these sites being directly anthropogenically impacted, coupled with the retentive circulation of Gordon's Bay. Nonetheless, a similar relationship between δ¹⁵NNO₃ and δ¹⁵NPON was evident at the other sites, suggesting that their ecosystems were also supported by a mixture of anthropogenic and marine N, consistent with expectations for coastal environments under anthropogenic pressure (Howard et al., 2014).

The influence of anthropogenic N was also apparent in the high δ¹⁵Nmussel measured at site 3 (Muizenberg, 9.1 ± 0.2‰). Here, the δ¹⁵NPON was also elevated (6.6‰) while δ¹⁵NNO₃ was consistent with the source SAMW and STW (6.8‰). Site 3 is situated in an embayment on the west side of False Bay, considered an upwelling shadow where water originating from the east side of the bay can be retained due to a combination of onshore wind stress and shallow water-column stratification (Largier, 2020). The implication is that, given the right meteorological conditions, pollution inputs to the east side of the bay could be transported and retained in the west. An alternative explanation for the high-δ¹⁵NPON and δ¹⁵Nmussel measured at Muizenberg could be outflow of high-δ¹⁵N N from storm water drains, groundwater, or the Zandvlei River. This river experiences eutrophication and poor water quality (van Niekerk et al., 2015, 2013), although its mouth is only intermittently open (generally in winter/spring) (City of Cape Town, 2018) and was closed prior to our sampling. Another source of anthropogenic nutrients to site 3 may be groundwater, as Muizenberg Beach receives a higher groundwater nutrient flux than any other beach along the South African coast because of its proximity to the polluted Cape Flats Aquifer (Engelbrecht, and Tredoux, 1989). High terrestrial nutrient inputs can favour blooms of the diatom *Anaulus australis*, a species that is non-toxic and non-harmful to humans and that proliferates in the surf zone of sandy beaches with elevated wave action (City of Cape Town, 2020). This species dominates the phytoplankton community once present, outcompeting species known to cause harmful algal blooms (Campbell and Bate, 1996). However, *A. australis* was not present during our sampling (Fig. 4), which took place at the end of the Cape Town drought (2015 to mid-2018; Cole et al., 2021) when groundwater inputs to False Bay were likely reduced.

Another possible anthropogenic N source to the bay is atmospheric deposition. The NO₃, NH₄, and non-sea-salt (nss)-sulfate concentrations in the aerosols collected during this study are typical for mixed coastal and anthropogenic aerosols (Brunke et al., 2004) and the ²²²Rn data support this provenance (Chambers et al., 2018). Aerosols generated near the coast are usually primarily sea salt. Sodium chloride ions made up ~80% of the total coarse mode and ~60% of the fine mode aerosol concentrations in our samples, with NO₃ and nss-sulfate as the next-highest-concentration species. In polluted air masses, NO₃ is typically present as fine mode ammonium nitrate, but in coastal aerosols with large amounts of sea salt, chloride displacement causes NO₃ to shift into the coarse mode as polluted air mixes with sea spray aerosols (Spokes et al., 2000). Additionally, the concentrations of all species decrease following dilution with relatively clean marine air, causing fine mode NO₃ and NH₄ aerosols to dissociate back to gaseous ammonia and nitric acid (Allen et al., 1989), with the dissociated nitric acid subsequently forming coarse mode sodium nitrate (Spokes et al., 2000). This aerosol size transition influences coastal ecosystems insofar as coarse mode aerosols have much higher deposition velocities than fine mode aerosols. The rate of NO₃ aerosol dry deposition estimated in our study is consistent with a moderately polluted system (Hastings et al., 2003; Gobel et al., 2013), whereas NH₄ deposition was relatively low and more representative of a marine environment (Altieri et al., 2014). The δ¹⁵N of the aerosol NO₃ (average of 4.8‰) is higher than would be expected for clean marine air (Altieri et al., 2021a) and is instead consistent with anthropogenic N oxide sources, while its δ¹⁸O (average of 71.4‰) indicates a significant contribution of ozone to NO₃ formation, as expected for polluted regions (Altieri et al., 2016).

Our seawater NO₃⁻ isotope data suggest that atmospheric NO₃⁻ deposition may have been significant near Simons Town and Muizenberg. When NO₃⁻ is assimilated by phytoplankton, its δ¹⁵N and δ¹⁸O rise in a ratio of ~1:1 (Granger et al., 2004; 2010). Such a relationship was observed at all sites/transects except 2 and 3, which were characterized by anomalously high δ¹⁸ONO₃ for their δ¹⁵NNO₃ (Fig S.4). This trend is best explained by atmospheric NO₃⁻ deposition – since aerosol NO₃⁻ δ¹⁸O is so high compared to that of seawater (while aerosol NO₃⁻ δ¹⁵N is similar), a fairly modest deposition rate can feasibly influence the surface seawater δ¹⁸ONO₃ (Hastings et al. 2003).

### 5.1.2. Metal pollution

Possible anthropogenic effects were further evident, especially at site 6 (Bikini Beach), in the elevated metal concentrations measured in the mussels and sediments, in some cases exceeding permissible levels for shellfish consumption (e.g., Cd and Pb; DOH, 1994, 2004). The high metal concentrations could have resulted from urban-industrial discharge and/or from boat construction and/or repair in the Gordon's Bay Marina located adjacent to site 6. The latter is likely the case for Ba, Cu, Pb, Sn, and Zn, which are commonly found in antifouling paints (Turner, 2010; Ytreberg et al., 2010), although Sn-based paints are banned in South Africa. Our observations require that Sn-containing paint is flaking off old crafts or that Sn-based paints are still in use.

Metals can also enter the coastal environment via aerosol deposition and rainfall (Gao et al., 2003; Mikulic et al., 2004), upwelling events (Johnson et al., 1999), or freshwater inputs (Hydes and Liss, 1977; Stallard and Edmond, 1983). The fact that the highest metal concentrations in both the mussels and sediment occurred at site 6 near the Gordon's Bay Marina and Lourens River outflow implicates a land-based – and thus, anthropogenic – source. The combination of a metal pollution point-source and the anticyclonic circulation of Gordon's Bay may facilitate metal bioaccumulation in the mussels, as well as in the sediments.

Higher than average concentrations of Cd were observed in mussels at sites 1 (Millers Point), 7 (Kogel Bay), and 8 (Rooi-Els), in addition to at site 6. Cd occurs naturally in rocks and soil and is also found in phosphate fertilizers, which are commonly used in the catchment areas near the northern False Bay coast (Thornton, 1992; Mdzeke, 2004; Chiarelli et al., 2019). Cd can also enter aquatic environments via storm water canals during times of drought (Meerkotter, 2012) as its concentration increases in soils, crops, and aquifers in the absence of the diluting effect of rain. Our sampling occurred at the end of the Cape Town drought, which lasted from 2015 to mid-2018 (Cole et al., 2021). Additionally, several storm water outflows are present around False Bay (Taljaard et al., 2000a, 2000b), providing a conduit between land and the coastal environment. This mechanism of supply could explain the high concentrations of Cd found in mussels at sites 1, 7, and 8, which are far from direct anthropogenic inputs. Alternately, the high Cd concentrations at sites 7 and 8 could be due to upwelling events, which occur on the east side of False Bay (Largier, 2020). However, given the low Cd concentrations in oceanic waters (e.g., <400 pM in SAMW, the ultimate source water to the bay; Cloete et al., 2021), it is unlikely that the natural supply of Cd alone can explain the elevated Cd levels measured in the mussels and sediments.

The high metal concentrations in the mussels, in most cases several orders of magnitude higher than in the sediment, indicate that *M. galloprovincialis* can remove these contaminants from the marine environment, thus mitigating anthropogenic inputs. However, metal bioaccumulation, even at low levels, can cause negative effects on mussels, including inhibiting growth (Calabrese et al., 1984) and adversely affecting reproduction (Beiras and Albentosa, 2004; Fitzpatrick et al., 2008) and lipid metabolism (Vlahogianni and Valavanidis, 2007). Moreover, metal bioaccumulation has implications for the ecosystem services that mussels provide, such as being a major food source for humans (Stankovic et al., 2012).
### 5.1.3. Mussel bed biodiversity

One of our main hypotheses was that we would detect low species diversity associated with mussel beds at sites proximate to anthropogenic inputs, such as site 6 (Bikini Beach). However, this was not the case. Shannon Diversity and Pielou's Evenness Indexes were the lowest at sites 1 (Millers Point) and 8 (Rooi-Els), and highest at site 7 (Kogel Bay), indicating no direct link between diversity and the anthropogenic contaminants identified in our study. In fact, site 1 is located near the Table Mountain National Park marine protected area and site 8 is situated near the mouth of False Bay where open ocean waters frequently intrude (Dufois and Rouault, 2012); both sites are thus distant from the identified hotspots of anthropogenic inputs (sites 5 (Strand) and 6). Studies have shown that high species richness is often associated with pristine marine areas dominated by mussels as these bioengineers provide habitats for numerous other species (López Gappa et al., 1990; Vallarino et al., 2002). In our study, species richness varied considerably, with the highest number of species associated with the mussel beds at sites 1 and 2 (Simons Town), and the lowest at sites 4 (Monwabisi) and 7. Our results suggest that species richness associated with the mussel beds in False Bay is not directly influenced by the pollution sources investigated here.

There are other factors than can influence the communities associated with mussel beds, however. For instance, the low species richness at sites 4 and 7 could be due to the physical characteristics of the sites. The rocky shore of site 4 is exposed to high wave action and is surrounded by sandy beaches that extend for 10–15 km in both directions. In contrast, the other sites are characterised by extended rocky shores, some of which are associated with large kelp forests. The pressure of wave action can inhibit the success of marine species, including *M. galloprovincialis* (Bustamante and Branch, 1996; Blanchette, 1997; Zardi et al., 2008), whereas rocky shores adjacent to kelp forests have been shown to support high species diversity (Blamey and Branch, 2009; Teagle et al., 2017). This is because kelp acts as a nursery area and offers habitat and food for many adult marine species (Graham, et al., 2008; Smale et al., 2013; von Biela et al., 2016) while also acting as a natural barrier, protecting coastal sites from wave action and erosion (Elwany et al., 1995; Løvås and Tørum, 2001; Morris et al., 2020). The absence of kelp may explain the low species richness at site 4; however, the same explanation does not apply to site 7, which is surrounded by kelp. The interactions of bottom-up and top-down processes (e.g., predation, competition, food availability) can also influence the species associated with mussel beds, making it difficult to disentangle the influence of individual factors (Menge, 2000). We also note that our data were collected during one month only, and while mussels integrate chemical signals over a few months (i.e., SI and FA; Hill and McQuaid, 2009; Pirini et al., 2007), the biodiversity associated with mussel beds may change more rapidly due to, for example, the reproductive- or life cycles of the mussel-bed species (Lathlean and McQuaid, 2017). The spatial differences that we observed are nonetheless robust We conclude that mussel-bed biodiversity is either not directly influenced by anthropogenic pressures in False Bay, or that other factors such as water circulation and/or kelp mitigate these anthropogenic inputs, weakening their effect (s) on mussel-bed biodiversity.

### 5.2. West-east patterns

We observed a clear west-east trend, with several biological components decreasing/increasing from west to east, separating transects 1, 2, 3, and 4 in the west from 5, 6, 7, and 8 in the east. This zonal trend was evident in the number of species associated with the mussel beds, the number of recruits, pH, $\Omega_{Ca}$, and $\Omega_{Ar}$, all of which decreased from west to east. Additionally, the eastern side of the bay hosted mussels that were longer and characterized by diatom and dinoflagellate FA trophic markers, a higher $\delta^{13}\text{C}$, and a higher condition index than those on the western side, as well as a higher abundance of benthic invertebrate larvae.

The observations from the east may be linked to topography-wind driven upwelling events (Largier, 2020), which are generally associated with the south-easterly winds that are typical of summer (November-March) (Dufois and Rouault, 2012). Despite our sampling taking place in autumn, the low temperatures recorded at transect 8 (Rooi-Els, minimum of 13.5 °C) and the high $\text{NO}_3$, $\text{Si(OH)}_4$, and chlorophyll a concentrations observed at depth at station 8B, as well as the low pH measured on the eastern side of the bay, may indicate the early stage of an upwelling event.

Upwelling supplies high concentrations of nutrients that typically promote a phytoplankton bloom, initially dominated by diatoms that are succeeded by dinoflagellates when nutrients become depleted (Brink, 1983; Hutchins and Bruland, 1998; Tilstone et al., 2000; Allan et al., 2010). These two phytoplankton taxa are the main producers of polysaturated FA (PUFA) in marine systems, which are critical compounds for the correct functioning of primary consumers and higher trophic levels (Dalsgaard et al., 2003; Parrish et al., 2000), with high levels of PUFA indicating good food quality (Brett and Müller-Navarra, 1997; Ruess and Müller-Navarra, 2019). As such, upwelling events play an important role in providing high-quality food for consumers. Our hypothesis of a role for upwelling in controlling the biological and biogeochemical trends observed in eastern False Bay is supported by the mussel FA results, with specimens collected from the east characterised by diatom and dinoflagellate FA trophic markers, as opposed to those from the west that were characterized by BAME, 20:2NMI, 20:4n-6, 22:4n-6, and 22:5n-3, which together do not indicate the dominance of a specific phytoplankton group. Similarly, mussel condition index and length were higher to the east, indicating a favourable growth environment. Indeed, larger mussels are common in upwelling systems due to the enhanced food supply that supports faster growth rates (Figueiras et al., 2002; Xavier et al., 2007; Smith et al., 2009). A role for upwelling to the east is also supported by the high abundance of phytoplankton at stations 6C (Bikini Beach) and 8B. Combined, analyses indicative of short temporal variability (days) such as nutrient concentrations and phytoplankton abundance, as well as parameters that integrate upwelling signals over longer period (weeks to months) such as FA and condition index, indicate that mussels living on the east side of False Bay were in good condition as a result of high-quality food. That said, the high metal content of some of these east-side mussels (e.g., at site 6) may ultimately be detrimental to higher consumers even though the identified pollutants appear to have had no overt effects on the health of the mussels.

Upwelling on the east side of the bay was not reflected in the $\delta^{13}\text{C}_{\text{mussel}}$, however, which was instead typical of non-upwelling conditions (-14.5 ± 0.5‰). The $\delta^{13}\text{C}$ of consumers is set by the $\delta^{13}\text{C}$ of their food source (plus a trophic enrichment factor of ~1‰; McCutchan et al., 2003), which, in the case of mussels, is the suspended material in the water. In coastal areas, the main food source to mussels includes a mix of phytoplankton, macroalgae, and organic and inorganic debris (Bustamante and Branch, 1996; Vizzini et al., 2002) with a combined $\delta^{13}\text{C}$ of approximately -15‰ (Hill et al., 2006). By contrast, the $\delta^{13}\text{C}_{\text{mussel}}$ in upwelling regions reflects a combination of nearshore and pelagic food sources (Puccinelli et al., 2016c, 2019), and is typically 3-4‰ lower than for mussels not influenced by upwelling. Since the abductor muscle in mussels integrates the $\delta^{13}\text{C}$ of their food source over approximately nine months (Hill and McQuaid, 2009), which in our case means from before the upwelling season, this tracer may not robustly capture stochastic upwelling events, in contrast to FA that provide information on shorter time scales (approximately one month; Dalsgaard et al., 2003; Pirini et al., 2007).

Although mussel condition index was higher on the east side of the bay, the pattern reversed for the number of species associated with mussel beds, with increased adult and recruit abundance observed in the west. Macrofaunal abundance has been shown to be negatively correlated with mussel size in a bed of *M. galloprovincialis*, indicating that smaller mussels facilitate higher associated species richness by
providing space and food (McQuaid and Lindsay, 2007; Cole and McQuaid, 2010). This dynamic could explain the higher species richness observed on the west side of False Bay. A similar trend was observed for the recruitment of propagules on the rocky shore, a process tightly related to adult mussel abundance, with the highest number of recruits observed at sites 2 (Simons Town) and 3 (Muizenberg). Successful recruitment of benthic propagules depends mainly on two processes: larval supply and post settlement survival. High larval supply is linked to high larval production and/or retention (Porri et al., 2008), yet larval abundance was very low on the west side of the bay and high to the east. The contrasting pattern observed between recruits and larvae could be due to small-scale circulation features such as eddies or onshore transport, resulting in propagules originating in the east being delivered to the west, into what is considered a strong retention zone near sites 2 and 3 (Largier, 2020). Post-settlement processes such as low mortality (Pineda et al., 2010) due to limited competition or elevated habitat availability (von der Meden et al., 2012) could also have enhanced recruitment in the west.

The west-east patterns in pH, ΩCa, and ΩAr are consistent with a role for upwelling to the east insofar as the deep cold waters coming to the surface will contain elevated DIC concentrations, resulting in a lower pH, and thus ΩCa and ΩAr, than under non-upwelling conditions (Feely et al., 2010). Mussel shell production is tightly linked to ΩCa and ΩAr since calcite and aragonite are the main constituents of the outer and inner shell, respectively (Fitzer et al., 2015). Several studies have shown that a decrease in CO₂ (and thus ΩCa and ΩAr) can limit the ability of mussels to produce shells (Doney et al., 2009; Waldbusser et al., 2015) and reduce mussel performance (i.e., growth, survival, recruitment; Talmage and Gobler, 2009; Barton et al., 2012). Since aragonite is more soluble than calcite, ΩAr will be lower than ΩCa for a given set of conditions, making it a more sensitive indicator of ocean acidification. While neither ΩAr nor ΩCa were <1 at any site (i.e., indicative of undersaturation; Riebesell, et al., 2010)), the values of ΩAr estimated for the east side of False Bay (1.1–1.9) were below current mean oceanic values (2–2.5; Riebesell, et al., 2010). These results indicate that a continued decline in pH could rapidly become detrimental to mussels in False Bay, and highlight the need for monitoring of carbonate system parameters to assess acidification effects on the filter feeder populations, as well as on the ecosystem services they provide.

### 5.3. Onshore-offshore gradient

A third observed pattern of variation was an onshore-offshore decrease in δ¹³C~POC~ and increase in larval abundance. δ¹³C~POC~ decreased from -11.8 ± 0.4‰ at the rocky shore sites to -18.3 ± 0.9‰ at the most offshore stations. Such a decline in δ¹³C~POC~ with distance from the coast is commonly observed in marine systems due to a shift from a POC pool comprised of a mix of phytoplankton and macroalgae detritus (~-15‰, Bustamante and Branch, 1996; Vizzini et al., 2002; Hill et al., 2006) to a pelagic POC pool dominated by oceanic phytoplankton (~-20‰, Fry and Sherr, 1989; Hill et al., 2006). The average δ¹³C~POC~ recorded at the rocky shore sites (-11.7 ± 2.8‰) was higher than in the coastal waters, suggesting a large contribution of macroalgae detritus.

The onshore-offshore increase in larval abundance can be linked to two processes: propagule supply and circulation. Benthic invertebrate larvae are usually abundant inshore during their early life stage (i.e., eggs just fertilised) or when they are ready to settle on the rocky shore as competent larvae (Porri et al., 2006; Pineda et al., 2010). In our study, the larvae of *M. galloprovincialis* were at an advanced developmental stage, such that we expected their numbers to be highest inshore. Our offshore stations were located within 1.7 km of the coast, however, which can be considered near to the shore if the larvae are competent. The dynamic circulation of the bay could have quickly transported gametes off the coast and promoted larvae fertilisation at our offshore stations (Porri et al., 2008; Weidberg et al., 2015), thus explaining the

observed onshore-offshore trend.

### 5.4. Socio-economic implications

False Bay is an important socio-economical hotspot for South Africa. The bay not only hosts a large residential community, but also supports several small- and medium-scale fisheries (including subsistence fishers) and is a major tourist destination in South Africa, thus contributing to both local communities and the national economy. The tourism value of the bay has been estimated to be approximately US$ 63 million per annum (Pfaff et al., 2019), while the recreational and commercial fisheries of South Africa's west coast (including False Bay) are worth approximately US$ 22 million per annum (Ward et al., 2018). An improved understanding of the potential sources of pollution to False Bay, as well as the processes that may mitigate or exacerbate them, is thus of high importance for the protection and maintenance of the valuable ecosystem services provided by the bay.

Among the recreational areas on the shores of False Bay, the beaches at sites 3 (Muizenberg) and 6 (Bikini Beach) are the most popular and were awarded Blue Flag status in 2019, 2020, and 2021 (The City of Cape Town, 2019, 2020, 2021). This status is awarded on the basis of water quality during the summer months (November-March), which needs to reach a grade of “excellent” in terms of the abundance of *Escherichia coli* and enterococci in the water (i.e., water quality is evaluated using a bacterial index only). However, Bikini Beach is the site where we inferred inputs of anthropogenic N and measured the highest metal concentrations (in some cases exceeding the (inter)national thresholds) in both the mussels and sediments. Our results suggest that additional parameters should be considered when evaluating water quality and Blue Flag status. This recommendation is of particular relevance for fishers (particularly subsistence fishers) who may assume that seafood collected from Blue Flag beaches will be safe for human consumption.

In this study, we highlight several potential sources of pollution to False Bay and find that they are largely attenuated by the broad-scale bay circulation (i.e., dilution), as well as by the presence of mussels that act as a sink for some pollutants. In some regions of the bay, however, the local (i.e., small-scale) circulation may retain and/or concentrate certain pollutants such as inorganic N derived from anthropogenic sources, with implications for algal blooms and seawater oxygen concentrations (Dawood, 1990). A higher resolution temporal dataset is required to evaluate the persistence of these pollutants and the severity of their consequences. In addition, while bivalves have been used as model species for environmental assessments and are considered good bioindicators (Ostapczuk et al., 1997; Chandurvelan et al., 2015), under anthropogenic stress, some metabolic features of mussels may be weakened. This may compromise their role as ecosystem services provider, with knock-on consequences for the associated fauna, ecosystem functioning, and ultimately, services.

Our study extends the current knowledge of nearshore False Bay waters, which have been subjected to habitat degradation and overexploitation over the last few decades (Reimers et al., 2014; Ward et al., 2018; Pfaff et al., 2019). While anthropogenic inputs are certainly influencing this region, our results highlight the role that key species and environments play in mitigating such effects. Similar dynamics may apply to any other coastal systems under anthropogenic stress, under-scoring the need for such knowledge to be considered in management decisions and used by national and international stakeholders to develop appropriate polices and monitoring strategies for marine ecosystem management.

### CRediT authorship contribution statement

**Eleonora Puccinelli:** Conceptualization, Data curation, Methodology, Investigation, Formal analysis, Project administration, Visualization, Writing – original draft. **Francesca Porri:** Conceptualization, Data
curation, Methodology, Investigation, Resources, Writing – original draft. **Katye Altieri:** Data curation, Methodology, Formal analysis, Resources, Visualization, Writing – original draft. **Raquel Flynn:** Data curation, Methodology, Investigation, Formal analysis, Visualization, Writing – original draft. **Hazel Little:** Investigation, Writing – original draft. **Tayla Louw:** Investigation, Data curation, Formal analysis. **Paula Pattrick:** Investigation, Visualization, Writing – original draft. **Conrad Sparks:** Resources, Writing – original draft. **Mutshutshu Tsanwani:** Data curation, Formal analysis, Writing – original draft. **Sonya de Waardt:** Data curation, Formal analysis, Writing – original draft. **David Walker:** Resources, Writing – original draft. **Sarah Fawcett:** Conceptualization, Methodology, Funding acquisition, Resources, Writing – original draft.

## Declaration of Competing Interest

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.

## Acknowledgements

We acknowledge the Marine Biogeochemistry Lab and the Stable Isotope Laboratory at UCT, the Granger Lab at the University of Connecticut, the LIPIDOCEN at the Institut Universitaire Européen de la Mer, the Central Analytical Facility at Stellenbosch University, and the UC Davis Stable Isotope Facility, as well as the South African Department of Science and Innovation's Biogeochemistry Research Infrastructure Platform (BIOGRIP) and the Aquatic Ecophysiology Research Platform at the South African Institute for Aquatic Biodiversity (SAIAB). We are grateful to Mathieu Rouault for his support of this work, and to Pieter Truter and the Research Dive Unit at UCT for their assistance at sea. Finally, we thank the Altieri, Fawcett, Porri, and Walker research groups for their help with sample collection.

## Funding

This work was supported by funding from the South African National Research Foundation (105895, 115335, 116142, 129320), the Claude Leon Foundation, the Swiss Polar Institute through the Antarctic Circumnavigation Expedition (ACE) Project 12, the University of Cape Town (UCT) Research Committee, and a Royal Society/African Academy of Sciences Future Leaders Africa Independent Researcher (FLAIR) fellowship to SF and the ISblue project, Interdisciplinary graduate school for the blue planet (ANR-17-EURE-0015), co-funded by the French government under the program "Investissements d'Avenir" and SAD programme fellowship to EP.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.ecolind.2022.108899.

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