Testing the intermittent upwelling hypothesis: Intercontinental comparisons of barnacle recruitment between South Africa and Australia

Estuarine, Coastal and Shelf Science 224 (2019) 197–208

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Testing the intermittent upwelling hypothesis: Intercontinental comparisons of barnacle recruitment between South Africa and Australia

T

Justin A. Lathleana,∗, Jaqueline A. Trassierraa, Jason D. Everettb, Christopher D. McQuaida a b

Department of Zoology and Entomology, Rhodes University, Grahamstown, 6140, South Africa School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, 2052, Australia

A R T I C LE I N FO

A B S T R A C T

Keywords: Agulhas current Chlorophyll a Coastal productivity East Australian current Propagule supply Western boundary currents

Recent debates have arisen as to whether productivity and subsequent ecological processes increase linearly with increasing intensity of upwelling, or whether productivity responds more favourably to upwelling of intermediate magnitude, as predicted by the intermittent upwelling hypothesis (IUH). Most studies on the topic take place within eastern boundary systems, where the intensity and frequency of upwelling are high. Here, we test the generality of the IUH towards the other end of the upwelling spectrum, within two regions located at similar latitudes along western boundary currents of two continents. We measured barnacle recruitment and colonisation, which we expected to be linked positively to productivity, across eight rocky shores along the east coasts of South Africa and Australia selected to capture a range of upwelling regimes. Based on Bakun Upwelling Indices (BUI), the four South African sites experienced persistent to intermittent levels of upwelling, whilst the four sites along the east coast of Australia were predominantly downwelling sites with occasional upwelling events. Satellite chlorophyll a concentrations ([Chl-a]) also showed a marked difference between the two continents, with 2–3 times higher concentrations in South Africa than Australia. In situ sea temperature measurements revealed slightly different oceanographic patterns, which were nonetheless compatible with both BUI and [Chl-a] measurements. Barnacle recruitment was typically greater within South Africa and but was generally found to vary unimodally with mean BUI (i.e. being greater at sites that experienced moderate upwelling conditions) and to increase linearly with increasing upwelling frequency between January and April when barnacle larvae are known to be most abundant in the water column. Viewed in isolation, our data provide moderate support for the IUH. But when placed in a broader context, with our eight study locations representing just one end of the upwelling continuum, they provide strong evidence for the IUH.

1. Introduction It is widely accepted that large-scale oceanographic processes, such as upwelling, exert strong bottom-up control on coastal communities (Menge, 2000; Nielsen and Navarrete, 2004; Wieters, 2005). However, the intensity, duration and frequency of upwelling may vary significantly within and amongst biogeographic regions and across oceanographic boundaries so that the strength of ecological subsidies and interactions at any one site could be placed on a continuum ranging from strong persistent upwelling, to intermittent upwelling/downwelling, to strong, persistent downwelling (Menge and Menge, 2013). It has previously been shown that the supply of ecological subsidies, such as nutrients and propagules, displays a positive linear relationship with the frequency and intensity of upwelling (Menge et al., 1997a, b). New evidence suggests, however, that regions experiencing

∗

intermittent levels of upwelling, downwelling and relaxation events may be more productive than those that experience consistent upwelling (Menge and Menge, 2013). This ‘Intermittent Upwelling Hypothesis’ (IUH) may change our understanding of how large-scale oceanographic processes are linked to biological diversity and productivity and influence predictions of how entire coastlines are expected to respond to the anticipated future intensification and spatial homogenisation of coastal upwelling under climate change (Wang et al., 2015). The hypothesis makes different predictions depending on the metric used to measure upwelling. Based on the magnitude or intensity of upwelling, the IUH predicts a unimodal increase in rates of ecological dynamics and species interactions, with maximum rates at intermediate values. Based on the intermittency of upwelling (i.e. the frequency of switching between upwelling and downwelling or vice versa) processes are predicted to increase monotonically with intermittency (Menge and

Corresponding author. E-mail address: [email protected] (J.A. Lathlean).

https://doi.org/10.1016/j.ecss.2019.04.040 Received 22 February 2018; Received in revised form 13 April 2019; Accepted 23 April 2019 Available online 26 April 2019 0272-7714/ © 2019 Published by Elsevier Ltd.

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Menge, 2013). A difficulty here is that most research on the role of coastal currents in driving community structure has been carried out in eastern boundary upwelling ecosystems (e.g., Broitman and Kinlan, 2006; Nielsen and Navarrete, 2004; Fenberg et al., 2015). This is not surprising since eastern boundary upwelling systems, like those found off the Californian, Chilean and West African coastlines, sustain productive fisheries and contribute to the majority of global fish catches (Pauly and Christensen, 1995). With few exceptions (e.g., Menge and Menge, 2013; Lathlean et al., 2015), however, western boundary systems that experience intermittent upwelling or persistent downwelling such as those in eastern Australia, eastern Africa and Brasil, have received relatively little attention so that few data exist to test the predictions of the IUH towards the less intense end of the continuum. This indicates the need for a focus on such systems to broaden our understanding of the interplay between coastal currents and benthic community structure. For example, Lathlean et al. (2015) found no evidence of strong bottom-up effects on the abundance of rocky intertidal functional groups along the east coast of Australia. Likewise, Menge et al. (2003) found significantly lower cover of sessile organisms along the shores of southeast New Zealand, where there is little or no upwelling, than on the west coast where there is intermittent upwelling. Such studies appear to support the IUH but, apart from Menge and Menge (2013), this hypothesis has yet to be empirically tested on wide scales across a fuller spectrum of upwelling strength. Here, we investigate how differences in proxies for oceanographic processes are related to barnacle recruitment and survival along two western boundary currents, the east coasts of South Africa and Australia. By undertaking such intercontinental comparisons we test whether oceanographic processes within two independent systems exert a similar degree of bottom-up control on recruitment. Our sites all lie towards the weak end of a continuum from net upwelling to net downwelling and none exhibit strong or highly intermittent levels of upwelling. Our measures of upwelling were all proxies for magnitude rather than intermittency and consequently we predicted that sites that experienced intermediate levels of upwelling would exhibit the greatest barnacle recruitment and survival, while sites experiencing mostly downwelling conditions would have low barnacle recruitment.

Fig. 1. Map illustrating the location of the eight study sites along the southeast coasts of South Africa and Australia.

Likewise, the East Australia Current flows southwards, parallel to the coastline until it reaches approximately 31.5°S latitude where it separates from the coast (Cetina-Heredia et al., 2014), leaving behind an avenue of southward moving eddies (Everett et al., 2012). The two coasts exhibit different patterns of coastal upwelling with sites along the east coast of South Africa experiencing similar frequencies of downwelling and relatively weak upwelling events (Lutjeharms et al., 2000), whilst sites along the east coast of Australia are generally characterised by persistent downwelling (Suthers et al., 2011; Rossi et al., 2014). To make relevant comparisons of biological processes between these two systems, we focused on populations of intertidal barnacles, since they dominate the high to midshore region in both countries (note that mussels dominate the low intertidal region in South African sites, whilst sea squirts and macroalgae dominate the low intertidal region in Australia). At the four Australian sites, Tesseropora rosea is the most abundant barnacle inhabiting the mid shore region followed closely by Catomerus polymerus, which is generally found lower on the shore. In South Africa, Tetraclita serrata is the most abundant barnacle within the midshore region on rocky shores, along with Octomeris angulosa and Chthamalus dentatus, which are found lower and higher on the shore, respectively. All five species display similar life history strategies (Table 1) and perform similar ecological functions within their communities (Underwood et al., 1983; Dye, 1988; Boland, 1997). Apart from C. dentatus, which grows to about 8 mm, they exhibit similar growth rates and maximum sizes of 20–25 mm (J.A. Lathlean pers. obs.).

2. Materials and methods 2.1. Study regions and species The study was undertaken at eight moderately exposed rocky shores spread across equivalent latitudes along the east coasts of South Africa and Australia (Fig. 1). In South Africa these sites were: Haga (32.77°S, 28.24°E), Kidd's Beach (33.15°S, 27.70°E), Kayser's Beach (33.21°S, 27.61°E) and Old Woman's River (33.48°S, 27.15°E). The four Australian sites were: Nambucca Heads (30.65°S, 153.02°E), Port Macquarie (31.46°S, 152.93°E), Seal Rocks (32.43°S, 152.53°E) and Garie Beach (34.17°S, 151.06°E). Apart from being situated on moderately exposed locations across similar latitudes, these eight sites were also chosen based on a number of other shared characteristics, including substratum type (i.e. sandstone/siltstone), orientation (i.e. east-southeast) and slope (i.e. 10–15° inclination). All but two locations (Old Woman's River and Nambucca Heads) are located more than 20 km away from any major land or riverine inputs, which could potentially affect nearshore nutrient levels. We also used a priori knowledge to choose sites that we believed would collectively experience a range of upwelling and downwelling conditions. Furthermore, each study region is situated along a warm-temperate western boundary current. Along eastern South Africa, the Agulhas Current generally flows to the southwest, parallel and in close proximity to the coastline until it reaches approximately 34°S latitude. Farther south it diverges from the coast, following the continental shelf break (Lutjeharms et al., 2000).

2.2. Quantifying upwelling regimes We used three complementary approaches for characterising upwelling/downwelling regimes at each of our eight locations, each with different advantages and disadvantages. The first method involved calculating Bakun Upwelling Indices (BUI) based on oceanographic data obtained from the Pacific Fisheries Environmental Laboratory (PFEL) Live Access Server (http://www.pfeg.noaa.gov/products/las. html). This index represents the water flux (cubic metres per second per 100 m of coastline) seaward (upwelling; positive values) or shoreward (downwelling; negative values). The major advantage of the PFEL server is that it is capable of calculating upwelling indices for any location around the world at 0.5° intervals (averaged over 3° pixels centred over the desired latitude and longitude) after inputting the latitude, longitude and coastal angle (measured in degrees from North). We downloaded data from the PFEL server that allowed us to calculate BUI at six-hourly intervals for regions adjacent to our eight study 198

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Table 1 Comparison of early life history processes amongst the five predominant species of barnacles that were recorded during the present study. Breading season refers to the period when adult barnacles have generally been found to have mature embryos; Recruitment period refers to the period newly settled cyprids and recruits are generally observed on rocky shores; Larval development refers to amount of time for larvae to development into cyprids whilst in the water column. Species

Breeding season

Recruitment period

Larval development

Reference(s)

Tetraclita serrata Octomeris angulosa Chthamalus dentatus Tesseropora rosea

Nov–Mar Oct–Feb Jan–May Jan–Jun

Jan–May Jan–May Feb–May Jan–July

2–3 weeks 2–3 weeks 2–3 weeks 2 weeks

Catomerus polymerus

Mar–Nov

May–Sept*

2–3 weeks

Sandison and Day (1954) Griffiths (1979) Sandison and Day (1954) Griffiths (1979) Sandison & Day (1954) Wisely and Blick, 1964 Anderson (1969), Caffey (1985), Egan and Anderson (1988), Lathlean et al., (2010) Egan and Anderson (1989), *JA Lathlean, pers obs

offshore) around the sampling location. The 2 pixels closest to the coast (∼8 km) were removed to minimise the effects of land or riverine inputs to the coastal zone (following Everett et al., 2014). All remaining pixels were averaged to provide a daily chlorophyll-a measure for each site. A linear interpolation was used to fill in missing data due to cloud cover and a cumulative chlorophyll-a concentration for each sampling period was calculated by summing the chlorophyll a concentration for each day within the sampling period. It is important to remember, however, that while chlorophyll-a concentrations have been used to quantify phytoplankton abundance, this relationship does not necessarily tell us anything about the relationship between phytoplankton abundance and upwelling conditions. Furthermore, chlorophyll-a concentrations taken 10 km offshore may not accurately reflect the nearshore oceanographic conditions experienced by dispersing barnacle larvae or sessile recruits. Therefore, of the three methods used to quantify upwelling and downwelling regimes within the present study, satellite chlorophyll-a concentrations may be the least reliable. However, we believe it worthwhile to incorporate such analyses into the present study since they would, at the very least, provide a relevant comparison of the large-scale oceanographic differences between the two continents.

locations. Means and standard deviations (SD) of BUI were calculated for each location during each sampling period (see ‘Quantifying recruitment’ below) with positive and negative BUI values indicating predominant upwelling and downwelling conditions respectively. We used mean BUI as a measure of upwelling intensity and standard deviation of BUI as an estimate of the intermittency of upwelling. Thus, locations with high standard deviations in BUI values were indicative of locations that experienced more frequent fluctuations in upwelling and downwelling conditions. The second method for characterising oceanographic conditions involved deploying temperature DS1921L iButtons® (n = 2 loggers per location) embedded in waterproof electrical resin (3 M Scotchcast 2130 Flame Retardant Compound) within the mid intertidal region at each location to record ambient air and sea temperatures every 30 min from May 2015 to April 2016. Since iButtons record both air and sea temperatures, we used local tide predictions, with a sampling interval of 30 min, to identify periods when loggers were submerged during high tide (see Lathlean et al. 2011 for more detail). Thus, changes in temperature presented and analysed in this study represent nearshore sea water temperatures, not air temperatures. In order to reduce the potential effects of spatial and temporal variation in wave-exposure on estimated changes in sea temperatures, we built a 0.5 m buffer into the estimated tidal height of the logger. We applied similar methods to Tapia et al. (2009) in that we used declines in mean (n = 2 loggers) sea temperatures to identify and characterise the frequency, intensity and duration of upwelling events. Upwelling events were identified by negative values after subtracting a 20-day running mean from the daily mean temperature. This daily temperature anomaly highlights deviations from mean temperatures without the confounding influence of between-site differences in mean temperature (Tapia et al., 2009). The durations of upwelling events were calculated as the number of days elapsed between the onset of a temperature drop and the time it takes for temperature anomalies return to positive values. The intensity of each upwelling event was calculated as the rate of cooling i.e. the slope with which the temperature anomaly drops from a local maximum to a local minimum ΔT/d, where d is the number of days elapsed so that steeper slopes indicate more intense upwelling. The advantages of using such in situ sea-temperature data to estimate upwelling frequencies (compared to Bakun Upwelling Indices) are that, firstly, they do not depend entirely on differences in wind-driven Ekman transport and, secondly, they are more likely to capture smallscale variation between individual sites since they represent localised in situ conditions at scales relevant to the target organisms. The disadvantages, however, are: (i) that many localised factors other than upwelling and downwelling may influence variation in nearshore sea water temperatures, and (ii) that changes in nearshore sea temperatures can only be used to characterise upwelling events and not downwelling events. The third approach utilised satellite chlorophyll-a concentrations to quantify phytoplankton abundance, which typically varies according to the frequency and intensity of upwelling events. Satellite chlorophyll-a data (mg.m−3) were retrieved from MODIS-Aqua 4 km (L3) at daily time-scales for a 0.5° × 0.5° grid (0.25° north and south, and 0.5°

2.3. Quantifying recruitment Barnacle recruitment was calculated by establishing ten permanent 20 cm × 20 cm plots within the midshore region at each location and clearing the substratum of all benthic invertebrates and macroalgae at the beginning of the study period using a metal brush and chisel. Natural plots were used instead of artificial plates in order to capture ‘natural’ patterns of recruitment and avoid any potential artefacts of using artificial surfaces. These plots were situated on horizontal to slightly sloping (0°–10° inclination) emergent rock characterised by high abundances of adult barnacles. Within South Africa, all plots were originally cleared in early May 2015 and resampled approximately once every three months until April 2016 (i.e. 11 months). In Australia, plots were initially cleared in July 2015 and resampled every 2–3 months until late March 2016 (i.e. 8 months). These differences in sampling periods and frequencies could not be avoided due to the logistical nature of carrying out concurrent sampling across two continents. For this reason, we standardised sampling periods by dividing the total number of barnacle recruits observed in each plot by the number of days since the last sampling event (see ‘Statistical Analysis’ below). Importantly, the eight to 11 month sampling period encompassed the major reproductive and recruitment periods of the five dominant barnacle species observed in this study (see Table 1). During each resampling event, high resolution digital photographs were taken of each plot during low-tide and later used to count the total number of barnacle recruits using the digital software package ImageJ. Once photographs had been taken, half of the plots were re-cleared in order to facilitate the estimation of recruitment for the following sampling period. The remaining five quadrats were left undisturbed and accumulated barnacle recruits over the entire sampling period. This was done to provide an estimate of ‘recruitment success’ at each location – hereafter referred 199

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and the lowest occurring from January to April. In contrast to BUI calculations, in situ temperature measurements revealed that a greater number upwelling events occurred among the four Australian sites than amongst the four South African sites (Fig. 3, Table 3). However, despite the greater upwelling frequencies within Australia, upwelling duration was typically longer and more intense within South Africa, which explains why BUI calculations demonstrated greater overall upwelling conditions within South Africa compared to Australia. Based on in situ temperature data for the entire sampling period (July 2015–April 2016), Port Macquarie in Australia exhibited the highest number of upwelling events, whilst Old Woman's River experienced the greatest intensity of upwelling. At the other end of the spectrum, upwelling events at Garie Beach in Australia were shown to be consistently less frequent, less intense and of shorter duration than at any of the other seven study locations (Table 3). Satellite images of nearshore coastal waters revealed consistently higher daily and cumulative chlorophyll concentrations along the South African coastline than in Australia (Fig. 4, Table 4). Indeed, chlorophyll concentrations were generally one to two orders of magnitude higher in South Africa (Fig. 4, Table 4). Based on cumulative chlorophyll concentrations for the entire sampling period (July 2015–April 2016), Old Woman's River in South Africa exhibited the highest chlorophyll concentrations, followed closely by two other South African sites, Kidd's Beach and Kaysers Beach. Such dramatic differences in nearshore chlorophyll concentrations between the two countries are consistent with BUI calculations, which showed upwelling frequency, duration and intensity to be greater along the South African coastline. Indeed, total cumulative chlorophyll concentration over the entire sampling period was positively correlated to mean BUI at each of the eight study sites (r2 = 0.726, n = 8, p < 0.05).

to as colonisation. Due to the difficulty of identifying species of recently settled barnacle larvae, estimates of barnacle recruitment were combined for all species within each plot. However, colonisation plots revealed that the majority of barnacles that recruited into plots were Tesseropora rosea in Australia and Tetraclita serrata in South Africa. 2.4. Statistical analysis To standardise estimates of barnacle recruitment across the eight study sites, the total number of barnacles observed within each of the re-cleared plots was divided by the number of days since the last sampling event (usually between 78 and 90 days). Likewise, to standardise estimates of barnacle colonisation, we divided the total number of barnacles observed within each colonisation plot by the total number of days since the beginning of the sampling period (i.e. between 237249 days and 340–341 days for Australian and South African sites, respectfully). Two-way nested ANOVA was used to test for differences in this standardised daily barnacle recruitment amongst sites (orthogonal, random, 4 levels), sites were nested within countries (orthogonal, fixed, 2 levels: Australia and South Africa) and sampling period (orthogonal, fixed, 3 levels: July/Aug to Oct 2015, Oct 2015 to Jan 2016, Jan to Mar/Apr, 2016). A two-way nested ANOVA was used to test for differences in barnacle colonisation over the entire sampling period (i.e. May 2015–April 2016). Spearman-rank correlations (r) were used to test for possible relationships between barnacle recruitment and colonisation with: (i) mean BUI, (ii) standard deviation of BUI, (iii) frequency of upwelling events (as estimated using in situ temperatures), and (iv) cumulative chlorophyll-a concentrations. Under the IUH we might expect recruitment and colonisation values to be greater at sites that experience an intermediate number of upwelling events than at sites experiencing little or no upwelling. One-way ANOVAs were used to test for significant differences in mean BUI amongst the eight study locations for each sampling period separately. Statistical analyses were not undertaken on in situ temperature or satellite chlorophyll a concentrations due to lack of replication at each site.

3.2. Barnacle recruitment Mean barnacle recruitment (number.d−1) differed significantly amongst locations (Fig. 5, Table 5), though the ranking of sites was not consistent across the three sampling periods. For example, Nambucca Heads in Australia experienced the greatest rates of barnacle recruitment during the two sampling periods between July 2015 and January 2016, but was amongst the lowest ranked sites during the last sampling period (January to March 2016; Fig. 5). By comparison, Old Woman's River in South Africa exhibited the greatest recruitment during the last sampling period but only intermediate levels of recruitment during the two previous sampling periods (Fig. 5). Daily rates of barnacle recruitment also differed significantly between the two countries, with differences being most pronounced during the last sampling period when all South African sites except Haga experienced three to four times as many recruits as the four Australia sites. Regardless of country or site, daily barnacle recruitment was lowest from October 2015 to January 2016, the period when upwelling frequencies were greatest. Barnacle colonisation, that is, the final number of barnacles within plots that were untouched after initial clearing, differed significantly amongst sites, with mean barnacle densities being greatest at Nambucca Heads followed by Port Macquarie and Kidd's Beach (Fig. 6, Table 5). Colonisation remained quite low at the remaining three South African and two Australian sites (Fig. 6). Statistical comparisons showed that colonisation was significantly higher in Australia than South Africa (Table 5), in direct contrast to the results for daily recruitment and chlorophyll concentrations. Such discrepancies indicate higher post-recruitment survival in Australia than in South Africa. Interestingly, the Australian site that experienced the greatest mean daily recruitment (i.e. Nambucca Heads) also recorded the highest colonisation rate. This was not the case amongst the four South African sites, as mean daily recruitment during the four sampling periods was greatest at Old Woman's River, whereas cumulative barnacle recruitment was greatest at Kidd's Beach (Fig. 6).

3. Results 3.1. Oceanographic conditions Oceanographic conditions differed considerably amongst the eight study locations with the most distinct differences being found between the two continents (Fig. 2, Tables 2 and 3). Based on mean and standard deviation in Bakun Upwelling Indices (BUI), sites in South Africa predominantly experienced upwelling conditions with a high degree of intermittency as indicated by high standard deviation values (Table 2). By comparison, sites in Australia predominantly experienced downwelling conditions with a low degree of intermittency as indicated by the relatively low standard deviation values (Fig. 2, Table 2). For example, over the entire 11 month sampling period for which BUI values were calculated, mean BUI values amongst the four South African sites ranged from 41.53 at Haga to 20.48 at Kaysers Beach (Table 2). Whereas within Australia mean BUI values ranged from −28.09 at Garie Beach to −15.43 at Port Macquarie. Interestingly, oceanographic conditions showed strong seasonal patterns that were consistent within each of the four locations on each continent. For example, within South Africa all four locations were characterised by moderate downwelling conditions between May and August, whilst upwelling conditions were predominant between August and April, being most intense between October and January (Table 2). In comparison, sites in Australia experienced predominantly downwelling conditions from May to October 2015 with weak upwelling from November 2015 to April 2016 (Fig. 2, Table 2). Seasonal patterns in the standard deviation (or intermittency) values were also consistent across the two continents with greatest intermittency being observed in both countries between May and August, 200

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Fig. 2. Temporal variation in Bakun Upwelling Index (BUI) at each of the four study locations in South Africa (left column) and Australia (right column) over the 10month sampling period. N.B. negative values indicate periods of downwelling; positive values indicate periods of upwelling.

differed significantly with BUI variability, which we used as a measure of upwelling intermittency. The IUH predicts a monotonic relationship and this was the case when recruitment rates were highest (January–April 2016) with daily barnacle recruitment increased with increasing standard deviation values of BUI (r2 = 0.729, n = 8, p < 0.05) (Fig. 7). In contrast, barnacle colonisation (as measured within permanent plots that were initially cleared then left untouched) appeared to decrease with increasing upwelling intermittency (r2 = 0.258, n = 8, p > 0.05) (Fig. 8). Colonisation rates also seemed to vary unimodally with mean BUI, with greater colonisation at sites that experienced intermediate levels of upwelling and lower colonisation at sites that experienced weak downwelling or persistent upwelling, though the relationship was non-significant (Fig. 8).

3.3. Barnacle recruitment vs oceanographic conditions 3.3.1. Bakun Upwelling Index (BUI) Daily rates of barnacle recruitment appeared to display a significant (P < 0.05) unimodal relationship with mean BUI values, as predicted by the IUH (Fig. 7). For example, during the last sampling period (i.e. Jan–Apr, 2016), when all five species of barnacles where predicted to be most active reproductively and recruitment rates were markedly elevated (note axis on Fig. 7), daily barnacle recruitment was greatest at sites which experienced low to moderate upwelling conditions compared to sites that experienced either persistent upwelling or downwelling (r2 = 0.574, n = 8, p < 0.05). This was also true for the cumulative number of barnacle recruits within re-cleared plots over the entire sampling period, which was greater at sites that experienced moderate upwelling conditions and lower at sites that experienced either persistent upwelling or weak downwelling (r2 = 0.725, n = 8, p < 0.05) (Fig. 7). Geographic variation in daily recruitment rates also

3.3.2. In situ sea temperatures Daily barnacle recruitment appeared to increase with increasing upwelling frequencies across the eight study locations during the last

Table 2 Mean and standard deviations (SD) of Bakun Upwelling Indices (BUI) calculated for each of the eight study locations using data collected from the Pacific Fisheries Environmental Laboratory (PFEL) Live Access Server. Negative values indicate primarily downwelling conditions, whilst positive values indicate primarily upwelling conditions. Period

South Africa

Australia

HH

KI

KA

OWR

NH

PM

SR

GB

MEAN BUI 7 May – 4 Aug 2015 5 Aug – 28 Oct 2015 29 Oct 2015–25 Jan 2016 26 Jan – 9 Apr 2016 OVERALL

−63.40 67.35 112.38 54.63 41.53

−56.81 37.31 70.91 42.31 22.15

−52.87 36.36 63.02 40.44 20.48

−64.44 41.46 84.46 46.35 25.64

−77.44 −21.32 24.52 10.83 −17.15

−80.42 −24.87 27.08 23.19 −15.43

−72.90 −31.31 12.23 11.67 −21.48

−100.91 −40.44 22.63 13.52 −28.09

SD BUI 7 May – 4 Aug 2015 5 Aug – 28 Oct 2015 29 Oct 2015–25 Jan 2016 26 Jan – 9 Apr 2016 OVERALL

227.31 151.18 161.47 99.58 181.38

211.25 159.16 133.74 96.14 165.34

219.37 163.19 136.40 96.26 168.55

203.61 151.45 137.17 108.58 165.82

140.46 92.77 75.92 42.19 104.38

145.75 99.34 84.57 45.42 111.31

143.99 111.35 115.92 49.89 118.07

168.50 111.55 57.20 42.91 120.12

201

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Table 3 Frequency, intensity and duration of upwelling events at the eight study sites as estimated using in situ temperature data. *Overall values only incorporates the three sampling periods where data exist for all eight locations (i.e. from July/August 2015 to April 2016). Period

South Africa

Australia

HH

KI

KA

OWR

NH

PM

SR

GB

Frequency May–July/Aug 2015 July/Aug–Oct 2015 Oct 2015–Jan 2016 Jan–Mar/Apr 2016 OVERALL*

7 5 9 8 22

9 6 8 7 21

8 6 8 6 20

6 6 7 8 21

– 6 10 4 20

– 9 10 6 25

– 7 11 4 22

– 7 9 3 19

Intensity May–July/Aug 2015 July/Aug–Oct 2015 Oct 2015–Jan 2016 Jan–Mar/Apr 2016 OVERALL*

0.763 0.478 0.956 1.400 1.009

0.632 0.847 0.937 1.133 0.977

0.434 0.837 0.923 0.831 0.870

0.730 0.747 1.877 1.369 1.361

0.903 1.191 0.899 1.046

0.562 1.056 1.891 1.079

0.510 1.466 0.742 1.030

0.539 0.943 0.523 0.728

Duration May–July/Aug 2015 July/Aug–Oct 2015 Oct 2015–Jan 2016 Jan–Mar/Apr 2016 OVERALL*

5.857 8.2 7 4.875 6.5

4.778 5.333 7.75 5.571 6.333

6.375 5.5 7.5 6.333 6.55

8 4.5 7 4.375 5.286

6.167 4.2 5 4.95

5.889 5.1 3.667 5.04

6.143 3.545 7 5

4.143 4 8.333 4.737

Fig. 3. Temporal variation in in situ sea temperatures recorded at each of the four study locations in South Africa (left column) and Australia (right column) over the 10-month sampling period. N.B. Different scales on y-axis. Grey line represents the 20-day running mean.

frequency intensity or duration (p > 0.05 in all cases) (Fig. 10). Interestingly, colonisation was somewhat greater at sites that experienced moderate upwelling intensities and intermediate upwelling durations compared to those sites which experienced persistent weak and strong upwelling intensities or consistently short or long upwelling durations (Fig. 10).

sampling interval (i.e. Jan–Apr, 2016) when barnacle reproduction was predicted to be highest (r2 = 0.402, n = 8, p < 0.05) (Fig. 9). Likewise, a positive correlation was found between the total number of upwelling events during the entire sampling period and the combined number of recruits observed within re-cleared plots (r2 = 0.309, n = 8, p < 0.05) (Fig. 9). In contrast to upwelling frequencies, upwelling intensity and duration seemed to have little effect on barnacle recruitment when assessed separately for each of the three sampling intervals (Fig. 9). However, upwelling intensity was found to have a significant and positive relationship with the total number of recruits when measured over the entire sampling period (r2 = 0.442, n = 8, p < 0.05) (Fig. 9). Barnacle colonisation rates did not vary in response to upwelling

3.3.3. Satellite chlorophyll-a concentrations Barnacle recruitment was highly positively correlated with satellite chlorophyll-a concentrations between January and April 2016, when daily barnacle recruitment rates were high (r2 = 0.889, n = 8, p < 0.05) (Fig. 9). Likewise, when measured over the entire sampling period, the total number of recruits observed within re-cleared plots 202

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Fig. 4. Daily variation in satellite chlorophyll-a concentrations (arithmetic running average) measured 10 km offshore of each of the four study sites in South Africa (left column) and Australia (right column). N.B. Different scales on y-axis. Table 4 Cumulative chlorophyll concentrations recorded by satellite images 10 km offshore at each of the eight study sites from May 2015 to April 2016.*Overall cumulative chlorophyll concentrations only incorporates the three sampling periods where data exist for all eight locations (i.e. from July/August 2015 to April 2016). Period

May–Aug/July 2015 July/Aug–Oct 2015 Oct 2015–Jan 2016 Jan–Mar/Apr 2016 OVERALL*

South Africa

Australia

HH

KI

KA

OWR

NH

PM

SR

GB

78.08 79.96 35.26 46.73 162.0

97.60 126.2 67.17 44.84 238.2

91.17 110.8 68.94 49.96 229.7

114.2 102.9 82.84 61.13 246.9

– 29.85 25.21 7.70 62.76

– 30.10 23.61 7.17 60.89

– 40.54 21.60 22.54 84.68

– 30.14 23.03 11.25 64.43

previous studies which describe nearshore oceanographic conditions along the east coast of South Africa as being primarily dominated by a number of upwelling-cells, which, at times, may switch to weak downwelling systems (Lutjeharms, 2006). Interestingly, in situ temperature measurements indicated that the four Australian sites experienced a greater number of upwelling ‘events’ than the four South African sites. However, upwelling events amongst the four Australian sites were generally less intense and shorter in duration. This explains not only how BUI values could be significantly greater in South Africa, even though upwelling frequency was found to be greater in Australia, but also why cumulative chlorophyll-a concentrations were one to two orders of magnitude higher along the east coast of South Africa. It is important to note here that, whilst chlorophyll-a is a response to, rather than a measure of upwelling, it represents one of the key subsidies that drive the community level consequences of upwelling (Menge et al., 2004). Differences between the continents in chlorophyll-a probably reflect the comparatively low nutrient availability that characterises surface waters along the east coast of Australia for most of the year (Condie and Dunn, 2006; Everett et al., 2014; Yoder et al., 1993). In contrast, frequent vertical mixing along the east coast of South Africa brings nutrient rich South Indian Central Water into the surface coastal waters of the Agulhas Current system (Lutjeharms et al., 2000; Lutjeharms, 2006). Thus, differences in chlorophyll-a concentrations between the two countries probably reflect differences not only in the

also increased with increasing chlorophyll-a concentrations (r2 = 0.892, n = 8, p < 0.05) (Fig. 9). Interestingly, barnacle colonisation appeared to vary somewhat unimodally with chlorophyll-a concentrations (r2 = 0.214, n = 8, p > 0.05), with greater colonisation rates being found at sites that experienced either high or low concentrations than at sites that experienced intermediate levels of chlorophyll-a concentrations (Fig. 10).

4. Discussion Any relationship between larval recruitment and upwelling is unlikely to fit model predictions when reproductive rates are low, but based on BUI data, our findings provide good support for the IUH during periods of high recruitment. In contrast, this was not true for colonisation, presumably because any possible relationship would be disrupted by events following larval settlement, particularly post-settlement mortality. Quantifying oceanographic conditions along the east coasts of South Africa and Australia, using three complementary techniques confirmed our a priori predictions on the frequency, intensity and intermittency of upwelling regimes at our study sites. For example, mean and standard deviation BUI revealed that the four South African sites experienced predominantly upwelling conditions with stronger upwelling and greater intermittency than the four Australian sites. This supports 203

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Fig. 5. Mean ( ± SE) barnacle recruitment within the midshore region at four rocky shores along the east coast of South Africa (left column) and the east coast of Australia (right column). Values as standardised by the number of days between sampling events. No data were collected in Australia from May to June 2015. Letters indicate results of post hoc analyses (Tukey HSD) – sites without common letters were found to be significantly different.

intensity and duration of upwelling but also in the sources of upwelled water. There are two ways in which the results of our study can be interpreted in relation to the IUH. Firstly, the results can be viewed in isolation, making conclusions based on the range of oceanographic conditions that were present across the eight locations and two continents, in other words towards one end of the full net upwelling to net downwelling spectrum. Secondly, the results can be placed among a broader context of studies that incorporate either a broader range of oceanographic characteristics or a different suite of upwelling regimes than those detected in the present study (i.e. strong-persistent upwelling). In what follows, we will consider both approaches, putting greater emphasis on placing the results of this study alongside others undertaken within areas with a broader range of upwelling conditions. Under the IUH, we would expect that barnacle recruitment would exhibit a unimodal relationship with upwelling intensity (mean BUI) and monotonically with intermittency (standard deviation of BUI). Viewed in isolation, our data conformed well to these predictions, particularly when rates of recruitment were high. Thus, for example, recruitment rates were two to four times higher in South Africa than Australia during peak recruitment (Jan–April 2016), while there was a

Table 5 Statistical summary of (i) three-way nested ANOVA investigating differences in daily barnacle recruitment amongst the eight study sites (nested within Country) across three sampling periods (July/Aug–Oct 2015; Oct 2015–Jan 2016; Jan 2016 Mar/April 2016), and (ii) two-way nested ANOVA testing differences in cumulative barnacle recruitment over the entire sampling period. df

MS

F-ratio

p-value

Daily recruitment Country Sampling period Site [Country] Country*Sampling period Site [Country]*Sampling period Error

1 2 6 2 12 96

103.6 109.4 19.8 91.7 12.5 2.71

38.155 40.316 7.292 33.767 4.609

< 0.001 < 0.001 < 0.001 < 0.001 < 0.001

Colonisation rates Country Site [Country] Error

1 6 32

1.189 1.246 0.261

4.555 4.773

0.041 0.001

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Fig. 6. Mean ( ± SE) barnacle colonisation within the midshore region at four rocky shores along the east coast of South Africa (left plot) and the east coast of Australia (right plot). Values as standardised by the number of days from the first to last sampling date. Letters indicate results of posthoc analyses (TukeyHSD) – sites without common letters were found to be significantly different.

In terms of recruitment rates, our data were also generally supportive of the IUH when placed in the broader context of other studies. For example, when we focus only on results obtained for the last sampling interval (i.e. January to April 2016), which is the peak reproductive period for both the dominant Australian barnacle Tesseropora rosea (Caffey, 1985; Egan and Anderson, 1988; Lathlean et al., 2010) and South African barnacle Tetraclita serrata (Griffiths, 1979), then oceanographic conditions appear to exert strong bottom-up control on these barnacle assemblages. However, our results at times also provide evidence in support of the classic upwelling model that predicts that recruitment should increase linearly with upwelling frequency and intensity (Roughgarden et al., 1988). For example, daily barnacle recruitment increased with increasing upwelling frequency and chlorophyll-a concentrations (as measured by changes in in situ sea temperatures and satellite imagery, respectively) during the last sampling

strong relationship with intermittency during the same period. This did not apply in the case of colonisation, however, for which the opposite was true. Nambucca Heads in southeast Australia accumulated the highest number of barnacles over the 10-month sampling period, followed closely by Port Macquarie, also in Australia, and only then Kidd's Beach in South Africa. The difference between recruitment and colonisation clearly indicates that post-settlement mortality is higher along the east coast of South Africa than amongst the four Australian sites. This highlights the important assumption that patterns of recruitment are primarily the result of larval settlement patterns. In other words, oceanographic conditions may have a powerful influence on settlement rates, but be over-ridden when we incorporate post-settlement factors and consider population regulation and community structure. Consequently, we detected no significant relationships between our oceanographic metrics and barnacle colonisation.

Fig. 7. Relationships between mean and standard deviations of Bakun Upwelling Index (BUI) with daily barnacle recruitment rate recorded during the three sampling intervals: 5 August to 28 October 2015 (top-row), 29 October 2015 to 25 January 2016 (second-row) and 26 January to 9 April 2016 (third-row). Bottom-row represents correlations over the entire 10-month sampling period using cumulative barnacle recruitment.

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Fig. 8. Relationship between mean and standard deviations of Bakun Upwelling Index (BUI) with mean barnacle colonisation (standardised per day). N.B. In the present study, barnacle colonisation was based on the number of barnacles at the end of the 10-month sampling period within permanent quadrats that were initially cleared at the beginning of the study period and then left untouched.

Fig. 9. Correlations between daily barnacle recruitment rate and upwelling frequency, intensity and duration calculated using in situ sea surface temperatures; and cumulative satellite chlorophyll-a concentrations. Bottom-row represents correlations over the entire 10-month sampling period using cumulative barnacle recruitment.

Fig. 10. Correlations between daily barnacle colonisation rate and upwelling frequency, intensity and duration calculated using in situ sea surface temperatures; and cumulative satellite chlorophyll-a concentrations.

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communities has significant implications for understanding the future and management of coastal marine ecosystems.

period when barnacle reproduction was predicted to be greatest. Could the two perspectives can be reconciled by remembering that the two study regions here represent only a portion of the upwelling/downwelling continuum and therefore should be viewed in light of other studies that have undertaken similar investigations across a broader, or complementary, range of oceanographic conditions. For example, Menge et al. (2004) investigated the role of oceanographic conditions on the recruitment, abundance and predation of the intertidal mussel Mytilus californianus across 17 locations along the west coast of the United States. The authors found that nearshore chlorophyll a concentrations were 12–13 times greater at sites that experienced intermittent upwelling compared to those that experienced persistent or weak upwelling and that this in turn appeared to reflect large-scale patterns of mussel recruitment, which was 23.3 times greater at sites that experienced intermittent upwelling than at sites that experienced either persistent upwelling and 47.7 greater than at sites with weak upwelling. However, mussel abundance, growth and predation differed independently of upwelling regime and instead were generally more variable amongst sites within each region. A more recent study by Menge and Menge (2013), which assessed the intermittent upwelling hypothesis across 44 wave exposed rocky shores in Oregon, California and New Zealand, found that phytoplankton abundance, barnacle and mussel recruitment, mussel growth and predation rates all varied unimodally along a gradient of upwelling with maximal levels at intermittent frequencies. Importantly, mean BUI values reported by Menge and Menge (2013) varied from −50 to 175, while our values only ranged from −30 to 45. Thus, our results were generally congruent with what might be expected to occur if the IUH was applied across the full spectrum of upwelling-downwelling. However, with such a short dataset (i.e. 10-months), and fairly infrequent sampling (3-months), some caution should be used when interpreting our data since the effects of oceanographic conditions are most likely to have the greatest effect on larval development and settlement processes, both of which may have been obscured by early post-settlement processes. Furthermore, critics of the IUH correctly point out that many local processes, other than those that directly contribute to large-scale differences in upwelling regimes, have repeatedly been shown to have a greater effect on intertidal barnacle settlement and recruitment. For example, Shanks et al. (2010) showed that barnacle and limpet recruits were far more abundant where surf zones were wide and dissipative than at more reflective shores, irrespective of upwelling frequency and intensity. Thus, whether the IUH is applicable to the majority of coastal systems around the world requires further investigation..

Acknowledgements This work is based upon research supported by the National Research Foundation of South Africa (Grant number 64801). Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ecss.2019.04.040. References Anderson, D.T., 1969. On the embryology of the cirripede crustaceans Tetraclita rosea (Krauss), Tetraclita purpurascens (Wood), Chthamalus antennatus (Darwin) and Chamaesipho columna (Spengler) and some considerations of crustacean phylogenetic relationships. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 256, 183–235. Boland, J.M., 1997. The horizontal zonation of two species of intertidal barnacle in South Africa. S. Afr. J. Mar. Sci. 18, 49–61. Broitman, B.R., Kinlan, B.P., 2006. Spatial scales of benthic and pelagic producer biomass in a coastal upwelling ecosystem. Mar. Ecol. Prog. Ser. 327, 15–25. Caffey, H.M., 1985. Spatial and temporal variation in settlement and recruitment of intertidal barnacles. 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5. Conclusion Both when viewed in isolation and when placed in a broader context, our findings are largely consistent with the IUH. On a continuum between strong-persistent upwelling to strong-persistent downwelling, our sites all lie within a limited range from intermittent upwelling to persistent downwelling. Yet although we lacked sites that experience strong-persistent upwelling, barnacle recruitment was greatest within South Africa where there were intermittent levels of upwelling. Importantly, studies of western boundary currents, which typically fall within the persistent downwelling side of the spectrum, are rare (but see Shanks et al., 2003; Shanks and Brink, 2005 for examples) and attempts to investigate the generality of the IUH would benefit from the inclusion of more sites such as those found on the east coasts of South Africa, Australia, Brazil or Japan. Such comparative studies are important because recent climate models predict that within highly productive Eastern Boundary Upwelling Systems, such as the Canary, Benguela and Humboldt systems, upwelling intensity and duration will increase at higher latitudes, resulting in the homogenisation of regional differences in upwelling/downwelling regimes (Wang et al., 2015). Determining the degree to which the intensity, timing and spatial distribution of upwelling are critical to the structure of coastal marine 207

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Byrne, M., Condie, S.A., Hartog, J.R., Hassler, C.S., Hobday, A.J., Holbrook, N.J., Malcolm, H.A., Oke, P.R., Thompson, P.A., Ridgway, K., 2011. The strengthening East Australian Current, its eddies and biological effects - an introduction and overview. Deep-Sea Res. Part II Top. Stud. Oceanogr. 58, 538–546. Underwood, A.J., Denley, E.J., Moran, M.J., 1983. Experimental analysis of the structure and dynamics of mid-shore rocky intertidal communities in New South Wales. Oecologia 56, 202–219. Wang, D., Gouhier, T.C., Menge, B.A., Ganguly, A.R., 2015. Intensification and spatial homogenization of coastal upwelling under climate change. Nature 518, 390–394. Wieters, E.A., 2005. Upwelling control of positive interactions over mesoscales: a new link between bottom-up and top-down processes on rocky shores. Mar. Ecol. Prog. Ser. 301, 43–54. Wisely, B., Blick, R., 1964. Seasonal abundance of first stage nauplii in 10 species of barnacles at Sydney. Mar. Freshw. Res. 15, 162–171. Yoder, J.A., McClain, C.R., Feldman, G.C., Esaias, W.E., 1993. Annual cycles of phytoplankton chlorophyll concentrations in the global ocean: a satellite view. Glob. Biogeochem. Cycles 7 (1), 181–193.

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