Drivers of pH Variability in Coastal Ecosystems - ACS Publications

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Critical Review

Drivers of pH variability in coastal ecosystems Jacob Carstensen, and Carlos M. Duarte Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b03655 • Publication Date (Web): 20 Mar 2019 Downloaded from http://pubs.acs.org on March 23, 2019

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Environmental Science & Technology

Critical Review

Drivers of pH variability in coastal ecosystems

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Jacob Carstensena,* and Carlos M. Duarteb,c

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Aarhus University, Department of Bioscience, Frederiksborgvej 399, DK-4000 Roskilde,

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a

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Denmark

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b

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(RSRC), Thuwal, 23955-6900, Saudi Arabia

King Abdullah University of Science and Technology (KAUST), Red Sea Research Center Arctic Research Centre, Department of Bioscience, Aarhus University, C.F. Møllers Allé 8, DK-

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c

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8000 Århus C, Denmark

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*

Corresponding author: [email protected]

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1 ACS Paragon Plus Environment


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ABSTRACT

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A synthesis of long-term changes in pH of coastal ecosystems shows that, in contrast to the

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uniform trends of open-ocean acidification (-0.0004 to -0.0026 pH units yr-1) driven by increased

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atmospheric CO2, coastal ecosystems display a much broader range of trends (-0.023 to 0.023

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pH units yr-1) and are as likely to show long-term increase as decline in pH. The majority of the

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83 investigated coastal ecosystems displayed non-linear trends, with seasonal and interannual

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variations exceeding 1 pH unit for some sites. The high pH variability of coastal ecosystems is

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primarily driven by inputs from land. These include freshwater inputs that typically dilute the

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alkalinity of seawater thereby resulting in reduced buffering, nutrients enhancing productivity

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and pH, as well as organic matter supporting excess respiration driving acidification. For some

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coastal ecosystems, upwelling of nutrient-rich and corrosive water may also contribute to

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variability in pH. Metabolic control of pH was the main factor governing variability for the majority

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of coastal sites, displaying larger variations in coastal ecosystems with low alkalinity buffering.

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pH variability was particularly pronounced in coastal ecosystems with strong decoupling of

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production and respiration processes, seasonally or through stratification. Our analysis

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demonstrate that coastal pH can be managed by controlling inputs of nutrients, organic matter,

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and alkalinity. In well-mixed coastal waters, increasing productivity can improve resistance to


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ocean acidification, whereas increasing productivity enhances acidification in bottom waters of

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stratified coastal ecosystems. Environmental management should consider the balance

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between the negative consequences of eutrophication versus those of acidification, to maintain

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biodiversity and ecosystem services of our coastal ecosystems.

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INTRODUCTION There is growing concern that ocean acidification by anthropogenic CO2, clearly reflected

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in long-term trends toward a decline by 0.02 pH units decade-1 in open-ocean waters1–4, may

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significantly impact marine calcifiers, such as corals and mollusks1,5–7. This has led to increased

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attention to coastal ecosystems, where many of the vulnerable calcifiers inhabit. Coastal

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ecosystems have been shown to display complex and diverse patterns of pH change over time8–

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12,

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open-ocean surface waters1–4. Indeed, changes in pH in coastal ecosystems appear

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idiosyncratic, displaying a diversity of patterns11,13.

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in contrast to the more monotonic, uniform decrease in pH in response to increased CO2 in

Efforts to understand the regulation of pH, including anthropogenic impacts, on coastal

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waters have revealed a complex set of interacting processes driving pH changes8,11,12,14,15. Initial

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attempts to understand variability in coastal pH extended concepts and models developed for

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the open ocean, dominated by the expected ocean acidification trends derived from

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anthropogenic CO2 emissions and mixing between the marine and freshwater end-members

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controlling carbonate chemistry in coastal ecosystems16. However, examination of the control of

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coastal pH has identified the involvement of a variety of additional drivers, including watershed

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and biological processes, which support a variety of metabolically intense communities8–12,14,15.


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In particular, coastal eutrophication has been shown to exert a strong control on patterns of pH

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change9,10,17–19 consistent with the strong nutrient control of biological activity in coastal

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ecosystems20–23. Because the timing and strength of management of nutrient inputs to coastal

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ecosystems differ across the world24, we expect coastal ecosystems to exhibit a diversity of

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patterns of pH variability. However, this expectation derives largely from reports documenting

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pH changes in individual coastal ecosystems, which have not allowed the detection of patterns

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of changes in pH, either in terms of the repertoire of seasonal and long-term trends exhibited, or

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the relationships with potential drivers, such as inputs of nutrients, levels of chlorophyll a,

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salinity or alkalinity buffering. We argue here that a critical review of the patterns of pH change

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in coastal ecosystems provides an improved opportunity to resolve the contributions of different

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factors, including the role of eutrophication processes, in driving seasonal and long-term

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changes in pH. In turn, understanding drivers of change in coastal pH may allow interventions,

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at the watershed scale, to reach desirable target pHs25, thereby helping protect coastal

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ecosystems.

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Here we critically review patterns of long-term pH change in coastal ecosystems

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across the world, based on a synthesis of available data (ranging from 6 to 67 years), to (1)

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characterize the patterns and rates of change at seasonal and interannual time scales, (2)



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assess the role of mixing between freshwater and marine waters that characterize these

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ecosystems, and (3) quantify the effect of eutrophication and changes in phytoplankton

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abundance on seasonal and decadal patterns of change in pH in coastal ecosystems.

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VARIATIONS IN COASTAL pH

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Records of long-term changes in pH in surface coastal waters (0-10 m) are available from public

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databases from a number of sources (Table 1), representing 83 different coastal ecosystems in

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11 regions of the world (Fig. S1), and a total number of 147,042, 186,956, and 148,731 samples

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for pH, salinity, and Chla, respectively (Table 1). These datasets allow the characterization of

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the long-term changes (>10 year with the exception of two French sites) in pH, along with

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relevant ecosystem properties, such as salinity, temperature, chlorophyll a (Chla), total nitrogen

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(TN) and total phosphorus (TP). Total alkalinity (TA) is an important property affecting pH,

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allowing coastal ecosystems to be classified as weakly or strongly buffered, depending on

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whether the TA for the freshwater entering the ecosystems, which was reported for 47 of the

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coastal ecosystems for which time series are available, was below or above 1.2 mmol kg-1 ,

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(~half ocean TA), respectively, while the degree of buffering was estimated from the literature

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for the remaining coastal ecosystems (see Table S1 for details on classification).

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The pH in surface waters of coastal ecosystems can be characterized through their overall

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mean levels, as well as seasonal and interannual variations. However, comparing pH across

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coastal ecosystem can be cumbersome due to differences in procedures and pH scales used.

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Coastal and estuarine monitoring programs generally use glass electrodes for measuring pH



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that are calibrated on a series of low ionic strength buffer solutions available from the US

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National Bureau of Standards (NBS). The NBS scale was employed by all monitoring authorities

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in the long-term data sets available, except for France where the seawater scale (SWS) was

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employed (1997-2016; Table 1). Laboratory measurements of pH cannot be readily compared,

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as temperature and hence pH may have shifted from in-situ conditions. Although the pH scale of

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older monitoring data cannot always be retrieved from data sources or literature, they were

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assumed reported on the NBS scale, i.e. maintaining the same analysis and reporting scale

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over time. In order to characterize pH trends across ecosystems, pH was converted to the total

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scale, using salinity-dependent conversion of pH on the NBS scale26 and assuming pH on SWS

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and total scales to be equal. pH measured on the NBS scale expresses an activity as opposed

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to total, free and SWS scales representing the hydrogen ion concentration. Since hydrogen ion

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activity varies with salinity, comparison of pH levels in relation to changes in atmospheric CO2

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and metabolic processes across coastal ecosystems covering a broad span in salinity is more

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meaningful on the total scale. Although potentiometric measurements of pH are inherently less

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precise (±0.1; ref. 11), the uncertainty introduced by this measurement error on mean values is

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small relative to seasonal and interannual variations, as mean values were typically calculated

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from tens or hundreds of observations.


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Variations in the water quality variables were partitioned into spatial variation between stations

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within coastal ecosystem, seasonal variation using monthly means and trends using annual

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means with a general linear model (GLM)27. This decomposition approach is based on a

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parametric decomposition of spatial and temporal variations, which is particularly useful for

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irregularly sampled monitoring data. Chla, TN and TP were log-transformed prior to this

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decomposition because variations typically scaled with the means, whereas pH, salinity and

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temperature were not transformed. This implies that sources of variations were additive for

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salinity and temperature, and multiplicative for Chla, TN, and TP as well as pH that represents a

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log-scale. Means for the log-transform of Chla, TN, and TP were subsequently back-

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transformed as geometric means using the exponential function. For comparative purposes,

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long-term records of pH in oceanic waters were also retrieved from existing databases, the

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Hawaii Ocean Time-series (HOT; http://hahana.soest.hawaii.edu/hot/) and the Bermuda Atlantic

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Time Series (BATS; http://bats.bios.edu/), with the corresponding long-term slopes of

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decreasing pH and their SE (Table S2). Ocean acidification (OA) is subsequently characterized

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by the mean slope of these time series of -0.0018 yr-1 (Table S2).

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Interannual variations in pH were further investigated using a Generalized Additive Model

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(GAM) containing a parametric component (linear trend with slope β) and a non-parametric

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component (spline S()) to describe deviations from the ocean acidification (OA) by subtraction of

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0.0018 yr-1. The pH trends of the 83 ecosystems were partitioned into four categories: (1) no

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deviation from OA (β and S() are both non-significant), (2) linear trend with slope different from

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OA (β is significant and S() is non-significant), (3) non-linear trend with slope equal to OA (β is

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non-significant and S() is significant), and (4) non-linear trend with slope different from OA (β

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and S() are both significant). Furthermore, we tested if the magnitude of trends, given by the

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absolute value of β, as well as seasonal and interannual ranges in pH were different for weakly

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versus strongly buffered systems by analysis of variance.

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pH time series from 83 coastal ecosystems across the world (Fig. 1; Fig. S3) demonstrated a

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broad span of trends with slopes ranging from -0.023 to 0.023 yr-1, i.e. trends up to one order of

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magnitude larger than ocean acidification (OA) and 46 sites (~55%) experiencing declining pH

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(Fig. 2). Coastal systems with weak buffering (Table S1) did not show larger trends than

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stronger buffered systems (F1,81=0.51; p=0.4793). In fact, only 16 sites exhibited changes over

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time similar to the OA trend (Table 2), whereas most sites (1) experienced trends deviating


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significantly from OA by different slopes (13 sites), (2) multiannual to decadal departures from a

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linear trend similar to OA (20 sites), or (3) multiannual to decadal departures from a linear trend

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different from OA (34 sites). This diversity of trend patterns was not specific to any particular

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region but was observed across all regions. Coastal pH was decreasing significantly faster than

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OA for 21 sites, whereas changes over time in pH were significantly larger than OA for 26 sites

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(Table 2).

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The coastal systems displayed large seasonal and interannual variations in pH, typically up to 1

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pH unit, although seasonal and interannual variability could be as high as 1.4 and 1.6,

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respectively. The predominant drivers of pH variations were investigated at different scales:

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spatial, seasonal, and interannual. Drivers of seasonal and interannual variation were

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investigated by calculating the range among monthly and annual means for each ecosystem

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and examining their relationships to salinity and Chla seasonal and interannual ranges. We

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used range as a more informative statistic of variability although it increases with the number of

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observations, but this bias was small given the lengths of time series (Fig. S2). We found that

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temporal variations in coastal pH far exceeded those observed in open ocean environments



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(Table S2, Fig. 2) and were more closely coupled to variability of chlorophyll a (Chla) than

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salinity (Fig. 3).

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Largest seasonal ranges in pH were found at high-latitude sites in the Baltic Sea and

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Danish Straits, whereas pH in low- and mid-latitude sites typically varied by less than 0.4 over

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the year. Nevertheless, at the low- and mid-latitude sites pH seasonal variability was still

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positively correlated with variability in Chla (Fig. 3B; r=0.48; p=0.0002 for log-transform of Chla).

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Similar pH associations with salinity were not observed in general, although pH seasonal

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variability in WA estuaries was significantly linked to salinity variations (Fig. 3A; r=0.79;

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p=0.0350). Seasonal ranges in pH were significantly higher for coastal systems with weak

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buffering (F1,81=10.39; p=0.0018), although one high-buffered coastal ecosystem, the

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permanently stratified Mariager Fjord in the Danish Straits, deviated from this general pattern

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with ~1 pH unit seasonal range despite high total alkalinity (TA).

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Interannual variability exceeded 1 pH unit for two sites in the Baltic Sea and one site in

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Neuse River Estuary. Variations in pH increased with salinity variability (Fig. 3C), but the

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relationship to Chla was even stronger (Fig. 3D). However, coastal systems with large

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interannual variability in salinity also had large variability in Chla (r=0.56; p1.2 meq kg-1

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(strong buffering) had modest variations in pH across the salinity gradient, demonstrating that

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pH variability due to mixing would be less than 0.3. Seasonal variability in temperature among

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sites (temperature ranges from 6.3 to 24 °C) could almost account for similar pH variability over

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the season, although for some coastal systems (Baltic Sea, Danish Straits, and Hong Kong; Fig.

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S4A) amplifying salinity-induced pH variability, while balancing the effect of salinity for other

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systems (French Atlantic coast, North Sea, Texas estuaries, and WA estuaries; Fig. S4B).

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Low pH mean values were almost exclusively found for coastal systems with weak

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buffering (Fig. 4B). Coastal systems within regions having similar end-members (e.g. sites along

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the mainstem of Chesapeake Bay) underlined that mixing overall controls the mean pH level.

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However, the salinity gradients were less pronounced for regions with high alkalinity buffering.


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Importantly, mean levels of Chla did not explain variation in pH among coastal systems (Fig.

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4D).

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Our simulations also showed that imbalance between production and respiration could

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change pH substantially, particularly in low-salinity coastal systems with low alkalinity buffering

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(Fig. 4C). Whereas the effect of changing net DIC uptake was minor for well-buffered systems

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at salinities above ~10 and low-buffered systems at salinities above ~20, drastic changes in pH

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could be observed for small DIC changes in systems with low salinity and low buffering.

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Although the position and magnitude of the sharp increase in pH varied with the TA and pH

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values employed for the end-members, the simulated changes in pH could clearly encapsulate

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those observed on both seasonal and interannual scales (Fig. 3).

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INSIGHTS INTO THE PATTERNS AND DRIVERS OF LONG-TERM CHANGE IN pH IN

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COASTAL ECOSYSTEMS

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The analysis of long-term changes in pH across 83 coastal ecosystems shows that

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these ecosystems present a much broader range (~ 20 times larger) of rates of change in pH

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than the open ocean does. In contrast to oceanic time-series, which show long-term trends of

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decline in pH ranging from -0.0004 to -0.0026 pH units yr-1 (Table S2, Fig. 2), long-term



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changes in pH in coastal systems range from -0.023 to 0.023 yr-1, with 65% of the ecosystems

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showing no monotonic trends, and 45% of the ecosystems studied showing positive trends, in

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contrast of the negative trends expected from CO2 emissions. The modal trajectory, i.e. that

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displayed by the largest number of coastal ecosystems, was one of broad oscillations around a

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long-term trend in pH departing from that expected from open-ocean ocean acidification.

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Provided the broad range of behaviors, we submit that, unlike the case for the open

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ocean, an average rate of pH change across coastal ecosystems is not representative of the

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expected behavior of ecosystems encompassed by the data set assembled here. Indeed, there

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is considerably variability in pH trends not only among coastal ecosystems in widely distributed

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regions but also within regions. Yet, the pH trajectories of coastal ecosystems are not entirely

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idiosyncratic, as some general patterns emerged from our analyses that help develop

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expectations for other coastal ecosystems not included here, and informs about controlling

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mechanisms and intervention options. Indeed, understanding the drivers of variability in coastal

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pH is of fundamental importance, as these ecosystems are inhabited by many of the calcifiers

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(e.g. mollusks, crustaceans, echinoderms, corals) that supply fundamental services30, and are

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vulnerable to ocean acidification1,6.


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A previous conceptual model of pH regulation in coastal ecosystems considered three

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components: (1) an oceanic end-member, in which variability is largely affected by air-sea CO2

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exchange characterized by a monotonic decline by about 0.02 pH unit decade-1 due to ocean

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acidification, (2) a freshwater end-member, often, but not always, characterized by low pH and

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CO2 supersaturation31–34, and (3) biological metabolism, either raising pH for autotrophic

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ecosystems (production > respiration) or decreasing pH for heterotrophic ones (production

Drivers of pH Variability in Coastal Ecosystems - ACS Publications

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