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Impact of salinity and nutrients on salt marsh stability
MARY ALLDRED,
1,2
ANNE LIBERTI,
1,3
AND STEPHEN B. BAINES
1
1
Department of Ecology and Evolution, Stony Brook University, 650 Life Sciences Building, Stony Brook, New York 11794 USA
Citation: Alldred, M., A. Liberti, and S. B. Baines. 2017. Impact of salinity and nutrients on salt marsh stability.
Ecosphere 8(11):e02010. 10.1002/ecs2.2010
Abstract. Belowground growth in coastal plants is critical for marsh stability and the ability of coastal wet-
lands to keep pace with sea-level rise. Quantifying the effectsofnutrientloadingonbelowgroundplantgrowth
is an ongoing controversy in wetland research, with previous experiments demonstrating both positive and neg-
ative impacts. Moreover, salinity may also decrease belowground growth through sulfide toxicity, or plants may
increase root growth to oxidize sediments and respond to sulfide stress. Because salinity influences plant nitro-
gen assimilation and sediment nitrogen retention, salinity and nitrogen may interact to influence belowground
plant growth. We sampled an urban-to-rural land-use gradient of 11 Spartina alterniflora marshes on Long Island,
New York, to look for correlates of belowground biomass. We found that belowground biomass was related
positively to salinity and negatively to extractable nitrogen content in sediments. Total belowground plant bio-
mass was reduced by 60–70% in high-nitrogen marshes and enhanced by as much as 70% in high-salinity
marshes. Further, we found no evidence of interaction between salinity and nitrogen, indicating that these fac-
tors were independently related to belowground plant growth. Our results indicate that chronic eutrophication
and increasing salinity resulting from sea-level rise are likely to have opposing effects on future marsh stability.
Key words: belowground biomass; eutrophication; multiple stressors; sea-level rise; shoreline stability; Spartina
alterniflora.
Received 2 October 2017; accepted 5 October 2017. Corresponding Editor: Debra P. C. Peters.
Copyright: ©2017 Alldred et al. This is an open access article under the terms of the Creative Commons Attribution
License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
2
Present address: Center for Earth and Environmental Science, SUNY Plattsburgh, 101 Broad Street, Hudson Hall 132,
Plattsburgh, New York 12901 USA.
3
Present address: Virginia Department of Conservation and Recreation, 600 East Main Street, Richmond, Virginia 23219 USA.
E-mail: malldred1@gmail.com
INTRODUCTION
The future resilience of many ecosystems
depends on their response to a range of stressors
that vary simultaneously over space and time
(Staudt et al. 2013). Models that account for the
concurrent impacts of these stressors will be
essential to maintain services provided by these
ecosystems. This fact is especially true for coastal
salt marshes that will face multiple spatially
heterogeneous stressors going forward, includ-
ing coastal eutrophication and sea-level rise
(Crain et al. 2008). Salt marshes provide services
such as shoreline stabilization, flood and storm
surge protection, and maintenance of coastal
water quality (Zedler 2003, Costanza et al. 2008,
Gedan et al. 2011). Consequently, understanding
how marshes respond to multiple stressors is
critical for the health and economic well-being of
coastal communities worldwide (Millennium
Ecosystem Assessment 2005). To keep pace with
sea-level rise, marshes must accumulate sedi-
ment and organic matter, while resisting erosion
from waves and storm surges. Both features of
resilient marshes depend on well-developed root
systems (Nyman et al. 2006, Perillo et al. 2009,
Pratolongo et al. 2009). Despite a long history of
study (Valiela et al. 1976, Mendelssohn and Mor-
ris 2000, Wigand et al. 2009, Graham and Men-
delssohn 2014), the relationships between abiotic
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factors and root-mass production and accumula-
tion remain poorly understood.
One of the abiotic factors influencing root
growth in coastal marsh vegetation is the availabil-
ity of inorganic nitrogen. Relative to preindustrial
levels, human activities have doubled the global
inputs of fixed nitrogen, a limiting nutrient in
many coastal marshes (Vitousek et al. 1997, Men-
delssohn and Morris 2000, Bertness et al. 2002,
Millennium Ecosystem Assessment 2005). Marshes
receive excess nitrogen as acid precipitation, sew-
age waste, and fertilizer runoff (Seitzinger et al.
2005). In response to fertilization, plants generally
allocate a lower proportion of their growth to
belowground biomass because they require fewer
roots to acquire the nutrients needed to support
growth of photosynthetic tissues aboveground
(Ericsson 1995). Reductions in living root mass
have been observed in nutrient enrichment studies
and were often accompanied by a decrease in sedi-
ment stability (Turner et al. 2009, Kearney et al.
2011, Deegan et al. 2012, Watson et al. 2014).
However, physiological models of marsh vegeta-
tion and other enrichment studies have suggested
that nitrogen additions can result in greater
growth of belowground biomass and can also lead
to increased sediment capture due to enhanced
aboveground biomass and stem density (Howes
et al. 1986, Morris et al. 2002, Darby and Turner
2008, Anisfeld and Hill 2012, Fox et al. 2012, Gra-
ham and Mendelssohn 2014). An increase in
belowground biomass with nitrogen fertilization
is expected if the increase in total growth compen-
sates for lower relative allocation of growth to
roots and rhizomes (Morris et al. 2013). Alterna-
tively, nitrogen fertilization could result in limita-
tion by another nutrient, such as phosphorus,
which would require that extensive root systems
be maintained (Turner 2011).
In the future, responses to nitrogen will occur
against a backdrop of changing porewater salin-
ity. Salinity may increase with increasing sea
levels as seawater intrudes into brackish marshes.
Alternatively, it may decrease as greater precipita-
tion increases freshwater discharge from ground-
water and rivers (Craft et al. 2008). The impacts of
such changes on wetlands are potentially com-
plex. Increasing salinity correlates with a higher
concentration of sulfate ions, which can be
reduced to hydrogen sulfide in low redox marsh
sediments (Mendelssohn and Morris 2000).
Because sulfide is toxic to plants, root production
is generally expected to decline as salinity
increases in anoxic marsh sediments (Linthurst
and Seneca 1981, Mendelssohn and Morris 2000).
However, marsh plants may also increase root
density in the presence of sulfide to introduce
more oxygen into sediments, thereby facilitating
oxidation of sulfide to non-toxic sulfate (Arm-
strong et al. 1994). Salinity and nitrogen may also
interact to affect marsh plants (Mendelssohn and
Morris 2000). Salinity is known to directly inhibit
ammonium assimilation by plants (Bradley and
Morris 1990) while increasing ammonium fluxes
to porewater from sediments (Giblin et al. 2010).
Field evidence for effects of salinity on below-
ground growth is sparse and does not clearly sup-
port a positive or negative relationship between
the variables, nor is it sufficient to address poten-
tial interactions with nutrient availability (Drake
and Gallagher 1984, Howes et al. 2010).
We examined the simultaneous influences of
salinity and sediment nutrient availability on
belowground growth of Spartina alterniflora across
11 coastal salt marshes that span an urban-to-
rural land-use gradient from western to eastern
Long Island, New York (Fig. 1). The study sites
represent a 50- to 100-yr chronosequence of devel-
opment from forested to agricultural-to-urban
land-use types, a series of land-use transitions that
reflects development patterns occurring world-
wide (Millennium Ecosystem Assessment 2005).
Using 430 observations of total belowground bio-
mass collected in June and August over two years,
we constructed linear models to assess the ability
of salinity and inorganic nutrients to explain site-
level variation in belowground biomass. Because
aboveground plant growth has the potential to
offset marsh loss by enhancing sediment capture,
we also examined the influence of salinity and
nutrients on aboveground plant biomass. The pri-
mary goal of our study was to identify the major
correlates of marsh stability, in the hopes of identi-
fying those factors that have most affected marsh
development over multidecadal scales.
MATERIALS AND METHODS
Long Island, New York, represents a well-
established gradient ranging from high-intensity
land use in urban areas of western Long
Island near New York City to comparatively
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ALLDRED ET AL.
Fig. 1. (A) Research locations on Long Island, New York, ranging from high human population density in
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ALLDRED ET AL.
low-intensity land use in agricultural and
forested areas of eastern Long Island (O’Shea
and Brosnan 2000, Scorca and Monti 2001, Monti
and Scorca 2003, Benotti et al. 2007). Whereas
pre-development nitrogen fluxes to Long Island
marshes originated almost entirely from ground-
water, post-development fluxes are dominated
by overflows from sewage treatment and drai-
nage from septic systems and cesspools (Ayers
et al. 2000, Benotti et al. 2007, Gobler 2016). Fer-
tilization of golf courses, parks, agricultural
areas, and lawns also contributes a small amount
to total nitrogen loads, including legacy effects
from historically extensive duck farms in eastern
Long Island (Ayers et al. 2000, Benotti et al.
2007, Gobler 2016). Because wastewater is the
largest source of nitrogen (at least 70%), total
nitrogen inputs are generally found to be greatest
in areas of highest human population density
(United States Geological Survey [USGS] 2010).
Additionally, variation in tidal range and stream
discharge among the various Long Island em-
bayments offered a high probability that average
salinity would vary among sites independently
of variation in nitrogen (Scorca and Monti 2001,
Monti and Scorca 2003).
Eleven salt marshes on Long Island, each domi-
nated by a near monoculture of Spartina alterniflora,
were selected for sampling (Fig. 1) to examine the
effects of nutrient availability and salinity on
aboveground and belowground plant biomass.
Sampling was conducted in June and August of
2012 and 2013, times chosen to correspond to the
period of active plant growth and the period just
after peak biomass was attained. This allowed us
to address potential seasonal differences in correla-
tions between abiotic variables and standing plant
biomass resulting from new plant growth. For each
marshsite,ten25925 cm quadrats were ran-
domly placed at least 1 m apart, five within the
marsh platform where short-form S. alterniflora are
typically found, and five near a creek edge where
tall-form S. alterniflora aremorecommon.Within
each quadrat, we clipped all aboveground
vegetation. Clippings were dried at 50°C for at least
48 h and weighed to determine aboveground bio-
mass. A sediment core (diameter 5cm, length
10 cm) was taken from the center of each quadrat
to determine total belowground plant biomass.
Total belowground biomass was determined by
wet sieving core samples through a 1000-lmsieve
and removing non-vegetative material by hand.
Because the living and dead fractions of below-
ground plant material were impossible to distin-
guish for all of our samples, our belowground
biomass measurements necessarily include the total
contribution of living and dead roots and rhizomes
to total belowground plant material in marsh
sediments. Hereafter, this variable is referred to as
“belowground biomass”for simplicity.
We collected sediment porewater from each
quadrat using vacuum sippers (Kolker 2005).
Samples were transported on ice and frozen at
20°C until analysis of salinity with a refrac-
tometer and analysis of ammonium and nitrate
content using standard methods (Jones 1984, Par-
sons et al. 1984). Nitrate and ammonium were
summed and reported as dissolved inorganic
nitrogen (DIN). In 2013, an additional 5-g sedi-
ment sample from each plot was extracted with
10-mL 2N KCl and analyzed for ammonium,
nitrate, and phosphate contents (Jones 1984,
Parsons et al. 1984, Wetzel and Likens 2000).
Models were constructed to predict patterns in
aboveground and belowground biomass using
JMP 7.0 statistical software (JMP(R) 1989–2007).
Initial models were constructed as an ANCOVA,
with sampling time included as a categorical pre-
dictor and nutrients and salinity as continuous
predictors. All potential second-order interactions
among predictor variables were also included. A
step-wise linear regression was performed to
select final models, with a threshold of P=0.10
for variables to enter or leave models. Interaction
terms were eliminated if main effects were not
significant. Because all predictor variables were
not measured in all years, two separate sets of
models were constructed, one containing all
western Long Island to rural areas in eastern Long Island (United States Geological Survey [USGS] 2010).
Marshes varied in (B) extractable inorganic nitrogen and (C) salinity. Error bars show standard error for site-level
means (n=10); the moving averages (solid lines) and confidence regions (shaded areas) were computed using a
loess smoothing function.
(Fig. 1.Continued)
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ALLDRED ET AL.
predictor variables collected in 2012–2013 (salin-
ity, porewater DIN) and one containing all vari-
ables collected in 2013 (salinity, extractable DIN,
extractable phosphate). Extractable phosphate
and all porewater nutrient measurements were
log
10
-transformed to satisfy assumptions of nor-
mality. Measurements in tall- and short-form
S. alterniflora were not found to differ systemati-
cally in total aboveground or belowground bio-
mass and were pooled such that analyses were
conducted on mean values for sites and sampling
times. Relationships between predictor variables
and biomass were calculated and plotted in R ver-
sion 3.0.3 (R Core Team 2012) as standard major
axis (SMA) regressions to account for appreciable
measurement error in both dependent and inde-
pendent variables. Details of analyses and R code
are provided in Appendix S1. All data and meta-
data are available in Data S1 and MetaData S1,
respectively. Tests with P-values <0.05 were con-
sidered statistically significant, while values
between 0.1 and 0.05 were considered marginally
significant.
RESULTS
Among variables measured in June and August
2013, total belowground biomass was negatively
related to extractable DIN (P=0.013; Table 1,
Fig. 2A) and positively related to porewater salin-
ity (P=0.056; Table 1, Fig. 2B). Mean below-
ground biomass differed between sampling times
(P=0.015; Table 1). However, the slopes relating
belowground biomass to salinity or DIN did not
differ between sampling times (Fig. 2A, B), as the
interactions between these variables and sampling
time were not significant (P=0.71 and 0.45,
respectively). Aboveground biomass was posi-
tively related to sampling time only (Table 1);
however, we did observe a trend in which above-
ground biomass increased with DIN availability
(Fig. 2C). Overall, for the 2013 data, we detected a
60–70% reduction in belowground biomass and a
70% increase in aboveground biomass with
increasing DIN availability at the site level
(Fig. 2A, C). Additionally, belowground biomass
was found to increase with increasing salinity by
as much as 70%. No interactions between salinity
and DIN were retained in final models, indicating
that the effects of salinity and DIN were additive
(Table 1). Overall, we were able to explain over
53% of the total variation in belowground biomass
with extractable DIN, salinity, and season. Not sur-
prisingly, the difference between the periods of
biomass accrual (June) and peak biomass (August)
explained 32% of the total variation in above-
ground biomass among marsh sites (Table 1).
For the full set of aboveground and below-
ground biomass measurements (2012–2013), only
sampling time, porewater DIN, and salinity were
available as independent variables. Salinity was
positively related to belowground biomass, and
although mean belowground biomass again dif-
fered significantly among sampling times, the
slope of the relationship was similar among all
sampling times (Table 1, Fig. 2B). Differences
among sampling times alone explained 56% of
the variation in aboveground biomass (Table 1).
Table 1. Best model for predicting belowground and aboveground biomass (g/m
2
)ofSpartina alterniflora at the
site level.
Parameter
Belowground biomass Aboveground biomass
Model R
2
df SS FP Model R
2
df SS FP
2013 data only 0.53 0.32
Time 1 2.40 910
6
7.29 0.015 1 3.22 910
5
9.59 0.006
Salinity (ppt) 1 1.37 910
6
4.16 0.056
DIN (lmol/L) 1 2.50 910
6
7.59 0.013
Residuals 18 5.94 910
6
20 6.72 910
5
2012 and 2013 data 0.31 0.56
Time 3 5.28 910
6
3.96 0.015 3 9.00 910
5
16.84 <0.0001
Salinity (ppt) 1 4.59 910
6
10.33 0.003
Residuals 38 1.69 910
7
39 1.59 910
6
Notes: Two sets of models were run, one set initially including all variables measured in 2013, and one including all variables
measured in 2012 and 2013. In all cases, interaction terms were non-significant and were removed from final models. df,
degrees of freedom; DIN, extractable dissolved inorganic nitrogen; SS, sum of squares.
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ALLDRED ET AL.
Sampling time and salinity explained 31% of the
variation in belowground mass for the 2012–2013
dataset. In all cases, porewater nitrogen and
extractable phosphate measurements were found
to be poor predictors of aboveground and below-
ground biomass and were discarded from final
models. Among all sampling times, above-
ground and belowground plant biomass mea-
surements were uncorrelated among sites and
sampling dates (n=43, r=0.06, P=0.72).
DISCUSSION
This work supports the hypothesis that eutro-
phication due to nitrogen loading exerts a
negative influence on belowground biomass, and
thus marsh stability, in coastal marshes. This
result is consistent with a growing body of evi-
dence suggesting that increasing nutrient avail-
ability decreases the amount of growth allocated
to roots and rhizomes (Valiela et al. 1976, Deegan
et al. 2012, Watson et al. 2014). Notably, most pre-
vious studies have been based on relatively short-
term enrichment experiments and have witnessed
a response in only the living fraction of below-
ground biomass. This study is one of the few that
has detected a response in total belowground bio-
mass, including both living and dead root mate-
rial (Morris and Bradley 1999, Wigand et al.
2009). A reduction in total belowground biomass,
Fig. 2. (A) Among sites, total belowground plant biomass of Spartina alterniflora, including living and dead
roots and rhizomes, was negatively associated with extractable inorganic nitrogen content of sediments in June
2013 (slopeSMA =9.02) and August 2013 (slopeSMA =8.94). (B) Belowground biomass was positively asso-
ciated with the salinity of sediment porewater in June 2012 (slopeSMA =145.6), August 2012
(slopeSMA =109.4), June 2013 (slopeSMA =90.11), and August 2013 (slopeSMA =101.4). (C) Total above-
ground biomass showed a positive but non-significant trend with extractable inorganic nitrogen in August 2013
(slopeSMA =2.75) and June 2013 (slopeSMA =1.74). (D) Aboveground biomass was not related to salinity.
SMA, standard major axis.
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ALLDRED ET AL.
from both the accumulation and decomposition
of dead root matter, is a slow-response variable
that is less likely to be detected in short- to moder-
ate-term (i.e., 5–15 yr) experiments. By compar-
ison, the variation in total belowground biomass
in Long Island marshes represents a long-term
response to 50–100 yr of differences in enrichment
and thus reflects the effects of chronic eutrophica-
tion on belowground biomass and marsh stability.
Notably, a negative relationship between total
belowground plant biomass and nitrogen inputs
was also observed in a previous study of extant
marshes in Narragansett Bay, RI, which were sub-
ject to chronic nutrient enrichment; however, this
relationship was observed only in higher eleva-
tion marshes dominated by Spartina patens
(Wigand et al. 2009). Together these findings have
important implications for the long-term stability
of marshes that are believed to be currently stable
under nutrient enrichment.
Sediment capture by marsh plants is not likely
to be an important determinant of marsh stability
on Long Island and marshes along coastal barrier
islands generally, which typically receive lower
sediment loads than marshes with large riverine
inputs (Darby and Turner 2008, Wigand et al.
2009). Hypothetically, nitrogen fertilization could
stimulate aboveground plant growth and more
effectively trap suspended particles, offsetting
losses in organic matter accumulation (Morris
et al. 2002). Our lack of correlation between
aboveground and belowground production
(P=0.72) suggests that controls on these
responses may be decoupled, which may seem
counterintuitive as both are at least weakly asso-
ciated with DIN (Fig. 2). However, biomass
responds to variables other than DIN, such as
salinity in the case of belowground biomass
(Fig. 2B) or tidal range in the case of above-
ground biomass (Steever et al. 1976). Also, as
DIN increases, the opposing effects of increasing
aboveground and decreasing belowground bio-
mass on sediment retention may depend on a
range of variables, including rates of sediment
delivery via streams and the strength of tidal and
storm surges. In marshes with low sediment
deposition, such as in Long Island and other
northeastern marshes (Kim and Bokuniewicz
1991, Watson et al. 2014), factors controlling
belowground growth and organic matter accu-
mulation are likely to be more important
determinants of vertical marsh growth than sedi-
ment capture by aboveground biomass.
The nutrient-loading context of Long Island
marshes may explain why the responses of plant
root variables differed from those observed in
some other studies. While DIN had an effect on
belowground biomass, we found no evidence of
phosphate effects. This difference may result
from low N:P ratio in sediment porewater, which
never exceeded 15 for any of the sites included in
our study, making it extremely unlikely these
marshes are phosphorus limited (Verhoeven
et al. 1996). In marshes with lower phosphorus
availability, nitrogen enrichment may cause
plants to become phosphorus limited, and they
may allocate more growth to roots to scavenge
for phosphate (Turner 2011). The background
nutrient supply ratios should be taken into con-
text when comparing results of studies relating
eutrophication to marsh vegetation.
The consistently positive effect of salinity on
belowground biomass in Spartina alterniflora
marshes was the most surprising result we
observed (Fig. 2B). This result supports the
hypothesis that plants allocate more growth to
roots and rhizomes as a stress response, aerating
sediments to increase sulfide oxidation and allevi-
ate sulfide stress (McKee et al. 1988). Our results
are consistent with one other field study, which
found that high-salinity marshes produce more
roots and have a higher sediment shear strength
than nearby low-salinity marshes (Howes et al.
2010). These results suggest that increasing salin-
ity from sea-level rise may enhance stability of
brackish coastal marshes for a given amount of
sediment delivery and total production.
Though consistent with previous work showing
that nutrient loading negatively impacts root
mass, our findings suggest a larger role for salinity
in determining total root and rhizome mass than
is commonly expected. Our results indicate that
eutrophication may reduce marsh stability and
that increasing salinity in inland marshes as sea
level rises may increase stability of those marshes.
Because high sulfide concentrations inhibit nitro-
gen assimilation (Mendelssohn and Morris 2000),
we expected an interaction between the effects of
salinity and DIN on belowground biomass. How-
ever, our analysis determined that salinity and
DIN acted independently and that their combined
effects are therefore additive. Therefore, though
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ALLDRED ET AL.
their effects on total belowground biomass are
likely to exhibit complex spatial signatures over
time, the fact that they act independently and con-
sistently means that we should be able to predict a
significant proportion of the variation using rela-
tively simple biological relationships. Given suffi-
cient knowledge of hydrology and sediment load,
a holistic management approach that accounts for
hydrological and chemical determinants of marsh
growth may well be within reach. Such an
approach would enhance our ability to assess the
stability of marshes under future scenarios of sea-
level rise and eutrophication.
ACKNOWLEDGMENTS
This work was supported by New York Sea Grant
(R/CMC-10), a Tibor T. Polgar and a Graduate Research
Fellowship from the Hudson River Foundation, and a
Robert R. Sokal Award and Lawrence Slobodkin Award
from the Department of Ecology and Evolution, Stony
Brook University. Dianna Padilla, Jessica Gurevitch,
Stuart Findlay, and Alistair Rogers provided helpful
comments on earlier versions of this manuscript. We
also thank Stoycho Velkovsky, Matthew Sarubbi, and
many undergraduates for analytical assistance. Site
access was provided by the Nature Conservancy of
Long Island, Suffolk County Parks, U.S. Fish and Wild-
life, the Town of Hempstead, the Village of Sands Point,
and the Ward Melville Heritage Organization.
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