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Enhanced nitrogen loss may explain alternative stable states in dune slack successionAdema, Erwin B.; van de Koppel, Johan; Meijer, Harro; Grootjans, Albert

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DOI:10.1111/j.0030-1299.2005.13339.x

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Enhanced nitrogen loss may explain alternative stable states in dune

slack succession

Erwin B. Adema, Johan Van de Koppel, Harro A. J. Meijer and Ab P. Grootjans

Adema, Erwin B. Van de Koppel, J., Meijer, H. A. J. and Grootjans, Ab. P. 2005.Enhanced nitrogen loss may explain alternative stable states in dune slack succession.�/ Oikos 109: 374�/386.

Ecological theory emphasizes competitive interactions between plant species whenexplaining primary succession in plants. Ecosystem processes, such as nutrientaccumulation, are often regarded as independent, steering successional changeswithout being affected by the interacting plant species. We present experimentalevidence that plant species in wet dune slack systems are able to affect ecosystemprocesses in their favor by reducing the rate of nitrogen accumulation by couplednitrification�/denitrification, promoting their competitive position. We compareddenitrification rates of two early successional species having radial oxygenloss (ROL) with two non-ROL late successional species in a mesocosm experiment.The denitrification rates were significantly higher in mesocosms planted withearly successional species Littorella uniflora (PB/0.001) and Schoenus nigricans(PB/0.05), relative to the rates found in the presence of non-ROL species, Carexnigra and Calamagrostis epigejos. We analyzed the consequences of enhanced nitrogenloss on the competition between an early and a late successional species by means of asimple theoretical model. Our analysis revealed that early successional species capableof ROL might retard successional changes and lock the ecosystem in an unproductivestate for an extended period of time. We emphasize that understanding of ecosystemprocesses is crucial in successful conservation of high biodiversity vegetation in wetdune slacks.

E. B. Adema and Ab. P. Grootjans, Community and Conservation Ecology Group, Univ. ofGroningen, P.O. Box 14, NL-9750 AA, Haren, the Netherlands (e.b.Adema@biol.rug.nl).�/ J. Van de Koppel, Netherlands Institute of Ecology, Centre for Estuarine and CoastalEcology, P.B.140, NL-4400 AC Yerseke, the Netherlands. �/ H. A. J. Meijer, Centerfor Isotope Research, Univ. of Groningen, Nijenborgh 4, NL-9747 AG Groningen, theNetherlands.

The mechanisms of primary succession have been a

dominant theme in plant ecology for over two decades

(Grime 1979, Tilman 1985, 1988, Bertness and Callaway

1994, Engstrom et al. 2000, Fagan and Bishop 2000).

Mathematical theory emphasizes community aspects in

explaining successional patterns, focusing on competi-

tion between plant species as the dominant factor

explaining species changes (Tilman 1985, 1988). During

primary succession, increased availability of nutrients

causes a shift in dominance of species adapted to low

nutrients to species adapted to low light (Tilman 1985,

Olff et al. 1993). Changes in boundary conditions, such

as the nutrient supply rate, are assumed to be the driving

force behind successional change and they are generally

described as being independent from the dynamics of the

competing species themselves.

More recent developments emphasize ecosystem pro-

cesses in explaining successional trajectories. Herbivory

can influence nutrient accumulation by affecting the

abundance of nitrogen-fixing legumes (Maron and

Accepted 18 October 2004

Copyright # OIKOS 2005ISSN 0030-1299

OIKOS 109: 374�/386, 2005

374 OIKOS 109:2 (2005)

Jefferies 1999), or by influencing fire-induced losses of

nitrogen (Knops et al. 2000). Herbivores were found to

affect primary succession on a salt marsh by reducing

mineralization rates and preventing accumulation of

litter (Van Wijnen et al. 1999). But also the plants

themselves may influence the rate of nutrient accumula-

tion (Knops and Tilman 2000), and thereby affect the

competitive balance. These studies show that processes

that occur on the level of the ecosystem are a significant

factor determining primary succession.

In this study, we report on plants affecting ecosystem

processes that strongly influence primary succession

in wet dune slacks. In a recent study, Adema et al.

(2002) reported the presence of two different succes-

sional stages that occur side by side in the same

unmanaged dune slack. An early successional stage,

dominated by Littorella uniflora (L.) Aschrs., has existed

alongside a later successional stage dominated by

Phragmites australis (Cav.) for more than 60 years. As

neither the substrate nor the hydrological conditions

differed between the two stages, biotic interactions

possibly explain the differences in vegetation develop-

ment. We hypothesize that retarded net accumulation of

nitrogen in early stages of succession can explain this

phenomenon.

As field experiments have shown most early stages of

dune slack development are N-limited (Willis 1963,

Dougherty et al. 1990, Olff et al. 1993, Koerselman

and Meuleman 1996, Lammerts et al. 1999). Moreover,

Adema and Grootjans (2003) made a nitrogen balance

that showed under experimental conditions significantly

higher nitrogen losses in dune slack systems containing

L. uniflora, an early successional species, than in systems

containing its possible successor C. nigra . This indicates

that L. uniflora may enhance the nitrogen loss from the

ecosystem.

L. uniflora, as many early successional species has

high oxygen loss rates from their roots (ROL). In dune

slack systems species capable of ROL, are absent in later

stages of dune slack succession. In de present study

we investigate if early successional species capable

of ROL can enhance nitrogen losses from the soil

by means of coupled nitrification-denitrification

(Christensen and Sorensen 1986, Olsen and Andersen

1994, Risgaard Petersen N. and Jensen K. 1997). By

lowering the net rate of accumulation of nitrogen, these

species could delay ecosystem development. In the

second part, we investigate by means of a simple

theoretical model if early successional species capable

of ROL can trigger a positive feedback between

decreased productivity and enhanced nitrogen losses

that stops successional changes and locks the eco-

system in an unproductive state for an extended period

of time.

Material and methods

Enhanced nitrogen loss

Two laboratory experiments were conducted to test

if early successional species capable of ROL increase

the denitrification rate. Both experiments used meso-

cosms that mimic the situation of a seepage zone where

the groundwater flow reaches the soil surface (Grootjans

et al. 1998). Glass containers with a surface area of 25�/

18 cm and a height of 22 cm were filled with a 4 cm layer

of fine river gravel, followed by 18 cm of calcareous sand

from the beach of Texel, the Netherlands. A PVC cover

prevented lateral light penetration through the glass.

A water inlet was placed in the gravel layers to ensure

equal distribution of the artificial ground water; the

outlets were placed at the soil surface level. The

composition of the water was derived from groundwater

of the Frisian Island of Schiermonnikoog (Stuyfzand et

al. 1992), supplemented with 0.6 mM ammonium sulfate.

Oxygen-free water, stored in bottles under nitrogen gas

at a pressure of 0.1 bar in excess of atmospheric pressure,

was supplied to each mesocosm at a rate of 250 ml

day�1 using multi-channel peristaltic pumps (Master-

flex). A thin layer of a microbial mat, harvested in the

dune slack ‘Buiten Muy’ on the Frisian Island of Texel,

was spread out on the mesocosms. Six replicates each of

four plant species were used in the experiment, Littorella

uniflora and Schoenus nigricans (L.) as species having

ROL, Carex nigra (L.) Reichard and Calamagrostis

epigejos (L.) Roth as their successor species without

notable ROL. These successor also can form a stable

vegetation that may exist for decades (Westhoff 1947,

Petersen 2000). All plants originated from the Wadden

Sea area and were pregrown in a greenhouse. After

addition of the microbial mat and plants, the mesocosms

were left undisturbed in a climate chamber with a 12h

of fluorescent light with an intensity of 350 mE m�2 per

day, a temperature regime of 228C during light periods,

178C during dark periods and an air humidity of

50�/60%.

After five months of growth in the first experiment,

soil oxygen concentrations were measured using stainless

steel needle electrodes with a sensing tip ofB/0.1 mm

(Van Gemerden et al. 1989) and custom-made nA-meter.

Profiles were recorded during the light periods applying

depth increments of 0.5 mm (0�/10 mm depth), 1 mm

(10�/25 mm depth) and 10 mm (50�/120 mm depth),

while continuous recordings were made at fixed depths

of 20 and 50 mm using a multi-channel data logger

(Campbell Scientific CR10x) set to measure every 2.5

second and to store the average every minute. Profiles

of oxygen were also measured in the field. Oxygen

profiles in vegetation dominated by Carex nigra or

Littorella uniflora and in bare soil were measured in

the ‘Buiten Muy’ on the Frisian island of Texel (53807?N

OIKOS 109:2 (2005) 375

04846?E). Profiles in vegetation dominated by Schoenus

nigricans were measured in the ‘Kroon’s Polders’ on the

Frisian island of Vlieland (53815?N 04857?E).

In a second experiment we replaced, after five months

of undisturbed growth, the ammonium in the stock by

60% 15N-labeled ammonium. Three weeks after the

labeling, when all the water in the mesocosms was

replaced by water containing labeled ammonium, deni-

trification rates were measured. For this purpose each

mesocosm was sealed with an airtight plexiglas covering

with four vacuum gas sample flasks. During four days,

each day, one sample flask was opened to sample the

headspace. N2 gas was cryogenically purified from the

gas samples. In the first cold trap (�/788C) water was

removed from the air sample. After this step, a copper

oven (6008C) withdrew oxygen from the samples and

converted N2O to N2. Then, carbon dioxide was frozen

and removed in a liquid nitrogen trap (�/1978C). Finally,

the purified di-nitrogen gas was trapped in flasks

with active charcoal at �/1978C. After purification

the samples were stored under vacuum until analysis.

Mass 28, 29, and 30 were measured from the purified

samples on a dual inlet Isotope Ratio Mass Spectro-

meter (Micromass Sira 10). The amount of additional15N in the headspace was calculated, after correction

for super saturation of the groundwater. At the end

of the experiment, plants were harvested and dried at

708C after which above- and belowground biomass

were determined. One-way analysis of variance was

applied to detect differences between species in denitri-

fication rates and biomass. Different subgroups at

the 0.05 and 0.001 P levels were distinguished by

student-Newman-Keuls post hoc multiple comparison

(Zar 1984).

Results

Soil oxygen

The oxygen profiles were distinctly different in meso-

cosms with early successional species capable of ROL as

compared to mesocosms with late successional species.

In mesocosms with non-ROL species, oxygen was

depleted within the top 20 mm of the profile, whereas

in the mesocosms with ROL species, oxygen could be

detected up to 100 mm depth (Fig. 1A, 1B). This is

comparable with the oxygen profiles as measured in the

field (Fig. 2), in which both ROL species have a positive

effect on the soil oxygen concentration. Moreover, the

oxygen profiles in mesocosms with ROL species showed

a pattern that strongly varied with depth. Apart from the

high variability of oxygen concentrations in space,

oxygen measurements showed a distinct pattern in

time, with high oxygen concentrations during the

day and low oxygen concentrations during the night

(Fig. 1C).

Denitrification

The denitrification rates were significantly higher in

mesocosms with species capable of ROL than in

mesocosms with non-ROL species (Fig. 3). The deni-

trification rate in mesocosms planted with Schoenus

Fig. 1. Oxygen concentrations as measured in the mesocosms.(A) and (B) show the oxygen profiles in L. uniflora and C. nigra(8 profiles each; from 4 mesocosms with 2 replicates) mesocosmsrespectively. The symbols mark the different replicate meso-cosms, whereas the black and the gray line with the samesymbol marks simultaneously measured oxygen replicas withina mesocosm. (C) shows two replicate time series measured ontwo depths in a mesocosm with L. uniflora . The black linesdepict the replicate oxygen measured at 20 mm depth, the graylines at 50 mm depth.

Fig. 2. Oxygen concentrations as measured in the field at theFrisian islands of Vlieland (Schoenus nigricans ) and Texel (allothers). The high oxygen concentrations in the top centimeterare due to microbial activity. The increase in oxygen concentra-tions deeper in the soil profile by Littorella and Schoenus isattributed to radial oxygen loss.

376 OIKOS 109:2 (2005)

nigricans was approximately 10 times higher than the

denitrification rates in the mesocosms of Calamagrostis

epigejos and Carex nigra (PB/0.05). Even more pro-

nounced, mesocosms with Littorella uniflora revealed a

30 times higher denitrification rate than those measured

in mesocosms containing the two high-productive

species (PB/0.001).

Littorella uniflora produced the lowest biomass

(Table 1). However, biomass measured for this species

is almost the same as found in a dune slack under

natural conditions (Adema et al. 2002). The other

species reached higher biomass levels than L. uniflora

that reflected the different morphologies of the species.

The higher root biomass of those species contributed

most to the differences. Note that differences in the

biomass of plants at the onset of the experiment explain

a part of the differences found between species, notably

in Schoenus nigricans (Table 1).

Interaction between ecosystem processes and plant

competition: a theoretical analysis

To explore the effects of enhanced nitrogen losses from

the ecosystem by early successional species on succession

and ecosystem development, we developed a simple

resource competition model.

Our model describes the interaction between two

species that are representatives for early successional

and late successional species in dune slacks. A number of

assumptions underlie our analysis. We assume that the

early successional species is the best competitor for

nitrogen when the nitrogen availability, and hence the

standing crop, is low (Olff et al. 1993) The late

successional species is assumed to be the best competitor

when the available nitrogen in the system is high, because

of a high growth potential or a high shade tolerance. As

a model system we adopted the frame developed by

Tilman (1990). Note that this is just an example system,

as we focus in our analysis on the effects of radial oxygen

loss on ecosystem processes such as denitrification and

the availability of nitrogen. Similar results may be

obtained using a different description of competition

(e.g. Lotka�/Volterra equations with nitrogen-dependent

growth of competition coefficients). Two differential

equations describe the changes in biomass for a repre-

sentative species for successional stages, an early succes-

sional species having ROL (V1) and a late successional

non-ROL species (V2). The third equation represents the

dynamics of available nitrogen in the soil (N). First, we

analyze a model that does not include enhanced nitrogen

loss. After that, we explore a model that includes

enhanced nitrogen loss when the early successional

species dominates.

The change in biomass (dV/dt) depends on the

biomass Vi of species i and the net specific growth

rate (G):

Fig. 3. Denitrification rates of 4 typical dune slack species. Theletters represent the different subgroups (PB/0.05 for b, PB/

0.001 for c) defined by a one-way ANOVA and student�/

Newman�/Keuls post hoc multiple-comparison test.

Table 1. Standing crop, separated in above- and belowground biomass. The initial masses are calculated from individual plantweights (n�/15). End masses are measured from the mesocosms at the end of the denitrification experiment. (SE�/standard error;n�/6). Letters indicate the different subgroups (PB/0.05) distinguished by a student�/Newman�/Keuls post hoc multiplecomparison.

Species Aboveground Belowground Total

g m�2 SE g m�2 SE g m�2 SE

Initial standingcrop

L. uniflora 2.70 0.57 a 6.80 1.58 a 9.50 1.96 aS. nigricans 11.77 1.46 b 5.65 1.12 a 16.77 2.24 bC. nigra 8.93 0.90 b 18.27 2.39 b 27.21 2.69 cC. epigejos 11.11 1.46 b 5.66 1.12 a 16.77 2.24 b

Standing cropL. uniflora 85 20 a 111 33 a 196 51 aS. nigricans 227 10 c 300 15 b 527 16 cC. nigra 87 5 a 285 25 b 372 29 bC. epigejos 153 12 b 267 32 b 421 43 b

OIKOS 109:2 (2005) 377

dVi

dt�Vi�Gi(N;I) (1)

The net specific growth rate G of both species is a

function of the availability of nitrogen and light, and of

the mortality:

Gi(N;I)�ri�N

hi � N

I

mi � I�di (2)

Here r is the maximal specific growth rate of the species,

hi and mi are half saturation constants for species i, I is

light availability, and di is the mortality rate of plant

tissue for species i. Light availability, in turn, is

determined by the total standing crop of the vegetation,

and is based on the Lambert�/Beer’s law (Huisman and

Weissing 1994):

I�I0�e�k(SVi) (3)

Here k is the light extinction constant for plant biomass,

and is assumed to be the same for both species.

The early successional species is assumed to have a

lower maximum growth rate (r) and half-saturation

constant for nitrogen (h) compared to the late succes-

sional species as indicated by earlier research (Ernst

1991, Adema et al. 2003). The half-saturation constant

for light (m) and the mortality (d) are the same for both

species (Table 2). The model assumes that mortality is

linearly related to species biomass. As a result of

these parameter settings, the low-productive species

will dominate at low nitrogen availability, whereas the

more-productive species will dominate at high nitrogen

availability.

If we ignore additional losses due to enhanced

denitrification, the nitrogen balance is determined by

three fluxes of nitrogen (Eq. 4). The first one is the input

of nitrogen in the system (Nin) through atmospheric

deposition and incoming groundwater (Stuyfzand 1993).

The second flux of nitrogen is the loss of nitrogen from

the system (L) due to water infiltration to deeper

groundwater layers. This is assumed to be a fixed

proportion of the available nitrogen. The third flux of

nitrogen is formed by the net uptake of nitrogen from the

soil by the vegetation that depends on the net growth of

both vegetation types.

dN

dt�Nin�L�N�

Xi

�ci

dVi

dt

�(4)

For the sake of simplicity, we ignore soil organic matter.

This introduced the implicit assumption that the flow of

nitrogen from the vegetation to the organic matter is the

same as the flow to the soil as result of mineralization.

This is not unrealistic for an early successional dune

slack system, as there is almost no accumulating of

organic matter in these early stages of succession

(Lammerts et al. 1995, Grootjans et al. 1998). To

investigate the consequences of this assumption, we

analyzed a model that included the organic matter pools

for both species. This did not affect the principle

behavior of the model, although the predicted transient

dynamics were slightly altered.

Graphical analysis

In conformity with mathematical theory on competition,

we analyzed the dynamics of this model using graphical

methods (Yodzis 1989). The growth of both plant species

is determined by the availability of nitrogen and light.

The direction of change can therefore be analyzed

graphically by depicting the isoclines (at which there is

no change in vegetation biomass) for both species in the

nitrogen�/light plane (Fig. 4). Above its isocline, the

growth of a species is positive, as there is sufficient light

and nitrogen, whereas underneath the isocline, growth is

negative. In equilibrium, both dV1/dt and dV2/dt are

Table 2. Model parameters.

Symbol Interpretation Dimension

V vegetation biomass g m�2

G relative net growth rate yr�1

r maximum relative growth rate yr�1

d relative death rate yr�1

h half saturation constant nitrogenuptake

mg m�2

m half saturation constant light cdD relative denitrification rate m2 g�1 yr�1

N available nitrogen in the soil mg m�2

Nin nitrogen input mg m�2 yr�1

L relative nitrogen loss yr�1

c nitrogen content of the vegetation mg g�1

I light intensity cdk light extinction factor m2 g�1

Iin light input Cd

Fig. 4. Three possible stable equilibria of the basic modeldepending on the available nitrogen. The zero-change isoclinesfrom the low-productive vegetation (solid), high-productivevegetation (long dashed) are depicted. The zero-change isoclinefor available nitrogen (short dashed) is depicted at threedifferent nitrogen input levels (N1, N2, and N3). Solid circlesrepresented stable equilibria. 0- below Nmin (the minimalnitrogen input level) the nitrogen availability is too low tosupport plant growth. V1- At low nitrogen levels between Nmin

and C (the critical nitrogen load) the low-productive vegetationwill be stable. V2 -if the nitrogen availability exceeds C the high-productive vegetation will win the competition.

378 OIKOS 109:2 (2005)

zero. Consequently, from Eq. 4 follows that the system

can only be in balance with regard to nitrogen if the

equilibrium nitrogen concentration N* equals Nin/L,

expressed as a straight vertical line in the nitrogen�/light

plane.

Figure 4 indicates that this model has only one stable

equilibrium, independent of the nitrogen input Nin. If

the nitrogen input is very low, no vegetation can grow, as

nitrogen availability is insufficient (Fig. 4; N�1 ). V1 is able

to invade a bare ecosystem if nitrogen availability

exceeds a minimal value Nmin, defined as G1(Nin/L,

Iin)�/0. The species that obtains the highest biomass i.e.

reduces the light availability to the lowest possible value,

will competitively exclude the other species. Since the

early successional species is a better competitor for

nutrients, this species will dominate at low nitrogen

input levels (Fig. 4; N�2 ). With increasing nitrogen

availability the standing crop of the vegetation increases,

low light availability will favor the competitive abilities

of the late successional species. Hence, above a critical

level denoted as C, the late successional species can

obtain the highest biomass and dominate (Fig. 4; N�3 ).

To summarize, if plant species do not interfere with

the input�/output balance of nitrogen in the ecosystem,

our model predicts that either the early successional

species or the late successional species will dominate.

Independent of the nitrogen input rate, only one stable

equilibrium is found in the system.

Enhanced nitrogen loss

Thus far, the species only differed in their ability to

compete for light and nitrogen. Below, we include

enhanced nitrogen loss caused by the early successional

species, due to its radial oxygen loss. We assume a simple

linear relationship between the biomass of the early

successional species and additional nitrogen loss. Incor-

porating this loss term in Eq. 4 results in:

dN

dt�Nin�L�N�

Xi

�ci

dVi

dt

��V1�D�N (5)

In which D is a denitrification constant. Including

enhanced nitrogen loss due to denitrification around

the roots of the early successional species introduces an

additional effect of the early successional species to the

nitrogen balance. At equilibrium, Eq. 5 reduces to:

N��Nin

L � D � V�1(6)

where the term D�/V�1 introduces a feedback by which

an increased nitrogen input leads to an increased output

of nitrogen from in the system, as a consequence of the

effect of species 1 on the nitrogen balance in the system.

This feedback reduces nitrogen availability relative to a

system without enhance nitrogen losses.

Analyzing the total potential behavior of this two-

species model would require a three dimensional phase-

space. However, in the appendix, we show that any

equilibrium of both plant species is unstable. Therefore,

we do not pursue a graphical approach to understand

the behavior of the system with two species. Rather, we

analyze the boundary conditions for their persistence

against invasion (Grover 1994).

The stability of the N-boundary equilibria can be

analyzed by plotting Eq. 6 in the phase plane for both

boundary equilibria, one containing only the early

successional species (Fig. 5, curved dashed line), and

one only containing the late successional species (Fig. 5,

straight dashed line). At low nitrogen input rates, both

nutrient isoclines are situated to the left of the critical

nitrogen level C (Fig. 5A). Under these circumstances,

the early successional species is able to reduce light

Fig. 5. The zero-change isoclines from the enhanced nitrogenloss model are depicted at three different nitrogen input levels.In all graphs, the solid line represents the early successionalspecies zero-change isocline, the long dashed line the latesuccessional species. The available nitrogen zero-change iso-clines are short dashed. The curved line represents the isoclinein presence of the early successional species. The straight linedepicts the isocline when the late successional species is present.Solid circles represent stable equilibria; open circles representunstable equilibria. The dotted arrows depict different trajec-tories from various initial conditions. The horizontal vectorsdepict the direction of chance of available nitrogen. The verticalvectors depict the direction of chance in the vegetation biomass.(A) At low nitrogen input levels both isoclines from theavailable nitrogen are situated below C. Therefore, only theequilibrium of early successional species is stable againstinvasion by the other. (B) At intermediate nitrogen input levelsboth species equilibria are stable against invasion by the otherspecies since the equilibrium for V1 is below C and theequilibrium for V2 is above C. The gray area marks the initialconditions were both species can win the competition dependingon the initial species composition. (C) At high nitrogen inputlevels both isoclines from the available nitrogen are situatedabove C. Therefore, only the equilibrium of late successionalspecies is stable against invasion by the other.

OIKOS 109:2 (2005) 379

availability to a level at which the late successional

species cannot survive. Hence, the N-boundary equili-

brium of the early successional species is persistent

against invasion, whereas the N-boundary equilibrium

of the late successional species is not persistent against

invasion by the early successional species. Simulations

indicate that for all starting values, the late successional

species was replaced by the early successional species. At

high nitrogen input rates, both nitrogen isoclines are

situated to the right of the critical nitrogen level C. At

these input rates, the late successional species reduces the

light levels to values at which the early successional

species cannot survive. Similar to the former case, the

late successional species replaces the early successional

species for all starting values. For these two cases the

behavior is similar to that of the system without

enhanced nitrogen losses, as described in the previous

paragraph, and the denitrification characteristics of the

early successional species do not influence the outcome

of competition.

A qualitatively different behavior is observed

at intermediate nitrogen input rates. Under these

conditions, the nitrogen isocline associated with the

N-boundary equilibrium of the late successional species

is situated to the right of the critical nitrogen level, C

(Fig. 5B). However, the nitrogen isocline associated with

the boundary equilibrium of the early successional

species intersects with the plant isoclines to the left of

the C position. As a result, both species are superior

competitors at their N-boundary equilibrium. Simula-

tions confirm that contingent competition (Yodzis 1989)

occurs at these conditions, and that the outcome of the

competition depends on the starting values.

The occurrence of contingent competition has impor-

tant consequences for the functioning of the eco-

system. In Fig. 6, we depicted the equilibrium nitrogen

availability in the ecosystem as a function of the

nitrogen-input rate. If vegetation has no influence on

the input-output balance of nitrogen in the ecosystem,

the equilibrium nitrogen availability is determined by the

input rate of nitrogen Nin and the loss rate l: N*�/Nin/L,

depicted in Fig. 6 as the straight line. If N*�/Nmin, the

early successional species can establish in the system,

and at N*�/C, the late successional species is capable of

competitively replacing the early successional species.

As the late successional species does not affect the input-

output balance in the ecosystem, all stable equilibria

with this species are situated on the N*�/Nin/L line

(Fig. 6). By enhancing the nitrogen-loss rate, the early

successional species reduces the nitrogen availability at

equilibrium, and stable equilibria with this species are,

therefore, characterized by a lower equilibrium nitrogen

content (Fig. 6, N*�/Nin/L�/D�/V1).

For an extended range of nitrogen-input rates, con-

tingent competition occurs between the two species, and

hence alternative stable states occur at the ecosystem

level. One state is characterized by the early successional

species, high nitrogen losses and low nitrogen availabil-

ity. The other state harbors the late successional species,

and is characterized by low losses of nitrogen and hence

high nitrogen availability. Note that these states occur at

the same nitrogen input levels.

The existence of two stable states at the level of the

ecosystem has important consequences for successional

development. At intermediate nitrogen input rates, the

development of the system is locked in the early

successional, low-productive state, as early successional

species are the first to establish in the system. Our model

predicts that this state is stable, and hence succession is

arrested. Only following a severe disturbance the system

will develop to the later stage. At high nitrogen input

rates, ROL associated nitrogen losses from the system

are insufficient to lower the nitrogen availability below

the critical level C. As a consequence, the late succes-

sional species is able to invade the system. The system

will eventually move to the state dominated by the late

successional species.

Discussion

Mechanistic explanations of primary succession focus

on direct interactions between plant species to

explain species replacement (Tilman 1988, Connell

1990, Callaway and Walker 1997, Levine 2000). This

Fig. 6. Relation between the nitrogen input and availablenitrogen in the different species. Without plant species therelation between nitrogen input and available nitrogen is astraight line given by N*�/Nin/L. This relation is unaffected ifthe late successional species is present, since the late succes-sional species does not interfere with the nitrogen equilibrium.The straight part of the line depicts the internal stable latesuccessional species persistent against invasion by the earlysuccessional species. Above Nmin, when the early successionalspecies dominates, the relation of nitrogen input and theavailable nitrogen at equilibrium is given by N*�/Nin/L�/D�/

V1. This result in a line that bends away from N*�/Nin/L. Thestraight part of the lower line depicts the internal stable earlysuccessional species persistent against invasion by the latesuccessional species. Note that between the nitrogen-input levelsA and A* both stages are persistent against invasion by theother. The gray arrows depict the development of the ecosystemwhen the system is not in a stable state.

380 OIKOS 109:2 (2005)

study indicates that plant species can affect successional

changes by influencing processes that affect the ecosys-

tem as a whole. We provide experimental evidence that

species typical of low-productive, early successional

stages in wet dune slacks can influence the loss rate of

nitrogen from the ecosystem. Radial oxygen loss from

their roots, a characteristic of these species, was found to

create an oxygen gradient in the soil that stimulates

coupled nitrification�/denitrification. This stimulation

was not only due to spatial heterogeneity in soil oxygen

concentrations but time series measurements provide

that temporal heterogeneity in oxygen can also be

important. Coupled nitrification�/denitrification retards

the accumulation of nitrogen, which is the nutrient

limiting plant growth in dune ecosystems (Olff et al.

1993, Lammerts and Grootjans 1997). As a result,

productivity remains low, which feeds back by favoring

the competitive position of early successional species.

Our model analysis shows that this feedback invokes

alternate stable states on the level of the ecosystem

(Fig. 6). One state is characterized by a high loss rate of

nitrogen from the system, and harbors low-productive,

early successional vegetation, which is characterized by

high biodiversity. The other state is characterized by low

nitrogen losses, leading to high nitrogen availability, and

holds a highly productive stand that contains only a

small number of common species.

Our model results provide a mechanistic explanation

for the findings of Adema et al. (2002) that describe

the co-occurrence of two types of vegetation under

similar conditions in dune slacks. An early successional

stage dominated by Littorella uniflora was found to

exist alongside a later successional stage dominated

by Phragmites australis for more than 60 years. As

neither the substrate nor the hydrological conditions

differed between the two stages, biotic interactions likely

explained the differences in vegetation development. Our

findings confirms the views of Wilson and Agnew (1992)

who state that co-occurrence of different vegetation

types under similar conditions and sharp boundaries

between the vegetation types are outcomes of positive

feedback.

Our study is not the first to point at the interference of

ecosystem processes with successional changes. Van der

Wal et al. 2000 found that early successional species such

as Triglochin maritima (L.) and Puccinellia maritima

(Huds.) Parl. were able to delay succession on salt

marshes by attracting herbivores. Enhanced grazing

increases nutrient losses and prevents accumulation

of a large nutrient pool in the form of litter (Van Wijnen

et al. 1999). This creates conditions to which early

successional species are well adapted. Species that

characterize late successional stages on salt marshes,

such as Elymus pungens (Pers.) are typically avoided

by herbivores. Furthermore, they produce large quan-

tities of litter, stimulating build-up of nutrients in the

system (Van Wijnen and Bakker 1999). This promotes

species adapted to fast growth and competition for

light, as are most species of old salt marshes. The

studies of Van der Wal and Van Wijnen show that

processes that affect the rate of accumulation of

nutrients rather than direct species interactions deter-

mine the rate of successional changes in plant commu-

nities on salt marshes.

We did not measured coupled nitrification�/denitrifi-

cation in situ. However we may assume that the

mechanism is operating in the field because the environ-

mental conditions measured in the field (Adema et al.

2002) are well comparable to the conditions found in the

experiment. The high water table in dune slacks lowers

the penetrating of oxygen in the soil leading to a steep

oxygen gradient in the soil. Moreover, A well developed

microbial mat often occurring in early stages of succes-

sion may even lead to a steeper oxygen gradient by the

use of oxygen by heterotrophic bacteria (Adema et al.

2003). Additionally, excretion of organic matter by

microorganisms from the microbial mat are an extra

organic matter source for denitrifying bacteria (van

Gemerden 1993). The occurrence of early successional

species capable of ROL under this circumstances leads to

a patchy environment with spots with and without

oxygen in the soil ideal for coupled nitrification and

denitrification. Supplementary, diurnal differences in

soil oxygen caused by photosynthetic activity of both

plants and microorganisms may lead to a coupling of

nitrification and denitrification in time as earlier indi-

cated in previous studies (Risgaard-Petersen et al. 1994,

Ottosen et al. 1999). Increased nitrification�/denitrifica-

tion rates were also found in the rhizosphere of Lobelia

dortmanna L. (Risgaard Petersen and Jensen 1997) and

Potamogeton perfoliates L. (Caffrey and Kemp 1992) in

shallow lake sediments. Christensen and Sorensen (1986)

already mentioned increased denitrification rates in the

rhizosphere of Littorella uniflora from in situ cores. They

did not investigate if coupled nitrification�/denitrifica-

tion took place although they already suggest that

oxygen release from the root zone may stimulate

nitrification.

Several alternative mechanisms have been proposed in

the literature that could explain retarded succession.

Stochastic colonization limitation is mechanism that

may retard primary succession as found in Lake

Michigan sand dunes and at Glacier Bay Alaska.

(Chapin et al. 1994, Lichter 1998). However this

mechanism is not likely an alternative for the observed

successional delay in our ecosystem. In wet calcareous

dune slack succession later species are often al ready

present in the vegetation within a few years after the

succession starts (Lammerts et al. 1999, Grootjans et al.

2001). They occur in small numbers with very low

biomass and are not able to suppress the pioneer species.

The successor species may even occur dominantly side by

OIKOS 109:2 (2005) 381

side with the pioneer vegetation in the same dune slack

(Adema et al. 2002).

Another possible feedback mechanism that can cause

alternative stable states would be indirect storage of

nutrient in the accumulation of litter, which increase the

internal nutrient cycle within the ecosystem. (Berendse et

al. 1998). Furthermore, late successional species may be

more efficient in retaining nutrients (Ernst et al. 1996).

However, since radial oxygen loss not only leads to

enhanced nitrogen loss but also stimulates the decom-

position of organic matter this may decrease the effec-

tiveness of the strategy, preventing dominance by late

successional species in pioneer vegetation.

Implications for conservation of early successional

vegetation

Atmospheric nitrogen input in the dune area has

increased significantly in the past decades (Stuyfzand

1993). Moreover, the dune areas are extensively used for

the extraction of drinking water (Van Dijk and Groot-

jans 1993), which has significantly reduced the height of

the water table in dune slacks. This has been accom-

panied by a spectacular decline in the abundance of early

successional vegetation, containing many rare and

endangered species, in the last decades (Van Dorp

et al. 1985).

The consequences of these two disturbing agents,

increased atmospheric deposition and lowering of the

water table on the stability of early successional stages in

dune slacks can be illustrated using a marble-and-cup

diagram (Scheffer 1990). In undisturbed conditions with

low atmospheric deposition and high water tables, the

feedback between enhanced nitrogen losses and de-

creased productivity stabilizes low-productive vegeta-

tion, and hence locks successional development in an

early stage. Under such conditions, we find two stable

states in the system, illustrated by two valleys in the

stability landscape (Fig. 7A). When atmospheric deposi-

tion increases, or the water table is reduced slightly, the

feedback is insufficient to stabilize the early successional

vegetation, and only the late successional state is stable

(Fig. 7B). However, feedback processes may still delay

succession and hence expand the life span of early

successional stages. If hydrological conditions in the

dune slack deteriorate further a very rapid succession

towards the climax vegetation is expected (Fig. 7C). It is

easy to see that management policies that focus on

improving the competitive balance between early and

late successional species, for instance by mowing,

are tackling the symptoms of a change of ecosystem

properties of dune slacks. This will require a continued

management effort, hence is not a very effective means of

conserving high-biodiversity vegetation types. Improving

the conditions for ecosystem processes, such as restoring

the hydrological regime or reducing of the nitrogen

input, that stabilize early successional stages is likely to

be more successful. For this, a thorough understanding

of the interaction between plant competition and

ecosystem processes is imperative.

Acknowledgements �/ The authors would like to thank Prof.Dr. R. L. Jefferies, Prof. Dr. J. van Andel, Dr. P. van Bodegomand Dr. H. van Gemerden for their comments on earlierversions of the manuscript. Many thanks for Henk Jansenand Bert Kers for assisting by the isotope analyses.

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Appendix

Before stability analyses the model is re-scaled for parameter reduction. After re-scaling the vegetation state variables

are expressed in units nitrogen. The superscript * indicates that the matrices are evaluated at equilibrium.

Stability without species

Parameter values: V�1�V�2�0; N��Nin

L; I��Iin

The equilibrium without plants is stable when at equilibrium the growth of both species is negative:

G�i (N�; I�)50[N5dihi(Iin � mi)

riIin � di(Iin � mi)

Stability of the monocultures

In order to establish the internal local stability of the equilibrium of the monocultures we investigated the Jacobian

matrix of the system.

In equilibrium the values of the model state variables are:

early successional species: late successional species:

V�1�0; V�2�0; N��Nin

L � DV�1; I��Iine-k1�V�1 V1��0; V�2�0; N��

Nin

L; I��Iine�k2�V�2

The jacobians are given by:

J1��V�1 k1I�

@G1

@IV�1

@G1

@N

�a11�DN� �a12�Nin

N�

26664

37775 J2�

�V�2 k2I�@G2

@IV�2

@G2

@N

�a11 �a12�Nin

N�

26664

37775

Given that:

@Gi

@I�

ri

I � mi

N

N � hi

�riI

(I � m2)2

N

N � hi

�0[1�I

I � mi

�0

and:

@Gi

@N�

ri

N � hi

I

I � mi

�riN

(N � hi)2

I

I � mi

�0[1�N

N � hi

�0

both monocultures are internal stable since both stability criteria are met; Trace JIB/0 and Det JI�/0 (Edelstein-

Keshet 1988). Moreover, the monocultures are stable against invasion by the other species as long:

384 OIKOS 109:2 (2005)

early successional species: late successional species:

G2

�Nin

L � DV�1; Iine�k1V1

�50 G2

�Nin

L � DV�1; Iine�k1V1

�50

In the coexistence equilibrium the values of the model state variables are:

V�1�0; V�2�0; N��Nin

L � DV�1; I��Iine�

PkiV�i

The jacobian is given by:

Jv�

�V�1 k1I�@G1

@I�V�1 k2I�

@G1

@IV�1

@G1

@N

�V�2 k1I�@G2

@I�V�2 k2I�

@G2

@IV�2

@G2

@N

�a11�a21�DN� �a12�a22 �a13�a23�Nin

N�

2666666664

3777777775

According to the Routh-Hurwitz criteria (Edelstein-Keshet 1988) stability requires: (1) A1�/0, (2) A3�/0,

(3) A1A2�/A3�/0 were;

A1��a11�a22�a33

A2�a11a22�a11a33�a22a33�a21a21�a23a32�a13a31

A3��a11a22a33�a11a23a32�a22a31a13�a33a12a21�a12a31a23�a13a21a32

Stability criterion (1) is fulfilled since:

a11,a22 and a33 are negative A1�/0

Stability criterion (2) is not fulfilled since:

A3�/DN(a12a23�/a22a13)�/N*(h1�/h2)�/I*(m2�/m1)�/I*N*(m2h1�/m1h2�/I*(h1�/h2)�/N*(m2�/m1))

h1B/h2 because V1 is a better competitor for nitrogen

m1�/m2 because V2 is a better competitor for light

Therefore A3 alwaysB/0

Therefore we conclude that the coexistence equilibrium is never local stable in our model system.

Stability of the coexistence equilibrium

Calculation of the critical nitrogen level C

The former paragraph showed that the coexistence equilibrium is not stable. This equilibrium lies on the critical

nitrogen availability content that determined the dominant species. Therefore we can calculate C by solving

G1(N; I)�G2(N; I)�0:

We can eliminate I from the equation. We then retrieve:

d1m(N � h1)

r1N � d1N � d1h1

�d2m2

(N � h2)

r2N � d2N � d2h2

This equation can be rewritten in the form aN2�bN�c�0

With

a�d1m1(r2�d2)�d2m2(r1�d1)

b�d1m1(h1(r2-d2)�d2h2)�d2m2(h2(r1�d1)�d1h1)

c��d1d2h1h2(m1�m2)

This quadric equation can be solved with:

OIKOS 109:2 (2005) 385

N(1;2)��b 9

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffib2 � 4ac

p2a

In our case we can simplify the equation even further because:

/d�d1�d2 m�m1�m2 h1Bh2 r1Br2

Then: Resulting in:

a�dm(r2�r1)

b�dm(h1r2�h2r1) N1;2��b 9 b

2a�

�0;

2(h2r1 � h1r2)

(r1 � r2)

�

c�0

386 OIKOS 109:2 (2005)