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Journal of
Ecology 2001
89, 1033 – 1040
Control of environmental variables on species density in
fens and meadows: importance of direct effects and
effects through community biomass
Blackwell Science, Ltd
H. OLDE VENTERINK 1, M. J. WASSEN, J. D. M. BELGERS 2 and
J. T. A. VERHOEVEN*
Utrecht University, Environmental Sciences, PO Box 80115, 3508 TC Utrecht, the Netherlands,
*Utrecht University, Geobiology, PO Box 80084, 3508 TB Utrecht, the Netherlands
Summary
1 We tested whether patterns of species density are controlled not only by variations in
community biomass but also by variations in environmental conditions, which may
be related or unrelated to community biomass. Environmental variables (soil characteristics, acidity, water regime, nutrient availabilities) were measured in 46 sites in
wet meadows and fens, and related to above-ground biomass and to densities of all
vascular plants and of threatened species.
2 Both meadows and fens showed a hump-backed species density–biomass relationship, although there was much variability and the study did not include very highly productive sites. In fens a significant quadratic relationship was observed (R2 = 0.42).
3 Environmental factors could explain 57% (in meadows) and 40% (in fens) of variation in species density. The majority of the variance explained was attributable to factors that were not related to community biomass (increasing pH in meadows) or the
organic soil–mineral soil gradient in fens.
4 Density of threatened species vs. biomass was also consistent with a hump-back curve
covering a narrow biomass range. Density of threatened species increased with decreasing P availability, regardless of whether P availability was related to biomass (as in
meadows) or not (fens).
Key-words: acidity, hydrology, mineralization, nutrient availability, productivity, species richness, species pool, wetland vegetation
Journal of Ecology (2001) 89, 1033–1040
Introduction
Explaining species density is of widespread interest
among ecologists, especially because of concern about
the world-wide loss of biodiversity. The relationship
between species density and community biomass has
been studied extensively (see Grace 1999; Waide et al.
1999; for recent reviews) with the conclusion that a
hump-back relationship between species density and
biomass (cf. Grime 1979) may be general, with this
curve encompassing all possible combinations of species density and biomass. This means that biomass
alone could explain (1) maximum species density and
(2) absence of high species density at very low and very
© 2001 British
Ecological Society
Correspondence: H. Olde Venterink (fax + 31–15–2122921;
e-mail [email protected]).
Present addresses: 1IHE, Wetland Ecosystems, PO Box 3015,
2601 DA Delft, the Netherlands and 2Alterra, Ecotoxicology,
PO Box 47, 6700 AA Wageningen, the Netherlands.
high biomass values. However, several studies revealed
that the hump-back curve was only observed when a
broad range of vegetation types was compared, and
biomass was a poor predictor of species density within
a more limited range (Moore & Keddy 1989; Wheeler
& Shaw 1991; Guo & Berry 1998).
A conceptual model has been developed from
Grime’s proposals (cf. Gough et al. 1994; Grace 1999)
in which species density is controlled by environmental
conditions indirectly via community biomass which
subsequently affects species density, and directly by
determining the number of species physiologically
capable of living at a site. Application of this model in
coastal wetlands showed that environmental conditions per se, exerting control on the species pool, were
equally important or better predictors of species density than community biomass. In particular, salinity
and flooding could explain a large part of variation in
species density (Gough et al. 1994; Grace & Pugesek
1997; Grace & Jutila 1999).
JEC616.fm Page 1034 Wednesday, November 21, 2001 9:19 AM
1034
H. Olde Venterink
et al.
We applied the conceptual model of Gough and
Grace to inland freshwater wetlands (wet meadows
and fens), where there is less flooding stress, to determine whether direct environmental influence on species density is also important in these systems and, if
so, which environmental conditions are in control. We
focus on the role of nutrient availability, as this may
influence species density directly as well as via community biomass.
A second aim was to investigate whether the occurrence of threatened species was controlled by the same
mechanisms as overall species density. Although the
loss of species in European wetlands is often associated
with eutrophication, i.e. increased nutrient availability and consequent biomass increase (e.g. Stanners
& Bourdeau 1995), different aspects may vary in their
response to other factors.
We measured soil characteristics, above-ground biomass and densities of species and threatened species at
46 sites in wet meadows and fens in the Netherlands
and Belgium to test our hypothesis that variation in
species density is controlled both directly and indirectly by environmental factors, whereas variation in
density of threatened species is controlled primarily via
effects on biomass. We therefore predicted that regressions would show that variation in species density is at
least partly explained by environmental factors that do
not contribute to variation in community biomass.
or Valeriano-Filipenduletum dominated by Glyceria
maxima (Stortelder et al. 1999). Fens were classified as
Caricion nigrae, Carici curtae-Agrostietum caninae or
Caricion gracilis. (Schaminée et al. 1995). Meadows
and fens also differed in their hydrology, with fens
being were constantly wet, whereas meadows were
generally dryer and subject to a more dynamic water
regime (Table 1) (cf. Mitsch et al. 1994).
The number of threatened species was determined
according to the ‘red list’ of threatened species for the
Netherlands (van der Meijden et al. 1991), including
only those that had disappeared in at least 25% of map
units (25 km2) compared to a historical reference.

Above-ground biomass of the vegetation (standing living and standing dead) was harvested at the peak of the
growing season (17–21 July 1995). Within every 4 m2
site, vegetation in three quadrats (50 × 50 cm) vegetation was cut near the soil surface, and bryophytes
were also collected. Samples from the three quadrats
were combined and sorted into graminoids, herbs and
bryophytes. The samples were dried for 48 h at 70 °C
and weighed. Soil litter was not collected, but was not
a large fraction because of the annual mowing and
removal of hay.
 
Methods
 
© 2001 British
Ecological Society,
Journal of Ecology,
89, 1033 – 1040
The 46 sites (4 m2) in meadows and fens were located in
seven nature reserves along the river Dommel (The
Netherlands) and in three reserves along the Zwarte
Beek (Belgium) (5°15′–5°40′E and 51°05′–51°45′N).
Five of the Dutch nature reserves were surrounded
by heavily fertilized agricultural land and the other
reserves by forest or extensively used meadows. All
sites are subject to annual hay-making but are not
fertilized.
Species composition was recorded at all sites in June
1995 by means of the Braun Blanquet method, i.e. one
4 m2 recording per site. Bryophytes, which were not
recorded at all sites, are not included in species density.
Only 0 –3 bryophyte species occurred at our sites compared with 8 – 43 vascular plant species, and species
density vs. biomass or environmental variables relationships have been shown to be very similar for total
species density and density of vascular plants (Pollock
et al. 1998), suggesting that this omission is not critical.
To enable comparison with other studies we grouped
the sites into four types of wet meadows and three
types of fens on the basis of vegetation composition (Table 1), clustered by means of Flexclus (van
Tongeren 1986). The meadows were classified as JuncoMolinion, Calthion palustris, a degraded Calthion
dominated by Holcus lanatus (Schaminée et al. 1996),
Net N mineralization was measured at every site by in
situ soil incubation (without within site replication)
between 1 May 1995 and 1 May 1996. We followed the
incubation technique as described in detail by Olff
et al. (1994). Soil cores were incubated during five
periods of 8 weeks and one winter period of 12 weeks.
At the start of every period, paired soil cores (10-cm
depth, 4.8-cm diameter) were taken at 1–5 cm from
each other, with PVC tubes. One of the paired tubes
was incubated and the other transported to the laboratory and stored overnight at 2 °C before soil extraction. Soil extractable N was determined using 1  KCl
(Olff et al. 1994) and after centrifugation, NO3– and
NH4+ concentrations were measured colorimetrically
with a continuous flow analyser. Net N mineralization
was calculated by subtracting soil extractable NO3– and
NH4+ in the initial soil cores from that in the incubated
cores. Values per unit area were calculated from values
per unit dry soil and the average bulk density of the top
10 cm soil layer.
Although soil extractable pool indices for P and K
provide no information on flow rates, they reflect P and
K availability for plants better than release rates measured by means of soil incubation techniques (cf. Jungk
& Claassen 1986; Walbridge 1991; Olde Venterink
2000). Soil extractable K was determined in all initial soil cores of the mineralization experiment using
1  HCl (Jungk & Claassen 1986; Scheffer & Schachtschabel 1989) and extractable P using ammonium
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Table
1035 1 Environmental, biomass and species density characteristics of the study sites, as averaged ( ± SD) for the major types of meadows and fens. Soil
variables
were
measured in the top 10 cm soil layer. Two meadow sites could not be classified into one of the vegetation types
Direct and
indirect
environmental
control on
species density
Meadows
Fens
Number of sites:
JuncoMolinion
8
Calthion
palustris
7
Holcus
community
6
ValerianoFilipenduletum
9
Caricion
nigrae
6
Carici curtae
Agrostietum
3
Caricion
gracilis
5
Environmental variables
Bulk density (g cm–3)
Organic matter (%)
Clay content (%)
pH-H2O
Extractable Al (g m–2)
Extractable Fe (g m–2)
Extractable Ca (g m–2)
Extractable K (g m–2)
Extractable P (g m–2)
N mineralization (g m–2 y–1)
Summer moisture content (%)
Soil moisture dynamics (%)
Spring water level (cm-surf.)
Water level dynamics (cm)
Number of flooded sites
Flood /inundation depth (cm)
0.48 ± 0.32
35 ± 25
6±3
5.6 ± 0.8
21 ± 17
35 ± 10
79 ± 61
7.2 ± 0.6
1.3 ± 0.5
2.9 ± 1.8
49 ± 20
15 ± 8
40 ± 15
73 ± 21
0
0
0.20 ± 0.02
63 ± 4
9±4
5.6 ± 0.2
19 ± 3
55 ± 11
107 ± 24
8.2 ± 0.5
2.0 ± 0.6
4.5 ± 3.7
66 ± 6
15 ± 5
23 ± 9
73 ± 9
7
5±2
0.58 ± 0.14
23 ± 4
6±1
5.7 ± 0.2
35 ± 7
118 ± 39
87 ± 25
7.2 ± 2.1
2.7 ± 0.4
10.8 ± 5.8
41 ± 18
15 ± 10
35 ± 26
68 ± 21
1
2±4
0.52 ± 0.11
29 ± 7
14 ± 3
5.1 ± 0.4
34 ± 6
94 ± 15
70 ± 16
8.9 ± 2.0
4.1 ± 1.7
13.3 ± 4.4
37 ± 10
25 ± 6
29 ± 7
88 ±
9
16 ± 6
0.32 ± 0.06
38 ± 7
11 ± 8
5.9 ± 0.2
21 ± 13
251 ± 190
70 ± 28
5.3 ± 1.7
2.9 ± 1.7
1.9 ± 2.2
69 ± 6
6±3
7±4
47 ± 16
1
2±4
0.28 ± 0.12
43 ± 17
12 ± 11
5.5 ± 0.5
26 ± 15
71 ± 13
72 ± 50
5.7 ± 0.8
2.4 ± 1.3
4.3 ± 2.3
69 ± 10
5±3
11 ± 1
59 ± 6
1
2±3
0.30 ± 0.12
40 ± 13
6±2
5.7 ± 0.2
25 ± 16
139 ± 124
72 ± 9
7.7 ± 2.0
2.8 ± 1.3
5.8 ± 2.2
69 ± 11
7±5
5±5
60 ± 16
2
4±5
Above-ground biomass (g m–2 )
Vascular plants
Graminoids
Herbs
Bryophytes
Total standing crop
352 ± 67
274 ± 66
78 ± 81
131 ± 102
483 ± 115
479 ± 112
376 ± 66
103 ± 62
24 ± 20
503 ± 111
581 ± 173
541 ± 165
40 ± 38
5±4
586 ± 173
915 ± 168
802 ± 138
113 ± 85
3±3
918 ± 168
339 ± 81
279 ± 92
60 ± 31
53 ± 53
392 ± 81
584 ± 63
512 ± 73
73 ± 54
10 ± 11
594 ± 73
902 ± 132
801 ± 206
101 ± 141
16 ± 16
918 ± 131
Species density (no. 4 m–2)
Vascular plants
Threatened species
25 ± 11
1.4 ± 1.8
25 ± 5
0.6 ± 0.5
23 ± 2
0
17 ± 4
0
23 ± 5
0.5 ± 0.6
26 ± 6
0
22 ± 7
0
© 2001 British
Ecological Society,
Journal of Ecology,
89, 1033 – 1040
acetic-acid lactic-acid (Scheffer & Schachtschabel
1989; Koerselman et al. 1993). Concentrations of K
and P (and also Ca, Fe, and Al) were determined by
inductively coupled plasma atomic emission spectrometry (ICP-AES), after centrifuging the extracts. Seven
measurements over time were made for each element
at every site: no temporal trends were observed and
average values were calculated.
Most soil characteristics were also determined in the
initial soil cores for the mineralization experiment. Soil
moisture content was determined by measuring loss of
weight of the top 10 cm soil after 48 h in a drying oven
at 105 °C. Summer moisture content was measured at
the end of August 1995. ‘Moisture content dynamics’
was represented by the difference between the highest
and lowest of the seven values over the year. Bulk density was determined from the fresh weight of the cores
and the moisture content. Organic matter content was
measured by loss on ignition at 550 °C. Average bulk
density and organic matter values were calculated from
all initial mineralization cores of a site. Clay contents of
the top 10-cm soil layer (fraction < 2 µm) were determined by sieving dried and mixed subsamples (n = 5),
taken at every site in November 1995.
Acidity was measured in soil moisture derived from
the top 10-cm soil, by means of Rhizon soil moisture
samplers (Eijkelkamp Agrisearch Equipment, Gies-
beek, the Netherlands). The average acidity values of
eight soil moisture samples, taken throughout the year,
were used.
Groundwater levels were measured at regular intervals (14 times) between August 1995 and September
1996, in piezometres at a depth of 0.8–1.2 m below the
surface. Spring water level was taken to be the average
value for the months February–April 1996 and water
level dynamics to be the difference between the highest
and lowest values. Some sites were flooded in spring
1995 for about a week and the flood depth was then
measured.

The statistical procedure was based on Verhoeven et al.
(1996a) and Bridgham et al. (1998). A PCA (with varimax rotation) was performed to reduce the number of
autocorrelated environmental variables, all variables
were standardized to a Z-distribution and multiplied
by the factor coefficients to produce factor scores for
each sample and non-normal distributed variables
were log-transformed. Stepwise multiple regressions
were then carried out for biomass and species richness
variables using factor scores of the PCA as explanatory
variables. Using regressions, instead of correlations,
means that we explicitly assumed that variance in the y
JEC616.fm Page 1036 Wednesday, November 21, 2001 9:19 AM
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H. Olde Venterink
et al.
direction (species density or biomass) was dependent
of variance in PCA score, and not vice versa.
Results
Values of all environmental, biomass and species
density variables, as averaged for the major vegetation
types (groups of sites with a comparable vegetation),
are shown in Table 1.
  . 
Species density in the meadows (or in the whole set)
was neither significantly related to biomass of vascular
plants, nor to total standing crop (Fig. 1a,b). For the
fens, a significant quadratic relationship was observed
between species density and total standing crop (P =
0.049, R2 = 0.42). Threatened species only occurred at
sites with a relatively low biomass of vascular plants
(Fig. 1c,d) and there was a significant negative inverse
relationship for meadows (and whole set) between their
number and biomass of vascular plants (P = 0.015), but
not with total standing crop (P = 0.22). The explained
variance was, however, weak (R2 = 0.15, 0.18, 0.28 for
whole set, meadows and fens, respectively).
    .
 
A principal component analysis of the environmental
variables of Table 1 resulted in four factors for mead-
© 2001 British
Ecological Society,
Journal of Ecology,
89, 1033 – 1040
ows and three factors for fens (Table 2), with total
explained variance 77% and 74% for meadows and
fens, respectively.
For meadows, the first factor was positively related
to bulk density, extractable Al, and N mineralization,
and negatively to organic matter and soil moisture
(Table 2). This factor can be interpreted as representing the mineral soil–peat gradient, with higher N mineralization rates at the mineral soils. The second factor,
which was positively related to flood depth, soil clay
content, N mineralization and extractable P and Fe,
represents differences in flooding, which is associated
with higher N and P availabilities for plants at the
flooded sites. The third factor, negatively related to
acidity and extractable Ca, and positively related to
extractable K and Al, represents the acidity gradient
that was associated with a higher K availability for
plants at the relatively acid sites. The fourth factor
represents water regime dynamics, as it is positively
related to annual dynamics of both water level and
soil moisture.
For fens, as for meadows, the first factor was positively related to bulk density and negatively related to
organic matter and soil moisture, but was also positively related to extractable Fe, Al and P (Table 2). The
second factor, positively related to extractable Ca and
clay content, and negatively to extractable P and Al,
represents P availability and associated chemical complexes. The third factor represented the gradient from
hydrological stable fens with low N and K availabilities on the one hand to hydrological dynamic fens with
Fig. 1 Density of vascular plant species and threatened species vs. above-ground biomass of vascular plants (standing living and
dead) or total standing crop (including bryophytes) in meadows (s) and fens (d). Threatened species are from the ‘red list’ of
plant species in The Netherlands (van der Meijden et al. 1991).
JEC616.fm Page 1037 Wednesday, November 21, 2001 9:19 AM
1037
Direct and indirect
environmental
control on
species density
Table 2 Principal component analysis of environmental variables, including nutrient availability, for meadows (n = 32) and fens
(n = 14). Only correlations < – 0.5 and > 0.5 are shown
Meadows
Factor 1
Bulk density
Organic matter content
Soil moisture in summer
Extractable Al
N mineralization
Flood depth
Extractable Fe
Extractable P pool
Clay content
Extractable Ca
pH
Extractable K
Soil moisture dynamics
Water level dynamics
Water level in spring
Variance explained (%)
0.97
– 0.95
– 0.88
0.54
0.57
Fens
Factor 2
Factor 3
Factor 4
0.55
0.52
0.81
0.79
0.78
0.69
Factor 1
Factor 2
0.96
– 0.93
– 0.80
0.51
–0.59
0.76
0.74
0.54
–0.78
0.80
0.89
– 0.87
– 0.90
0.74
–0.70
0.70
0.51
0.80
0.72
0.71
35
Factor 3
19
13
10
35
24
15
Table 3 Stepwise multiple regression of above-ground biomass and species density variables vs. PCA factors of Table 2, for
meadows (n = 32) and fens (n = 14)
Meadows
Above-ground biomass
Vascular plants
Step 1
Step 2
Graminoids
Step 1
SteP 2
Herbs
Step 1
Bryophytes
Step 1
Step 2
Total standing crop
Step 1
Step 2
Step 3
Species density
Vascular plants
Step 1
Step 2
Threatened species
Step 1
Fens
Entered
variables
R2
F
P
Entered
variables
R2
F
Factor 2
Factor 1
0.44
0.54
23.50
6.34
< 0.001
0.018
0.66
0.32
Factor 3
0.51
12.57
0.004
0.72
Factor 2
Factor 1
0.52
0.61
32.79
6.85
< 0.001
0.014
0.72
0.30
Factor 3
0.43
9.20
0.010
0.66
Factor 4
0.12
4.20
0.049
0.35
Factor 2
Factor 1
0.59
0.66
42.36
6.27
< 0.001
0.018
–0.77
–0.27
Factor 3
0.41
8.20
0.014
–0.64
Factor 2
Factor 4
Factor 1
0.23
0.36
0.46
9.16
5.51
5.36
0.005
0.026
0.028
0.48
0.35
0.32
Factor 3
0.42
8.61
0.013
0.65
Factor 3
Factor 2
0.40
0.57
19.75
11.88
< 0.001
0.002
–0.63
–0.42
Factor 1
0.39
7.81
0.016
0.63
Factor 2
0.27
10.83
0.003
–0.52
Factor 2
0.41
8.40
0.013
0.64
SC
SC
P
> 0.1
R2 are cumulative values per step, F and P show significant change per step, standardized coefficients (SC) are shown for the
final step.
© 2001 British
Ecological Society,
Journal of Ecology,
89, 1033 – 1040
relatively high N and K availabilities on the other. The
stable fens also had a slightly lower pH (cf. Table 1
for differences in pH).
Slightly more than half of the variance in biomass of
vascular plants was explained by PCA factors, in both
meadows and fens (Table 3). In meadows, factors 2 and
1, which represented N and P availabilities as well as
flooding and bulk density, explained 54% of biomass of
vascular plants. In fens, factor 3, which represented
both hydrological and acidity variation and differences
in N and K availabilities, explained 51% of vascular
plant biomass. In both meadows and fens, the same
factors explained the biomass of vascular plants,
graminoids and (in the reverse direction) bryophytes.
The total above-ground biomass of plants was generally related to the same PCA factors but the variance
JEC616.fm Page 1038 Wednesday, November 21, 2001 9:19 AM
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H. Olde Venterink
et al.
explained was less, due to the opposite influence on
graminoids and bryophytes. Little of the variation in
herb biomass could be explained by the PCA factors.
Variation in vascular plant species density was
explained by other PCA factors than those related to
their biomass (Table 3). In meadows, 40% of the variance in species density was explained by factor 3 (acidity and K availability) and only an additional 17% by
the ‘biomass-related’ factor 2 (flooding, N and P availability). In fens, 39% of variance in species density was
explained by factor 1 (bulk density, P availability), a
factor not related to biomass.
Density of threatened species, in both meadows and
fens, was related to factors other than those related to
species density in general. Density of threatened species decreased with the ‘biomass-related’ factor 2 in
meadows and with fen factor 2 (P availability), which
was neither related to biomass nor to species density in
general (Table 2).
All statistical analyses were repeated for fens and
meadows combined, but this did not provide new
insights. The PCA for the entire data set was similar
to that for meadows, although hydrological variables
became more differentiating. The multiple regressions also yielded the same explanatory variables as
for meadows only, but less variance was explained.
Meadows were the dominant subset because of the
greater number of sites and the wider range seen in
most variables (Table 1).
Discussion
© 2001 British
Ecological Society,
Journal of Ecology,
89, 1033 – 1040
Our results were consistent with a hump-back relationship between species and biomass (Grime 1979), given
that species density is zero at zero biomass, and we had
no very high biomass sites (cf. Vasander 1982; Moore &
Keddy 1989; Wheeler & Shaw 1991). Most of our
meadows and fens fell in the biomass range where species density is potentially high. The hump-back curve
derives from the effects of nutrient stress and competitive exclusion on species density but the species pool,
via factors such as niche differentiation, may affect the
height of the peak and variation under the curve (cf.
Grime 1979; Grace 1999). Near the peak (as for most
of our sites) species density should therefore be sensitive to direct effects of environmental variables. Much
variation (40%) in species density could indeed be
explained by direct environmental effects rather than
by environmental factors that influence biomass.
Biomass, particularly of graminoids, increased with
increasing N mineralization in both meadows and fens,
and with extractable P or extractable K in meadows
and fens, respectively (Tables 2 and 3; bivariate regressions, P < 0.05, R2 values 0.32–0.43). This result is consistent with N, P and K as the major growth-limiting
nutrients in herbaceous wetlands (Verhoeven et al.
1996b; Olde Venterink et al. 2001). Biomass related
factors might explain 17% of variance in species density in the meadows (Table 3), although even this might
simply reflect increased N and P availabilities (as wells
as biomass) with increasing flooding depth (Table 2).
Flooding was an important explanatory factor for
species density in coastal wetlands, through its effect
on the size of the potential species pool (Gough et al.
1994; Grace & Pugesek 1997; Grace & Jutila 1999).
Although the flooding in coastal wetlands imposes
much more stress than on our sites where it is restricted
to a few weeks in winter or spring, it may be important
for species density in freshwater wetlands (Day et al.
1988; Pollock et al. 1998).
The PCA factor that explained 40% of species density in meadows was primarily related to soil acidity.
Bivariate regressions showed that, of the variables
related to this factor, pH (+, R2 = 0.50) and extractable
Al (–, R2 = 0.45) were the best predictors of species
density. Grime (1979) found a similar strong increase of
species density with increasing pH in English grasslands and Gough et al. (2000) in Arctic tundra, suggesting an effect of acidity on the potential species
pool. When European plant species of wet meadow or
comparable habitats are sorted according to their habitat preferences for acidity (cf. Ellenberg et al. 1991),
it is clear that a much larger proportion is adapted
to slightly acid to base-rich soils (R7-R8) than to acid
soils (R < 4) (Fig. 2). This suggests that here too, acidity effects on density may be acting via species pool
(cf. Pärtel et al. 1996; Zobel 1997). The negative correlation with extractable Al suggests that aluminium
toxicity at a low pH contributes to the relatively low
number of species adapted to a low pH.
Although in fens 42% of variation in species density
was explained via biomass, a further 39% could be
explained by environmental factors not related to biomass (Table 3). The lack of an acidity effect in this habitat was probably due to the narrow pH range (Table 1),
with species density increasing instead from relatively
Fig. 2 Distribution of Ellenberg indication values for acidity
(R: 1, extremely acid to 9, alkaline; × indifferent) for all
European plant species from fen, meadow or comparable
habitats (i.e. species of non-shaded (L > 5), non-saline
(S < 3), and wet to moist terrestrial ecosystems (F5-10), which
are not restricted to alpine or warm areas (T4-6); cf. Ellenberg
et al. 1991).
JEC616.fm Page 1039 Wednesday, November 21, 2001 9:19 AM
1039
Direct and indirect
environmental
control on
species density
© 2001 British
Ecological Society,
Journal of Ecology,
89, 1033 – 1040
wet organic soils to dryer, relatively mineral-rich soils
(Table 3). Grace & Pugesek (1997) also observed a
negative relationship between species density and soil
organic content in American coastal wetlands, and
ascribed this relationship to a species pool effect: fewer
species may be adapted to waterlogged peat-forming
conditions than to aerated soils (cf. Silvertown et al.
1999).
We did not measure potential species pool sizes in
our geographically separated sites but it is likely that
these mediate the direct influence of environmental
factors on species density in our sites, as in other grasslands and wetlands (e.g. Grime 1979; Gough et al.
1994; Grace & Pugesek 1997; Grace & Jutila 1999).
However, other explanations, such as position within
the landscape or historical effects (Grace & Guntenspergen 1999), which could lead to correlations
between environmental factors and species density,
cannot be ruled out.
About half of the variance in overall species density
remained unexplained by PCA factors. Factors such
as disturbance, seed bank size and seed dispersal,
sampling errors, light, plant density, soil ecosystem
composition and small-scale heterogeneity (Grace
1999) may be involved at our sites. Heterogeneity was
also likely to have been a major factor for the unexplained biomass variance, given the lack of within-site
replication in measurements of environmental variables as mineralization rates.
A second aim of this study was to find out whether
the occurrence of threatened species was controlled by
the same mechanism as overall species density. Moore
et al. (1989) and Wheeler & Shaw (1991) showed that
the hump-back curves for species density in Canadian
and British wetlands, were narrower when only rare
species were considered. The narrow envelope at low
biomass seen for our threatened species was more
marked for vascular biomass than for total standing
crop (Fig. 1). This suggests that competition from
more productive vascular plants (graminoids), which
can benefit from increased anthropogenic nutrient
sources (e.g. atmospheric N deposition), is crucial.
In meadows, density of threatened species was negatively related to the biomass-related factor 2 (Table 3)
and, in particular, to P availability (bivariate regressions, P = 0.001, R2 = 0.31). A similar effect of P availability was seen in fens, although it was no longer
related to biomass (Table 3). Many threatened European wetland species occur in P-limited conditions
(Olde Venterink 2000), but there is large-scale disappearance of P-limited low productive wetlands in
Western Europe (e.g. seepage fens; Boyer & Wheeler
1989; Wassen et al. 1996). We therefore conclude that
although maintaining relatively low biomass of vascular plants (500 –600 g m–2) is essential for conservation
of threatened species (Fig. 1c), the importance of P
availability for threatened species and of environmental variables, such as acidity, for species density in
general means that practices such as haymaking do
not, by themselves, guarantee high species richness.
Management to maintain threatened species might
also need to consider reducing P availability, for
example, by liming or sod-cutting.
Acknowledgements
We thank N. Pieterse, A. de Hamer and W. Peeters
for their help in the field and laboratory, as well as
P. de Ruiter, N. Pieterse, P. Denny, J. Grace, A. Davy,
L. Haddon and an anonymous referee for their helpful comments to improve the manuscript. AMINAL
Ekologisch Impulsgebied Zwarte Beek, Belgian Ministry of Defence, Staatsbosbeheer, Natuurmonumenten,
and the city of Eindhoven are acknowledged for permission to carry out measurements and experiments in
their nature reserves. We thank the local staff of these
organizations for logistical support.
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