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RESEARCH ARTICLE
Green hay application and diverse seeding approaches
to restore grazed lowland meadows: progress after
4 years and effects of a flood risk gradient
Markus Wagner1,2 , Lucy Hulmes1, Sarah Hulmes1, Marek Nowakowski3, John W. Redhead1,
Richard F. Pywell1
The two most common approaches to target species introduction in European meadow restoration are green-hay transfer from
species-rich donor sites and the use of diverse seed mixtures reflecting the chosen target community. The potential of both
approaches to restore species-rich grassland has been variously reviewed, but very few studies have experimentally compared
them at one and the same site. Moreover, studies involving one or both approaches have rarely taken into account environmental
gradients at a site, and measured the impacts of such gradients on restoration outcomes. Such gradients do, for example, exist
during grassland restoration on former arable land in river floodplains, where gradients in the occurrence of flooding, and in
associated edaphic characteristics such as nutrient availability, might affect restoration outcomes. Using a randomized complete
block experimental design, based on five different indicators of restoration progress, we compared the usefulness of green-hay
application and diverse seeding to restore species-rich grazed meadows of the MG5 grassland type according to the British
National Vegetation Classification, and also investigated how restoration outcomes differed after 4 years between areas within
experimental plots characterized by high flood risk and areas characterized by low flood risk. Overall, both restoration
approaches yielded similar results over the course of the experiment, whereas high flood risk and associated edaphic factors such
as high availability of phosphorus negatively affected restoration progress particularly in terms of floristic similarity to restora-
tion targets. These results highlight the need to take into account environmental gradients during meadow restoration.
Key words: competition filter, MG5 grassland, microsite limitation, phosphorus availability, species sorting, target similarity
Implications for Practice
•Carefully designed seed mixtures can produce restoration
outcomes as good as those from application of green hay
from species-rich donor sites. However, depending on
context, other considerations such as species availability
or cost might take precedence.
•Environmental gradients within sites such as those exist-
ing in river floodplains due to differential flooding and
related edaphic characteristics such as nutrient availabil-
ity can affect restoration outcome, and should be taken
into account at the planning stage.
•When assessing restoration progress based on floristic
similarity to a reference, no net change does not necessar-
ily imply compositional stability, and can instead be a
result of opposing trends of individual target species can-
celing each other out. For a proper assessment of pro-
gress, multiple indicators are required.
Introduction
Due to agricultural intensification, species-rich lowland semi-
natural grassland has markedly declined in extent over the last
70 years both in the United Kingdom (Bullock et al. 2011;
Ridding et al. 2015) and in continental Europe (Veen et al.
2009). In the United Kingdom, conversion into agriculturally
improved grassland has been a main driver of this decline
(Ridding et al. 2015). In the case of grazed hay meadows of
the Cynosurus cristatus–Centaurea nigra type, classified as
MG5 grassland in the British National Vegetation Classification
(NVC; Rodwell 1992), and once the most widespread type of
lowland hay meadow in Britain (Rodwell et al. 2007), less than
10,000 ha are now left across England and Wales (Maddock
2008). Remaining MG5 grassland is now strongly fragmented,
comprising isolated and small stands in otherwise highly inten-
sified pastoral landscapes (Rodwell et al. 2007). Consequently,
there is a substantial risk of local extinction of MG5 specialist
Author contributions: RP conceived and designed the research with the help of MN, JR;
SH, LH, MW carried out botanicaland soil monitoring; MW analyzedthe data and led and
coordinated the writing of the manuscript; SH, LH, MN, JR, RP edited the manuscript.
1
UK Centre for Ecology & Hydrology, Benson Lane, Wallingford, Oxfor dshire, OX10
8BB, U.K.
2
Address correspondence to M. Wagner, email mwagner@ceh.ac.uk
3
Wildlife Farming Company, Alchester Road, Bicester, Oxfordshire, OX26 1UN, U.K.
© 2020 The Authors. Restoration Ecology published by Wiley Periodicals LLC on
behalf of Society for Ecological Restoration.
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.
doi: 10.1111/rec.13180
Supporting information at:
http://onlinelibrary.wiley.com/doi/10.1111/rec.13180/suppinfo
Restoration Ecology 1
species due to small population sizes and strongly reduced dis-
persal between sites (Ozinga et al. 2009). To reduce fragmenta-
tion and its negative effects on such specialist species, and to
restore a coherent and resilient network of sites, both the floristic
diversification of existing species-poor habitat and the creation
of additional high-quality habitat are needed (Lawton et al.
2010). However, unassisted reversion of species-poor intensive
grassland to species-rich lowland meadow habitat solely relying
on management adaptation is hampered by limited dispersal of
target species even where suitable source habitat exists nearby
(Coulson et al. 2001), and usually requires many decades
(Stampfli & Zeiter 1999; Bischoff 2002). This is due to the oper-
ation of two key constraints, seed limitation and microsite limi-
tation (Bakker & Berendse 1999; Walker et al. 2004). Seed
limitation means that propagules of target species fail to reach
a restored site, and microsite limitation means that site-specific
constraints prevent establishment even after propagules arrive
at the site.
To overcome these constraints, active restoration is required.
Seed limitation is usually addressed via target-species introduc-
tion (Bakker & Berendse 1999; Walker et al. 2004). In the case
of meadow restoration, the two most common approaches are
species-rich seed mixtures and transfer of green hay from
high-quality local donor sites (Hedberg & Kotowski 2010; Kiehl
et al. 2010). The term “green hay”in grassland restoration indi-
cates that freshly harvested hay from a species-rich donor
meadow is applied to a restoration site for seed transfer, usually
on the same day as harvested, while it is still green (Jones 1993;
Albert et al. 2019). A detailed discussion of practical aspects of
this method can be found in Trueman and Millett (2003). While
attempts have been made to compare results from both seeding
and green hay approaches (Hedberg & Kotowski 2010; Kiehl
et al. 2010), very few studies have directly compared them
(Jones et al. 1995). Also, we know of no such study that has
simultaneously involved a gradient in site conditions that might
affect microsite limitation and thus restoration outcome.
Such microsite limitation can be very pronounced (Walker
et al. 2004), with raised soil fertility and associated primary pro-
ductivity exacerbating competition among plant species (Foster
2001; Öster et al. 2009). In such situations, short-term allevia-
tion of microsite limitation is crucial to allow initial establish-
ment of actively introduced target species, and can be achieved
through disturbance by cultivation, resulting in bare-ground cre-
ation and provision of a low-competition environment
(Hofmann & Isselstein 2004; Wagner et al. 2016). However,
competitive generalists tend to establish more reliably than
uncompetitive specialists whose occurrence is more restricted
to agriculturally unimproved grassland (Pywell et al. 2003).
Moreover, such differences in establishment success in relation
to plant strategy often tend to become more pronounced with
time, as ecological filtering causes a gradual decline of uncom-
petitive specialists after initially successful establishment
(Pywell et al. 2003).
In river floodplains, soil fertility is usually higher in low-lying
areas close to the river channel than in more distant high-lying
areas less affected by flooding and sediment deposition (Sival
et al. 2005). This is also usually reflected by grassland species
composition, with lower species richness and increased cover
of generalist species adapted to high fertility closer to the river
channel (Klaus et al. 2011). Differential flooding and associated
environmental gradients, e.g. in soil fertility, thus represent an
opportunity to explore trajectories and outcomes of ecological
restoration as simultaneously affected by different approaches
and by pre-existing environmental variation.
In this study, we investigated the following two main
questions:
(1) Provided both green hay application and diverse seeding are
carefully designed and carried out to restore MG5 grassland,
is one approach superior over the other in terms of short-
term progress after 4 years of restoration?
(2) To what extent can occasional flooding and associated gra-
dients in soil fertility affect such outcomes?
Methods
Field Site and Experimental Design
A 4-year meadow restoration experiment was set up in July
2013 in three species-poor grassland fields at Hillesden Estate,
a 1,000 ha arable farm in Buckinghamshire, England
(515705800N0
5801500W), along the western bank of the small
river Padbury Brook, a tributary to the River Twins. These fields
were arable until 2007, and then sown with a mixture of peren-
nial ryegrass Lolium perenne and white clover Trifolium repens,
and managed intensively as agriculturally improved L. perenne
grassland (= MG7 in the NVC; Rodwell 1992). The reason for
this conversion was that parts of the field were subjected to occa-
sional flooding, and were thus no longer considered reliable
enough for crop production. The soil in all three fields is alluvial
clay and clay loam, with a pH of about 6.5. Mean annual temper-
ature is 9.7C and annual rainfall is 648 mm, of which 381 mm
falls between April and October (data from 1981 to 2010; Met
Office 2019).
The experimental design was a randomized complete block
design with four replicate blocks, two of which were located in
the same field. Within each block, three restoration treatments
were applied to plots of between 0.95 and 2.7 ha, depending
on overall size and shape of the field in which the block was
located. These treatments were: (1) a green hay treatment to
which target species were introduced by application of freshly
harvested hay from a species-rich donor meadow; (2) a diverse
seeding treatment to which target species were introduced by
sowing of a specifically tailored seed mixture containing many
grasses and forbs; and (3) a control treatment as provided by
the species-poor extant grassland.
Treatments (1) and (2) were designed to restore Cynosurus
cristatus–Centaurea nigra grassland, that is MG5 grassland
according to the NVC (Rodwell 1992), which had been deter-
mined as a suitable restoration target, based on location, soil,
hydrology, and a proposed management as grazed hay meadow.
To prepare the experimental plots for green hay application
and seeding, a silage cut was carried out in the w/c 17 June,
2013. This was followed by the marking out of experimental
plots, and subsequent glyphosate spraying and cultivation of
Restoration Ecology2
Grazed meadow restoration: short-term progress
those plots assigned to the green hay and diverse seeding’treat-
ments, to create a suitable shallow tilth and bare ground to facil-
itate seedling establishment of target species. Spraying was
carried out in the w/c 24 June, 2013 and cultivation in the w/c
8 July, 2013. In doing so, we followed recommendations for
green hay restoration by Natural England to create a short sward
followed by bare-ground creation prior to hay application
(Natural England 2010), and by Trueman and Millett (2003) to
combine cultivation and spraying to achieve more lasting bare-
ground creation.
The hay applied in the green hay treatment was from species-
rich MG5 grassland 3.68 ha in size, located within Rushbeds
Wood SSSI nature reserve, c. 15 km south of the experimental site.
A hay cut was carried out on 24 July, 2013 using a disk mower,
and a forage harvester was used to load a tractor trailer for transport
to the experimental site. On the same day as the cut took place, the
hay was evenly spread onto the green hay treatment plots using a
muck spreader. The total area of the four replicate green hay resto-
ration plots was 8.15 ha, resulting in an actual area ratio of 1:2.2 for
the spreading of green hay from the donor site, thus exceeding a
recommended ratio of 1:3 (Natural England 2010).
The diverse seeding’treatment was applied in September
2013 at a rate of 12 kg of seed per hectare, using a targeted seed
mixture of 6 grasses and 20 forbs, supplied by a specialist com-
pany for native seed (Emorsgate Seeds Ltd., Ling’s Lynn, U.K.;
Table S1).
Post-establishment management from 2014 onwards was
identical for all experimental plots and based on the typical man-
agement of MG5 grassland, involving a single cut in the sum-
mer, followed by aftermath and winter grazing (Rodwell 1992).
Vegetation Monitoring and Soil Analysis
Vegetation recording at the green hay donor site was carried out
on 3 July, 2013, 3 weeks before the hay cut. A total of 24 quad-
rats of 1 ×1 m were randomly placed within the site, avoiding a
margin of 2 m width around the edge, and percentage cover was
visually estimated for all vascular plant species, following the
nomenclature of Stace (2010). The assessment also involved a
recording of site-level species abundance using the DAFOR
scale (Kershaw & Looney 1985), also capturing species not
picked up during the quadrat-based assessment. For a full spe-
cies list, see Table S2.
Vegetation sampling in the restoration experiment was carried
out annually in July between 2014 and 2017. Within each repli-
cate plot, areas were delineated as either being at high or low risk
of flooding, using aerial photographs (25 cm resolution) taken in
2007 and 2012. Areas determined as being at higher risk of flood-
ing were, as expected, generally closer to watercourses and in the
lower-lying areas of the field. Based on this delineation, within
each experimental plot, seven randomly placed 1 ×1 m quadrats
were recorded annually within areas designated as being at high
flood risk, and another seven within areas designated as being at
low flood risk. As with the green hay donor site, a margin of 2 m
width around the edge of each treatment plot was avoided. Using
this stratified sampling approach allowed us to take flood risk
into account in our analyses.
Soil sampling for textural, chemical, and bulk density ana-
lyses was carried out in October 2017, to confirm soil gradients
in accordance with our delineation of areas of high and low flood
risk, and to test whether experimental treatments had any effects
on the measured soil parameters. Three pooled samples were
collected in each experimental plot, two from the area of the plot
characterized by low risk of flooding, and one from the—usually
smaller—area characterized by high risk of flooding. We also
collected four pooled soil samples in nearby arable fields, also
located at Hillesden Estate and characterized by comparable ele-
vation and distance from the river as the experimental plots, and
another four pooled samples from the green hay donor meadow.
These additional samples enabled us to determine soil character-
istics both for the starting point of restoration on former arable
land and for an endpoint of successful ecological restoration of
MG5 grassland. Soil chemical and textural analyses were car-
ried out by NRM Laboratories (Berkshire, U.K.). They included
measurement of soil pH by 1:2.5 water extract, of available
phosphorus (Olsen et al. 1954), of available potassium via
ammonium-nitrate extraction (Ministry of Agriculture, Fisheries
and Food 1981), of soil texture via laser diffraction, of loss-on-
ignition via dry combustion at 430C, and of total N by high-
temperature combustion in a Carlo Erba NCS2500 elemental
analyzer (Carlo Erba Instruments, Milan, Italy).
Data Analysis
Soil Characteristics. To test for treatment and flood risk
effects on soil characteristics, we constructed linear mixed
models (LMM) as provided in SAS 9.3 PROC MIXED (SAS
Institute, Cary, NC, U.S.A.). We included restoration treatment,
flood risk level, and their interaction as fixed factors, and speci-
fied main plots, nested within blocks, as random effects
(Schabenberger & Pierce 2002). To ensure normality of resid-
uals and variance homogeneity, all soil data was Box–Cox-
transformed (Quinn & Keough 2002).
Restoration Progress. Restoration progress was character-
ized in several ways, including (1) calculation of floristic simi-
larity with the vegetation at the green hay donor site,
(2) calculation of goodness-of-fit with MG5 grassland as defined
by Rodwell (1992), (3) total cover and species density per m
2
of
positive indicator species of MG5 grassland sensu Robertson
and Jefferson (2000), and (4) total species density per m
2
. This
multi-pronged approach was chosen to enable a direct compari-
son with the green hay donor site as well as a quantification of
progress towards a more general target of MG5 grassland, and
to allow deeper insights into underlying processes.
Floristic similarity with the vegetation of the green hay donor
site was calculated as follows. First, on the basis of individual
quadrat data standardized to total cover, we calculated inter-
quadrat Bray–Curtis similarity values (Bray & Curtis 1957) for
each quadrat recorded during 4 years in the experiment with
each of the 24 quadrats recorded in 2013 at the green hay donor
site. This was followed by a two-step averaging procedure, first
individually for each quadrat recorded in the experiment with
Restoration Ecology 3
Grazed meadow restoration: short-term progress
the 24 donor-site quadrats, and then across the 7 replicate quad-
rats annually recorded per treatment plot in a given sub-area and
level of flood risk.
In contrast to this purely cover-based approach, calculation
of goodness-of-fit with MG5 grassland, as carried out by
TABLEFIT, version 2.0 (Hill 2015), takes into account both spe-
cies cover and frequency of occurrence (Hill 1989). TABLEFIT
analyses were also carriedout for the dataset of 24 quadrats from
the green hay donor site, to determine the donor grassland’s clos-
est match within the NVC (Rodwell 1992).
Summed cover and species density of MG5 positive indicator
species sensu Robertson and Jefferson (2000), as well as total
species density, were calculated by averaging across the seven
replicate quadrats annually recorded per sub-area of high or
low flood risk within a given treatment plot. For comparison,
for the latter three parameters, we also calculated average cover
and species density values for the set of 24 green hay donor-site
quadrats recorded in 2013.
Statistical analyses of these indicators of restoration progress
were carried out using repeated-measures LMM as provided in
SAS 9.3 PROC MIXED (SAS Institute, Cary, NC, U.S.A.).
Prior to analyses, to ensure normality of residuals and variance
homogeneity, species density and summed cover parameters
were Box–Cox-transformed, and similarity and goodness-of-fit
parameters that have an upper bound of 100% were arcsine-
transformed (Quinn & Keough 2002). We were primarily inter-
ested in comparing restoration progress following active
intervention via green hay application or diverse seeding. As
already mentioned, grassland restoration is much faster via such
interventions than via unassisted natural regeneration (Bakker &
Berendse 1999; Walker et al. 2004), rendering moot the ques-
tion of differences due to intervention versus non-intervention.
This point was also illustrated for our experiment by a prelimi-
nary exploratory ordination analysis using nonmetric-
dimensional scaling (NMDS; Fig. S1), as provided by PC-
ORD, Version 7.02 (McCune & Mefford 2015), indicating a
clear difference between the two treatments involving active res-
toration and the control treatment. Hence, for clearer analysis of
the differences in outcome between green hay application and
diverse seeding approaches, only these two active restoration
treatments were compared in LMM analyses. We included res-
toration treatment, flood risk level, year, and all possible interac-
tions between these as fixed factors, and specified year as
repeated-measures factor, and main plots nested within blocks
as random effects (Schabenberger & Pierce 2002). We repeated
each analysis using various alternative covariance structures for
the repeated factor, including unstructured, compound symmet-
ric, and several autoregressive structures. The model with the
most suitable error structure was identified using Akaike’s infor-
mation criterion (AIC; Akaike 1974). In case of a significant
main effect of year, pairwise comparisons between years were
carried out using two-sided Tukey HSD tests.
Compositional Dynamics. Initial differences in species com-
position between restoration treatments necessitated separate
analyses for each treatment to test compositional shifts across
the 4 years of the experiment. Hence, data from each treat-
ment was analyzed separately for the occurrence of two sepa-
rate trends, including (1) a general trend in species
composition independent of flood risk level and (2) a modifi-
cation to this general trend in response to floodrisklevel.Both
types of analysis were carried out using CANOCO, version
5.10 (ter Braak & Šmilauer 2018). For general trends in each
treatment, prior to analyses, plant quadrat cover data was aver-
aged across all 14 quadrats recorded in a given year and treat-
ment plot. For modifications to these general trends as caused
by differences in flood risk, prior to analyses, plant quadrat
cover data was averaged across the seven quadrats recorded
at the respective level of flood risk in a given year and
treatment plot.
Prior to analyses, all species percent cover data was log(x+1)
transformed, and as we were interested in absolute changes in
species cover, cover data was not standardized. Length of the
longest gradient in initial detrended correspondence analyses
ranged from 1.55 to 2.38 for the six datasets, indicating a partic-
ular suitability of linear ordination techniques (Šmilauer & Lepš
2014). Hence, partial redundancy analysis (pRDA) was used for
both types of analysis. For statistical significance testing, Monte
Carlo permutation with 9,999 permutations was used (ter
Braak & Šmilauer 2018). General trends were tested using a
time series permutation scheme, specifying Year as explanatory
variable and Block as covariate, with permutation blocks
defined accordingly. Differential trends in response to flood risk
level were tested by specifying the Flood Risk ×Year interac-
tion as explanatory variable, and Block, Year, and the
Block ×Year interaction as covariates, thus effectively remov-
ing block effects and general and block-related compositional
trends. In this case, a hierarchical design was used for permuta-
tions, with “whole-plots”defined on the basis of areas of a given
flood risk within treatment plots and “split-plots”defined as
individual years within one such area, and permutations were
carried out at whole-plot level. To provide a baseline measure
of compositional variation within each dataset, we also carried
out principal component analyses.
To test whether species-level trends in cover of successfully
introduced species in each of the two active restoration treat-
ments, and trends of extant species in the control treatment, were
affected by life strategy or realized niche, we then carried out
Spearman correlation analyses of species’constrained pRDA
axis 1 scores versus their C-, S-, and R-scores for established
plant strategies (Hunt et al. 2004; Grime et al. 2007) and versus
their Ellenberg indicator values for light, moisture, reaction, and
nitrogen (Hill et al. 2004). Again, analyses were carried out to
investigate general trends as well as modifications to these
trends in response to flood risk level. In these Spearman correla-
tion analyses, we tested for the strength and direction of mono-
tonic relationships between pRDA axis 1 scores of species on
the one hand, and their life history and realized niche character-
istics on the other hand.
In all correlation analyses, to minimize the impact of rare spe-
cies that might have been characterized with low precision along
pRDA ordination axes, all species recorded in only 1 year in a
given experimental treatment were excluded from analysis.
Restoration Ecology4
Grazed meadow restoration: short-term progress
Furthermore, in the analyses of extant species’trends in the con-
trol treatment, only species were included that were not poten-
tially augmented by diverse seeding or green hay application.
Finally, to characterize performance with time of individual
introduced species in the green hay and diverse seeding treat-
ments, and of extant species in the control treatment, we calcu-
lated species response curves using generalized additive
models as provided by CANOCO (ter Braak & Šmilauer
2018), as characterized by species’case scores on the con-
strained first pRDA ordination axis of general trend analyses
(Šmilauer & Lepš2014). For the control treatment, we calcu-
lated species response curves only for species recorded with an
average cover exceeding 1% in at least 1 year. For each species
whose response was modeled in a given experimental treatment,
we compared two alternative models with one and two degrees
of freedom, respectively. Based on AIC (Akaike 1974), we then
chose the more parsimonious model.
Results
Soil Characteristics
Restoration treatments did not affect any of the soil characteris-
tics measured in the final year of the experiment (see Table S3).
However, for seven of the nine characteristics, we detected an
independent main effect of flood risk level (Table S3; Fig. 1).
The soil in areas of high flood risk had much higher levels of
available phosphorus (Fig. 1A) and of available potassium
(Fig. 1B). Furthermore, soil in areas of high flood risk also dif-
fered texturally by having lower sand content (Fig. 1D) and
higher clay content (Fig. 1F), and had higher organic matter con-
tent as determined by loss-on-ignition (LOI; Fig. 1G), lower pH
(Fig. 1H), and lower bulk density (Fig. 1I).
Also shown in each panel in Figure 1 in the form of orange
bands is the range of values for each soil parameter measured
in the four arable reference samples, with green bands indicating
(A) (B) (C)
(D) (E) (F)
(G) (H) (I)
Figure 1. Soil characteristics in experimental plot areas of low and high flood risk. Bar charts show back-transformed mean values, and error bars indicate SE
(n= 12). For comparison, the range of values for these parameters as measured in local arable fields is indicated by orange bands, and the range of values as
measured at the green hay donor site is indicated by green bands, representing potential starting points and a potential endpoint of grassland restoration,
respectively (in each case n= 4).
Restoration Ecology 5
Grazed meadow restoration: short-term progress
the range of soil parameter values measured in reference sam-
ples from the green hay donor site. As indicated by these green
bands, both available P and soil pH were much higher at the
experimental site than at the green hay donor site (Fig. 1A &
1H), whereas total N and LOI were lower (Fig. 1C & 1G).
Restoration Progress
As indicated by highly significant effects of year in LMM ana-
lyses, all five indicators of restoration progress were highly
dynamic (see Table S4). Flood risk level mostly affected indica-
tors based on floristic similarity or goodness-of-fit, whereas res-
toration approach in terms of green hay application versus
diverse seeding had few effects, and only in interaction with
other factors (Table S4).
Floristic similarity with the green hay donor site was affected
by flood risk level (F
[1,42]
= 6.67, p= 0.013), with higher simi-
larity achieved in areas characterized by low risk (Fig. 2A). It
also differed highly significantly between years (F
[3,42]
=
29.93, p< 0.001), and was lower in year 1 than in years 2–4
(Tukey’st≤−6.70, p< 0.001 for all three pairwise compari-
sons involving year 1). Vegetation restored by green hay appli-
cation was marginally non-significantly more similar to that of
the green hay donor site than vegetation restored via diverse
seeding (F
[1,3]
= 9.33, p= 0.055).
Goodness-of-fit of actively restored grassland to MG5 grass-
land was also significantly affected by flood risk level (F
[1,42]
=
9.33, p= 0.004), with a closer goodness-of-fitinlow-flood-risk
areas (Fig. 2B). Grassland restored via green hay application and
grassland restored by diverse seeding did not consistently differ
from each other (F
[1,3]
=1.51,p= 0.306), but goodness-of-fit
was affected by a three-way interaction between year, restoration
treatment, and level of flood risk (F
[3,42]
=5.50,p= 0.003), with
diversely seeded areas of low floodriskhavinganonlyslightly
higher fit to the MG5 reference than diversely seeded areas of high
flood risk in the second and third year of the experiment, but
with much higher fit than the latter to the reference in the first
and fourth year of the experiment (Fig. 2B). As with similarity
to the green hay donor site, goodness-of-fit to MG5 grassland
differed highly significantly between years (F
[3,42]
= 81.10,
0
20
40
(A) Similarity to hay donor site
Similarity (%)
0
20
40
60
(B) Goodness-of-fit to MG5
Goodness-of-fit (%)
0
20
40
60
(C) MG5 indicator cover
Year
2014 2015 2016 2017
Cover (%)
0
2
4
Species m
-2
(D) MG5 indicator species richness
0
10
20
Species m
-2
(E) Total species richness
Year
2014 2015 2016 2017
Control
Green hay
Diverse seeding
Low High
Flood risk
Figure 2. Restoration progress from 2014 to 2017 for areas of low flood risk and areas of high flood risk in the three experimental treatments. Parameters include
(A) Bray–Curtis similarity to the vegetation at the hay donor site, (B) TABLEFIT goodness-of-fit to MG5 grassland (Hill 2015), (C) total cover of MG5 positive
indicator species (Robertson & Jefferson 2000), (D) MG5 positive indicator species richness per m
2
and (E) total species richness per m
2
. Back-transformed
means SE are shown (n= 4).
Restoration Ecology6
Grazed meadow restoration: short-term progress
p< 0.001), again with lower levels in year 1 than in years 2–4
(Tukey’st≤−7.77, p< 0.001 for all three pairwise compari-
sons involving year 1). The closest goodness-of-fittoMG5
grassland was found in the low-flood-risk areas within the
green hay treatment, leveling off at 52% from year 2 onwards
(Fig. 2B). This is slightly lower than a goodness-of-fitto
MG5 grassland of 66% calculated for the vegetation at the
green hay donor site, which conformed more closely to MG5
grassland than to any other NVC vegetation type.
Total cover of MG5 positive indicator species in both restora-
tion treatments also highly significantly differed between years
(F
[3,42]
= 51.81, p< 0.001), increasing over time (Fig. 2C). Pair-
wise comparisons based on Tukey tests indicate that cover was
lowest in year 1, and highest in years 3 and 4, with intermediate
cover in year 2. MG5 positive indicator cover reached its highest
level (45%) in year 4 in the low-flood-risk areas of diversely
seeded restored grassland (Fig. 2C), which is almost as high as
the mean positive indicator cover of 49.1% (SE: 3.3%;
n= 24) found at the green hay donor site in 2013. While it
appears from Fig. 2C that the diversely seeded treatment was
characterized by higher total cover of MG5 indicator species
than the green hay treatment, this difference was not significant
(F
[1,3]
= 5.54, p= 0.100).
Species density per m
2
of MG5 positive indicators in active res-
toration treatments also differed between years (F
[3,42]
=5.06,
p= 0.004; Fig. 2D), and was also lower in year 1 than in years
3(Tukey’st=−3.63, p< 0.001) and 4 (Tukey’st=−2.96,
p= 0.025). In year 4 of the experiment, average MG5 positive
indicator species density in active restoration treatments at a given
flood risk level ranged from 1.9 to 2.6 species per m
2
(Fig. 2D),
and was still markedly lower than the species density of MG5 pos-
itive indicators of 6.9 species per m
2
(SE: 0.3; n= 24) found at
the green hay donor site in 2013.
Total species density in the two active restoration treatments
also differed highly significantly between years (F
[3,42]
=14.48,
p< 0.001; Fig. 2E). Pairwise comparisons based on Tukey tests
indicate that it was slightly lower overall in year 1, and highest
in year 3, with intermediate levels in years 2 and 4. Patterns were
also affected by two-way interactions between year and restoration
treatment (F
[3,42]
=7.28,p< 0.001), and between year and level of
flood risk (F
[3,42]
=5.10,p= 0.004). The first of these interactions
appears to have been the result of higher initial species richness in
year 1 in the diverse seeding treatment than in the green hay treat-
ment (Fig. 2E). The second interaction appears to have resulted
from a temporary reversal in year 2 of the experiment of the pattern
of slightly lower species richness in high-flood-risk areas that was
observed in other years (Fig. 2E). Average total species density in
the final year of the experiment in the active restoration treatments
at a given flood risk level ranged from 12.3 to 14.8 species per m
2
and was still markedly lower than the average total species density
at the green hay donor site in 2013 of 21.9 species per m
2
(SE:
0.7; n= 24).
Compositional Dynamics
General Trends With Time. As established by pRDA ana-
lyses, pronounced shifts in plant species composition occurred
in all three treatments (Table S5). Taking into account relevant
covariates, year as an explanatory variable explained 32% of
partial variation left in the control treatment, 39% in the
diverse seeding treatment, and 43% in the green hay treatment,
with Monte Carlo permutation tests indicating these shifts to
be highly significant (pseudo-Fvalues from 6.6 to 9.9 and
p< 0.001 for all three analyses; Table S5).
As established by a second set of pRDA analyses, specifying
the Flood Risk ×Year interaction as explanatory variable and a
different set of covariates, species compositional trends were
modified by flood risk level in the two active restoration treat-
ments (pseudo-F= 8.3 for diverse seeding and pseudo-F= 8.9
for green hay application; for both treatments p= 0.031; see
Table S5), but not in the control treatment (pseudo-F= 3.1;
p= 0.204).
Neither for the green hay treatment nor for the diverse seeding
treatment did Spearman correlation of experimentally intro-
duced species’pRDA axis 1 scores, representing overall trends
in performance with time, and their life strategy and realized
niche characteristics yield any significant relationships
(Table S6). However, while no such dependence could be estab-
lished in relation to life history and realized niche, as indicated
by species response curves for both treatments, significant shifts
in percentage cover occurred over the 4 years of the experiment
in several of the introduced target species (Fig. S2A,B). More-
over, a comparison of species response curves for both active
restoration treatments indicates similarities in temporal patterns
of percentage cover of several species simultaneously intro-
duced in both treatments (Fig. S2A,B). Notably, in both treat-
ments, cover of Agrostis capillaris and of Centaurea nigra
steadily increased with time, whereas cover of
Leucanthemum vulgare first increased, and then decreased
(Fig. S2A,B). One notable difference between treatments was
that Plantago lanceolata established a high initial cover in the
first year in the green hay treatment, followed by a steady
decline, whereas in the diverse seeding treatment, it appeared
to establish less well initially, to then steadily increase in cover
(Fig. S2A,B). Another notable difference between both treat-
ments was that cover of Trifolium pratense increased rapidly
in the green hay treatment, reaching a plateau of about
18–21% in years 2–4 of the experiment (Fig. S2B), whereas in
the diverse seeding treatment, it remained under 2% in the first
3 years, and the species was no longer recorded in year 4.
For extant species already present in the control treatment at
the start of the experiment, Spearman correlation analyses estab-
lished that species characterized by high Ellenberg N-values
were more likely to decline than species characterized by lower
N-values (r
S
=−0.53, n= 21, p= 0.013). The most obvious
cover changes at species level were a decrease in ryegrass
L. perenne, and an increase in T. repens (Fig. S3).
Trends in Response to Flood Risk Level. Species-level cover
trends of experimentally introduced green hay species in
response to differential flood risk, as characterized by pRDA
axis 1 scores of an ordination analysis of such trends, were sig-
nificantly related to Cand Rstrategy scores sensu Grime et al.
Restoration Ecology 7
Grazed meadow restoration: short-term progress
(2007), with high-flood-risk areas being associated with a rela-
tive increase with time of species characterized by high C-scores
(r
S
= 0.52, n= 29, p= 0.004), when compared to low-flood-risk
areas, and a relative decrease of species characterized by high
R-scores (r
S
=−0.47, n= 29, p= 0.009). Compared to low-
flood-risk areas, high-flood-risk areas were also associated with
a relative increase with time of species characterized by high
Ellenberg R-values (r
S
= 0.38, n= 29, p= 0.043), and of species
characterized by high Ellenberg N-values (r
S
= 0.59, n= 29,
p< 0.001). In the diverse seeding treatment, trends in relation
to these characteristics of introduced species had the same direc-
tion as in the green hay treatment, but were not significant
(Grime’sC-score: r
S
= 0.14, n= 21, p= 0.545; Grime’sR-score:
r
S
=−0.26, n= 29, p= 0.263; Ellenberg’sR-value: r
S
= 0.30,
n= 29, p= 0.183; Ellenberg’sN-value: r
S
= 0.24, n= 29,
p= 0.293; see Table S6 for full results).
Spearman correlation analyses of differential trends within
control treatment plots in relation to flood risk level indicate a
relative increase of extant species characterized by high Ellen-
berg N-values in plot areas characterized by high flood risk
when compared to areas of low flood risk (r
S
= 0.47, n= 21,
p= 0.033), indicating that the overall negative trend of high-N
species was more pronounced in low-flood-risk areas than in
high-flood-risk areas.
Discussion
Soil Characteristics
High levels of available P and K, combined with low total N and
soil organic matter, as was the case in our study in at least in part
of the experimental area, are a common starting point for restor-
ing grassland on former arable land (McCrea et al. 2004; Donath
et al. 2007). However, a requirement of sufficiently low levels of
available P has been identified as prerequisite for high plant spe-
cies richness in grassland (Janssens et al. 1998; Critchley et al.
2002a). Our site was converted from arable land to species-poor
intensive grassland 6 years prior to the experiment, and accord-
ingly, at the end of our experiment, particularly in high-flood-
risk areas, total N and organic matter content were already
higher than at local arable reference sites. On the other hand,
Olsen-P and extractable K are still high in these high-flood-risk
areas, whereas in low-flood-risk areas, P levels are already lower
than those found at local arable reference sites, and K levels are
at the lower end of the range of values at these sites. While
Olsen-P is still slightly higher in areas of low flood risk than at
the green hay donor site, its levels in these areas are already
comparable with those typically found in MG5 grassland
(Critchley et al. 2002b), and below a threshold for Olsen-P of
15 mg P/L defined by Critchley et al. (2002b) as critical for
the formation of species-rich grassland. In the case of extracta-
ble K, levels found in low-flood-risk areas at the experimental
site are similar to both those found at the green hay donor site
and those typically found in MG5 grassland (Critchley et al.
2002b). In contrast, in high-flood-risk areas, both P and K levels
were higher than those found at the green hay donor site and
those typically encountered in MG5 grassland (Critchley et al.
2002b).
The fact that levels of various soil parameters differed
between areas according to flood risk level was not unexpected.
Nutrient inputs by river flooding have been described for
similar-sized rivers to ours (Sival et al. 2005), as have increased
levels, e.g. of soil P in more regularly flooded parts of flood-
plains (Klaus et al. 2011). Hence, conditions at our site are likely
reflect those found on other ex-arable land similarly subjected to
occasional flooding whose limited utility for arable cropping
makes it a candidate for grassland restoration.
Restoration Progress and Compositional Dynamics
Both our active restoration treatments resulted in grassland veg-
etation much more floristically similar to MG5 grassland and to
the green hay donor site than the control treatment. In the con-
trol, we observed shifts in the relative cover of extant species,
in line with the shift from previously intensive management to
extensive management characteristic of species-rich MG5 grass-
land, but independent colonization by restoration target species
from outside the experiment did not occur.
Somewhat surprisingly, green hay application did not pro-
duce a sward more similar to that of the green hay donor site than
diverse seeding, although a near-significant trend was observed.
Our results in terms of the diversely seeded vegetation’s
goodness-of-fit to MG5 grassland and similarity to the green
hay donor site vegetation underline that good results can also
be achieved with species-rich seed mixtures. Other indicators
of restoration progress in our study, such as summed cover
and species density of MG5 positive indicator species sensu
Robertson and Jefferson (2000), and total species density, also
yielded comparable results for the green hay and diverse seeding
approaches. As we also carried out an analysis of green hay seed
content (data not shown), we were able to ascertain that the
seeds of similar numbers of MG5 positive indicator species were
introduced in both treatments (green hay application: 11; diverse
seeding: 12), indicating an equivalence of both treatments in
terms of their potential to restore MG5 grassland.
Notably, regardless of approach, similarity of restored vege-
tation to that of the green hay donor site and goodness-of-fitto
MG5 grassland, after an initial increase in the first 2 years, there-
after remained more or less constant, whereas cover of MG5
positive indicator species continued to increase. This continued
increase in positive indicator species cover in subsequent years
was mainly caused by C. nigra. Another positive indicator in
both treatments, L. vulgare peaked in years 2–3, again decreas-
ing in the final year. As a relatively ruderal grassland species of
the CR/CSR type according to Grime et al. (2007), this species
establishes reliably and often initially abundantly from seed in
the early open phase of grassland restoration (Pywell et al.
2003). Leontodon saxatilis, another positive indicator species
in the green hay treatment, continuously declined between years
1 and 4. Several other species that occur in MG5 grassland, but
are not defined by Robertson and Jefferson (2000) as positive
indicators, similarly declined over the course of the experiment,
including Festuca rubra in the diverse seeding treatment, and
Restoration Ecology8
Grazed meadow restoration: short-term progress
P. lanceolata and Scorzoneroides autumnalis in the green hay
treatment. It thus appears that the observed leveling-off of com-
positional similarity with the two references was not a reflection
of compositional stability, but the net outcome of increases in
the abundance of some target species and of decreases by others,
with these opposing trends canceling each other out. This means
that, ultimately, only those target species particularly well-
adapted to the prevailing conditions at the experimental site
may persist, whereas other, less well-adapted species likely con-
tinue to decline and may get gradually eliminated from the
sward, due to abiotic and competition filters at this former arable
site continuing to affect plant species composition.
Notably, we found that the strength of these filters is posi-
tively linked with flood risk level. The similarity of grassland
restored by green hay application or by diverse seeding with
both references was markedly lower in high-flood-risk areas
than in low-flood-risk areas. Stronger filtering in high-flood-risk
areas has also been indicated by correlation analyses, indicating
that species performing increasingly better with time in high-
flood-risk areas than in low-flood-risk areas tended to be more
competitive and better-adapted to high levels of soil fertility as
indicated by the correlation of species responses with Ellenberg
N-values reflecting site productivity (Wagner et al. 2007), in line
with existing edaphic gradients of extractable P and K. Similar
patterns in terms of Ellenberg R-values of species match existing
gradients in soil pH. For the R-score sensu Grime et al. (2007),
which characterizes the “ruderality”of plant species, we found
an opposite trend. This finding suggests that, with increasing
time after initial restoration, continued opportunities for plant
establishment from seed, as required by species with a more
ruderal strategy, primarily persist in low-flood-risk areas charac-
terized by lower fertility. Overall, these differential trends in the
performance of species introduced via active restoration,
between areas of low and of high flood risk, indicate a process
of species sorting in line with underlying environmental gradi-
ents. It appears that, once the window-of-opportunity for initial
target species establishment is closed, pre-existing environmen-
tal filters gradually affect species in accordance with their estab-
lished life strategies, sorting them according to their realized
niche requirements along spatial environmental gradients.
Eventually, species compositional patterns in our restored grass-
land will likely resemble those found in extant grassland along
river floodplains where competitive nutrient-demanding grass-
land species tend to be more common in floodplain compart-
ments that are not protected from flooding (Klaus et al. 2011).
However, it remains to be seen how such processes of species
sorting affect species composition in the longer-term, both
in terms of community assembly and with respect to the degree
of success in restoring the reference plant community (Bischoff
et al. 2018; Harvolk-Schöning et al. 2020).
Another important finding of our study is that on its own, no
single indicator of restoration progress allows a detailed enough
assessment of the underlying dynamics to evaluate prospects for
longer-term success. In fact, the chosen indicators displayed
very different trajectories, as e.g. exemplified by the quick level-
ing off of indicators of reference similarity, compared to a steady
increase in MG5 positive indicator cover.
Total species density, the least specific of our indicators, was
high in year 1 in the diverse seeding treatment and dropped in
year 2, whereas in the green hay treatment, it started off from a
lower level but then constantly increased until year 3 of the
study. Similar increases in species density in the first few years
after green hay application, both in terms of introduced target
species and across all species, were also found by Schmiede
et al. (2012). In our study, the difference in patterns between
the two active restoration treatments partly reflects the fact that
species from the weed seed bank in the soil on this relatively
recent ex-arable site initially established in much greater abun-
dance in the diversely seeded treatment, causing a transient flush
in their occurrence. Similar patterns in other studies have been
interpreted as a result of weed seedling emergence being stimu-
lated by cultivation, with this effect being negated by green hay
application but not seeding, due to the added cover of mulch
provided by green hay decreasing light availability at the soil
surface, and adding to the thickness of the soil layer that seed-
lings from the soil seed bank must penetrate in order to emerge
(Jones et al. 1995; Desserud & Naeth 2011). A continued
increase in overall species richness in the second year after
green hay application, and sometimes even in the third year as
observed in our study, is not uncommon (Mann & Tischew
2010; Sengl et al. 2017), and is attributed to an initial delay of
seedling emergence caused by green hay mulching (Sengl
et al. 2017) or to primary seed dormancy resulting in delayed
germination (Mann & Tischew 2010).
Recommendations for Restoration
In our study comparing green hay application with the use of a
specifically tailored species-rich seed mixture, neither approach
proved superior over the other, that is restoration of MG5 grass-
land can be achieved with either approach. However, depending
on context, other considerations might favor one approach over
the other. Green hay application tends to be less costly than the
use of diverse commercial seed mixtures, and also allows the
transfer of species not available commercially. This is especially
important as about twothirds of the species of European grassland
are still not commercially available (Ladouceur et al. 2018).How-
ever, green hay donor sites may not always be available, as high-
quality remnants of species-rich grassland are rare, and as there is
a requirement for such sites to be local to recipient sites, as the
quick transfer of green hay is essential (Trueman & Millett 2003).
It is also possible to combine green hay and seed-sowing
approaches from the start, e.g. if the amount of green hay avail-
able is not sufficient to cover a whole site, or if the aim is to
establish as many species as possible from the reference commu-
nity. As shown by Baasch et al. (2016), such a combination has
the potential to produce better results than either approach on
its own.
In our study, total species richness and richness of MG5 indi-
cator species did not increase after year 2. As indicated by
longer-term follow-up studies after green hay restoration
(Sullivan et al. 2020) and/or restoration by other means
(Bissels et al. 2004; Harvolk-Schöning et al. 2020), further pro-
gress towards the reference beyond the first 4 years is often also
Restoration Ecology 9
Grazed meadow restoration: short-term progress
slow or absent, due to low functional connectivity with high-
quality remnant sites. It has thus been suggested that to achieve
further restoration progress, deliberate introduction of additional
target species may be required during later stages of restoration
(Sullivan et al. 2020).
Another implication of our results is that the variation in envi-
ronmental conditions between different parts of a field can affect
patterns of results at a recipient site. In such situations, a more
spatially targeted approach might be more efficient, particularly
if resources are limited and have to be concentrated on those
areas characterized by the most favorable conditions for restora-
tion of species-rich references. With respect to MG5 grassland
restoration as carried out in our experiment, elevated levels spe-
cifically of phosphorus in those areas characterized by higher
flood risk likely represent a bigger obstacle than elevated levels
of other nutrients. This is further underlined by results from a
study on MG5 grassland creation by McCrea et al. (2001),
who found that plant species diversity was closely negatively
associated with soil P levels, whereas no such relationship was
found for soil K levels. In a subsequent study that also included
old MG5 grassland reference sites, McCrea et al. (2004) found
that high K levels favored plant diversity. Accordingly, Klaus
et al. (2011) have questioned the suitability of regularly flooded
areas next to river channels that are characterized by high P
inputs, for the restoration of grassland vegetation typically
occurring at sites characterized by low nutrient levels, and other
targets may have to be defined for such areas. Even when such
gradients, e.g. in soil fertility, are less obvious but nonetheless
suspected, it might be worth investing in spatial monitoring of
site conditions to have this information available at the planning
stage.
Acknowledgments
This project was funded by Defra and Natural England as part
of the Hillesden project BD5209. Soil sampling was supported
by research programme NE/N018125/1 LTS-M ASSIST—
Achieving Sustainable Agricultural Systems, funded by NERC
and BBSRC. Valuable advice was provided by V. Robinson
from Natural England. The experiment was set up and managed
in cooperation with Faccenda Farms Ltd. and farm manager
R. Franklin. We thank BBOWT who own Rushbeds Wood
SSSI, our green hay donor site, for permission to harvest green
hay, and to carry out vegetation recording and soil sampling.
We thank N. Mitschunas, P. Nuttall, and J. Peyton for help with
vegetation recording in the experiment, and J. Christelow for
help with soil sampling at Rushbeds Wood SSSI.
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Supporting Information
The following information may be found in the online version of this article:
Figure S1. NMDS sample plot of a joint analysis of vegetation quadrats in the exper-
iment and at the green hay donor site.
Figure S2. Species response curves for experimentally introduced species in the
diverse seeding and green hay treatments.
Figure S3. Species response curves for extant species in the control treatment.
Table S1. Species composition of the seed mixture used in the diverse seeding
treatment.
Restoration Ecology 11
Grazed meadow restoration: short-term progress
Table S2. Plant composition of the Rushbeds Wood SSSI green hay donor site
in 2013.
Table S3. Linear mixed model results for soil parameters in the final year of the
experiment.
Table S4. Linear mixed model results for five indicators of restoration progress.
Table S5, Results of partial redundancy analysis (pRDA).
Table S6. Spearman coefficients relating species performance trends to life history and
realized niche characteristics.
Guest Coordinating Editor: Peter Török Received: 15 January, 2020; First decision: 25 February, 2020; Revised: 16
April, 2020; Accepted: 16 April, 2020
Restoration Ecology12
Grazed meadow restoration: short-term progress
