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SID 5
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SID 5 (Rev. 3/06)
Project identification
DB1327
Management of wet grassland habitat to reduce the
impact of predation on breeding waders: Phase 2.
Contractor
organisation(s)
Royal Society for the Protection of Birds
The Lodge
Sandy
Bedfordshire
SG19 2DL
54. Total Defra project costs
(agreed fixed price)
5. Project:
Page 1 of 25
£
154,849
start date ................
01 March 2008
end date .................
31 March 2010
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Executive Summary
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The executive summary must not exceed 2 sides in total of A4 and should be understandable to the
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with any other significant events and options for new work.
Background: The loss of suitable breeding habitat has played a major role in the severe
declines of breeding wader populations across Europe. In the UK specifically, species such as
lapwing Vanellus vanellus and redshank Tringa totanus have been affected by loss of lowland
wet grassland. There is a substantial body of knowledge about the breeding habitat
requirements of both species, and breeding success is the key limiting factor for lapwing. Site
wetness is important for increasing densities, but lapwing favour short swards for nesting, while
redshank prefer a taller sward. The chicks of both species require open areas of damp ground to
forage for invertebrates. However, even within suitably managed habitat, high predation levels
by generalist predators such as foxes and corvids can be sufficient to prevent the recovery of
populations. Economic and socio-political practicalities mean that predator control is not a
realistic landscape-scale solution. Previous research has demonstrated that lapwing hatching
success is enhanced at higher breeding densities further from field edges.
Aims & Objectives: We investigated the impact of two habitat manipulations on the density,
distribution and nesting success of lapwing and redshank using a before-after controlled
experiment. The manipulations were specifically designed to encourage lapwing to nest at high
densities in field centres. However, as redshanks have different requirements, they were also
monitored to ensure benefits could be maximised for a suite of wader species. The study
objectives were:
1) To investigate the effects on in-field wader nesting distribution, density and breeding success
of the following two habitat manipulations:
a) ‘Sward’ fields - margins (0-50 m from field edge) made less attractive for nesting through lack
of mowing and spring fertilising to create taller swards
b) ‘Wet’ fields - centres made more attractive by enhancing the extent of wet features
2) To investigate the effects of the two habitat manipulation treatments on predator distribution
and foraging behaviour
3) To provide an overall evaluation of the most cost-efficient option to benefit waders
Methods: All fieldwork was conducted at Berney Marshes RSPB reserve, and was divided
between five-study blocks based on prior knowledge of differences in predator abundance. 2008
was used as a baseline year with nest and chick survival of lapwing and redshank, and the
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abundance and distribution of predators (foxes, raptors, herons, gulls and corvids), monitored
across 37 fields in which wader breeding attempts were found. 36 fields large enough to allow
manipulations to be implemented were then included in the experiment. 12 fields were allocated
to each treatment with 12 remaining unaltered as controls. To examine whether the
manipulations altered the habitat as expected, sward height and wet features were assessed in
all fields in early and late spring. Sward height was measured along transects in the edge and
centre of fields. Wet features were mapped using GPS, digitised, and the total area of suitable
foraging habitat was calculated through assessment from fixed points.
To examine the impact of manipulations on nest and chick survival, nests of both species were
found (417 nests), and their survival monitored until hatching or failure. A combination of nest
temperature loggers, field sign and remote nest cameras (100 nests) were used to determine the
main predators. Within-field nest distribution was recorded, with the number of pairs and nests
monitored allowing for assessment of nesting densities relative to treatments. Chicks of both
species were ringed and colour marked (778 chicks), and a sample was fitted with lightweight
radio transmitters to monitor movements and survival (125 chicks).
Predator abundance and distribution was assessed in a variety of ways. The number of avian
predators was recorded through timed counts in all study fields. Reserve-scale fox abundance
was assessed through weekly night-time lamping surveys, and field-scale activity was examined
with tracking plots. In 2009, an MSc student measured the presence and distribution of stoats
and weasels and small mammal populations across three of the five study blocks.
Results: Experimental manipulations were successful in altering field habitats, with sward height
initially higher, and remaining tallest, in the edge of sward treatment fields. The length of
footdrains (shallow linear wet features easily installed in grazing marshes) was increased by
16% in wet treatment fields, and these fields retained water better despite reduced rainfall in
2009 compared to 2008. Lapwing nesting attempts increased in sward, and particularly in wet,
fields, with the distribution shifting towards the centre of wet fields, but towards the edge of
sward fields. There was no substantial change in either number or distribution of lapwing in
control fields, or of redshank across all treatments. Temperature loggers revealed that most nest
predation events occurred at night, and thus must be by mammalian predators. Cameras
recorded few predation events, but all were by foxes. Lapwing nest success varied little between
years, with nests significantly more likely to survive in sward treatment fields in both the pre- and
post- manipulation years. For redshank, nests in all treatments survived significantly better in
2009 than 2008, with a more marked increase in survival in sward fields. Lapwing chicks were
more likely to survive than redshank chicks in both years, and while there was a suggestion that
the habitat manipulations increased chick survival, neither species fledged enough chicks overall
to sustain the wader populations.
Fewer foxes were seen in 2009 than in 2008 over the whole reserve. However, tracking plots did
not show the same pattern, with similar visitation rates found in both years. This suggests these
methods may not produce comparable results. The plots showed foxes moved more evenly
across fields in 2009, whereas they had remained closer to the edge of fields in 2008.
Discussion: The nesting success of both species was highest in sward treatment fields,
suggesting that this manipulation could play a role in increasing wader productivity. This is
particularly interesting as we initially predicted that redshanks’ preference for nesting in taller
vegetation would lead to higher predation rates at the edge of sward fields. However, redshank
nested closer to field edges in all treatments in 2009 compared to 2008, but predation rates
declined. This is important as redshank breeding ecology is more representative of other wader
species that breed on wet grassland e.g. snipe Gallinago gallinago and black-tailed godwit
Limosa limosa. The benefit of the sward treatment may be connected to its effect on small
mammal populations, the main prey of mammalian nest predators. In 2009, small mammal
activity was significantly higher in sward fields than control fields. However, anecdotal evidence
suggests that overall small mammal numbers were low in 2009, so predators may still have
needed to search more widely for food. This, alongside the drier conditions in 2009, could
explain why foxes moved more evenly across fields in 2009. Clearly, if habitat manipulations
were designed to spatially separate predators from lapwing nests, and predator distributions
SID 5 (Rev. 3/06)
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then change, lapwing nest survival is less likely to improve. This may also be a factor in
explaining the increase in redshank nest survival as, if foxes are spending less time on the
edges of fields, then their chances of discovering redshank nests will be reduced.
Creating additional wet features cost approx. £100 ha-1, with such expenditure necessary at
roughly five yearly intervals. However, maintenance of existing features would cost significantly
less. The sward treatment cost approx. £30 ha-1 year-1, but without some suitable wet foraging
habitat, this alone is unlikely to benefit breeding waders. Our research suggests that the nesting
success of a suite of waders could be increased through straightforward habitat manipulations.
The benefits are likely to accrue over time as shifts in wader distribution become more apparent,
and with an increased understanding of the relationship between small mammal cycles and
wader predation. Given the encouraging wader responses to experimental treatments, a second
trial year was proposed for 2010 but, unfortunately, suitable funding was not available to
complete this project. Two avenues for new research are underway though. Chick survival is
arguably the key aspect of wader breeding cycles, yet our understanding of the importance of
different predators is limited because it is difficult to measure, however new technologies are
being deployed to bridge this gap. Research into the dynamics of mammalian predators and
their prey in lowland wet grasslands continues through complimentary postgraduate studies.
These results will further contribute to developing landscape-level improvements in wader nest
survival.
Project Report to Defra
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seeking to publish a full, formal scientific report/paper in an appropriate scientific or other
journal/publication. Indeed, Defra actively encourages such publications as part of the contract terms.
The report to Defra should include:
 the scientific objectives as set out in the contract;
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 possible future work; and
 any action resulting from the research (e.g. IP, Knowledge Transfer).
SID 5 (Rev. 3/06)
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Introduction
Globally, the availability of wetland habitats has at least halved over the past century (Millenium
Ecosystem Assessment, 2005), with such losses, and concurrent declines in biodiversity, particularly
marked within intensive agricultural systems such as those found in western Europe (Donald et al.,
2006). Remaining areas of wetland are also at risk from sea level rise and the increased frequency of
droughts and flooding linked to global climate change (Thompson et al., 2009). The loss of suitable
breeding and wintering habitat has played a major role in the severe declines in breeding wader
populations across Europe (Donald et al., 2001; Wilson et al., 2004; Stillman et al., 2006). In the UK
specifically, species such as lapwing Vanellus vanellus and redshank Tringa totanus have been
affected by direct loss of habitat such as lowland wet grassland (Wilson et al., 2007) and by
degradation of remaining grassland habitat (Wilson et al., 2004). Breeding success is the key limiting
demographic rate for lapwing (Catchpole et al., 1999), and there is a substantial body of knowledge
about the breeding habitat requirements for both the nesting and chick rearing periods of these two
species (e.g.Milsom et al., 2002; Smart et al., 2006; Shrubb 2007; Eglington et al., 2008, 2009).
Options exist within agri-environment schemes (AES) for the creation, restoration and management of
wet grassland habitat for breeding waders (Natural England, 2008).
Large-scale distribution and densities of lapwing and redshank are positively influenced by site wetness
(Smart et al., 2006; Shrubb 2007; Eglington et al., 2008). At a smaller spatial scale, lapwing favour
open short swards for nesting, while redshank prefer a longer sward in which to hide their nests (Smart
et al., 2006; Shrubb 2007). The extent to which sites remain wet is also crucial, as the chicks of both
species require open areas of wet mud and shallow water to forage for invertebrates (Ausden et al.,
2001). Shallow flooding also suppresses vegetation growth, and a mosaic of unflooded grassland,
shallow water and damp mud creates larger areas of suitable wader breeding habitat (Ausden et al.,
2001). However, recent research has shown that the creation or sensitive management of such
habitats, even on reserves dedicated to the success of breeding waders, may not be sufficient to
reverse the declines in wader populations (Stillman et al., 2006; MacDonald & Bolton, 2008). Nest
predation by generalist avian and mammalian predators such as corvids, larids, red fox Vulpes vulpes
and mustelids is natural, but such predators have benefited from the increasing dominance of
agricultural landscapes and a decline in predator control operations (Gregory & Marchant, 1996;
Reynolds & Tapper, 1996). Thus, levels of predation can be sufficient to sustain declines and then
prevent recovery even with the creation and management of suitable habitat.
A long-term experiment on the dynamics of breeding lapwing in relation to crow and fox control
demonstrated that lapwing nesting success can be enhanced by control of these species, but effects
varied and were site-specific (Bolton et al., 2007a). However such predator control is not realistic at a
landscape-scale because of processes such as the immigration of non-territory holding individuals
(Bolton et al., 2007a), increased ethical considerations concerning the culling of native predators, and
the need for collaboration across multiple landholdings. While predator abundance is an important
factor, lapwing also achieve higher rates of nest survival when breeding at higher densities, and when
nests are distant from field edges (MacDonald & Bolton, 2008). Many mammalian predators follow
such linear edges in travelling and hunting within their home ranges, and have only a limited ability to
detect nests while searching for small mammals, typically their main prey (Seymour et al., 2003). Using
habitat manipulations to encourage higher nesting densities within the centre of fields may thus prove
to be highly beneficial for lapwing and, as this species’ aggressive nest defence is often exploited by
other species (Quinn & Ueta, 2008), for other waders as well. The alteration of habitats to achieve
conservation aims is an increasing research area, although implementation largely remains at an
experimental phase (Stillman et al., 2006; Gibbons et al., 2007). Recognition of predation as a key
issue, and explicit attempts to provide a solution through AES may also increase grant uptake by
farmers who often do not feel that current schemes tackle the predation issue (Morris & Potter, 1995;
Smallshire et al., 2004). This is particularly true given that only the more demanding higher level
enhancement schemes were found to benefit both lapwing and redshank populations (Wilson et al.,
2007).
AES are the likely mechanism for delivery of large areas of sympathetically managed breeding wader
habitat in the wider countryside. We investigated the impact of two straightforward habitat
manipulations (see below) on the density, distribution and nesting success of lapwing and redshank
using a before-after controlled experiment (BACE). The manipulations were specifically designed to
SID 5 (Rev. 3/06)
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encourage the mechanisms identified by MacDonald & Bolton (2008) as producing higher lapwing nest
success. However, other waders (e.g. redshank and snipe Gallinago gallinago) typically prefer a taller
sward for breeding, so redshank were also monitored to gain an understanding of the impacts of
habitat manipulations on both species to ensure benefits could be maximised for a suite of wader
species. The specific objectives were:
1) To investigate the effects on in-field wader nesting distribution, density and breeding success of the
two habitat manipulations.
2) To investigate the effects of the habitat manipulations on predator distribution and foraging
behaviour.
3) To quantify the economic cost of each manipulation and provide an overall evaluation of the most
cost-efficient option to benefit breeding waders.
Methods
Study Site
All experimental work was conducted at Berney Marshes RSPB reserve (5235’N 0135’E), a 487 ha
area of lowland wet grassland that supports over 300 pairs of breeding waders. The site is grazed by
commercial livestock, typically at densities of 1 Lu ha-1 to promote a heterogeneous sward suitable for
breeding waders. Previous research demonstrated considerable variation in predation rates between
areas of the reserve that are divided by barriers to predator movement (deep ditches and a railway
line), and which border either more intensive grassland and arable systems or rivers (Eglington et al.,
2008). We used this prior knowledge to ensure our experimental design incorporated this variation in
predation rates, and this resulted in five study blocks across the reserve (Fig. 1).
Habitat manipulations and experimental design
Habitat manipulations were conducted using a BACE approach, and in the baseline monitoring year
(2008), 56 fields were monitored, with nests found in 37 fields. Study fields were selected to cover the
low densities typical of wider countryside sites, up to the high densities found in key fields in nature
reserves. Two habitat manipulations plus controls were implemented between July 2008 and March
2009 and consisted of:
a) ‘sward’ treatment – a 50 m strip around the perimeter of the field was left un-mown in late summer,
with a light dressing of fertiliser (65kg / ha) applied in early March to encourage early grass growth,
with grazing delayed until 15th May.
b) ‘wet’ treatment – additional footdrains (shallow linear channels designed to move water from
ditches to field centres) were added to the central part of these fields (> 50 m from the field edge)
with a rotary ditcher (Eglington et al., 2009). Some footdrains were dammed to prevent water loss
to ditches, and some wet features within edge areas were drained.
c) ‘control’ – no changes in standard reserve management were made in these fields.
Wet feature density was already very high in a few fields (n = 8), and the addition of further features
was deemed unlikely to yield any benefits (M Smart pers. obs.). Therefore, these fields were excluded,
and the wet treatment was assigned at random among the remaining fields in each block. We then
imposed a constraint that adjacent fields sharing an entire boundary could not be allocated to the same
treatment, and randomly allocated treatments to fields (Fig. 1). In only one case was it not possible to
enforce this rule. We tested for biases in both the number of wader pairs and 2008 field-scale nest
predation rates following allocation of treatments, these are described in the statistical analysis below.
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Fig. 1: Map of Berney Marshes study site showing allocation of habitat manipulations between different
study blocks and important boundary features. Fields in white are part of the reserve but were not
included within the experiment.
Habitat assessment
Vegetation and wet features were assessed in all fields in late March – early April (laying phase), and
again in late May – early June (chick-rearing phase). Sward height was assessed using a sward stick
(Stewart et al., 2001) by taking three measures at each of four points along five transects running from
ditch edge to 40 m (total 20 sample points), and at ten points along a transect through the centre of the
field. Wet features were classified following Eglington et al., (2008) as footdrains (shallow linear
channels), footdrain floods (areas of flooding associated with footdrains) and isolated pools (formed in
natural depressions from precipitation). All pre-existing footdrains were digitised on MapInfo using the
Millenium Map 2000, and ground-truthed using hand-held GPS. Newly created footdrains, and all
footdrain floods and pools, were mapped in the field in both years and then digitised. The percentage
cover of water and wet mud within all wet features was assessed from fixed vantage points. Changes
in the vegetation structure enabled identification of the outer extent of dried floods. The total area of
suitable wader foraging habitat (shallow water and wet mud, ha) was calculated from the percent cover
of footdrain floods and pools, and for footdrains as:
Area = 2 * 0.0003 * footdrain length * % appropriate habitat
with footdrains considered to have a suitable feeding strip 30 cm wide on both sides of their length.
Wader nest density, distribution and survival
All fields were surveyed every 4-5 days to locate wader nests, either by observation from a vehicle
(lapwing), or by flushing birds during systematic surveys (redshank). The clutch size, and the length
and breadth at the widest point (0.1 mm) and weight (0.1 g) of each egg was recorded. The number of
days to hatching was calculated using the regression equation derived from successful nests (Smart
2005):
Days to hatch = 271919 * (egg weight / egg volume) - 113.88
with lay dates back calculated from actual or projected (in the case of failed nests) hatch days (laying &
incubation days: lapwing = 31; redshank = 29). Ibutton dataloggers (Maxim Integrated Products Ltd,
CA, USA) were placed in most nests (2008: 70 %, 2009: 100 %) to record the temperature at seven
minute intervals. Nests were monitored every 4-5 days and, if no incubating bird was seen, nests were
visited to check their status. Nests were considered successful if at least one egg hatched. The
temperature trace from the datalogger was examined to determine time and date of failure. When this
was inconclusive, the failure day was taken as the mid point between visits. Causes of nest failure were
classified as predated (eggs missing prior to hatch date and/or remains of eaten eggs present),
deserted (clutch present but cold on two consecutive visits) and trampled (eggs obviously flattened in
the nest). As both species can lay replacement clutches, nests were assigned to either early or late
SID 5 (Rev. 3/06)
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categories depending on the incubation start date relative to the median incubation start date for each
year. Nest cameras (Bolton et al., 2007b) were additionally placed on 100 nests over the two years to
determine the specific identity of predators.
Predator Monitoring
To quantify the relative predation pressure of diurnal avian species that can be important nest (e.g.
carrion crow Corvus corone and other corvids, large gulls Larus spp.) and chick predators (e.g. grey
heron Ardea cinerea, marsh harrier Circus aeruginosus, and other raptors and corvids), we undertook
timed counts of these predators in our study blocks, recording the number of different individuals seen
throughout the field season every 4-5 days. However, the principal predators of lapwing nests are
mammals (Ausden et al., 2009), and most of these events occur during the hours of darkness. At
Berney, the only potential mammalian predators are the red fox and small mustelids such as the stoat
Mustela erminea. Large-scale fox monitoring was carried out through weekly nocturnal lamping surveys
across the whole reserve between early April and the end of June. The route and start point was varied
so that all areas received coverage at different times, and began one hour after sunset using a white
light (1 million candle power). Foxes were searched for by a minimum of two observers standing in the
back of an open top vehicle driven at a constant speed of 10 km hr-1. Block level counts of foxes were
recorded.
Field-scale fox distribution was examined using tracking plots, a method developed and tested by the
Game and Wildlife Conservation Trust (GWCT, M. Short pers. comm.). Plots consisted of a 1 m square
area cleared of vegetation using a turf cutter and filled with fine builders sand that was then sprinkled
with a fine layer of topsoil. A short range bait (‘Chappie’ dog food) was buried in the centre of the plot.
Plots were checked daily (and the soil layer reapplied when necessary) for nine dry nights or until the
plot had been visited by a fox. Heavy rain can disrupt the results of tracking plots, so if plots were
obscured, the period they were run for was extended until nine dry nights had been covered. This
occurred more often in 2008 as it was much wetter than 2009 (see Habitat assessment in results). In
2008, plots were run in 20 fields, divided evenly between four contiguous blocks forming part of the
experimental area (Fig. 1) to control for spatial variation in predation rates. In 2009, the number of
fields was increased to 24, so that two fields under each treatment could be included within each of the
same four blocks. To assess the relative use of field edges versus field centres, five plots were
deployed in each field, one immediately adjacent to the field edge, one at 10 m from the field edge, one
at 30 m and two randomly located within the field centre (>50 m). The three edge track plots were
randomly allocated to a different field edge and distance from the field corner using a random number
generator. Central plots were a minimum of 30 m apart, and all plots were at least 30 m from all entry
and exit points into the field. For logistical reasons it was not possible to run all tracking plots
simultaneously, so plots in two blocks were run in late April, while those in the other two blocks were
run later, in late May and early June respectively in both years. This led to some variation in the rates of
fox activity recorded in different blocks, but this was consistent between years. Complementary
monitoring of mustelid and small mammal activity was conducted by an additional fieldworker as part of
their MSc degree in 2009 only. Tracking tunnels adapted from the GWCT’s mink raft (Reynolds et al.,
2004) were examined weekly and run throughout the wader breeding season in all fields in three of the
study blocks (Blocks 1,2 & 4, Fig. 1, Robertson, 2009).
Extensive efforts were made to attempt to live-capture one or more foxes. This involved the
construction and deployment of six large cage traps during the winter of 2008, and the baiting and
checking of these prior to, and throughout, the 2009 wader breeding season. In addition, a lightweight
GPS collar with remote release capability was developed in-house at the RSPB for deployment on any
captured individuals. This work was undertaken to try and gain a better understanding of the
movements of this important predator at both a within-block and, more importantly, at a within-field
scale during the period when nests and chicks would be at risk of predation. Such information would be
very useful in elucidating any changes in fox behaviour between treatment types. Unfortunately,
although foxes were visiting some of the traps during the pre-baiting period, these visits stopped prior
to the desired capture period. Thus, despite much effort, this technique did not prove successful so will
not be discussed further.
Chick Survival
Most chicks hatching from monitored nests, and any subsequently found in study fields, were ringed
with both a BTO metal ring and a combination of a coloured ring and a legflag bearing a unique two
SID 5 (Rev. 3/06)
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digit code. In addition to these colour markings which allow individual recognition in the field, a 0.4g
radio transmitter was glued to the down on the back of a subsample of chicks. This sample was spread
between species, study blocks and time of hatching to cover the full range from early to late hatching
as it is known that later hatching chicks are less likely to fledge. Once tagged, chicks were monitored
every second day until fledging, death, shedding of the tag or disappearance. Chicks were radiotracked
from a vehicle using a Telonics receiver and three-pronged Yagi antenna, with time and field location
recorded. Extensive efforts were made to relocate chicks that ‘disappeared’. Due to the need to reduce
weight, tag batteries are small and short-lived, so a cut-off point of 20 days was used to census chick
survival, as beyond this time tag failure on a perfectly healthy chick becomes an increasing possibility
with each day that passes. Bill length and weight were recorded on all newly ringed chicks, and tagged
chicks were recaptured every seven days to repeat these measurements and ascertain chick condition
while minimising disturbance (Sharpe et al., 2009).
Statistical Analysis
Vegetation height measurements were pooled within the edge and middle transects to create average
field values for both transects at each visit. These were natural log transformed to conform to
assumptions of normality, and differences between the edge and middle in the laying phase, and in the
edge of fields at laying and chick-rearing phases were examined with ANOVAs including transect and
treatment and their interaction as factors. The availability of wet features was summed by feature type
for each treatment for both assessment periods. Footdrains were the manipulated feature, so the
extent to which these provided suitable foraging habitat was examined by calculating the length of
footdrain required to produce one hectare of wet habitat.
The number of breeding wader pairs in fields assigned to different treatments and variation in fieldscale predation rates was examined using a general linear model (GLM) with a poisson error structure
and log link function and a binomial error structure and logit link function respectively. Nest survival of
both species was examined using Mayfield logistic regression with a generalised linear mixed model
(GLMM) with a binomial error term and logit link implemented in the lme4 package within R (R
development core team 2009). As we were examining the specific effect of implemented habitat
manipulations, year, treatment, study block (the area of the reserve) and lay date (early or late) were
fitted as fixed factors with all two-way interactions, with nest field included as a random term. Model
selection was based on AIC values, with model averaging of terms included in models within 2 ΔAIC
units of the most favoured model (Burnham & Anderson, 2002).
The occurrence of foxes at tracking plots was modelled as a binomial trial using a GLMM with logit link
and binomial error term. Field identity was included as a random term to control for any between-field
variance. Two different metrics of plot position were modelled. In the first analysis, plots were modelled
at the four different position levels (i.e. 0, 10, 30 and >50 m from the field edge). In the second, the first
three plot positions were all considered to be ‘edge’ plots, with the remaining two considered as
‘middle’, and then visitation rates were modelled on this two level metric (EorM). Other factors included
in the models were year and block, the latter included in all models to account for known variation in fox
activity within the reserve.
Chick survival was modelled using logistic regression with a GLMM with a binomial error term and logit
link. Data from chicks of both species was pooled, with daily chick fate as the response variable and
species, year, block, treatment of hatch field, and treatment of current location as fixed factors, and
chick age, hatch day, fox rate (models were run both with number of foxes seen per hour in lamping
surveys in the relevant block in the relevant month and separately with the tracking plot hit rate for the
relevant block in the relevant year) and two avian predator rates (number of potential chick predators
seen per hour in the relevant block at a) the midpoint of the chick’s known survival period, and b) on
the last day the chick was recorded) as covariates, and chick ID as a random term. For a few chicks,
the avian predator rate was found to be extremely high either because a large corvid flock had been
observed or because several predators were seen in only a very short observation window. The
analysis was run after excluding these chicks (n = 12), and avian predation rates were found to no
longer feature in strongly supported models. The results from this latter analysis are presented. To
examine the impact of movement on chick survival, only those individuals which survived to at least 10
days of age were included, and their survival was modelled with a similar GLMM incorporating extent of
movement (number of times a chick was found in a different field over its tracked lifespan) as a three
SID 5 (Rev. 3/06)
Page 9 of 25
level factor (no change in field, 1-2 field changes, >2 changes) alongside year, species, hatch day and
chick ID as specified above.
To assess whether treatment affected chick body condition, independent of chick age, a logistic growth
curve was fitted to the relationship between chick age and mass with the formula:
Chick body mass = m / (1 + T * exp(- k * chick age)
where m = asymptotic mass, T = age at curve inflection, and k = the growth coefficient
An index of chick body condition was then calculated as per Eglington et al. (2010) from the
standardized residuals obtained from these curves. Separate curves were fitted for lapwing and
redshank in each year. The impact of treatments on chick condition (and so, potentially, survival) were
examined using a GLMM with a normal error term and identity link, with year, species, treatment of
hatch field, and treatment of current location as fixed factors, and chick ID as a random term.
Results
Experimental design
In 2008, redshank nests suffered consistently higher daily predation rates than those of lapwing (X21 =
7.10, p = 0.008) but, after accounting for this consistent species effect, there was no overall difference
in predation rate (X23 = 0.09, p = 0.96) between treatments. There were also no differences in the
distribution of lapwing pairs in relation to the treatment allocation (X22 = 1.69, p = 0.43). Although there
is a significant difference in the field-scale distribution of redshank (X22 = 6.13, p = 0.047), this is solely
due to a difference in redshank numbers in fields allocated to the ‘wet’ and ‘sward’ treatments (X21 =
5.87, p = 0.02). There are no significant differences in the number of redshank in either of these
treatments compared with the controls (X21 = 1.52, p = 0.22, and X21 = 1.65, p = 0.20 respectively).
Since the key comparison is between habitat manipulations and control fields, this difference in
redshank numbers between the two experimental treatments was not considered problematical.
Habitat assessment
Experimental manipulations successfully altered field habitats. Vegetation height in field edges was
significantly greater than in field centres (treatment F2,138 = 3.17, p = 0.04; transect position F1,138 =
13.58, p = 0.0003), and sward height increased significantly between measurement phases (treatment
F2,138 = 3.88, p = 0.02; phase F1,138 = 49.33, p <0.0001). Changes in all treatments were in the same
direction i.e. edge vegetation was taller than central vegetation, and became still taller as the season
progressed, with vegetation initially higher, and remaining tallest, in the edge of sward fields (Table 1).
The length of footdrains was increased overall by 16% in wet treatment fields (Table 2). However, as
2008 was a much wetter spring than 2009 (Berney Marshes reserve data, Mar – May average monthly
rainfall: 2008, 35.6 mm; 2009, 16 mm), field wetness was significantly lower in all fields in both
assessment periods in 2009 compared to the same fields in 2008 (all wet features combined (ha),
mean ± se, early 2008: 1.86 ± 0.22; early 2009: 1.54 ± 0.19; late 2008: 0.71 ± 0.11; late 2009: 0.34 ±
0.06; t71 = 5.06, p <0.0001). Lower precipitation reduced the availability of feeding habitat in pools and
footdrains and, because the latter were not full, in footdrain floods as well (Table 2). Despite the
reduction in precipitation, wet fields had better water retention, as the total length of footdrain required
(m) to create one hectare of feeding habitat decreased in wet fields between years (2008 = 3541, 2009
= 3220), but increased in both control and sward fields (control: 2008 = 2846, 2009 = 3001; sward:
2008 = 3199, 2009 = 3517).
Table 1: Mean (se) vegetation heights (cm) in the edge and middle of experimental treatment fields
manipulations in 2009 in both assessment periods.
Treatment
Control
Sward
Wet
Edge early Middle early Edge late
3.5 (0.3)
3.3 (0.2)
6.8 (0.9)
4.8 (0.5)
3.0 (0.4)
9.9 (1.1)
4.0 (0.3)
3.1 (0.4)
6.1 (0.7)
Middle late
5.8 (0.8)
5.8 (0.4)
4.3 (0.7)
Table 2: Total extent of wet features of each type and the combined flooded foraging habitat in the
three experimental treatments in both study years at early (late Mar – early Apr) and late (late May –
early June) assessment periods. Footdrain lengths did not change between assessment periods.
SID 5 (Rev. 3/06)
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Wet Feature
Footdrain length (m)
Area of footdrain floods (ha)
Area of pools (ha)
Total foraging habitat (ha)
Year
2008
2009
2008
2009
2008
2009
2008
2009
Control
Early
Late
9 616
9 638
15.35
4.86
13.89
1.28
0.39
0.07
0.27
0.00
21.18
8.26
18.87
3.10
Sward
Early
Late
13 030
13 153
20.01
7.39
14.92
4.08
0.45
0.11
0.13
0.00
27.76
11.46
21.09
6.14
Wet
Early
Late
10 615
12 350
9.64
2.11
9.29
0.87
2.40
0.72
0.25
0.00
18.20
5.78
15.63
3.04
Wader nest density, distribution and survival
The number of lapwing nesting attempts increased in wet and sward fields with more marked increases
in wet fields, and the distribution shifted towards the middle in wet fields and towards the edge in sward
fields (Table 3). There was no substantial change in either number or distribution of lapwing in control
fields, or of redshank across all treatments (Table 3). Results from nest data loggers revealed that the
majority of recorded nest predation events occurred during the hours of darkness (84% of 100 nests
over both years), and so must have been due to mammalian predation. Cameras successfully recorded
11 predation events, all at night, with red fox being the only species observed.
Table 3: Total number of nesting attempts for both species in both study years grouped by field
treatment type, showing the change between study years.
2008
Species Treatment
Lapwing
Control
Sward
Wet
Control
Redshank Sward
Wet
2009
edge
28
14
19
middle
18
31
15
total
46
45
34
edge
31
23
27
middle
16
31
33
total
47
54
60
12
16
15
10
9
7
22
25
22
16
14
15
6
6
5
22
20
20
Change between
years
edge Middle total
+3
-2
+1
+9
0
+9
+8
+ 18
+ 26
+4
-2
0
-4
-3
-2
0
-5
-2
The most parsimonious model of nest survival differed between species (Table 4). For lapwing, there
were two strongly supported models, both of which contained treatment as a main effect, with nest
survival higher in the sward treatment (Fig. 2a), but the interaction between year and treatment was not
important. For redshank, there were also only two competing models, with year the principal factor of
interest in the most favoured model. Nest survival increased significantly across all treatments between
years (Fig. 2b), so again the interaction term was not strongly supported. Lay date (early/late)
explained additional variation in nest survival for both species, and block also explained some variation
in redshank survival, reflecting the known benefits of early nesting and the known differences in
predation rates in different parts of the reserve. Higher densities of nesting lapwing also increased nest
survival, again a result previously described and which the manipulations succeeded in promoting.
Table 4: Generalised linear mixed models of species-specific nest survival for a) lapwing and b)
redshank. For full details on model parameters see methods. Field was included as a random term in
all examined models. ΔAIC is the difference between AIC values for each model and that with the
lowest AIC, and w is the AIC weight. Models with ΔAIC > 2 are not displayed.
a)
Model Parameters
AIC
ΔAIC
w
Model likelihood Deviance
Treatment, Lay date, Nest density
366.5
0
0.41
1.00
354.5
Treatment, Lay date, Nest density, Year
367.3
0.8
0.27
0.67
353.3
SID 5 (Rev. 3/06)
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b)
Model Parameters
Year, Block, Lay date
Year, Block
AIC
112.8
113.5
ΔAIC
0
0.7
w
0.49
0.35
Model likelihood Deviance
1.00
96.79
0.70
99.46
Estimates of daily nest survival from the model averaged results for each species show these changes
between treatments (for lapwing) and years (for redshank) lead to biologically important differences in
the probability of nests surviving to hatch. For redshank, hatching success in 2008 was 7 %, but this
increased to 18 % in 2009. Examination of straightforward Mayfield estimates for changes in redshank
survival in different treatments suggest even greater improvements, particularly in sward fields where
the probability of surviving incubation (± 95% CI) changed from 2008 = 9.8 (2.8 – 32.3), 2009 = 69.7
(48.8 – 99.1). However, the powerful effect of year as an explanatory variable in the linear model
means that treatment does not feature in highly favoured models, so differences between treatments
are less apparent than differences between years. For lapwing, model averaged hatching success was
almost identical between years but varied between treatments: control 22 %, sward 34 %, wet 24 %.
These hatching rates reveal that, despite efforts to reduce nest predation within the reserve, hatching
success is still not high, and is particularly low for redshank. Thus, even small improvements generated
through the manipulations are beneficial.
Fig. 2: Significant effects on daily failure rates from the best nest survival models (mean  95% CI) for
a) lapwing showing the effect of habitat manipulations and b) redshank showing the effect of year.
Predator Monitoring
The principal avian predators observed were carrion crow, grey heron and marsh harrier. Over the
entire reserve, average avian predator counts were 2.31 hr-1 in 2008 and 2.45 hr-1 in 2009. The
percentage composition of types varied little overall between years with corvids the most frequently
observed, and raptors the least often recorded.
Table 5: The average number of adult foxes seen per hour of survey effort in 2008 and 2009, and the
percentage change between years, in the different study blocks.
Reserve area
Old arable
Office
Shearmans
Wickhampton
Mean adult foxes hour of survey-1
2008
2009
% change
1.5
0.6
-57.7
0.6
0.2
-66.7
0.4
0
-100.0
4.2
0.7
-83.3
Lamping surveys showed that fox abundance varied greatly both between years and between blocks
on the reserve (Table 5). While the between-block variation was anticipated, the large reduction in
sightings of foxes in all study areas in 2009 was not. These patterns were not confirmed by the footprint
tracking plots however. The overall tracking rate did not differ between years, suggesting no difference
in overall levels of fox activity, and considerable numbers of plots were tracked by foxes in blocks with
very few sightings during lamping surveys. When plot position was modelled as EorM, then plot
SID 5 (Rev. 3/06)
Page 12 of 25
position was strongly favoured in the models explaining the likelihood of a plot being tracked (Table
6a), with edge plots more likely to be visited (Fig. 3a). However, this effect was much weaker when all
plot positions were included (Table 6b), although edge plots had higher visitation rates than middle
plots (Fig. 3b). While the interaction between
Fig. 3: Daily probability of foxes visiting tracking plots for both years combined for a) edge (<50 m to
field edge) versus middle (>50 m) only and b) for all plot distances.
year and plot did not feature in the top model, it was still a competing model when EorM was
considered. This reflects a less definite pattern in 2009, with fox activity not as confined to field edges
as was found in 2008 (Fig. 4) (2008: 23 = 9.10, p = 0.02; 2009: 23 = 0.46, p = 0.92). It was not
possible to compare the effect of treatments across years as fox plots were created in 2008 prior to any
knowledge regarding treatment assignment to fields, and plots were placed in different fields between
years. However, examining the effect of treatment within 2009 alone suggests that it may contribute in
a minor way, with fox visitation at plots more frequent in both treatment fields than in control fields.
Tracking tunnels for mustelids and small mammals revealed an increase in both mustelid and small
mammal activity in sward fields as compared to control and wet fields (Fig. 5), with field edge sward
height a significant predictor of mustelid and small mammal presence (Fig. 6).
Table 6: Generalised linear mixed models of tracking plot visitation by foxes for a) plots split by position
(edge v middle) and b) all plot positions (0, 10, 30 and >50 m from field edge). For full details on model
parameters see methods. Field was included as a random term in all examined models. ΔAIC is the
difference between AIC values for each model and that with the lowest AIC, and w is the AIC weight.
a)
AIC
ΔAIC
w
Model likelihood
Deviance
Position, Block
Position, Year, Block, Position:Year
199.7
200.9
0.0
1.2
0.45
0.25
1.00
0.55
187.7
184.9
Position, Year, Block
Year, Block
201.7
202.0
2.0
2.3
0.16
0.14
0.37
0.32
187.7
190.0
AIC
ΔAIC
w
Model likelihood
Deviance
Year, Block
Plot, Block
202.0
202.9
0.0
0.9
0.52
0.33
1.00
0.64
190.0
186.9
Plot, Year, Block
Plot, Year, Block, Plot:Year
204.9
207.6
2.9
5.6
0.12
0.03
0.23
0.06
186.9
183.6
SID 5 (Rev. 3/06)
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Model Parameters
b)
Model Parameters
Fig. 4: Probability of fox plot visitation rate ( se) for 2008 (white bars) and 2009 (grey bars) showing
variation between years in visit likelihood.
Fig. 5: Number of tracking tunnels in each treatment where small mammals were present and absent
(total n = 104). From Robertson (2009).
SID 5 (Rev. 3/06)
Page 14 of 25
Fig. 6: Change in probability of presence for A) small mammals and B) mustelids with increasing sward
height. Histograms represent sward height at tracking tunnels where small mammals and mustelids
were found to be absent (bottom) and present (top). From Robertson (2009).
Chick Survival
A total of 778 chicks were ringed over the two study years (2008: 249 lapwing, 71 redshank; 2009: 344
lapwing, 114 redshank), with 125 chicks monitored using radio transmitters (2008: 39 lapwing, 16
redshank; 2009: 52 lapwing, 18 redshank). Survival varied between species and year, with lapwing
chick survival higher than that of redshank chicks in both years (survival to 20 days, lapwing 2008:
43%, 2009: 14%; redshank 2008: 19%, 2009: 6%). However, these differences were not large enough
for species to feature as a significant factor in the most supported models (Table 7).
Table 7: Generalised linear mixed models of chick survival. For full details on model parameters see
methods. Chick ID was included as a random term in all examined models. ΔAIC is the difference
between AIC values for each model and that with the lowest AIC, and w is the AIC weight.
Model Parameters
AIC
Hatch Treatment, Where Treatment, Chick age,
Hatch day, Fox, Chick ID
575.8
Hatch Treatment, Where Treatment, Chick age,
Hatch day, Fox, Year, Chick ID
576.1
Hatch Treatment, Where Treatment, Chick age,
Hatch day, Fox, Year, Block, Chick ID
577.6
ΔAIC
w
Model Likelihood
Deviance
0.0
0.34
1.00
557.8
0.3
0.29
0.86
556.1
1.8
0.14
0.41
551.6
Removal of either treatment of hatch field or treatment of field where chick was observed caused
significant changes in the deviance of the model and produced models with a much poorer fit, even
though large differences in survival rates between different treatments were not apparent (Fig. 7). This
suggests that there is a large degree of uncertainty and unexplained variation within these models,
reflecting the need for a greater understanding of this part of the reproductive cycle. However, it is clear
that overall survival rates were poor across the entire reserve in both years.
Later hatching chicks are known to have poorer survival, and older chicks are more likely to survive, so
the inclusion of these parameters in favoured models was expected. Interestingly, the observed fox
density was also an important model factor, with chick survival found to be lowest when the fewest
foxes were seen (Fig. 8). This pattern was almost identical when activity from tracking plots was
included as the measure of fox abundance instead, so this result is not shown. So, although there was
a discrepancy between fox activity seen on lamping surveys and that found from tracking plots, this
was not reflected here. In both cases, increasing fox activity was associated with increased chick
survival. The number of times chicks were recorded as moving between fields did not influence
survival, with none of the competing models containing the chick movement factor. Chick condition did
SID 5 (Rev. 3/06)
Page 15 of 25
not vary significantly between years or species (mean  sd, lapwing 2008: 0.004  0.18, lapwing 2009:
0.031  0.15, redshank 2008: 0.022  0.15, redshank 2009: 0.019  0.19). The null model, with no
variables other than the random term was the best performing model explaining impacts on chick
condition, so these results are not displayed. However, this does suggest that treatments did not
appear to have an important bearing on chick condition.
Fig. 7: Effect of experimental treatments (mean  95% CI) on daily chick survival of radio-tagged chicks
for a) treatment of hatch field and b) treatment of occupied field.
Fig. 8: Effect of fox density recorded from weekly lamping surveys on daily probability of chick
predation (mean  95% CI).
The overall effect of treatments on breeding success of both wader species from Mayfield estimates of
hatching and fledging success can be seen to vary significantly between years and treatment types
(Table 8). While annual variation clearly had a very important impact, with low chick survival leading to
much poorer overall breeding success for both species in 2009, this impact was buffered to a greater
degree in sward treatment fields where both nest and chick survival was highest.
SID 5 (Rev. 3/06)
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Table 8: Overall parameters of breeding success split by species, year and treatment type. As the
majority of chicks did not move between treatment types, treatment type for chicks is considered to be
the treatment of the field in which they hatched. PSI = probability of surviving incubation, FS = fledging
success. Fledging success is based on survival to 35 days for lapwing and 30 days for redshank.
Species
Year
2008
Lapwing
2009
2008
Redshank
2009
Parameter
Number of nests
PSI (%)
Nests hatching
Mean clutch size
Total chicks hatching
FS (%)
Total chicks fledging
Chicks fledging per nest
Number of nests
PSI (%)
Nests hatching
Mean clutch size
Total chicks hatching
FS (%)
Total chicks fledging
Chicks fledging per nest
Control
46
0.29
13.3
3.8
50.7
0.15
7.6
0.17
47
0.29
13.6
3.8
51.8
0.01
0.5
0.01
Sward
45
0.48
21.6
3.8
82.1
0.27
22.2
0.49
54
0.52
28.1
3.8
106.7
0.09
9.6
0.18
Wet
34
0.29
9.9
3.8
37.5
0.43
16.1
0.47
60
0.30
18.0
3.8
68.4
0.03
2.1
0.03
Change in fledging 08-09
Number of nests
PSI (%)
Nests hatching
Mean clutch size
Total chicks hatching
FS (%)
Total chicks fledging
Chicks fledging per nest
Number of nests
PSI (%)
Nests hatching
Mean clutch size
Total chicks hatching
FS (%)
Total chicks fledging
Chicks fledging per nest
-7.1
22
0.11
2.4
3.8
9.2
0.21
1.9
0.09
22
0.40
8.8
3.8
33.4
0.08
2.7
0.12
-12.6
25
0.04
1.0
3.8
3.8
0.23
0.9
0.03
20
0.61
12.2
3.8
46.4
0.07
3.2
0.16
-14.1
15
0.13
2.0
3.8
7.4
0.06
0.4
0.03
20
0.55
11.0
3.8
41.8
0.01
0.4
0.02
Change in fledging 08-09
0.7
2.4
0.0
Discussion
Wader nest density, distribution and survival
We have demonstrated that simple manipulations can successfully alter wader breeding habitat, and
that these have the potential to improve nest survival, even on a relatively short time scale when
compared to the ecological processes involved. For example, waders are highly site faithful (Thompson
& Hale, 1989; Thompson et al., 1994), and so dramatic changes in nest distribution would not be
expected when the entire reserve is being managed for breeding waders. Manipulations successfully
encouraged lapwing to nest in central areas and at higher densities in wet fields, but in sward and
control fields the opposite trends were observed (Table 2). The substantial increase in lapwing nesting
attempts on wet fields suggests that birds were identifying this as suitable nesting habitat despite the
decrease in spring rainfall.
SID 5 (Rev. 3/06)
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Overall, nest survival was higher across all study fields combined in 2009 than 2008, with this
difference being driven primarily by biologically significant improvements in redshank nesting success.
Lapwing nest survival did not significantly change in any treatment, but was highest in sward fields.
Lapwing nesting nearer field edges have higher predation rates (MacDonald & Bolton 2008), so there
was the potential for redshank to fare poorly in sward fields where the species’ preference for nesting in
taller vegetation could have created an ecological trap (Robertson & Hutto, 2006). However, redshank
nested closer to field edges in all treatments in 2009 compared to 2008 (Table 2), but predation rates
declined. This is particularly important as redshank breeding ecology is more representative of other
wader species that breed on wet grassland e.g. snipe and black-tailed godwit Limosa limosa.
The nesting success of both species was highest in sward treatment fields, suggesting that this
manipulation could play a role in increasing wader productivity when applied to areas already
containing suitable foraging habitat. However, lapwing nest density did not increase in these fields, so it
cannot be the result of improved mobbing defence (Quinn & Ueta, 2008). The principal predator of
lapwing nests in the UK is the red fox (Ausden et al., 2009), although predation on wader nest is
incidental while foxes search for small mammals, their primary prey (Seymour et al. 2003). Numerous
studies have demonstrated the impact that declines in small mammal numbers can have on predation
rates on ground-nesting birds such as waders (e.g. Beintema & Muskens, 1987; Blomqvist et al., 2002;
Brook et al., 2005). In 2009, small mammal activity was significantly higher in sward fields than control
fields (Robertson, 2009). Field voles Microtus agrestis are particularly sensitive to over-grazing
(Battersby 2005, Evans et al., 2006) and changes in field margins (Macdonald & Tattersall, 2001), and
so are likely to have benefited from this treatment. Both foxes and mustelids have been found to
preferentially use corridor strips rather than surrounding hayfields (Salek et al., 2009), and so may have
used these margins for both movement and hunting when available.
An increase in favoured prey may have allowed small predators such as mustelids to concentrate their
activities within taller field margins and/or focus on such prey, and thus have little impact on wader
nests. However, anecdotal evidence suggests that small mammal numbers were low in 2009
(http://www.bto.org/survey/bomp/latest_info.htm, accessed 11-12-09), and Beintema & Muskens (1987)
found that the impact of low small mammal numbers was greatest on early nesting species such as
lapwing. Such patterns may explain why nest survival increased considerably more for later nesting
redshank than for lapwing.
Predator monitoring
Foxes were likely to be the most important predator of wader nests at Berney Marshes. They were the
only predator captured by remote cameras predating nests and, as the vast majority of nests were
predated during the hours of darkness, it is likely that foxes were the predator in many of these
instances. Our monitoring found strong variation in both within-field fox activity and overall fox
abundance both between years, and between blocks of the reserve. While tracking plots suggested
there was still an overall decreased likelihood of foxes being present closer to field centres, foxes
clearly ranged more evenly across fields and so spent more time further from field boundaries in 2009
compared to 2008 (Figs. 3, 4). Such changes in predator behaviour may be a result of lower primary
prey availability and an increased need to search for food. While small mammal numbers in sward
treatment field margins may have been sufficient to support the low numbers of mustelids present on
the reserve (Robertson, 2009), larger species such as foxes may have needed to range more widely to
find sufficient food. They may also be a reflection on the dryer nature of the study site in 2009, with
reduced overall site wetness allowing foxes easier access across fields, resulting in a change in
distribution. In the wetter summer of 2008, foxes may have been more inclined to remain close to the
drier edges of fields rather than cross through the centres. However, in 2009, when surface flooding on
most fields was considerably lower or absent, foxes may have more readily explored these additional
dry areas, and so the reduction in predator tracking rates seen towards the centre of fields in 2008 may
not have translated into increased central nest survival in a drier year when such patterns were not
apparent. Unfortunately the direct impact of habitat manipulations on within-field fox distribution could
not be examined as, in 2008, plots had to be dug and run prior to the allocation of treatments, as this
was only ascertained at the conclusion of the 2008 field season. The same fields were not necessarily
used in 2009 when tracking plots were spread between treatment types, and so this comparison could
not be drawn. However, clearly if habitat manipulations were designed to spatially separate predators
from avian prey and predators then change their spatial distribution, effects on nest survival are likely to
SID 5 (Rev. 3/06)
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be diminished. This may also be a factor in the increase in redshank nest survival as, if foxes are
spending less time on the edges of fields, then their chances of discovering redshank nests will be
concomitantly reduced.
The difference seen between fox activity noted using tracking plots and that of actual animals observed
during lamping surveys suggests that the results from these two methods are probably not comparable.
In particular, the most northerly block of the reserve, which is bordered on three sides by agricultural
land, had relatively high fox activity based on both tracking plots and numbers of predated nests
(including a number of recorded images from nest cameras). However, only two individuals were seen
in this block on one lamping survey over two years. It may well be that scat transects (Webbon et al.
2004) are a less demanding way of obtaining fox abundance data than either of the two approaches
used in this project, and comparison of a variety of assessment methods is underway. However,
tracking plots were extremely useful for resolving specific experimental questions with regards to the
treatment manipulations applied in this study.
Avian species are clearly far less significant predators of wader nests than mammalian species.
However, at the chick stage a number of species, such as marsh harriers, kestrels Falco tinnunculus
and grey herons are known to have an important impact (Teunissen et al., 2008). This is likely to be
true at Berney, and a number of clearly avian predated chicks were found as the radio tags were still
functioning. However, recovery of operational radio tags will be biased towards chicks killed by avian
predators as they are more likely to pluck their prey and thus remove the tag without damaging it.
Therefore simple tag recovery does not reveal the relative importance of avian and mammalian
predators as the latter, particularly foxes, are likely to consume chicks in their entirety, and tags are
unlikely to survive either chewing or digestion. More focussed observation, possibly combining both
study of waders and study of prey brought to avian predator nest sites, would provide greater detail on
the relative importance of this suite of predators.
Chick survival
Chick survival in our study is only considered up to 20 tag-days as tag signals become less reliable
after this point. However, some chicks were known to have survived right through to fledging and
beyond with functioning tags. Extensive efforts were made to relocate chicks that had ‘disappeared’
both prior to and after the 20 day limit, but many were never relocated and it is presumed that the
majority of these chicks were predated. Berney provides the most suitable chickrearing habitat in the
area so movement away from the site was doubtful (but was searched for). However, tags are unlikely
to survive the digestive tract of predators such as foxes, and avian species may carry them far beyond
detection range. Of those predated chicks that were recovered (n = 20), seven were taken by an avian
predator, four by a mammalian predator and in four the predator could not be ascertained, with the
remainder dying for non-predation reasons.
The use of automatic radio tracking stations (ARTS) was trialled at Berney in 2009 and funded by
Natural England. These stations monitor the frequencies of radio transmitters within range of the
tracking station, 24 hours a day, and the timing of signal disappearance is indicative of different
predators in the same way that temperature loggers operate for nests. We monitored 21 chicks using
these ARTS (14 lapwing & 7 redshank). Of these 21 chicks, nine disappeared during daylight hours,
one at dawn and 11 during the night, suggesting that 52% of chicks are predated by nocturnal
mammals, with the remainder taken either by avian predators or diurnal mammals such as stoats and
weasels. Indeed, one radio-tagged lapwing chick was observed being taken by a weasel in 2009 (J.
Smart pers comm).
Two metrics of fox abundance were examined separately in the chick survival models, and both were
found to be important explanatory components of the models in which they featured. This is interesting
as the results from lamping surveys differed strongly from those found from tracking plots operated in
the same areas. One area of the reserve in particular had high fox activity as measured by tracking
plots in both years, yet almost no foxes were ever seen on lamping surveys in either year. This may be
a highly biologically relevant result though, as small mustelids such as stoats could be more important
predators of chicks than eggs, and may be more important in this respect than foxes. Larger predators
are known to actively kill and/or displace smaller ones (Donadio & Buskirk 2006, Ritchie & Johnson
2009), and smaller predators are often found at lower densities in the presence of their larger
competitors (Ritchie & Johnson 2009). Robertson (2009) found a decrease in mustelid activity in the
SID 5 (Rev. 3/06)
Page 19 of 25
area where lamping surveys recorded the highest number of fox sightings, and there is limited
evidence for this specific relationship from elsewhere in Europe (e.g. Lindstrom et al. 1995). Given that,
in most contexts, the key chick predators of most wader species remain unknown, this relationship
merits further study.
Treatment of both hatch fields and final observation fields was also found to be important in chick
survival models. While differences between treatments were not significant, removal of either of these
terms resulted in very poor model performance. Chicks hatching from sward fields had higher survival
rates, and this was also reflected in the fields chicks were subsequently observed in, where chicks in
both sward and wet treatments were more likely to survive. While these results may hint at ecological
differences between treatment types and their impact on chick survival, the key factor is that overall
chick survival rates for both species were not sufficient to sustain the breeding populations (Insley et al.
1997, Catchpole et al. 1999). Body condition of tagged chicks did not vary significantly between either
species or years. A caveat here is that more data was available for older lapwing chicks in 2008
because a greater proportion of tagged chicks survived for longer than in 2009, so curve estimates for
lapwing in 2009 are likely to be less robust. Thus lower survival rates observed in 2009, as compared
to 2008, may still be at least partly explained by the drier conditions leading to a reduction in suitable
chick foraging habitat and prey availability, although this is not certain. Regardless, it is clear that much
additional work on addressing this key breeding parameter is still required.
Cost-benefit evaluation and conclusions
An important part of implementing an AES is the cost of suggested methodologies. Creating additional
wet features cost approx. £100 ha-1, with such expenditure necessary at roughly five yearly intervals.
However, these features were added later in the year than initially intended when the ground was much
dryer and harder. Under more ideal digging conditions the rotary ditcher could be expected to install
footdrains at a rate of approximately 200 m hr-1, and this would reduce costs by about one third. The
sward treatment cost approx. £30 ha-1 year-1, but without some suitable wet foraging habitat, this alone
is unlikely to benefit breeding waders. This treatment is also susceptible to the vagaries of fertiliser
pricing (Table 9). Thus, it may be necessary to tailor management dependent on existing features. For
example, under current higher level stewardship schemes (HLS) where breeding waders are already
present, or habitat is being restored to enhance its condition and suitability for breeding waders, many
of the costs involved in the wet treatment (such as the need to create wet features themselves) will be
substantially reduced, and only maintenance of existing features may be necessary. If such
maintenance was combined with suitable mowing to create a tall field edge sward, additional costs
could be small. However, in the case of starting from scratch in an arable reversion where all wet
features need to be created, initial costs will be much higher.
Table 9. The economic cost of manipulating the vegetation in field edges and improving the wet
features in field centres. Fertiliser was applied at the rate of 65kg/ha.
Treatment
Detail
Vegetation
Field margin mowing
Fertiliser Purchase
Fertiliser Application
Wet features Contractor charges
Supervisor charge
Internal ditcher charge
Amount
30.30 Ha
3.25 tons
47.62 Ha
Total
hours
£/hour or
ton
Cost (£)
Total cost
(£) £ per ha
20.03
8.50
£33.00
£345.00
£47.60
£660.99
£1,121.25
£404.60
£2,186.84
63.00
63.00
£10.53
£13.00
£5,661.87
£663.39
£819.00
£7,144.26 £103.21
£28.07
Our research suggests that the nesting success of a suite of waders could be increased through
straightforward habitat manipulations, and we intend to continue to investigate these manipulations in
2010 to further clarify their impacts and the underlying mechanisms, as well as investigating chick
survival, another key demographic parameter. This is particularly important as, even with improvements
in nest survival, the current levels of chick survival do not ensure improvements in overall breeding
success. However, the relative importance of key chick predators are unknown, although the list of
species is undoubtedly more extensive than that for nest predators. The pilot study in 2009 using ARTS
SID 5 (Rev. 3/06)
Page 20 of 25
to monitor chicks (so that their presence is recorded every few minutes) revealed that chicks were
‘disappearing’ (equated to predation) evenly between day and night, in contrast to the heavily nighttime biased predation of nests. Subsequent research starting this summer will focus on improving
understanding of this breeding metric and the main wader chick predators. Research into the dynamics
of predators and prey, particularly small mammals, on lowland wet grassland will also continue through
complimentary postgraduate studies (R. Laidlaw, UEA/RSPB PhD). With increasing study it is clear that
even superficially simple foodwebs can have a high degree of complexity, with declines in the
population of one species having a range of knock-on and counter-intuitive effects on others. An
example of this can be seen in a simple high Arctic system where lemmings Lemmus spp. typically
support arctic foxes Alopex lagopus. However, in poor lemming years, predation pressure increases
substantially on ground-nesting birds such as red knot Calidris canutus and curlew sandpiper C.
ferruginea (Blomqvist et al., 2002).
Thus a fuller understanding of predation at all breeding stages will hopefully allow for the development
of a habitat manipulation approach that benefits the entire breeding cycle, building on these results.
Our current manipulations could easily be incorporated into an AES, and this would be the goal of
further work, as it would allow for examination at a wider scale. The benefits for nest survival are likely
to accrue over time as shifts in wader distribution become more apparent, the manipulated habitats
mature, and with increased understanding of the relationship between factors such as small mammal
population cycles and predation on ground-nesting birds. Therefore implementation of these
methodologies currently has the potential to contribute to landscape-level improvements in wader nest
survival and, with further research, to overall productivity as well.
Acknowledgements
We thank Stephanie Bentham-Green, Becky Laidlaw, Ralph Loughlin, Andrew Robertson, Janine
Robinson, Jim Rowe and Jennifer Stockdale for assistance with fieldwork and data collation. Mark
Bolton, Richard Brand-Hardy and Ken Smith were fundamental in the development of the project. This
work was funded by DEFRA (project no. BD1327) through the Environmental Stewardship Research &
Devlopment Fund.
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References to published material
9.
This section should be used to record links (hypertext links where possible) or references to other
published material generated by, or relating to this project.
SID 5 (Rev. 3/06)
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Stillman R A, MacDonald M A, Bolton M R, Durrell S E A le V dit, Caldow R W G and West A D.
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