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\begin{document}

\title{The effects of forest edge and nest height on nest~predation in a U.K.
deciduous forest fragment}



\author[1]{Noah Atkin}%
\affil[1]{Imperial College London}%


\vspace{-1em}



  
  \date{May 20, 2024}


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\selectlanguage{english}
\begin{abstract}
It has been previously hypothesised that nest predation is higher at
forest edges. This has important conservation implications for the
increasingly fragmented U.K. climax community. I aimed to test the
generality of this edge effect in a mixed deciduous forest fragment
which borders open grassland.~Artificial nests containing a combination
of quail and plasticine eggs were used, at ground and arboreal levels. I
found an overall edge effect on nest predation rates, however this
effect was not specifically seen in ground nests. Ground nests
experienced significantly higher levels of predation than arboreal
nests. I suggest this edge effect is due in part to the steep
productivity gradient over the ecotone.%
\end{abstract}%



\sloppy


\section*{Introduction}

{\label{623215}}

Habitat fragmentation is the process whereby a large area of habitat is
split into a number of smaller habitat patches, with a smaller total
area~\hyperref[csl:1]{(Wilcove, McLellan \& Dobson, 1986)}. Habitat fragmentation in the modern day is
largely driven by anthropogenic land use change, such as urbanisation,
deforestation and intensive agriculture. These dramatic changes expose
pre-existing climax communities to artificial habitats, often with lower
productivity~\hyperref[csl:2]{(Ries \textit{et al.}, 2004)}. Anthropogenic-mediated fragmentation
often results in unnatural and intricate shapes, increasing the
proportion of the new habitat which is affected by the edge
(Fig.~{\ref{965599}}). Habitat fragmentation
significantly reduces the species richness of animals and plants across
communities, through time-delayed but deterministic extinction of
previously dominant species in a habitat - known as extinction
debt~.~Given the continued increase in habitat fragmentation, and~Haddad
(2015)'s finding that 20\% of remaining forest is within 100m of the
forest edge, it's important to understand the effects these edges can
have on existing biological communities.

\par\null\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.81\columnwidth]{figures/Habitat-fragmentaion/mASTERPIECE}
\caption{{The process of human driven~habitat fragmentation, whereby a large
habitat is split into smaller sections each with a smaller area than the
original, with a larger proportion of edge~\protect\hyperref[csl:1]{(Wilcove, McLellan \& Dobson, 1986)}.~
{\label{965599}}%
}}
\end{center}
\end{figure}

Edge~effects are the changes in community structure that are present at
the boundary between two or more habitats~\hyperref[csl:3]{(Yahner \& Scott, 1988)}. Edges,
also known as ecotones, are affected by the abiotic conditions of both
habitats, and the subsequent combination can affect ecosystem
processes~\hyperref[csl:4]{(Ries \& Sisk, 2004)}. The rate of some ecosystems processes have
been shown to increase under the effect of edge-mediated abiotic
factors,~such as carbon sequestration. For example, it has been shown
temperate forest growth and biomass increase with proximity to the
forest edge~\hyperref[csl:5]{(Cochrane \& Laurance, 2002)}. However, these same abiotic factors can
also decrease certain ecosystem processes, such as
decomposition~\hyperref[csl:6]{(Harper \textit{et al.}, 2005)}. Edge environments tend to be drier and
warmer than those of the interior due to wind exposure and increased
insolation. These factors are drivers of decomposition and previous
studies have shown decomposition increases with distance from the
edge~\hyperref[csl:7]{(Crockatt \& Bebber, 2014)}. Significant changes in these ecosystem
processes are an indication of alteration to food web and community
structure, and can be deleterious to endemic specialists~. As well as
abiotic factors, biotic factors can also affect ecosystem processes at
the forest edge.~Ecological generalists are more able to adapt to the
varied conditions of edges, while edge effects are generally considered
to have negative effects on existing specialist biological communities~.
An increased proportion of these generalists can affect overall
ecosystem functioning through degradation of underlying ecological
processes, such as nest predation~\hyperref[csl:4]{(Ries \& Sisk, 2004)}.~

\par\null

Increased nest predation as an edge effect was initially suggested as a
general rule in 1978, and was hypothesised to be driven by increased
bird population density at edges~and may form a so-called ``ecological
trap'' for nesting birds~\hyperref[csl:8]{(Gates \& Gysel, 1978)}. This ecological trap is
formed of 2 parts: i) The previously observed effect of nest predation
increasing with nest density~, and ii) increased nest density at
edges~\hyperref[csl:8]{(Gates \& Gysel, 1978)}, which together form the cumulative edge effect
on nest predation.~While many previous studies have shown nest predation
can increase with proximity to the forest edge, the universality of this
rule has been challenged~. In a meta-analysis, Lahti (2001) found the
hypothesis had been rejected in a majority of experiments, and the
underlying causes of such an effect are not as simple as the ecological
trap hypothesis suggests. It's been subsequently proposed that a nest
predation edge effect is mediated by abiotic edge factors, such as the
land use of the bordering habitat\hyperref[csl:4]{(Ries \& Sisk, 2004)}. For example, forest
fragments bordering open grassland~has been hypothesised to assist
p{redators using linear geographic features such as edges as a foraging
route~}{.~}Geographic orientation is another edge factor which can
exacerbate edge effects, and is rarely controlled for in edge effect
studies. There is strong evidence to support the hypothesis that
south-facing edges in the Northern hemisphere suffer larger edge
effects, due to increased insolation~\hyperref[csl:2]{(Ries \textit{et al.}, 2004)}. Similarly
temporal factors, such as seasonality and annual changes in temperature
have been seen to play a role in edge effects, and some edge responses
can even reverse depending on the season, although this is
rare~\hyperref[csl:2]{(Ries \textit{et al.}, 2004)}. All of these abiotic edge factors interact
with the native biota and can create unique combinations of edge
effects.~Given the vast variability in these edge factors worldwide, and
that~{predator composition and behaviour differs between regions, this
suggests previous findings on edge-mediated nest predation may not be
applicable to new experimental environments~ Particularly given that
most nest predation experiments do not identify predators responsible
for the effect~\hyperref[csl:9]{(Whyte, Didham \& Briskie, 2005)}.~~}

\par\null

Edge effects may have significant impacts for birds in the United
Kingdom (U.K.). Native forest cover in the U.K. has been declining since
the early Holocene, and the remaining areas are increasingly
fragmented~\hyperref[csl:10]{(Whitehouse \& Smith, 2010)}. Historical forest cover in the U.K. is
inherently difficult to calculate, as undocumented prehistoric land
conversion from forest to subsistence farming destroyed most of the
native climax community and replaced it with artificial habitats, such
as heath and moorland~.~ From the 19th century onward, land use change
in temperate regions has trended away from subsistence farming towards
urbanisation and intensive agriculture. These trends have only spread to
tropical regions in the last 50 years, which has resulted in a loss of
1/3 of the world's forested areas~. Urbanisation has been responsible
for vast deforestation in sub-Saharan Africa, as urbanisation drives up
demand for fuel wood~. While intensive agriculture is the current main
driver of deforestation in the Amazon rainforest, due to the economic
incentives of cattle ranching~.~~Despite these global trends, forest
cover in the U.K. has been increasing since the
1920s~\hyperref[csl:11]{(DEFRA, 2013)}. However, the majority of original forest
cover has been replaced with non-native conifer monocultures. These
monocultures do not provide the same ecological function as native
forests and further fragments the U.K. deciduous climax
community~\hyperref[csl:12]{(Liu, Kuchma \& Krutovsky, 2018)}. This high level of fragmentation is
particularly problematic for the contained biological communities, as
edge effects increase as a function of habitat fragmentation~. In
addition, U.K. forest fragments often border open farming landscapes due
to economic incentives for intensive agriculture~. These open landscapes
provide a ``sharp'' border to the forest, and are capable of supporting
high densities of opportunistic generalist predators, which can then
prey on the exposed edges~\hyperref[csl:13]{(Lahti, 2001)}. These risks are
particularly high for increasingly endangered U.K. ground nesting birds,
given the predominantly terrestrial morphology of opportunistic
generalist predators.~

\par\null

Research on the effects of edges~on nest predation in temperate ecotones
have largely been performed~{in the U.S.A.~\hyperref[csl:13]{(Lahti, 2001)}.~As U.K.
predator composition and behaviour differs greatly from North America,
this suggests findings from these studies may not be applicable to U.K.
deciduous woodland~}This study aims to examine whether the previously
hypothesised generality of edge effect mediated nest predation applies
to a U.K. mixed deciduous forest fragment, at both ground and arboreal
levels. It was hypothesised that predation rates would increase with
proximity to the forest edge regardless of height. Given the previous
mixed effects of edge on nest predation, a large scale study seemed
appropriate to examine the effect on the forest fragment and this
experiment is the first of its scale to study these effects in the U.K.

\par\null

Many previous studies on nest predation using artificial nests have been
unable to identify predators responsible for the predation, despite
predator identity being hypothesised as a significant driver of nest
predation at forest edges~\hyperref[csl:9]{(Whyte, Didham \& Briskie, 2005)}. Therefore, in this study,
predators were identified using bite marks left on plasticine eggs. This
should~provide insight into the composition of predators that prey on
forest edges in deciduous woodland and~elucidate pest control priorities
around these fragmented areas.

\par\null

\section*{Methods}

{\label{682083}}

\subsubsection*{Study Site}

{\label{525625}}

The experiment took place at Silwood Park, Imperial College London
(51\selectlanguage{ngerman}°24'30.6``N 0°38'31.3''W) in a 200m x 350m stretch of mixed deciduous
woodland which borders open grassland
(Fig.~{\ref{621552}}). An experiment focusing on the
breeding ecology of blue tits was also being conducted in the woodland
using artificial nesting boxes and marked trees. No trees were shared
between the two experiments, and a minimum of 10m from each marked tree
was maintained to avoid bias.~\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=1.00\columnwidth]{figures/Mapofsite/Mapofsite}
\caption{{Map of Great Britain showing the location of the study site at Silwood
Park, Berkshire
{\label{621552}}%
}}
\end{center}
\end{figure}

\subsubsection*{Pilot Study}

{\label{324496}}

A pilot study was performed for 2 weeks in March 2019 using 8 artificial
nests to examine basic questions about predator behaviour and whether
the experiment was suitable for a larger study. Specifically, the pilot
study aimed to answer i) whether predators in the forest would be able
to locate artificial nests and ii) whether the presence of artificial
plasticine eggs would significantly affect predation rates. The pilot
examined predation rates on artificial nests containing 1 quail and 1
plasticine egg, using nests containing only 1 quail egg as a control.
This revealed nests containing plasticine eggs had significantly higher
predation rates (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}~= 17.681, p \textless{} 0.0001),
suggesting additional methods would be required to reduce olfactory cues
given off by the artificial eggs. Full methods and results for the pilot
study can be read in the supplementary information~{(S1)}.

\subsubsection*{Power Analysis}

{\label{651284}}

To estimate the number of experimental nests I needed, I carried out a
power analysis. The pilot study was too limited in number of replicates
to generate an accurate estimate of the effect size of edge effects, so
effect sizes were gathered from a variety of papers who had performed
similar experiments~\hyperref[csl:14]{(Kotze \& Lawes, 2007}; \hyperref[csl:15]{Cooper \& Francis, 1998}; \hyperref[csl:16]{Burkey, 1993}; \hyperref[csl:17]{Temple \& Cary, 1988)}. An average was taken which
indicated a low effect size (w\emph{~}= 0.256). Using the default values
of~ p = 0.05 and power = 0.8, this showed that N=119.8, meaning 120
nests would be used for the full experiment. ~

\subsubsection*{Materials and Methods}

{\label{324496}}

The experiment was run for 2 weeks from 13-26 May 2019. 120 artificial
birds nests made from conifer leaves and metal wire were used in this
experiment. 30 trees were selected at the forest edge and interior.
Trees at the forest edge were selected using a linear transect across
the forest edge, with trees selected at 10m intervals. Due to the size
of the fragment, a linear transect was unable to be used for the forest
interior. After arbitrarily choosing an initial tree in the centre of
the interior, trees were chosen using a random number generator, which
generated a bearing and a tree in that bearing was chosen if i) it was
not within 5m of any other tree and ii) if it was still within the
forest interior.~Each tree contained 2 nests, 1 ground and 1 arboreal.
In total, 60 nests were placed at the forest edge (\textless{}10m away
from the edge) and remaining 60 were placed at the forest interior
(\textgreater{}100m away from the edge). Where necessary, arboreal nests
were attached to trees using steel wire. Each tree was a minimum of 5m
away from any other selected tree, and no attempts were made to disguise
or hide the nests. Since nest markers may cue predators to the presence
of the nest, no nest markers were used.

\par\null

3 eggs were placed in each nest, 1 quail egg and 2 plasticine eggs. The
pilot study indicated a high risk of artificial eggs being removed or
destroyed, for this reason 2 plasticine eggs were used instead of
1~{(S1)}.~ Plasticine eggs were made by hand to have the dimensions of a
reference quail egg (3.5cm long, 2.8cm diameter), and were aerated for 3
days after manufacture to mitigate the strong scent. To reduce the scent
further, plasticine eggs were coated with a thin layer of rubber
(PlastiDip\selectlanguage{ngerman}\textsuperscript{®}) before aeration, which has been shown to
reduce overestimation of mammalian predation rates~\hyperref[csl:18]{(Purger \textit{et al.}, 2012)}.
Eggs were marked on their base to identify the nest they were placed in,
to assists in cases where an egg was removed from the nest but able to
be recovered.~ A nest was considered to be predated if any of the eggs
were damaged or missing.~ Nests were examined daily and predated eggs
were replaced. Predator tooth marks in the plasticine eggs were
identified using reference photos of woodland predators skulls. ~For
spatial analysis, nest locations were recorded using a Garmin eTrex 10,
and co-ordinates were averaged from 5 measurements over the course of 1
day for increased accuracy.~

\subsubsection*{Statistical Analyses}

{\label{298448}}

The statistical effect of edge and nest height was measured using
generalized linear model, using a binomial distribution which measured
the overall nest predation rates over the 2 week period. The response
variable was the proportion of days a nest was predated, and the
explanatory variables were nest height and nest location.~Given the
previous inconsistency between nest predation experiments, it seemed
appropriate to calculate a comparable effect size of an edge effect for
future reference. Cohen's~\emph{d} was calculated from the generalized
linear model output using the~\emph{sos~}package in R~. ~Mantel tests
were performed to examine the role spatial autocorrelation plays in nest
predation at the edge and interior. All statistical analyses was
performed in R~.~ A significance level of~ p \textless{} 0.05 was used
in all tests.

\section*{Results}

{\label{266915}}

Proximity to edge was shown to significantly increase nest predation
rates. The generalized linear model showed when accounting for all
nests, the effect of edge on nest predation was statistically
significant (p~= 0.007, z-value = 2.687). Regardless of proximity to
edge, ground nests experienced significantly higher predation rates than
arboreal nests (p \textless{} 0.001, z-value = -19.239). There was no
significant interaction effect between nest height and edge (p~= 0.16).
When analysed separately, the effect of edge on nest predation in
arboreal nests was found to be significant (p = 0.01, z-value = 2.576),
but not for ground nests (p = 0.121, z-value = 1.549). It should also be
noted that every ground nest was predated at least once during the
course of the experiment. The overall edge effect size on ground and
arboreal nests was calculated to be~\emph{d} = 0.245, indicating a small
effect of edge proximity on nest predation. ~

\pagebreak\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.84\columnwidth]{figures/Rplot02/saving-plot3}
\caption{{Differences in daily predation rates at ground and arboreal levels.
Arboreal nest predation rates were significantly lower than ground
nests~ (p \textless{} 0.001, z-value = -19.239). Nest location was also
found to be significant, albeit with a smaller effect size~ (p~= 0.007,
z-value = 2.687)~ ~~
{\label{919163}}%
}}
\end{center}
\end{figure}

Mantel tests were performed separately for ground and arboreal nests due
to the significant differences between their predation rates and
predator composition. Ground nests did not show any spatial
autocorrelation (r = 0.024, p = 0.273)
(Fig.~{\ref{986875}}), however predation in arboreal
nests revealed some level of spatial auto-correlation (r = 0.089, p =
0.025) (Fig.~{\ref{154374}}). The observed correlation
between arboreal nests, r = 0.089, suggests a slight positive
association, so smaller differences in predation rates are generally
seen among pairs of arboreal nests that are closer to each other.~ ~ ~ ~
~\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.63\columnwidth]{figures/Rplot03/newlat-long-ground}
\caption{{Geographic representation of ground nests and their Daily Predation
Rates (DPR). A mantel test indicated no significant association between
nest adjacency and predation rates~ (r = 0.024, p = 0.273).~
{\label{986875}}%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.63\columnwidth]{figures/newlat-long-arboreal/newlat-long-arboreal}
\caption{{Geographic representation of arboreal nest location and their daily
predation rates. A mantel test indicated a significant association
between nest adjacency and predation rates, with a small effect size (r
= 0.089, p = 0.025)
{\label{154374}}%
}}
\end{center}
\end{figure}

\pagebreak

6 types of nest predator were identified. The majority of the identified
predation came from mice (Muridae spp.), which accounted for 47.8\% of
predation across both heights, and 50.7\% of ground nest predation
(Fig.~{\ref{524812}}). Ground nests were also preyed
upon by hedgehogs (\emph{Erinaceus europaeus,~}4.1\%\emph{)}, rats
(\emph{Rattus~}spp\emph{.,~}12.3\%), badgers (\emph{Meles
meles,~}24.1\%) and occasionally foxes (\emph{Vulpes vulpes}, 8\%). Most
of the identified arboreal nest predation is due to bird predation
(92.9\%), however the high rate of missing eggs in arboreal nests means
the majority of arboreal predation is unable to be attributed to a
specific ntified predator. Over both heights sampled, the majority of
the predations were unable to be identified (64.6\%), most commonly due
to eggs being unable to be located (53.9\%), and a considerable portion
were destroyed beyond recognition (10.7\%).

\par\null\par\null\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.98\columnwidth]{figures/table1/Capture}
\caption{{Percentage of ground and arboreal nests predated upon, their Daily
Predation Rate (DPR), and the identity of predators responsible for
predation. 'Unknown refers to nest predations where the eggs were
destroyed beyond recognition, or unable to be located. 30 nests were
sampled at each location and height combination.
{\label{524812}}%
}}
\end{center}
\end{figure}

\subsubsection*{}

{\label{544901}}

\section*{Discussion}

{\label{849653}}

At the experiment site there was an overall significant effect of nest
predation at the forest edge compared to the interior, however our
hypothesis was incorrect that this would be effect would be present on
ground nests. As previously mentioned, the universality of a linear edge
effect on nest predation has been effectively disproved. As Lahti (2001)
showed, the majority of nest predation experiments show no significant
difference between edge and interior, which may be because the gradient
of predation rates is not always linear. Previous research has indicated
that nest predation edge effects can follow unusual, eratic gradients at
intermediate distances from the edge~ The varied nature of these
previous findings is suggested to be due to interactions between
multiple abiotic edge factors, causing unique microclimates at various
distances from the edge. Hence the focus should be on the abiotic and
biotic factors specific to this edge and interior which may interact to
cause such an edge effect on arboreal nests.

\par\null

\subsubsection*{Abiotic Edge Factors Affecting
Predation}

{\label{676349}}

Edge contrast has previously been hypothesised to exaggerate edge
effects~\hyperref[csl:4]{(Ries \& Sisk, 2004)}. The bordering habitat to the examined forest
fragment is open grassland, which has a comparatively low productivity
compared to forests~\hyperref[csl:13]{(Lahti, 2001)}. Previous studies have indicated
that the steepness of the gradient in productivity over an ecotone may
play a role in nest predation, and that such an effect is exaggerated by
high levels of habitat fragmentation~.~Lahti (2001)'s meta-analysis did
not show such an effect, however it did show that a edge effect on nest
predation is significantly less likely where the gradient in
productivity is shallow (e.g grassland and agricultural land). This
suggests steepness of ecotone productivity gradients may only increase
nest predation conditionally, subject to other factors. The large
productivity contrast in this study between woodland and open grassland
may partially explain increased nest predation at the edge, however
other U.K. forest fragments with smaller productivity contrasts will
need to be examined before a casual effect can be established.

The effect of orientation may not have played a significant role on the
observed edge effect in this study. The experimental forest edge~is east
facing and previous studies on the effect of orientation on edges focus
on North-South orientation. Current understanding of orientations impact
on edges suggests east-west orientation does not significantly influence
edge effects~\hyperref[csl:2]{(Ries \textit{et al.}, 2004)}.~

There may however be a temporal impact on this experiment, as the study
was only carried out for 2 weeks post-spring, where U.K. bird
populations are near their peak~ Previous studies in Scotland have shown
significant seasonality in nest predation rates around spring. Nest
predation rates were shown to peak in late April, and then slowly
decline until late June~\hyperref[csl:19]{(Malzer \& Helm, 2015)}. If this seasonal predation
effect is also seen in England, it may help account for the unusually
high levels of predation seen in this experiment. However it should be
noted that although Malzer \& Helm (2015) found an overall effect of
season on nest predation, it did not influence the edge effect, which
was constant year round. ~

\subsubsection*{Predator idendity}

{\label{433033}}

The main predators of ground nests identified in this study were mice,
and other nest predation experiments have identified mice as a
significant predator of artificial nests~{. These results are in
contrast to previous findings that cast doubt on rodents willingness to
predate quail eggs in artificial nest experiments~.~Natural experiments
in the U.S. have found over 75\% of ground nest predations are caused by
terrestrial rodents~}\hyperref[csl:20]{(Sanders \& Chalfoun, 2019)}{ These results are slightly
higher than our experiment (63\%), however my results underline the
ubiquity of the significant impacts rodents have on ground nesting bird
communities. Particularly given that nest predation is the most
significant cause of nest failure~. Mouse-driven nest predation
decreased with proximity to the edge, as 58.6\% of mouse depredations
took place in the forest interior. This may be due to the populations
dynamics and range size of mice in forested regions. Previous studies in
tropical habitats have suggested that forest edges are a more preferable
habitat to various species of mice, particularly over ecotones with
sharp productivity gradients~. Generally mouse population density is
lower in the interior of forests, this is suggested to be due to the
edge being a richer habitat which could be modelled using an ideal
despotic distribution (IDD)~ However it's also been shown small forest
fragment size has positive impacts on the fitness associated traits of
mice, such as body size~}.~ In this particularly small forest fragment
it may be that the distance to edge to maximise mouse fitness is
\textgreater{}10m, and the beneficial abiotic factors of the edge reach
further into the forest than the edge as defined in this study.

\par\null

\subsubsection*{Autocorrelation of arboreal nest
locations}

One of the more unusual results from this experiment is the spatial
autocorrelation between arboreal nest proximity and location, which is
not present on ground nests. Particularly given that the dispersal
constraints of terrestrial predators are usually larger than those of
arboreal predators. As there is a smaller diversity of arboreal
predators in the U.K., the autocorrelation could be due to a smaller
number of individuals predating the nests, limited by their dispersal
constraints. In conjunction, the ground nests were predated on by more
individuals, disguising individual dispersal patterns. This could be an
avenue of future study, however it should be noted the spatial
autocorrelation was quite weak (r = 0.089), so the result may not be
ecologically significant.~

\par\null

\subsubsection*{Predation intensity}

{\label{786272}}

Predation intensity at ground levels were significantly larger than
those in arboreal nests, which supports some previous studies~, although
this result is not universal~ Ground nest predation rates in this
experiment were very high compared to other artificial nest experiments,
regardless of nest location~\hyperref[csl:9]{(Whyte, Didham \& Briskie, 2005)}. There are many potential
reasons for this effect. As previously mentioned, it may be due to an
annual seasonal effect of spring increasing predation rates
nationwide~\hyperref[csl:19]{(Malzer \& Helm, 2015)}. The sharp edge of the forest may also
play a role. The bordering open grassland is capable of supporting high
densities of opportunistic generalist predators which can follow linear
foraging routes of the edge. However, while this may have guided
mesopredators to edge nests, but does not adequately explain the high
interior predation rates~\hyperref[csl:13]{(Lahti, 2001)}.~

I suggest that predator intelligence may be responsible. The hypothesis
that predators can learn the locations of artificial nests has been
tested previously using arboreal nests. Yahner \& Mahan (1999) examined
avian and non-avian predation between fixed-location and randomly
relocated nests, and found no such learning effexct. Similar analysis of
learning behaviour has been performed by Anglestam (1986), who~used
cryptic nests in edge predation experiments, but was also unable to find
a significant effect of learning. However, most learning studies utilise
arboreal nests, and a previous study on ground nests using chicken eggs
in a heavily fragmented forest indicated the predators had become
habituated to the nests, and sought them out~\hyperref[csl:21]{(Yahner \& Mahan, 1996)}. This
risk is particularly prevalent in small isolated forest fragments, where
populations are small and the rate of migration is low~ In such a small
area, mammalian predators can learn to associate olfactory cues with
artificial nests, and previous studies have indicated that mammalian
predators already use olfactory cues to locate artificial nests
containing plasticine eggs~\hyperref[csl:18]{(Purger \textit{et al.}, 2012)}. While plasticine scent
was controlled for in this study, the nests were manufactured from
conifer leaves, which are not present in the experimental forest
fragment, and their cryptic scent and appearance which may provide
routes for habituation. Population densities of predator species in the
forest fragments should be examined in future study to examine evidence
of possible learning behaviour, and hence the usefulness of artificial
nest experiments in this small forest fragment.

\par\null

Another possible mechanism for this unusually high level of predation is
the mesopredator release effect. In the absence of large predators,
mid-ranking predators can take over the ecological role of apex
predators in the food web~ In unfragmented habitats, apex predators can
exert top down ecological control of an ecosystem, which has indirect
benefits on prey populations by suppressing mid-level predators~.
However, larger species are more vulnerable to habitat fragmentation due
to their larger range size, meaning mesopredator release may become a
growing problem for an increasingly fragmented U.K. forest habitat~.
Future study in this area which should aim to examine the populations of
apex predators and mesopredators in this woodland, and examine whether
the mesopredator release hypothesis is a good fit for these findings. If
so, apex predator control measures may be a valid conservation action
for ground nesting bird populations through top-down control of rodent
populations. ~

\par\null

\subsubsection*{Limitations}

{\label{470237}}

Artificial nest experiments have inherent flaws, and the results are not
always directly applicable to wild bird populations. Artificial nests
can overestimate predation rates, by attracting different predators and
may not mimic the seasonal variation in predation rates observed in
natural nest experiments~. However, comparisons between nest height and
edge proximity to examine the factors that drive predation are useful
model of underlying predator behaviour, and continue to be a useful tool
in avian nesting success studies.~

\par\null

\section*{Acknowledgements}

{\label{264431}}

I would like to thank Cristina Banks-Leite~of Imperial College London
for help and advice regarding the pilot study, statistical analysis and
invaluable guidance throughout the project. I would also like to thank
the technical staff at Silwood Park for their assistance using the GPS
unit for spatial analysis. Many thanks to the Department of Life
Sciences at Imperial College London, and specifically the Biology
Undergraduate department, without whom this project could not be
possible.

\pagebreak

\section*{Supplementary Material}
\beginsupplement

A pilot study was undertaken for 2 weeks in March 2019 using 8
artificial nests to answer questions about predator behaviour and to
discover whether the suggested experimental protocols were suitable for
a larger study.~The pilot aimed to answer 2 main questions: Are
predators in the forest would locate and predate upon the nests at
ground and arboreal levels, and does the presence of artificial
plasticine eggs significantly affect predation rates?~While plasticine
eggs are very malleable and allow for the identification of predators
through bite marks, some studies have shown that the olfactory cues
given off by plasticine eggs can lead to an overestimation of mammalian
nest predation~\hyperref[csl:22]{(Batáry, 2008)}.

\subsubsection*{Methods}

{\label{718861}}

1 quail egg and 1 plasticine egg was placed in half of the nests, and
the remaining nests contained only 1 quail egg as a control. Plasticine
eggs were manufactured by hand to have the dimensions of a reference
quail egg ( 3.5cm long, 2.8cm diameter), and no attempt was made to
prevent olfactory cues. The nests were split equally between ground and
arboreal locations. Ground nests were placed in, or at the base of
trees, where each tree is more than 15m away from any other selected
tree. Arboreal nests were mounted to trees using steel wire where
necessary, and were all accessible via branches capable of supporting
the weight of predators. No attempts were made to disguise, or hide the
nests either at ground or arboreal levels. ~4 nests were placed in the
forest interior and the remaining 4 were placed on the forest edge. For
the purposes of the pilot, forest edge was defined as within 10m of the
edge of the forest, and forest interior was \textgreater{}100m away from
any edge. Nests were considered to be predated if they were missing,
broken or otherwise interfered with (e.g bite marks). Nests were
examined daily for predation.

The statistical analysis used \selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}~tests were performed
using R to examine the observed predation from nests containing
plasticine eggs to the expected predation (control
nests)~\hyperref[csl:23]{(R Core Team, 2019)}.~

\subsubsection*{Results}

{\label{468127}}

The pilot study found no significant difference between ground and
arboreal nests (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2} = 0.210, p = 0.647) indicating the
full study can use ground and arboreal nests, and that the arboreal
nests are being predated. The pilot did however find a significant
difference in predation rates between nests with and without the
plasticine eggs (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}~= 17.681, \selectlanguage{greek}ρ \selectlanguage{english}\textless{} 0.001),
possibly due to the olfactory cues the plasticine was emitting,
indicating either a different material for artificial eggs should be
used, or steps should be taken to reduce the smell. It should also be
noted that every day of the trial, at least 1 plasticine egg was
completely eviscerated preventing predator identification.

\pagebreak

\selectlanguage{english}
\FloatBarrier
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\end{document}

