Evaluating the influence of habitat on nest distribution and breeding performance of the Marsh Harrier, Circus aeruginosus, in the UK

Charles Bennett September 2014

A thesis submitted for the partial fulfillment of the requirements for the degree of Master of Science at Imperial College London

Submitted for the MSc in Conservation Science

i DECLARATION OF OWN WORK

I declare that this thesis, “Evaluating the influence of habitat on nest distribution and breeding performance of the Marsh Harrier, Circus aeruginosus, in the UK”, is entirely my own work, and that where material could be construed as the work of others, it is fully cited and referenced, and/or with appropriate acknowledgement given.

Signature: ______

Student: Charles Bennett

Supervisors: Dr. Marcus Rowcliffe

Dr. Daniel Hayhow

i Table of Contents

List of Figures ...... iii List of Tables ...... iii List of Acronyms ...... iiv Abstract ...... v Acknowledgements ...... vi 1 Introduction ...... 1 1.1 Problem statement ...... 1 1.2 Project Aim ...... 5 1.3 Objectives: ...... 5 2 Background ...... 6 2.1 The Buffer Effect ...... 6 2.2 Drivers for avian expansion into human dominated landscapes ...... 7 2.3 Ecological Traps ...... 10 2.4 The ecology of the Marsh Harrier ...... 12 2.5 History of Marsh Harriers in Britain ...... 13 3 Methodology ...... 15 3.1 Rare Bird Breeding Panel monitoring methods ...... 15 3.2 National Survey methods ...... 15 3.3 Marsh Harrier population trends and distribution ...... 16 3.4 Influence of landscape-scale habitat variables on nest site selection ...... 17 3.5 Influence of fine-scale habitat variables on nest site selection ...... 18 3.6 Influence of habitat types on breeding performance ...... 19 3.7 Problems using multiple and aggregated datasets ...... 20 4 Results ...... 21 4.1 Population trends ...... 21 4.2 Distribution of Marsh Harrier nest sites across the UK ...... 22 4.3 Distribution and frequency of Marsh Harrier nest across the UK...... 24 4.4 The influence of landscape features on nest habitat selection ...... 26 4.5 Nest site distribution across different habitats ...... 29 4.6 The influence of different habitat types on fledged brood sizes ...... 31 4.7 Breeding success in different habitat types ...... 35 5 Discussion...... 38 5.1 Influence of habitat type on Marsh Harrier nest site selection and breeding performance ..... 38 5.2 Impact of oilseed rape and arable land area on population dynamics ...... 40 5.3 Assumptions and limitations ...... 41 5.4 Recommendations for future surveys ...... 43 5.5 Management implications ...... 43 References ...... 45 Appendices ...... 48 Appendix 1 ...... 48 Appendix 2 ...... 50 Appendix 3 ...... 51 Appendix 4 ...... 52

ii List of Figures

Figure 1 Number of breeding pairs in the UK between 1973 and 2008 ______21 Figure 2 The proportional distribution of breeding pairs across UK counties ______22 Figure 3 Location and number of Breeding pairs compared over time ______24 Figure 4 Predicted models investigating landscape habitat variables against the density of nests __ 27 Figure 5 Percentage of pairs nesting in each habitat, compared over time ______29 Figure 6 Proportional distribution of nest in wetland and agricultural habitats, compared over time 29 Figure 7 Mean (±SD) fledged brood size for pairs in different habitat types, compared over time _ 31 Figure 8 Influence of different habitat types on fledged brood size, compared over time ______32 Figure 9 Proportion of breeding success in each habitat, compared over time ______36 Figure 10 Proportional breeding success in wetland and agricultural habitats, compared over time 36

List of Tables

Table 1 Model selection table investigating landscape features and density of nests in 1995 ______26 Table 2 Model selection table investigating landscape features and density of nests in 2005 ______26 Table 3 Model results investigating the influence of habitat on fledged brood sizes in 1995 ______32 Table 4 Model results investigating the influence of habitat on fledged brood sizes in 2005 ______32 Table 5 Model selection table displaying minimum AIC values of nest site features within 100m and fledged brood sizes, 2005 ______33 Table 6 Model results of different nest habitat types on breeding success in 1995 ______35 Table 7 Model results of different nest habitat types on breeding success in 1995 ______35 Table 8 Model results displaying the influence of nest site features on breeding success, 2005 ____ 37

iii List of Acronyms

RBBP Rare Breeding Bird Panel RSPB Royal Society for the Protection of Birds GIS Geographical Information System CSV Comma separated value

iv Abstract

Increased nesting and breeding success of Marsh Harriers (Circus aeruginosus) in intensive agricultural habitats raises a number of long-term conservation concerns. These intensively managed environments are perceived to threaten the physiological health, fitness and sustainability of Marsh Harrier populations as a result of higher exposure to chemical pesticides, as well as stimulate greater levels of nest disturbance and destruction. Wetland and agricultural habitats were evaluated for their impact on Marsh Harrier breeding performance and nest distribution in the UK, to understand its influence on population dynamics. Results showed that the majority of Marsh Harrier nests were found in wetland habitats. Model predictions suggested that Marsh Harriers preferred habitats with more low area to perimeter water body ratios, such as streams and ditches, and tended to avoid larger areas of arable land. Although, fewer nesting pairs were found in agricultural habitats, the breeding performance did not differ between the two habitats. Temporal analysis suggested no change in these patterns between 1995 and 2005, either. Findings indicate that intensive agricultural lands may not be the primary threat to the stability of the Marsh Harrier population in the UK, as they did not limit the recovery of the species between 1995 and 2005. Despite the short-term benefits agricultural habitats provide, the long-term conservation implications are still a concern, as equal breeding performance across wetland and agricultural habitats support the original problem. Management of the species should be precautionary focused and continue with current monitoring strategy, while also engaging with farmland owners to reduce wetland habitat loss.

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v ACKNOWLEDGEMENTS

I would like to express my sincere and grateful thanks to Dr. Marcus Rowcliffe, whose support, guidance, and patience throughout the completion of this project has been invaluable.

I would like to extend my special thanks to Dr. Daniel Hayhow, for his vital input and support in the completion of this study. I really enjoyed my visit to Sandy, and thank you for providing me with the opportunity to work with yourself and RSPB.

To Paul Britten, Greg Miller, Dave Fourace from RSPB, thank you sincerely for your time and technical assistance with GIS.

vi 1 Introduction

1.1 Problem statement

Habitat loss is described as the main driver of species loss in terrestrial ecosystems (Millennium Ecosystem Assessment, 2005). Land use change is the leading cause of habitat loss, which is motivated by the need for agricultural expansion, urbanization and infrastructural development to support the growing human population (Millennium Ecosystem Assessment, 2005). The human population is expected to increase to between 8.1 and 9.6 billion by 2050, with habitat loss consequently expected to increase (Millennium Ecosystem Assessment, 2005; Platteeuw et al. 2010). Wetlands in particular, are a threatened habitat, which is largely due to agricultural processes that aim to take advantage of hydrodynamic and ecological functions (Thiere et al. 2009; Platteeuw et al. 2010). These threats affect a number of specialist species that depend on wetland habitats, both directly and indirectly (Platteeuw et al. 2010).

Wetland habitats are inland water systems that exist between terrestrial land and the coastal zone (Millennium Ecosystem Assessment, 2005). They have been defined as areas of high groundwater that can be permanently or temporarily inundated (Dawson et al. 2003). Wetlands are considered very important habitats because they perform a variety of functions, such as preserving water quality, providing habitat to wildlife, reducing flood damage as well as aesthetics and recreation (Heimlich et al. 2014). Initially, they are converted into agricultural land with the aim of exploiting specific services for economic gain (Heimlich et al. 2014). Since 1900, wetlands have been estimated to have declined by 50% globally (Millennium Ecosystem Assessment, 2005) and 90% of which was documented in Europe and North America alone (Thiere et al. 2009). The expansion and intensification of agricultural practices has been suggested as the major driver accelerating the loss of wetland habitats (Gallant et al. 2007).

Wetland loss is largely due to the conversion of wetland habitat into farmland (Gallant et al. 2007). Intensive agricultural land is typically associated to the loss of wetland habitat as it is often situated near to wetland habitats (Daily et al. 2001). Intensive agricultural land typically modifies landscapes and encourages the implementation of monoculture practices that require

1 flat land, lots of space and access to fresh water (Daily et al. 2001). Economic incentives are the driving force behind wetland habitat conversion to farmland. However, wetland habitat loss, coupled with intensification of agriculture has led to dramatic reductions in biodiversity (Daily et al. 2001) as well as significant disruptions to ecosystem functioning (Giralt et al. 2008). Besides direct clearance of wetlands for land, intensive agricultural land often employs the use of pesticides to maximize yields, which cause additional environmental degradation that can contribute to further declines in biodiversity (Cardador et al. 2011). Worryingly, the intensification of agricultural practices is likely to increase due to the current and future threats of climate change. Human populations are motivated to adopt more of these practices in order to adapt to probable increases in risk of droughts, water scarcity and food insecurity that often outweigh the importance of biodiversity (Millennium Ecosystem Assessment, 2005).

The population dynamics of a number of species has been impacted by the conversion of wetland habitats into intensive agricultural land. Birds in particular are considered highly sensitive to these changes and can experience decreases in individual fitness that increase direct mortality rates and reduce reproductive outputs (Giralt et al. 2008; Wolff et al. 2002). For example, agricultural intensification can ignite fiercer intraspecific competition for resources by reducing the availability of nesting sites in natural habitats, nest building materials and food resources (Giralt et al. 2008; Gunnarsson et al. 2005; Bretagnolle et al. 2008). Bretagnolle et al. (2008) suggested that competition between individuals for resources could determine the distribution and density of animal populations. A number of studies on recovering bird populations have been able to illustrate that at low population sizes, the preferred high quality habitats are the first to become occupied (Gunnarsson et al. 2005). As populations expand, a greater proportion of a population will spill into poorer quality habitats (Gunnarsson et al. 2005). This phenomenon is known as the ‘buffer effect’, whereby populations are regulated by density dependent mechanisms and the expansion into poor quality habitats, such as intensive farmlands, can lead to a reduction in survival and/or fecundity (Bretagnolle et al. 2008). Another example is that intensive agriculture is essentially an artificial habitat which can affect how an organism perceives its quality. Bird studies have been reported to experience a decline in fitness, breeding success and overall population size due to the ‘ecological trap’ theory because human modified habitats can deliver the wrong settlement cues, which misrepresent and overestimate the true quality of the habitat (Schlaepfer et al. 2002; Shochat et al. 2005).

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Intensive agricultural areas have not impacted all bird species equally and there are a variety of ground nesting avian species that have shown a tolerance to such landscapes. Cereal crops have been used as appropriate nesting sites by a number of species, most notably the Montagu’s Harrier Circus pygargus, as it uses crops as nest building materials (Arroyo et al. 2002). In addition, intensive landscapes have been identified as important habitats for essential prey species. Habitat selection of some birds is strongly influenced by prey resource availability, as it can determine the species’ reproductive success (Arroyo et al. 2002). Intensive agricultural habitats provide additional benefits to ground nesting birds as farmers can implement a variety of predator control management measures that reduces nest predation and damage (Sternalski et al. 2013). Nest predation is an important factor determining the reproductive success of raptor species (Sternalski et al. 2013).

The Marsh Harrier Circus aeruginosus, the focus species in this project, is a medium-sized raptor known for its preference for nesting and breeding in wetland habitat (Cardador et al. 2011). This has largely been linked to the presence of tall emergent reed vegetation found within this habitat that are important for the construction of nests, protection from human disturbance and terrestrial predators, as well as resistance from local flooding events (Underhill-Day 1998; Cardador et al. 2011). Wetland habitats served an important role for the species during its devastating decline in the 1900s, as the species was able to persist the longest in UK reed bed reserves before eventually going nationally extinct (Underhill-Day 1998). It is not unfamiliar for Marsh Harriers to also nest in agricultural areas and they have been found occupying various agricultural landscapes in the Iberian Peninsula (Cardador et al. 2011). However, more recently, it was discovered that a Spanish population of Marsh Harriers appeared to have greater breeding success in agricultural areas, in comparison to natural habitats (Sternalski et al 2013). The study investigated the impact of natural and agricultural habitats on breeding success, which, despite the potential benefits with expanding breeding habitats, suggest that the benefits are too short-term (Sternalski et al. 2013). The long-term implications should be highlighted as a conservation concern (Sternalski et al. 2013).

The first considers the high natal philopatry of Marsh Harriers (Sternalski et al. 2013). Marsh Harriers breed during the spring and summer months, and have been identified to concentrate on providing food to their young in autumn (Underhill-Day 1998; IUCN Red List 2013). With

3 higher numbers of the species noticed to be breeding successfully in agricultural landscapes, it was suggested that due to natal philopatry, and the continued decline of available core wetland habitat, a higher proportion of the breeding population will eventually exist in what is often considered ‘poorer’ quality habitat (Sternalski et al. 2013). In this context, though currently a minor concern, it is strongly believed that nest disturbance and damage will become a major concern in the future, as agricultural sowing and harvesting practices take place earlier each year due to climate change, increasing the overlap with Marsh Harrier breeding and feeding activities (Sternalski et al. 2013; Aurbacher et al. 2013).

The second conservation implication considers the impact of nesting in poorer quality habitat on population fitness and long-term survivorship (Sternalski et al. 2013). Particularly in Marsh Harriers, young adults considered of a lower fitness, tend to breed more frequently in atypical habitats, as they are seen as less competitive (Sternalski et al. 2013). In the scenario where the Marsh Harrier population has succeeded in less competitive agricultural habitats, it could infact result in a higher number of poorer quality nestlings to be produced, which could subsequently suffer higher mortality rates if exposed to harsher environmental conditions (Sternalski et al. 2013). Considering the increasing motives to intensify agricultural processes, there is the potential risk that should these less competitive agricultural habitats encourage higher breeding success and a larger proportion of the population may become exposed to chemical substances (Sternalski et al. 2013). Higher exposure to chemicals and intensive farming practices will have health implications on a larger proportion of the population, which has the potential to threaten the sustainability of the population (Sternalski et al. 2013).

Taking into consideration these concerns, Sternalski et al. (2013) challenges the European commission’s assessment that the Marsh Harrier at both a national and European level is of ‘Least Concern’ and insists it is premature to consider the species is safe. This is largely due to uncertainties associated with crop phenology, breeding times and a reduction in fitness that may have greater long-term conservation concerns for the species should they continue their expansion into intensive agricultural land.

4 1.2 Project Aim

In the UK, Marsh Harrier population surveys have been conducted and aggregated over the course of the species’ recovery since the early 1970s. This will be used to investigate whether habitat selection and breeding performance trends noticed in Spain are in fact also happening in the UK. It is important to understand the effect of different habitats on population dynamics for determining nest site selection. To address this, the project aims to investigate the influence of different habitat variables on nest site selection and breeding performance of Marsh Harriers, in the UK. It will use the 1973 to 2008 Rare Breeding Bird Panel dataset and two National Census Surveys conducted in 1995 and 2005. This data will first describe the past species distribution and population trend, second, explore spatially and temporally if Marsh Harrier nest site selection is moving into agricultural land, and third, evaluate the species’ fledged brood size and breeding success across different habitat types. Understanding where the species is distributed, what factors influence their distribution, productivity and breeding success, and how it may have changed temporally is important for forecasting future challenges, associated with protecting key habitats, and developing more robust monitoring strategies to ensure the long-term conservation of the recovering Marsh Harrier, in the UK.

1.3 Objectives:

1. To evaluate the population size and distribution of Marsh Harriers in the UK, between 1973 and 2008 2. To identify the important habitat variables that influence nest site selection, and determine whether it has changed between 1995 and 2005 3. To examine spatially, the influence of different landscape habitat features on nest site distribution 4. To examine the influence of different habitat factors on fledged brood size and breeding success, and determine whether it has changed between 1995 and 2005

5 2 Background

The ‘buffer effect’ and ‘ecological trap’ will be reviewed first to provide a conceptual background on how and why species populations may be driven to, and regulated in, atypical habitats. This section will also review and provide examples of species expansion into human-dominated environments, and explore the linkages between habitat and breeding success. Lastly, the ecology of the Marsh Harrier and its history in the UK will be included for contextual depth and understanding.

2.1 The Buffer Effect

The buffer effect describes the large-scale density dependent variation in patterns of habitat use, which determine the level of change in population size across different habitat-qualities (Gunnarsson et al. 2005; Gill et al. 2001). In poor quality sites there are greater fluctuations in population size in comparison to good-quality sites, hence, poor sites ‘buffer’ the good sites (Gill et al. 2001). Naturally populations can be regulated by the buffer effect because it works as negative feedback mechanism between population growth rate and population density, which determines various population demographics such as fecundity and survivorship (Bretagnolle et al. 2008; Gill et al. 2001). By this definition, poor sites should be avoided at low population densities and only when a population increases will density dependent factors force a proportion of a species into these habitats (Gill et al. 2001).

The buffer effect is ecologically important as it describes the mechanisms underlying density dependent changes in fecundity and mortality (Gill et al. 2001). Intraspecific competition is a term that describes the interactions between different individuals in a species that can be considered to increase when the size of a population increases, and resource availability become limited, in terms of prey, territory and mates (Gill et al. 2001). Intraspecific competition can also impact social behaviour that at high population densities can increase levels of interference by individuals. This ultimately would reduce a species’ chance to copulate, establish territory and utilize food resources, which can determine fecundity rates (Bretagnolle et al. 2008). In some bird species, density dependent processes are most influenced by intraspecific competition for food and social intolerance (Bretagnolle et al. 2008).

6

There are significant challenges in determining the occurrence of buffer effects, which are associated with the detectability of density dependence (Gunnarsson et al. 2005). In order to detect and measure buffer effects in wild populations it requires a population to have experienced a decline, and a subsequent recovery, to explore how a species distributes and regulate over time, in accordance to density dependent mechanisms (Gunnarsson et al. 2005).

Evidence of the buffer effect occurring in the wild has been seen in a number of recovering and expanding bird populations. The Icelandic black-tailed godwit Limosa limosa islandica is a winter wader in the UK that exhibited the buffer effect in response to its expanding population (Gill et al. 2001; Gunnarsson et al. 2005). This increase resulted in a disproportionate growth in the number of individuals shifting to poor quality sites associated with lower survival rates and lower breeding success (Gill et al. 2001). It was determined that the increased population size enhanced competition for important prey resources, which only individuals that arrived earlier to the estuarine wetland habitats could benefit from (Gill et al. 2001). The population in poorer quality habitats was subjected to poorer survival and breeding success, which were responsible for regulating the population (Gill et al. 2001).

2.2 Drivers for avian expansion into human dominated landscapes

Worldwide, vast areas of the natural landscape are experiencing rapid transformations, which have been modified or managed for particular human uses (Daily et al. 2001). The human population has grown dramatically, and with it so has the demand for natural resources and space. Over the last 10,000 years, humans have been responsible for extensive habitat change, fragmentation and homogenization through the expanse of urbanization and agricultural intensification (Daily et al. 2001). The spread of these human-dominated landscapes has impacted habitat function and disrupted unbroken tracts of natural wilderness (Daily et al. 2001). Numerous organisms that now exist in these habitats have needed to adapt to human- dominated landscapes (Daily et al. 2001; Wolff et al. 2002).

A number of species have proven to adapt to human dominated landscapes and in many cases profited greatly due to a number of direct and indirect benefits. Habitat transformation, specifically agricultural expansion, has not been uniform but instead created an expanding mosaic of a different habitats with varying intensities (Wolff et al. 2002). Over the last 2000

7 years, England and Wales have transformed 80% of the land into a diverse agricultural mosaic of crops, grasses and complex hedgerow systems (Williams 1967). A census carried out on avian species colonizing these areas concluded that 24 to 35 species could be found in over 90% of these areas (Williams 1967). The census also concluded that for most farms, densities ranged between 100 and 400 pairs per 100 hectares, suggesting agricultural farmland were able to support fairly large numbers of bird species (Williams 1967).

In the case of the little bustard Tetrax tetrax, the conversion of a natural steppe habitat into agricultural land that brought back the presence after a 50 year absence in Crau, Southern France (Wolff et al. 2002). Prior to the 1900s, the little bustard was a common bird in open fields of Europe, until significant declines threatened its survival. Between 1900 and 1950, there was no presence of little bustards in what was the only natural steppe habitat in Crau (Wolff et al. 2002). It was only from 1950, after World War II, were investments put towards developing farming techniques and irrigation systems did the little bustard begin to colonize the Crau (Wolff et al. 2002). Investigations identified that overall population densities of the species were highest in grazed legume crops, while none were seen to be in areas of remaining natural steppe habitat (Wolff et al. 2002).

Another species that is dependent on agricultural habitats is the Montagu’s Harrier, which breeds primarily in farmed crops, such as wheat, barley, rye-grass and alfalfa fields, in Western Europe (Arroyo et al. 2002). In France, 70% of the population nests in crops, while in Spain and Portugal it is 90% (Arroyo et al. 2002). For the Montagu’s Harrier, the abundance of the common vole Microtus arvalis is a key-determining factor for breeding (Arroyo et al. 2002). In some agricultural areas, particularly those containing game birds for recreation hunting, prey densities could actually increase due the introduction of human management strategies to control predators (Sternalski et al. 2013), therefore allowing common voles to thrive and thus Montagu’s Harrier to benefit.

However, in recent decades the speed and scale in which agricultural intensification is occurring has been the major issue, as it has been forecasted to have an even greater ecological and environmental implications on a variety of species that ever before (Kleijn & Sutherland 2003). Agricultural intensification, continues to encourage the mechanization, pesticide spraying, manipulation of vegetation phenology and composition across vast areas of the landscape, which reduces the capacity of farmland to support avifauna (Wolff et al.

8 2002; Kleijn & Sutherland 2003; Daily et al. 2001). These processes in intensive agricultural areas therefore reduces biodiversity and arthropod biomass, which reduces prey abundance: a key factor in bird distribution (Wolff et al. 2002; Marchesi et al. 2002). In a study investigating the Lesser Grey Shrike Lanius minor, Giralt et al. (2008) highlighted the importance of maintaining pockets of natural and semi-natural habitats in intensive agricultural areas as they serve as high quality food reservoirs that improve fledgling success. In Europe, agricultural areas harbor the highest proportion of birds with negative conservation statuses due to the sharp population declines in response to intensification (Wolff et al. 2002; Giralt et al. 2008).

Urban areas are arguably the most transformed habitats in the world and considering that a number of avian species have colonized these habitats suggest they can be adapted to. This is particularly the case for a number of raptor species that have been attracted towards urban environments. For example, in Sicily the Eagle owl Bubo bubo has been shown to take advantage of suburban/urban areas because the benefits these habitats contain outweigh the costs (Marchesi et al. 2002). In this case, prey abundance and availability of the Brown rat Rattus norvegicus was the major driving factor influencing the species’ expansion into the human landscape, which outweighed a reduced survivorship (Marchesi et al. 2002). As the Brown rat was available all year round, specializing and redistributing to the location of this species resulted in Eagle owl populations to increase in size and benefit from improved breeding performance (Marchesi et al. 2002). Urban environments have also been shown to have a positive influence on foraging success for a number of other bird species, such as the Red-tailed Hawk Buteo jamaicensis and Swainson’s Hawk Buteo swainsoni in Boulder Colorado, USA (Berry & Bock 1998). Boulder City contains a 100km2 network of open grassland spaces, mainly used for agriculture, which surrounds the city. The Hawks were shown to move into the area where it could take advantage of its preferred prey - prairie voles Microtus ochrogaster - much more easily due to mowing activities, which made the prairie voles more conspicuous, and therefore generating more suitable foraging habitats than elsewhere (Berry & Bock 1998).

Moreover, avian fecundity in urban areas has been described as a reflection of a species’ ability to adapt to the disturbances and challenges associated with these habitats (Chace & Walsh 2006). Breeding performance of the peregrine falcon Falco peregrinus and lesser kestrel Falco naumanni has also been better in urban landscapes due to abundant smaller bird

9 species found within such habitats (Chace & Walsh 2006). The smaller birds species and small mammal species have also been able to accumulate and serve as a sufficient prey resource due to fewer large bird and mammalian predators in urban landscapes (Chace & Walsh 2006).

Although some species have been able to benefit from city habitats, it is still understood that not all avian species can thrive and often it is the predatory, omnivorous, granivorous and cavity nesting species that tend to be better suited (Chace & Walsh 2006). Cities continue to replace vast rural habitats causing organisms to live in closer proximities to humans, which is likely to cause a number of problems in the future (McDonnell & Hahs 2008). In particular the increase in level of disturbance, physiological stress and disease transmission in cities, which increase mortality threats (Chace & Walsh 2006). As cities expand to accommodate growing human populations it will also encourage an influx of many other organisms to cluster in semi-natural pockets where resources may be available. This could potentially amplify chances for disease mutation and transmission (Chace & Walsh 2006).

2.3 Ecological Traps

An ecological trap is the concept of organisms choosing low quality habitats over superior habitats (Battin 2004). Typically when populations are recovering from low densities, primary habitat will be preferentially selected first until density dependence factors result in population regulation (Shochat et al. 2005). Equilibrium in population size occurs when the population distributes across different habitats. Organisms use indirect cues in the physical environment to make guided decisions regarding habitat selection and life history behaviour (Schlaepfer et al. 2002; Shochat et al. 2005). These decisions can include when to migrate, how many young to bear and what to eat (Schlaepfer et al. 2002). An ecological trap occurs when these cues are overestimated by the organism as a good predictor of quality, resulting in the majority of individuals to settle in trap habitats and subsequently a population with a lower mean fitness (Shochat et al. 2005).

An ecological trap can be encouraged when high quality habitats experience a change in appearance, even having had no impact on its function and quality, it can send false cues and reduce its attractiveness (Gilroy & Sutherland 2007). However, alterations can also include

10 the introduction of novel habitat features, or completely new habitats, which results in high quality habitats functioning as undervalued resources and low quality habitats being overvalued (Gilroy & Sutherland 2007).

Ecological traps have been described for a number of bird species but most notably for Cooper’s Hawk Accipiter cooperii found in Tucson, Arizona USA. The hawk was documented to occur in higher densities within the city, instead of exurban peripheral areas, which was credited to plentiful prey resources and nest sites (Battin 2004). The trap was that nestling mortality was higher in the city (50%) due to the presence of trichomoniasis transferred by pigeons and doves, which the hawks prey on (Battin 2004).

Due to the increasing scale of anthropogenic activities, the biological functioning and appearance of natural environments are being modified so rapidly and suddenly that organisms are often not able to adapt quickly enough (Schlaepfer et al. 2002; Gilroy & Sutherland 2007). Naturally, organisms would have taken the time to synchronize and adapt to succeed in its environment. However, these changes result in the organism becoming constrained by its evolutionary history causing it to make an unconscious mistake, such as choosing to settle in poor quality habitats instead of better quality ones (Schlaepfer et al. 2002). It is for this reason the ecological trap is considered part of the broader phenomenon known as an evolutionary trap that specifically highlights the significance of a sudden anthropogenic change in the environment, as the cause for an organism to become disassociated from its environment and make poor behavioural and life history choices, resuled in a maladaptive outcome (Schlaepfer et al. 2002).

The challenge has been to identify the cues which organisms use to make decisions, as well as determining which cues turn habitats into traps, because they can be difficult to detect (Shochat et al. 2005). There are various examples suggesting an ecological trap may be occurring, however, the mechanisms driving a species’ behaviour is often uncertain. For example, in California, Towhees Pipilo crissalis were seen to prefer grazed habitats that had an increased level of human disturbance, over ungrazed habitats, simply because it is able to produce greater numbers of offspring (Battin 2004). Also, American Robins Turdus migratorius preferred to nest in exotic shrubs Lonicera mackii, despite being documented to have poorer nest success (Battin 2004). In many cases these studies were inconclusive due to

11 time limitations preventing the understanding whether the traps were causing the population to decline (Battin 2004).

Humans have been very influential in the modification of habitats that have changed how organisms perceive the quality of habitats (undervaluing or overestimating). Trap habitats appear to hold a variety of short-term benefit to a population, which is often the presence of an appropriate resource supply or lower density of predators (Shochat et al. 2005). To prevent more long-term problems associated with fitness and breeding success, ultimately leading to population decline or extinction, requires the identification of what cues a species uses to determine the attractiveness of a habitat before settling in it (Schlaepfer et al. 2002).

2.4 The ecology of the Marsh Harrier

The Marsh Harrier Circus aeruginosus is a medium-sized ground nesting raptor that breeds mainly in wetland habitats and behaves as an open-habitat hunter (Sternalski et al. 2008; Cardador et al. 2011; Underhill-Day 1984). The Marsh Harrier is known principally as a migratory species with populations in Western Europe, North Africa and parts of Asia and is considered as native in over 230 countries within its global range (IUCN Red List 2013). However, the species has been known to behave sedentarily, noticed in some juvenile populations in France, which did not migrate in their first year (Sternalski et al. 2008). The migratory population will breed during the spring and summer months in Western Europe, including the UK, before migrating to North Africa in autumn and winter (Cardador et al. 2011; IUCN Red List 2013). Europe maintains a large proportion of the breeding populations global range, measuring between 25-49%, which is estimated to contain as many as 140,000 breeding pairs (IUCN Red List, 2013).

Research conducted on the ecology of the Marsh Harrier has established a consensus that its primary nesting habitat is dense marsh vegetation, typical of wetland habitat with the presence of fresh or brackish water (Birdlife International 2014; Scottish Raptor Study Group; Underhill-Day, 1984). They are ground nesting birds and the wetlands are important nest sites because it contains grasses, reeds and twigs to build nests (Birdlife International 2014). Wetland vegetation also provides protection from human disturbance and terrestrial predators, as well as resistance from local flooding events (Underhill-Day 1998; Cardador et al. 2011).

12 The species is not completely restricted to wetlands and has also been shown to nest in grain fields and other arable crop habitats (Birdlife International 2014; Scottish Raptor Study Group; Underhill-Day, 1984). The major threats to this species include wetland drainage; persecution by shooting and poisoning from heavy metals and pesticide use (Birdlife International 2014). Besides its threats, the species is considered ‘Least Concern’ globally due to its extremely large range (Birdlife International 2014).

A Marsh Harriers dispersal behaviour study conducted by Sternalski et al. (2008) in France between 2001 and 2007 concluded various patterns of dispersal between different age and sex groups. Marsh Harriers dispersal range at post fledging for males and females was 104±81m and 765±1838m, respectively (Sternalski et al. 2008). However, after the age one 1, males dispersed further than females: 2062±1208 and 1581±2126 m (Sternalski et al. 2008). In addition, distinctive differences were also noticed between breeding and non-breeding populations. The breeding population had a much smaller home range (349±185ha) in comparison to the non-breeding population (1603±2126ha) (Sternalski et al. 2008)

2.5 History of Marsh Harriers in Britain

Over that last 200 years, Marsh Harrier Circus aeruginosus in Britain have experienced significant fluctuations in their population in terms of both range and abundance. In 1870, it was suggested that scarce populations of Marsh Harriers had become confined to Norfolk, where its last known breeding attempt occurred in 1899 (Underhill-Day 1984). For 12 years Marsh Harriers were considered to be completely absent from Britain despite having previously existed in counties such as Somerset, Dorset, Shropshire, Lancashire and Yorkshire (Underhill-Day, 1984). It was only in 1911, following a recorded re-colonization by European Marsh Harrier populations in Britain that the number of breeding pairs increased to five by 1944 before eventually increasing to fifteen by 1958 (Underhill-Day, 1984). Between 1959 and 1971, the population experienced another decline that took the population down to a single breeding pair, which was credited to habitat disturbance and destruction, persecution, and the use of organochlorine pesticides in agricultural lands (Underhill-Day, 1984). The population in Britain has since made a recovery reaching approximately 18 breeding pairs by 1982 (Underhill-Day, 1984). This recovery was due to an initial increase in the number of Marsh Harriers emigrating from the Netherlands, as most Dutch reedbed

13 habitats were experiencing significant declines during this time. However, it has been considered that declines in the use of organochlorine pesticides on agricultural land in the UK were another important factor enabling this recovery (Underhill-Day, 1984).

14 3 Methodology

This project uses datasets collated by the Rare Breeding Bird Panel (RBBP), an ornithological body which collects population data on rarer species of birds in the UK, between 1973 and 2009, and two UK National surveys, 1995 and 2005, initiated by the Royal Society for the Protection of Birds (RSPB), a UK charity that promotes conservation and protection of birds and the natural environment (RSPB, 2014).

3.1 Rare Bird Breeding Panel monitoring methods

Data aggregated in the RBBP was a collation of surveys collected by various county bird recorders. Recorders were often citizen scientists that followed a monitoring method that surveyed the population and productivity of Marsh Harriers during the breeding season, between mid-April and mid-June (Gilbert et al. 1998). In the population surveys, it was instructed that at least three Marsh Harrier focused visits would take place between mid-April and mid-May to locate ‘probable’ nest sites (Gilbert et al. 1998). ‘Probable’ nests would be observed from vantage points for a minimum of 4 hours and were characterized by the presence of females carrying nest materials, and if a female is stationary for more than 4 hours and receives a prey delivery from a male (Gilbert et al. 1998). A further two or more visits was recommended during mid-May and mid-June to confirm nesting, which was determined by the observation of males delivering prey to nest sites (Gilbert et al. 1998). Productivity surveys during the breeding season were conducted over 2 to 3 hours at each confirmed nest site, where fledged young that could fly with adults were noted. Additional information was noted from late August onwards to identify evidence of eggs failing to hatch, and prey remains. Region, county, and site information were also included as attributes to nest locations, establishing a 36 yearlong dataset of population and distribution trends.

3.2 National Survey methods

The survey strategy for the 1995 and 2005 National Marsh Harrier Surveys was based on the 1995 survey design developed from a study conducted by John Underhill-Day in 1990. These National surveys adopted a census survey approach, without a formal sampling strategy. The census surveys were conducted in known areas of Marsh Harriers, determined from on going

15 monitoring and protection work carried out for the RBBP (RSPB, 2011). Additional nests were confirmed with evidence of skydancing males (Gilbert et al. 1998). Once nests had been identified, they were observed from vantage points for a minimum of 4 hours for Marsh Harrier breeding behaviours. Evidence of females carrying nest material, females being stationary for more than 4 hours and receiving prey delivered by males, were recorded as breeding sites (Gilbert et al. 1998). Productivity information was also recorded in National Surveys based on evidence of fledged young flying with adults, during 2 to 3 hour observations (Gilbert et al. 1998). Additional breeding information was also collected establishing whether eggs had failed to hatch or in fact been lost to predation. Besides population and productivity information, nest site habitat was also surveyed and characterized as wet, tidal or dry. However, after the 1995 National Survey, surveys were improved for the 2005 National Survey to include the presence of other environmental variables within 100m of the nest site. These variables indicated the presence and absence of trees and bushes, buildings, open water, navigational waterways, private paths, public paths, private roads, public roads within 100m.

3.3 Marsh Harrier population trends and distribution

The RBBP dataset was analysed to determine the population and regional distribution trends of Marsh Harriers in the UK, during its 1973-2009 recovery. The dataset was first manipulated and cleaned to remove any highlighted duplicates and incomplete records in order to eliminate errors and inaccuracies. To determine the population trends, the sum of nesting pairs was calculated for each year from 1973 to 2008, as data was incomplete for 2009. The calculation of the total number of nesting pairs in each year was then classified into different UK counties in which they were recorded.

Further distributional analysis of Marsh Harrier nesting pairs was conducted using the 1995 and 2005 National Survey datasets. Two GIS maps illustrating the spatial distribution and density of Marsh Harrier nesting pairs within 10km square grids were created for data collected in the 1995 National Survey and 2005 National Survey separately. Maps were created in ArcGIS 10 once each National Survey dataset had been transformed, using Merlin systems manager, into a shapefile consisting of all the UK 10km2 grid cells that Marsh Harriers were sighted in. Each shapefile was added into ArcGIS 10 (co ordinate system:

16 WGS84) on top of shapefiles outlining the regional administration boundaries of the UK, derived from free spatial data on the DivaGIS website. A frequency count was calculated for each National Survey’s raw data that summed the total number of nests within each 10km square grid, which was then joined to the shapefile created in Merlin. The change in density of 10km square grid cells between 1995 and 2005 was calculated from exported files containing frequencies in each grid reference.

The quantification and spatial illustration of population and distributional trends is important for understanding how the Marsh Harrier population has behaved during its recovery period, while also providing a historical background, context and patterns of change to aid in prioritizing and developing more strategic conservation management and monitoring plans for Marsh Harriers in the future.

3.4 Influence of landscape-scale habitat variables on nest site selection

A GIS was created for both 1995 and 2005 National Surveys datasets using the same UK administrative boundary shapefile taken from the DivaGIS website and the 10km square grid cells containing the frequency of Marsh Harriers nests, to produce maps analyzing population and distribution trends. Two additional habitat variable shapefiles; arable land and water bodies, for the whole of the UK were provided by RSPB and added to the GIS. The purpose of creating this GIS was to extract water body and arable land perimeters, areas, and the ratio between area and perimeter to identify how these variables influence frequency of nests within a 10km2 grid cell (See appendix 1 for extracted measurements). To achieve this, 10km2 grids, water bodies and arable land shapefiles were clipped to the terrestrial land boundaries of the UK to eliminate spatial inaccuracies and provide a true density on terrestrial land. The new water body and arable land shapefiles were then clipped again to the new grid cells that Marsh Harrier nests were found in. This enabled water body and arable land polygons to be representative of only the areas where Marsh Harrier nests were found. A dissolve tool was applied to each polygon in order to merge multiple polygons into a single polygon for the purpose of extracting a single total perimeter and area value for water bodies and arable land within each grid cell. Polygon perimeters and areas were calculated within the attributes table, and using the calculator divided area by perimeter to determine the ratio for each grid cell.

17 CSV files extracted from the GIS were analyzed individually using linear models. Key variables explored were; arable area km2, water body area km2 and ratio of water body area to perimeter. These variables were selected because they would best represent landscape features such as lakes, streams and agricultural areas. These habitat variables were incorporated into the linear models with the response variable being the number of nests per UK grid cell, divided by the terrestrial area (km2 of non-marine land) to provide a true density value. For each National Survey, a linear model was created and the dredge and importance functions applied. These tests were used to identify the minimum AIC model and which predictor variables were most important in determining the density of nests. The purpose of this was to determine the importance of different landscape features in species distribution. This method of model selection was favored over the automatized stepwise procedure that can lead to impacts of response data being influenced by even the most insignificant variables (Guisan & Edwards 2002). Ultimately, the stepwise selection can lead to a model that is not globally the best, thus missing important effects. Predictive models were plotted for each predictor variable and assessed for its individual impact on density of nests.

3.5 Influence of fine-scale habitat variables on nest site selection

The 1995 and 2005 National Surveys the percentage of the total number of Marsh Harriers pairs nesting in different habitats was measured. Twelve different habitats types; reed bed, dry reed bed, tidal reed bed, wet reed bed, sedge bed, a wet mixture of sedge and reed bed, saltings, wheat, barley, oilseed rape, rough grass and dry club rush were classified into 5 habitat types: barley, oilseed rape, wheat, wetland and others (see appendix 2 for detailed habitat type breakdown). To determine whether agricultural habitats are becoming more inhabited by the species, a chi-squared analysis was performed between the proportion of nests in wetland, intermediate agricultural land and intensive agricultural land between the two years the National Surveys. To determine the categories, all reed bed, sedge bed, saltings, club rush and mixtures were aggregated into wetland habitats. Rough grass was considered an intermediate agricultural land because it was neither a wetland nor intensive arable crop. The remaining barley, wheat and oilseed rape habitat types were grouped into an intensive agricultural land habitat. Identifying whether there was a significant difference in habitats nested in, between the two surveys, would determine if agricultural habitats were becoming increasingly, or decreasingly important as a nesting habitat.

18 3.6 Influence of habitat types on breeding performance

Breeding performance for this project referred to the fledged brood sizes and breeding success in both 1995 and 2005 National Surveys. The measurements for these factors were extracted for each nesting pair attached to habitat variables to determine whether certain habitat types fledged larger broods or had a higher proportion of successful breeding attempts. The mean fledged brood size per nest was calculated for each National Survey and displayed graphically against the classified habitat types to first, explore their influence, and second identify if it had change by the 2005 National Survey (See appendix 3 for detailed habitat breakdown).

A total of three Poisson GLMs were created; two for the 2005 National Survey and one for the 1995 National Survey, to analyse the influence of habitat types and the surrounding nest site variables on mean fledged brood sizes. The first GLM for the 2005 National Survey was constructed with the response variable, fledged brood size, and a simplified group of habitat types: wetland, wheat, oilseed rape, barley and others. Habitat types, such as “saltings”, “sedge bed” and “rough grass”, contained few data points and therefore were classified under “others” for the purpose of improving the modeling process. A second GLM created for the 2005 National Survey incorporated just the influence of habitat variables within 100m of the nest site on fledged brood size. The dredge and importance functions were applied to identify the preferred model with the minimum AIC value and then measured for the relative importance of each predictor variable. The third Poisson GLM was created for the 1995 National survey for temporal comparisons with how fledged brood size responded to different habitat types. Again, variables with few data points, “club rush” and “barley” were classified under the group “others”.

Breeding success was determined by whether Marsh Harriers were successful in producing at least one fledged young, otherwise it was considered a failure. Three binomial GLMs were created to determine the significance of different habitat variables for each National Survey: two 2005 National Survey and one 1995 National Survey. Two binomial GLMs were created for the 2005 dataset to investigate the influence of habitat variables on Marsh Harrier breeding success in the UK. The first was constructed with habitat types only, classified in exactly the same way fledged brood size had been, and breeding success. The second binomial GLM created for the 2005 National Survey using a all the habitat variables within 100m of the nest, i.e. presence of buildings, water bodies, roads, paths and trees/bushes, in

19 order to test which habitats were significant. The dredge and importance functions were applied to identify the preferred model with the minimum AIC value and to measure the relative importance of each predictor variable. The third and final binomial GLM was constructed for the 1995 National Survey, which examined only habitat types, in order to compare it with 2005 dataset. Habitat types with fewer data points were classified under “others”, which for 1995 was “club rush” and “barley”.

In order to determine whether breeding success was increasing in agricultural habitats temporally, a chi-squared test was performed. The same was applied to wetland habitats for the purpose of comparison and to identify any temporal patterns of change.

3.7 Problems using multiple and aggregated datasets

Many research ecologists attempt to integrate large numbers of datasets that consider spatial, temporal, historical and topical elements in order to understand and explain species ecology with greater scope (Parr et al. 2006; White et al. 2010). There are many benefits for combining datasets, which was shown in various plant evolution and adaptation, community composition and climatic perturbation studies such as the Park Grass Experiment (Magurran et al. 2010). However, the integration of multiple datasets has its challenges and limitations. There are issues concerning the processes of collation, as assembling multiple datasets lead to errors during the merging phase (Parr et al. 2006).

Bias may be another issue to consider when dealing with data that has been aggregated by different groups or individuals, with different interests and motivations. For citizen scientists, it often depends on the motivation for survey collection, as it can influence the level of effort invested, which eventually determines the quality of data collected (Crowston & Prestopnik 2013).

20 4 Results

4.1 Population trends

500 450 400

350

300 250

200 No. of PairsNo.of 150 100 50

0

1976 1984 1973 1974 1975 1977 1978 1979 1980 1981 1982 1983 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Year

Figure 1 Number of Marsh Harrier breeding pairs in the UK between 1973 and 2008

The population of the Marsh Harrier has increased from 5 to 454 breeding pairs between 1973-2008 (Figure. 1). Between 1973 and 1987, the Marsh Harrier breeding population gently increased by 42 pairs, over 14 years. By 1988, in the space of 1 year, the number of breeding pairs increased by 57 pairs, more than doubling the breeding population to reach 107 in Britain.

Beyond 1988, the number of breeding pairs is shown to fluctuate before maintaining a positive trajectory between 2003 2008. Figure. 1 shows 3 distinct peaks and troughs during the 20-year period. First, by 1992, the breeding population is shown to reach a high of 167 before decline by 55 breeding pairs in 1993. The number of Marsh Harrier breeding pairs subsequently increased and peaked at 203 in 1995 before declining again by 90 pairs in 1998. Immediately after this decline, the number of pairs significantly increases from 113 in 1998 to 307 in 2000. This increase of 196 breeding pairs, over 2 years, is shown as the sharpest and largest increase the species had experienced at the time. The number of breeding pairs then declines by 73 in 2001, before recovering by 50 and reaching 284 breeding pairs in 2002, only to experience another sharp decline (of 119 breeding pairs) to 165 in following year.

21 From this distinct trough shown in 2003, the number of Marsh Harrier breeding pairs makes a recovery, and maintains its recovery over the next 5 years to reach 454 pairs in 2008.

4.2 Distribution of Marsh Harrier nest sites across the UK

100%

90% 80% 70% 60% 50% 40%

Proportion of nesting pairsnestingof Proportion 30% 20% 10%

0%

1975 2004 1973 1974 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2005 2006 2007 2008 Year Suffolk Norfolk Fife Cambridgeshire Lancashire Lincolnshire Gower Hampshire Essex Kent Anglesey NE Scotland

Figure 2 The proportional distribution of Marsh Harrier breeding pairs across UK counties between 1973 and 2008

As the number of Marsh Harrier breeding pairs has increased during its 1973 and 2008 recovery, Figure 2 illustrates that specific counties have been able to accommodate the species more sustainably than others.

For the first two years of the RBBP dataset the entire population of Marsh Harriers was identified within Suffolk, before later expanding into Norfolk in 1975. Between 1975 and 1990, the majority of the population existed in Suffolk and Norfolk. During this period, the population increased from 11 to 131 pairs and the proportion of Marsh Harriers in Norfolk was gradually increasing. By 1983, 65% (30 pairs) of the population was occupying Norfolk, which was the highest proportion of Marsh Harriers in one county by this point during its recovery. In contrast, during this period, Suffolk was experiencing a gradual proportional decline. On two occasions during this period the proportion of Marsh Harriers in Suffolk

22 decline to below 20% in less than 10 years. In 1981, Suffolk contained 13% (3 pairs), while in 1983 it was 17% (8 pairs). The proportion of Marsh Harriers in Suffolk appeared to steeply decline between 1992 and 1996, from 34% (63 pairs) to 1% (1 pair). In the lead up to this proportional decline in Suffolk, the proportion of Marsh Harriers in counties such as Kent and Lincolnshire were seen to rapidly increase. In 1989, there were 5 pairs (5%) of the population in Lincolnshire, which by 1990 increased to 19 pairs (15%). By 1996, Lincolnshire contained 18% of the Marsh Harriers in the UK. However, it was proportion increase witnessed in Kent, which appeared to replace the population previously held in Suffolk. In 1992, there was 12% (20 pairs) in Kent, which in 1996 jumped to 65% (30 pairs).

The population in Suffolk gradually recovered over the next 10 years, peaking in 2003 with 31% (51 pairs). During this 10 year period, Norfolk was experiencing a proportional decline in Marsh Harriers, dropping to 16%. The proportional distribution by 2008 was equalizing, as Suffolk, Norfolk, Lincolnshire and Kent shared the highest proportion of Marsh Harriers across the UK, 19%, 22%, 22% and 24%, respectively. Lincolnshire and Kent containing over 100 pairs.

23 4.3 Distribution and frequency of Marsh Harrier nest across the UK

1995 2005 Number of nesting pairs Number of nesting pairs

Figure 3 Location and number of Marsh Harrier Breeding pairs recorded in the 1995 (left) and 2005 (right) National surveys in the UK, per 10km2 grid cell.

In the space of 10 years, Marsh Harriers have displayed a growth in terms of range and number as illustrated in figure 3. The 10km2 grid cell with the greatest measured change is TR06 (Kent), which increases to 31, from an original 11 nests. Grid reference TF33 (Lincolnshire) was the next largest change in number of nests with an increase of 16, from 0. This was followed by TF16 (Lincolnshire) with an increase of 15, from 0 and TF84 with an increase of 14 nests from 7. Grid cells TG42 (Norfolk) and TF25 (Lincolnshire) saw relatively large increases of 12 and 11, respectively. While TF15 (Lincolnshire), TG30

24 (Norfolk) and TM47 (Suffolk) also increased by 10 nests, between the 1995 and 2005 National surveys.

There were also a number of grid cells that experienced declines in the number of Marsh Harrier nests, between 1995 and 2005 National surveys. Grid cells SK92 (North Lincolnshire) and TG40 (Norfolk) had the greatest declines (4). SK92 declined from 5 to just 1 nest, where as TG40 declined from 8 to 4. Grid cells NJ25 (Grampian) and NO60 (Perthshire) saw declines of 2 Marsh Harrier nests over the 10-year period.

The top five more densely nested 10km2 grid cells in the UK were TR06 (42), TF84 (21), TM42 (20), TM47 (19) and TF33 (16). This combination of grid cells is different to what was identified in the 1995 National survey that showed grid cells TQ96 with 13 nests, TR06 with 11, TF62 with 10, and SE82 and TM47 both with 9, were the top five most densely nested 10km2 grid cells in the UK at the time. See appendix 4 for measured changes in nested grid cells.

25 4.4 The influence of landscape features on nest habitat selection

Table 1 Model selection table displaying the minimum AIC values for model combinations investigating the influence of water body and arable land dimensions on the density of Marsh Harrier nests, in 1995

Model Combinations AIC delta Weight Density ~ Arable land area + Water body ratio -106.1 0.00 0.565 Density ~ Arable land area + Water body area + Water body ratio -104.5 1.57 0.257 Density ~ Arable land area -102.3 3.81 0.084 Density ~ Arable land area + Water body area -100.3 5.81 0.031 Density ~ Water body ratio -99.9 6.16 0.026 Density ~ Water body area + Water body ratio -98.7 7.40 0.014 Null -98.7 7.42 0.014 Density ~ Water body area -97.8 8.31 0.009

Table 2 Model selection table displaying minimum AIC values for model combinations investigating the influence of water body and arable land dimensions on the density of Marsh Harrier nests, in 2005

Model Combinations AIC delta Weight Density ~ Arable land area + Water body area + Water body ratio 288.5 0.00 0.555 Density ~ Arable land area 291.2 2.64 0.148 Density ~ Arable land area + Water body area 291.2 2.67 0.146 Density ~ Arable land area + Water body ratio 291.3 2.80 0.137 Null 297.6 9.10 0.006 Density ~ Water body area 299.0 10.49 0.003 Density ~ Water body ratio 299.0 10.50 0.003 Density ~ Water body area + Water body ratio 299.7 11.17 0.002

26 1995 National Survey 2005 National Survey

Figure 4 Arable land area, water body area and water body ratio against the density of Marsh Harrier nests, within UK 10km grid references, recorded in 1995 (left) and 2005 (right) National Surveys

27 The preferred model to analyse 1995 National Survey density records, in response to landscape features, is displayed in table 1, which includes arable land area (km2) and water body ratio, as it has an AIC of 288.5 and weight of 0.565. In the 2005 National Survey, table 2 illustrates that predictor variables Arable land area, water body area and water body ratio produce the model with the minimum AIC value, 288.5 with a weight of 0.555.

In the 1995 National Survey, arable land area, water body area and water body ratio had importance values 0.986, 0.706 and 0.697, respectively, and should be considered important variables causing an effect on the density of nests. Whereas, in the 2005 National Survey, only arable land area and water body ratio that were important variables (Importance = 0.937 and 0.862, respectively), to effect density of nests.

Area of arable land (km2) and water body ratio, plotted against density of nests within a 10km2 grid cell in 1995 and 2005, displayed negative correlations. While Area of water bodies showed a positive correlation when plotted against density of nests.

28 4.5 Nest site distribution across different habitats

100.0 1995 National Survey

90.0 2005 National Survey 80.0 70.0 60.0 50.0 40.0 30.0 20.0

Percentage of nesting Pairs(%) of nestingPercentage 10.0 0.0 Barley Oilseed Rape Wheat Wetland Other Habitat Type

Figure 5 The percentage of Marsh Harrier pairs nesting in different habitat types, between 1995 and 2005

Figure 6 The proportional distribution of Marsh Harrier nest sites occupying wetland, intermediate agricultural and intensive agricultural habitats, between 1995 and 2005

29 Illustrated in figure 5, Marsh Harriers have nested across 5 groups of habitat, between 1995 and 2005. In 1995, Marsh Harriers nested in only 4 of these habitat groups: Wetland, wheat, oilseed rape and a collection of others. In 1995, wetland habitat had the highest proportion of nesting pairs in the UK (78.8%). Wheat habitats had the next highest proportion of nesting pairs (15.9%), followed by oilseed rape with 4.4%. The remaining 0.9% of the population was occupying other habitats neither agricultural nor wetland. In 2005, wetland habitat contained the highest proportion of nesting pairs (75.7%). Wheat, oilseed rape and barley habitats each contained 10.6%, 8.6% and 3.4% of the total nesting population of Marsh Harriers. The remaining 1.7% made up in the other habitat group.

Illustrated in figure 6, the 1995 National Survey data shows 78.38% of Marsh Harrier breeding pairs nested in wetland habitat types, while the remaining 21.62% were nesting in intensive agricultural land. For the 2005 national survey, 76.98% of the population was shown to nest in wetland habitat, 1.53% in intermediate agricultural land and 21.48% in intensive agricultural land. Statistically, the habitats Marsh Harriers were nesting in 1995 were not significantly different to the habitats Marsh Harriers were nesting in 2005 (χ²= 1.55, df = 2, p-value = 0.46, Pearson’s Chi-squared test) therefore the null hypothesis is accepted: there is no significant difference in the proportion of habitats nested by Marsh Harriers, between 1995 and 2005.

30 4.6 The influence of different habitat types on fledged brood sizes

1995 National Survey

4 2005 National Survey

3.5 3 2.5 2 1.5 1

Mean Fledged broodsizeFledged Mean 0.5 0 Wheat Barley Oilseed Rape Wetland Other

Habitat Type

Figure 7 The mean (±SD) fledged brood size for Marsh Harrier pairs across different habitat types, between 1995 and 2005

In 1995, wheat, oilseed rape, wetland and other were identified to produce fledged brood young. Club rush, which had been classified under the group ‘other’, was a single recording and therefore could not calculate a mean for. Wheat had the highest mean fledged brood size of 2.86±0.62. Wetland habitat was next highest with 2.35±0.145, which was then followed by oilseed rape habitats with 2±0.53. In 2005, Wheat habitats had the highest mean fledged brood size again, with 2.77±0.3, which didn’t differ from the 1995 values. Barley habitats had the next highest mean fledged brood size with 2.5±0.34, which had previously not been inhabited during the 1995 National Survey. Wetland habitats had similar mean fledged brood sizes (2.46±0.09) to barley, and did not differ from 1995 results. Oilseed rape had a mean fledged brood size of 1.73±0.29, which was slightly less than in 1995. It also had a notably smaller mean fledged brood size than wetland, wheat and barley habitats. In other habitats, the mean fledged brood size of 2.25±0.75.

31 Table 3 Model results for tested GLM investigating the influence of only nest site habitat types on fledged brood sizes recorded in the 1995 National Survey

Coefficients: Estimate Std. Error z value Pr (>|z|)

Intercept (Wetland) 0.782 0.062 12.565 0.000 *** Oilseed Rape 0.340 0.274 1.241 0.215 Other -0.376 0.580 -0.649 0.516 Wheat 0.221 0.143 1.542 0.123

Table 4 Model results for tested GLM investigating the influence of nest site habitat types on fledged brood sizes recorded in the 2005 National Survey

Coefficients: Estimate Std. Error z value Pr (>|z|) Intercept (Wetland) 0.899 0.042 21.246 0.000 *** Barley 0.016 0.204 0.083 0.934 Oilseed Rape -0.350 0.154 -2.264 0.024 * Other 0.016 0.261 0.065 0.948 Wheat 0.120 0.115 1.044 0.296

Figure 8 The influence of different classified habitat types on Marsh Harrier fledged brood sizes, in the 1995 (left) and 2005 (right) National Surveys

32 Table 5 Model selection table displaying minimum AIC values for model combinations investigating the influence of nest site features within 100m on the fledged brood sizes, recorded in the 2005 National Survey.

Model Combinations: AIC Delta Weight Null 1090.3 0.00 0.161 Fledged Brood size ~ Trees & bushes 1091.5 1.23 0.087 Fledged Brood size ~ All paths 1091.8 1.50 0.076 Fledged Brood size ~ Buildings 1092.1 1.83 0.064 Fledged Brood size ~ All roads 1092.2 1.90 0.062 Fledged Brood size ~ Water bodies 1092.3 1.99 0.059 Fledged Brood size ~ All paths +All roads 1093.2 2.86 0.038 Fledged Brood size ~ All roads + Trees & Bushes 1093.2 2,93 0.037 Fledged Brood size ~ All paths + Trees & Bushes 1093.3 3.00 0.036 Fledged Brood size ~ Trees & Bushes + Water bodies 1093.4 3.08 0.035 Fledged Brood size ~ Buildings + Trees & Bushes 1093.4 3.10 0.034 Fledged Brood size ~ All paths + Buildings 1093.7 3.38 0.030 Fledged Brood size ~ All paths + Water bodies 1093.7 3.43 0.029 Fledged Brood size ~ All roads + Buildings 1094.0 3.70 0.025 Fledged Brood size ~ Buildings + Water bodies 1094.1 3.82 0.024 Fledged Brood size ~ All roads + Water bodies 1094.2 3.89 0.023 Fledged Brood size ~ All paths + All roads + Trees & Bushes 1094.5 4.21 0.020 Fledged Brood size ~ All paths + All roads + Buildings 1095.0 4.71 0.015 Fledged Brood size ~ All roads + Buildings + Trees & Bushes 1095.1 4.76 0.015 Fledged Brood size ~ All paths + Trees & Bushes + Water bodies 1095.1 4.78 0.015 Fledged Brood size ~ All paths + All roads + Water bodies 1095.1 4.78 0.015 Fledged Brood size ~ All roads + Trees & Bushes + Water bodies 1095.1 4.78 0.015 Fledged Brood size ~ All paths + Buildings + Trees & Bushes 1095.2 4.89 0.014 Fledged Brood size ~ Buildings + Trees & Bushes + Water bodies 1095.2 4.94 0.014 Fledged Brood size ~ All paths + Buildings + Water bodies 1095.6 5.31 0.011 Fledged Brood size ~ All roads + Buildings + Water bodies 1096.0 5.70 0.009 Fledged Brood size ~ All paths + All roads + Trees & Bushes + Water bodies 1096.2 5.93 0.008 Fledged Brood size ~ All paths + All roads + Buildings + Trees & Bushes 1096.4 6.07 0.008 Fledged Brood size ~ All roads + Buildings + Trees & Bushes + Water bodies 1096.9 6.61 0.006 Fledged Brood size ~ All paths + All roads + Buildings +Water bodies 1096.9 6.63 0.006 Fledged Brood size ~ All paths + Buildings + Trees & Bushes + Water bodies 1097.0 6.67 0.006 Fledged Brood size ~ All paths + All roads + Buildings + Trees & Bushes + Water bodies 1098.1 7.78 0.003

33 The model investigating fledged brood size records from the two National Survey, in response to habitat type, was displayed in table 3 and 4. An analysis of variance confirms was carried out on fledged brood size in response to habitat types, in 1995. Habitat types were not significant in determining fledged brood sizes of Marsh Harriers recorded in 1995 National Surveys (F = 1.443, df = 3, p = 0.233). However, an analysis of variance confirms a weak significance of the habitat types in 2005 (F = 2.077, df = 4, p = 0.0838). Only oilseed rape had a significantly negative effect on fledged brood size (Estimate = -0.35084, p = 0.0236). However, barley, wheat and other habitats did not display any significant p values in 2005.

Boxplots displayed in figure 8 shows there was a slight variation in fledged brood size between each National Survey. In 1995, wetland and wheat habitats had a median of 3 fledged broods, and were both able to produce a maximum number of 5 and a minimum number of 0. In 2005, wheat habitats were the same and had a lower and upper quartiles were 2 and 4, respectively. In 2005, fledged brood size in wetland habitats differed slightly to 1995 results. Firstly, the maximum fledged brood had dropped to 4, while the minimum had increased to 1, ultimately narrowing the range. In addition, the lower quartile was now 2 fledged broods instead of the 0 in 1995. Oilseed Rape in 1995 and 2005 had the same median number while the minimum fledged brood size dropped from 2 to 0. The maximum fledged brood size differed slightly in oilseed rape between the two surveys, with 2005 having a wider range (0-4). Barley habitat in 2005 showed similarities to that of wetlands, with a median of 3, a lower quartile of 2 and a maximum fledged brood size of 4.

Taking into consideration how other surrounding variables may influence the fledged brood size, table 5 illustrates the model selection process. The null model produces the minimum AIC value, 1090.3 with the weight 0.161. This was relatively similar to the subsequent lowest AIC model (1091.5) of fledged brood size and Trees & Bushes, 0.087. All predictor variables scored below 0.5 when an importance test was run. Trees and bushes had the highest importance factor (0.35), while water bodies had the lowest (0.28), in determining fledged brood size.

34 4.7 Breeding success in different habitat types

Table 6 Model results for tested GLM investigating the influence of different nest habitat types on attempted breeding outcome collected in the 1995 National Survey

Coefficients: Estimate Std. Error z value Pr (>|z|) Intercept (Wetland) 0.782 0.062 12.565 0.000 *** Oilseed Rape -0.340 0.274 -1.241 0.215 Other -0.377 0.581 -0.649 0.516 Wheat 0.221 0.143 1.542 0.123

Table 7 Model results for tested GLM investigating the influence of different nest habitat types on attempted breeding outcome collected in the 2005 National Survey

Coefficients: Estimate Std. Error z value Pr (>|z|) Intercept (Wetland) 0.866 0.127 6.784 0.000 *** Barley 0.231 0.678 0.341 0.733 Oilseed Rape -0.927 0.371 2.500 0.012 * Other -1.049 0.618 -1.695 0.090 . Wheat -0.287 0.115 0.803 0.422

Model results in table 6 showed that all habitat types did not significantly affect the breeding outcome of Marsh Harriers in 1995. In contrast, model results for breeding outcomes in 2005 showed oilseed rape habitats had a significantly negative effect on breeding outcomes.

35 1995 2005

Figure 9 The proportion of Marsh Harrier breeding pairs successful in producing ≥1 fledgling in the 1995 (left) and 2005 (right) National Survey datasets, compared between habitats

Wetland Argircultural land

Figure 10 The proportional breeding success of Marsh Harriers in wetland habitat (left) and agricultural habitats (right), compared between 1995 and 2005

36 Table 8 Model results for preferred GLM investigating the influence of nest site features within 100m on breeding success, recorded in the 2005 National Survey

Coefficients: Estimate Std. Error z value Pr (>|z|) Intercept (Wetland) 0.6970 0.159 4.383 0.000 *** WaterbodyYes 0.3304 0.222 1.491 0.1361 AllRoadsYes -0.847 0.302 -2.805 0.005 **

From the 1995 National Survey, 85% of Marsh Harriers nesting in wheat habitats were successful in producing ≥1 fledgling, which was the highest proportion in comparison to other habitat types. 80% of nests in wetland habitats were successful at producing ≥1 fledglings, while 71.4% were successful in oilseed rape habitats. Nests in the aggregated other habitat, 50% were successful. For the 2005 National Survey, barley habitats were shown to have the greatest proportion of successful breeding outcomes (75%) for Marsh Harrier pairs producing ≥1 fledgling. Wetland habitats produced the next highest proportion of successful breeding outcomes with 70.4%, followed by wheat with 64.1%. Marsh Harriers nesting in oilseed rape were 48% successful in producing ≥1 fledgling, slightly above the 45.5% successful in the other habitats.

Breeding success is illustrated to be best predicted using a model with predictor variables; all roads and water bodies. This model had the minimum AIC value of 486.4, with a weighting of 0.184.These two predictor variables generated importance values of 0.957 and 0.516, respectively. Illustrated in table 8, roads had a significant negative effect on breeding success, while the presence of water bodies is suggested to have a positive influence.

Within agricultural habitats, figure 10 (right) shows the proportional difference in breeding success was not significantly different between 1995 and 2005 (χ²= 3.498, df = 1, p-value = 0.061, Pearson’s Chi-squared test). Similarly in figure 10 (left), the proportional breeding success in wetland habitats were not significantly different between 1995 and 2005 χ²= 2.146, df = 1, p-value = 0.1429, Pearson’s Chi-squared test). Agricultural habitats and wetland habitats had higher breeding success in 1995 (80% and 80.18%), in comparisons to 2005 (67% and 70.23%). However, agricultural and wetland habitats had nearly identical proportions of breeding success.

37 5 Discussion

The Marsh Harrier population is increasing and over the course of its recovery it has dispersed into a number of UK counties. The estimated population size as of 2008 is at 450 pairs, with a majority of Marsh Harriers exist in Suffolk, Norfolk, Lincolnshire and Kent. Within these counties, Marsh Harriers have been identified to nest in a variety of different agricultural and wetland habitats. Wetland habitats contain a greater proportion of Marsh Harrier nests. However, results have suggested that relationships between habitats, and productivity and breeding success may not be able to explain this pattern of distribution. Firstly, the mean fledge brood sizes were mildly different across different habitat types suggesting all habitats had a fairly similar brood sizes regardless of which habitat they nest in. Secondly, the proportional breeding success in agricultural habitats was near the same as the proportional breeding success in wetland habitats. The analysis of landscape habitat features indicated that the area of arable land and water body ratio influenced density of nests within an area. Generally smaller water body ratios, and smaller arable land areas affect the density of nests within an area. Through temporally analyzing these trends, the results showed that there has been no significant difference between the proportional distribution of nest sites in wetland and agricultural areas. Additionally, breeding success in agricultural habitats has not significantly increased between 1995 and 2005. These two results suggest that the conservation concerns for the Marsh Harrier in Spain, are not occurring in the UK at this point in time.

5.1 Influence of habitat type on Marsh Harrier nest site selection and breeding performance

As more than three quarters of the population is occupying natural wetlands, the habitat may be considered more important than agricultural habitat for the species. This result supports the general consensus that wetland habitats are primarily selected by Marsh Harriers in the UK and that the presence of tall emergent reed vegetation found within this habitat may be key for nest construction, protection from disturbance and predation, as well as resistance from local flooding events (Underhill-Day 1998; Cardador et al. 2011).

38 Habitat quality is an important factor in nest site selection, which has often been described as a function of food availability, predation risk and level of intra-specific competition (Sternalski et al. 2013). Agricultural habitats are commonly considered of poor quality, largely due to the strong connection between intensive agricultural habitats and the decrease of avian species. Intensive agriculture is involved in pesticide use, removal of hedgerows, harvest disturbances and loss of habitat heterogeneity, which subsequently lead to degraded hunting, nesting habitats and the increased mortality and reproductive failures (Cardador et al. 2011). However, Cardador et al (2011) identified agricultural habitats can be attractive to avian species, in particular the Marsh Harrier, as they can provide adequate food availability and nest protection, defined as important factors that influence nest selection. In addition, agricultural land can contain fewer large bodies of water, because they often require the manipulation of the landscape and hydrological systems to maximize their yields (Smith et al. 2002). The Marsh Harrier prefers water body features with a low area to perimeter ratio, such as streams and ditches, which are not limited to wetland environments. Similar water features are found in agricultural habitats, which are often created as narrow irrigation systems (Smith et al. 2002), or more specifically in the UK to improve land drainage.

Defining habitat quality in isolation to productivity and breeding success would be inadequate as these population dynamics are affected by habitat quality (Smith et al. 2002). For nearly a quarter of the Marsh Harrier’s existing in agricultural habitats, the proportional breeding success was almost the same as the proportional breeding success for the remaining population nesting in wetland habitats, (80% and 80.18%, respectively). In addition, the mean fledged brood size was shown not to vary dramatically between different habitat types. Despite, oilseed rape habitats, there was no significant effect from alternative habitat types implying that agricultural habitats were not less productive than wetland habitats. Interestingly, the temporal decline in breeding success between 1995 and 2005 in agricultural habitats, which was the near exact proportional change seen in wetlands. Breeding success has remained near identical across different habitats. Even when breeding success declined in 2005, very similar breeding success across the different habitats was apparent, suggesting both habitats consistent. This decline in breeding success may be due to the increase in population size rather than the effect of habitat quality.

During the breeding season, interference from other nesting pairs, and individuals may disturb breeding activities. This was witnessed in raptor species, as an increase in population density

39 led to greater territorial intrusions and interactions resulting in negative effects on breeding performance (Bretagnolle et al. 2008). Moreover, as Marsh harriers have shown a constant proportional habitat distribution, between 1995 and 2005, it may be accurate to claim the buffer effect is not occurring on this population.

Taking these beneficial characteristics into consideration, it may therefore be false to define agricultural land as a poor quality habitat. Instead, it may be these benefits in conjunction with the small channels and ditches commonly found in agricultural habitats that maybe encouraging Marsh Harriers to nest there (Smith et al. 2002; Gordon et al. 2010). However, there is distinctly smaller proportion of nesting pairs in agricultural areas. One suggestion for this pattern is there may be an increased level of mortality, potentially due to persecution and chemical use in agricultural areas. Persecution of raptors in the UK has restricted the range and abundance of most of these species (Thirgood et al. 2000). The persecution of Marsh Harriers is documented in the Ebro delta, Spain, where it was one of the major causes for population declines in the 1960s (Mateo et al. 1999). Despite efforts to reduce persecution through stricter bird protection laws, and agricultural policies, there remains a strong motive for managing raptor populations in agricultural areas (Thirgood et al. 2000). Due to the nature of human-raptor conflicts, killings may be taking place illegally and therefore difficult to account for (Thirgood & Redpath 2008).

5.2 Impact of oilseed rape and arable land area on population dynamics

Specific habitat types affected the breeding performance of Marsh Harriers differently. Individual habitats could not have significantly influence effects on the fledged brood sizes and breeding success of the species. Oilseed rape slightly different as it is shown to have a negative effect on fledged brood size in 2005, which may explain the habitat’s pronounced decline in breeding success, between 1995 and 2005. A reason for this trend may be linked to the area of agricultural land, which is shown to have a negative correlation with density of nests. Chamberlain et al. (2000) identified in England and Wales that during the time when agricultural practices were intensifying, the farming area of oilseed rape increased. The extent oilseed rape was being farmed increased due to its profitability, but also because it was a popular crop incorporated into set-aside schemes (Chamberlain et al. 2000). A negative relationship between density of nests and the area of arable land is shown, which may be the

40 result of Marsh Harriers avoiding oilseed rape habitats because mean fledged brood size is generally lower, and breeding success much poorer. Being a profitable crop, intensive farming practices may be more concentrated in oilseed rape habitats to maximize yield. This may require greater fertilizer and pesticide use in comparison to other habitats, which increases risk of human and chemical disturbance (Sternalski et al. 2008). Historically, the species has been known to suffer significantly higher breeding failures due to the use of chemical pesticides that caused eggshell thinning (Underhill-Day, 1984). Alternatively, the increase in the abundance of Marsh Harriers nesting in oilseed rape habitats in 2005 may have triggered stronger intra specific competition, hence a reduced breeding success.

Arguably, there is reduced prey availability in larger intensive arable land areas, which may be influencing these patterns of nest distribution. Small mammals have been identified to use field boundaries as areas of refugia, because it is disturbed less (Bilenca et al. 2007), which suggests that larger more homogenous habitats would be less adequate for nest selection. Water bodies, streams and ditches are also likely to be on the periphery of arable areas, and not necessarily all the way around. This could concentrate prey and water features on the edge of large field may be concentrated, therefore may ignite higher intraspecific competition.

Although there is available information on the productivity and breeding success of the species, the absence of mortality information limits the ability to distinguish whether agricultural habitats are truly good or poor quality. Even though the proportion of nesting pairs in oilseed rape habitats has increased, and breeding success and mean fledged brood size have decreased, between 1995 and 2005, it wouldn’t be possible to determine whether the habitat was an ecological trap. For determining the habitat quality of agricultural land requires information on species survivorship.

5.3 Assumptions and limitations

Significant assumptions and limitations were apparent in this study that inhibited the overall strength of the project results. This was largely due to two key problems: the number and consistency of replicated National Surveys, and reporting biases.

RBBP data quality and accuracy was weak, which restricted the ability to incorporate information into the analysis of this project. The accuracy of RBBP reported data decreased

41 towards the second half of the 36-year aggregated dataset for a number of reasons. A key problem involved the issue of bias in that survey counts were becoming more arbitrary and included “county total counts”. This is a form of cognitive bias, which may have arisen due to the increase in Marsh Harrier population size, which made it more difficult to count and monitor the species. The increase in Marsh Harrier population created additional bias relating to the rarity of the species. Individuals carrying out surveys may be more motivated, and likely to put in more effort, into recording observations of a rarer bird (Crowston & Prestopnik 2013). As the species became less rare each year, its attractiveness for recorders may have declined. For this reason, the RBBP dataset were primarily used as a coarse guide of general trends, which limited its value and use in analysis.

Data quality was also a concern when constructing GIS maps of Marsh Harrier distribution using National Surveys. In the 2005 National Survey, the location of nest sites was recorded at the scale of 1km2. However, in the 1995 National Survey, though a 1km grid references was provided for some sites, for the majority of records only a site name was provided. As some of these sites were large reserves, with more than 1 site location, multiple records were given the same site name location, which created challenges when attempting to identify individual nest sites at a fine 1km2 grid cell resolution. To accommodate for the few that could be identified, a 10km2 grid cell reference had to be adopted, which meant accuracy was lost. Also, records that a 10km2 grid reference could not be determined for were omitted from the final 1995 National Survey distribution map, further limiting results.

An important assumption made in this project was that it would be adequate to investigate population dynamics temporally with just two National Surveys. A third National Survey would be more scientifically and statistically more robust temporal study. Temporal analysis was further limited by the inconsistency of National Survey datasets. In the 2005 National Survey, much greater detail was provided in comparison to the 1995 National Survey. For example, missing from the 1995 National Survey is information regarding the surrounding environmental variables, which could have been compared for a more detailed breeding performance information.

42 5.4 Recommendations for future surveys

Currently only two National Surveys have been conducted for the species. The project suffers statistical limitations and would improve with an additional detailed National Survey to follow up habitat studies. It is recommended that they continue to follow the structure of the 2005 National Survey for nest site information. However, strengthening the detail of the habitat variables surrounding the nest site could be exercised, as at the moment it is presence only. Additional spatial information on the presence of environmental variables could be incorporated into a GIS where more detailed quantitative patterns can be analysed.

Currently, GIS maps have identified that at least three grid references NO60, TF50 and TM23 all declined to 0 2005, having previously been nested by Marsh Harriers in 1995. Future studies could explore more thoroughly the drivers for determining Marsh Harrier distribution. Adding to these datasets, could provide a better insight into what may be causing nest numbers to decline, especially as the population is increasing.

5.5 Management implications

Although globally considered ‘least concern’ (IUCN Red List 2013), in the UK the Marsh Harrier is classified under the Amber status, suggesting that its conservation status is still critical (RSPB, 2014). In contrast to what is seen to be happening in the Spanish population of Marsh Harriers, breeding success in agricultural habitats are not superior to wetland habitats in the UK. Instead, they are consistently the same across each habitat and between 1995 and 2005. However, considering the history of Marsh Harriers in the UK, having experienced extinction in 1900 for over a decade, and then near extinction in the 1970s, it suggests the population in the UK is vulnerable to declines.

In terms of management, it is clear that wetlands are the most important habitat for the majority of the population and threats of wetland drainage and degradation is still topical (Millennium Ecosystem Assessment, 2005). Managing wetland drainage and degradation may be considered a priority for not just the Marsh Harrier, but for wider environmental and ecosystem functions. In parallel, agricultural habitats may also be considered an important habitat that should be included in the management strategy of this recovering species.

43 Given that the population is still recovering, and the sustainability of the species does not appear to be equally successful in both natural wetland and agricultural habitats, a short-term management plan may be most appropriate. This could involve engaging with the agricultural community to raise awareness of conservation implications, and taking the initiative in building relationships with farmland owners to develop more considerate and sustainable long-term targets to conserve important habitats. An example may be to work with farmland owners to build on reducing their impacts on natural wetland habitats, through improving water drainage and practice of chemical use. Working on reducing the threat to natural wetland habitats and maximizing the quality of suboptimal habitats (agricultural land) will have positive outcomes for the Marsh Harrier in the long-term. Taking a precautionary approach to protect natural habitats is a sensible strategy as there are still many uncertainties associated with climate change, especially in agricultural landscapes.

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47 Appendices

Appendix 1

Extracted files from GIS calculating measurements of different habitat features in 1995 and 2005.

1995 National Survey nest locations MH_De WB_perimeter_ AL_Area_km AL_Perime Terrestrial_Lan Grid_Ref nsity km WB_Area_km2 WB_Ratio_AP 2 ter_km AL_Ratio_AP d_Area_km2 TF50 1 1353.826387 2.759626528 0.00203839 89.707415 296.171 0.30289061 100 TF73 1 23.64997765 0.108920722 0.004605532 86.42983 311.664 0.277317335 100 TG32 1 495.5319755 3.136144371 0.006328844 78.187501 391.56 0.199682044 100 TL39 1 1198.896878 2.739912458 0.002285361 94.09515 179.057 0.52550389 100 TM23 1 154.5770478 0.790356675 0.005113027 39.849261 377.29 0.105619712 70 TM33 1 124.2885695 0.375419376 0.003020546 10.820504 81.72 0.132409496 16 TM45 1 468.272162 1.345381774 0.002873077 28.65344 317.428 0.090267525 63 TM59 1 140.206295 0.458648636 0.003271241 19.02411 190.913 0.09964806 46 TQ77 1 598.7830416 4.215568318 0.007040227 50.954595 440.685 0.115625889 86 NJ25 2 85.65406829 0.717094827 0.008371988 34.003033 342.788 0.099195517 100 NO60 2 0.743763587 0.001985383 0.002669373 7.957958 39.288 0.202554419 9 SD47 2 132.2769363 0.748522257 0.005658751 20.023922 281.101 0.071233905 51 SE92 2 261.5032782 1.326146164 0.005071241 45.940443 384.96 0.119338225 72 TG04 2 184.9909351 0.849467875 0.004591943 35.65919 196.591 0.181387703 51 TL57 2 714.3081013 2.01036867 0.002814428 85.648782 323.824 0.264491767 100 TM34 2 311.6840108 1.032848581 0.003313768 44.840396 403.141 0.111227575 82 TM58 2 139.3366474 0.608235109 0.00436522 23.035386 170.79 0.134875496 33 TF52 3 545.4900205 0.836756712 0.001533954 53.871155 134.725 0.399860122 70 TF63 3 241.1641217 0.865670473 0.003589549 31.395181 200.537 0.156555553 47 TG31 3 939.8954283 5.27908415 0.005616672 65.843179 382.92 0.171950222 100 TF74 4 103.9411561 0.615212077 0.00591885 37.785905 164.979 0.229034635 53 TM49 4 1187.912695 2.244256906 0.001889244 53.584045 328.996 0.162871418 100 SK92 5 79.37039455 0.212443754 0.002676612 73.815036 508.46 0.145173732 100 TG30 6 822.9920612 2.447441401 0.002973834 70.530114 403.098 0.174970141 100 TF84 7 227.3803186 0.796251521 0.003501849 40.304764 216.406 0.186246056 61 TM46 7 338.6845592 1.31193143 0.003873609 47.299044 385.869 0.122577984 76 TG40 8 1564.890321 3.643918849 0.002328546 57.91944 418.463 0.138409943 100 TG42 8 813.7226513 1.596179045 0.001961576 32.687161 219.467 0.148938843 54 SE82 9 549.275344 1.490548167 0.002713663 64.422127 490.715 0.131282164 93 TM47 9 487.8626106 1.362775347 0.002793359 56.066319 493.288 0.113658388 93 TF62 10 535.7609006 1.12543448 0.002100628 50.907582 333.615 0.152593804 96 TR06 11 468.2877559 1.591907733 0.003399422 39.573221 366.794 0.107889499 69 TQ96 13 661.6686293 3.026098479 0.004573435 47.72184 493.26 0.096747841 91

48 2005 National Survey nest locations Gridref Density_ Terrestrial_Ar WaterB_perim WaterB_are WaterB_Ratio_ Arable_peri Arable_Area_k nests ea_km2 eter_km a_km2 AP meter_km m2 Arable_Ratio_AP TF83 9 100 35.837 0.085507 0.002385998 322 2.577716 0.008005329 SE92 7 72 113.221 0.439897 0.003885295 419 3.5625 0.008502387 TM35 1 100 160.882 0.273704 0.001701272 560 17.65 0.031517857 SE72 1 100 131.715 0.746854 0.005670227 527 20.023922 0.037996057 TG20 1 100 54.523 0.125419 0.002300295 462 18.401162 0.039829355 SE61 1 100 59.781 0.147118 0.002460949 575 24.8523 0.043221391 TG30 16 100 175.132 0.652893 0.003728005 458 20.949515 0.045741299 TF15 10 100 140.206 0.458649 0.003271251 384 17.770766 0.046278036 SE82 10 93 139.391 0.606147 0.004348538 495 23.268571 0.047007214 TF25 11 100 406.428 7.514714 0.018489656 322 17.477434 0.054277745 TF94 6 53 106.767 0.342183 0.003204951 168 10.161648 0.060486 TQ96 12 91 382.841 1.911609 0.004993219 516 31.540979 0.061125928 TG40 4 100 232.638 0.532651 0.002289613 416 27.380409 0.065818291 TF61 1 100 292.871 1.208903 0.004127766 449 34.884458 0.07769367 TF06 12 100 468.561 1.417374 0.003024951 466 36.622819 0.07858974 TG41 2 100 97.302 0.289284 0.002973053 402 32.229115 0.080171928 TQ87 4 53 147.274 0.643924 0.004372286 234 21.916629 0.093660808 TA02 2 76 255.308 0.894034 0.003501786 360 35.104033 0.097511203 TL58 4 100 287.564 1.12611 0.003916033 339 33.107836 0.097663233 TL56 2 100 180.783 0.815466 0.004510745 337 33.315107 0.098857884 NJ26 1 91 170.781 1.171673 0.006860675 457 47.834166 0.104669947 TQ86 1 90 234.816 0.599122 0.002551453 484 51.024914 0.105423376 TF84 21 61 342.093 0.711523 0.002079911 234 25.790032 0.110213812 TF34 1 100 288.06 1.392441 0.004833858 435 49.203097 0.113110568 TG31 6 100 307.058 0.948783 0.003089915 393 44.503109 0.113239463 TM46 12 76 90.009 0.50989 0.005664878 382 45.327523 0.118658437 HY32 1 83 41.791 2.762654 0.066106434 250 29.812872 0.119251488 TF07 1 100 337.63 1.590366 0.004710381 508 60.839775 0.119763337 TF93 8 100 337.166 1.307102 0.003876731 364 45.515617 0.125042904 TA04 1 100 357.218 1.100179 0.003079853 570 71.571618 0.125564242 SK92 1 100 536.096 2.233158 0.004165593 508 65.724029 0.12937801 TM24 2 97 359.292 0.935458 0.002603615 570 75.845925 0.133063026 TL78 2 100 272.575 1.138184 0.004175673 425 59.228573 0.139361348 TM39 2 100 1423.447 2.825946 0.001985284 384 53.754444 0.139985531 TQ06 1 100 557.052 0.857281 0.00153896 403 57.005541 0.141452955 TF62 11 96 594.74 4.202053 0.007065361 345 49.774706 0.14427451 TM47 19 93 564.624 1.916309 0.003393956 509 74.160189 0.145697817 TQ78 1 80 853.947 1.483062 0.001736714 380 58.483033 0.153902718 TM02 1 100 867.912 2.161115 0.002490016 563 86.998088 0.154525911 TM49 8 100 508.453 1.398565 0.002750628 370 57.450381 0.1552713 TL66 1 100 831.698 1.515239 0.001821862 475 74.450575 0.156738053 TG42 20 54 494.325 1.822696 0.003687242 242 41.246825 0.170441426 TF30 4 100 402.203 1.095538 0.002723843 253 43.563189 0.172186518 TG03 1 100 130.801 0.361447 0.002763335 435 75.608308 0.173812202 NJ93 1 100 76.777 0.372466 0.004851271 483 84.487148 0.174921631 TF74 7 53 488.259 1.386009 0.002838676 170 30.432045 0.179012029 TF16 15 100 1064.968 2.622643 0.00246265 490 89.492667 0.182638096 TM01 4 57 199.154 1.873358 0.00940658 304 55.535692 0.182683197 TF33 16 97 651.736 2.85829 0.004385656 264 48.471653 0.183604746 SE91 4 100 1037.155 2.711419 0.002614285 491 90.456238 0.184228591 TM59 2 46 980.918 3.914134 0.003990276 189 34.831784 0.184295153 TR26 6 94 430.27 1.174452 0.00272957 403 75.077029 0.186295357 TM11 3 65 149.259 0.364457 0.002441776 297 55.434952 0.18664967 TM34 1 82 684.173 1.184888 0.001731854 412 78.414691 0.19032692 TR06 42 69 883.921 2.437174 0.002757231 379 72.311294 0.190794971 TG32 1 100 388.011 0.8287 0.002135764 395 76.871443 0.194611248 TQ77 2 86 1177.249 2.480922 0.002107389 445 88.083125 0.197939607 TL28 5 100 205.159 0.847281 0.004129875 280 55.920794 0.199717121 NO22 3 87 177.098 0.514217 0.002903573 404 82.279329 0.203661705 TA12 1 58 527.348 1.454869 0.00275884 296 61.808981 0.208814125 TF82 4 100 258.379 6.046222 0.023400594 355 74.838145 0.210811676 TL29 1 100 406.832 1.322962 0.003251863 330 70.467979 0.21353933 TM58 4 33 185.508 0.784463 0.004228729 180 38.616988 0.214538822 HY22 1 64 103.023 4.291523 0.04165597 232 49.893684 0.215058983 TM45 2 63 1011.984 3.436861 0.003396161 336 74.592586 0.222001744 TQ99 1 100 749.729 3.80734 0.005078288 276 65.248027 0.236405895 TF40 2 100 133.765 0.373729 0.002793922 372 88.285263 0.237325976 TQ92 2 100 1062.552 3.039248 0.002860329 309 73.775216 0.238754744 TL44 1 100 1171.925 2.613846 0.002230387 348 85.455463 0.245561675 TL47 1 100 877.378 2.452301 0.002795034 333 82.503024 0.247756829 TF35 3 100 1157.392 3.095099 0.002674201 332 82.842367 0.249525202

49 TF63 9 47 1298.475 3.029515 0.002333133 225 58.115494 0.258291084 TL91 2 95 841.062 2.480122 0.002948798 294 76.243264 0.25933083 TF73 3 100 673.342 1.426739 0.002118892 334 86.751748 0.259735772 TL57 3 100 1133.733 3.186048 0.002810228 363 96.408556 0.265588309 TF49 1 56 172.702 1.847768 0.01069917 138 37.033428 0.268358174 NX95 1 46 87.577 0.175152 0.001999977 226 63.336453 0.280249792 TL48 3 100 710.538 2.193351 0.003086888 304 87.095305 0.286497714 NJ92 1 98 76.87 0.204895 0.002665474 283 84.236564 0.297655703 TL68 3 100 988.869 2.191082 0.002215745 299 89.24743 0.298486388 SD47 3 51 864.92 1.569613 0.001814749 281 85.504202 0.304285416 TF57 2 54 237.155 0.809004 0.003411288 135 42.37375 0.31387963 TF42 3 98 105.575 0.192496 0.00182331 279 88.680138 0.317849957 TL55 1 100 698.453 1.827037 0.002615834 263 84.25563 0.320363612 TF56 1 71 326.189 1.568216 0.004807691 203 70.993214 0.349720266 TM22 2 47 903.456 5.203325 0.005759356 177 64.313587 0.363353599 TA15 2 83 23.65 0.108921 0.004605539 234 86.89025 0.371325855 TL39 2 100 109.824 0.495235 0.004509351 197 78.199196 0.396950234 TR09 1 31 521.767 1.097833 0.002104068 119 48.50935 0.407641597 TL59 1 100 1355.044 2.568745 0.001895691 229 97.163182 0.424293371 TG04 2 51 103.787 0.212433 0.002046817 195 92.000016 0.471794954 TQ97 2 41 1226.742 2.768516 0.002256804 193 93.950955 0.486792513 TF52 2 70 29.933 0.093162 0.003112351 157 79.77125 0.508097134 TA31 2 21 103.941 0.615212 0.005918858 54 36.712415 0.679859537 TM00 1 33 867.952 2.11623 0.002438188 87 72.600941 0.834493575 TF43 1 33 79.37 0.212444 0.002676628 82 73.815037 0.900183378 TM33 1 16 1276.595 2.503485 0.001961064 85 78.462538 0.923088682 TM44 1 13 722.15 1.211451 0.001677561 39 48.670028 1.247949436 TM57 6 6 317.303 0.957059 0.003016231 35 57.350455 1.638584429

Appendix 2

Proportional distribution of Marsh Harriers across all identified habitats, between 1995 and 2005

60.0

50.0 1995

40.0 2005

30.0

20.0

10.0 Percentage of pairs (%) pairs of Percentage

0.0

Barley

Wheat

Saltings

Reedbed

Sedge bed Sedge

Rough grass Rough

Dry Reedbed Dry

Oilseed Rape Oilseed

Dry Club rush Club Dry

Wet Reedbed Wet

Tidal Reedbed Tidal

Sedgebed mix Sedgebed Wet Reedbed and Reedbed Wet Habitat Type

50 Appendix 3

Mean fledged brood size and breeding success across all habitat types, between 1995 and 2005

3.5 1995 2005

3

2.5

2

1.5

1

Mean Fledge Brood Size Brood Fledge Mean 0.5

0

Barley

Wheat

Saltings

Reedbed

Sedge bed Sedge

DryReedbed

Rough Grass Rough

Oilseed Rape Oilseed

Wet Reedbed Wet

Tidal Reedbed Tidal Rush Club Dry Sedgebed mix Sedgebed Habitat Type and Reedbed Wet The proportion of Marsh Harrier breeding pairs successful in producing ≥1 fledgling in 1995 100%

90%

80% 70% 60% 50% 40% 30% 20% producing ≥1 ≥1 fledgling producing 10%

Proportional outcome of pairs pairs of outcome Proportional 0%

Barley

Wheat Reedbed

Failed Successful

WetReedbed

Dry Reedbed Dry Oilseed Rape Oilseed Habitat Reedbed Tidal The proportion of Marsh Harrier breeding pairs successful in producing ≥1 fledgling in 2005

100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

0%

producing ≥1 fledgling ≥1 producing

Proportional outcome of pairs pairs of outcome Proportional

Barley

Wheat

Saltings

Reedbed

Sedge bed Sedge

Sedge mix Sedge

Rough grass Rough

WetReedbed

Dry Reedbed Dry

Oilseed Rape Oilseed

Wet Reed and Reed Wet

Dry Club Rush Club Dry Tidal Reedbed Tidal

Dry Oilseed Rape Oilseed Dry Failed Successful Habitat Type

51 Appendix 4

The change in number of Marsh Harrier nests in different UK grid cell references between 1995 and 2005

Number of Nests Number of Nests Number of Nests identified in National identified in National identified in National UK Grid Surveys UK Grid Surveys UK Grid Surveys Reference 1995 2005 Change Reference 1995 2005 Change Reference 1995 2005 Change HY22 1 1 TF50 1 -1 SE91 4 4

HY32 1 1 TQ78 1 1 TF30 4 4

NJ25 2 -2 TQ86 1 1 TF82 4 4

NJ26 1 1 TQ92 1 1 TG40 8 4 -4

NJ92 1 1 TQ99 1 1 TL58 4 4

NJ93 1 1 TR00 1 1 TM01 4 4

NX95 1 1 TR09 1 1 TM58 2 4 2

NO60 2 -2 TA02 2 2 TM23 1 -1

SE61 1 1 TA15 2 2 TQ87 4 4

SE72 1 1 TA31 2 2 TL28 5 5

SK92 5 1 -4 TF40 2 2 TF94 6 6

SR92 1 1 TF52 3 2 -1 TG31 3 6 3

TA04 1 1 TF57 2 2 TM57 6 6

TA12 1 1 TG04 2 2 0 TR26 6 6

TF07 1 1 TG41 2 2 SE92 2 7 5

TF34 1 1 TL39 1 2 1 TF74 4 7 3

TF43 1 1 TL56 2 2 TF93 8 8

TF49 1 1 TL78 2 2 TM49 4 8 4

TF56 1 1 TM22 2 2 TF63 3 9 6

TF61 1 1 TM24 2 2 TF83 9 9

TG03 1 1 TM39 2 2 SE82 9 10 1

TG20 1 1 TM45 1 2 1 TF15 10 10

TG32 1 1 0 TM59 1 2 1 TF25 11 11

TL29 1 1 TQ77 1 2 1 TF62 10 11 1

TL44 1 1 TQ97 2 2 TF06 12 12

TL47 1 1 NO22 3 3 TM46 7 12 5

TL55 1 1 SD47 2 3 1 TQ96 13 12 -1

TL59 1 1 TF35 3 3 TF16 15 15

TL66 1 1 TF42 3 3 TF33 16 16

TM02 1 1 TF73 1 3 2 TG30 6 16 10

TM33 1 1 0 TL48 3 3 TM47 9 19 10

TM34 2 1 -1 TL57 2 3 1 TG42 8 20 12 TM35 1 1 TL68 3 3 TF84 7 21 14

TM44 1 1 TL91 3 3 TR06 11 42 31

TQ06 1 1 TM11 3 3

52 Appendix 5

Model selection table displaying minimum AIC values for model combinations investigating the influence of nest site features within 100m on breeding success, recorded in the 2005 National Survey

Model Combinations: AIC delta Weight Breeding Success ~ All roads + Water bodies 486.4 0.00 0.184 Breeding Success ~ All roads 486.6 0.23 0.163 Breeding Success ~ All roads + Trees & Bushes 488.0 1.63 0.081 Breeding Success ~ All roads + Buildings + Water bodies 488.2 1.82 0.074 Breeding Success ~ All roads + Trees & Bushes + Water bodies 488.3 1.93 0.070 Breeding Success ~ All paths + All roads + Water bodies 488.3 1.99 0.068 Breeding Success ~ All paths + All roads 488.5 2.11 0.064 Breeding Success ~ All roads + Buildings 488.5 2.14 0.063 Breeding Success ~ All roads + Buildings + Trees & Bushes 489.9 3.50 0.032 Breeding Success ~ All paths + All roads + Trees & bushes 490.0 3.63 0.030 Breeding Success ~All roads + Buildings + Tress & Bushes + Water bodies 490.1 3.73 0.028 Breeding Success ~ All paths + All roads + Buildings + Water bodies 490.2 3.82 0.027 Breeding Success ~ All paths + All roads + Trees & Bushes + Water bodies 490.3 3.89 0.026 Breeding Success ~ All paths + All roads + Buildings 490.4 3.99 0.025 Breeding Success ~ All paths + All roads + Buildings + Trees & Bushes 491.8 5.49 0.012 Breeding Success ~ All paths + All roads + Buildings + Trees & Bushes + Water bodies 492.1 5.72 0.011 Breeding Success ~Water bodies 492.1 5.77 0.010 Null 493.4 7.07 0.005 Breeding Success ~ Buildings + Water bodies 493.8 7.41 0.005 Breeding Success ~ Trees & Bushes + Water bodies 494.0 7.64 0.004 Breeding Success ~ All paths + Water bodies 494.1 7.75 0.004 Breeding Success ~ Buildings 495.2 8.87 0.002 Breeding Success ~ All paths 495.3 8.91 0.002 Breeding Success ~ Trees & Bushes 495.4 9.00 0.002 Breeding Success ~ Buildings + Trees & Bushes + Water bodies 495.7 9.31 0.002 Breeding Success ~ All paths + Buildings + Water bodies 495.8 9.41 0.002 Breeding Success ~ All paths + Trees & Bushes + Water bodies 496.0 9.64 0.001 Breeding Success ~ All paths + Buildings 497.0 10.65 0.001 Breeding Success ~ Buildings + Trees & Bushes 497.1 10.78 0.001 Breeding Success ~ All paths + Trees & Bushes 497.3 10.89 0.001 Breeding Success ~ All paths + Buildings + Trees & Bushes + Water bodies 497.7 11.31 0.001 Breeding Success ~ All paths + Buildings + Trees & Bushes 499.0 12.63 0.000

53