1
The relation between breeding grey herons (Ardea
cinerea) and urban brown rats (Rattus norvegicus) at
Flevopark, the Netherlands
Name: Amée van Boheemen - 11903392
Supervisors: Dr. ir. E.E. (Emiel) van Loon Dr. C.E. (Caitlin) Black Dr. R.P.J. (Renske) Hoondert
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Abstract
Dutch urban areas are expected to expand in the future. Brown rats are attracted to these areas due to the presence of edible garbage. Brown rats can cause food losses, damages and possibly spread infectious diseases. Due to the knowledge gaps concerning urban brown rats, current management methods are seen as short term solutions. The aim of this study is to help fill in the ecological knowledge gaps, with a focus on the relation between grey herons and urban brown rats, to be able to implement long term (biological) management methods.
The methods during this study comprised chew cards (CCs) and an observation camera. The difference between rat responses on the CCs within a grey heron breeding area and outside this breeding area was non-significant (p = 0.5332), showing that the present brown rats did not avoid the breeding area of the grey herons. The images of the observation camera did not include any brown rat sightings and were not able to provide additional information about the rat population or predation.
The suitability of CCs for the collection of presence/ absence data on urban brown rats was also examined. The CCs were not influenced by the time they were up. However their functioning was influenced through the removal and/ or damaging of CCs by humans and dogs. Furthermore, the amount of rat responses on the CCs seemed to be influenced by the amount of shelter present at the location.
Key words: brown rat, Rattus norvegicus, grey heron, Ardea cinerea, predation, chew cards, urbanization
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Content table
Introduction ...4
Methods & Data ...5
Location of study ...5 Data collection ...6 Data analysis ...7 Results ...7 Discussion...9 Conclusion ... 10 References... 11 Acknowledgements ... 13 Appendix 1 ... 14
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Introduction
The density gradients of most Dutch cities are increasing rapidly. This is expected to continue in the future (Broitman & Koomen, 2020). Liu et al. (2003), found that the global average household size has steadily decreased between 1985-2000, especially in Europe. Together, this is resulting in a higher demand for areas to build residences (Liu et al., 2003). Even if the Dutch population would be decreasing overall, the Dutch urban areas would still expand due to the decreasing household sizes (Haase et al., 2013).
Besides humans, brown rats are also attracted to Dutch cities, mainly due to the presence of garbage which serves as their main food source (Margulis, 1977). In these urban areas, rats are seen as a nuisance due to their relation to food losses (Stenseth et al., 2003), damages and the possible spread of infectious diseases (Bonnefoy et al., 2008). The article of van Adrichem et al. (2013) shows that with an increasing number of inhabitants in urban areas, the number of reports on rat encounters will increase as well. For example, Childs et al. (1998), found that most incidents concerning rat bites occurred in city blocks with high human densities. Furthermore, the indicated climate changes show a global trend of increased warm periods and decreased cool periods (Christensen et al., 2007). This will be favourable towards infectious organisms that can be spread by rats and cause diseases (Lau et al., 2010). The threats of these diseases associated with the warming of the climate will intensify as a result of the predicted climate change (Harvell et al., 2002).
Currently, there are no overall rules or directions on how to manage urban rat populations in the Netherlands. Municipalities have the responsibility to control the rat populations in public areas and they implement different approaches to achieve this (Maas et al. 2020). The urban rat control often comprises traditional methods using poison bait and/or rat traps (Himsworth et al., 2013). However, Himsworth et al. (2013), showed that pest control professionals (PCPs) often indicated these
methods as short term solutions. Due to their ability to breed every month, brown rat populations seem to be very resilient to disturbances in their population size as long as they can find food and shelter (Emlen et al., 1948). There are multiple knowledge gaps concerning urban rats (Parsons et al., 2017). Filling these gaps by conducting ecological research on urban brown rats can support the implementation of long-term management and lower the urban rats’ potential risks.
The brown rat (Rattus norvegicus) is spread throughout the Netherlands and will therefore most likely be present at the study site; Flevopark, Amsterdam (van Wijngaarden & de Vries, 1953). The brown rat is an omnivore and is dependent on food supplies, flora, soil type and coverage for survival (van Adrichem et al., 2013). In urbanised areas, brown rats collect edible human waste and thus seem to be more present in areas with food spillage (van Adrichem et al., 2013). Brown rats live in groups and make underground burrow systems. They are very protective of their habitat and, if not necessary, they normally do not go far from their burrows. Most likely, they use the same pathways repeatedly (van Adrichem et al., 2013; Davis et al., 1948). To make the burrows, they prefer natural soils which are not too dense, but also not too airy. Besides that, the brown rat prefers water and shrubs or tall flora to be present in or near their habitat. This results in larger rat population sizes in urban areas with a higher percentage of green surface (van Adrichem et al., 2013).
Brown rats also serve as a food source for certain predators. One of these predators is the grey heron (Ardea cinerea)(van Adrichem et al., 2013; van Dijk, 1989; Thijsse, 1908). This species used to live in polder areas, but has adapted well to the urbanisation of The Netherlands (van Daalen, 1974; de Jong, 1990). Currently, the grey heron can be found in multiple different areas, as long as there are nesting trees and semi-shallow waterbodies with fish available (van Vessem & Draulans, 1986; de Jong, 1990). Although the grey herons’ main food source is fish, it will eat other animal food sources when fish is scarce or harder to find due to certain conditions, such as ice formation in winter and/or algae blooming in summer (de Jong, 1990).
5 During this study, the relation between the urban brown rats breeding grey herons is examined. These two species are both very well adapted to urbanised areas. Furthermore, both species prefer habitats with tall flora and water, and thus will most likely inhabit the same areas within Dutch cities. The grey heron is considered to be an important predator of rats (van Adrichem et al., 2013; Thijsse, 1908). However, there is no documentation of this predation happening in Dutch cities. In addition, the paper of Etezadifar et al. (2010), on the reproductive success of western reef herons showed that rats predated on the eggs of the herons. Because there is no literature found on this happening between brown rats and grey herons, during this study, the possibility of brown rat predation on the eggs of the grey heron in the Netherlands is also investigated. The results of van Vessem & Draulans (1986), covers the presence of egg predation in Belgium, mostly by corvids, but does not elaborate on this. Since there is an increased interest in biological pest management, including avian predation (Labuschagne et al., 2016), information on the predative relation between grey herons and brown rats can possibly help with the implementation of long term biological management solutions. As mentioned before, there is a lack of information on the ecology of urban rats in The Netherlands. The aim of this study is to help fill the knowledge gap on the urban brown rat ecology, in particular the relation between the brown rat and the grey heron. This will be helpful in order to map out urban rat ecology and behaviour, and to eventually implement urban rat population management that will reduce the nuisances and risks caused by urban brown rats. This aim will be supported by the following main research question: What is the relation between breeding grey herons and urban brown rats at Flevopark, an urban green area in Amsterdam?
Furthermore, the used methods during this study will be examined. This will be supported by the following sub questions:
Are chew cards a suitable method to collect presence/ absence data of brown rats at Flevopark? And:
Can observation cameras be used as a method to obtain information about urban rat populations?
Methods & Data
Location of study
This study was executed in Flevopark, located in the eastern part of Amsterdam (see Figure 1). This area is the habitat of a colony of grey herons, which have built a group of nests in the forest area near the big green meadow (van der Sijde, 2015) (see Figure 2). This breeding site is secluded by a paved path. The large waterbody Nieuwe Diep and the fact that Flevopark is a large urban green area, also create suitable living conditions for the brown rat (van der Sijde, 2015; van Adrichem et al., 2013).
Figure 1: Map of Amsterdam with an enlarged map of the Flevopark area. The park itself is outlined in pink.
6 Data collection
The fieldwork to collect data comprised 42 days between the 24th of March and the 4th of May. This
period most likely covered the breeding season of the grey herons at Flevopark since van Vessem & Draulans (1986) found the breeding season in Belgium to be from the beginning of February until the start of June, with most active nests at the turning point from March to April. The fieldwork was conducted during the breeding season to study the possibility of predation both ways.
Chew cards
For this first method, chew cards (CCs) were placed within the area in Flevopark where grey herons breed, and within the surroundings of this breeding area (see figure 2). These cards were used to examine the differences in the amount of rat presence inside and outside the grey heron breeding area. The choice for CCs was based on the low pricing in combination with its sensitivity to the detection of rats (Sweetapple & Nugent, 2011). Thereby, the dental marks are not difficult to interpret with minimal prior knowledge and the lure encourages biting responses (Sweetapple & Nugent, 2011). During this study, the suitability of CCs to retrieve presence/absence data on brown rats was also examined. During the first round, 15 CCs were adhered in total. All 15 CCs were situated within the breeding area and served as a try out. All 15 CCs from the first round were removed after 5 days. Before placement of the second round of CCs, the grey heron nests were observed to check on activity. Afterwards, there was a CC attached to every tree
containing an active herons’ nest. Outside of the breeding area, CCs were placed in different locations which provided a somewhat sheltered tree for attachment, to minimize the
opportunity of damages by larger organisms, possibly destroying previous bitemarks and/ or influencing the functioning of the CCs. During the second round, 20 CCs were adhered.
In total there were 6 observation rounds. Burge et al. (2017), suggest in their paper to use a time span of 5 nights for the detection of moderate pest densities. Therefore, each round comprised 5-6 days, with the exception of round 4, due to the delay of materials. After each round, the CCs were replaced or removed. During the observation period, several CCs were removed when certain locations turned out to encounter many disturbances, and several new CCs were added when additional active nests were found. Per round, the CCs were checked on bitemarks minimal 4 days out of the 5-6 days, except for round 4, which had 7 observation days out of the 12 days. The collected bitemarks were analysed according to Sweetapple & Nugent (n.d.).
The CCs were cut out of thick corflute with the following dimensions: 180 x 90 mm. The hollow parts of the corflute were situated horizontally. To attract the rats to bite the CCs, peanut butter was used as lure inside the hollow parts of the corflute on opposite sides (Sweetapple & Nugent, 2011) (see
Figure 3). The CCs were attached to trees at a height between 20-30 cm above the ground, using nails (Burge et al., 2017; Nottingham et al., 2021; Sweetapple & Nugent, 2011).
Unfortunately, the CCs did not give a clear indication on the exact amount of rats present due to the possibility of the same rat leaving multiple dental marks on one CC (Feng & Himsworth, 2014). Therefore, the results of the CCs were noted as presence/ absence (presence = 1, absence = 0).
Figure 2: A map of the area where fieldwork was conducted. The first area is the breeding site of the grey herons and is enclosed by a paved road, indicated with an orange line. The second area comprises everywhere outside of the breeding site. The numbers indicate the locations of the individual CCs, starting from round 2. The yellow dot indicates the location of the observation camera.
Figure 3: A CC mounted on a tree. The areas which contain peanut butter are outlined in red.
7 Observation camera
For the second method, an observation camera was placed inside the breeding area of the grey herons (see Figure 2). Due to the herons’ nests being too high up in the trees, it was not possible to aim the camera at the inside of a nest to observe potential rat activity. Therefore, the camera was attached to a tree inside the breeding area of the grey herons, overlooking the ground. This was used as an extra method to examine the presence of rats in this area, and to possibly see the amount of rats present, which is not possible by only using the CCs.
The used camera was a Spypoint Force-Dark trail camera. To prevent the camera from being stolen or disturbed, it was placed in a Spypoint Security Box SB-200. It was attached to a tree at around 10 centimetres above the ground, using a Masterlock Python cable. The camera was equipped with an SD card with 32 GB and lithium AA batteries. The batteries were not changed throughout the study. The SD cards were changed every other day. On the camera, the multi-shot option was installed, in combination with the no-glow setting. This resulted in the camera taking up to 6 shots per detection of motion without a flash. With the camera taking multiple shots per detection, the chances on collecting usable photo’s was higher.
Data analysis Chew cards
For the first method, a chi square test was conducted to test on differences in the amount of CCs chewed by rats in the grey heron breeding area and outside this breeding area. The presence/ absence data of the CCs bitten by rats was taken as the dependent variable and the area was taken as the independent variable.
To examine the suitability of CCs to retrieve presence/ absence data on brown rat, a general linear model (glm) was used to test the dependency of the amount of CCs bitten by brown rats over time. The presence/ absence data of the CCs bitten by rats was taken as the dependent variable and the amount of cumulative days a location contained a CC was taken as the independent variable.
Both tests were conducted using Rstudio (version 1.1.419), an open source tool for the programming language R (Allaire, 2012).
Observation camera
The organisms visible on the collected photos were annotated using the computer program Agouti. This shows the organism(s) visible and the quantity.
Results
Chew cards
Dental marks on the CCs were examined following the method of Sweetapple & Nugent (n.d.). Rat dental marks were
recognised by the amount of card that was chewed away and the jagged edges (Sweetapple & Nugent, 2011) (see Figure 4). The amount of positive responses as well as the amount of negative responses within the breeding area and outside of the breeding area can be seen in Table 1.
Figure 4: A CC mounted to a tree. The area outlined in red shows the dental mark made by a rat/rats.
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No rat dental marks Rat dental marks
Inside breeding area 358 77
Outside breeding area 146 37
Figure 5 shows the boxplot using the proportional data of Table 1. The boxes do overlap and the medians of each box does not lie outside the other box. Therefore it is not expected to see a significant difference in rat response between the two areas. The chi square test confirmed this by showing a non-significant difference (p = 0.5332) in the amount of rat responses between the herons’ breeding area and outside the breeding area. This means that the brown rats do not avoid the breeding area of the grey herons.
To examine the suitability of CCs for retrieving presence/ absence data, a general linear model (glm) was used. For all 35 days, no significant result was found (see Appendix 1). This means that the amount of chew cards bitten by rats were not influenced by time.
Observation camera
The camera provided 631 observations, before it broke on the 27th observation day. The most
frequently observed organisms were humans (37 sightings), dogs (8 sightings) and common
blackbirds (7 sightings). Table 2 shows the complete list of observed organisms and the quantities of the observations. No rat has been captured by the camera during the observation period, resulting in no additional information about the rats present.
Table 1: A summary of the presence/ absence data in the two observed areas.
Figure 5: A boxplot showing the proportional differences between the heron breeding area and outside the breeding area. The boxes show the interquartile rages (IQR). The dark lines inside the boxes show the medians. The wiskers at the top and the bottom show the highest and lowest scores present.
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Number of individuals
1 2 3 4 5 6 Total
Dog
(Canis lupus familiaris)
8 8
Human
(Homo sapiens)
10 2 1 1 2 1 37
Common wood pigeon
(Clumba palumbus)
3 3
Eurasian blue tit
(Cyanistes caeruleus) 3 3 Eurasian magpie (Pica pica) 1 1 Common blackbird (Turdus merula) 7 7
Discussion
During this study, CCs and an observation camera were used to try and answer the following research questions: What is the relation between breeding grey herons and urban brown rats at Flevopark, an urban green area in Amsterdam?, Are chew cards a suitable method to use for the collection of presence/ absence data of brown rats at Flevopark? and Can observation cameras be used as a method to obtain information about urban rat populations?
The chi squared test, which was performed using the data from the CCs, showed a non-significant difference in rat responses between the grey herons’ breeding area and outside the breeding area. This shows that the present urban brown rats do not avoid this breeding area. For further research, it would be interesting to see if the brown rats avoid other areas where grey herons can be found, especially their feeding areas.
To test if the CCs were a suitable method for acquiring data, a glm was used. This did not reveal any significant outcomes, showing that the rat responses were not depending on the time. This suggest that the CCs are a stable method. However, during the fieldwork conducted for this study, the usage of CCs also showed some disadvantages. The areas used for this study, especially the breeding site, are popular among park visitors. People walk through the breeding site on a daily basis and children sometimes play there. Although the CCs were located as much out of sight as possible, there were multiple occasions where they were removed from the trees. Furthermore, the breeding site is located next to a field popular among dog owners. Therefore, a lot of humans and dogs are attracted to this part of Flevopark. During the fieldwork, dogs were allowed to walk through the park without a leash, resulting in the dogs not only being present on the field, but also roaming through the
vegetation within the breeding site. This resulted in CCs with dental marks belonging to dogs and sometimes damaged and/or removed CCs.
While checking the CCs, it was remarkable that the CCs which were somewhat sheltered by plants were the ones that had the most rat responses. Halfway through the fieldwork, extra CCs were placed. Some of these were located somewhere sheltered and were bitten by rats within two days. Afterwards, the CCs close to that location, but without the shelter, were bitten by brown rats as well. For further research, it would be interesting to look further into the placement of CCs and if the amount of shelter has a significance influence on the rat responses. It can also be interesting to see if the rats get used to the cards and memorizing its connection with peanut butter. In addition to this, the influence of the distance between the CCs with and without shelter on the rat responses can be examined.
Table 2: The different organisms identified on the images taken by the observation cameras, and their quantities.
10 To improve similar studies in the future, it is recommended to use a larger sample size. Within the breeding site, the CCs were attached to all the trees with herons’ nests in them. However, because this breeding area was limited, there were only 22 CCs placed within the breeding area. The area surrounding the breeding site, used as the second area within this study, was also limited. Only 7 CCs were located here. Johanson & Brooks (2010) discuss a proper sample size to conduct statistical tests on to be at least 30. Therefore, it should have been better to have a sample size of minimal 30 CCs within the breeding site and 30 CCs surrounding the breeding site.
Furthermore, a similar experiment has not been conducted before, therefore there were no
guidelines to follow. The conducted fieldwork was based on trial and error, resulting diverse amounts of CCs throughout the fieldwork. To reduce uncertainties, the amount of CCs should be kept
consistent, unless the influence of density of CCs is being examined.
Etezadifar et al. (2010), found egg shells with rat dental marks on them while they were looking into the breeding success of western reef herons. This study included a different heron species, in a different habitat type, with different rat species present. Since there was no literature to be found on brown rats predating on the eggs of grey herons, it was included within this research. However, it could not be included as was anticipated. The observation camera which was used during the fieldwork was supposed to be aimed at a grey herons’ nest. Unfortunately all nests were too high up in the trees to be reached. Therefore the camera was aimed at the ground underneath one of the nests to look for behaviour that suggested interest in the nests. An advantage of this location would be to get more insight in the amount of rats present.
The images from the observation camera did not capture any brown rats, probably due to its location. It was attached to a tree without much shelter and close to one of the paths crossing the breeding site, resulting in a lot of humans and dogs passing by. This was supported by the CCs located near the camera, showing no signs of rat presence.
The camera also broke on the 27th day of the fieldwork. This was likely due to water damage. An
improvement during further research would be to place the camera in a more sheltered and more quiet location, preferably after retrieving presence/ absence data to select a location with a high chance on rat sightings.
To further examine the extent of the predation on brown rats by grey herons and the possibility of brown rats predating on grey herons’ eggs, a camera could be located aiming at a grey herons’ nest. Furthermore, evidence, in the form of herons’ egg shells and disgorged pellets, could be collected from the ground. The egg shells could be checked on rat dental marks (Etezadifar et al., 2010), whereas the pellets could be checked on rat bones (de Jong, 1990; Thijsse, 1927).
Conclusion
The brown rats at Flevopark do not avoid the breeding area of the grey herons. The chew cards used to study this were not influenced by the time they were up. However their functioning was
influenced through the removal and/ or damaging of CCs by humans and dogs. Furthermore, the amount of rat responses on the CCs seemed to be influenced by the amount of shelter present at the location.
The observation camera did not capture any brown rats, probably due to its placement. The camera was located close to a path and had not much shelter. The CCs surrounding the camera also showed no rat responses. As a result of the absence of rat footage, no additional information about the rat population or predation was provided.
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Acknowledgements
I want to thank Dr. C.E. (Caitlin) Black for arranging all the equipment necessary for the fieldwork, and for the help and guidance during the execution of the fieldwork and writing of this paper. I want to thanks Dr. R.P.J. (Renske) Hoondert for help during the writing process and statistical analysis.
I also want to thank my team members Mathijs Blom, Ilja van Vuuren, Sacha Rem, Antonia van der Grinten and Lune Walder for the teamwork.
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Appendix 1
Summary of the glm:
Coefficients:
Estimate Std. Error z value Pr(>|z|) (Intercept) -1.757e+01 6.255e+02 -0.028 0.978 CC_days_cumulative2 1.582e+01 6.255e+02 0.025 0.980 CC_days_cumulative3 1.687e+01 6.255e+02 0.027 0.978 CC_days_cumulative4 1.577e+01 6.255e+02 0.025 0.980 CC_days_cumulative5 1.393e+01 6.255e+02 0.022 0.982 CC_days_cumulative6 1.462e+01 6.255e+02 0.023 0.981 CC_days_cumulative7 1.601e+01 6.255e+02 0.026 0.980 CC_days_cumulative8 1.435e+01 6.255e+02 0.023 0.982 CC_days_cumulative9 1.701e+01 6.255e+02 0.027 0.978 CC_days_cumulative10 -1.456e-09 1.102e+03 0.000 1.000 CC_days_cumulative11 1.601e+01 6.255e+02 0.026 0.980 CC_days_cumulative12 1.624e+01 6.255e+02 0.026 0.979 CC_days_cumulative13 1.468e+01 6.255e+02 0.023 0.981 CC_days_cumulative14 1.623e+01 6.255e+02 0.026 0.979 CC_days_cumulative15 1.618e+01 6.255e+02 0.026 0.979 CC_days_cumulative16 1.610e+01 6.255e+02 0.026 0.979 CC_days_cumulative17 3.513e+01 2.368e+03 0.015 0.988 CC_days_cumulative18 1.549e+01 6.255e+02 0.025 0.980 CC_days_cumulative19 1.738e+01 6.255e+02 0.028 0.978 CC_days_cumulative20 1.549e+01 6.255e+02 0.025 0.980 CC_days_cumulative21 1.723e+01 6.255e+02 0.028 0.978 CC_days_cumulative22 1.654e+01 6.255e+02 0.026 0.979 CC_days_cumulative23 1.665e+01 6.255e+02 0.027 0.979 CC_days_cumulative24 1.676e+01 6.255e+02 0.027 0.979 CC_days_cumulative25 1.606e+01 6.255e+02 0.026 0.980 CC_days_cumulative26 1.631e+01 6.255e+02 0.026 0.979 CC_days_cumulative27 1.757e+01 6.255e+02 0.028 0.978 CC_days_cumulative28 1.596e+01 6.255e+02 0.026 0.980 CC_days_cumulative29 1.734e+01 6.255e+02 0.028 0.978 CC_days_cumulative30 1.606e+01 6.255e+02 0.026 0.980 CC_days_cumulative31 1.706e+01 6.255e+02 0.027 0.978 CC_days_cumulative32 1.618e+01 6.255e+02 0.026 0.979 CC_days_cumulative33 1.661e+01 6.255e+02 0.027 0.979 CC_days_cumulative34 1.661e+01 6.255e+02 0.027 0.979 CC_days_cumulative35 1.687e+01 6.255e+02 0.027 0.978
