The bottlenose dolphins (Tusiops truncatus) of Cardigan Bay, Wales: safe from harm?
By
Heather Payton University of Glamorgan
In association with the Cardigan Bay Marine Wildlife Centre
May 2011
This work was carried out in part fulfilment of the requirements for the award of BSc (Hons) Coastal Zone and Marine Environment Studies.
Acknowledgments
My sincere thanks first of all to Steve Hartley and Sarah Perry of the Cardigan Bay Marine Wildlife Centre for help, support and most of all, use of the photo ID data without which this wouldn’t have been possible.
Thanks also to Kate Redman, photo ID supremo, and to all the other CBMWC volunteers who spent many hours perched atop Sulaire looking for dolphins.
At Pembrokeshire College my thanks go to my supervisors Powell Strong and Dr Steve Morris for their patience, help, advice and encouragement.
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 2
CONTENTS
ABSTRACT...... Page 5 1. INTRODUCTION 1.1. Background...... Page 7 1.2. Population...... Page 8 1.3. Threats...... Page 9 1.4. Network analysis...... Page 11 1.5. What can network analysis contribute?...... Page 12 2. STUDY AREA...... Page 14 3. AIMS...... Page 14 4. OBJECTIVES...... Page 14 5. METHODS 5.1. Data collection...... Page 15 5.2. Identification from photographs...... Page 16 5.3. Data analysis 5.3.1. Selection criteria...... Page 17 5.3.2. Association index...... Page 17 5.3.3. Defining preferred relationships...... Page 18 5.3.4. Social analysis...... Page 19 5.3.5. Visual representation...... Page 20 6. RESULTS 6.1. Associations...... Page 20 6.2. Filtering...... Page 21 6.3. Network analysis...... Page 24 6.3.1. Random attacks...... Page 25 6.3.2. Targeted attacks 6.3.2.1. Degree...... Page 27 6.3.2.2. Betweenness...... Page 29 7. DISCUSSION 7.1. Network properties...... Page 31 7.2. Network measures...... Page 33 7.3. Are targeted attacks so unlikely?...... Page 36 7.4. Why does network cohesiveness matter?...... Page 37 7.5. How real are the threats?...... Page 38 7.6. Implications for management and conservation...... Page 41 8. CONCLUSION...... Page 42 8.1. So are they safe from harm?...... Page 42 8.2. Management recommendations...... Page 44
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LIST OF FIGURES
Figure 1: Animal 004 (Connie) & calf...... Page 7 Figure 2: ‘Sue’ (021): head showing white mark over right eye...... Page 13 Figure 3: Animal 100 (Topnotch)...... Page 16 Figure 4: Preferred companionships using a HWI cutoff of 0.15..... Page 22 Figure 5: Preferred companionships as defined by permutation tests...... Page 23 Figure 6: Typical random network (10 were constructed)...... Page 24 Figure 7: Average shortest path length under different scenarios for the random and dolphin networks...... Page 25 Figure 8:Clustering co-efficients under different scenarios for the random and dolphin networks...... Page 25 Figure 9: Dolphin network after random removal of 20% of Individuals...... Page 26 Figure 10: Dolphin network with 30% of individuals removed randomly...... Page 27 Figure 11: Animal 067 – highest degree...... Page 27 Figure 12: Targeted dolphin network with 20% removed (degree).. Page 28 Figure 13: Targeted dolphin network with 30% removed (degree).. Page 28 Figure 14: Animal 104, highest betweenness...... Page 29 Figure 15: Targeted dolphin network with 20% removed (betweenness)...... Page 29 Figure 16: Targeted dolphin network with 30% removed (betweenness)...... Page 30 Figure 17: Proportion of nodes left in the largest component of the network as nodes are removed...... Page 30
APPENDICES (supplied in electronic form) Association indices Descriptive statistics for random and dolphin networks Results of UCINET tests on dolphin and random networks Dolphin network targeted by betweenness and degree
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THE BOTTLENOSE DOLPHINS (Tursiops truncatus) OF CARDIGAN BAY: SAFE FROM HARM?
ABSTRACT
Social animals like Bottlenose Dolphins live their lives in complex communities in which communication, collaboration and competition are the norm. They benefit from the ability to recognise, pass on information and learn from others, and they take on different roles within the group. It is important therefore for the future wellbeing of the network that its social structure and cohesiveness are maintained.
More than 300 well marked animals from the Cardigan Bay population have been photographed and positively identified and it’s thought they may be the biggest resident or semi resident population in United Kingdom waters. At present they face no major identified threat though others of their species elsewhere in the world do. Attacks from the usual predators, killer whales and sharks, are unknown in Cardigan Bay - making them unusual in global terms.
But that’s not to say that potential threats, mostly from human influences, don’t abound. And disease has all but wiped out dolphin populations elsewhere in the recent past.
This study uses network analysis techniques, developed for the study of human populations, to identify animals with large numbers of affiliations or which play the role of ‘brokers’ in their society, acting as links between sub communities.
The study then simulates attacks on the population as might be caused by disease or habitat degradation, removing animals first at random and then by targeting the attacks on the ‘brokers’ and the animals with large numbers of associates.
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In fact the network maintains its cohesiveness relatively well even when thirty percent of the individuals are removed at random, simulating a truly catastrophic attack. But it’s a different story when the attacks are targeted against the individuals who play important roles. The networks fragment rapidly, which in real life would deprive the animals of the advantages that enable them to live in a challenging environment.
The results would therefore suggest that targeted attacks on individuals in dolphin networks can have a disproportionately large effect on the community as a whole, and that an attack capable of removing any animals should be taken seriously.
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THE BOTTLENOSE DOLPHINS (Tursiops truncatus) OF CARDIGAN
BAY, WALES: SAFE FROM HARM?
Figure 1: Animal 004 (Connie) &
calf (CBMWC)
1. INTRODUCTION
1.1. Background.
The Bottlenose Dolphins (Tursiops truncatus) of Cardigan Bay are described variously as a resident (DECC) or semi-resident population (Evans et al 2003), one of only two in UK waters (the other being Moray Firth in Scotland).
Although they’re not thought to be under any immediate threat, others of their species elsewhere in the world are (Reeves et al 2002).
This study will attempt to show what would happen were the population to suffer catastrophic attack, either through disease or other factors. Because
Bottlenose Dolphins are social animals for whom communication, collaboration and competition play an important part, the cohesion of their social networks is paramount. If the network were to fragment, breaking up into constituent parts, all this would be lost and the population would be less successful (Lusseau 2003).
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There is evidence that cohesion depends on certain individuals with specific roles within the community who ‘glue’ the network together, and this report will also attempt to identify these animals, using network analysis techniques.
1.2. Population
Cardigan Bay’s dolphins are frequently sighted during the summer months but are relatively uncommon during the winter, with the exception of the area near
New Quay’s fish processing factory where a plentiful supply of food is available. The trip boats used as platforms of opportunity for surveys do not operate during the winter, but a small number of winter aerial surveys in 2007-
08 confirmed the presence of animals offshore (Pesante et al 2008a).
It is now clear however that at least some of the animals range further afield than Cardigan Bay. Photo-identification off the coast of Anglesey in 2007-08 found matches with at least 75 individuals photographed previously in Cardigan
Bay. Large groups of Bottlenose Dolphins have also been sighted near
Liverpool Bay (Pesante et al 2008).
One of the animals identified by the Cardigan Bay Marine Wildlife Centre
(CBMWC) in New Quay, number 100 (Topnotch) was photographed in
September 2009 off Mwnt, south of New Quay. Forty-eight hours later the same animal was identified off Point Lynus on the north coast of Anglesey, a distance of 175 kilometres (CBMWC).
Photo-ID surveys by CBMWC have identified more than 300 individuals (pers comm. Redman), but 78 of these have been seen only once or twice and others have not been seen for a couple of years (CBMWC 2010). Taken together with
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 8 data from Seawatch Foundation, this would suggest that only part of the population shows a large measure of site fidelity and it may well be described as a combination of transient animals, visitors and residents (Pesante et al
2008a).
Mark-recapture analysis of independently-gathered data, however, has indicated that up to 379 animals may have used the Bay over the period 2001-07. This would suggest that Cardigan Bay has the largest coastal Bottlenose Dolphin population in the British Isles (Pesante et al 2008a).
1.3.Threats.
There is no suggestion that the Cardigan Bay dolphins currently face a threat to their survival – in fact their numbers appear to be increasing (Pesante 2008) and in Cardigan Bay they are free from major predators. But there is also no shortage of future challenges, especially from anthropogenic factors.
The bay contains two Special Areas of Conservation (SAC) designated under the EU’s Habitats Directive, the Cardigan Bay and Pen Llyn a’r Sarnau SACs, and Bottlenose Dolphins are a feature of both (CCC 2007) with the responsibilities that entails. They are also a protected species in their own right.
Confirmation that the animals range so far afield has an impact on the way the population is managed by conservation authorities. For example, the highly industrialised nature of the Liverpool Bay area and the higher volume of recreational traffic off the North Wales coast could expose animals to pollution and interaction with boats. This would suggest that anthropogenic factors outside the SAC may affect the Cardigan Bay population (Pesante et al 2008).
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It is this type of information that must be taken into account in formulating future management strategies.
Their wide ranging activities may explain why unexpectedly high levels of organochlorines have been found in some Cardigan Bay animals, but heavy metal contamination apparently from abandoned mid-Wales mines has also been found. Agricultural run-off may also enter the bay from rivers running through a largely agricultural hinterland (Morris et al 1989).
Energy exploration in Cardigan Bay has in the past been at low level and recently the UK government assessment declined to support the granting of oil and gas exploration licences within Cardigan Bay. But it added that the matter might be revisited should more data become available (DECC 2007). Energy exploration (and perhaps more to the point in the current climate, plans for renewables) would involve seismic surveying, explosives, drilling, the laying of cables, sonar, pile driving and higher levels of boat traffic, all of which can cause physical problems for cetaceans (CCC 2007, Bailey et al 2010).
The animals are prone to disturbance by boats (Constantine et al 2004, Lusseau
2003) which, as well as the more obvious problems of collision, may incur other costs to the animals such as the extra energy expenditure involved in avoidance, or being driven away from foraging areas (Lusseau 2003, Stockin et al 2008).
Fishing methods, too, can cause problems. Scallop dredging for example disturbs the sea bed and can impact on species further down the food web (CCC et al 2007). Direct competition from fisheries may also deplete prey and by- catch caused by entanglement in nets can also pose a threat (CCC et al 2007).
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Food availability may also be affected by climate change, a factor whose future effects on cetacean populations is still largely unknown (Lister 2008).
1.4. Network analysis.
Network analysis techniques were first developed in the physical sciences and later taken up by the social sciences, first in man, and as recently as 2003 in non-human vertebrates. The technique sees a social system holistically as a network of nodes (individuals, in this case dolphins) and edges (the links between them), rather than as a series of individuals. It puts great store on graphical display of the connections (Whitehead 2008).
Network theory is also used for non living systems such as the world wide web.
The development of network analysis software such as UCINET (Borgatti et al
1999) has made it possible to identify features of the network such as how compact it is – a network in which all members could be reached in just a few steps, for example, would facilitate the spread of information – and features of individual members, such as their importance and the role they play in the community.
This is valuable in the case of long-lived species, such as Bottlenose Dolphins, which benefit from the transfer of information. This in turn depends on the social structure of the population (King 1991, McComb et al 2001). Structure also influences the spread of disease (Corner et al 2003), genetic makeup
(Pusey & Wolf 1996) and the way a population exploits its environment
(Hoelzel 1993, Connor et al 1998), making it a fundamental part of its biology.
Identifying preferred associations is thus an important starting point to defining
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 11 social structure, the relationship between pairs being defined by the amount of time they spend together, using an association index (Whitehead 1999 & 2008).
As with conventional social analysis, this plainly poses problems; animals won’t fill in forms or answer questions, so information-gathering relies on direct observation. One other weakness of the approach is that animals may be seen together purely because they range over the same area rather than because they prefer each other’s company (Lusseau 2005).
1.5. What can network analysis contribute?
Network analysis can give unparalleled insights into the way animal populations work; understanding this can help to define and target conservation strategies.
An example is the spread of disease. Many dolphin populations, including the
Cardigan Bay animals, are prone to various skin lesions (Magileviciute 2006) which may be due to immunosuppression caused by a high body load of PCBs
(Moeller 2003). The affected animals can be identified and to some extent quantified by photo identification, but network analysis can also track those likely to have numerous contacts with other animals to make a judgement about the speed of spread and severity of the disease.
Magileviciute (2006) identified four separate components in the Cardigan Bay population and found that certain groupings had a statistically higher prevalence of certain types of lesion, some of which had been linked with immunosuppressive pollution. She tracked the links between the animals, as shown by network analysis, to an individual with one of the highest degrees of
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 12 centrality within the component – who could have been responsible for spreading the disease.
Network analysis has been applied to the spread of HIV in humans
(Rothenburg 1995); network structure and the position in the network of individuals has been found to play an important part in the way disease
progresses through a population
(Newman 2002b).
Network analysis combined with
photo ID can also make it possible
to follow an animal over the course
Figure 2: ‘Sue’ (021): head showing white of its life and identify the mark over right eye. (CBMWC) individual’s position and influence in the population. An example in Cardigan Bay is ‘Sue’ (021), a female seen regularly for more than 25 years and identified by a white patch over one eye
(pers.comm.Steve Hartley). Sue was shown to be in the top ten of animals who act as ‘brokers’, forging links between sub-communities. This would suggest that she is an experienced animal the others would do well to follow. Her disappearance from the area, if it were to happen, might be seen as a warning for its possible effects on network cohesion.
Network analysis can also facilitate the visualisation of a network via software such as NetDraw, illustrating as well as measuring the effects of various events such as attack by disease, predation or changes in prey availability.
All in all it can serve as an early warning to conservationists about future events, and contribute to our knowledge of their social interactions.
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2.0. STUDY AREA
Cardigan Bay is the largest bay in the British Isles, with land on three sides and the Irish Sea to the west. The distance from St David’s Head in the south to the
Lleyn Peninsula and Bardsey Island to the north is approximately 100km and the area is 5,500 km². It is shallow; the depth does not exceed 50 metres, with an average depth of 40 metres (Evans 1995a).
3.0. AIMS:
The aim of this study was to subject photographic identification data gathered since 2005 to social network analysis.
4.0. OBJECTIVES:
To construct a matrix of association indices showing the strength of dyadic
relationships
To investigate network measures such as average shortest path length,
clustering co-efficient and betweenness, with a view to establishing network
and individual features.
To then remove individuals to simulate first a random then a targeted attack
on the network which would take out those with links to many others, with a
view to determining whether it retains its cohesion or fragments.
To illustrate the different roles played by individuals in a society.
To determine what threats the animals face in real life and if they are in fact
‘safe from harm’.
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5.0. METHODS
5.1. Data collection
Data for 2005 to 2009 were collected by volunteers from the Cardigan Bay
Marine Wildlife Centre (CBMWC) at New Quay, Ceredigion from MV Sulaire, a 10m vessel deployed as a ‘platform of opportunity’. Sulaire operates as a dolphin-spotting trip boat for the paying public from April to October each year, carrying an observer on each trip. The demands of this double identity could possibly limit spatial and temporal coverage and compromise the data if all members of a group are not photographed, but it is a cost effective method frequently employed by small research organisations (Kiszka et al 2007).
Observers were positioned approximately 3m above sea level and the possible angle of view was 360 degrees. The vessel normally followed a transect to the south west, close to the coast on the outbound leg, further out to sea for the return or vice versa. The average speed was approximately eight knots.
When animals were encountered, the vessel was stopped and if conditions were suitable, attempts were made to photograph the animals using a Canon D60 digital camera with a 75-300mm lens, with special attention to their dorsal fins, left and right sides, or to markings on their bodies. Efforts continued until either all members of the group had been photographed or contact was lost.
Volunteers were equipped with GPS, binoculars, 2-way radio and sheets to record encounters with Harbour Porpoises (Phocoena phocoena) and Atlantic
Grey Seals (Halichoerus grypus) as well as with Bottlenose Dolphins. Details of weather, sea state, position, boat speed and direction were recorded at least
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 15 every ten minutes, and when photo ID was carried out, a separate sheet was completed with details of the behaviour and composition of each group (adults, juveniles and calves), encounter number and duration, and position.
5.2. Identification from photographs.
The digital photographs were downloaded by CBMWC researchers, examined on screen, and classified according to the number of nicks, tooth rakes or scars on an animal’s dorsal fin or marks on its body. Using as many such features as possible is reckoned to aid accurate identification (Wursig & Jefferson 1990).
Attempts were then made by an experienced operator to match the image with photographs already in the catalogue. Once a match was made, the images were analysed independently by a second observer to avoid bias and reduce the possibility of mis-identification. When possible, animals were also classified according to gender. Bottlenose Dolphins do not show very obvious sexual dimorphism (Reeves et al 2002) so identification had to rely on sight of the animal’s genitals or the level of scarring on its dorsal fin. Tolley et al (1995) found that males had more scars and nicks from encounters with other males, so animals with heavily-marked fins were classified as ‘probable males’. Animals seen regularly in close proximity to calves were classified as females.
Occasionally, a heavily-marked animal was seen
with calves, as with one Cardigan Bay animal,
100 (Topnotch’), mentioned earlier, in which case
it was assumed to be female, albeit a particularly
Figure 3: Animal 100 feisty one. (Topnotch) (CBMWC)
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5.3. Data analysis.
5.3.1. Selection criteria.
CBMWC’s photo identification catalogue contains details of more than 300 positively-identified individuals but, of these, 78 have been recorded only once or twice, and others have not been seen for some years. Others were calves which tend to stay with their mothers for several years (Reeves et al 2002) so do not add a lot to the data. Accordingly, only adult animals which had been sighted five or more times and had been recorded during the previous two years were included. This figure was felt appropriate for the limitations of the dataset and also makes it possible to compare the results with those from other studies
(Lusseau 2003, Lott 2004).
All animals seen within the same group were considered to be associated, a strategy known as the ‘gambit of the group’ and used in other studies
(Whitehead 2008).
5.3.2. Association index.
The more often a pair (dyad) of dolphins are seen together in the same group, the more closely they’re deemed to be associated. For this study, the Half
Weight Index was chosen as the most appropriate measure of association. It is the most commonly-used measure (so easy to compare with other studies) and reckoned to correct shortcomings in sampling techniques (Whitehead 2008).
The Half Weight Index estimates the likelihood that two animals will be seen together, compared with the likelihood of seeing either of the pair when encountering a school:
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HWI: ______X______
X + 0.5 (Ya + Yb) where: X = the number of encounters that included both dolphins a & b
Ya = the number of encounters that included dolphin a but not b
Yb = the number of encounters that included dolphin b but not a
The Half Weight indices range from 0.00 for a pair of dolphins never seen together, to 1.00 for two always in each other’s company. They were calculated using SOCPROG 1.3, a program developed for MATLAB (version 5.1) developed by Whitehead (1999a).
5.3.3. Defining preferred relationships.
The significance of the association indices was tested by randomly permuting the data, to determine whether the associations from the real data were significantly different from those of the permuted (random) data. Preferred associations (i.e. non random associations) will have a higher Standard
Deviation than that for the random data (Whitehead 1999). The permutation tests show which dyad Coefficients of Association are significantly higher or lower than random values. After each permutation, the HWI for each pair was calculated and compared with the HWI from 20,000 permutations performed. If more than 95% of the expected Half Weight Indices were smaller than the real
HWI, then the pair was defined as a preferred relationship i.e. they were more likely to be seen together than by chance (Lusseau 2003, Whitehead 1999).
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5.3.4. Social analysis.
The resulting social network was compared with random networks using the same number of individuals (nodes) and links between them (edges). This was done using UCINET (Borgatti et al 2002). Several tests were run:
Path length is the distance, or number of links or edges, between a pair of individuals. In a complicated network there may be many routes, so the shortest route or path is the one traditionally used. The more-often-used average shortest path length is simply the average of all the path lengths linking pairs in the network (Croft et al 2008). It is the origin of the ‘six degrees of separation’ used famously by Milgram in 1967 to describe the idea that any two humans in the
US population could be linked via five intermediaries. The smaller it is, the more readily information (or disease) can be communicated across a network
(Croft et al 2008).
Clustering co-efficient measures social relatedness in a network, giving the likelihood that two associates of an individual are themselves socially related.
The problem with using network measures such as average shortest path length and clustering co-efficient however is that they take into account only reachable nodes. So if a network starts to fragment as nodes are removed, the individuals outside the main component will not be included and the measure will not reflect the change.
For this reason, network measures were used as an initial comparison between random and dolphin networks, but the proportion of nodes left inside the largest
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 19 component was also calculated as attacks on the network were simulated, and were plotted on a graph (Lusseau & Newman 2004, Lusseau 2003).
Degree simply measures how many links an individual has with other individuals, so individuals with a high degree can transmit information to other individuals (Croft et al 2008).
Betweenness is another measure of the ‘centrality’ of an individual, and is the number of shortest paths connecting other individuals that pass through it. It can show which individuals are ‘key players’ (Croft et al 2008). These animals may therefore be important in holding a network together (Lusseau & Newman
2004).
5.3.5 Visual representation.
Visual representations of data were constructed using Netdraw, a component of
UCINET.
6.0. RESULTS
6.1. Associations
After removing animals seen fewer than five times, calves, and animals not seen since 2007, there were 67 individuals left, with 1139 ties linking them.
One hundred and forty three of these links survived the permutations designed to select pairs whose association was more than random.
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Of the 67 animals, 16 were females and 13 were males or probable males. The rest were of unknown gender.
Typically of many (but not all) Bottlenose Dolphin populations, there were few close associations – in fact there were only 10 with a Coefficient of Association of 0.50 or more (suggesting they spent more than half their time together). The closest association was 0.83 between 172, a male, and 173, a female; 172 had another close association with a female, 167.
Males tended to be more ‘connected’ than females. Five known or probable males had high betweenness scores and five had high degrees. Of the females, four had high betweenness scores and two had high degrees. This tends to go against some other studies (e.g. Lusseau 2003) where adult females were found to be key players linking clusters, but in this study the proportion of known males and females was too small to draw firm conclusions.
6.2. Filtering.
It can be problematical deciding how much of the original network - individuals or associations - to use. Especially when using the ‘gambit of the group’ to define groups, some of the associations might arise through chance. For this reason most studies (including this one) limit the number of animals studied to those that have been observed a minimum number of times or that have been identified over a certain length of time (Croft et al 2008). But filtering out too many individuals or associations can mean missing out on links which may be important. For example it takes few individuals to pass on a disease or information (Croft 2008).
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For this study two methods were tried as an experiment: a simple Half Weight
Index cut-off and the previously-mentioned system of permutations. In the first, associations with an index of 0.15 and above were used.
Figure 4: Preferred companionships, using a HWI cut-off of 0.15.
This of course raises the problem of how to define the limit. This method produced a network with far more edges than the more frequently used system of permutations, shown in Figure 5.
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Figure 5: Preferred companionships, as defined by permutation tests
But interestingly the same basic structure of two loosely-connected clusters, survived both methods.
The permutations option was used thereafter because it facilitated comparisons with other studies.
6.3. Network analysis.
Ten random networks were also constructed with a similar number of individuals and links as the original, using UCINET. The aim was to test the significance of findings and to illustrate some of the differences between random and dolphin networks, As found in other studies (e.g. Lusseau 2003), the random networks were far more homogeneous than the dolphin network, i.e. in the dolphin network a few individuals had a large number of links while others had only a few. This can be seen in a visual comparison of Figures 5 and
6.
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Figure 6: A typical random network (10 were constructed).
And also as found in other studies, the average path lengths (L) of both were similar: Ldolphin = 3.71, Lrandom = 2.94 (s.d.random = 0.05). But the clustering co- efficients (C) were noticeably different: Cdolphin = 0.37, Crandom = 0.07 (s.d.random
= 0.01), suggesting that the dolphin network had a much higher level of clustering. This would define the population as a ‘small-world’ network, with a small mean path length and a relatively large clustering co-efficient: small worlds may enable the rapid passing on of social information (and disease) through highly clustered networks (Latora & Marchiori 2001).
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Shortest average path length 4.5 4 3.5 3 2.5 2 1.5 Random 1 Dolphin 0.5 0 Network Minus 20% Minus 20% Minus 30% random targetted random
Figure 7 : Average shortest path length under different scenarios for the random & dolphin networks.
Clustering co-efficients 0.4 0.35 0.3 0.25 0.2 Random 0.15 0.1 Dolphin 0.05 0 Network Minus 20% Minus 20% Minus 30% random targetted random
Figure 8: Clustering coefficients under different scenarios for the random & dolphin networks.
6.3.1. Random attacks
Both networks were able to withstand random attacks i.e. events that may reduce their numbers. The path length (L) of the dolphin network increased by only 0.15 with the removal of 20% of individuals (Ldolphin = 3.86, s.d. dolphin =
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0.31). Ten different trials to remove nodes randomly were carried out. However
L refers to reachable individuals, and as can be seen from the graph, there are now four unconnected individuals and a further dyad with no connection to others in the network. The random networks increased by 0.16 : Lrandom = 3.1, s.d.random = 0.06.
Figure 9: Dolphin network after random removal of 20% of individuals.
When an unrealistically high number of 30% of individuals were removed, the average path length rose to 4.23, still not a dramatic increase, though again this was only between reachable individuals. The network however still did not fragment, with a large cluster remaining which included most individuals.
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Figure 10: Dolphin network with 30% of individuals removed randomly.
6.3.2. Targeted attacks
6.3.2.1. Degree
The picture changed however when the attacks were targeted on animals shown to be playing an important part in the community. The animals with the most
connections with others are classified by
degree; an individual with a score of 5 would
simply have links with five others. In the
Cardigan Bay population animal 067 had the
highest degree, a total of 13 associates, and Figure 11: Animal 067 – highest degree.(CBMWC) therefore was removed first. The rest of the top
30 percent on this measure were then removed one by one. By 20% the number outside the main cluster is increasing but most individuals are still inside it:
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Figure 12: Targeted dolphin network with the top 20% removed (degree)
By 30% it has fragmented almost completely:
Figure 13: Targeted dolphin network with 30% removed (degree).
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6.3.2.2. Betweenness.
Betweenness – the animals shown to connect sub-communities - is to some minds a better measure of the role they play. Lusseau & Newman (2004) felt
that animals with a high betweenness
might play a particularly important role in
maintaining social cohesion. In this study,
the animal with the highest betweenness Figure 14: Animal 104, highest betweenness (CBMWC) was animal 104 and was the first to be removed. The others were then removed one by one. By 20% the largest cluster is shrinking:
Figure 15: Targeted dolphin network with 20% removed (betweenness).
By 30% again the network is fragmenting:
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 29
Figure 16 : Targeted dolphin network with 30% removed (betweenness).
Removing animals by betweenness had a greater effect when a smaller number were taken out (perhaps the more realistic scenario). Removing them by degree had the greatest effect on the network after approximately 25%. Targeting by betweenness and degree both had a far greater effect than removing animals at random.
Proportion of individuals left after random & targeted attacks 120 100 80 % left (degree) 60 40 % left (betweenness) 20 Random(dolphin) 0 Random(random) 0 10 20 30 40 Proportion of individuals removed
Proportion in giant componentgiantin Proportion
Figure 17: Proportion of nodes left in the largest component of the network as nodes are removed.
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 30
The results therefore suggest that the population is relatively resilient to attacks which affect individuals at random. However any attack on the population which for some reason affected even a comparatively small number of animals with central roles in the community would have a far greater effect. If attacks were targeted on those with the highest betweenness, the ‘brokers’ who interact with more than one sub-communities, the network would be more likely to fragment. They would thus lose all the advantages cohesion brings – learning, support, co-operation and the like. If the animals targeted were those with the largest number of associates (i.e. those with high degree), the effect would be even more pronounced in the (unlikely) event that more than 25% of the animals were removed.
The results also underline the fact that animals play different roles in a network and – an important point for managers - that threats which remove individuals can have a disproportionately greater effect than those affecting a community in general.
7.0. DISCUSSION:
7.1. Network properties:
The idea behind network analysis is that complex systems often exist in the form of networks and exploit to their advantage the interconnectivity which that brings. Non-living examples are transport networks and the World Wide Web; social networks and even cells in living organisms also work like this. And it seems that these networks share certain basic properties known as ‘scale-free’ behaviour (Aloy & Russell 2004).
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 31
In scale free networks, most nodes (individuals or constituent parts) have a small number of connections with hubs, but not necessarily with each other.
Various parts of the network are statistically similar to other parts and comply with the small-world phenomenon, that is the network is compact with few links needed to cross it (that is where ‘six degrees of separation’ comes in). But the nodes are also highly clustered. And these scale free networks are tolerant of random failures, though not to attacks on the ‘hubs’ (Aloy & Russell 2004,
Albert et al 2000).
The dolphin network in this study appears to fit the qualifications of scale-free and small world, with not all members of it fulfilling the same role. When random attacks were made, even to the quite unrealistic level of 30%, the size of the network measured in path lengths increased by only a small amount
(0.52). And all but five of the animals (7.4%) remained in the main cluster.
This may be because of the high clustering coefficient, compared with the random networks, which suggests that the animals have lots of alternative
(‘redundant’) links or information paths they can exploit should one, or a few, be removed. This makes the network more resilient. And indeed scale-free small-world networks are seen as facilitating the speedy spread of social information through a population even though a high level of clustering could in theory limit the spread of knowledge or disease throughout the network
(Croft et al 2008, Albert et al 2000).
But when the attacks were targeted at animals who play a central role in transmitting information, measured either by degree or betweenness, the
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 32 network became far more fragmented – though not as much as with other scale free networks such as the internet (Albert et al 2000).
Lusseau (2003) and Lusseau & Newman (2004) found a comparable effect with a population of Bottlenose Dolphins in Doubtful Sound, New Zealand and
Lusseau (2003) commented that it provided evidence that scale-free/small- world attributes did not depend solely on the constituents of the networks but were general laws. However other experts (e.g. Croft et al 2008) warn of the dangers of applying results from very large networks to far smaller ones.
7.2. Network measures.
On the relevance to real life of network measures, Lusseau & Newman (2004) noted that the temporary disappearance of the animal with the highest betweenness score, known as SN100, led to the breaking up of the community in Doubtful Sound into two groups. When SN100 reappeared the two groups got back together.
Girvan and Newman (2002) note that individuals in human societies with high betweenness are often information brokers and Lusseau (2007a) thinks the same is potentially true for Bottlenose Dolphins. The measure would indicate more diverse contacts and more knowledge about predators and prey, so it would be to the advantage of the group to follow such animals – and conversely, to their disadvantage if that animal were to disappear (Lusseau 2006).
This study charted the difference between removing animals with the highest degree compared with taking out those with the highest betweenness. Lusseau and Newman (2004) did the same and found that, despite the evidence of
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 33
SN100, removing animals with the highest betweenness produced less effect on the network than might be expected. In this study of Cardigan Bay animals, it had quite a dramatic effect, leaving only 40% in the main component of the network after 20% of animals had been removed. This chimes with Holme et al
(2002) who found that removing such individuals (human in their case) with high betweenness could destroy network connectivity.
However when the number of animals removed from the network was scaled up to 30%, perhaps a less realistic scenario in real life, the number remaining in the largest component was 28%. If the animals were targeted by degree (the greatest number of associates) the network was less fragmented with 20% removed, but much more so at 30% with only 16% remaining.
Lusseau (2003) also noted that the animals in his study with the highest degree tended to be older females, estimated to be older because of their larger size and the number of scars on their dorsal fins. In this study the gender of more than half the animals was unknown, but as noted previously, of the 29 known or probable males and females, rather more males than females had high betweenness or degree scores. And of those in the top ten percent for degree or betweenness (12 animals), only four had the maximum of five or more nicks or scars. However as well as indicating age, a much-nicked and scarred fin may also suggest that the animal is male rather than female so the results should be treated with caution. There were no records detailing size.
Differences with other dolphin populations, such as the Doubtful Sound animals might be explained by environmental and habitat differences together with their social dynamics. The Cardigan Bay and Doubtful Sound populations
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 34 studied are of a similar size but that in Doubtful Sound is constrained physically by the size and shape of the sound. There is also evidence that community size is limited by the availability of food (Lusseau 2007a). Animals with high betweenness who’d have more diverse associates across the network would know more about potential competitors because they’d had contact with them.
They might also know in which areas foraging by sub-groups had taken place recently and so which ones should be avoided. Following them therefore could cut foraging effort, so making them valuable members of the community.
In Cardigan Bay there is insufficient evidence to know if prey availability limits community size but it seems unlikely given that the animals can roam over a larger area in a shallow, productive bay with few if any predators. However the progressive removal from the Cardigan Bay population of individuals with a higher betweenness had, in the early stages of the experiment, a greater effect than the simulation had on the Doubtful Sound animals. With 10 percent of the
Doubtful Sound animals removed for example, more than 80 percent remained in the largest component, compared with 66 percent in Cardigan Bay. With 20 percent removed there were still more than half the animals remaining in
Doubtful Sound, compared with 40 percent in Cardigan Bay.
This may suggest that the Cardigan Bay animals are more affected by prey depletion than the assumptions would suggest. After all, all commercially fished species in the Irish Sea are said by the CCW to be below safe biological limits (CCW 2009). And the influence of individuals with high betweenness may well extend beyond the realms of prey availability. Animals with associates across the network would have the opportunity to pass on knowledge
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 35 but also to acquire it – as seen with the novel foraging methods noted in networks in Australia and dealt with on later pages.
Animals with high degree on the other hand would be familiar with animals in their own sub-group and, with large numbers of associates might well fit the traditional picture of a leader more closely (Lusseau 2007a). However their lack of wide-ranging experience may make them less effective decision makers. But the exception might perhaps be in the case of a truly catastrophic (and perhaps unrealistic) depletion of numbers when fragmentation of the group might make such decisions academic. The Cardigan Bay animals might be seen to fit this picture, with removal of high-degree animals having a greater effect on network cohesion than the removal of high-betweenness individuals when the numbers targeted exceeded 25-30%.
7.3. Are targeted attacks so unlikely?
It may seem fanciful to consider an event that would remove 20% or 30% of a population of Bottlenose Dolphins which are currently facing no major identified threat to their survival; even more so to speak of a targeted threat that would remove their most valuable members.
However such attacks are not unknown in the animal world. McComb et al
(2001) noted that older female elephants on an African reserve had better discriminatory abilities that could influence the group as a whole. These animals might also be the most likely to be shot by hunters because of their size. Whitehead et al (2000) speculates that selection of larger animals by whale hunters may have left a population with inherited tendencies to grow more slowly or to a smaller size. And Willams and Lusseau (2006), using network
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 36 techniques, found that attacks simulating historic live captures of whales in the northeastern Pacific were much more likely to result in fragmentation of the network than were random ones.
7.4. Why does network cohesiveness matter?
Dolphin societies are complex and social structure is crucial for many elements of their biology and the way they live (Lusseau 2006, Whitehead et al 2000).
The brains of odontocete whales and dolphins are much larger than any of the primates with the exception of man, and one theory is that this is in response to the need to function in a society where communication, collaboration and competition are the norm. The animals benefit from the ability to recognise others (Marino et al 2007) which may aid them in avoiding inbreeding with kin
(Pusey & Woolf 1996).
Dudzinski et al (2009) also noted what could be described as reciprocal altruism in Indo-Pacific Bottlenose Dolphins (Tursiops aduncus) and Atlantic
Spotted Dolphins (Stenella frontalis) which would also depend on the ability to recognise others and form social bonds. The animals had been observed rubbing each other’s pectoral fins which the authors noted might be likened to grooming in land animals. Such actions often led to support being given in aggressive encounters or the sharing of food and were based on a history of social interaction.
The animals also gain advantage from the ability to learn new behaviours from each other (Marino et al 2007). Examples include the well-known one of the dolphins of Shark Bay in Western Australia where some females have learned
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 37 to use sponges positioned on their rostra, presumably for foraging (Smolker et al 1997); ‘tail walking’ on the surface of the water by dolphins at Port River in
South Australia, in which the animals leap into the air, then appear to ‘walk’ backwards on their tails for several metres – again involving females (WDCS
2010); and use of conch shells for foraging in Shark Bay. It is thought these animals may drive fish into the shells then upend the shells to eat their contents
(Allen et al 2010).
There is also evidence for individuals taking on different roles in decision making (Lusseau 2007a) and co-operation in foraging (Gazda et al 2005).
It is also thought that strong social bonds could improve female calving success, either because of learnt reproductive abilities or the fact that females with calves might seek out other females with calves, perhaps for protection from males or predators (Frere et al 2010).
7.5. How real are the threats?
There are continued concerns over the conservation status of small cetaceans in
European waters, especially those which, like Bottlenose Dolphins in coastal areas, are most likely to be affected by anthropogenic influences. It is thought that numbers have dwindled especially in the North Sea, where the Moray Firth is the only area where they’re found consistently (Wilson et al 1997). There is no suggestion at this time however of any confirmed threat to the Cardigan Bay animals.
Knowledge gaps concerning the conservation status of Bottlenose Dolphins are a major problem. The Cetacean Specialist Group of the Species Survival
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 38
Commission of the World Conservation Union (IUED) classes them as ‘data deficient’. Population estimates too for cetaceans are notoriously inaccurate, and little appears to be known about causes of mortality.
Sharks and killer whales are the most common non-human predators of
Bottlenose Dolphins but there are no known cases of attacks in Cardigan Bay
(pers.comm.Steve Hartley) nor indeed in the Moray Firth, making the two UK populations unusual in global terms (Connor et al 2000).
Anthropogenic affects on dolphin populations however are well documented, from entanglement in fishing nets (IWC 1994a & 2010, BDMLR 2009) and prey depletion from scallop dredging (IWC 2010), to pollution.
The pollution threat in Cardigan Bay is of particular concern. Fifteen Bottlenose
Dolphins were found to have concentrations of PCBs of over 80mg/k, almost five times the threshold for adverse effects (CCW 2009). High contaminant concentrations may not kill animals outright but there is evidence suggesting that they lower immunity and the ability to ward off naturally-occurring diseases (Morris et al 1989). Links between high pollution levels and mass die- offs have been made in several studies (e.g. Lipscombe et al 1996, Domingo et al 1992). One survey (Mann et al 2010) also suggests that a high PCB load could have caused hearing loss in more than half the stranded or entangled animals they were able to test.
Given the importance of the acoustic environment to cetaceans, there is continued concern over anthropogenic noise levels. Sonar for example uses the same principles as dolphin echolocation and has been implicated in strandings
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 39 and behavioural changes in many parts of the world (BDMLR 2009, Frantzis
1998, Abate 2010).
Whitehead et al (2000) point out that noise can affect behaviour in other ways, causing cetaceans to fall silent or avoid areas. Bowles et al (1994) found that sperm whales and pilot whales appeared to react to a seismic survey vessel more than 300 km away in the Indian Ocean by avoiding the area. And a study of Blainville’s Beaked Whale (Mesoplodon densirostris) in the Bahamas using acoustic suction cup tags found that military sonar caused them to move away and stop vocalising (Southall 2011).
Attempts to further human knowledge and understanding of cetaceans can also misfire. Several studies have documented avoidance behaviour in Bottlenose
Dolphins when approached by marine mammal-watching tour boats. Several studies, including some in Cardigan Bay, noted that the animals often dived deeply or swam directly away (Constantine et al 2004, Lusseau 2003 & 2009,
Pierpoint & Allen 2006, Lamb 2004). Lamb (2004) also noted that the Cardigan
Bay animals used New Quay Bay most at night when boat traffic had subsided.
Constantine et al (2004) also found that the animals milled about more in the presence of a tour boat, commenting that a reduction in resting and foraging could affect behaviours such as vigilance and the giving of parental care. But
Lusseau (2003) found that animals in Doubtful Sound reacted less to the research vessel to which they’d become habituated.
Even swimming with dolphins has been shown to cause avoidance responses, especially among adult animals who, according to one researcher, had
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 40 apparently not found swimming with humans sufficient reward to continue doing it (Constantine 2001).
Climate change too could affect marine mammals though little work has been done in this area. Lusseau et al (2004) found that Killer Whales (Orcinus orca) and Bottlenose Dolphins tended to live in smaller groups when there was less salmon available, which in turn was dictated by changes in ocean currents.
Their conclusion was that climate could affect social organisation because of its effect on prey.
Climate change could also render unsuitable traditional cetacean calving grounds or migration routes. But species with catholic tastes in food like
Bottlenose Dolphins may be more resilient than most (Whitehead et al 2000).
7.6. Implications for management and conservation.
This and other studies have underlined the fact that dolphins have distinct roles in their societies. Some lead, some follow, some are solitary, others gregarious.
Lusseau’s work in particular identifies the brokers who liaise between sub- groups and who play such an important part in identifying the best foraging spots and passing on knowledge as well as the animals with large numbers of associates of all types (Lusseau et al 2005, Lusseau 2003 & 2007a, Lusseau &
Newman 2004). Removal of these animals in particular will have a far greater effect on network cohesion.
The assumption in most management plans and conservation objectives is that keeping population levels stable overall is a worthy target. But the implication of work such as this is that this approach may not be sufficient - that individuals
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 41 can, as with human populations, have a disproportionate effect on the whole.
So an activity with even a small or concentrated adverse impact could be significant.
One obvious example is with the effects of offshore renewable energy installations where it may be tempting to balance the number of marine mammals lost or driven away against the ‘good’ of saving carbon emissions. To say for example that a project is worth the loss of, say, five animals is missing the point if those five animals are the group’s leaders or brokers.
8.0. CONCLUSION
The problem of what we do not know is lamented time and time again by authors, even for a well-studied species such as the Bottlenose Dolphin. And knowledge gaps are exacerbated by the fact that the animals are long-lived and slow-breeding; so even with accurate data, trends might not become evident for decades. All of this makes it difficult to evaluate properly any threats from, for example, human activities.
However the departure of or the reduction in the Cardigan Bay population could have a secondary effect on the region’s status as a tourist destination.
Socio-economic effects coupled with conservation priorities make successful management even more crucial.
8.1. So are they safe from harm?
Network analysis showed the Cardigan Bay population to be resilient to attacks which affect animals at random rather than targeting individuals, probably the most likely form of threat. But catastrophic die-offs caused by diseases are
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 42 known to have taken the lives of tens to hundreds of animals. A population of fewer than 300 could easily fragment under those conditions. Susceptibility to such events appears to be increased by immune system damage which in turn can be caused by uptake of organochlorines – and we know this is a problem for Cardigan Bay animals (Law et al 1995).
Other human intrusions such as navy sonar and other acoustic disturbance do not appear to be a problem in Cardigan Bay at the present time and most of the boat traffic is of small size with the greatest concentration in New Quay harbour – where apparently unconcerned dolphins are also commonly found.
Changes in prey availability, caused by climate change or over-fishing, could take their toll in the future but again do not seem to be a current problem. And although entanglement in fishing nets has been a problem elsewhere, there is only one recent example, involving a calf, in Cardigan Bay.
As has been shown, removal of certain individuals can leave a population rudderless and fragmenting. While the idea of such targeted attacks may be felt to be unrealistic, it is not difficult to imagine circumstances in which for example food shortages would drive away animals which have the knowledge and contacts to seek prey elsewhere. It is also possible that older and more influential animals might be more likely to succumb to disease.
And even if there were no single threat capable of causing catastrophic breakdown, an accumulation of events – pollution, plus disease, plus climate change, plus a few rogue tour boat operators – might have the same effect.
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 43
So to return to the question: are they safe from harm? – the answer has to be a heavily qualified ‘probably’ – just as long as luck holds and certain recommendations are followed.
8.2. Management recommendations:
The most important is that managers should recognise the importance of the fate of individuals rather than objectives for population numbers as a whole.
Ideally far more research would be carried out including measures to calculate population levels more accurately. Much of the survey work is currently done by volunteers, who may stay only a few weeks, but it is difficult to see where funding for a more professional operation would come from under present conditions.
Further controls on fishing methods such as scallop dredging would be welcomed but at present law makers are caught between the demands of conservationists and those of the fishing community.
Controls on pollutants and nutrients from sewage and other run-off entering the bay from rivers should be enforced more strictly. But levels of, for example,
DDT may last for many years in the environment.
Monitoring of pollutants in the water, especially at known hubs of dolphin activity, may provide an early warning of possible disease levels.
The Ceredigion Marine Code advising boat owners to keep their distance from the animals has been shown to work – where it is followed there has been little negative response from animals. But it is sometimes ignored. Possible penalties
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 44 include withdrawal of launching or mooring facilities, or in extremis, criminal sanctions. But these are rarely, if ever, applied (Ceredigion Marine Code
22.1.11). They should be applied more strictly.
Heather Payton: The Bottlenose Dolphins of Cardigan Bay, Wales: Safe from harm? Page 45
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