Comparative phylogeography of ground
dwelling invertebrates on Banks
Peninsula, New Zealand
A thesis
submitted in partial fulfilment
of the requirements for the Degree of
Master of Natural Resource Management and Ecological Engineering
at
Lincoln University
by
N. L. Macdonald
Lincoln University
2013
1
Abstract of a thesis submitted in partial fulfilment of the
requirements for the Degree of M.N.R.M.& E.E.
Comparative phylogeography of ground
dwelling invertebrates on Banks Peninsula,
New Zealand
by
N.L. Macdonald
Recent research on Banks Peninsula of several invertebrate species shows that
populations in different parts of the peninsula are genetically distinct from one another.
This suggests vicariance, a continued evolutionary divergence, may be the driving
process and offers a model system to test ideas regarding the origins of new species and
their phylogeography. In this research, invertebrate taxon composition was used to
investigate a differentiation of multiple co-distributed ground-dwelling invertebrates
between east and west locations on Banks Peninsula. Genetic analysis was also used to
investigate invertebrate biodiversity, with particular interest in answering questions
regarding an east-west phylogeographic split among taxa (interspecific) and within tax
(intraspecific) on Banks Peninsula. Results showed that a phylogeographic split across
the east-west split was observed at both among- and within-species levels. More detailed
intraspecific analyses of two spider species, N. janus and P. antipodiana, revealed highly
divergent, genealogically exclusive clusters between east and west regions suggestive of
cryptic species complexes. The findings of this research ultimately provide better
understanding and crucial insight into the origins, maintenance and changes of
invertebrate biodiversity on Banks Peninsula. This could serve future biodiversity
research projects and be implemented into conservation management by distinguishing
areas for invertebrate protection and identifying key sources of invertebrate genetic
diversity.
Keywords – Banks Peninsula, invertebrate, phylogeography, MtDNA, divergence, taxon
composition, conservation management.
2
Acknowledgements
I am grateful to a number of people without whom this thesis would not have been
possible. Different people gave me support one way or another in each of the disciplines
that this thesis is composed.
First, I would like to thank my supervisors Dr. Hannah Buckley, Dr. Robert
Cruickshank and Dr. Atzberger Clements. Their support through logistics, motivation and
regular discussions assisted me immensely throughout the entirety of my thesis. I am
grateful to the Brian Mason Trust for being extremely generous by providing the funding
for this research. This allowed me to focus on my project and enjoy it.
This project would not have been possible without students: Sarah Mitchell, Jonathan
Ridden, Cathy Mountier who assisted in the sample collection and sorting of
invertebrates. I would also like to thank AgResearch for providing field equipment and
Dr. Cor Vink curator of natural history at Canterbury Museum for morphological
identification assistance. I thank Dr. Roddy Hale and Rachel van Heugten for helping me
with fieldwork site selection, and technicians; Dr. Emily Fountain of the Department of
Ecology and Norma Merrick of the Bio-Protection Centre at Lincoln University, where
all of the sequence data included in this study were obtained. Finally I would like to
thank my partner Fleur Steiner and family Rob, Sue and Finn Macdonald whose financial
and moral support was crucial in the completion of my thesis.
3
Table of Contents
Acknowledgements
3
Table of Contents
4
List of Figures
6
List of Tables
7
Chapter 1
1.1 Literature Review
1.1.1 Phylogeography
1.1.2 Mitochondrial DNA and species delimitation
1.2 Introduction
1.2.1 Banks Peninsula
1.2.2 Prior Research
1.3 Aim of the study
1.4 Study species
1.4.1 Neoramia janus
1.4.2 Porrothele antipodiana
1.5 Objectives and hypotheses
9
9
9
11
13
13
14
15
15
15
16
16
Chapter 2
18
2
18
18
19
20
20
20
21
21
24
25
25
Methods
2.1 Study area
2.2 Invertebrate sampling
2.3 Environmental variables
2.4 Sorting of invertebrates
2.5 Data analysis
2.6 Specimen selection for DNA analysis
2.7 DNA analysis
2.8 Identification of species
2.9 SplitsTree phylogenetic networks
2.10 Phylogenetic analysis of N. janus and P. antipodiana
Chapter 3
27
3
27
27
31
33
35
36
Results
3.1 Patterns in taxon composition
3.2 DNA analysis of taxa
3.3 Comparative phylogeography
3.4 Geophylogeny of N. janus and P. antipodiana
3.5 Phylogeny and GMYC of N. janus and P. antipodiana
Chapter 4
40
4
40
40
42
43
44
45
46
Discussion
4.1 Comparative phylogeography and community composition
4.2 Intraspecific phylogeography: N. janus and P. antipodiana
4.3 Explanations of phylogeography for P. antipodiana
4.4 Genetic and morphological decoupling
4.5 Implications for conservation
4.6 Limitations and future research
4
4.7
Conclusion
47
Appendix
49
References
52
5
List of Figures
Figure 1: Location of 22 sites visited during fieldwork on Banks Peninsula.
19
Figure 2: Eight taxa identified and chosen for comparative phylogeographic analysis. 25
Figure 3: Non-metric multidimensional scaling ordination of taxon composition at 22 east
and west sites on Banks Peninsula.
27
Figure 4: Non-metric multidimensional scaling ordination showing the relationship
between soil moisture and taxon composition.
29
Figure 5: Non-metric multidimensional scaling ordination showing the relationship
between canopy cover and taxon composition.
30
Figure 6: Non-metric multidimensional scaling ordination showing the relationship
between soil temperature and taxon composition.
30
Figure 7: Overall mean pairwise genetic distance for nine taxa collected from Banks
Peninsula, New Zealand.
33
Figure 8: Unrooted phylogenetic networks of eight taxa.
34
Figure 9: Geophylogeny showing monophyletic clusters for N. janus.
35
Figure 10: Geophylogeny showing monophyletic clusters for P. antipodiana.
36
Figure 11: N. janus log-lineage through time plot.
38
Figure 12: Generalised Mixed Yule-Coalescent model of N. janus sequences.
38
Figure 13: P. antipodiana log-lineage through time plot.
39
Figure 14: Generalised Mixed Yule-Coalescent model of P. antipodiana sequences.
39
6
List of Tables
Table 1: Mean, standard deviation and min/max ground soil moisture for 22 sites on
Banks Peninsula.
28
Table 2: Mean, standard deviation and min/max soil temperature for 22 sites on Banks
Peninsula.
28
Table 3: Mean, standard deviation and min/max canopy cover for 22 sites on Banks
Peninsula. .
29
Table 4:Taxonomic information for 15 taxa selected for initial DNA analysis.
31
Table 5: Nine out of 15 taxa selected for DNA analysis and their abundance per site.
31
Table 6: Nine out of fifteen specimens successfully amplified during initial DNA
analysis, their DNA fragment length and over all mean genetic divergence.
32
Table 7: Number of specimens successfully amplified during DNA analysis, DNA
fragment length and overall mean divergence for species N. janus and P.
antipodiana.
33
Table 8: Within and between group divergence (uncorrelated pairwise distance) for N.
janus.
37
Table 9: Within and between group divergence (uncorrelated pairwise distance) for P.
antipodiana.
37
7
Abbreviations
ALTER: Alogrithim transformation enviRonment
BEAST: Baysian evolutionary analysis tool
BLAST: Basic local alignment search tool
COI: Cytochrome oxidase subunit I
DNA: Deoxyribonucleic nucleic acid
ESU: Evolutionary significant unit
GMYC: Generalised Mixed Yule-Coalescent
GPS: Geographic positioning system
K2P distance: Kimura 2-pairwise distance
mtDNA: Mitochondrial deoxyribonucleic nucleic acid
MU: Management unit
NMS: Non-linear multidimensional scaling
PCR: Polymerase chain reaction
RMA: Resource managent act
UNCBD: United nation's convention on biological diversity
8
Chapter 1
1.1
Literature Review
1.1.1 Phylogeography
The term ‘phylogeography’ was coined many years ago by Avise et al (1987). It is a field
of study that works within the framework of biogeography (Avise, 1994), and is
concerned with the principles and historical processes governing geographical
distributions of genealogical lineages within species (intraspecific) and among species
(interspecific) (Avise, 1998, 2000).
Traditionally, phylogeographic studies have been primarily intraspecific, concerned
with the geographical structuring of gene lineages within single species (Avise, 1998).
This matching of species phylogeny with geography in combination with likelihood and
coalescent methods can infer major genetic lineages (monophyletic clusters) and
phylogeographic patterns within species (Arbogast & Kenagy, 2001). Intraspecific
phylogeography has proven successful in its ability to test for patterns of vicariance
(Arbogast, 1999; Wooding & Ward, 1997). It is also able to explore deep divergent
lineages suggestive of the existence of cryptic species, under the framework of the
genetic species concepts defined as: species are irreducible (basal) clusters of organisms
that are diagnosably distinct from other such clusters, and within which there is parental
pattern of ancestry and descent (Cracraft, 1989), and a species is the smallest (exclusive)
monophyletic group of common ancestry (Queiroz & Donoghue, 1988). Species are said
to be cryptic if they are, or have been, classified as a single species based on
morphological indistinguishability but have they recently diverged, separable by
molecular data, occur in sympatry or be reproductively isolated (Bickford et al., 2007).
The discovery of cryptic species based on mtDNA molecular data have been detected
among populations of the wood-feeding cockroach Cryptocercus punctulatus
(Kambhampati et al., 1996) and darkling beetle, Heteger politus, with interpopulation
Cytochrome oxidase subunit I (COI) divergences of 5 to 12% (Juan et al., 1996). They
have been uncovered in millipede, Anadenobolus excisus (Bond & Sierwald, 2002) and
9
tree snail Achatinella mustelina (Holland & Hadfield, 2002). Cryptic species have also
been reported in, the trapdoor spider Aptostichus simus (Bond et al., 2001), funnel-web
spiders belonging to genus Atrax (Beavis et al., 2006) and the North American tarantula
genus Aphonopelma (Hamilton et al., 2011).
Intraspecific phylogeography has also proven successful when designating
management units (MUs) or evolutionary significant units (ESUs) in invertebrates. For
example, three endemic Hawaiian tree snails were identified as six isolated ESUs from
mitochondrial DNA (mtDNA) sequences (Holland & Hadfield, 2002) and six ESUs were
identified from five morphospecies of sea snails (Claremont et al., 2011). MUs, defined
by Moritz (1994), are populations with significant divergence of allele frequencies at
nuclear or mtDNA loci, regardless of phylogenetic distinctiveness of alleles (Moritz,
1994). ESUs, according to Ryder (1986), are subsets of species that are historically
isolated and possess meaningful genetic divergence likely to have a distinct potential for
the present and future generations. Moritz (1994) states that ESUs must be reciprocally
monophyletic for mtDNA and show a significant divergence of allele frequencies at
nuclear loci. Identifying MUs and ESUs allows for the recognition of species that contain
divergent lineages. This information could guide future research and be of benefit to the
planning of long-term conservation strategies and priorities (Moritz, 1994).
Intraspecific phylogeography, in combination with morphological investigation, also
has the ability to identify instances of genetic divergence in the absence of changes to
genital morphology. This is evident in the soil-dwelling mite, Steganacarus carlosi, with
genetically well differentiated clades that lack morphological differentiation
morphological differentiation yet has genetically well-differentiated clades among
specimens collected across three islands (Salomone et al., 2002). This has also been seen
in trapdoor spiders (Bond et al., 2001) and cave spiders (Hedin, 1997), where genetic
divergence and cryptic species complexes were found among specimens that were
morphologically conserved.
A recent extension of phylogeography has been the comparison of phylogeographic
data across multiple co-distributed taxa, or ‘comparative phylogeography’. This approach
allows for the evaluation of the spatial pattern of genetic diversity among groups of
closely related taxa providing the identification of biogeographically independent regions
and patterns of vicariance in modern biotic assemblages (Avise, 1992; Bermingham &
10
Avise, 1986; Riddle et al., 2000; Walker & Avise, 1998). In these cases, the congruent
patterns of phylogeography among multiple taxa suggest they have had a log-standing
geographical association with one another as a result of them being subjected to the same
environmental history (Arbogast & Kenagy, 2001). These patterns also suggests that taxa
have undergone local adaptation (Williams, 1966), a pattern whereby resident genotypes
of a local population have higher fitness in their local habitat than genotypes originating
from other habitats, this can be driven by ecological factors such as lack of gene flow
(Kawecki & Ebert, 2004).
Comparative phylogeography can also be combined with independent information on
landscape history (Bermingham & Martin, 1998; Da Silva & Patton, 1998; Schneider et
al., 1998) and compared to biodiversity assessments such as the distribution of endemic
species (Moritz & Faith, 1998). Here, comparative phylogeography can be used to
answer questions about the formation of contemporary biological communities
(Bermingham & Moritz, 1998). This has implications for conservation management as it
can be used to set conservation priorities such as areas that require protection or
maximize diversity (Moritz & Faith, 1998).
1.1.2 Mitochondrial DNA and species delimitation
The most commonly used molecular marker for empirical genetic research in animal
phylogeography has been animal mtDNA (Arbogast & Kenagy, 2001; Avise, 2000). Such
a widespread use of mtDNA permits comparisons across otherwise unrelated studies
(Garrick et al., 2006). In this study the gene region COI in mtDNA was used because it is
appropriate for both interspecific (across species) and intraspecific (within species)
aspects of the project. It also evolves rapidly (Avise, 1998) and at higher rate than nuclear
DNA (Brown et al., 1979; Moore, 1995) which means the difference and diversity of
sequences across taxa (Hebert, Ratnasingham, et al., 2003) and within species is enlarged
compared to nuclear DNA. Coalescence times are also four-fold shorter for mtDNA than
nDNA, meaning that they will achieve reciprocal monophyly four times faster after a
divergence event (Zink & Barrowclough, 2008). There are few sets of universal primers
are sufficient to obtain the target sequence in a wide variety of taxa (Hebert,
Ratnasingham, et al., 2003), and COI is highly effective at assigning analysed spider
11
specimens to the correct species (Barrett & Hebert, 2005). MtDNA is maternally
inherited (Hutchison et al., 1974) leaving interpretation of genealogical relationships
unaffected by genetic recombination. MtDNA is present in all animals and there are
many copies of it in each cell, as opposed to nDNA for which there are just two copies in
diploid organisms, so it is much easier to amplify. Finally, insertions and deletions
(indels) are relatively rare (Barrett & Hebert, 2005) making it easier to align sequences
during analysis (Hebert, Cywinska, et al., 2003).
There are, however, pitfalls that need to be acknowledged when using mtDNA in
phylogeographic research. Phylogeography studies based on mtDNA alone are only
evolutionary studies of a single molecule, not a species and maternal inheritance results
in studies that are sex-biased which only reflect the history of maternal lines (Garrick et
al., 2006). Also, on rare occasions, the supposed lack of recombination has been shown to
be incorrect (Lunt & Hyman, 1997). Despite these criticisms mtDNA makes a good
starting point and provides an acceptable approximation of evolutionary history of
organisms.
In this research a Generalised Mixed Yule-Coalescent (GMYC) method was used for
species delimitation. The aim of GMYC is to delimit independently evolving species
based on single locus data (Fujisawa & Barraclough, 2013) such as COI from mtDNA.
GMYC works by identifying a time of transition in an ultrametric phylogenetic tree that
differentiates speciation events from population coalescence events based on the
branching rate within a taxon. It is a widely used method that has been successfully
applied to invertebrates in previous studies including species delimitation of North
American tarantulas (Hamilton et al., 2011), Atlantic and Pacific marine snails
(Claremont et al., 2011), New Zealand tiger beetles (Pons et al., 2011) and European
mayflies (Vuataz et al., 2011).
12
1.2
Introduction
1.2.1 Banks Peninsula
Banks Peninsula is a remnant volcanic complex located in the middle of the east coast of
the South Island, New Zealand. It is connected to the mainland by alluvial gravels from
the Canterbury Plains that accumulated in the late Quaternary (Sewell, 1988; Soons et al.,
2002). The volcanic complex measures 1200km2 and contains two large calderas that
form Lyttleton and Akaroa Harbours (Sewell, 1988). Paleoenvironmental conditions,
geological processes, and human intervention have shaped floral and faunal composition,
and the current state of the environment. For example, during glacial period MIS6, only
three beetle fossil species out of nineteen found were of modern Banks Peninsula fauna
(Marra, 2007) and vegetation during interglacial periods consisted of podocarp forests
with shrub understory, while glacial periods were primarily characterised by open
shrubby vegetation (Soons et al., 2002). It is probable that during cooler phases,
vegetation acted as refugia for many invertebrate species (Buckley et al., 2010; Marra,
2007). The fossil record of beetle Rhicnobelus metallicus (Belidae), which is host specific
to Podocarpus totara and P. hallii, provides confirmation that this forest type was present
during glaciation MIS6 (Marra, 2008). Environmental niche modelling Buckley et al.,
(2010) also predicts small patches of suitable habitat for stick insect C. hookeri along the
eastern coast regions of Banks Peninsula during the last glacial maximum MIS2.
Prior to the arrival humans to New Zealand about 1000 years ago (Atkinson &
Cameron, 1993) Banks Peninsula was almost completely covered by a richly varied
forest (Wilson, 1993). With human settlement the landscape of Banks Peninsula was
subjected to significant change with Polynesian and European colonisation both being
responsible for widespread deforestation with the removal of 98% of indigenous forest
(Harding, 2003). Early settlers repeatedly burned forests to clear land, resulting in longterm changes to landscape vegetation, depletion of soil seed banks, and accelerated
erosion (Taylor et al., 1997). Humans have introduced an average of 11 species per year
since their arrival and have initiated an influx of animals, such as possums, that can act as
disease vectors and threaten native flora and fauna (Atkinson & Cameron, 1993). Since
settlement humans have been responsible for the extinction of 32% of endemic land and
13
freshwater birds, 18% of endemic seabirds, 42% of native frog species (Taylor et al.,
1997) and one native freshwater fish species (McDowall, 1990). Today, vegetation on the
Banks Peninsula is comprised of indigenous and exotic species. Tussocks primarily
dominate higher altitudes and while lower areas have been converted to pasture with
fragments of natural forest existing in some valleys and scenic reserves (Harding, 2003).
1.2.2 Prior Research
Previous studies of invertebrate phylogeography on banks peninsula have produced
insightful descriptions of invertebrate genetic variation indicating genetic divergence and
a phylogeographic split, east/west, on Banks Peninsula. Sampling for these studies has
typically been done by visiting sites where the species of interest are present which
makes it difficult to adequately draw conclusions regarding patterns of intra and
interspecific phylogeography. Species in prior research showing phylogeographic split
and/or high evolutionary divergence include the beetle species Megadromus guerinii
(Chaudoir) (Coleoptera: Carabidae) (Wiseman et al., unpubl.) and a rare six-eyed spider
Periegops suterii (Urquhart, 1892) (Arachnida: Araneae) (Vink et al., 2013).
Megadromus guerinii are endemic forest specialists with relatively few other habitat
requirements (Anderson, 2000). They follow a clustered spatial distribution pattern most
likely due to specific topography and the proportion of stones in the substrate (Anderson
et al., 2004). Mitochondrial and nuclear genes were used to determine phylogeographic
patterns, and whether this species represented a single population, or several discrete
populations restricted to different parts of Banks Peninsula with restricted gene flow
between them (Wiseman et al., unpubl.).
Vink et al (2013) observed genetic divergence among populations of a rare six eyed
spider, Periegops suterii from Kennedys Bush Reserve, in the west of Banks Peninsula,
compared to eastern localities. The Kimura 2-parameter distance (K2P distance) in this
species was 8.7–9.2%, which is considered relatively high compared with the average
maximum within-population divergence of 3.16% (K2P-distance) observed in other
spiders (Robinson et al., 2009). The fact that a slower evolving nuclear marker showed
no divergence, and there was no morphological difference among specimens, lead to the
assumption that the specimens were of the same species.
14
Also, the geographic distribution of two species of tree weta Hemideina ricta and H.
femorata (Hutton) (Orthoptera: Rhaphidophoroidea) reflect a similar geographic pattern
as the other examples (Townsend et al., 1997). These two species are geographically
separate from each other, except in small areas of overlap adjacent to the east of Akaroa
township. It is thought that the separation of these species is due to the distribution of
vegetation on Banks Peninsula, corresponding to a vegetation transition at 500 m a.s.l.
(Wilson, 1992). H. femorata was shown to approximately correspond to this vegetation
limit, while H. ricta showed no concordance with the transition (Townsend et al., 1997).
Finally, a pilot study carried out by an undergraduate at Lincoln University in the
summer of 2011/12 suggested that a similar geographic pattern in genetic structure across
the peninsula might exist for an unidentified species of longhorned beetle and an
unidentified species of cave weta (van Driel, unpubl.). In the case of the longhorned
beetle, COI sequence data revealed a mean genetic distance between specimens from the
two sides of the peninsula of 4% (van Driel, unpubl.). Taxonomy and identification of
species in this project were not carried out; meaning further research is necessary to
adequately assess these patterns.
1.3
Aim of the study
The aim of this research is to establish the commonality of a phylogeographic split and
geographic difference in taxon composition east/west of Banks Peninsula among grounddwelling saproxylic (dead-wood dependent) invertebrates in native bush patches. The
research will also determine if this is related to variation in environmental characteristics.
1.4
Study species
1.4.1 Neoramia janus
Neoramia janus (Agelenidae) (Bryant, 1935) is a species of spider endemic to
Canterbury, South Island, New Zealand. On Banks Peninsula it is very abundant and
considerably widespread (Hodge et al., 2007). A study of spider communities in
Canterbury’s nature reserves found that, in terms of species composition, N. janus was
15
the most dominant species, comprising of 42% of the spiders collected in the final sample
(Hodge et al., 2007). N. janus is currently placed in the family Agelenidae; however,
phylogenetic evidence suggests that it does not belong in this family (Spagna & Gillespie,
2008), thus it is probably appropriate to view this species as representing a distinct clade
until its correct placement is properly determined (Paquin et al., 2010).
1.4.2 Porrothele antipodiana
Porrothele antipodiana (Hexathelidae) (Walckenaer, 1837), is a black tunnelweb spider
found in subalpine and coastal areas throughout the North and South Islands of New
Zealand (Jackson & Pollard, 1990). P. antipodiana belongs to suborder Mygalomorphae
and family Hexathelidae, which consists of two genera and 25 species (Paquin et al.,
2010). They are closely related to the notorious and occasionally deadly genus Atrax or
‘Funnel Web Spider’ (Underhill & Sutherland, 1987). P. antipodiana is endemic and
usually found on the ground surface under rocks, logs and in hollows in trees building
bulky, silken tunnels within crevices (Paquin et al., 2010). By weight they are New
Zealand’s largest spider (Jackson & Pollard, 1990), disperse only by walking (Decae,
1987) and then to a very limited extent (Forster & Wilton, 1967). Many members of other
spider infraorders such as Araneomorphae are able to disperse great distances across
geological barriers by aerial ballooning (releasing silken threads that are captured by the
wind and carry the spiders aloft) (Greenstone et al., 1987). However, ballooning in
mygalomorphae has only been observed in small spiderlings (Coyle, 1983; Coyle et al.,
1985). Therefore, their distribution could be a good indicator of land patterns and
vicariance (Poinar Jr & Early, 1990) on Banks Peninsula.
1.5
Objectives and hypotheses
1. Compare taxon composition on opposite sides, east and west, of the peninsula and
identify if environmental characteristics related to patterns of species
composition.
16
Hypothesis 1: Species composition of invertebrates will differ between the east
and west sides of the peninsula. This difference will be related to environmental
variables such as: soil moisture, canopy cover and soil temperature.
2. Compare phylogeography across a variety of invertebrate taxa to identify
evidence for a common pattern of genetic subdivision, separated east and west of
Banks Peninsula. If taxa exhibit similar phylogeographic patterns this could
indicate that they were subjected to similar historical biogeographic events. This
could allow determination of historical and evolutionarily independent regions
(Bermingham & Moritz, 1998) in which generalizations about natural processes
can be tested.
Hypothesis 2: Individuals within multiple invertebrate taxa collected on each side
of Banks Peninsula will be considerably more closely related to conspecifics from
the same side of the peninsula than they are to conspecifics from the other side of
the peninsula. There will be a distinct gap between the distributions of intra- and
inter-regional pairwise genetic distances.
3. Undertake an in depth phylogeographical analysis of spider species N. janus and
P. antipodiana to identify deep genealogical divergence and a phylogeographic
split on Banks Peninsula. This could establish phylogenetic clustering within gene
trees identifying deep historical subdivision within the species phylogeny (Avise,
1998), and answer questions regarding speciation and population history (Garrick
et al., 2004).
Hypothesis 3: Individuals of P. antipodiana and N. janus collected on each side of
Banks Peninsula will be considerably more closely related to conspecifics from
the same side of the peninsula than they are to conspecifics from the other side of
the peninsula. There will be a distinct gap between the distributions of intra- and
inter-regional pairwise genetic distances.
17
Chapter 2
2
Methods
2.1
Study area
Sites selected in this study were located in natural forest fragments that were larger than
five hectares. Sites were located close to the middle of forest fragments to reduce edge
effects. Forest fragments were visually inspected on Google Earth and in the field to see
if they had a relatively dense canopy cover estimated at above 40%, and whether they
could be driven to. These criteria ensured sites contained suitable amounts of logs and
leaf litter that harbour invertebrates. It also made it possible to visit three sites per day,
maximizing the sample size of the study. A total of 22 sites located east, west and central
were visited during fieldwork. Fieldwork was carried out in the summer months of
November 2012 and March 2013. Two sampling sessions per month lasting three weeks
each were conducted to produce an accurate account of invertebrate abundance during the
entire summer season. When a trio of sites in one region (east or west) was sampled on
one day, a corresponding trio of sites were sampled in the adjacent region the following
day. This was done to keep visiting times of sites as similar as possible, reducing the any
temporal bias. All sites will be marked with geographic positioning system (GPS).
18
Figure 1: Location of 22 sites (orange circles) visited during fieldwork on Banks Peninsula.
2.2
Invertebrate sampling
The sampling effort was standardised with logs being used as the sampling unit. This
controlled bias introduced by independent variables and allowed invertebrate abundance
data to be compared across sites. Ten logs at each site were sampled for a period of 5
minutes each; this was timed using a wristwatch. Once the timer was set the log was
uplifted. Invertebrates found on the underside of the log, within crevices of the log, and
on the ground surface from where the log was lying were collected. Outer-bark and wood
thought to be concealing invertebrates was also broken open to search for invertebrates.
This is done to ensure the maximum numbers of invertebrates per log were captured, thus
increasing the total number of specimens and taxa collected at each site. All invertebrates
were placed into vials labelled with date, site and log number. On the same day,
invertebrates were transported to the laboratory at Lincoln University and placed in 100%
ethanol for sorting.
19
2.3
Environmental variables
Biotic and abiotic environmental variables were recorded to compare to invertebrate
abundance data across sites, east and west of the peninsula. The same person carried out
all biotic and abiotic recordings throughout the sampling effort to provide consistent
measures.
At each site canopy cover per log was estimated to the nearest five per cent. Soil
moisture was measured using a 12cm Hydrosense Soil Moisture Probe that produces a
reading of average soil moisture content. To ensure probes measure surface soil, with
which invertebrates are more likely to interact, they were inserted into the soil under each
log on a 45° angle at a depth less than 5cm. Soil temperature was measured using a Fluke
62 Mini Infrared Thermometer. Readings were obtained per log directly after collection
of invertebrates. For all logs, two readings were taken, and the average temperature
recorded.
2.4
Sorting of invertebrates
Throughout the sorting procedure, a reference list was produced for each invertebrate
taxon collected during the fieldwork. Invertebrates from each log that looked like the
same species, or ‘recognisable taxonomic units’ were counted and placed into smaller
sorting vials containing 100% ethanol. The number of invertebrates, date, log number,
site, and reference number were recorded on a label placed inside the vial and on a
sorting datasheet entered into Microsoft Excel. Vials were eventually placed in trays
marked with the site name and date of collection for storage at Lincoln University.
Voucher specimens for each taxon are lodged in the Lincoln University Entomological
Research Museum (LUNZ).
2.5 Data analysis
Non linear multidimensional scaling (NMS) in PC-ORD (McCune & Mefford, 1999)
was used to examine variation in taxon composition in east and west sites on Banks
Peninsula. NMS arranged sites so that the distance between each site in ordination space
is in rank order with their similarities in taxon composition. Multiple iterations were
20
performed to minimise the lack of fit (stress) between distance in the original matrix (first
randomisation) and distance in the final reduced ordination space. Prior to ordination the
original data set was relativized by maximum to dampen the effects of dominant taxa.
Because the data had a relatively high number of zeros the Sørenson (Bray-Curtis)
distance measure was used. Dimensionality was chosen based on low stress scores that
were accompanied by a randomization test p < 0.05. Instability criterion was set at 1 ×
10-5 and 250 runs were performed with real data. NMS has an advantages over other
ordination methods as it can be used with a variety of distance measures, for example,
Euclidean, Sørenson and Jaccard, and is less affected by quadratic distortions or arch
effects (Peck, 2010). Mean soil moisture, soil temperature and canopy were then
calculated from the ten sampled logs at each site and compared to the NMS ordination of
taxon composition in PC-ORD. R-squared and tau values were used to quantitatively
evaluate the fit of the data with each axis.
2.6 Specimen selection for DNA analysis
After the sorting of specimens a pivot table was constructed in Microsoft Excel 2011 to
calculate the distribution and abundance of each taxon per site. From this initial
visualization, pairs of 15 taxa that had the highest abundance and presence per site were
selected for an initial round of DNA analysis. Of the 15 taxa, mitochondrial DNA for
nine was successfully amplified and sequenced.
2.7 DNA analysis
Pairs of specimens that were the most geographically separate (east and west of the
peninsula) were selected for DNA analysis for each of the 15 most widespread and
abundant taxa. The target gene for all genetic analysis was the mitochondrial gene, COI,
which was amplified by polymerase chain reaction (PCR) for each specimen. For
Cambridgea quadromaculata (Stiphidiidae) (Blest & Taylor, 1995), Mamoea pilosa
(Amphinectidae) (Bryant, 1935), Maniho ngaitahu (Amphinectidae) (Forster & Wilton,
1973), N. janus, P. antipodiana, Uliodon albopunctatus (Zoropsidae) (Koch, 1873),
Pleioplectron sp. (Rhaphidophoroidae) (Richards, 1959) and Megalopsalis sp.
21
(Monoscutidae) (Roewer, 1923) DNA was extracted from two hind legs by removing and
crushing the legs in a 200µl microcentrifuge tube. In cases of small specimens, such as
juveniles, three legs were used, as two may not have contained enough DNA for
amplification. For ‘flatworm4’ (Platyhelminthes: Tricladida) specimens the uppermost
layer of anterior skin was removed from the middle of the specimen using a scalpel. All
DNA extractions were conducted by following the tissue protocols of the Qiagean®
DNeasy™ blood and tissue Kit (Auckland, catalog #69504).
The forward primer LC01490: 5’-GGTCAACAAATCATAAAGATATTGG-3’
(Folmer et al., 1994) and the reverse primer HC02198: 5’TAAACTTCAGGGTGACCAAAAAATCA-3’ (Folmer et al., 1994) were used for C.
quadromaculata, P. antipodiana, Pleioplectron sp., Megalopsalis sp. and ‘flatworm4’
resulting in a 658bp fragment of the CO1 gene. For spiders M. pilosa, M. ngaitahu, N.
janus and U. albopunctatus forward primer C1-J-1718-spider (5’GGNGGATTTGGAAATTGRT- TRGTTCC-3’) (Vink et al., 2005)and reverse primer
C1-N-2776-spider (5’-GGATAAT- CAGAATANCGNCGAGG-3’) (Vink et al., 2005)
was used resulting in a 700bp fragment of COI.
For all specimens, COI amplification was carried out in a total volume of 12µl,
containing 3µl of DNA template, 1.6 µl H2O, 0.4µl MgCl2 at 10mM concentration, 0.5µl
of each primer at 10 mM concentraion, and 6µl of GoTaq® Green Master Mix (Promega,
Madison, WI, USA). All PCRs included a negative control (H2O). The thermocycle
parameters for the PCR process were an initial denaturation of 94°C for 2 minutes
followed by 40 cycles of 15 seconds at 94°C for denaturation, 30 seconds at 49°C for
annealing, and 30 seconds at 72°C for elongation, with a final elongation of 7 minutes at
72°C. All PCR products were run through a 1.5% agarose electrophoresis gel and
visualized under an ultraviolet light. PCR products that were successfully amplified for
both specimens (9 of the 15 taxa) were then sequenced.
Sequencing PCR was carried out in both 3’ and 5’ directions in a 10µl eppendorf tube
consisting of 0.5µl PCR product, 0.8µl of forward and reverse primer at 10mM
concentration, 2.0µl BigDye® Sequencing buffer (v 1.1/3.1), and 0.5µl BigDye®
Terminator (v3.1) (Applied Biosystems®). The profile used in the PCR machine was 1
cycle of 96°C (1minute), 25 cycles of 96°C (10 s), 50°C (5 s) and 60°C (4 min) and a
final cycle of 60° C (1minute) and extension of 4°C. The resulting product was then run
22
on an AVANT 3100 (ABI) sequencer at the Lincoln University sequencing facility,
located within the Bio-Protection Research Centre, Lincoln University, New Zealand.
For all specimens, the resulting chromatograms for the reverse and forward primers
were manually checked in FinchTV 1.4.0. (Geospiza, Inc.; Seattle, WA, USA;
http://www.geospiza.com). Chromatograms from the reverse primers were reverse
complemented then both pairs were cut and pasted into the program Molecular
Evolutionary Genetic Analysis (MEGA) version 5.1. (Tamura et al., 2011) where any
apparent insertions/deletions, residual primer base pairs and codons were checked and
corrected. This process was repeated for pairs of specimens of each species. Final
sequences were aligned, trimmed and compared with sequences on GenBank (Benson et
al., 2010) using the nucleotide Basic Local Alignment Search Tool (BLAST)(Altschul et
al., 1997).
Out of the 15 taxon undergoing analysis, the DNA from nine taxon, with a total
number of 84 specimens, was successfully amplified. These DNA sequences were used to
generate a genetic distance matrix for each taxon using uncorrected pairwise COI
distances with pairwise deletion of missing sites. Despite the fact that the Kimura-2Parametre (K2P) evolutionary distance model, which treats transitional and transvertional
substitutions separately, has been commonly used in most DNA barcoding studies (e.g.
(Robinson et al., 2009), there is no evidence to suggest that this model is better for
specimen identification than simpler metrics such as uncorrected pairwise distances
(Astrin et al., 2006; Collins et al., 2012).
A clustered bar graph of overall mean genetic distance was produced for the 9 taxa.
Limited numbers of sequences were obtained for ‘flatworm4’ due to difficulty in DNA
extraction and amplification, which meant this species was withdrawn from subsequent
phylogeographic analysis that was undertaken on the remaining 8 taxa. Due to budget
constraints MtDNA sequence sample sizes within species were kept at fewer than twelve
sequences per taxon. This was a trade-off that allowed an increase in the number of taxa
that could be included in the DNA analysis. Matrices of mean within/across region
genetic distances and overall mean genetic distance were computed for each of the 8 taxa.
23
random starting tree using a strict clock model with tree prior model set to coalescent:
constant size. The analysis was run for 100 million generations sampling every 1000th
tree. All analyses were repeated four times to confirm that they had converged on the
same results. TreeAnnotator version 1.7.5 (Drummond et al., 2012) was used to construct
maximum clade credibility trees discarding the first 10% of trees generated as burn in.
FigTree version 1.4.0 (Rambaut, 2012) was used to view and save trees in a graphic
format.
To test hypothesis regarding intraspecific divergence, gene genealogies for N. janus
and P. antipodiana were assessed separately for the presence of divergent and
genealogically exclusive clusters that represent independent coalescent processes using
generalised mixed Yule-coalescent (GMYC) species delimitation methods. Maximum
clade credibility trees generated with TreeAnnotator were used as input data for GMYC
models (Pons et al., 2006). Trees were analysed with the package SPLITS (http://rforge.r-project.org/projects/splits/) in the software RStudio (RStudio, 2012), optimising
single and multiple thresholds for the transition from inter- to intraspecific branching
(Fontaneto et al., 2007; Pons et al., 2006). Finally, GenGIS 2.1.0 (Parks et al., 2009) was
used to produce geophylogenies for species N. janus and P. antipodiana.
26
Chapter 3
3
Results
3.1 Patterns in taxon composition
A total of 2,499 specimens belonging to 171 different taxa were collected during
fieldwork. The NMS ordination revealed an apparent separation in taxon composition
between east and west sites. NMS resulted in a 3 dimensional optimum solution. Final
stress value was 10.146 after 249 iterations, which is within the 10–20 range commonly
observed for ecological community data sets (McCune et al., 2002). The final stress was
unlikely to have been obtained by chance as p = 0.004. Axis 1v3 of the NMS ordination
showed a slight separation of taxon composition between east and west sites, while axes
1v2 and 2v3 showed no separation (Figure 3).
Figure 3: Non-metric multidimensional scaling ordination of taxon composition at 22 east and
west sites on Banks Peninsula. Blue dots represent western sites and red dots represent eastern
sites.
27
Along with NMS ordination mean environmental variables per site such as soil
temperature, canopy cover and soil temperature were calculated. Their standard
deviation, minimum and maximum values for 22 sites are presented below (Table 1, Table
2 and Table 3).
Table 1: Mean, standard deviation and min/max ground soil moisture for 22 sites on Banks
Peninsula.
Site
sgl1
sgl2
knd1
knd2
omh1
ahr1
ktu1
okt1
mgm1
wnu1
hyr1
thp1
otp1
rbn1
ellg1
lbe1
hnw1
hnw2
trt1
kyh1
npm1
tka1
Location Mean moisture (%) Stdv moisture (%) Min moisture (%) Max moisture (%)
west
79.7
2.79
75
86
west
79.9
2.66
77
89
west
84
2.22
77
95
west
83.2
3.05
78
96
west
83.95
3.02
75
96
west
85.55
3.01
78
96
west
79.85
3.04
77
85
west
82.4
3.51
78
89
west
83.1
3.47
77
93
west
79.65
3.51
77
89
west
82.35
3.50
77
91
east
81
3.41
77
93
east
85.05
3.41
79
98
east
81.2
2.69
77
87
east
86.65
2.70
93
99
east
79.7
2.66
76
88
east
80.35
2.62
75
90
east
79.95
1.46
77
88
east
86.2
1.50
77
98
east
80.2
2.55
77
85
east
80.05
3.41
76
82
east
79.8
3.92
76
91
Table 2: Mean, standard deviation and min/max soil temperature for 22 sites on Banks Peninsula.
Site
sgl1
sgl2
knd1
knd2
omh1
ahr1
ktu1
okt1
mgm1
wnu1
hyr1
thp1
otp1
rbn1
ellg1
lbe1
hnw1
hnw2
trt1
kyh1
npm1
tka1
Location Mean temperature (C°) Stdv temperature (C°) Min temperature (C°) Max tempertaure (C°)
west
11.635
2.34
8.8
14.8
west
12.105
2.54
9.3
14.6
west
12.51
2.67
6.9
17.9
west
9.93
2.79
3.5
15.6
west
9.19
2.89
8.5
10.4
west
10.955
3.00
10.6
12.4
west
12.035
3.09
7.9
15.8
west
13.91
3.08
11.3
16.8
west
12.86
3.09
9.6
16.1
west
13.55
3.11
10
16.9
west
13.37
3.10
12.3
14.1
east
13.895
3.09
11.7
15.9
east
9.21
3.07
8
10.4
east
12.37
3.09
9.7
14.3
east
8.275
3.12
5.2
11.7
east
12.515
3.07
9.3
14.7
east
11.975
3.04
6.8
17.9
east
10.735
3.00
7.8
13.7
east
12.14
3.00
10.6
13.6
east
13.13
3.01
10.7
16.2
east
16.235
3.01
13
18.8
east
14.085
2.85
10.2
17.9
28
Table 3: Mean, standard deviation and min/max canopy cover for 22 sites on Banks Peninsula. .
Site
sgl1
sgl2
knd1
knd2
omh1
ahr1
ktu1
okt1
mgm1
wnu1
hyr1
thp1
otp1
rbn1
ellg1
lbe1
hnw1
hnw2
trt1
kyh1
npm1
tka1
Location Mean canopy cover (%) Stdv canopy cover (%) Min canopy cover (%) Max canopy cover (%)
west
86
9
70
95
west
77
12
50
90
west
79
13
70
95
west
71
14
60
80
west
80
14
70
90
west
80
14
70
90
west
81
13
80
85
west
67
13
60
85
west
75
12
70
85
west
73
12
60
90
west
77
11
60
90
east
78
10
60
95
east
72
10
50
95
east
67
9
60
80
east
64
9
40
80
east
73
9
50
95
east
48
9
15
75
east
69
10
50
70
east
71
11
50
90
east
79
11
70
95
east
63
12
30
75
east
69
12
60
70
R-squared and tau values showed a very weak correlation between taxon composition and
environmental variables soil moisture and canopy cover (Figure 4 and Figure 5). Soil
temperature also showed a very weak correlation except in axis three, which showed a
moderate correlation with taxon composition (Figure 6).
Figure 4: Non-metric multidimensional scaling ordination showing the relationship between soil
moisture and taxon composition. Red line represents the temperature gradient. Blue dots represent
west sites and red dots represent east sites. Ordination data points are sized in proportion to mean
moisture per site.
29
Figure 5: Non-metric multidimensional scaling ordination showing the relationship between
canopy cover and taxon composition. Red line represents the canopy density gradient. Blue dots
represent west sites and red dots represent east sites. Ordination data points are sized in
proportion to mean percentage of canopy cover per site.
Figure 6: Non-metric multidimensional scaling ordination showing the relationship between soil
temperature and taxon composition. Red line represents the temperature gradient. Blue dots
represent west sites and red dots represent east sites. Ordination data points are sized in
proportion to mean percentage of canopy cover per site.
30
3.2 DNA analysis of taxa
Out of 171 taxa, 15 were selected for DNA analysis based on specimen abundance and
presence across sites (Table 4). Of those 15 taxa, DNA from nine taxa was successfully
amplified and sequenced (Table 5).
Table 4:Taxonomic information for 15 taxa selected for initial DNA analysis.
Taxa reference
beetle1
spider2
centipede1
earthworm6
flatworm4
spider1
spider55
harvestman2
millipede1
millipede2
spider58
caveweta1
spider21
slater1
spider33
Phylum
Arthropoda
Arthropoda
Arthropoda
Annelida
Platyhelminthes
Arthropoda
Arthropoda
Arthropoda
Arthropoda
Arthropoda
Arthropoda
Arthropoda
Arthropoda
Arthropoda
Arthropoda
Subphylum
Hexapoda
Myriapoda
Arthropoda
Arthropoda
Myriapoda
Myriapoda
Arthropoda
Hexapoda
Arthropoda
Arthropoda
Class
Insecta
Arachnida
Chilopoda
Oligochaeta
Turbellaria
Arachnida
Arachnida
Arachnida
Diplopoda
Diplopoda
Arachnida
Insecta
Arachnida
Crustacea
Arachnida
Order
Coleoptera
Araneae
Suborder
Megadrilacea
Tricladida
Araneae
Araneae
Family
Genus
Species
Stiphidiidae
Cambridgea
quadromaculata
Amphinectidae
Amphinectidae
Mamoea
Maniho
pilosa
ngaitahu
Opiliones
Araneae
Orthoptera
Araneae
Isopoda
Araneae
Agelenidae
Neoramia
janus
Ensifera
Rhaphidophoroidae Pleioplectron
Mygalomorphae Hexathelidae
Porrothele
antipodiana
Zoropsidae
Uliodon
albopunctatus
5
2
13 1
8
1
7
2
6
3
1
5
6
1
5
2
2
3
4
1
8
2
10 1
1 11
3
7
1
4
6
1
4
1
11
3
1
9
3
19 134 19
1
1
2
4
1
1
3
3
9
1
1
1
1
1
1
11
2
1
21
4
5
6
8
1
5
4
2
15 5
3
18 4
6
2 12
15 8
3
3 17
6
3
17
9
4
7
3
6
2
1
9
5
1
2
2
5
2 15 3
4
4
6
2
4
6
72 152 50
1
4
3
1
2
1
1
13
1
4
1
1
5
1
3
1
2
1
2
7
1
10
1
1
1
2
1
2
1
2
2
1
29
1
46
3
3
1
1
11
6
2
1
3
4
3
6
4
1
5
1
49
2
1
2
3
3
13
1
1
11
6
12
3
1
1
60
1
1
9
2
5
3
1
5
2
1
6
1
5
1
5
2
50
U. albopunctatus
slater1
P. antiposiana
1
2
4
3
3
1
Pleioplectron sp.
millipede1
Megalopsalis sp.
M. ngaitahu
M. Pilosa
flatworm4
earthworm6
centipede1
3
N. janus
1
1
millipede2
Sites
sglT
sglL
knd1
knd2
omh
ahr
ktu
okt
mgm
wnu
hyr
thp
otp
rbn
ellg
lbe
hnw1
hnw2
trt
kyh
npm
tka
Total
C. quadromaculata
beetle1
Table 5: Nine out of 15 taxa selected for DNA analysis and their abundance (number of
individuals) at each site. Specimens selected for sequencing are highlighted in grey.
5
5
9
11
3
2
3
6
4
7
5
5
2
2
5
50
31
The success of DNA amplification and sequencing varied among specimens. This meant
that the number of sequences from sites east and west of the peninsula, and the length of
COI fragment available for calculating divergence differed among taxa (Table 6). DNA
amplification for ‘flatworm4’ proved to be the least successful with only two west and
one east specimen successfully sequenced. Pleioplectron sp. was also problematic; only
specimens from three west and five east sites were sequenced. DNA amplification was
most successful for P. antipodiana and N. janus with six sequences from six sites, east
and west, being produced. These species were therefore chosen for intraspecific
phylogeographic analysis and underwent continued DNA amplification and sequencing
of specimens (Table 7).
Table 6: Nine out of fifteen specimens successfully amplified during initial DNA analysis, their
DNA fragment length and over all mean genetic divergence (uncorrelated p distance).
Specimen
Sequences (west) Sites (west) Sequences (east) Sites (east)
Fragement length (bp) Divergence (%) Standard deviation
C. quadromaculata
5
5
6
5
614
1.5
0.003
flatworm4
2
2
1
1
677
3.6
0.006
M. ngaitahu
5
4
4
4
662
2.5
0.003
M. pilosa
5
4
4
4
773
0.9
0.002
Megalopsalis sp.
5
5
5
5
628
1
0.002
N. janus
6
6
6
6
454
3.8
0.007
P. antipodiana
6
6
6
6
562
5.2
0.007
Pleioplectron sp.
3
3
7
5
559
4.7
0.005
U. albopunctatus
7
5
5
4
611
0.1
0
beetle1
-
-
-
-
-
-
-
centipede1
-
-
-
-
-
-
-
earthworm6
-
-
-
-
-
-
-
millipede1
-
-
-
-
-
-
-
millipede2
-
-
-
-
-
-
-
slater1
-
-
-
-
-
-
-
32
(east/otp) to a maximum of 9.0% (centre/otp), and within cluster divergence minimum of
0.1% (centre) to 1% (west) (Table 9).
Table 8: Within and between group divergence (uncorrelated pairwise distance) for N. janus. The
names East and West are clusters that are made up of specimen sequences primarily collected
from east or west sites on Banks Peninsula. The cluster mixture contains specimens from both
east and west sites.
Cluster
Within divergence (%) Clusters
Between divergence (%)
West
0.1 West-East
4.3
East
0.1 West-Mixture
4.4
Mixture
0.5 Mixture-East
6
Table 9: Within and between group divergence (uncorrelated pairwise distance) for P.
antipodiana. The names east and west are clusters that are made up of specimen sequences
primarily collected from those locations on Banks Peninsula. The name Opt refers specimens
sequences collected from Otepatotu Scenic Reserve and Centre refers to sequences collected from
sites that are centrally located between east and west sites.
Cluster
Within divergence (%) Clusters
Between divergence (%)
East
0.7 East-Otp
Opt
0.4 East-West
7.1
1 Otp-West
7.5
0.1 East-Centre
8.4
Otp-Centre
9
West
Centre
West-Centre
5
7.5
GMYC analysis produced log lineage through time plots for N. janus (Figure 11) and P.
antipodiana (Figure 13) that showed an apparent increase in lineage accumulation with a
sharp increase in diversification rate toward the present. Phylogeny and GMYC models
for N. janus revealed three reciprocal monophyletic clusters (Kizirian & Donnelly, 2004)
(Figure 12). The analysis was represented by three ML clusters (confidence interval (CI)
3-6) and three ML entities (CI = 3-13) with p value = 0.213.
37
Chapter 4
4
Discussion
Comparative phylogeography was used to compare mtDNA phylogenies across multiple
co-distributed ground-dwelling invertebrate taxa to identify common patterns of
phylogeographic structure on Banks Peninsula. Community composition was also
analysed and compared to the comparative analysis to see if compositional patterns at the
community level mirrored the patterns observed in phylogeographic structure. Stemming
from the comparative phylogeography was a more in depth intraspecific phylogeography
analysis of species N. janus and P. antipodiana. This was done to evaluate the extent of
mtDNA divergence and intraspecific phylogeography of these species on Banks
Peninsula. All findings are discussed in the context of their implications for conservation
management and future research on Banks Peninsula.
4.1 Comparative phylogeography and community composition
The most consistent and dominant feature of the comparative phylogeography among
ground-dwelling invertebrate taxa was a longitudinal phylogeographic split between east
and west sites on Banks Peninsula. Unrooted phylogeographic networks for seven out of
eight invertebrate taxa showed a congruent pattern of a phylogeographic split that occurs
near the centrally located sites of Wainui and Montgomery Scenic Reserves, of which
could be placed either east or west regions of the split. These phylogeographic patterns
reveal that taxa have undergone local adaptation (Kawecki & Ebert, 2004; Williams,
1966). This is because the genotypes from invertebrates found in the eastern side of the
peninsula have a higher chance of survival in this region than the genotypes of
invertebrate found in the western side of the peninsula, and vice versa. This suggests that
invertebrate taxa within each of these areas have been subjected to the same long term
isolating events and a lack of gene flow between eastern and western sites, which has
resulted in phylogeographically independent regions on Banks Peninsula.
These results are largely in agreement with previous phylogeography research of a
40
carabid beetle on Banks Peninsula (Wiseman et al., unpubl.), which showed evidence of a
phylogeographic split on Banks Peninsula. The are also similar to findings that have been
reported on a biogeographical scale among multiple species in the Baja California
Peninsula Desert (Riddle et al., 2000) where comparative phylogeography found support
for previously hypothesised vicariance events and concluded that the peninsula could be
considered a separate regional desert with its own unique evolutionary history. Also, in
the wet tropic rainforests of Australia, comparisons of phylogeographic structure among
endemic vertebrates showed similar patterns of vicariant population differentiation on
either side of a previously identified biogeographic break (Schneider et al., 1998). These
studies emphasize how a phylogeographic split among co-distributed taxa, such as
ground-dwelling invertebrates, could be evidence of vicariance on Banks Peninsula with
east and west regions being separate having there own evolutionary history.
NMS ordination analysis found a geographic differentiation of taxon composition
between east and west sites on Banks Peninsula. Environmental variables, however,
showed no relationship to any east/west geographic differentiation of taxon composition.
Environmental variables also showed a very weak correlation with taxon composition
except on axis three for soil temperature, which had moderate correlation with taxon
composition. In a study by Moritz and Faith (1998), comparative phylogeography
analysis of vertebrates resident to the wet tropic rainforests of Australia were compared
to biodiversity assessments based on the distribution of endemic vertebrate species. They
found discrepancies between interspecific phylogeographies and the concentration of
endemic species across sites and concluded that the genetic vs. species approaches
produced different assessments of areas that were of conservation priority. Banks
Peninsula however showed no such discrepancy as congruent phylogeographic patterns
of an east/west split among invertebrate taxa could also be seen within invertebrate taxa
composition. The two approaches, genetic vs. species, collectively form a relatively
robust evaluation and suggest that the split is a relatively common pattern among grounddwelling invertebrates at the genetic level, which extends to the community level.
41
4.2 Intraspecific phylogeography: N. janus and P. antipodiana
GMYC analysis, phylogeny and mtDNA divergence for N. janus and P. antipodiana
recognised a number of divergent and genealogically exclusive clusters on Banks
Peninsula. They suggests that N. janus and P. antipodiana may contain previously
undiscovered cryptic species, in accordance with definitions of cryptic species by
Bickford et al (2007) and the phylogenetic species concepts (Cracraft, 1989; Queiroz &
Donoghue, 1988).
GMYC analysis for both N. janus and P. antipodiana failed to reject the null models
(p>0.05). This means that there are not different branching rates within models and that
clusters within models represent different species. However, this does not suggest that
each GMYC models represents a single species either, as confidence intervals show there
are 3-6 clusters within N. janus and 2-11 clusters within P. antipodiana. The most likely
reason for failure to reject the null is under-sampling within species as small samples per
species weaken the power to detect new species.
For N. janus, phylogeny branch lengths and posterior probabilities (PP= 0.719)
suggest that among three clusters there is questionable phylogenetic signal putting any
two clusters together as sister taxa relative to the third. These results suggest there are
three putative reciprocally monophyletic clusters within the phylogeny potentially
corresponding to previously undescribed cryptic species (Figure 12). This is supported by
between-cluster divergence being greater than maximum within cluster divergence (Table
8), and the geophylogeny which revealed an extent of phylogeographic separation of
clusters located east and west of Banks Peninsula (Figure 9).
For P. antipodiana, branch lengths and posterior probabilities (PP= 0.562) suggest that
among four clusters there is little phylogenetic signal putting any three clusters together
as sister taxa relative to the fourth. These results suggest there are four reciprocal
monophyletic clusters within the phylogeny that there may be four previously
undescribed cryptic species (Figure 14). Again this is strengthened by between-cluster
divergence being greater than maximum within cluster divergence (Table 9) and the
geophylogeny revealing strong phylogeographic separation of clusters confined to
discrete geographic boundaries located east, west, centre and Otepatotu Scenic Reserve
on Banks peninsula (Figure 10). Other mygalomorph spiders such as Aptostichus simus
42
(Bond et al., 2001), and Hadronyche atrax (Beavis et al., 2006) share similar mtDNA
divergence phylogeographic subdivision with P. antipodiana. Mygalomorph species such
as Antrodiaetus riversi (Starrett & Hedin, 2007) and Antrodiaetus unicolor (Hendrixson
& Bond, 2005) have also exhibited considerable molecular divergence suggesting they
contain cryptic species. Being mygalomorphs these species share similar life history
characteristics with P. antipodiana (e.g., limited dispersal capabilities (Forster & Wilton,
1967)) which makes their populations prone to phylogeographical splits and reinforces
that cryptic species complex is common to the infraorder Mygalomorphae (Hamilton et
al., 2011).
Overall, mean genetic divergence values for N. janus (3.7%, uncorrelated p-distance)
and P. antipodiana (5.1%) (Table 7) were high for intraspecific data. They surpass more
than the average maximum intraspecific divergence of 3.16% (K2P-distance) observed in
other spiders (Robinson et al. 2009) and exceeds what has been reported in the literature
for population level studies, for example Vogler et al (1993). In previous studies the
genetic species concept (Dobzhansky, 1950; Mayr & Ashlock, 1969; Simpson, 1943) has
been applied to taxa displaying 4% divergence (Holder et al., 1999) and established
genetic distances of mtDNA between 2 – 11 per cent as being indicative of separate
species that warrant further investigation into their specific status (Ballard et al., 2002;
Bradley & Baker, 2001). MtDNA divergence, however, has been said to be unsuitable for
recognizing species boundaries (Moritz & Cicero, 2004; Wheeler, 2004) and acts only act
as a starting point, identifying species that need further genetic research (Hebert &
Gregory, 2005; Smith et al., 2005).
4.3 Explanations of phylogeography for P. antipodiana
High divergence and phylogeographic clustering of P. antipodiana may be related to
species traits and paleoenvironmental vicariance events on Banks Peninsula.
Other research suggest that glacial and interglacial climate variations on Banks
Peninsula were mirrored by variations in dominant tree species with tall forest tree
species surviving in favourable niches during cooler phases and later recolonizing when
conditions were warmer (Soons et al., 2002). It is also possible that vegetation on Banks
Peninsula could have acted as refugia for invertebrate species during glaciations of the
43
Pleistocene (Buckley et al., 2010; Marra, 2007). Because mygalomorph spider species are
susceptible to desiccation due to their two pairs of book lungs, which present a large
surface area for water-loss (Foelix, 1982; Levi, 1967; Schmitz & Perry, 2000), the
geographic range of P. antipodiana could be intrinsically linked to climate and associated
with overall patterns of forestation. During glaciations, if conditions became drier, cooler
and forests fragmented, populations of P. antipodiana could probably only persist in
forest refugia and become geographically isolated. The dispersal ability of P. antipodiana
is also rather restricted (Forster & Wilton, 1967). Mygalomorph spiders seldom disperse
by ballooning (Coyle, 1983; Main, 1982) and usually juveniles do not walk far so
populations are highly clumped (Coddington, 2005).
The above suggests that P. antipodiana may be particularly prone to population
divergence and cryptic species complex. Temporal isolation and a lack of gene flow
between phylogeographic clusters of P.antipodiana (Bond et al., 2001; Bond & Sierwald,
2002) may have resulted in local adaptation (Kawecki & Ebert, 2004; Williams, 1966)
and explains how clusters gradually became separated from one another genetically,
isolated by distance into the present pattern of phylogeography.
4.4 Genetic and morphological decoupling
According to Eberhard (1996; 1985), animal genitalia evolve rapidly and divergently as a
result of sexual selection by female choice. Under this assumption, molecular and
morphological divergence may be aligned, thus monophyletci clusters of N. janus and P.
antipodiana under different evolutionary paths could exhibit divergent genital
morphology. Previous taxonomy of N. janus and P. antipodiana classifies them both as
single species because they are morphologically invariant (Paquin et al., 2010). In this
study no morphological divergence analysis was undertaken between monophyletic
clusters for these species, and half the genitalia identified for N. janus were from subadult specimens with immature reproductive structures. However, an examination of
genital morphology was conducted for P. antipodiana during identification, and all
specimens exhibited morphologically similar genitalia. For this species, reciprocal
monophyly and extreme genetic divergence of clusters may have occurred in the absence
of obvious changes in genital morphology. These findings agree with other research
44
regarding the decoupling of monophyletic cluster divergence from genital morphology in
the mygalomorph spider, Aptostichus simus (Bond et al., 2001). This suggests that
morphological species concepts that rely on spider genital morphological characteristics
may underestimate true evolutionary diversity.
4.5 Implications for conservation
This research emphasises the utility of using genetic and community level assessments, in
combination, to identify patterns of diversity among multiple co-distributed invertebrate
taxa on Banks Peninsula. Both assessments, genetic vs. community, demonstrate a
pattern of an east/west geographic separation among invertebrates that lead to similar
conclusions regarding conservation management. This shared pattern suggests that
ground-dwelling invertebrates on Banks Peninsula have a long-standing association with
one another and have responded in a concerted fashion to vicariance events and the
biogeographical history of the region. This has implications for conservation
management and denotes how conservation priorities and strategies are implemented at
the landscape level. Both assessments provide a rational for implementing and guiding
multifaceted conservation action plans aimed at protecting genetic diversity while also
ensuring the conservation of community level diversity. Such action plans may
distinguish east and west as discrete conservational regions and look to protect
independent areas within regions. Extensive translocations or restoration projects that
move species between these regions may result in erosion of the invertebrate genetic or
community diversity of regions that are now recognised to be generated and maintained
by geographical isolation. Conservation initiatives could designate regional biological
reserves in regions and introduce protocols or limitations on the artificial transplantation
of populations or species between regions. This is primarily relevant to long-term
conservation management strategies and provides a rationale for establishing the east and
west as discrete regions of the peninsula that have distinct priorities for conservation
management.
Intraspecific phylogeographic findings from this research could be used to identify
MUs and ESUs within certain taxa. With the genetic component of biodiversity being
explicitly acknowledged in the Resource Management Act 1991 (RMA) in section 7(d)
45
and the United Nations Convention on Biological Diversity (UNCBD) in article 1, MUs
and ESUs have become increasingly relevant for conservation management and provide a
means of incorporating the spatial information on genetic diversity into regional
biodiversity management schemes (Moritz & Faith, 1998).
Overall mean genetic distance for Pleioplectron sp. (4.7%), ‘flatworm4’ and M.
ngaitahu (2.5%) (Table 6) is comparatively high and is indicative of lineages within these
taxa being worthy of MU status (Moritz, 1994). Unrooted phylogenetic networks for
Pleioplectron sp. and M. ngaitahu showed that these taxa might have evolutionarily
independent phylogroups located at opposite sides, east and west, of Banks Peninsula.
These phylogroups may therefore warrant protection as distinct MUs (Moritz, 1994;
Soltis & Gitzendanner, 1999) and could be considered as logical units for population
monitoring, and future molecular and demographic studies.
In accordance with definitions by Ryder (1986) and partial fulfilment of Moritz
(1994), this research was able establish ESUs within species N. janus and P. antipodiana.
ESU designation was based on mtDNA divergences and phylogeographic clusters within
species showing historical isolation (Avise, 2000; Moritz, 1994). For N. janus three
putative ESUs could be established while P. antipodiana could be designated as four
separate ESUs. ESUs are not equivalent to biological species (Nichols, 2001); however,
phylogeographic separation of clusters does suggest that ESUs within N. janus and P.
antipodiana are likely to be historically isolated, have distinct evolutionary histories and
are therefore key sources of genetic diversity within species. The identification of ESUs
has implications for the conservation management for these species. Because each ESU
within N. janus and P. antipodiana contains unique genetic variation, conservation
management that aims to maintain all genetic diversity of these species could mix genetic
variation between ESUs to obtain optimal genetic diversity of the species.
4.6 Limitations and future research
This research had certain limitations; interspecific phylogeographic analysis primarily
consisted of taxa belonging to order Araneae because mtDNA amplification for other
taxa from other orders proved more difficult and time consuming. Future research would
do well to incorporate a preliminary study to establish protocols and methods of mtDNA
46
amplification for a variety of orders. This would ultimately allow more taxa to be
analysed and compared, improving hypotheses regarding the commonality of
phylogeographic patterns in invertebrates. All analysis in this research was based on
specimens of ground-dwelling invertebrates therefore conclusions regarding geographic
separation of diversity and conservation management may not apply to invertebrates
whom do not occupy the saproxylic environment.
Findings from this study are considered a step towards understanding patterns of
invertebrate phylogeography on Banks Peninsula. Phylogeography analysis provides a
historical framework when interpreting existing distribution and diversity on
invertebrates on Banks Peninsula and acts as a guide for future evolutionary or
community ecology studies. For example, further research could focus on undertaking
additional molecular studies on invertebrates of limited vagility and/or that are saproxylic
in additional areas of Banks Peninsula. This could elaborate on the extent, boundary and
trajectory of historical invertebrate phylogeography patterns and colonization. Studies
should also focus on nuclear DNA, morphological taxonomy or ecology of ground
dwelling invertebrates (particularly N. janus and P. antipodiana). This would strengthen
ESU designations, help uncover the genetic changes associated with speciation and
provide a link between the genetics of population divergence and the speciation
processes. Future research at the community level could look more in-depth at species
composition on Banks Peninsula undertaking a more rigorous sampling method
extending the sampling unit beyond saproxylic invertebrates to include soil or tree
dwelling invertebrates. These studies could investigate the implications of species
composition patterns on ecosystem functioning, such as decomposition rates or trophic
interactions on Banks Peninsula.
4.7 Conclusion
The primary aim of this study was to investigate patterns of a geographic split, east and
west, in genetic variation among log-dwelling invertebrates on Banks Peninsula, New
Zealand. Comparative phylogeography found evidence for a relatively common
phylogeographic split among multiple co-distributed log-dwelling invertebrates. This
split could also be seen within species composition of the invertebrate communities.
47
These findings recognise that ground-dwelling invertebrates within the eastern and
western areas of the peninsula could be on different evolutionary trajectories and
identifies these areas as potentially phylogeographic independent regions. However, this
could be disrupted by human activities, such as farming and logging, which alter
landscapes and ecological processes on Banks Peninsula. Because genetic diversity of
invertebrates on Banks Peninsula has been historically maintained in isolation in eastern
and western areas of the peninsula conservation strategies at the landscape level should
treat these areas as independent regions to conserve genetic and community level
diversity.
Intraspecific phylogeographic analysis in this study represents the most accurate and
up to date account of the genetic lineages for species N. janus and P. antipodiana on
Banks peninsula. Genetic analysis indicates that current populations of both species are
diverging and may represent cryptic species that occupy different locations of Banks
Peninsula. As this divergence may represent the early stages of allopatric speciation,
these taxa are worthy of further investigation as potential case studies for speciation
research. P. antipodiana has the highest divergences and clearest phylogeographic
clustering of all taxa studied, with apparent absence of morphological differentiation
among specimens this species is therefore particularly worthy of attention. Intraspecific
analysis established MUs and ESUs for invertebrate conservation management, which
could be used to inform and improve efforts to conserve and promote invertebrate genetic
diversity on Banks Peninsula.
48
Appendix
Table 1: Uncorrelated pairwise genetic distance for ‘flatworm4’.
1 4flatworm33
2 4flatworm34
3 4flatworm67
1
2
0.046
0.048
0.014
Table 2: Uncorrelated pairwise genetic distance for C. quadromaculata.
1
2
3
4
5
6
7
8
9
10
11
C.quadromaculata3
C.quadromaculata4
C.quadromaculata88
C.quadromaculata93
C.quadromaculata100
C.quadromaculata102
C.quadromaculata91
C.quadromaculata197
C.quadromaculata198
C.quadromaculata207
C.quadromaculata208
1
2
3
4
5
6
7
8
9
10
0.008
0.008
0.008
0.002
0.002
0.023
0.020
0.013
0.021
0.008
0.003
0.010
0.010
0.010
0.024
0.021
0.011
0.023
0.010
0.010
0.010
0.010
0.024
0.021
0.011
0.023
0.010
0.010
0.010
0.024
0.021
0.015
0.023
0.000
0.003
0.024
0.021
0.015
0.023
0.010
0.024
0.021
0.015
0.023
0.010
0.010
0.023
0.005
0.024
0.023
0.008
0.021
0.021
0.015
0.023
Table 3: Uncorrelated pairwise genetic distance for M. ngaitahu.
1
2
3
4
5
6
7
8
9
M.ngaitahu135
M.ngaitahu138
M.ngaitahu139
M.ngaitahu137
M.ngaitahu192
M.ngaitahu193
M.ngaitahu191
M.ngaitahu199
M.ngaitahu200
1
2
3
4
5
6
7
8
0.023
0.010
0.044
0.021
0.019
0.025
0.009
0.010
0.027
0.049
0.003
0.012
0.001
0.027
0.026
0.047
0.025
0.023
0.028
0.017
0.018
0.047
0.043
0.048
0.049
0.050
0.009
0.004
0.026
0.025
0.013
0.025
0.023
0.028
0.027
0.001
Table 4: Uncorrelated pairwise genetic distance for M. pilosa.
1
2
3
4
5
6
7
8
9
M.pilosa9
M.pilosa10
M.pilosa116
M.pilosa117
M.pilosa120
M.pilosa121
M.pilosa205
M.pilosa206
M.pilosa133
1
2
3
4
5
6
7
8
0.008
0.002
0.011
0.005
0.012
0.012
0.011
0.002
0.009
0.006
0.003
0.008
0.011
0.006
0.009
0.012
0.006
0.014
0.014
0.012
0.000
0.006
0.011
0.017
0.009
0.012
0.011
0.014
0.009
0.006
0.012
0.002
0.014
0.011
0.014
0.012
49
Table 5: Uncorrelated pairwise genetic distance for Megalopsalis sp.
1
2
3
4
5
6
7
8
9
10
Megalopsalis sp.1
Megalopsalis sp.2
Megalopsalis sp.104
Megalopsalis sp.105
Megalopsalis sp.106
Megalopsalis sp.109
Megalopsalis sp.184
Megalopsalis sp.203
Megalopsalis sp.204
Megalopsalis sp.196
1
2
3
4
5
6
7
8
9
0.006
0.002
0.006
0.002
0.014
0.006
0.010
0.019
0.005
0.008
0.000
0.008
0.013
0.000
0.010
0.021
0.002
0.008
0.003
0.016
0.008
0.011
0.021
0.006
0.008
0.013
0.000
0.010
0.021
0.002
0.016
0.008
0.008
0.018
0.006
0.013
0.018
0.030
0.011
0.010
0.021
0.002
0.013
0.008
0.021
Table 6: Uncorrelated pairwise genetic distance for U. albopunctatus.
1
2
3
4
5
6
7
8
9
10
11
12
U.albopunctatus8
U.albopunctatus7
U.albopunctatus130
U.albopunctatus129
U.albopunctatus128
U.albopunctatus127
U.albopunctatus126
U.albopunctatus124
U.albopunctatus123
U.albopunctatus122
U.albopunctatus209
U.albopunctatus210
1
2
3
4
5
6
7
8
9
10
11
0.002
0.002
0.002
0.002
0.002
0.002
0.003
0.002
0.002
0.002
0.002
0.000
0.000
0.000
0.000
0.000
0.002
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.002
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.002
0.000
0.000
0.000
0.000
0.000
0.000
0.002
0.000
0.000
0.000
0.000
0.000
0.002
0.000
0.000
0.000
0.000
0.002
0.000
0.000
0.000
0.000
0.002
0.002
0.002
0.002
0.000
0.000
0.000
0.000
0.000
0.000
50
Table 7: Uncorrelated pairwise genetic distances for N. janus.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
N.janus13
N.janus14
N.janus111
N.janus112
N.janus113
N.janus114
N.janus110
N.janus153
N.janus166
N.janus167
N.janus168
N.janus169
N.janus170
N.janus171
N.janus172
N.janus173
N.janus174
N.janus176
N.janus177
N.janus178
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
0.043
0.046
0.000
0.043
0.043
0.046
0.043
0.046
0.043
0.046
0.000
0.043
0.046
0.043
0.046
0.043
0.043
0.046
0.043
0.003
0.043
0.000
0.000
0.065
0.000
0.060
0.063
0.057
0.043
0.063
0.065
0.000
0.065
0.000
0.000
0.065
0.000
0.046
0.003
0.003
0.068
0.003
0.063
0.065
0.060
0.046
0.065
0.068
0.003
0.068
0.003
0.003
0.068
0.003
0.043
0.043
0.046
0.043
0.046
0.043
0.046
0.000
0.043
0.046
0.043
0.046
0.043
0.043
0.046
0.043
0.000
0.065
0.000
0.060
0.063
0.057
0.043
0.063
0.065
0.000
0.065
0.000
0.000
0.065
0.000
0.065
0.000
0.060
0.063
0.057
0.043
0.063
0.065
0.000
0.065
0.000
0.000
0.065
0.000
0.065
0.008
0.003
0.014
0.046
0.003
0.000
0.065
0.000
0.065
0.065
0.000
0.065
0.060
0.063
0.057
0.043
0.063
0.065
0.000
0.065
0.000
0.000
0.065
0.000
0.005
0.016
0.046
0.005
0.008
0.060
0.008
0.060
0.060
0.008
0.060
0.011
0.043
0.000
0.003
0.063
0.003
0.063
0.063
0.003
0.063
0.046
0.011
0.014
0.057
0.014
0.057
0.057
0.014
0.057
0.043
0.046
0.043
0.046
0.043
0.043
0.046
0.043
0.003
0.063
0.003
0.063
0.063
0.003
0.063
0.065
0.000
0.065
0.065
0.000
0.065
0.065
0.000
0.000
0.065
0.000
0.065
0.065
0.000
0.065
0.000
0.065
0.000
0.065
0.000
0.065
Table 8: Uncorrelated pairwise genetic distance for P. antipodiana.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
P.antipodiana141
P.antipodiana143
P.antipodiana144
P.antipodiana145
P.antipodiana146
P.antipodiana147
P.antipodiana148
P.antipodiana149
P.antipodiana140
P.antipodiana155
P.antipodiana157
P.antipodiana158
P.antipodiana160
P.antipodiana161
P.antipodiana163
P.antipodiana164
P.antipodiana180
P.antipodiana181
P.antipodiana182
P.antipodiana142
P.antipodiana5
P.antipodiana6
P.antipodiana76
P.antipodiana72
P.antipodiana77
P.antipodiana82
P.antipodiana83
P.antipodiana84
P.antipodiana86
P.antipodiana71
P.antipodiana47
P.antipodiana175
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
0.044
0.068
0.005
0.084
0.004
0.071
0.002
0.068
0.069
0.071
0.012
0.050
0.084
0.016
0.004
0.073
0.000
0.007
0.073
0.068
0.004
0.077
0.046
0.002
0.068
0.002
0.068
0.073
0.082
0.066
0.068
0.073
0.050
0.089
0.048
0.077
0.046
0.071
0.071
0.075
0.048
0.005
0.089
0.048
0.048
0.078
0.044
0.052
0.077
0.071
0.048
0.082
0.002
0.046
0.073
0.046
0.073
0.077
0.087
0.071
0.071
0.068
0.077
0.069
0.016
0.068
0.002
0.011
0.005
0.071
0.075
0.077
0.071
0.069
0.018
0.068
0.069
0.007
0.002
0.066
0.020
0.075
0.068
0.009
0.066
0.009
0.007
0.075
0.009
0.002
0.082
0.005
0.069
0.004
0.068
0.069
0.071
0.014
0.055
0.082
0.018
0.005
0.071
0.005
0.002
0.073
0.068
0.005
0.075
0.052
0.004
0.068
0.007
0.068
0.073
0.080
0.066
0.068
0.085
0.075
0.084
0.075
0.075
0.073
0.089
0.091
0.000
0.089
0.085
0.077
0.084
0.084
0.075
0.075
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0.085
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0.075
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0.077
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0.069
0.071
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0.053
0.085
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0.007
0.075
0.069
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0.078
0.050
0.002
0.069
0.005
0.069
0.075
0.084
0.068
0.069
0.071
0.014
0.009
0.018
0.077
0.078
0.075
0.077
0.073
0.002
0.071
0.071
0.020
0.014
0.069
0.011
0.078
0.071
0.007
0.069
0.007
0.020
0.073
0.009
0.014
0.068
0.069
0.071
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0.052
0.084
0.014
0.002
0.073
0.002
0.005
0.073
0.068
0.002
0.077
0.048
0.000
0.068
0.004
0.068
0.073
0.082
0.066
0.068
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0.004
0.073
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0.075
0.073
0.069
0.016
0.068
0.069
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0.000
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0.073
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0.069
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0.053
0.089
0.004
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0.078
0.012
0.016
0.075
0.073
0.012
0.082
0.050
0.011
0.073
0.014
0.073
0.075
0.087
0.071
0.073
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0.053
0.080
0.050
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0.078
0.073
0.053
0.084
0.004
0.052
0.075
0.052
0.075
0.078
0.089
0.073
0.073
0.089
0.085
0.077
0.084
0.084
0.075
0.075
0.082
0.078
0.091
0.084
0.075
0.085
0.075
0.075
0.002
0.077
0.075
0.016
0.078
0.016
0.020
0.075
0.073
0.016
0.082
0.050
0.014
0.073
0.018
0.073
0.075
0.087
0.071
0.073
0.075
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0.007
0.075
0.069
0.004
0.078
0.050
0.002
0.069
0.005
0.069
0.075
0.084
0.068
0.069
0.073
0.073
0.021
0.016
0.071
0.012
0.080
0.073
0.009
0.071
0.009
0.021
0.075
0.011
0.016
0.007
0.073
0.068
0.004
0.077
0.046
0.002
0.068
0.002
0.068
0.073
0.082
0.066
0.068
0.075
0.069
0.007
0.077
0.053
0.005
0.069
0.009
0.069
0.075
0.082
0.068
0.069
0.005
0.071
0.023
0.078
0.073
0.012
0.071
0.012
0.000
0.073
0.012
0.005
0.066
0.018
0.073
0.068
0.007
0.066
0.007
0.005
0.073
0.007
0.000
0.075
0.050
0.002
0.066
0.005
0.066
0.071
0.080
0.064
0.066
0.084
0.077
0.011
0.075
0.011
0.023
0.077
0.012
0.018
0.048
0.075
0.048
0.075
0.078
0.089
0.073
0.073
0.068
0.004
0.068
0.073
0.082
0.066
0.068
0.066
0.000
0.012
0.073
0.002
0.007
0.066
0.071
0.084
0.064
0.066
0.012
0.073
0.002
0.007
0.073
0.012
0.005
0.075
0.073
0.007
51
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