Spatial variation in the phylogenetic structure of flea assemblages across geographic ranges of small mammalian hosts in the Palearctic

Mitrani Department of Desert Ecology, Institute for Dryland Environmental Research, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede-Boqer Campus, 84990 Midreshet Ben-Gurion, Israel. Electronic address: .
International journal for parasitology (Impact Factor: 3.87). 06/2013; 43(9). DOI: 10.1016/j.ijpara.2013.05.001
Source: PubMed
ABSTRACT
We investigated spatial variation in the phylogenetic structure (measured as a degree of phylogenetic clustering) of flea assemblages across the geographic ranges of 11 Palearctic species of small mammalian hosts and asked whether the phylogenetic structure of the flea assemblage of a host in a locality is affected by (i) distance of this locality from the centre of the host's geographic range, (ii) geographic position of the locality (distance to the equator) and (iii) phylogenetic structure of the entire flea assemblage of the locality. Our results demonstrated that the key factor underlying spatial variation of the phylogenetic structure of the flea assemblage of a host was the distance from the centre of the host's geographic range. However, the pattern of this spatial variation differed between host species and might be explained by their species-specific immunogenetic and/or distributional patterns. Local flea assemblages may also, to some extent, be shaped by environmental filtering coupled with historical events. In addition, the phylogenetic structure of a local within-host flea assemblage may mirror the phylogenetic structure of the entire across-host flea assemblage in that locality and, thus, be affected by the availability of certain phylogenetic lineages.

Full-text

Available from: Irina S. Khokhlova, Jul 21, 2014
Spatial variation in the phylogenetic structure of flea assemblages across
geographic ranges of small mammalian hosts in the Palearctic
Boris R. Krasnov
a,
, Shai Pilosof
a
, Georgy I. Shenbrot
a
, Irina S. Khokhlova
b
a
Mitrani Department of Desert Ecology, The Swiss Institute for Dryland Environmental and Energy Research, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University
of the Negev, Sede-Boqer Campus, 84990 Midreshet Ben-Gurion, Israel
b
Wyler Department of Dryland Agriculture, French Associates Institute for Agriculture and Biotechnology of Drylands, Jacob Blaustein Institutes for Desert Research,
Ben-Gurion University of the Negev, Sede-Boqer Campus, 84990 Midreshet Ben-Gurion, Israel
article info
Article history:
Received 19 March 2013
Received in revised form 9 May 2013
Accepted 10 May 2013
Available online 4 June 2013
Keywords:
Fleas
Geographic range
Phylogenetic structure
Small mammals
abstract
We investigated spatial variation in the phylogenetic structure (measured as a degree of phylogenetic
clustering) of flea assemblages across the geographic ranges of 11 Palearctic species of small mammalian
hosts and asked whether the phylogenetic structure of the flea assemblage of a host in a locality is
affected by (i) distance of this locality from the centre of the host’s geographic range, (ii) geographic posi-
tion of the locality (distance to the equator) and (iii) phylogenetic structure of the entire flea assemblage
of the locality. Our results demonstrated that the key factor underlying spatial variation of the phyloge-
netic structure of the flea assemblage of a host was the distance from the centre of the host’s geographic
range. However, the pattern of this spatial variation differed between host species and might be
explained by their species-specific immunogenetic and/or distributional patterns. Local flea assemblages
may also, to some extent, be shaped by environmental filtering coupled with historical events. In addi-
tion, the phylogenetic structure of a local within-host flea assemblage may mirror the phylogenetic struc-
ture of the entire across-host flea assemblage in that locality and, thus, be affected by the availability of
certain phylogenetic lineages.
Ó 2013 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.
1. Introduction
Spatial variation in the composition of plant and animal com-
munities is a central theme in ecological biogeography. Thousands
of publications have been dedicated to patterns of spatial variation
in species richness and diversity such as latitudinal gradients (e.g.,
Rohde, 1992), distance decay of similarity (e.g., Nekola and White,
1999) or species–area relationships (e.g., Rosenzweig, 1995). The
vast majority of these studies have dealt with free-living species,
while parasites have received less attention despite forming a large
if not the largest proportion of the diversity of life (Windsor, 1998;
Poulin and Morand, 2000, 2004). Nevertheless, the last decade and
a half has witnessed a burst of studies on spatial patterns in species
diversity and composition in parasite communities (e.g., Poulin
and Morand, 1999; Carney and Dick, 2000; Rohde, 2002; Poulin
and Valtonen, 2002; Poulin, 2003; Calvete et al., 2004; Krasnov
et al., 2005; Oliva and González, 2005; Vinarski et al., 2007;
Pérez-del-Olmo et al., 2009), although some pioneering studies
were carried out earlier (e.g., Kisielewska, 1970; Kennedy and
Bush, 1994). Many spatial patterns found initially for free-living
species have been supported by data on parasites. However, some
parasite-specific patterns have also been revealed due to the inti-
macy of their relationships with their hosts (e.g., Poulin, 2010;
Krasnov et al., 2004, 2012).
Recently, phylogenetic information has started to be introduced
into community ecology and biogeography and has proven to be a
powerful tool allowing better understanding of evolutionary pro-
cesses involved in the assembly of plant and animal communities
and their spatial variation (Webb et al., 2002; Cavender-Bares
et al., 2009; Morlon et al., 2011). Unsurprisingly, the studies com-
bining phylogenetic data with community ecology and biogeogra-
phy have been carried out on free-living species, while the role of
phylogeny in determining spatial variation of parasite assemblages
remains to be studied, although some initial steps have already
been taken (Poulin, 2010; Krasnov et al., 2012).
The species composition of a community in a locality is shaped
by a variety of ecological and evolutionary factors (Vuilleumier and
Simberloff, 1980; Ricklefs, 1987). The parasite assemblage of a par-
ticular host in a particular locality is determined by two main com-
ponents. One part of an assemblage is due to host identity, while
another part is due to the host’s biotic and abiotic environments
(Kennedy and Bush, 1994). Some of the parasite species on a host
may be inherited from its ancestors, whereas other parasites can
switch from other hosts that occupy the same habitat as the focal
host (e.g., Paterson and Gray, 1997). In addition, the abiotic envi-
0020-7519/$36.00 Ó 2013 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.ijpara.2013.05.001
Corresponding author. Tel.: +972 8 6596841; fax: +972 8 6596772.
E-mail address: krasnov@bgu.ac.il (B.R. Krasnov).
International Journal for Parasitology 43 (2013) 763–770
Contents lists available at SciVerse ScienceDirect
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Page 1
ronment may act as a filter that excludes some species from a par-
asite assemblage due to their environmental requirements (Lebri-
ja-Trejos et al., 2010). This is especially important for parasites that
spend some part of their life cycle as free-living (e.g., Krasnov et al.,
2001). Thus, processes that shape the parasite assemblage of a host
in a locality have a historical component (associated with parasites
inherited from ancestors), an abiotic environmental component
(associated with parasites for which the environment offered by
a host is favourable) and a biotic environmental component (asso-
ciated with parasites that switch from co-occurring hosts). Consid-
ering the variation in phylogenetic structure of parasite
assemblages may allow us to disentangle these components and
to identify the predominant force behind assemblage composition.
Here, we investigated spatial variation in the phylogenetic
structure of flea assemblages across the geographic ranges of 11
Palearctic species of small mammalian hosts. Fleas are characteris-
tic insect ectoparasites of small mammals. Imagos of these insects
are holometabolous obligatory haematophages. Their larvae are
usually not parasitic, feed on various kinds of organic matter and
reside in the host’s burrow or nest. Abiotic conditions (tempera-
ture, humidity, and substrate texture) strongly affect the survival,
longevity and reproductive performance of fleas (Krasnov et al.,
2001, 2002a,b). Furthermore, there is a substantial difference in
abiotic environmental preferences among flea species (see Kras-
nov, 2008 for review).
We used a recently proposed index of phylogenetic species
clustering (Helmus et al., 2007; see details below; see Section 2.4)
and asked whether the phylogenetic structure of the flea assem-
blage of a host in a locality is affected by (i) distance of this locality
from the centre of the host’s geographic range, (ii) geographic po-
sition of the locality (that is, latitude; measured as distance to the
equator) and (iii) phylogenetic structure of the entire flea assem-
blage of the locality (that is, flea species recorded on all host spe-
cies inhabiting the locality). The relationships between the
phylogenetic structure of a host’s flea assemblage in a locality
and the centre of the host’s geographic range are likely to reflect
historical processes involved in the shaping of flea assemblages.
In many species, the centre of a geographic range is an area where
a species attains its highest abundance, while abundance decreases
toward the periphery of the range (Hengeveld and Haeck, 1982;
Hengeveld, 1990). Although this pattern is not universal (Sagarin
and Gaines, 2002; Gaston, 2003; Sagarin, 2006), it is rather wide-
spread (Hengeveld, 1990). Among several explanations of the
‘‘abundant-centre’’ hypothesis (e.g., Carson, 1959; Brown, 1984;
Kirkpatrick and Barton, 1997), the most parsimonious one is that
conditions for survival and reproduction are most favourable at
the centre of the range, and become gradually poorer toward the
periphery (Hengeveld, 1990). The decline in abundance away from
the centre of the range is often accompanied with increased patch-
iness and isolation in peripheral populations (Lawton, 1993). Small
and isolated populations of both hosts and parasites may be sub-
jected to random evolutionary forces such as inbreeding and drift
(Holt, 1990), experience genetic bottlenecks (Brussard, 1984) and
thus be characterised by low genetic diversity. We expected that
flea assemblages of peripheral host populations would be more
phylogenetically diverse than those of the central populations be-
cause (i) a host may acquire new parasites from different phyloge-
netic lineages at the periphery of its range (Hoberg and Brooks,
2008a,b), (ii) hosts in isolated populations may be less immuno-
competent than those in the core populations (Whiteman et al.,
2006), and (iii) parasites in the isolated populations may eventu-
ally speciate (Banks and Paterson, 2005).
Relationships between the phylogenetic structure of a host’s
flea assemblage in a locality and its geographic position (distance
to the equator) may mirror environmental processes affecting flea
assemblages. Successful development of pre-imaginal fleas takes
place at air temperatures greater than 10–15 °C but lower than
30 °C, and relative humidities greater than 60% (Marshall, 1981;
Krasnov, 2008). As a result, their geographic distribution in the
Palearctic is characterised by peaks of species richness in the tem-
perate and steppe zones, with a decrease to the north (tundra and
boreal forests) and south (deserts) (Yudin et al., 1976; Medvedev,
1996). Given that the southernmost localities in our study did
not include hyperarid areas and desert host species (Krasnov
et al., 2010; see Section 2), we expected an increase in phylogenetic
clustering of flea assemblages with increasing latitudes because (i)
the occurrence of phylogenetically distant lineages is more proba-
ble in richer assemblages and (ii) environmental filtering may re-
strict flea assemblages in the coldest localities to a certain
phylogenetic subset. The association between phylogenetic struc-
ture of the local flea assemblage of a host with that of the entire
flea community on all flea-supporting host species may be ex-
pected if a host’s flea assemblage represents a random sample from
the surrounding species pool (Krasnov et al., 2004), so that phylo-
genetic structure of within-host assemblages correlates positively
with that of across-host assemblages.
2. Materials and methods
2.1. Selection of data on fleas and small mammals
We used data from our database compiled from published sur-
veys of fleas parasitic on small mammals (Soricomorpha, Erinace-
omorpha, Rodentia and Lagomorpha) across the Palearctic (60
surveys in 52 localities). These surveys reported the number of
fleas of each individual species found on a given number of individ-
uals of each mammalian species. The complete list and geographic
location of surveys can be found elsewhere (Krasnov et al., 2010;
see also Supplementary Fig. S1). We selected host species that
were recorded in at least six localities, harboured at least six flea
species per locality, and for which at least 10 individuals per local-
ity were examined. This resulted in datasets of local flea assem-
blages for 11 host species (10 rodents and one shrew; see
Supplementary Fig. S1) occurring in six to 20 localities situated
at latitudes from 38°Nto68°N.
2.2. Phylogenetic information
The phylogenetic tree of fleas was based on the only available
molecular phylogeny of fleas recently constructed by Whiting
et al. (2008). This tree includes 128 flea species (ca. 6% of the global
fauna) belonging to 83 genera (ca. 34% of the entire number of flea
genera). Most genera in our dataset were represented by the tree
published by Whiting et al. (2008), but this was not the case for
species. Consequently, the positions of the species which were
not represented in the original tree of Whiting et al. (2008) were
determined using their morphologically-derived taxonomy (see
details in Krasnov et al., 2011). All branch lengths were set equal
to 1.0. The tree was ultrametrised using the option ‘‘chronopl’’ in
the package ‘‘ape’’ (2.8) (Paradis et al., 2004) implemented in the
R 2.15 statistical environment (R Development Core Team, 2011,
http://www.R-project.org).
2.3. Geographic information
To estimate the geographic range of a host species, we applied
species distribution modelling based on occurrence records and
environmental data (see details in Shenbrot and Krasnov, 2005;
Shenbrot, in press). In brief, records of occurrences of a species
were obtained from the Global Biodiversity Information Facility
(GBIF; http://data.gbif.org
), museum collection databases and pub-
764 B.R. Krasnov et al. / International Journal for Parasitology 43 (2013) 763–770
Page 2
lished sources. All localities that had no original geo-referencing
information in data sources were geo-referenced using Geographic
Names Gazetteers (http://earth-info.nga.mil/gns/html/cntry_fi-
les.html). Data that could not be geo-referenced precisely
(±5 km), were excluded. Environmental data for modelling were
used as 30 arc-second grids (approximately 1 km resolution) and
were represented by climate, relief, substrate and vegetation vari-
ables. The climate variables were obtained as a part of the
WORLDCLIM Version 1.4 (BIOCLIM) package (Hijmans et al.,
2005) available at http://www.worldclim.org
. Slope data were de-
rived from altitude (extracted from a GOTOPO30 data set distrib-
uted with an ArcGIS) using the Spatial Analyst module of ArcMap
software. The data on the Normalised Difference Vegetation Index
(NDVI) were obtained from the VEGETATION Programme (http://
www.spot-vegetation.com; http://free.vgt.vito.be; data for 1998–
2007, estimations every 10 days) and averaged by seasons (winter,
spring, summer and fall) across all available years. The models of
species distribution were built with the MAXENT 3.3.3 k software
(Phillips et al., 2006).
To delineate the areas of real species occurrence, the original
model values, ranging continuously from 0 to 1, were transformed
to binary 0 or 1 using a threshold value equal to the smallest prob-
ability value that contains all of the observed presences in a region
(the ‘‘lowest presence threshold’’; Pearson et al., 2007; McCormack
et al., 2009), and the raster was transformed to polygons. Only
polygons containing occurrence records were considered as areas
of occurrence. The area of each polygon included in a geographic
range was calculated in square km using the Calculate Geometry
tool of ArcMap 10.1. The centre of a geographic range and its dis-
tance to the equator were calculated using Mean Center utility
with weighting by area (Measuring Geographic Distributions, Spa-
tial Statistics Tools, ArcMap 10.1). Both distance measures were
log-transformed prior to analyses.
2.4. Phylogenetic community structure
Various metrics have been proposed to estimate the phyloge-
netic structure of a species assemblage (Webb et al., 2002). In gen-
eral, these metrics indicate whether species in a community are
more or less phylogenetically related than expected by chance
(phylogenetic clustering and phylogenetic overdispersion, respec-
tively) or else a community is randomly assembled from a phylo-
genetic viewpoint. Initially, we calculated two indices of
phylogenetic structure for each regional flea assemblage of each
host. These indices were the phylogenetic species variability
(PSV) and phylogenetic species clustering (PSC) (Helmus et al.,
2007). Both indices compare the expected variance of a neutral
trait that evolves under Brownian motion along the real phyloge-
netic tree of species in a community with the variance of a neutral
trait expected if these species would evolve simultaneously from
the same ancestor, so that their pairwise phylogenetic distances
would be equal (e.g., star phylogeny). The main differences be-
tween the two indices is that PSV considers all species, while PSC
takes into account close relatives only and is thus similar to the
Nearest Taxon Index (NTI) proposed earlier (Webb, 2000; Webb
et al., 2002). In other words, the two indices capture different com-
ponents of phylogenetic structure. Values of both indices vary be-
tween 0 and 1 with values close to 0 indicating high phylogenetic
relatedness, while maximal values of 1 may be observed only in a
community of phylogenetically independent species (Helmus et al.,
2007). We calculated PSV and PSC using the package ‘‘picante’’
(1.5–2) (Kembel et al., 2010) implemented in R 2.15 (R Develop-
ment Core Team, 2011; http://www.R-project.org). Hereafter, we
focus on PSC because spatial variation in PSV was rather low (see
Section 3).
2.5. Data analyses
To test whether the phylogenetic structure of each local flea
assemblage of a host species differed significantly from that ex-
pected by chance, we compared the observed index (PSC) with
the average of the indices calculated for 500 randomly generated
assemblages. In each replicate, the null assemblage was generated
by random sampling of the observed number of species from the
total pool of flea species harboured by a given host across its geo-
graphic range. For the sake of biological reality, for each given host
species we restricted the pool of fleas from which null communi-
ties were assembled only to those flea species that were recorded
on this host throughout its geographic range. To characterise the
phylogenetic structure of each across-hosts flea assemblage, we
calculated its PSC as described above but the null communities
were generated using the entire pool of flea species recorded in
all 52 regions. In subsequent analyses, we used only those flea
assemblages in which phylogenetic structure differed significantly
from that expected by chance.
To test for the relationships between the phylogenetic structure
of flea assemblages of a given host in a given locality and (i) dis-
tance of that locality from the centre of the host’s geographic
range, (ii) distance of the locality from the equator and (iii) phylo-
genetic structure of the entire across-hosts flea assemblage, we ap-
plied Generalised Linear Models (GLMs) with normal distribution
and log-link separately for each host species. The phylogenetic
structure of the across-host flea assemblages in a locality corre-
lated with the distance of this locality from the equator (see Sec-
tion 3). Consequently, prior to analysis, we substituted the
original values of PSC for these flea assemblages with their residual
deviations from the linear regression on log-transformed distance
to the equator. We selected the best model using Akaike’s Informa-
tion Criterion (AIC). Then, we further investigated the best models
and tested for significance of coefficients using Wald statistics.
P < 0.05 was considered significant.
3. Results
The phylogenetic structure in terms of both PSV and PSC of the
absolute majority of within-host local flea assemblages differed
significantly from that expected by chance (PSV: from 62% of
assemblages in Microtus arvalis to 100% of assemblages in Arvicola
amphibius; P < 0.05 for all; and PSC: from 71% of assemblages in
Microtus agrestis to 100% of assemblages in A. amphibius and Crice-
tulus migratorius; P < 0.05 for all). The phylogenetic structure of 45
(in terms of PSC) or 49 (in terms of PSV) from 52 across-hosts flea
assemblages proved to be significantly different from those ex-
pected by chance. Spatial variation of PSV for regional flea assem-
blages within a host species was extremely low (coefficient of
variation within species ranged from 0.84% in Apodemus uralensis
to 2.58% in Apodemus agrarius). The same was true for the across-
host regional assemblages (coefficient of variation across regions
was 0.84%). Spatial variation of PSC was much higher (within host
species: coefficient of variation ranged from 21.99% in Microtus
oeconomus to 40.84% in M. agrestis; and across-regions: coefficient
of variation 36.23%).
The phylogenetic structure in terms of PSC varied from a mini-
mum of 0.08 for fleas on M. agrestis of the middle Ural Mountains
(Russia) to a high value of 0.46 for fleas on C. migratorius of Terskey
Alatau Mountains (Tien Shan; Kyrgyzstan). The phylogenetic struc-
ture of across-hosts flea assemblages varied from a low of 0.08 for
fleas of Kamchatka peninsula (Russia) to a high of 0.43 for fleas of
Tarbagatai Mountains (Kazakhstan). PSC of the across-hosts flea
assemblages in a locality correlated negatively with the distance
of that locality to the equator (r
2
= 0.16, F
1,51
= 8.8, P = 0.005;
slope = 0.40 ± 0.13).
B.R. Krasnov et al. / International Journal for Parasitology 43 (2013) 763–770
765
Page 3
The results of the GLM of the relationships between PSC of the
within-host flea assemblages and distance of the region from the
centre of the host’s geographic range, distance of the region from
the equator and residual PSC of the across-hosts flea assemblage
are presented in Table 1 (see all tested models and their respective
AIC values in Supplementary Table S1). In eight of 11 host species,
the phylogenetic structure of flea assemblages was associated with
the distance from the centre of the geographic range. Furthermore,
in six species, the degree of phylogenetic relatedness of flea assem-
blages decreased (as PSC increased) from the centre toward the
periphery of the geographic range (Fig. 1A), while the opposite
was true for two host species (both belonging to the same genus,
Myodes)(Fig. 1B). Removal of the data point from the upper right
corner of the graph of Fig. 1B (flea assemblage of the population
from Central Yakutia (Russia)) did not change the relationship be-
tween phylogenetic structure of flea assemblages and the centre of
geographic range of Myodes rutilus (Table 1). Significant relation-
ships between PSC of local flea assemblages and latitude (mea-
sured as distance to the equator) were found in four hosts.
Higher latitudes were associated with a higher degree of phyloge-
netic clustering (lower PSC) of fleas harboured (see illustrative
example with M. rutilus in Fig. 2). PSC of the within-host flea
assemblages were positively correlated with PSC of the entire pool
of flea species in a locality (after controlling for the effect of lati-
tude) in five host species. In two of these hosts, the phylogenetic
structure of the across-hosts flea assemblages was the only factor
associated with the phylogenetic structure of their local assem-
blages (see illustrative example with Myodes glareolus in Fig. 3).
4. Discussion
Our study demonstrated that factors affecting spatial variation
in the phylogenetic structure of flea assemblages of a host species
differed among host species. The distance of a local population
from the centre of the host’s geographic range appeared to be
the main factor explaining variation in the phylogenetic structure
of fleas harboured by this population as its effect was found in
the majority of species. However, the direction of the relationship
was positive in some species and negative in others. The geo-
graphic position of a locality and the phylogenetic structure of
the entire flea species pool affected the phylogenetic structure of
the flea assemblage of a host population to a lesser extent.
Spatial variation in the phylogenetic structure of flea assem-
blages was manifested mainly in the PSC rather than in the PSV in-
dex. This suggests that flea assemblages in different populations of
the same host differed at shallow rather than at deep phylogenetic
levels. The main difference between these two indices is that PSV is
related to mean phylogenetic distance among all species, while PSC
measures distance among nearest neighbours (Helmus et al., 2007;
Kembel et al., 2010; Gonzalez-Caro et al., 2012). Consequently, the
phylogenetic structure of within-host flea assemblages varied
across space due to differences in closely-related species, while
variation among these assemblages in the presence or absence of
basal flea lineages was much weaker (if at all).
Lower phylogenetic clustering (higher PSC) in flea assemblages
farther from the centre of the host’s geographic range may arise
due to the small size, isolation and substantial density fluctuations
in host populations in suboptimal conditions (Lesica and Allendorf,
1995; Williams et al., 2003). All of these may facilitate interspecific
contacts and acquisition of ectoparasites from other host species.
Fleas can easily be acquired via direct contact (Krasnov and
Khokhlova, 2001) or during visits to burrows occupied by other
hosts (Krasnov, 2008). Another reason behind the differences in
the phylogenetic structure of flea assemblages between central
and peripheral host populations might be decreasing genetic diver-
sity towards the range periphery, especially if these populations
have experienced genetic bottlenecks (Brussard, 1984; Eckert
et al., 2008). In particular, the decreased genetic diversity can be
manifested in decreased polymorphism in the Major Histocompat-
ibility Complex (MHC; responsible for acquired immunity) and/or
Toll-like receptor (TLR; responsible for innate immunity) genes. In-
deed, a recent meta-analysis of studies on five fish, one amphibian,
four reptile, seven bird and five mammalian species has demon-
strated that bottlenecks have resulted in greater loss of MHC diver-
sity than neutral genetic diversity (Sutton et al., 2011). However,
polymorphism at TLR genes was found to be relatively high in a
bottleneck population of a New Zealand bird (Grueber et al., 2012).
Interestingly, patterns of geographic variation of diversity in
immune genes appear to be different among species even if they
are ecologically similar and their geographic distributions overlap.
Recently, Tschirren et al. (2011a) studied the diversity and popula-
tion differentiation in TLR2 genes across several populations of
Apodemus flavicollis and M. glareolus.InA. flavicollis, the across-
population diversity at TLR was low and one haplotype was pre-
dominant in all populations, so that there was no population differ-
entiation. On the contrary, populations of M. glareolus differed
substantially in predominant haplotypes. Moreover, genetic differ-
ences in TLR increased with increasing geographic distances be-
tween populations in M. glareolus, while this was not the case for
A. flavicollis. Species-specific immunogenetic patterns might
underlie the spatial patterns of variation in the phylogenetic struc-
Table 1
Best models explaining the relationships between the phylogenetic structure (measured as phylogenetic species clustering (PSC)) of flea assemblages of a given host in a region
and distance of the region from the centre of the host’s geographic range (DC), position of the region relative to the equator (DE) and phylogenetic structure of the across-hosts
flea assemblage (AHPSC; controlled for confounding effect of distance to Equator; see Section 2.5).
Species Model AIC L-l
v
2
P
Apodemus agrarius PSC = 0.86DC + 0.90AHPSC
a
28.45 7.51 0.02
Apodemus uralensis PSC = 0.48DC-1.90DE 34.08 14.86 <0.01
Arvicola amphibius PSC = 18.07–5.42DE + 7.48AHPSC 14.76 4.12 0.04
Cricetulus migratorius PSC = 0.72DC + 2.42AHPSC 27.32 14.36 <0.01
Microtus agrestis PSC = 3.82DC
a
17.86 15.19 <0.01
Microtus arvalis PSC = 2.71DE
a
+3.18AHPSC 31.57 6.50 0.03
Microtus oeconomus PSC = 0.95DC + 1.33AHPSC
a
33.07 12.49 <0.01
Myodes glareolus PSC = 4.10AHPSC 27.50 14.34 <0.01
Myodes rufocanus PSC = 31.68–1.69DC-7.38DE 19.37 10.73 <0.01
Myodes rutilus PSC = 20.33–0.42DC-5.39DE + 4.38AHPSC 54.43 32.03 <0.01
Myodes rutilus
b
PSC = 15.02–1.02DC-3.44DE + 5.25AHPSC 54.91 34.33 <0.01
Sorex araneus PSC = 1.08DC 24.22 8.14 <0.01
AIC, Akaike Information Criterion; L-l
v
2
, log-likelihood
v
2
.
a
Terms with non-significant coefficients. Only significant intercept terms are shown.
b
After removal of the data from populations of Central Yakutia (see Section 3 for explanation).
766 B.R. Krasnov et al. / International Journal for Parasitology 43 (2013) 763–770
Page 4
ture of parasite assemblages found in our study. The only two spe-
cies for which an increase of phylogenetic clustering (that is, a de-
crease in PSC) with increasing distance from the centre of the range
was found were congenerics (M. rutilus and Myodes rufocanus). The
exact mechanisms behind a particular species-specific spatial pat-
tern of immunogenetic variation and its effect on the structure of
parasite communities are unknown and warrant further investiga-
tion. One explanation can be that parasite-mediated selection has
acted differently in different host species. For example, Tschirren
et al. (2011b) reported results suggesting that past positive selec-
tion has shaped parts of the TLR genes differently in Myodes voles,
on the one hand, and Apodemus mice and Microtus voles, on the
other hand.
Contrasting spatial patterns of phylogenetic structure of flea
communities between M. rufocanus/M. rutilus and other species
in this study might also be related to the positions of their geo-
graphic ranges. Among our study species, M. rufocanus and M. ruti-
lus are the only true boreal species with geographic ranges situated
almost entirely between 50°N and 70°N(Shenbrot and Krasnov,
2005). The majority of the regions where these species were sam-
pled and their ectoparasites collected are to the north and to the
east of the centres of their ranges. These regions are characterised
by depauperate flea faunas (e.g., Yudin et al., 1976), so that popu-
lations of M. rufocanus and M. rutilus at the northern and eastern
periphery of their ranges simply do not have a source pool to diver-
sify their flea assemblages. In contrast, such a source may be pres-
ent for the southern populations of these hosts.
Although the effect of distance to the equator on the phyloge-
netic clustering of flea assemblages was found in four host species
only, it was consistently negative and conformed to our expecta-
tion. The pattern of this relationship conformed to the above expla-
nation, namely the PSC of flea assemblages decreases (that is,
phylogenetic clustering increases) to the north. The mechanisms
underlying this pattern could be both ecological and historical.
From an ecological perspective, the increasing phylogenetic clus-
tering of flea assemblages harboured by the northernmost host
populations may be due to environmental filtering that allows
the occurrence of only those flea species that are resistant to low
Fig. 1. Relationships between the phylogenetic structure of local flea assemblages (measured as phylogenetic species clustering (PSC)) of Apodemus agrarius (A) and Myodes
rutilus (B) and distances from the centre of their geographic ranges.
B.R. Krasnov et al. / International Journal for Parasitology 43 (2013) 763–770
767
Page 5
temperatures. For example, among fleas parasitic on rodents in
northern regions, representatives of the ceratophyllid genera
Megabothris and Amalaraeus are very common (Yudin et al.,
1976; Holland, 1985). However, the temperature preferences of
these species are unknown, making this explanation rather specu-
lative. Nevertheless, earlier we demonstrated that the taxonomic
diversity of flea assemblages of a host often, albeit not always, cor-
relates with environmental variables such as air temperature and
precipitation (Krasnov et al., 2005). The results of this study show
that this may also be the case for the phylogenetic structure.
From a historical perspective, the phylogenetic structure of par-
asites may follow the phylogenetic structure of their hosts (Kras-
nov et al., 2012). In general, northern assemblages of the
Palearctic mammals are less phylogenetically diverse than south-
ern assemblages (e.g., Davis and Buckley, 2011). In particular this
may be related to Quaternary climate fluctuations and periodic gla-
ciation of the northern part of the Palearctic that have led to the
high level of diversification of many taxa in southern refugia, while
northern species are mainly derived from these refugium popula-
tions, expanding their ranges in late glacial and early post-glacial
periods (Hewitt, 1996). Higher phylogenetic clustering of fleas
(that is, lower PSC) in both within-host and across-host assem-
blages of the northern localities might be a response to the spatial
pattern of variation in phylogenetic structure of their hosts. In
Fig. 2. Relationships between the phylogenetic structures of local flea assemblages of Myodes rutilus (measured as phylogenetic species clustering (PSC)) and distance to the
equator.
Fig. 3. Relationships between the phylogenetic structure of local flea assemblages (measured as phylogenetic species clustering (PSC)) of Myodes glareolus and the
phylogenetic structures of the across-host flea assemblages in a locality (controlled for the distance to the equator; see Section 2.5 for explanations).
768 B.R. Krasnov et al. / International Journal for Parasitology 43 (2013) 763–770
Page 6
addition, the geographic distribution of extant flea taxa suggests
that glaciation/post-glaciation cycles could affect flea diversity in
a fashion similar to that of their hosts but independently of the
hosts’ phylogeographic processes (Medvedev, 1996).
The effect of the phylogenetic structure of the surrounding flea
assemblage on that of the assemblages harboured by individual
host species was consistently positive in all species for which this
effect was found. In other words, the phylogenetic affinities of the
set of flea species harboured by some hosts reflected the availabil-
ity of certain flea lineages among all fleas inhabiting the locality.
Host species for which the phylogenetic structure of the across-
host assemblages was the only factor affecting the phylogenetic
structure of their local assemblages (M. arvalis and M. glareolus)
seemed thus to be random samplers of flea lineages from the sur-
rounding pools. However, for other host species, the surrounding
pool of flea species affected the phylogenetic structure of within-
host assemblages together with other factors.
In conclusion, our results demonstrated that the key factor
underlying spatial variation of the phylogenetic structure of the
flea assemblage of a host was the distance from the centre of the
host’s geographic range. However, the pattern of this spatial varia-
tion differed between host species and might be explained by their
species-specific immunogenetic and/or distributional patterns. Lo-
cal flea assemblages may also, to some extent, be shaped by envi-
ronmental filtering coupled with historical events. In addition, the
phylogenetic structure of a local within-host flea assemblage may
mirror the phylogenetic structure of the entire across-host flea
assemblage in that locality and, thus, be affected by the availability
of certain phylogenetic lineages.
Acknowledgements
We thank Robert Poulin for helpful comments on an earlier ver-
sion of the manuscript. This study was partly supported by the Is-
rael Science Foundation (Grant No. 26/12 to B.R.K. and I.S.K.). S.P.
was supported by a fellowship from the Kreitman Foundation, (Is-
rael). This is Publication No. 803 of the Mitrani Department of Des-
ert Ecology, (Israel).
Appendix A. Supplementary data
Supplementary data associated with this article can be found, in
the online version, at http://dx.doi.org/10.1016/j.ijpara.2013.
05.001.
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  • Source
    [Show abstract] [Hide abstract] ABSTRACT: Background: Ectoparasites exhibit pronounced variation in life history characteristics such as time spent on the host and host range. Since contemporary species distribution (SD) modelling does not account for differences in life history, the accuracy of predictions of current and future species’ ranges could differ significantly between life history groups. Results: SD model performance was compared between 21 flea species that differ in microhabitat preferences and level of host specificity. Distribution models generally performed well, with no significant differences in model performance based on either microhabitat preferences or host specificity. However, the relative importance of predictor variables was significantly related to host specificity, with the distribution of host-opportunistic fleas strongly limited by thermal conditions and host-specific fleas more associated with conditions that restrict their hosts’ distribution. The importance of temperature was even more pronounced when considering microhabitat preference, with the distribution of fur fleas being strongly limited by thermal conditions and nest fleas more associated with variables that affect microclimatic conditions in the host nest. Conclusions: Contemporary SD modelling, that includes climate and landscape variables, is a valuable tool to study the biogeography and future distributions of fleas and other parasites taxa. However, consideration of life history characteristics is cautioned as species may be differentially sensitive to environmental conditions.
    Full-text · Article · Mar 2016 · Parasites & Vectors