capacity (Ngamprasertwong et al., 2008; Atterby et al., 2010; Laine et al., 2013). This
observed genetic homogeneity, reflected in low variation across genetic diversity metrics,
was not associated with the abundance of bat flies, wing mites or *P. murinus*. Instead,
parasite loads appeared to be more closely linked with host sex and age, highlighting the
importance of bat life-history traits over genetic diversity in shaping infection dynamics.
Although no relationship was detected between parasite abundance and genetic
variation, including in immune-relevant regions such as the MHC, the limited variation in
genetic diversity may have constrained our ability to detect such associations. Future
studies incorporating broader geographic sampling and targeted sequencing of immune-
related loci may reveal finer-scale genetic patterns and provide a deeper understanding
of the evolutionary interaction between host genetics and parasite pressure in this
species. Finally, given that bat flies are known vectors of *P. murinus* (Gardner and
Molyneux, 1988), examining the dynamics of this haemosporidian in relation to the bat fly
presence and abundance could clarify whether the observed increase in *P. murinus*
relative abundance results from host life-history traits or an increase in vector prevalence.

**Acknowledgements.** The authors would like to thank Anouk Hoang and David Baumgartner for their help collecting the samples. Thanks to Zoé Dumas for her help improving the RAD protocol. Thanks to Eddie Perochon and Kim Schalcher for their help in the analyses and Camille Thomas-Bulle for her invaluable comments on the manuscript.

**Data availability.** All scripts necessary to generate genomic data and perform analyses used in this study have been made available on https://github.com/clca98/PhD.

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# Supplementary Materials

## Appendices

### Appendix S1. Comparison between qPCR and smears results

To validate the qPCR assay for detecting *Polychromophilus murinus* in the blood of Daubenton's bats, we compared its results to microscopic counts of *P. murinus* gametocytes in blood smears (Table 1). The relative abundance of *P. murinus* was calculated as the proportion of parasite DNA relative to total DNA, defined as the quantity of *P. murinus* DNA divided by the sum of *P. murinus* and bat DNA. This molecular ratio was then compared to the microscopic ratio, calculated as the number of gametocytes per red blood cell.

First, to estimate the repeatability of the gametocyte counts, five randomly selected smears were each counted three times. Repeatability was obtained using the intra-class correlation coefficient (ICC) from the rptR package in R, with 1000 permutation to evaluate the significance (Nakagawa and Schielzeth, 2010). This analysis revealed a high and statistically significant repeatability (R = 0.924; p = 0.001), indicating that gametocyte counts were highly consistent across repeated measurements and thus represent a reliable metric.

To assess the consistency between the two detection methods, we performed a Spearman's rank correlation using the cor.test function in R. The correlation between the qPCR-based relative abundance and the gametocyte-to-RBC ratio was significantly positive (Fig.1; rho = 0.536, S = 6146.4, p = 2.125e-04) indicating concordance between molecular and microscopic quantification.

To evaluate differences in detection sensitivity, we conducted a McNemar's test using the *mcnemar.test* function in R. The results revealed a significant discrepancy between the two methods, with qPCR demonstrating higher sensitivity than gametocyte counts from blood smears (Table 1; $\chi^2 = 12.071$, df = 1, p = 5.12e-04).

<table><caption>**Table 1. Detection of *P. murinus* in the Daubenton's bat blood.** The red blood cell (RBC) counts, initial gametocyte counts, and qPCR-based quantification of *P. murinus* and bat DNA are reported. The relative abundance of *P. murinus* derived from qPCR is also included.</caption><thead><tr><th rowspan="2">ID</th><th colspan="2">Microscopy</th><th colspan="3">qPCR</th></tr><tr><th>RBC</th><th><i>P. murinus</i> gametocytes</th><th>Quantity <i>P. murinus</i></th><th>Quantity Bat</th><th>Relative abundance <i>P. murinus</i></th></tr></thead><tbody><tr><td>003</td><td>41800</td><td>0</td><td>3,84614E-08</td><td>9,37773E-08</td><td>0,29084806</td></tr><tr><td>004</td><td>45000</td><td>0</td><td>0</td><td>1,11891E-07</td><td>0</td></tr></tbody></table>
<table><tr><td>005</td><td>41200</td><td>1</td><td>1,02654E-07</td><td>1,26373E-05</td><td>0,008057675</td></tr><tr><td>008</td><td>50200</td><td>5</td><td>1,54785E-06</td><td>3,63763E-05</td><td>0,040814436</td></tr><tr><td>009</td><td>45200</td><td>2</td><td>1,31152E-06</td><td>2,05986E-05</td><td>0,059858827</td></tr><tr><td>011</td><td>41800</td><td>0</td><td>1,27309E-09</td><td>5,8098E-06</td><td>0,00021908</td></tr><tr><td>012</td><td>50000</td><td>3</td><td>1,32975E-09</td><td>1,66386E-05</td><td>7,99132E-05</td></tr><tr><td>013</td><td>43600</td><td>1</td><td>1,64853E-09</td><td>2,47262E-07</td><td>0,006622987</td></tr><tr><td>017</td><td>34800</td><td>2</td><td>1,91146E-08</td><td>3,19615E-06</td><td>0,005944955</td></tr><tr><td>019</td><td>38000</td><td>0</td><td>2,15443E-07</td><td>5,60891E-06</td><td>0,036990109</td></tr><tr><td>020</td><td>43800</td><td>1</td><td>4,49603E-08</td><td>1,32344E-05</td><td>0,003385727</td></tr><tr><td>021</td><td>49000</td><td>0</td><td>0</td><td>7,09044E-07</td><td>0</td></tr><tr><td>022</td><td>37600</td><td>2</td><td>3,20511E-09</td><td>8,01076E-07</td><td>0,003985058</td></tr><tr><td>023</td><td>38600</td><td>NA</td><td>0</td><td>6,8034E-07</td><td>0</td></tr><tr><td>026</td><td>48600</td><td>0</td><td>0</td><td>2,32175E-07</td><td>0</td></tr><tr><td>027</td><td>44600</td><td>0</td><td>0</td><td>7,43506E-06</td><td>0</td></tr><tr><td>029</td><td>43000</td><td>0</td><td>0</td><td>1,39225E-06</td><td>0</td></tr><tr><td>030</td><td>43600</td><td>0</td><td>7,73351E-09</td><td>5,75752E-06</td><td>0,001341399</td></tr><tr><td>031</td><td>36400</td><td>1</td><td>2,24475E-07</td><td>7,39198E-06</td><td>0,029472408</td></tr><tr><td>032</td><td>40400</td><td>0</td><td>0</td><td>3,27766E-06</td><td>0</td></tr><tr><td>034</td><td>39400</td><td>0</td><td>0</td><td>3,00792E-06</td><td>0</td></tr><tr><td>036</td><td>49000</td><td>0</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>038</td><td>32000</td><td>0</td><td>0</td><td>1,44072E-05</td><td>0</td></tr><tr><td>042</td><td>39000</td><td>2</td><td>5,21681E-08</td><td>1,06361E-05</td><td>0,004880871</td></tr><tr><td>051</td><td>37800</td><td>2</td><td>5,15987E-08</td><td>1,21728E-05</td><td>0,004220956</td></tr><tr><td>079</td><td>49200</td><td>7</td><td>2,89999E-06</td><td>1,44072E-05</td><td>0,167559789</td></tr><tr><td>082</td><td>30800</td><td>0</td><td>0</td><td>3,34609E-06</td><td>0</td></tr><tr><td>084</td><td>39600</td><td>1</td><td>8,4044E-08</td><td>3,00404E-06</td><td>0,027215581</td></tr><tr><td>089</td><td>30000</td><td>0</td><td>0</td><td>3,14395E-06</td><td>0</td></tr><tr><td>101</td><td>49000</td><td>0</td><td>0</td><td>8,22019E-06</td><td>0</td></tr><tr><td>104</td><td>48400</td><td>0</td><td>0</td><td>1,54835E-05</td><td>0</td></tr><tr><td>111</td><td>41000</td><td>0</td><td>6,97328E-09</td><td>1,18501E-05</td><td>0,00058811</td></tr><tr><td>113</td><td>43000</td><td>0</td><td>8,62869E-08</td><td>4,26995E-06</td><td>0,019807677</td></tr><tr><td>121</td><td>43400</td><td>0</td><td>0</td><td>7,33367E-06</td><td>0</td></tr><tr><td>123</td><td>46600</td><td>0</td><td>3,16332E-07</td><td>1,2996E-05</td><td>0,023762246</td></tr><tr><td>125</td><td>42400</td><td>0</td><td>2,23364E-07</td><td>3,64799E-05</td><td>0,006085672</td></tr><tr><td>130</td><td>48200</td><td>0</td><td>2,94037E-08</td><td>2,96572E-05</td><td>0,000990468</td></tr><tr><td>134</td><td>52000</td><td>3</td><td>1,38722E-06</td><td>2,34565E-05</td><td>0,055837851</td></tr><tr><td>138</td><td>34800</td><td>0</td><td>1,85444E-07</td><td>2,24695E-05</td><td>0,008185604</td></tr><tr><td>139</td><td>35800</td><td>0</td><td>7,03138E-08</td><td>1,10331E-05</td><td>0,006332645</td></tr><tr><td>143</td><td>34400</td><td>0</td><td>0</td><td>2,61594E-05</td><td>0</td></tr><tr><td>144</td><td>50600</td><td>0</td><td>7,97144E-08</td><td>3,86403E-05</td><td>0,00205874</td></tr><tr><td>146</td><td>35600</td><td>0</td><td>1,31508E-06</td><td>2,41946E-05</td><td>0,051552341</td></tr><tr><td>147</td><td>47400</td><td>14</td><td>1,72322E-06</td><td>9,40814E-06</td><td>0,154807627</td></tr><tr><td>148</td><td>48800</td><td>0</td><td>4,49149E-08</td><td>1,18914E-05</td><td>0,003762875</td></tr></table>
<figure><img src="image_27.png" /><figcaption>Fig. 1. Correlation between the qPCR-based and the microscopic-based relative abundance of *P. murinus*.</figcaption></figure>

## Appendix S2. Kinship analysis and special cases

### Case 1:

Among the 27 pairs of related individuals identified, two pairs were found across different sampling sites with kinship coefficients around 0.25 and fraternity coefficients consistent with parent-offspring relationships (pairs 497–810 and 434–810, **Table 1**). Age comparisons within each pair allowed to infer that the first pair (497–810) represents a father-son relationship (**Fig. 1A**), while the second pair (434–810) corresponds to a mother-son relationship (**Fig. 1A**), suggesting that individuals 434 and 497 are the parents of individual 810.

Interestingly, individuals 434 and 497 themselves share a kinship coefficient of 0.12, indicative of a second-degree relationship such as half-siblings or grandparent-grandchild. Under typical expectations, mating between relatives of this degree would likely result in an inbred offspring. However, individual 810 exhibits a low inbreeding coefficient ($F_{AS} = 0.002$; $F_{UNI} = -0.005$; **Table 2**) and is not an outlier in the distribution of the genotypes (**Fig. 1B**), contradicting this assumption.

Given the difficulty in distinguishing between relationship types associated with a kinship coefficient of 0.125, alternative explanations must be considered. One possibility is a misclassification of individual 810's age (from adult to subadult). If individual 810 were in fact an adult, several scenarios could explain the observed kinship patterns without implying inbreeding:

Scenario 1: Individual 810 is the parent of individuals 434 and 497, who are half-siblings (**Fig. 1C**).
Scenario 2: Individual 434 is the parent of individual 810 and 810 is the parent of individual 497, consistent with grandparent-grandchild relationship between 434 and 497 (Fig. 1D).

Scenario 3: Individual 497 is the parent of individual 810, and 810 is the parent of 434, producing a second-degree relationship between 434 and 497 (Fig. 1E).

This case illustrates the power of genome-wide SNP data generated via RADseq to reconstruct lineage relationships using kinship and fraternity coefficients. With a larger sample size, more extensive family networks could be resolved, offering deeper insights into bat social structure and reproductive dynamics.

<figure><img src="image_28.png" /><figcaption>**Fig. 1. Relationships between individuals 434, 497 and 810.** (A) Kinship between the focal individuals. (B) Distribution of the genotypes of each individual. Diamonds represent the 3 individuals. In green, 434, in orange 497 and in purple 810. (C) Scenario 1. (D) Scenario 2. (E) Scenario 3.</figcaption></figure>

<table><caption>**Table 1. Pairwise kinship and relationship between individuals 434, 497 and 810.** For each pair, the age (AD = adult, SAD = subadult, JUV = juvenile), the sex (F = female, M = male), the sampling site and the kinship estimates of the individuals are reported. The types of relationship represent either recaptures (R), full-siblings (FS) or parent-offsprings (PO).</caption><thead><tr><th colspan="4">Individual 1</th><th colspan="4">Individual 2</th><th rowspan="2">Pairwise kinship</th><th rowspan="2">Relationship</th></tr><tr><th>ID</th><th>Site</th><th>Sex</th><th>Age</th><th>ID</th><th>Site</th><th>Sex</th><th>Age</th></tr></thead><tbody><tr><td>434</td><td>7</td><td>F</td><td>AD</td><td>810</td><td>15</td><td>M</td><td>SAD</td><td>0.24</td><td>PO</td></tr><tr><td>497</td><td>13</td><td>M</td><td>AD</td><td>810</td><td>15</td><td>M</td><td>SAD</td><td>0.24</td><td>PO</td></tr></tbody></table>
<table><caption>**Table 2.** Genetic diversity estimates for individuals **434**, **497** and **810**. The relative heterozygosity (H) and the inbreeding coefficients (F<sub>AS</sub> and F<sub>UNI</sub>) are reported.</caption><thead><tr><th></th><th>H</th><th>F<sub>UNI</sub></th><th>F<sub>AS</sub></th></tr></thead><tbody><tr><th>434</th><td>0.190</td><td>-0.013</td><td>-0.040</td></tr><tr><th>497</th><td>0.188</td><td>0.0002</td><td>-0.002</td></tr><tr><th>810</th><td>0.189</td><td>0.002</td><td>-0.005</td></tr></tbody></table>

**Case 2:**

This second special case includes three pairs of individuals from the same sampling site (individuals 345, 416 and 431 from site 7). Kinship analysis identified two parent-offspring relationship between individuals 345 and 431 and between 416 and 431 (Fig. 2A). In the first pair, the directionality could not be resolved as both individuals belonged to the same age group. In contrast, the second pair was more clearly defined with individual 416 identified as the offspring and 431 as the parent (Table 3).

Additionally, individuals 345 and 416 had a kinship of 0.16, consistent with a second-degree relationship such as half-siblings, grandparent-grandchild (Fig. 2A). Based on the observed kinship values and age groups, two plausible relationship scenarios are proposed:

Scenario 1: Individuals 345 and 416 are half-siblings, sharing individual 431 as their common parent (Fig. 2B).

Scenario 2: Individual 345 is the parent of 431 and the grandparent of 416 (Fig. 2C).

This case highlights the challenge of reconstructing familial relationships, particularly when distinguishing among second-degree relationships. The development of methods capable of resolving such ambiguities would significantly improve the inference of accurate family linkage, contributing to a deeper understanding of mating systems and social structure.
<figure><img src="image_29.png" /><figcaption>**Fig. 2. Relationships between individuals 345, 416 and 431.** (A) Kinship between the focal individuals. (B) Scenario 1. (D) Scenario 2.</figcaption></figure>

<table><caption>**Table 3. Pairwise kinship and relationship between individuals 345, 416 and 431.** For each pair, the age (AD = adult, SAD = subadult, JUV = juvenile), the sex (F = female, M = male), the sampling site and the kinship estimates of the individuals are reported. The types of relationship represent either recaptures (R), full-siblings (FS) or parent-offsprings (PO).</caption><thead><tr><th colspan="4">Individual 1</th><th colspan="4">Individual 2</th><th rowspan="2">Pairwise kinship</th><th rowspan="2">Relationship</th></tr><tr><th>ID</th><th>Site</th><th>Sex</th><th>Age</th><th>ID</th><th>Site</th><th>Sex</th><th>Age</th></tr></thead><tbody><tr><td>345</td><td>7</td><td>F</td><td>AD</td><td>431</td><td>7</td><td>F</td><td>AD</td><td>0.24</td><td>PO</td></tr><tr><td>416</td><td>7</td><td>M</td><td>SAD</td><td>431</td><td>7</td><td>F</td><td>AD</td><td>0.26</td><td>PO</td></tr></tbody></table>
Supplementary Tables

<table><caption>**Table S1. Pairwise kinship and relationship between pairs of related individuals.** For each pair, the age (AD = adult, SAD = subadult, JUV = juvenile), the sex (F = female, M = male), the sampling site and the kinship estimates of the individuals are reported. The types of relationship represent either recaptures (R), full-siblings (FS) or parent-offsprings (PO).</caption><thead><tr><th colspan="4">Individual 1</th><th colspan="4">Individual 2</th><th rowspan="2">Pairwise kinship</th><th rowspan="2">Relationship</th></tr><tr><th>ID</th><th>Site</th><th>Sex</th><th>Age</th><th>ID</th><th>Site</th><th>Sex</th><th>Age</th></tr></thead><tbody><tr><td>315</td><td>16</td><td>M</td><td>AD</td><td>666</td><td>16</td><td>M</td><td>AD</td><td>0.5</td><td>R</td></tr><tr><td>335</td><td>16</td><td>M</td><td>AD</td><td>669</td><td>16</td><td>M</td><td>AD</td><td>0.5</td><td>R</td></tr><tr><td>336</td><td>16</td><td>M</td><td>SAD</td><td>657</td><td>16</td><td>M</td><td>SAD</td><td>0.5</td><td>R</td></tr><tr><td>337</td><td>7</td><td>M</td><td>AD</td><td>352</td><td>7</td><td>F</td><td>AD</td><td>0.27</td><td>FS</td></tr><tr><td>345</td><td>7</td><td>F</td><td>AD</td><td>431</td><td>7</td><td>F</td><td>AD</td><td>0.24</td><td>PO</td></tr><tr><td>349</td><td>7</td><td>F</td><td>AD</td><td>415</td><td>7</td><td>F</td><td>AD</td><td>0.25</td><td>PO</td></tr><tr><td>393</td><td>9</td><td>F</td><td>AD</td><td>400</td><td>9</td><td>F</td><td>AD</td><td>0.25</td><td>FS</td></tr><tr><td>416</td><td>7</td><td>M</td><td>SAD</td><td>431</td><td>7</td><td>F</td><td>AD</td><td>0.26</td><td>PO</td></tr><tr><td>421</td><td>7</td><td>M</td><td>AD</td><td>423</td><td>7</td><td>F</td><td>AD</td><td>0.24</td><td>FS</td></tr><tr><td>434</td><td>7</td><td>F</td><td>AD</td><td>810</td><td>15</td><td>M</td><td>SAD</td><td>0.24</td><td>PO</td></tr><tr><td>461</td><td>6</td><td>F</td><td>AD</td><td>468</td><td>6</td><td>M</td><td>SAD</td><td>0.25</td><td>PO</td></tr><tr><td>492</td><td>13</td><td>F</td><td>AD</td><td>504</td><td>13</td><td>F</td><td>JUV</td><td>0.25</td><td>PO</td></tr><tr><td>497</td><td>13</td><td>M</td><td>AD</td><td>810</td><td>15</td><td>M</td><td>SAD</td><td>0.24</td><td>PO</td></tr><tr><td>510</td><td>2</td><td>F</td><td>AD</td><td>514</td><td>2</td><td>M</td><td>JUV</td><td>0.24</td><td>PO</td></tr><tr><td>529</td><td>14</td><td>F</td><td>AD</td><td>551</td><td>14</td><td>F</td><td>AD</td><td>0.24</td><td>PO</td></tr><tr><td>544</td><td>14</td><td>F</td><td>AD</td><td>545</td><td>14</td><td>F</td><td>AD</td><td>0.25</td><td>PO</td></tr><tr><td>582</td><td>1</td><td>F</td><td>SAD</td><td>583</td><td>1</td><td>M</td><td>JUV</td><td>0.25</td><td>PO</td></tr><tr><td>617</td><td>5</td><td>F</td><td>AD</td><td>637</td><td>5</td><td>F</td><td>SAD</td><td>0.24</td><td>PO</td></tr><tr><td>623</td><td>5</td><td>F</td><td>AD</td><td>644</td><td>5</td><td>F</td><td>AD</td><td>0.24</td><td>PO</td></tr><tr><td>632</td><td>5</td><td>F</td><td>JUV</td><td>646</td><td>5</td><td>F</td><td>SAD</td><td>0.25</td><td>PO</td></tr><tr><td>634</td><td>5</td><td>F</td><td>SAD</td><td>645</td><td>5</td><td>F</td><td>JUV</td><td>0.24</td><td>PO</td></tr><tr><td>655</td><td>16</td><td>F</td><td>AD</td><td>671</td><td>16</td><td>M</td><td>AD</td><td>0.25</td><td>PO</td></tr><tr><td>665</td><td>16</td><td>F</td><td>AD</td><td>670</td><td>16</td><td>M</td><td>SAD</td><td>0.25</td><td>PO</td></tr><tr><td>676</td><td>17</td><td>M</td><td>JUV</td><td>683</td><td>17</td><td>F</td><td>AD</td><td>0.25</td><td>PO</td></tr><tr><td>677</td><td>17</td><td>M</td><td>SAD</td><td>691</td><td>17</td><td>F</td><td>JUV</td><td>0.29</td><td>FS</td></tr><tr><td>740</td><td>11</td><td>F</td><td>AD</td><td>741</td><td>11</td><td>F</td><td>JUV</td><td>0.25</td><td>PO</td></tr><tr><td>801</td><td>12</td><td>M</td><td>AD</td><td>805</td><td>12</td><td>M</td><td>JUV</td><td>0.25</td><td>PO</td></tr></tbody></table>
<table><caption>Table S2. Bats 95% confidence intervals for population-specific F<sub>IS</sub> and F<sub>ST</sub>.</caption><thead><tr><th>Sites</th><th>F<sub>IS</sub></th><th>F<sub>ST</sub></th></tr></thead><tbody><tr><td>All</td><td>0.003 [0.0029;0.004]</td><td>0.003' [0.003;0.0035]</td></tr><tr><td>1</td><td>0.007 [0.0046;0.011]</td><td>0.004 [0.0005;0.008]</td></tr><tr><td>2</td><td>0.019 [0.0185;0.025]</td><td>0.007 [0.0046;0.012]</td></tr><tr><td>3</td><td>0.009 [0.005;0.011]</td><td>-0.001 [-0.0017;0.005]</td></tr><tr><td>4</td><td>0.007 [0.0016;0.009]</td><td>0.003 [-0.003;0.004]</td></tr><tr><td>5</td><td>-0.001 [-0.003;0.002]</td><td>0.003 [0.0006;0.007]</td></tr><tr><td>6</td><td>-0.001 [-0.006;0.001]</td><td>0.003 [-0.001;0.007]</td></tr><tr><td>7</td><td>0.001 [-0.001;0.0034]</td><td>-0.0003 [-0.0002;0.005]</td></tr><tr><td>8</td><td>0.003 [-0.002;0.0046]</td><td>0.007 [0.001;0.011]</td></tr><tr><td>9</td><td>0.0003 [-0.004;0.002]</td><td>0.008 [0.002;0.0082]</td></tr><tr><td>10</td><td>0.0002 [-0.003;0.011]</td><td>-0.005 [-0.016;-0.0015]</td></tr><tr><td>11</td><td>0.005 [0.003;0.007]</td><td>0.003 [-0.0002;0.005]</td></tr><tr><td>12</td><td>-0.007 [-0.008;0.0014]</td><td>0.015 [0.008;0.018]</td></tr><tr><td>13</td><td>0.002 [0.0014;0.007]</td><td>0.0004 [-0.003;0.004]</td></tr><tr><td>14</td><td>0.003 [-0.0001;0.004]</td><td>0.004 [0.001;0.006]</td></tr><tr><td>15</td><td>0.008 [0.005;0.015]</td><td>-0.003 [-0.0099;0.0007]</td></tr><tr><td>16</td><td>0.001 [-0.0016;0.003]</td><td>0.008 [0.005;0.011]</td></tr><tr><td>17</td><td>-0.002 [-0.003;0.003]</td><td>0.005 [0.002;0.008]</td></tr><tr><td>18</td><td>-0.0037 [-0.0039;0.002]</td><td>0.003 [0.0006;0.007]</td></tr></tbody></table>
<table><caption>**Table S3. Bats 95% confidence intervals (CI) of F statistics among sampling sites.** The lower matrix represents the 95% CI of the mean kinship between sampling sites based on the FsM matrix. The upper matrix represents the 95% CI of the pairwise FST between sampling sites based on the Fst2x2 matrix.</caption><thead><tr><th></th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th><th>12</th></tr></thead><tbody><tr><td>1</td><td>0</td><td>0.0034<br/>[0.00295;0.0044]</td><td>0.0035<br/>[0.0032;0.0044]</td><td>0.0014<br/>[0.00085;0.0022]</td><td>0.0026<br/>[0.0021;0.0034]</td><td>0.0019<br/>[0.0018;0.0032]</td><td>0.003<br/>[0.002974;0.004]</td><td>0.00083<br/>[0.00047;0.0019]</td><td>0.005<br/>[0.0046;0.0063]</td><td>0.00297<br/>[0.0016;0.0051]</td><td>0.0025<br/>[0.0021;0.0031]</td><td>0.008<br/>[0.0071;0.0092]</td></tr><tr><td>2</td><td>0.0017 [-6.944e-05;5.549e-03]</td><td>0</td><td>0.0034<br/>[0.0031;0.0043]</td><td>0.0031<br/>[0.0017;0.003]</td><td>0.004<br/>[0.0034;0.0048]</td><td>0.0035<br/>[0.0023;0.0038]</td><td>0.0035<br/>[0.0027;0.004]</td><td>0.0014<br/>[0.0005;0.0023]</td><td>0.0058<br/>[0.0052;0.0065]</td><td>0.0016 [-2.67e-05;3.12e-03]</td><td>0.0028<br/>[0.0022;0.0034]</td><td>0.0097<br/>[0.008;0.0106]</td></tr><tr><td>3</td><td>-0.002 [-0.0031;0.0022]</td><td>-0.0004 [-0.00086;0.0036]</td><td>0</td><td>0.002<br/>[0.0012;0.0024]</td><td>0.0042<br/>[0.0038;0.0048]</td><td>0.0033<br/>[0.0029;0.0042]</td><td>0.0036<br/>[0.0034;0.0044]</td><td>0.0017<br/>[0.0011;0.0025]</td><td>0.0016<br/>[0.0013;0.0022]</td><td>0.00082 [-0.0006;0.0025]</td><td>0.0014<br/>[0.0009;0.0017]</td><td>0.0052<br/>[0.0032;0.0055]</td></tr><tr><td>4</td><td>0.0017 [-0.0015;0.00369]</td><td>0.0015 [-0.00029;0.005]</td><td>-0.001 [-0.0026;0.0016]</td><td>0</td><td>0.0022<br/>[0.0013;0.0023]</td><td>0.0023<br/>[0.0014;0.0029]</td><td>0.0021<br/>[0.0012;0.0024]</td><td>0.0006 [-0.0004;0.0011]</td><td>0.0046<br/>[0.0032;0.0045]</td><td>0.0011 [-0.0014;0.0019]</td><td>0.0014<br/>[0.0005;0.0015]</td><td>0.007<br/>[0.0058;0.0077]</td></tr><tr><td>5</td><td>0.00059 [-0.00111;0.00366]</td><td>0.00078 [-0.00049;0.0043]</td><td>-0.0032 [-0.0038;0.0003]</td><td>4.878e-04 [-0.0014;0.0031]</td><td>0</td><td>0.0036<br/>[0.0029;0.0039]</td><td>0.0036<br/>[0.0034;0.0042]</td><td>0.0023<br/>[0.0015;0.0026]</td><td>0.0057<br/>[0.0048;0.0059]</td><td>0.0041<br/>[0.0013;0.0045]</td><td>0.0034<br/>[0.0028;0.0037]</td><td>0.0097<br/>[0.0075;0.0098]</td></tr><tr><td>6</td><td>0.0016 [-0.00125;0.0038]</td><td>0.0016 [6.946e-05;5.281e-03]</td><td>-0.002 [-0.004;0.0012]</td><td>7.156e-05 [-0.0027;0.003]</td><td>-0.0005 [-0.0031;0.0026]</td><td>0</td><td>0.0027<br/>[0.0025;0.0037]</td><td>0.0019<br/>[0.0006;0.0023]</td><td>0.0061<br/>[0.005;0.0066]</td><td>0.0022 [-0.0003;0.0033]</td><td>0.0025<br/>[0.00198;0.0032]</td><td>0.0097<br/>[0.0072;0.0098]</td></tr><tr><td>7</td><td>-0.0014 [-0.0020;0.0025]</td><td>-0.0003 [-0.00015;0.0044]</td><td>-0.0042 [-0.0041;0.0004]</td><td>-9.398e-04 [-0.002;0.0021]</td><td>-0.0023 [-0.003;0.0018]</td><td>-0.0012 [-0.0025;0.0023]</td><td>0</td><td>0.0012<br/>[0.00069;0.002]</td><td>0.0052<br/>[0.00496;0.006]</td><td>0.0024<br/>[0.00042;0.0037]</td><td>0.0022<br/>[0.0019;0.0028]</td><td>0.0092<br/>[0.0075;0.0094]</td></tr><tr><td>8</td><td>0.0045<br/>[0.0016;0.0065]</td><td>0.0055<br/>[0.0029;0.0079]</td><td>0.0015 [-0.0005;0.0038]</td><td>4.173e-03 [-1.23e-06;5.95e-03]</td><td>0.0026 [-0.00012;0.0047]</td><td>0.0033 [7.644e-05;5.127e-03]</td><td>0.0021<br/>[0.0003;0.0057]</td><td>0</td><td>0.003<br/>[0.0024;0.0038]</td><td>0.00021 [-0.0021;0.001]</td><td>0.00023 [-0.00029;0.00097]</td><td>0.0055<br/>[0.0048;0.007]</td></tr><tr><td>9</td><td>0.0006 [-0.0029;0.0019]</td><td>0.0015 [-0.0018;0.003]</td><td>0.002 [-0.0011;0.004]</td><td>6.136e-04 [-0.003;0.0011]</td><td>-0.0004 [-0.003;0.0017]</td><td>-0.0004 [-0.0045;0.0007]</td><td>-0.0014 [-0.0039;0.0005]</td><td>0.0042 [-0.00031;0.0044]</td><td>0</td><td>0.0037<br/>[0.0015;0.0046]</td><td>0.0036<br/>[0.0026;0.0038]</td><td>0.0074<br/>[0.0053;0.0075]</td></tr><tr><td>10</td><td>-0.0039 [-0.0091;-0.0015]</td><td>-0.0009 [-0.0053;0.0019]</td><td>-0.0039 [-0.0078;-0.001]</td><td>-2.591e-03 [-0.007;-0.0008]</td><td>-0.0054 [-0.0088;-0.0017]</td><td>-0.0032 [-0.0076;-0.0006]</td><td>-0.0053 [-0.008;-0.0015]</td><td>0.00058 [-0.0049;0.003]</td><td>-0.0025 [-0.008;-0.00095]</td><td>0</td><td>0.00019 [-0.0012;0.0016]</td><td>0.0061<br/>[0.0037;0.0079]</td></tr><tr><td>11</td><td>0.0007 [-0.0012;0.0035]</td><td>0.002<br/>[0.0003;0.0048]</td><td>-0.0003 [-0.001;0.003]</td><td>1.379e-03 [-0.00097;0.0032]</td><td>-0.00053 [-0.0019;0.0024]</td><td>0.00067 [-0.0019;0.0025]</td><td>-0.0009 [-0.0019;0.0024]</td><td>0.0047<br/>[0.001;0.0064]</td><td>0.0018 [-0.0014;0.0027]</td><td>-0.0014 [-0.007;0.0005]</td><td>0</td><td>0.0079<br/>[0.0055;0.0078]</td></tr><tr><td>12</td><td>0.001 [-0.0022;0.0039]</td><td>0.0009 [-0.0014;0.0049]</td><td>0.0018<br/>[0.0003;0.006]</td><td>1.258e-03 [-0.0028;0.0037]</td><td>-0.001 [-0.0027;0.0025]</td><td>-0.00077 [-0.0034;0.0025]</td><td>-0.0021 [-0.0034;0.0028]</td><td>0.0053<br/>[0.0006;0.007]</td><td>0.0038 [-0.00085;0.006]</td><td>-0.0015 [-0.008;0.0005]</td><td>8.593e-04 [-0.0013;0.005]</td><td>0</td></tr><tr><td>13</td><td>-0.0004 [-0.00299;0.0028]</td><td>0.0011 [-0.0012;0.0039]</td><td>-0.0035 [-0.0048;-0.0006]</td><td>-6.603e-04 [-0.0037;0.0011]</td><td>-0.0014 [-0.003;0.0015]</td><td>-0.0007 [-0.00353;0.0021]</td><td>-0.0022 [-0.0025;0.0015]</td><td>0.0035 [-0.0002;0.005]</td><td>-0.00069 [-0.004;0.00001]</td><td>-0.0046 [-0.009;-0.002]</td><td>7.426e-06 [-0.002;0.0015]</td><td>-0.00088 [-0.003;0.002]</td></tr><tr><td>14</td><td>0.00036 [-0.0019;0.0026]</td><td>0.0011 [-0.00075;0.0036]</td><td>-0.0017 [-0.0025;0.0016]</td><td>1.140e-03 [-0.0017;0.0033]</td><td>-0.0006 [-0.0025;0.002]</td><td>0.00046 [-0.0026;0.0027]</td><td>-0.0023 [-0.0034;0.001]</td><td>0.0034<br/>[0.0006;0.005]</td><td>0.0014 [-0.0025;0.002]</td><td>-0.0032 [-0.008;-0.001]</td><td>2.605e-04 [-0.001;0.002]</td><td>0.00088 [-0.0015;0.0042]</td></tr><tr><td>15</td><td>-0.0012 [-0.0048;0.001]</td><td>-0.0006 [-0.003;0.0031]</td><td>-0.0034 [-5.399e-03;5.439e-05]</td><td>-9.538e-04 [-0.0052;0.0015]</td><td>-0.0021 [-0.005;0.0005]</td><td>-0.0012 [-0.0048;0.0017]</td><td>-0.0023 [-0.0048;0.001]</td><td>0.0028 [-0.0022;0.004]</td><td>-0.00071 [-0.005;0.0002]</td><td>-0.0048 [-0.011;-0.003]</td><td>-3.955e-04 [-0.004;0.001]</td><td>-0.0009 [-0.004;0.0036]</td></tr><tr><td>16</td><td>0.0016<br/>[0.00031;0.0045]</td><td>0.00197<br/>[0.00058;0.0046]</td><td>0.0006 [-0.00045;0.0038]</td><td>1.624e-03 [-0.00045;0.0038]</td><td>0.00018 [-0.001;0.002]</td><td>0.0009 [-0.00197;0.0036]</td><td>-0.00103 [-0.002;0.002]</td><td>0.0042<br/>[0.0017;0.007]</td><td>0.0032 [-0.0002;0.004]</td><td>-0.0021 [-0.006;0.0001]</td><td>1.712e-03 [-0.0005;0.003]</td><td>0.0026 [-0.0002;0.006]</td></tr><tr><td>17</td><td>0.00034 [-0.0016;0.0036]</td><td>0.0018 [7.578e-05;4.865e-03]</td><td>-0.0016 [-0.0031;0.002]</td><td>9.014e-04 [-0.0014;0.003]</td><td>-0.00038 [-0.0027;0.0023]</td><td>0.0011 [-0.0019;0.0033]</td><td>-0.0012 [-0.0019;0.002]</td><td>0.0044<br/>[0.0006;0.006]</td><td>0.00056 [-0.003;0.0001]</td><td>-0.0036 [-0.008;-0.0008]</td><td>1.112e-05 [-0.0017;0.003]</td><td>0.0006 [-0.0019;0.0036]</td></tr><tr><td>18</td><td>-0.0015 [-0.0031;0.0016]</td><td>0.0003 [-0.0007;0.004]</td><td>0.00055 [-0.0001;0.0046]</td><td>-6.906e-05 [-0.0025;0.0026]</td><td>-0.0019 [-0.0027;0.0016]</td><td>-0.00089 [-0.0035;0.0019]</td><td>-0.00296 [-0.0035;0.001]</td><td>0.0031<br/>[0.0006;0.006]</td><td>0.0032 [-6.026e-05;4.163e-03]</td><td>-0.0048 [-0.0084;-0.00096]</td><td>9.886e-04 [-0.0004;0.003]</td><td>0.00336<br/>[0.00078;0.007]</td></tr></tbody></table>
<table><thead><tr><th></th><th>13</th><th>14</th><th>15</th><th>16</th><th>17</th><th>18</th></tr></thead><tbody><tr><td>1</td><td>0.002<br/>[0.002;0.0032]</td><td>0.0035<br/>[0.0032;0.0042]</td><td>0.0014<br/>[0.0011;0.0031]</td><td>0.0042<br/>[0.0036;0.0047]</td><td>0.00417<br/>[0.0036;0.0047]</td><td>0.0046<br/>[0.0041;0.0055]</td></tr><tr><td>2</td><td>0.0025<br/>[0.0024;0.0036]</td><td>0.004<br/>[0.00401;0.0051]</td><td>0.0024<br/>[0.001;0.0032]</td><td>0.0054<br/>[0.0049;0.0062]</td><td>0.0042<br/>[0.0034;0.0047]</td><td>0.0044<br/>[0.0034;0.0049]</td></tr><tr><td>3</td><td>0.0034<br/>[0.003;0.0039]</td><td>0.003<br/>[0.0027;0.0036]</td><td>0.0014<br/>[0.0007;0.0026]</td><td>0.003<br/>[0.0027;0.0036]</td><td>0.004<br/>[0.0038;0.0049]</td><td>0.00045 [6.042e-05;9.39e-04]</td></tr><tr><td>4</td><td>0.002<br/>[0.0012;0.0024]</td><td>0.0022<br/>[0.0016;0.0025]</td><td>0.00059 [-0.0009;0.00086]</td><td>0.0036<br/>[0.0022;0.0033]</td><td>0.0031<br/>[0.0018;0.003]</td><td>0.0027<br/>[0.0016;0.0029]</td></tr><tr><td>5</td><td>0.003<br/>[0.0025;0.0033]</td><td>0.004<br/>[0.0036;0.0044]</td><td>0.0018<br/>[0.0012;0.003]</td><td>0.0052<br/>[0.0046;0.0054]</td><td>0.0045<br/>[0.0038;0.0048]</td><td>0.0046<br/>[0.0039;0.0049]</td></tr><tr><td>6</td><td>0.0027<br/>[0.0018;0.0028]</td><td>0.003<br/>[0.0028;0.0037]</td><td>0.0013<br/>[0.0003;0.0024]</td><td>0.0047<br/>[0.0039;0.0053]</td><td>0.0033<br/>[0.0024;0.0038]</td><td>0.0039<br/>[0.0035;0.0048]</td></tr><tr><td>7</td><td>0.0023<br/>[0.0017;0.0025]</td><td>0.0042<br/>[0.0039;0.0047]</td><td>0.00055 [8.69e-06;1.77e-03]</td><td>0.0048<br/>[0.0046;0.0054]</td><td>0.0038<br/>[0.0032;0.0044]</td><td>0.0041<br/>[0.0039;0.0048]</td></tr><tr><td>8</td><td>0.00017<br/>[0.00024;0.0014]</td><td>0.0022<br/>[0.0013;0.0025]</td><td>-0.0009 [-0.0019;0.0003]</td><td>0.0033<br/>[0.0021;0.0032]</td><td>0.0018<br/>[0.0012;0.0029]</td><td>0.0017<br/>[0.00092;0.0023]</td></tr><tr><td>9</td><td>0.0048<br/>[0.0041;0.0053]</td><td>0.0046<br/>[0.0043;0.0053]</td><td>0.003<br/>[0.002;0.0042]</td><td>0.0047<br/>[0.00397;0.0049]</td><td>0.0061<br/>[0.0054;0.0068]</td><td>0.0021<br/>[0.0016;0.0027]</td></tr><tr><td>10</td><td>0.002 [-0.00019;0.0027]</td><td>0.0025<br/>[0.00064;0.0039]</td><td>0.0005 [-0.0015;0.0026]</td><td>0.0033<br/>[0.0018;0.0045]</td><td>0.0035<br/>[0.001;0.0042]</td><td>0.0034<br/>[0.0011;0.0043]</td></tr><tr><td>11</td><td>0.0017<br/>[0.0014;0.0022]</td><td>0.0033<br/>[0.0027;0.0035]</td><td>0.0002 [-0.0002;0.0015]</td><td>0.0037<br/>[0.0031;0.004]</td><td>0.003<br/>[0.002998;0.004]</td><td>0.0018<br/>[0.0013;0.0023]</td></tr><tr><td>12</td><td>0.008<br/>[0.0067;0.0089]</td><td>0.008<br/>[0.0066;0.0087]</td><td>0.0065<br/>[0.0035;0.0067]</td><td>0.0086<br/>[0.0068;0.0088]</td><td>0.009<br/>[0.007;0.0094]</td><td>0.0053<br/>[0.0034;0.0053]</td></tr><tr><td>13</td><td>0</td><td>0.0037<br/>[0.0031;0.0038]</td><td>-0.0004 [-0.0012;0.00047]</td><td>0.004<br/>[0.0037;0.0046]</td><td>0.0023<br/>[0.0023;0.0034]</td><td>0.0036<br/>[0.0029;0.0039]</td></tr><tr><td>14</td><td>-1.394e-03 [-0.0036;0.0003]</td><td>0</td><td>0.0026<br/>[0.0016;0.0033]</td><td>0.0037<br/>[0.0032;0.004]</td><td>0.0052<br/>[0.0045;0.0055]</td><td>0.0037<br/>[0.003;0.0039]</td></tr><tr><td>15</td><td>-0.0008e-04 [-0.005;0.001]</td><td>-0.0021 [-5.886e-03;3.668e-05]</td><td>0</td><td>0.0032<br/>[0.0024;0.0039]</td><td>0.002<br/>[0.0015;0.0033]</td><td>0.002<br/>[0.0011;0.0029]</td></tr><tr><td>16</td><td>-5.723e-05 [-0.0023;0.0018]</td><td>0.0023 [9.433e-05;4.696e-03]</td><td>-0.00085 [-0.004;0.0014]</td><td>0</td><td>0.005<br/>[0.0048;0.0059]</td><td>0.0037<br/>[0.0029;0.0039]</td></tr><tr><td>17</td><td>6.069e-04 [-0.002;0.0023]</td><td>-0.0004 [-0.003;0.002]</td><td>-0.0014 [-0.004;0.0008]</td><td>1.294e-03 [-0.00078;0.0038]</td><td>0</td><td>0.0042<br/>[0.0036;0.0049]</td></tr><tr><td>18</td><td>-2.003e-03 [-0.0036;0.00057]</td><td>-0.00029 [-0.002;0.003]</td><td>-0.0022 [-0.005;0.00076]</td><td>1.569e-03<br/>[0.0001;0.004]</td><td>-0.00017 [-0.002;0.0028]</td><td>0</td></tr></tbody></table>
Supplementary Figures

<figure><img src="image_30.png" /><figcaption>Fig. S1. Number of reads per individuals.</figcaption></figure>

<figure><img src="image_31.png" /><figcaption>Fig. S2. Distribution of the linkage disequilibrium over all RAD sequences of bats.</figcaption></figure>
<figure><img src="image_32.png" /><figcaption>**Fig. S3.** Supplementary population genetic analyses based on the RAD sequences of the bats. (A) Population-specific *F*<sub>IS</sub> based on 100 bootstraps on loci considered independent. The dotted red line represents *y* = 0. (B) Distribution of the entropy across 10 runs for each genetic cluster. (C) Parallel coordinate plot based on the two first principal component. Each bar corresponds to an individual and each colour refers to a sampling site.</figcaption></figure>
<figure><img src="image_33.png" /><figcaption>**Fig. S4.** Results on the dataset of bat including only rare alleles (mac ≤ 10). (A) Heatmap of the mean kinship and pairwise F<sub>ST</sub> over pairs of sampling sites. The upper matrix is the mean kinship between sites (FsM), high values represent pairs of populations whose individuals are more closely related to each other than to individuals from other populations. The diagonal represents the intra-populational mean kinship (population-specific F<sub>ST</sub>) and the lower matrix represent the pairwise F<sub>ST</sub>. (B) Population-specific F<sub>IS</sub>. (C) Population-specific F<sub>ST</sub>. Each population-specific F<sub>ST</sub> statistics are based on 100 bootstraps on loci considered independent. The dotted red line represents y = 0.</figcaption></figure>
<figure><img src="image_34.png" /><figcaption>Fig. S5. Effect of the bat inbreeding coefficient $F_{AS}$ on its parasite abundance.</figcaption></figure>

<figure><img src="image_35.png" /><figcaption>Fig. S6. Effect of the bat relative heterozygosity of the MHC region on its parasite abundance.</figcaption></figure>
# Chapter 3

## Hitchhiking parasites: unstructured populations of bat ectoparasites reveal host-driven dispersal

Clara Castex<fnref n="1" />, Tristan Cumer<fnref n="1" />,<fnref n="2" />, Jérôme Goudet<fnref n="1" />,<fnref n="2" />* and Philippe Christe<fnref n="1" />*

Corresponding author: clara.castex@unil.ch

**Authors contributions:** CC, JG and PC conceived and planned the study. CC did the field work and CC ran the analyses with the help of TC. All authors contributed to the interpretation of the results. CC wrote the first draft of the manuscript with valuable inputs of TC, and all authors provided critical feedback and approved the final manuscript.

**Status:** This chapter is under review in *Molecular Ecology*, special issue **"Ecology and Evolution of Wildlife Parasites: Novel Insights from Natural Populations"**.

<footnote n="1">¹Department of Ecology and Evolution, University of Lausanne, Switzerland</footnote>

<footnote n="2">²Swiss Institute of Bioinformatics, Lausanne, Switzerland</footnote>

<footnote>*Co-senior authors</footnote>
Abstract

Understanding factors influencing the dynamic and distribution of parasites is essential to decipher the mechanism behind their spread and the identification of populations with elevated risks of infection. Bats – together with the diverse parasite they host and the influence of their social behaviour on parasitism – offer a suitable system. We investigated the extent to which differences in life history traits between parasite species found on the same host influence their dispersal dynamics across bat metapopulations. To do so, we compared the population genetic structure of two obligate ectoparasites of the same bat, the Daubenton's bat (*Myotis daubentonii*): the specialist wing mite *Spinturnix andegavinus* and the more generalist bat fly *Nycteribia kolenatii* and we expected the bat fly to exhibit a higher connectivity than the wing mites. Using double-digest restriction site associated DNA sequencing (ddRADseq), we genotyped 426 bat flies and 171 wing mites, across 13 maternity colonies and foraging sites and 1 putative swarming site in Switzerland. We found high genetic homogeneity across the metapopulations for both species, highlighting the dispersal capacity of *N. kolenatii* and *S. andegavinus*, probably driven by the high mobility of its bat hosts. The positive population-specific *F*<sub>IS</sub> and the excess of low-frequency alleles in both species suggest within-site expansion and provide insights into the life cycle of these ectoparasites. Altogether, these findings enhance our understanding of interplay between nycteribid flies and spinturnicid mites and their host movement in shaping population structure in Europe, offering broader insights into their potential role in pathogen transmission across bat populations.

**Keywords:** bat flies, bat mites, gene flow, RADseq, host-parasite evolution
Introduction

Parasites depend on their host for survival and spread (Combes, 2004), making
their spatial dynamics closely linked to host dispersal capacity (Mazé-Guilmo et al.,
2016). While specialist parasites rely on a single host, others navigate complex life cycles
involving multiple host species. In such systems, limited dispersal in one host can be
offset by the high mobility of another, facilitating parasite spread (Louhi et al., 2010).
These host-parasite interactions create a complex dynamic network that is shaped by the
life-history traits of all species involved. Thus, life cycle complexity, reproductive strategy,
host specificity, and dispersal behaviour are key traits known to significantly influence
parasite evolutionary trajectories (Olsen, 1974; Barrett et al., 2008). In parallel, the life
history and spatial structure of the host species also affects the dispersion, connectivity
and genetic structure between population of parasites (Jarne and Théron, 2001; Barrett et
al., 2008). Yet, mismatches between the genetic structure of hosts and that of their
parasites are frequently observed (Mazé-Guilmo et al., 2016). Therefore, a
comprehensive understanding of how parasites spread in populations require to decipher
how host and parasites interact and how their respective life-history traits shape their
distribution and dynamics. Genetic and genomic approaches offer powerful tools to
understand the mechanisms driving parasites transmission within and between
populations (Blanchong et al., 2016). Specifically, differences in spatial genetic
structures can reveal important patterns highlighting the variety of parasite spreading
strategies (Biek and Real, 2010; Blanchong et al., 2016).

In this context, bats form a suitable model for the many parasites they host as well
as their dynamic life cycle influencing their susceptibility to parasitism. The
spatiotemporal heterogeneity of movements between different bat species, among
populations or even between sexes affects the dispersal of their obligate parasites
(Christe et al., 2000, 2007; Amman et al., 2012; Witsenburg et al., 2014; Dietrich et al.,
2015; Webber and Willis, 2016; van Schaik and Kerth, 2017; Sándor et al., 2019). Among
ectoparasites, bat flies and wing mites are two obligate hematophagous bat parasites
that reproduce on their host. Their life cycle differences are based on the deposition of
their early developmental stages and their degree of host specialisation. Mites of the
family Spinturnicidae are viviparous, they complete their entire life cycle on the
membranous part of their host and are strictly dependent of close contact between
individuals to disperse and infect new hosts (Rudnick, 1960; Dowling, 2006). Because most
wing mite species are associated with one or a few bat species (Bruyndonckx et al.,
2009a), the coevolution between wing mites and bats is strict and highly specialised
(some host switch can occasionally occur). Given this strong host specificity, wing mite
dispersal is expected to be entirely dependent on the host movements. On the other
hand, bat flies are less specific, while they have a major host, they can be found in several
bat species (Szentivanyi et al., 2016). The eggs and the larval stages occur within the
female and the terminal larva (prepupa) is deposited by the female fly on the cavity wall
of the roost of the bat (Dick and Patterson, 2006). When an adult fly emerges, it seeks out
and colonizes a new bat, potentially creating more gene flow in the bat fly population than
in the wing mite. Consequently, bat fly connectivity is expected to be higher between host
populations than that of the wing mite.

Studies investigating population genetics of bat flies and wing mites are scarce and give contrasting results (Bruyndonckx et al., 2009b; van Schaik et al., 2014; Witsenburg et al., 2015b; Pejić et al., 2022). On the same bat species, *Myotis bechsteinii*, two different parasite have been shown to have different connectivity patterns: the wing mite (*Spinturnix bechsteini*) populations are strongly geographically and temporally differentiated (van Schaik et al., 2014), whereas populations of the bat fly (*Basilia nana*) have no genetic structure within and between sites (van Schaik et al., 2015). But these results are not consistent among all wing mite species. For example, the wing mite S. *myoti*, specific of *Myotis myotis* high levels of genetic diversity and very little genetic differentiation (van Schaik et al., 2014). These studies pointed that genetic population differentiation in parasites is driven by the host life history traits such as bat population size, social structure, mating system and dispersal patterns (van Schaik et al., 2014). All these studies rely on genetic markers such as mtDNA gene fragments and/or few numbers of microsatellites. While such markers provide valuable insights, their resolution is often limited, especially for detecting fine-scale population structure or recent demographic events (Sunde et al., 2020; Cumer et al., 2022; Dufresnes et al., 2023). To resolve this issue, restriction site associated DNA sequencing (RADseq) can be used to genotype thousands of Single Nucleotide Polymorphism (SNPs) across the
populations (Davey and Blaxter, 2010; Peterson et al., 2012; Andrews et al., 2016), as it
allows to detect genetic differentiation where microsatellite cannot (Sunde et al., 2020;
Cumer et al., 2022; Dufresnes et al., 2023) and thus gives insight into individual
movements, population differentiation and even disease spread (Wilder et al., 2015;
Dufresnes et al., 2022, 2023).

Understanding how parasite life history influences local genetic structure can
provide key insights into their dispersal dynamics across bat metapopulations. Both
ectoparasites carry a great variety of pathogens and act as vectors within bat populations
(Leulmi et al., 2016; McKee et al., 2019; Jaenson and Wilhelmsson, 2021; Tendu et al.,
2022) and can transmit agents associated with human zoonoses (Reeves et al., 2006;
Nováková et al., 2009; Lack et al., 2011; Sándor et al., 2018; Szentiványi et al., 2019;
Szubert-Kruszyńska et al., 2019; Thiévent et al., 2020; Sándor et al., 2021; Szentiványi et
al., 2022; Sándor et al., 2024a). Because of their distinct life-history traits, obligate bat
ectoparasites such as bat flies and wing mites are likely to differ in their role as potential
disease transmitters. Examining bat flies and wing mites genetic diversity and structure
can reveal the degree of connectivity among parasites populations and provide an initial
insight into pathogen spread in bat populations. Here, we investigated the genetic
diversity and structure of bat flies (Nycteribia kolenatii) and wing mites (Spinturnix
andegavinus) of the Daubenton's bat (Myotis daubentonii) in Western Switzerland.
Daubenton's bat usually form small colonies and primarily rely on swarming to find
partners and reproduce (Bogdanowicz, 1994; Encarnação and Becker, 2023). At the local
and European scale, the Daubenton's bat exhibit an absence of genetic structure
(Ngamprasertwong et al., 2008; Atterby et al., 2010; Laine et al., 2013). We hypothesised
that if the life-history of the parasite their dispersal opportunities then the bat fly should
exhibit less population structure than the wing mite due to its time spent off-host and the
lower degree of specialisation. However, the host life-history may also shape the parasite
population genetics and therefore, the lack of spatial structure in the Daubenton's bat
could facilitate gene flow between bat flies and wing mites metapopulations. To test these
hypotheses, we used population genetic analyses based on RADseq data on parasites
collected across maternity colonies, foraging sites and a putative swarming site.
# Materials & Methods

## Data collection

389 *M. daubentonii* were captured in 14 sampling sites (bat maternity colonies, foraging sites and a putative swarming site) across the Vaud canton in Switzerland, between June and September 2023, under the license authorization VD3679 (Fig. 1). For each bat, all bat flies and wing mites were collected, put in absolute ethanol and conserved in -20°C freezers. In total, 1197 bat flies and 1307 wing mites were collected. The species and sex of each ectoparasite were identified. To compare genetic diversity within bat, between bats and between sampling sites while maintaining the number of ectoparasites sequenced reasonable, we randomly selected two bat flies (*Nycteribia kolenatii*) and two wing mites (*Spinturnix andegavinus*) per bats. Since not all bats had two or more ectoparasites, 228 bats were retained for a total of 456 bat flies (*N. kolenatii*) and 456 wing mites (*S. andegavinus*).

<figure><img src="image_36.png" /><figcaption>**Fig. 1. Map of the 14 sampling sites of the study.** Number in bold depict the sampling site ID and number in brackets, the number of bat flies and wing mites sampled per sites (identical number of individuals for both species). Sampling sites are: **1** – Boiron Nyon, **2** – Bois de la Râpe, **3** – Clarens, **4** – Cully, **5** – Dorigny, **6** – Embouchure Aubonne, **7** – La Cascade, **8** – Lac Morat, **9** – Le Pont, **10** – Maison de la Rivière, **11** – Moudon, **12** – Rossinière, **13** – Vufflens la Ville and **14** – Yvonand.</figcaption></figure>
## DNA extraction and library preparation

To maximise individual DNA and avoid contamination from the intestinal tracks, parasites legs were dissected under binocular magnifier for every individual. DNA of bat flies and wing mites was then extracted from the legs using the DNAeasy Blood & Tissue kit (Qiagen, Hilden, Germany) following the instruction of the manufacturer. Extracted DNA samples were kept at -20°C until library preparation.

ddRAD sequencing and library preparation was done in plates, with the parasites from the different sampling sites present in each plate. The protocol followed Brelsford et al. (2016), adapted from Parchman et al. (2012) and was modified for the Aviti sequencer. First, DNA was digested using the EcoRI-HF and Msel restriction enzymes (New England Biolab, Ipswich, MA, USA). Then, enzymes adapters were ligated to the fragments. A unique barcode was included in the EcoRI adaptors for library tagging. After purification, RAD fragments were amplified with i5- and i7-indexed adaptors (Unique Dual Indexes UDI) combined with PCR primers for individual tagging. Samples were then pooled by libraries and ectoparasites. DNA fragments were size selected in between 300-500 base pair (bp) using BluePippin 2% DF Marker V2 cassette (Sage Science, MA, USA). Species-specific size-selected libraries were then quantified, pooled and sequenced on two separated lanes of the SP flowcell in the Aviti sequencer at the Lausanne Genomic Technologies Facility (GTF, University of Lausanne) using paired-end 150 bp sequencing. For the bat flies, a total of 495'854'653 reads was sequenced. The number of reads per individuals ranged from 181'596 to 4'807'453, with an average of 1'087'401 reads per individuals (Fig. S1). For the wing mites, two sequencing were necessary because of the low coverage initially obtained (Appendix S1). After the resequencing, a total of 1'025'309'625 were obtained with an average number of read per wing mites of 2'204'967 (Fig. S1). The number of reads per individuals ranged from 7'967 to 11'194'013.

## ddRAD genotyping and SNPs calling

Bat flies and wing mites RAD sequences were processed separately but with the same pipeline, an adaption of the ProcessMyRad pipeline from Cumer et al. (2021). First, reads were trimmed to remove the Illumina adapter sequences, using the *bbduk* function
from bbmap v39.1 (Bushnell, 2014). Reads were then processed with Stacks v2.53 (Catchen et al., 2013). Individual sequences were demultiplexed using *process-radtags*. The filters used had to be adapted to each species-specific dataset (**Table S1**). Using the *de novo* pipeline of Stacks v2.53, we tested different ranges of thresholds to call loci and decided on filters that gave the best coverage and number of SNPs. We set a mismatch threshold within individuals (M) of 3 and 5 for the bat flies and wing mites respectively, a coverage threshold within individuals (m) of 4 and 3 for the bat flies and wing mites respectively and a mismatch threshold between individuals (n) of 4 and 6 for the bat flies and wing mites respectively. SNPs were identified with *gstacks* and first filters were done using *populations*. For both species, SNPs were filtered to be present in 60% of the individuals within and among sampling sites, including markers of heterozygosity of 0.5 (-*max_obserhet* 0.5). After quality control on each VCF file, correlation between heterozygosity and coverage was checked.

Individuals that had more than 25% missing data were excluded of the analyses (30 individuals out of 456 for the bat flies and 285 individuals out of 456 for the wing mites). Further filtering was done using *vcftools* v0.1.16 (Danecek et al., 2011b), with some parameters variations depending on the dataset. To minimize errors heterozygosity call, genotypes were filtered for a minimum coverage (--minDP) of 5X and 10X for the bat flies and the wing mites respectively. SNPs that were shared between 80% and 70% of the individuals were kept for the analysis (--max-missing) for the bat flies and the wing mites respectively). A mean minimum coverage (--min-meanDP) of 10X and 20X and a mean maximum coverage (--max-meanDP) of 65 and 60X for the bat flies and the wing mites respectively was set up. Finally, for both species, only SNPs under Hardy-Weinberg equilibrium were retained with a p-value threshold of 0.05 (--hwe 0.05) and SNPs with less than 5 minor allele count (mac) were discarded (--mac). A total of 1'544 SNPs were retained for 426 bat flies with a mean coverage per individual of 32.22X (ranging between 11.82X and 129.04X) and 9'525 SNPs for 171 wing mites with a mean coverage of 28.42X (ranging from 17.77X to 77.53X).

In both species, some individuals showed high kinship with many others, likely due to an excess of reference alleles (Appendices S2 and S3). Although including these individuals did not appear to have a clear impact on the results (Appendices S2 and S3),
we decided to exclude them from further analyses. Consequently, 354 bat flies and 163 wing mites were retained for the subsequent analyses.

## Data analysis

To determine the genetic diversity and differentiation of the vectors at the individual and population level, individual heterozygosity was determined based on the number of heterozygous sites divided by the total number of genotyped loci for the focal individual. Values were then averaged per sampling sites and overall to obtain per site and overall heterozygosity. We used a Kruskal-Wallis test to test if there was a significant difference of heterozygosity per sampling sites. If this test was significant, a Tukey's HSD post-hoc test was conducted to identify the population significantly different from the other populations. To analyse the population genetic structure of bat flies and wing mites, the following analyses were performed using the hierfstat v0.5.11 package (Goudet et al., 2022) unless otherwise indicated. First, principal component analyses (PCA) were performed to look for genetic clustering between sampling sites using *indpca* function. To assess the genetic differentiation between sampling sites, population-specific $F_{ST}$ and $F_{IS}$, population mean pairwise kinship (FsM matrix) and $F_{ST}$ (Fst2x2 matrix) per sampling sites were calculated using the *fs.dosage* function. These F statistics were bootstraps 100 time over loci, with all loci considered independent since loci could not be mapped to a reference genome. To verify if any population structuring could be detected within the rare alleles, *fs.dosage* function was applied on a down-sampled dataset keeping only the rare alleles (mac ≤ 10). The pairwise kinship between pairs of individuals was measured using the *beta.dosage* function. To test for isolation by distance, the correlation between the pairwise $F_{ST}$ and the geographical distances between sampling sites was done using a mantel test with 1000 permutations with the *mantel* function from the vegan package (Dixon, 2003). Sex-biased dispersal between bat flies and wing was tested using the *sexbias.test* function with the mAlc method as described in Goudet et al. (2002). Finally, to understand the vectors population dynamics, allele frequency distribution was drawn and the Tajima's D were estimated for each SNPs using the *--TajimaD* function from vcftools v0.1.16 before any minor allele filters (Danecek et al., 2011b).
# Results

## Population genetics of the bat flies

At the individual level, the mean heterozygosity per individuals ranged from 0.067 to 0.101 with an average of 0.084. After removing outliers, pairwise kinship between individuals ranged from -0.194 to 0.142 with a mean of 3.263e-17 (Fig. 2A; Appendix S2).

The distribution of the diversity was homogeneous across sampling sites but revealed some non-random mating in the population. Mean heterozygosity per sampling sites ranged between 0.081 and 0.088, with a consistent level of individual heterozygosity across sampling sites (Kruskal-Wallis test: $\chi^2 = 21.676, p = 0.061$). However, the overall inbreeding coefficients ($F_{IS}$) of 0.028 (95% CI = [0.022; 0.033]) was significantly different from 0. This trend was similar for population-specific $F_{IS}$, ranging from -0.031 to 0.075, with confidence intervals of 12 out of 14 sampling sites not overlapping 0 (Fig. S2; Table S2).

Population genetic analyses revealed high levels of connectivity among bat fly sampling sites. The overall fixation index was extremely low ($F_{ST} = -7.923e^{-05}$; 95% CI [-0.001;0.001]), indicating little to no genetic differentiation across sampling sites. Consistently, a principal component analysis (PCA) of individual genotypes showed no clustering by sampling location (Fig. 2B). Pairwise $F_{ST}$ analysis between sampling sites ranged from -0.003 to 0.003, with all confidence intervals overlapping zero (Fig. 2C; Table S3). Estimates of average genetic kinship between sites ranged from -0.021 to 0.026 (Fig. 2C; Table S3), further supporting the absence of genetic structure. There was no significant correlation between the pairwise $F_{ST}$ between sampling sites and the geographic distances (Fig. S3A; mantel test: $r = 0.06586; p = 0.35365$), suggesting a lack of isolation by distance. Down sampling the dataset to keep only loci with $mac \le 10$ yield to the same pattern and revealed the high connectivity across bat fly's populations (Fig. S4).

The dynamic of the population was further assessed using the allele frequency distribution along with Tajima's D statistic (Fig. 2D). The Tajima's D was significantly negative indicating an excess of rare alleles (mean Tajima's D = -0.708; Wilcoxon test: $V =$
1004951, *p* < 2.2e-16). Finally, our results also showed that there was no significant sex-biased dispersal between bat flies (test mAlc: t = -1.155, *p* = 0.249).

<figure><img src="image_37.png" /><figcaption>**Fig. 2.** Population genetic analyses based on the RAD sequences of the bat flies. (A) Distribution of the pairwise kinship between individuals. (B) Principal Component Analysis (PCA). (C) Heatmap of the mean kinship and pairwise F<sub>ST</sub> over pairs of sampling sites. The upper matrix is the mean kinship between sites (FsM), high values represent pairs of populations where individuals are more related than that with other populations. The diagonal represents the intra-populational mean kinship (population-specific F<sub>ST</sub>) and the and lower matrix represent the pairwise F<sub>ST</sub>. (D) Allele frequency distribution.</figcaption></figure>
Population genetics of the wing mites

At the individual level, the mean heterozygosity per individuals ranged from 0.102 to 0.175 with an average of 0.158. After removing outliers, pairwise kinship between individuals ranged from -0.065 to 0.131 with a mean of 9.795e-17 (Fig. 3A; Appendix S3).

Heterozygosity of the wing mites showed little variation between sampling sites, ranging from 0.148 to 0.161 (Kruskal Wallis: $\chi^2 = 20.98, p = 0.073$). Population-specific $F_{ST}$ were consistent with all sampling site having low values. However, five sampling sites (sites 4, 7, 8, 10 and 11) had confidence intervals that did not overlap 0 (Fig. S5; Table S2). As in bat flies, the population-specific $F_{IS}$ were low (ranging from 0.043 to 0.098 with an overall population-specific $F_{IS}$ of 0.063), yet confidence intervals of all 14 sampling sites did not overlap 0, suggesting substructure in the metapopulation (Fig. S5; Table S2).

Population genetic analyses revealed low levels of structure among the wing mites sampling sites. The overall fixation index was low ($F_{ST} = 0.001$; 95% CI [0.0006; 0.003]) and individuals were scattered in the PCA without any clear clustering according to the sampling site (Fig. 3B). Consistently, pairwise $F_{ST}$ analysis between sampling sites revealed low values, ranging from -0.008 to 0.006 (Fig. 3C; Table S4). The pairwise kinship between sampling sites were low and ranged from -0.013 to 0.030 (Fig. 3C; Table S4), supporting a high connectivity between sampling sites. A lack of isolation by distance was identified with an absence of significant correlation between the pairwise $F_{ST}$ between sampling sites and the geographic distances (Fig. S3B; mantel test: $r = -0.1827; p = 0.83516$). The high connectivity was also present in the dataset including only rare alleles, in line with estimates based on the full dataset (Fig. S6).

The dynamic of the wing mites population was assessed with the allele frequency distribution and Tajima's D statistic (Fig. 3D). Tajima's D was significantly negative indicating an excess of rare alleles (mean Tajima's D = -0.539; Wilcoxon test: $V = 54992098, p < 2.2e-16$). Finally, there was no significant sex-biased dispersal between wing mite individuals (test mAIC: $t = 0.231, p = 0.818$).
<figure><img src="image_38.png" /></figure>

<figure><img src="image_39.png" /></figure>

<figure><img src="image_40.png" /></figure>

<figure><img src="image_41.png" /></figure>

**Fig. 3.** Population genetic analyses based on the RAD sequences of the wing mites. (A) Distribution of the pairwise kinship between individuals. (B) Principal Component Analysis (PCA). (C) Heatmap of the mean kinship and pairwise F<sub>ST</sub> over pairs of sampling sites. The upper matrix is the mean kinship between sites (FsM), high values represent pairs of populations where individuals are more related than that with other populations. The diagonal represents the intra-populational mean kinship (population-specific F<sub>ST</sub>) and the and lower matrix represent the pairwise F<sub>ST</sub>. (D) Allele frequency distribution.

Discussion

In this study, we explored how different life-history traits and level of specialisation
influence patterns of genetic structure and dispersal in bat ectoparasites. We used
Restriction site Associated DNA sequencing (RADseq) to sequence the genome of two
ectoparasites of the Daubenton's bat (*Myotis daubentonii*), the generalist bat fly
*Nycteribia kolenatii* and the specialist wing mite *Spinturnix andegavinus*. We assessed how their life-history traits and degree of specialisation shape their spatial genetic patterns within populations. We found that both ectoparasite species are genetically homogeneous across bat metapopulations along an excess of rare alleles and negative Tajima's D in both species. Our results enlighten the demographic dynamics of these parasites, enabling us to further discuss the implication of the high connectivity between populations of both species on the distribution of the potential pathogens they carry.

## Using RADseq to study population genetics of bat parasites

We investigated the degree of connectivity of different bat ectoparasites species at the genomic level using RADseq, a method that enables the genotyping of thousands of SNPs across populations. Our study is the first investigating population genetic structure of bat ectoparasites at the genomic level by using RADseq, a method that allows to genotype thousands of SNPs across populations (Davey and Blaxter, 2010; Andrews et al., 2016). Studies comparing RADseq and microsatellites analyses have concluded that RADseq provide comparable to better results (Sunde et al., 2020): by increasing the number of markers, RADseq increases the power of the analysis and can even allow to infer structure in populations where microsatellites could not (Dufresnes et al., 2023). Dufresnes et al. (2023) found that 500 SNPs was enough to detect structure in the bent-winged bat *Miniopterus schreibersii* and a minimum of 1000 SNPs were required to resolve regional substructure. After filtering, we retained 1'544 SNPs for the bat flies and 9'525 SNPs for the wing mites; far exceeding the 5-10 microsatellite loci used in previous studies (van Schaik et al., 2011, 2014, 2015; Witsenburg et al., 2015); making our dataset suitable to detect genetic differentiation across sampling sites if present in both bat flies and the bat mites.
**High connectivity between sampling sites in both parasites**

*Spatial homogeneity*

Our aim was to test if different parasite life-history traits would influence dispersal potential in two bat ectoparasites and would show different patterns of genetic structure. The wing mite *S. andegavinus* is strictly associated with the Daubenton's bat whereas the bat fly *N. kolenatii* can infect several bat species, even if their major host is the Daubenton's bat (Bruyndonckx et al., 2009a; Szentivanyi et al., 2016). Because of this higher degree of specialisation, we predicted that the wing mite would exhibit higher population structure than the bat fly. In terms of diversity, our results were consistent with previous studies based on microsatellites loci that showed lower genetic diversity in bat flies than in bat mites. Heterozygosity based on microsatellites ranged from 0.455-0.650 for the bat flies with an average 4.6 alleles per locus and 0.465-0.870 for the wing mites with an average 17 alleles per locus (van Schaik et al., 2011, 2015), whereas heterozygosity in our study was lower overall but was following the same pattern with higher heterozygosity in wing mites (0.102-0.175) than in bat flies (0.062-0.101). However, regarding the genetic structure of the populations, in both mites and flies, the low overall and pairwise F<sub>ST</sub>, the homogeneous heterozygosity across sampling sites and low kinships between pairs of individuals independently of their locality of origin suggested strong gene flow across sampling sites (Fig. 2 and Fig. 3). This pattern was further supported by the absence of isolation by distance (Fig. S3).

The strong connectivity of bat flies was consistent with previous studies
investigating the population genetic structure of different species of bat flies in several
bat species (Olival *et al.*, 2013; van Schaik *et al.*, 2015; Witsenburg *et al.*, 2015b).
However, studies investigating the population genetic structure of wing mites showed
contrasting results (Bruyndonckx *et al.*, 2009b; van Schaik *et al.*, 2014; Zamora-Mejías *et
al.*, 2022). No spatial genetic structure was detected in *S. myoti* infecting the Greater
mouse-eared bat whereas strong genetic differentiation was highlighted in *S. bechsteini*,
infecting Bechstein's bat (van Schaik *et al.*, 2014). Genetic differentiation between these
two mite species reflected the importance of the host social system, in particular in terms
of home range size, population size, mating system and dispersal patterns (van Schaik et
al., 2014). Host life-history is a strong driver of its parasite genetic structure (Biek and Real, 2010; Blanchong et al., 2016; Mazé-Guilmo et al., 2016).

## Population expansion

Significant negative Tajima's D were obtained for both the bat flies and the wing mites, underlying an excess of rare alleles in both species and suggesting that populations are expanding (Tajima, 1989; Aris-Brosou and Excoffier, 1996). In bat flies, one nycteribiid species has been reported to reproduce year-round, whereas wing mites do not reproduce during winter (Lourenço and Palmeirim, 2008). Both populations have been described to experience seasonal bottlenecks during the bat hibernation period with a drop in the number of gravid bat flies and wing mites from late autumn and throughout hibernation (Lourenço and Palmeirim, 2008). Because of this annual bottleneck we were expecting to measure a reduced effective population size and increased genetic structure between sampling sites. Significant positive FIS (Fig. S2A and S5A) showed that bat flies and wing mites reproduce more with individuals from the same sampling site. It appears that, after the winter bottleneck in all populations, the population size increases when bat flies and wing mites reproduce in maternity colonies (Lourenço and Palmeirim, 2008), consistent with an excess of rare alleles in the populations. It could be of interest to study the mutation rate of bat flies and wing mite to investigate if the population expansion found from the Tajima's D results is due to the winter bottleneck or not.

## Population substructure at swarming site

Despite the high connectivity in both species, significant population-specific FIS suggested substructure in the metapopulation (Fig. S2A and S5A). As FIS measures the degree of inbreeding within population, significant FIS reflects that both ectoparasites mate more with individuals from the same sampling site than with individuals from different sites. This is consistent with the biology of the species since they spend all or most of their time on the bat. Their reproduction is synchronized with that of the host, with more gravid bat flies and wing mites during the pregnancy and the lactation of bats (Christe et al., 2000; Lourenço and Palmeirim, 2008). The generation time of bat flies (2 generations
per year; Reckardt & Kerth, 2006) shows that there is indeed several generations of bat
flies in a sampling site. The generation time of wing mites is not well known but removal
experiment on *S. bechsteini* showed that there is no barrier to mite dispersal within a bat
colony (Bruyndonckx *et al.*, 2009b), increasing the likelihood that wing mites mate more
with other mites from the same site.

The substructure was more visible in the mean kinship and pairwise F<sub>ST</sub> between
sampling sites for the wing mites, as site 7 was more related and less differentiated to
others (Fig. 3C), but this could be due to a lack of power due to the lowest number of
individuals. Initially 10 individuals were sampled in this site, but because of the filtering
only 6 individuals were kept for the analyses. Even though most sampled sites are
maternity colonies or foraging sites, site 7 is a presumed swarming site for Daubenton's
bats. The higher mean kinship between sampling sites could mean that individuals
sampled in this site are genetically closer to individuals from the other sites because bats
sampled in site 7 (and therefore wing mites) come from different maternity colonies, as it
is usually the case in swarming sites (Johnson *et al.*, 2015b). The lack of genetic structure
between bat flies and wing mites are more likely to be due to the exchange of individuals
between bats at swarming sites, shuffling alleles across all sampling sites. These findings
present exciting opportunities to confirm the swarming potential of this site, through
capture-mark-recapture (CMR) of bats or by investigating the population genetic
structure of the Daubenton's bats in the Vaud canton.

## Bat-induced high mobility of the parasites

Despite their different level of specificity, Daubenton's bat flies and wing mites
exhibit high connectivity between sampling sites and other factors could help increase
the dispersion of these two ectoparasites. Bat life history has been highlighted as shaping
the population genetic structure of its bat flies and wing mites in different ways (Olival *et al.*, 2013; van Schaik *et al.*, 2014, 2015; Witsenburg *et al.*, 2015b; Zamora-Mejías *et al.*, 2022). Globally bat flies are expected to be less impacted by their host life-history traits
and usually show higher connectivity and less genetic structure than their host, as it is the
case for *N. schmidlii* parasitizing the bent-winged bat *Miniopterus schreibersii*
(Witsenburg *et al.*, 2015b). An explanation to the high mobility of the bat flies could be that their lower specificity enables them to parasite a large number of bat species (Szentivanyi *et al.*, 2016), increasing their effective population size and leading to a reduce genetic drift. Finally, because bat flies move from their host to the walls of the roosting cavity to deposit the prepupal stage, this could increase their dispersal and the connectivity potential (Marshall, 1982). Wing mites are more strongly influenced by their host's life-history, but the effect vary depending on the social context and dispersal behaviours of the bats. For instance, *Spinturnix bechsteini*, which parasitize the highly philopatric Bechstein's bat, shows clear genetic structure, whereas *S. myotis*, the wing mite associated with the highly mobile Greater mouse-eared bat does not (van Schaik *et al.*, 2014).

Because the mating system of the Daubenton's bat is comparable to the one of the Bechstein's bat (van Schaik and Kerth, 2017), we expected *N. kolenatii* and *S. andegavinus* to exhibit similar patterns of population structure to those observed in the Bechstein's bat fly *Basilia nana* and wing mite *S. bechsteini*. In the latter system, strong female philopatry was shown to drive pronounced genetic differentiation among *S. bechsteini* populations, consistent with the wing mite's host specificity and lack of free-living stages (van Schaik *et al.*, 2014). In contrast, bat flies appeared less influenced by their host population genetic structure (van Schaik *et al.*, 2015; Witsenburg *et al.*, 2015b).

Daubenton's bat and Bechstein's bat share key life-history traits including usually small colonies size and swarming mating systems, which limits inter-individual contact and consequently, parasite transmission outside of the mating season. However, unlike the Bechstein's bat, Daubenton's bat populations exhibit high genetic diversity and low population differentiation at both the European and local scales, as shown using mitochondrial gene or microsatellite markers (Ngamprasertwong *et al.*, 2008; Atterby *et al.*, 2010; Laine *et al.*, 2013) and shown in **Chapter 2**. While swarming is hypothesised to be the primary mating strategy, male bats frequent in female-dominated roosts in the late summer and genetic analysis, suggested that mating occurs within these roosts as well (Encarnação *et al.*, 2004; Encarnação, 2012a; b; Angell *et al.*, 2013). Additionally, Daubenton's bats show fidelity to summer roosting area, although switch between maternity roosts (Ngamprasertwong *et al.*, 2014), and hibermate in small or large groups
from different maternity colonies. These behaviours enhance inter-roost connectivity and
likely promote parasite gene flow of both the bat flies and the wing mites (Bogdanowicz,
1994; Johnson et al., 2015b). Therefore, the high connectivity among Daubenton's bat
roosts offers a compelling explanation for the observed low genetic differentiation in their
ectoparasites. Indeed, a lack of genetic structure may reflect large and well connected
host populations size and increasing host density is known to facilitate greater parasite
prevalence and diversity (Morand and Poulin, 1998).

**Conclusion**

Our study highlights the importance of the subtle interplay between parasite life
cycles and their host movement in shaping population structure. In this case, the high
mobility of the Daubenton's bat facilitates greatly the transmission and spreading of *N.
kolenatii* and *S. andegavinus* between hosts within and across sampling sites. Population
genetics is a powerful approach for evaluating local genetic diversity and structure and
can be applied, for instance, to determine the likelihood of swarming at a particular site.
Bat flies and wing mites are known to be vectors of a wide diversity of pathogens such as
*Bartonella*, *Rickettsiae* and others (Jaenson & Wilhelmsson, 2021; Leulmi et al., 2016; McKee
et al., 2019; Thiévent et al. 2020; Tendu et al., 2022) and this study raises questions about
their role in the circulation of pathogens within bat metapopulations. Because of the high
connectivity between the vectors, a lack of barrier to pathogens dispersal among the
Daubenton's bats from the studied sampling sites could be expected. Studying the
spread of pathogens could be of interest in bat species carrying pathogens associated
with zoonotic disease (Nováková et al., 2009; Lack et al., 2011; Sándor et al., 2018, 2021;
Szentiványi et al., 2019, 2022). In general, this study gives insight in the ecology and
evolution of natural population of obligate specialized parasite of non-model species and
the role of the host in the spread of its parasites.

**Acknowledgements.** The authors would like to thank Marc Bastardot, Anouk Hoang and David Baumgartner for their help collecting the samples. Thanks to Anouk, David and Molly Baur for their help for the dissections. Thanks to Antoine Perrin for his useful
brainstorming. Finally, thanks to Zoé Dumas for her help improving the RAD protocol and
to Camille Thomas-Bulle for her invaluable advice on the manuscript.

**Data availability.** All scripts necessary to generate genomic data and perform analyses used in this study have been made available on https://github.com/clca98/PhD.

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# Supplementary Materials

## Appendices

### Appendix S1. Wing mite's resequencing.

After the first sequencing batch of wing mites, we obtained a total of 511'710'189 reads, with on average 1'122'171 reads per individuals. We used the same filters to create the catalog of loci than after resequencing. However, after the first filters (using *populations* function from the Stacks 2.53 software), and before using vcftools v0.1.16, we only obtained 1'888 SNPs, with a mean coverage per loci of 10.17X. Moreover, 316 individuals had more than 25% missing data. Generally, these individuals had low number of reads (Fig. 1). The goal of the resequencing was to increase the coverage, the number of final SNPs and to keep more individuals in the analysis.

<figure><img src="image_42.png" /><figcaption>**Fig. 1.** Reads and stacks coverage per individuals before the resequencing batch of wing mites. (A) Reads per individuals. In red, the 316 individuals having more than 25% of missing data. (B) Distribution of stacks coverage per individuals.</figcaption></figure>
**Appendix S2. Population genetics of bat flies on the entire dataset.**

At the individual level, the mean heterozygosity per individuals ranged from 0.062 to 0.101 with an average of 0.082. Pairwise kinship between individuals ranged from 6.057e⁻⁰⁶ to 0.463 with a mean of 0.046 (Fig. 1A). There were 117 pairs that had a kinship larger than 0.25 but one individual (553N1) was involved in 111 of these pairs and another one (508N1) in the 6 other pairs. These individuals were outliers in the distribution of the genotypes with low number of heterozygous sites and homozygous sites for the alternative allele (Fig. 1B; Table 1) and removing them did not affect the results (see Results section in the main manuscript).

At the population level, the distribution of the diversity was homogeneous across sampling sites but revealed some non-random mating the population. Mean heterozygosity per sampling sites ranged between 0.081 and 0.084, with a consistent level of individual heterozygosity across sampling sites (Kruskal-Wallis test: $\chi^2 = 10.423$, $p = 0.659$). However, the overall inbreeding coefficients ($F_{IS}$) of 0.028 (95% CI = [0.023; 0.034]) was significantly different from 0. This trend was similar for population-specific $F_{IS}$, ranging from -0.038 to 0.068, with confidence intervals of 11 out of 14 sampling sites not overlapping 0 (Fig. 1C; Table 2).

Population genetic analyses revealed high levels of connectivity among bat fly sampling sites. The overall fixation index was extremely low ($F_{ST}$ = 1.543e-05; 95% CI [-8.873e⁻⁰⁴; 8.885e⁻⁰⁴]), indicating little to no genetic differentiation across sampling sites. Consistently, pairwise $F_{ST}$ analysis between sampling sites ranged from 0.003 to -0.003, with all confidence intervals overlapping zero (Fig. 1D; Table 3). Estimates of average genetic kinship between sites ranged from -0.027 to 0.025 (Fig. 1D; Table 3), further supporting the absence of genetic structure.
<table><caption>Table 1. Information on kinship outliers (508N1 and 553N1).</caption><thead><tr><th></th><th>508N1</th><th>553N1</th></tr></thead><tbody><tr><td>Sampling site</td><td>10</td><td>11</td></tr><tr><td># links</td><td>6</td><td>111</td></tr><tr><td>Coverage</td><td>23.94</td><td>39.80</td></tr><tr><td>Proportion missing data</td><td>0.052</td><td>0.07</td></tr><tr><td>Heterozygosity</td><td>0.063</td><td>0.069</td></tr><tr><td>Inbreeding</td><td>0.175</td><td>-0.006</td></tr></tbody></table>

<table><caption>Table 2. Bat flies 95% confidence intervals for population-specific F<sub>IS</sub> and F<sub>ST</sub>.</caption><thead><tr><th>Sites</th><th>F<sub>IS</sub></th><th>F<sub>ST</sub></th></tr></thead><tbody><tr><td>All</td><td>0.028 [0.023;0.034]</td><td>4.448e-05 [-0.001;0.001]</td></tr><tr><td>1</td><td>0.031 [0.017;0.046]</td><td>-2.837e-02 [-0.052;-0.001]</td></tr><tr><td>2</td><td>0.040 [0.020;0.056]</td><td>3.716e-03 [-0.023;0.029]</td></tr><tr><td>3</td><td>0.011 [-0.012;0.028]</td><td>1.241e-02 [-0.023;0.043]</td></tr><tr><td>4</td><td>0.038 [0.022;0.051]</td><td>-1.326e-02 [-0.042;0.008]</td></tr><tr><td>5</td><td>0.042 [0.022;0.063]</td><td>-1.866e-03 [-0.027;0.030]</td></tr><tr><td>6</td><td>0.034 [0.016;0.048]</td><td>-8.768e-03 [-0.032;0.006]</td></tr><tr><td>7</td><td>0.005 [-0.030;0.034]</td><td>2.461e-02 [-0.012;0.063]</td></tr><tr><td>8</td><td>0.040 [0.020;0.057]</td><td>-6.047e-03 [-0.038;0.021]</td></tr><tr><td>9</td><td>0.019 [0.010;0.033]</td><td>-1.567e-02 [-0.038;0.006]</td></tr><tr><td>10</td><td>0.011 [-0.002;0.027]</td><td>2.228e-02 [0.0005;0.041]</td></tr><tr><td>11</td><td>0.016 [0.004;0.027]</td><td>8.111e-03 [-0.011;0.030]</td></tr><tr><td>12</td><td>0.0498 [0.035;0.062]</td><td>-1.974e-02 [-0.044;0.001]</td></tr><tr><td>13</td><td>0.0359 [0.016;0.054]</td><td>1.683e-03 [-0.025;0.027]</td></tr><tr><td>14</td><td>0.016 [0.002;0.033]</td><td>2.154e-02 [-0.0001;0.049]</td></tr></tbody></table>
<table><caption>**Table 3.** Bat flies 95% confidence intervals (CI) of F statistics among sampling sites. The lower matrix represents the 95% CI of the mean kinship between sampling sites based on the FsM matrix. The upper matrix represents the 95% CI of the pairwise F<sub>ST</sub> between sampling sites based on the Fst2x2 matrix.</caption><thead><tr><th></th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th><th>12</th><th>13</th><th>14</th></tr></thead><tbody><tr><td>1</td><td>0</td><td>0.001 [-0.032;0.004]</td><td>-0.002 [-0.025;0.014]</td><td>0.0002 [-0.032;-0.005]</td><td>0.002 [-0.030;0.005]</td><td>-0.001 [-0.031;-0.003]</td><td>0.001 [-0.029;0.018]</td><td>0.002 [-0.037;-0.005]</td><td>0.001 [-0.038;-0.009]</td><td>-0.0003 [-0.019;0.013]</td><td>0.001 [-0.024;0.002]</td><td>-0.001 [-0.037;-0.006]</td><td>0.001 [-0.030;0.008]</td><td>-0.002 [-0.021;0.013]</td></tr><tr><td>2</td><td>-0.014 [-0.032;0.004]</td><td>0</td><td>6.856e-05 [-0.011;0.025]</td><td>-1.134e-05 [-0.024;0.011]</td><td>-4.301e-04 [-0.017;0.018]</td><td>1.226e-03 [-0.022;0.010]</td><td>1.520e-03 [-0.013;0.035]</td><td>4.751e-04 [-0.026;0.013]</td><td>1.822e-03 [-0.024;0.006]</td><td>1.228e-03 [-0.006;0.028]</td><td>1.275e-03 [-0.011;0.018]</td><td>-2.638e-04 [-0.027;0.006]</td><td>8.720e-04 [-0.024;0.018]</td><td>2.195e-04 [-0.005;0.026]</td></tr><tr><td>3</td><td>-0.006 [-0.025;0.014]</td><td>0.006 [-0.011;-0.005]</td><td>0</td><td>-0.001 [-0.017;0.020]</td><td>0.003 [-0.014;0.021]</td><td>-0.002 [-0.014;0.021]</td><td>0.001 [-0.003;0.043]</td><td>0.0004 [-0.015;0.023]</td><td>0.001 [-0.020;0.016]</td><td>-0.002 [-0.009;0.030]</td><td>-0.001 [-0.009;0.030]</td><td>-0.001 [-0.020;0.015]</td><td>-0.0002 [-0.012;0.029]</td><td>-0.00003 [-0.001;0.035]</td></tr><tr><td>4</td><td>-0.020 [-0.032;0.025]</td><td>-0.006 [-0.024;0.011]</td><td>0.0003 [-0.017;0.020]</td><td>0</td><td>-3.858e-04 [-0.022;0.013]</td><td>-1.639e-03 [-0.022;0.004]</td><td>-3.041e-02 [-0.015;0.035]</td><td>9.720e-04 [-0.026;0.005]</td><td>-2.798e-05 [-0.029;0.002]</td><td>-3.219e-04 [-0.010;0.019]</td><td>-1.280e-04 [-0.014;0.009]</td><td>-5.685e-04 [-0.029;-0.003]</td><td>-4.796e-04 [-0.020;0.013]</td><td>-2.518e-05 [-0.013;0.020]</td></tr><tr><td>5</td><td>-1.479e-02 [-0.030;0.005]</td><td>7.233e-04 [-0.017;0.018]</td><td>2.835e-03 [-0.014;0.021]</td><td>-6.032e-03 [-0.022;0.013]</td><td>0</td><td>-0.001 [-0.017;0.012]</td><td>-0.002 [-0.015;0.037]</td><td>0.0004 [-0.020;0.010]</td><td>0.001 [-0.023;0.007]</td><td>0.001 [-0.006;0.026]</td><td>-0.0003 [-0.011;0.018]</td><td>0.001 [-0.028;0.001]</td><td>0.001 [-0.017;0.018]</td><td>-0.0005 [-0.004;0.029]</td></tr><tr><td>6</td><td>-0.017 [-0.031;-0.004]</td><td>-0.005 [-0.022;0.010]</td><td>0.003 [-0.014;0.021]</td><td>-0.009 [-0.022;0.004]</td><td>-0.004 [-0.017;0.012]</td><td>0</td><td>-0.002 [-0.013;0.032]</td><td>-0.001 [-0.027;0.008]</td><td>-0.0005 [-0.025;0.001]</td><td>-0.0004 [-0.007;0.020]</td><td>-0.0002 [-0.011;0.013]</td><td>-0.001 [-0.026;-0.002]</td><td>-0.001 [-0.019;0.014]</td><td>-0.001 [-0.011;0.021]</td></tr><tr><td>7</td><td>-0.002 [-0.029;0.018]</td><td>0.011 [-0.013;0.035]</td><td>0.017 [-0.003;0.043]</td><td>0.009 [-0.015;0.035]</td><td>0.014 [-0.015;0.037]</td><td>0.010 [-0.013;0.032]</td><td>0</td><td>0.001 [-0.017;0.031]</td><td>0.001 [-0.023;0.027]</td><td>-0.002 [0.003;0.045]</td><td>-0.001 [-0.004;0.037]</td><td>-0.003 [-0.015;0.026]</td><td>-0.003 [-0.006;0.036]</td><td>-0.001 [-0.006;0.05]</td></tr><tr><td>8</td><td>-0.019 [-0.037;-0.005]</td><td>-0.004 [-0.026;0.013]</td><td>0.001 [-0.015;0.023]</td><td>-0.011 [-0.026;0.005]</td><td>-0.004 [-0.020;0.010]</td><td>-0.007 [-0.027;0.008]</td><td>0.008 [-0.017;0.031]</td><td>0</td><td>0.001 [-0.031;0.004]</td><td>0.001 [-0.012;0.021]</td><td>-0.0004 [-0.015;0.014]</td><td>-0.0001 [-0.033;0.005]</td><td>0.001 [-0.022;0.017]</td><td>0.0002 [-0.010;0.023]</td></tr><tr><td>9</td><td>-0.021 [-0.038;-0.009]</td><td>-0.009 [-0.024;0.006]</td><td>-0.003 [-0.019;0.016]</td><td>-0.014 [-0.029;0.002]</td><td>-0.009 [-0.023;0.007]</td><td>-0.012 [-0.025;0.001]</td><td>0.004 [-0.023;0.027]</td><td>-0.013 [-0.031;0.004]</td><td>0</td><td>0.001 [-0.010;0.016]</td><td>0.001 [-0.018;0.012]</td><td>1.007e-05 [-0.033;-0.005]</td><td>-0.001 [-0.023;0.012]</td><td>0.001 [-0.015;0.019]</td></tr><tr><td>10</td><td>-0.003 [-0.019;0.013]</td><td>0.009 [-0.006;0.028]</td><td>0.018 [-0.002;0.038]</td><td>0.004 [-0.010;0.019]</td><td>0.010 [-0.006;0.026]</td><td>0.006 [-0.007;0.020]</td><td>0.025 [0.003;0.045]</td><td>0.006 [-0.012;0.021]</td><td>0.002 [-0.010;0.016]</td><td>0</td><td>0.001 [0.0002;0.026]</td><td>-0.001 [-0.013;0.015]</td><td>0.001 [-0.008;0.025]</td><td>0.0003 [0.004;0.036]</td></tr><tr><td>11</td><td>-0.010 [-0.024;0.002]</td><td>0.004 [-0.012;0.018]</td><td>0.011 [-0.009;0.030]</td><td>-0.002 [-0.014;0.009]</td><td>0.005 [-0.011;0.018]</td><td>0.0002 [-0.011;0.013]</td><td>0.018 [-0.004;0.037]</td><td>0.001 [-0.015;0.014]</td><td>-0.004 [-0.018;0.012]</td><td>0.014 [0.0002;0.0263]</td><td>0</td><td>-0.0003 [-0.020;0.007]</td><td>0.002 [-0.013;0.019]</td><td>0.001 [-0.003;0.030]</td></tr><tr><td>12</td><td>-0.022 [-0.037;-0.006]</td><td>-0.009 [-0.027;0.006]</td><td>-0.003 [-0.020;0.015]</td><td>-0.016 [-0.029;-0.003]</td><td>-0.011 [-0.028;0.001]</td><td>-0.013 [-0.026;-0.002]</td><td>0.005 [-0.015;0.026]</td><td>-0.014 [-0.033;0.005]</td><td>-0.018 [-0.033;-0.005]</td><td>0.001 [-0.013;0.015]</td><td>-0.005 [-0.019;0.007]</td><td>0</td><td>-0.001 [-0.023;0.006]</td><td>0.001 [-0.014;0.014]</td></tr><tr><td>13</td><td>-1.340e-02 [-0.030;0.008]</td><td>4.127e-04 [-0.024;0.018]</td><td>7.119e-03 [-0.012;0.029]</td><td>-4.947e-03 [-0.020;0.013]</td><td>5.669e-06 [-0.017;0.018]</td><td>-2.963e-03 [-0.019;0.014]</td><td>1.594e-02 [-0.006;0.036]</td><td>-3.856e-03 [-0.022;0.017]</td><td>-5.473e-03 [-0.023;0.012]</td><td>1.031e-02 [-0.008;0.025]</td><td>4.031e-03 [-0.013;0.019]</td><td>-7.901e-03 [-0.023;0.006]</td><td>0</td><td>0.002 [-0.008;0.025]</td></tr><tr><td>14</td><td>-0.0001 [-0.021;0.013]</td><td>0.011 [-0.005;0.026]</td><td>0.017 [-0.001;0.035]</td><td>0.005 [-0.013;0.020]</td><td>0.012 [-0.004;0.029]</td><td>0.008 [-0.011;0.021]</td><td>0.24 [-0.006;0.050]</td><td>0.007 [-0.010;0.023]</td><td>0.003 [-0.015;0.019]</td><td>0.021 [0.004;0.036]</td><td>0.015 [-0.003;0.030]</td><td>0.001 [-0.014;0.014]</td><td>0.010 [-0.008;0.025]</td><td>0</td></tr></tbody></table>
A

<figure><img src="image_43.png" /></figure>

B

<figure><img src="image_44.png" /></figure>

C

<figure><img src="image_45.png" /></figure>

D

<figure><img src="image_46.png" /><figcaption>**Fig. 1.** Population genetics of bat flies on the entire dataset. (A) Distribution of the pairwise kinship between individuals. (B) Distribution of the genotypes of each individual. Triangles represent the two individuals related to the others. In orange, 508N1 and in blue 553N1. (C) Population-specific F<sub>IS</sub>. (D) Heatmap of the mean kinship and pairwise F<sub>ST</sub> over pairs of sampling sites. The upper matrix is the mean kinship between sites (FsM), high values represent pairs of populations whose individuals are more closely related to each other than to individuals from other populations. The diagonal represents the intra-populational mean kinship (population-specific F<sub>ST</sub>) and the and lower matrix represent the pairwise F<sub>ST</sub> (Fst2x2).</figcaption></figure>
**Appendix S3. Population genetics of the wing mites on the entire dataset.**

At the individual level, the mean heterozygosity per individuals ranged from 0.102 to 0.175 with an average of 0.157. Pairwise kinship between individuals ranged from -0.078 to 0.463 with a mean of 2.982e⁻⁰⁴ (Fig. 1A). There were 276 pairs that had a kinship higher than 0.2 but one individual (498S1) was involved in 164 of these pairs and another one (792S2) in 103 others. These individuals did not come from the same site, had high percentage of missing data compared to the filter used, high inbreeding coefficients (Table 1). They were outliers in the distribution of the genotypes with low number of heterozygous sites and homozygous sites for the alternative allele (Fig. 1B) and removing them did not affect the results (see Results section in the main manuscript). A pair of individuals from the different sampling site had a kinship close to 0.5, suggesting potential twins (477S2 from site 5 and 486S1 from site 10; *k* = 0.463). They had low inbreeding coefficients (0.094 for both), high coverage (20.23X and 27.01X, respectively) but they had a high proportion of missing data (0.216 and 0.185, respectively).

Heterozygosity of the wing mites showed little but significant variation between sampling sites, ranging from 0.144 to 0.162 (Kruskal Wallis: $\chi^2 = 23.4, p = 0.037$), but a post-hoc test revealed that this significance is explained by the difference between site 7 (N = 6) and site 11 (N = 30) (Tukey test: *p* = 0.0082) and the differences between all the other pairs of sites were not. Population-specific $F_{ST}$ were consistent with all sampling site having low values. However, only the sampling site 7 had a high value with a mean of 0.131 and eight sampling sites had confidence intervals that did not overlap 0 (Fig. 1C; Table 2). The population-specific $F_{IS}$ were low (ranging from -0.03 to 0.115 with an overall population-specific $F_{IS}$ of 0.052), yet confidence intervals of 13 out of 14 sampling sites did not overlap 0, suggesting substructure in the metapopulation (Fig. 1D; Table 2).

Population genetic analyses revealed low levels of structure among the wing mites sampling sites. The overall fixation index was low ($F_{ST} = 0.003$; 95% CI [0.0018; 0.0034]) and individuals were scattered in the PCA without any clear clustering according to the sampling site (Fig. 1E). Two individuals from the same site clustered together (535S2 and 544S2 from site 11; Fig. 1E). They were not outliers in terms of the distribution of their genotypes (Fig. 1B), nor in terms of coverage, proportion of missing data and heterozygosity (Table 1). However, their kinship was 0.264. Removing them did not influence the clustering in the PCA (see Results section in the main manuscript). Consistently, pairwise $F_{ST}$ analysis between sampling sites revealed low values, ranging from -0.003 to 0.007 (Fig. 1E; Table 3), The mean kinship between sampling sites were low and ranged from -0.027 and 0.132 (Fig. 1E; Table 3), supporting a high connectivity between sampling sites.
<table><caption>Table 1. Information on the outliers of the kinship and on the outliers clustering together in the PCA.</caption><thead><tr><th></th><th>498S1</th><th>792S2</th><th>535S2</th><th>544S2</th></tr></thead><tbody><tr><th>Sampling site</th><td>10</td><td>7</td><td>11</td><td>11</td></tr><tr><th>Coverage</th><td>38.15</td><td>36.73</td><td>23.87</td><td>27.42</td></tr><tr><th>Proportion missing data</th><td>0.268</td><td>0.216</td><td>0.065</td><td>0.061</td></tr><tr><th>Heterozygosity</th><td>0.124</td><td>0.128</td><td>0.172</td><td>0.170</td></tr><tr><th>Inbreeding</th><td>0.120</td><td>0.117</td><td>-0.034</td><td>-0.018</td></tr></tbody></table>

<table><caption>Table 2. Wing mites 95% confidence intervals for population-specific F<sub>IS</sub> and F<sub>ST</sub>.</caption><thead><tr><th>Sites</th><th>F<sub>IS</sub></th><th>F<sub>ST</sub></th></tr></thead><tbody><tr><td>All</td><td>0.052 [0.048;0.054]</td><td>0.003 [0.002;0.0034]</td></tr><tr><td>1</td><td>0.039 [0.030;0.046]</td><td>0.005 [-0.005;0.014]</td></tr><tr><td>2</td><td>0.048 [0.39;0.056]</td><td>-0.023 [-0.036;-0.012]</td></tr><tr><td>3</td><td>0.073 [0.063;0.084]</td><td>-0.011 [-0.026;0.003]</td></tr><tr><td>4</td><td>0.057 [0.048;0.067]</td><td>0.0098 [-0.001;0.022]</td></tr><tr><td>5</td><td>0.046 [0.036;0.055]</td><td>-0.017 [0.029;-0.005]</td></tr><tr><td>6</td><td>0.089 [0.079;0.101]</td><td>-0.015 [-0.027;-0.006]</td></tr><tr><td>7</td><td>-0.007 [-0.023;0.008]</td><td>0.132 [0.119;0.149]</td></tr><tr><td>8</td><td>0.059 [0.052;0.065]</td><td>-0.026 [-0.035;-0.017]</td></tr><tr><td>9</td><td>0.066 [0.052;0.078]</td><td>-0.008 [-0.022;0.007]</td></tr><tr><td>10</td><td>0.019 [0.012;0.025]</td><td>0.024 [0.016;0.032]</td></tr><tr><td>11</td><td>0.042 [0.037; 0.046]</td><td>-0.025 [-0.031;-0.018]</td></tr><tr><td>12</td><td>0.050 [0.042;0.058]</td><td>-0.015 [-0.025;-0.008]</td></tr><tr><td>13</td><td>0.042 [0.027;0.052]</td><td>0.009 [-0.001;0.021]</td></tr><tr><td>14</td><td>0.099 [0.089;0.111]</td><td>-0.005 [-0.020;0.010]</td></tr></tbody></table>
<table><caption>**Table 3.** Wing mites 95% confidence intervals (CI) of F statistics among sampling sites. The lower matrix represents the 95% CI of the mean kinship between sampling sites based on the FsM matrix. The upper matrix represents the 95% CI of the pairwise FST between sampling sites based on the Fst2x2 matrix.</caption><thead><tr><th></th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th><th>12</th><th>13</th><th>14</th></tr></thead><tbody><tr><td>1</td><td>0</td><td>0.003<br/>[0.001;0.005]</td><td>8.606e-04 [-<br/>0.002;0.003]</td><td>0.003<br/>[0.001;0.005]</td><td>0.004<br/>[0.002;0.006]</td><td>0.003<br/>[0.001;0.005]</td><td>0.004 [-<br/>0.001;0.008]</td><td>1.045e-03 [-<br/>0.0006;0.003]</td><td>0.004<br/>[0.0015;0.007]</td><td>1.257e-03 [-<br/>0.0004;0.003]</td><td>0.003<br/>[0.002;0.006]</td><td>2.153e-03<br/>[0.0006;0.004]</td><td>0.004<br/>[0.002;0.007]</td><td>0.004<br/>[0.0015;0.007]</td></tr><tr><td>2</td><td>-0.012<br/>[0.0005;0.005]</td><td>0</td><td>1.407e-03 [-<br/>0.002;0.004]</td><td>0.004<br/>[0.002;0.006]</td><td>0.005<br/>[0.002;0.008]</td><td>0.002 [-<br/>4.335e-<br/>05;4.807e-03]</td><td>0.0007 [-<br/>0.003;0.005]</td><td>8.352e-04 [-<br/>0.0012;0.002]</td><td>0.004<br/>[0.0012;0.008]</td><td>1.667e-03 [-<br/>0.0003;0.003]</td><td>0.003<br/>[0.0016;0.005]</td><td>3.381e-03<br/>[0.002;0.005]</td><td>0.004<br/>[0.0013;0.007]</td><td>0.006<br/>[0.0025;0.008]</td></tr><tr><td>3</td><td>-0.004 [-<br/>0.021;0.004]</td><td>-0.018 [-<br/>0.024;-0.011]</td><td>0</td><td>0.001 [-<br/>0.002;0.005]</td><td>0.003 [-<br/>0.001;0.007]</td><td>-0.001 [-<br/>0.004;0.002]</td><td>-0.003 [-<br/>0.007;0.002]</td><td>-2.243e-03 [-<br/>5.100e-<br/>03;7.374e-05]</td><td>0.004 [-<br/>0.0003;0.008]</td><td>-6.532e-03 [-<br/>0.003;0.002]</td><td>0.001 [-<br/>0.0008;0.0035]</td><td>-3.866e-04 [-<br/>0.003;0.002]</td><td>0.003 [-<br/>0.00046;0.0065]</td><td>0.004<br/>[0.00015;0.008]</td></tr><tr><td>4</td><td>0.005 [-<br/>0.010;0.013]</td><td>-0.010 [-<br/>0.017;-0.003]</td><td>-0.001 [-<br/>0.009;0.006]</td><td>0</td><td>0.003 [-<br/>0.0001;0.006]</td><td>0.001 [-<br/>0.001;0.004]</td><td>0.002 [-<br/>0.003;0.006]</td><td>2.492e-03<br/>[0.0004;0.0047]</td><td>0.005<br/>[0.002;0.008]</td><td>3.083e-03<br/>[0.0013;0.005]</td><td>0.003<br/>[0.002;0.005]</td><td>2.314e-03<br/>[0.0002;0.0044]</td><td>0.005<br/>[0.002;0.008]</td><td>0.006<br/>[0.003;0.010]</td></tr><tr><td>5</td><td>-0.010 [-<br/>0.017;-0.004]</td><td>-0.025 [-<br/>0.033;-0.017]</td><td>-0.017 [-<br/>0.027;-0.009]</td><td>-0.006 [-<br/>0.015;0.003]</td><td>0</td><td>0.0025 [-<br/>0.001;0.006]</td><td>0.005<br/>[0.001;0.010]</td><td>2.537e-03<br/>[0.0001;0.0055]</td><td>0.005<br/>[0.0017;0.008]</td><td>1.730e-03 [-<br/>0.0004;0.004]</td><td>0.004<br/>[0.002;0.006]</td><td>2.549e-03 [-<br/>0.0004;0.005]</td><td>0.003<br/>[0.0007;0.007]</td><td>0.006<br/>[0.002;0.010]</td></tr><tr><td>6</td><td>-0.008 [-<br/>0.014;-0.001]</td><td>-0.021 [-<br/>0.027;-0.015]</td><td>-0.012 [-<br/>0.020;-0.004]</td><td>-0.003 [-<br/>0.010;0.005]</td><td>-0.019 [-<br/>0.027;-0.012]</td><td>0</td><td>-0.003 [-<br/>0.007;0.002]</td><td>1.048e-03 [-<br/>0.0015;0.003]</td><td>0.002 [-<br/>0.0007;0.005]</td><td>-1.525e-04 [-<br/>0.002;0.001]</td><td>0.003<br/>[0.001;0.005]</td><td>-5.052e-04 [-<br/>0.003;0.002]</td><td>0.003 [-<br/>0.0001;0.006]</td><td>0.003 [-<br/>0.0005;0.0066]</td></tr><tr><td>7</td><td>0.065<br/>[0.056;0.073]</td><td>0.054<br/>[0.045;0.061]</td><td>0.063 [-<br/>0.052;0.072]</td><td>0.070<br/>[0.059;0.077]</td><td>0.053<br/>[0.040;0.061]</td><td>0.062<br/>[0.053;0.072]</td><td>0</td><td>9.341e-04 [-<br/>0.003;0.004]</td><td>0.0004 [-<br/>0.004;0.0047]</td><td>6.668e-04 [-<br/>0.003;0.004]</td><td>0.003 [-<br/>0.0003;0.006]</td><td>1.746e-04 [-<br/>0.003;0.003]</td><td>0.007<br/>[0.0025;0.012]</td><td>0.002 [-<br/>0.002;0.006]</td></tr><tr><td>8</td><td>-0.011 [-<br/>0.018;-0.005]</td><td>-0.025 [-<br/>0.033;-0.018]</td><td>-0.016 [-<br/>0.022;-0.008]</td><td>-0.010 [-<br/>0.016;-0.003]</td><td>-0.024 [-<br/>0.031;-0.018]</td><td>-0.021 [-<br/>0.027;-0.015]</td><td>0.052<br/>[0.043;0.059]</td><td>0</td><td>0.003<br/>[0.0002;0.005]</td><td>4.797e-04 [-<br/>0.0012;0.0017]</td><td>0.0008[-<br/>0.0004;0.002]</td><td>-8.441e-05 [-<br/>0.0015;0.0013]</td><td>0.003<br/>[0.0008;0.0056]</td><td>0.001 [-<br/>0.002;0.004]</td></tr><tr><td>9</td><td>-0.006 [-<br/>0.014;0.002]</td><td>-0.021 [-<br/>0.030;-0.014]</td><td>-0.014 [-<br/>0.022;-0.007]</td><td>-0.004 [-<br/>0.013;0.004]</td><td>-0.018 [-<br/>0.029;-0.010]</td><td>-0.014 [-<br/>0.022;-0.005]</td><td>0.061<br/>[0.050;0.070]</td><td>-0.020 [-0.028;-<br/>0.014]</td><td>0</td><td>2.169e-03 [-<br/>0.0004;0.005]</td><td>0.004<br/>[0.002;0.007]</td><td>3.529e-03<br/>[0.0008;0.006]</td><td>0.003 [-<br/>0.0005;0.007]</td><td>0.003 [-<br/>0.0008;0.0067]</td></tr><tr><td>10</td><td>0.014<br/>[0.009;0.021]</td><td>-0.001 [-<br/>0.009;0.006]</td><td>0.007 [-<br/>0.0002;0.013]</td><td>0.015<br/>[0.008;0.023]</td><td>0.002 [-<br/>0.006;0.009]</td><td>0.005 [-<br/>0.002;0.012]</td><td>0.078<br/>[0.068;0.086]</td><td>-0.001 [-<br/>0.0065;0.005]</td><td>0.006 [-<br/>0.002;0.014]</td><td>0</td><td>0.001<br/>[0.0003;0.0026]</td><td>1.837e-03<br/>[0.0003;0.003]</td><td>0.004<br/>[0.002;0.006]</td><td>0.002 [-<br/>0.0007;0.004]</td></tr><tr><td>11</td><td>-0.014 [-<br/>0.019;-0.007]</td><td>-0.027 [-<br/>0.033;-0.021]</td><td>-0.019 [-<br/>0.025;-0.012]</td><td>-0.010 [-<br/>0.017;-0.003]</td><td>-0.025 [-<br/>0.032;-0.019]</td><td>-0.023 [-<br/>0.029;-0.017]</td><td>0.051<br/>[0.042;0.058]</td><td>-0.026 [-0.032;-<br/>0.020]</td><td>-0.021 [-<br/>0.028;-0.013]</td><td>-0.0016 [-<br/>0.009;0.003]</td><td>0</td><td>1.733e-03<br/>[0.0006;0.003]</td><td>0.005<br/>[0.003;0.007]</td><td>0.003<br/>[0.001;0.006]</td></tr><tr><td>12</td><td>-0.008 [-<br/>1.398e-02;-<br/>2.525e-05]</td><td>-0.023 [-<br/>0.029;-0.016]</td><td>-0.13 [-<br/>0.0195;-0.006]</td><td>-0.005 [-<br/>0.012;0.001]</td><td>-0.019 [-<br/>0.027;-0.013]</td><td>-0.015 [-<br/>0.021;-0.008]</td><td>0.058<br/>[0.048;0.064]</td><td>-0.021 [-0.027;-<br/>0.013]</td><td>-0.016 [-<br/>0.024;-0.007]</td><td>0.0026 [-<br/>0.004;0.008]</td><td>-0.022 [-0.029;-<br/>0.014]</td><td>0</td><td>0.004<br/>[0.0017;0.006]</td><td>0.003<br/>[0.0003;0.006]</td></tr><tr><td>13</td><td>0.003 [-<br/>0.005;0.011]</td><td>-0.011 [-<br/>0.018;-0.003]</td><td>-0.004 [-<br/>0.012;0.003]</td><td>0.005 [-<br/>0.002;0.015]</td><td>-0.008 [-<br/>0.015;0.0001]</td><td>-0.006 [-<br/>0.013;0.0026]</td><td>0.064<br/>[0.055;0.074]</td><td>-0.012 [-<br/>0.0185;-0.006]</td><td>-0.003 [-<br/>0.013;0.0046]</td><td>0.013<br/>[0.0051;0.020]</td><td>-0.013 [-0.018;-<br/>0.006]</td><td>-0.0076 [-<br/>1.396e-02;8-<br/>682e-05]</td><td>0</td><td>0.007<br/>[0.004;0.011]</td></tr><tr><td>14</td><td>-0.004 [-<br/>0.012;0.004]</td><td>-0.020 [-<br/>0.028;-0.012]</td><td>-0.012 [-<br/>0.021;-0.002]</td><td>-0.003 [-<br/>0.010;0.007]</td><td>-0.017 [-<br/>0.026;-0.009]</td><td>-0.013 [-<br/>0.022;-0.003]</td><td>0.062<br/>[0.052;0.073]</td><td>-0.016 [-0.024;-<br/>0.009]</td><td>-0.010 [-<br/>0.018;0.0016]</td><td>0.008<br/>[0.0012;0.016]</td><td>-0.018 [-0.025;-<br/>0.010]</td><td>-0.014 [-0.022;-<br/>0.005]</td><td>-0.005 [-<br/>0.012;0.003]</td><td>0</td></tr></tbody></table>
A

<figure><img src="image_47.png" /></figure>

B

<figure><img src="image_48.png" /></figure>

C

<figure><img src="image_49.png" /></figure>

D

<figure><img src="image_50.png" /></figure>

E

<figure><img src="image_51.png" /></figure>

F

<figure><img src="image_52.png" /></figure>
**Fig. 1. Population genetics of wing mites on the entire dataset.** (A) Distribution of the pairwise kinship between individuals. (B) Distribution of the genotypes of each individual. Triangles represent the outliers in the kinship and the PCA. In blue 498S1, in orange 792S2, in red 535S2 and in green 544S2. (C) Population-specific $F_{ST}$. (D) Population-specific $F_{IS}$. (E) Principal component analysis. (F) Heatmap of the mean kinship and pairwise $F_{ST}$ over pairs of sampling sites. The upper matrix is the mean kinship between sites (FsM), high values represent pairs of populations whose individuals are more closely related to each other than to individuals from other populations. The diagonal represents the intra-populational mean kinship (population-specific $F_{ST}$) and the and lower matrix represent the pairwise $F_{ST}$ (Fst2x2).
Supplementary Tables

<table><caption>Table S1. Filters used per species and number of SNPs at each filtering step.</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Filters</th><th colspan="2">Bat flies</th><th colspan="2">Wing mites</th></tr><tr><th>Thresholds</th><th>#SNPs</th><th>Thresholds</th><th>#SNPs</th></tr></thead><tbody><tr><td rowspan="3">Loci calling</td><td>mismatch threshold (M)</td><td>3</td><td></td><td>5</td><td></td></tr><tr><td>coverage threshold within individuals (m)</td><td>4</td><td></td><td>3</td><td></td></tr><tr><td>coverage threshold between individuals (n)</td><td>4</td><td></td><td>6</td><td></td></tr><tr><td rowspan="2">SNPs calling</td><td>% sharing within sampling sites (r)</td><td>60</td><td>13596</td><td>60</td><td>92807</td></tr><tr><td>% sharing among sampling sites (R)</td><td>60</td><td>13596</td><td>60</td><td>92807</td></tr><tr><td>Individuals filtering</td><td>Individual missing data (%)</td><td>25</td><td>30 individuals removed</td><td>25</td><td>285 individuals removed</td></tr><tr><td rowspan="6">SNPs filtering</td><td>Minimum coverage</td><td>5</td><td>13596</td><td>10</td><td>92807</td></tr><tr><td>Loci missing data (%)</td><td>20</td><td>10016</td><td>30</td><td>37199</td></tr><tr><td>Mean minimum coverage</td><td>10</td><td>9900</td><td>20</td><td>36658</td></tr><tr><td>Mean maximum coverage</td><td>65</td><td>9900</td><td>60</td><td>36658</td></tr><tr><td>Hardy-Weinberg equilibrium</td><td>0.05</td><td>7597</td><td>0.05</td><td>32811</td></tr><tr><td>Minor allele count</td><td>5</td><td>1544</td><td>5</td><td>9525</td></tr></tbody></table>
<table><caption>Table S2. Bat flies and wing mites 95% confidence intervals for population-specific F<sub>IS</sub> and F<sub>ST</sub> without the outlier individuals.</caption><thead><tr><th rowspan="2">Sites</th><th colspan="2">Bat flies</th><th colspan="2">Wing mites</th></tr><tr><th>F<sub>IS</sub></th><th>F<sub>ST</sub></th><th>F<sub>IS</sub></th><th>F<sub>ST</sub></th></tr></thead><tbody><tr><td>All</td><td>0.028 [0.022;0.033]</td><td>-7.923e-05 [-0.001;0.001]</td><td>0.063 [0.060;0.065]</td><td>0.001 [0.0006;0.003]</td></tr><tr><td>1</td><td>0.031 [0.013;0.045]</td><td>-0.026 [-0.053;0.001]</td><td>0.052 [0.044;0.060]</td><td>0.0002 [-0.011;0.010]</td></tr><tr><td>2</td><td>0.040 [0.018;0.069]</td><td>0.002 [-0.022;0.026]</td><td>0.049 [0.39;0.059]</td><td>-0.010 [-0.023;0.001]</td></tr><tr><td>3</td><td>0.009 [-0.013;0.029]</td><td>0.013 [-0.010;0.042]</td><td>0.072 [0.061;0.084]</td><td>0.004 [-0.008;0.021]</td></tr><tr><td>4</td><td>0.036 [0.021;0.051]</td><td>-0.012 [-0.034;0.013]</td><td>0.058 [0.049;0.066]</td><td>0.025 [0.016;0.036]</td></tr><tr><td>5</td><td>0.042 [0.027;0.056]</td><td>-0.002 [-0.026;0.029]</td><td>0.047 [0.037;0.059]</td><td>-0.004 [-0.016;0.009]</td></tr><tr><td>6</td><td>0.034 [0.018;0.047]</td><td>-0.009 [-0.033;0.008]</td><td>0.089 [0.080;0.096]</td><td>0.0004 [-0.011;0.012]</td></tr><tr><td>7</td><td>0.005 [-0.024;0.034]</td><td>0.021 [-0.016;0.058]</td><td>0.090 [0.072;0.108]</td><td>0.026 [0.007;0.046]</td></tr><tr><td>8</td><td>0.040 [0.020;0.057]</td><td>-0.007 [-0.031;0.019]</td><td>0.058 [0.050;0.066]</td><td>-0.011 [-0.021;-0.003]</td></tr><tr><td>9</td><td>0.019 [0.005;0.033]</td><td>-0.017 [-0.036;0.006]</td><td>0.067 [0.057;0.079]</td><td>0.005 [-0.008;0.016]</td></tr><tr><td>10</td><td>0.011 [0.001;0.023]</td><td>0.021 [-0.0002;0.038]</td><td>0.046 [0.037;0.055]</td><td>-0.010 [-0.018;-0.002]</td></tr><tr><td>11</td><td>0.016 [0.005;0.025]</td><td>0.009 [-0.011;0.027]</td><td>0.043 [0.038; 0.049]</td><td>-0.010 [-0.017;-0.005]</td></tr><tr><td>12</td><td>0.050 [0.037;0.064]</td><td>-0.021 [-0.043;-0.003]</td><td>0.050 [0.043;0.058]</td><td>-0.001 [-0.009;0.009]</td></tr><tr><td>13</td><td>0.036 [0.018;0.053]</td><td>0.002 [-0.029;0.033]</td><td>0.062 [0.052;0.073]</td><td>-0.003 [-0.014;0.011]</td></tr><tr><td>14</td><td>0.018 [0.003;0.032]</td><td>0.021 [0.0003;0.042]</td><td>0.098 [0.084;0.111]</td><td>0.009 [-0.006;0.021]</td></tr></tbody></table>
<table><caption>**Table S3.** Bat flies 95% confidence intervals (CI) of F statistics among sampling sites without the outlier individuals. The lower matrix represents the 95% CI of the mean kinship between sampling sites based on the FsM matrix. The upper matrix represents the 95% CI of the pairwise F<sub>ST</sub> between sampling sites based on the Fst2x2 matrix.</caption><thead><tr><th></th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th><th>12</th><th>13</th><th>14</th></tr></thead><tbody><tr><td>1</td><td>0</td><td>0.001 [-0.002;0.004]</td><td>-0.002 [-0.005;0.001]</td><td>-2.719e-04 [-0.002;0.002]</td><td>0.001 [-0.001;0.005]</td><td>-0.001 [-0.003;0.0008]</td><td>0.002 [-0.005;0.005]</td><td>0.003 [-0.001;0.004]</td><td>0.001 [-0.002;0.003]</td><td>2.383e-04 [-0.002;0.001]</td><td>0.001 [-0.001;0.003]</td><td>-0.0005 [-0.003;0.001]</td><td>0.001 [-0.003;0.004]</td><td>-0.0006 [-3.747e-03;1.026e-05]</td></tr><tr><td>2</td><td>-0.003 [-0.028;0.003]</td><td>0</td><td>-0.0004 [-0.003;0.002]</td><td>-4.908e-05 [-0.003;0.0026]</td><td>-0.0003 [-0.004;0.003]</td><td>0.002 [-0.001;0.004]</td><td>0.002 [-0.005;0.008]</td><td>0.0005 [-0.003;0.003]</td><td>0.002 [-0.001;0.004]</td><td>2.129e-03 [-0.001;0.004]</td><td>0.002 [-0.001;0.003]</td><td>0.0001 [-0.003;0.002]</td><td>0.002 [-0.004;0.004]</td><td>0.003 [-0.002;0.003]</td></tr><tr><td>3</td><td>-0.002 [-0.024;0.017]</td><td>0.007 [-0.009;0.022]</td><td>0</td><td>-2.210e-03 [-0.003;0.002]</td><td>0.003 [-0.0006;0.007]</td><td>-0.003 [-0.004;0.001]</td><td>0.001 [-0.006;0.007]</td><td>-0.001 [-0.003;0.003]</td><td>-0.0002 [-0.002;0.004]</td><td>-3.077e-03 [-0.004;0.0006]</td><td>-0.0016 [-0.003;0.001]</td><td>-0.002 [-0.003;0.002]</td><td>-0.0002 [-0.003;0.0025]</td><td>-0.001 [-0.003;0.003]</td></tr><tr><td>4</td><td>-0.008 [-0.037;0.001]</td><td>0.002 [-0.021;0.009]</td><td>0.003 [-0.014;0.022]</td><td>0</td><td>-0.001 [-0.003;0.002]</td><td>-0.002 [-0.004;0.0008]</td><td>-0.001 [-0.008;0.002]</td><td>0.001 [-0.001;0.003]</td><td>-0.001 [-0.0026;0.003]</td><td>-5.518e-04 [-0.002;0.0016]</td><td>-0.0005 [-0.002;0.002]</td><td>-0.0006 [-0.003;0.002]</td><td>-0.0006 [-0.004;0.003]</td><td>0.0005 [-0.002;0.003]</td></tr><tr><td>5</td><td>-0.011 [-0.031;0.005]</td><td>0.001 [-0.019;0.020]</td><td>-0.003 [-0.011;0.021]</td><td>0</td><td>-0.004 [-0.022;0.015]</td><td>0</td><td>-0.001 [-0.003;0.0016]</td><td>0.0001 [-0.008;0.004]</td><td>0.002 [-0.002;0.003]</td><td>1.042e-03 [-0.002;0.003]</td><td>-0.001 [-0.002;0.002]</td><td>0.001 [-0.001;0.004]</td><td>0.002 [-0.002;0.0045]</td><td>0.001 [-0.003;0.002]</td></tr><tr><td>6</td><td>-0.012 [-0.033;0.0002]</td><td>-0.005 [-0.023;0.011]</td><td>-0.0005 [-0.012;0.020]</td><td>-0.006 [-0.024;0.006]</td><td>-0.008 [-0.023;0.013]</td><td>0</td><td>0.002 [-0.009;0.003]</td><td>-0.001 [-0.003;0.0002]</td><td>-0.0003 [-0.002;0.0016]</td><td>4.257e-06 [-0.002;0.001]</td><td>-0.0007 [-0.002;0.001]</td><td>-0.001 [-0.003;0.0004]</td><td>0.001 [-0.003;0.002]</td><td>-0.0001 [-0.002;0.001]</td></tr><tr><td>7</td><td>-0.007 [-0.025;0.017]</td><td>0.004 [-0.014;0.034]</td><td>0.003 [-0.001;0.044]</td><td>0.0007 [-0.014;0.031]</td><td>-0.002 [-0.011;0.032]</td><td>-0.007 [-0.014;0.029]</td><td>0</td><td>0.003 [-0.006;0.006]</td><td>0.003 [-0.006;0.007]</td><td>-3.455e-04 [-0.007;0.002]</td><td>0.0004 [-0.007;0.004]</td><td>0.0008 [-0.010;0.002]</td><td>0.0001 [-0.009;0.003]</td><td>0.002 [-0.007;0.005]</td></tr><tr><td>8</td><td>-0.020 [-0.036;-0.003]</td><td>-0.007 [-0.021;0.015]</td><td>-0.006 [-0.013;0.021]</td><td>-0.013 [-0.027;0.007]</td><td>-0.013 [-0.024;0.015]</td><td>-0.016 [-0.025;0.009]</td><td>-0.012 [-0.014;0.030]</td><td>0</td><td>0.001 [-0.0007;0.0035]</td><td>5.930e-04 [-0.001;0.003]</td><td>-0.001 [-0.002;0.001]</td><td>0.0009 [-0.002;0.002]</td><td>0.002 [-0.0017;0.0039]</td><td>0.002 [-0.002;0.002]</td></tr><tr><td>9</td><td>-0.012 [-0.037;-0.004]</td><td>-0.002 [-0.026;0.007]</td><td>-0.001 [-0.019;0.012]</td><td>-0.005 [-0.030;-5.323e-05]</td><td>-0.009 [-0.027;0.010]</td><td>-0.010 [-0.027;0.001]</td><td>-0.005 [-0.018;0.026]</td><td>-0.016 [-0.031;-0.001]</td><td>0</td><td>5.060e-04 [-0.0007;0.003]</td><td>0.0002 [-0.0005;0.003]</td><td>0.0004 [-0.002;0.002]</td><td>-0.0005 [-0.003;0.001]</td><td>0.003 [-0.0007;0.003]</td></tr><tr><td>10</td><td>0.006 [-0.016;0.012]</td><td>0.015 [-0.007;0.023]</td><td>0.019 [-0.002;0.037]</td><td>0.012 [-0.011;0.021]</td><td>0.009 [-0.008;0.030]</td><td>0.007 [-0.008;0.018]</td><td>0.015 [-0.003;0.045]</td><td>0.002 [-0.009;0.019]</td><td>0.010 [-0.016;0.013]</td><td>0</td><td>0.0005 [-0.001;0.002]</td><td>-0.0003 [-0.002;0.001]</td><td>0.002 [-0.0015;0.004]</td><td>0.001 [-0.001;0.002]</td></tr><tr><td>11</td><td>-0.010 [-0.025;0.009]</td><td>0.0002 [-0.008;0.018]</td><td>0.002 [-0.002;0.028]</td><td>-0.004 [-0.017;0.015]</td><td>-0.004 [-0.012;0.021]</td><td>-0.008 [-0.018;0.012]</td><td>-0.001 [-0.002;0.037]</td><td>-0.012 [-0.016;0.013]</td><td>-0.006 [-0.018;0.008]</td><td>0.011 [-0.001;0.028]</td><td>0</td><td>-0.0003 [-0.002;0.001]</td><td>0.001 [-0.0009;0.004]</td><td>0.001 [-0.001;0.003]</td></tr><tr><td>12</td><td>-0.007 [-0.037;-0.003]</td><td>0.003 [-0.026;0.005]</td><td>0.003 [-0.017;0.015]</td><td>-0.002 [-0.031;0.002]</td><td>-0.006 [-0.030;0.008]</td><td>-0.007 [-0.033;0.001]</td><td>-0.0004 [-0.020;0.024]</td><td>-0.013 [-0.032;0.001]</td><td>-0.006 [-0.031;-0.006]</td><td>0.012 [-0.014;0.012]</td><td>-0.003 [-0.021;0.008]</td><td>0</td><td>-0.001 [-0.004;0.002]</td><td>0.001 [-0.0016;0.003]</td></tr><tr><td>13</td><td>0.001 [-0.030;0.002]</td><td>0.010 [-0.020;0.015]</td><td>0.011 [-0.011;0.030]</td><td>0.007 [-0.023;0.013]</td><td>0.003 [-0.016;0.020]</td><td>0.001 [-0.020;0.014]</td><td>0.010 [-0.011;0.041]</td><td>-0.004 [-0.021;0.015]</td><td>0.005 [-0.022;0.011]</td><td>0.019 [-0.005;0.028]</td><td>0.005 [-0.011;0.019]</td><td>0.008 [-0.027;0.009]</td><td>0</td><td>0.003 [-0.0002;0.004]</td></tr><tr><td>14</td><td>0.003 [-0.015;0.017]</td><td>0.010 [-0.005;0.030]</td><td>0.012 [-0.002;0.040]</td><td>0.006 [-0.013;0.021]</td><td>0.005 [-0.006;0.033]</td><td>0.002 [-0.008;0.021]</td><td>0.008 [-0.002;0.046]</td><td>-0.003 [-0.007;0.021]</td><td>0.002 [-0.015;0.018]</td><td>0.021 [-0.008;0.035]</td><td>0.005 [-0.0005;0.028]</td><td>0.006 [-0.014;0.012]</td><td>0.014 [-0.010;0.032]</td><td>0</td></tr></tbody></table>
<table><caption>**Table S4.** Wing mites 95% confidence intervals (CI) of F statistics among sampling sites without the outlier individuals. The lower matrix represents the 95% CI of the mean kinship between sampling sites based on the FsM matrix. The upper matrix represents the 95% CI of the pairwise FST between sampling sites based on the Fst2x2 matrix.</caption><thead><tr><th></th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th><th>12</th><th>13</th><th>14</th></tr></thead><tbody><tr><td>1</td><td>0</td><td>0.003<br/>[0.0008;0.005]</td><td>0.0008 [-<br/>0.002;0.0035]</td><td>0.003<br/>[0.0003;0.005]</td><td>0.003<br/>[0.0007;0.006]</td><td>0.002<br/>[0.0004;0.005]</td><td>-0.004 [-<br/>0.009;0.002]</td><td>0.0009 [-<br/>0.0007;0.003]</td><td>0.004<br/>[0.0003;0.007]</td><td>0.0006 [-<br/>0.001;0.003]</td><td>0.003<br/>[0.002;0.005]</td><td>0.0016 [-<br/>1.762e-<br/>05;3.819]</td><td>0.003<br/>[0.0002;0.007]</td><td>0.004<br/>[0.001;0.007]</td></tr><tr><td>2</td><td>-0.007 [-<br/>0.015;-0.001]</td><td>0</td><td>0.001 [-<br/>0.001;0.005]</td><td>0.004<br/>[0.001;0.006]</td><td>0.005<br/>[0.002;0.008]</td><td>0.002 [-<br/>0.0009;0.005]</td><td>-0.006 [-<br/>0.012;-0.0003]</td><td>0.0008 [-<br/>0.001;0.002]</td><td>0.004<br/>[0.0008;0.007]</td><td>0.002 [-<br/>0.0002;0.0036]</td><td>0.003<br/>[0.001;0.005]</td><td>0.003<br/>[0.001;0.005]</td><td>0.0055<br/>[0.002;0.009]</td><td>0.003 [-<br/>5.217e-<br/>05;6.710e-03]</td></tr><tr><td>3</td><td>0.001 [-<br/>0.006;0.009]</td><td>-0.004 [-<br/>0.013;0.005]</td><td>0</td><td>0.001 [-<br/>0.003;0.004]</td><td>0.003 [-<br/>0.001;0.008]</td><td>-0.001 [-<br/>0.004;0.003]</td><td>-0.008 [-<br/>0.014;-0.002]</td><td>-0.002 [-<br/>0.0046;0.0008]</td><td>0.004 [-<br/>0.0003;0.008]</td><td>-0.0006 [-<br/>0.003;0.002]</td><td>0.0009 [-<br/>0.002;0.004]</td><td>-0.0004 [-<br/>0.003;0.002]</td><td>0.0025 [-<br/>0.0007;0.006]</td><td>0.004 [-<br/>0.0002;0.008]</td></tr><tr><td>4</td><td>0.010<br/>[0.003;0.017]</td><td>0.004 [-<br/>0.0026;0.012]</td><td>0.013<br/>[0.006;0.024]</td><td>0</td><td>0.003<br/>[0.0002;0.0056]</td><td>0.001 [-<br/>0.002;0.004]</td><td>-0.005 [-<br/>0.010;0.00096]</td><td>0.002<br/>[0.0002;0.0045]</td><td>0.005<br/>[0.001;0.009]</td><td>0.003<br/>[0.00046;0.005]</td><td>0.003<br/>[0.001;0.004]</td><td>0.002 [9.672e-<br/>05;4.131e-03]</td><td>0.004<br/>[0.001;0.007]</td><td>0.006<br/>[0.002;0.009]</td></tr><tr><td>5</td><td>-0.004 [-<br/>0.013;0.002]</td><td>-0.011 [-<br/>0.021;-0.005]</td><td>-0.003 [-<br/>0.012;0.007]</td><td>0.008<br/>[0.0003;0.017]</td><td>0</td><td>0.0025 [-<br/>0.0002;0.006]</td><td>-0.0003 [-<br/>0.006;0.007]</td><td>0.0025 [-<br/>0.00002;0.006]</td><td>0.005 [-<br/>0.0005;0.0088]</td><td>0.004<br/>[0.0018;0.007]</td><td>0.0036<br/>[0.001;0.006]</td><td>0.0025 [-<br/>0.0002;0.005]</td><td>0.0036 [-<br/>0.0004;0.008]</td><td>0.0056<br/>[0.002;0.0098]</td></tr><tr><td>6</td><td>-0.002 [-<br/>0.009;0.005]</td><td>-0.007 [-<br/>0.013;0.0002]</td><td>0.002 [-<br/>0.006;0.012]</td><td>0.011<br/>[0.004;0.0195]</td><td>-0.004 [-<br/>0.010;0.003]</td><td>0</td><td>-0.007 [-<br/>0.012;-0.0016]</td><td>0.001 [-<br/>0.0008;0.003]</td><td>0.002 [-<br/>0.001;0.005]</td><td>0.0005 [-<br/>0.001;0.002]</td><td>0.002<br/>[0.0009;0.005]</td><td>-0.0005 [-<br/>0.002;0.002]</td><td>0.002 [-<br/>0.001;0.005]</td><td>0.003 [-<br/>0.0006;0.007]</td></tr><tr><td>7</td><td>0.018<br/>[0.006;0.026]</td><td>0.014<br/>[0.003;0.025]</td><td>0.023 [-<br/>0.012;0.0345]</td><td>0.030<br/>[0.021;0.041]</td><td>0.012<br/>[0.002;0.022]</td><td>0.019<br/>[0.008;0.031]</td><td>0</td><td>-0.004 [-<br/>0.009;0.001]</td><td>-0.0066 [-<br/>0.014;-0.001]</td><td>-0.007 [-0.012;-<br/>0.002]</td><td>-0.004 [-<br/>0.008;0.0015]</td><td>-0.0079 [-<br/>0.013;-0.003]</td><td>-0.0001 [-<br/>0.006;0.006]</td><td>-0.0045 [-<br/>0.0099;0.003]</td></tr><tr><td>8</td><td>-0.006 [-<br/>0.012;-0.001]</td><td>-0.011 [-<br/>0.018;-0.005]</td><td>-0.0017 [-<br/>0.008;0.008]</td><td>0.004 [-<br/>0.002;0.012]</td><td>-0.0098 [-<br/>0.018;-0.002]</td><td>-0.007 [-<br/>0.013;0.0005]</td><td>0.012<br/>[0.002;0.021]</td><td>0</td><td>2.920e-03<br/>[0.0006;0.006]</td><td>1.059e-03 [-<br/>0.0007;0.003]</td><td>3.429e-04 [-<br/>0.0007;0.0016]</td><td>-8.441e-05 [-<br/>0.0016;0.002]</td><td>2.647e-03<br/>[0.0002;0.006]</td><td>1.217e-03 [-<br/>0.0016;0.004]</td></tr><tr><td>9</td><td>-0.0009 [-<br/>0.0097;0.006]</td><td>-0.006 [-<br/>0.0135;0.0001]</td><td>0.0003 [-<br/>0.008;0.012]</td><td>0.010<br/>[0.002;0.0186]</td><td>-0.004 [-<br/>0.012;0.005]</td><td>0.0002 [-<br/>0.007;0.009]</td><td>0.022<br/>[0.010;0.033]</td><td>-0.006 [-0.015;]</td><td>0</td><td>0.003 [-<br/>0.0004;0.005]</td><td>0.004<br/>[0.0006;0.0066]</td><td>0.003<br/>[0.00046;0.006]</td><td>0.002 [-<br/>0.002;0.005]</td><td>0.003 [-<br/>0.0008;0.006]</td></tr><tr><td>10</td><td>-0.005 [-<br/>0.012;0.001]</td><td>-0.012 [-<br/>0.019;-0.006]</td><td>-0.003 [-<br/>0.012;0.006]</td><td>0.004 [-<br/>0.002;0.011]</td><td>-0.011 [-0.019;-<br/>0.004]</td><td>-0.006 [-<br/>0.012;0.001]</td><td>0.015<br/>[0.004;0.023]</td><td>-0.012 [-0.018;-<br/>0.006]</td><td>-0.0055 [-<br/>0.013;0.001]</td><td>0</td><td>0.001 [-<br/>0.0001;0.003]</td><td>0.002<br/>[0.0009;0.004]</td><td>0.003<br/>[0.0004;0.006]</td><td>0.002 [-<br/>0.00025;0.005]</td></tr><tr><td>11</td><td>0.008 [-0.015;-<br/>0.004]</td><td>-0.013 [-<br/>0.021;-0.006]</td><td>-0.004 [-<br/>0.011;0.005]</td><td>0.004 [-<br/>0.002;0.011]</td><td>-0.010 [-0.016;-<br/>0.003]</td><td>-0.008 [-<br/>0.014;-0.0004]</td><td>0.012<br/>[0.002;0.020]</td><td>-0.011 [-0.017;-<br/>0.006]</td><td>-0.007 [-<br/>0.013;0.0007]</td><td>-0.012 [-0.017;-<br/>0.006]</td><td>0</td><td>0.001 [-2.832e-<br/>05;2.403e-03]</td><td>0.004<br/>[0.0015;0.006]</td><td>0.003<br/>[0.0002;0.006]</td></tr><tr><td>12</td><td>-0.002 [-<br/>0.009;0.005]</td><td>-0.009 [-<br/>0.017;-0.002]</td><td>0.001 [-<br/>0.005;0.0103]</td><td>0.009<br/>[0.003;0.016]</td><td>-0.005 [-<br/>0.011;0.002]</td><td>-0.0007 [-<br/>0.007;0.008]</td><td>0.020<br/>[0.010;0.030]</td><td>-0.006 [-0.013;-<br/>0.0004]</td><td>-0.002 [-<br/>0.008;0.006]</td><td>-0.008 [-0.014;-<br/>0.002]</td><td>-0.007 [-0.013;-<br/>0.0003]</td><td>0</td><td>0.003<br/>[0.0013;0.006]</td><td>0.003 [-<br/>0.00016;0.006]</td></tr><tr><td>13</td><td>-0.004 [-<br/>0.012;0.0036]</td><td>-0.009 [-<br/>0.018;-0.001]</td><td>-0.002 [-<br/>0.0116;0.008]</td><td>0.007 [-<br/>0.001;0.014]</td><td>-0.006 [-<br/>0.014;0.0008]</td><td>-0.003 [-<br/>0.0097;0.006]</td><td>0.012<br/>[0.0006;0.022]</td><td>-0.009 [-0.016;-<br/>0.0013]</td><td>-0.0008 [-<br/>0.009;0.007]</td><td>-0.0096 [-<br/>0.016;-0.0015]</td><td>-0.010 [-0.017;-<br/>0.004]</td><td>-0.005 [-<br/>0.013;0.004]</td><td>0</td><td>0.006<br/>[0.002;0.010]</td></tr><tr><td>14</td><td>0.001 [-<br/>0.007;0.009]</td><td>-0.005 [-<br/>0.013;0.001]</td><td>0.0025 [-<br/>0.007;0.012]</td><td>0.011<br/>[0.004;0.018]</td><td>-0.0025 [-<br/>0.012;0.007]</td><td>0.001 [-<br/>0.008;0.008]</td><td>0.022<br/>[0.011;0.032]</td><td>-0.002 [-<br/>0.012;0.005]</td><td>0.004 [-<br/>0.005;0.014]</td><td>-0.003 [-<br/>0.011;0.003]</td><td>-0.004 [-<br/>0.010;0.002]</td><td>0.0006 [-<br/>0.007;0.007]</td><td>-0.002 [-<br/>0.013;0.007]</td><td>0</td></tr></tbody></table>
Supplementary Figures

<figure><img src="image_53.png" /><figcaption>B</figcaption></figure>

<figure><img src="image_54.png" /></figure>

**Fig. S1. Distribution of the number of reads per individuals.** (A) For the bat flies and (B) the wing mites. Each bar represents an individual.

<figure><img src="image_55.png" /><figcaption>B</figcaption></figure>

<figure><img src="image_56.png" /></figure>

**Fig. S2. Bat flies population-specific F statistics based on 100 bootstraps on loci considered independent without the outlier individuals.** The dotted red line represents y = 0. (A) Population-specific $F_{IS}$. (B) Population-specific $F_{ST}$.
<figure><img src="image_57.png" /><figcaption>Fig. S3. Isolation by distance. (A) Between bat flies. (B) Between wing mites.</figcaption></figure>

<figure><img src="image_58.png" /></figure>

<figure><img src="image_59.png" /></figure>

<figure><img src="image_60.png" /></figure>

<figure><img src="image_61.png" /><figcaption>Fig. S4. Results on the dataset of bat flies including only rare alleles (mac ≤ 10). (A) Heatmap of the mean kinship and pairwise FST over pairs of sampling sites. The upper matrix is the mean kinship between sites (FsM), high values represent pairs of populations whose individuals are more closely related to each other than to individuals from other populations. The diagonal represents the intra-populational mean kinship (population-specific FST) and the and lower matrix represent the pairwise FST. (B) Population-specific FST. (C) Population-specific FST.</figcaption></figure>
<figure><img src="image_62.png" /><figcaption>Fig. S5. Wing mites population-specific F statistics based on 100 bootstraps on loci considered independent without the outlier individuals. The dotted red line represents y=0. (A) Population-specific $F_{IS}$. (B) Population-specific $F_{ST}$.</figcaption></figure>

<figure><img src="image_63.png" /></figure>

<figure><img src="image_64.png" /></figure>

<figure><img src="image_65.png" /></figure>

<figure><img src="image_66.png" /><figcaption>Fig. S6. Results on the dataset of wing mites including only rare alleles (mac ≤ 10). (A) Heatmap of the mean kinship and pairwise FST over pairs of sampling sites. The upper matrix is the mean kinship between sites (FsM high values represent pairs of populations whose individuals are more closely related to each other than to individuals from other populations. The diagonal represents the intra-populational mean kinship (population-specific $F_{ST}$) and the and lower matrix represent the pairwise $F_{ST}$. (B) Population-specific $F_{IS}$. (C) Population-specific $F_{ST}$.</figcaption></figure>
**Chapter 4**

**Infestation dynamics of the Daubenton’s bat main parasites**

**Clara Castex**<fnref n="1" />, Antoine Perrin<fnref n="1" />, Molly Baur<fnref n="1" />, Monica Zanutta<fnref n="1" />, Marc Bastardot<fnref n="1" />, Jérôme Goudet<fnref n="1" />,<fnref n="2" />* and Philippe Christe<fnref n="1" />*

Corresponding author: clara.castex@unil.ch

**Authors contributions:** CC, JG and PC conceived and planned the study. CC and MBas did the field work. MBau and MZ developed and ran the qPCR in the lab. CC and AP ran the analyses. All authors contributed to the interpretation of the results. AP wrote the result section. CC wrote the first draft of the manuscript, and all authors provided critical feedback and approved the final manuscript.

**Status:** This chapter has not been submitted to a journal or archived in a preprint yet.

<footnote n="1">¹Department of Ecology and Evolution, University of Lausanne, Switzerland</footnote>

<footnote n="2">²Swiss Institute of Bioinformatics, Lausanne, Switzerland</footnote>

<footnote>*Co-senior authors</footnote>
**Abstract**

Identifying the drivers of parasite prevalence and intensity across multiple scales is central to understand host-parasite ecology. This study investigates the infection dynamics of three parasites, the wing mites (*Spinturnix andegavinus*), the bat flies (*Nycteribia kolenatii*), and the haemosporidian *Polychromophilus murinus*, in Daubenton's bats (*Myotis daubentonii*) across temporal, spatial, and host life-history traits. Over four years, 951 bats were sampled across 25 sites in Switzerland. Using generalized additive models, generalized linear models, and structural equation modelling, we evaluated the influence of seasonality, host traits, and parasite interactions on infection patterns. The three parasite species showed sex-biased infection, with females being more heavily parasitized probably due to higher aggregation in maternity colonies. Wing mite abundance peaked in July and was higher in lactating females, suggesting a trade-off between reproduction and immunity. In contrast, bat fly abundance remained stable across seasons and was not affected by host traits, likely reflecting their high mobility and frequent host-switching. *P. murinus* prevalence was higher in subadults, suggesting age-dependent immunological maturity. Its persistence year-round suggested chronic infection dynamics. Importantly, *P. murinus* presence and intensity were shaped by distinct ecological pressures and infection intensity peaked in midsummer. Structural equation modelling revealed a positive association between wing mite and bat fly abundance, and an indirect link between *P. murinus* presence and wing mite abundance, potentially mediated by the bat body condition. These findings highlight the complexity of coinfection dynamics and underscore the importance of integrative, multi-parasite approaches to understanding parasite transmission in wild bat populations.

**Keywords:** bat flies, wing mites, *Polychromophilus murinus*, temporal analyses, infection dynamics
Introduction

Host-parasite interactions have been extensively studied, yet several fundamental questions remain unresolved. In particular, identifying the factors that drive parasite transmission and shape global spatiotemporal patterns of distribution remains a challenge (Stephens et al., 2016; Poulin, 2021). Parasite loads are typically heterogeneous across hosts (Shaw et al., 1998; Poulin, 2013), with a small fraction of individuals contributing disproportionately to parasite transmission and persistence (Altizer et al., 2003; Poulin, 2007, 2021). This heterogeneity is influenced by biotic and abiotic conditions (Sorci and Garnier, 2018) as well as by host and parasite life histories (Dick and Patterson, 2007; Barrett et al., 2008). Understanding the determinants of such variation is crucial, as it informs predictions about parasite spread and the risk of novel emergence (Stephens et al., 2016). Within hosts, differences in parasite load often reflect variation in susceptibility or exposure, shaped by behavioural, physiological, or immunological traits (Poulin, 2013). Across populations, infection prevalence and intensity also fluctuate over space and time (Poulin, 2013; Penczykowski et al., 2015). Therefore, elucidating the mechanisms underlying parasite distribution at multiple spatiotemporal scales is a central question in parasite ecology (Penczykowski et al., 2015; Stephens et al., 2016; Poulin, 2021).

Most studies, however, have examined single host-parasite systems. Broader approaches are needed to capture the complexity of natural infections, where coinfections are frequent and parasite interactions can shape infection outcomes (Petney and Andrews, 1998; Morand et al., 2006; Merrill et al., 2022). Such interactions are well documented in terrestrial mammals (Jolles et al., 2008; Telfer et al., 2008; Vaumourin et al., 2015; Ezenwa, 2016), but remain largely unexplored in bats (Tello et al., 2008; Presley, 2011; Aguillon et al., 2025).

Bats are an excellent model to study parasite heterogeneity of distribution among individuals, as they host a wide diversity of specialised parasites including bat flies, wing mites, and haemosporidians (Bruyndonckx et al., 2009a; Megali et al., 2011; Szentivanyi et al., 2016). Their social structure, strongly shaped by sex and season, generates marked temporal and demographic variation in contact rates. In temperate zones, females form maternity colonies in springtime, while males usually roost solitarily or in small groups;
later, both sexes gather at mating sites (Johnson et al., 2015b). Parasite dynamics may track this seasonal cycle. For example, wing mites and bat flies reproduce during the nursing period (Lourenço and Palmeirim, 2008; van Schaik and Kerth, 2017), and the infections of the haemosporidian, *Polychromophilus murinus*, peak in midsummer (Witsenburg et al., 2014). Detecting such fine-scale seasonal patterns, however, requires high-resolution sampling (Lambin, 1996; Stetz et al., 2019).

Host traits also modulate parasite dynamics. Females generally experience higher parasite burdens due to their aggregation in maternity colonies (Christe et al., 2000; Lučan, 2006; Christe et al., 2007; Patterson et al., 2008b; van Schaik and Kerth, 2017; Szentiványi et al., 2017), while juveniles are particularly susceptible because of weaker immune defences and less effective grooming behaviour (Christe et al., 2000, 2003; Zhang et al., 2010; Witsenburg et al., 2014). Reproductive status further contributes to variation, although this factor has rarely been explicitly measured (Christe et al., 2000; Lučan, 2006).

Despite this knowledge, few studies have examined multiple bat parasites simultaneously or assessed how they may interact (Tello et al., 2008; Presley, 2011). Yet in natural populations, coinfecting parasites can influence one another. For instance, the bat fly *Nycteribia kolenatii* transmits the haemosporidian *P. murinus*, but its survival decreases when infected, and highly infected bats are less frequently chosen as hosts (Witsenburg et al., 2015a). Such findings highlight the potential for reciprocal interactions between parasites, but the extent to which they shape transmission dynamics in wild bat populations remains unclear.

Here, we addressed this gap by studying coinfection dynamics in the Daubenton's bat (*Myotis daubentonii*), a species heavily parasitised by the wing mite *Spinturnix andegavinus* (Bruyndonckx et al., 2009a), the bat fly *N. kolenatii* (Szentiványi et al., 2016), and the haemosporidian *P. murinus* (Megali et al., 2011). Specifically, we (i) assessed seasonal variation in ectoparasite abundance and *P. murinus* infection, (ii) tested how host sex, age, and reproductive status shape infection risk, and (iii) explored potential interactions among coinfecting parasites to better understand how they are maintained in bat populations.
# Materials & Methods

## Data collection

Between 2021 and 2024, a total of 951 Daubenton's bats (*Myotis daubentonii*) were captured across 25 sites in the Vaud canton in Switzerland (Fig. 1), under the license authorization VD3679. Bats were captured using a harp trap or mist nets at dusk. For each individual, sex and age were determined. Age classification followed morphological criteria (Richardson, 1994; Haarsma, 2008). Adults (AD) were identified by a light chinspot and fused phalangeal epiphyses, subadults (SAD) exhibited a dark chinspot with fused epiphyses and juveniles (JUV) showed a dark chinspot and unfused epiphyses. Female reproductive status was assessed and categorized as follow: pregnant (P) were estimated through slight palpation of the abdomen, lactating (L) identified by chewed and swollen nipples, post-lactating (PL) had flaccid nipples and other (O) included non-reproductive individuals (juveniles or females that had not mated the previous year) (Kunz and Parsons, 2009). Male reproductive status was classified as reproductive (R) based on the presence of enlarged testes and swollen epididymides, or non-reproductive (NR) (Encarnação et al., 2004).

Ectoparasite abundance was quantified by counting the number of bat flies and wing mites present on each individual, including non-infested individuals. To estimate the infection of the haemosporidian parasite *Polychromophilus murinus*, a blood sample was collected from the uropatagial vein using a 0.5 mm gauge needle (HSW, Germany). Blood was drawn into heparinized microcapillary tubes (VWR International), transferred in 60 µL phosphate-buffered saline (PBS) and stored at -80°C. Following the blood sample, 45 random-selected blood smears were prepared and stained with Giemsa solution, after fixation in 100% methanol.

## DNA extraction and quantitative PCRs

DNA was extracted from blood samples (N = 710) using the Blood & Tissue spin column kit (Qiagen, CA), following the manufacturer protocol. The *P. murinus* infection in the blood samples was estimated for each individual through quantitative PCRs (qPCR), following the protocol described in Castex et al., *in prep* (a) (cf **Chapter 2**). Two measures
were used to describe the infection of *P. murinus*: the presence/absence and the intensity of infection. When the DNA of *P. murinus* was detected in the blood of the bat, it was considered as “present”. The intensity of infection corresponds to the quantity of *P. murinus* DNA in the blood of already infected bats.

<figure><img src="image_67.png" /><figcaption>**Fig. 1. Map of the 25 sampling sites of the study.** Sampling sites are: **1** – Aigle Grande Eau, **2** – Arboretum, **3** – Baulmes, **4** – Boiron de Nyon, **5** – Bois de la Râpe, **6** – Chavornay Le Moulin, **7** – Clarens, **8** – Cully, **9** – Dorigny, **10** – Embouchure Aubonne, **11** – Grottes aux Fées, **12** – La Cascade, **13** – Lac Morat, **15** – Le Brassus, **16** – Le Pont, **17** – Les Clées, **18** – Maison de la Rivière, **19** – Marais des Monods, **20** – Moudon, **21** – Papiboum, **22** – Provence, **23** – Résurgence de Vallorbe, **24** – Rossinière, **25** – Vufflens la Ville, **26** – Yvonand.</figcaption></figure>

## Data analyses

All the following analyses were carried out with the R software (v 4.4.2).

To assess seasonal variation in ectoparasite abundance and *P. murinus* infection, we restricted the dataset to individuals sampled in 2023 across 20 sampling sites. This year had the most extensive sampling effort, making it the most representative for capturing seasonal patterns. Ectoparasite dynamics were evaluated in 603 bats, while *P*.
murinus infection was analysed in a subset of 505 individuals, as blood samples could not be obtained from all bats. We used generalized additive models (GAMs) with a Gaussian error distribution, with the function *gam* from the mgcv package (Wood, 2001), to analyse log-transformed abundances of wing mites, bat flies, and *P. murinus* infection intensity, and a binomial error distribution for *P. murinus* presence/absence. To evaluate spatial variation in parasite dynamics, we repeated the same GAMs including a fixed effect of sampling site, focusing on the two sites with the highest sampling effort (sites 9 and 18, Fig. 1).

To test the effects of sex, age class, and reproductive status on ectoparasite abundance and *P. murinus* infection, we used a larger dataset combining four years of monitoring across 25 sampling sites. Juveniles were removed from the following analyses to avoid any bias in the effect of the reproductive status as they were non reproductive young of the year. A total of 733 bats were used to assess the dynamics of the ectoparasites, while *P. murinus* infection was investigated in 565 bats, as blood samples were not available for all bats. Ectoparasite abundances and *P. murinus* infection intensity (both log-transformed) were analysed using generalized linear models (GLMs) with a Gaussian error distribution, from the *glmmTMB* function of the *glmmTMB* package (Brooks et al., 2017). *P. murinus* presence/absence was modelled with a binomial GLM. Sex, age class, and reproductive status were included as fixed effects, and interactions among them were tested. However, none were significant and thus are not reported in this manuscript. To account for seasonal variation, we included a categorical covariate representing the reproductive period at the time of capture: before July (pregnancy), July (lactation), and after July (post-lactation) (Encarnação and Becker, 2023). Sampling site and year were included as random effects in all models.

We used structural equation modelling (SEM) to explore the relationships between ectoparasite abundance and *P. murinus* infection using the same four-year dataset across 25 sampling sites. Path models were based on the previous analyses, including all covariates (site, sex, age, reproductive period and reproductive status). SEMs were fitted using the *psem* function in the package piecewiseSEM (Lefcheck, 2016). From each model, we extracted path coefficients and Fisher's C statistic with associated p-values. Fisher's C statistic tests the assumption that there are no missing paths among the
independent variables. SEMs were considered adequate when the test was not significant ($p > 0.05$), indicating no missing links or explanatory variables. Shipley's test of directed separation was used to identify potential missing correlations.

## Results

Over the four years of sampling, Daubenton's bats exhibited high prevalence, with 91.6% and 82.4% of parasitized individuals by bat flies and wing mites, respectively. Among infected individuals, the mean ectoparasite abundance was 5.2 for bat flies and 6.6 for wing mites. Additionally, qPCR analysis revealed that 57.6% of Daubenton's bats were infected by *P. murinus*.

### Spatiotemporal variation in ectoparasite abundance and *P. murinus* infection

We found a significant seasonal trend in the wing mite abundance across the sampling period (smooth term: *F* = 37.29; *edf* = 3.7, *p* < 0.0001; **Fig. 2A**), but no significant spatial variation between sites (*t* = 1.034; *p* = 0.304). In contrast, the bat fly abundance was not significantly affected by sampling date (*F* = 1.488; *edf* = 1; *p* = 0.223; **Fig. 2B**) or site (*t* = -1.044; *p* = 0.299). For *P. murinus*, prevalence did not vary significantly over time ($\chi^2$ = 1.944; *edf* = 1; *p* = 0.163; **Fig. 2C**) and was not influenced by site (*z* = 0.861; *p* = 0.389). Similarly, infection intensity was not affected by site (*t* = -1.272, *p* = 0.210) but did vary significantly across the season (*F* = 7.16, *edf* = 3.349, *p* < 0.001; **Fig. 2D**). Both wing mite abundance and *P. murinus* intensity peaked during the summer months.
<figure><img src="image_68.png" /><figcaption>Fig. 2. Dynamics of (A) abundance of wing mites (log-transformed), (B) abundance of bat flies (log-transformed), (C) infection intensity of *P. murinus* (log-transformed), and (D) infection prevalence of *P. murinus* over time. Grey dots represent individual observations, and black lines show smooth trends fitted using generalized additive models (GAMs) with 95% confidence intervals. Dates are formatted as day-month.</figcaption></figure>
*Influence of sex, age, and reproductive status on bat parasitism*

Female bats carried significantly higher number of both wing mites (glmmTMB: *estimate* = 0.549; *t* = 7.926; *p* < 0.0001) and bat flies (glmmTMB: *estimate* = 0.222; *t* = 4.663; *p* < 0.0001) than males and showed higher *P. murinus* prevalence (glmmTMB: *estimate* = 0.571; *z* = 3.074; *p* = 0.002, **Fig. 3**). Reproductive status did not significantly affect bat fly abundance (anova: χ² = 6.448; *df* = 4; *p* = 0.168) or *P. murinus* presence

<figure><img src="image_69.png" /><figcaption>**Fig. 3.** Sex-specific differences in wing mite and bat fly abundances as well as *P. murinus* prevalence and intensity in bats. Points represent the mean value ± 95% confidence interval for each sex. *P. murinus* intensity, wing mite and bat fly abundances are log-transformed.</figcaption></figure>
(anova: $\chi^2 = 3.181$; df = 3; p = 0.365) but was a strong predictor of wing mite abundance (anova: $\chi^2 = 27.876$; df = 4; p < 0.0001). Among females, lactating individuals had significantly higher wing mite abundance than both pregnant (glmmTMB: estimate = 0.443; t = 3.366; p = 0.005) and non-reproductive individuals (glmmTMB: estimate = 0.539; t = 4.816; p < 0.0001), while post-lactating females showed intermediate wing mite abundance (Fig. 4). No significant difference was observed among reproductive categories in males (glmmTMB: estimate = 0.161; t = 1.565; p = 0.118). *P. murinus* prevalence was significantly higher in subadult bats compared to adults (glmmTMB: estimate = -1.280; z = -6.114; p < 0.0001), but age had no significant effect on wing mite (anova: $\chi^2 = 0.483$; df = 1; p = 0.487) or bat fly (anova: $\chi^2 = 0.950$; df = 1; p = 0.330) abundance. There was no significant effect of bat traits on *P. murinus* intensity.

<figure><img src="image_70.png" /><figcaption>**Fig. 4.** Wing mite abundance per reproductive status in bats. Points represent the mean value ± 95% confidence interval for each reproductive status in each sex. Wing mite abundance is log-transformed.</figcaption></figure>

## Associations between ectoparasite abundance and haemosporidian infection

Structural equation modelling (SEM), accounting for spatial, temporal, and host-related variables, revealed a positive correlation between wing mite and bat fly abundances ($\beta = 0.096$; $p = 0.011$). Bat fly abundance was not a significant predictor of *P. murinus* presence ($\beta = -0.246$; $p = 0.088$). However, the SEM test of directed separation indicated a missing path between *P. murinus* presence and wing mite abundance (*Crit. Value* = 2.818; $p = 0.005$), suggesting a potential influence of the haemosporidian
infection on wing mite abundance. There was no significant relationship between wing mite or bat fly abundances and *P. murinus* intensity.

Discussion

In this study we examined the infection dynamics of three parasites of the Daubenton's bat: the wing mite *Spinturnix andegavinus*, the bat fly *Nycteribia kolenatii* and the haemosporidian *Polychromophilus murinus*. We revealed distinct dynamics shaped by seasonal variation, host traits and potential interspecific interactions, reflecting the different ecologies and life cycles of each parasite. These patterns underscore the complexity of coinfections and the importance of integrating temporal, spatial and host-related factors to understand parasite transmission in bats.

Consistent with previous studies, female bats harboured higher ectoparasite loads and *P. murinus* prevalence than males (Fig. 3; Lučan, 2006; Christe et al., 2007; van Schaik and Kerth, 2017; Tai et al., 2022). This female-biased parasitism was likely driven by maternity roosting behaviour, which facilitates increased contact rates. Female Daubenton's bats form large maternity colonies (Arthur and Lemaire, 2009), which enhances opportunities for horizontal transmission. Interestingly, parasites were influenced differently by age, reproductive status, and time, suggesting parasite-specific responses to host physiology and behaviour.

Wing mites exhibited a clear seasonal variation with a peak of abundance in July (Fig. 2A), corresponding to the lactating period of the bat. Consistently, lactating females were more susceptible to wing mite infestation (Fig. 4). This aligns with previous studies showing elevated mite loads during reproductive phases (Christe et al., 2000; Lučan, 2006; Lourenço and Palmeirim, 2007, 2008; van Schaik and Kerth, 2017). This pattern likely reflected a physiological trade-off between reproduction and immunity, where the energetic demands of lactation reduce immunocompetence, increasing susceptibility to ectoparasites (Racey and Entwistle, 2000; Christe et al., 2000). Female bats exhibit a seasonal variation of cellular and innate immunity with lower levels in spring and summer, during pregnancy and lactation periods (Otálora-Ardila et al., 2022). In contrast, no significant differences were observed among reproductive status in males (Fig. 4),
suggesting that sex-specific behaviours and physiologies play a more decisive role in shaping parasite dynamics. Although a trade-off between reproduction and immunity has been documented in male Daubenton's bats (Ruoss et al., 2019), the energetic costs appear to be higher in reproductive females, making them more susceptible to parasitism.

In contrast, bat fly abundance remained stable across the season (Fig. 2B), suggesting that bat flies maintained a continuous presence among hosts regardless of the reproductive period. This temporal stability may be due to their high movements between bat colonies, diluting seasonal effects. Although bat flies spend their entire lives on bats, female bat flies must leave their host to deposit pupae on the roost, leading to high mobility and frequent host-switching (Ching and Marshall, 1968; Marshall, 1970). In addition, the lack of genetic structure among bat fly populations suggests strong genetic connectivity, showing they are highly mobile parasites (Castex et al., in prep (b), cf Chapter 3). While some studies have reported seasonal variation of bat fly infestation (Lourenço and Palmeirim, 2008; Witsenburg et al., 2015a; Sándor et al., 2024b), our results suggest species-specific dynamics. The absence of clear seasonal patterns highlights the need for standardized approaches when comparing bat fly ecology across systems. Host preferences in bat flies are sex-specific, with female bat flies being more influenced by the bat sex and body condition than males (Szentiványi et al., 2017). This suggests that host-parasite interactions may differ between bat fly sexes, highlighting the need for further investigation into sex-specific temporal dynamics to determine whether seasonal variation affects male and female bat flies differently. Additionally, bat fly abundance has been shown to positively correlate with the host body condition (Szentiványi et al., 2017; Tai et al., 2022), indicating that healthier individuals may support larger parasite loads. In our study, we were unable to reliably assess the body condition of the Daubenton's bats, as individuals were captured during foraging periods. Given that nightly food intake in this species can range from 20% to nearly 50% of their body mass (Encarnação and Dietz, 2006), measurements taken at different times of night may not accurately reflect the bat condition.

Parasite presence and infection intensity capture different aspects of host-parasite interactions (Warren, 1973; Bichet et al., 2014; Young et al., 2015; Bommarito et
al., 2022). Parasite presence is often shaped by factors that govern exposure and susceptibility, while intensity reflects host condition, immune regulation, and parasite replication dynamics (Abebe et al., 2002; Miller et al., 2012; Loiseau et al., 2013; Martins and Poulin, 2024). Considering both metrics is therefore essential, as they jointly determine infection costs for the host and transmission potential to vectors. In our study system, host traits shaped parasite presence with females and subadults more parasitized than males and adults (Fig. 3), whereas parasite intensity varied seasonally, showing a peak in late July to early August (Fig. 2D). These results suggests that host-parasite dynamics can be structured by different sets of drivers across contexts. This highlights the need to investigate both prevalence and intensity simultaneously to avoid oversimplifying the processes underlying parasite persistence and transmission in natural populations.

In addition to being more common in females, *P. murinus* was more frequently detected in subadult individuals compared to adults. This age-related pattern is consistent with earlier findings showing that initial exposure to haemosporidian parasites typically results in higher infections than subsequent encounters (Garnham, 1966). Supporting this observation, previous studies have shown that juveniles were more infected by *P. murinus* than other age classes with subadults being intermediately parasitized (Witsenburg et al., 2014; Castex et al., in prep (a), cf Chapter 2). Our results suggested that older bats are better able to cope with the infection, likely due to more developed immune responses. This progressive infection from juveniles to adult may reflect age-dependent immunological maturity. Juveniles are immunologically compromised, providing an ideal environment for transmission of pathogens (Friedrichs et al., 2022; Roffler et al., 2024). The observed pattern may also result from higher mortality rates among subadult individuals. It would be valuable to experimentally assess the impact of *P. murinus* infections on the survival of Daubenton's bats.

The prevalence of *P. murinus* in the Daubenton's bats observed in this study aligned with previous reports, which ranged from 51 to 74% (Megali et al., 2011; Witsenburg et al., 2014). We found no evidence of seasonal variation in *P. murinus* presence (Fig. 2C). This absence of seasonal trends is consistent with Witsenburg et al. (2014), who reported that temporal effects were detectable only in certain years,