Research Article |
Corresponding author: Nelson Colihueque ( ncolih@ulagos.cl ) Academic editor: Ana Maria Leal-Zanchet
© 2022 Nelson Colihueque, Javier Cabello, Andrea Fuentes-Moliz.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Colihueque N, Cabello J, Fuentes-Moliz A (2022) Genetic divergence and demography of pudu deer (Pudu puda) in five provinces of southern Chile, analyzed through latitudinal and longitudinal ranges. Neotropical Biology and Conservation 17(2): 117-142. https://doi.org/10.3897/neotropical.17.e81324
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Pudu deer (Pudu puda) is endemic to the temperate rainforests of Chile. Genetic studies at different geographic scales for this species are required to better determine the genetic divergence within and among populations and their demography across the distribution range. These data can provide unique insights into the species or population status for conservation plans and decision-makers. We analyzed the mtDNA control region (CR) and cytochrome b (Cyt b) sequences of pudu deer in five provinces of southern Chile located at different latitudinal locations (Cautín, Valdivia, Osorno, Llanquihue and Chiloé Island) and three geographic areas within the studied provinces, representative of different longitudinal sites (Andes range, Central Valley and Coastal Range), to understand their genetic divergence and demography. The haplotype (H) and nucleotide (Π) diversities of CR and Cyt b ranged from 0.64286 to 0.98333 and from 0.00575 to 0.01022, respectively. CR diversity was significantly different among provinces, with Valdivia showing higher values than Llanquihue and Chiloé Island (H = 0.98333 vs. 0.64286–0.92727, P < 0.05). Cyt b variation also showed significant differences among provinces, particularly, among Cautín and Llanquihue (H = 1.000 vs. 0.222, P < 0.05). Genetic structuring among provinces was relatively high, as indicated by the FST index (FST = 0.41905). Clustering analysis indicated the presence of a distinctive cluster for Chiloé Island individuals. Fu’s FS and Tajima’s D based on CR revealed significant, negative deviations from equilibrium for Chiloé Island (D = -1.65898), Valdivia (Fs = -7.75335) and Llanquihue (Fs = -3.93267), suggesting population expansion in these provinces. Analysis at the longitudinal range showed significant differences among areas based on Π (P < 0.05), with the Andes range and Central Valley showing higher diversity than the Coastal Range. Neither population structuring (FST = 0.01360, P > 0.05) nor distinctive clusters in the longitudinal range were observed. Fu’s Fs and Tajima’s D were negative and significant for the Coastal Range based on CR (Fs = -6.64752, P < 0.001) and Cyt b (D = -1.74110, P < 0.05), suggesting the existence of population expansion. Our results suggest that pudu deer in the analyzed provinces is a genetically structured species, which could be associated with reduced panmixia among populations. The genetic divergence pattern and the population expansion recorded are likely to be associated with past processes of recolonization after Pleistocene glaciation events.
Control region, cytochrome b, genetic divergence, population structure, pudu deer
Pudu deer, Pudu puda (Molina, 1782), is endemic to southern South America and is characterized as being one of the smallest deer in the world due to its short shoulder height (30–40 cm) and small body weight (< 15 kg) (
Cautín, Valdivia, Osorno, Llanquihue and Chiloé Island are provinces in Southern Chile (39–44°S latitude) that contain a significant remnant of native temperate rainforest that covers a large proportion of each province. For example, Osorno Province contains approximately 42.9% of native forest, and in Llanquihue and Chiloé provinces they cover approximately 54.5% and 68.3%, respectively (
Inferences based on analyses of the geographic distribution of genetic diversity indicate that the Coastal mountain range in Osorno Province and other neighboring provinces, such as Cautín, Valdivia and Llanquihue, was a lowland refuge for vertebrates during the Pleistocene glaciation in the Last Glacial Maximum (LGM), which occurred approximately 23,000–18,000 years ago (
Phylogenetic studies performed on pudu deer populations from the northernmost distribution of southern Chile (36–42°S) using mtDNA control region and cytochrome b markers (
The objective of this study was to assess the level of genetic divergence and the demography of pudu deer in five provinces in southern Chile that are located at different latitudinal sites (from 39°S to 42°S) (Cautín, Valdivia, Osorno, Llanquihue and Chiloé Island) and three characteristic geographic areas within these provinces representative of distinctive longitudinal sites (Andes range, Central Valley (i.e., Longitudinal Valley) and Coastal Range), based on new and publicly available mtDNA control region (CR) and cytochrome b (Cyt b) sequences. We hypothesized that among provinces located at the extreme of the distribution, including those that inhabit an island, pudu deer populations must exhibit marked genetic divergence and reduced gene flow, given the existence of geographic barriers or the effect of Pleistocene glaciations that have modified the genetic structure of the populations. Moreover, pudu deer populations from the Coastal Range, are likely to have experienced an expansion process, since this site was a lowland refuge for vertebrates during the Pleistocene glaciations, to later recolonize the areas where the ice sheet retreated. In addition, populations located in this geographic area should exhibit a higher level of genetic diversity than populations located in other sites, for example, to those located in the Andean mountain range, due to its refugial nature. It is also possible that pudu deer population from some provinces may conform to a distinctive genetic cluster since these populations can present characteristic haplotype frequencies due to local selection pressure or population-specific haplotypes due to its relictual nature. Clarifying this issue is relevant for the sustainability of pudu deer in southern Chile, given that some populations may constitute an evolutionarily significant unit, whose identification is of major importance when conservation plans for threatened species are considered (
Pudu deer samples collected from Osorno (n = 6), Llanquihue (n = 8) and Chiloé (n = 6) provinces were analyzed (Table
Sampling for genetic analysis of pudu deer from southern Chile. † Coordinates data were recovery from GeoNames (http://www.geonames.org/) according to district location. ‡
Site number, locality and district | Province | Longitudinal range | Coordinates (Lat., Long.) | Sampling year | Specimen voucher |
---|---|---|---|---|---|
1. Parque Nacional Puyehue, Puyehue | Osorno | Andes range | 40.7820°S, 72.2114°W | 2014 | 1279ULA |
2. Las Cascadas, Puerto Octay | Osorno | Andes range | 41.0869°S, 72.6360°W | 2016 | 1330ULA |
3. Colonia Zagal, Purranque | Osorno | Coastal range | 40.9644°S, 73.4288°W | 2016 | 1331ULA |
4. Chan Chan, Osorno | Osorno | Central Valley | 40.7244°S, 73.0231°W | 2016 | 1337ULA |
5. Parque Nacional Puyehue, Puyehue | Osorno | Andes range | 40.7353°S, 72.3081°W | 2016 | 1505ULA |
6. Puaucho, San Juan de la Costa | Osorno | Coastal range | 40.6142°S, 73.3732°W | 2017 | 1515ULA |
7. Ensenada, Puerto Varas | Llanquihue | Andes range | 41.2082°S, 72.5383°W | 2018 | 1520ULA |
8. Chinquihue, Puerto Montt | Llanquihue | Coastal range | 41.6050°S, 73.2623°W | 2019 | 1522ULA |
9. U§, Puerto Montt | Llanquihue | Coastal range | 41.48917°S, 72.79531°W† | 2018 | 1524ULA |
10.U, Calbuco | Llanquihue | Coastal range | 41.72311°S, 73.19511°W† | 2018 | 1525ULA |
11. Guayún, Calbuco | Llanquihue | Coastal range | 41.6992°S, 73.2445°W | 2018 | 1526ULA |
12. U, Maullín | Llanquihue | Coastal range | 41.63242°S, 73.5083 °W† | 2018 | 1527ULA |
13. U, Puerto Montt | Llanquihue | Coastal range | 41.48917°S, 72.79531°W† | 2019 | 1529ULA |
14. Ensenada, Puerto Varas | Llanquihue | Andes range | 41.2082°S, 72.5383°W | 2017 | 1532ULA |
15. Chepu, Ancud | Chiloé | – | 42.0439°S, 73.9679°W | 2019 | 1516ULA |
16. Degañ, Quemchi | Chiloé | – | 42.1426°S, 73.4743°W | 2019 | 1517ULA |
17. Pauldeo, Ancud | Chiloé | – | 41.8991°S, 73.8893°W | 2019 | 1518ULA |
18. Chonchi, Chonchi | Chiloé | – | 42.7231°S, 73.7855°W | 2019 | 1519ULA |
19.Butalcura, Ancud | Chiloé | – | 42.2332°S, 73.7499°W | 2019 | 1523ULA |
20. Cotao, Quellón | Chiloé | – | 43.15178°S, 73.9954°W† | 2019 | 1531ULA |
21. Pucón, Pucón | Cautín | Andes range | 39.2500°S, 71.9000°W | NA | Previous study‡ |
22. Villarrica, Villarrica | Cautín | Andes range | 39.3000°S, 72.2666°W | NA | Previous study‡ |
23. Villarrica, Villarrica | Cautín | Andes range | 39.3000°S, 72.2666°W | NA | Previous study‡ |
24. Loncoche, Loncoche | Cautín | Central Valley | 39.3666°S, 72.6666°W | NA | Previous study‡ |
25. Lican Ray, Villarrica | Cautín | Andes range | 39.4666°S, 72.0833°W | NA | Previous study‡ |
26. Coñaripe, Panguipulli | Valdivia | Andes range | 39.6166°S, 72.0500°W | NA | Previous study‡ |
27. Caleta Mehuín, San José de la Mariquina | Valdivia | Coastal range | 39.4333°S, 73.2000°W | NA | Previous study‡ |
28. San José de la Mariquina, San José de la Mariquina | Valdivia | Coastal range | 39.5333°S, 72.9500°W | NA | Previous study‡ |
29. Máfil, Máfil | Valdivia | Central Valley | 39.6666°S, 72.8500°W | NA | Previous study‡ |
30. Cayumapu, Valdivia | Valdivia | Coastal range | 39.7166°S, 73.1000°W | NA | Previous study‡ |
31. Cayumapu, Valdivia | Valdivia | Coastal range | 39.7166°S, 73.1000°W | NA | Previous study‡ |
32. Lago Panguipulli, Panguipulli | Valdivia | Andes range | 39.7666°S, 72.1000°W | NA | Previous study‡ |
33. Collico, Valdivia | Valdivia | Coastal range | 39.8000°S, 73.1666°W | NA | Previous study‡ |
34. Cutipay, Valdivia | Valdivia | Coastal range | 39.8000°S, 73.2166°W | NA | Previous study‡ |
35. Valdivia, Valdivia | Valdivia | NA | 39.8166°S, 73.1833°W | NA | Previous study‡ |
36. Valdivia, Valdivia | Valdivia | NA | 39.8166°S, 73.1833°W | NA | Previous study‡ |
37. Valdivia, Valdivia | Valdivia | NA | 39.8166°S, 73.1833°W | NA | Previous study |
38. Valdivia, Valdivia | Valdivia | NA | 39.8166°S, 73.1833°W | NA | Previous study‡ |
39. Valdivia, Valdivia | Valdivia | NA | 39.8166°S, 73.1833°W | NA | Previous study‡ |
40. Valdivia, Valdivia | Valdivia | NA | 39.8166°S, 73.1833°W | NA | Previous study‡ |
41. Valdivia, Valdivia | Valdivia | NA | 39.8166°S, 73.1833°W | NA | Previous study‡ |
42. Puyehue, Puyehue | Osorno | Andes range | 40.7166°S, 72.3166°W | NA | Previous study‡ |
43. Lago Llanquihue, Llanquihue | Llanquihue | Central Valley | 41.2833°S, 73.0166°W | NA | Previous study‡ |
44. Lago Llanquihue, Llanquihue | Llanquihue | Central Valley | 41.2833°S, 73.0166°W | NA | Previous study‡ |
45. Lago Llanquihue, Llanquihue | Llanquihue | Central Valley | 41.2833°S, 73.0166°W | NA | Previous study‡ |
46. Cucao, Chonchi | Chiloé | – | 42.6166°S, 74.1000°W | NA | Previous study‡ |
47. Cucao, Chonchi | Chiloé | – | 42.6166°S, 74.1000°W | NA | Previous study‡ |
The MtDNA control region was amplified through polymerase chain reaction (PCR) using the primers Pudu-1F (5’ CCCCACTATCAACACCCAAA 3’) and Pudu-2R (5’ ACCATTATGGGGATGCTCAA 3’), according to
We used DNASP version 5.1 software to estimate genetic variation within populations based on the number of haplotypes (h), polymorphic sites (s), haplotype diversity (H), nucleotide diversity (Π) and average number of nucleotide differences (k) (
Sampling sites of pudu deer in southern Chile. A) Sample sites at the latitudinal range (i.e., for provinces) and B) sample sites at the longitudinal range (i.e., for the Andes range, Central Valley and Coastal Range). In A), the blue dots indicate sampling sites within each province, and in B), sampling sites identified by dark dots within specific area of the longitudinal range, with different colors for the Andes range, Central Valley and Coastal Range areas. Sampling site numbers are detailed in Table
The number of migrants per generation (Nm) among provinces was estimated from FST values using ARLEQUIN version 3.1 (
We used a clustering analysis through kMeans version 1.1 (
We tested for patterns of demographic history with Tajima’s D (
CR and Cyt b haplotypes and nucleotide polymorphism
Thirty-three CR haplotypes were detected in 47 pudu deer individuals across the five provinces analyzed (Table
Recorded haplotypes for pudu deer of five provinces from southern Chile based on mtDNA Control region (CR) and Cytochrome b (Cyt b) markers. Bold indicates new recorded haplotypes.
Province | Coordinates (Lat., Long.) | Sample size (n) | No. of haplotypes | Haplotypes |
---|---|---|---|---|
CR | ||||
Cautín | 39°0'0"S, 72°30'0"W | 5 | 4 | Y02, Y08, Y16, Y18 |
Valdivia | 39°45'0"S, 72°30'0"W | 16 | 14 | Y17, Y23, Y24, Y10, Y14, Y21, Y25, Y04, Y11, Y09, Y19, Y22, Y03, Y20 |
Osorno | 40°35'0"S, 73°10'0"W | 7 | 6 | Y17, Y05, Y27, Y28, Y15, Y26 |
Llanquihue | 41°20'0"S, 72°50'0"W | 11 | 8 | Y17, Y06, Y36, Y35, Y34, Y32, Y07, Y05 |
Chiloé | 42°30'0"S, 74°0'0"W | 8 | 4 | Y12, Y13, Y31, Y29 |
Overall | 47 | 33 | ||
Cyt b | ||||
Cautín | 39°0'0"S, 72°30'0"W | 3 | 3 | A, G, H |
Valdivia | 39°45'0"S, 72°30'0"W | 4 | 4 | A, E, I, F |
Osorno | 40°35'0"S, 73°10'0"W | 7 | 4 | A, I, L, M |
Llanquihue | 41°20'0"S, 72°50'0"W | 9 | 2 | A, C |
Chiloé | 42°30'0"S, 74°0'0"W | 7 | 4 | A, B, J, K |
Overall | 30 | 12 |
Summary of genetic diversity indices for pudu deer of five provinces from southern Chile based on mtDNA Control region (CR) and Cytochrome b (Cyt b) markers. D, Tajima’s D statistic; Fs, Fu’s Fs statistic; H, haplotype diversity ± standard deviation; Hap, number of haplotypes; k, average number of pairwise nucleotide differences; n, sample sizes; Neh, average number of expected haplotypes with 95% confidence interval in parenthesis based on coalescent simulations; S, number of polymorphic sites; Π, nucleotide diversity ± standard deviation. Within a row, means followed by different letters are significantly different. *P < 0.05, **P < 0.01.
Province | n | Hap | S | H | Π | k | Neh | D | Fs |
---|---|---|---|---|---|---|---|---|---|
CR | |||||||||
Cautín | 5 | 4 | 14 | 0.90000 ± 0.161a | 0.01022 ± 0.00208a | 6.40000 | 3.947 (2–4) | -0.34706 | 0.88316 |
Valdivia | 16 | 14 | 18 | 0.98333 ± 0.028a | 0.00797 ± 0.00067b* | 4.99167 | 7.783 (4–11) | -0.31815 | -7.75335** |
Osorno | 7 | 6 | 9 | 0.95238 ± 0.096a | 0.00624 ± 0.00105b* | 3.90476 | 4.223 (2–6) | 0.33464 | -1.64228 |
Llanquihue | 11 | 8 | 12 | 0.92727 ± 0.066b* | 0.00575 ± 0.00119b* | 3.60000 | 5.794 (3–9) | -0.52679 | -3.93267* |
Chiloé | 8 | 4 | 16 | 0.64286 ± 0.184b* | 0.00668 ± 0.00387b* | 4.17857 | 5.421 (3–8) | -1.65898* | 1.75610 |
Overall | 47 | 33 | 36 | 0.97600 ± 0.011 | 0.01126 ± 0.00104 | 7.04903 | 16.034 (11–22) | -0.50327 | -2.13781 |
Cyt b | |||||||||
Cautín | 3 | 3 | 2 | 1.000 ± 0.272a | 0.00179 ± 0.00060a | 1.333 | 1.960 (1–3) | - | - |
Valdivia | 4 | 4 | 5 | 1.000 ± 0.177a | 0.00336 ± 0.00103a | 2.500 | 2.774 (1–4) | -0.79684 | -1.514 |
Osorno | 7 | 4 | 4 | 0.810 ± 0.130a | 0.00192 ± 0.00055a | 1.429 | 3.206 (1–5) | -0.59756 | -0.780 |
Llanquihue | 9 | 2 | 1 | 0.222 ± 0.166b** | 0.00030 ± 0.00022b** | 0.222 | 1.803 (1–4) | -1.08823 | -0.263 |
Chiloé | 7 | 4 | 6 | 0.810 ± 0.130a | 0.00256 ± 0.00102a | 1.905 | 3.718 (2–6) | -1.12898 | -0.226 |
Overall | 30 | 12 | 14 | 0.798 ± 0.068 | 0.00315 ± 0.00052 | 2.338 | 8.421 (4–13) | -1.12937 | -4.562 |
Measures of genetic diversity based on CR sequences recorded in this study for pudu deer from southern Chile. A) and B) Genetic diversity observed in Cautín (CAU), Valdivia (VAL), Osorno (OSO), Llanquihue (LLA) and Chiloé Island (CHI) provinces and C) and D) genetic diversity recorded in the Andes range (AND), Central Valley (CEN) and Coastal Range (COA). Columns and bar errors represent the means and standard deviation of the means, respectively. Significant differences between means were calculated according to Welch´s t-test. *P < 0.05, NS = Non significant difference.
Ten new haplotypes for CR were observed, which were named Y26–Y29, Y31–Y32 and Y34–Y36 (Table
Haplotype frequencies for the CR sequence found in pudu deer from southern Chile. A) Haplotype frequency observed in Cautín (CAU), Valdivia (VAL), Osorno (OSO), Llanquihue (LLA) and Chiloé Island (CHI)provinces and B) haplotype frequency recorded in the Andes range (AND), Central Valley (CEN) and Coastal Range (COA). Asterisks indicate a heterogeneous frequency based on the chi-square test (P < 0.001). Haplotypes are shown by different color codes as is indicated at the right side of figure.
Twelve Cyt b haplotypes were detected in 30 pudu deer individuals across the five provinces analyzed (Table
Four new haplotypes for Cyt b were observed, which were named J–M (Table
Haplotype frequencies for the Cyt b sequence found in pudu deer from southern Chile. A) Haplotype frequency observed in Cautín (CAU), Valdivia (VAL), Osorno (OSO), Llanquihue (LLA) and Chiloé Island (CHI) provinces and B) haplotype frequency recorded in the Andes range (AND), Central Valley (CEN) and Coastal range (COA). Asterisks indicate a heterogeneous frequency based on the chi-square test (P < 0.001). Haplotypes are shown by different color codes as is indicated at the right side of figure.
Global AMOVA results as a weighted average over loci, conducted by partitioning variation among and within populations, revealed that CR haplotype variation was attributed mainly to within-population differences (58.1%) but also to differences among populations (41.9%). In fact, the FST index reached a value of 0.41905 (P < 0.001). Population pairwise FST values ranged from 0.03617 to 0.68651, with seven out of ten pairwise comparisons showing significant differences (P < 0.05) (Table
Results of the clustering analysis based on the CR sequence for pudu deer from southern Chile. A) Clusters observed for individuals from Cautín (CAU), Valdivia (VAL), Osorno (OSO), Llanquihue (LLA) and Chiloé Island (CHI) provinces and B) clusters recorded for individuals from the Andes range (AND), Central Valley (CEN) and Coastal range (COA). K values correspond to the optimal number of clusters according to the Caliński–Harabasz pseudo-F statistic.
Pairwise estimate of Nm for CR haploytpe data ranged from 0.22832 to 13.32296. The number of migrants per generation was high among Osorno, Valdivia and Llanquihue provinces (Nm = 5.18197–13.32296), medium between Cautín and Osorno plus Valdivia and Llanquihue (Nm = 2.47437–3.66488), and low for Chiloé Island compared to the other four continental provinces (Nm = 0.2283–0.34740) (Table
Tajima’s D estimate for CR was negative and significant in one province that corresponds to Chiloé (D = -1.65898, P < 0.05). In contrast, Tajima’s D statistic of other provinces was consistent with population equilibrium (Table
Analysis at the longitudinal range based on CR revealed a number of haplotypes per area ranging from 6 to 11 in 32 analyzed individuals (Table
Recorded haplotypes for pudu deer of three longitudinal ranges from southern Chile based on mtDNA Control region (CR) and Cytochrome b (Cyt b) markers. Bold indicates new recorded haplotypes.
Longitudinal range | Coordinates (Lat., Long.) | Sample size (n) | No. of haplotypes | Haplotypes |
---|---|---|---|---|
CR | ||||
Andes range | 39°-41°S, 72°7'W | 12 | 9 | Y08, Y09, Y17, Y02, Y18, Y15, Y26, Y27, Y28 |
Coastal range | 39°-41°S, 73°30'W | 14 | 11 | Y17, Y05, Y10, Y14, Y11, Y03, Y04, Y36, Y32, Y35, Y34 |
Central Valley | 39°-41°S, 72°57'W | 6 | 6 | Y27, Y05, Y10, Y07,Y16, Y06 |
Overall | 32 | 22 | ||
Cyt b | ||||
Andes range | 39°-41°S, 72°7'W | 12 | 6 | A, I, C, F, H, L |
Coastal range | 39°-41°S, 73°30'W | 10 | 4 | A, I, E, M |
Overall | 22 | 8 |
Summary of genetic diversity indices for pudu deer of three longitudinal ranges from southern Chile based on mtDNA Control region (CR) and Cytochrome b (Cyt b) markers. D, Tajima’s D statistic; Fs, Fu’s Fs statistic; H, haplotype diversity ± standard deviation; Hap, number of haplotypes; k, average number of pairwise nucleotide differences; n, sample sizes; Neh, average number of expected haplotypes with 95% confidence interval in parenthesis based on coalescent simulations; S, number of polymorphic sites; Π, nucleotide diversity ± standard deviation. Within a row, means followed by different letters are significantly different. *P < 0.05. **P < 0.01.
Longitudinal range | n | Hap | S | H | Π | k | Neh | D | Fs |
---|---|---|---|---|---|---|---|---|---|
CR | |||||||||
Andes range | 12 | 9 | 15 | 0.955 ± 0.047a | 0.007890 ± 0.00101a | 4.939 | 6.413 (3–9) | -0.02394 | -2.24957 |
Coastal range | 14 | 11 | 17 | 0.956 ± 0.045a | 0.006513 ± 0.00110b* | 4.077 | 7.178 (4–11) | -0.97905 | -6.64752** |
Central Valley | 6 | 6 | 13 | 1.000 ± 0.096a | 0.008307 ± 0.00103a | 5.200 | 4.366 (2–6) | -0.52988 | -2.08376 |
Overall | 32 | 22 | 26 | 0.968 ± 0.018 | 0.00741 ± 0.00067 | 4.639 | 11.866 (7–17) | -0.51095 | -3.66028 |
Cyt b | |||||||||
Andes range | 12 | 6 | 6 | 0.803 ± 0.096a** | 0.00167 ± 0.00040a | 1.242 | 4.270 (1–7) | -1.42890 | -2.666 |
Coastal range | 10 | 4 | 5 | 0.533 ± 0.180b** | 0.00135 ± 0.00064a | 1.000 | 3.793 (2–6) | -1.74110* | -0.876 |
Overall | 22 | 8 | 9 | 0.688 ± 0.099 | 0.00151 ± 0.00039 | 1.121 | 6.147 (3–10) | -1.82961* | -4.230 |
Pairwise FST values (below the diagonal) and number of migrants per generation (Nm) (above the diagonal) among pudu deer of five provinces from southern Chile based on mtDNA control region. Average F–Statistics over all loci: FST = 0.41905. *P < 0.05.
Cautín | Valdivia | Osorno | Llanquihue | Chiloé | |
---|---|---|---|---|---|
Cautín | 2.47437 | 3.66488 | 2.75000 | 0.34740 | |
Valdivia | 0.16810 * | 13.32296 | 5.18197 | 0.28967 | |
Osorno | 0.12005 | 0.03617 | 9.71845 | 0.27240 | |
Llanquihue | 0.15385 * | 0.08800 * | 0.04893 | 0.22832 | |
Chiloé | 0.59004 * | 0.63318 * | 0.64733 * | 0.68651 * |
Global AMOVA results as a weighted average over loci revealed that CR haplotype variation was attributed mostly to within area differences (98.6%) and scarcely to differences between areas (1.3%). In fact, the FST index was not significant and reached a value of only 0.01360 (P > 0.05). Pairwise FST values based on CR haplotype frequencies ranged from -0.01741 to 0.03434, with no significant differences observed in any comparison (P > 0.05). Pairwise estimate of Nm for CR haplotype data ranged from 14.05932 to infinity, revealing the occurrence of an important number of migrants per generation among the Andes range, Central Valley and Coastal Range. Tajima’s D was negative in all areas, but it was not significant (D = from -0.02394 to -0.97905, P > 0.05) (Table
Analysis of the CR and Cyt b mitochondrial sequences from pudu deer populations of five provinces from southern Chile revealed different levels of genetic variation, haplotype heterogeneity, a large proportion of unique haplotypes, and strong genetic structuring and clustering of individuals in some provinces. The most likely explanation for our results is that pudu deer from the study area have a low to moderate level of gene flow among populations, which suggests the occurrence of reduced panmixia across the collection range. This genetic pattern is in accordance with our predictions of marked genetic divergence among pudu deer populations, especially those located at the extremes of the distribution or those that inhabit islands, due to the existence of geographic barriers that may have promoted genetic divergence. In fact, individuals from Chiloé Island that are separated from the continental populations by the Chacao channel formed clear single groups in the clustering analysis in concordance with the existence of such a geographic barrier, which should have reduced gene flow with the other continental analyzed populations. In this regard, the separation among continental and island populations of pudu deer, estimated at least 217,500 year ago (
In addition, our results also suggest that some provinces, particularly Valdivia, Llanquihue and Chiloé Island, underwent population expansion given that they showed significant negative Tajima’s D and Fu's Fs values. This expansion process could explain the shared haplotypes among neighboring provinces, such as Valdivia, Osorno and Llanquihue, where the Y05 and Y17 CR haplotypes were highly frequent. In the case of the Cyt b marker, although it did not present any significant population disequilibrium, the occurrence of shared haplotypes for this marker among all provinces analyzed, particularly the A and I haplotypes, suggests that population expansion for pudu deer could be a more extensive process. Of note is that the analysis at the longitudinal range supports that populations located in the Coastal Range would be an important source of individuals for colonization, given that both markers showed significant population disequilibrium in this geographic area. These results are in accordance with the statement that this area was a lowland refuge for vertebrates during the Pleistocene glaciations (
A number of studies have indicated that Pleistocene glaciations modified the landscape in southern Chile, which affected the species distribution and created habitat fragmentation of areas that species used as refuges (
Previous reports indicate that pudu deer from Chiloé Island have marked genetic divergence with respect to continental populations of this species, especially those from the northernmost distribution (
Genetic and demographic analyses of the mtDNA control region and cytochrome b sequences carried out for pudu deer of five provinces located at different latitudinal sites in southern Chile, indicate the existence of different levels of genetic variation, haplotype heterogeneity, a large proportion of unique haplotypes, strong genetic structuring, clustering of individuals in a province (i.e., Chiloé Island) and a signature of population expansion in some provinces (i.e., Valdivia, Llanquihue and Chiloé Island). These results indicate that pudu deer have a low to moderate level of gene flow, especially among distant continental provinces or between continental provinces and Chiloé Island, which suggests the occurrence of reduced panmixia. This genetic pattern could be related to the existence of geographic barriers and/or paleoclimatic events that may have promoted genetic divergence, such as the Pleistocene glaciations that modified the landscape in southern Chile. Analysis at the longitudinal range within the studied provinces revealed haplotype variation attributed mostly to within areas differences and the existence of a population expansion process in the Coastal mountain range. The last finding supports the statement that this area was a lowland refuge for vertebrates during the Pleistocene glaciations, where the vertebrates persisted during this geological period to later recolonize the areas where the ice sheet retreated. Since pudu deer in Chile is a threatened species, our results have conservation implications because populations of some analyzed geographic areas may constitute significant evolutionary units, which is of major importance when conservation plans are considered.
We would like to thank the following people for providing samples of Pudu deer from Osorno Province: Carlos Oyarzún, Museo de Historia Natural de Purranque; Carlos Hernández, Parque Nacional Puyehue; Mario Prussing, Centro de Reproducción del Pudu, Osorno; and Hugo Oyarzo, Sitio Paleontológico de Pilauco, Osorno. This study was supported by grant R25-19 of the Dirección de Investigación of the Universidad de Los Lagos. The mapping support by Alicia Vásquez Parraguez is also appreciated.