How Do Natural Disasters Contribute To Genetic Drift

PLoS One. 2011; half dozen(9): e23822.

The Event of Recurrent Floods on Genetic Composition of Marble Trout Populations

José Martin Pujolar

¹ Section of Biology, University of Padova, Padova, Italian republic

Simone Vincenzi

² Department of Ecology Sciences, University of Parma, Parma, Italy

Lorenzo Zane

¹ Department of Biology, Academy of Padova, Padova, Italia

Dusan Jesensek

³ Tolmin Angling Association, About na Soci, Slovenia

Giulio A. De Leo

² Section of Environmental Sciences, University of Parma, Parma, Italy

Alain J. Crivelli

⁴ Station Biologique de la Tour du Valat, Arles, France

Sergios-Orestis Kolokotronis, Editor

Received 2011 Apr 1; Accustomed 2011 Jul 26.

Abstruse

A changing global climate can threaten the diverseness of species and ecosystems. We explore the consequences of catastrophic disturbances in determining the evolutionary and demographic histories of secluded marble trout populations in Slovenian streams subjected to weather extremes, in item recurrent flash floods and debris flows causing massive mortalities. Using microsatellite data, a pattern of extreme genetic differentiation was establish among populations (global F _ST of 0.716), which exceeds the highest values reported in freshwater fish. All locations showed depression levels of genetic diversity as evidenced by low heterozygosities and a mean of only ii alleles per locus, with few or no rare alleles. Many loci showed a discontinuous allele distribution, with missing alleles across the allele size range, suggestive of a population contraction. Accordingly, bottleneck episodes were inferred for all samples with a reduction in population size of 3–4 orders of magnitude. The reduced level of genetic diversity observed in all populations implies a strong affect of genetic drift, and suggests that along with express gene menstruum, genetic differentiation might have been exacerbated by recurrent mortalities likely caused past flash flood and droppings flows. Due to its low evolutionary potential the species might neglect to cope with an intensification and contradistinct frequency of flash inundation events predicted to occur with climatic change.

Introduction

Climatic change poses a serious threat to species persistence. Many species will feel selection in new directions and at new intensities, and the caste to which species respond adaptively to dynamic and uncertain futures will determine their survival over the coming decades and millenia [ane]. Intensification of weather extremes and associated catastrophic disturbances is emerging equally one of the most important aspects of climatic change and research is advancing from studying the impacts of changes in mean climate values (trend furnishings) to those produced by changes in the magnitude or frequency of extreme events (event effects) [2]. Catastrophes are characterized past their statistical extremeness combined with a short duration relative to the life cycle of the organisms afflicted; they can disrupt ecosystem, customs or population structure and alter resources, substrate availability, or the physical environment [ii]–[4]. Evidence suggests that the frequency and intensity of farthermost weather condition events (i.east. floods, droughts) is increasing in many regions in response to global climate alter [5]–[vii]. Despite the urgent need to advance research on extreme events and catastrophic disturbances, their evolutionary consequences have largely been unexplored [eight].

Freshwater salmonids are ordinarily discipline to substantial ecology variability in the form of changes in stream flow at different time scales [9]–[11]. Extreme events such as floods, droughts or landslides play an important office in the regulation of population dynamics in salmonids, to the extent that in high-density streams, fish demography and persistence might exist largely shaped past extreme flow events [12]–[15]. The direct and brusque-term effects of floods are largely a result of loftier-water velocities and sediment movement that cause the displacement and death of fish. The touch of floods is expected to be higher in the coming years. According to IPCC predictions, an increment of rainfall is expected in the next 50 years along with an intensification and altered frequency of catastrophic disturbances [5]. Contempo advances in the statistical theory of extreme events suggest that large flood events will be more frequent, with render times markedly shorter than expected fifty-fifty in the absence of climate change [xvi].

Our model organization is the stream-abode salmonid marble trout Salmo marmoratus, an endemism of the Adriatic Bounding main and its tributaries, currently restricted to Northern Italy, former Yugoslavia (Slovenia, Croatia, Bosnia-Herzegovina) and Albania [17]. Marble trout is considered to be 1 of the most endangered species in the Adriatic basin [18]. For decades, massive restocking practices have been conducted throughout its natural range by ways of introduction of exotic brown trout. Hybridization between marble and brownish trout has been so all-encompassing that hybrids now boss most rivers [19]. Molecular data confirm a high level of introgression in the Po river in Northern Italy [xx], [21], the Soca river system in the Italian/Slovene border [18], [22], [23], and recently, the Adige river system in South Tyrol [24], [25]. Nevertheless, all studies also reported pure populations of marble trout in headwaters of all river systems, persisting above natural barriers (i.eastward. waterfalls). While those barriers prevent the upstream migration of conspecifics and consequent hybridization, the secluded nature and the small size of the remnant marble trout populations makes them extremely vulnerable to stochastic factors, including environmental events such as floods, droughts or landslides.

A project for the conservation and rehabilitation of marble trout in Slovenia started in 1993 [17]. But 7 remnant pure (not-introgressed with brown trout; [23]) populations of marble trout remain in the Adriatic basin of Slovenia, persisting in totally isolated headwaters without predators or fishing [17]. Recurrent major floods and debris flows are the nearly important risk factor for the viability of marble trout populations in Slovenian streams [15], [26]. The trigger of debris flows in the area is extreme precipitation, with records of intense flows going dorsum to the 18^thursday century, and with a presumable occurrence interval of approximately fifty years (i.e. in the 20^th century major floods were recorded in 1926, 1954 and 1990; [27]). All the same, an intensification of the frequency of flash floods has been observed in the final decade, with iv important flood events recorded in the 1999–2010 menstruum (Tabular array one).

Table one

Occurrence and intensity of alluvion events in the report area in the period 1999–2010, showing medium floods (m, 10 to 20-year recurrence interval) and major floods (M, l to 100-year recurrence interval).

Population	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010
Zadlascica	A/yard					A/Thou			A/M		S/m	A/thou
Lipovscek	A/M	A/thousand			A/m	A/M			A/K		A/M	A/chiliad
Sevnica			A/m			A/M	A/k				Southward/m	S/m
Studenc		A/m	A/thou			A/M	A/m				S/m	S/one thousand

The aim of this study is to explore the affect of catastrophic atmospheric condition events on the genetic composition of isolated marble trout populations from the Adriatic basin of Slovenia (Figure one). As a upshot of intense precipitation and associated flash flood and debris flows, which causes mass mortalities but does not change connectivity among isolated streams and basins, low levels of genetic multifariousness and high genetic substructuring at local geographic scale are expected. In this study, we were peculiarly interested in the comparing of pre- and post-alluvion samples, testing shifts in genetic composition and genetic variety and estimating the possible existence of bottleneck/population declines.

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Location of all marble trout sampling locations.

Results

A total of 18 out of 24 loci were polymorphic, showing from 2 to 8 alleles per locus (Table two). All locations showed low levels of genetic variety as evidenced by heterozygosities <0.25 and allelic richness <2 (Table 3). Many loci showed a discontinuous allele distribution, with missing alleles across the allele size range, and few or no rare alleles (Table S1). A total of 31 location-specific private alleles were found, representing 49% of the total number of alleles sampled. Across locations, Studenc showed the highest genetic diversity, with intermediate levels found in Zadlascica and the lowest genetic variability found in Lipovscek and Sevnica (Table iii). When comparing pre- and post-flood samples, a moderate drop in genetic diversity was observed in all 4 locations in terms of H _o and H _e and allele richness (AR), mostly due to the loss of rare alleles (Table three; Table S1). However, statistic comparisons between pre- and post-flood values of genetic diversity were not-pregnant at all locations: Zadlascica (H _o: p = 0.714; H _e: p = 0.891; AR: p = 0.747), Lipovscek (H _o: p = 0.650; H _e: p = 0.650; AR: p = 0.396), Sevnica (H _o: p = 0.591; H _e: p = 0.554; AR: p = 0.551) and Studenc (H _o: p = 0.726; H _{due east}: p = 0.451; AR: p = 0.999).

Tabular array 2

Microsatellite loci analyzed in marble trout including microsatellite type, repeat motif, size range (in bp), maximum number of alleles per locus (NA), and species in which the microsatellites were originally developed (Salmo salar, Due south. trutta, S. marmoratus).

Name	Blazon	Motif	Size	NA	MX	Species	Reference
{"type":"entrez-nucleotide","attrs":{"text":"CA048828","term_id":"24354998"}}CA048828	EST	CA	246–276	iv	1	S. salar	Vasemagi et al. 2005
{"type":"entrez-nucleotide","attrs":{"text":"CA048687","term_id":"24354857"}}CA048687	EST	AC	216	1	ii	S. salar	Vasemagi et al. 2005
{"type":"entrez-nucleotide","attrs":{"text":"CA060208","term_id":"24390451"}}CA060208	EST	CA	166	1	2	S. salar	Vasemagi et al. 2005
{"type":"entrez-nucleotide","attrs":{"text":"CA039543","term_id":"24340151"}}CA039543	EST	AT	145–147	2	1	South. salar	Vasemagi et al. 2005
{"type":"entrez-nucleotide","attrs":{"text":"CB515794","term_id":"29327020"}}CB515794	EST	GT	262–264	two	ii	Southward. salar	Vasemagi et al. 2005
{"blazon":"entrez-nucleotide","attrs":{"text":"CB512797","term_id":"29324023"}}CB512797	EST	AC	375–407	7	2	S. salar	Vasemagi et al. 2005
{"type":"entrez-nucleotide","attrs":{"text":"CA060177","term_id":"24390420"}}CA060177	EST	TGAC	300–320	5	1	S. salar	Vasemagi et al. 2005
{"type":"entrez-nucleotide","attrs":{"text":"CA769358","term_id":"25998613"}}CA769358	EST	AC	98	one	ii	S. salar	Vasemagi et al. 2005
{"blazon":"entrez-nucleotide","attrs":{"text":"CA053293","term_id":"24383536"}}CA053293	EST	Air-conditioning	156–158	ii	ane	South. salar	Vasemagi et al. 2005
{"type":"entrez-nucleotide","attrs":{"text":"CA040282","term_id":"24341208"}}CA040282	EST	AT	121	ane	two	S. salar	Vasemagi et al. 2005
{"type":"entrez-nucleotide","attrs":{"text":"CA059136","term_id":"24389379"}}CA059136	EST	TA	329–355	8	2	S. salar	Vasemagi et al. 2005
{"type":"entrez-nucleotide","attrs":{"text":"CA058902","term_id":"24389145"}}CA058902	EST	TA	179–181	2	2	South. salar	Vasemagi et al. 2005
{"type":"entrez-nucleotide","attrs":{"text":"CA050376","term_id":"24380619"}}CA050376	EST	GT	283–291	2	1	S. salar	Vasemagi et al. 2005
{"blazon":"entrez-nucleotide","attrs":{"text":"BG935488","term_id":"15845316"}}BG935488	EST	CAAT	131–143	ii	one	S. salar	Vasemagi et al. 2005
CL47345	EST	TG	220–232	three	ane	S. salar	Siemon et al. 2005
Str73	Genomic	CT	151–165	3	1	S. trutta	Estoup et al. 1993
Str151	Genomic	GT	216	1	1	South. trutta	Estoup et al. 1993
Str85	Genomic	CT	171–181	3	2	S. trutta	Presa & Guyomard 1996
Str543	Genomic	CT	130–134	3	1	Due south. trutta	Presa & Guyomard 1996
Str591	Genomic	CT	152–156	3	ii	Due south. trutta	Presa & Guyomard 1996
T3-thirteen	Genomic	GT	162–168	iv	2	S. trutta	Estoup et al. 1998
Strutta58	Genomic	GT	104–124	4	2	S. trutta	Poteaux et al. 1999
Ssa85	Genomic	GT	108	one	2	Due south. salar	O'Really et al. 1996
BFRO001	Genomic	TG	202–212	3	1	S. marmoratus	Snoj et al. 1997

Tabular array 3

Summary of genetic variability estimates beyond samples including number of individuals (North), expected (H _e) and observed (H _o) heterozygosities, total (TNA) and mean (MNA) number of alleles and allelic richness (AR).

Sample	Northward	H _e	H _o	TNA	MNA	AR
1A- Zadlascica 2007	30	0.179	0.166	29	one.56	1.50
1B- Zadlascica 2008	xv	0.173	0.163	28	one.50	one.49
2A- Lipovscek 2004	thirty	0.116	0.141	30	1.67	ane.45
2B- Lipovscek 2005	28	0.094	0.112	26	1.44	i.33
3A- Sevnica 2004	xxx	0.128	0.138	32	ane.78	1.60
3B- Sevnica 2005	thirty	0.102	0.110	xxx	1.61	ane.43
4A- Studenc 2004	thirty	0.242	0.204	35	1.94	1.75
4B- Studenc 2005	30	0.205	0.189	34	1.89	i.72

All loci were at HWE after Bonferroni correction. A neutrality test using LOSITAN suggested no loci to be subject to balancing option or directional pick. No difference in values of genetic diversity was found between EST-derived microsatellites and genomic microsatellites, including H _o (EST-microsatellites: 0.126; genomic microsatellites: 0.195; p = 0.232), H _e (EST-microsatellites: 0.138; genomic microsatellites: 0.180; p = 0.464) and AR (EST-microsatellites: 2.87; genomic microsatellites: 2.78; p = 0.964).

A highly significant extreme overall genetic differentiation was found among samples (F _ST = 0.716; p<0.001). All pairwise F _ST and genetic distances between samples from different locations were loftier (F _ST = 0.649–0.779; D_CE = 0.592–0.839) and statistically significant (p<0.001; Tabular array four). By contrast, comparison of pre- and post-flood samples from the aforementioned location showed low non-significant F _ST and genetic distances with the exception of Studenc (F _ST = 0.041, p = 0.020; D_CE = 0.021, p = 0.035). Accordingly, comparison of allele frequencies between pre- and post-flood samples using an exact test showed no temporal differences at Lipovscek (p = 0.993), Sevnica (p = 0.450) and Zadlascica (p = 0.985), while meaning differences were found at Studenc (p<0.001) caused by loci {"type":"entrez-nucleotide","attrs":{"text":"CA059136","term_id":"24389379"}}CA059136 and Str151.

Table four

Pairwise F _ST estimates (higher up diagonal) and genetic distances (D_CE, beneath diagonal) between samples, labeled as in Table three.

Sample	1A	1B	2A	2B	3A	3B	4A	4B
1A	***	0.001	0.737^**	0.758^**	0.707^**	0.733^**	0.673^**	0.681^**
1B	0.004	***	0.752^**	0.779^**	0.719^**	0.753^**	0.679^**	0.673^**
2A	0.712^**	0.719^**	***	0.001	0.738^**	0.761^**	0.693^**	0.717^**
2B	0.735^**	0.743^**	0.007	***	0.755^**	0.778^**	0.709^**	0.734^**
3A	0.658^**	0.669^**	0.606^**	0.601^**	***	0.002	0.649^**	0.673^**
3B	0.673^**	0.680^**	0.598^**	0.592^**	0.011	***	0.668^**	0.694^**
4A	0.833^**	0.839^**	0.753^**	0.779^**	0.630^**	0.673^**	***	0.040^*
4B	0.787^**	0.793^**	0.725^**	0.753^**	0.595^**	0.609^**	0.021^*	***

Accordingly, an AMOVA analysis partitioned genetic differentiation significantly among locations (F _CT = 0.713; p<0.001) merely not amongst (pre- and post-flood) samples within locations (F _SC = 0.011; p = 0.067) (Table v). We conducted a Multidimensional Scaling analysis using D_CE at all loci (Figure 2). When plotting the values of the first and 2nd primary components, samples amassed co-ordinate to location, the Zadlascica location (from a tributary of the Soca river) appeared very different from the residue of locations (from tributaries of the Idrijca river), but and so did Studenc despite existence twenty km apart from Sevnica. In this sense, when testing Isolation-by-Distance, no correlation was found between genetic and geographic (shortest waterway) distances (r = 0.715; F = 4.19; p = 0.110). Consignment analysis using Structure confirmed the farthermost genetic differentiation among locations and suggested a scenario with G = 4 groups as the most likely (p<0.001), corresponding to the iv sampled locations, Zadlascica, Lipovscek, Sevnica and Studenc.

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Plots of the values of the first and second principal coordinates obtained from Cavalli-Sforza and Edwards (1967) chord distances at all loci.

Samples labeled as in Table three. A = pre-flood samples; B = post-overflowing samples. Stress value = 0.062.

Table 5

Results from AMOVA assay division genetic differentiation among locations (4 locations: Zadlascica, Lipovscek, Sevnica and Studenc) and among samples within locations (pre- and post-flood samples).

AMOVA	Sum of squares	Var	F
Amidst locations	1124.41	3.46	F _CT = 0.713 (p = 0.000)
Among samples within locations	8.88	0.02	F _SC = 0.011 (p = 0.067)
Within samples	570.76	1.38
Overall	1704.06	4.86	F _ST = 0.716 (p = 0.000)

The MSVAR process for assessing past demographic history strongly supported a turn down in all marble trout populations. All sampled points of log_ten(r) were substantially below naught in all 8 samples, suggesting that the past population size was larger than the electric current population size (Figure iii). All sampled points of log₁₀(θ) were negative, pointing to small current effective population sizes. Using a conservative mutation rate of μ = 10⁻⁴, Northward ₁ varied beyond locations between 3 and 41 individuals, with a maximum upper-bound CI of N ₁ of 396 individuals (Table vi). Using higher mutation rates (i.due east. 5×10⁻⁴ and 10^−three), Due north ₁ values <than 1 were obtained, while lower mutation rates (i.e. 5×10⁻⁵) yielded unrealistic N ₀ values. The time of the bottleneck varied between 31 and 268 generations across locations (or roughly 100–800 years assuming a generation time of two.seven–3 years), with a maximum upper-bound CI of 2300 generations (roughly 7000 years).

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Plots of the faux points from the marginal posterior distributions of log_ten (r) (x-axis) and log_ten (t_f) (y-axis).

Samples labeled equally in Table 3.

Tabular array 6

Summary statistics of MSVAR across all locations, including the genetic parameter θ = 2N ₀μ, which was calculated using a mutation rate of μ = 10⁻⁴, r =Northward ₀/N _one (N ₀ = current effective population size; Due north ₁ = constructive population size at the time of population expansion or decline), and t _f =t _a/North ₀ (t _a = number of generations since the get-go of the expansion/decline).

	1A	1B	2A	2B	3A	3B	4A	4B
θ	0.0006	0.0024	0.0006	0.0063	0.0069	0.0082	0.0014	0.0023
r	3.8×x⁻⁵	i.i×10⁻⁴	nine.0×10⁻⁴	nine.2×ten⁻⁴	6.1×10⁻⁴	1.ane×10⁻³	1.half-dozen×ten⁻⁴	1.i×ten^−four
t _f	14.52	11.27	seven.67	seven.43	8.18	six.47	7.xiii	eight.44
N ₀	three	12	31	32	35	41	7	12
	(i–27)	(ane–66)	(ane–257)	(1–259)	(1–299)	(1–396)	(1–55)	(i–68)
N ₁	8.0×10⁵	1.5×x^v	8.nine×10⁴	7.6×10^iv	1.1×10⁵	4.one×x^four	6.0×10⁴	1.1×10⁵
	(5.half dozen×10⁴–1×10^six)	(three.6×10^four–4.3×ten^v)	(viii×10³–iv.7×ten⁵)	(8×10^three–iii.7×10^five)	(1.six×10⁴–4.iii×10⁵)	(5.four×10³–1.7×10⁵)	(1.7×ten⁴–ane.7×10^five)	(2.4×10^iv–3×x⁵)
t _a	31	106	172	179	215	268	83	73
	(1–264)	(one–529)	(1–1400)	(1–1507)	(ane–1902)	(1–2300)	(1–301)	(1–405)

Clogging-detection tests (Table 7) using the sofware BOTTLENECK and M_P_VAL showed some indications of population wrinkle at all locations. Garza and Williamson [28] suggested that values of Chiliad lower than 0.7 would indicate testify of a bottleneck, while values above 0.8 would announce no bottleneck history. In our data ready, all Zadlascica and Studenc samples plus the pre-overflowing Lipovscek sample showed M values betwixt 0.518–0.661. The two Sevnica samples plus the post-flood Lipovscek sample showed M values betwixt the 0.seven–0.viii limits.

Table seven

Results of the bottleneck analyses.

Sample	P value (Wilcoxon test)	Chiliad value (M_P_VAL)	p value (M_P_VAL)
1A	0.009	0.566	0.001
1B	0.043	0.518	0.001
2A	0.103	0.661	0.038
2B	0.381	0.733	0.343
3A	0.691	0.744	0.328
3B	0.606	0.793	0.751
4A	0.044	0.638	0.011
4B	0.193	0.610	0.003

Discussion

Extreme differentiation amongst marble trout populations

Freshwater fish species bear witness a greater average degree of genetic differentiation among locations than marine species, resulting from the isolation of fish populations among drainages [29]. The marked zoogeography produced past the historical patterns of isolation amongst drainages is subjected to the continuous remodeling of the river drainage and to climatic fluctuations of which the glacial/interglacial periods of the Pleistocene played a crucial role [thirty]. Species reply actively to fluctuations in their natural range, with hydrographic networks beingness used for colonization and for retreat throughout geological times. College levels of population subdivision accept been constitute in many salmonid studies reflecting circuitous genetic structures often resulting from isolation amid drainages. In beck charr Salvelinus fontinalis, a global F _ST of 0.37 was establish among 26 populations from La Maurice National Park in Canada located 3–42 km apart [31]. In cutthroat trout Oncorhynchus clarkii, Taylor et al. [32] found an overall F _ST of 0.32 and pairwise F _ST values upwards to 0.45 in populations from British Columbia, while the recent report of Pritchard et al. [33] reported a global F _ST of 0.41 for Rio Grande populations. In bull trout Salvelinus confluentus, Taylor and Costello [34] found an F _ST = 0.33 among xx Northward-W America coastal locations, while recent papers reported an overall F _ST of 0.fifteen and pairwise F _ST values up to 0.31 in Alberta [35] and pairwise F _ST values upward to 0.66 betwixt lake samples in a 50 km expanse off Montana [36].

Collectively, the extreme level of genetic differentiation found among Slovenian marble trout populations (overall F _ST = 0.716; pairwise F _ST betwixt drainages = 0.649–0.779; 49% private alleles sampled) exceeds the highest values reported in salmonid populations found above waterfalls and/or in small-scale streams similar the ones in this study. Such extremely loftier F _ST is indicative of complete genetic isolation that has persisted over time. This is concordant with the previous study of Fumagalli et al. [23], which reported a global F _ST of 0.66 in the aforementioned area using a smaller number of microsatellites. At present, the four locations in our report are completely isolated from each other and from the chief river drainage by means of impassable natural barriers (waterfalls) that restrict dispersal abilities. Baloux and Lugon-Moulin [37] argued that fifty-fifty in the total absence of gene flow, extreme genetic differentiation of the magnitude found in our study is not expected due to the high mutation rate of microsatellites [38], with appearance of new variants counteracting inside-population fixation of alleles. However, the depression level of genetic diversity observed in all locations (low heterozygosities and depression number of alleles) implies a strong impact of local genetic drift, and suggests that, together with absence of gene menses, genetic differentiation among locations may accept been exacerbated by recurrent mortalities likely acquired past flash overflowing and droppings flows. The combined furnishings of genetic migrate and inbreeding following demographic bottlenecks may have thus contributed to alter distinctly the genetic limerick of each population, so that over fourth dimension dissimilar populations ended upwards having different alleles at each locus every bit well every bit different allele combinations from multiple loci, resulting in the observed pattern of farthermost genetic differentiation.

The MSVAR procedure clearly suggested a population contraction with a reduction in population size of three–4 orders of magnitude to current effective densities of around 3–41 (CI: one–396) individuals per location. Bottleneck signatures were observed in all samples. First, almost polymorphic loci presented a biallelic pattern with few (or none) rare alleles. Second, a discontinuous allele range was plant at many loci (Table S1). For instance, merely alleles 104, 110, 118 and 124 were sampled across locations at locus Strutta58, which suggests that the non-observed alleles have been lost over time. By dissimilarity, samples nerveless in tributaries of the river Po in Northern Italy showed a continuous allele distribution and a higher number of alleles at five microsatellite loci [39], suggestive of demographically stable populations with no signatures of bottlenecks. Loci Ssa85 and Str15, which were monomorphic in Slovenian locations (our study), showed six–9 alleles in Italian locations. Loci Str85, Str543 and Str591, which presented three alleles each in our study, showed higher allelic richness in the Italian samples (7–17 alleles). Pujolar et al. [39] also reported a lower genetic differentiation among Italian pure marble trout locations (global F _ST of 0.235). The different pattern suggested for Italian and Slovenian populations of marble trout, with signatures of a bottleneck only observed in the latter, might be due to the particular geography and the extreme issue of meteorological events in the region of Slovenia studied. Rainfall data have been caused since 1961 (ARSO, Ecology Agency of Slovenia). While the almanac mean atmospheric precipitation was 2,400 mm in the 1961–2004 period, showing little variation across years, monthly rainfall showed upwards to 500-fold variation. Morphological features of the streams and watersheds in the region (i.east. high slopes, narrow walls, stream bed fragmentation, limited flood manifestly) are largely responsible for the high water catamenia in the stream afterwards heavy rainfalls, and might explain the massive mortalities caused by flood events.

In contrast with the farthermost differentiation found at microsatellite loci, one single mitochondrial DNA control region haplotype (MA1) has been reported for marble trout in Slovenia [22], [39]. This suggests that despite the current complete geographic isolation of marble trout populations in Slovenian streams, those populations were interconnected in a relatively contempo past prior to the fragmentation of habitats. On the basis of microsatellite data, Fumagalli et al. [23] suggested that the pure populations within the Idrijca drainage belonged to an independent river system. Even so, our analysis on a larger number of microsatellite loci does not support the segmentation by river basins, as the two locations from the Idrijca basin in our sampling (Sevnica and Studenc) did not cluster together in the Multidimensional Scaling analysis, and appeared conspicuously differentiated despite existence but 20 km autonomously inside the same river basin.

Genetic consequences of series bottlenecks

The analysis of pre- and post-overflowing samples in our study allowed united states to explore the genetic consequences of population bottlenecks. The effects of bottlenecks are directly related to the increase of stochastic events associated with small population sizes, leading in well-nigh cases to a loss in genetic variability [twoscore]. Recently, Bouzat [41] suggested that the potential genetic outcomes of demographic bottlenecks can only be assessed when because replicated bottlenecked populations. In our study, nosotros explored four separate locations that experienced episodes of massive mortalities with consequent reductions in population size ranging from 56 to 77%. Collectively, and taking into the consideration the magnitude of the demographic pass up, only a express genetic effect was observed. A moderate drop in genetic variety was establish in all locations, both in terms of heterozygosities and allelic richness, but all comparisons were statistically non significant. However, a total of ix alleles were lost locally, in all the cases representing rare alleles with frequencies <0.05 prior to the overflowing that were no longer sampled subsequently the alluvion events. Moreover, bottlenecks resulted in alteration of allele frequencies, peculiarly secondary alleles, which in some cases experienced a drib of 20–xxx% in frequency. This was notably observed at Studenc, where genetic composition was significantly dissimilar in pre- and mail service-flood samples, but not at the other populations.

The moderate reduction of allelic diversity and heterozygosity might be attributable to the particular demographic history of those populations. In his contempo review, Bouzat [41] emphasized the potential role of population history in determining the outcome of demographic bottlenecks. Specifically, ane can expect that populations experiencing recurrent bottlenecks might have had their genetic pool already eroded over time, which would subtract the effectiveness of both purifying selection and random allele emptying. This holds especially true for the Slovenian marble trout populations in our study, which accept been repeatedly impacted past severe flood events, with a presumable occurrence interval of fifty–100 years [27]. Bayesian demographic analysis using the MSVAR procedure is concordant with a scenario of serial bottleneck episodes that might have been occurring for 150–1340 years.

On the question of how do the Slovenian population still maintain some polymorphism despite experiencing overflowing events for hundreds of years, one possible explanation is that our sampling is not representative of the entire population, and other compartments of the population might keep some genetic variation. One hypothesis could be that immature fish (historic period 0+ and one+) might be less sensible to flows because usually they are not establish in the main stream but in more protected small tributaries, repopulating the stream even if all adults have been removed. Nonetheless, field observations suggest that eggs and young fish are more than vulnerable to floods than adults and that there is no recruitment at all when floods occur subsequently reproduction (Crivelli, unpublished information). Alternatively, an upstream part of the population could be preserved. This hypothesis is supported by tagging data (Crivelli, unpublished information) that show not-tagged individuals in mail-alluvion samples, whereas all pre-alluvion samples had been tagged, which suggests that the newly-arrived non-tagged individuals came from a compartment of the population located upstream, flushed by the flood.

Coping with environmental change

Our findings strongly propose that the evolutionary and demographic history of marble trout populations living in secluded Slovene streams has been shaped by massive mortalities acquired past disturbance factors such every bit flash flood and debris flows. Overall, genetic assay revealed an extremely loftier genetic differentiation among remnant pure populations, together with much depression levels of genetic diversity in all populations. Effective population sizes estimated using the MSVAR procedure ranged from three to 41 (CI:i–396) individuals per population. The low genetic variability institute does not seem to affect the viability of the populations so far, as they have persisted upwardly to the present despite recurrent and unpredictable disturbances. To mitigate their ecological impact, fish populations might showroom several adaptations that event from trade-off amongst growth, reproduction and survival. According to life-history theory, recurrent floods can have of import evolutionary consequences past selecting for life-histories that are synchronized to either avoid or exploit the straight and indirect effects of extreme flows [42]. However, due to the predicted intensification of extreme weather condition leading to increased floods, heatwaves, droughts and rainfall in the adjacent l years [five], [43], marble trout may non have the sufficient genetic potential for the development of life-histories able to mitigate their impact. Recent studies by the European Commission's Joint Research Centre (JCR) take confirmed rising temperatures (around 1.5°C in the last 35 years) and higher levels of atmospheric precipitation in Slovenia, with a projected increase in the occurrence of extreme rainfall events and wink floods. For 2020, Lehner et al. [44] predict major flood events for the Adriatic basin of Slovenia to become more than frequent and intense. This might jeopardize the survival of marble trout as the occurrence of consecutive floods in a very brusk period of time could wipe out the population. This nearly occurred in the Lipovscek stream: a good recovery was observed following the 2004 alluvion, but in September 2007 a new of import debris flood occurred with a mortality of 92.4% that left only 38 fish in the whole population. After a new major flood in 2009 followed by a moderate flood in 2010, the population has been decimated to simply x individuals, and so that at present, the recovery of Lipovscek remains uncertain (Crivelli, unpublished information). Medium flows (10 to twenty-year recurrence interval) have also get more than frequent with three–v moderate flow events observed in the last 10 years in the four populations in our study, and additionally, since 2009 jump floods take been observed for the offset time in the region.

Collectively, while the Slovene marble trout populations have coped successfully with recurrent yet unpredictable disturbance events over time, the low genetic variation found in the species makes information technology difficult to assess its evolutionary potential since a genetically depauperate population might neglect to adapt to future ecology change. Moreover, all populations are closed, and there is no potential for spontaneous colonization of new habitats or re-colonization after local extinction. It has been proposed that an constructive population size of 500 individuals is large plenty to maintain genetic diversity for primal history traits [45]. The estimation in our study of effective population sizes of 3–41 individuals is one-two orders of magnitude lower than the threshold of 500 individuals, plus the upper-bound CI of population size does not overlap with the threshold value. This suggests that the Slovenian marble trout populations are beyond the critical population size for genetically secure populations. The future evolution of an integrated genetic/ecologic model that explores different demographic scenarios with varying caste of intensity and frequency of flood events might help disentangling the role of catastrophic disturbances in determining the genetic structure and genetic multifariousness of marble trout.

Materials and Methods

Sampling

All fauna piece of work was approved by the Ministry of Agronomics, Forestry and Food of Republic of Slovenia and the Fisheries Research Institute of Slovenia. Original championship of the Programme: RIBISKO - GOJITVENI NACRT za TOLMINSKI RIBISKI OKOLIS, razen Soce s pritoki od izvira practise mosta v Cezsoco in Krnskega jezera, za obdobje 2006–2010. Sampling was supervised past the Tolmin Angling Association (Slovenia).

A total of 223 pure marble trout Salmo marmoratus individuals were defenseless using electrofishing at four tributaries of the Soca (1.Zadlascica), Baca (two.Lipovscek) and Idrijca (3.Sevnica and four.Studenc) rivers in Slovenia (Figure 1). During field work fin clips were nerveless from anaesthetised individuals that were tagged and immediately released back into the streams. At Lipovscek, Sevnica and Studenc, samples were obtained in September 2004 prior to a flooding upshot that acquired a bloodshed of 56.four%, 77.6%, and 67.9% in fish ≥ age-1, respectively. Post-overflowing samples were obtained at all three locations in September 2005. At Zadlascica, samples were obtained in September 2007 prior to a flooding event that caused a 74.nine% drop in population size. Post-inundation samples from Zadlascica were obtained in September 2008. Number of individuals in post-flood samples were constrained to the high mortalities and consistent low number of survivors, with only 15 individuals left in the case of Zadlascica after the flash flood event.

Microsatellite amplification

Minute sections of tissue from ethanol-preserved finclips were digested in a lysis buffer containing 100 µl TE Buffer, seven µl 1 M DTT (dithiothreitol) solution pH five.ii (diluted in 0.08 M NaAC) and ii µl proteinase Grand solution (20 mg/ml) for at least 8 hours at 56°C. After incubation at 96°C for 10 min, samples were centrifuged at 13,000 rpm for xi min, and the supernatant was stored at −20°C.

All samples were scored for a total of 24 microsatellite loci (Table two). 15 loci were derived from Expressed Sequence Tags (ESTs) previously described by Vasemagi et al. [46] and Siemon et al. [47] in Atlantic salmon Salmo salar. We selected those loci with the highest genetic variation and a positive cantankerous-species amplification in brownish trout Salmo trutta. Additionally, 9 genomic microsatellite loci isolated and characterized from other salmonids, seven from dark-brown trout (Str73, Str151: [48]; Str85, Str543, Str491: [49]; T3-13: [fifty]; Strutta58: [51]), i from Atlantic salmon (Ssa85: [52]) and one from marble trout (BFRO001: [53]) were amplified and scored. Microsatellites were grouped in two split up multiplexes in order to reduce polymerase chain reaction (PCR) and genotyping costs (Table two).

PCR products were obtained in a GeneAmp PCR Organization 2700 Thermocycler (Practical Biosystems) using the QIAGEN Multiplex PCR Kit. PCR reactions consisted of ii µl template DNA, 5 µl QIAGEN Multiplex PCR Master Mix, 0.2 µl 10 µM forward and opposite primers, and water up to 10 µl. PCR conditions were equally follows: three min at 95°C, 35 cycles of thirty sec at 94°C, ninety sec at 57°C and 1 min at 72°C, and final elongation for 5 min at sixty°C. PCR products were visualized in 1.8% agarose gels and screened for microsatellite polymorphism using an ABI 3130 AVANT automatic capillary sequencer (Applied Biosystems). Alleles were sized according to a Liz500 (50–500 bp) marking.

Data assay

Inside-sample genetic diversity statistics were assessed by observed (H _o) and expected (H _e) heterozygosities per locus using GENETIX version iv.05 [54] and allelic richness (AR) using FSTAT [55]. Differences in genetic multifariousness among samples were tested past 1-way ANOVA using STATISTICA version half-dozen.0 (StatSoft Inc.). Deviations from Hardy-Weinberg Equilibrium (HWE), linkage disequilibrium and differences in allele and genotype frequencies amid samples were tested using GENEPOP version iii.four [56].

Neutrality of the markers was tested using the software LOSITAN [57], which implements a F _ST outlier detection approach. This method evaluates the relationship betwixt F _ST and expected heterozygosity (H _e), describing the expected distribution of Wright's inbreeding coefficient F _ST vs. H _{due east} under an island model of migration with neutral markers. This distribution is used to identify outlier loci that testify excessive high or low F _ST compared to neutral expectations. Such outlier loci are candidates for being bailiwick to pick. We used the 0.99 criterion in society to minimize imitation positives as suggested by the authors.

Population structure was explored using not-hierarchical and hierarchical F-Statistics [58] calculated using ARLEQUIN [59]. Showtime, overall and pairwise F _ST values were calculated. Genetic differentiation was also partitioned among locations (4 locations: Zadlascica, Lipovscek, Sevnica and Studenc) and amongst samples within locations (pre- and post-inundation samples). Significance tests were assessed with 10,000 permutation tests. In all cases, significance levels were corrected for multiple comparisons using Bonferroni [60]. Pairwise multilocus comparisons betwixt samples were calculated past Cavalli-Sforza and Edwards [61] chord altitude (D_CE) and graphically represented by Multidimensional Scaling (MDS) analysis using STATISTICA version seven.0 (StatSoft). Isolation-past-Distance (IBD) was tested using a Mantel test implemented in GENETIX, past correlating linearized genetic distance (F _ST/(1−F _ST)) vs. geographic altitude (shortest waterway distance measured along the streams between pairs of samples).

A model-based clustering algorithm as implemented in the software Construction [62] was used in lodge to infer the virtually likely number of populations in the data. The software organizes individuals into a predefined number of clusters (Yard) with a given likelihood, which may represent putative groups. The analysis was performed with 1<K<8 to business relationship for population substructuring within species, using the admixture model and without a population prior. The most probable M was determined using the benchmark of Evanno et al. [63] and so used to assign each individual. A burn-in length of x⁵ iterations followed by 10^half-dozen additional Markov Chain Monte Carlo (MCMC) iterations were performed. A minimum of five runs were performed for each G to bank check repeatability of results.

Historical demographic changes were inferred using the Bayesian coalescent-based arroyo implemented in MSVAR [64]. Using a strict stepwise mutation model, the procedure provides distributions of the exponential growth rate r =North ₀/Due north _one (where North ₀ is the present effective population size, N ₁ is the effective population size at the fourth dimension of population expansion or decline), the fourth dimension since the population started to expand or decline t _f =t _a/North ₀ (where t _a is the number of generations since the beginning of the expansion/decline) and the genetic parameter θ = 2N ₀μ. A mutation rate of μ = 10^−iv was used [65], [66]. Rectangular priors were chosen for all parameters, with limits of (−9, +5) for log₁₀(r), log₁₀(t _f) and log₁₀(θ) and starting values of 1 for θ at each locus, r and t _f. The assay was performed for an exponential model of population modify. We used 50,000 thinned updates and a thinning interval of 50,000 steps, with an initial 10% discarded as burn-in. Convergence was assessed using Tracer v1.iv [67].

Finally, we tested for a recent genetic clogging episode with ii different approaches. Beginning, we used the software Bottleneck [68], based on the principle that after a recent reduction of effective population size, number of alleles (chiliad) decreases faster than heterozygosity (H _e) at polymorphic loci. Thus, in a recently bottlenecked population, the observed gene multifariousness is higher than the expected equilibrium cistron diversity (H _eq) which is computed from the observed number of alleles (thou), under the assumption of a abiding-size (equilibrium) population [69]. We used the Multiple-step Stepwise (TPM) model [70], which consists of by and large one-step mutations just a pocket-sized pct of multi-pace changes, and is the recommended model for microsatellite information sets rather than the Infinite Alleles (IAM) or Single-step Stepwise (SMM) models [71]. The proportion of singlestep mutation events was set to ninety% (variance = 12%). Observed and expected heterozygosities were compared using a Wilcoxon sign-rank examination equally suggested by Piry et al. [68]. 2nd, we calculated M, the hateful ratio between number of alleles (grand) and range in allele size (r), bold that during a clogging episode chiliad decreases faster than r (M_P_Val; [28]). Hence, the value of M decreases when a population is reduced in size. Average Grand was calculated beyond loci and compared with the critical value 1000_crit estimated afterward x,000 simulations and assuming the population to be at equilibrium. In all simulations, 3 different values of θ were used (v, x and 20). A range of mutation models were examined and bourgeois values were used for p_south (frequency of ane-stride mutations) and Δ_g (average size of non one-pace mutations), p_s = 0.90 and Δ_g = three.five, respectively.

Supporting Information

Table S1

Allele frequencies at all loci. Samples labelled as in Tabular array 3.

(Medico)

Acknowledgments

Nosotros thank the Tolmin Angling Association (Slovenia) for support in sampling.

Footnotes

Competing Interests: The authors take declared that no competing interests exist.

Funding: This work has been funded by a contract by Fondation Tour du Valat to LZ. The funders had no role in study pattern, data collection and analysis, decision to publish, or grooming of the manuscript.

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