Evidence from recently deglaciated mountain ranges that Baetis alpinus (Ephemeroptera) could lose...

Evidence from recently deglaciated mountain ranges that Baetis alpinus (Ephemeroptera) couldlose significant genetic diversity as alpine glaciers disappearAuthor(s): Debra S. Finn, Carmen Zamora-Muñoz, Cesc Múrria, Marta Sáinz-Bariáin, and JavierAlba-TercedorSource: Freshwater Science, Vol. 33, No. 1 (March 2014), pp. 207-216Published by: The University of Chicago Press on behalf of Society for Freshwater ScienceStable URL: http://www.jstor.org/stable/10.1086/674361 .

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MOLECULAR APPROACHES IN FRESHWATER ECOLOGY

Evidence from recently deglaciated mountain ranges thatBaetis alpinus (Ephemeroptera) could lose significantgenetic diversity as alpine glaciers disappear

Debra S. Finn1,2,6, Carmen Zamora-Muñoz3,7, Cesc Múrria4,5,8, Marta Sáinz-Bariáin3,9,and Javier Alba-Tercedor3,10

1Department of Zoology, Oregon State University, Corvallis, Oregon 97331 USA2School of Geography, Earth, and Environmental Sciences, University of Birmingham, Edgbaston B15 2TT, UK3Department of Zoology, Faculty of Sciences, University of Granada, 18071 Granada, Spain4Grup de Recerca Freshwater Ecology and Management (FEM), Departament d’Ecologia, Facultat de Biologia, Universitat de

Barcelona, 08028 Barcelona, Catalonia, Spain5Department of Entomology, Natural History Museum, London SW7 5BD, UK

Abstract: Climate change will cause relict alpine glaciers to disappear within decades. Associated high-altitudestreams will face significant hydrological changes that might affect population genetic diversity of lotic species. Ina recent study of glacier-fed streams in the Pyrenees, Finn et al. (2013) predicted that a large proportion ofregional genetic diversity of the mayfly Baetis alpinus would be lost as glacial meltwater sources disappear. Weexpanded the analysis of Finn et al. to include genetic data (mitochondrial barcoding region) collected fromB. alpinus occupying recently deglaciated locations including multiple basins in 2 mountain ranges (Sierra Nevadaand Picos de Europa) on the Iberian Peninsula and 1 additional, deglaciated Pyrenean basin. We hypothesizedthat regional genetic diversity at scales of entire mountain ranges (γ diversity) and population structure withinranges (β diversity) would be lower in recently deglaciated mountain ranges than in the still-glaciated Pyrenees.For 4 cryptic lineages of the B. alpinus species complex in 3 mountain ranges, we found significantly lowergenetic diversity in recently deglaciated than glaciated regions. β and γ genetic diversity were correlated, suggestingthat population structure (β) strongly influences total regional diversity. Results support the hypothesis of Finnet al. (2013) that disappearance of alpine glaciers will result in substantial loss of genetic diversity. The distinctivehydrological environment created by glacial meltwater might drive an interaction between reproductive barriers(between highly and minimally glacier-influenced reaches within basins) and physical barriers (isolating highlyglacier-influenced reaches among basins) that amplifies regional genetic diversity in mountain ranges still con-taining alpine glaciers.Key words: Baetis alpinus, population genetics, genetic diversity, climate change, alpine glaciers, cryptic species,Europe

Climate change is expected to take a particularly heavy tollon freshwater biodiversity, in part, because many freshwa-ter species occupy isolated aquatic habitat embedded in aterrestrial landscape matrix (Olden et al. 2010, Strayer andDudgeon 2010, Isaak and Rieman 2012). Isolation of onefreshwater habitat from the next could render dispersal inresponse to climate-induced local environmental change dif-ficult or impossible, although lengthy north–south-flowingriver systems or high-gradient mountain streams couldprovide exceptions if hydrologic connectivity is main-

tained along dynamic environmental gradients (Poff et al.2012). High-gradient mountain streams are useful settingsfor evaluating biodiversity distribution along steep envi-ronmental gradients (e.g., Allan 1975, Ward 1986, Finnand Poff 2005, Wang et al. 2010) and, more recently, up-stream shifts of species distributions as environmentalconditions change, particularly as they warm (Finn et al.2010, Sheldon 2012). Connectivity along gradients proba-bly buffers to some extent against species extinction, butthe buffering capacity ends at the uppermost headwaters

E-mail addresses: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]

DOI: 10.1086/674361. Received 30 March 2013; Accepted 06 August 2013; Published online 31 October 2013.Freshwater Science. 2014. 33(1):207–216. © 2014 by The Society for Freshwater Science. 207



of stream networks, where hydrologic connectivity comesto an abrupt halt. Evidence is accumulating that speciesoccupying these ‘summit traps’ at the upper extremes ofstream gradients are either at risk of extinction (e.g., Finnand Adler 2006, Muhlfeld et al. 2011) or already are locallyor regionally extinct (e.g., Durance and Ormerod 2010,Bogan and Lytle 2011).

Effects of climate change on intraspecific genetic di-versity in mountain-stream organisms have been discussedminimally within this framework, but effects at this level oforganization also could present a significant threat to fresh-water biodiversity (Bálint et al. 2011, Pauls et al. 2013).Species with distributions that extend into mountain head-waters typically show significant population genetic struc-ture (β diversity), which can contribute substantially toregional-scale genetic diversity (γ diversity = total geneticdiversity of a species across multiple sites in a region; Finnet al. 2011). Common species that are distributed alonglengthy stream gradients (including headwaters) probablydo not face imminent climate-related extinction at the spe-cies level, but their unique intraspecific genetic diversityharbored in headwater populations could be at risk. Thisrisk is conceptually the same as that described in the previ-ous paragraph, but instead of loss of species from the upperextremes of dynamic environmental gradients to extinc-tion, unique alleles or haplotypes face this outcome.

A recent population genetic study of a cold-tolerant may-fly (Baetis alpinus Pictet) in the Pyrenees mountain rangeshowed that a substantial proportion of its genetic γ di-versity (according to mitochondrial sequence data) existsamong highest-altitude reaches, which are strongly influ-enced by the runoff of relict alpine glaciers (Finn et al.2013). Glacial meltwater hydrology creates a unique aquaticenvironment that might be particularly vulnerable to lossof biodiversity (Brown et al. 2007, Füreder 2012, Jacobsenet al. 2012) because many small (<1 km2) alpine glaciersare expected to disappear within this century (e.g., Grune-wald and Scheithauer 2010). All remaining glaciers inthe Pyrenees (one of the southernmost glaciated moun-tain ranges in Europe) are significantly <1 km2 in size butstill exert a strong influence on local environmental condi-tions in streams within 1 to 2 km downstream of the source(Brown et al. 2007, Brown and Hannah 2008). Finn et al.(2013) applied a space-for-time design along a longitudinal/hydrological gradient (highly–minimally glacially influencedreaches) across 4 glaciated basins in the Pyrenees to inferpotential future effects of glacier disappearance on re-gional genetic diversity of B. alpinus. The bulk of β andγ diversity occurred across populations occupying highlyglacially influenced (‘high-glaciality’) reaches, whereas min-imally glacially influenced reaches were dominated by asingle, common haplotype. The conclusion reached by Finnet al. (2013) was that continued climate change leading toglacier disappearance would lead to a severe reduction ofthe associated genetic diversity in Pyrenean B. alpinus.

In this paper, we expand the space-for-time conceptto a broader spatiotemporal scale to evaluate genetic di-versity patterns in B. alpinus populations occupying basinsand mountain ranges that have been deglaciated within thepast 50 to 200 y. We sampled multiple basins in 2 moun-tain ranges on the Iberian Peninsula to the south of thePyrenees that have lost glaciers since the Little Ice Age(LIA), and we added samples from 1 recently deglaciatedbasin in the Pyrenees to the data of Finn et al. (2013). Wehypothesized that both β and γ levels of population gen-etic diversity would be significantly lower in regions thathave experienced a complete loss of glacial meltwater hy-drology since the peak of the LIA (∼250 ybp) than in thePyrenean headwaters where small glaciers remain and ge-netic diversity is substantial.

METHODSStudy taxon

Baetis alpinus is a common mayfly found in Euro-pean mountain streams and other cold streams generallynot >20°C (Sartori and Landolt 1999), although Alba-Tercedor (1981, 1984) noted 2 populations in the SierraNevada of southern Spain in streams reaching temper-atures of 21.5°C. Its life cycle is remarkably plastic, par-ticularly with regard to emergence timing and voltinism(multi-, uni-, or semivoltine, depending on temperature/altitude or other environmental drivers) (Lavandier 1988,Kukula 1997, Knispel et al. 2006, López-Rodríguez et al.2008). Adult flight dispersal is minimal across high moun-tain drainage divides (e.g., Finn et al. 2013), and when flightdispersal does occur, it tends to be focused along streamchannels (Lavandier 1982) and can be interrupted by lakes(Monaghan et al. 2001).

The genus Baetis is gaining international notorietyfor harboring cryptic diversity (presumably at the spe-cies level), i.e., morphologically indistinguishable speci-mens recognized as evolutionarily distinct entities basedon genetics. Cryptic diversity has now been discoveredin the important indicator species B. bicaudatus in theUSA (Peckarsky et al. 2005), B. rhodani in Europe (Wil-liams et al. 2006, Gattolliat and Sartori 2008, Lucentiniet al. 2011), and B. harrisoni in Africa (Pereira-da-Conceicoaet al. 2012), and evidence from ongoing barcoding worksuggests the presence of multiple cryptic lineages ofB. alpinus as well, both across Europe (CM, unpublisheddata) and within mountain ranges (Alps and Pyrenees,M. T. Monaghan [Leibniz-Institute for Freshwater Ecol-ogy and Inland Fisheries, Berlin] and DSF, respectively,unpublished data). We anticipated cryptic diversity be-cause the spatial extent of our study spans B. alpinuspopulations occupying 3 isolated mountain ranges, andwe included separate population genetic analyses foreach cryptic lineage found in each mountain range (seeIdentifying cryptic diversity below).

208 | Does glacier loss equal genetic diversity loss? D. S. Finn et al.



Study sites and data collectionWe collected B. alpinus from multiple drainage basins

in each of 3 Iberian mountain ranges: the Pyrenees (1 basinin addition to 4 previously reported by Finn et al. 2013),Picos de Europa (3 basins), and Sierra Nevada (5 basins)(Fig. 1A–C). Other high-altitude regions of the Iberian Pen-insula were glaciated during the Pleistocene, but these3 ranges harbored the only LIA glaciers in Iberia (GonzálezTrueba et al. 2008). Of the 3, the Pyrenees contain the onlycontemporary glacial activity, and these glaciers are small(maximum size = 46 ha in 2009; Association Pyrénéennede Glaciologie 2009) and are expected to disappear withindecades (Grunewald and Scheithauer 2010). Nearly all head-water basins of the High Pyrenees (central massif, includ-

ing all of Fig. 1A) also contained LIA glaciers, several ofwhich have disappeared in the past 50 to 200 y. We sam-pled the headwaters of 1 such basin (Cirque de Troumouse[CT]; Fig. 1A). We sampled all basins lacking contempo-rary glaciation (henceforth termed nonglacial), includingCT and each of the basins in the Picos de Europa andSierra Nevada, at single representative reaches (15–50 mstream length). For regional-scale analysis of nonglacialstreams in the Pyrenees, we also incorporated data col-lected by Finn et al. (2013) from ‘low-glaciality’ reachesin basins with glaciated headwaters. These reaches were2.5 to 5 km downstream of contemporary glaciers (sitesNS, VG, OS, TL; Fig. 1A) with a negligible hydrologicalsignal of glacial meltwater. We included data that Finn

Figure 1. Iberian Peninsula showing locations of Pleistocene glaciation including the Pyrenees (A), Picos de Europa (B), and SierraNevada (C). In all panels, heavy blacks lines show highest ridgelines (drainage divides; in A the arrowheads indicate E–W continuationof the ridgeline) and white stars mark sampling basins. In A, all of the high cirques had Little Ice Age (LIA) glaciers. White circlesindicate locations of some contemporary glaciers. Each of the 4 glaciated basins marked in A included 2 sampling reaches in our study:one nonglacial (downstream of glacial hydrologic influence) and one with high glacial influence (closer to the glacier snout; Finn et al.2013) for comparison (Table 2; Fig. 2). In B and C, gray circles show locations of glaciers in the LIA. See Table 1 for site codes.

Volume 33 March 2014 | 209



et al. (2013) measured in ‘high-glaciality’ reaches (<1500 mdownstream of glacier snouts) in these same 4 basins forcomparative purposes.

During field seasons from 2008 to 2012, we collectedB. alpinus specimens from each of the basins marked inFig. 1A–C. We preserved specimens in 80 to 100% etha-nol and stored them in the laboratory between –20 and20°C. We amplified and sequenced the standard mito-chondrial barcoding region for insects, which consists ofa 658-bp section of the cytochrome oxidase I (COI) gene,following standard methods (Wishart and Hughes 2003,Finn et al. 2013).

Identifying cryptic diversityTo identify genetic clusters representing unique evo-

lutionary entities of morphological B. alpinus, we appliedthe Generalized Mixed Yule-Coalescent (GMYC) model(Pons et al. 2006). This model tests for changes in branch-ing rates at the species/population boundary and classifiesbranches as either interspecific (diversification) or intra-specific (coalescent). The GMYC model considers eachdelimited diversification branch to be an independentlyevolving mitochondrial deoxyribonucleic acid (mtDNA)cluster (typically interpreted as a species-level entity). Toimprove the accuracy of the GMYC model, we collatedall COI haplotypes obtained in our study, all haplotypesfrom Finn et al. (2013), and several unpublished haplo-types from across Europe (provided by CM and M. T.Monaghan). All haplotypes were used to generate a max-imum likelihood tree with RAxML (version 7.0.4; Sta-matakis 2006) under a general time reversible + gamma(GTR+Γ) substitution model. The resulting topology wasmade ultrametric by using penalized likelihood as im-plemented in r8s (version 1.7; Sanderson 2003). We con-ducted the GMYC analysis in the R package Splits(http://r-forge.r-project.org/projects/splits//; R Project forStatistical Computing, Vienna, Austria) with the single-threshold option, which consistently outperforms themultiple-threshold option in delineating taxonomic spe-cies (Fujisawa and Barraclough 2013). Results showed4 clearly delineated B. alpinus GMYC entities across thesampled basins in our study: 2 (SN_Pyr and Pyr_B) inthe Pyrenees, 2 (SN_Pyr and SN_B) in the Sierra Nevada,and 1 (Picos_A) in the Picos de Europa. These GMYC en-tities were separated by up to 17.1% mean sequence di-vergence (Table S1). A rule-of-thumb criterion forspecies delimitation with COI data is often just 2 to 4% se-quence divergence (Sweeney et al. 2011). Therefore, weconsidered each of the 4 B. alpinus GMYC entities sep-arately for analyses of population genetic diversity.

Population genetic analysisTo meet our objective of comparing intraspecific ge-

netic diversity among mountain ranges and between high-glaciality and nonglacial reaches in the Pyrenees, we ap-

proximated measures of regional (region = mountainrange) diversity at the β level (population structure, or di-versity among basins within mountain ranges) and the γlevel (total diversity within mountain ranges regardless ofpopulation structure). For the β level, we calculated ΦST

with pairwise differences in Arlequin (version 3.5; Excof-fier and Lischer 2010). ΦST is a traditional measure of pop-ulation genetic structure that essentially reports structureas a measure of among-population differentiation weightedby the degree of within-population differentiation (Finnet al. 2011). We also calculated Jost D as a measure ofβ diversity in the software SPADE (February 2009 update;Chao and Shen 2010). Jost D measures differentiationamong populations without regard for within-populationdifferentiation (Jost 2008). Input data for Jost D calcula-tions were mitochondrial haplotype identities (includingabundance) found in each population and did not includeinformation about evolutionary distance (nucleotide diver-gence) among haplotypes. For calculations of both ΦST andJost D for each mountain range/GMYC entity, we removedany populations that were represented by single individ-uals. Small sample sizes (N ) at the scale of local popula-tions can lead to overestimation of genetic differentiation(e.g., Holsinger and Weir 2009), primarily because of in-creased probability of perceived local-scale haplotype fix-ation with decreased N. Many basins in the recently de-glaciated mountain ranges had small sample sizes evenfollowing removal of those with N = 1 (Table 1), so thesemeasures are a conservative approach to testing the hy-pothesis that β diversity is lower in deglaciated mountainranges than in the Pyrenees, where mean per-site N wasgreater (Finn et al. 2013).

To compare γ diversity among the 3 mountain rangesand between high-glaciality and nonglacial sets of reachesin the Pyrenees, we estimated total haplotype richness(number of unique haplotypes present) and calculated theShannon–Wiener diversity index (H ) for each mountainrange/GMYC entity. Mountain ranges had unequal sam-ples sizes, so we estimated regional haplotype richness viararefaction to the sample size of the mountain range/GMYC entity with the lowest sample size (N = 15 for Si-erra Nevada entity SN_B) by applying the rarefaction func-tion in the vegan package for R (version 2.0-6; Oksanenet al. 2013). We calculated H for each mountain range/GMYC entity with the software SPADE.

RESULTSAcross the 3 Iberian mountain ranges and 4 GMYC

entities, only 1 GMYC entity (SN_Pyr) was present on >1mountain range (Pyrenees and Sierra Nevada; Table 1).No haplotypes of SN_Pyr were shared between these 2mountain ranges, and mean sequence divergence betweenranges was 1.8%, suggesting lengthy isolation. Total num-ber of haplotypes/GMYC entity ranged from 1 in Picos_A(across 18 individuals) to 25 in SN_Pyr. Twenty-three of




the 25 SN_Pyr haplotypes were found in the Pyrenees (across188 individuals, most of these sampled by Finn et al.2013), and only 2 in the Sierra Nevada (across 17 individu-als). GMYC entity SN_B had 5 haplotypes (across 15 indi-viduals), and Pyr_B had 4 (across 18 individuals). Table S2includes detailed information on the spatial distributionand GenBank accession numbers of individual haplotypes.

All measures of β and γ diversity followed similartrends across mountain range/GMYC entity combinations

(Table 2, Fig. 2A, B). All diversity measures were 0 in thePicos de Europa, where the single GMYC entity found wasrepresented by a single haplotype (richness = 1). GMYCentities SN_Pyr (in nonglacial reaches in the Pyrenees andSierra Nevada) and Pyr_B in nonglacial reaches of thePyrenees each had low and nonsignificant estimates of βdiversity (Table 2, Fig. 2A) and correspondingly relativelylow values of γ diversity at the mountain-range scale (Ta-ble 2, Fig. 2B). The greatest values of β (including a signifi-cant ΦST; Fig. 2A) and γ diversity for any nonglacial regionwere for GMYC entity SN_B in the Sierra Nevada. None-theless, when B. alpinus individuals from high-glacialityreaches in the Pyrenees from the Finn et al. (2013) studywere included for comparison, β and γ diversity valuesfrom this group (SN_Pyr glacial in Fig. 2A, B, Table 2)were consistently greater than any of the nonglacial GMYCentities or mountain ranges.

Correlations between diversity estimates were strongacross the 6 mountain range/GMYC entity combinations(including 3 GMYC entities unique to single mountainranges and GMYC entity SN_Pyr in the Sierra Nevada andin nonglacial and high-glaciality Pyrenees) (β diversity es-timates ΦST and Jost D, r = 0.93, p = 0.004; γ diversityestimates of total haplotype richness and Shannon–Wienerdiversity, r = 0.99, p < 0.0001). Furthermore, β diversity wasa strong predictor of γ diversity (e.g., r = 0.89, p = 0.009between Fig. 2A and Fig. 2B; r = 0.92, p = 0.005 betweenJost D and Shannon–Wiener diversity).

DISCUSSIONOverall, B. alpinus occupying recently deglaciated

mountain ranges on the Iberian Peninsula and nonglacialreaches in the Pyrenees showed significantly lower re-

Table 1. Summary information for sampled nonglacial drainage basins and Generalized Mixed Yule-Coalescent (GMYC) entitiesacross 3 Iberian mountain ranges. Altitude is the altitude of the collection site (reach) within basins. * indicates information for reachesoccupying currently glaciated basins, at downstream, hydrologically nonglacial stream reaches (‘low-glaciality’ in Finn et al. 2013).

Sample size for each GMYC group:

Mountain range Sample basin Altitude (m) Code SN_Pyr SN_B Pyr_B Picos_A

Sierra Nevada Mulhacén (Refugio Poqueira) 2800 ML 9 1

Corral del Veleta 3127 CV 7

Barranco del San Juan 2421 SJ 3 1

Borreguiles del Monachil 2679 MN 3 2

Borreguiles del Dílar 2855 DL 2 4

Picos de Europa Peguera 617 PG 2

Duje 855 DJ 10

Bejes 550 BJ 6

Pyrenees *Néous 1740 NS 13

*Vignemale 1820 VG 13

*Ossoue 1830 OS 11

*Taillon 1650 TL 13

Cirque de Troumouse 2100 CT 4 7

Table 2. Results at β and γ diversity levels for each GeneralizedMixed Yule-Coalescent (GMYC) entity in each Iberian mountainrange. SN_Pyr_glacial represents 4 reaches with high glacialinfluence in the Pyrenees (‘high glaciality’ in Finn et al. 2013).Richness is haplotype richness (SE) rarefied to smallest regionalsample size (N = 15 for SN_B). H is the Shannon–Wienerdiversity index.

β diversity(populationstructure)

γ(regional)diversity

Mountainrange

GMYCentity

ΦST

(p-value)JostD

Richness(SE) H

SierraNevada SN_Pyr 0.18 (0.48) 0 1.88 (0.32) 0.22

SN_B 0.35 (0.04) 0.64 5 (0) 1.23

Picosde Europa Picos_A 0 (1) 0 1 (0) 0

Pyrenees SN_Pyr 0.03 (0.41) 0.03 2.32 (0.65) 0.44

Pyr_B 0.03 (0.38) 0 3.65 (0.52) 0.76

SN_Pyr_glacial 0.68 (0) 0.81 7.25 (1.17) 2.1




gional genetic diversity (γ) and population structure (β)than the set of Pyrenean stream reaches classified as hav-ing a high-glaciality hydrologic signature in the study byFinn et al. (2013). The high-glaciality reaches were popu-lated predominantly by GMYC entity SN_Pyr, which alsowas present in the Sierra Nevada and the Pyrenean non-glacial reaches but showed negligible population struc-ture and regional diversity in these locations. These pat-terns provide additional evidence (to Finn et al. 2013) thatB. alpinus populations associated with high-glaciality streamreaches account for a strongly disproportionate amountof total, intraspecific genetic diversity at the mountain-rangescale.

Not surprisingly, our GMYC analysis revealed crypticdiversity (4 GMYC entities) within morphological B. alpi-nus across the 3 focal mountain ranges. Cryptic diversityhas become a common discovery in Baetis species fromaround the globe (e.g., Peckarsky et al. 2005, Williams et al.2006, Pereira-da-Conceicoa et al. 2012) and often explainswhat were previously thought to be different generations ofthe same species living in sympatry (e.g., Peckarsky et al.2001, 2005). Multiple generations of B. alpinus have beenreported in the Sierra Nevada following observations ofdistinct temporal size and emergence cohorts in the Mul-hacén basin (Alba-Tercedor 1984, López-Rodríguez et al.

2008), a basin in which we observed both Sierra NevadaGMYC entities (Table 1), and further evaluation will berequired to determine whether these GMYC entities canexplain the reports of multiple generations.

We ran individual population genetic analyses on eachGMYC entity in each mountain range, and our general ob-servation was that recently deglaciated mountain rangesharbored significantly less total genetic diversity (γ diver-sity) than the set of high-glaciality Pyrenean reaches stud-ied by Finn et al. (2013) and that these differences areinfluenced primarily by decreased population structure (β di-versity) within nonglacial regions. However, the story is notthis simple. The GMYC entity found only in the SierraNevada (SN_B) had the only significant ΦST among thenonglacial GMYC entities, relatively high Jost D, and in-termediate values of γ diversity (Table 2, Fig. 2A, B). SN_Balso was the only GMYC entity found in the Corral delVeleta (Table 1), which was the only Sierra Nevada basinthat contained a LIA glacier (CV; Fig. 1C). It is reasonableto hypothesize that SN_B in the Sierra Nevada was thelineagemost closely associated with glacial hydrology (analo-gous to SN_Pyr in the Pyrenees). The glacier that occupiedthe Corral del Veleta until ∼100 ybp was large and dy-namic (at LIA maximum), and contemporary evidence ofit remains in the form of a rock glacier that is nonmovingbut thought to be 10 to 20 m thick (Gómez Ortiz et al.2008, González Trueba et al. 2008). Hydrology of surfacewaters in the Corral del Veleta basin might continue tobe influenced by melt patterns of the rock glacier, which,along with its associated permafrost, is expected to disap-pear completely within the next 2 decades (Gómez Ortizet al. 2008, 2012). This situation presents a timely opportunity to monitor SN_B population genetics as the rock gla-cier shrinks and disappears to test a hypothesis of ongoinggenetic diversity loss in tandem with complete glacier loss.

In contrast to the relatively diverse population geneticpatterns for SN_B in the Sierra Nevada, the singleGMYC entity found in the Picos de Europa had 0 diver-sity. In a sample of N = 18 individuals sequenced, all hadthe same haplotype. We sampled from 3 relatively low-altitude (for B. alpinus) stream reaches in this mountainrange, and none of the reaches were in basins that wereglaciated during the LIA. Furthermore, the LIA glacia-tion in the Picos de Europa was of short duration, andthe glaciers did not attain exceptional mass (GonzálezTrueba et al. 2008). This combination of circumstancesprobably contributed to the lack of genetic diversity weobserved in our samples from this mountain range, al-though it is a striking pattern for an aquatic insect at theCOI marker, which typically is useful (polymorphic) forboth population genetic analysis and barcoding (see Finnet al. 2011).

What is a probable mechanism for highly glacially in-fluenced stream reaches to contribute disproportionately

Figure 2. ΦST (A) and regional haplotype richness (B) foreach Generalized Mixed Yule-Coalescent (GMYC) entity/mountain range across 3 Iberian mountain ranges. The finalentity SN_Pyr_glacial represents data from Finn et al. (2013)and is provided for comparison. In A, asterisks indicate asignificant (p < 0.05) ΦST. Values in B are rarefied richness(±2 SE) adjusted to the GMYC entity with smallest sample size(SN_B).




to regional genetic diversity in B. alpinus GMYC entities?We propose that the mechanism might be an interactionbetween reproductive isolation between highly and mini-mally glacially influenced reaches within the same basinand physical isolation among populations occupying theupper tips of mountain headwater streams (Fig. 3A, B).

Mountain streams have steep environmental gradients(e.g., temperature, discharge) that typically translate tosteep biotic gradients (e.g., Ward 1986, Wang et al. 2010),but the findings of Finn et al. (2013) suggest that conditionsdo not change at a constant rate along Pyrenean glacier-fed streams. The differences between high-glaciality reachesand those just downstream with attenuated glaciality ap-pear to represent such a drastic change in environmentthat the biotic response might be more zonal than gradient-like, including strong B. alpinus population genetic dif-ferences (β diversity) between zones of high and atten-uated glaciality, even within the same stream. These strongand consistent within-basin patterns could result from re-

productive isolation driven by significant differences intiming of emergence or other key life-history events (Finnet al. 2013). Harper and Peckarsky (2006) experimentallydemonstrated that emergence timing of congener B. bicau-datus is influenced directly by water temperature (highertemperature = earlier emergence), and similar argumentshave been made for other aquatic insects in mountains(West and Black 1998, Shama and Robinson 2009). Majorlife-history differences driven by steep environmental gra-dients could translate to minimal interbreeding betweenpopulations and the development over generations of strongpopulation genetic structure within the same species (orGMYC entity), even between hydrologically connected pop-ulations.

Strong population genetic structure also occurs fromone basin to the next in Pyrenean headwaters with highlyglacier-influenced hydrology. This pattern was not unex-pected because physical isolation of high-altitude head-waters typically increases population genetic structure

Figure 3. Conceptual diagram of the proposed interaction of physical isolation among and reproductive isolation within alpineglacier-fed streams. White circles in panel A represent populations of the same species occupying high-glaciality reaches. In bothpanels, black circles represent populations in nonglacial or minimally glacier-influenced stream reaches. A.—Reproductive isolationminimizes gene flow between high-glaciality and downstream nonglacial populations. Reproductive isolation could be caused bystrong temporal differences in life-history events, driven by the extreme environmental differences between high-glaciality andnonglacial stream reaches (see text). Populations occupying high-glaciality reaches also are physically isolated from one another bysteep, harsh drainage divides. Gene flow among basins can occur among populations occupying the nonglacial reaches at loweraltitudes, but the high-glaciality populations are completely isolated. B.—No glaciers occur. An upstream–downstream environmentalgradient is expected, but the gradient is not extreme enough to cause strong upstream–downstream reproductive isolation (geneflow occurs along the stream gradient). The highest-altitude headwater populations are physically isolated from one another, butupstream–downstream gene flow can link headwaters to lower-altitude among-basin gene flow, such that highest-altitude populationsare not completely isolated. With climate change and mass loss of alpine glaciers, many glaciated alpine streams might follow atemporal trajectory from panel A to panel B, with decreased reproductive isolation driving decreased regional genetic diversity.




among basins, especially in populations confined to smallheadwaters (e.g., Finn et al. 2006, 2007, 2011). Moreover,extreme events (e.g., floods, droughts) in these isolatedhabitats can further increase population genetic structureif they cause periodic local population bottlenecks (whichoften increase ΦST; e.g., Shama et al. 2011). We proposethat the reproductive isolation that might occur withinglaciated basins along exceptionally steep environmentalgradients created by upstream glacial hydrology couldamplify the effects of physical isolation from one high-altitude headwater to the next (Fig. 3A). Conversely, inthe absence of strong upstream–downstream reproduc-tive isolation (as expected in nonglaciated basins with lessextreme environmental gradients; Fig. 3B), populationsare more likely to be connected by gene flow with an asso-ciated decrease in β diversity within and among basins.This hypothesis hinges on strong reproductive barriersisolating upstream and downstream populations withinglaciated basins, and more research is needed to evaluatethe importance of reproductive barriers along these steepenvironmental gradients.

In conclusion, our broadening of the space-for-timeapproach used by Finn et al. (2013) for multiple basinswithin 1 mountain range (Pyrenees) to multiple recentlydeglaciated mountain ranges provides further evidence(across more extensive spatial/temporal scales) that ge-netic diversity in B. alpinus can be expected to suffer sig-nificant losses as glacial hydrological influence disappears.An interaction between within-basin reproductive barriersthat minimizes gene flow between highly and minimallyglacier-influenced reaches and among-basin physical bar-riers in complex topographic settings could be driving thesignificant contribution to regional genetic diversity bypopulations in high-glaciality streams. These geneticallydiverse sets of populations occupy the uppermost tips ofstream networks and are essentially “falling off” these tipsat the end of steep environmental gradients (e.g., Poff et al.2012). Concurrently, entire species are likely to be lostfrom these uppermost tips of stream networks as shrink-ing glaciers decrease their influence on stream hydrology(Snook and Milner 2001, Ilg and Castella 2006, Brownet al. 2007, Finn et al. 2010). Our work illustrates thatspace-for-time observational approaches applied at multi-ple scales can be useful for predictive inference. In futurework, a combination of space-for-time evaluations andmodeling approaches (e.g., Bálint et al. 2011, Pfenningeret al. 2012) should provide powerful complementary infor-mation for predicting effects of climate change on distri-butions of genetic diversity in freshwater species.

ACKNOWLEDGEMENTSThis work was supported in part by a Marie Curie Inter-

national Incoming Fellowship (PIIF-GA-2009-253801) to DSF;a funded project (reference 039/2007) from the OrganismoAutónomo de Parques Nacionales (O.A.P.N.) of the Spanish

Ministerio de Agricultura, Alimentación y Medio Ambiente;project CGL2007-60163/BOS (‘RICHABUN’) funded by theSpanish Ministry of Education and Science; a Beatriu de Pinóspostdoctoral fellowship (BP-DGR-2011) to CM by the Agènciade Gestió d’Ajuts Universitaris i de Recerca, Generalitat deCatalunya; and a pre-doctoral grant to MSB by the Gobierno deNavarra and the Junta de Andalucía (RNM-02654) and FondoEuropeo de Desarrollo Regional (FEDER, RNM-102) investiga-tion groups. We thank Sierra Nevada National Park for logistichelp and sampling permits and the following people for theircontributions to field collections, laboratory work, and othersupport: Kieran Khamis, Núria Bonada, Laine Wallace, MelanieMarine, Dave Lytle, Mike Blouin, Sandy Milner, Alfried Vogler,and all members and collaborators on the RICHABUN project.

LITERATURE CITEDAlba-Tercedor, J. 1981. Efemerópteros de Sierra Nevada: ciclos

de desarrollo, taxonomía, y ecología de las ninfas. DoctoralThesis, University of Granada, Granada, Spain.

Alba-Tercedor, J. 1984. Ecología, distribución y ciclos de desar-rollo de efemerópteros de Sierra Nevada (Granada, España).II: Baetidae (Insecta, Ephemeroptera). Limnetica 1:234–246.

Allan, J. D. 1975. The distributional ecology and diversity ofbenthic insects in Cement Creek, Colorado. Ecology 56:1040–1053.

Association Pyrénéenne de Glaciologie. 2009. Les glaciers desPyrénées françaises. Rapport d’étude 2008-09. AssociationMoraine, Poubeau, France.

Bálint, M., S. Domisch, C. H. M. Engelhardt, P. Haase, S.Lehrian, J. Sauer, K. Theissinger, S. U. Pauls, and C. Nowak.2011. Cryptic biodiversity loss linked to global climate change.Nature Climate Change 1:313–318.

Bogan, M. T., and D. A. Lytle. 2011. Severe drought drivesnovel community trajectories in desert stream pools. Fresh-water Biology 56:2070–2081.

Brown, L. E., and D. M. Hannah. 2008. Spatial heterogeneity ofwater temperature across an alpine river basin. HydrologicalProcesses 22:954–967.

Brown, L. E., D. M. Hannah, and A. M. Milner. 2007. Vulnera-bility of alpine stream biodiversity to shrinking glaciers andsnowpacks. Global Change Biology 13:958–966.

Chao, A., and T.-J. Shen. 2010. Program SPADE (Species Pre-diction and Diversity Estimation). Program and user’s guide.National Tsing Hua University, Taiwan. (Available at: http://chao.stat.nthu.edu.tw/blog/)

Durance, I., and S. J. Ormerod. 2010. Evidence for the role ofclimate in the local extinction of a cool-water triclad. Journalof the North American Benthological Society 29:1367–1378.

Excoffier, L., and H. Lischer. 2010. Arlequin suite ver 3.5: a newseries of programs to perform population genetics analysesunder Linux and Windows. Molecular Ecology Resources10:564–567.

Finn, D. S., and P. H. Adler. 2006. Population genetic structureof a rare high-elevation black fly, Metacnephia coloradensis,occupying Colorado lake outlet streams. Freshwater Biology51:2240–2251.

Finn, D. S., M. S. Blouin, and D. A. Lytle. 2007. Populationgenetic structure reveals terrestrial affinities for a headwaterstream insect. Freshwater Biology 52:1881–1897.




Finn, D. S., N. Bonada, C. Múrria, and J. M. Hughes. 2011.Small but mighty: headwaters are vital to stream networkbiodiversity at two levels of organization. Journal of the NorthAmerican Benthological Society 30:963–980.

Finn, D. S., K. Khamis, and A. M. Milner. 2013. Loss of smallglaciers will diminish beta diversity in Pyrenean streams attwo levels of biological organization. Global Ecology andBiogeography 22:40–51.

Finn, D. S., and N. L. Poff. 2005. Variability and convergencein benthic communities along the longitudinal gradients offour physically similar Rocky Mountain streams. FreshwaterBiology 50:243–261.

Finn, D. S., K. Räsänen, and C. T. Robinson. 2010. Physical andbiological changes to a lengthening stream gradient follow-ing a decade of rapid glacial recession. Global Change Biol-ogy 16:3314–3326.

Finn, D. S., D. M. Theobald, W. C. Black, and N. L. Poff. 2006.Spatial population genetic structure and limited dispersal ina Rocky Mountain alpine stream insect. Molecular Ecology15:3553–3566.

Fujisawa, T., and T. G. Barraclough. 2013. Delimiting speciesusing single-locus data and the Generalized Mixed Yule Co-alescent approach: a revised method and evaluation on sim-ulated data sets. Systematic Biology (in press).

Füreder, L. 2012. Freshwater ecology: melting biodiversity. Na-ture Climate Change 2:318–319.

Gattolliat, J. L., and M. Sartori. 2008. What is Baetis rhodani(Pictet, 1843) (Insecta, Ephemeroptera, Baetidae)? Designa-tion of a neotype and redescription of the species from itsoriginal area. Zootaxa 1957:69–80.

Gómez Ortiz, A., F. Salvador Franch, J. J. Sanjosé Blasco, D.Palacios Estremera, M. Oliva Franganillo, M. Salvà Catari-neu, L. M. Tanarro, J. M. Raso Nadal, A. Atkinson Gordo, L.Schulte, J. M. Plana Castellvi, B. Milheiro Santos, and D. Ser-rano Giné. 2012. Degradación de hielo fósil y permafrost ycambio climático en Sierra Nevada. Pages 25–43 in L. Ra-mírez and B. Asensio (editors). Proyectos de investigación enparques nacionales: 2008-2011. Naturaleza y parques naciona-les. Serie investigación en la red. Organismo Autónomo de Par-ques Nacionales, Madrid, Spain.

Gómez Ortiz, A., J. J. Sanjosé Blasco, and D. Palacios Estre-mera. 2008. Evolución morfodinámica de un enclave mon-tañoso recién deglaciado: el caso del Corral del Veleta (SierraNevada), ¿Consecuencia del cambio climático? Revista Elec-trónica de Geografía y Ciencias Sociales 12:1–16.

González Trueba, J., R. M. Moreno, E. Martínez de Pisón, andE. Serrano. 2008. “Little Ice Age” glaciation and current gla-ciers in the Iberian Peninsula. Holocene 18:551–568.

Grunewald, K., and J. Scheithauer. 2010. Europe’s southern-most glaciers: response and adaptation to climate change.Journal of Glaciology 56:129–142.

Harper, M. P., and B. L. Peckarsky. 2006. Emergence cues of amayfly in a high-altitude stream ecosystem: potential responseto climate change. Ecological Applications 16:612–621.

Holsinger, K. E., and B. S. Weir. 2009. Genetics in geographi-cally structured populations: defining, estimating and inter-preting FST. Nature Reviews Genetics 10:639–650.

Ilg, C., and E. Castella. 2006. Patterns of macroinvertebrate traitsalong three glacial stream continuums. Freshwater Biology51:840–853.

Isaak, D. J., and B. E. Rieman. 2012. Stream isotherm shifts fromclimate change and implications for distributions of ectother-mic organisms. Global Change Biology 19:742–751.

Jacobsen, D., A. M. Milner, L. E. Brown, and O. Dangles. 2012.Biodiversity under threat in glacier-fed river systems. NatureClimate Change 2:361–364.

Jost, L. 2008. GST and its relatives do not measure differentia-tion. Molecular Ecology 17:4015–4026.

Knispel, S., M. Sartori, and J. E. Brittain. 2006. Egg develop-ment in the mayflies of a Swiss glacial floodplain. Journal ofthe North American Benthological Society 25:430–443.

Kukula, K. 1997. The life cycles of three species of Ephemeropterain two streams in Poland. Hydrobiologia 353:193–198.

Lavandier, P. 1982. Evidence of upstream migration by femaleadults of Baetis alpinus Pictet (Ephemeroptera) at high alti-tude in the Pyrenees. Annales de Limnologie 18:55–59.

Lavandier, P. 1988. Semivoltinisme dans des populations dehaute montagne de Baetis alpinus Pictet (Ephemeroptera).Bulletin de la Société d’Histoire Naturelle de Toulouse 124:61–64.

López-Rodríguez, M. J., J. M. Tierno de Figueroa, and J. Alba-Tercedor. 2008. Life history and larval feeding of some spe-cies of Ephemeroptera and Plecoptera (Insecta) in the SierraNevada (Southern Iberian Peninsula). Hydrobiologia 610:277–295.

Lucentini, L., M. Rebora, M. E. Puletti, L. Gigliarelli, D. Fon-taneto, E. Gaino, and F. Panara. 2011. Geographical and sea-sonal evidence of cryptic diversity in the Baetis rhodani com-plex (Ephemeroptera, Baetidae) revealed by means of DNAtaxonomy. Hydrobiologia 673:215–228.

Monaghan, M. T., P. Spaak, C. T. Robinson, and J. V. Ward. 2001.Genetic differentiation of Baetis alpinus Pictet (Ephemerop-tera: Baetidae) in fragmented alpine streams. Heredity 86:395–403.

Muhlfeld, C. C., J. J. Giersch, F. R. Hauer, G. T. Pederson, G.Luikart, D. P. Peterson, C. C. Downs, and D. B. Fagre. 2011.Climate change links fate of glaciers and an endemic alpineinvertebrate. Climatic Change 106:337–345.

Oksanen, J., F. G. Blanchet, R. Kindt, P. Legendre, P. Minchin,R. B. O’Hara, G. L. Simpson, P. Solymos, M. Henry, H. Stevens,and H. Wagner. 2013. vegan: community ecology package.R package version 2.0-6. (Available from: http://CRAN.R-project.org/package=vegan)

Olden, J. D., M. J. Kennard, F. Leprieur, P. A. Tedesco, K. O.Winemiller, and E. García-Berthou. 2010. Conservation bio-geography of freshwater fishes: recent progress and futurechallenges. Diversity and Distributions 16:496–513.

Pauls, S. U., C. Nowak, M. Bálint, and M. Pfenninger. 2013. Theimpact of global climate change on genetic diversity withinpopulations and species. Molecular Ecology 22:925–946.

Peckarsky, B. L., J. M. Hughes, P. B. Mather, M. Hillyer, andA. C. Encalada. 2005. Are populations of mayflies living in ad-jacent fish and fishless streams genetically differentiated? Fresh-water Biology 50:42–51.

Peckarsky, B. L., B. W. Taylor, A. R. McIntosh, M. A. McPeek,and D. A. Lytle. 2001. Variation in mayfly size at metamor-phosis as a developmental response to risk of predation. Ecol-ogy 82:740–757.

Pereira-da-Conceicoa, L. L., B. W. Price, H. M. Barber-James,N. P. Barker, E. C. de Moor, and M. H. Villet. 2012. Cryptic




variation in an ecological indicator organism: mitochondrialand nuclear DNA sequence data confirm distinct lineages ofBaetis harrisoni Barnard (Ephemeroptera: Baetidae) in south-ern Africa. BMC Evolutionary Biology 12:26.

Pfenninger, M., M. Bálint, and S. U. Pauls. 2012. Methodologi-cal framework for projecting the potential loss of intra-specific genetic diversity due to global climate change. BMCEvolutionary Biology 12:224.

Poff, N. L., J. D. Olden, and D. L. Strayer. 2012. Climate changeand freshwater extinction risk. Pages 309–336 in L. Hannah(editor). Saving a million species: extinction risk from cli-mate change. Island Press, Washington, DC.

Pons, J., T. C. Barraclough, J. Gomez-Zurita, A. Cardoso, D. P.Duran, S. Hazell, S. Kamoun, W. D. Sumlin, and A. P. Vogler.2006. Sequence-based species delimitation for the DNA tax-onomy of undescribed insects. Systematic Biology 55:595–609.

Sanderson, M. J. 2003. r8s: inferring absolute rates of molecularevolution and divergence times in the absence of a molecu-lar clock. Bioinformatics 19:301–302.

Sartori, M., and P. Landolt. 1999. Atlas de distribution des éphém-ères de Suisse (Insecta, Ephemeroptera). Centre Suisse de Car-tographie de la Faune, Neuchâtel, Switzerland.

Shama, L. N. S., K. B. Kubow, J. Jokela, and C. T. Robinson. 2011.Bottlenecks drive temporal and spatial genetic changes in al-pine caddisfly metapopulations. BMC Evolutionary Biology11:278.

Shama, L. N. S., and C. T. Robinson. 2009. Microgeographic lifehistory variation in an alpine caddisfly: plasticity in responseto seasonal time constraints. Freshwater Biology 54:150–164.

Sheldon, A. L. 2012. Possible climate-induced shift of stonefliesin a southern Appalachian catchment. Freshwater Science 31:765–774.

Snook, D. L., and A. M. Milner. 2001. The influence of gla-cial runoff on stream macroinvertebrate communities in theTaillon catchment, French Pyrenees. Freshwater Biology 46:1609–1623.

Stamatakis, A. 2006. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixedmodels. Bioinformatics 22:2688–2690.

Strayer, D. L., and D. Dudgeon. 2010. Freshwater biodiversityconservation: recent progress and future challenges. Journalof the North American Benthological Society 29:344–358.

Sweeney, B. W., J. M. Battle, J. K. Jackson, and T. Dapkey.2011. Can DNA barcodes of stream macroinvertebrates im-prove descriptions of community structure and water qual-ity? Journal of the North American Benthological Society30:195–216.

Wang, J., J. Soininen, Y. Zhang, B. Wang, X. Yang, and J. Shen.2010. Contrasting patterns in elevational diversity betweenmicroorganisms and macroorganisms. Journal of Biogeogra-phy 38:595–603.

Ward, J. V. 1986. Altitudinal zonation in a Rocky Mountainstream. Archiv für Hydrobiologie Supplement 74:133–199.

West, D. F., and W. C. Black. 1998. Breeding structure of threesnow pool Aedes mosquito species in northern Colorado. He-redity 81:371–380.

Williams, H. C., S. J. Ormerod, and M. W. Bruford. 2006. Mo-lecular systematics and phylogeography of the cryptic spe-cies complex Baetis rhodani (Ephemeroptera, Baetidae). Mo-lecular Phylogenetics and Evolution 40:370–382.

Wishart, M. J., and J. M. Hughes. 2003. Genetic populationstructure of the net-winged midge, Elporia barnardi (Dip-tera: Blephariceridae) in streams of the south-western Cape,South Africa: implications for dispersal. Freshwater Biology 48:28–38.




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