Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. West-Roberts Parker Lillian small endemic environments Bornean montane a tropical in heterogeneous across flow gene High ei iegne h vial aargrigti rdcinaecnrdcoy-sm tde aefound have studies some - contradictory ge- are in prediction results Janzen’s this gradients from elevational regarding stemming spanning data prediction available narrower populations the The among documented tested flow groups have have divergence. gene taxonomic studies netic studies diverse restricted Fewer many across that 2006). hypothesis species hypothesis, al., dispersal (1967) temperate et (1967) effective than Ghalambor Janzen’s low species 2009; with montane in (McCain, tropical Consistent 2006; result among Wang, turn & ranges Tewksbury, 2016). elevational environmental in Martin, al., Huey, spatial which (Ghalambor, et with gradients tolerances, paired elevational Gill ex- thermal across stability mountains isolation narrow thermal population tropical al., for temporal and zone, et this select (Polato temperate precipitation, that should stratification the hypothesized elevational temperature, heterogeneity in greater (1967) those generates Janzen (e.g. which to environ- variables variation Relative 2018). of environmental temperature seasonal consequences distances. in less genetic short shifts perience over and rapid evolutionary radiation) the of solar study to and the due to heterogeneity valuable mental highly are ecosystems Montane in connectivity genetic Introduction maintain will treeshrews mountain mountain on change that stronghold. climate conservation predict its result of we important with effects the an CE, future associated be mitigate it 2100 communities instead and making plant for identify may KNP, unique predictions to pattern hypothesis, to Given foundation this KNP. due our a that as MT in to serve on propose treeshrews MT contrary results flow We Our on gene that, elevation. differentiation habitats. upslope implies by montane genetic restricted upper shaped This greater with primarily combined found variation. not (MK) history We environmental is colonization Kinabalu of system peaks. associated this between and Mt. polymorphisms in and elevation and nucleotide structure elevations lower single (MT) genetic across its Tambuyukon 1.9 flow despite of gene Mt. average MK high on an than detected containing elevations We ( elements across treeshrews ultraconserved locus. individuals mountain 4,106 per 83 that and sampled hypothesis mitogenomes We the sequenced and test . to dispersal in approach low (KNP) genomics Park in population tropical in result a heterogeneity use to environmental elevational we montana predicted of Here, consequences is mountains, genetic tropical stability . the In investigated montane to environmental have structure. opportunities studies seasonal genetic Few provide and with elevations. flow ecosystems across combined gene montane on heterogeneity in heterogeneity environmental environmental changes of elevational spatial effects with the regarding associated hypotheses variables test environmental in shifts Rapid Abstract 2020 28, April 3 2 1 Jes´us Maldonado and ereMsnUiest olg fScience of College University Mason George Estaci´on Do˜nana Biol´ogica Institute de Biology Conservation Smithsonian xii iie eeflwars lvtoa rdet n ewe w egbrn ek ihnKnbl National Kinabalu within peaks neighboring two between and gradients elevational across flow gene limited exhibit ) 1 1 am Wilbert Tammy , eis Hawkins Melissa , 1 1 1 a ha Lim Chuan Haw , iulCamacho-Sanchez Miguel , 1 3 ar Rockwood Larry , 2 ihe Campana Michael , 3 enfrLeonard Jennifer , 1 Jacob , 2 , Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. rce niiul o n ot tPrn o pig K(0 al.Emn 20)sget that suggests (2000) Emmons other to masl). who compared (900 (2000), ranges MK Emmons are home by Spring, species small conducted (Camacho- Hot this was zones has Poring of vegetation date evolution treeshrew at three to and month mountain and study behavior, one the summit ecology, ecological for the The comprehensive to individuals most 2016). masl tracked The Phillipps, 900 & lowland known. ca. Phillipps (1992): poorly from 2019; Kitayama spans al., following species et zones range the Sanchez vegetation treeshrew’s MT, four mountain On encompassing the indicating masl, masl). MK, potentially 3200 On forest, to lowland 2000). 900 ( The occupy Stuebing, ca. species & 2019). from related Sheldon, Hawkins, spans closely (Han, 2016; other partitioning ( Phillipps and niche treeshrew and treeshrew elevational ruddy (Payne ruddy the inset) The lineage, 1 sister 2011). (Figure its Sarawak from diverged and species Sabah montane of only regions the (Roberts, montane is lineages center endemic treeshrew a and The mountain is widespread The both Borneo Asia. including 2011). that Southeast species Olson, showed extant and & date 20 South Sargis, to of Lanier, to 9 treeshrews native with of diversity, Scandentia phylogeny treeshrew of order molecular the subordinal in comprehensive most mammals are small-bodied landscape are Treeshrews this in Liew, structure 2019; have genetic studies al., treeshrews population multiple et Mountain on Although Camacho-Sanchez studies 2018). 2009). 2001), al., (e.g. major al., its et Nor, KNP - (Camacho-Sanchez et 2010; in older limited (Hall Lakim, gradients is Range MT elevational bin is Crocker across & 1a). Eighteen It the (Figure Schilthuizen, richness 2009). of masl species region. 2,579 part al. 4,095 on at biogeographical et as stands At focused (Hall Sundaland Mya MT (Mya) the less-studied 7–11 ago 1992). the years occurred in (Kitayama, MK, million uplift mountain of scrub 1 north tallest elevation ca. the the height high to present containkilometers is to its which reached MK forest (MT), having tropical (masl), Tambuyukon young, relatively lowland level Mt. from sea and above habitats (MK) Kinabalu meters of Mt range mountains, wide major a two comprises park The (6 Park cli- National Kinabalu global population of of impacts paucity 2018). Park al. the the al., National and to et et Kinabalu 2015) (Muenchow ecosystems Camacho-Sanchez Svenning, Asia montane & 2018; Southeast Lenoir tropical in 2017; Ray, of Perez, studies environ- & vulnerability & genetic changing Stroud, Frable, the (Feeley, to given (GCC) Epps, change responses critical Vardaro, mate species’ is is Castillo track This treeshrew distinct and 1994; mountain 2018). and predict (Moritz, dynamics the to metapopulation conditions like and identify mental taxa protection to warranting researchers montane enables units tropical it evolutionary of because conservation structure be- for genetic (Camacho-Sanchez, structure important 2001). KNP population population in Nor, the on mammals 2019; small gradients Leonard, Understanding other environmental & to Maldonado, provides of compared Yu, treeshrew effect distribution Yit mountain elevational the Tuh The broad Hawkins, study a 1). to has (Figure which Tambuyukon it mountain cause in the Mt. of system and structure interesting Kinabalu genetic an Mt. population elevational Borneo: the see Sabah, across elucidating but (KNP), by 2018; mammals Wehrden, gap small von knowledge & of this treeshrew, Kessler address structure Kluge, We Dieker, genetic (Muenchow, 1995). 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Data may be preliminary. eoigidvdasta ol o easge oaSRCUEcutr(cutoff cluster separates STRUCTURE partially a to With explained) With assigned mountains, variation 6). two be ( (4% (Figure the 0.05 not together 2 is could separates clustered Eigenvector individuals that explained) elevation individuals variation masl. lower removing (7% with 900 1 elevation, at by Eigenvector with individuals individuals 5), pattern. 2000 among & and overlap similar 4 masl) a with (900 (Figures shows MK MK elevation PCA + low The at MT ancestry elevation mixed 5). low assigned (Figure from individuals MT cluster with masl For MK, separate MT. and When masl a MT, 2000 form elevation 2012). is at Waits, MT STRUCTURE individuals & while on ancestry Adams 2014) masl mixed (Bohling, al., 2400 previous ancestry et as and (Frosch mixed unexpected 2000 admixture assigning not is underestimate at This may accurate STRUC- DAPC not. more did except that DAPC analyses, shown while STRUCTURE have individuals masl and many studies to 2000 DAPC ancestry the [?] mixed between assigned individuals concordant TURE with mostly one is - membership clusters Cluster two into individuals divided with were for one individuals simulations both and MT for ran analyses we individuals. two MK except the and of among above each model described by relevant defined settings a as with this cluster consider each we in membership S4a), K scenarios (Table individual of analysis in proportion STRUCTURE better the the show performs in STRUCTURE MeanLnP(K) highest from the low output and (MeanLnP(K)) flow gene probability high with mean the the and that BIC the and by shown two determined was clusters as population toward three, of biased was number likely likely most most the that second indicated STRUCTURE and DAPC Both Structure Population .) sn h aae ih1%msigdt,tepoaiiyo w niiul aigietclgenotypes identical having individuals two of probability t-test the ( two-sample Welch data, present respectively, missing are 0.01 10% and siblings with (0.04 assuming dataset significant not the was Using difference 0.2). the but MT, ( inbreeding than different average MK significantly not the were and heterozygosity 0.027), expected and (SD data, 0.2297 0.027), missing was no (SD individuals with dataset 80 SNP ( all the coefficient Using for heterozygosity 0.000022). 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Data may be preliminary. ao pito K n eodclnzto vn curdltr hswudepantesgaueo two MT of elevation signature high the the at explain to would individuals prior this among MT later, diversity on from genetic occurred resident treeshrews al. event higher-than-average were mountain et colonization treeshrews find of mountain We second Liew split If a 1998; clusters. the and 2011). 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Pfenninger, & Bohning-Gaese, Prinzinger, Hof, (Khaliq, kg 1 10 F ST . ewe the between Treached MT Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. t rsMd,amuti ot fM ihnteCokrRne(iue7.Teptenifre from inferred pattern The on 7). found (Figure lineage Range Crocker a the to within sister MK lineage of 4 one south with mountain (ca. MK, a ( species on blackeyes Madi, haplogroups mountain the Trus in mitochondrial of Mt. pattern divergent the age similar two in a the found plants documented including and they (2014) is taxa, years) which al. other million et in ybp, Gawin 7 inferred 450,000 been least have (at ca. 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Data may be preliminary. aaatv eei iest.Hwvr euto naalbehbttcudmk h pce vulnerable. species with the upslope countered make that introducing be could by means habitat risk not elevations available extinction could across increase in elevational structure distribution not reduction likely upper However, population its will diversity. strong the of MK genetic on of occupies bound treeshrews maladaptive lack lower mountain already elevation The the lower species of limit. in The dispersal upper shift upslope contraction. its expanding upslope range at species an expansion lowland experience so with shift KNP, will interactions upslope within it m ecological limits that 490 or predicted predict limitations 2100 the we its climatic tracks by at - of species m treeshrew the because 490 mountain that whether the scenarios assuming ca. - limit Change unknown, of that Climate are on shift factors boundary Panel elevational the gene genetic upslope Intergovernmental lower Although mild population an historical assuming GCC-induced www.ipcc.ch/report/ar5/wg1/). experience 2018), and monitor 2013, could al., diversity, (IPCC to et KNP Camacho used genetic in 1999; be communities (Still, structure, can Montane CE data population These time. of KNP. over in changes estimate treeshrews foundational therefore mountain for is a flow and It dispersal provide monitor, increased we predict, 2019). to populations, Here, Shaw, order structured in GCC. & structured highly of (Weiss-Lehman et are effects adapted, genes populations Williams the montane locally maladaptive mitigate 2008; tropical of introduce how al., habitat, understand case could et fragmented to the upslope or imperative (Moritz reduced flow in extinction in gene addition, to result and vulnerable In can shifts species These 2007). making 2009). al., and al., to diversity et response genetic Chen in Fitzparick, 2008b; decreasing shifts & are & range al., Ruiz-Gutierrez, Jackson, they upslope et Scholer, Freeman, documented (Williams, Raxworthy because have tolerance 2018; (e.g. effects studies changes 2015; climatic Several greatest precipitation Tingley, narrow and 2010). the temperature and & Jetz, suffer GCC-associated ranges & (Elsen to Sorte geographic biodiversity La predicted restricted Earth’s 2007; are with Kutzbach, to endemic species threats montane be Tropical significant to likely most 2014). 2019). the al., al., of et et Bellard one Tsai is 2016, historical GCC Braun, from & Anthropogenic derived Lim DNA al., 2020; such including et al., DNA, repeatability the (Harvey et Implications low-quality offers regions Lim about Conservation on geographic capture 2016; drawn performed and al., UCE be be time et 2) to (Hawkins across can 2020), specimens species capture conclusions al., museum same UCE allowing the et 3) species, for (Lim and across inferences taxa 2016), compare comparison loci diverse can direct of on studies enable are set data processes that UCEs resources produces same 1) historical genomic capture the RAD-seq: of UCE over few from effects benefits genomes, which drawn several reference for inferences has require treeshrew and of not content mountain do information the also similar studies. like with methods genomic species RAD-seq population for Although studying used for available. be valuable to are UCEs ca. UCEs for potential of area the capture an KNP, suggests sequence This within that resolve treeshrews estimates. show mountain ( can we in probability UCEs high structure Here, km with population These 2014). 754 2016). of genomics. patterns approximately al., al., population resolve landscape-scale et of et to for Zarza Sun suitable able (e.g. datasets 2018; were 2014; informative species datasets al., highly al., diverged two et recently yielded et Winker UCEs of Smith 5,000 2016; (e.g. history al., taxa 2012; demographic across et and al., and Harvey structure, timescales et multiple population McCormack at patterns, (Faircloth phylogenies 2016; phylogeographic tetrapods resolving for al., of UCEs capable et sequence proven and have Hawkins capture UCEs to 2012), probes hybridization al., DNA et of design original the genomics events Since population colonization Borneo. fine-scale multiple in for of species UCEs hypothesis this of of the al., Utility history test et treeshrews, and phylogeographic to (Manthey mountain blackeyes the Range, MK of mountain determine Crocker on sampling between to the geographic found history and across broader lineage colonization from include single common individuals should a a including studies with indicate Future concordant, may treeeshrews. not pattern mountain was similar study This subsequent 2017). a in data SNP P IDsib 2 h N aae rvddsffiin ttsia oe oietf individuals identify to power statistical sufficient provided dataset SNP The . .4x10 x 1.54 = -199 n oietf uaiefml rusuigpiws kinship pairwise using groups family putative identify to and ) 12 Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. oln,J . dm,J . at,L .(03.Eautn h blt fBysa lseigmethods set. clustering Bayesian data of wolf ability red the empirical Evaluating an (2013). using P. https://doi.org/10.1111/mec.12109 bird. introgression L. island Waits, 74–86. and an & hybridization in R., Heeb, detect flow J. gene J., to Adams, and Cornuault, H., dispersal R., J. reduced Garcia-Jimenez, Bohling, Extremely T., (2014). Duval, C. B., Thebaud, Delahaie, & C, Vul- B., Heredity X. Pujol, Y. (2014). B., Bourgeois, Mila, F. P., M., Courchamp, A. & J. W., Bertrand, Thuiller, S., change. Veloz, global M., to Bakkenes, https://doi.org/10.1111/geb.12228 hotspots B., biodiversity Leroy, of C., nerability param- genetic Leclerc, population C., of Bellard, inference maximum-likelihood and Bayesian of eters. Comparison among direction (2005). migration P. and ultraconserved Beerli, panmixia of evaluate Faircloth, to utility framework A., phylogenetic locations. Unified Aleixo, sampling the (2010). multiple B., improves M. Palczewski, Oxelman, greatly & P., phasing B., Beerli, Allele Pfeil, M., (2018). Topel, A. U., Antonelli, elements. Olsson, & M., C., A. B. Fernandes, manuscript. T., the LDP of Andermann, and version JAW final and MTRH the MGC of study; bioinformatics; phyloge- acceptance in and the performed References revisions assisted MTRH for in MGC analyses; participated resources and SNP authors JEM, HCL, provided all performed TRW, JAL, vcf2aln; LLR figures; and MTRH, developed contributed manuscript and work; MCS the field JEM, analyses; wrote conducted netic JAL, LDP MCS work; study; and laboratory MTRH the did work; designed field LDP organized and JAL and MCS, MTRH, FigShare Contributions on Author available alignments sequence multiple XX pseudo-haplotype SRA: -UCE NCBI XX-XX; accessions Genbank sequences: -DNA de was Biologica support Estacion Logistical la Accessibility de Data University. Teledeteccion Mason y ICTS-RBD. Geografica George Informacion Donana at de and Biology Sistemas Donana de of Laboratorio Department by the provided and (CGL2010-21524, provided Government 1717498), helpful Lee Spanish (1547168, provided Chien the Kaganer by Rico, support. funded Phylogenomics W. Castaneda logistical eration was ( A. provided S. work Institution Fleischer and Smithsonian This the R. scripts. Kearns, CGL2017-86068-P), and photograph. calling M. Helgen treeshrew SNP A. mountain K. his McInerney, the manuscript. shared R. the gracefully N. on Giarla Venkatraman, comments T. M. Ochirbat, kit. M-E. sequencing provided MiSeq UMMZ a and donated Thompson, and C. flow Olson, gene forested L. facilitate high-elevation to greatest the masl refugium the 900 of future and at a rest region habitat Acknowledgements as the the forest KNP and in protecting of on peak KNP diversity. importance focus genetic highest between the preserve should the connectivity highlights efforts However, contains This and Conservation MT. it masl, area. as 7). and 1400 species, (Figure MK montane severed above between for be peaks connectivity could few maintain Range would has Crocker treeshrews Range mountain Crocker that the predict also We Bioinformatics 1() 9–9.https://doi.org/10.1038/hdy.2013.91 190–196. 112(2), , ytmtcBiology Systematic 23,314.https://doi.org/10.1093/bioinformatics/bti803 341–45. 22(3), , mtsna rn hlegsAad 02-21) h ainlSineFoundation Science National the 2014), - 2012 Awards Challenges Grand Smithsonian Genetics 81,3–6 https://doi.org/10.1093/sysbio/syy039 32–46. 68(1), , 8() 1–2.https://doi.org/10.1534/genetics.109.112532 313–326. 185(1), , uaasplendidula Tupaia uligteFaeoko idvriySine etGen- Next Science: Biodiversity of Framework the Building 13 lblEooyadBiogeography and Ecology Global N xrcs .LnlyadteFDA the and Lindley S. extracts. DNA oeua Ecology Molecular 31) 1376–1386. 23(12), , 22(1), , Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. aee,P,Atn . bcss . les .A,Bns . erso .A,...10 Genomes 1000 . . . A., M. DePristo, E., Banks, VCFtools. A., and format C. call variant Albers, The G., (2011). Abecasis, Group. Analysis A., genetic Project recent Auton, of estimation P., Model-free population Danecek, (2016). A. Spatial T. Thornton, & S., (2017). B. Weir, J. relatedness. P., A. Munshi-South, Reiner, P., M. & Conomos, D., ( Mims, rat J., brown Richardson, https://doi.org/10.1111/mec.14437 Kinabalu. the E., Mt. of of E. genomics Sciences history Puckett, Biological geological B, M., and Series Combs, geology London the of of Society account Royal short the of A (1964). from P. species Collenette, plant pitcher montane giant three size. in body geometry shrew Trap 8137.2009.03166.x tree of (2010). function C. a Clarke, is & Borneo A., J. mitochon- Moran, of L., adaptation Chin, local and https://doi.org/10.1111/j.1558-5646.2009.00644.x Thomas, balance 1593–1605. & ( Migration-selection 63(6), sparrows K., , (2009). rufous-collared J. T. mountain. in Hill, R. tropical haplotypes S., Brumfield, a drial H. & on Barlow, A., years Z. K., 42 Cheviron, V. over Chey, assemblages Sciences D., moth of J. Academy in Holloway, National increases S., Elevation the Benedick, phylogenetic (2009). J., in D. H. use C. Shiu, their C., for I. alignments multiple Chen, from blocks and conserved zone of contact Selection analysis. a (2000). of J. Identification Castresana, (2018). ( C. pika Ray, American & W., the ONE are B. of PLOS Frable, Sundaland subspecies W., two of C. for rainforests Epps, hybridization refugial A., current J. The Vardaro, Castillo (2009). G. disturbance. B. to Sciences vulnerable A. highly of and Bush, and Academy summarizing past & biogeographic for J., their Software R. of unrepresentative Morley, CorrSieve: H., C. (2011). Cannon, J. White, & H., Jones, 0998.2010.02917.x (2019). V., output. A. H. Structure J. Hunt, mountains.evaluating Leonard, G., Bornean & M. neighboring E., Campana, two J. sum- Maldonado, along the F., mammals Yu, from small Yit insights Tuh of https://doi.org/10.7717/peerj.7858 J. Novel R., diversity T. Maldonado, and M. nountains: K., Endemism Hawkins, tropical Wells, & on M., F., Camacho-Sanchez, refugia Yu, Interglacial Yit Tuh (2018). R., https://doi.org/10.1111/ddi.12761 ( A. T. rat J. M. of mit Leonard, Hawkins, Absence & I., (2017). E. V. Quintanilla, V. chickadees M., Pravosudov, mountain & Camacho-Sanchez, in L. variation phenotypic T. large Parchman, despite Y., gradients D. ( elevational Kozlovsky, across P., structure J. BEAST population Jahner, (2014). L., J. C. A. Branch, Drummond, , sequence . analysis. . . Illumina evolutionary D., Bayesian for Xie, for trimmer C., https://doi.org/10.1371/journal.pcbi.1003537 platform Wu, flexible software T., Vaughan, A A D., 2: Trimmomatic: Kuhnert, J., Heled, (2014). R., B. Bouckaert, Usadel, & M., Lohse, data. M., A. Bolger, ocl gambeli Poecile Bioinformatics oeua ilg n Evolution and Biology Molecular atsbaluensis Rattus h mrcnJunlo ua Genetics Human of Journal American The 37,e193.https://doi.org/10.1371/journal.pone.0199032 e0199032. 13(7), , ). oa oit pnScience Open Society Royal 0(7,118113 https://doi.org/10.1073/pnas.0809865106 11188–11193. 106(27), , 01) 1422.https://doi.org/10.1093/bioinformatics/btu170 2114–2120. 30(15), , ,aBre onanendemic. mountain Borneo a ), oeua clg Resources Ecology Molecular atsnorvegicus Rattus 0() 4918.https://doi.org/10.1073/pnas.0809320106 1479–1483. 106(5), , 74,540–552. 17(4), , e Phytologist New oorci capensis Zonotrichia () 707 https://doi.org/10.1098/rsos.170057 170057. 4(3), , nNwYr City. York New in ) 14 81,174.https://doi.org/10.1016/j.ajhg.2015.11.022 127–48. 98(1), , cooaprinceps Ochotona 12,395.https://doi.org/10.1111/j.1755- 349–52. 11(2), , LSCmuainlBiology Computational PLoS 8() 6–7.https://doi.org/10.1111/j.1469- 461–470. 186(2), , 6,56-63. 161, , iest n Distributions and Diversity ln neeainlgradient. elevational an along ) oeua Ecology Molecular Bioinformatics ihnasnl rtce area. protected single a within ) rceig fteNational the of Proceedings 7(5,2156–58. (15), 27 , 04,e1003537. 10(4), , PeerJ 24,1252-1266. , 71,83–98. 27(1), , rceig of Proceedings Proceedings 7,e7858. , Evolution Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. esnti,J 20) cuayo olsetlklho siae:D ene oests oesequences, more sites, more need we elevational Do along estimates: selection likelihood Divergent loci? coalescent more populations. of (2019). or Accuracy mammal Q. (2005). Yang, small J. & Felsenstein, among climate L., to disparities Xia, responses phenotypic D., species’ and Ge, of Evolution genetic reviews J., ‘global’ promotes Cheng, T. Most gradients Z., Glenn, Wen, (2017). & A., M. Feijo, T. T., Perez, global. R. & truly evolutionary Brumfield, not T., multiple are J. G., change spanning Stroud, M. markers J., Harvey, genetic K. Feeley, of G., thousands N. anchor Crawford, elements E., timescales. Ultraconserved J. loci. (2012). McCormack, genomic C. conserved C., of analysis multilocus B. the using Faircloth, for structure package software population a of is PHYLUCE perform Inference formatics (2016). to frequencies. C. (2003). programs allele B. K. of Faircloth, correlated and J. series loci Pritchard, new Linked & A data: M., genotype 3.5: Stephens, ver. D., Falush, suite Windows. Arlequin and Linux (2010). L. under https://doi.org/10.1111/j.1755-0998.2010.02847.x E. analyses H. genetics expansions. Lischer, range population of & consequences L., Genetic Excoffier, (2008). J. R. Systematics Petit, and Evolution, & Ecology, M., Foll, L., soft- Excoffier, the using individuals of clusters of number 294X.2005.02553.x the Detecting study. simulation (2005). A J. STRUCTURE: Goutdet, ware & S., Regnaut, G., Evanno, under species montane of Press. fate (2000). the H. and L. topography Emmons, mountain Global (2015). W. change. M. Tingley, climate & R., P. Elsen, visualizing for program and website method. https://doi.org/10.1007/s12686-011-9548-7 A Evanno HARVESTER: 361. STRUCTURE the implementing (2012). and across M. output flow B. STRUCTURE vonHoldt, gene & restricted A., flycatchers. D. and tit-tyrant Earl, adaptation Andean high-altitude Differential in Trees. zone (2014). https://doi.org/10.1111/mec.12836 Sampling C. hybrid by C. mid-elevation Witt, Analysis a & Evolutionary ecologists. Bayesian G., for S. BEAST: DuBay, diagram (2007). duality A. the Biology Rambaut, Implementing Evolutionary & BMC package: J., NeEstimator Ade4 A. The (2014). Drummond, R. (2007). J. Software B. from Statistical Ovenden, (Ne) A. of & size Dufour, Journal J., population & B. effective S., contemporary Tillett, Dray, of M., estimation G. the Macbeth, for data. D., software squirrels, genetic Peel, of tree SE Re-implementation S., Sundaland the of in R. v2: dynamics biogeography Waples, Speciation and C., phylogeny (2010). Do, the A. on J. Leonard, perspective & time E., a Sundasciurus. J. putting Maldonado, R., tropics: Thorington, Asian J., R. Tex, den https://doi.org/10.1093/bioinformatics/btr330 25,768.https://doi.org/10.1093/bioinformatics/btv646 786–88. 32(5), , (2,78–05 https://doi.org/10.1002/ece3.5273 7080–7095. 9(12), , ytmtcBiology Systematic oeua clg Resources Ecology Molecular oeua ilg n Evolution and Biology Molecular oeua hlgntc n Evolution and Phylogenetics Molecular aueCiaeChange Climate Nature ua:Afil td fBrentreeshrews Bornean of study field A Tupai: iest n Distributions and Diversity () 1.https://doi.org/10.1186/1471-2148-7-214 214. 7(1), , 15,7776 https://doi.org/10.1093/sysbio/sys004 717–726. 61(5), , () -0 https://doi.org/10.18637/jss.v022.i04 1-20. 1(4), , 01,4151 https://doi.org/10.1146/annurev.ecolsys.39.110707.173414 481–501. 40(1), , oeua Ecology Molecular () 7–7.https://doi.org/10.1038/nclimate2656 772–776. 5(8), , 41,291.https://doi.org/10.1111/1755-0998.12157 209–14. 14(1), , 33,6170 https://doi.org/10.1093/molbev/msj079 691–700. 23(3), , 15 , 55 33,2124 https://doi.org/10.1111/ddi.12517 231–234. 23(3), , 2,7170 o:10.1016/j.ympev.2009.12.023 doi: 711-720. (2), 48,21–60 https://doi.org/10.1111/j.1365- 2611–2620. 14(8), , oeua clg Resources Ecology Molecular Genetics osrainGntc Resources Genetics Conservation oeua Ecology Molecular ekly A nvriyo California of University CA: Berkeley, . 6() 1567–1587. 164(4), , 31) 3551–3565. 23(14), , nulRve of Review Annual 03,564–567. 10(3), , clg and Ecology () 359– 4(2), , Bioin- Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. akn,M .R,Load .A,Hle,K . coog,M . okod .L,&Maldonado, & mitogenomes L., and L. UCEs Rockwood, from M., constructed M. squirrels McDonough, Sulawesi M., endemic K. of history Helgen, Evolutionary A., J. (2016). E. Leonard, J. R., T. (Eds.) M. Wilson E. Hawkins, Colugos D. and & Sloths, Mittermeier Insectivores, A. 8: R. Volume Spain. In capture World . Sequence the Family of (2016). (2019). Mammals T. R. R. T. Brumfield, M. Hawkins, & systematics. C., shallow of B. for Faircloth, biogeography sequencing https://doi.org/10.1093/sysbio/syw036 C., DNA and T. 924. associated compar- Glenn, relationships site morphometric T., Interspecific restriction B. and versus Smith, hybridization (2000). G., DNA M. B. Harvey, on R. based Stuebing, Tupaia), & (Tupaiidae shrews H., isons. (2009). tree F. E. Bornean Sheldon, G. some Batt, H., & K. C., Hall Han, R. Sperber, In F., Tongkul, sea. S., and Suggate, land Kinabalu M., of Cottam, distribution R., the Hall, and Asia Netherlands. SE The Leiden, (Eds.) Cenozoic Holloway of Publishers: freshwater tectonics D. of plate J. communities The and & (2017). genes N. (1998). Alvarez, structuring R. , in . Hall, . driver . common I., A. the Kamil, as J., islands organisms. Jamsari, sky J., tropical Gattolliat, in S., Elevation Rutschmann, T., , Suchan, . . M., . Gueuning, pop- G., infer to larvae D. sampling from Gannon, bias of 0998.2009.02755.x reduction S., structure. and Quantification genetic A. landscape (2010). and are P. ulation Flecker, L. passes Waits, & ‘mountain C., S., C. the A. Goldberg, for Encalada, support biogeographic hypothesis. L., reveals tropics’ K. diversity https://doi.org/10.1098/rspb.2016.0553 the species Casner, Cryptic in C., higher (2016). B. and C. Empirical Kondratieff, W. radiation: Funk, recent A., rapid, B. a resolving Gill, of challenges The shrews. (2015). Philippine A. passes of J. phylogenomics mountain simulated Esselstyn, Are & C., (2006). T. G. Giarla, Wang, revisited. & hypothesis F.H. J., Janzen’s Sheldon, J. Tewksbury, & R., tropics? G., https://doi.org/10.1093/icb/icj003 P. R. the Martin, Moyle, B., in C., R. higher Huey, H. K., Lim, ( C. T., black-eye mountain Ghalambor, B. endemic the Smith, of S., case C. The F. Witt, Borneo: M. in emiliae & diversification Ramji, for avian E., A., of tests Patterns M. Bautista, stable-isotope (2014). Rahman, C., and F., Genetic S. D. Galen, Gawin, songbirds. species? N., generalist some elevational A. for (2014). https://doi.org/10.1111/1365-2656.12779 ‘low’ Chavez, in 741–753. C. passes expansion J., 87(3), Nowak, mountain and E. tropical & migration Beckman, are differentiation, J., D., Why Teubner, S. Europe. (2018). J., Newsome, C. central R., Michaux, in C. R., reintroductions Gadek, Allgower, beaver C., multiple Angst, of S., https://doi.org/10.1371/journal.pone.0097619 legacy H. genetic R. causes community.The Kraus, change bird Climate C., tropical (2018). Frosch, a W. in J. Fitzpatrick, extirpations Sciences and mountaintop of V., Academy and Ruiz-Gutierrez, N., shifts M. upslope Scholer, G., B. Freeman, ilgclJunlo h ina Society Linnean the of Journal Biological ). aa ak:Sbh Malaysia. Sabah, Parks: Sabah . h Auk The cetfi Reports Scientific 3() 69.https://doi.org/10.1642/AUK-13-190.1 86–99. 131(1), , 1(7,192197 https://doi.org/10.1073/pnas.1804224115 11982–11987. 115(47), , igorpyadtegooia vlto fS Asia SE of evolution geological the and Biogeography () 68.https://doi.org/10.1038/s41598-017-16069-y 16089. 7(1), , rceig fteRylSceyB ilgclSciences Biological B: Society Royal the of Proceedings oeua clg Resources Ecology Molecular ytmtcBiology Systematic 01,11.https://doi.org/10.1006/bijl.1999.0358 1–14. 70(1), 16 nertv n oprtv Biology Comparative and Integrative 45,7770 https://doi.org/10.1093/sysbio/syv029 727-740. 64(5), , p.4–9.Ln dcos Barcelona, Edicions: Lynx 42–69). (pp. 02,3433 https://doi.org/10.1111/j.1755- 304–313. 10(2), ytmtcBiology Systematic ora fAia Ecology of Journal LSONE PLOS rceig fteNational the of Proceedings p.9-3) Backhuys 99-131). (pp. . h elg fMount of Geology The adoko the of Handbook () e97619. 9(5), , 61,5–17. 46(1), , 55,910– 65(5), , Chlorocharis 8,1832. 283, , , Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. ird,P,&Rzs .(09.DaPv:Asfwr o opeesv nlsso N polymorphism DNA of analysis comprehensive Data for software Project A Genome v5: 1000 DnaSP , SAMtools. . (2009). . . J. and data. Rozas, N., format & Homer, P., Alignment/Map Librado, J., Sequence Ruan, The T., https://doi.org/10.1093/bioinformatics/btp352 BWA-MEM. Fennell, 2078–2079. (2009). with 25(16), A., contigs Wysoker, Subgroup. assembly B., and Processing Handsaker, sequences H., clone Li, reads, sequence and Aligning synthesis multidimensional 1303.3997v1. global (2013). construction. a H. network - shifts Li, haplotype range for Climate-related software (2015). directions. Full-feature C. research J. new Svenning, Popart: & J., (2015). Lenoir, D. Evolution and Bryant, Ecology & in BayesianMethods W., of J. performance Relative Leigh, population (2006). of levels E. low O. of at assignment Rhodes, selection individual & and Combined differentiation. substructure C., population J. inferring PartitionFinder: Glaubitz, for software G., clustering (2012). Dharmarajan, K., S. E. Guindon, Latch, & analyses. W., phylogenetic https://doi.org/10.1093/molbev/mss020 for Y. 1695–1701. models S. 29(6), substitution Ho, and schemes B., warm- partitioning global Calcott, under biodiversity R., montane of Lanfear, contractions range Projected (2010). W. Jetz, ing. 7.0 & version A., analysis F. genetics Sorte, evolutionary La Molecular MEGA7: (2016). datasets. K. Tamura, bigger for & Borneo G., Kinabalu, Stecher, Mount S., on Kumar, vegetation the www.jstor.org/stable/20046210 of study 149–171. transect 102(2), altitudinal , mul- An (1992). rapid K. thermal Kitayama, for in change. variation Global method climate (2014). to novel M. endotherms Pfenninger, A Sciences of & K., MAFFT: vulnerability Bohning-Gaese, and R., tolerances Prinzinger, (2002). C., Hof, T. transform. I., Khaliq, fourier Miyata, fast & on K., based https://doi.org/10.1093/nar/gkf436 Kuma, alignment K., sequence tiple Misawa, K., markers. Katoh, genetic of analysis multivariate https://doi.org/10.1093/bioinformatics/btn129 the for 1403–1405. package 24(11), R An , tropics. Adegenet: the (2008). in T. Jombart, higher are L. passes R. mountain Andrew, https://doi.org/10.1086/282487 Why & I., 233–249. (1967). C. Cullingham, H. C., D. J. Gorrell, Janzen, conundrum. M., 2 R. = Malenfant, R., K J. for The Dupuis, M., program (2017). J. permutation Miller, K., and structure. J. matching population Janes, of cluster analysis A in CLUMPP: multimodality https://doi.org/10.1093/bioinformatics/btm233 divergence and (2007). 1801–1806. Ancient switching (in A. A. label N. with J. squirrels. Rosenberg, dealing tree Leonard, & Sundaland & M., dependent E., Jakobsson, forest J. in Maldonado, adaptation ecological A., and Achmadi, review) isolation R., geographic T. by M. driven Hawkins, A., Hinckley, specimens. 016-0650-z museum from sequenced rceig fteRylSceyB ilgclSciences Biological B: Society Royal the Proceedings of Bioinformatics rnir nEooyadEvolution and Ecology in Frontiers 8,2119.https://doi.org/10.1098/rspb.2014.1097 20141097. 281, , osrainGenetics Conservation oeua ilg n Evolution and Biology Molecular 51) 4115.https://doi.org/10.1093/bioinformatics/btp187 1451–1452. 25(11), , Ecography oeua Ecology Molecular 81,1–8 https://doi.org/10.1111/ecog.00967 15–28. 38(1), , () 1011.https://doi.org/10.1111/2041-210X.12410 1110–1116. 6(9), , M vltoayBiology Evolutionary BMC () 9–0.https://doi.org/10.1007/s10592-005-9098-1 295–302. 7(2), , . 61) 5430.https://doi.org/10.1111/mec.14187 3594–3602. 26(14), , 37,17–84 https://doi.org/10.1093/molbev/msw054 1870–1874. 33(7), , 17 7(69,30–0 https://doi.org/10.1098/rspb.2010.0612 3401–10. 277(1699), , uli cd Research Acids Nucleic rceig fteRylSceyBiological Society Royal the of Proceedings 61.https://doi.org/10.1186/s12862- 16(1). , h mrcnNaturalist American The oeua ilg n Evolution and Biology Molecular Bioinformatics 01) 3059–3066. 30(14), , Bioinformatics Bioinformatics 101(919): , Vegetatio 23(14), , ArXiv , , Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. oiz .(94.Dfiig‘vltoaiysgicn nt’frconservation. https://doi.org/10.1016/0169-5347(94)90057-4 for 373–375. units’ 9(10), significant ‘evolutionarily , Defining century (1994). a USA. C. of Park, Moritz, Impact National (2008). Yosemite S.R. in Beissinger, communities & https://doi.org/10.1126/science.1162547 C., mammal G. small 261. White, (Aves: on L, white-eye change J. Parra, grey climate J., of Mascarene C. islands: Conroy, the J., on Patton, in diversification C., scale of Moritz, scale spatial geographic small The very (2010). a borbonicus C. at Zosterops Thebaud, divergence & C. morphological P., mountain. T. and Heeb, tropical K. Genetic H., Peijnenburg, young propor- B. E., a Warren, by L. on B., Becking, endemism revealed Mila, B., of C. are Evolution Mennes, Paralogs K., (2015). https://doi.org/10.1038/nature14949 K. M. popu- Beentjes, Schilthuizen, 347–350. P., 2017. natural , K. . . from J.E. Hendriks, . T., data A., Seeb, F. genotyping-by-sequencing S. & in V. W., ratios Merckx, read L. M. in Seeb, DePristo, deviations K., DNA , and lations. . . next-generation heterozygotes R. . analyzing of Waples, A., for tion Kernytsky, J., framework K., G. MapReduce A McKinney, Cibulskis, A., Toolkit: Sivachenko, Analysis Genome data. E., sequencing The Banks, (2010). M., when A. Hanna, phylogeny A., mammal (2012). placental C. McKenna, T. resolve Glenn, & that T., markers analysis. R. species-tree phylogenomic Brumfield, with A., combined novel P. Gowaty, are G., N. tropics. elements Crawford, the Ultraconserved C., in B. Faircloth, ‘higher’ E., be J. may McCormack, mountains that indicate endemism, sizes white- range Hidden Vertebrate the Letters 2009. of (2018). M. Diversification C. G. McCain, Tehuantepec: A. of Navarro-Siguenza, Isthmus & the (Thraupidae: https://doi.org/10.1002/ece3.3799 J., across complex I. dispersal seedeater Lovette, (2017). repeated collared H. A., and F. polyphyly, Olvera-Vital, Sheldon, deep A., & N. S., diversification. F. Mason, Pleistocene M. of Ramji, ( patterns A., Borneo https://doi.org/10.1111/jbi.13028 in M. of differ 2272–2283. black-eye Rahman, populations mountain F., lowland endemic D. and the Gawin, relation- of G., Robust phylogeography elevational R. (2010). Genomic Moyle, an M. W. D., across Chen, J. & flow Manthey, M., gene Sale, K., studies. and Daly, association S., genome-wide Speciation in S. inference Rich, ship C., (2019). J. P. Mychaleckyj, A., J. Manichaikul, Dumbacher, kingfishers. DNA. H. & Guinea historical F. New G., and Sheldon, in B. genomic gradient & capture Freeman, Comparative J., target E., M. Asia: using Braun, Linck, Southeast species C., in R. bird inference Fleischer, rainforest phylogeographic G., codistributed greater Evolution, R. five Moyle, to G., of door M. study the Harvey, Opening B., samples S. (2020). modern Shakya, and C., elements. historical H. ultraconserved of Lim, genotyping of SNP capture High-throughput sequence a https://doi.org/10.1111/1755-0998.12568 via (2016). along 1204–1223. species J. diversity bird M. snail five Braun, land of and of C., determinants H. The Lim, (2010). M. niches. and Lakim, geometry bin https://doi.org/10.1111/j.1365-2699.2009.02243.x Insularity, & gradient: M., elevational Schilthuizen, tropical S., T. Liew, oeua clg Resources Ecology Molecular 26,5050 https://doi.org/10.1111/j.1461-0248.2009.01308.x 550–560. 12(6), , 0 2234.https://doi.org/10.1002/ece3.5964 3222–3247. 10, eoeResearch, Genome ). M vltoayBiology Evolutionary BMC BioRxiv eoeResearch Genome 74:6669 https://doi.org/10.1111/1755-0998.12613 656–669. 17(4): , 09,19–33 https://doi.org/10.1101/gr.107524.110 1297–1303. 20(9), prpiatorqueola Sporophila 804 https://doi.org/10.1101/589044 589044. , Bioinformatics 018.https://doi.org/10.1186/1471-2148-10-158. 10(158). , 18 24,7674 https://doi.org/10.1101/gr.125864.111 746–754. 22(4), , ora fBiogeography of Journal ). 6(2,26–83 https://doi.org/10.1093/bioinformatics/btq559 2867–2873. (22), 26 , clg n Evolution and Ecology oeua clg Resources Ecology Molecular ora fBiogeography of Journal hoohrsemiliae Chlorocharis rnsi clg Evolution & Ecology in Trends Science, Nature 76,1071–1078. 37(6), , () 1867–1881. 8(3): , 2(89,258– 322(5899), clg and Ecology 524(7565), , :Montane ): 44(10), , Ecology 16(5), , Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. mt,B . avy .G,Ficoh .C,Gen .C,&Bufil,R .(04.Tre capture Target (2014). T. R. Brumfield, & C., evolutionary shallow T. at studies Glenn, comparative C., for elements B. scales. ultraconserved Faircloth, time of sequencing G., parallel M. massively Harvey, and T., B. Smith, of genome mitochondrial orders. complete Eutherian https://doi.org/10.1093/oxfordjournals.molbev.a026417 other The to 1334–43. (2000). Scandentia of H. affiliation Zischler, phylogenetic & the M., models. treeshrews mixed Ohme, of under J., inference phylogeny Schmitz, phylogenetic Molecular Bayesian 3: MrBayes (2011). (2003). E. P. Bioinformatics J. Asia. L. Huelsenbeck, Southeast & Olson, F., in & Ronquist, diversification J., of E. timescale Sargis, Evolution the and C., from and H. endemism Scandentia) Madagascar. montane Lanier, in (Mammalia: tropical E., massif Rase- of T. highest B., vulnerability the Roberts, Extinction J. for appraisal Ramanamanjato, (2008b). preliminary M., A. A Biology A. D. Change displacement: Rakotondrazafy, Stone, upslope N., , and . Ingram, Rabibisoa, . warming . & G., P., A., R. A. R. in Pearson, limanana, divergence Nussbaum, J., of J., C. patterns Raxworthy, A. biogeographic Deo, contrasting S., tropics: Reddy, the 7998.2008.00460.x M., in B. speciation Continental Zimkus, multilocus the using G., (2008a). structure R. M. population Pearson, C. of J., Inference C. (2000). Raxworthy, P. Donnelly, & (2018). M., data. R. genotype Stephens, K. Zamudio, K., , . mountains. J. . . tropical Pritchard, A., in Barthelet, speciation L., Sciences higher K. drive Casner, of Academy M., dispersal M. low National expan- Gray, and A., range A. tolerance during Shah, thermal A., variation Narrow B. Genetic Gill, R., N. (2017). Polato, K.S. Pfennig, hybridization. & and https://doi.org/10.1098/rspb.2017.0007 M., novelty A. 284(1852). habitat Rice, of effects R., Gutierrez, sion: A., Malaysia. A. Sabah, Pierce, Kinabalu, Kota Publications: History Natural (2016). estimated Kinabalu K. with Phillipps, structure & Q., population Phillipps, spatial Visualizing (2016). surfaces. M. migration Stephens, for effective software & genetic J., Population Novembre, Excel. D., in Petkova, analysis Genetic 6.5: GenAlEx update. , research-an . (2012). . and . E. teaching P. L., Smouse. & D. R., (2016). Peakall, Dittmann, Malaysia. K. of W., Sabah, Phillipps, history Kinabalu, evolutionary S. & Kota the M., Cardiff, of Society: C. view U., Francis, genomic D. A J., Foxworth, Payne, two? or C., species R. one be Remsen, Willet semipalmata G., (2016). Malaysia. T. M. Sabah, R. Harvey, Kinabalu, Brumfield, A., Mount on J. mammals Oswald, small of Biogeography patterns and diversity Ecology Elevational Global gradient (2001). ecological priorities. S.M. of conservation Nor, review and A directions, future (2018). gaps, H. Wehrden, research Conservation von Identifying and & tropics: M., the Kessler, in J., research Kluge, P., Dieker, J., Muenchow, Uroplatus ytmtcBiology Systematic . eftie ek aito fMadagascar. of radiation gecko leaf-tailed 03,3832 https://doi.org/10.1016/j.ympev.2011.04.021 358–372. 60(3), , h Auk The 91) 5217.https://doi.org/10.1093/bioinformatics/btg180 1572–1574. 19(12): , Genetics 48,10–70 https://doi.org/10.1111/j.1365-2486.2008.01596.x 1703–1720. 14(8), , 72,2325 https://doi.org/10.1007/s10531-017-1465-y 273–285. 27(2), , 3() 9–1.https://doi.org/10.1642/AUK-15-232.1 593–614. 133(4), , 5() 945–959. 155(2), , aueGenetics Nature 1(9,141146 https://doi.org/10.1073/pnas.1809326115 12471–12476. 115(49), , 31,8–5 https://doi.org/10.1093/sysbio/syt061 83–95. 63(1), , Bioinformatics 01:4–2 https://doi.org/10.1046/j.1466-822x.2001.00231.x 41–62. 10(1): , hlis edgiet h aml fBre n hi ecology. their and Borneo of mammals the to guide field Phillips’ 81:9–0.https://doi.org/10.1038/ng.3464 94–100. 48(1): , 81) 5723.https://doi.org/10.1093/bioinformatics/bts460 2537–2539. 28(19), , rceig fteRylSceyB ilgclSciences Biological B: Society Royal the of Proceedings il ud oteMmaso Borneo. of Mammals the to Guide Field A 19 ora fZoology of Journal oeua ilg n Evolution and Biology Molecular 7() 2–4.https://doi.org/10.1111/j.1469- 423–440. 275(4), , oeua Phylogenetics Molecular uaabelangeri Tupaia rceig fthe of Proceedings Biodiversity h Sabah The 17(9), , Tringa Global Kota and , Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. .83-004 hr re 1 8973026490 25850 793.0 322.8 a Tambuyukon. (m) Mount distance = Max MT parenthesis; Kinabalu, Mount (m) = 4819 distance MK Median 1247 2. Table (m) 112 distance Average 56 order Third order < Second n 0.0442 - 0.0883 Relatedness 0.0884 - 0.177 > and second and relatives Kinship showed second-order test and Differences first Significant except Honest pairs Tukey ( all and relatives between ANOVA third-order distances software. in KING differences the Hidden significant with (2016). analysis E. on J. based McCormack, & markers. 1. J., genomic Klicka, Table with W., revealed R. birds Bryson highland https://doi.org/10.1111/mec.13813 E., in L. 5157. flow W. gene Taiwan. Tsai, of in C., histories mammals B. small Faircloth, of E., structure Zarza, population genetic Society and Linnean diversification the of of dis- Journal Patterns Biological popula- and (1995). the T. illuminate novel H. (UCEs) Yu, elements event. of speciation Ultraconserved avian distributions high-latitude (2018). recent, B.C. Projected a Faircloth, of & genomics tion C., (2007). T. Glenn, E. K., Winker, J. Kutzbach, & AD. 2100 T., https://doi.org/10.1073/pnas.0606292104 by S. climates Jackson, data appearing W., from climate- in J. size risk extinction Williams, population determines structure effective population estimating Spatial shifts. range (2019). for K. induced A. program Shaw, & A C., Weiss-Lehman, Ldne: (2008). C. 0998.2007.02061.x disequilibrium. Do, linkage & on S., in genotypes R. among Waples, identity of probability the Estimating 294X.2001.01185.x (2001). guidelines. pedogenesis P. and Cautions Taberlet, of & populations: implications natural G., Ecological Luikart, (2018). P., McCor- G. L. Echevarria, Waits, (Malaysia). , Park . & Kinabalu . . M., in the soils Tibbett, M., ultramafic in of D., J. geochemistry wood-partridges Cardace, and Maley, Dendrortyx A., Y., of Ent, E. history der van speciation Liang, The the R., reveals Bhowmik, (2014). genomics O., T. Museum highlands. Rojas-Soto, mesoamerican R. (2019). Kimball, C., E. approach. Mota-Vargas, & J. phylogenomic E., mack, L., a L. E. W. (eyespots): Braun, Tsai, C., ocelli T. with Sciences Biological Glenn, taxa B: C., other Society B. and Royal tropical Faircloth, peafowl on A., change of K. climate evolution Meiklejohn, of K., effects class-interval. the Sun, a of Simulating choice The (1999). (1926). H. H. S. Sturges, Schneider, & N., forests. P. cloud Foster, montane J., C. Still, . .4 itn 9213019029430 570.1 15960 100.8 12310 2932 162.5 Distant 42 order First 0.044 0.18 ffciepplto ie n pairwise and sizes population Effective egahcdsacsbtenpiso niiul ihdffrn eeso siae relatedness estimated of levels different with individuals of pairs between distances Geographic F ST siae r eo h ignl ihassociated with diagonal, the below are estimates p h mrcnNaturalist American The Nature < oeua hlgntsadEvolution and Phylogenetis Molecular 0.05). oeua clg Resources Ecology Molecular 9(78,6860 https://doi.org/10.1038/19293 608–610. 398(6728), , rceig fteNtoa cdm fSciences of Academy National the of Proceedings 8(70.https://doi.org/10.1098/rspb.2014.0823 281(1790). , 51:6–9 https://doi.org/10.1111/j.1095-8312.1995.tb01050.x 69–89. 55(1): , oeua Ecology Molecular 029 https://doi.org/10.1086/706259 706259. , F ora fteAeia ttsia Association, Statistical American the of Journal ST 20 fpplto lseswith clusters population of N () 5–5.https://doi.org/10.1111/j.1755- 753–756. 8(4), , e siae r ntedaoa ih9%C in CI 95% with diagonal the on are estimates PeerJ 3,2–4 https://doi.org/10.1016/j.ympev.2019.03.017 29–34. 136, , 01,2926 https://doi.org/10.1046/j.1365- 249–256. 10(1), , Catena p ,e75 https://doi.org/10.7717/peerj.5735 e5735. 6, , vle bv h diagonal. the above -values 6,1419 https://doi.org/10.1016/j.catena.2017.08.015 154–169. 160, oeua Ecology Molecular a) K 0(4,5738–5742. 104(14), , and 3 = rceig fthe of Proceedings 52) 5144– 25(20): , b) 1 65–66. 21, K 2. = Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. ln n ntr rvd h ln irgntruhfcs(hn oa,&Cak,2010). Clarke, & Moran, the (Chin, by provided feces secretions through sugary nitrogen plant the on the provide feed turn treeshrews mountain in which and treeshrew in plant mountain relationship of mutualistic portion lines, a black upper have by and ( lower transects plant indicates lines, and pitcher Shading dashed masl by circles. (900–2000 demarcated white habitat are by boundaries locations Park sampling and Borneo. Sabah, Park, (left) Kinabalu a 1. Figure MT MT + MK K b. 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Data may be preliminary. nBysfcos o agnllklho ausaelse nTbeS.M,M.Tmuuo;M,Mt. MK, Tambuyukon; Mt. MT, S4. Table in listed Low are masl; values 2000 likelihood [?] marginal High Kinabalu; log factors; Bayes on 2. Figure ouainsrcueadmgainmdl vlae sn IRT-.Mdlrnsaebased are ranks Model MIGRATE-N. using evaluated models migration and structure Population < 00masl. 2000 23 Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. t abyknfloe ylweeainM.Knbl ohg lvto t Kinabalu. elevation Mt. low elevation to high Tambuyukon to Mt. Kinabalu file be elevation can Mt. Hosted high ancestry elevation from each’s low arranged of by much are followed how Tambuyukon Individuals showing Mt. shading cluster. with each individual to single attributed a represents line horizontal Each 5. Figure of proportion heterogeneous-tropical-montane-environments-in-a-bornean-endemic-small-mammal the elevation each grey). for image5.emf (dark indicate 2 charts cluster pie mitochondrial and pie file SNP from grey) Mitogenome Hosted (light haplotype grey). 1 a above. (dark cluster with clusters 2 to sampled SNP assigned and treeshrews ancestry and grey) of number (light line the 1 transect elevation, haplogroup each each below for shown indicate, elevation charts per haplogroups drial 4. Figure to shown not are haplogroups two Colors substitutions. the bp that 40. Note exceeds 186 differences by blue). of separated MK, number are orange; the and (MT, where mountains scale cases two in the except to haplotypes correspond between differences pair base 3. Figure lse ebrhpbsdo ACadSRCUEaaye for analyses STRUCTURE and DAPC on based membership Cluster lvtoa rfie fM.Knbl n t abyknwt h itiuino mitochon- of distribution the with Tambuyukon Mt. and Kinabalu Mt. of profiles Elevational einjiigntoko 4mtgnm eune.Dse ie ersn h ubrof number the represent lines Dashed sequences. mitogenome 34 of network joining Median vial at available https://authorea.com/users/313978/articles/444406-high-gene-flow-across- 24 a) K and 2 = b) K 3. = Posted on Authorea 22 Apr 2020 — CC BY 4.0 — https://doi.org/10.22541/au.158757034.48320167 — This a preprint and has not been peer reviewed. Data may be preliminary. heterogeneous-tropical-montane-environments-in-a-bornean-endemic-small-mammal with black, in image8.emf shown are masl, study 1400 this IPCC. file in [?] by Hosted sampled circles. indicates projected Transects white as grey by change lines. dark indicated climate dashed habitat; mild locations by assuming treeshrew sampling demarcated 2100 mountain are in current areas habitat is Protected treeshrew which mountain potential masl, is 900 which [?] shows grey 7. Figure heterogeneous-tropical-montane-environments-in-a-bornean-endemic-small-mammal image7.emf 4%. explains file PC2 Hosted variance; of 7% explains PC1 orange. 6. Figure heterogeneous-tropical-montane-environments-in-a-bornean-endemic-small-mammal image6.emf siae onantesrwhbtti h er20 Easmn idIC cnro.Light scenarios. IPCC mild assuming CE 2100 year the in habitat treeshrew mountain Estimated C ltwt niiul agto t iaausae nbu n t abyknin Tambuyukon Mt. and blue in shaded Kinabalu Mt. on caught individuals with Plot PCA vial at available at available at available https://authorea.com/users/313978/articles/444406-high-gene-flow-across- https://authorea.com/users/313978/articles/444406-high-gene-flow-across- https://authorea.com/users/313978/articles/444406-high-gene-flow-across- 25