Journal of Biogeography (J. Biogeogr.) (2016) 43, 1412–1424

ORIGINAL Multiscale partitioning of small mammal ARTICLE b-diversity provides novel insights into the Quaternary faunal history of Qinghai– and Zhixin Wen1, Qisen Yang1,*, Qing Quan1,2, Lin Xia1, Deyan Ge1 and Xue Lv1,2

1Key Laboratory of Zoological Systematics and ABSTRACT Evolution, Institute of Zoology, Chinese Aim To assess the validity of four hypothesized drivers (Quaternary climate, Academy of Sciences, Beijing 100101, China, 2 niche conservatism, contemporary climate, spatial configuration) of small College of Life Science, University of Chinese – Academy of Sciences, Beijing 100049, China mammal beta diversity in the Qinghai Tibetan Plateau (QTP) and the Hengduan Mountains (HDM). Location QTP and HDM of China. Methods We partitioned the beta diversity of small mammals in QTP and HDM into the spatial turnover and nestedness components at the regional (longitudinal/latitudinal zones) and grid (1° 9 1°) scales. Regional beta diver- sity was evaluated by calculating the multiple-site dissimilarities and the dis- tance-dissimilarity relationships. We examined the relative effects of geographical distance, environmental difference, habitat diversity, geographical isolation and Quaternary climate stability on the beta diversity patterns. Results The overall beta diversity in all longitudinal/latitudinal zones of both regions was primarily driven by spatial turnover, longitudinal nestedness pat- terns were almost non-existent in QTP. Turnover was stronger in the latitudi- nal direction of QTP and in the longitudinal direction of HDM, which corresponded to the general topography of each region. At the grid scale, higher turnover was primarily concentrated in mountainous areas. Turnover was highly correlated with geographical distance and environmental difference in both regions, and geographical isolation was another strong predictor of turnover in HDM. Habitat diversity independently explained most of the varia- tion in nestedness of HDM. Main conclusions Spatial turnover is the primary cause of the small mammal beta diversity in QTP and HDM. Three non-exclusive mechanisms including the historic effect of past glaciation, contemporary climate and spatial configu- ration of the landscape might act in combination to shape the beta diversity patterns in QTP and HDM, particularly the directional patterns. Our results challenge the prevailing view that the current distribution of QTP fauna is pri- marily explained by westward post-glacial recolonization, and support the alter- native idea that QTP retained considerable refugia and even centres of origin during the Quaternary glaciations.

*Correspondence: Qisen Yang, Institute of Keywords Zoology, Chinese Academy of Sciences, No. 1 Contemporary climate, glaciations, Hengduan Mountains, nestedness, Qing- Beichen West Road, Chaoyang District, Beijing hai–Tibetan Plateau, Quaternary climatic oscillations, recolonization, small 100101, China E-mail: [email protected] mammals, spatial configuration, spatial turnover

1412 http://wileyonlinelibrary.com/journal/jbi ª 2016 John Wiley & Sons Ltd doi:10.1111/jbi.12706 Beta diversity partitioning reveals Quaternary mammalian faunal history

turnover by promoting speciation and endemism, the glacial INTRODUCTION extinction and post-glacial recolonization due to the large Since the seminal work of Whittaker (1960), ecologists have oscillations in past climates may cause prominent nested recognized three components of species diversity (alpha, beta subset patterns in the composition of species (Dobrovolski and gamma diversity). In the broadest definition, beta diver- et al., 2012). As a consequence of this decomposition sity is generally applied to any measure of variation in the approach, the historical scenarios of how beta diversity pat- identities of species among sites (Anderson et al., 2011). terns formed in some taxa (e.g. global patterns of freshwater Therefore, an understanding of the patterns and underlying fishes and amphibians: Leprieur et al., 2011 and Baselga mechanisms of beta diversity is crucial to explain many eco- et al., 2012; European mammals: Svenning et al., 2011; New logical phenomena, from metacommunity dynamics (Soini- World vertebrates: Dobrovolski et al., 2012; and western nen et al., 2007a,b; Heino, 2013) to the origin and Mediterranean butterflies: Dapporto et al., 2014) were finely distribution of global biodiversity (Buckley & Jetz, 2008). detailed. To date, only a small number of studies have Because of the significance of beta diversity in a wide array focused on East Asia (e.g. Srinivasan et al., 2014), which of theoretical issues, in recent decades the increase in the contains two major biogeographical regions (Palearctic and number of studies exploring the deterministic and stochastic Oriental) and is the origin of many extant animals (Mayr, drivers of beta diversity has been dramatic (Shmida & Wil- 1963). Moreover, most previous studies on the partitioning son, 1985; Soininen et al., 2007a,b; Qian & Ricklefs, 2012), of beta diversity were conducted at a single scale. Therefore, with different definitions and measures of beta diversity con- multiscale examinations of the patterns of beta diversity are stantly being proposed (e.g. Tuomisto, 2010a,b; Anderson required to obtain more thorough insights into the mecha- et al., 2011). nisms behind (Barton et al., 2013). Among the theories used to explain beta diversity patterns, The Qinghai–Tibetan Plateau (QTP) and the Hengduan the theories on dispersal limitations (i.e. limited dispersal Mountains (HDM) are two adjacent regions located in abilities of species and geographical and environmental barri- south-west China, and HDM is a world hotspot of biodiver- ers to dispersal) and niche filtering have received the most sity (Mittermeier et al., 1998). Although QTP and HDM are attention in previous empirical studies. This attention indi- close geographically, the Quaternary climatic and faunal his- cates that both mechanisms play a significant role in struc- tories are thought to be largely different. For the diversity of turing beta diversity, but that the relative contributions may QTP, the prevailing view is that mass extinction of species vary substantially among taxa and regions (e.g. Buckley & had occurred several times in most regions of the plateau Jetz, 2008; Qian & Ricklefs, 2012). Nevertheless, historical during the Last Glacial Maximum (LGM) and other glacia- processes are equally important for their influence on pat- tions and that, a narrow zone at the eastern edge of QTP terns of beta diversity, but far fewer studies have explored with HDM served as a glacial refugium and sources of west- these mechanistic processes (but see Dobrovolski et al., 2012; ward interglacial and post-glacial recolonization (Zhang, Gavilanez & Stevens, 2013; Kubota et al., 2014). This smaller 2002; Qu et al., 2010). However, for HDM, most researchers number of studies is most probably because disentangling maintain that this large mountainous region harboured the roles of current and historical factors remains a difficult many climatically suitable habitats in low elevational areas task given that climatic conditions co-vary, and species typi- throughout the Quaternary. Thus, these refugia retained a cally follow more than one evolutionary path. large number of species from QTP and were the centres of Recently, with the methodological advance in the parti- subsequent speciation (Chen et al., 2010). Additionally, the tioning of beta diversity, this situation has changed; the total spatial configuration of the landscape also differs between beta diversity can be additively decomposed into two com- the two regions, which is primarily evident in the orientation ponents, which represent the pure spatial turnover and nest- of the mountain ranges (QTP: longitudinal orientation; edness (Baselga, 2010). A typical spatial turnover pattern HDM: latitudinal orientation). Based on these different his- occurs when the species at one site are replaced by different torical scenarios and spatial configurations of the landscape, species at another site (Gaston & Blackburn, 2000), with dif- we expected different patterns of spatial turnover and nested- ferent pools of species constituting the sources of the indi- ness of the taxa between QTP and HDM, particularly for vidual assemblages. Spatial turnover can be attributed to those in the latitudinal and longitudinal directions. Alterna- many causes, including dispersal limitations and niche filter- tively, if niche conservatism (Wiens & Donoghue, 2004) con- ing along climatic gradients (Qian et al., 2009; Dapporto stitutes a primary mechanism for the distribution of small et al., 2014). In contrast to turnover, nestedness is a pattern mammals in QTP and HDM, a nestedness pattern should be in which the biota present in one site are a strict subset of evident along the latitudinal gradient of both regions because the biota that occur at another more species-rich site, which of the failure of species to colonize the high-latitude regions may result from interspecific variation in environmental tol- (Svenning et al., 2011). erance and habitat nestedness (Ulrich et al., 2009). More- In this study, we partitioned the beta diversity of non- over, the historical drivers that lead to spatial turnover and volant small mammals (hereafter referred to as small mam- nestedness are different. Whereas the relatively stable climatic mals, including the orders Erinaceomorpha, Soricomorpha, conditions during glacial-interglacial cycles may cause spatial Scandentia, Lagomorpha and Rodentia) in QTP and HDM

Journal of Biogeography 43, 1412–1424 1413 ª 2016 John Wiley & Sons Ltd Z. Wen et al. into the spatial turnover and nestedness components, with particularly in the latitudinal direction. The environmental the patterns examined at both the regional and grid scales. difference is also expected to exert a strong influence on the According to the widely accepted faunal histories of QTP spatial patterns. At the grid scale, the highest turnover is pre- and HDM and their respective spatial configurations, we dicted in the mountainous areas due to the wide range of developed and tested four alternative hypotheses regarding climatic conditions that occur over short distances (Baselga the potential drivers of small mammal beta diversity in QTP et al., 2012). and HDM: 4. Spatial configuration hypothesis. The spatial configura- 1. Quaternary climate hypothesis. Beta diversity pattern is a tion of regions determines beta diversity by influencing the product of the Quaternary climatic oscillations (Leprieur dispersal of species across landscapes (Nekola & White, et al., 2011). At the regional scale, because the current QTP 1999). Accordingly, this hypothesis predicts that latitudinal fauna is explained primarily by westward post-glacial recolo- turnover should be stronger than longitudinal turnover in nization, this hypothesis predicts strong nestedness and weak QTP but weaker than longitudinal turnover in HDM, spatial turnover, particularly in the longitudinal direction. By because major mountain ranges of the two regions extend in contrast, for HDM which served as a glacial refugium and a opposite directions. Additionally, a large proportion of the centre of speciation, the primary contribution to small mam- variation in turnover can be explained by geographical mal beta diversity should be from spatial turnover in either distance. direction. In addition to Quaternary climate stability, geo- graphical isolation is expected to be an important process in MATERIALS AND METHODS shaping the turnover patterns in HDM, because historically, the substantial number of isolated mountain ranges and val- Study Areas leys would favour allopatric speciation (Qian et al., 2013). At the grid (small) scale, the highest turnover is most likely to The geographical and climatic characteristics differ greatly occur in the mountainous areas that typically acted as local between QTP and HDM (Fig. 1). QTP is the highest plateau refugia during the glaciations. on earth and contain a group of mountain ranges oriented 2. Niche conservatism hypothesis. The QTP and HDM fau- roughly in the longitudinal direction. A large part of QTP nas originated primarily from the tropics and with strong lies at an elevation above 5000 m, including Mount Everest, niche conservatism so that a latitudinal nestedness pattern is the world’s tallest peak (8848 m). QTP is bounded to the predicted in both regions. north by the Tarim Basin, reaches south to the Himalayan 3. Contemporary climate hypothesis. Beta diversity is deter- Mountains and extends westward to the Pamirs. Under the mined by the contemporary climate (Qian et al., 2009), control of the plateau climate, extensive areas of the plateau because most climatic factors (e.g. temperature and rainfall) interior have a very dry and cool environment. However, the vary with latitude, spatial turnover should be the dominant climate at the eastern periphery of QTP is much milder, with component at the regional scale in QTP and HDM, steppes and mountains being the dominant landscapes.

(a) 80 E 100 E 120 E

50 N (c) N

Figure 1 (a) Major mountain ranges and basins in the Qinghai–Tibetan Plateau and the Hengduan Mountains (Aitoff’s 40 N projection): 1. , 2. Tarim 2 1 3 4 Hengduan Mountains Basin, 3. Altun Mountains, 4. , 5. Kekexili Mountains, 6. Bayan 1 5 6 (b) 7 16 Har Mountains, 7. Har goolun Range, 8. , 9. Gangdise 8 9 15 Mountains, 10. Nyainqentanglha Mountains, 30 N 10 14 11. Himalayan Mountains, 12. Yunling 11 13 17 Mountains, 13. Shaluli Mountains, 14. 12 Elevation (m) Daxue Mountains, 15. Qionglai Mountains, < 200 16. Minshan Mountains, 17. Ta-liang 18 200 - 500 3000 - 4000 Qinghai-Tibetan Plateau Mountains and 18. Wuliang Mountains; (b) 500 - 1000 4000 - 5000 location of the Qinghai–Tibetan Plateau, 20 N 1000 - 2000 5000 - 6000 2000 - 3000 > 6000 which was rasterized into 279 grid cells 0 300 600 900 1,200 (1° 9 1°); and (c) location of the KM Hengduan Mountains, which was rasterized 80 E 100 E 120 E into 89 grid cells.

1414 Journal of Biogeography 43, 1412–1424 ª 2016 John Wiley & Sons Ltd Beta diversity partitioning reveals Quaternary mammalian faunal history

Moreover, subtropical habitats are found in many lowland attributions for the cells that were at the boundary between regions of the south and southeast QTP (Lei et al., 2014). QTP and HDM. As a result, our study contained a total of HDM is located to the south-east of QTP and is a typical 279 QTP and 89 HDM grid cells. mountainous region characterized by a series of parallel mountain ranges and rivers running south to north. This Environmental and geographical data region has an enormous range in elevation of 7480 m, from the Yuanjiang River at the south-eastern fringe (76 m) to the To quantify the effects of the contemporary climate on the peak of the Gongga Mountain (7556 m). Most regions of beta diversity of QTP and HDM, we measured the following HDM are simultaneously influenced by the subtropical mon- eight environmental variables for each grid cell: (1) mean soon and plateau climates. These geographical and climatic annual temperature (MAT, °C), (2) mean temperature of the features result in a large number of natural habitats and a warmest month (MWT, °C), (3) mean temperature of the complicated topography in HDM, particularly along the ele- coldest month (MCT, °C), (4) temperature seasonality vational gradients (Zhang et al., 1997). (TS = MWTÀMCT, °C), (5) mean annual precipitation (MAP, mm), (6) precipitation seasonality (precipitation dif- ference between the wettest and driest month, PS, mm), (7) Species distribution data mean annual potential evapotranspiration (PET, mm), and The data on the distribution of small mammals in QTP and (8) annual normalized difference vegetation index (NDVI). HDM were compiled based on museum records (Mammal These parameters are robust in explaining the broad-scale pat- Collections of Institution of Zoology, Chinese Academy of terns of mammalian diversity (Qian et al., 2009; Svenning Sciences; Zoological Museum of China West Normal Univer- et al., 2011). The data for MAT, MWT, MCT, MAP and PS sity), scientific databases (Animal Resource Database of were from the WorldClim 1.4 database, the PET data were of Kunming Institution of Zoology, Chi- from the CGIAR-CSI Global PET Database (1 km 9 1 km, nese Academy of Sciences, http://www.swanimal.csdb.cn/), http://www.cgiar-csi.org/) (Zorner et al., 2008), and the NDVI field survey records and information from the specialized lit- data were derived from the 1998 monthly data layers in the erature (see Appendix S1 in Supporting Information). Thematic Database for Human-Earth System. We then con- Because the information on distribution in these sources was ducted principal component analyses on the correlation primarily documented at the county level, two county-level matrices of the environmental variables separately for QTP species presence/absence data sets were created for QTP (141 and HDM, to reduce the co-linearity among variables and the species) and HDM (197 species). Notably, using such data number of variables in subsequent analyses (Qian et al., sets on the distribution may introduce problems because of 2009). For both QTP and HDM, the first four principal com- incomplete inventories caused by counties that were inevita- ponents (PCs) accounted for more than 98% of the total vari- bly under-sampled (Yang et al., 2013). To minimize the ance in the eight variables (Appendix S2). The environmental effects of geographical sampling bias, we compared mam- difference (ENVdif) between each pair of cells in each region, malian habitat preferences, physiological characters and alti- as a single variable, was calculated as the Euclidean distance in tudes that were documented in the literature with the county the four-dimensional space of the first four PC axes. climate (extracted from the WorldClim 1.4 database, http:// Habitat diversity (number of habitat types; Stein & Kreft, www.worldclim.org/) (Hijmans et al., 2005), vegetation (The- 2015) and geographical isolation are two important corre- matic Database for Human-Earth System, http://www. lates of the beta diversity patterns of vertebrates. Within the data.ac.cn/) and topography (CGIAR-CSI SRTM 90-m Digi- same geographical region, the dissimilarities of species tal Elevation Data System, http://srtm.csi.cgiar.org/) data to among localities tend to decrease with the diversity of differ- verify the information on species occurrence in the counties ent habitat types in each locality, because of the potential for which were inadequately investigated (i.e. detailed checklists more shared species that are derived from the similar niche were unavailable). The values in all data sets were compiled processes (Qian & Ricklefs, 2012). Moreover, geographical at the resolution of 1 km 9 1 km. For calibration, the data isolation affects beta diversity primarily by decreasing the sets were finally cross-checked by two experienced tax- rates of species dispersal among sites (Melo et al., 2009). In onomists, and all dubious records were removed. this study, we used the altitudinal range (ALTrange, m) and

We used ArcGIS 9.3 to transform the county-level species mean altitude (ALTmean, m) to measure the habitat diversity distributions into gridded distributions. QTP and HDM were (Stein & Kreft, 2015) and geographical isolation (Leprieur rasterized with a cell size of 1° 9 1°, and for each small et al., 2011) of a grid cell respectively. The elevational data mammal species, the presence in a cell was recorded when were obtained from the SRTM 90-m Digital Elevation Data the counties in which the species was distributed covered System. more than 50% of the cell area (Dobrovolski et al., 2012), For the final explanatory factor, we calculated the annual except for cells on the border of the grid (the presence of a temperature difference between the present day and LGM species was recorded when the distributed counties covered (TEMdif, °C), with a high value indicating lower Quaternary the cell area). A comprehensive assessment of the faunas, climate stability (Leprieur et al., 2011; Baselga et al., 2012). environments, topography and geohistory determined the The source for LGM temperature was WorldClim 1.4.

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performed with 1000 permutations to determine the statisti- Beta diversity decomposition and pattern cal significance and to obtain the model R2 (Legendre et al., examination 1994). Following (Baselga, 2010), we calculated three beta diversity Last, we used hierarchical partitioning analyses to deter- measures that formed the basis of our analyses: the overall mine the relative importance of each factor in explaining the beta diversity (Sørenson dissimilarity, bsor), and its spatial spatial patterns of small mammals in QTP and HDM. For species turnover (Simpson dissimilarity, bsim) and species each variable in our model, the hierarchical partitioning gain/loss (nestedness-driven dissimilarty, bnes) components. measured both the independent effect and joint effect with The patterns of beta diversity were examined at the regio- other variables, with the independent effect representing the nal and grid scales. For regional beta diversity, we first com- relative importance (Chevan & Sutherland, 1991). All analy- puted the multiple-site dissimilarities (bMulti-sor, bMulti-sim ses were performed in the R environment (3.1; R Develop- and bMulti-nes) of small mammals in QTP and HDM to ment Core Team, 2014), using the packages ‘betapart’ quantify the relative effects of turnover and nestedness on (Baselga & Orme, 2012), ‘ecodist’ (Goslee & Urban, 2007) regional compositional heterogeneity (Baselga, 2013). The and ‘hier.part’ (Walsh & Mac Nally, 2013). beta diversity in the latitudinal and longitudinal directions was also examined with the multiple-site measures to test the RESULTS first three hypotheses (e.g. Quaternary climate hypothesis: strong longitudinal nestedness in QTP). To this end, QTP Beta diversity at the regional scale was divided into four longitudinal (73°–83°E, 83°–89°E, 89°–95°E and 95°–105°E) and three latitudinal (26°–31°N, For the entire QTP, overall beta diversity of small mammals ° ° ° ° 31 –36 N, and 36 –40 N) zones, and HDM was divided into was primarily driven by spatial turnover (bMulti-sim = 0.98), two longitudinal (97°–101°E and 101°–106°E) and three lati- with nestedness accounting for only a small proportion ° ° ° ° ° ° tudinal (21 –26 N, 26 –30 N and 30 –35 N) zones. For (bMulti-nes = 0.01). A similar pattern for bMulti-sim and bMulti-

QTP, because the numbers of grid cells varied among the nes also emerged in all QTP longitudinal/latitudinal zones, longitudinal/latitudinal zones, we resampled 64 cells (the cell and turnover was dominant throughout the region (Table 1). number of the smallest zone) from each zone 100 times and Positive distance-bPair-sim relationships were found in all the then calculated the mean multiple-site dissimilarities. The longitudinal/latitudinal zones (Fig. 2b–e, k–m). However, number of cells resampled in each zone of HDM was 26. As because the regression slopes were significantly greater in the the second measure of the regional beta diversity, we con- latitudinal direction than in the longitudinal direction (inde- structed the pairwise dissimilarity matrices for each of the pendent-samples t-test, df = 5, P = 0.005; Table 1), the lati- three beta diversity measures (bPair-sor, bPair-sim and bPair- tudinal turnover was higher than the longitudinal turnover. nes) and plotted the distance-dissimilarity linear relation- The negative distance-bPair-sne relationships in all the longitu- ships (i.e. bPair-sim and bPair-nes as a function of geographi- dinal zones indicated that in the latitudinal direction, turn- cal distance between grid cells) for each longitudinal/ over was so high that distant cells did not constitute nested latitudinal zone. The slopes and intercepts were used to subsets. In the longitudinal direction, a negative relationship compare the beta diversity between the latitudinal and lon- was revealed between bPair-nes and geographical distance gitudinal directions in order to test the spatial configura- in two of three latitudinal zones, although the only tion hypothesis. positive slope for the 31°–36°N zone was weak (Table 1, To assess the beta diversity patterns at the grid scale, we Fig. 2f–i, n–p). calculated the beta diversity for each cell (bGrid-sim and bGrid- When the overall beta diversity of small mammals in nes) as the mean of the dissimilarity values between a focal HDM was disentangled, spatial turnover (bMulti-sim = 0.924) cell and each of the adjacent cells. This method is widely made a much greater contribution to regional faunal hetero- employed in examining the compositional heterogeneity at geneity than nestedness (bMulti-nes = 0.025). Turnover was smaller scales (Melo et al., 2009; Dobrovolski et al., 2012), the prevailing process within all the HDM longitudinal/lati- which enabled us to test the predictions of the Quaternary tudinal zones (Table 1). As indicated by the regressions, climate and contemporary climate hypotheses (higher turn- bPair-sim increased with geographical distance in all the longi- over in mountainous areas). tudinal/latitudinal zones (Fig. 3b,d,g,i,k), and a higher rate was found in the latitudinal direction (regression slope: df = 3, P = 0.078). However, because of the significantly lar- Drivers of beta diversity in QTP and HDM ger intercepts for the latitudinal zones (df = 3, P = 0.019), We used multiple regressions on the distance matrices the turnover in the longitudinal direction was higher than (MRM) to estimate the portion of the total variances in that in the latitudinal direction (Table 1). Still, the negative b b Pair-sim and Pair-nes of the entire QTP and HDM that could distance-bPair-sne relationships in all longitudinal zones indi- be explained by the five environmental and geographical fac- cated that in the latitudinal direction, turnover was so high tors, including geographical distance (GEOdis, km), ENVdif, that distant cells did not form nested subsets (Fig. 3c,e). By

ALTrange, ALTmean and TEMdif. Each regression analysis was contrast, although the longitudinal nestedness was weaker

1416 Journal of Biogeography 43, 1412–1424 ª 2016 John Wiley & Sons Ltd Beta diversity partitioning reveals Quaternary mammalian faunal history

Table 1 Regional spatial turnover and nestedness of non-volant small mammals in each longitudinal/latitudinal zone of the Qinghai– Tibetan Plateau (QTP) and the Hengduan Mountains (HDM). Beta diversity was quantified with the multiple-site dissimilarity (bMulti- À1 sim and bMulti-nes) and the slope (1000 km ) and intercept of the regression of distance-dissimilarity linear relationship (pairwise dissimilarities bPair-sim and bPair-nes as a function of geographical distance, P-value of each relationship was evaluated based on 1000 permutations).

Multiple-site dissimilarities Distance-bPair-sim relationship Distance-bPair-sne relationship

bMulti-sim bMulti-nes Slope Intercept P Slope Intercept P

QTP Longitudinal zones 73°–83°E 0.923 0.03 1.1 À0.02 < 0.01 À0.23 0.24 < 0.01 83°–89°E 0.891 0.058 0.744 À0.057 < 0.01 À0.056 0.248 < 0.01 89°–95°E 0.904 0.049 0.716 0.045 < 0.01 À0.15 0.274 < 0.01 95°–105°E 0.932 0.02 0.734 0.091 < 0.01 À0.11 0.156 < 0.01 Latitudinal zones 26°–31°N 0.89 0.064 0.331 0.205 < 0.01 À0.062 0.277 < 0.01 31°–36°N 0.876 0.076 0.278 0.088 < 0.01 0.01 0.258 0.079 36°–40°N 0.902 0.051 0.295 0.162 < 0.01 À0.012 0.187 < 0.01 HDM Longitudinal zones 97°–101°E 0.774 0.079 0.724 À0.039 < 0.01 À0.017 0.117 0.055 101°–106°E 0.777 0.058 0.563 À0.007 < 0.01 À0.045 0.109 < 0.01 Latitudinal zones 21°–26°N 0.624 0.134 0.262 0.051 < 0.01 0.136 0.053 < 0.01 26°–30°N 0.613 0.125 0.327 0.032 < 0.01 0.237 0.019 < 0.01 30°–35°N 0.694 0.118 0.494 0.041 < 0.01 0.226 0.041 < 0.01

than the turnover, as indicated by the smaller slopes and Patterns in relation to environmental and intercepts (Table 1), a moderately strong, positive relation- geographical variables ship was found between bPair-nes and geographical distance in each latitudinal zone, showing that clear patterns of species We regressed bPair-sim for small mammals of QTP against nestedness occurred in the longitudinal direction of HDM GEOdis, ENVdif, ALTrange, ALTmean and TEMdif simultane- (Fig. 3h,j,l). ously, and these variables together explained 36.5% of the total variation. According to hierarchical partitioning analy- ses, the two strongest predictors GEO and ENV indepen- Beta diversity at the grid scale dis dif dently accounted for 18.1% and 9.9% of the variation in b b We mapped the mammalian Grid-sim and Grid-nes for QTP. bPair-sim respectively. By comparison, the explanatory power b Grid-sim was generally low in a substantial proportion of the of the full model was weak when applied to bPair-nes, and the cells, whereas relatively high values were observed at the east- model explained only 5.6% of the total variation. The contri- ern edge of QTP, bordering on the north-east of HDM. butions of all factors to the spatial pattern of bPair-nes in Another region with a slightly higher bGrid-sim was the Nyain- QTP were negligible (Table 2). b b qentanglha Mountains (Fig. 4a). In contrast to Grid-sim, Grid-nes In HDM, the proportion of variation in bPair-sim that was of small mammals presented a more heterogeneous spatial explained by the five explanatory variables reached 84.0%, pattern. The high values were primarily located in mountain- with most of the explanatory power deriving from GEOdis ous areas, including the eastern Altun Mountains, the west- (59.5%) and ALTmean (16.7%). As for bPair-nes, the full model ern Tanggula Mountains, the western Gangdise Mountains, explained 19.8% of the total variation. The hierarchical parti- the Nyainqentanglha Mountains and the Himalayan Moun- tioning analyses showed that ALTrange had the largest effect b tains. Additionally, we found relatively high Grid-nes values at on the bPair-nes pattern, uniquely explaining 14.3% of the the southern edge of the Tarim Basin. (Fig. 4b). total variation (Table 2).

In HDM, bGrid-sim was low in most cells, with slightly higher values found in the regions between the Daxue DISCUSSION Mountains and the Shaluli Mountains and along the Jinsha River watershed and the Yunling Mountains (Fig. 5a). The China is a country with mega-biodiversity and is an impor- areas with high bGrid-nes values included the Yunling Moun- tant provider of genetic resources to global biodiversity. In tains and along the Jinsha River and the Yuanjiang River many regions of China, QTP and HDM have received much (Fig. 5b). attention from ecologists because of their significant roles in

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Latitudinal direction Longitudinal direction (a) 83-89°E 89-95°E 95-105°E (j) 36-40°N 31-36°N 26-31°N

1.0 (b) 1.0 (f) 1.0 (k) 1.0 (n) 0.8 73-83°E 0.8 73-83°E 0.8 0.8 26-31°N R2=0.60 R2=0.14 R2=0.01 0.6 0.6 0.6 0.6

0.4 0.4 0.4 0.4 βPair-sim βPair-sim βPair-sne βPair-sne 0.2 0.2 0.2 26-31°N 0.2 R2=0.21 0 0 0 0 0 0.5 1.0 1.5 2.0 2.5 3.0 0 0.5 1.0 1.5 2.0 2.5 3.0 0 0.5 1.0 1.5 2.0 2.5 3.0 0 0.5 1.0 1.5 2.0 2.5 3.0 1.0 (c) 1.0 (g) 1.0 (l) 1.0 (o) 83-89°E 0.8 0.8 83-89°E 0.8 0.8 31-36°N R2=0.44 R2=0.01 R2=5.1×10-4 0.6 0.6 0.6 0.6

0.4 0.4 0.4 0.4 βPair-sim βPair-sim βPair-sne βPair-sne 0.2 0.2 0.2 31-36°N 0.2 R2=0.30 0 0 0 0 0 0.5 1.0 1.5 2.0 2.5 3.0 0 0.5 1.0 1.5 2.0 2.5 3.0 0 0.5 1.0 1.5 2.0 2.5 3.0 0 0.5 1.0 1.5 2.0 2.5 3.0 1.0 (d) 1.0 (h) 1.0 1.0 (p) 0.8 89-95°E 0.8 89-95°E 0.8 (m) 0.8 36-40°N R2=0.48 R2=0.06 R2=2.3×10-3 0.6 0.6 0.6 0.6

0.4 0.4 0.4 0.4 βPair-sim βPair-sim βPair-sne βPair-sne 0.2 0.2 0.2 36-40°N 0.2 R2=0.43 0 0 0 0 0 0.5 1.0 1.5 2.0 2.5 3.0 0 0.5 1.0 1.5 2.0 2.5 3.0 0 0.5 1.0 1.5 2.0 2.5 3.0 0 0.5 1.0 1.5 2.0 2.5 3.0 Geographical distance (1000 km) 1.0 (e) 1.0 (i) 95-105°E 0.8 0.8 95-105°E R2=0.66 R2=0.13 0.6 0.6

0.4 0.4 βPair-sim βPair-sne 0.2 0.2

0 0 0 0.5 1.0 1.5 2.0 2.5 3.0 0 0.5 1.0 1.5 2.0 2.5 3.0 Geographical distance (1000 km)

Figure 2 Increase in spatial turnover (bPair-sim) and nestedness (bPair-nes) pairwise dissimilarities with geographical distance (km) between grid cells (1° 9 1°) for non-volant small mammals in four longitudinal (bPair-sim:b–e; bPair-nes:f–i) and three latitudinal (bPair- sim:k–m; bPair-nes:n–p) zones of the Qinghai–Tibetan Plateau. The lines indicate the simple linear regressions, and the slopes and intercepts are presented in Table 1.

the generation and sustainment of biodiversity, particularly taxonomic groups (but see babblers and murid rodents in during the Quaternary climatic oscillations (Wang et al., Srinivasan et al., 2014). With the separation of the turnover 2010; Hofmann, 2012). Although previous studies have and nestedness components at multiple scales, our central demonstrated how the cyclical variations in climate and gla- goal was to assess the validity of four hypothesized drivers of cier coverage influenced the evolution and population small mammal beta diversity in QTP and HDM. On the dynamics of QTP and HDM taxa, most of these studies used basis of the results, the contemporary climate and spatial molecular methods with a single species or several sibling configuration of the landscape were influential in both species serving as the objects of interest (e.g. Liu et al., 2006; regions, whereas the Quaternary climate and niche conser- Chen et al., 2010). Moreover, few macroecological studies vatism hypotheses had limited predictive power for the have examined the processes and mechanisms for large detected patterns in QTP.

1418 Journal of Biogeography 43, 1412–1424 ª 2016 John Wiley & Sons Ltd Beta diversity partitioning reveals Quaternary mammalian faunal history

Latitudinal direction (a) 97-101°E 101-106°E

1.0 (b) 1.0 (c) 1.0 (d) 1.0 (e) 0.8 97-101°E 0.8 97-101°E 0.8 101-106°E 0.8 101-106°E 0.6 R2=0.88 0.6 R2=4.3×10-3 0.6 R2=0.87 0.6 R2=0.05

0.4 0.4 0.4 0.4 βPair-sim βPair-sne βPair-sim βPair-sne 0.2 0.2 0.2 0.2

0 0 0 0 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Geographical distance (1000 km) (f) Longitudinal direction

1.0 1.0 1.0 1.0 1.0 1.0

30-35°N (g) (h) (i) (j) (k) (l) 0.8 21-26°N 0.8 21-26°N 0.8 26-30°N 0.8 26-30°N 0.8 30-35°N 0.8 30-35°N 2 2 2 0.6 R2=0.29 0.6 R2=0.08 0.6 R2=0.32 0.6 R =0.18 0.6 R =0.60 0.6 R =0.22

0.4 0.4 0.4 0.4 0.4 0.4 26-30°N βPair-sim βPair-sim βPair-sne βPair-sne βPair-sim βPair-sne 0.2 0.2 0.2 0.2 0.2 0.2

0 0 0 0 0 0 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 21-26°N Geographical distance (1000 km)

Figure 3 Increase in spatial turnover (bPair-sim) and nestedness (bPair-nes) pairwise dissimilarities with geographical distance (km) between grid cells (1° 9 1°) for non-volant small mammals in two longitudinal (bPair-sim: b,d; bPair-nes: c,e) and three latitudinal (bPair- sim: g,i,k; bPair-nes: h,j,l) zones of the Hengduan Mountains. The lines indicate the simple linear regressions, and the slopes and intercepts are presented in Table 1.

βGrid-sim (a)

0 - 0.1 0.1 - 0.2 0.2 - 0.3 0.3 - 0.4 0.4 - 0.5 βGrid-sne 0.5 - 0.6 (b) 0.6 - 0.7

Figure 4 Geographical patterns of (a) spatial turnover (bGrid-sim) and (b) nestedness (bGrid-nes) for non-volant small mammals in the Qinghai–Tibetan Plateau at the grid scale (1° 9 1°). Beta diversity in each cell was calculated as the mean of the dissimilarity values between a focal cell and each of the adjacent cells.

were affected by climatic oscillations, particularly on how Quaternary climate and niche conservatism different taxa responded to the recurrent glaciations and hypotheses interglaciations. A common view is that extremely low tem- Quaternary climatic oscillations are widely acknowledged to peratures and harsh environments characterized most regions have had significant effects on the present-day patterns of of QTP during glaciations, such as LGM. Thus, mass extinc- biodiversity in QTP (Lei et al., 2014). However, a long- tions occurred on the plateau platform, and only some cold- standing debate continues as to the extent that the organisms resistant species with good dispersal abilities were able to

Journal of Biogeography 43, 1412–1424 1419 ª 2016 John Wiley & Sons Ltd Z. Wen et al.

βGrid-sim βGrid-sne (a) (b)

0 - 0.05 0.05 - 0.10 Figure 5 Geographical patterns of (a) 0.10 - 0.15 spatial turnover (bGrid-sim) and (b) 0.15 - 0.20 nestedness (bGrid-nes) for non-volant small mammals in the Hengduan Mountains at the grid scale (1° 9 1°). Beta diversity in each cell was calculated as the mean of the dissimilarity values between a focal cell and each of the adjacent cells.

Table 2 Independent and joint effects (explained variation, %) of geographical distance (GEOdis), environmental difference (ENVdif), altitudinal range (ALTrange), mean altitude (ALTmean) and annual temperature difference between the present day and the Last Glacial Maximum (TEMdif) on spatial turnover (bPair-sim) and nestedness (bPair-nes) pairwise dissimilarities of non-volant small mammals in the Qinghai–Tibetan Plateau (QTP) and the Hengduan Mountains (HDM). The results were calculated based on hierarchical partitioning analyses.

bPair-sim of QTP bPair-nes of QTP bPair-sim of HDM bPair-nes of HDM

Explanatory factor Independent Joint Independent Joint Independent Joint Independent Joint

GEOdis 18.1 8.8 0.9 0.8 59.5 19.9 3.6 0.8 ENVdif 9.9 11.5 1.2 1.6 4.7 9.1 1.3 0.8 ALTrange 3.6 2.5 1.4 0. 5 0.6 À0.5 14.3 À0.5 ALTmean 4.8 5.8 1.9 1.2 16.7 19.7 0.5 0.6 TEMdif 0.1 0.03 0.2 0.1 2.5 3.8 0.1 À0.1 retreat to refugia in HDM and the eastern fringe areas of variety of organisms were widespread in QTP during LGM QTP (Yang et al., 2008; Chen et al., 2010; Qu et al., 2010). and earlier glaciations, including in the central (Wang et al., During the interglacial and post-glacial periods, those surviv- 2010), north-western (Shan et al., 2011) and south-western ing species, together with their descendants, were constant regions (Hofmann, 2012). For small mammals, Tang et al. source of recolonization for the entire QTP from east to (2010) have revealed that the Plateau zokor (Eospalax fonta- west. If this view is true, then we would expect a nestedness nierii) maintained stable populations in several high-altitude pattern in the direction of the presumed recolonization tra- regions in the plateau interior throughout the Quaternary jectory. However, the nestedness component in the longitu- climatic oscillations, possibly because of the relatively com- dinal direction of QTP was almost non-existent (Table 1), fortable subterranean conditions. Even in the Tarim Basin, whereas the turnover was high in all longitudinal/latitudinal which was barely inhabitable due to the particularly dry and zones irrespective of the method (i.e. multiple-site dissimilar- cold climate, a LGM refugium for the Yarkand hare (Lepus ities or distance-dissimilarity relationships) used to examine yarkandensis) has recently been identified on the its south- the beta diversity patterns. From a historical perspective, western margin of the basin. This species of hare lived although the possibility of multiple trajectories could not be through that period mainly by using meltwater from glaciers ruled out which might turn nestedness patterns into segrega- in the Tishan and Kunlun Mountains (Shan et al., 2011). On tion co-occurrence patterns (Fattorini & Ulrich, 2012), our the basis of these collective results, we argue that the prevail- findings provide better support for the minority view that ing view that most extant species in the central and western QTP retained many local refugia and even centres of origin regions of QTP occupy their current ranges through post- that occurred in different parts of QTP during the glacia- glacial recolonization from eastern refugia requires further tions. For example, the relatively high bGrid-sim at the eastern verification, at least for small mammals. In research similar edge of the plateau and in the Nyainqentanglha Mountains to ours, with a deconstruction of the beta diversity of Euro- indicate that local differentiation and diversification might pean mammals, Svenning et al. (2011) have questioned the have occurred at those locations (Fig. 4a). Furthermore, classic source-sink dynamics between northern and southern there is growing evidence showing that multiple refugia of a biotas during the Pleistocene.

1420 Journal of Biogeography 43, 1412–1424 ª 2016 John Wiley & Sons Ltd Beta diversity partitioning reveals Quaternary mammalian faunal history

In HDM, the dominance of spatial turnover corresponded for the contemporary climate hypothesis. The spatial varia- well with the Quaternary evolutionary dynamics of small tion in species composition has often been interpreted as a mammals here. During the glacial-interglacial cycles, HDM product of climatic gradients (Qian & Ricklefs, 2012). In served not only as a mountainous refugium for species QTP and HDM, in our analyses, each of the eight environ- retreating from QTP, but also offered opportunities for mental variables displayed a strong latitudinal gradient (data genetic divergence because of the relatively stable climate not shown) along which the species composition changed as (Zhang, 2002; Chen et al., 2010). As a result of the collision a consequence of species-specific niche requirements. For between the Indian plate and the Eurasian plate, a series of example, with a decreasing trend of mean annual tempera- rugged north–south oriented alpine ridges (often > 5000 m) ture towards the higher latitudes, the cold-adapted mammal gradually formed in HDM, with altitudinal ranges between species might gradually substitute for the warm-adapted ones the tops of mountains and valleys typically greater than in the assemblages, which constitutes a typical pattern of 2000 m (Zhang et al., 1997). For many small mammal spe- spatial turnover. Furthermore, by examining beta diversity at cies, the numerous, isolated valleys that were ice-free the grid scale, we found that the mountainous areas were throughout the Quaternary provided areas for different pop- associated with higher turnover. This finding is consistent ulations of a common ancestor to persist and evolve inde- with the prediction of the contemporary climate hypothesis pendently (Zhang, 2002), which might be an important that the effects of ecological sorting should be strong in mechanism for the rapid species replacement that occurred. mountainous areas in which, tremendous topographical relief A similar situation also occurred high on mountain tops: for and complex terrain offer substantial climatic and habitat millions of years, substantial mountain ranges were spatially heterogeneity within a short distance. Heterogeneity provides separate from one another by deep valleys, thus producing opportunities for niche filtering (Baselga et al., 2012) and many isolated ‘montane islands’ among which gene exchange locations for parapatric speciation (genus Eothenomys: Luo was rare, leading to the differentiation of species (Brown, et al., 2004). 1971). The effects of Quaternary climate stability and geo- Spatial configuration of the landscape that dictates the dis- graphical isolation on the spatial turnover patterns of HDM persal rate of organisms among localities has a large effect on were confirmed by hierarchical partitioning analyses, with beta diversity patterns (Nekola & White, 1999; Soininen et al., geographical isolation as the second strongest predictor of 2007b). The major mountain ranges in QTP (longitudinal ori- bPair-sim. Moreover, geographical isolation that leads to areas entation) and HDM (latitudinal orientation) extend in oppo- of endemism has previously been shown to affect the spatial site directions; these mountain ranges are expected to act as turnover of vertebrates (Leprieur et al., 2011; Qian & Rick- barriers for small mammal dispersal, resulting in stronger spa- lefs, 2012), particularly when dispersal barriers were difficult tial turnover along the latitudinal gradient in QTP and along to surmount, such as those in HDM. the longitudinal gradient in HDM. Our results showed such

The tropical niche conservatism hypothesis has become patterns, and GEOdis explained most of the variation in bPair- one of the leading explanations for broad-scale patterns of sim among the different factors in each region. Thus, the effect biodiversity, particularly to account for the latitudinal gradi- of spatial configuration on the spatial turnover patterns in ent in species richness (Wiens & Donoghue, 2004; Smith QTP and HDM is evident. Similarly, Qian et al. (2005) have et al., 2012). With regard to geographical variation in species suggested that the latitudinally oriented mountain ranges in composition, based on the hypothesis, the predictions are HDM accounted for the high beta diversity of angiosperms that there should be apparent nestedness of species assem- along the longitudinal gradient. Notably, species also clearly blages in the latitudinal direction, provided that most of the exhibited a longitudinal nestedness pattern in HDM. In addi- taxa are of tropical origins and that the niche conservatism tion to spatially constrained dispersal and environmental gra- is strong (Svenning et al., 2011). However, such expectations dients, habitat nestedness (Ulrich et al., 2009) might also play were not fulfilled for QTP or HDM because of the negative a role, because the habitat diversity measured by ALTrange has distance-bPair-sne relationships in all the longitudinal zones of considerable explanatory power on bPair-nes. Most of the eleva- the two regions. This result apparently confirmed that the tional gradients in HDM are located in the subtropics and centres of small mammal origin were not confined only to have similar vertical climate and vegetation characteristics low-latitude regions in QTP or HDM. Alternatively, a con- (with increasing altitude, evergreen broadleaf forest to mixed siderable number of southern-origin taxa might have broadleaf-conifer forest to dark coniferous forest; Zhang expanded far into temperate areas because niches are not et al., 1997). Accordingly, a region with a smaller ALTrange necessarily conservative in mammals (Cooper et al., 2011). typically contains a subset of the habitat types of those that are present in regions with greater relief, and therefore a sub- set of the species there. Contemporary climate and spatial configuration hypotheses CONCLUSIONS In both QTP and HDM, the dominance of spatial turnover in the latitudinal direction (Table 1) and the moderately This study shows that spatial turnover makes a greater con- strong effect of ENVdif on bPair-sim provide explicit support tribution than nestedness to the present-day small mammal

Journal of Biogeography 43, 1412–1424 1421 ª 2016 John Wiley & Sons Ltd Z. Wen et al. beta diversity in QTP and HDM. Three distinct but not Buckley, L.B. & Jetz, W. (2008) Linking global turnover of mutually exclusive mechanisms including the historic effect species and environments. Proceedings of the National of past glaciation, contemporary climate and spatial configu- Academy of Sciences USA, 105, 17836–17841. ration of the landscape might act in combination to shape Chen, W.-C., Liu, S.-Y., Liu, Y., Hao, H.-B., Zeng, B., Chen, the beta diversity patterns in QTP and HDM, particularly S.-D., Peng, H.-Y., Yue, B.-S. & Zhang, X.-Y. (2010) Phy- those in the latitudinal and longitudinal directions. In con- logeography of the large white-bellied rat Niviventer excel- trast to the prevailing view that the current distribution of sior suggests the influence of Pleistocene Glaciations in the QTP fauna is primarily explained by westward post-glacial Hengduan Mountains. Zoological Science, 27, 487–493. recolonization, our results support the alternative idea that Chevan, A. & Sutherland, M. (1991) Hierarchical Partition- QTP retained considerable refugia and even centres of origin ing. The American Statistician, 45,90–96. that occurred in different regions of QTP during the Quater- Cooper, N., Freckleton, R.P. & Jetz, W. (2011) Phylogenetic nary glaciations. Clearly, the understanding of the QTP conservatism of environmental niches in mammals. Pro- mammalian faunal history would be immensely strengthened ceedings of the Royal Society B: Biological Sciences, 278, by future studies that integrate fossil and molecular evidence. 2384–2391. Dapporto, L., Fattorini, S., Voda, R., Dinca, V. & Vila, R. ACKNOWLEDGEMENTS (2014) Biogeography of western Mediterranean butterflies: combining turnover and nestedness components of faunal We are deeply grateful to Wei Huang for compiling the data dissimilarity. Journal of Biogeography, 41, 1639–1650. – of the Qinghai Tibetan Plateau. We thank Jinchu Hu in the Dobrovolski, R., Melo, A.S., Cassemiro, F.A.S. & Diniz-Filho, China West Normal University who provided us with species J.A.F. (2012) Climatic history and dispersal ability explain distribution data. This study was supported by the National the relative importance of turnover and nestedness com- Science Fund for Fostering Talents in Basic Research (Special ponents of beta diversity. Global Ecology and Biogeography, Subjects in Animal Taxonomy, NSFC-J1210002) and grant 21, 191–197. from the Key Laboratory of the Zoological Systematics and Fattorini, S. & Ulrich, W. (2012) Spatial distributions of Evolution of the Chinese Academy of Sciences (No. European Tenebrionidae point to multiple postglacial col- Y229YX5105). onization trajectories. Biological Journal of the Linnean Society, 105, 318–329. Gaston, K.J. & Blackburn, T.M. (2000) Pattern and process in REFERENCES macroecology. 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correlation with the Quaternary climate change. Molecular Appendix S2 Principal component analyses of eight envi- Ecology, 17, 5135–5145. ronmental variables in the Qinghai–Tibetan Plateau and the Yang, W.-J., Ma, K.-P. & Kreft, H. (2013) Geographical sam- Hengduan Mountains. pling bias in a large distributional database and its effects on species richness-environment models. Journal of Bio- BIOSKETCH geography, 40, 1415–1426. Zhang, R.-Z. (2002) Geological events and mammalian dis- This work was conducted by the Group of Mammalogy in tribution in China. Acta Zoologica Sinica, 48, 141–153. the Institute of Zoology, Chinese Academy of Sciences. The Zhang, R.-Z., Zheng, D., Yang, Q.-Y. & Liu, Y.-H. (1997) focus of our research group is mammalian biogeography, Physical geography of Hengduan Mountains, 1st edn. biodiversity conservation, evolutionary morphology and Science Press, Beijing. molecular phylogenetics. We are particularly interested in the Zorner, R.J., Trabucco, A., Bossio, D.A. & Verchot, L.V. biogeographical patterns of mammal species diversity in the (2008) Climate change mitigation: a spatial analysis of glo- Hengduan Mountains and Qinghai–Tibetan Plateau at differ- bal land suitability for clean development mechanism ent scales, as well as the biodiversity patterns in the arid and afforestation and reforestation. Agriculture, Ecosystems & semi-arid regions of China. 126 – Environment, ,67 80. Author contributions: L.X. and Z.W. conceived the ideas and designed the research; Q.Y., Q.Q., Z.W. and X.L. collected the data and did the statistical work; Z.W. and D.G. led the SUPPORTING INFORMATION writing. Additional Supporting Information may be found in the online version of this article: Editor: Holger Kreft Appendix S1 Species lists of small mammals in the Qing- hai–Tibetan Plateau and the Hengduan Mountains.

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