Acta Chiropterologica, 15(2): 353–363, 2013 PL ISSN 1508-1109 © Museum and Institute of Zoology PAS doi: 10.3161/150811013X678973 Conservation units of Pteronotus davyi (Chiroptera: Mormoopidae) in Mexico based on phylogeographical analysis LUIS M. GUEVARA-CHUMACERO1, 3, 4, RICARDO LÓPEZ-WILCHIS1, JAVIER JUSTE3, CARLOS IBÁÑEZ3, LUIS A. MARTÍNEZ-MÉNDEZ1, and IRENE D. L. A. BARRIGA-SOSA2 1Departamento de Biología, Universidad Autónoma Metropolitana Iztapalapa, México D.F., Mexico Departamento de Hidrobiología, Universidad Autónoma Metropolitana Iztapalapa, México D.F., Mexico 3 Departamento de Ecología Evolutiva, Estación Biológica de Doñana-CSIC, Sevilla 41080, Spain 4 Corresponding author: E-mail: lmgc1@yahoo.com 2 The analysis of genetic diversity is routinely used to identify divergent intraspecific units and contribute to the knowledge base of biodiversity. In this study we used mitochondrial genetic diversity to propose three management units (MUs) for the Davy’s nakedbacked bat (Pteronotus davyi), an insectivorous forest-dwelling species that is distributed in tropical and subtropical areas of America. We analyzed a 555 bp segment of the mitochondrial DNA (mtDNA) control region in 144 individuals from 18 localities spread across the species distribution range in Mexico. Our results demonstrated that the mitochondrial genetic diversity of P. davyi is distributed in three MUs, namely Gulf North, Pacific-Veracruz and Southeastern, with conservation priority, due to either the high mitochondrial genetic diversity or the high proportion of unique haplotypes, for the following populations: Playa de Oro, Arroyo del Bellaco and Catemaco in the Pacific-Veracruz region, and Agua Blanca, Sardina, Calakmul, Calcehtok and Kantemó from the Southeastern region. The Gulf North unit shows signs of the recent loss of genetic variability. These proposed conservation units could be considered a generalized model of conservation for other species of cave-dwelling bats that share the same habitats. Key words: conservation, control region, mtDNA, management units, Mexico, Mormoopidae INTRODUCTION Phylogeographic studies are very useful in identifying the principles and processes governing the geographical distributions of genealogical lineages, especially those at the intraspecific level (Avise et al., 1987), aspects that are essential for biodiversity conservation (Moritz, 2002). The identification of evolutionarily divergent populations is crucial for the maintenance of intraspecific genetic diversity (Avise, 2004), and molecular characters provide a valuable source of information for the analysis of this intraspecific history and the delineation of population units, such as the Evolutionary Significant Unit (ESU) and the Management Unit (MU), the latter of which is fundamental to short-term conservation goals (Moritz, 1994). An ESU can be defined as a group of individuals or populations with reciprocal monophyly for mitochondrial markers. ESUs represent historically isolated lineages that cover the evolutionary diversity of a taxon and therefore have a high priority for conservation. MUs consist of one or more populations with significant divergence of allele frequencies at nuclear or mitochondrial loci, regardless of whether the alleles are monophyletic. In operational terms, MUs represent populations that exhibit limited gene flow and, as a result, show some level of demographic independence (Moritz, 1994). The Davy’s naked-backed bat, Pteronotus davyi Gray 1838, is a forest-dwelling insectivorous bat (Adams, 1989) belonging to the family Mormoopidae that is distributed mainly in tropical and subtropical areas of America. In Mexico all nakedbacked bats are included within the subspecies P. d. fulvus, which is distributed along two separated narrow strips that extend along the Pacific coast (from Sonora to Chiapas) and the Gulf of Mexico (from Tamaulipas to Tabasco) that converge in the lowlands of the Isthmus of Tehuantepec and then penetrate into the Yucatan Peninsula (Smith, 1972). Due to the typically large size of Davy’s nakedbacked bat populations, this species plays an essential role not only in regulating forest insect populations, but also in the maintenance of these tropical 354 L. M. Guevara-Chumacero, R. López-Wilchis, J. Juste, C. Ibáñez, L. A. Martínez-Méndez, et al. ecosystems (Bateman and Vaughan, 1974; Adams, 1989). Nevertheless, tropical forests are continuously shrinking, primarily as the result of human activities. The official document ‘Mexico’s REDD+ vision’ (CONAFOR, 2010) states that the country lost on average 155,152 hectares of forest extent each year for the period 2002–2007, and nearly all of this deforestation (99.9%) occurred in the tropical forests, the main habitat of P. davyi. If this trend continues it is very likely that in the near future populations of this forest bat species will need active management to prevent the loss of genetic diversity. In this study we analyzed the evolutionary history of P. davyi in Mexico, focusing on its genetic geographic variation and establishing dates for the main recent evolutionary events. We then utilized this information to identify MUs for P. davyi in Mexico. The MUs proposed are used to determine priorities for the conservation of the genetic diversity of this species. Finally, P. davyi is employed as a model species to define conservation priorities for other forest-dwelling fauna whose shared habitat is being similarly affected by human activities. MATERIALS AND METHODS Samples and Study Area We sampled 18 P. davyi populations (names and acronyms are provided in Appendix) throughout the whole distribution area of the species in Mexico. Specimens were captured using harp traps, measured, and then biopsied from wing membranes using a three-mm biopsy puncher (Fray Products Corp., Buffalo, NY). Tissue samples were stored in 70% ethanol. The sampled bats were then immediately released, except for a few specimens which were preserved as vouchers and deposited in the scientific collections at the Estación Biológica de Doñana (CSIC) (catalogue nos.: EBD12750, EBD21346, EBD25382 and EBD25383). For appropriate ethics we followed our institutional protocol (Anonymous, 2010) and Sikes et al. (2011). DNA Extraction, Amplification and Sequencing A total of 144 bats were used (accession nos. EF989018– EF989084, JN375694–JN375710). Total DNA extraction was performed using the DNeasy Tissue Kit (Qiagen, Inc., Valencia, CA). Primers, amplification conditions and sequencing of the hypervariable domain (HVII) of the control region followed the methods described by Guevara-Chumacero et al. (2010). Genealogical Analyses and Genetic Structure We explored global genetic structure using Spatial Analysis of Molecular Variance (SAMOVA), ver. 1.0 (Dupanloup et al., 2002). This method defines k as continuously homogenous but genetically differentiated populations where the proportion of total genetic variance (FCT) is maximized. We ran SAMOVA with 1,000 simulated annealing processes for a range of k values from two to four. An analysis of molecular variance (AMOVA) was then used to examine the amount of genetic variability partitioned within and among populations, as well as among groups of populations, using Arlequin, ver. 3.11 (Excoffier et al., 2005). To explore the relationships among haplotypes a median-joining network was built using Network, ver. 4.5.1.6 (Bandelt et al., 1999). Average genetic distances among regional groups were evaluated using the Tamura-Nei (TrN) substitution model (Tamura and Nei, 1993) implemented in Mega, ver. 4 (Tamura et al., 2007). We used this model because it is suitable for comparisons among closely related taxa (Palma et al., 2005; GuevaraChumacero et al., 2010). Polymorphism levels were estimated by haplotype diversity (H) and nucleotide diversity (π), which were determined with-in geographic regions using DNAsp, ver. 4 (Rozas et al., 2003). Finally, linear regressions were generated with NCSS, ver. 2000 (Hintze, 1999), to examine the relationship between latitude and nucleotide diversity for each geographic region (Gulf, Pacific and Southeastern) in order to help evaluate possible post-Pleistocene expansions from southern refugia. It is expected that weaker relationships will be observed in the north due to leading edge expansion (Hewitt, 2000). Divergence Time and Migration The isolation with migration (IM) coalescent model, as implemented in the program IM (update 2009; Hey and Nielsen, 2007), was used to estimate the divergence times (t) and migration rates in both directions (m1 and m2), among the groups of populations of P. davyi previously defined by SAMOVA. To calculate these parameters we estimated the effective population sizes of the current (θ1 and θ2) and ancestral populations (θA) using the same software. The model uses Metropolis–Hasting Markov Chain Monte Carlo (MCMC) simulations to find the optimal combination of values for these demographic parameters that best fit the dataset. The inheritance scalar was set to 0.25, and the model of evolution was set to Hasegawa– Kishino–Yano (HKY) (Hasegawa et al., 1985) nucleotide substitution model, as recommended for mitochondrial DNA (IM manual). We initially performed exploratory runs to define the minimum range of bounded priors for demographic parameters that ensure the incorporation of full marginal posterior probability densities. The prior values used for the final analyses were as follows: t = 20, θ1 = 400, θ2 = 300, θA = 100 and m1 = m2 = 2. The convergence was assessed through two independent MCMC runs (with different seed numbers carried out with 20,000,000 recorded steps after a burn-in of two million steps), and by monitoring the ESS values, the update acceptance rates and the trend lines. A divergence rate of 10% per million years, assuming one generation per year, was used for the control region (Wilkinson and Fleming, 1996). We converted t to real time (t) using t = t/µ. The effective number of female migrants between populations was calculated using the formulae: M1 = θ1 * m/2 and M2 = θ2 * m/2 (Hey and Nielsen, 2004). RESULTS Nucleotide Sequences and Haplotypes A 555-base pair fragment that covered the complete HVII domain of the mtDNA control region of Davy’s naked-backed bat conservation units P. davyi was analyzed. In this fragment, 61 positions were variable, of which 65.6% was parsimony informative. Eighty-three different haplotypes were identified, the most common of which was haplotype 53, which occurred in 14.4% of the sampled individuals. A total of 17 (20.5%) shared haplotypes and 66 (79.5%) unique haplotypes were observed (Fig. 1). Genealogical Analyses and Genetic Structure The hierarchical and spatial analysis of genetic structure (SAMOVA) identified three units (K = 3, FCT = 0.52, P < 0.001) as the most fundamental subdivisions: Gulf North (GULN) that covers TR, TA, and PU populations; Pacific-Veracruz (PAC-VER) which includes TI, SD, FR, VI, AM, OR, PO, LA, CA, and AR populations; and the Southeastern Unit (SOU) that comprises the populations of AB, SA, 355 CK, KA, and CAL. The distinction of the three groups is supported by a haplotype network, in which six haplotypes belonging to the GULN region, 43 to the PAC-VER region, 32 to the SOU region, and two haplotypes shared among regions (Fig. 2). The Analysis of Molecular Variance (AMOVA) among these three groups revealed a significantly higher percentage of genetic variance between regional groups than among populations within regional groups (36.2% and 6.6%, respectively), with the largest fraction (57.2%) due to differences within populations (fixation indices: FSC = 0.103, FST = 0.427, FCT = 0.362, all P-values significant at < 0.05). Genetic distances based on the Tamura-Nei substitution model (TrN) indicated that the greatest difference was between regions PAC-VER and SOU and GULN and SOU (2.02% and 1.84%, respectively); differentiation between PAC-VER FIG. 1. Distribution of haplotypes for 18 populations of P. davyi sampled across Mexico. Each circle represents the haplotype diversity of one population, with the relative size of each wedge proportional to the frequency of each haplotype in the population. Unique haplotypes are represented by different numbers in black wedge. The two letter acronym signifies the population (see Appendix). Management units are presented and priority populations for conservation are indicated with acronyms listed in red 356 L. M. Guevara-Chumacero, R. López-Wilchis, J. Juste, C. Ibáñez, L. A. Martínez-Méndez, et al. and GULN was 1.52%. The PAC-VER and SOU regions presented similar levels of haplotype diversity, which was lower in the GULN region. Nucleotide diversity also was lower in the GULN region (Table 1). There was a significant negative correlation between nucleotide diversity and latitude from Pacific (R2 = 0.73, P = 0.015) and Gulf (R2 = 0.87, P = 0.021) geographic regions. For the Southeastern region this correlation also was negative, although not significant (R2 = 0.27, P = 0.367 — Fig. 3). The isolation with migration coalescent model (IM) suggests that the number of migrants between PAC-VER and SOU regions are effectively low, and also among regions PAC-VER, GULN and SOU. The posterior distribution of m in these regions was 0.033 and 0.041, respectively. The migration estimates were less than one for the PAC-VER-GULN groups, mPAC-VER vs GULN = 0.155 [90% highest posterior density interval (HPD) = 0 to 1.075] and TABLE 1. Genetic diversity indices [sample size (n), number of segregating sites (S), nucleotide diversity (π), number of haplotypes (h), and haplotype diversity (H)] for populations (PACVER, GULN and SOU) within the proposed management units of P. davyi Statistics n S π h H PAC-VER 73 50 0.0166 45 0.963 GULN 30 13 0.0029 8 0.740 SOU 41 34 0.0087 33 0.977 mGULN vs PAC-VER = 0.505 (90% HPD = 0 to 1.359) (Table 2). Divergence time between PAC-VER, GULN and SOU geographical groups during the Pleistocene was 67,500 years ago (90% HPD = 50,200–84,100 years ago). Divergence time between PAC-VER and GULN geographical groups was shorter (t = 21,100, 90% HPD = 8,500–36,600 years ago) (Table 2). FIG. 2. Median-joining network of 83 haplotypes of P. davyi in Mexico. Circles represent haplotypes and the size of circle is proportional to the number of individuals sharing that haplotype. Each line is connecting a circle or square (hypothetical internode, i.e. presumed unsampled or missing intermediate haplotypes) and numbers near a branch indicate the number of mutations when greater than one Davy’s naked-backed bat conservation units 357 TABLE 2. Demographic parameter estimates for the geographic regions comparisons (PAC-VER vs GULN, PAC-VER vs SOU, and PAC-VER, GULN vs SOU) of P. davyi as inferred by the IM analysis. Mean migration rates per generation and divergence times in years; 95% confidence intervals are given in parentheses Migration (m) Migration (m) Time (t) PAC-VER vs GULN Pairwise analysis PAC-VER vs GULN 0.155 (0.000–1.075) GULN vs PAC-VER 0.505 (0.000–1.359) PAC-VER vs GULN 21,100 (8,500–36,600) PAC-VER vs SOU PAC-VER vs SOU 0.033 (0.000–0.105) SOU vs PAC-VER 0.041 (0.000–0.129) PAC-VER vs SOU 69,133 (51,444–86,823) PAC-VER, GULN vs SOU 0.033 (0.000–0.103) SOU vs PAC-VER, GULN 0.039 (0.000–0.121) PAC-VER, GULN vs SOU 67,500 (50,200–84,100) PAC-VER, GULN vs SOU DISCUSSION Our results indicate a phylogeographic structure with three haplogroups: GULN, PAC-VER, and SOU, genetically isolated but with a common Pleistocene origin. The isolation with migration results suggest that populations from PAC-VER and GULN regions diverged from populations of the Southeastern region at least 67,000 years ago; a date corresponding to the Wisconsin glacial period (Martínez and Fernández, 2004; Hall, 2005). A similar date was obtained by Guevara-Chumacero et al. (2010) for the divergence between PAC-VER-GUL and SOU groups, indicating a long period of isolation supported by very low levels of gene flow, which corroborates the estimates obtained from the IM model (Table 2). Despite the clear differentiation between populations of P. davyi on both sides of the Isthmus of Tehuantepec (1.97%) they are not monophyletic groups due to the presence of some shared haplotypes, and they cannot be considered ESUs. However, determining ESUs based on a single molecular genetic marker is not ideal; instead, the above mitochondrial data should becombined with nuclear information (Crandall et al., 2000). The pair-wise FST, SAMOVA and network analyses indicate a significant subdivision of P. davyi into three population groups, PAC-VER, GULN and SOU, and that these populations merit assignment to different management units (MUs), which are defined as “one or more populations with significant differentiation in their mitochondrial haplotypes, regardless of the phylogenetic distinctiveness of the alleles” (Moritz, 1994: 374). The three MUs are the result of the complex recent evolutionary history of P. davyi, with different expansion episodes occurring during the Pleistocene. The significant negative correlation between mitochondrial genetic diversity and latitude among bat populations inhabiting both the Pacific and Atlantic coasts (Fig. 3) suggests to a rapid geographic expansion from southern refugia to formerly unsuitable areas (Toledo, 1982; Gutiérrez-García and Vázquez-Domínguez, 2013), through a process of repeated founder events (and loss of alleles) during the range expansion of the populations (Hewitt, 2000). The identified MUs are important in terms of conservation, but given their high mitochondrial genetic diversity and high proportion of unique haplotypes (above 70% by population) (Fig. 1), conservation efforts should be focused foremost on bat populations from Playa de Oro, Arroyo del Bellaco and Catemaco (PAC-VER region), as well as those from Agua Blanca, Sardina, Calakmul, Calcehtok and Kantemó (SOU region). The populations of Agua Blanca and Sardina are located geographically close to the contact area between the regions PAC-VER and SOU, a zone that should be considered under some conservation plan given that the infrastructure for generating wind energy has had a strong negative impact on bat populations, similar to what occurred in many parts of North America (Johnson, 2005; Kunz et al., 2007; Arnett et al., 2008). For example, a recent study of this contact area in Mexico reported the presence of 20 different bat species found dead beneath wind turbines with P. davyi the most frequently killed species (INECOL, 2009). Furthermore, caves in Mexico have been sealed off because of the purported presence of vampires (Desmodus rotundus), thus threatening non-target species that use these sites (Pint, 1994). Bats have also been killed in their roosts using dynamite, shotguns, smoke and fire, and cyanide gas (Mickleburgh et al., 2002). This type of slaughter occurs in the geographic regions proposed as MUs in this study, calling for the implementation of active cave conservation projects, such as those already underway in the UK and USA (Hensley, 1992; Hutson et al., 1995). Translocation is a powerful conservation tool that has been used in the management of a wide range of taxa (Seddon et al., 2007); although these 358 L. M. Guevara-Chumacero, R. López-Wilchis, J. Juste, C. Ibáñez, L. A. Martínez-Méndez, et al. measures have been unsuccessful in the conservation of bats (Guilbert et al., 2007). Ruffell and Parsons (2009) demonstrated that translocated bats of Mystacina tuberculata remained at their release site and survived; however, after several months many bats had damaged, infected ears and some individuals were balding. The best alternative strategy for conservation is the protection of geographic areas in which utilized caves exhibit either unusually high diversity or multispecies populations (Arita, 1993). Due to their loss of genetic variability, the populations of Taninul, Troncones and Pujal (GULN region) should also be considered primary targets Pacific coast Nucleotide diversity Gulf coast Southeastern Latitude FIG. 3. Linear regressions, correlation values and significance of nucleotide diversity of P. davyi populations in relation to latitude for the Pacific and Gulf versants, and the Southeastern region. The maps on the bottom represent the populations included for each linear regression Davy’s naked-backed bat conservation units of conservation. In this region other bat species with low levels of genetic diversity have also been identified (Natalus mexicanus — López-Wilchis et al., 2012; Pteronotus personatus — L. M. Guevara-Chumacero, unpublished data; Tadarida brasiliensis — Russell et al., 2005), and similarly low levels of genetic diversity have been identified in other mammals (Arteaga et al., 2012) and plants (González-Astorga et al., 2006). The status of genetic diversity of bats and plants populations in this zone is possibly due to the geographic isolation of the GULN region. As Eckert et al. (2008) showed, nucleotide diversity is reduced in marginal areas with respect to central areas of the species distribution. Furthermore, results from IM analysis indicate that P. davyi bat populations in the GULN region diverged from the PAC-VER region at least 21,000 years ago, corresponding to the last glacial maximum (LGM). Isolation between GULN and PAC-VER regions is probably amplified by the loss of habitat due to deforestation (Jahrsdoerfer and Leslie, 1988; OrtegaHuerta and Peterson, 2004). In addition, it has been shown that among the causes of decline of genetic diversity in bats are recent changes in land-use, as observed for example in the trefoil horseshoe bat Rhinolophus trifoliatus, papillose woolly bat Kerivoula papillosa (Struebig et al., 2011) and Seba’s short-tailed bat Carollia perspicillata (Meyer et al., 2009). An urgent conservation goal should be to manage the populations of the GULN region with actions focused on maintaining their current demographic and genetic diversity, given that isolated populations are likely to become extinct in the near future (Templeton et al., 1990), which recently occurred, for example, to the Chihuahuan meadow vole, Microtus pennsylvanicus chihuahuensis (List et al., 2010). The importance of considering the proposed MUs for P. davyi lies in the fact that this species typically inhabits areas where habitat fragmentation has increased dramatically in recent years due to exceptionally high rates of deforestation, as the result of agricultural transformation and other human activities (Bray and Klepeis, 2005; Newton, 2007). In addition, the proposed conservation units in this study can probably be generalized to other species of forest-dwelling bats, such as Pteronotus personatus, P. parnellii, Mormoops megalophylla and Natalus mexicanus, which in many cases share habitat and shelters (Bayona-Miramontes and SánchezChávez, 2007), and for its large population sizes are important ecosystem service providers and 359 help control insect populations, essential even for the maintenance of tropical ecosystems (Kunz et al., 2011). Conservation management in Davy’s nakedbacked bats should aim to maintain connectivity between populations to guarantee the observed high levels of gene flow among populations. In conclusion, this study identifies three different management units for P. davyi, all of conservation concern, due to the loss of Mexican forests, the main habitat for this species, and the impact caused by human activities. The management of P. davyi populations as MUs proposed in this study can be used as a guideline in making decisions concerning the conservation of these forest-dwelling bats, as well as populations of other bat species that exhibit similar ranges and ecological requirements. The importance of the reduction in deforestation rates and the design of connecting geographic corridors are highlighted as the main ways of preserving genetic diversity not only for this and other species of bats, but also for the remaining Mexican forest flora and fauna. ACKNOWLEDGEMENTS We would like to thank Alejandro Soto Castruita, R. M. Aguilar and M. L. Galván for their support in the field. We thank James Macaluso and anonymous reviewers for their helpful comments and suggestions. This work was partially supported by the bilateral agreement between the Spanish CSIC and the Mexican CONACYT scientific agencies. We gratefully thank CESGA (Galician supercomputing center) for providing access to the HP Superdome computer. Fellowship CONACYT 164703, 126899 and 150712 were granted to LMG-C. LITERATURE CITED ADAMS, J. 1989. Pteronotus davyi. Mammalian Species, 346: 1–5. ANONYMOUS. 2010. Lineamientos para la conducción ética de la investigación, docencia y difusión. División de Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana, Iztapalapa, México, D.F., 39 pp. ARITA, H. T. 1993. Conservation biology of the cave bats of Mexico. Journal of Mammalogy, 74: 693–702. ARNETT, E. B., K. BROWN, W. P. ERICKSON, J. K. FIEDLER, B. L. HAMILTON, T. H. HENRY, A. JAIN, G. D. JOHNSON, J. KERNS, R. R. KOFORD, et al. 2008. Patterns of mortality of bats at wind energy facilities in North America. Journal of Wildlife Management, 72: 61–78. ARTEAGA, M. C., D. PIÑERO, L. E. EGUIARTE, J. GASCA, and R. A. MEDELLÍN. 2012. Genetic structure and diversity of the nine-banded armadillo in Mexico. Journal of Mammalogy, 93: 547–559. AVISE, J. C. 2004. Molecular markers, natural history and evolution. Chapman and Hall, New York, 511 pp. AVISE, J. C., J. ARNOLD, R. M. BALL, JR., E. BERMINGHAM, T. LAMB, J. E. NEIGEL, C. A. REEB, and N. C. SAUNDERS. 1987. Intraspecific phylogeography: the mitochondrial 360 L. M. Guevara-Chumacero, R. López-Wilchis, J. Juste, C. Ibáñez, L. A. Martínez-Méndez, et al. DNA bridge between population genetics and systematics. Annual Review of Ecology and Systematics, 18: 489–522. BANDELT, H. J., P. FORSTER, and A. RÖHL. 1999. Median-joining networks for inferring intraspecific phylogenies. Molecular Biology and Evolution, 16: 36–48. BATEMAN, G. C., and T. A. VAUGHAN. 1974. Nightly activities of mormoopid bats. Journal of Mammalogy, 55: 45–65. BAYONA-MIRAMONTES, A., and J. SÁNCHEZ-CHÁVEZ. 2007. Proyecto Kantemó. La cueva de las serpientes colgantes. CONABIO. Biodiversitas, 73: 1–7. BRAY, D. B., and P. KLEPEIS. 2005. Deforestation, forest transitions, and institutions for sustainability in south-eastern México, 1900–2000. Environmental History, 11: 195–223. CONAFOR (COMISIÓN NACIONAL FORESTAL). 2010. Visión de México sobre REDD+ Hacia una estrategia nacional. Gobierno Federal/SEMARNAT/CONAFOR, México, D.F., 54 pp. CRANDALL, K. A., O. R. P. BININDA-EMONDS, G. M. MACE, and R. K. WAYNE. 2000. Considering evolutionary processes in conservation biology. Trends in Ecology and Evolution, 15: 290–295. DUPANLOUP, I., S. SCHNEIDER, and L. EXCOFFIER. 2002. A simulated annealing approach to define the genetic structure of populations. Molecular Ecology, 11: 2571–2581. ECKERT, C. G., K. E. SAMIS, and S. C. LOUGHEED. 2008. Genetic variation across species’ geographical ranges: the central marginal hypothesis and beyond. Molecular Ecology, 17: 1170–1188. EXCOFFIER, L., L. G. LAVAL, and S. SCHNEIDER. 2005. Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online, 1: 47–50. GONZÁLEZ-ASTORGA, J., A. P. VOVIVES, P. OCTAVIO-AGUILAR, D. AGUIRRE-FEY, F. NICOLALDE-MOREJÓN, and C. IGLESIAS. 2006. Genetic diversity and structure of the cycad Zamia loddigesii Miq. (Zamiaceae): implications for evolution and conservation. Botanical Journal of the Linnean Society, 152: 533–544. GUEVARA-CHUMACERO, L. M., R. LÓPEZ-WILCHIS, F. F. PEDROCHE, J. JUSTE, C. IBÁÑEZ, and I. D. L. A BARRIGA-SOSA. 2010. Molecular phylogeography of Pteronotus davyi (Chiroptera: Mormoopidae) in Mexico. Journal of Mammalogy, 91: 220–232. GUILBERT, J. M., M. M. WALKER, S. GREIF, and S. PARSONS. 2007. Evidence of homing following translocation of longtailed bats (Chalinolobus tuberculatus) at Grand Canyon Cave, New Zealand. New Zealand Journal of Zoology, 34: 239–246. GUTIÉRREZ-GARCÍA, T. A., and E. VÁZQUEZ-DOMÍNGUEZ. 2013. Consensus between genes and stones in the biogeographic and evolutionary history of Central America. Quaternary Research, 79: 311–324. HALL, S. 2005. Ice age vegetation and flora of New Mexico. In New Mexico’s Ice Ages (S. G. LUCAS, G. S. MORGAN, and K. E. ZEIGLER, eds.). New Mexico Museum of Natural History and Science Bulletin, 28: 171–183. HASEGAWA, M., H. KISHINO, and T. YANO. 1985. Dating of the human–ape splitting by a molecular clock of mitochondrial DNA. Journal of Molecular Evolution, 22: 160–174. HENSLEY, D. 1992. The James River bat cave. Bats, 10: 17. HEWITT, G. M. 2000. The genetic legacy of the Quaternary ice ages. Nature, 405: 907–913. HEY, J., and R. NIELSEN. 2004. Multilocus methods for estimating population sizes, migration rates and divergence time, with applications to the divergence of Drosophila pseudoobscura and D. persimilis. Genetics, 167: 747–760. HEY, J., and R. NIELSEN. 2007. Integration within the felsenstein equation for improved markov chain monte carlo methods in population genetics. Proceedings of the National Academy of Sciences of the USA, 104: 2785–2790. HINTZE, J. L. 1999. NCSS 2000 statistical system for Windows. Kaysville, UT. HUTSON, A. M., S. MICKLEBURGH, and A. J. MITCHELL-JONES. 1995. Bats underground: a conservation code, 2nd edition. The Bat Conservation Trust, London, 6 pp. ! ). 2009. Plan de INECOL (INSTITUTO NACIONAL DE ECOLOGIA Vigilancia de la Fauna (Aves y Murciélagos) dentro de la Central Eoloeléctrica La Venta II, Municipio de Juchitán, Oaxaca: Informe Final 2009. Instituto Nacional de Ecología, Veracruz, México, D.F., 224 pp. JAHRSDOERFER, S. E., and D. M. LESLIE. 1988. Tamaulipan brush-land of the Lower Rio Grande Valley of South Texas: descriptions, human impacts, and management options. U.S. Fish and Wildlife Service Biological Report, 88: 36–63. JOHNSON, G. D. 2005. A review of bat mortality at wind-energy developments in the United States. Bat Research News, 46: 45–49. KUNZ, T. H., E. B. ARNETT, B. M. COOPER, W. P. ERICKSON, R. P. LARKIN, T. MABEE, M. L. MORRISON, M. D. STRICKLAND, and J. M. SZEWCZAK. 2007. Methods and metrics for studying impacts of wind energy development on nocturnal birds and bats. Journal of Wildlife Management, 71: 2449–2486. KUNZ, T. H., E. BRAUN DE TORREZ, D. BAUER, T. LOBOVA, and T. H. FLEMING. 2011. Ecosystem services provided by bats. Annals of the New York Academy of Sciences, 1223: 1–38. LIST, R., O. R. W. PERGAMS, J. PACHECO, J. CRUZADO, and G. CEBALLOS. 2010. Genetic divergence of Microtus pennsylvanicus chihuahuensis and conservation implications of marginal population extinctions. Journal of Mammalogy, 91: 1093–1101. LÓPEZ-WILCHIS, R., L. M. GUEVARA-CHUMACERO, N. A. PÉREZ, J. JUSTE, C. IBÁÑEZ, and I. D. L. A. BARRIGA-SOSA. 2012. Taxonomic status assessment of the Mexican populations of funnel-eared bats, genus Natalus (Chiroptera: Natalidae). Acta Chiropterologica, 14: 305–316. MARTÍNEZ, J., and A. FERNÁNDEZ. 2004. Cambio climático: una visión desde México (A. FERNÁNDEZ BREMAUNTZ, ed.). Instituto Nacional de Ecología, Veracruz, México, D.F., 525 pp. MEYER, C. F. J., K. M. V. KALKO, and G. KERTH. 2009. Smallscale fragmentation effects on local genetic diversity in two phyllostomid bats with different dispersal abilities in Panama. Biotropica, 41: 95–102. MICKLEBURGH, S. P., A. M. HUTSON, and P. A. RACEY. 2002. A review of the global conservation status of bats. Oryx, 36: 18–34. MORITZ, C. 1994. Defining ‘Evolutionary Significant Units’ for conservation. Trends in Ecology and Evolution, 9: 373–375. MORITZ, C. 2002. Strategies to protect biological diversity and the processes that sustain it. Systematic Biology, 51: 238–254. NEWTON, A. C. (ed.). 2007. Biodiversity loss and conservation in fragmented forest landscapes: the forests of montane Davy’s naked-backed bat conservation units Mexico and temperate South America. CABI Publishing, Wallingford, UK, 416 pp. ORTEGA-HUERTA, M. A., and A. T. PETERSON. 2004. Modeling spatial patterns of biodiversity for conservation prioritization in north-eastern Mexico. Diversity and Distributions, 10: 39–54. PALMA, E. R., E. M. RIVERA, E. RIVERA-MILLA, J. SALAZARBRAVO, F. TORRES-PÉREZ, U. F. PARDIÑAS, P. A. MARQUET, A. E. SPOTORNO, A. P. MEYNARD, and T. L. YATES. 2005. Phylogeography of Oligoryzomys longicaudatus (Rodentia: Sigmodontinae) in temperate South America. Journal of Mammalogy, 86: 191–200. PINT, J. J. 1994. Who cares about Mexican bats? National Speleological Society News, 52: 94. ROZAS, J., I. SANCHEZ-DE, J. C. BARRIO, X. MESSEGUER, and R. ROZAS. 2003. DNASP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics, 19: 2496–2497. RUFFELL, J., and S. PARSONS. 2009. Assessment of the short-term success of a translocation of lesser short-tailed bats Mystacina tuberculata. Endangered Species Research, 8: 33–39. RUSSELL, A. L., R. A. MEDELLÍN, and G. F. MCCRACKEN. 2005. Genetic variation and migration in the Mexican free-tailed bat (Tadarida brasiliensis mexicana). Molecular Ecology, 14: 2207–2222. SEDDON, P. J., D. P. ARMSTRONG, and R. F. MALONEY. 2007. Developing the science of reintroduction biology. Conservation Biology, 21: 303–312. SIKES, R. S., W. L. GANON, and ANIMAL CARE AND USE 361 COMMITTEE. 2011. Guidelines of the American Society of Mammalogists for the use of wild mammals in research. Journal of Mammalogy, 92: 235–253. SMITH, J. D. 1972. Systematics of the chiropteran family Mormoopidae. Miscellaneous Publications of the Museum of Natural History, University of Kansas, 56: 1–132. STRUEBIG, M. J., T. KINGSTON, E. J. PETIT, E. C. LE COMBER, A. ZUBAID, A. MOHD-ADNAN, and S. J. ROSSITER. 2011. Parallel declines in species and genetic diversity in tropical forest fragments. Ecology Letters, 14: 582–590. TAMURA, K., and M. NEI. 1993. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Molecular Biology and Evolution, 10: 512–526. TAMURA, K., J. DUDLEY, M. NEI, and S. KUMAR. 2007. MEGA 4: molecular evolutionary genetics analysis (mega) software version 4.0. Molecular Biology and Evolution, 24: 1596–1599. TEMPLETON, A. R., K. SHAW, E. ROUTMAN, and S. K. DAVIS. 1990. The genetic consequences of habitat fragmentation. Annals of the Missouri Botanical Garden, 77: 13–27. TOLEDO, V. M. 1982. Pleistocene changes of vegetation in tropical Mexico. Pp. 93–111, in Biological diversification in the tropics (G. T. PRANCE, eds.). Columbia University Press, New York, 714 pp. WILKINSON, G. S., and T. H. FLEMING. 1996. Migration and evolution of lesser long-nosed bat Leptonycteris curasoae, inferred from mitochondrial DNA. Molecular Ecology, 5: 329–339. Received 14 January 2013, accepted 05 June 2013 APPENDIX List of localities, acronyms, GenBank accession numbers (D-Loop), haplotypes of the sequences, and references of the samples used in the study Location Arroyo del Bellaco Laguitos Frontera Ortices Tigre Santo Domingo Frontera Viejas Amatlán de Cañas Viejas Amatlán de Cañas Catemaco Amatlán de Cañas Santo Domingo Santo Domingo Ortices Catemaco Arroyo del Bellaco Ortices Kantemó Acronyms AR LA FR OR TI SD FR VI AM VI AM CA AM SD SD OR CA AR OR KA D-Loop hapl. H1 (1) H2 (1) H3 (1) H3 (1) H4 (1) H4 (3) H4 (4) H4 (1) H4 (2) H5 (1) H6 (1) H7 (1) H8 (2) H9 (1) H10 (1) H11 (1) H12 (1) H13 (1) H14 (1) H15 (1) GenBank accession No. EF989018 EF989019 EF989081 EF989020 EF989021 EF989021 EF989021 EF989021 EF989021 EF989022 EF989023 EF989024 EF989025 EF989026 EF989027 EF989028 EF989029 EF989030 EF989031 EF989032 Reference Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) 362 L. M. Guevara-Chumacero, R. López-Wilchis, J. Juste, C. Ibáñez, L. A. Martínez-Méndez, et al. APPENDIX. Continued Location Calakmul Arroyo del Bellaco Laguitos Sardina Calakmul Sardina Calcehtok Agua Blanca Agua Blanca Kantemó Calcehtok Kantemó Agua Blanca Sardina Catemaco Calcehtok Catemaco Calakmul Sardina Calakmul Calcehtok Calakmul Sardina Calakmul Sardina Ortices Santo Domingo Tigre Santo Domingo Frontera Viejas Pujal Kantemó Calcehtok Calakmul Agua Blanca Sardina Kantemó Calcehtok Kantemó Calcehtok Catemaco Amatlán de Cañas Catemaco Arroyo del Bellaco Ortices Playa de Oro Ortices Amatlán de Cañas Taninul Troncones Troncones Taninul Taninul Pujal Pujal Troncones Troncones Taninul Taninul Acronyms CK AR LA SA CK SA CAL AB AB KA CAL KA AB SA CA CAL CA CK SA CK CAL CK SA CK SA OR SD TI SD FR VI PU KA CAL CK AB SA KA CAL KA CAL CA AM CA AR OR PO OR AM TA TR TR TA TA PU PU TR TR TA TA D-Loop hapl. H16 (1) H17 (1) H18 (1) H19 (1) H20 (1) H21 (1) H22 (1) H23 (1) H24 (1) H25 (1) H26 (1) H27 (1) H27 (1) H28 (1) H29 (1) H30 (1) H31 (1) H32 (1) H33 (1) H34 (1) H35 (1) H35 (1) H35 (1) H36 (1) H37 (1) H38 (1) H39 (1) H40 (1) H40 (1) H40 (1) H40 (1) H40 (1) H41 (1) H41 (1) H41 (1) H41 (1) H41 (1) H42 (1) H43 (1) H44 (1) H45 (1) H46 (1) H47 (1) H48 (1) H49 (1) H50 (1) H50 (1) H51 (1) H51 (1) H52 (1) H53 (2) H53 (1) H53 (2) H53 (2) H53 (3) H53 (2) H54 (2) H54 (2) H54 (1) H54 (3) GenBank accession No. EF989033 EF989034 EF989035 EF989036 EF989037 EF989045 EF989060 EF989040 EF989041 EF989044 EF989039 EF989042 EF989042 EF989038 EF989046 EF989043 EF989048 EF989049 EF989050 EF989051 EF989052 EF989052 EF989052 EF989053 EF989054 EF989055 EF989056 EF989057 EF989057 EF989057 EF989057 EF989057 EF989058 EF989058 EF989058 EF989058 EF989058 EF989059 EF989062 EF989061 EF989047 EF989063 EF989064 EF989065 EF989049 EF989068 EF989068 EF989067 EF989067 EF989069 EF989070 EF989070 EF989070 EF989070 EF989070 EF989070 EF989071 EF989071 EF989071 EF989071 Reference Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) This paper Davy’s naked-backed bat conservation units 363 APPENDIX. Continued Location Pujal Taninul Troncones Pujal Arroyo del Bellaco Agua Blanca Laguitos Arroyo del Bellaco Laguitos Arroyo del Bellaco Catemaco Tigre Viejas Amatlán de Cañas Frontera Amatlán de Cañas Amatlán de Cañas Viejas Viejas Playa de Oro Playa de Oro Playa de Oro Playa de Oro Playa de Oro Playa de Oro Playa de Oro Troncones Pujal Troncones Kantemó Kantemó Kantemó Kantemó Agua Blanca Agua Blanca Agua Blanca Agua Blanca Acronyms PU TA TR PU AR AB LA AR LA AR CA TI VI AM FR AM AM VI VI PO PO PO PO PO PO PO TR PU TR KA KA KA KA AB AB AB AB D-Loop hapl. H54 (2) H55 (1) H56 (1) H56 (1) H56 (1) H56 (1) H57 (1) H58 (1) H59 (2) H60 (1) H61 (1) H63 (5) H63 (2) H63 (1) H64 (1) H64 (1) H65 (1) H66 (1) H67 (1) H68 (1) H69 (1) H70 (3) H71 (1) H72 (1) H73 (1) H74 (1) H75 (1) H75 (1) H76 (1) H77 (1) H78 (1) H79 (1) H80 (1) H81 (1) H82 (1) H83 (1) H84 (1) GenBank accession No. EF989071 EF989072 EF989073 EF989073 EF989073 EF989073 EF989074 EF989075 EF989076 EF989077 EF989078 EF989080 EF989080 EF989080 EF989020 EF989020 EF989082 EF989083 EF989084 JN375694 JN375695 JN375696 JN375697 JN375698 JN375699 JN375700 JN375701 JN375701 JN375702 JN375703 JN375704 JN375705 JN375706 JN375707 JN375708 JN375709 JN375710 Reference This paper Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) This paper Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) Guevara-Chumacero et al. (2010) This paper This paper This paper This paper This paper This paper This paper This paper This paper This paper This paper This paper This paper This paper This paper This paper This paper This paper