Synthesis of geological data and comparative phylogeography of lowland tetrapods suggests recent dispersal through lowland portals crossing the Eastern Andean Cordillera.

Vicariance is the simplest explanation for divergence between sister lineages separated by a potential barrier, and the northern Andes would seem to provide an ideal example of a vicariant driver of divergence. We evaluated the potential role of the uplift of the Eastern Cordillera (EC) of the Colombian Andes and the Mérida Andes (MA) of Venezuela as drivers of vicariance between lowland populations co-distributed on both flanks. We synthesized published geological data and provided a new reconstruction showing that the EC-MA grew from north to south, reaching significant heights and separating drainages and changing sediment composition by 38-33 million years ago (Ma). A few lowland passes across the EC-MA may have reached their current heights (~1,900 m a.s.l.) at 3-5 Ma. We created a comparative phylogeographic data set for 37 lineages of lowland tetrapods. Based on molecular phylogenetic analyses, most divergences between sister populations or species across the EC-MA occurred during Pliocene and the Quaternary and a few during the latest Miocene, and coalescent simulations rejected synchronous divergence for most groups. Divergence times were on average slightly but significantly more recent in homeotherms relative to poikilotherms. Because divergence ages are mostly too recent relative to the geological history and too asynchronous relative to each other, divergence across the northern Andes may be better explained by organism-environment interactions concomitant with climate oscillations during the Pleistocene, and/or dispersal across portals through the Andes.

Coalescent-based species delimitation meets deep learning: Insights from a highly fragmented cactus system.

Delimiting species boundaries is a major goal in evolutionary biology. An increasing volume of literature has focused on the challenges of investigating cryptic diversity within complex evolutionary scenarios of speciation, including gene flow and demographic fluctuations. New methods based on model selection, such as approximate Bayesian computation, approximate likelihoods, and machine learning are promising tools arising in this field. Here, we introduce a framework for species delimitation using the multispecies coalescent model coupled with a deep learning algorithm based on convolutional neural networks (CNNs). We compared this strategy with a similar ABC approach. We applied both methods to test species boundary hypotheses based on current and previous taxonomic delimitations as well as genetic data (sequences from 41 loci) in Pilosocereus aurisetus, a cactus species complex with a sky-island distribution and taxonomic uncertainty. To validate our method, we also applied the same strategy on data from widely accepted species from the genus Drosophila. The results show that our CNN approach has a high capacity to distinguish among the simulated species delimitation scenarios, with higher accuracy than ABC. For the cactus data set, a splitter hypothesis without gene flow showed the highest probability in both CNN and ABC approaches, a result agreeing with previous taxonomic classifications and in line with the sky-island distribution and low dispersal of P. aurisetus. Our results highlight the cryptic diversity within the P. aurisetus complex and show that CNNs are a promising approach for distinguishing complex evolutionary histories, even outperforming the accuracy of other model-based approaches such as ABC.

Complex genetic admixture histories reconstructed with Approximate Bayesian Computation.

Admixture is a fundamental evolutionary process that has influenced genetic patterns in numerous species. Maximum-likelihood approaches based on allele frequencies and linkage-disequilibrium have been extensively used to infer admixture processes from genome-wide data sets, mostly in human populations. Nevertheless, complex admixture histories, beyond one or two pulses of admixture, remain methodologically challenging to reconstruct. We developed an Approximate Bayesian Computation (ABC) framework to reconstruct highly complex admixture histories from independent genetic markers. We built the software package MetHis to simulate independent SNPs or microsatellites in a two-way admixed population for scenarios with multiple admixture pulses, monotonically decreasing or increasing recurring admixture, or combinations of these scenarios. MetHis allows users to draw model-parameter values from prior distributions set by the user, and, for each simulation, MetHis can calculate numerous summary statistics describing genetic diversity patterns and moments of the distribution of individual admixture fractions. We coupled MetHis with existing machine-learning ABC algorithms and investigated the admixture history of admixed populations. Results showed that random forest ABC scenario-choice could accurately distinguish among most complex admixture scenarios, and errors were mainly found in regions of the parameter space where scenarios were highly nested, and, thus, biologically similar. We focused on African American and Barbadian populations as two study-cases. We found that neural network ABC posterior parameter estimation was accurate and reasonably conservative under complex admixture scenarios. For both admixed populations, we found that monotonically decreasing contributions over time, from Europe and Africa, explained the observed data more accurately than multiple admixture pulses. This approach will allow for reconstructing detailed admixture histories when maximum-likelihood methods are intractable.

"Colonization routes and demographic history of Chirostoma humboldtianum in the central Mexican plateau".

In the present study we evaluate the population structure and potential colonization routes of the silverside Chirostoma humboldtianum through approximate Bayesian computations. Six microsatellite loci were amplified in a total of 288 individuals from six different locations covering the complete geographic distribution of the species. Additionally, two mitochondrial DNA markers, a D loop control region and cytochrome b were amplified in a subset of 107 individuals. The results found with microsatellites allow recovering well-structured populations that have experienced a drastic reduction in the effective population size. On the other hand, mtDNA sequences showed a moderate phylogeographic structure with shared haplotypes between geographic localities and signalsof a slight increase in the effective population size. Finally, the approximate Bayesian computation analysis performed with both datasets suggested a west-to-east colonization route for the species in Central Mexico.

Using approximate Bayesian inference for a "steps and turns" continuous-time random walk observed at regular time intervals.

The study of animal movement is challenging because movement is a process modulated by many factors acting at different spatial and temporal scales. In order to describe and analyse animal movement, several models have been proposed which differ primarily in the temporal conceptualization, namely continuous and discrete time formulations. Naturally, animal movement occurs in continuous time but we tend to observe it at fixed time intervals. To account for the temporal mismatch between observations and movement decisions, we used a state-space model where movement decisions (steps and turns) are made in continuous time. That is, at any time there is a non-zero probability of making a change in movement direction. The movement process is then observed at regular time intervals. As the likelihood function of this state-space model turned out to be intractable yet simulating data is straightforward, we conduct inference using different variations of Approximate Bayesian Computation (ABC). We explore the applicability of this approach as a function of the discrepancy between the temporal scale of the observations and that of the movement process in a simulation study. Simulation results suggest that the model parameters can be recovered if the observation time scale is moderately close to the average time between changes in movement direction. Good estimates were obtained when the scale of observation was up to five times that of the scale of changes in direction. We demonstrate the application of this model to a trajectory of a sheep that was reconstructed in high resolution using information from magnetometer and GPS devices. The state-space model used here allowed us to connect the scales of the observations and movement decisions in an intuitive and easy to interpret way. Our findings underscore the idea that the time scale at which animal movement decisions are made needs to be considered when designing data collection protocols. In principle, ABC methods allow to make inferences about movement processes defined in continuous time but in terms of easily interpreted steps and turns.

Rain forest shifts through time and riverine barriers shaped the diversification of South American terrestrial pit vipers (Bothrops jararacussu species group)

Aim To investigate (a) historical biogeographical connections and species interchange among rain forest habitats and (b) the role of riverine barriers on population divergence and speciation in the Neotropical region. Location Amazonia and Atlantic Forest in South America. Taxon Bothrops jararacussu species group (Serpentes: Viperidae). Methods We inferred phylogenetic relationships within Bothrops with an emphasis on the jararacussu species group under a Bayesian framework based on six molecular loci. We also used genetic coalescent simulations and approximate Bayesian computation to infer historical demography within the jararacussu group based on tests of alternative scenarios. Results We found the jararacussu species group to be monophyletic. The Atlantic Forest species B. pirajai and B. muriciensis were inferred nested within this group, closely related to B. jararacussu, confirming that Atlantic Forest species form a clade. The historical demographic analyses support vicariant separation between populations of B. brazili north and south of the Amazon River during the Miocene–Pliocene border, as well as colonization of the Atlantic Forest by a northern Amazonian ancestor in the Pleistocene. Main Conclusion The evolutionary history of the jararacussu species group sheds light on the dynamism of Neotropical rain forests over time, with at least one event of forest expansion leading to faunal interchange between Amazonian and Atlantic forests in the Pleistocene. Moreover, tests of alternative demographic scenarios suggest that the populations of B. brazili from north and south of the Amazon River originated from a vicariant event during the Miocene–Pliocene border, in agreement with the proposed age of establishment of the modern Amazon River drainage. Our results also have taxonomic implications for these medically important venomous snakes, supporting unrecognized diversity at the species level.

Genetic Diversity and Population Structure of Wild Sunflower (Helianthus annuus L.) in Argentina: Reconstructing Its Invasion History.

Studying the levels and patterns of genetic diversity of invasive populations is important to understand the evolutionary and ecological factors promoting invasions and for better designing preventive and control strategies. Wild sunflower (Helianthus annuus L.) is native to North America and was introduced, and has become invasive, in several countries, including Argentina (ARG). Here, using classical population genetic analyses and approximate Bayesian computation (ABC) modeling, we studied the invasion history of wild sunflower in ARG. We analyzed 115 individuals belonging to 15 populations from ARG (invasive range) and United States (US, native range) at 14 nuclear and 3 chloroplast simple sequence repeat markers along with 23 phenotypic variables. Populations from ARG showed similar levels of nuclear genetic diversity to US populations and higher genetic diversity in the chloroplast genome, indicating no severe genetic bottlenecks during the invasion process. Bayesian clustering analysis, based on nuclear markers, suggests the presence of 3 genetic clusters, all present in both US and ARG. Discriminant analysis of principal components (DAPC) detected an overall low population structure between central US and ARG populations but separated 2 invasive populations from the rest. ABC modeling supports multiple introductions but also a southward dispersal within ARG. Genetic and phenotypic data support the central US as a source of introduction while the source of secondary introductions could not be resolved. Finally, using genetic markers from the chloroplast genome, we found lower population structure in ARG when compared with US populations, suggesting a role for seed-mediated gene flow in Argentina.

Parameter estimates of the 2016-2017 Zika outbreak in Costa Rica: An Approximate Bayesian Computation (ABC) approach.

In Costa Rica, the first known cases of Zika were reported in 2016. We looked at the 2016-2017 Zika outbreak and explored the transmission dynamics using weekly reported data. A nonlinear differential equation single-outbreak model with sexual transmission, as well as host availability for vector-feeding was used to estimate key parameters, fit the data and compute the basic reproductive number, R0, distribution. Furthermore, a sensitivity and elasticity analysis was computed based on the R0 parameters.

A Service-Oriented Platform for Approximate Bayesian Computation in Population Genetics.

Approximate Bayesian computation (ABC) is a useful technique developed for solving Bayesian inference without explicitly requiring a likelihood function. In population genetics, it is widely used to extract part of the information about the evolutionary history of genetic data. The ABC compares the summary statistics computed on simulated and observed data sets. Typically, a forward-in-time approach is used to simulate the genetic material of a population starting from an initial ancestral population and following the evolution of the individuals by advancing generation by generation under various demographic and genetic forces. This approach is computationally expensive and requires a large number of computations making the use of high-performance computing crucial for decreasing the overall response times. In this work, we propose a fully distributed web service-oriented platform for ABC that is based on forward-in-time simulations. Our proposal is based on a client-server approach. The client enables users to define simulation scenarios. The server enables efficient and scalable population simulations and can be deployed on a distributed cluster of processors or even in the cloud. It is composed of four services: a workload generator, a simulation controller, a simulation results analyzer, and a result builder. The server performs multithread simulations by executing a simulation kernel encapsulated in a proposed libgdrift library. We present and evaluate three different libgdrift library approaches whose algorithms aim to reduce execution times and memory consumption.

The geography of evolutionary divergence in the highly endemic avifauna from the Sierra Madre del Sur, Mexico.

BACKGROUND: Mesoamerica is a remarkable region with a high geological and ecological complexity. Within northern Mesoamerica, the biotic province of the Sierra Madre del Sur (SMS) in southwestern Mexico harbors exceptionally high avian endemism and diversity. Herein, we searched for spatially and temporally concordant phylogeographic patterns, in four bird genera from three distinct avian orders co-distributed across Mesoamerica and investigated their causes through hypothesis testing regarding historical processes. Selected species include endemic and differentiated populations across the montane forests of Mesoamerica, and particularly within the SMS. RESULTS: We gathered mitochondrial DNA sequences for at least one locus from 177 individuals across all species. We assessed genetic structure, demographic history, and defined a framework for the coalescent simulations used in biogeographic hypothesis testing temporal and spatial co-variance. Our analyses suggested shared phylogeographic breaks in areas corresponding to the SMS populations, and between the main montane systems in Mesoamerica, with the Central Valley of Oaxaca and the Nicaragua Depression being the most frequently shared breaks among analyzed taxa. Nevertheless, dating analyses and divergence patterns observed were consistent with the hypothesis of broad vicariance across Mesoamerica derived from mechanisms operating at distinct times across taxa in the SMS. CONCLUSIONS: Our study provides a framework for understanding the evolutionary origins and historical factors enhancing speciation in well-defined regions within Mesoamerica, indicating that the evolutionary history of extant biota inhabiting montane forests is complex and often idiosyncratic.

Simultaneous Model Selection and Model Calibration for the Proliferation of Tumor and Normal Cells During In Vitro Chemotherapy Experiments.

In vitro experiments were conducted in this work to analyze the proliferation of tumor (DU-145) and normal (macrophage RAW 264.7) cells under the influence of a chemotherapeutic drug (doxorubicin). Approximate Bayesian Computation (ABC) was used to select among four competing models to represent the number of cells and to estimate the model parameters, based on the experimental data. For one case, the selected model was validated in a replicated experiment, through the solution of a state estimation problem with a particle filter algorithm, thus demonstrating the robustness of the ABC procedure used in this work.

Genetic Pattern and Demographic History of Salminus brasiliensis: Population Expansion in the Pantanal Region during the Pleistocene.

Pleistocene climate changes were major historical events that impacted South American biodiversity. Although the effects of such changes are well-documented for several biomes, it is poorly known how these climate shifts affected the biodiversity of the Pantanal floodplain. Fish are one of the most diverse groups in the Pantanal floodplains and can be taken as a suitable biological model for reconstructing paleoenvironmental scenarios. To identify the effects of Pleistocene climate changes on Pantanal's ichthyofauna, we used genetic data from multiple populations of a top-predator long-distance migratory fish, Salminus brasiliensis. We specifically investigated whether Pleistocene climate changes affected the demography of this species. If this was the case, we expected to find changes in population size over time. Thus, we assessed the genetic diversity of S. brasiliensis to trace the demographic history of nine populations from the Upper Paraguay basin, which includes the Pantanal floodplain, that form a single genetic group, employing approximate Bayesian computation (ABC) to test five scenarios: constant population, old expansion, old decline, old bottleneck following by recent expansion, and old expansion following by recent decline. Based on two mitochondrial DNA markers, our inferences from ABC analysis, the results of Bayesian skyline plot, the implications of star-like networks, and the patterns of genetic diversity (high haplotype diversity and low-to-moderate nucleotide diversity) indicated a sudden population expansion. ABC allowed us to make strong quantitative inferences about the demographic history of S. brasiliensis. We estimated a small ancestral population size that underwent a drastic fivefold expansion, probably associated with the colonization of newly formed habitats. The estimated time of this expansion was consistent with a humid and warm phase as inferred by speleothem growth phases and travertine records during Pleistocene interglacial periods. The strong concordance between our genetic inferences and this historical data could represent the first genetic record of a humid and warm phase in the Pantanal in the period since the Last Interglacial to 40 ka.

Approximate Bayesian computation for spatial SEIR(S) epidemic models.

Approximate Bayesia n Computation (ABC) provides an attractive approach to estimation in complex Bayesian inferential problems for which evaluation of the kernel of the posterior distribution is impossible or computationally expensive. These highly parallelizable techniques have been successfully applied to many fields, particularly in cases where more traditional approaches such as Markov chain Monte Carlo (MCMC) are impractical. In this work, we demonstrate the application of approximate Bayesian inference to spatially heterogeneous Susceptible-Exposed-Infectious-Removed (SEIR) stochastic epidemic models. These models have a tractable posterior distribution, however MCMC techniques nevertheless become computationally infeasible for moderately sized problems. We discuss the practical implementation of these techniques via the open source ABSEIR package for R. The performance of ABC relative to traditional MCMC methods in a small problem is explored under simulation, as well as in the spatially heterogeneous context of the 2014 epidemic of Chikungunya in the Americas.

Evolutionarily significant units of the critically endangered leaf frog Pithecopus ayeaye (Anura, Phyllomedusidae) are not effectively preserved by the Brazilian protected areas network.

Protected areas (PAs) are essential for biodiversity conservation, but their coverage is considered inefficient for the preservation of all species. Many species are subdivided into evolutionarily significant units (ESUs) and the effectiveness of PAs in protecting them needs to be investigated. We evaluated the usefulness of the Brazilian PAs network in protecting ESUs of the critically endangered Pithecopus ayeaye through ongoing climate change. This species occurs in a threatened mountaintop ecosystem known as campos rupestres. We used multilocus DNA sequences to delimit geographic clusters, which were further validated as ESUs with a coalescent approach. Ecological niche modeling was used to estimate spatial changes in ESUs' potential distributions, and a gap analysis was carried out to evaluate the effectiveness of the Brazilian PAs network to protect P. ayeaye in the face of climate changes. We tested the niche overlap between ESUs to gain insights for potential management alternatives for the species. Pithecopus ayeaye contains at least three ESUs isolated in distinct mountain regions, and one of them is not protected by any PA. There are no climatic niche differences between the units, and only 4% of the suitable potential area of the species is protected in present and future projections. The current PAs are not effective in preserving the intraspecific diversity of P. ayeaye in its present and future range distributions. The genetic structure of P. ayeaye could represent a typical pattern in campos rupestres endemics, which should be considered for evaluating its conservation status.

Testing Domestication Scenarios of Lima Bean (Phaseolus lunatus L.) in Mesoamerica: Insights from Genome-Wide Genetic Markers.

Plant domestication can be seen as a long-term process that involves a complex interplay among demographic processes and evolutionary forces. Previous studies have suggested two domestication scenarios for Lima bean in Mesoamerica: two separate domestication events, one from gene pool MI in central-western Mexico and another one from gene pool MII in the area Guatemala-Costa Rica, or a single domestication from gene pool MI in central-western Mexico followed by post-domestication gene flow with wild populations. In this study we evaluated the genetic structure of the wild gene pool and tested these two competing domestication scenarios of Lima bean in Mesoamerica by applying an ABC approach to a set of genome-wide SNP markers. The results confirm the existence of three gene pools in wild Lima bean, two Mesoamerican gene pools (MI and MII) and the Andean gene pool (AI), and suggest the existence of another gene pool in central Colombia. The results indicate that although both domestication scenarios may be supported by genetic data, higher statistical support was given to the single domestication scenario in central-western Mexico followed by admixture with wild populations. Domestication would have involved strong founder effects reflected in loss of genetic diversity and increased LD levels in landraces. Genomic regions affected by selection were detected and these may harbor candidate genes related to domestication.

The emergence of the hyperinvasive vine, Mikania micrantha (Asteraceae), via admixture and founder events inferred from population transcriptomics.

Biological invasions that involve well-documented rapid adaptations to new environments provide unequalled opportunities for testing evolutionary hypotheses. Mikania micrantha Kunth (Asteraceae), a perennial herbaceous vine native to tropical Central and South America, successfully invaded tropical Asia in the early 20th century. It is regarded as one of the most aggressive weeds in the world. To elucidate the molecular and evolutionary processes underlying this invasion, we extensively sampled this weed throughout its invaded range in South-East and South Asia and surveyed its genetic structure using variants detected from population transcriptomics. Clustering results suggest that more than one source population contributed to this invasion. Computer simulations using genomewide genetic variation support a scenario of admixture and founder events during invasion. The genes differentially expressed between native and invasive populations were found to be involved in oxidative and high light intensity stress responses, pointing to a possible ecological mechanism of adaptation. Our results provide a foundation for further detailed mechanistic and population studies of this ecologically and economically important invasion. This line of research promises to provide new mitigation strategies for invasive species as well as insights into mechanisms of adaptation.

The niche and phylogeography of a passerine reveal the history of biological diversification between the Andean and the Atlantic forests.

The Atlantic Forest is separated from the Andean tropical forest by dry and open vegetation biomes (Chaco and Cerrado). Despite this isolation, both rainforests share closely related lineages, which suggest a past connection. This connection could have been important for forest taxa evolution. In this study, we used the Saffron-billed Sparrow (Arremon flavirostris) as a model to evaluate whether the Andean and the Atlantic forests act as a refugia system, as well as to test for a history of biogeographic connection between them. In addition, we evaluated the molecular systematic of intraspecific lineages of the studied species. We modeled the current and past distribution of A. flavirostris, performed phylogeographic analyses based on mitochondrial and nuclear genes, and used Approximate Bayesian Computation (ABC) analyses to test for biogeographic scenarios. The major phylogeographic disjunction within A. flavirostris was found between the Andean and the Atlantic forests, with a divergence that occurred during the Mid-Pleistocene. Our paleodistribution models indicated a connection between these forest domains in different periods and through both the Chaco and Cerrado. Additionally, the phylogeographic and ABC analyses supported that the Cerrado was the main route of connection between these rainforests, but without giving decisive evidence against a Chaco connection. Our study with A. flavirostris suggest that the biodiversity of the Andean and of the Atlantic forests could have been impacted (and perhaps enriched?) by cycles of connections through the Cerrado and Chaco. This recurrent cycle of connection between the Andean and the Atlantic Forest could have been important for the evolution of Neotropical forest taxa. In addition, we discussed taxonomic implications of the results and proposed to split the studied taxon into two full species.

Sea-level driven glacial-age refugia and post-glacial mixing on subtropical coasts, a palaeohabitat and genetic study.

Using a novel combination of palaeohabitat modelling and genetic mixture analyses, we identify and assess a sea-level-driven recolonization process following the Last Glacial Maximum (LGM). Our palaeohabitat modelling reveals dramatic changes in estuarine habitat distribution along the coast of California (USA) and Baja California (Mexico). At the LGM (approx. 20 kya), when sea level was approximately 130 m lower, the palaeo-shoreline was too steep for tidal estuarine habitat formation, eliminating this habitat type from regions where it is currently most abundant, and limiting such estuaries to a northern and a southern refugium separated by 1000 km. We assess the recolonization of estuaries formed during post-LGM sea-level rise through examination of refugium-associated alleles and approximate Bayesian computation in three species of estuarine fishes. Results reveal sourcing of modern populations from both refugia, which admix in the newly formed habitat between the refuges. We infer a dramatic peak in habitat area between 15 and 10 kya with subsequent decline. Overall, this approach revealed a previously undocumented dynamic and integrated relationship between sea-level change, coastal processes and population genetics. These results extend glacial refugial dynamics to unglaciated subtropical coasts and have significant implications for biotic response to predicted sea-level rise.

A mid-Pleistocene rainforest corridor enabled synchronous invasions of the Atlantic Forest by Amazonian anole lizards.

Shifts in the geographic distribution of habitats over time can promote dispersal and vicariance, thereby influencing large-scale biogeographic patterns and ecological processes. An example is that of transient corridors of suitable habitat across disjunct but ecologically similar regions, which have been associated with climate change over time. Such connections likely played a role in the assembly of tropical communities, especially within the highly diverse Amazonian and Atlantic rainforests of South America. Although these forests are presently separated by open and dry ecosystems, paleoclimatic and phylogenetic evidence suggest that they have been transiently connected in the past. However, little is known about the timing, magnitude and the distribution of former forest connections. We employ sequence data at multiple loci from three codistributed arboreal lizards (Anolis punctatus, Anolis ortonii and Polychrus marmoratus) to infer the phylogenetic relationships among Amazonian and Atlantic Forest populations and to test alternative historical demographic scenarios of colonization and vicariance using coalescent simulations and approximate Bayesian computation (ABC). Data from the better-sampled Anolis species support colonization of the Atlantic Forest from eastern Amazonia. Hierarchical ABC indicates that the three species colonized the Atlantic Forest synchronously during the mid-Pleistocene. We find support of population bottlenecks associated with founder events in the two Anolis, but not in P. marmoratus, consistently with their distinct ecological tolerances. Our findings support that climatic fluctuations provided key opportunities for dispersal and forest colonization in eastern South America through the cessation of environmental barriers. Evidence of species-specific histories strengthens assertions that biological attributes play a role in responses to shared environmental change.

Crop domestication facilitated rapid geographical expansion of a specialist pollinator, the squash bee Peponapis pruinosa.

Squash was first domesticated in Mexico and is now found throughout North America (NA) along with Peponapis pruinosa, a pollen specialist bee species of the squash genus Cucurbita The origin and spread of squash cultivation is well-studied archaeologically and phylogenetically; however, no study has documented how cultivation of this or any other crop has influenced species in mutualistic interactions. We used molecular markers to reconstruct the demographic range expansion and colonization routes of P. pruinosa from its native range into temperate NA. Populations east of the Rocky Mountains expanded from the wild host plant's range in Mexico and were established by a series of founder events. Eastern North America was most likely colonized from squash bee populations in the present-day continental Midwest USA and not from routes that followed the Gulf and Atlantic coasts from Mexico. Populations of P. pruinosa west of the Rockies spread north from the warm deserts much more recently, showing two genetically differentiated populations with no admixture: one in California and the other one in eastern Great Basin. These bees have repeatedly endured severe bottlenecks as they colonized NA, following human spread of their Cucurbita pollen hosts during the Holocene.