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Abstract AimBiogeographers have used three primary data types to examine shifts in tree ranges in response to past climate change: fossil pollen, genetic data and contemporary occurrences. Although recent efforts have explored formal integration of these types of data, we have limited understanding of how integration affects estimates of range shift rates and their uncertainty. We compared estimates of biotic velocity (i.e. rate of species' range shifts) using each data type independently to estimates obtained using integrated models. LocationEastern North America. TaxonFraxinus pennsylvanicaMarshall (green ash). MethodsUsing fossil pollen, genomic data and modern occurrence data, we estimated biotic velocities directly from 24 species distribution models (SDMs) and 200 pollen surfaces created with a novel Bayesian spatio‐temporal model. We compared biotic velocity from these analyses to estimates based on coupled demographic‐coalescent simulations and Approximate Bayesian Computation that combined fossil pollen and SDMs with population genomic data collected across theF. pennsylvanicarange. ResultsPatterns and magnitude of biotic velocity over time varied by the method used to estimate past range dynamics. Estimates based on fossil pollen yielded the highest rates of range movement. Overall, integrating genetic data with other data types in our simulation‐based framework reduced apparent uncertainty in biotic velocity estimates and resulted in greater similarity in estimates between SDM‐ and pollen‐integrated analyses. Main ConclusionsBy reducing uncertainty in our assessments of range shifts, integration of data types improves our understanding of the past distribution of species. Based on these results, we propose further steps to reach the integration of these three lines of biogeographical evidence into a unified analytical framework. 

Abstract The decorator wormDiopatra cupreaBosc, 1802 (Annelid; Polycheate; Onuphidae) is an ecosystem engineer within high-salinity estuaries of the southern and eastern United States. A previous study revealed five morphologically cryptic mitochondrial lineages across its broad geographic distribution. Here, we explore mitonuclear concordance of these lineages using single nucleotide polymorphisms (SNPs) genotyped with RADseq. We genotyped 3,162 SNPs from 233D. cupreaand detected four deep lineages in the nuclear genome: a northern US clade (Massachusetts), a single nuclear clade within mid-Atlantic populations (i.e., Virginia south through northeastern Florida), a southeastern Florida clade, and a Gulf of Mexico clade. There was mitonuclear concordance within most individuals for three lineages, while two mitochondrial lineages were detected in a single mid-Atlantic nuclear lineage. Thus, there appear to be four cryptic lineages ofD. cupreathat suggest four distinct species that rarely hybridize. Within the mid-Atlantic lineage, we detected increasing genetic isolation of populations with increasing geographic distance, a pattern consistent with low dispersal ofD. cuprealarvae. Cryptic diversity within theD. cupreacomplex is consistent with other common and geographically widespread annelid andDiopatraspecies that are now being revealed using high-throughput sequencing. 

The massive geographic expansion of terrestrial plant crops, livestock, and marine aquacultured species during the 19th and 20th centuries provided local economic benefits, stabilized food demands, and altered local ecosystems. The invasion history of these translocations remains uncertain for most species, limiting our understanding of their future adaptive potential and historical roles as vectors for coinvaded species. We provide a framework for filling this gap in invasion biology using the widely transplanted Pacific oyster as a case study. A two-dimensional summary of population-level variation in single nucleotide polymorphisms in native Japan reflected the geographical map of Japan and allowed identification of the source regions for the worldwide expansion. Pacific oysters proliferate in nonnative areas with environmental temperatures similar to those areas where native lineages evolved. Using Approximate Bayesian Computation, we ranked the likelihood of historical oyster or shipping vectors to explain current-day distribution of genotypes in 14 coinvaded algal and animal species. Oyster transplants were a more likely vector than shipping for six species, shipping activity was more likely for five species, and a vector was ambiguous for three species. Applying this approach to other translocated species should reveal similar legacy effects, especially for economically important foundation species that also served as vectors for nonnative species. 

Bonamia(Haplosporida) are oyster parasites capable of devastating oyster populations. The near-circumglobal distribution of the host generalistB. exitiosahas previously been associated with the natural and anthropogenic dispersal of broadly distributed non-commercial oysters in theOstrea stentinaspecies complex. Here, we took a global snapshot approach to explore the role of the widely introduced Pacific oysterMagallana gigas, a commercially important species that can be found on every continent except Antarctica, in transportingBonamia.We screened 938M. gigasindividuals from 41 populations in this oyster’s native and non-native geographic range for presence ofBonamiaDNA using PCR.B. exitiosawas the only species detected and only within 2 of 5 populations from southern California, USA (10 and 42% PCR prevalence). Therefore,M. gigascould have played a role in transportingB. exitiosato California (if introduced) and/or maintainingB. exitiosapopulations within California, but morphological confirmation of infection needs to be done to better understand the host-parasite dynamics within this system. We detected noBonamiaDNA within any other non-nativeM. gigaspopulations (n = 302) nor within nativeM. gigaspopulations in Japan and Korea (n = 582) and thus found no evidence to support the co-dispersal ofM. gigasand otherBonamiaspecies. Lower sample sizes within some populations and the non-systematic nature of our sampling design may have led to false negatives, especially in areas whereBonamiaare known to occur. Nevertheless, this global snapshot provides preliminary guidance for managing both natural and farmed oyster populations. 

Climate change poses a threat to biodiversity, and it is unclear whether species can adapt to or tolerate new conditions, or migrate to areas with suitable habitats. Reconstructions of range shifts that occurred in response to environmental changes since the last glacial maximum (LGM) from species distribution models (SDMs) can provide useful data to inform conservation efforts. However, different SDM algorithms and climate reconstructions often produce contrasting patterns, and validation methods typically focus on accuracy in recreating current distributions, limiting their relevance for assessing predictions to the past or future. We modeled historically suitable habitat for the threatened North American tree green ashFraxinus pennsylvanicausing 24 SDMs built using two climate models, three calibration regions, and four modeling algorithms. We evaluated the SDMs using contemporary data with spatial block cross‐validation and compared the relative support for alternative models using a novel integrative method based on coupled demographic‐genetic simulations. We simulated genomic datasets using habitat suitability of each of the 24 SDMs in a spatially‐explicit model. Approximate Bayesian computation (ABC) was then used to evaluate the support for alternative SDMs through comparisons to an empirical population genomic dataset. Models had very similar performance when assessed with contemporary occurrences using spatial cross‐validation, but ABC model selection analyses consistently supported SDMs based on the CCSM climate model, an intermediate calibration extent, and the generalized linear modeling algorithm. Finally, we projected the future range of green ash under four climate change scenarios. Future projections using the SDMs selected via ABC suggest only minor shifts in suitable habitat for this species, while some of those that were rejected predicted dramatic changes. Our results highlight the different inferences that may result from the application of alternative distribution modeling algorithms and provide a novel approach for selecting among a set of competing SDMs with independent data. 

Marine annelid taxonomy is experiencing a period of rapid revision, with many previously “cosmopolitan” species being split into species with more limited geographic ranges. This is exemplified by the Diopatra genus, which has recently witnessed dozens of new species descriptions rooted in genetic analyses. In the northwestern Atlantic, the name D. cuprea (Bosc 1802) has been applied to populations from Cape Cod through the Gulf of Mexico, Central America, and Brazil. Here, we sequenced mitochondrial cytochrome oxidase I (COI) in D. cuprea populations from the Gulf of Mexico to Massachusetts. We find evidence for several deep mitochondrial lineages, suggesting that cryptic diversity is present in the D. cuprea complex from this coastline.