Find research datasets worth reusing

Data from: A test of the central-marginal hypothesis using population genetics and ecological niche modelling in an endemic salamander (Ambystoma barbouri)

The central-marginal hypothesis (CMH) predicts that population size, genetic diversity, and genetic connectivity are highest at the core and decrease near the edges of species' geographic distributions. We provide a test of the CMH using three replicated core-to-edge transects that encompass nearly the entire geographic range of the endemic streamside salamander (Ambystoma barbouri). We confirmed that the mapped core of the distribution was the most suitable habitat using ecological niche modelling (ENM) and via genetic estimates of effective population sizes. As predicted by the CMH, we found statistical support for decreased genetic diversity, effective population size, and genetic connectivity from core to edge in western and northern transects, yet not along a southern transect. Based on our niche model, habitat suitability is lower towards the southern range edge, presumably leading to conflicting core-to-edge genetic patterns. These results suggest that multiple processes may influence a species' distribution based on the heterogeneity of habitat across a species' range and that replicated sampling may be needed to accurately test the CMH. Our work also emphasizes the importance of identifying the geographic range core with methods other than using the Euclidean center on a map, which may help to explain discrepancies among other empirical tests of the CMH. Assessing core to edge population genetic patterns across an entire species' range accompanied with ENM can inform our general understanding of the mechanisms leading to species' geographic range limits.

Data from: Can impacts of climate change and agricultural adaptation strategies be accurately quantified if crop models are annually re-initialized?

Estimates of climate change impacts on global food production are generally based on statistical or process-based models. Process-based models can provide robust predictions of agricultural yield responses to changing climate and management. However, applications of these models often suffer from bias due to the common practice of re-initializing soil conditions to the same state for each year of the forecast period. If simulations neglect to include year-to-year changes in initial soil conditions and water content related to agronomic management, adaptation and mitigation strategies designed to maintain stable yields under climate change cannot be properly evaluated. We apply a process-based crop system model that avoids re-initialization bias to demonstrate the importance of simulating both year-to-year and cumulative changes in pre-season soil carbon, nutrient, and water availability. Results are contrasted with simulations using annual re-initialization, and differences are striking. We then demonstrate the potential for the most likely adaptation strategy to offset climate change impacts on yields using continuous simulations through the end of the 21st century. Simulations that annually re-initialize pre-season soil carbon and water contents introduce an inappropriate yield bias that obscures the potential for agricultural management to ameliorate the deleterious effects of rising temperatures and greater rainfall variability.

Data from: Genome-wide single nucleotide polymorphism (SNP) identification and characterization in a non-model organism, the African buffalo (Syncerus caffer), using next generation sequencing

This study aimed to develop a set of SNP markers with high resolution and accuracy within the African buffalo. Such a set can be used, among others, to depict subtle population genetic structure for a better understanding of buffalo population dynamics. In total, 18.5 million DNA sequences of 76 bp were generated by next generation sequencing on an Illumina Genome Analyzer II from a reduced representation library using DNA from a panel of 13 African buffalo representative of the four subspecies. We identified 2534 SNPs with high confidence within the panel by aligning the short sequences to the cattle genome (Bos taurus). The average sequencing depth of the complete aligned set of reads was estimated at 5x, and at 13x when only considering the final set of putative SNPs that passed the filtering criterion. Our set of SNPs was validated by PCR amplification and Sanger sequencing of 15 SNPs. Of these 15 SNPs, 14 amplified successfully and 13 were shown to be polymorphic (success rate: 87%). The fidelity of the identified set of SNPs and potential future applications are finally discussed.

Data from: Energy benefits and emergent space use patterns of an empirically parameterized model of memory-based patch selection

Many species frequently return to previously visited foraging sites. This bias towards familiar areas suggests that remembering information from past experience is beneficial. Such a memory-based foraging strategy has also been hypothesized to give rise to restricted space use (i.e. a home range). Nonetheless, the benefits of empirically derived memory-based foraging tactics and the extent to which they give rise to restricted space use patterns are still relatively unknown. Using a combination of stochastic agent-based simulations and deterministic integro-difference equations, we developed an adaptive link (based on energy gains as a foraging currency) between memory-based patch selection and its resulting spatial distribution. We used a memory-based foraging model developed and parameterized with patch selection data of free-ranging bison Bison bison in Prince Albert National Park, Canada. Relative to random use of food patches, simulated foragers using both spatial and attribute memory are more efficient, particularly in landscapes with clumped resources. However, a certain amount of random patch use is necessary to avoid frequent returns to relatively poor-quality patches, or avoid being caught in a relatively poor quality area of the landscape. Notably, in landscapes with clumped resources, simulated foragers that kept a reference point of the quality of recently visited patches, and returned to previously visited patches when local patch quality was poorer than the reference point, experienced higher energy gains compared to random patch use. Furthermore, the model of memory-based foraging resulted in restricted space use in simulated landscapes and replicated the restricted space use observed in free-ranging bison reasonably well. Our work demonstrates the adaptive value of spatial and attribute memory in heterogeneous landscapes, and how home ranges can be a byproduct of non-omniscient foragers using past experience to minimize temporal variation in energy gains.

opencc-zeroDec 2011View details →

Data from: Exploring foraging decisions in a social primate using discrete choice models

There is a growing appreciation of the multiple social and nonsocial factors influencing the foraging behavior of social animals, but little understanding of how these factors depend on habitat characteristics or individual traits. This partly reflects the difficulties inherent in using conventional statistical techniques to analyze multi-factor, multi-context foraging decisions. Discrete choice models provide a way to do so, and we demonstrate this by using them to investigate patch preference in a wild population of social foragers (chacma baboons, Papio ursinus). Data were collected from 29 adults across two social groups encompassing 683 foraging decisions over a six-month period, and the results interpreted using an information theoretic approach. Baboon foraging decisions were influenced by multiple nonsocial and social factors, and were often contingent on the characteristics of the habitat or individual. Differences in decision-making between habitats were consistent with changes in interference competition costs but not changes in social foraging benefits. Individual differences in decision-making were suggestive of a trade-off between dominance rank and social capital. Our findings emphasize that taking a multi-factor, multi-context approach is important to fully understand animal decision-making. We also demonstrate how discrete choice models can be used to achieve this.

opencc-zeroDec 2013View details →

Data from: Ocean circulation model predicts high genetic structure in a long-lived pelagic developer

Understanding the movement of genes and individuals across marine seascapes is a long-standing challenge in marine ecology, and can inform our understanding of local adaptation, the persistence and movement of populations, and the spatial scale of effective management. Patterns of gene flow in the ocean are often inferred based on population genetic analyses coupled with knowledge of species' dispersive life histories. However, genetic structure is the result of time-integrated processes, and may not capture present-day connectivity between populations. Here we use a high-resolution oceanographic circulation model to predict larval dispersal along the complex coastline of western Canada that includes the transition between two well-studied zoogeographic provinces. We simulate dispersal in a benthic sea star with a 6-10 week pelagic larval phase, and test predictions of this model against previously observed genetic structure including a strong phylogeographic break within the zoogeographical transition zone. We also test predictions with new genetic sampling in a site within the phylogeographic break. We find that the coupled genetic and circulation model predicts the high degree of genetic structure observed in this species, despite its long pelagic duration. High genetic structure on this complex coastline can thus be explained through ocean circulation patterns which tend to retain passive larvae within 20 - 50 km of their parents, suggesting a necessity for close-knit design of Marine Protected Area networks.

opencc-zeroDec 2012View details →

Data from: Population genetic data of a model symbiotic cnidarian system reveal remarkable symbiotic specificity and vectored introductions across ocean basins

The Aiptasia-Symbiodinium symbiosis is a promising model for experimental studies of cnidarian-dinoflagellate associations, yet relatively little is known regarding the genetic diversity of either symbiotic partner. To address this we collected Aiptasia from 17 localities throughout the world and examined the genetic diversity of both anemones and their endosymbionts. Based on newly-developed SCAR markers, Aiptasia consisted of two genetically-distinct populations, one Aiptasia lineage from Florida and a second network of Aiptasia genotypes found at other localities. These populations did not conform to the distributions of described Aiptasia species, suggesting that taxonomic re-evaluation is needed in light of molecular genetics. Associations with Symbiodinium further demonstrated the distinctions among Aiptasia populations. According to 18S-RFLP, ITS2-DGGE, and microsatellite flanker region sequencing, Florida anemones engaged in diverse symbioses predominantly with members of Symbiodinium Clades A and B, but also C, whereas anemones from elsewhere harboured only S. minutum within Clade B. Symbiodinium minutum apparently does not form a stable symbiosis with other hosts, which implies a highly-specific symbiosis. Fine-scale differences among S. minutum populations were quantified using six microsatellite loci. Populations of S. minutum had low genotypic diversity and high clonality (R=0.14). Furthermore, minimal population structure was observed among regions and ocean basins, due to allele and genotype sharing. The lack of genetic structure and low genotypic diversity suggest recent vectoring of Aiptasia and S. minutum across localities. This first ever molecular-genetic study of a globally-distributed cnidarian and its Symbiodinium assemblages reveals host-symbiont specificity and widely-distributed populations in an important model system.

opencc-zeroDec 2016View details →

Data from: Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models

Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations.

Data from: Demography of Euterpe precatoria and Mauritia flexuosa in the Amazon: application of integral projection models for their harvest

Non-Timber Forest Products like palm fruits are fundamental in the livelihood of Amerindian groups. For the last 10 years the fruits of wild palm species, like Euterpe precatoria and Mauritia flexuosa, have been entering into global markets. These species are mostly harvested felling the adults, a practice that may have a disproportionate impact in the conservation of the populations. We studied the demography of E. precatoria and M. flexuosa, two important palms of the Amazon, using integral projection models, to characterize the population dynamics and project impact of different fruit harvest methods: adult felling and direct fruit harvest. We followed over 1400 individuals from populations with low harvest intensities in the Tikuna community of Amacayacu, Amazonas, Colombia from 2011 to 2013, establishing four plots for E. precatoria in seasonally inundated forests and two for M. flexuosa in swamps. The population growth in E. precatoria was slightly declining, whereas M. flexuosa was stable. As expected, the simulations of adult felling diminished λ and the number of available adults under any scenario for either species. On the contrary, the simulations support existing information that climbing and other non-destructive harvest methods would probably allow a sustainable management, satisfying the demand and preserving wild populations.

Data from: An exceptionally preserved Late Devonian actinopterygian provides a new model for primitive cranial anatomy in ray-finned fishes

Actinopterygians (ray-finned fishes) are the most diverse living osteichthyan (bony vertebrate) group, with a rich fossil record. However, details of their earliest history during the middle Palaeozoic (Devonian) 'Age of Fishes' remains sketchy. This stems from an uneven understanding of anatomy in early actinopterygians, with a few well-known species dominating perceptions of primitive conditions. Here we present an exceptionally preserved ray-finned fish from the Late Devonian (Middle Frasnian, ca 373 Ma) of Pas-de-Calais, northern France. This new genus is represented by a single, three-dimensionally preserved skull. CT scanning reveals the presence of an almost complete braincase along with near-fully articulated mandibular, hyoid and gill arches. The neurocranium differs from the coeval Mimipiscis in displaying a short aortic canal with a distinct posterior notch, long grooves for the lateral dorsal aortae, large vestibular fontanelles and a broad postorbital process. Identification of similar but previously unrecognized features in other Devonian actinopterygians suggests that aspects of braincase anatomy in Mimipiscis are apomorphic, questioning its ubiquity as stand-in for generalized actinopterygian conditions. However, the gill skeleton of the new form broadly corresponds to that of Mimipiscis, and adds to an emerging picture of primitive branchial architecture in crown gnathostomes. The new genus is recovered in a polytomy with Mimiidae and a subset of Devonian and stratigraphically younger actinopterygians, with no support found for a monophyletic grouping of Moythomasia with Mimiidae.

Data from: A rapid and scalable method for multilocus species delimitation using Bayesian model comparison and rooted triplets

Multilocus sequence data provide far greater power to resolve species limits than the single locus data typically used for broad surveys of clades. However, current statistical methods based on a multispecies coalescent framework are computationally demanding, because of the number of possible delimitations that must be compared and time-consuming likelihood calculations. New methods are therefore needed to open up the power of multilocus approaches to larger systematic surveys. Here, we present a rapid and scalable method that introduces 2 new innovations. First, the method reduces the complexity of likelihood calculations by decomposing the tree into rooted triplets. The distribution of topologies for a triplet across multiple loci has a uniform trinomial distribution when the 3 individuals belong to the same species, but a skewed distribution if they belong to separate species with a form that is specified by the multispecies coalescent. A Bayesian model comparison framework was developed and the best delimitation found by comparing the product of posterior probabilities of all triplets. The second innovation is a new dynamic programming algorithm for finding the optimum delimitation from all those compatible with a guide tree by successively analyzing subtrees defined by each node. This algorithm removes the need for heuristic searches used by current methods, and guarantees that the best solution is found and potentially could be used in other systematic applications. We assessed the performance of the method with simulated, published, and newly generated data. Analyses of simulated data demonstrate that the combined method has favorable statistical properties and scalability with increasing sample sizes. Analyses of empirical data from both eukaryotes and prokaryotes demonstrate its potential for delimiting species in real cases.

opencc-zeroDec 2018View details →

Data from: Environmental filtering improves ecological niche models across multiple scales

1. A clear challenge for ecological niche modeling is determining how to best mitigate the effects of sampling bias from commonly collected biodiversity data. Recent approaches have focused on filtering occurrences in overrepresented regions based on geographic or environmental proximity. 2. We tested the efficacy of filtering in geographic and environmental space using occurrence data from four species. Our evaluation strategies examined 14 distance measures in geographic and environmental spaces and eight combinations of environmental variables and their ordinations. This resulted in 78 datasets for each species, which we evaluated using area under the curve (AUC), the difference between training and testing AUC, omission rate, the true skill statistic, and Schoener's D to examine the effects of different filtering schemes. 3. The degree of change produced by filtering on predicted suitability and evaluation statistics increased with increasing range size. Environmental filtering resulted in higher model fit at larger extents and retained more occurrences than geographic filtering. 4. Our results indicate that models should be evaluated using multiple evaluation statistics at multiple thresholds. The use of bin sizes when filtering in environmental space allows for simple comparison between species and filter types and makes for an easily reportable and repeatable distance metric. We specifically recommend that ecological niche models using natural history collection data filter in environmental space with variables derived from permutation importance or the first few axes of a principal components ordination.

opencc-zeroDec 2013View details →

Data from: Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.

opencc-zeroDec 2012View details →

Data from: Host resistance, population structure and the long-term persistence of bubonic plague: contributions of a modelling approach in the Malagasy focus

Although bubonic plague is an endemic zoonosis in many countries around the world, the factors responsible for the persistence of this highly virulent disease remain poorly known. Classically, the endemic persistence of plague is suspected to be due to the coexistence of plague resistant and plague susceptible rodents in natural foci, and/or to a metapopulation structure of reservoirs. Here, we test separately the effect of each of these factors on the long-term persistence of plague. We analyse the dynamics and equilibria of a model of plague propagation, consistent with plague ecology in Madagascar, a major focus where this disease is endemic since the 1920s in central highlands. By combining deterministic and stochastic analyses of this model, and including sensitivity analyses, we show that (i) endemicity is favoured by intermediate host population sizes, (ii) in large host populations, the presence of resistant rats is sufficient to explain long-term persistence of plague, and (iii) the metapopulation structure of susceptible host populations alone can also account for plague endemicity, thanks to both subdivision and the subsequent reduction in the size of subpopulations, and extinction-recolonization dynamics of the disease. In the light of these results, we suggest scenarios to explain the localized presence of plague in Madagascar.

opencc-zeroDec 2016View details →

Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling

Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to parameterize SDMs consist of spatially interpolated climate surfaces obtained from ground weather station data and have omitted the Antarctic continent, a landmass covering c. 20% of the Southern Hemisphere and increasingly showing biological effects of global change. Here we introduce MERRAclim, a global set of satellite-based bioclimatic variables including Antarctica for the first time. MERRAclim consists of three datasets of 19 bioclimatic variables that have been built for each of the last three decades (1980s, 1990s and 2000s) using hourly data of 2 m temperature and specific humidity. We provide MERRAclim at three spatial resolutions (10 arc-minutes, 5 arc-minutes and 2.5 arc-minutes). These reanalysed data are comparable to widely used datasets based on ground station interpolations, but allow extending their geographical reach and SDM building in previously uncovered regions of the globe.

Data from: Modeling spatial expansion of invasive alien species: relative contributions of environmental and anthropogenic factors to the spreading of the harlequin ladybird in France

Species distribution models (SDM) have often been used to predict the potential ranges of introduced species and prioritize management strategies. However, this approach assumes equilibrium between occurrences and environmental gradients, an assumption which is violated during the invasion process, where many suitable sites are empty because the species has not yet reached them. Here we considered the invasive ladybird Harmonia axyridis as a case study to show the benefits of using a dynamic colonization–extinction model that does not assume equilibrium. We used a multi-year occupancy model incorporating environmental, anthropogenic and neighborhood effects, to identify factors that explained spreading variation of this species in France from 2004, when only a few occupied sites were detected, to 2011. We found that anthropogenic factors (urbanization, agriculture, vineyards, and presence/absence of highways) explained more variation in the diffusion process than environmental factors (winter and summer temperatures, wind-speed, and rainfall). The surface of urbanization was the major anthropogenic factor increasing the probability of colonization. The average summer temperature was the main environmental factor affecting colonization, with a negative effect when high or low. The neighborhood effect revealed that colonization was mostly influenced by contributions coming from a radius of 24 km around the focal cell. The contribution of neighborhood decreases over time, suggesting that H. axyridis is reaching its equilibrium in France. This is confirmed by the small discrepancy observed between the performance of our approach and a SDM approach when predicting a single year occupancy pattern at the end of the study period. Our approach has the advantage of explicitly modelling the state of the biological system during the spatial expansion and identifying colonization constraints. This allows managers to explore the effect of different actions on the system at key moments of the invasion process, hence providing a powerful approach to prioritize management strategies.

Data from: Can the source-sink hypothesis explain macrofaunal abundance patterns in the abyss? A modeling test

Low food availability is a major structuring force in deep-sea benthic communities, sustaining only very low densities of organisms in parts of the abyss. These low population densities may result in an Allee effect, whereby local reproductive success is inhibited, and populations are maintained by larval dispersal from bathyal slopes. This slope–abyss source–sink (SASS) hypothesis suggests that the abyssal seafloor constitutes a vast sink habitat with macrofaunal populations sustained only by an influx of larval 'refugees' from source areas on continental slopes, where higher productivity sustains greater population densities. Abyssal macrofaunal population densities would thus be directly related to larval inputs from bathyal source populations. We evaluate three predictions derived from the SASS hypothesis: (i) slope-derived larvae can be passively transported to central abyssal regions within a single larval period, (ii) projected larval export from slopes to the abyss reproduces global patterns of macrofaunal abundance and (iii) macrofaunal abundance decreases with distance from the continental slope. We find that abyssal macrofaunal populations are unlikely to be sustained solely through influx of larvae from slope sources. Rather, local reproduction probably sustains macrofaunal populations in relatively high-productivity abyssal areas, which must also be considered as potential larval source areas for more food-poor abyssal regions.

Data from: Demographic modelling with whole-genome data reveals parallel origin of similar Pundamilia cichlid species after hybridization

Modes and mechanisms of speciation are best studied in young species pairs. In older taxa, it is increasingly difficult to distinguish what happened during speciation from what happened after speciation. Lake Victoria cichlids in the genus Pundamilia encompass a complex of young species and polymorphic populations. One Pundamilia species pair, P. pundamilia and P. nyererei, is particularly well suited to study speciation because sympatric population pairs occur with different levels of phenotypic differentiation and reproductive isolation at different rocky islands within the lake. Genetic distances between allopatric island populations of the same nominal species often exceed those between the sympatric species. It thus remained unresolved whether speciation into P. nyererei and P. pundamilia occurred once, followed by geographical range expansion and interspecific gene flow in local sympatry, or if the species pair arose repeatedly by parallel speciation. Here, we use genomic data and demographic modelling to test these alternative evolutionary scenarios. We demonstrate that gene flow plays a strong role in shaping the observed patterns of genetic similarity, including both gene flow between sympatric species and gene flow between allopatric populations, as well as recent and early gene flow. The best supported model for the origin of P. pundamilia and P. nyererei population pairs at two different islands is one where speciation happened twice, whereby the second speciation event follows shortly after introgression from an allopatric P. nyererei population that arose earlier. Our findings support the hypothesis that very similar species may arise repeatedly, potentially facilitated by introgressed genetic variation.

opencc-zeroDec 2011View details →

Data from: Biophysical modeling of the temporal niche: from first principles to the evolution of activity patterns

Most mammals can be characterized as nocturnal or diurnal. However infrequently, species may overcome evolutionary constraints and alter their activity patterns. We modeled the fundamental temporal niche of a diurnal desert rodent, the golden spiny mouse, Acomys russatus. This species can shift into nocturnal activity in the absence of its congener, the common spiny mouse, A. cahirinus, suggesting that it was competitively driven into diurnality, and that this shift in a small desert rodent may involve physiological costs. Therefore, we compared metabolic costs of diurnal vs. nocturnal activity using a biophysical model to evaluate the preferred temporal niche of this species. The model predicted that energy expenditure during foraging is almost always lower during the day except during mid-day in summer at the less sheltered microhabitat. We also found that a shift in summer to foraging in less sheltered microhabitats in response to predation pressure and food availability involves a significant physiological cost moderated by midday reduction in activity. Thus adaptation to diurnality may reflect the 'ghost of competition past'; Climate-driven diurnality is an alternative but less likely hypothesis. While climate is considered to play a major role in the physiology and evolution of mammals, this is the first study to model its effect on the evolution of activity patterns of mammals.

Data from: Genome assembly and annotation of Arabidopsis halleri, a model for heavy metal hyperaccumulation and evolutionary ecology

The self-incompatible species Arabidopsis halleri is a close relative of the self-compatible model plant Arabidopsis thaliana. The broad European and Asian distribution and heavy metal hyperaccumulation ability make A. halleri a useful model for ecological genomics studies. We used long-insert mate-pair libraries to improve the genome assembly of the A. halleri ssp. gemmifera Tada mine genotype (W302) collected from a site with high contamination by heavy metals in Japan. After five rounds of forced selfing, heterozygosity was reduced to 0.04%, which facilitated subsequent genome assembly. Our assembly now covers 196 Mb or 78% of the estimated genome size and achieved scaffold N50 length of 712 kb. To validate assembly and annotation, we used synteny of A. halleri Tada mine with a previously published high-quality reference assembly of a closely related species, Arabidopsis lyrata. Further validation of the assembly quality comes from synteny and phylogenetic analysis of the HEAVY METAL ATPASE4 (HMA4) and METAL TOLERANCE PROTEIN1 (MTP1) regions using published sequences from European A. halleri for comparison. Three tandemly duplicated copies of HMA4, key gene involved in cadmium and zinc hyperaccumulation, were assembled on a single scaffold. The assembly will enhance the genomewide studies of A. halleri as well as the allopolyploid Arabidopsis kamchatica derived from A. lyrata and A. halleri.