Genomic time-series data show that gene flow maintains high genetic diversity despite substantial genetic drift in a butterfly species

Limited Migration From Physiological Refugia Constrains the Rescue of Native Gastropods Facing an Invasive Predator

Biological invasions have caused the loss of freshwater biodiversity worldwide. The interplay between adaptive responses and demographic characteristics of populations impacted by invasions is expected to be important for their resilience, but the interaction between these factors is poorly understood. The freshwater gastropod Amnicola limosus is native to the Upper St. Lawrence River and distributed along a water calcium concentration gradient within which high-calcium habitats are impacted by an invasive predator fish (Neogobius melanostomus, round goby), whereas low-calcium habitats provide refuges for the gastropods from the invasive predator. Our objectives were to (1) test for adaptation of A. limosus to the invasive predator and the low-calcium habitats, and (2) investigate if migrant gastropods could move from refuge populations to declining invaded populations (i.e., demographic rescue), which could also help maintain genetic diversity through gene flow (i.e., genetic rescue). We conducted a laboratory reciprocal transplant of wild F0 A. limosus sourced from the two habitat types (high calcium/invaded and low calcium/refuge) to measure adult survival and fecundity in home and transplant treatments of water calcium concentration (low/high) and round goby cue (present/absent). We then applied pooled whole-genome sequencing of 12 gastropod populations from across the calcium/invasion gradient. We identified patterns of life-history traits and genetic differentiation across the habitats that are consistent with local adaptation to low-calcium concentrations in refuge populations and to round goby predation in invaded populations. We also detected restricted gene flow from the low-calcium refugia towards high-calcium invaded populations, implying that the potential for demographic and genetic rescue is limited by natural dispersal. Our study highlights the importance of considering the potentially conflicting effects of local adaptation and gene flow for the resilience of populations coping with invasive predators.

Boom-bust population dynamics drive rapid genetic change

Increasing environmental threats and more extreme environmental perturbations place species at risk of population declines, with associated loss of genetic diversity and evolutionary potential. While theory shows that rapid population declines can cause loss of genetic diversity, populations in some environments, like Australia's arid zone, are repeatedly subject to major population fluctuations yet persist and appear able to maintain genetic diversity. Here, we use repeated population sampling over 13 y and genotype-by-sequencing of 1903 individuals to investigate the genetic consequences of repeated population fluctuations in two small mammals in the Australian arid zone. The sandy inland mouse (Pseudomys hermannsburgensis) experiences marked boom-bust population dynamics in response to the highly variable desert environment. We show that heterozygosity levels declined, and population differentiation (FST) increased, during bust periods when populations became small and isolated, but that heterozygosity was rapidly restored during episodic population booms. In contrast, the lesser hairy-footed dunnart (Sminthopsis youngsoni), a desert marsupial that maintains relatively stable population sizes, showed no linear declines in heterozygosity. These results reveal two contrasting ways in which genetic diversity is maintained in highly variable environments. In one species, diversity is conserved through the maintenance of stable population sizes across time. In the other species, diversity is conserved through rapid genetic mixing during population booms that restores heterozygosity lost during population busts.

Considerable genetic diversity and structure despite narrow endemism and limited ecological specialization in the Hayden's ringlet, Coenonympha haydenii

Understanding the processes that underlie the development of population genetic structure is central to the study of evolution. Patterns of genetic structure, in turn, can reveal signatures of isolation by distance (IBD), barriers to gene flow, or even the genesis of speciation. However, it is unclear how severe range restriction might impact the processes that dominate the development of genetic structure. In narrow endemic species, is population structure likely to be adaptive in nature, or rather the result of genetic drift? In this study, we investigated patterns of genetic diversity and structure in the narrow endemic Hayden's ringlet butterfly. Specifically, we asked to what degree genetic structure in the Hayden's ringlet can be explained by IBD, isolation by resistance (IBR) (in the form of geographic or ecological barriers to migration between populations), and isolation by environment (in the form of differences in host plant availability and preference). We employed a genotyping-by-sequencing (GBS) approach coupled with host preference assays, Bayesian modelling, and population genomic analyses to answer these questions. Our results suggest that despite their restricted range, levels of genetic diversity in the Hayden's ringlet are comparable to those seen in more widespread butterfly species. Hayden's ringlets showed a strong preference for feeding on grasses relative to sedges, but neither larval preference nor potential host availability at sampling sites correlated with genetic structure. We conclude that geography, in the form of IBR and simple IBD, was the major driver of contemporary patterns of differentiation in this narrow endemic species.

Spatial variation in population genomic responses to over a century of anthropogenic change within a tidal marsh songbird

Combating the current biodiversity crisis requires the accurate documentation of population responses to human-induced ecological change. However, our ability to pinpoint population responses to human activities is often limited to the analysis of populations studied well after the fact. Museum collections preserve a record of population responses to anthropogenic change that can provide critical baseline data on patterns of genetic diversity, connectivity, and population structure prior to the onset of human perturbation. Here, we leverage a spatially replicated time series of specimens to document population genomic responses to the destruction of nearly 90% of coastal habitats occupied by the Savannah sparrow (Passerculus sandwichensis) in California. We sequenced 219 sparrows collected from 1889 to 2017 across the state of California using an exome capture approach. Spatial-temporal analyses of genetic diversity found that the amount of habitat lost was not predictive of genetic diversity loss. Sparrow populations from southern California historically exhibited lower levels of genetic diversity and experienced the most significant temporal declines in genetic diversity. Despite experiencing the greatest levels of habitat loss, we found that genetic diversity in the San Francisco Bay area remained relatively high. This was potentially related to an observed increase in gene flow into the Bay Area from other populations. While gene flow may have minimized genetic diversity declines, we also found that immigration from inland freshwater-adapted populations into tidal marsh populations led to the erosion of divergence at loci associated with tidal marsh adaptation. Shifting patterns of gene flow through time in response to habitat loss may thus contribute to negative fitness consequences and outbreeding depression. Together, our results underscore the importance of tracing the genomic trajectories of multiple populations over time to address issues of fundamental conservation concern.

Out to sea: ocean currents and patterns of asymmetric gene flow in an intertidal fish species

Passive dispersal via wind or ocean currents can drive asymmetric gene flow, which influences patterns of genetic variation and the capacity of populations to evolve in response to environmental change. The mangrove rivulus fish (Kryptolebias marmoratus), hereafter "rivulus," is an intertidal fish species restricted to the highly fragmented New World mangrove forests of Central America, the Caribbean, the Bahamas, and Florida. Mangrove patches are biological islands with dramatic differences in both abiotic and biotic conditions compared to adjacent habitat. Over 1,000 individual rivulus across 17 populations throughout its range were genotyped at 32 highly polymorphic microsatellites. Range-wide population genetic structure was evaluated with five complementary approaches that found eight distinct population clusters. However, an analysis of molecular variance indicated significant population genetic structure among regions, populations within regions, sampling locations within populations, and individuals within sampling locations, indicating that rivulus has both broad- and fine-scale genetic differentiation. Integrating range-wide genetic data with biophysical modeling based on 10 years of ocean current data showed that ocean currents and the distance between populations over water drive gene flow patterns on broad scales. Directional migration estimates suggested some significant asymmetries in gene flow that also were mediated by ocean currents and distance. Specifically, populations in the center of the range (Florida Keys) were identified as sinks that received migrants (and alleles) from other populations but failed to export individuals. These populations thus harbor genetic variation, perhaps even from extirpated populations across the range, but ocean currents and complex arrangements of landmasses might prevent the distribution of that genetic variation elsewhere. Hence, the inherent asymmetry of ocean currents shown to impact both genetic differentiation and directional migration rates may be responsible for the complex distribution of genetic variation across the range and observed patterns of metapopulation structure.

Variance effective population size is affected by census size in sub-structured populations

Measurement of allele frequency shifts between temporally spaced samples has long been used for assessment of effective population size (N_e ), and this 'temporal method' provides estimates of N_e referred to as variance effective size (N_eV ). We show that N_eV of a local population that belongs to a sub-structured population (a metapopulation) is determined not only by genetic drift and migration rate (m), but also by the census size (N_c ). The realized N_eV of a local population can either increase or decrease with increasing m, depending on the relationship between N_e and N_c in isolation. This is shown by explicit mathematical expressions for the factors affecting N_eV derived for an island model of migration. We verify analytical results using high-resolution computer simulations, and show that the phenomenon is not restricted to the island model migration pattern. The effect of N_c on the realized N_eV of a local subpopulation is most pronounced at high migration rates. We show that N_c only affects local N_eV , whereas N_eV for the metapopulation as a whole, inbreeding (N_eI ), and linkage disequilibrium (N_eLD ) effective size are all independent of N_c . Our results provide a possible explanation to the large variation of N_e /N_c ratios reported in the literature, where N_e is frequently estimated by N_eV . They are also important for the interpretation of empirical N_e estimates in genetic management where local N_eV is often used as a substitute for inbreeding effective size, and we suggest an increased focus on metapopulation N_eV as a proxy for N_eI .

The Biological Hierarchy, Time, and Temporal 'Omics in Evolutionary Biology: A Perspective

Sequencing data-genomics, transcriptomics, epigenomics, proteomics, and metabolomics-have revolutionized biological research, enabling a more detailed study of processes, ranging from subcellular to evolutionary, that drive biological organization. These processes, collectively, are responsible for generating patterns of phenotypic variation and can operate over dramatically different timescales (milliseconds to billions of years). While researchers often study phenotypic variation at specific levels of biological organization to isolate processes operating at that particular scale, the varying types of sequence data, or 'omics, can also provide complementary inferences to link molecular and phenotypic variation to produce an integrated view of evolutionary biology, ranging from molecular pathways to speciation. We briefly describe how 'omics has been used across biological levels and then demonstrate the utility of integrating different types of sequencing data across multiple biological levels within the same study to better understand biological phenomena. However, single-time-point studies cannot evaluate the temporal dynamics of these biological processes. Therefore, we put forward temporal 'omics as a framework that can better enable researchers to study the temporal dynamics of target processes. Temporal 'omics is not infallible, as the temporal sampling regime directly impacts inferential ability. Thus, we also discuss the role the temporal sampling regime plays in deriving inferences about the environmental conditions driving biological processes and provide examples that demonstrate the impact of the sampling regime on biological inference. Finally, we forecast the future of temporal 'omics by highlighting current methodological advancements that will enable temporal 'omics to be extended across species and timescales. We extend this discussion to using temporal multi-omics to integrate across the biological hierarchy to evaluate and link the temporal dynamics of processes that generate phenotypic variation.

Monitoring genetic diversity with new indicators applied to an alpine freshwater top predator

Genetic diversity is the basis for population adaptation and long-term survival, yet rarely considered in biodiversity monitoring. One key issue is the need for useful and straightforward indicators of genetic diversity. We monitored genetic diversity over 40 years (1970-2010) in metapopulations of brown trout (Salmo trutta) inhabiting 27 small mountain lakes representing 10 lake systems in central Sweden using >1200 fish per time point. We tested six newly proposed indicators; three were designed for broad, international use in the UN Convention on Biological Diversity (CBD) and are currently applied in several countries. The other three were recently elaborated for national use by a Swedish science-management effort and applied for the first time here. The Swedish indicators use molecular genetic data to monitor genetic diversity within and between populations (indicators ΔH and ΔF_ST , respectively) and assess the effective population size (N_e -indicator). We identified 29 genetically distinct populations, all retained over time. Twelve of the 27 lakes harboured more than one population indicating that brown trout biodiversity hidden as cryptic, sympatric populations are more common than recognized. The N_e indicator showed values below the threshold (N_e  ≤ 500) in 20 populations with five showing N_e  < 100. Statistically significant genetic diversity reductions occurred in several populations. Metapopulation structure appears to buffer against diversity loss; applying the indicators to metapopulations suggest mostly acceptable rates of change in all but one system. The CBD indicators agreed with the Swedish ones but provided less detail. All these indicators are appropriate for managers to initiate monitoring of genetic biodiversity.

Laplace's demon in biology: Models of evolutionary prediction

Our ability to predict natural phenomena can be limited by incomplete information. This issue is exemplified by "Laplace's demon," an imaginary creature proposed in the 18th century, who knew everything about everything, and thus could predict the full nature of the universe forward or backward in time. Quantum mechanics, among other things, has cast doubt on the possibility of Laplace's demon in the full sense, but the idea still serves as a useful metaphor for thinking about the extent to which prediction is limited by incomplete information on deterministic processes versus random factors. Here, we use simple analytical models and computer simulations to illustrate how data limits can be captured in a Bayesian framework, and how they influence our ability to predict evolution. We show how uncertainty in measurements of natural selection, or low predictability of external environmental factors affecting selection, can greatly reduce predictive power, often swamping the influence of intrinsic randomness caused by genetic drift. Thus, more accurate knowledge concerning the causes and action of natural selection is key to improving prediction. Fortunately, our analyses and simulations show quantitatively that reasonable improvements in data quantity and quality can meaningfully increase predictability.

Minor Genetic Consequences of a Major Mass Mortality: Short-Term Effects in Pisaster ochraceus

AbstractMass mortality events are increasing globally in frequency and magnitude, largely as a result of human-induced change. The effects of these mass mortality events, in both the long and short term, are of imminent concern because of their ecosystem impacts. Genomic data can be used to reveal some of the population-level changes associated with mass mortality events. Here, we use reduced-representation sequencing to identify potential short-term genetic impacts of a mass mortality event associated with a sea star wasting outbreak. We tested for changes in the population for genetic differentiation, diversity, and effective population size between pre-sea star wasting and post-sea star wasting populations of Pisaster ochraceus-a species that suffered high sea star wasting-associated mortality (75%-100% at 80% of sites). We detected no significant population-based genetic differentiation over the spatial scale sampled; however, the post-sea star wasting population tended toward more differentiation across sites than the pre-sea star wasting population. Genetic estimates of effective population size did not detectably change, consistent with theoretical expectations; however, rare alleles were lost. While we were unable to detect significant population-based genetic differentiation or changes in effective population size over this short time period, the genetic burden of this mass mortality event may be borne by future generations, unless widespread recruitment mitigates the population decline. Prior results from P. ochraceus indicated that natural selection played a role in altering allele frequencies following this mass mortality event. In addition to the role of selection found in a previous study on the genomic impacts of sea star wasting on P. ochraceus, our current study highlights the potential role the stochastic loss of many individuals plays in altering how genetic variation is structured across the landscape. Future genetic monitoring is needed to determine long-term genetic impacts in this long-lived species. Given the increased frequency of mass mortality events, it is important to implement demographic and genetic monitoring strategies that capture baselines and background dynamics to better contextualize species' responses to large perturbations.

On the macroecological significance of eco-evolutionary dynamics: the range shift-niche breadth hypothesis

Global correlations of range size and niche breadth, and their relationship to latitude, have long intrigued ecologists and biogeographers. Study of these patterns has given rise to a number of hypothesized ecological and evolutionary processes purported to shape biogeographic outcomes, including the climate variability hypothesis, oscillation hypothesis, ecological opportunity, competitive release and taxon cycles. Here, I introduce the alternative range shift-niche breadth hypothesis, which posits that broader niches and larger range sizes are jointly determined under eco-evolutionary processes unique to expanding ranges, which may or may not be adaptive, but which co-shape observed latitudinal gradients in niche breadth and range size during periods of widespread range expansion. I formulate this hypothesis in comparison against previous hypotheses, exploring how each relies on equilibrium versus non-equilibrium evolutionary processes, faces differing issues of definition and scale, and results in alternative predictions for comparative risk and resilience of global ecosystems. Such differences highlight that accurate understanding of process is critical when applying macroecological insight to biodiversity forecasting. Furthermore, past conceptual emphasis on a central role of local adaptation under equilibrium conditions may have obscured a ubiquitous role of non-equilibrium evolutionary processes for generating many important, regional and global macroecological patterns. This article is part of the theme issue 'Species' ranges in the face of changing environments (part I)'.