Geology topics

Erin L. Landguth

Publications and source records attributed to Erin L. Landguth.

9 recordsLinked to original sources

USGS2025

Population genomics reveals local adaptation related to temperature variation in two stream frog species: Implications for vulnerability to climate warming

Identifying populations at highest risk from climate change is a critical component of conservation efforts. However, vulnerability assessments are usually applied at the species level, even though intraspecific variation in exposure, sensitivity and adaptive capacity play a crucial role in determining vulnerability. Genomic data can inform intraspecific vulnerability by identifying signatures of local adaptation that reflect population-level variation in sensitivity and adaptive capacity. Here, we address the question of local adaptation to temperature and the genetic basis of thermal tolerance in two stream frogs ( Ascaphus truei and A. montanus ). Building on previous physiological and temperature data, we used whole-genome resequencing of tadpoles from four sites spanning temperature gradients in each species to test for signatures of local adaptation. To support these analyses, we developed the first annotated reference genome for A. truei . We then expanded the geographic scope of our analysis using targeted capture at an additional 11 sites per species. We found evidence of local adaptation to temperature based on physiological and genomic data in A. montanus and genomic data in A. truei , suggesting similar levels of sensitivity (i.e., susceptibility) among populations regardless of stream temperature. However, invariant thermal tolerances across temperatures in A. truei suggest that populations occupying warmer streams may be most sensitive. We identified high levels of evolutionary potential in both species based on genomic and physiological data. While further integration of these data is needed to comprehensively evaluate spatial variation in vulnerability, this work illustrates the value of genomics in identifying spatial patterns of climate change vulnerability.

Idaho, Montana, Oregon, Washington↗

USGS2019

Simulating demography, genetics, and spatially explicit processes to inform reintroduction of a threatened char

The success of species reintroductions can depend on a combination of environmental, demographic, and genetic factors. Although the importance of these factors in the success of reintroductions is well‐accepted, they are typically evaluated independently, which can miss important interactions. For species that persist in metapopulations, movement through and interaction with the landscape is predicted to be a vital component of persistence. Simulation‐based approaches are a promising technique for evaluating the independent and combined effects of these factors on the outcome of various reintroduction and associated management actions. We report results from a simulation study of bull trout ( Salvelinus confluentus ) reintroduction to three watersheds of the Pend Oreille River system in northeastern Washington State, USA. We used an individual‐based, spatially explicit simulation model to evaluate how reintroduction strategies, life history variation, and riverscape structure (e.g., network topology) interact to influence the demographic and genetic characteristics of reintroduced bull trout populations in three watersheds. Simulation scenarios included a range of initial genetic stocks (informed by empirical bull trout genetic data), variation in migratory tendency and life history, and two landscape connectivity alternatives representing a connected network (isolation‐by‐distance) and a fragmented network (isolation‐by‐barrier, using the known existing barriers). A novel feature of these simulations was the ability to consider the interaction of both demographic and genetic (i.e., demogenetic) factors in riverscapes with implicit asymmetric movement probabilities across the barriers. We found that connectivity (presence or absence of barriers) had the largest effect on demographic and genetic outcomes over 200 yr, with a greater effect than both initial genetic diversity and life history variation. We also identified regions of the study system in which bull trout populations persisted across a wide range of demographic, life history, and environmental connectivity parameters. Finally, we found no evidence that initial neutral genetic diversity influenced genetic diversity and structure after 200 yr; instead, genetic drift due to stray rate and population isolation dominated and erased any initial differences in genetic diversity. Our results highlight the utility of spatially explicit demogenetic approaches in exploring and understanding population dynamics—and their implications for management strategies—in fresh waters.

Washington↗

USGS2016

Applications of genetic data to improve management and conservation of river fishes and their habitats

Environmental variation and landscape features affect ecological processes in fluvial systems; however, assessing effects at management-relevant temporal and spatial scales is challenging. Genetic data can be used with landscape models and traditional ecological assessment data to identify biodiversity hotspots, predict ecosystem responses to anthropogenic effects, and detect impairments to underlying processes. We show that by combining taxonomic, demographic, and genetic data of species in complex riverscapes, managers can better understand the spatial and temporal scales over which environmental processes and disturbance influence biodiversity. We describe how population genetic models using empirical or simulated genetic data quantify effects of environmental processes affecting species diversity and distribution. Our summary shows that aquatic assessment initiatives that use standardized data sets to direct management actions can benefit from integration of genetic data to improve the predictability of disturbance–response relationships of river fishes and their habitats over a broad range of spatial and temporal scales.

Fisheries↗

USGS2014

Combining demographic and genetic factors to assess population vulnerability in stream species

Accelerating climate change and other cumulative stressors create an urgent need to understand the influence of environmental variation and landscape features on the connectivity and vulnerability of freshwater species. Here, we introduce a novel modeling framework for aquatic systems that integrates spatially explicit, individual‐based, demographic and genetic (demogenetic) assessments with environmental variables. To show its potential utility, we simulated a hypothetical network of 19 migratory riverine populations (e.g., salmonids) using a riverscape connectivity and demogenetic model (CDFISH). We assessed how stream resistance to movement (a function of water temperature, fluvial distance, and physical barriers) might influence demogenetic connectivity, and hence, population vulnerability. We present demographic metrics (abundance, immigration, and change in abundance) and genetic metrics (diversity, differentiation, and change in differentiation), and combine them into a single vulnerability index for identifying populations at risk of extirpation. We considered four realistic scenarios that illustrate the relative sensitivity of these metrics for early detection of reduced connectivity: (1) maximum resistance due to high water temperatures throughout the network, (2) minimum resistance due to low water temperatures throughout the network, (3) increased resistance at a tributary junction caused by a partial barrier, and (4) complete isolation of a tributary, leaving resident individuals only. We then applied this demogenetic framework using empirical data for a bull trout ( Salvelinus confluentus ) metapopulation in the upper Flathead River system, Canada and USA, to assess how current and predicted future stream warming may influence population vulnerability. Results suggest that warmer water temperatures and associated barriers to movement (e.g., low flows, dewatering) are predicted to fragment suitable habitat for migratory salmonids, resulting in the loss of genetic diversity and reduced numbers in certain vulnerable populations. This demogenetic simulation framework, which is illustrated in a web‐based interactive mapping prototype, should be useful for evaluating population vulnerability in a wide variety of dendritic and fragmented riverscapes, helping to guide conservation and management efforts for freshwater species.

Montana↗

USGS2014

Sex-biased gene flow among elk in the greater Yellowstone ecosystem

We quantified patterns of population genetic structure to help understand gene flow among elk populations across the Greater Yellowstone Ecosystem. We sequenced 596 base pairs of the mitochondrial control region of 380 elk from eight populations. Analysis revealed high mitochondrial DNA variation within populations, averaging 13.0 haplotypes with high mean gene diversity (0.85). The genetic differentiation among populations for mitochondrial DNA was relatively high ( F ST = 0.161; P = 0.001) compared to genetic differentiation for nuclear microsatellite data ( F ST = 0.002; P = 0.332), which suggested relatively low female gene flow among populations. The estimated ratio of male to female gene flow ( m m / m f = 46) was among the highest we have seen reported for large mammals. Genetic distance (for mitochondrial DNA pairwise F ST ) was not significantly correlated with geographic (Euclidean) distance between populations (Mantel's r = 0.274, P = 0.168). Large mitochondrial DNA genetic distances (e.g., F ST > 0.2) between some of the geographically closest populations (<65 km) suggested behavioral factors and/or landscape features might shape female gene flow patterns. Given the strong sex-biased gene flow, future research and conservation efforts should consider the sexes separately when modeling corridors of gene flow or predicting spread of maternally transmitted diseases. The growing availability of genetic data to compare male vs. female gene flow provides many exciting opportunities to explore the magnitude, causes, and implications of sex-biased gene flow likely to occur in many species.

Yellowstone National Park↗

USGS2012

Sample design effects in landscape genetics

An important research gap in landscape genetics is the impact of different field sampling designs on the ability to detect the effects of landscape pattern on gene flow. We evaluated how five different sampling regimes (random, linear, systematic, cluster, and single study site) affected the probability of correctly identifying the generating landscape process of population structure. Sampling regimes were chosen to represent a suite of designs common in field studies. We used genetic data generated from a spatially-explicit, individual-based program and simulated gene flow in a continuous population across a landscape with gradual spatial changes in resistance to movement. Additionally, we evaluated the sampling regimes using realistic and obtainable number of loci (10 and 20), number of alleles per locus (5 and 10), number of individuals sampled (10-300), and generational time after the landscape was introduced (20 and 400). For a simulated continuously distributed species, we found that random, linear, and systematic sampling regimes performed well with high sample sizes (>200), levels of polymorphism (10 alleles per locus), and number of molecular markers (20). The cluster and single study site sampling regimes were not able to correctly identify the generating process under any conditions and thus, are not advisable strategies for scenarios similar to our simulations. Our research emphasizes the importance of sampling data at ecologically appropriate spatial and temporal scales and suggests careful consideration for sampling near landscape components that are likely to most influence the genetic structure of the species. In addition, simulating sampling designs a priori could help guide filed data collection efforts.

Conservation Genetics↗

USGS2012

A fine-scale assessment of using barriers to conserve native stream salmonids: a case study in Akokala Creek, Glacier National Park, USA

Biologists are often faced with the difficult decision in managing native salmonids of where and when to install barriers as a conservation action to prevent upstream invasion of nonnative fishes. However, fine-scale approaches to assess long-term persistence of populations within streams and watersheds chosen for isolation management are often lacking. We employed a spatially-explicit approach to evaluate stream habitat conditions, relative abundance, and genetic diversity of native westslope cutthroat trout (Oncorhynchus clarkii lewisi) within the Akokala Creek watershed in Glacier National Park- a population threatened by introgressive hybridization with nonnative rainbow trout (O. mykiss) from nearby sources. The systematic survey of 24 stream reaches showed broad overlap in fish population and suitable habitat characteristics among reaches and no natural barriers to fish migration were found. Analysis of population structure using 16 microsatellite loci showed modest amounts of genetic diversity among reaches, and that fish from Long Bow Creek were the only moderately distinct genetic group. We then used this information to assess the potential impacts of three barrier placement scenarios on long-term population persistence and genetic diversity. The two barrier placement scenarios in headwater areas generally failed to meet general persistence criteria for minimum population size (2,500 individuals, Ne = 500), maintenance of long-term genetic diversity (He), and no population subdivision. Conversely, placing a barrier near the stream mouth and selectively passing non-hybridized, migratory spawners entering Akokala Creek met all persistence criteria and may offer the best option to conserve native trout populations and life history diversity. Systematic, fine-scale stream habitat, fish distribution, and genetic assessments in streams chosen for barrier installation are needed in conjunction with broader scale assessments to understand the potential impacts of using barriers for conservation of native salmonid populations threatened by nonnative fish invasions.

Open Fish Science Journal↗

USGS2011

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r , but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.

Molecular Ecology Resources↗

USGS2011

CDFISH: an individual-based, spatially-explicit, landscape genetics simulator for aquatic species in complex riverscapes

We introduce Cost Distance FISHeries (CDFISH), a simulator of population genetics and connectivity in complex riverscapes for a wide range of environmental scenarios of aquatic organisms. The spatially-explicit program implements individual-based genetic modeling with Mendelian inheritance and k -allele mutation on a riverscape with resistance to movement. The program simulates individuals in subpopulations through time employing user-defined functions of individual migration, reproduction, mortality, and dispersal through straying on a continuous resistance surface.

Conservation Genetics Resources↗