Pacific salmon hatcheries aim to supplement declining wild populations and support commercial and recreational fisheries. However, there are also risks associated with hatcheries because the captive and wild environments are inherently different. It is important to understand these risks in order to maximize the success of hatcheries. Inbreeding, which occurs when related individuals interbreed, is one risk that may inadvertently be higher in hatcheries due to space limitations and other factors. Inbred fish may have reduced fitness and survival compared to non-inbred fish. We quantified inbreeding and its effect on key fitness traits across four generations in two hatchery populations of adult Chinook salmon that were derived from the same source. We utilized recent advancements in DNA sequencing technology, which provide much more precise estimates of inbreeding and its potential effects on fitness. Our results indicate that inbreeding may not be severe in salmon hatcheries, even small ones, provided that appropriate management practices are followed. However, we documented an influence of inbreeding on the phenology of adult spawners, which could have biological implications for individual fitness and population productivity. Our findings provide a better understanding of changes that may occur in hatchery salmon and will further inform research on “best” hatchery practices to minimize potential risks.
Article: Waters CD, Hard JJ, Fast DE, Knudsen CM, Bosch WJ, Naish KA. 2020. Genomic and phenotypic effects of inbreeding across two different hatchery management regimes in Chinook salmon. Molecular Ecology https://doi.org/10.1111/mec.15356.
Genetic variation in natural systems is complex and affected by a variety of processes, and this reality has contributed to the growing popularity of simulation-based approaches that can help researchers understand the processes acting in their systems. Despite the flexibility of simulation-based approaches, simulations of natural selection across a heterogeneous landscape have typically been limited to one or two loci (e.g. Landguth, Cushman, & Johnson, 2012). In a recent issue of Molecular Ecology Resources, Landguth et al. introduce an approach to model multilocus selection in a spatially-explicit, individual-based framework, implemented in the programs CDPOP and CDMetaPOP. Read the interview with lead author Erin Landguth below to learn about the challenges in developing this program, the potential of this approach to help understand complex genotype-environment associations, and the benefits of working with strong multidisciplinary team! Read the full article here.
What led to your interest in this topic / what was the motivation for this study?
Over the last two decades, there has been an exponential increase in landscape genetic studies, and still, the methodology and underlying theory of the field are under rapid and constant development. Furthermore, interest in simulating multilocus selection, including the ability to model more complex and realistic multivariate environmental scenarios, has been driven by the growing number of empirical genomic data sets derived from next-generation sequencing. We believe many of the major questions in landscape genetics require the development and application of sophisticated simulation tools to explore the interaction of gene flow, genetic drift, mutation, and natural selection in landscapes with a wide range of spatial and temporal complexities. Our interests lie in developing such tools and providing more flexible models that are linked to theory, and that better represent complex genetic variation in real systems. For example, adaptive traits often have a complex genetic basis that interacts with selection strength, gene flow, drift, and mutation rate in a multivariate environmental context; and this module provides the ability to simulate these processes across many adaptive and neutral loci in a landscape genetic context.
What difficulties did you run into along the way?
When developing new modules for existing software packages, my first and primary goal is to validate these modules to theory where possible. This can take some time and many decisions, questions, and trial and errors come up along the way through this very important validation process. For multilocus selection, our validation process was to match simulation output with the theoretical expected change in allele frequencies for selection models developed by Sewall Wright in 1935. If the module is placed in the wrong location in the simulation workflow (i.e., timing) or if all of the Wright-Fisher assumptions are not matched exactly, then the simulation output will not match theoretical expectations. However, once all of these pieces are lined up, there is definitely a eureka moment, and I am then confident in the module’s performance for more complex scenarios where we will not be able to evaluate against theoretical expectations.
What is the biggest or most surprising innovation highlighted in this study?
Multivariate environmental selection can produce complex landscape genetic patterns, even when only a few adaptive loci are involved. The relatively simple “complex” example simulated in the paper illustrates how complicated the underlying relationships can be between allele frequencies and environmental conditions. Simulating these complex relationships will be essential for testing genotype-environment association methods in a more rigorous fashion than has been seen so far. Additionally, the ability to simulate realistic landscape genetic scenarios that reflect the environmental complexity of actual landscapes will be important for validating findings from empirical data sets.
Moving forward, what are the next steps in this area of research?
Epigenetics! We of course have a number of applications in progress for this current module, but we have already started beta testing our next module for simulating epigenetic processes in landscape genetics.
What would your message be for students about to start developing or using novel techniques in Molecular Ecology?
Starting a simulation study in landscape genetics for the first time can be daunting and intimidating. Fear not, we say! As with all software packages, there will be a learning curve, but if you persevere and get past the first few hurdles (e.g., learning the ins and outs of file formats, running the program in a potentially unfamiliar programming interface), the door will be opened to unlimited questions that can be addressed with simulations in your system. Additionally, just like any other field study or experiment, simulation modeling is most informative when coupled with specific questions and hypotheses and well-thought-out study designs.
What have you learned about methods and resources development over the course of this project?
As we begin to add more complex modules to these simulation platforms, I am increasingly relying on multidisciplinary approaches and teams. For example, development of this current module required Brenna Forester for her expertise in landscape ecology and genotype-by-environment concepts, as well as Andrew Eckert, with his in-depth knowledge of population genetics theory, particularly the history of additive vs. multiplicative models for fitness.
Describe the significance of this research for the general scientific community in one sentence.
We have implemented a new module into the landscape genetic simulation programs CDPOP and CDMetaPOP that allows realistic multivariate environmental gradients to drive selection in a multilocus, individual-based, landscape genetic framework.
Describe the significance of this research for your scientific community in one sentence.
This new simulation module provides a valuable addition to the study of landscape genetics, allowing for explicit evaluation of the contributions and interactions between demography, gene flow, and selection-driven processes across multilocus genetic architectures and complex, multivariate environmental and landscape conditions.
Landguth EL, Forester BR, Eckert AJ, et al. (2020). Modelling multilocus selection in an individual-based, spatially-explicit landscape genetics framework. Molecular Ecology Resources, 20, 605–615. https://doi.org/10.1111/1755-0998.13121
Nominations are now open for the annual Molecular Ecology Prize.
The field of molecular ecology is young and inherently interdisciplinary. As a consequence, research in molecular ecology is not currently represented by a single scientific society, so there is no body that actively promotes the discipline or recognizes its pioneers. The editorial board of the journal Molecular Ecology therefore created the Molecular Ecology Prize in order to fill this void, and recognize significant contributions to this area of research. The prize selection committee is independent of the journal and its editorial board.
The prize will go to an outstanding scientist who has made significant contributions to molecular ecology. These contributions would mostly be scientific, but the door is open for other kinds of contributions that were crucial to the development of the field. The previous winners are: Godfrey Hewitt, John Avise, Pierre Taberlet, Harry Smith, Terry Burke, Josephine Pemberton, Deborah Charlesworth, Craig Moritz, Laurent Excoffier, Johanna Schmitt, Fred Allendorf, Louis Bernatchez, Nancy Moran, Robin Waples, and Scott Edwards.
Please send your nomination with a short supporting statement (no more than 250 words; longer submissions will not be accepted) and the candidate’s CV directly to Andrea Sweigart (email@example.com) by Thursday, April 2, 2020. Organized campaigns to submit multiple nominations for the same person are not necessary and can be counterproductive. Also, note that nominations from previous years do not roll over.
With thanks on behalf of the Molecular Ecology Prize Selection Committee
In an article published recently in the latest issue of Molecular Ecology, researchers from Researchers from the Leibniz Institute for Zoo and Wildlife Research and the Luxembourg National Museum of Natural History investigated differences between urban and rural red fox populations. They found that physical barriers in both habitats, such as a river or road, limited fox movement, and also that human activities influenced where foxes moved. This is important because it means that the interaction between human activity and other structures on the landscape may negatively alter the fox populations. For more information, please see the full article and the interview with lead author Sophia Kimmig below.
What led to your interest in this topic / what was the motivation for this study? Human population growth and land use are altering ecosystems worldwide and although continuing urbanization results in dramatic environmental changes, some species seem to cope well with the anthropogenic pressure. Foxes are distributed over the entire metropolitan area of Berlin, therefore it is usually assumed that they cope well with human presence. However, city life can affect key aspects of wildlife ecology and have substantial impact on the movement ecology and dispersal ability of populations. Dispersal in urban areas may be influenced by physical barriers, but also by behavioural barriers that we cannot directly see. Thus species that are physically capable of crossing the urban matrix may nevertheless face behavioural barriers due to avoidance of man-made objects (with their artificial structure, scents etc.) as well as human presence per se. We therefore wanted to understand how the landscape influences gene flow patterns in red foxes across the urban-rural matrix.
What difficulties did you run into along the way? With an increasing number of population genetic clustering approaches and R packages that differ in their precise working mechanisms, it becomes more challenging to interpret diverging results and recognize biological patterns. Further, the promising and fascinating possibilities of modelling gene flow through the landscape also come with uncertainties in how to deal with certain circumstances or type of data. For example, we discuss the issue of dealing with overlapping landscape features in the studied environment i.e. linear landscape elements (such as roads or rivers) that cross a surface structured landscape element (e.g. a forest or park). Especially in urban areas, the habitat has such a high level of complexity that you could easily spend years modelling and testing different land use layers.
What is the biggest or most surprising innovation highlighted in this study? Regarding the fox in the Berlin Metropolitan area: Foxes are quite common in urban areas, so we presumed that there would be few dispersal barriers in the urban environment. Our results have nevertheless shown that foxes disperse preferentially along linear landscape elements such as motorways and railway lines despite the inherent mortality risk. We interpreted this to mean that even urban foxes avoid the presence of humans if possible. Regarding a broader, biological perspective: Although we have to further improve our methods (for our study, for example, by including data on population densities, road traffic or other proxies of human presence and activity), it is fascinating that molecular genetic methods may enable us to answer more questions in behavioural ecology in the future.
Moving forward, what are the next steps in this area of research? Now that we have familiarised ourselves with the landscape genetic techniques, we are looking forward to applying the approaches to a broad range of taxa to better understand how animals move through the landscape. This is not just of academic interest, but may help to identify and protect dispersal corridors for endangered species in a scientifically robust way. For the Berlin foxes we are going to analyse data from a radio tracking study and research their movement patterns and space use – it will be interesting to compare those results with the ones from landscape genetics. We are looking forward to hopefully adding some more pieces to the puzzle of the city as a wildlife habitat.
What would your message be for students about to start developing or using novel techniques in Molecular Ecology? From a beginners’ perspective: For our project, we greatly benefitted from the exchange with other researchers working in this field. For example, we contacted William Peterman, who created the ResistanceGA package that we used for our landscape resistance analysis, with some methodological questions and he provided very helpful advice. I would therefore recommend getting in touch with people who work with the same methods and discussing your ideas and obstacles. Also, our work greatly benefitted from the thorough review process that it underwent. Although the requested changes and suggestions sometimes may come with a lot of re-thinking and -working effort and we usually do not always agree with every single given comment, it is crucial to take constructive criticism to improve our scientific work.
What have you learned about methods and resources development over the course of this project? Molecular genetic methods and the inherent potential to study complex ecological contexts have been changing a lot in the last decades. This is a field of frequent on-going development and improvement. Especially regarding the analytical methods, for an ecologist it is difficult to keep on track with all the latest approaches. Also, due to big data involved in the landscape analysis and the resulting time for computational analysis, the computational effort for a model becomes a real issue in landscape genetics. It is really a pity when more thorough analysis are theoretically possible and even free data is available but the analysis can just not be conducted in a feasible amount of time.
Describe the significance of this research for the general scientific community in one sentence. Assessing the impact of the habitat on (urban) wildlife beyond the physical properties of the landscape may help us to more deeply understand dispersal, behaviour and population genetic structure of populations.
Describe the significance of this research for your scientific community in one sentence. Methodological advancement due to more in depth comparisons of different genetic measures used in resistance modelling.
Kimmig ES, Behinde J, Brandt M, Schleimer A, Kramer-Schadt S, Hofer H, Börner K, Schulze C, Wittstatt U, Heddergott M, Halczok T, Staubach C, Frantz A. 2020. Beyond the landscape: resistance modeling infers physical and behavioral gene flow barriers to a mobile carnivore across a metropolitan area. Molecular Ecology. https://doi.org/10.1111/mec.15345.
The editorial board of the journal Molecular Ecology is seeking nominations for the Harry Smith Prize, which recognizes the best paper published in Molecular Ecology in the previous year by graduate students or early career scholars with no more than five years of postdoctoral or fellowship experience. The prize comes with a cash award of US$1000 and an announcement in the journal and in the Molecular Ecologist. The winner will also be asked to join a junior editorial board for the journal to offer advice on changing research needs and potentially serve as a guest editor. The winner of this annual prize is selected by the junior editorial board.
The prize is named after Professor Harry Smith FRS, who founded the journal and served as both its Chief and Managing Editor during the journal’s critical early years. He continued as the journal’s Managing Editor until 2008, and he went out of his way to encourage early career scholars. In addition to his editorial work, Harry was one of the world’s foremost researchers in photomorphogenesis, where he determined how plants respond to shading, leading to concepts such as “neighbour detection” and “shade avoidance,” which are fundamental to understanding plant responses to crowding and competition. More broadly his research provided an early example of how molecular data could inform ecology, and in 2008 he was awarded the Molecular Ecology Prize that recognized both his scientific and editorial contributions to the field.
Please send a PDF of the paper you are nominating, with a short supporting statement (no more than 250 words; longer submissions will not be accepted) directly to Dr. Janna Willoughby (firstname.lastname@example.org) by 31 May 2020. Self-nominations are accepted.