Tree diseases (old posts)

I have decided to get this section of my lab page going again after a very busy year of moving my lab to UC Berkeley and becoming a parent. As a first pass, I’ve decided to collapse my tree diseases tab and Blog tab into one. So here are two old posts that need a new home (I was unable to move the comments, so I apologize for losing those):

Tree disease update: Ash dieback        (published Dec 26, 2012)

Photo: Courtesy of The Danish Nature Agency/HEATHCLIFF O'MALLEY
Photo: Courtesy of The Danish Nature Agency/HEATHCLIFF O’MALLEY

If you’re living in the UK or elsewhere in Europe, then you’ve already heard about the scary new disease of ash trees, known here as Ash dieback or in France as “Chalarose.” Like many tree diseases that have devastated forests, this one is caused by a fungus, Hymenoscyphus pseudoalbidus (anamorph: Chalara fraxinea [1])According to the Forestry Commission, the fungus was introduced in February 2012 by import of infected trees from a nursery in the Netherlands to one in Buckinghamshire. It has already caused serious problems in Poland (where 3,000 infected trees fell on one windy night), Denmark (killing 95% of their trees), Lithuania (resulting in mortality of 60% of all ash stands), Austria, Belgium, the Czech Republic, Finland, France, Germany, Hungary, Italy, the Netherlands, Norway, Slovenia and Sweden, and is now wreaking havoc across the UK (Map of confirmed infections). This is very bad news indeed for our woodlands, as ash trees make up over 10% of the trees we have.

As a scientist, when I first hear about an emerging disease the questions I want answers to are: 1) Where did it come from? 2) How is it transmitted? 3) Why is it becoming a problem now? 4) What are the symptoms? And 5) Is there any natural variation in susceptibility? So, after surfing around on the web and reading some recent papers, here is what we know so far:

1) Where did it come from?  As with many emerging diseases, the answer to this is not clear. The pathogen is closely related to another non-pathogenic fungus, Hymenoscyphus albidus, which has been widespread in Europe since the mid 19th century. (Interestingly, it seems as though the spread of the pathogenic species has lead to local extinctions of the native fungus in parts of Denmark [2].) The fungus was first described in 2006, but seems to have been around since the early 90s, when it devastated forests in Poland. Whether the species is a mutant of the closely related, yet harmless, H. albidus remains to be seen. As we are now in the genome era, the most informative way of determining how this new species came to be is to take a comparative genomic approach. For many pathogens, comparing their whole genome to those of closely related, but non-pathogenic species has allowed researchers both to infer the phylogeny of the pathogen and to identify regions of the genome that are likely to be involved in making it harmful to its host. This approach has been successfully used to identify candidate genes associated with virulence in a number of Pseudomonas syringae bacterialpathogens [3] and to demonstrate the movement of genes from pathogens to free-living bacteria[4].

Comparative genomics can also help elucidate whether the pathogen is truly newly emerged (which you could conclude if there was very little genetic variation among the isolates collected from different parts of the species range) or whether it has been around for a while. Surprisingly, there is evidence from molecular characterization of strains from Finland, Estonia and Latvia that there is quite a bit of variation already, suggesting that this fungal species has either been around for quite some time already or has evolved multiple times from a closely related species [5]. For now, we will have to wait and see what story the H. pseudoalbidus genome has to tell us.

2) How is it transmitted? The latest headlines from BBC and the Guardian state that the number of sightings has doubled in the last month, with about 300 confirmed cases in the UK. (Of course, what they don’t emphasize is that the awareness of the disease has increased exponentially since the news broke that the first case had been found back in early November.) So how is it moving around? And how is it infecting new trees once it arrives? It seems that the sexual stage is wind dispersed, with a suggested dispersal distance of 20 to 30 km per year.

The best way to determine how a disease is transmitted is by having lots of data over multiple years and then building a series of models that predict how the spread would look under varying assumptions – e.g. if it is limited by the dispersal rate of a vector, such as an insect, or the wind – and then testing which model fit the actual spread the best. Given the speed at which this pathogen has spread across Europe, it seems that wind dispersal is the most likely explanation for spread within forests and that human transport of saplings from country to country is the most likely explanation for new epidemics. It’s unclear exactly how the pathogen infects new trees once it gets to a new place, but there is some evidence it is through the leaves (this is true of many plant pathogens).

3) Why is it becoming a problem now? Again, the short answer is that we don’t know. The longer answer is that it may be related to our colder, damper summers over the past few years or it may be related to tree stress.

4) What are the symptoms? A little video from the Forestry commission on how to identify the symptoms of ash dieback:

5) Is there any natural variation in susceptibility? The good news is that there is some burgeoning evidence for genetic resistance to the disease, as not all trees die of infection. A study of trees in Denmark found that individuals with early leaf senescence (i.e., those that lost their leaves early in the season) were less susceptible than late-senescing individuals [6]. Interestingly, early leaf loss is also a symptom of the disease. Unfortunately, it looks like only a very small proportion of trees are resistant [7]; most likely too few to prevent a severe population crash. However, the presence of resistance at all suggests that evolution can work its magic. That being said, natural selection can be a painfully slow process, especially for such a long-lived organism. Therefore, a little bit of artificial selection (where individuals that are known to be resistant are crossed and their offspring are planted) could be a good solution to slowing the spread of the disease and eventual eradication.

Finally, let’s not forget that it’s not just the ash trees that are under threat! These trees are host to about 30% of all UK lichens, many of which are currently considered endangered species, and any number of bacterial species [8]. Also, there are at least two moth species that specialize on ash: the Dusky thorn (Ennomos fuscantaria) the centre-barred sallow (Atethmia centrago). This disease therefore has the potential to be a real threat of local ecosystems if left unchecked.

For more information:

1) If, like me, you have no idea what an anamorph is, it turns out the species was described twice in two different stages of its life cycle: the sexual stage – the teleomorph, and the asexual stage – the anamorph. The former is usually a fruiting body while the latter is more mold-like, which explains why they might have been considered different species.

2) McKinney, L., Thomsen, I., Kjær, E., Bengtsson, S., & Nielsen, L. (2012). Rapid invasion by an aggressive pathogenic fungus (Hymenoscyphus pseudoalbidus) replaces a native decomposer (Hymenoscyphus albidus): a case of local cryptic extinction? Fungal Ecology, 5 (6), 663-669 DOI: 10.1016/j.funeco.2012.05.004.

3) Baltrus, David A., et al. “Dynamic evolution of pathogenicity revealed by sequencing and comparative genomics of 19 Pseudomonas syringae isolates.” PLoS pathogens 7.7 (2011): e1002132.

4) Ma, Li-Jun, et al. “Comparative genomics reveals mobile pathogenicity chromosomes in Fusarium.” Nature 464.7287 (2010): 367-373.

5) Rytkonen, A., Lilja, A., Drenkan, R., Gaitner, T., and Hantula, J. 2010. First record of Chalara fraxinea in Finland and genetic variation among isolates sampled from Åland, mainland Finland, Estonia, and Latvia. For. Path.

6) McKinney, Lea Vig, et al. “Genetic resistance to Hymenoscyphus pseudoalbidus limits fungal growth and symptom occurrence in Fraxinus excelsior.” Forest Pathology 42.1 (2011): 69-74.

7) McKinney, Lea Vig, et al. “Presence of natural genetic resistance in Fraxinus excelsior (Oleraceae) to Chalara fraxinea (Ascomycota): an emerging infectious disease.” Heredity 106.5 (2010): 788-797.

8) Ellis, Christopher J., Brian J. Coppins, and Peter M. Hollingsworth. “Tree fungus: Lichens under threat from ash dieback.” Nature 491.7426 (2012): 672-672.


Why I study tree diseases:                               (published Nov 26, 2012)

About 5 years ago this month, my research took a very interesting twist. When I arrived at Oxford as an NSF international research fellow with a plan to work on bacteria and phages in tomato plants, I discovered (thanks to conversations with the amazing Gail Preston) that the same bacterial species causing the disease I was interested in, Pseudomonas syringae, was also killing all of the horse chestnut trees in Britain. Continue reading “Tree diseases (old posts)”

Two new Evolutionary Applications research highlights

For the previous two research highlights at Evolutionary Applications, I first examined disease spillover into and from natural populations, and then examine some of the recent work on the CRISPR/Cas system in bacteria:

The CRISPR/Cas revolution

“The evolution of host defenses against parasites and pathogens has resulted in a wide array of mechanisms conferring resistance and tolerance. Many of these adaptations have been co-opted for use in the treatment of disease, for example the use of live vaccines to prime the host immune system through the memory of B and T cells or the creation of transgenic crop plants to increase resistance to pests and pathogens (e.g., Schoonbeek et al. 2015; Tripathi et al. 2015). Indeed, the acquisition of basic knowledge regarding host–pathogen coevolution has underpinned much of the advancement in applied sciences of healthcare and disease management. Few such examples, however, have generated the widespread excitement and rapid development as the CRISPR/Cas system discovered in bacterial and archaeal genomes.

When bacteria coevolve with their bacteriophage viruses, they typically face strong selection to recognize and resist infection by circulating phage genotypes. Among the many mechanisms that have evolved in response to this pressure is the CRISPR/Cas system, which provides adaptive immunity to its host against specific phages. The system is built from clustered regularly interspaced short palindromic repeats (CRISPRs) within the genome that act together with CRISPR-associated (Cas) proteins to target and destroy foreign nucleic acids, including those from viruses and plasmids (reviewed in Barrangou 2015).

In the laboratory, experimental coevolution between bacteria and phages has been used to uncover the exact mechanisms of resistance and counter-adaptation as well as to determine the potential ecological and evolutionary impacts of such coevolution in shaping microbial populations and communities. Recent work by David Paez-Espino and coauthors has clearly demonstrated that phage populations respond rapidly to CRISPR-mediated immunity both through the accumulation of single nucleotide polymorphisms within the region of the phage genome targeted by CRISPR and via rampant recombination among phage types. Using long-term experimental coevolution of Streptococcus thermophiles and phage 2972, they were able to track specific evolutionary responses of the phage populations through deep sequencing and show that mutation rates were much higher than those of corresponding host populations (Paez-Espino et al. 2015). Such a rapid response by phages suggests bacterial host populations will be under a constant selection pressure to renew resistance, and emphasizes the power of the CRISPR/Cas system to confer such evolutionary flexibility.

In natural populations, bacteria–phage coevolution has also been shown to occur rapidly under CRISPR-mediated selection. Laura Sanguino and collaborators have elegantly demonstrated that CRISPR sequences obtained through metagenomics can be used to build bioinformatics networks that link viruses with their coevolving hosts (Sanguino et al. 2015). Using Arctic glacier ice and soil samples, the authors compared the direct repeats of microbial origin and short sequence spacers of viral origin that make up the CRISPR region to uncover the interaction dynamics of hosts and their, often broad host range, viruses. They found more abundant CRISPRs in ice samples relative to soil, possibly indicating higher viral diversity and infectivity rates (although they note this may also be due to limited depth of coverage in the soil metagenome dataset), and evidence for phage-mediated transduction in the bacterial community.

Now, this mechanism of prokaryotic immunity is being successfully developed as a genome-editing tool, including the engineering of mammalian cells. The CRISPR/Cas system holds the potential to knockout specific regions of the genome, alter multiple loci simultaneously, and selectively manipulate gene expression over time. This newly emerging tool not only promises to revolutionize the field of genetics, but also has direct application to the treatment of disease (reviewed in Pellagatti et al. 2015). For example, the Cas9-based DNA editing system is being exploited to help combat viral diseases through the identification of human genes linked to viral replication and the direct targeting of DNA viruses within the human body (reviewed in Kennedy & Cullen 2015). Work by Hsin-Kai Liao and colleagues recently demonstrated how the CRISPR/Cas9 system can be adapted to human cells in order to mount intracellular defense against HIV-1 infection (Liao et al. 2015). Their work shows that engineered cells expressing HIV-targeted CRISPR/Cas9 can be used both to disrupt viral DNA integrated into the host genome and to prevent new viral infection, emphasizing the great therapeutic potential of the system.

The breadth of utility for the CRISPR/Cas system is only beginning to be uncovered, with potential applications ranging from cancer screening (Chen et al. 2015) to editing of crop plant genomes (Belhaj et al. 2015). Among the many perceived benefits of this new technology is the fact that it bypasses the current GMO legislation (Kanchiswamy et al. 2015) and, unlike transgenic crop production (Tabashnik et al. 2015), allows flexible and adaptive genome editing that can be used to stay ahead of any pest and pathogen counter-adaptation. However, the ethical issues surrounding CRISPR/Cas genome editing, especially in the case of altered human embryos (Kaiser & Normile 2015), has yet to be fully addressed and the scientific community must now come together to balance the amazing potential against possible consequences of this powerful new tool.”

Literature cited

Barrangou, R. 2015The roles of CRISPR–Cas systems in adaptive immunity and beyondCurrent Opinion in Immunology 32:3641.

Belhaj, K.A. Chaparro-GarciaS. KamounN. J. Patron, and V. Nekrasov 2015Editing plant genomes with CRISPR/Cas9Current Opinion in Biotechnology 32:7684.

Chen, S.N. E. SanjanaK. ZhengO. ShalemK. LeeX. ShiD. A. ScottJ. SongJ. Q. PanR. WeisslederH. LeeF. Zhang, and P. A. Sharp 2015Genome-wide CRISPR screen in a mouse model of tumor growth and metastasisCell 160:12461260.

Kaiser, J., and D. Normile 2015Embryo engineering study splits scientific communityScience 348:486487.

Kanchiswamy, C. N.M. MalnoyR. VelascoJ. S. Kim, and R. Viola 2015Non-GMO genetically edited crop plantsTrends in Biotechnology. doi:10.1016/j.tibtech.2015.04.002 [In press].

Kennedy, E. M., and B. R. Cullen 2015Bacterial CRISPR/Cas DNA endonucleases: a revolutionary technology that could dramatically impact viral research and treatmentVirology 479:213220.

Liao, H. K.Y. GuA. DiazJ. MarlettY. TakahashiM. LiK. SuzukiR. XuT. HishidaC.-J. ChangC. Rodriguez EstebanJ. Young, and J. C. I. Belmonte2015Use of the CRISPR/Cas9 system as an intracellular defense against HIV-1 infection in human cellsNature Communications 6:6413.

Paez-Espino, D.I. SharonW. MorovicB. StahlB. C. ThomasR. Barrangou, and J. F. Banfield2015CRISPR immunity drives rapid phage genome evolution in Streptococcus thermophilusmBio 6:e00262-15.

Pellagatti, A.H. DolatshadS. Valletta, and J. Boultwood2015Application of CRISPR/Cas9 genome editing to the study and treatment of diseaseArchives of Toxicology doi: 10.1007/s00204-015-1504-y [Epub ahead of print].

Sanguino, L.L. FranquevilleT. M. Vogel, and C. Larose2015Linking environmental prokaryotic viruses and their host through CRISPRsFEMS Microbiology Ecology 91:fiv046.

Schoonbeek, H. J.H. H. WangF. L. StefanatoM. CrazeS. BowdenE. WallingtonC. Zipfel, and C. J. Ridout 2015Arabidopsis EF-Tu receptor enhances bacterial disease resistance in transgenic wheatNew Phytologist 206:606613.

Tabashnik, B. E.Y. CarrièreM. SoberónA. Gao, and A. Bravo2015Successes and failures of transgenic Bt crops: global patterns of field-evolved resistanceBt resistance: characterization and strategies for GM crops producing Bacillus thuringiensis toxins14.

Tripathi, L.A. BabiryeH. RoderickJ. N. TripathiC. ChangaP. E. UrwinW. K. TushemereirweD. Coyne, and H. J. Atkinson2015Field resistance of transgenic plantain to nematodes has potential for future African food securityScientific Reports 5:8127.

Disease spillover among natural and managed populations

“The recent epidemic of the Ebola virus is a particularly horrific example of the consequences of disease transmission between species. Spillover infection from populations of one species, in which a pathogen may be endemic, coevolved, and often less harmful, into populations of a novel host species has the potential to lead to epidemics of particularly virulent pests and pathogens. Understanding the probability of such spillover and the evolutionary, as well as coevolutionary, processes that occur after a cross-species transmission event occurs is key to predicting disease emergence and spread. This is especially important in the case of transmission between natural populations and managed ones, where disease emergence may have significant societal impact.

A classic example is the spillover of canine distemper virus from domestic dog populations into wild lion populations in the Serengeti, which has lead to a series of disease outbreaks and subsequent population declines. Using data collected across three decades, Viana et al. (2015) recently compared the disease dynamics of dog and lion populations to determine whether and how the two were linked. Their model suggests that although spillover from dog populations was the likely driver of disease in lion populations initially, the peak infection periods for each of the two species became increasingly asynchronous over time, suggesting a role for other reservoir species and/or evolution of the circulating viral strains. This work is an elegant example of the value of long term data sets, especially with the development and application of new statistical and modeling techniques, for examining the changing disease dynamics over time.

One powerful tool for uncovering patterns of spillover is the use of social and contact networks to study transmission, as recently reviewed by Craft (2015). Understanding transmission likelihood is a key first step in determining the selection acting on pathogen populations and the potential for host shifts and the piece outlines current methods for using information about contact within populations, for example as resulting from movement, sociality, or behavior, to help inform questions of disease transmission across livestock and interacting wildlife. Craft distinguishes the utility of social network analysis, in which contact structure within and/or among populations is described, and network modeling, a tool with which to simulate disease spread across a contact network, for predicting the risk and consequences of disease spread. She also discusses how human intervention of spatial structure and group size can alter the likelihood of transmission, both within and among populations, and therefore how spillover involving managed populations may differ from that among wild populations.

Another topical example of spillover from managed into natural populations is the case of wild pollinator exposure to viruses from commercial pollinators. A recent review by Manley et al. (2015) demonstrates the potential threat for movement of RNA viruses into wild pollinators from managed honeybee populations. As many of these viruses are known to be rapidly evolving, such spillover events can lead to pathogen adaptation to novel hosts and eventual host shifts. By collating evidence for viral spillover events among populations, the authors demonstrate the potential importance of cross-species transmission in shaping disease emergence, especially when there are shared ranges, niches or behaviors between managed and wild species. Work by McMahon et al. (2015) used data from a large-scale survey of co-occurring managed honeybee and wild bumblebee populations to explore correlations in prevalence and viral loads between the two, as might be expected if cross-species transmission was common. Although they found a significant association between prevalence of viruses in honeybees and bumblebees, they also report large species-specific differences in prevalence and load across the viruses examined, suggesting more data is needed to determine the direction of transmission.

Of course, not all spillover will have negative consequences; the introduction of natural enemies of pests from wild populations into managed ones can play a key role in keeping infestation levels down. For example, in the case of crops growing near forests, González et al. (2015) recently demonstrated that the diversity of natural enemies capable of controlling herbivores on soybean is dependent on the surrounding forest. By studying crop lands within the Argentine Chaco Serrano forest, they found that both the amount of forest cover and proximity to the forest were important indicators of the richness and taxonomic composition of natural enemy assemblages, including predators and parasitoid species. This highlights the potential benefits of connectedness between natural and managed populations for hindering enemy escape by emerging pests and emphasizes the difficulties of managing pest and pathogen spread between the two given the complex coevolutionary dynamics of communities.”

Literature cited

Craft, M. E. 2015Infectious disease transmission and contact networks in wildlife and livestockPhilosophical Transactions of the Royal Society of London B: Biological Sciences 370:1669.

González, E.A. Salvo, and G. Valladares2015Sharing enemies: evidence of forest contribution to natural enemy communities in crops, at different spatial scalesInsect Conservation and Diversity (online early) DOI: 10.1111/icad.12117.

Manley, R.M. Boots, and L. Wilfert2015Emerging viral disease risk to pollinating insects: ecological, evolutionary and anthropogenic factorsJournal of Applied Ecology 52:331340.

McMahon, D. P.M. A. FürstJ. CasparP. TheodorouM. J. F. Brown, and R. J. Paxton2015A sting in the spit: widespread cross-infection of multiple RNA viruses across wild and managed beesJournal of Animal Ecology 84:615624.

Viana, M.S. CleavelandJ. MatthiopoulosJ. HallidayC. PackerM. E. CraftK. Hampson et al. 2015Dynamics of a morbillivirus at the domestic–wildlife interface: canine distemper virus in domestic dogs and lionsProceedings of the National Academy of Sciences, USA 112:14641469.

Applied evolution in fisheries science

For this month’s research highlights in Evolutionary Applications, I cover a few new papers that demonstrate the importance of thinking about evolution and ecology in fisheries science.

“The pressure on both natural and managed fish stocks to keep pace with worldwide consumption presents a number of critical challenges, including the prevention of population collapse, management of disease, and understanding of the impact that fishing practices may have on life history traits. Addressing such challenges requires the integration of data from long term population monitoring, empirical work, theoretical analysis, and implementation of policy change. Fortunately, many fish populations have been monitored either actively or passively over long periods of time, generating some of the best datasets with which to characterize the impact of human-mediated selection on population-level change.

The intensity of selection acting on fished populations has long been predicted to significantly impact upon life history traits. In a recent theoretical exploration of the consequences of commercial fishing, Lise Marty and coauthors highlight how exploitation of fish populations can lead to slower growth, early maturation, and higher investment in reproduction within stocks (Marty et al. 2015). The authors use an individual-based eco-genetic model to examine harvest-induced genetic change and show not only that fishing can influence life history trait evolution, but also that it can reduce effective population size and erode additive genetic variation. Together, they argue, these effects are likely to hinder recovery even after intense fishing has ceased.

Another recent theoretical analysis examining the consequences of fisheries on stock populations suggests that common fishing policies can result in disruptive selection for maturation strategies (Landi et al. 2015). Using an eco-evolutionary model, Pietro Landi and colleagues demonstrate how the interplay between adaptation of fish stocks and adaptation of fisheries policy can lead to dimorphism within populations, with some individuals reaching maturation early and others late, investing instead in growth and fecundity. This work highlights the potentially complex outcomes of size-selective harvesting and the need for adaptive policies that take into account evolutionary change of fish populations.

Harvest-mediated shifts in life history have thus far been demonstrated under a variety of scenarios. Recent empirical work examining size and weight distributions of exploited sea cucumber populations in Turkey finds evidence for the loss of larger size classes, as predicted from intensive size-dependent harvesting (González-Wangüemert et al. 2015). By comparing fishery and nonfishery populations, Mercedes González-Wangüemert and collaborators show that individuals from protected populations tend to be larger and heavier, with higher genetic diversity than those from exploited populations. Given that sea cucumber over-exploitation is a relatively recent and growing phenomenon, this work offers an important new data point in a rapidly expanding body of evidence for rapid fisheries-mediated evolutionary change in fish stocks.

Finally, just like natural populations, managed fish stocks face a constant onslaught of pests and pathogens. This is further exacerbated by high population densities, increased movement of disease agents among populations, and potentially by selection for desirable traits that are negatively correlated with resistance. A recent review by Kevin Lafferty and coauthors examines the ongoing challenges associated with controlling the emergence and spread of disease within fisheries and aquaculture, highlighting a number of significant infectious agents with severe economic impacts. The authors further explore how the novel evolutionary environment of fish farms might influence pathogen evolution, for example leading to higher virulence, and whether host resistance is likely to evolve under current fishing practices (Lafferty et al. 2015).

For bacterial pathogens within fish farms, there has been increasing interest in the use of bacteriophages as control agents. Although there is still uncertainty in regard to best practice for the application of phages within these complex environments, work from the laboratory suggests this as a promising avenue, especially in combination with other control measures. Recent work by Daniel Castillo and collaborators undertook a study on the common fish pathogen, Flavobacterium psychrophilum, to examine both the genetic changes underlying the evolution of bacterial resistance to phage and the physiological changes associated with such resistance (Castillo et al. 2015). They found numerous mutational changes underlying resistance, suggesting that resistance can be attained relatively easily and via a number of mechanisms, but also that these resistance mutations are often associated with a loss of virulence when measured in vitro.

Overall, the application of evolutionary and ecological theory to fisheries management over the last few decades has proven invaluable, but there remains a great need for further empirical and observational datasets testing the predictions put forward. Furthermore, translating such knowledge into policy change continues to present a formidable challenge for the field.”

Literature cited

  • Castillo, D.R. H. ChristiansenI. DalsgaardL. Madsen, and M. Middelboe 2015Bacteriophage resistance mechanisms in the fish pathogen Flavobacterium psychrophilum: Linking genomic mutations to changes in bacterial virulence factorsApplied and environmental microbiology 81:11571167.
  • González-Wangüemert, M.S. Valente, and M. Aydin 2015Effects of fishery protection on biometry and genetic structure of two target sea cucumber species from the Mediterranean SeaHydrobiologia 743:6574.
  • Lafferty, K. D.C. D. HarvellJ. M. ConradC. S. FriedmanM. L. KentA. M. KurisE. N. Powell et al. 2015Infectious diseases affect marine fisheries and aquaculture economicsAnnual review of marine science 7:471496.
  • Landi, P.C. Hui, and U. Dieckmann 2015Fisheries-induced disruptive selectionJournal of theoretical biology 365:204216.
  • Marty, L.U. Dieckmann, and B. Ernande 2015Fisheries-induced neutral and adaptive evolution in exploited fish populations and consequences for their adaptive potentialEvolutionary Applications 8:4763.

Previous two research highlights for Evolutionary Applications




















The ever-evolving field of agriculture








Literature cited










As I see it: the value of double blind peer review






More resources of interest:


Disease evolution and ecology across space

For this month’s Evolutionary Application Research Highlight, I explored:

Disease evolution and ecology across space






References cited:




