Both theory and experimental evolution studies predict migration to influence the outcome of antagonistic coevolution between hosts and their parasites, with higher migration rates leading to increased diversity and evolutionary potential. Migration rates are expected to vary in spatially structured natural pathosystems, yet how spatial structure generates variation in coevolutionary trajectories across populations occupying the same landscape has not been tested. Here, we studied the effect of spatial connectivity on host evolutionary potential in a natural pathosystem characterized by a stable Plantago lanceolata host network and a highly dynamic Podosphaera plantaginis parasite metapopulation. We designed a large inoculation experiment to test resistance of five isolated and five well‐connected host populations against sympatric and allopatric pathogen strains, over 4 years. Contrary to our expectations, we did not find consistently higher resistance against sympatric pathogen strains in the well‐connected populations. Instead, host local adaptation varied considerably among populations and through time with greater fluctuations observed in the well‐connected populations. Jointly, our results suggest that in populations where pathogens have successfully established, they have the upper hand in the coevolutionary arms race, but hosts may be better able to respond to pathogen‐imposed selection in the well‐connected than in the isolated populations. Hence, the ongoing and extensive fragmentation of natural habitats may increase vulnerability to diseases.
High levels of phenotypic variation in resistance appears to be nearly ubiquitous across natural host populations. Molecular processes contributing to this variation in nature are still poorly known, although theory predicts resistance to evolve at specific loci driven by pathogen-imposed selection. Nucleotide-binding leucine-rich repeat (NLR) genes play an important role in pathogen recognition, downstream defense responses and defense signaling. Identifying the natural variation in NLRs has the potential to increase our understanding of how NLR diversity is generated and maintained, and how to manage disease resistance. Here, we sequenced the transcriptomes of five different Plantago lanceolata genotypes when inoculated by the same strain of obligate fungal pathogen Podosphaera plantaginis. A de novo transcriptome assembly of RNA-sequencing data yielded 24,332 gene models with N50 value of 1,329 base pairs and gene space completeness of 66.5%. The gene expression data showed highly varying responses where each plant genotype demonstrated a unique expression profile in response to the pathogen, regardless of the resistance phenotype. Analysis on the conserved NB-ARC domain demonstrated a diverse NLR repertoire in P. lanceolata consistent with the high phenotypic resistance diversity in this species. We find evidence of selection generating diversity at some of the NLR loci. Jointly, our results demonstrate that phenotypic resistance diversity results from a crosstalk between different defense mechanisms. In conclusion, characterizing the architecture of resistance in natural host populations may shed unprecedented light on the potential of evolution to generate variation.
While the negative effects that pathogens have on their hosts are well-documented in humans and agricultural systems, direct evidence of pathogen-driven impacts in wild host populations is scarce and mixed. Here, to determine how the strength of pathogen-imposed selection depends on spatial structure, we analyze growth rates across approximately 4000 host populations of a perennial plant through time coupled with data on pathogen presence-absence. We find that infection decreases growth more in the isolated than well-connected host populations. Our inoculation study reveals isolated populations to be highly susceptible to disease while connected host populations support the highest levels of resistance diversity, regardless of their disease history. A spatial eco-evolutionary model predicts that non-linearity in the costs to resistance may be critical in determining this pattern. Overall, evolutionary feedbacks define the ecological impacts of disease in spatially structured systems with host gene flow being more important than disease history in determining the outcome.
Abstract. Better monitoring, reporting, and verification (MRV) of the amount, additionality, and persistence of the sequestered soil carbon is needed to understand the best carbon farming practices for different soils and climate conditions, as well as their actual climate benefits or cost efficiency in mitigating greenhouse gas emissions. This paper presents our Field Observatory Network (FiON) of researchers, farmers, companies, and other stakeholders developing carbon farming practices. FiON has established a unified methodology towards monitoring and forecasting agricultural carbon sequestration by combining offline and near-real-time field measurements, weather data, satellite imagery, modeling, and computing networks. FiON's first phase consists of two intensive research sites and 20 voluntary pilot farms testing carbon farming practices in Finland. To disseminate the data, FiON built a web-based dashboard called the Field Observatory (v1.0, https://www.fieldobservatory.org/, last access: 3 February 2022). The Field Observatory is designed as an online service for near-real-time model–data synthesis, forecasting, and decision support for the farmers who are able to monitor the effects of carbon farming practices. The most advanced features of the Field Observatory are visible on the Qvidja site, which acts as a prototype for the most recent implementations. Overall, FiON aims to create new knowledge on agricultural soil carbon sequestration and effects of carbon farming practices as well as provide an MRV tool for decision support.
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