Yearly Archives: 2023

From the severity patch to the landscape: Wildfire and spatial heterogeneity in northern Sierra Nevada conifer forests

Posted on by
From the severity patch to the landscape: Wildfire and spatial heterogeneity in northern Sierra Nevada conifer forests

Habitat mosaics due to shrub establishment in mixed conifer forest after fire creates high spatial heterogeneity at broader scales. However, reburned patches from high to high and low and moderate to low and moderate severities have less spatial heterogeneity. Under climate change-induced increase in wildfire within short return interval, conifer regeneration within large stand-replaced patches is uncertain.


Abstract

Aims

Prolonged fire suppression in conifer forests of the Sierra Nevada Mountain range, California, USA, has led to ingrowth of conifer seedlings, converting the open heterogeneous structure into uniformly dense and layered forest. The threat of a stand-replacing fire has increased because of fuel buildup in combination with rising drought and extreme heat frequency caused by climate change. With such high severity fire, there is also rising concern regarding conifer forest converting to shrublands as severe fire favors the establishment of large shrub patches altering landscape vegetation pattern and heterogeneity. However, a clear understanding of the effects of increased fire severity, size, and frequency on landscape-scale heterogeneity and postfire patch dynamics is lacking, which is critical in implementing restoration and forest management activities. Our aim was to understand multiscale dynamics and spatial heterogeneity patterns of conifer forests and chaparral shrublands due to repeated mixed-severity fire.

Location

A mosaic of burned and unburned patches spanning the boundary of Lassen and Plumas National Forests, CA, USA.

Methods

We used secondary geospatial landcover data classified by cover type before modern fires (1999) and after eight modern fires (2014). We calculated various landscape diversity and fragmentation metrics at patch and landscape scales using FRAGSTATS for comparison before and after fires.

Results

At the fire severity patch scale, high-severity fire reduced vegetation cover type heterogeneity by half, but reburning at low to moderate severity nearly doubled cover type heterogeneity. At the full landscape scale mixed-severity fire, including all burn severities, increased vegetation cover type heterogeneity. Fragmentation indexes confirmed that fire created larger patches of shrub and fragmented patches of conifer forest.

Conclusions

The effects of frequent large fire events on vegetation pattern and heterogeneity vary with the scale of analysis. Hence, heterogeneity and vegetation pattern change need to be evaluated at more than one scale to understand past and future ecological processes before prioritizing management actions for the conifer forests of the Sierra Nevada Mountain range.

Near‐gapless genome assemblies of Williams 82 and Lee cultivars for accelerating global soybean research

Posted on by

Abstract

Complete, gapless telomere-to-telomere chromosome assemblies are a prerequisite for comprehensively investigating the architecture of complex regions, like centromeres or telomeres and removing uncertainties in the order, spacing, and orientation of genes. Using complementary genomics technologies and assembly algorithms, we developed highly contiguous, nearly gapless, genome assemblies for two economically important soybean [Glycine max (L.) Merr] cultivars (Williams 82 and Lee). The centromeres were distinctly annotated on all the chromosomes of both assemblies. We further found that the canonical telomeric repeats were present at the telomeres of all chromosomes of both Williams 82 and Lee genomes. A total of 10 chromosomes in Williams 82 and eight in Lee were entirely reconstructed in single contigs without any gap. Using the combination of ab initio prediction, protein homology, and transcriptome evidence, we identified 58,287 and 56,725 protein-coding genes in Williams 82 and Lee, respectively. The genome assemblies and annotations will serve as a valuable resource for studying soybean genomics and genetics and accelerating soybean improvement.

Genomic selection of soybean (Glycine max) for genetic improvement of yield and seed composition in a breeding context

Posted on by

Abstract

Genomic selection has been utilized for genetic improvement in both plant and animal breeding and is a favorable technique for quantitative trait development. Within this study, genomic selection was evaluated within a breeding program, using novel validation methods in addition to plant materials and data from a commercial soybean (Glycine max) breeding program. A total of 1501 inbred lines were used to test multiple genomic selection models for multiple traits. Validation included cross-validation, inter-environment, and empirical validation. The results indicated that the extended genomic best linear unbiased prediction (EGBLUP) model was the most effective model tested for yield, protein, and oil in cross-validation with accuracies of 0.50, 0.68, and 0.64, respectively. Increasing marker number from 1000 to 3000 to 6000 single nucleotide polymorphism markers leads to statistically significant increases in accuracy. Cross-environment predictions were statistically lower than cross-validation with accuracies of 0.24, 0.54, and 0.42 for yield, protein, and oil, respectively, using the extended genomic BLUP model. Empirical validation, predicting the yield of 510 soybean lines, had a prediction accuracy of 0.34, with the inclusion of a maturity covariate leading to a notable increase in accuracy. Genomic selection identified high-performance lines in inter-environment predictions: 34% of lines within the upper quartile of yield, and 51% and 48% of the highest quartile protein and oil lines, respectively. Statistically similar results occurred comparing rankings in empirical validation and selection for advancements in yield trials. These results indicate that genomic selection is a useful tool for selection decisions.

FER meets the Nod factor pathway

Posted on by

Nature Plants, Published online: 25 September 2023; doi:10.1038/s41477-023-01531-9

Single-nucleus transcriptomic analysis of Medicago roots reveals dynamic cell-specific responses to the Nod factor — a bacterially secreted chito-lipopolysaccharide with a key role in the root nodule symbiosis between legumes and rhizobia — and identifies the receptor-like kinase FERONIA as a phosphorylation target of the Nod factor receptor LYK3, which together function to control nodule formation and bacterial infection.

Single-nucleus transcriptomes reveal spatiotemporal symbiotic perception and early response in <i>Medicago</i>

Posted on by

Nature Plants, Published online: 25 September 2023; doi:10.1038/s41477-023-01524-8

Single-nucleus transcriptomes uncover cell type-specific gene reprogramming in response to nod factors in Medicago, including a defence response at 30 min, which largely returned to normal at 6 h. The results reveal that MtFER interacts with LYK3 and regulates rhizobial symbiosis.

A new set of international Leptosphaeria maculans isolates as a resource for elucidation of the basis and evolution of blackleg disease on Brassica napus

Posted on by
A new set of international Leptosphaeria maculans isolates as a resource for elucidation of the basis and evolution of blackleg disease on Brassica napus

An international collection of Leptosphaeria maculans isolates has been established as a key resource to help understand the interaction between this fungal pathogen and its host, canola (Brassica napus).


Abstract

A collection of isolates of the fungi Leptosphaeria maculans and L. biglobosa, which cause blackleg disease on Brassica napus (canola/oilseed rape) and other Brassicaceae species, was assembled to represent the global diversity of these pathogens and a resource for international research. The collection consists of 226 isolates (205 L. maculans and 21 L. biglobosa) from 11 countries. The genomes of all 205 L. maculans isolates were sequenced, and the distribution and identity of avirulence gene alleles were determined based on genotypic information and phenotypic reactions on B. napus lines that hosted specific resistance genes. Whilst the frequencies of some avirulence alleles were consistent across each of the regions, others differed dramatically, potentially reflecting the canola/oilseed rape cultivars grown in those countries. Analyses of the single-nucleotide polymorphism (SNP) diversity within these L. maculans isolates revealed geographical separation of the populations. This "open access" resource provides a standardized set of isolates that can be used to define the basis for how these fungal pathogens cause disease, and as a tool for discovery of new resistance traits in Brassica species.