Fusiform Rust Research Articles

Enhanced fusiform rust hazard maps for loblolly pine: Incorporating genotype and climate to predict disease

Hazard maps are a critical component in determining the regional disease pressure for fusiform rust disease [caused by the fungal pathogen Cronartium quercuum (Berk.) Miyabe ex Shirai f. sp. fusiforme], which is considered the most important disease of loblolly pine (Pinus taeda L.) in the southeastern United States. Genetically improved fusiform rust resistant stock should be deployed in areas that are estimated to be at a high hazard for the disease, while stocks with lower resistance to the disease, but perhaps other favorable traits, can be deployed in areas with a lower estimated hazard. Current hazard maps are based on the historic presence of the disease but do not consider the effect of host genotype or climate which can influence the presence and distribution of fungal pathogens. Here, we aim to improve current hazard maps for fusiform rust by identifying, modeling, and predicting the relationship between the disease and yearly climate indicators. Different loblolly pine genotypes were tested: one family improved for resistance and non-improved checklots for each location. We found that, for the non-improved genotypes, location, potential evapotranspiration, consecutive cloud cover, diurnal temperature range, and a yearly available water indicator can explain 89.2 % of the deviance for disease occurrence. For the improved family, we found that longitude, yearly water deficit, yearly consecutive frost days, yearly consecutive cloud cover, and yearly diurnal temperature range explain 93.1 % deviance for disease incidence. We produce two rust hazard maps based on each model, illustrating the probability of the incidence of the disease. With this project, we pave the way for a better-informed determination of where and what loblolly pine resistant stock should be deployed to limit the damage and costs associated with the management of fusiform rust disease.

Stem Defect Rates and Ice Storm Damage for Families of Pinus taeda from Coastal and Piedmont Provenances Planted on a North Carolina Piedmont Site

Abstract Twenty Pinus taeda L. families from both the Coastal Plain and Piedmont provenances in the southeastern United States were planted on an upper Piedmont site that experienced a severe ice storm at age 3 years. Storm damage and defect rates through age 11 years were compared with the seed transfer distance and the seed parents’ breeding values to develop prediction models for storm damage and rates of forking, stem break, and sawtimber potential. Warmer-source families had higher probability of limb or stem breaks and foliage injury from the storm. Taller trees were more likely to experience breaks and foliage injury, even after accounting for seed transfer distance. Trees with forks or fusiform rust (Cronartium quercuum f. sp. fusiforme) infection had a higher probability of breaks. Trees with limb breaks or foliage injury did not have reduced sawtimber potential, but broken stems reduced sawtimber potential. The storm did not cause immediate mortality, but trees with major limb breaks, stem breaks, or foliage injury were less likely to be alive at age 8 years. At age 11 years, families with the best combination of breeding values for forking, straightness, and rust resistance had a predicted 60% of stems having sawtimber potential, whereas families with the worst combination had 30%. Study Implications: Planting warmer-source Pinus taeda (loblolly pine) families farther north and inland may lead to greater growth but poses a risk of damage from cold temperatures and ice storms. Trees grown for solid-wood products must be relatively defect-free and require a longer rotation, whereas bioenergy and pulpwood can use smaller, defective trees. This analysis presents predictions of defect rates through age 11 years based on the seed source and breeding values using data from a planting in the upper Piedmont of North Carolina. Land managers can use these models to weigh the benefits and risks when choosing families for reforestation.

Genetic Parameter Estimates from a Polymix Breeding Population of Pinus taeda L.

Abstract Estimation of genetic parameters from progeny testing is essential for many important decisions in forest tree breeding. In this study, we estimated heritabilities, trait-trait genetic correlations, and genotype by environment (GxE) interactions using a large multi-environmental data set of Pinus taeda L. in the southern United States. In the study, 284 parents were pollinated with a pollen mix and were field tested in four different test series. A total of twenty tests (two to seven tests per series) were established using randomized complete block design with single tree plots. Half-sib family-mean heritability estimates within individual test series varied considerably for all the traits. Pooled estimates of half-sib family-mean heritability estimates across series were 0.81 for fusiform rust incidence; they were relatively lower for tree height (0.68), diameter at breast height (DBH; 0.66), and stem straightness (0.58). Genetic correlations between pairs of traits were low except for height and diameter, which had a high genetic correlation (0.79). Additive genetic correlations between pairs of sites within test series (as a measure of GxE) varied. The pooled estimates ranged between 0.65 (DBH) to 0.80 (fusiform rust). The results suggest that polymix mating is efficient for parental selection in Pinus taeda L. and for deployment in the seed orchards. Study Implications: This study focused on genetic variation in the Piedmont breeding population of Pinus taeda L. in the United States. The Piedmont population was developed for more inland and colder regions of the species. Fusiform rust disease incidence of pine species of southeastern United States is a major threat to pine plantations. Understanding the level of genetic control on disease outcome is vital to develop sound breeding strategies and recommend deployment practices to mitigate the economic loss of landowners. The results provide valuable information to breeders to select disease-resistant genotypes to breed and put into seed orchards to mass-produce stock for planting.

Modeling slash pine mortality rates incorporating responses to silvicultural treatments and fusiform rust infection rates

The evaluation of stand survival at any age is an essential task that allows foresters to estimate stand dynamics and ultimately, the value of a forest stand. Therefore, any growth and yield system developed with the aim of predicting or projecting standing value requires precise estimates of the number of trees surviving at any point in time. When describing survival through modeling the mortality rate, differential equations using height increments rather than time increments have been shown to improve the overall fit of survival models. Using a long-term data set of slash pine plantations (Pinus elliottii Engelm.) in which silvicultural treatments (i.e., bedding and complete vegetation control) were applied during the establishment phase, and fusiform rust (Cronartium quercuum Berk.) infection rates were recorded, a survival/mortality model of this nature was constructed. Height increments were taken from a proposed dominant height model that included explicit treatment effects. In addition, the proportion of trees infected with fusiform rust at an age of 5 years was added as a predictor describing the mortality rate. Our results show that stand survival is better described by a model in which time increments are used rather than height increments, and although silvicultural treatments were essential for modeling dominant height, mortality was not greatly affected by these treatments and therefore, no additional parameter modifiers associated to these treatments were needed. On the other hand, the inclusion of average fusiform rust infections was essential to describe mortality rates in these stands, with higher infection rates associated to higher mortality rates.

Performance Based on Measurements from Individual-Tree Progeny Tests Strongly Predicts Early Stand Yield in Loblolly Pine

Abstract To facilitate the utility of genetic improvement in loblolly pine, individual-tree volume (productivity) scores estimated from single-tree plot or row-plot progeny test designs were compared with stand-level volume per unit area from block plots. A large number of families representing a wide range of progeny test scores for volume were established in growth and yield trials to generalize the results to families created by the breeding program. Individual-tree volume scores from progeny tests strongly corresponded with stand-level volume from block plots, especially after accounting for site quality and the risk of fusiform rust disease. A ten-point increase in the volume score from progeny test data was estimated to increase stand-level volume by 3.9 m3 ha-1 at age 6 years. A prediction model is presented that includes a new statistic, rust risk index, which is the expected rust incidence for a family at a new site when the hazard of rust for a checklot can be estimated from historical data. The study results through age 6 years corroborate the Performance Rating System as effective in guiding family deployment decisions. The models presented are based on pre-crown closure data at 6 years and will be updated with older measurements as the study matures. Study Implications: The Performance Rating System (PRS™) has been a successful tool for presenting genetic merit of improved loblolly pine families for landowners and forest managers in a more coherent and standardized manner. This system can be easily applied in other forest tree improvement programs, because it makes genetic improvement user-friendly for silviculturists and forest managers. Landowners can use this system to make decisions for selecting improved families suited to their specific forest management objectives. Seed orchard and nursery managers also depend on the PRS to choose the families to produce and as a third-party verification to market their genetic merit to customers. This study demonstrates that higher stand-level volume per unit area can be achieved when forest managers plant fast growing families with low fusiform rust disease risk on productive sites. The combined effect of genetic improvement for productivity and fusiform rust disease resistance is significant on stand-level volume per unit area.

Modeling Slash Pine Mortality Rates Incorporating Responses to Silvicultural Treatments and Fusiform Rust Infection Rates

Modeling Slash Pine Mortality Rates Incorporating Responses to Silvicultural Treatments and Fusiform Rust Infection Rates

NLR diversity and candidate fusiform rust resistance genes in loblolly pine

Resistance to fusiform rust disease in loblolly pine (Pinus taeda) is a classic gene-for-gene system. Early resistance gene mapping in the P. taeda family 10-5 identified RAPD markers for a major fusiform rust resistance gene, Fr1. More recently, single nucleotide polymorphism (SNP) markers associated with resistance were mapped to a full-length gene model in the loblolly pine genome encoding for a nucleotide-binding site leucine-rich repeat (NLR) protein. NLR genes are one of the most abundant gene families in plant genomes and are involved in effector-triggered immunity. Inter- and intraspecies studies of NLR gene diversity and expression have resulted in improved disease resistance. To characterize NLR gene diversity and discover potential resistance genes, we assembled de novo transcriptomes from 92 loblolly genotypes from across the natural range of the species. In these transcriptomes, we identified novel NLR transcripts that are not present in the loblolly pine reference genome and found significant geographic diversity of NLR genes providing evidence of gene family evolution. We designed capture probes for these NLRs to identify and map SNPs that stably cosegregate with resistance to the SC20-21 isolate of Cronartium quercuum f.sp. fusiforme (Cqf) in half-sib progeny of the 10-5 family. We identified 10 SNPs and 2 quantitative trait loci associated with resistance to SC20-21 Cqf. The geographic diversity of NLR genes provides evidence of NLR gene family evolution in loblolly pine. The SNPs associated with rust resistance provide a resource to enhance breeding and deployment of resistant pine seedlings.

Hyperspectral Imaging Combined with Machine Learning for the Detection of Fusiform Rust Disease Incidence in Loblolly Pine Seedlings

Loblolly pine is an economically important timber species in the United States, with almost 1 billion seedlings produced annually. The most significant disease affecting this species is fusiform rust, caused by Cronartium quercuum f. sp. fusiforme. Testing for disease resistance in the greenhouse involves artificial inoculation of seedlings followed by visual inspection for disease incidence. An automated, high-throughput phenotyping method could improve both the efficiency and accuracy of the disease screening process. This study investigates the use of hyperspectral imaging for the detection of diseased seedlings. A nursery trial comprising families with known in-field rust resistance data was conducted, and the seedlings were artificially inoculated with fungal spores. Hyperspectral images in the visible and near-infrared region (400–1000 nm) were collected six months after inoculation. The disease incidence was scored with traditional methods based on the presence or absence of visible stem galls. The seedlings were segmented from the background by thresholding normalized difference vegetation index (NDVI) images, and the delineation of individual seedlings was achieved through object detection using the Faster RCNN model. Plant parts were subsequently segmented using the DeepLabv3+ model. The trained DeepLabv3+ model for semantic segmentation achieved a pixel accuracy of 0.76 and a mean Intersection over Union (mIoU) of 0.62. Crown pixels were segmented using geometric features. Support vector machine discrimination models were built for classifying the plants into diseased and non-diseased classes based on spectral data, and balanced accuracy values were calculated for the comparison of model performance. Averaged spectra from the whole plant (balanced accuracy = 61%), the crown (61%), the top half of the stem (77%), and the bottom half of the stem (62%) were used. A classification model built using the spectral data from the top half of the stem was found to be the most accurate, and resulted in an area under the receiver operating characteristic curve (AUC) of 0.83.

A Reevaluation of Superior Tree Performance After 48 Years for a Loblolly Pine Progeny Test in Southern Arkansas

A plus-tree progeny test of full- and half-sib “superior” loblolly pine (Pinus taeda) was installed in 1969 on the Crossett Experimental Forest (CEF) to consider the performance of 28 improved families with unimproved planting stock from the CEF (family W29). Performance was evaluated using data from young (3-year-old; early 1970s), maturing (25-year-old; 1994), and mature (48-year-old; 2017) trees. With the exception of a single improved family, early survival was high (>80%), with most families exceeding 90%. Three years post-planting, fusiform rust infection rates were also low, with most families having less than 1% of seedlings infected. At this early stage, the unimproved CEF family W29 only slightly underperformed the best full- and half-sib superior families. By 1994, W29 had slightly higher than average merchantable volume. This trend continued for W29 when remeasured in 2017, with the average merchantable volume yield for W29 statistically similar to the most productive families. This study found only limited volume performance gains from crossing plus-trees. However, it was important to note that several of the best height growth-performing families in 1972 were not the highest merchantable volume producers at 25 or 48 years, and some of the worst early performers moved into the upper tiers by the later remeasurements. These outcomes suggest that depending solely on early height performance to select families for long-term (>50 year) volume (especially if adjusted for wood density) or biomass yields may not be the best approach for forest managers seeking to increase carbon sequestration.

Genomic prediction for fusiform rust disease incidence in a large cloned population of Pinus taeda.

In this study, 723 Pinus taeda L. (loblolly pine) clonal varieties genotyped with 16920 SNP markers were used to evaluate genomic selection for fusiform rust disease caused by the fungus Cronartium quercuum f. sp. fusiforme. The 723 clonal varieties were from five full-sib families. They were a subset of a larger population (1831 clonal varieties), field-tested across 26 locations in the southeast US. Ridge regression, Bayes B, and Bayes Cπ models were implemented to study marker-trait associations and estimate predictive ability for selection. A cross-validation scenario based on a random sampling of 80% of the clonal varieties for the model building had higher (0.71–0.76) prediction accuracies of genomic estimated breeding values compared with family and within-family cross-validation scenarios. Random sampling within families for model training to predict genomic estimated breeding values of the remaining progenies within each family produced accuracies between 0.38 and 0.66. Using four families out of five for model training was not successful. The results showed the importance of genetic relatedness between the training and validation sets. Bayesian whole-genome regression models detected three QTL with large effects on the disease outcome, explaining 54% of the genetic variation in the trait. The significance of QTL was validated with GWAS while accounting for the population structure and polygenic effect. The odds of disease incidence for heterozygous AB genotypes were 10.7 and 12.1 times greater than the homozygous AA genotypes for SNP11965 and SNP6347 loci, respectively. Genomic selection for fusiform rust disease incidence could be effective in P. taeda breeding. Markers with large effects could be fit as fixed covariates to increase the prediction accuracies, provided that their effects are validated further.

Major QTL confer race-nonspecific resistance in the co-evolved Cronartium quercuum f. sp. fusiforme-Pinus taeda pathosystem.

Fusiform rust disease, caused by the endemic fungus Cronartium quercuum f. sp. fusiforme, is the most damaging disease affecting economically important pine species in the southeast United States. Unlike the major epidemics of agricultural crops, the co-evolved pine-rust pathosystem is characterized by steady-state dynamics and high levels of genetic diversity within environments. This poses a unique challenge and opportunity for the deployment of large-effect resistance genes. We used trait dissection to study the genetic architecture of disease resistance in two P. taeda parents that showed high resistance across multiple environments. Two mapping populations (full-sib families), each with ~1000 progeny, were challenged with a complex inoculum consisting of 150 pathogen isolates. High-density linkage mapping revealed three major-effect QTL distributed on two linkage groups. All three QTL were validated using a population of 2057 cloned pine genotypes in a 6-year-old multi-environmental field trial. As a complement to the QTL mapping approach, bulked segregant RNAseq analysis revealed a small number of candidate nucleotide binding leucine-rich repeat genes harboring SNP associated with disease resistance. The results of this study show that in P. taeda, a small number of major QTL can provide effective resistance against genetically diverse mixtures of an endemic pathogen. These QTL vary in their impact on disease liability and exhibit additivity in combination.

Marker associations for fusiform rust resistance in a clonal population of loblolly pine (Pinus taeda, L.)

Fusiform rust resistance in loblolly pine, Pinus taeda L., is comprised of both polygenic and major gene effects. In this study, we applied a Bayesian approach to test for single nucleotide polymorphisms (SNPs) associated with resistance to fusiform rust, which is caused by Cronartium quercuum (Berk.) Miyabe ex Shirai f.sp. fusiforme. A population of 3810 clonal varieties from 100 full-sib families was produced through somatic embryogenesis and planted in replicated field experiments in the Southeastern United States. Rust phenotypes were measured after 6 growing seasons, and each of 863 clones from 35 full-sib families was genotyped with 3340 SNPs. We identified five associated SNPs with posterior probabilities of inclusion above 0.4 in the clonal population using a BayesCπ model. A second experiment was conducted with one of the identified SNPs (SNP2374) using seedlings from 2 full-sib families that were included in the first experiment. Resistant genotypes exhibited an overall infection rate of 11% compared to the susceptible genotype which had 57% infection. Using one of the full-sib families, we were able to map SNP2374 (CL1208Contig1-03-75) to linkage group 7. Confirmation of the SNP2374 association with rust resistance demonstrates the potential for selecting and screening genotypes to further reduce disease incidence in forest plantations of loblolly pine.

Association of Recent Incidence of Foliar Disease in Pine Species in the Southeastern United States with Tree and Climate Variables

Pine forests in the southern United States are a major contributor to the global economy. Through the last three decades, however, there have been concerns about the decline of pine forests attributed mostly to pests and pathogens. A combination of biotic agents and environmental factors and their interaction often influences outbreaks and the resultant damage in the forests. Southern pines experience periodic mortality from bark beetles and root rot fungi and losses from fusiform rust and pitch canker have long been important for management. In recent years, there is also growing evidence of increasing damage from foliar disease in southern pines. Early detection of diseases following changes in foliar characteristics and assessment of potential risks will help us better utilize our resources and manage these forests sustainably. In this study, we used Forest Inventory and Analysis (FIA) data to explore the intensity of foliar disease in three common pines: loblolly (Pinus taeda L.), longleaf (Pinus palustris Mill.), and slash (Pinus elliottii Engelm.) in spatial and temporal terms using tree-level and climatic variables. Results from a tree-level model suggests that crown ratio may be an important factor in pine foliar disease (p < 0.1). We applied the MaxEnt model, a presence-only species distribution model (SDM), to explore any association of foliar disease incidences with the climatic variables at a landscape level. Results indicate that mean dew point temperature, maximum vapor pressure deficit, and precipitation during cold months had more influence over disease incidences than other climatic variables. While the sample size is limited as this is an emerging disease in the region, our study provides a basis for further exploration of disease detection methods, disease etiology studies, and hazard mapping.

Implications of future risk of fusiform rust on optimal forest management of even-aged slash pine plantations

We simulate the impacts of future reductions of risk of fusiform rust, increases in forest productivity and seedling costs on the optimal forest management of an even-aged slash pine stand using a generalised economic model. Our numerical findings show that future land values are increased with future reductions of fusiform rust risk, ranging approximately between $2919 ha−1 and $4962 ha−1. Compared to the base-case ($1106 ha−1), the current land values are increased ($1468 ha−1 – $2601 ha−1) with future reductions of fusiform rust risk. Landowners are encouraged to replant earlier (reduced harvest ages) given higher economic revenues associated with future reductions of fusiform rust risk. Our approach could serve as a tool to rank efficient tree breeding programs given the level of resistance of slash pine to fusiform rust with different level of increases in forest growth.

Loblolly pine outperforms slash pine in the southeastern United States – A long-term experimental comparison study

Loblolly pine (Pinus taeda L.) and slash pine (Pinus elliottii Engelm.) are the two most important commercial timber species in the southeastern U.S. A long-term experimental comparison study, in which loblolly and slash pine plots were paired for combinations of planting density (741, 2224, 3706 trees ha−1) and cultural intensity (operational versus intensive), was established in the lower Coastal Plain to investigate species differences in growth dynamics. Using age 2–21-year inventory plot data and destructive biomass/nutrient sampling data, species comparisons were conducted comprehensively, and the reasons of the species differences and management implications were discussed. When compared to slash pine, loblolly pine had higher stand basal area carrying capacity and maximum stand density index, lower fusiform rust infection rate and less wind damage, leading to its lower mortality. With no species difference in average DBH, loblolly pine consistently had greater average height and live crown length and higher level of tree size inequality. Loblolly pine had lower foliar biomass and lower foliar density, and higher crown length/width ratios due primarily to its longer crowns, suggesting perhaps a slightly greater shade tolerance or less dense canopy. As a result, loblolly pine outperformed slash pine in terms of stand basal area, total volume, aboveground biomass and carbon accumulation. Loblolly pine consistently accumulated more potassium, and this species difference increased with increasing stand age; while slash pine had slightly higher nitrogen and phosphorus contents before age 12. Species differences in mortality patterns and in nutrient accumulations in aboveground biomass emphasized the need to develop species-specific management strategies including different thinning and fertilization regimes.

Genetically determined fungal pathogen tolerance and soil variation influence ectomycorrhizal traits of loblolly pine.

Selection on genetically correlated traits within species can create indirect effects on one trait by selection on another. The consequences of these trait correlations are of interest because they may influence how suites of traits within species evolve under differing selection pressures, both natural and artificial. By utilizing genetic families of loblolly pine either tolerant (t) or susceptible (s) to two different suites of pathogenic fungi responsible for causing either pine decline or fusiform rust disease, we investigated trait variation and trait correlations within loblolly pine (Pinus taeda L.) by determining how ectomycorrhizal (EM) colonization relates to pathogen susceptibility. We detected interactions between susceptibility to pathogenic fungi and soil inoculation source on loblolly pine compatibility with the EM fungi Thelephora, and on relative growth rate of loblolly pine. Additionally, we detected spatial variation in the loblolly pine–EM fungi interaction, and found that variation in colonization rates by some members of the EM community is not dictated by genetic variation in the host plant but rather soil inoculation source alone. The work presented here illustrates the potential for indirect selection on compatibility with symbiotic EM fungi as a result of selection for resistance to fungal pathogens. Additionally, we present evidence that the host plant does not have a single “mycorrhizal trait” governing interactions with all EM fungi, but rather that it can interact with different fungal taxa independently. Synthesis. An understanding of the genetic architecture of essential traits in focal species is crucial if we are to anticipate and manage the results of natural and artificial selection. As demonstrated here, an essential but often overlooked symbiosis (that between plants and mycorrhizal fungi) may be indirectly influenced by directed selection on the host plant.

Temporal Trends in Fusiform Rust Infections and Their Relationships with Stand Structure in Pine Plantations in East Texas

Temporal Trends in Fusiform Rust Infections and Their Relationships with Stand Structure in Pine Plantations in East Texas

Correspondence of Loblolly Pine Response for Fusiform Rust Disease from Local and Wide-Ranging Tests in the Southern United States

Correspondence of Loblolly Pine Response for Fusiform Rust Disease from Local and Wide-Ranging Tests in the Southern United States

Fusiform Rust Hazard Mapping for Loblolly Pine in the Southeastern United States Using Progeny Test Data

Fusiform Rust Hazard Mapping for Loblolly Pine in the Southeastern United States Using Progeny Test Data

Correspondence of Loblolly Pine Response for Fusiform Rust Disease from Local and Wide-Ranging Tests in the Southern United States

Correspondence of Loblolly Pine Response for Fusiform Rust Disease from Local and Wide-Ranging Tests in the Southern United States