Biology and ecology of Leptographium species and their vectos as components of loblolly pine decline

Loblolly pine (Pinus taeda L.) decline (LPD) has been present in upland sites of central Alabama since the 1960s. Symptoms of LPD (fine root deterioration, short chlorotic needles, sparse crowns, reduced radial growth) begin in the 30-40 yr age class, resulting in premature death at ages 35-50. Previously, declining loblolly was diagnosed as littleleaf disease (LLD); however, site conditions associated with LPD are different from LLD sites. Littleleaf disease only occurs on eroded, heavy clay soils and is secondarily associated with the fungus, Phytophthora cinnamomi. In contrast, LPD occurs on sandy, well-drained soils and is associated with Leptographium spp., as well as with root-feeding bark beetles and weevils. In the present study, 17 species (eleven newly reported) of subcortical root- and lower-stem feeding beetles were identified as vectors of Leptographium species, of which Hylastes salebrosus, H. tenuis, Hylobius pales and Pachylobius picivorus were statistically more abundant (F3,14=13.90, p=0.003) in LPD sites. Leptographium terebrantis, L. procerum, L. lundbergii, and L. serpens were isolated from the roots and insects. Pathogenicity studies suggested that L. lundbergii and L. serpens, fungi not previously reported in the U.S., were more virulent on loblolly pine. Spatial analysis correlated LPD to site and stand physical factors. Slope and aspect were the predominant predictive variables of LPD in central Alabama. Convexity and elevation were predictive only in combination with other topographical factors. These analyses have allowed the creation of LPD risk maps to accurately predict areas of loblolly decline, providing a vital new tool for managing southern forests for predetermined purposes

The Response of Visible/Near Infrared Absorbance to Wood-Staining Fungi

The influence of blue-stain fungi [Ophiostoma minus (Hedgcock) H. and P. Sydow and Leptographium serpens (Goid.) Siemaszko] on absorbance at the visible and near infrared wavelengths was investigated. Forty trees were sampled at breast height from longleaf pine (Pinus palustris Mill.). One half of each increment core was inoculated with one of two fungi treatments while the other half served as a control. Visible and near infrared spectra were acquired between rings 3-40 for the stained and control-clear wood samples (n = 304). Absorbance was greater for the stained than the control wood at wavelengths between 464 to 1334 nm. Statistical techniques were applied to the NIR data to determine which wavelengths, and their corresponding chemical assignments, were most affected by the fungi. First and 2nd derivative pretreatments to the original spectra resulted in some blue-stain sensitive wavelengths throughout the 350 to 2500 nm range, some of which are associated with nitrogen in the melanin present in blue stain. However, for the 2nd derivative pretreatment, the stained wood exhibited a different signal to noise ratio than the control wood, and thus the pretreatment method should be used with vigilance. For the raw, 1st, and 2nd derivatives, the absorbance of L. serpens (n = 164) significantly differed from O. minus (n = 140) between 424-554 nm. The results of this study are important because the absorbance at visible and NIR wavelengths may be used to classify stained wood

Rapid Quantitative Analysis of Forest Biomass Using Fourier Transform Infrared Spectroscopy and Partial Least Squares Regression

Fourier transform infrared reflectance (FTIR) spectroscopy has been used to predict properties of forest logging residue, a very heterogeneous feedstock material. Properties studied included the chemical composition, thermal reactivity, and energy content. The ability to rapidly determine these properties is vital in the optimization of conversion technologies for the successful commercialization of biobased products. Partial least squares regression of first derivative treated FTIR spectra had good correlations with the conventionally measured properties. For the chemical composition, constructed models generally did a better job of predicting the extractives and lignin content than the carbohydrates. In predicting the thermochemical properties, models for volatile matter and fixed carbon performed very well (i.e., R2 > 0.80, RPD > 2.0). The effect of reducing the wavenumber range to the fingerprint region for PLS modeling and the relationship between the chemical composition and higher heating value of logging residue were also explored. This study is new and different in that it is the first to use FTIR spectroscopy to quantitatively analyze forest logging residue, an abundant resource that can be used as a feedstock in the emerging low carbon economy. Furthermore, it provides a complete and systematic characterization of this heterogeneous raw material

Menulis Kreatif Cerita Fiksi Anak

<p>Predictive performance of TG-based chemometric models versus kinetic models.</p

Microsatellite and mating type markers reveal unexpected patterns of genetic diversity in the pine root-infecting fungus Grosmannia alacris

Grosmannia alacris is a fungus commonly associated with root-infesting bark beetles occurring on Pinus spp. The fungus has been recorded in South Africa, the USA, France, Portugal and Spain and importantly, has been associated with pine root diseases in South Africa and the USA. Nothing is known regarding the population genetics or origin of G. alacris, although its association with root-infesting beetles native to Europe suggests that it is an invasive alien in South Africa. In this study, microsatellite markers together with newly developed mating type markers were used to characterize a total of 170 isolates of G. alacris from South Africa and the USA. The results showed that the genotypic diversity of the South African population of G. alacris was very high when compared to the USA populations. Two mating types were also present in South African isolates and the MAT1-1/MAT1-2 ratio did not differ from 1:1 (χ2 = 1·39, P = 0·24). This suggests that sexual reproduction most probably occurs in the fungus in South Africa, although a sexual state has never been seen in nature. In contrast, the large collection of USA isolates harboured only a single mating type. The results suggest that multiple introductions, followed by random mating, have influenced the population structure in South Africa. In contrast, limited introductions of probably a single mating type (MAT1-2) may best explain the clonality of USA populations.The Members of Tree Protection Co-operative Programme (TPCP), the National Research Foundation (NRF) and the University of Pretoria, Pretoria, South Africa,http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-30592016-02-27hj201

The Impact of Drought and Vascular-Inhabiting Pathogen Invasion in Pinus taeda Health

The complex interaction of various biotic and abiotic factors may put the overall stand health of Pinus spp. at risk. A study was designed to determine the combined impact of drought and vascular-inhabiting fungi (Leptographium terebrantis and Grosmannia huntii) in Pinus taeda. Seedlings from two P. taeda families were planted and watering treatments, (i) normal watering, (ii) moderate drought, and (iii) severe drought, were applied. One month following the initiation of watering treatments, seedling stems were artificially inoculated with L. terebrantis and G. huntii. Drought and fungal interaction significantly affected lesion length/seedling height, occlusion length/seedling height, and seedling fine root biomass. Leptographium terebrantis was more pathogenic under moderate and severe drought than normal watering condition, whereas the pathogenicity of G. huntii remains unaltered. The susceptibility of the families to vascular-inhabiting fungi remained the same under different watering treatments. Drought and specific vascular-inhabiting fungi may negatively impact P. taeda stand health

Data from: Genetically determined fungal pathogen tolerance and soil variation influences ectomycorrhizal traits of loblolly pine

1. 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. 2. 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 (PD) or fusiform rust (FR) disease, we investigated trait variation and trait correlations within loblolly pine (Pinus taeda L.) by determining how ectomycorrhizal (EM) colonization relates to pathogen susceptibility. 3. 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. 4. 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. 5. 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

Rapid Quantitative Analysis of Forest Biomass Using Fourier Transform Infrared Spectroscopy and Partial Least Squares Regression

Fourier transform infrared reflectance (FTIR) spectroscopy has been used to predict properties of forest logging residue, a very heterogeneous feedstock material. Properties studied included the chemical composition, thermal reactivity, and energy content. The ability to rapidly determine these properties is vital in the optimization of conversion technologies for the successful commercialization of biobased products. Partial least squares regression of first derivative treated FTIR spectra had good correlations with the conventionally measured properties. For the chemical composition, constructed models generally did a better job of predicting the extractives and lignin content than the carbohydrates. In predicting the thermochemical properties, models for volatile matter and fixed carbon performed very well (i.e., R2 > 0.80, RPD > 2.0). The effect of reducing the wavenumber range to the fingerprint region for PLS modeling and the relationship between the chemical composition and higher heating value of logging residue were also explored. This study is new and different in that it is the first to use FTIR spectroscopy to quantitatively analyze forest logging residue, an abundant resource that can be used as a feedstock in the emerging low carbon economy. Furthermore, it provides a complete and systematic characterization of this heterogeneous raw material

A new Ophiostoma species from loblolly pine roots in the southeastern United States

During the course of a survey of fungi in loblolly pine (Pinus taeda) roots in Georgia, USA, a species of Ophiostoma morphologically similar to O. pluriannulatum, was isolated. Morphological characteristics and DNA sequence comparisons were used to identify the fungus. The isolates produced perithecia with unusually long necks similar to those of O. pluriannulatum but they had few or no annuli. DNA sequences for the ribosomal internal transcribed spacer regions 1 and 2 were identical to those of O. pluriannulatum. Sequence data of the β-tubulin gene region revealed the absence of intron 4 and presence of intron 5, distinguishing the isolates from O. pluriannulatum, which has intron 4 but not intron 5. Phylogenetic analyses of the β-tubulin sequences showed that the isolates from loblolly pine roots grouped together in a lineage distinct from O. multiannulatum and O. subannulatum, both of which lack intron 4 and have intron 5. The fungus is consequently described as O. sparsiannulatum sp. nov., a novel taxon in the O. pluriannulatum complex.United States Department of Defense via Fort Benning Military Reservation, members of the Tree Protection Cooperative Program (TPCP), DST/NRF Centre of Excellence in Tree Health Biotechnology (CTHB

Identifying Plant Part Composition of Forest Logging Residue Using Infrared Spectral Data and Linear Discriminant Analysis

As new markets, technologies and economies evolve in the low carbon bioeconomy, forest logging residue, a largely untapped renewable resource will play a vital role. The feedstock can however be variable depending on plant species and plant part component. This heterogeneity can influence the physical, chemical and thermochemical properties of the material, and thus the final yield and quality of products. Although it is challenging to control compositional variability of a batch of feedstock, it is feasible to monitor this heterogeneity and make the necessary changes in process parameters. Such a system will be a first step towards optimization, quality assurance and cost-effectiveness of processes in the emerging biofuel/chemical industry. The objective of this study was therefore to qualitatively classify forest logging residue made up of different plant parts using both near infrared spectroscopy (NIRS) and Fourier transform infrared spectroscopy (FTIRS) together with linear discriminant analysis (LDA). Forest logging residue harvested from several Pinus taeda (loblolly pine) plantations in Alabama, USA, were classified into three plant part components: clean wood, wood and bark and slash (i.e., limbs and foliage). Five-fold cross-validated linear discriminant functions had classification accuracies of over 96% for both NIRS and FTIRS based models. An extra factor/principal component (PC) was however needed to achieve this in FTIRS modeling. Analysis of factor loadings of both NIR and FTIR spectra showed that, the statistically different amount of cellulose in the three plant part components of logging residue contributed to their initial separation. This study demonstrated that NIR or FTIR spectroscopy coupled with PCA and LDA has the potential to be used as a high throughput tool in classifying the plant part makeup of a batch of forest logging residue feedstock. Thus, NIR/FTIR could be employed as a tool to rapidly probe/monitor the variability of forest biomass so that the appropriate online adjustments to parameters can be made in time to ensure process optimization and product quality