Search Results (12)

The American elm (Ulmus americana L.), once a dominant species in North American floodplain forests, has suffered significant population declines due to Dutch elm disease (DED). Despite this, some elms persist, potentially exhibiting disease resistance and climate-adaptive traits that could facilitate restoration. Understanding these traits is crucial for selecting genotypes suited to current and future climatic conditions, particularly in colder regions. This study evaluated the mid-winter cold tolerance of American elm genotypes across a climatic gradient to ascertain evidence of local climate adaptation. We used relative electrolyte leakage (REL) to assess mid-winter cold tolerance of current-year shoots on eleven survivor genotypes from New England and one susceptible, control genotype from Ohio. The lethal temperature, at which 50% of cellular leakage occurs (LT₅₀), was determined and compared with 30-year climate data to identify potential climate adaptation. Genotypes from colder regions exhibited greater cold hardiness, indicating local adaptation to climate. Observed mid-winter LT₅₀ values (−42.8 °C to −37.7 °C) were in excess of the 30-year minimum air temperature, even at the coldest source location. This calls into question whether mid-winter cold tolerance is the critical period for injury to American elm and more attention should be given to environmental conditions that cause de-acclimation to cold. By understanding the adaptive capacity of American elm, managers can better select mother trees for regional seed orchards, ensuring the long-term success of restoration initiatives. Full article

The task of tree species classification through deep learning has been challenging for the forestry community, and the lack of standardized datasets has hindered further progress. Our work presents a solution in the form of a large bark image dataset called CentralBark, which enhances the deep learning-based tree species classification. Additionally, we have laid out an efficient and repeatable data collection protocol to assist future works in an organized manner. The dataset contains images of 25 central hardwood and Appalachian region tree species, with over 19,000 images of varying diameters, light, and moisture conditions. We tested 25 species: elm, oak, American basswood, American beech, American elm, American sycamore, bitternut hickory, black cherry, black locust, black oak, black walnut, eastern cottonwood, hackberry, honey locust, northern red oak, Ohio buckeye, Osage-orange, pignut hickory, sassafras, shagbark hickory silver maple, slippery elm, sugar maple, sweetgum, white ash, white oak, and yellow poplar. Our experiment involved testing three different models to assess the feasibility of species classification using unaltered and uncropped images during the species-classification training process. We achieved an overall accuracy of 83.21% using the EfficientNet-b3 model, which was the best of the three models (EfficientNet-b3, ResNet-50, and MobileNet-V3-small), and an average accuracy of 80.23%. Full article

Maize gross primary productivity (GPP) contributes the most to the global cropland GPP, making it crucial to accurately estimate maize GPP for the global carbon cycle. Previous research validated machine learning (ML) methods using remote sensing and meteorological data to estimate plant GPP, yet they disregard vegetation physiological dynamics driven by phenology. Leaf nitrogen content per unit leaf area (i.e., specific leaf nitrogen (SLN)) greatly affects photosynthesis. Its maximum allowable value correlates with a phenological factor conceptualized as normalized maize phenology (NMP). This study aims to validate SLN and NMP for maize GPP estimation using four ML methods (random forest (RF), support vector machine (SVM), convolutional neutral network (CNN), and extreme learning machine (ELM)). Inputs consist of vegetation index (NDVI), air temperature, solar radiation (SSR), NMP, and SLN. Data from four American maize flux sites (NE1, NE2, and NE3 sites in Nebraska and RO1 site in Minnesota) were gathered. Using data from three NE sites to validate the effect of SLN and MMP shows that the accuracy of four ML methods notably increased after adding SLN and MMP. Among these methods, RF and SVM achieved the best performance of Nash–Sutcliffe efficiency coefficient (NSE) = 0.9703 and 0.9706, root mean square error (RMSE) = 1.5596 and 1.5509 gC·m⁻²·d⁻¹, and coefficient of variance (CV) = 0.1508 and 0.1470, respectively. When evaluating the best ML models from three NE sites at the RO1 site, only RF and CNN could effectively incorporate the impact of SLN and NMP. But, in terms of unbiased estimation results, the four ML models were comprehensively enhanced by adding SLN and NMP. Due to their fixed relationship, introducing SLN or NMP alone might be more effective than introducing both simultaneously, considering the data redundancy for methods like CNN and ELM. This study supports the integration of phenology and leaf-level photosynthetic factors in plant GPP estimation via ML methods and provides a reference for similar research. Full article

One of the most destructive diseases affecting grapevine in Europe is caused by Flavescence Dorée phytoplasma (FDp), which belongs to the 16Sr-V group and is a European Union quarantine pathogen. Although many molecular techniques such as loop-mediated isothermal amplification (LAMP) are widely used for the rapid detection of FDp in infected grapevine plants, there is no developed isothermal amplification assay for FDp detection in the insect vectors that are fundamental for the spread of the disease. For this reason, a simple in-field real-time LAMP protocol was optimized and developed for the specific detection of FDp in the insect vector Scaphoideus titanus. The LAMP assay was optimized to work with crude insect extracts obtained by manually shaking a single insect in a buffer for 5 min. Such a simple, sensitive, specific, economic, and user-friendly LAMP assay allowed the detection of FDp in S. titanus in less than half an hour, directly in the field. The developed insect tissue preparation procedure, combined with the LAMP protocol, promptly revealed the presence of FDp in infected S. titanus directly in the vineyards, allowing for monitoring of the spread of the pathogen in the field and to apply timely strategies required for the mandatory control of this pathogen. Full article

Evening Grosbeak (Coccothraustes vespertinus) populations have been hypothesized to be in steep decline across North America. Data characterizing long-term changes are needed to quantify the magnitude of the declines. We surveyed grosbeaks at a spring migratory stop-over site in Corvallis, Oregon, USA, where birds gather annually during April and May to feast on elm (Ulmus spp.) seeds before departing to breeding sites. An estimate produced by a statistics professor in the 1970s indicated peak numbers were 150,000 to 250,000 birds. Our surveys in 2013–2015 found annually variable numbers, from a few hundred grosbeaks in the lowest year to less than five thousand birds in the highest year. If the original estimate is approximately true, Evening Grosbeak numbers have experienced dramatic declines, averaging −2.6%/year, over the last four decades. Our local observation of declines during spring aligns with declines documented in winter across North America by bird feeder studies and in summer by the Breeding Bird Survey. We explore potential explanations for the changes in population size, such as influences of spruce budworm outbreaks, disease, and decreased structural diversity of forests owing to harvest practices. We also consider the challenges of interpreting changes in abundance of species with exceptionally variable populations, especially if population fluctuations or cycles may have long periodicities. Finally, we call for additional planned surveys to track the numbers of this enigmatic and charismatic species. Full article

The Ascomycete Ophiostoma novo-ulmi threatens elm populations worldwide. The molecular mechanisms underlying its pathogenicity and virulence are still largely uncharacterized. As part of a collaborative study of the O. novo-ulmi-elm interactome, we analyzed the O. novo-ulmi ssp. americana transcriptomes obtained by deep sequencing of messenger RNAs recovered from Ulmus americana saplings from one resistant (Valley Forge, VF) and one susceptible (S) elm genotypes at 0 and 96 h post-inoculation (hpi). Transcripts were identified for 6424 of the 8640 protein-coding genes annotated in the O. novo-ulmi nuclear genome. A total of 1439 genes expressed in planta had orthologs in the PHI-base curated database of genes involved in host-pathogen interactions, whereas 472 genes were considered differentially expressed (DEG) in S elms (370 genes) and VF elms (102 genes) at 96 hpi. Gene ontology (GO) terms for processes and activities associated with transport and transmembrane transport accounted for half (27/55) of GO terms that were significantly enriched in fungal genes upregulated in S elms, whereas the 22 GO terms enriched in genes overexpressed in VF elms included nine GO terms associated with metabolism, catabolism and transport of carbohydrates. Weighted gene co-expression network analysis identified three modules that were significantly associated with higher gene expression in S elms. The three modules accounted for 727 genes expressed in planta and included 103 DEGs upregulated in S elms. Knockdown- and knockout mutants were obtained for eight O. novo-ulmi genes. Although mutants remained virulent towards U. americana saplings, we identified a large repertoire of additional candidate O. novo-ulmi pathogenicity genes for functional validation by loss-of-function approaches. Full article

The ascomycetous fungus Ophiostoma novo-ulmi is the causative agent of the current Dutch elm disease (DED) pandemic, which has ravaged many tens of millions of European and North American elm trees. Host responses in vascular traits were studied in two Dutch elm hybrids, ‘Groeneveld’ and ‘Dodoens’, which show different vascular architecture in the secondary xylem and possess contrasting tolerances to DED. ‘Groeneveld’ trees, sensitive to DED, possessed a high number of small earlywood vessels. However, these trees showed a poor response to DED infection for the earlywood vascular characteristics. Following infection, the proportion of least vessels with a vessel lumen area less than 2500 µm² decreased from 65.4% down to 53.2%. A delayed response in the increasing density of vessels showing a reduced size in the latewood prevented neither the rapid fungal spread nor the massive colonisation of the secondary xylem tissues resulting in the death of the infected trees. ‘Dodoens’ trees, tolerant to DED, possessed a low number of large earlywood vessels and showed a prominent and fast response to DED infection. Vessel lumen areas of newly formed earlywood vessels were severely reduced together with the vessel size : number ratio. Following infection, the proportion of least vessels with a vessel lumen area less than 2500 µm² increased from 75.6% up to 92.9%. A trend in the increasing density of vessels showing a reduced size was maintained not only in the latewood that was formed in the year of infection but also in the earlywood that was formed in the consecutive year. The occurrence of fungal hyphae in the earlywood vessels that were formed a year following the infection was severely restricted, as revealed by X-ray micro-computed tomography imaging. Possible reasons responsible for a contrasting survival of ‘Groeneveld’ and ‘Dodoens’ trees are discussed. Full article

Dutch elm disease (DED), caused by Ophiostoma novo-ulmi (Onu), is a destructive disease of American elm (Ulmus americana L.). The molecular mechanisms of resistance and susceptibility against DED in American elm are still largely uncharacterized. In the present study, we performed a de novo transcriptome (RNA-sequencing; RNA-Seq) assembly of U. americana and compared the gene expression in a resistant genotype, ’Valley Forge’, and a susceptible (S) elm genotype at 0 and 96 h post-inoculation of Onu. A total of 85,863 non-redundant unigenes were identified. Compared to the previously characterized U. minor transcriptome, U. americana has 35,290 similar and 55,499 unique genes. The transcriptomic variations between ‘Valley Forge’ and ‘S’ were found primarily in the photosynthesis and primary metabolism, which were highly upregulated in the susceptible genotype irrespective of the Onu inoculation. The resistance to DED was associated with the activation of RPM1-mediated effector-triggered immunity that was demonstrated by the upregulation of genes involved in the phenylpropanoids biosynthesis and PR genes. The most significantly enriched gene ontology (GO) terms in response to Onu were response to stimulus (GO:0006950), response to stress (GO:0050896), and secondary metabolic process (GO:0008152) in both genotypes. However, only in the resistant genotype, the defense response (GO:0006952) was among the topmost significantly enriched GO terms. Our findings revealed the molecular regulations of DED resistance and susceptibility and provide a platform for marker-assisted breeding of resistant American elm genotypes. Full article

The increased abundance of historically rare native tree species is symptomatic of land-use change, which causes ecosystem regime shifts. I tested for an association between mean agricultural area, a proxy for land-use change, and native tree species. I first modeled agricultural area during the years 1850 to 1997 and the historical and current percent composition of tree genera, along with the dissimilarity and difference between the historical and current composition, for the northern part of the eastern U.S. I then modeled agricultural area and current genera and species for the eastern U.S. and regionally. For the northeast, agricultural area was most associated (R² of 78%) with the current percentage of elms and a diverse, uncommon “other” genera. For the eastern U.S., Ulmus, Juglans, Prunus, boxelder (Acer negundo), black cherry (Prunus serotina), and hackberry (Celtis occidentalis) best predicted agricultural area (R² of 66%). Regionally, two elm and ash species, black walnut (Juglans nigra), mockernut hickory (Carya tomentosa), red maple (Acer rubrum), sweetgum (Liquidambar styraciflua), and American sycamore (Platanus occidentalis) increased with agricultural area. Increases in historically rare and diverse species associated with agricultural area represent an overall pattern of invasive native tree species that have replaced historical ecosystems after land-use change disrupted historical vegetation and disturbance regimes. Full article

The potential use of elm wood in lignocellulosic industries has been hindered by the Dutch elm disease (DED) pandemics, which have ravaged European and North American elm groves in the last century. However, the selection of DED-resistant cultivars paves the way for their use as feedstock in lignocellulosic biorefineries. Here, the production of cellulose nanofibers from the resistant Ulmus minor clone Ademuz was evaluated for the first time. Both mechanical (PFI refining) and chemical (TEMPO (2,2,6,6-tetramethylpiperidine-1-oxyl radical)-mediated oxidation) pretreatments were assessed prior to microfluidization, observing not only easier fibrillation but also better optical and barrier properties for elm nanopapers compared to eucalyptus ones (used as reference). Furthermore, mechanically pretreated samples showed higher strength for elm nanopapers. Although lower nanofibrillation yields were obtained by mechanical pretreatment, nanofibers showed higher thermal, mechanical and barrier properties, compared to TEMPO-oxidized nanofibers. Furthermore, lignin-containing elm nanofibers presented the most promising characteristics, with slightly lower transparencies. Full article

The production of a desired product needs an effective use of the experimental model. The present study proposes an extreme learning machine (ELM) and a support vector machine (SVM) integrated with the response surface methodology (RSM) to solve the complexity in optimization and prediction of the ethyl ester and methyl ester production process. The novel hybrid models of ELM-RSM and ELM-SVM are further used as a case study to estimate the yield of methyl and ethyl esters through a trans-esterification process from waste cooking oil (WCO) based on American Society for Testing and Materials (ASTM) standards. The results of the prediction phase were also compared with artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS), which were recently developed by the second author of this study. Based on the results, an ELM with a correlation coefficient of 0.9815 and 0.9863 for methyl and ethyl esters, respectively, had a high estimation capability compared with that for SVM, ANNs, and ANFIS. Accordingly, the maximum production yield was obtained in the case of using ELM-RSM of 96.86% for ethyl ester at a temperature of 68.48 °C, a catalyst value of 1.15 wt. %, mixing intensity of 650.07 rpm, and an alcohol to oil molar ratio (A/O) of 5.77; for methyl ester, the production yield was 98.46% at a temperature of 67.62 °C, a catalyst value of 1.1 wt. %, mixing intensity of 709.42 rpm, and an A/O of 6.09. Therefore, ELM-RSM increased the production yield by 3.6% for ethyl ester and 3.1% for methyl ester, compared with those for the experimental data. Full article

Emerald ash borer (EAB) continues to spread across North America, infesting native ash trees and changing the forested landscape. Black ash wetland forests are severely affected by EAB. As black ash wetland forests provide integral ecosystem services, alternative approaches to maintain forest cover on the landscape are needed. We implemented simulated EAB infestations in depressional black ash wetlands in the Ottawa National Forest in Michigan to mimic the short-term and long-term effects of EAB. These wetlands were planted with 10 alternative tree species in 2013. Based on initial results in the Michigan sites, a riparian corridor in the Superior Municipal Forest in Wisconsin was planted with three alternative tree species in 2015. Results across both locations indicate that silver maple (Acer saccharinum L.), red maple (Acer rubrum L.), American elm (Ulmus americana L.), and northern white cedar (Thuja occidentalis L.) are viable alternative species to plant in black ash-dominated wetlands. Additionally, selectively planting on natural or created hummocks resulted in two times greater survival than in adjacent lowland sites, and this suggests that planting should be implemented with microsite selection or creation as a primary control. Regional landowners and forest managers can use these results to help mitigate the canopy and structure losses from EAB and maintain forest cover and hydrologic function in black ash-dominated wetlands after infestation. Full article