Mapping phyllopshere and soil fungal function using AVRIS-NG hyperspectral data

Challenge Microbial communities play a crucial role in forest ecosystems, where they are fundamental to the health, structure, and sustainability of the forest. Developments in molecular research allow for the evaluation of these understudied communities but are generally too costly and labour intensive for large-scale assessments. In temperate forests, the collection of samples from the top canopy (phyllopshere) especially poses challenges due to the accessibility of the crown of tall (30+ meter) trees, greatly limiting the spatial and temporal density of existing sample points. Advances in hyperspectral sensors offers a solution for bridging these data gaps, enabling the extrapolation of environmental DNA (eDNA)-based microbial profiles across extensive regions. Methodology To demonstrate the utilisation of hyperspectral airborne data to predict and map microbial functions of temperate European forests, we modelled the spatial distribution of fungal trophic groups in the soil and top-canopy using AVRIS-NG hyperspectral airborne data collected from the Bavarian Forest National Park in Germany. Putative functional profiles were created from eDNA (genetic material obtained from environmental samples [e.g. canopy, soil] without capturing the organisms themselves) samples from soil and top-canopy leaf material. The public data base “Funguild” was used to concatenate eDNA taxonomic data to functional profiles, allowing linking microbial profiles to ecosystem functions. The fungal functional profiles were used as training and validation data for the models (using PLSR and gaussian processing algorithms), which were consecutive inverted for prediction and mapping. Results Our results show for the first time that microbial function in the soil and canopy can accurately predicted for temperate European forests when combining eDNA point profiles with AVRIS-NG hyperspectral airborne data. The findings demonstrate that fungal trophic groups show substantial variation in their spatial distribution across a forest landscape. Furthermore, top canopy functions were predicted with higher reliability than soil microbial functions, presumably due to the stronger link between the phyllosphere and host-tree attributes (chemical, compositional, and functional characteristics) that can be sensed remotely using spectral reflectance. Outlook for the futureThis study demonstrates a clear example of how spaceborne next generation hyperspectral data could be used to effectively predict putative microbial functions, providing maps and models with high relevance for forest ecology and management. The findings of this study highlight a significant breakthrough in utilizing airborne or spaceborne next-generation hyperspectral data to effectively predict putative microbial functions, and this research offers valuable insights and tools essential for the sustainable management of forests. Looking ahead, novel next-generation remote sensing platforms, such as the imminent launch of the CHIME satellite, holds the promise of revolutionizing the utilisation and upscaling of environmental DNA (eDNA) point-based information, offering innovative solutions for addressing ecological challenges on a global scale.<br/

Temperate forest soil pH accurately Quantified with image spectroscopy

Forest canopies to some extent obscure passive reflectance of soil traits such as pH, as well as below-canopy vegetation, in the optical to middle infrared portions of the electromagnetic spectrum (approximately 400–2500 nm) which are typically used in airborne and spaceborne image spectrometers. In this study, we present, for the first time, an accurate estimation of soil pH across extensive areas using hyperspectral imaging data obtained from the DLR Earth Sensing Imaging Spectrometer (DESIS) satellite. Furthermore, we investigate the impact of predicted soil pH variation on the concentrations of micronutrients in both leaves and soil. Our modelling is based on a comprehensive in-situ field campaign conducted during the summers of 2020 and 2021. This campaign collected soil pH data for model calibration and validation from 197 plots located across three distinct temperate forest sites: Veluwezoom and Hoge Veluwe National Parks in the Netherlands, as well as the Bavarian Forest National Park in Germany. The soil pH for each test site was accurately predicted by means of a partial least squares regression (PLSR) model, root mean square error (RMSEcv) of 0.22 and the cross-validated coefficient of determination (R2CV) of 0.66. Our findings demonstrate that there are patches of extremely low soil pH possibly due to ongoing soil acidification processes. We saw a particularly significant decrease in soil pH (p ≤ 0.05) in the coniferous forests when compared to the deciduous forest. The acidification of forest soils had a profound impact on the variation of soil and leaf micronutrient content, particularly iron concentration. These results highlight the potential of image spectroscopy data from the DESIS satellite to monitor and estimate soil pH in forested areas over extensive areas given sufficient data. Our findings hold significant implications for soil pH monitoring programs, enabling forest managers to assess the impact of their management practices and gauge their effectiveness in maintaining soil and forest vitality

Postsecondary Outcomes of Georgia’s Adult Education Students

The Technical College System of Georgia (TCSG) oversees Georgia’s public technical colleges, workforce development programs, and adult basic skills education (“adult education”) system. Classes in this system help adult students (“adult learners”) improve literacy, numeracy, communications, and other skills. A goal for some learners is to develop the skills needed to enroll and succeed in a two- or four-year postsecondary institution. This report, by researchers in the Adult Literacy Research Center and the Child & Family Policy Lab, examines the number and characteristics of these learners in Georgia who subsequently enroll in the state’s public technical colleges, colleges, and universities and their postsecondary academic outcomes. It analyzes administrative data from the TCSG adult education system, TCSG technical colleges, and the University System of Georgia (USG). It also compares the characteristics of technical college and USG students who had and had not previously enrolled in this system. A quarter of learners who enter with advanced secondary education skills subsequently enroll in public postsecondary institutions. Enrollments are lower if learners enter with fewer skills. Learners who are younger, attend more hours of classes, earn high school equivalency credentials, take integrated education and training classes, make measurable skill gains, or have more experienced or full-time teachers have higher postsecondary enrollment rates than other learners. Compared to other students in public technical colleges, students with adult education backgrounds are more likely to be women or Asian and slightly less likely to be Black or Hispanic.https://scholarworks.gsu.edu/gpl_reports/1042/thumbnail.jp

A fringe projection profilometry scheme based on embedded speckle patterns and robust principal component analysis

2019 SPIE. Phase unwrapping is one of the key steps for fringe projection profilometry (FPP)-based 3D shape measurements. Conventional spatial phase unwrapping schemes are sensitive to noise and discontinuities, which may suffer from low accuracies. Temporal phase unwrapping is able to improve the reliability but often requires the acquisition of additional patterns, increasing the measurement time or hardware costs. This paper introduces a novel phase unwrapping scheme that utilizes composite patterns consisting of the superposition of standard sinusoidal patterns and randomly generated speckles. The low-rankness of the deformed sinusoidal patterns is studied. This is exploited together with the sparse nature of the speckle patterns and a robust principal component analysis (RPCA) framework is then deployed to separate the deformed fringe and speckle patterns. The cleaned fringe patterns are used for generating the wrapped phase maps using the standard procedures of phase shift profilometry (PSP) or Fourier Transform profilometry (FTP). Phase unwrapping is then achieved by matching the deformed speckle patterns that encode the phase order information. In order to correct the impulsive fringe order errors, a recently proposed postprocessing step is integrated into the proposed scheme to refine the phase unwrapping results. The analysis and simulation results demonstrate that the proposed scheme can improve the accuracy of FPP-based 3D shape measurements by effectively separating the fringe and speckle patterns

Quantifying Canopy Nitrogen Content in a Soil-Acidified Temperate Forest Using Image Spectroscopy

The challenge of monitoring the impact of soil acidification on forest health is a critical ecological concern, particularly in the context of increasing nitrogen deposition, which results in decreased soil pH levels. Soil acidification, often stemming from excess nitrogen deposition from sources such as industrial emissions and agricultural runoff, has far-reaching consequences on forest ecosystems. It disrupts the delicate natural nutrient balance within these ecosystems, directly influencing nutrient availability to the forest's resident trees. The interplay of soil acidification and nitrogen deposition creates a multifaceted problem for forest management and conservation. When soil pH levels drop, it can lead to leaching of essential nutrients, like calcium and magnesium, which are vital for the health of both the soil and the trees. This nutrient imbalance negatively affects the growth and vitality of the forest ecosystem, making it imperative to monitor and mitigate these changes effectively. Traditionally, monitoring the impact of soil acidification on forest health has been a challenging task. To address this, scientists and environmental researchers have been exploring advanced technologies, one of which is the use of hyperspectral satellites like PRISMA. These newly launched satellites have the potential to revolutionize our ability to assess the effects of soil acidification on forest ecosystems

Forest soils further acidify in core Natura 2000 areas amongst unaware government policy

The intensification of agriculture and livestock husbandry has led to increasing atmospheric deposition of nitrogenous compounds and soil acidification. We field measured extremely acidic soils with pH &lt; 3 (i.e., soils with the acidity of domestic vinegar) over extensive areas of the forested national parks on sandy soils in the Netherlands. These areas show stress from the negative impacts of increased soil acidity on forest health and biodiversity. We demonstrate that soil acidity has worsened from an average pH of approximately 4.5 to the current average pH = 3.2 over the last 22 years for extensive areas of Natura 2000 forest soils in the Netherlands. Current government policy has been guided without knowledge of such extreme acidity because the field data sampling does not cover Natura 2000 areas, and soil acidification was estimated based on poorly calibrated atmospheric nitrogen deposition models. The policy challenge of soil acidification in Natura2000 areas is solvable with the following recommendations: • Implement regulatory action to biennially field sample soil pH across Natura 2000 forest parks, focusing on sandy soils with limited buffering capacity. • To include in models of nitrogen deposition all sources of nitrogen, including for example off-leash dog walking areas in Natura 2000 forest areas. • To use these soil pH field samples to regularly recalibrate estimates of soil pH from atmospheric nitrogen deposition models to better inform government, industry, and the agricultural sector about the ongoing impact of N deposition on already severely acidic soils. • To implement further significant reductions in the deposition of all nitrogen compounds on Natura 2000 areas.</p

How Fragile is Relation Extraction under Entity Replacements?

Relation extraction (RE) aims to extract the relations between entity names from the textual context. In principle, textual context determines the ground-truth relation and the RE models should be able to correctly identify the relations reflected by the textual context. However, existing work has found that the RE models memorize the entity name patterns to make RE predictions while ignoring the textual context. This motivates us to raise the question: ``are RE models robust to the entity replacements?'' In this work, we operate the random and type-constrained entity replacements over the RE instances in TACRED and evaluate the state-of-the-art RE models under the entity replacements. We observe the 30\% - 50\% F1 score drops on the state-of-the-art RE models under entity replacements. These results suggest that we need more efforts to develop effective RE models robust to entity replacements. We release the source code at https://github.com/wangywUST/RobustRE

Forest top canopy bacterial communities are influenced by elevation and host tree traits

Background: The phyllosphere microbiome is crucial for plant health and ecosystem functioning. While host species play a determining role in shaping the phyllosphere microbiome, host trees of the same species that are subjected to different environmental conditions can still exhibit large degrees of variation in their microbiome diversity and composition. Whether these intra-specific variations in phyllosphere microbiome diversity and composition can be observed over the broader expanse of forest landscapes remains unclear. In this study, we aim to assess the variation in the top canopy phyllosphere bacterial communities between and within host tree species in the temperate European forests, focusing on Fagus sylvatica (European beech) and Picea abies (Norway spruce).Results: We profiled the bacterial diversity, composition, driving factors, and discriminant taxa in the top canopy phyllosphere of 211 trees in two temperate forests, Veluwe National Parks, the Netherlands and Bavarian Forest National Park, Germany. We found the bacterial communities were primarily shaped by host species, and large variation existed within beech and spruce. While we showed that there was a core microbiome in all tree species examined, community composition varied with elevation, tree diameter at breast height, and leaf-specific traits (e.g., chlorophyll and P content). These driving factors of bacterial community composition also correlated with the relative abundance of specific bacterial families.Conclusions: While our results underscored the importance of host species, we demonstrated a substantial range of variation in phyllosphere bacterial diversity and composition within a host species. Drivers of these variations have implications at both the individual host tree level, where the bacterial communities differed based on tree traits, and at the broader forest landscape level, where drivers like certain highly plastic leaf traits can potentially link forest canopy bacterial community variations to forest ecosystem processes. We eventually showed close associations between forest canopy phyllosphere bacterial communities and host trees exist, and the consistent patterns emerging from these associations are critical for host plant functioning

Identification of 3 key genes as novel diagnostic and therapeutic targets for OA and COVID-19

BackgroundCorona Virus Disease 2019 (COVID-19) and Osteoarthritis (OA) are diseases that seriously affect the physical and mental health and life quality of patients, particularly elderly patients. However, the association between COVID-19 and osteoarthritis at the genetic level has not been investigated. This study is intended to analyze the pathogenesis shared by OA and COVID-19 and to identify drugs that could be used to treat SARS-CoV-2-infected OA patients.MethodsThe four datasets of OA and COVID-19 (GSE114007, GSE55235, GSE147507, and GSE17111) used for the analysis in this paper were obtained from the GEO database. Common genes of OA and COVID-19 were identified through Weighted Gene Co-Expression Network Analysis (WGCNA) and differential gene expression analysis. The least absolute shrinkage and selection operator (LASSO) algorithm was used to screen key genes, which were analyzed for expression patterns by single-cell analysis. Finally, drug prediction and molecular docking were carried out using the Drug Signatures Database (DSigDB) and AutoDockToolsResultsFirstly, WGCNA identified a total of 26 genes common between OA and COVID-19, and functional analysis of the common genes revealed the common pathological processes and molecular changes between OA and COVID-19 are mainly related to immune dysfunction. In addition, we screened 3 key genes, DDIT3, MAFF, and PNRC1, and uncovered that key genes are possibly involved in the pathogenesis of OA and COVID-19 through high expression in neutrophils. Finally, we established a regulatory network of common genes between OA and COVID-19, and the free energy of binding estimation was used to identify suitable medicines for the treatment of OA patients infected with SARS-CoV-2.ConclusionIn the present study, we succeeded in identifying 3 key genes, DDIT3, MAFF, and PNRC1, which are possibly involved in the development of both OA and COVID-19 and have high diagnostic value for OA and COVID-19. In addition, niclosamide, ciclopirox, and ticlopidine were found to be potentially useful for the treatment of OA patients infected with SARS-CoV-2