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FINE ROOT AND ECTOMYCORRHIZAL FUNCTIONAL TRAITS OF QUERCUS RUBRA POPULATIONS FROM ACROSS A LATITUDINAL GRADIENT
No full textForests are increasingly considered for their carbon sequestration value, but their ability to store carbon is dependent on a close balance between carbon fluxes into and out of ecosystems. Nutrient uptake of roots and associated symbiotic communities results in respiratory carbon release, which is projected to increase with warming and represents a substantial uncertainty in earth system modeling. Traits that are functionally related to nutrient uptake can be used to estimate carbon fluxes, but our understanding of the trade-offs that govern root, and especially fungal, traits is limited. Fine roots in surface soils are responsible for the bulk of plant nutrient uptake and therefore C release, and are thought to vary along two trade-off dimensions that describe their nutrient uptake and soil foraging capacities. Multiple hypotheses have been proposed to explain the second dimension, including differences in ectomycorrhizal collaboration. In this dissertation, I investigated fine root and ectomycorrhizal trait coordination across Quercus rubra populations, as well as relationships between these traits and environmental factors across a Midwest, U.S. latitudinal gradient. In addition, I measured these traits in an established common garden experiment to assess their potential for adaptive plasticity and relationships to aboveground growth. Intraspecific root traits were governed by similar trade-offs as those across species, and the second dimension was related to ectomycorrhizal traits. Fine root carbon fluxes did relate to root traits, but the total root respiratory flux was heavily dependent on fine root biomass variation. In a replicated common garden experiment, root activity-related traits, but not root respiration, showed strong potential for adaptive plasticity. Root foraging traits related to aboveground growth and showed moderate evidence of plasticity, while ectomycorrhizal community traits appeared to adjust to common garden site. Though there were some potential growth rate reductions mediated by fine root and fungal traits between populations and common garden sites, the generalist ectomycorrhizal community and relatively strong potential for adaptive plasticity suggests that nutrient uptake of Q. rubra populations may be resilient to a moderate degree of environmental change, though reductions in fine root biomass would likely be needed to offset carbon loss from increased root respiration rates
ECOLOGICAL FACTORS THAT DICTATE THE OCCURRENCE OF UNIQUE BIOTA ON GRANITE BEDROCK GLADES
No full textThis is a multi-taxa study of the ecological factors which differentiate communities of granite bedrock glades from surrounding areas (peripheral and matrix forest). It includes vascular plants, lichens, bryophytes, reptiles and birds. This study demonstrated that the same predictor variables (percent canopy cover and amount of exposed bedrock) were associated with the strongest gradient for all taxonomic groups evaluated.
Microclimates were studied in bedrock glades and surrounding communities by deploying 60 data loggers. Data were collected on vascular plants and cryptogams (lichens and mosses) at the precise logger locations and related to climatic factors. Annual mean temperature, growing degree days, and the 95th percentile of maximum temperature were analyzed as potential drivers for the three habitats. The climate variables demonstrated that bedrock glades were significantly warmer than periphery and matrix forest, 11-20 m and 41-50 m from the edge of the glades respectively.
Models were made for pre-selected southern disjunct species with measured habitat and climatic variables using nonparametric multiplicative regression (NPMR) conducted using Hyperniche (version 2.3). Significant environmental models showed that variables related to lichen guilds, distance to Lake Superior, canopy cover, elevation and distance to human roads and trails were most important for the target animal species. The most important climatic variables in the models were related to soil and ground-level growing degree days, and daily temperature range on the ground.
The impacts of drought have been less studied in terrestrial plant communities than other types of natural disturbance. Most drought studies have focused on regional impacts or used climate modeling over a broad geographic area. In May 2021, prior to drought conditions, 100-m-long transects were established; they were sampled with 1-m² plots in September 2021 after an unusually dry spring and summer. Environmental variables were recorded at two scales (site and plot level), and cover values for alive and top-killed vegetation cover were given for each species. Among the 48 species in our study, 18 experienced at least some top-kill, and 26% of the total vegetation cover was top-killed in 2021.
Nonmetric multidimensional scaling ordination (NMS) was used to describe the variation in top-killed plant data among plots and species. The plots with the highest dead plant cover were on south-facing slopes with no tree canopy cover. This study also reports the first collection of two plant species, Nuttallanthus canadensis (L.) D.A.Sutton (Plantaginaceae), and Opuntia cespitosa Raf. (Cactaceae) from the Lake Superior drainage basin, and both appear to be the northernmost occurrences of these species in eastern North America
THE ROLE OF REMOTE SENSING AND GIS TECHNIQUES IN ANALYSIS OF SOUTHERN CALIFORNIA WILDFIRES IN JANUARY 2025
No full textCalifornia is no stranger to wildfires, with them becoming more frequent and larger in recent years. In early January 2025, Southern California had one of the worst outbreaks of wildfires in its history, with the Pacific Palisades and Eaton Fires being considered among the most destructive in state history. To help prevent this from happening in the future, remote sensing techniques are essential in combating these issues. In this report, geographic information systems (GIS) and remote sensing data utilized to explore fire behavior by various organizations were investigated. By using this data, this study aims to predict and monitor fire behavior, including smoke plume dispersion, as well as analyze post-fire data. This is achieved through the examination of satellite imagery and spatial datasets. These results are valuable for the development and future of remote sensing and protecting the environment from future natural disasters
Price Adjustment Clauses in Highway Construction: State of the Practice
No full textMaterial price volatility creates uncertainty for highway construction projects. This uncertainty complicates bid preparation because suppliers may be unable to guarantee fixed material prices for the project duration. In response, contractors often include risk premiums, leading to price speculation and inflated bid prices. These embedded contingencies may cause transportation agencies to overpay under fixed-price contracts. To address these risks, state DOTs implement material price adjustment clauses (PACs) in certain highway construction contracts. While PACs are commonly applied to construction materials such as fuel, asphalt, steel, and cement, their implementation varies across several decision factors—including eligible bid items, trigger thresholds, opt-in/opt-out provisions, caps, and more. The growing interest in PACs, along with these variations, underscores the need for a review of current practices to identify the key elements shaping their use. This study reviews PAC implementation across 50 state DOTs, focusing on variations in PAC eligibility requirements, contractual conditions, triggering events, and calculation process. Data were collected from publicly available specifications, verified through direct communication with state DOT construction-related representatives, and analyzed using content analysis. Results show that 96% of state DOTs implement at least one type of material price adjustment (including pilot implementation), with fuel (84%) and asphalt (80%) being the most common, followed by steel (36%) and cement (6%). Most PACs require a 5% trigger value to activate price adjustment and use an indexed material usage per unit method for calculation. These findings offer a national reference point for evaluating the current practices and considering potential improvements to PAC implementation strategies
Urban real-time rainfall-runoff prediction using adaptive SSA-decomposition with dual attention
No full textUrban real-time rainfall-runoff prediction is a complex task in hydrological simulation due to the strong nonlinearity and fluctuation inherent in urban rainfall-runoff processes. Recently, decomposition based deep-learning (DD) frameworks have gained popularity for significantly improving runoff prediction accuracy. However, most of these DD frameworks treat the entire data sequence as a single decomposition unit, which brings the risk of data leakage, limiting their real-time practical applicability. Additionally, these DD frameworks also neglected careful consideration of how sub-sequences obtained from decomposition should be extracted in subsequent deep-learning (DL) modules. To address these limitations, this investigation proposes adaptive singular spectrum analysis (SSA) decomposition with dual attention (ASDA) model. This model first segments the entire rainfall-runoff sequence into many short decomposition units, thus effectively eliminating the risk of data leakage; then we design 3 filters based on adaptive SSA that can adaptively decompose each such short unit into trend, fluctuation and noise sub-sequences by dynamically calculating singular values of embedding matrix. As for DL-based feature extraction procedure, dual attention mechanism that consists of a back-query attention (BQA) and a trans self-attention (TSA) is proposed, BQA dynamically assess the contributions of trend and fluctuation sequences before LSTM-based main feature extractors, and TSA interactively fuse the two extracted features after extractors. Additionally, soft dynamic time warping (soft-DTW) is incorporated into the loss evaluation to better guide ASDA model training. Performance of the proposed ASDA is validated by our observed urban rainfall events from January 2018 to December 2019 in a complex terrain covering 3.52 km2 in Chongqing, China. Key experimental results outperform conventional DL and machine-learning models: LSTM, GRU, RNN, TCN, Transformer and LightGBM in terms of NSE, KGE, RMSE, MAE and Pbias coefficients, providing a potential URRP approach for water-resource management in urban areas
Three-step LES-C models for flows at high Reynolds numbers
No full textWe investigate the need for the second correction step in the recently proposed LES-C models for fluid flows at high Reynolds numbers. These models use a predictor-corrector idea to enhance the efficiency of the existing Large Eddy Simulation models. Different three-step (one defect step, two corrections) LES-C models, based on the Leray-α, ADM and NS-ω LES models, are tested in three different situations. The new Leray-α-C2 model (C2 stands for two correction steps) is applied to the Navier–Stokes equations; the ADC2 is applied to the MagnetoHydroDynamic flow; and the NS-ω-C2 is used in the fluid-fluid interaction problem. We evaluate the effectiveness of the second correction step in all these settings, using qualitative and quantitative numerical tests
Lower ACLR Failure Rates in Bone–Soft Tissue Versus Soft Tissue–Only Allografts in Adults: A Systematic Review and Meta-analysis
No full textBackground: While allografts are commonly used for anterior cruciate ligament reconstruction (ACLR), evidence to guide specific allograft selection is lacking. Purpose: To compare clinical and graft failure rates after ACLR using soft tissue–only allografts and bone–soft tissue allografts in adults. Study Design: Systematic review and meta-analysis; Level of evidence, 4. Methods: English-language studies with clinical outcome data on primary and revision ACLR in adults with nonirradiated soft tissue–only and bone–soft tissue grafts were identified in the search. Data extracted included allograft type, patient characteristics, follow-up time, and failure rates. The cumulative failure rate was defined as International Knee Documentation Committee grade C/D, graft retear, grade ≥2+ Lachman, grade ≥2+ pivot shift, and/or side-to-side KT-1000 laxity of \u3e5 mm. The graft rupture rate was defined solely by the proportion of patients who had a graft rupture. Meta-analyses using the inverse variance method were used to estimate the pooled rates with 95% CIs. Subgroup analysis was conducted to compare allograft types and determine whether age, sex, and follow-up time influenced the estimates. Results: A total of 14 studies met the inclusion criteria: 7 investigated bone–soft tissue allografts, 6 investigated soft tissue–only allografts, and 1 investigated both. The comparative study showed a difference in the cumulative failure rate between bone–patellar tendon–bone and soft tissue–only allografts. The pooled cumulative failure rates for bone–soft tissue and soft tissue–only allografts were 11% (95% CI, 7-17) and 20% (95% CI, 14-29), respectively (P =.05). The pooled graft rupture rates for bone–soft tissue and soft tissue–only allografts were 6% (95% CI, 4-9) and 13% (95% CI, 7-23), respectively (P =.07). Conclusion: The meta-analysis results showed that bone–soft tissue allografts have lower cumulative failure rates than soft tissue–only allografts. Bone–soft tissue allografts may be the preferred allograft choices for ACLR
Assessing Perceptions of Genetically Improved Tree Species Among Family Forest Owners (FFO) in Michigan, Minnesota, and Wisconsin
No full textForests face ongoing challenges that can threaten species\u27 survival, forest health, and potentially create human impacts. Genetic engineering allows scientists to potentially address these concerns by creating genetically improved trees (GITs). Little research exists regarding the acceptance of GITs among potential implementers, such as family forest owners (FFO). This study explores stated GIT acceptance among FFOs in Michigan, Minnesota, and Wisconsin through survey data and alongside existing research. We problematize “social acceptance” when detached from the realities of adoption, implementation, and decision-making. This paper contributes insights into FFO perceptions of GITs and regarding the research design of similar studies. Respondents associated greater benefit and less risk with genetic improvement methods that may be perceived as “more natural,” and stated that they would be willing to consider planting GITs under certain conditions. Policymakers and scientists should consider the perspectives of potential technology implementers related to GIT use given their role in greater forest management
Synthesis of Fe3O4@MIL-101-OH/Chitosan for adsorption and release of doxorubicin
Get PDFThis study reports the synthesis and characterization of a magnetic composite metal-organic framework, The Fe3O4@MIL-101-OH/Chitosan nanocomposite was used for the first time to adsorb and release the drug doxorubicin (DOX). The nanocomposite was characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), Brunauer-Emmett-Teller (BET), X-ray diffraction (XRD), and vibrating sample magnetometry (VSM). The characterization results showed that the synthesized nanocomposite has a crystalline structure and good magnetic properties. Also, this nanocomposite has a high specific surface area (610.36 m2/g). In this article, the effect of pH, contact time, and drug concentration on DOX adsorption were investigated, and the results showed that at optimal conditions, pH = 8, contact time = 90 min, and drug concentration is 350 ppm, the adsorption capacity of MIL-101-OH/Chitosan and Fe3O4@MIL-101-OH/Chitosan are equal to 185 and 174.3 mg/g. The adsorption data follows pseudo-second-order kinetic and Langmuir isotherm models. The adsorption was physical and reversible. As a result, drug release was checked. The Fe3O4@MIL-101-OH/Chitosan exhibited a controlled release over the period of 84 h at pH 5 and reached 80 % of the DOX release rate after 60 h. In conclusion, the Fe3O4@MIL-101-OH/Chitosan composite has great potential as a drug delivery system as a result of its high adsorption capacity and magnetic properties. This research provides a promising approach for the development of novel drug delivery systems for cancer therapy
Stochastic Open Pit Optimization Under Volume and Grade Uncertainty: An Application to African Copper Mine
No full textScheduling production for an open pit mining operation is essential to determine the returns on investment. Several methods for production scheduling have been proposed for the deterministic and stochastic version where grade uncertainty is accounted, assuming the shape of the orebody is known. However, the major risk of not meeting the ore and metal targets is coming from the shape of the orebody model. The poor representation of the orebody shape either over-or underestimates the volume and grade, leading to an inaccurate mine plan. In this study, we have accounted for the volume and grade uncertainty during production scheduling for a copper deposit from Africa. In addition, a comparative study is performed for the deterministic version, the stochastic version with grade uncertainty, and stochastic version with volume and grade uncertainty. The results demonstrated that the incorporation of both the volume and grade uncertainty significantly reduces the risk of deviation from the target. The results also show that incorporation of volume and grade uncertainty increases the net present value of the case study mining project as compared to the mine plan generated from the deterministic model and the stochastic model with only grade uncertainty. The results show that the production schedule generates high revenue over a wide range of initial assumptions and the expected NPV is 3% higher than the deterministic version. A sensitivity analysis was also performed to understand the effect of penalty factor for deviating the constraints