Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA

Quantifying forest structure is important for sustainable forest management, as it relates to a wide variety of ecosystem processes and services. Lidar data have proven particularly useful for measuring or estimating a suite of forest structural attributes such as canopy height, basal area, and LAI. However, the potential of this technology to characterize forest succession remains largely untested. The objective of this study was to evaluate the use of lidar data for characterizing forest successional stages across a structurally diverse, mixed-species forest in Northern Idaho. We used a variety of lidar-derived metrics in conjunction with an algorithmic modeling procedure (Random Forests) to classify six stages of three-dimensional forest development and achieved an overall accuracy \u3e95%. The algorithmic model presented herein developed ecologically meaningful classifications based upon lidar metrics quantifying mean vegetation height and canopy cover, among others. This study highlights the utility of lidar data for accurately classifying forest succession in complex, mixed coniferous forests; but further research should be conducted to classify forest successional stages across different forests types. The techniques presented herein can be easily applied to other areas. Furthermore, the final classification map represents a significant advancement for forest succession modeling and wildlife habitat assessment

The role of pH on the thermodynamics and kinetics of muscle biochemistry: An in vivo study by 31P-MRS in patients with myo-phosphorylase deficiency

AbstractIn this study we assessed ΔG′ATP hydrolysis, cytosolic [ADP], and the rate of phosphocreatine recovery using Phosphorus Magnetic Resonance Spectroscopy in the calf muscle of a group of patients affected by glycogen myo-phosphorylase deficiency (McArdle disease). The goal was to ascertain whether and to what extent the deficit of the glycogenolytic pathway would affect the muscle energy balance. A typical feature of this pathology is the lack of intracellular acidosis. Therefore we posed the question of whether, in the absence of pH decrease, the rate of phosphocreatine recovery depends on the amount of phosphocreatine consumed during exercise. Results showed that at the end of exercise both [ADP] and ΔG′ATP of patients were significantly higher than those of matched control groups reaching comparable levels of phosphocreatine concentration. Furthermore, in these patients we found that the rate of phosphocreatine recovery is not influenced by the amount of phosphocreatine consumed during exercise. These outcomes provide experimental evidence that: i) the intracellular acidification occurring in exercising skeletal muscle is a protective factor for the energy consumption; and ii) the influence of pH on the phosphocreatine recovery rate is at least in part related to the kinetic mechanisms of mitochondrial creatine kinase enzyme

Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA

Quantifying forest structure is important for sustainable forest management, as it relates to a wide variety of ecosystem processes and services. Lidar data have proven particularly useful for measuring or estimating a suite of forest structural attributes such as canopy height, basal area, and LAI. However, the potential of this technology to characterize forest succession remains largely untested. The objective of this study was to evaluate the use of lidar data for characterizing forest successional stages across a structurally diverse, mixed-species forest in Northern Idaho. We used a variety of lidar-derived metrics in conjunction with an algorithmic modeling procedure (Random Forests) to classify six stages of three-dimensional forest development and achieved an overall accuracy \u3e95%. The algorithmic model presented herein developed ecologically meaningful classifications based upon lidar metrics quantifying mean vegetation height and canopy cover, among others. This study highlights the utility of lidar data for accurately classifying forest succession in complex, mixed coniferous forests; but further research should be conducted to classify forest successional stages across different forests types. The techniques presented herein can be easily applied to other areas. Furthermore, the final classification map represents a significant advancement for forest succession modeling and wildlife habitat assessment

Children in Vegetative State and Minimally Conscious State: Patients' Condition and Caregivers' Burden

Caring for children in vegetative state (VS) or minimally conscious state (MCS) challenges parents and impacts on their well-being. This study aims to evaluate caregivers' health condition, coping, anxiety and depression levels, and how these issues relate to children's disability. 35 children with VS and MCS were administered the disability rating scale (DRS) and 35 caregivers completed the Coping Orientations to Problem Experiences, Short Form-12, Beck Depression Inventory, and the Spielberger State-Trait Anxiety Inventory-Y. Children were mainly males (68.6%), hosted at domicile (77.1%), and diagnosed with VS (60%), with anoxic aetiology (45.7%). Caregivers were mainly mothers (85.7%), married (82.9%), and housewives (51.4%); 60% declared financial difficulties, and 82.9% provided full-time assistance. 57.2% reported depressive symptoms, poor mental health, and high level of state and trait anxiety. “Problem-oriented” (P < 0.001) and “emotional-oriented” (P < 0.001), were more adopted than “potentially dysfunctional” ones. DRS scores (mean = 22.0; SD = 1.9) did not significantly correlate to any psychological measure. Rehabilitative programs for children with SV and SMC should also provide interventions on surrounding systems: improving the network of psychological support and social assistance may decrease the burden of caregivers and, in turn, improve caring abilities and children quality of life

Current And Future Land Use Around A Nationwide Protected Area Network

Land-use change around protected areas can reduce their effective size and limit their ability to conserve biodiversity because land-use change alters ecological processes and the ability of organisms to move freely among protected areas. The goal of our analysis was to inform conservation planning efforts for a nationwide network of protected lands by predicting future land use change. We evaluated the relative effect of three economic policy scenarios on land use surrounding the U.S. Fish and Wildlife Service\u27s National Wildlife Refuges. We predicted changes for three land-use classes (forest/range, crop/pasture, and urban) by 2051. Our results showed an increase in forest/range lands (by 1.9% to 4.7% depending on the scenario), a decrease in crop/pasture between 15.2% and 23.1%, and a substantial increase in urban land use between 28.5% and 57.0%. The magnitude of land-use change differed strongly among different USFWS administrative regions, with the most change in the Upper Midwestern US (approximately 30%), and the Southeastern and Northeastern US (25%), and the rest of the U.S. between 15 and 20%. Among our scenarios, changes in land use were similar, with the exception of our restricted-urban-growth\u27\u27 scenario, which resulted in noticeably different rates of change. This demonstrates that it will likely be difficult to influence land-use change patterns with national policies and that understanding regional land-use dynamics is critical for effective management and planning of protected lands throughout the U.S

Economic-based projections of future land use in the conterminous United States under alternative policy scenarios

Land-use change significantly contributes to biodiversity loss, invasive species spread, changes in biogeochemical cycles, and the loss of ecosystem services. Planning for a sustainable future requires a thorough understanding of expected land use at the fine spatial scales relevant for modeling many ecological processes and at dimensions appropriate for regional or national-level policy making. Our goal was to construct and parameterize an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous United States under several alternative land-use policy scenarios. We parameterized the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points. Land-use transitions were estimated for five land-use classes (cropland, pasture, range, forest, and urban). We predicted land-use change under four scenarios: business-as-usual, afforestation, removal of agricultural subsidies, and increased urban rents. Our results for the business-as-usual scenario showed widespread changes in land use, affecting 36% of the land area of the conterminous United States, with large increases in urban land (79%) and forest (7%), and declines in cropland (\-16%) and pasture (\-13%). Areas with particularly high rates of land-use change included the larger Chicago area, parts of the Pacific Northwest, and the Central Valley of California. However, while land-use change was substantial, differences in results among the four scenarios were relatively minor. The only scenario that was markedly different was the afforestation scenario, which resulted in an increase of forest area that was twice as high as the business-as-usual scenario. Land-use policies can affect trends, but only so much. The basic economic and demographic factors shaping land-use changes in the United States are powerful, and even fairly dramatic policy changes, showed only moderate deviations from the business-as-usual scenario. Given the magnitude of predicted land-use change, any attempts to identify a sustainable future or to predict the effects of climate change will have to take likely land-use changes into account. Econometric models that can simulate land-use change for broad areas with fine resolution are necessary to predict trends in ecosystem service provision and biodiversity persistence. © 2012 by the Ecological Society of America

Economic-based Projections Of Future Land Use In The Conterminous United States Under Alternative Policy Scenarios

The article presents a study which constructs and parameterizes an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous U.S. under several alternative land-use policy scenarios. It parameterizes the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points

Long-Lasting Immune Responses 4 Years after GAD-Alum Treatment in Children with Type 1 Diabetes

A phase II clinical trial with glutamic acid decarboxylase (GAD) 65 formulated with aluminium hydroxide (GAD-alum) has shown efficacy in preserving residual insulin secretion in children and adolescents with recent-onset type 1 diabetes (T1D). We have performed a 4-year follow-up study of 59 of the original 70 patients to investigate long-term cellular and humoral immune responses after GAD-alum-treatment. Peripheral blood mononuclear cells (PBMC) were stimulated in vitro with GAD65. Frequencies of naïve, central and effector memory CD4+ and CD8+ T cells were measured, together with cytokine secretion, proliferation, gene expression and serum GAD65 autoantibody (GADA) levels. We here show that GAD-alum-treated patients display increased memory T-cell frequencies and prompt T-cell activation upon in vitro stimulation with GAD65, but not with control antigens, compared with placebo subjects. GAD65-induced T-cell activation was accompanied by secretion of T helper (Th) 1, Th2 and T regulatory cytokines and by induction of T-cell inhibitory pathways. Moreover, post-treatment serum GADA titres remained persistently increased in the GAD-alum arm, but did not inhibit GAD65 enzymatic activity. In conclusion, memory T- and B-cell responses persist 4 years after GAD-alum-treatment. In parallel to a GAD65-induced T-cell activation, our results show induction of T-cell inhibitory pathways important for regulating the GAD65 immunity

Unexpected detection of SARS-CoV-2 antibodies in the prepandemic period in Italy

There are no robust data on the real onset of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and spread in the prepandemic period worldwide. We investigated the presence of SARS-CoV-2 receptor-binding domain (RBD)–specific antibodies in blood samples of 959 asymptomatic individuals enrolled in a prospective lung cancer screening trial between September 2019 and March 2020 to track the date of onset, frequency, and temporal and geographic variations across the Italian regions. SARS-CoV-2 RBD-specific antibodies were detected in 111 of 959 (11.6%) individuals, starting from September 2019 (14%), with a cluster of positive cases (&gt;30%) in the second week of February 2020 and the highest number (53.2%) in Lombardy. This study shows an unexpected very early circulation of SARS-CoV-2 among asymptomatic individuals in Italy several months before the first patient was identified, and clarifies the onset and spread of the coronavirus disease 2019 (COVID-19) pandemic. Finding SARS-CoV-2 antibodies in asymptomatic people before the COVID-19 outbreak in Italy may reshape the history of pandemic

元代散曲と険韻としての「車遮韻」

Visualization of fluid flows at a high-Reynolds number (Re similar to 10(5)) presents difficulties for user comprehension due to density and ambiguous interactions between vortices. Prior work has used cluster-based reduced-order modelling (CROM) to analyze the wake of a High-Speed Train (HST) with Re = 86,000. In this paper, we present a novel surface visualization to convey the spatiotemporal changes undergone by clustered vortices in the HST wake. This visualization is accomplished through dimensional reduction of 3D volumetric vortices into 1D ridges, and physics-based feature tracking. The result is 3D surfaces visualizing the behavior of the vortices in the HST wake. Compared to conventional still-image representations, these surfaces allow the user to quickly compare and analyze the two shedding cycles identified via CROM. The spatiotemporal differences of the primary vortices in these shedding cycles provide analytic insight to influence the aerodynamics of the HST