Chronic Shoulder Pain in Manual Wheelchair (MWC) Users with Spinal Cord Injury (SCI): The Lived Experience

Background: Existing research on the lived experience of those with spinal cord injury (SCI) resulting in paraplegia who use a manual wheelchair and experience shoulder pain is extremely limited. This research aimed to begin the process of understanding the lived experience of this population and to describe how chronic shoulder pain impacts occupational engagement and quality of life. Method: A phenomenological approach using a constant comparative method was used to analyze data and to construct and redefine themes throughout the research process. The qualitative data obtained from two semi-structured interviews with the four study participants is presented below. Results: Five overarching themes emerged. The themes of putting on the brakes, intrinsic factors, extrinsic factors, hope, and resilience emerged among the participants to describe their lived experience of shoulder pain as a manual wheelchair user with SCI. Conclusion: The themes presented increased the understanding of the lived experience of shoulder pain in this population. Though the experience was unique to each participant, many similarities emerged from the themes, such as the benefit of having a strong support network including others wheelchair users with SCI and demonstrating a resilient spirit

Exploring open-source multispectral satellite remote sensing as a tool to map long-term evolution of salt marsh shorelines

From an ecological and socio-economic perspective, salt marshes are one of the most valuable natural assets on Earth. As external pressures are causing their extensive degradation and loss globally, the ability to monitor salt marshes on a long-term scale and identify drivers of change is essential for their conservation. Remote sensing has been demonstrated to be one of the most adept methods for this purpose and open-source multispectral satellite remote sensing missions have the potential to provide worldwide long-term time-series coverage that is non-cost-prohibitive. This study derives the long-term lateral evolution of four salt marsh patches in the Ria Formosa coastal lagoon (Portugal) using data from the Sentinel-2 and Landsat missions as well as from aerial photography surveys to quantitatively examine the accuracy and associated uncertainty in using open-source multispectral satellite remote sensing for this purpose. The results show that these open-source satellite archives can be a useful tool for tracking long-term salt marsh extent dynamics. During 1976-2020, there was a net loss of salt marsh in the study area, with erosion rates reaching an average of-3.3 m/yr opposite a tidal inlet. The main source of error in the satellite results was the dataset spatial resolution limits, but the specific salt marsh shoreline environment contributed to the relative magnitude of that error. The study notes the influence of eco-geomorphological dynamics on the mapping of sedimentary environments, so far not extensively discussed in scientific literature, highlighting the difference between mapping a morphological process and a sedimentary environment.info:eu-repo/semantics/publishedVersio

Toward coherent space–time mapping of seagrass cover from satellite data: an example of a Mediterranean lagoon

Seagrass meadows are a highly productive and economically important shallow coastal habitat. Their sensitivity to natural and anthropogenic disturbances, combined with their importance for local biodiversity, carbon stocks, and sediment dynamics, motivate a frequent monitoring of their distribution. However, generating time series of seagrass cover from field observations is costly, and mapping methods based on remote sensing require restrictive conditions on seabed visibility, limiting the frequency of observations. In this contribution, we examine the effect of accounting for environmental factors, such as the bathymetry and median grain size (D50) of the substrate as well as the coordinates of known seagrass patches, on the performance of a random forest (RF) classifier used to determine seagrass cover. Using 148 Landsat images of the Venice Lagoon (Italy) between 1999 and 2020, we trained an RF classifier with only spectral features from Landsat images and seagrass surveys from 2002 and 2017. Then, by adding the features above and applying a time-based correction to predictions, we created multiple RF models with different feature combinations. We tested the quality of the resulting seagrass cover predictions from each model against field surveys, showing that bathymetry, D50, and coordinates of known patches exert an influence that is dependent on the training Landsat image and seagrass survey chosen. In models trained on a survey from 2017, where using only spectral features causes predictions to overestimate seagrass surface area, no significant change in model performance was observed. Conversely, in models trained on a survey from 2002, the addition of the out-of-image features and particularly coordinates of known vegetated patches greatly improves the predictive capacity of the model, while still allowing the detection of seagrass beds absent in the reference field survey. Applying a time-based correction eliminates small temporal variations in predictions, improving predictions that performed well before correction. We conclude that accounting for the coordinates of known seagrass patches, together with applying a time-based correction, has the most potential to produce reliable frequent predictions of seagrass cover. While this case study alone is insufficient to explain how geographic location information influences the classification process, we suggest that it is linked to the inherent spatial auto-correlation of seagrass meadow distribution. In the interest of improving remote-sensing classification and particularly to develop our capacity to map vegetation across time, we identify this phenomenon as warranting further research.</p

Characterizing Alpine peatlands from drones: a case study

Alpine peatlands occur in alpine, sub-alpine and mountain regions of the world and can be frequently found on the Alps as well as on the Andes, on the Tibetan Plateau, on the Australian Alps and in other regions of the world. Italian Alps host a large number of relatively small bogs and fens that can be found on gently sloping surfaces or in small valleys created by past glaciers. The high precipitation-low temperature climatic regime ensures large water availability to these ecosystems. The uniqueness and importance of peatlands in the Alpine territory is strongly linked to the countless ecosystem services that they provide, including their ability of sequestering and stocking carbon, providing habitat for flora and fauna including endangered species, supporting important biological diversity, being reservoir of high-quality freshwater during warm and dry seasons, and having the role of paleo-climate archives. Despite their importance, the peatlands of the Alps are still poorly studied and incompletely mapped, probably because they are relatively small and difficult to access. The use of remote sensing techniques provides a possible solution, allowing extending local measurements to wider areas in a fast and cost-effective way. Our hypothesis is that the spatial distribution of different plant associations as well as the spatial variability of vegetation biomass may provide important information for mapping the spatial distribution of peat properties, thus making remote sensing an effective method for peatland studies. In this work, we present the results obtained by using data collected by Unmanned Aerial Vehicles (UAVs) on the Val di Ciampo alpine peatland (Province of Belluno, northeast Italy) in July 2021. LiDAR data, hyperspectral data and aerial digital photos were simultaneously collected on an area of 88.000 m2. Field observations and measurements were performed in the same period, providing georeferenced ground information on vegetation and peat characteristics. Peat and vegetation samples were collected and analyzed in the lab. For each vegetation association we measured the height of plants and determined their above- and below-ground biomass based on 20 above-ground and 15 below-ground samples. As for the peat, we measured the peat thickness and determined the bulk density and the organic carbon content of 46 samples. Our results show that some of the correlations found between the parameters that characterize different vegetation associations can be used to calibrate the data collected by UAVs and extend the results from point locations to the entire peatland. For example, we found that the aboveground biomass is significantly correlated (r = 0.81, p &lt; 0.001) to the local average vegetation height, therefore both LiDAR data and the Digital Surface Model (DSM) extracted from the photos can be used to estimate and map the vegetation aboveground biomass. The correlation between the surface microtopography and the aboveground biomass will also be presented, as well as other correlations between vegetation patterns and peat depth and properties. The significance of combining UAVs multi-sensor data with field observations for the characterization of Alpine peatlands will be discussed

Driving and limiting factors of CH4 and CO2 emissions from coastal brackish-water wetlands in temperate regions

Coastal wetlands play a fundamental role in mitigating climate change thanks to their ability to store large amounts of organic carbon in the soil. However, degraded freshwater wetlands are also known to be the first natural emitter of methane (CH4). Salinity is known to inhibit CH4 production, but its effect in brackish ecosystems is still poorly understood. This study provides a contribution to understanding how environmental variables may affect greenhouse gas (GHG) emissions in coastal temperate wetlands. We present the results of over 1 year of measurements performed in four wetlands located along a salinity gradient on the northeast Adriatic coast near Ravenna, Italy. Soil properties were determined by coring soil samples, while carbon dioxide (CO2) and CH4 fluxes from soils and standing waters were monitored monthly by a portable gas flux meter. Additionally, water levels and surface and groundwater physical–chemical parameters (temperature, pH, electrical conductivity, and sulfate concentrations of water) were monitored monthly by multiparametric probes. We observed a substantial reduction in CH4 emissions when water depth exceeded the critical threshold of 50 cm. Regardless of the water salinity value, the mean CH4 flux was 5.04 g m−2 d−1 in freshwater systems and 12.27  g m−2 d−1 in brackish ones. In contrast, when water depth was shallower than 50 cm, CH4 fluxes reached an average of 196.98  g m−2 d−1 in freshwater systems, while non-significant results are available for brackish/saline waters. Results obtained for CO2 fluxes showed the same behavior described for CH4 fluxes, even though they were statistically non-significant. Temperature and irradiance strongly influenced CH4 emissions from water and soil, resulting in higher rates during summer and spring

Peatland Volume Mapping Over Resistive Substrates With Airborne Electromagnetic Technology

open6siDespite the importance of peatlands as carbon reservoirs, a reliable methodology for the detection of peat volumes at regional scale is still missing. In this study we explore for the first time the use of airborne electromagnetic (AEM) to detect and quantify peat thickness and extension of two bogs located in Norway, where peat lays over resistive bedrock. Our results show that when calibrated using a small amount of field measurements, AEM can successfully detect peat volume even in less ideal conditions, that is, relatively resistive peat over resistive substrata. We expect the performance of AEM to increase significantly in presence of a conductive substratum without need of calibration with field data. The organic carbon content retrieved from field surveys and laboratory analyses combined with the 3-D model of the peat extracted from AEM allowed us to quantify the total organic carbon of the selected bogs, hence assessing the carbon pool.openSilvestri S.; Christensen C.W.; Lysdahl A.O.K.; Anschutz H.; Pfaffhuber A.A.; Viezzoli A.Silvestri S.; Christensen C.W.; Lysdahl A.O.K.; Anschutz H.; Pfaffhuber A.A.; Viezzoli A

Long‐Term Monitoring of Coupled Vegetation and Elevation Changes in Response to Sea Level Rise in a Microtidal Salt Marsh

Tight interplays between physical and biotic processes in tidal salt marshes lead to self-organization of halophytic vegetation into recurrent zonation patterns developed across elevation gradients. Despite its importance for marsh ecomorphodynamics, however, the response of vegetation zonation to changing environmental forcings remains difficult to predict, mostly because of lacking long-term field observations of vegetation evolution in the face of changing rates of sea level rise and marsh vertical accretion. Here we present novel data of coupled marsh elevation-vegetation distribution collected in the microtidal Venice Lagoon (Italy) over nearly two decades. Our results suggest that: (a) despite increasing absolute marsh elevations (i.e., above a fixed datum), vertical accretion rates across most of the studied marsh were not high enough to compensate for relative sea-level rise (RSLR), thus leading to a progressive marsh drowning; (b) accretion rates ranging 1.7–4.3 mm/year are overall lower than the measured RSLR rate (4.4 mm/year) and strongly site-specific. Accretion rates vary largely at sites within distances of a few tens of meters, being controlled by local elevation and sediment availability from eroding marsh edges; (c) vegetation responds species-specifically to changes in environmental forcings by modifying species-preferential elevation ranges. For the first time, we observe the consistency of a sequential vegetation-species zonation with increasing marsh elevations over 20 years. We suggest this is the signature of vegetation resilience to changes in external forcings. Our results highlight a strong coupling between geomorphological and ecological dynamics and call for spatially distributed marsh monitoring and spatially explicit biomorphodynamic models of marsh evolution

Pathogenic alleles in microtubule, secretory granule and extracellular matrix-related genes in familial keratoconus.

Keratoconus is a common corneal defect with a complex genetic basis. By whole exome sequencing of affected members from 11 multiplex families of European ancestry, we identified 23 rare, heterozygous, potentially pathogenic variants in 8 genes. These include nonsynonymous single amino acid substitutions in HSPG2, EML6 and CENPF in two families each, and in NBEAL2, LRP1B, PIK3CG and MRGPRD in three families each; ITGAX had nonsynonymous single amino acid substitutions in two families and an indel with a base substitution producing a nonsense allele in the third family. Only HSPG2, EML6 and CENPF have been associated with ocular phenotypes previously. With the exception of MRGPRD and ITGAX, we detected the transcript and encoded protein of the remaining genes in the cornea and corneal cell cultures. Cultured stromal cells showed cytoplasmic punctate staining of NBEAL2, staining of the fibrillar cytoskeletal network by EML6, while CENPF localized to the basal body of primary cilia. We inhibited the expression of HSPG2, EML6, NBEAL2 and CENPF in stromal cell cultures and assayed for the expression of COL1A1 as a readout of corneal matrix production. An upregulation in COL1A1 after siRNA inhibition indicated their functional link to stromal cell biology. For ITGAX, encoding a leukocyte integrin, we assayed its level in the sera of 3 affected families compared with 10 unrelated controls to detect an increase in all affecteds. Our study identified genes that regulate the cytoskeleton, protein trafficking and secretion, barrier tissue function and response to injury and inflammation, as being relevant to keratoconus

Subsidence due to peatland oxidation in the Venice Lagoon catchment

Abstract. The Venice Lagoon is characterized by a fast morphodynamics appreciable not only over the geological scale but also in historical and modern times. The lagoon environment proves very sensitive to even minor modifications of the natural and anthropogenic controlling factors. An important human endeavor accomplished in the past century is the reclamation of the southernmost lagoon area that has been turned into a fertile farmland. The reclaimed soil is reach in organic matter (peat) that may oxidize with release of carbon dioxide to the atmosphere. The continuous loss of carbon is causing a pronounced settlement of the farmland that lies below the present sea/lagoon level. This enhances the flood hazard and impacts noticeably on the maintenance and operational costs of the drainage system. Total peatland subsidence is estimated at 1.5 m over the last 70 years with a current rate of 1.5-2 cm/year. The geochemical reaction is primarily controlled by soil water content and temperature, and is much influenced by agricultural practices, crop rotation, and depth to the water table. A small (24 km2) controlled catchment located in the area has been instrumented for accurately monitoring the basic parameters and recording the ground motion. The in situ measurements have been integrated with the combined use of remote sensing data to help cast light on the process and identify the mitigation strategies.Published81-906A. Monitoraggio ambientale, sicurezza e territorioope