First confirmed occurrence of Codium fragile (Suringar) Hariot in the Iberian Peninsula coast of Portugal

Invasive macroalgae represent a major threat to marine ecosystems worldwide. Codium fragile ssp. fragile is one of the most invasive species in the world. The species has deleterious impacts on marine ecosystems, but can also coexist with other Codium congeners, with neutral impact. Several invasive macroalgae have been described to occur along the west coast of the Iberian Peninsula, including C. fragile. However, despite its presence being noted in citizen science surveys, the occurrence of C. fragile on the coast of Portugal was not confirmed (except in the Azores Islands). The cryptic nature of this invasive macroalga has led to several misidentifications, and strict taxonomic approaches must therefore be used to confirm sightings. Previous intensive field sampling (2017–2018) aimed at recording the presence of different macroalgae did not find C. fragile along the Portuguese coast, northwards from Praia do Matadouro. Here, we report the first confirmed record of C. fragile on the coast of Portugal, in the Avencas Marine Park. Identification of the alga was confirmed by microscopic examination of the utricles. Early detection of invasive species is essential, and further research should be carried out in the surrounding areas in order to better understand the invasion pathways to enable correct application of management plans

Physical and psychological consequences of serious road traffic injuries, deliverable 7.2 of the H2020 project SafetyCube

SafetyCube aims to develop an innovative road safety Decision Support System (DSS) that will enable policy-makers and stakeholders to select the most appropriate strategies, measures and cost-effective approaches to reduce casualties of all road user types and all severities. Work Package 7 of SafetyCube is dedicated to serious road traffic injuries, their health impacts and their costs. This Deliverable discusses health impacts of (serious) road traffic injuries

Astrocytes are important mediators of Aβ-induced neurotoxicity and tau phosphorylation in primary culture

Alzheimer's disease (AD) is pathologically characterised by the age-dependent deposition of β-amyloid (Aβ) in senile plaques, intraneuronal accumulation of tau as neurofibrillary tangles, synaptic dysfunction and neuronal death. Neuroinflammation, typified by the accumulation of activated microglia and reactive astrocytes, is believed to modulate the development and/or progression of AD. We have used primary rat neuronal, astrocytic and mixed cortical cultures to investigate the contribution of astrocyte-mediated inflammatory responses during Aβ-induced neuronal loss. We report that the presence of small numbers of astrocytes exacerbate Aβ-induced neuronal death, caspase-3 activation and the production of caspase-3-cleaved tau. Furthermore, we show that astrocytes are essential for the Aβ-induced tau phosphorylation observed in primary neurons. The release of soluble inflammatory factor(s) from astrocytes accompanies these events, and inhibition of astrocyte activation with the anti-inflammatory agent, minocycline, reduces astrocytic inflammatory responses and the associated neuronal loss. Aβ-induced increases in caspase-3 activation and the production of caspase-3-truncated tau species in neurons were reduced when the astrocytic response was attenuated with minocycline. Taken together, these results show that astrocytes are important mediators of the neurotoxic events downstream of elevated Aβ in models of AD, and suggest that mechanisms underlying pro-inflammatory cytokine release might be an important target for therapy

Estimation of forest structure and canopy fuel parameters from small-footprint full-waveform LiDAR data

Precise knowledge of fuel conditions is important for predicting fire hazards and simulating fire growth and intensity across the landscape. We present a methodology to retrieve and map forest canopy fuel and other forest structural parameters using small-footprint full-waveform airborne light detection and ranging (LiDAR) data. Full-waveform LiDAR sensors register the complete returned backscattered signal through time and can describe physical properties of the intercepted objects. This study was undertaken in a mixed forest dominated by Douglas-fir, occasionally mixed with other conifers, in north-west Oregon (United States). We extracted two sets of LiDAR metrics using pulse detection and waveform modelling and then constructed several predictive models using forward stepwise multiple linear regression. The resulting models explained ~80% of the variability for many of the canopy fuel and forest structure parameters: aboveground biomass (R2 = 0.84), quadratic mean diameter (R2 = 0.82), canopy height (R2 = 0.79), canopy base height (R2 = 0.78) and canopy fuel load (R2 = 0.79). The lowest performing models included basal area (R2 = 0.76), stand volume (R2 = 0.73), canopy bulk density (R2 = 0.67) and stand density index (R2 = 0.66). Our results indicate that full-waveform LiDAR systems show promise in systematically characterising the structure and canopy fuel loads of forests, which may enable accurate fire behaviour forecasting that in turn supports the development of prevention and planning policies.This paper was developed as a result of two mobility grants funded by the Erasmus Mundus Programme of the European Commission under the Transatlantic Partnership for Excellence in Engineering (TEE Project) and the Generalitat Valenciana (BEST/2012/235). The authors appreciate the financial support provided by the Spanish Ministry of Science and Innovation in the framework of the project CGL2010-19591/BTE. In addition, the authors thank the Panther Creek Remote Sensing and Research cooperative program for the data provided for this research, Jim Flewelling (Seattle Biometrics) and George McFadden (Bureau of Land Management) for their help in data availability and preparation.Hermosilla Gómez, T.; Ruiz Fernández, LÁ.; Kazakova, AN.; Coops, N.; Moskal, LM. (2014). Estimation of forest structure and canopy fuel parameters from small-footprint full-waveform LiDAR data. International Journal of Wildland Fire. 23(2):224-233. https://doi.org/10.1071/WF13086S224233232Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716-723. doi:10.1109/tac.1974.1100705Andersen, H.-E., McGaughey, R. J., & Reutebuch, S. E. (2005). Estimating forest canopy fuel parameters using LIDAR data. Remote Sensing of Environment, 94(4), 441-449. doi:10.1016/j.rse.2004.10.013Arroyo, L. A., Pascual, C., & Manzanera, J. A. (2008). Fire models and methods to map fuel types: The role of remote sensing. Forest Ecology and Management, 256(6), 1239-1252. doi:10.1016/j.foreco.2008.06.048Ashworth, A., Evans, D. L., Cooke, W. H., Londo, A., Collins, C., & Neuenschwander, A. (2010). Predicting Southeastern Forest Canopy Heights and Fire Fuel Models using GLAS Data. Photogrammetric Engineering & Remote Sensing, 76(8), 915-922. doi:10.14358/pers.76.8.915Buddenbaum, H., Seeling, S., & Hill, J. (2013). Fusion of full-waveform lidar and imaging spectroscopy remote sensing data for the characterization of forest stands. International Journal of Remote Sensing, 34(13), 4511-4524. doi:10.1080/01431161.2013.776721Chuvieco, E., & Congalton, R. G. (1989). Application of remote sensing and geographic information systems to forest fire hazard mapping. 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Assessing canopy fuel stratum characteristics in crown fire prone fuel types of western North America. International Journal of Wildland Fire, 12(1), 39. doi:10.1071/wf02024Drake, J. B., Dubayah, R. O., Clark, D. B., Knox, R. G., Blair, J. B., Hofton, M. A., … Prince, S. (2002). Estimation of tropical forest structural characteristics using large-footprint lidar. Remote Sensing of Environment, 79(2-3), 305-319. doi:10.1016/s0034-4257(01)00281-4Erdody, T. L., & Moskal, L. M. (2010). Fusion of LiDAR and imagery for estimating forest canopy fuels. Remote Sensing of Environment, 114(4), 725-737. doi:10.1016/j.rse.2009.11.002Falkowski, M. J., Gessler, P. E., Morgan, P., Hudak, A. T., & Smith, A. M. S. (2005). Characterizing and mapping forest fire fuels using ASTER imagery and gradient modeling. Forest Ecology and Management, 217(2-3), 129-146. doi:10.1016/j.foreco.2005.06.013Flannigan, M. ., Stocks, B. ., & Wotton, B. . (2000). Climate change and forest fires. Science of The Total Environment, 262(3), 221-229. doi:10.1016/s0048-9697(00)00524-6García, M., Popescu, S., Riaño, D., Zhao, K., Neuenschwander, A., Agca, M., & Chuvieco, E. (2012). Characterization of canopy fuels using ICESat/GLAS data. Remote Sensing of Environment, 123, 81-89. doi:10.1016/j.rse.2012.03.018González-Olabarria, J.-R., Rodríguez, F., Fernández-Landa, A., & Mola-Yudego, B. (2012). Mapping fire risk in the Model Forest of Urbión (Spain) based on airborne LiDAR measurements. Forest Ecology and Management, 282, 149-156. doi:10.1016/j.foreco.2012.06.056Hall, S. A., Burke, I. C., Box, D. O., Kaufmann, M. R., & Stoker, J. M. (2005). Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests. Forest Ecology and Management, 208(1-3), 189-209. doi:10.1016/j.foreco.2004.12.001Harding, D. J. (2005). ICESat waveform measurements of within-footprint topographic relief and vegetation vertical structure. Geophysical Research Letters, 32(21). doi:10.1029/2005gl023471Heinzel, J., & Koch, B. (2011). Exploring full-waveform LiDAR parameters for tree species classification. International Journal of Applied Earth Observation and Geoinformation, 13(1), 152-160. doi:10.1016/j.jag.2010.09.010Höfle, B., Hollaus, M., & Hagenauer, J. (2012). Urban vegetation detection using radiometrically calibrated small-footprint full-waveform airborne LiDAR data. ISPRS Journal of Photogrammetry and Remote Sensing, 67, 134-147. doi:10.1016/j.isprsjprs.2011.12.003HYDE, P., DUBAYAH, R., PETERSON, B., BLAIR, J., HOFTON, M., HUNSAKER, C., … WALKER, W. (2005). Mapping forest structure for wildlife habitat analysis using waveform lidar: Validation of montane ecosystems. Remote Sensing of Environment, 96(3-4), 427-437. doi:10.1016/j.rse.2005.03.005Keane, R. E., Burgan, R., & van Wagtendonk, J. (2001). Mapping wildland fuels for fire management across multiple scales: Integrating remote sensing, GIS, and biophysical modeling. International Journal of Wildland Fire, 10(4), 301. doi:10.1071/wf01028Kim, Y., Yang, Z., Cohen, W. B., Pflugmacher, D., Lauver, C. L., & Vankat, J. L. (2009). Distinguishing between live and dead standing tree biomass on the North Rim of Grand Canyon National Park, USA using small-footprint lidar data. Remote Sensing of Environment, 113(11), 2499-2510. doi:10.1016/j.rse.2009.07.010Koetz, B., Morsdorf, F., Sun, G., Ranson, K. J., Itten, K., & Allgower, B. (2006). Inversion of a Lidar Waveform Model for Forest Biophysical Parameter Estimation. IEEE Geoscience and Remote Sensing Letters, 3(1), 49-53. doi:10.1109/lgrs.2005.856706Lefsky, M. A., Cohen, W. B., Acker, S. A., Parker, G. G., Spies, T. A., & Harding, D. (1999). Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests. Remote Sensing of Environment, 70(3), 339-361. doi:10.1016/s0034-4257(99)00052-8Listopad, C. M. C. S., Drake, J. B., Masters, R. E., & Weishampel, J. F. (2011). Portable and Airborne Small Footprint LiDAR: Forest Canopy Structure Estimation of Fire Managed Plots. Remote Sensing, 3(7), 1284-1307. doi:10.3390/rs3071284Mallet, C., & Bretar, F. (2009). Full-waveform topographic lidar: State-of-the-art. ISPRS Journal of Photogrammetry and Remote Sensing, 64(1), 1-16. doi:10.1016/j.isprsjprs.2008.09.007Morsdorf, F., Meier, E., Kötz, B., Itten, K. I., Dobbertin, M., & Allgöwer, B. (2004). LIDAR-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildland fire management. Remote Sensing of Environment, 92(3), 353-362. doi:10.1016/j.rse.2004.05.013Neuenschwander, A. L. (2009). Landcover classification of small-footprint, full-waveform lidar data. Journal of Applied Remote Sensing, 3(1), 033544. doi:10.1117/1.3229944Reich, R. M., Lundquist, J. E., & Bravo, V. A. (2004). Spatial models for estimating fuel loads in the Black Hills, South Dakota, USA. International Journal of Wildland Fire, 13(1), 119. doi:10.1071/wf02049Reitberger, J., Krzystek, P., & Stilla, U. (2008). Analysis of full waveform LIDAR data for the classification of deciduous and coniferous trees. International Journal of Remote Sensing, 29(5), 1407-1431. doi:10.1080/01431160701736448Riaño, D., Chuvieco, E., Salas, J., Palacios-Orueta, A., & Bastarrika, A. (2002). Generation of fuel type maps from Landsat TM images and ancillary data in Mediterranean ecosystems. Canadian Journal of Forest Research, 32(8), 1301-1315. doi:10.1139/x02-052Riaño, D. (2003). Modeling airborne laser scanning data for the spatial generation of critical forest parameters in fire behavior modeling. Remote Sensing of Environment, 86(2), 177-186. doi:10.1016/s0034-4257(03)00098-1Riaño, D., Chuvieco, E., Condés, S., González-Matesanz, J., & Ustin, S. L. (2004). Generation of crown bulk density for Pinus sylvestris L. from lidar. Remote Sensing of Environment, 92(3), 345-352. doi:10.1016/j.rse.2003.12.014Riaño, D., Chuvieco, E., Ustin, S. L., Salas, J., Rodríguez-Pérez, J. R., Ribeiro, L. M., … Fernández, H. (2007). Estimation of shrub height for fuel-type mapping combining airborne LiDAR and simultaneous color infrared ortho imaging. International Journal of Wildland Fire, 16(3), 341. doi:10.1071/wf06003SKOWRONSKI, N., CLARK, K., NELSON, R., HOM, J., & PATTERSON, M. (2007). Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey. Remote Sensing of Environment, 108(2), 123-129. doi:10.1016/j.rse.2006.09.032Skowronski, N. S., Clark, K. L., Duveneck, M., & Hom, J. (2011). Three-dimensional canopy fuel loading predicted using upward and downward sensing LiDAR systems. Remote Sensing of Environment, 115(2), 703-714. doi:10.1016/j.rse.2010.10.012Van Leeuwen, M., & Nieuwenhuis, M. (2010). Retrieval of forest structural parameters using LiDAR remote sensing. European Journal of Forest Research, 129(4), 749-770. doi:10.1007/s10342-010-0381-4Vaughn, N. R., Moskal, L. M., & Turnblom, E. C. (2012). Tree Species Detection Accuracies Using Discrete Point Lidar and Airborne Waveform Lidar. Remote Sensing, 4(2), 377-403. doi:10.3390/rs4020377Wagner, W., Hollaus, M., Briese, C., & Ducic, V. (2008). 3D vegetation mapping using small‐footprint full‐waveform airborne laser scanners. International Journal of Remote Sensing, 29(5), 1433-1452. doi:10.1080/01431160701736398Wilson, B. A., Ow, C. F. Y., Heathcott, M., Milne, D., McCaffrey, T. M., Ghitter, G., & Franklin, S. E. (1994). Landsat MSS Classification of Fire Fuel Types in Wood Buffalo National Park, Northern Canada. Global Ecology and Biogeography Letters, 4(2), 33. doi:10.2307/2997751Zhao, K., Popescu, S., Meng, X., Pang, Y., & Agca, M. (2011). Characterizing forest canopy structure with lidar composite metrics and machine learning. Remote Sensing of Environment, 115(8), 1978-1996. doi:10.1016/j.rse.2011.04.00

Neurological diseases as primary gliopathies: a reassessment of neurocentrism

Diseases of the human brain are almost universally attributed to malfunction or loss of nerve cells. However, a considerable amount of work has, during the last decade, expanded our view on the role of astrocytes in CNS (central nervous system), and this analysis suggests that astrocytes contribute to both initiation and propagation of many (if not all) neurological diseases. Astrocytes provide metabolic and trophic support to neurons and oligodendrocytes. Here, we shall endeavour a broad overviewing of the progress in the field and forward the idea that loss of homoeostatic astroglial function leads to an acute loss of neurons in the setting of acute insults such as ischaemia, whereas more subtle dysfunction of astrocytes over periods of months to years contributes to epilepsy and to progressive loss of neurons in neurodegenerative diseases. The majority of therapeutic drugs currently in clinical use target neuronal receptors, channels or transporters. Future therapeutic efforts may benefit by a stronger focus on the supportive homoeostatic functions of astrocytes

Predicting understory maximum shrubs cover using altitude and overstory basal area in different Mediterranean forests

In some areas of the Mediterranean basin where the understory stratum represents a critical fire hazard, managing the canopy cover to control the understory shrubby vegetation is an ecological alternative to the current mechanical management techniques. In this study, we determine the relationship between the overstory basal area and the cover of the understory shrubby vegetation for different dominant canopy species (Pinaceae and Fagaceae species) along a wide altitudinal gradient in the province of Catalonia (Spain). Analyses were conducted using data from the Spanish National Forest Inventory. At the regional scale, when all stands are analysed together, a strong negative relationship between mean shrub cover and site elevation was found. Among the Pinaceae species, we found fairly good relationships between stand basal area and the maximum development of the shrub stratum for species located at intermediate elevations (Pinus nigra, Pinus sylvestris). However, at the extremes of the elevationclimatic gradient (Pinus halepensis and Pinus uncinata stands), stand basal area explained very little of the shrub cover variation probably because microsite and topographic factors override its effect. Among the Fagaceae species, a negative relationship between basal area and the maximum development of the shrub stratum was found in Quercus humilis and Fagus sylvatica dominated stands but not in Quercus ilex. This can be due to the particular canopy structure and management history of Q. ilex stands. In conclusion, our study revealed a marked effect of the tree layer composition and the environment on the relationship between the development of the understory and overstory tree structure. More fine-grained studies are needed to provide forest managers with more detailed information about the relationship between these two forest strata

Size-Frequency Distributions along a Latitudinal Gradient in Middle Permian Fusulinoideans

Geographic gradients in body size within and among living species are commonly used to identify controls on the long-term evolution of organism size. However, the persistence of these gradients over evolutionary time remains largely unknown because ancient biogeographic variation in organism size is poorly documented. Middle Permian fusulinoidean foraminifera are ideal for investigating the temporal persistence of geographic gradients in organism size because they were diverse and abundant along a broad range of paleo-latitudes during this interval (∼275–260 million years ago). In this study, we determined the sizes of Middle Permian fusulinoidean fossils from three different paleo-latitudinal zones in order to examine the relationship between the size of foraminifers and regional environment. We recovered the following results: keriothecal fusulinoideans are substantially larger than nonkeriothecal fusulinoideans; fusulinoideans from the equatorial zone are typically larger than those from the north and south transitional zones; neoschwagerinid specimens within a single species are generally larger in the equatorial zone than those in both transitional zones; and the nonkeriothecal fusulinoideans Staffellidae and Schubertellidae have smaller size in the north transitional zone. Fusulinoidean foraminifers differ from most other marine taxa in exhibiting larger sizes closer to the equator, contrary to Bergmann's rule. Meridional variation in seasonality, water temperature, nutrient availability, and carbonate saturation level are all likely to have favored or enabled larger sizes in equatorial regions. Temporal variation in atmospheric oxygen concentrations have been shown to account for temporal variation in fusulinoidean size during Carboniferous and Permian time, but oxygen availability appears unlikely to explain biogeographic variation in fusulinoidean sizes, because dissolved oxygen concentrations in seawater typically increase away from the equator due to declining seawater temperatures. Consequently, our findings highlight the fact that spatial gradients in organism size are not always controlled by the same factors that govern temporal trends within the same clade

Insulin and IGF1 signalling pathways in human astrocytes <i>in vitro</i> and <i>in vivo</i>; characterisation, subcellular localisation and modulation of the receptors.

Background The insulin/IGF1 signalling (IIS) pathways are involved in longevity regulation and are dysregulated in neurons in Alzheimer’s disease (AD). We previously showed downregulation in IIS gene expression in astrocytes with AD-neuropathology progression, but IIS in astrocytes remains poorly understood. We therefore examined the IIS pathway in human astrocytes and developed models to reduce IIS at the level of the insulin or the IGF1 receptor (IGF1R). Results We determined IIS was present and functional in human astrocytes by immunoblotting and showed astrocytes express the insulin receptor (IR)-B isoform of Ir. Immunocytochemistry and cell fractionation followed by western blotting revealed the phosphorylation status of insulin receptor substrate (IRS1) affects its subcellular localisation. To validate IRS1 expression patterns observed in culture, expression of key pathway components was assessed on post-mortem AD and control tissue using immunohistochemistry. Insulin signalling was impaired in cultured astrocytes by treatment with insulin + fructose and resulted in decreased IR and Akt phosphorylation (pAkt S473). A monoclonal antibody against IGF1R (MAB391) induced degradation of IGF1R receptor with an associated decrease in downstream pAkt S473. Neither treatment affected cell growth or viability as measured by MTT and Cyquant® assays or GFAP immunoreactivity. Discussion IIS is functional in astrocytes. IR-B is expressed in astrocytes which differs from the pattern in neurons, and may be important in differential susceptibility of astrocytes and neurons to insulin resistance. The variable presence of IRS1 in the nucleus, dependent on phosphorylation pattern, suggests the function of signalling molecules is not confined to cytoplasmic cascades. Down-regulation of IR and IGF1R, achieved by insulin + fructose and monoclonal antibody treatments, results in decreased downstream signalling, though the lack of effect on viability suggests that astrocytes can compensate for changes in single pathways. Changes in signalling in astrocytes, as well as in neurons, may be important in ageing and neurodegeneration