This paper aims to enhance the reliability of underwater acoustic (UWA) communications by evaluating the effectiveness of various Forward Error Correction (FEC) codes. In the absence of standardized UWA physical layer simulators, we rely on in-situ data to assess the performance of six FEC codes: convolutional, turbo, Low-Density Parity Check (LDPC), Bose– Chaudhuri–Hocquenghem (BCH), Turbo Product Code (TPC), and polar. We examine two common payload sizes: 128-bit packets at a 1/5 encoding rate and 1024-bit packets at a 1/2 rate. Our comparative analysis leverages previously recorded single-carrier Phase-Shift Keying (PSK) signals, originally not intended for FEC evaluation. The signals were transmitted over various underwater links in a High North environment, including areas of sea surface ice floes, northwest of the Svalbard Islands. Using these signals, we formulate an optimal channel replay framework for FEC comparison through constellation dithering for M-ary PSK (M-PSK) modulation. This framework involves a Channel Estimate-Based-Decision Feedback Equalizer (CEB-DFE) with a varying number of input channels (hydrophones) at the receiver end. We focus on the Packet Error Rate (PER), maintaining consistent channel conditions for all codes under consideration. The polar code demonstrates the best performance by achieving the lowest PER for all tested packet lengths and varying number of hydrophones. Moreover, upgrading the equalizer with a turbo feature enables the polar code to achieve up to a 45% further reduction in PER in certain scenarios.

Abstract. In the Mediterranean area, wind-driven wildfires with crown fires are rising, causing an increment in atmospheric pollutant emissions. Quantifying gas emissions in these wildfires requires a better understanding of the components that contribute to the total emission estimate. Here, we aimed to analyze the differences in pre-fire available biomass distribution among layers of fuel types in Pinus halepensis and Quercus suber (hereafter, pine and oak) forests burned in one of the largest wildfires (“La Jonquera”, 10,264 ha) of the past decades. This was done in order to try to unravel the differences in fire severity linked to the percentage of available biomass consumed in each layer and pollutant emissions (CO2, CO, CH4, PM2.5). We used field data (>100 post-fire plots) in which measures from crown, shrub and litter layers, fire severity and consumption assessments were combined with data from National Forest Inventories to quantify final atmospheric pollutant emissions. Total pre-fire available biomass among pine and oak forests showed different vertical distribution. Pine forests had a higher percentage of crown fine and shrub biomass for all fuel types while oak had more litter biomass. The fuel types with large trees and low tree density, together with fuel types with has lower tree density and vertical continuity had the highest non-charred fire severity in pine and oak. The presence of Erica arborea caused higher fire severity in oak stands. Fuel types of pine were more resistant to the effects of surface fires because they had taller trees than oak. Percent biomass consumption was higher in pine and oak stands in low fire severities because the taller trees could withstand surface fire at high intensities without increasing fire severity. The wildfire analyzed was a large fire with massive crown and high-intensity surface fires, but only a small amount of the finest crown biomass and coarse surface fuels were consumed. Fire severity was the main factor determining different amount of emissions without significant influence of fuel types, and only emissions of CO2 and CH4 were higher in pine than in oak in low fire severities. Although remote sensing technologies are extremely useful for biomass and wildfire severity assessments, field data is essential to quantify biomass consumption, atmospheric pollutant emissions from different fuel types and fuel layers.

The Arctic sheet is transitioning from a continuous cover of thick multi-year ice to a fragmented landscape of thin young ice. If the type of acoustic transmission allows repetitive interaction of rays with the sea surface, in the fragmented scenario acoustic rays will undergo a random sequence of reflections from water or sea-ice interfaces. Calm sea conditions in the water channels between the ice floes (leads) and the smooth, flat surface of the young ice bottom reduce scattering due to interface roughness, resulting only in scattering due to inhomogeneity in surface reflectivity. Using an idealized framework, this study investigates the extent to which the mid- to high-frequency underwater acoustic propagation is altered due to repetitive interactions of acoustic signals with a sea surface consisting of a random distribution of ice sheets and leads. An expression for the coherent field (the acoustic field averaged over an ensemble of realizations of sea-ice distributions) was derived from theory. Any deviation from a homogeneous surface condition (either by randomly adding ice slabs in a free ice surface or by including leads in a fully ice-covered sea surface) leads to an excess attenuation of the coherent field. Results are validated by numerical simulations.

Extreme fire severity patterns driven by climate change have deep consequences on vegetation, subsequent fire regimes and have consequences on the effectiveness of extinction. In this work, we aimed to determine if extreme fire severity defined as the 90th percentile of RdNBR has changed in Spain in the last 3 decades, if extreme fire severity patterns have differed among the different vegetation types and what drivers have influenced extreme fire severity in both summer and non-summer fires. We have used perimeters of large wildfires (>= 100 ha, n = 1719) from 1985 to 2018 in four pyroregions and the main dominant vegetation types. We have analyzed time series for each pyroregion and vegetation type to determine if there were significant trends and breakpoints in extreme fire severity. We have also analyzed the effects of drought, weather, topography and vegetation on extreme fire severity in seasonal wildfires. Extreme fire severity increased in summer fires from 1985 to 2018, especially in the East and North pyroregions, while the Southwest pyroregion reached highest values in summer. There has been an increase of severity in shrubland, mosaic vegetation and conifer forests in summer. Broadleaved forests had the lowest values of fire severity and did not show any trend in the period considered. The most important drivers of extreme fire severity are, in order of importance, pyroregion, elevation, slope, vapor pressure deficit (VPD) and vegetation type for summer fires, and VPD, vegetation types, pyroregion, windspeed and drought for non-summer fires. Global change is increasing climate-related events. Our results indicate that extreme fire severity in summer has been on the rise in recent decades in Spain, suggesting that, in a climate warming context, without strategic management of these increasingly flammable landscapes, further increases may be likely.

Abstract. Leads in the sea ice pack have been extensively studied due to their climate relevance. An intense heat exchange between the ocean and the atmosphere occurs at leads in winter. As a result, a major salt input to the Arctic mixed layer is generated at these locations by brine rejection. Leads also constitute preferential melting locations in the early melting season, but their oceanography and climate relevance, if any, still remain unexplored during this period of the year. This study investigates the oceanographic circulation under a melted lead, resulting from the combined effect of the lead geometry, solar radiation and sea ice melting. Results derived from an idealized framework, suggest the daily generation of near surface convection cells that extend from the lead sides to the lead center. Convection cells disappear when melting is diminished during the period of minimum solar insolation. The cyclical generation and evolution of convection cells with the solar cycle, impacts the heat storage rate in the mixed layer below the lead. The contribution of this circulation pattern to the generation of the Near Surface Temperature Maximum (NSTM), is discussed in terms of its capability to inject warm surface waters below the open and sea ice surface. It has been suggested that the NSTM probably affects the oceanographic structure and acoustic properties of the upper ocean and the overlying ice cover.

As the Arctic Ocean becomes increasingly accessible due to the continuous sea-ice retreat during the last decades, UnderWater Acoustic (UWA) communications will play a pivotal role in future underwater Arctic exploration/exploitation activities that will inevitably emerge. In this paper, we aim to improve the reliability of short packet transmission typically needed for low-latency low-packet-loss communications. In particular, we compare the Packet Error Rates (PERs) of convolutional, turbo, Low-Density Parity-Check (LDPC) and polar codes. These four codes are implemented in the physical layer of a software modem, which uses single-carrier, Binary Phase Shift Keying (BPSK) modulation achieving 360 bits/s over the 3830-6170 Hz band. The modem transmitted 128-, 256-, 384-bit long packets over various UWA links north-west off the Svalbard Islands in June 2021. The packets were recorded in a linear hydrophone array and our offline analysis shows that there is an enormous reduction in the PER for all codes as the number of the used hydrophones increases from one to four. In addition, our results confirm the superiority of the polar code for all packet lengths and number of hydrophones.

Disturbances such as wildfires are an integral part of forest ecosystems, but climate change is increasing their extent, frequency, intensity and severity, compromising forest ecosystem services (ES) that are fundamental to human well-being. Thus, evaluating the risk of losing ecosystem services due to wildfires is essential for anticipating and adapting to future conditions. Here, we analyze the spatial patterns of the risk of losing key forest ES and biodiversity (that is, carbon sink, bird richness, hydrological control and erosion control) due to wildfires in Catalonia (NE Spain), taking into account exposed values, hazard magnitude, susceptibility and lack of adaptive capacity. We also determine the effect of climate and different forest functional types on the risk of losing ES under average and extreme hazard conditions (defined as median and 90th percentile values of the Fire Weather Index, respectively), as well as on the increase in risk. Our results show that hazard magnitude is the most important component defining risk under average conditions. Under extreme conditions, exposed values (carbon sink capacity and erosion control) emerged as the most important components of risk. Climate was the main driver of ES at risk under average conditions, but the high vulnerability of non-Mediterranean conifer forests with a low adaptive capacity gained importance under extreme conditions. The increase in risk between average and extreme conditions was driven by precipitation, as the highest increases in risk were found in relatively wet forests with low average risk at present. These results have direct implications on the future risk of losing ES to wildfires in Mediterranean forests but also in other regions, and they could contribute to future policies by anticipating conditions associated with particularly high risk that can be used to guide efficient forest management.

Mediterranean forests are prone to fire and highly diverse in environmental conditions, species composition, and forest structure. While much is known about fire hazard and forest responses to fire in Mediterranean climate regions, our understanding of the spatial distribution of fuel characteristics and their dynamics remains incomplete. We hypothesized that fire hazard in heterogeneous Mediterranean regions is primarily explained by the variation in fuel loading and flammability characteristics of the understory layer across the landscape and over time. We used the Spanish National Forest Inventory data to estimate overstory and understory fuel characteristics, compare their spatial and temporal variations across Catalonia (NE Spain) over the last 25 years, and assess the role of climate conditions in explaining spatial distribution and dynamics of fuel characteristics. Our results showed that fuel characteristics strongly depend on the species composition of the overstory and understory layers. Fuel characteristics of both vegetation layers were significantly different and poorly correlated with each other. Although both strata showed significantly different rates of change in most fuel characteristics, the average changes were, in general, very small for the time window considered. Forests in the warmest and driest environments showed the highest flammability characteristics in both overstory and understory layers in contrast to mountain communities. We did not find, however, a remarkable effect of climatic conditions on the rates of change of fuel characteristics during the study period. Altogether, these findings confirm the importance of considering the spatial variation of fuel characteristics of different vegetation strata separately and provide critical information on forest vulnerability to develop appropriate fire mitigation policies in Mediterranean ecosystems.

Wildfires, drought, insect outbreaks, and windstorms are altering the forest‐associated ecosystem services that are essential for human well‐being, and the impacts of such events are likely to increase under ongoing climate change. However, a widely accepted and operational framework for evaluating forest vulnerability and risk to these disturbances remains lacking. We propose a general framework to assess forest vulnerability and risk based on the widely used concepts of exposure, hazard magnitude, susceptibility, and lack of adaptive capacity as defined by the Intergovernmental Panel on Climate Change. We suggest a standardized procedure for defining and combining these components, as well as a list of indicators readily applicable to the primary hazards to forests associated with climate change. This framework and its methodology constitute a basis for a systematic assessment of forest risk and vulnerability for policy makers, as well as for forest and land managers, that can aid in the development of forward‐looking policies.

Motivated by experimental evidence, a mechanistic model is used to investigate the impact of marine echosounder transmissions on seagrass leaves. The interaction of the ultrasonic field with the seagrass is solved within the leaf cross-section. The leaf tissue is assumed to be elastic, homogeneous and isotropic, with embedded cavities representing lacunae. A standard Galerkin finite element method is employed to numerically solve the resulting equations. Natural vibration frequencies are computed for leaves of Halodule wrightii and Syringodium filiforme. Strong perturbations in the leaf structure are expected when natural and echosounder frequencies match. The results reveal that a significant number of natural frequencies are within or near the typical frequency bands of echosounder operations. In addition, stresses in the leaf tissues of seagrass at 20 m depth were computed in a typical scenario for echosounder operations. Leaf-tissue damage in S. filiforme could result under these conditions. Within the framework of the theoretical assumptions, the results highlight the potential and, until now, unnoticed risks to seagrass meadows posed by marine echosounders.

Context Protected areas (PAs) are essential for biodiversity conservation and the provision of ecosystem services (ES), representing 15% of the earth’s surface and targeted to increase until 17% by 2020. But previous studies showed different results on the effectiveness of PAs in preserving ES and biodiversity, which has implications for landscape conservation. Objectives (1) To know whether the spatial distribution of ES (carbon stocks and water provision), biodiversity (woody and bird richness) and conservation variables (threatened bird richness, habitats and geology) varies between PAs (with different protection status) and buffer zones; and (2) to quantify and compare the percentage of high values (hotspots) of ES, biodiversity and conservation variables inside PAs (with different protection status) and buffer zones. Methods We analyzed 108 PAs from a Mediterranean region using linear mixed models with ES, biodiversity and conservation variables as response factors, and type of zone (PA vs buffer) and protection status as fixed factors. Results We found higher values of carbon stocks in PAs than in buffer zones. We also found more coverage of community-interest habitats, priority-habitats and geological-interest sites in PAs than in buffer zones. However, PAs with higher degree of protection did not provide higher levels of ecosystem services and biodiversity, or vice versa. We found more hotspots of woody richness, bird richness and threatened bird richness in buffer zones than in PAs. Conclusions This study highlights the importance of landscape planning in conservation, which should include PAs within broader landscapes by considering also their buffer zones and non-PAs. It also emphasizes the importance of integrating ES and biodiversity to define effective conservation policies.

Motivated by observational and experimental evidence, a theoretical model is proposed to relate the secondary dispersal of seagrass seeds with the complexity of microtopography in natural environments. Complexity is encoded in terms of the Hurst exponent of a fractal description of the microtopographical geometry. The percentage of a seafloor transect where secondary dispersal of seagrass seeds occurs, is quantified in terms of the mainstream velocity, bottom complexity and properties of the seeds. Theoretical expressions are validated considering the cases of Zostera marina and Posidonia oceanica seeds and using computational fluid dynamics (CFD). A total of 200 CFD simulations with different bottom complexities and flow conditions, were done for each seagrass genus to validate the theoretical model. Numerical results agree with theoretical predictions. This finding provides a management tool to assess the degree of seed retention in seed-based restoration areas.

Consistent between-individual differences in movement are widely recognised across taxa. In addition, foraging plasticity at the within-individual level suggests a behavioural dependency on the internal energy demand. Because behaviour co-varies with fast-slow life history (LH) strategies in an adaptive context, as theoretically predicted by the pace-of-life syndrome hypothesis, mass/energy fluxes should link behaviour and its plasticity with physiology at both between- and within-individual levels. However, a mechanistic framework driving these links in a fluctuating ecological context is lacking. Focusing on home range behaviour, we propose a novel behavioural-bioenergetics theoretical model to address such complexities at the individual level based on energy balance. We propose explicit mechanistic links between behaviour, physiology/metabolism and LH by merging two well-founded theories, the movement ecology paradigm and the dynamic energetic budget theory. Overall, our behavioural-bioenergetics model integrates the mechanisms explaining how (1) behavioural between- and within-individual variabilities connect with internal state variable dynamics, (2) physiology and behaviour are explicitly interconnected by mass/energy fluxes, and (3) different LHs may arise from both behavioural and physiological variabilities in a given ecological context. Our novel theoretical model reveals encouraging opportunities for empiricists and theoreticians to delve into the eco-evolutionary processes that favour or hinder the development of between-individual differences in behaviour and the evolution of personality-dependent movement syndromes.

The thermal and hydrodynamic response of a Sea-Bird unpumped CTD SBE 41, is numerically modeled to assess the biases occurring at the slow flushing rates typical of glider operations. Based on symmetry considerations, the sensor response is approximated by coupling the incompressible Navier-Stokes and the thermal advection-diffusion equations in two dimensions. Numerical results illustrate three regimes in the thermal response of the SBE 41 sensor, when crossing water layers with different thermal signatures. A linear decay in time of the bulk temperature of the conductivity cell is initially found. This is induced by the transit of the inflow through the conductivity cell in the form of a relatively narrow jet. Water masses with new thermal signatures do not immediately fill the sensor chambers, where the cross-section widens. Thermal equilibrium of these water masses is then achieved, in a second regime, via a cross-flow thermal diffusion between the boundary of the jet and the walls. Consequently, the evolution of the bulk temperature scales with the square root of time. In a third regime, the evolution of the bulk temperature depends on the thermal gradient between the fluid and the coating material. This results on an exponential decay of the bulk temperature with time. A comprehensive analytical model of the time evolution of the bulk temperature inside a cell is proposed based on these results.

Motivated by experimental findings, a computational fluid dynamics (CFD) model was used to investigate whether the clam Mercenaria mercenaria may alter its cue downstream variability by an exhalant random pumping behavior. This behavior was hypothesized to occur in the presence of predator chemical signals in order to prevent successful tracking by the predator. Simulated downstream flow and mixing conditions derived from the random nature of the clam exhalant jet in a crossflow were analyzed by computing an intermittency factor, determining the field of finite-time Lyapunov exponents (FTLEs) and identifying the resulting Lagrangian coherent structures (LCSs). Numerical simulations illustrate that the effectiveness of a fluctuating exhalant jet to prevent downstream tracking by a crab, depends on the ratio of the exhalant jet to the crossflow. Specifically, the clam could effectively enhance the downstream dispersion to prevent tracking, but only in the range of parameters where LCSs are generated (jet-to-crossflow ratio >= 1). Then, the probability of detection is reduced with respect to the case of a less fluctuating exhalant jet. (C) 2018 Elsevier Ltd. All rights reserved.

Carbon storage in forests and its ability to offset global greenhouse gas emissions, as well as biodiversity and its capacity to support ecosystem functions and services, are often considered separately in landscape planning. However, the potential synergies between them are currently poorly understood. Identifying the spatial patterns and factors driving their co-occurrence across different climatic zones is critical to more effectively conserve forest ecosystems at the regional level. Here, we integrated information of National Forest Inventories and Breeding Bird Atlases across Europe and North America (Spain and Quebec, respectively), covering five subclimates (steppe, dry Mediterranean, humid Mediterranean, boreal, and temperate). In particular, this study aimed to (1) determine the spatial patterns of both forest carbon stocks and biodiversity (bird richness, tree richness, and overall biodiversity) and the factors that influence them; (2) establish the relationships between forest carbon stocks and biodiversity; and (3) define and characterize the areas of high (hotspots) and low (coldspots) values of carbon and biodiversity, and ultimately quantify their spatial overlap. Our results show that the factors affecting carbon and biodiversity vary between regions and subclimates. The highest values of carbon and biodiversity were found in northern Spain (humid Mediterranean subclimate) and southern Quebec (temperate subclimate) where there was more carbon as climate conditions were less limiting. High density and structural diversity simultaneously favored carbon stocks, tree, and overall biodiversity, especially in isolated and mountainous areas, often associated with steeper slopes and low accessibility. In addition, the relationship between carbon stocks and biodiversity was positive in both regions and all subclimates, being stronger where climate is a limiting factor for forest growth. The spatial overlap between hotspots of carbon and biodiversity provides an excellent opportunity for landscape planning to maintain carbon stocks and conserve biodiversity. The variables positively affecting carbon and biodiversity were also driving the hotspots of both carbon and biodiversity, emphasizing the viability of "win-win" solutions. Our results highlight the need to jointly determine the spatial patterns of ecosystem services and biodiversity for an effective and sustainable planning of forest landscapes that simultaneously support conservation and mitigate climate change.

Data assimilation through an ensemble Kalman filter (EnKF) is not exempt from deficiencies, including the generation of long-range unphysical correlations that degrade its performance. The covariance localization technique has been proposed and used in previous research to mitigate this effect. However, an evaluation of its performance is usually hindered by the sparseness and unsustained collection of independent observations.This article assesses the performance of an ocean prediction system composed of a multivariate EnKF coupled with a regional configuration of the Regional Ocean Model System (ROMS) with a covariance localization solution and data assimilation from an ocean glider that operated over a limited region of the Ligurian Sea. Simultaneous with the operation of the forecast system, a high-quality data set was repeatedly collected with a CTD sensor, i.e., every day during the period from 5 to 20 August 2013 (approximately 4 to 5 times the synoptic time scale of the area), located on board the NR/V Alliance for model validation. Comparisons between the validation data set and the forecasts provide evidence that the performance of the prediction system with covariance localization is superior to that observed using only EnKF assimilation without localization or using a free run ensemble. Furthermore, it is shown that covariance localization also increases the robustness of the model to the location of the assimilated data. Our analysis reveals that improvements are detected with regard to not only preventing the occurrence of spurious correlations but also preserving the spatial coherence in the updated covariance matrix. Covariance localization has been shown to be relevant in operational frameworks where short-term forecasts (on the order of days) are required.

Capsule: The sex of Black-necked Grebes Podiceps nigricollis in Spain can be determined successfully using a locally derived discriminant function analysis (DFA) but a function derived from a North American population was not successful. Aims: To determine the extent of sexual size dimorphism in the Black-necked Grebe and develop discriminant functions based on morphometric data. We also assessed the accuracy of visual sexing by fieldworkers with different levels of experience and compared the discriminant function for European birds with one for North American birds, in order to determine the geographical specificity of the function. Methods: We used a data set of 370 Black-necked Grebes from a European population throughout the non-breeding seasons of 2008-11 in the Odiel saltmarshes (Spain), as well as published data from North America, to compare the accuracy of DFAs developed for European and North American populations when applied to the same population. Results: Males were significantly larger than females for all body measurements. The DFA with the highest success rate included one single linear dimension (head-bill length), showing an efficiency of 88.5% in the same sample used to build the function and up to 91.5% in independent samples of birds. The more experienced ringer showed higher accuracy in visual sexing than the less experienced one (84 vs. 70%), although self-consistency in sex assignment of a given individual was similar. The function developed for European birds performed poorly for American birds (79.1% sexed correctly) and vice versa (18.4% sexed correctly). Conclusion: Morphological and sex ratio differences between European and American subspecies both contribute to the discrepancy in the success rate. This illustrates the need for caution when applying discriminant functions developed in one bird population to individuals elsewhere.

The perinatal brainstem is known to be very vulnerable to hypoxic–ischemic events which can lead to deafness, swallowing dysfunction, and defective respiratory control. The aim of the present work was to evaluate the potential neuroprotective effects of nicotine, melatonin, resveratrol, and docosahexaenoic acid on the expression of a panel of genes in the brainstem following hypoxic–ischemic damage. Quantitative PCR was used to examine gene expression 3 and 12 h after the damage, and immunohistochemistry was employed to evaluate neurons, astrocytes, and synaptic vesicles 24 h post insult. We found that the expression of some immediate-early genes, as well as that of inflammatory genes TNF-α, COX2, and caspase 3, was upregulated in response to the insult. Twenty-four hours after the damage, the percentage of NeuN and synaptophysin immunolabeled cells was found to be reduced while GFAP expression was upregulated. No differences were observed in ROS gene expression following treatments.

As the interest in the neuroprotective possibilities of docosahexaenoic acid (DHA) for brain injury has grown in the recent years, we aimed to investigate the long-term effects of this fatty acid in an experimental model of perinatal hypoxia–ischemia in rats. To this end, motor activity, aspects of learning, and memory function and anxiety, as well as corticofugal connections visualized by using tracer injections, were evaluated at adulthood. We found that in the hours immediately following the insult, DHA maintained mitochondrial inner membrane integrity and transmembrane potential, as well as the integrity of synaptic processes. Seven days later, morphological damage at the level of the middle hippocampus was reduced, since neurons and myelin were preserved and the astroglial reactive response and microglial activation were seen to be diminished. At adulthood, the behavioral tests revealed that treated animals presented better long-term working memory and less anxiety than non-treated hypoxic–ischemic animals, while no difference was found in the spontaneous locomotor activity. Interestingly, hypoxic–ischemic injury caused alterations in the anterograde corticofugal neuronal connections which were not so evident in rats treated with DHA. Thus, our results indicate that DHA treatment can lead to long-lasting neuroprotective effects in this experimental model of neonatal hypoxia–ischemic brain injury, not only by mitigating axonal changes but also by enhancing cognitive performance at adulthood.