Sensitivity of atmospheric dispersion simulations by HYSPLIT to the meteorological predictions from a meso-scale model

Mesoscale transport and dispersion of air pollutants from a few major point sources in the Mississippi Gulf coastal region is calculated using a coupled modeling system consisting of the atmospheric dynamical model WRF and the lagrangian particle model HYSPLIT. The sensitivity of the dispersion model results to the meteorological fields is studied by conducting an ensemble of simulations using the WRF model for the same dispersion case. Several parameterization schemes for the physical processes of boundary layer turbulence and land surface temperature/moisture prediction in WRF are used in various combinations to produce different meteorological members which are then used for dispersion simulation. The uncertainty in the simulated concentration probabilities to the meteorological model configurations and the ensemble mean are presented. The parameters used for determining the uncertainties include the wind fields, temperature, area of concentration and the levels of concentration. The results indicate that dispersion model results are influenced by the choices made in respect of the planetary boundary layer and land surface schemes in the mesoscale model to produce the meteorological forecast thereby leading to certain amount of uncertainty in the resultant concentrations. Results show that the specific choices made about the atmospheric model configuration can significantly after the simulated concentrations.     

Importance of decadal scale variability in shoreline response: examples from soft rock cliffs,East Anglian coast,UK

Rapidly eroding soft rock cliffs typically retreat at rates in excess of several metres per year, thus allowing the resolution of linkages between cliff dynamics and a range of climatic and marine forcing factors. New evidence from UK coastline of East Anglian coastline, southern North Sea shows that unprotected soft rock cliffs at three widely-spaced locations all show similar variability in retreat behaviour on decadal timescales, which we attribute to changing patterns of storminess in these decades. The 1990s were characterized by frequent months in which the North Atlantic Oscillation (NAO; a well-established measure of inter-annual climatic variability in North-West Europe) was extremely positive (more positive than +3) or extremely negative (more negative than ?3), while the 2000s showed few occurrences of such extreme values. Depression tracks in positive NAO phases make the East Anglian coast prone to storm surges in which raised water levels result from deeply developed low pressure systems, generally associated with westerly air streams. In negative NAO phases the region is prone to easterly airflow which results in periods of strong onshore wind. Both phases are associated with high energetics in the forcing factors. Decadal-scale variability in cliffline retreat rates has implications for the practice of coastal management and policy making and suggests that cliff system responses to global environmental change are not simply driven by secular sea level rise.     

Factors affecting information transfer from knowledgeable to naive individuals in groups

There is evidence that individuals in animal groups benefit from the presence of knowledgeable group members in different ways. Experiments and computer simulations have shown that a few individuals within a group can lead others, for a precise task and at a specific moment. As a group travels, different individuals possessing a particular knowledge may act as temporary leaders, so that the group will, as a whole, follow their behaviour. In this paper, we use a model to study different factors influencing group response to temporary leadership. The model is based on four individual behaviours. Three of those, attraction, repulsion, and alignment, are shared by all individuals. The last one, attraction toward the source of a stimulus, concerns only a fraction of the group members. We explore the influence of group size, proportion of stimulated individuals, number of influential neighbours, and intensity of the attraction to the source of the stimulus, on the proportion of the group reaching this source. Special attention is given to the simulation of large group size, close to those observed in nature. Groups of 100, 400 and 900 individuals are currently simulated, and up to 8,000 in one experiment. We show that more stimulated individuals and a larger group size both induce the arrival of a larger fraction of the group. The number of influential neighbours and the intensity of the stimulus have a non-linear influence on the proportion of the group arrival, displaying first a positive relationship and then, above a given threshold, a negative one. We conclude that an intermediate level of group cohesion provides optimal transfer information from knowledgeable to naive individuals.     

An effective dietary survey framework for the assessment of total dietary arsenic intake in Bangladesh: Part-A—FFQ design

Groundwater contaminated with arsenic (As), when extensively used for irrigation, causes potentially long term detrimental effects to the landscape. Such contamination can also directly affect human health when irrigated crops are primarily used for human consumption. Therefore, a large number of humans are potentially at risk worldwide due to daily As exposure. Numerous previous studies have been severely limited by small sample sizes which are not reliably extrapolated to large populations or landscapes. Human As exposure and risk assessment are no longer simple assessments limited to a few food samples from a small area. The focus of more recent studies has been to perform risk assessment at the landscape level involving the use of biomarkers to identify and quantify appropriate health problems and large surveys of human dietary patterns, supported by analytical testing of food, to quantify exposure. This approach generates large amounts of data from a wide variety of sources and geographic information system (GIS) techniques have been used widely to integrate the various spatial, demographic, social, field, and laboratory measured datasets. With the current worldwide shift in emphasis from qualitative to quantitative risk assessment, it is likely that future research efforts will be directed towards the integration of GIS, statistics, chemistry, and other dynamic models within a common platform to quantify human health risk at the landscape level. In this paper we review the present and likely future trends of human As exposure and GIS application in risk assessment at the landscape level.     

Two and three-dimensional shoreline behaviour at a MESO-MACROTIDAL barred beach

The present work investigates cross-shore shoreline migration as well as its alongshore variability (with deformation) on timescales of days to years using 6 years of time-averaged video images. The variability of the shoreline is estimated through empirical statistical methods with comprehensive reference to three scales of variability. At the meso-to macro-tidal barred Biscarrosse beach, shoreline responds in decreasing order at seasonal (winter/summer cycles, 52%), event (storms, 28%) and inter-annual scales. Whereas seasonal evolution is dominated by wave climate modulation, short-term evolution is influenced by tidal range and surf-zone sandbar characteristics. The influence of tide range and sandbars increases when timescale decreases. This is even more the case for the alongshore deformation of the shoreline which is dominated by short-term evolution. An EOF analysis reveals that the first mode of shoreline change time series is associated with cross-shore migration and explains 58% of the shoreline variability. The rest of the modes are associated to deformation which explain 42% of shoreline variability.     

Currents connecting communities: nearshore community similarity and ocean circulation

Understanding the mechanisms that create spatial heterogeneity in species distributions is fundamental to ecology. For nearshore marine systems, most species have a pelagic larval stage where dispersal is strongly influenced by patterns of ocean circulation. Concomitantly, nearshore habitats and the local environment are also influenced by ocean circulation. Because of the shared dependence on the seascape, distinguishing the relative importance of the local environment from regional patterns of dispersal for community structure remains a challenge. Here, we quantify the "oceanographic distance" and "oceanographic asymmetry" between nearshore sites using ocean circulation modeling results. These novel metrics quantify spatial separation based on realistic patterns of ocean circulation, and we explore their explanatory power for intertidal and subtidal community similarity in the Southern California Bight. We find that these metrics show significant correspondence with patterns of community similarity and that their combined explanatory power exceeds that of the thermal structure of the domain. Our approach identifies the unique influence of ocean circulation on community structure and provides evidence for oceanographically mediated dispersal limitation in nearshore marine communities.     

Effects of near‐future ocean acidification,fishing, and marine protection on a temperate coastal ecosystem

Understanding ecosystem responses to global and local anthropogenic impacts is paramount to predicting future ecosystem states. We used an ecosystem modeling approach to investigate the independent and cumulative effects of fishing, marine protection, and ocean acidification on a coastal ecosystem. To quantify the effects of ocean acidification at the ecosystem level, we used information from the peer‐reviewed literature on the effects of ocean acidification. Using an Ecopath with Ecosim ecosystem model for the Wellington south coast, including the Taputeranga Marine Reserve (MR), New Zealand, we predicted ecosystem responses under 4 scenarios: ocean acidification + fishing; ocean acidification + MR (no fishing); no ocean acidification + fishing; no ocean acidification + MR for the year 2050. Fishing had a larger effect on trophic group biomasses and trophic structure than ocean acidification, whereas the effects of ocean acidification were only large in the absence of fishing. Mortality by fishing had large, negative effects on trophic group biomasses. These effects were similar regardless of the presence of ocean acidification. Ocean acidification was predicted to indirectly benefit certain species in the MR scenario. This was because lobster (Jasus edwardsii) only recovered to 58% of the MR biomass in the ocean acidification + MR scenario, a situation that benefited the trophic groups lobsters prey on. Most trophic groups responded antagonistically to the interactive effects of ocean acidification and marine protection (46%; reduced response); however, many groups responded synergistically (33%; amplified response). Conservation and fisheries management strategies need to account for the reduced recovery potential of some exploited species under ocean acidification, nonadditive interactions of multiple factors, and indirect responses of species to ocean acidification caused by declines in calcareous predators.     

Tracking the response of industrial fishing fleets to large marine protected areas in the Pacific Ocean

Large marine protected areas (MPAs) of unprecedented size have recently been established across the global oceans, yet their ability to meet conservation objectives is debated. Key areas of debate include uncertainty over nations’ abilities to enforce fishing bans across vast, remote regions and the intensity of human impacts before and after MPA implementation. We used a recently developed vessel tracking data set (produced using Automatic Identification System detections) to quantify the response of industrial fishing fleets to 5 of the largest MPAs established in the Pacific Ocean since 2013. After their implementation, all 5 MPAs successfully kept industrial fishing effort exceptionally low. Detected fishing effort was already low in 4 of the 5 large MPAs prior to MPA implementation, particularly relative to nearby regions that did not receive formal protection. Our results suggest that these large MPAs may present major conservation opportunities in relatively intact ecosystems with low immediate impact to industrial fisheries, but the large MPAs we considered often did not significantly reduce fishing effort because baseline fishing was typically low. It is yet to be determined how large MPAs may shape global ocean conservation in the future if the footprint of human influence continues to expand. Continued improvement in understanding of how large MPAs interact with industrial fisheries is a crucial step toward defining their role in global ocean management.     

A proposal of an indicator for quantifying model robustness based on the relationship between variability of errors and of explored conditions

The evaluation of biophysical models is usually carried out by estimating the agreement between measured and simulated data and, more rarely, by using indices for other aspects, like model complexity and overparameterization. In spite of the importance of model robustness, especially for large area applications, no proposals for its quantification are available. In this paper, we would like to open a discussion on this issue, proposing a first approach for a quantification of robustness based on the variability of model error to variability of explored conditions ratio. We used modelling efficiency (EF) for quantifying error in model predictions and a normalized agrometeorological index (SAM) based on cumulated rainfall and reference evapotranspiration to characterize the conditions of application. Population standard deviations of EF and SAM were used to quantify their variability. The indicator was tested for models estimating meteorological variables and crop state variables. The values provided by the robustness indicator (I_R) were discussed according to the models’ features and to the typology and number of processes simulated. I_R increased with the number of processes simulated and, within the same typology of model, with the degree of overparameterization. No correlation were found between I_R and two of the most used indices of model error (RRMSE, EF). This supports its inclusion in integrated systems for model evaluation.     

Redesigning harvest strategies for sustainable fishery management in the face of extreme environmental variability

Short-lived, fast-growing species that contribute greatly to global capture fisheries are sensitive to fluctuations in the environment. Uncertainties in exact stock–environment relationships have meant that environmental variability and extremes have been difficult to integrate directly into fisheries management. We applied a management strategy evaluation approach for one of Australia's large prawn stocks to test the robustness of harvest control rules to environmental variability. The model ensemble included coupled environmental-population models and an alternative catchability scenario fitted to historical catch per unit effort data. We compared the efficacy of alternative management actions to conserve marine resources under a variable environment while accounting for fisher livelihoods. Model fits to catch per unit effort were reasonably good and similar across operating models (OMs). For models that were coupled to the environment, environmental parameters for El Niño years were estimated with good associated precision, and OM3 had a lower AIC score (77.61)  than the base model (OM1, 80.39), whereas OM2 (AIC 82.41) had a similar AIC score, suggesting the OMs were all plausible model alternatives. Our model testing resulted in a plausible subset of management options, and stakeholders selected a permanent closure of the first fishing season based on overall performance of this option; ability to reduce the risk of fishery closure and stock collapse; robustness to uncertainties; and ease of implementation. Our simulation approach enabled the selection of an optimal yet pragmatic solution for addressing economic and conservation objectives under a variable environment with extreme events.     

Neural network modelling for the analysis of forcings/temperatures relationships at different scales in the climate system

A fully non-linear analysis of forcing influences on temperatures is performed in the climate system by means of neural network modelling. Two case studies are investigated, in order to establish the main factors that drove the temperature behaviour at both global and regional scales in the last 140 years. In particular, our neural network model shows the ability to catch non-linear relationships among these variables and to reconstruct temperature records with a high degree of accuracy. In this framework, we clearly show the need of including anthropogenic inputs for explaining the temperature behaviour at global scale and recognise the role of El Niño southern oscillation for catching the inter-annual variability of temperature data. Furthermore, we analyse the relative influence of global forcing and a regional circulation pattern in determining the winter temperatures in Central England, showing that the North Atlantic oscillation represents the driven element in this case study. Our modelling activity and results can be very useful for simple assessments of relationships in the complex climate system and for identifying the fundamental elements leading to a successful downscaling of atmosphere–ocean general circulation models.     

Enhancing synergies between action on ocean acidification and the post-2020 global biodiversity framework

Ocean acidification is a substantial emergent threat to marine biodiversity and the goods and services it provides. Although efforts to address ocean acidification have been taken under the Convention on Biological Diversity (CBD), a far greater potential to do so exists by finding synergies between biodiversity conservation efforts and ocean acidification action. The ongoing process to develop a post-2020 global biodiversity framework offers an opportunity to ensure that opportunities for addressing ocean acidification are capitalized on and not overlooked. I argue that to achieve this, the following are needed: a technical integration of ocean acidification across the targets to be included in the post-2020 framework and a reframing of the issue as a biodiversity problem so as to highlight the synergies between existing biodiversity work and action needed to address ocean acidification. Given that the post-2020 framework is intended to establish the global biodiversity agenda for the coming decades, integration of ocean acidification will set a precedent for the other biodiversity-related conventions and encourage greater uptake of the issue across the wider international community. My approach is of direct relevance to those participating in the negotiations, both from a CBD Party perspective and the perspective of those advocating for a strong outcome to protect marine biodiversity and marine socioecological systems. My discussion of framing is relevant to those working beyond the CBD within other biodiversity-related conventions in which goals to address ocean acidification are sorely lacking.     

Multi-decadal drought and amplified moisture variability drove rapid forest community change in a humid region

Climate variability, particularly the frequency of extreme events, is likely to increase in the coming decades, with poorly understood consequences for terrestrial ecosystems. Hydroclimatic variations of the Medieval Climate Anomaly (MCA) provide a setting for studying ecological responses to recent climate variability at magnitudes and timescales comparable to expectations of coming centuries. We examined forest response to the MCA in the humid western Great Lakes region of North America, using proxy records of vegetation, fire, and hydroclimate. Multi-decadal moisture variability during the MCA was associated with a widespread, episodic decline in Fagus grandifolia (beech) populations. Spatial patterns of drought and forest changes were coherent, with beech declining only in areas where proxy-climate records indicate that severe MCA droughts occurred. The occurrence of widespread, drought-induced ecological changes in the Great Lakes region indicates that ecosystems in humid regions are vulnerable to rapid changes in drought magnitude and frequency.     

The accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors

Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I found that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.     

A two-stage ensemble Kalman filter for smooth data assimilation

The ensemble Kalman Filter (EnKF) applied to a simple fire propagation model by a nonlinear convection-diffusion-reaction partial differential equation breaks down because the EnKF creates nonphysical ensemble members with large gradients. A modification of the EnKF is proposed by adding a regularization term that penalizes large gradients. The method is implemented by applying the EnKF formulas twice, with the regularization term as another observation. The regularization step is also interpreted as a shrinkage of the prior distribution. Numerical results are given to illustrate success of the new method.     

基于数据库的植物功能性状研究现状文献计量学分析

植物功能性状数据库是功能生态学研究的重要工具.了解基于植物功能性状数据库的植物功能性状研究现状,对探讨功能多样性和生物多样性具有重要的指导意义.介绍植物功能性状数据库的类型、影响力的评价方法和使用方法,并整理了17个植物功能性状库(附表).同时,通过Web of Science检索了2008-2018年间基于植物功能性...     

Mitochondrial control region variability and global population structure in the swordfish,Xiphias gladius

Little is known about what limits genetic exchange in highly vagile, open ocean vertebrate species, such as the swordfish Xiphias gladius L. Reduced abundance of swordfish in some regions, and increased fishing pressure in others, has raised concerns and fueled interest in a more complete evaluation of the resource. In this study, global population structure in swordfish was assessed by sequencing a 300 base pair segment of the 5 end of mitochondrial DNA control region from 159 swordfish collected in three ocean basins: the Mediterranean, Atlantic and Pacific, over the years 1988 to 1994. Among the 159 individuals, 95 polymorphic sites delineated 121 unique haplotypes, indicating a high level of polymorphism on a global scale. A phylogenetic analysis of the unique DNA haplotypes revealed two divergent clades with differing geographic distributions. Phylogeographic concordance of this pattern with that of two other pelagic fish species suggests a biogeographic explanation for this structure. An analysis of molecular variance (AMOVA) revealed significant geographic partitioning of molecular variation among the three ocean basins, indicating that swordfish populations are structured on a global scale. Estimates of genetic exchange among populations within an ocean basin were high, indicating panmixia within ocean basins. Since the haplotypic diversity exhibited by the swordfish control regions is extremely high, much larger sample sizes may be necessary to detect subdivision within ocean basins.     

A little movement orientated to the geomagnetic field makes a big difference in strong flows

Whilst a range of animals have been shown to respond behaviourally to components of the Earth’s magnetic field, evidence of the value of this sensory perception for small animals advected by strong flows (wind/ocean currents) is equivocal. We added geomagnetic directional swimming behaviour for North Atlantic loggerhead turtle hatchlings (Caretta caretta) into a high-resolution (1/4°) global general circulation ocean model to simulate 2,925-year-long hatchling trajectories comprising 355,875 locations. A little directional swimming (1–3 h per day) had a major impact on trajectories; simulated hatchlings travelled further south into warmer water. As a result, thermal elevation of hatchling metabolic rates was estimated to be between 63.3 and 114.5% after 220 days. We show that even small animals in strong flows can benefit from geomagnetic orientation and thus the potential implications of directional swimming for other taxa may be broad.     

海洋酸化对鱼类感觉和行为影响的研究进展

海洋酸化是指大气增多的二氧化碳(CO2)溶解于海水而导致海水p H值降低的过程。海洋酸化将改变海水碳酸盐平衡体系,使依赖于原化学环境的多种海洋生物乃至生态系统面临巨大威胁。海洋酸化对钙质生物影响的研究最早引起大家关注,而海洋鱼类具有较完善的酸碱调节机制,大家普遍认为酸化对其影响不大。但在过去的5年中,不少实验证明海洋酸化会影响海洋鱼类仔稚鱼的感觉和行为,减弱其野外的生存能力及增加被捕食率,很可能将威胁自然种群补给量和影响全球的渔业资源量。本文从嗅觉、听觉、视觉及高级意识和相关行为角度,综述近几年海洋酸化对鱼类感觉和行为影响的研究进展,介绍了鱼类神经行为生物学的研究,为全面了解和预测海洋酸化的生态、经济和社会效应提供科学依据。     

Geospatial analysis of vulnerable beach-foredune systems from decadal time series of lidar data

Time series of lidar data, acquired over the past decade along the North American East Coast, provide opportunities to gain new insights into 3D evolution of barrier islands and their beach and dune systems. GIS-based per grid cell statistics and map algebra was applied to time series of Digital Surface Models representing two sections of North Carolina barrier islands to quantify elevation change trends, map dynamic and stable locations, identify new and lost buildings, measure relative volume evolution in the beach and foredune systems and analyze shoreline dynamics. Results show a relatively small stable core in both study areas, with beaches and the ocean side of the dunes exhibiting systematic high rates of elevation loss while areas landward from the dunes increase slightly in elevation. Significant number of new homes have been built at locations with very small core surface elevation, and homes built within the shoreline dynamics band have already been lost. The raster-based methodology used in this study can be applied to perform similar analyses in other coastal areas where time series of lidar data are available.