Understanding the implications of a changing environment on harvested bivalve populations using habitat suitability models

Habitat suitability models are useful to forecast how environmental change may affect the abundance or distribution of species of interest. In the case of harvested bivalves, those models may be used to estimate the vulnerability of this valued ecosystem good to stressors. Using literature-derived natural history information, rule-based habitat suitability models were constructed in a GIS for several bivalve species (Clinocardium nuttallii, Mya arenaria, and Tresus capax) that are recreationally and commercially harvested in NE Pacific estuaries, including in the Salish Sea. Spatially-explicit habitat maps were produced for two Oregon estuaries using environmental data (salinity, depth, sediment grain size, and burrowing shrimp density) from multiple studies (1960-2012). Habitat suitability values ranged from 1-4 (lowest to highest) depending on the number of environmental variables that fell within a bivalve’s tolerance limits. The models were tested by comparing the observed distribution of bivalves reported in benthic community studies (1996-2012) to the range of each suitability class. Results primarily showed that habitats of highest predicted suitability contained the greatest proportion of bivalve observations and highest population densities. Our model was further supported by logistic regression analyses that showed correspondence between predicted habitat suitability values and logistic model probabilities. We demonstrate how these models can be used as tools to forecast changes in the availability of suitable habitat for these species using projected changes in salinity and depth associated with environmental change scenarios. The advantage of this approach is that disparate, independent sets of existing data are sufficient to parameterize the models, and to produce and validate maps of habitat suitability. We believe that these models are transferable across estuaries (such as in the Salish Sea) and bivalve species, and thus can be applied to data-poor systems with only modest investment

Incorporation of diet information derived from Bayesian stable isotope mixing models into mass-balanced marine ecosystem models : a case study from the Marennes-Oléron Estuary, France

This thesis presents two related studies on the methodology for creating, and subsequently analyzing, an inverse food web model of an intertidal seagrass bed. The first study (Chapter 2) describes, for the first time in the literature, a method for incorporating isotopic information gained from Bayesian mixing models into an inverse food web model. The second study (Chapter 3) analyzes the results of this food web model from an ecological perspective, which includes the first complete description of the carbon budget of an intertidal seagrass food web incorporating isotopic information. Linear inverse modeling (LIM) is a technique that estimates a complete network of flows in an under-determined system (e.g., a food web) using a combination of site-specific data and previously published data. This estimation of complete flow networks of food webs in marine ecosystems is becoming more recognized as a powerful tool for understanding ecosystem functioning. However, diets and consumption rates of organisms are often difficult or impossible to accurately and reliably measure in the field, resulting in a large amount of uncertainty in the magnitude of consumption flows and resource partitioning in food web models. In order to address this issue, Chapter 2 utilized stable isotope data to help aid in estimating these unknown flows. δ¹³C and δ¹⁵N isotope data of consumers and producers in the Marennes-Oleron seagrass system were used in Bayesian mixing models; the output of which were then used to constrain consumption flows in an inverse analysis food web model of the seagrass ecosystem. We hypothesized that incorporating the diet information gained from the stable isotope mixing models would result in a more constrained food web model. In order to test this, two inverse food web models were built to track the flow of carbon through the seagrass food web on an annual basis, with units of mg C m⁻² d⁻¹. The first model (Traditional LIM) included all available data, with the exception of the diet constraints formed from the stable isotope mixing models. The second model (Isotope LIM) was identical to the Traditional LIM, but included the SIAR diet constraints. Both models were identical in structure, and intended to model the same Marennes- Oleron intertidal seagrass bed. Each model consisted of 27 compartments (24 living, 3 detrital) and 175 flows. Comparisons between the outputs of the models showed the addition of the SIAR-derived isotopic diet constraints further constrained the solution range of all food web flows on average by 26%. Flows that were directly affected by an isotopic diet constraint were 45% further constrained on average. These results confirmed our hypothesis that incorporation of the isotope information would result in a more constrained food web model, and demonstrated the benefit of utilizing multi-tracer stable isotope information in ecosystem models. In Chapter 3, Ecological Network Analysis (ENA) was used to investigate the functional ecology of the system. The majority of seagrass food web studies thus far have relied on trophic marker analyses (i.e. stable isotopes, fatty acids) to investigate food sources and trophic positions, and as a result, few studies have examined seagrass beds from a perspective of whole-ecosystem functioning. By quantifying the Marennes- Oleron seagrass food web using linear inverse modeling coupled with results from isotopic mixing models, this study investigated the relative trophic importance of primary producers in the system, the trophic structure of the seagrass bed flora and fauna, the relative importance of allochthonous versus autochthonous carbon, and both the sequestration and export of organic carbon to the surrounding environment. Additionally, results of these analyses were compared with other coastal systems, including a neighboring bare mudflat located in the Marennes-Oleron estuary. Grazing rates indicated that microphytobenthos was directly consumed about 7 times more than Zostera, while a novel metric of total food web dependency derived from network analysis showed the consumer compartments relied upon microphytobenthos 22 time more than on Z. noltii via direct and indirect pathways. Meiofauna was found to provide an important link between primary production and detritus with upper trophic levels (i.e. fish). Autochthonous carbon was utilized over 4 times more than allochthonous carbon by the seagrass food web in total, and the system was shown to be a net carbon sink. Our analysis supported the concept that seagrass meadows have a high metabolic capacity and the ability to accumulate large sedimentary carbon pools (e.g., carbon sequestration), which are important climate-regulating ecosystem services. ENA revealed the Oleron seagrass bed to be a relatively mature, stable system internally, with strong connections via energy transport to and from surrounding environments. To the best of the authors' knowledge, this study was the first to fully characterize the carbon budget of an intertidal seagrass food web utilizing probabilistic methods

Interactions amongst Local and Global Drivers of Coastal Acidification in Estuarine Habitats of the Northern California Current

The variability of coastal carbonate chemistry continues to provide significant hurdles for understanding interactions between anthropogenic and natural CO2 cycling and resultant effects on coastal acidification dynamics. Attribution of the anthropogenic component is vital for identifying the impacts of increasing atmospheric carbon on coastal habitats such as coral reefs, upwelling margins, inland seas, and estuaries. The dynamic nature of these systems has led some to conclude that the baseline shift in atmospheric CO2 is a relatively unimportant driver, but emerging evidence of rapidly acidifying coastal systems suggests otherwise. This dissertation addresses natural and anthropogenic inorganic carbon cycling interactions on diel, seasonal, and decadal time scales to determine current and future acidification trajectories in estuary habitats typical of the northern California Current. Chapter 2 focuses on alterations of diel-scale “carbonate weather” and accelerated rates of acidification in a seagrass habitat resulting from interactions between metabolic CO2 cycling and rising atmospheric CO2 levels. Chapter 3 quantifies how the seasonal variability of carbonate chemistry in two seagrass habitats is altered by rising atmospheric CO2, and how these alterations compare with perturbations driven by altered river discharge, warming temperatures, and eutrophication. Chapter 4 investigates the temporal and spatial dynamics of coastal acidification drivers in a small, open-coast estuary subject to seasonal upwelling and inputs from an agriculturally-developed watershed. This work shows that estuarine habitats are often poorly-buffered against increasing global atmospheric CO2 levels, resulting in accelerated changes of extreme carbonate weather and enhanced CO2 seasonality. Current and future acidification trajectories are significantly modulated by local biophysical processes, including net community metabolism and watershed chemistry. While these local processes control the variance of acidification trajectories amongst estuarine systems, our results suggests the global atmospheric CO2 perturbation is likely the dominant anthropogenic driver of coastal acidification in many systems. Management and policymaking for coastal acidification impacts will be more effective if the spatial and temporal interactions between local and global drivers of acidification are properly accounted for

Seasonal patterns of estuarine acidification in seagrass beds of the Snohomish Estuary, WA

Recent studies have begun to explore physical and biogeochemical mechanisms of carbonate chemistry variability in a variety of coastal habitats, including coral reefs, upwelling margins, and inland seas. To our knowledge, there have been limited mechanistic studies of annual carbonate chemistry variability in nearshore estuarine environments. Here, we present autonomous sensor and grab sample data of carbonate chemistry covering a 10 month period from two subtidal seagrass bed sites in Possession Sound, WA. Simple mass balance stoichiometric models are used to evaluate seasonal drivers of carbonate system parameters in the seagrass beds. Simulations of increasing anthropogenic carbon (Canth) burdens in the habitats reveal seasonal differences in the magnitude of carbonate system responses. The addition of Canth alters the thermodynamic buffer factors (e.g. the Revelle factor) of the carbonate system, decreasing the system’s ability to buffer natural variability in the seagrass habitat on high-frequency (e.g. tidal, diel) and seasonal timescales. As a result, the most harmful carbonate system indices for many estuarine organisms (minimum pHT, minimum Ωarag, and maximum pCO2(s.w.)) change most rapidly with increasing Canth. We highlight how the observed seasonal climatology and non-linear response of the carbonate system to increasing Canth drive the timing of the crossing of established physiological stress thresholds for endemic organisms, as well as thresholds relevant for water quality management. In this system, the relative benefits of the seagrass beds in locally mitigating ocean acidification during the growing season increase with the higher atmospheric CO2 levels predicted toward 2100. Presently however, these mitigating effects are mixed due to intense diel cycling of CO2 driven by community metabolism

Quantifying the combined impacts of anthropogenic CO2 emissions and watershed alteration on estuary acidification at biologically-relevant time scales: a case study from Tillamook Bay, OR, USA

The impacts of ocean acidification (OA) on coastal water quality have been subject to intensive research in the past decade, but how emissions-driven OA combines with human modifications of coastal river inputs to affect estuarine acidification dynamics is less well understood. This study presents a methodology for quantifying the synergistic water quality impacts of OA and riverine acidification on biologically-relevant timescales through a case study from a small, temperate estuary influenced by coastal upwelling and watershed development. We characterized the dynamics and drivers of carbonate chemistry in Tillamook Bay, OR (USA), along with its coastal ocean and riverine end-members, through a series of synoptic samplings and continuous water quality monitoring from July 2017 to July 2018. Synoptic river sampling showed acidification and increased CO2 content in areas with higher proportions of watershed anthropogenic land use. We propagated the impacts of 1). the observed riverine acidification, and 2). modeled OA changes to incoming coastal ocean waters across the full estuarine salinity spectrum and quantified changes in estuarine carbonate chemistry at a 15-minute temporal resolution. The largest magnitude of acidification (-1.4 pHT units) was found in oligo- and mesohaline portions of the estuary due to the poor buffering characteristics of these waters, and was primarily driven by acidified riverine inputs. Despite this, emissions-driven OA is responsible for over 94% of anthropogenic carbon loading to Tillamook Bay and the dominant driver of acidification across most of the estuary due to its large tidal prism and relatively small river discharges. This dominance of ocean-sourced anthropogenic carbon challenges the efficacy of local management actions to ameliorate estuarine acidification impacts. Despite the relatively large acidification effects experienced in Tillamook Bay (-0.16 to -0.23 pHT units) as compared with typical open ocean change (approximately -0.1 pHT units), observations of estuarine pHT would meet existing state standards for pHT. Our analytical framework addresses pressing needs for water quality assessment and coastal resilience strategies to differentiate the impacts of anthropogenic acidification from natural variability in dynamic estuarine systems

Solutions to the chronic wounds problem in Australia: A call to action

Background: Chronic wounds are a silent epidemic in Australia. They are an under-recognised public health issue, and their significant health and economic impact is underestimated. Evidence-based practice in wound care has significant health and economic benefits, yet there are still considerable evidence–practice gaps. Methods: Stakeholders attended a national forum to refine and prioritise solutions to the chronic wounds problem in Australia. A survey was administered to identify key priorities and recommendations. Results: Stakeholders agreed on 17 recommendations and strategies to improve the outcomes of Australians with chronic wounds. The identified priorities for immediate action were to raise awareness of the significance of chronic wounds, and to make chronic wounds a strategic priority for governments. The Chronic Wounds Solutions Collaborating Group was established to encourage, support and monitor action on the implementation of these recommendations. Conclusions: Large health and economic gains can be achieved with modest investments in evidence-based strategies for the prevention and control of chronic wounds in Australia. We call for a critical and sustained national effort to prevent and treat chronic wounds in Australia. Urgent action is needed at all levels if Australia is to reduce the significant preventable burden of chronic wounds and improve patient outcomes

Sans titres: Anthologie collective Français 335 (automne 2011)

http://deepblue.lib.umich.edu/bitstream/2027.42/89432/1/sans_titres.pd

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate