Modelling the size distribution of cosmic voids

The Standard Cosmological Model is generally accepted by the scientific community, there are still an amount of unresolved issues. From the observable characteristics of the structures in the Universe,it should be possible to impose constraints on the cosmological parameters. Cosmic Voids (CV) are a major component of the LSS and have been shown to possess great potential for constraining DE and testing theories of gravity. But a gap between CV observations and theory still persists. A theoretical model for void statistical distribution as a function of size exists (SvdW) However, the SvdW model has been unsuccesful in reproducing the results obtained from cosmological simulations. This undermines the possibility of using voids as cosmological probes. The goal of our thesis work is to cover the gap between theoretical predictions and measured distributions of cosmic voids. We develop an algorithm to identify voids in simulations,consistently with theory. We inspecting the possibilities offered by a recently proposed refinement of the SvdW (the Vdn model, Jennings et al., 2013). Comparing void catalogues to theory, we validate the Vdn model, finding that it is reliable over a large range of radii, at all the redshifts considered and for all the cosmological models inspected. We have then searched for a size function model for voids identified in a distribution of biased tracers. We find that, naively applying the same procedure used for the unbiased tracers to a halo mock distribution does not provide success- full results, suggesting that the Vdn model requires to be reconsidered when dealing with biased samples. Thus, we test two alternative exten- sions of the model and find that two scaling relations exist: both the Dark Matter void radii and the underlying Dark Matter density contrast scale with the halo-defined void radii. We use these findings to develop a semi-analytical model which gives promising results.

Data to Decision in a Dynamic Ocean: Robust Species Distribution Models and Spatial Decision Frameworks

Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.

Chemistry and grain-size distribution of terrigenous sediments deposited at Site GeoB9501

The Sahara Desert is the largest source of mineral dust in the world. Emissions of African dust increased sharply in the early 1970s, a change that has been attributed mainly to drought in the Sahara/Sahel region caused by changes in the global distribution of sea surface temperature. The human contribution to land degradation and dust mobilization in this region remains poorly understood, owing to the paucity of data that would allow the identification of long-term trends in desertification. Direct measurements of airborne African dust concentrations only became available in the mid-1960s from a station on Barbados and subsequently from satellite imagery since the late 1970s: they do not cover the onset of commercial agriculture in the Sahel region ~170 years ago. Here we construct a 3,200-year record of dust deposition off northwest Africa by investigating the chemistry and grain-size distribution of terrigenous sediments deposited at a marine site located directly under the West African dust plume. With the help of our dust record and a proxy record for West African precipitation we find that, on the century scale, dust deposition is related to precipitation in tropical West Africa until the seventeenth century. At the beginning of the nineteenth century, a sharp increase in dust deposition parallels the advent of commercial agriculture in the Sahel region. Our findings suggest that human-induced dust emissions from the Sahel region have contributed to the atmospheric dust load for about 200 years.

Planktic foraminiferal distribution and stable isotope ratios of sediment core MSM05/5_712-1 from the Arctic Ocean

The Arctic is responding more rapidly to global warming than most other areas on our planet. Northward flowing Atlantic Water is the major means of heat advection towards the Arctic and strongly affects the sea ice distribution. Records of its natural variability are critical for the understanding of feedback mechanisms and the future of the Arctic climate system, but continuous historical records reach back only ~150 years. Here, we present a multidecadal scale record of ocean temperature variations during the last 2000 years, derived from marine sediments off Western Svalbard (79°N). We find that early-21st-century temperatures of Atlantic Water entering the Arctic Ocean are unprecedented over the past 2000 years and are presumably linked to the Arctic Amplification of global warming.

Exchange-Trade Funds Evaluation using Performance Measures Distribution

In this study we propose the use of the performance measure distribution rather than its punctual value to rank hedge funds. Generalized Sharpe Ratio and other similar measures that take into account the higher-order moments of portfolio return distributions are commonly used to evaluate hedge funds performance. The literature in this field has reported non-significant difference in ranking between performance measures that take, and those that do not take, into account higher moments of distribution. Our approach provides a much more powerful manner to differentiate between hedge funds performance. We use a non-semiparametric density based on Gram-Charlier expansions to forecast the conditional distribution of hedge fund returns and its corresponding performance measure distribution. Through a forecasting exercise we show the advantages of our technique in relation to using the more traditional punctual performance measures.

CT Image Electron Density Quantification in Regions with Metal Implants: Implications for Radiotherapy Treatment Planning

In radiotherapy planning, computed tomography (CT) images are used to quantify the electron density of tissues and provide spatial anatomical information. Treatment planning systems use these data to calculate the expected spatial distribution of absorbed dose in a patient. CT imaging is complicated by the presence of metal implants which cause increased image noise, produce artifacts throughout the image and can exceed the available range of CT number values within the implant, perturbing electron density estimates in the image. Furthermore, current dose calculation algorithms do not accurately model radiation transport at metal-tissue interfaces. Combined, these issues adversely affect the accuracy of dose calculations in the vicinity of metal implants. As the number of patients with orthopedic and dental implants grows, so does the need to deliver safe and effective radiotherapy treatments in the presence of implants. The Medical Physics group at the Cancer Centre of Southeastern Ontario and Queen's University has developed a Cobalt-60 CT system that is relatively insensitive to metal artifacts due to the high energy, nearly monoenergetic Cobalt-60 photon beam. Kilovoltage CT (kVCT) images, including images corrected using a commercial metal artifact reduction tool, were compared to Cobalt-60 CT images throughout the treatment planning process, from initial imaging through to dose calculation. An effective metal artifact reduction algorithm was also implemented for the Cobalt-60 CT system. Electron density maps derived from the same kVCT and Cobalt-60 CT images indicated the impact of image artifacts on estimates of photon attenuation for treatment planning applications. Measurements showed that truncation of CT number data in kVCT images produced significant mischaracterization of the electron density of metals. Dose measurements downstream of metal inserts in a water phantom were compared to dose data calculated using CT images from kVCT and Cobalt-60 systems with and without artifact correction. The superior accuracy of electron density data derived from Cobalt-60 images compared to kVCT images produced calculated dose with far better agreement with measured results. These results indicated that dose calculation errors from metal image artifacts are primarily due to misrepresentation of electron density within metals rather than artifacts surrounding the implants.

Multivariate Appoximations to Portfolio Return Distribution

This article proposes a three-step procedure to estimate portfolio return distributions under the multivariate Gram-Charlier (MGC) distribution. The method combines quasi maximum likelihood (QML) estimation for conditional means and variances and the method of moments (MM) estimation for the rest of the density parameters, including the correlation coefficients. The procedure involves consistent estimates even under density misspecification and solves the so-called ‘curse of dimensionality’ of multivariate modelling. Furthermore, the use of a MGC distribution represents a flexible and general approximation to the true distribution of portfolio returns and accounts for all its empirical regularities. An application of such procedure is performed for a portfolio composed of three European indices as an illustration. The MM estimation of the MGC (MGC-MM) is compared with the traditional maximum likelihood of both the MGC and multivariate Student’s t (benchmark) densities. A simulation on Value-at-Risk (VaR) performance for an equally weighted portfolio at 1% and 5% confidence indicates that the MGC-MM method provides reasonable approximations to the true empirical VaR. Therefore, the procedure seems to be a useful tool for risk managers and practitioners.

Causes of extreme variability of nest density among close and similar beaches of Boavista island (Cape Verde): From 1 to 2000 annual nests per km.

[EN] The 70 km of white sandy beaches of Boa Vista island in Cape Verde harbours one of the largest rookeries of the endangered loggerhead sea turtle, Caretta caretta. From middle June to early October, approximately 2000 to 4000 females lay up to 20000 nests annually. However, female beach selection, nesting success and nest density strongly varies among beaches and spatial patterns of nest abundance and distribution are relatively constant among seasons. The numbers of nesting activities and nests have been recorded along all beaches of the island during four nesting seasons (2007-2010)

Exact Probability Distribution versus Entropy

The problem addressed concerns the determination of the average numberof successive attempts of guessing a word of a certain length consisting of letters withgiven probabilities of occurrence. Both first- and second-order approximations to a naturallanguage are considered. The guessing strategy used is guessing words in decreasing orderof probability. When word and alphabet sizes are large, approximations are necessary inorder to estimate the number of guesses. Several kinds of approximations are discusseddemonstrating moderate requirements regarding both memory and central processing unit(CPU) time. When considering realistic sizes of alphabets and words (100), the numberof guesses can be estimated within minutes with reasonable accuracy (a few percent) andmay therefore constitute an alternative to, e.g., various entropy expressions. For manyprobability distributions, the density of the logarithm of probability products is close to anormal distribution. For those cases, it is possible to derive an analytical expression for theaverage number of guesses. The proportion of guesses needed on average compared to thetotal number decreases almost exponentially with the word length. The leading term in anasymptotic expansion can be used to estimate the number of guesses for large word lengths.Comparisons with analytical lower bounds and entropy expressions are also provided.

Ecological health analysis of Caspian marine environment based on the diversity and distribution pattern of meiofauna in the Mazandaran Province, Caspian Sea

Biodiversity and distribution of benthic meiofauna in the sediments of the Southern Caspian Sea (Mazandaran) was studied in order to introducing and determining of their relationship with the environmental factors. From 12 stations (ranging in depths 5, 10, 20 and 50 meters), sediment samples were gathered in 6 months (2012). Environmental factors of water near the bottom including temperature, salinity, dissolved oxygen and pH were measured during sampling with CTD and grain size and total organic matter percentage and calcium carbonate were measured in laboratory. In different months, the average water temperature (9.52-23.93), dissolved oxygen (7.71-10.53 mg/L), salinity (10.57±0/07 and 10.75±0/04 ppt), pH (7.44±0/29 and 7.41±0/22), EC (17.97±0/12 and 18.30±0/04μs/cm2), TDS (8.92±0/04 and 9.14±0/02 mg/L), total organic matter (5.83±1/43 and 6.25±0/97%) and calcium carbonate (2.36±0/36 and 1.68±0/19%) were measured respectively. Structure of the sediment samples mostly consisted of fine sand; very fine sand, silt and clay. From the 4 group animals (Foraminifera, Crustacea, Worms and Mollusca), there were identified 40species belong to 29 genera of 25 families. The cosmopolitan foraminifer, Ammonia beccarii caspica, was common in all sampling stations. Result showed that depth was important factor on distribution of meiofauna. Most density of foraminifera and crustacean was observed in depth of 20m and for mollusca and worms observed in 5m. Shannon diversity index decreased with depth that showed in shallow water diversity was higher than deep water. Mean of maximum and minimum Shannon index was obsorvers in depth of 5m and 50 m that was measured in order 0.93 and 0.43. Account of Shannon index showed that this area is under pressure. Account of peioleo index showed distribution in this area was not steady.

Ecological drivers of a vector borne pathogen: distribution and abundance of Borrelia burgdorferi sensu lato and its vector Ixodes ricinus in Scotland

Vector-borne disease emergence in recent decades has been associated with different environmental drivers including changes in habitat, hosts and climate. Lyme borreliosis is among the most important vector-borne diseases in the Northern hemisphere and is an emerging disease in Scotland. Transmitted by Ixodid tick vectors between large numbers of wild vertebrate host species, Lyme borreliosis is caused by bacteria from the Borrelia burgdorferi sensu lato species group. Ecological studies can inform how environmental factors such as host abundance and community composition, habitat and landscape heterogeneity contribute to spatial and temporal variation in risk from B. burgdorferi s.l. In this thesis a range of approaches were used to investigate the effects of vertebrate host communities and individual host species as drivers of B. burgdorferi s.l. dynamics and its tick vector Ixodes ricinus. Host species differ in reservoir competence for B. burgdorferi s.l. and as hosts for ticks. Deer are incompetent transmission hosts for B. burgdorferi s.l. but are significant hosts of all life-stages of I. ricinus. Rodents and birds are important transmission hosts of B. burgdorferi s.l. and common hosts of immature life-stages of I. ricinus. In this thesis, surveys of woodland sites revealed variable effects of deer density on B. burgdorferi prevalence, from no effect (Chapter 2) to a possible ‘dilution’ effect resulting in lower prevalence at higher deer densities (Chapter 3). An invasive species in Scotland, the grey squirrel (Sciurus carolinensis), was found to host diverse genotypes of B. burgdorferi s.l. and may act as a spill-over host for strains maintained by native host species (Chapter 4). Habitat fragmentation may alter the dynamics of B. burgdorferi s.l. via effects on the host community and host movements. In this thesis, there was lack of persistence of the rodent associated genospecies of B. burgdorferi s.l. within a naturally fragmented landscape (Chapter 3). Rodent host biology, particularly population cycles and dispersal ability are likely to affect pathogen persistence and recolonization in fragmented habitats. Heterogeneity in disease dynamics can occur spatially and temporally due to differences in the host community, habitat and climatic factors. Higher numbers of I. ricinus nymphs, and a higher probability of detecting a nymph infected with B. burgdorferi s.l., were found in areas with warmer climates estimated by growing degree days (Chapter 2). The ground vegetation type associated with the highest number of I. ricinus nymphs varied between studies in this thesis (Chapter 2 & 3) and does not appear to be a reliable predictor across large areas. B. burgdorferi s.l. prevalence and genospecies composition was highly variable for the same sites sampled in subsequent years (Chapter 2). This suggests that dynamic variables such as reservoir host densities and deer should be measured as well as more static habitat and climatic factors to understand the drivers of B. burgdorferi s.l. infection in ticks. Heterogeneity in parasite loads amongst hosts is a common finding which has implications for disease ecology and management. Using a 17-year data set for tick infestations in a wild bird community in Scotland, different effects of age and sex on tick burdens were found among four species of passerine bird (Chapter 5). There were also different rates of decline in tick burdens among bird species in response to a long term decrease in questing tick pressure over the study. Species specific patterns may be driven by differences in behaviour and immunity and highlight the importance of comparative approaches. Combining whole genome sequencing (WGS) and population genetics approaches offers a novel approach to identify ecological drivers of pathogen populations. An initial analysis of WGS from B. burgdorferi s.s. isolates sampled 16 years apart suggests that there is a signal of measurable evolution (Chapter 6). This suggests demographic analyses may be applied to understand ecological and evolutionary processes of these bacteria. This work shows how host communities, habitat and climatic factors can affect the local transmission dynamics of B. burgdorferi s.l. and the potential risk of infection to humans. Spatial and temporal heterogeneity in pathogen dynamics poses challenges for the prediction of risk. New tools such as WGS of the pathogen (Chapter 6) and blood meal analysis techniques will add power to future studies on the ecology and evolution of B. burgdorferi s.l.

Protein quality and distribution determines anabolic signaling, cellular energetics, and body composition

Building and maintaining muscle is critical to the quality of life for adults and elderly. Physical activity and nutrition are important factors for long-term muscle health. In particular, dietary protein – including protein distribution and quality – are under-appreciated determinants of muscle health for adults. The most unequivocal evidence for the benefit of optimal dietary protein at individual meals is derived from studies of weight management. During the catabolic condition of weight loss, higher protein diets attenuate loss of lean tissue and partition weight loss to body fat when compared with commonly recommended high carbohydrate, low protein diets. Muscle protein turnover is a continuous process in which proteins are degraded, and replaced by newly synthesized proteins. Muscle growth occurs when protein synthesis exceeds protein degradation. Regulation of protein synthesis is complex, with multiple signals influencing this process. The mammalian target of rapamycin (mTORC1) pathway has been identified as a particularly important regulator of protein synthesis, via stimulation of translation initiation. Key regulatory points of translation initiation effected by mTORC1 include assembly of the eukaryotic initiation factor 4F (eIF4F) complex and phosphorylation of the 70 kilodalton ribosomal protein S6 kinase (S6K1). Assembly of the eIF4F initiation complex involves phosphorylation of the inhibitory eIF4E binding protein-1 (4E-BP1), which releases the initiation factor eIF4E and allows it to bind with eIF4G. Binding of eIF4E with eIF4G promotes preparation of the mRNA for binding to the 43S pre-initiation complex. Consumption of the amino acid leucine (Leu) is a key factor determining the anabolic response of muscle protein synthesis (MPS) and mTORC1 signaling to a meal. Research from this dissertation demonstrates that the peak activation of MPS following a complete meal is proportional to the Leu content of a meal and its ability to elevate plasma Leu. Leu has also been implicated as an inhibitor of muscle protein degradation (MPD). In particular, there is evidence suggesting that in muscle wasting conditions Leu supplementation attenuates expression of the ubiquitin-proteosome pathway, which is the primary mode of intracellular protein degradation. However, this is untested in healthy, physiological feeding models. Therefore, an experiment was performed to see if feeding isonitrogenous protein sources with different Leu contents to healthy adult rats would differentially impact ubiquitin-proteosome (protein degradation) outcomes; and if these outcomes are related to the meal responses of plasma Leu. Results showed that higher Leu diets were able to attenuate total proteasome content but had no effect on ubiquitin proteins. This research shows that dietary Leu determines postprandial muscle anabolism. In a parallel line of research, the effects of dietary Leu on changes in muscle mass overtime were investigated. Animals consuming higher Leu diets had larger gastrocnemius muscle weights; furthermore, gastrocnemius muscle weights were correlated with postprandial changes in MPS (r=0.471, P<0.01) and plasma Leu (r=0.400, P=0.01). These results show that the effect of Leu on ubiquitin-proteosome pathways is minimal for healthy adult rats consuming adequate diets. Thus, long-term changes in muscle mass observed in adult rats are likely due to the differences in MPS, rather than MPD. Factors determining the duration of Leu-stimulated MPS were further investigated. Despite continued elevations in plasma Leu and associated translation initiation factors (e.g., S6K1 and 4E-BP1), MPS returned to basal levels ~3 hours after a meal. However, administration of additional nutrients in the form of carbohydrate, Leu, or both ~2 hours after a meal was able to extend the elevation of MPS, in a time and dose dependent manner. This effect led to a novel discovery that decreases in translation elongation activity was associated with increases in activity of AMP kinase, a key cellular energy sensor. This research shows that the Leu density of dietary protein determines anabolic signaling, thereby affecting cellular energetics and body composition.

Sea otter predation and the distribution of bivalve prey in the Elkhorn Slough National Estuarine Research Reserve

The California sea otter population is gradually expanding in size and geographic range and is consequently invading new feeding grounds, including bays and estuaries that are home to extensive populations of bivalve prey. One such area is the Elkhorn Slough, where otters have apparently established a spring and summer communal feeding and resting area. In anticipation of future otter foraging in the slough, an extensive baseline database on bivalve densities, size distributions, biomasses, and burrow depths has been established for three potential bivalve prey species, Saxidomus nuttalli, Tresus nutallii, and Zirphaea pilsbryi. In 1986, the Elkhorn Slough otters were foraging predominately at two areas immediately east and west of the Highway 1 bridge (Skipper's and the PG&E Outfall). Extensive subtidal populations of Saxidomus nuttalli and Tresus nuttallii occur in these areas. Shell records collected at these study areas indicated that sea otters were foraging selectively on Saxidomus over Tresus. The reason for this apparent preference was not clear. At the Skipper's study site, 51% of the shell record was composed of Saxidomus, yet this species accounted for only 16% of the in situ biomass, and only 39% of the available clams. Tresus represented 49% of the shell record at Skipper's, yet this species accounted for 84% of the in situ biomass and 61% of the available clams. There was no difference in mean burrow depth between the two species at this site so availability does not explain the disparity in consumption. At the PG&E Outfall, Saxidomus represents 66% of the in situ biomass and 81% of the available clams, while Tresus accounts for 34% of the in situ biomass and 19% of the available clams. Saxidomus accounts for 96% of the shell record at this site vs. 4% for Tresus, again indicating that the otters were preying on Saxidomus out of proportion to their density or biomass. High densities and biomasses of a third species, Zirphaea pilsbryi, occur in areas where sea otters were observed to be foraging, yet no cast-off Zirphaea shells were found. Although it is possible this species was not represented in the shell record because the otters were simply chewing up the shells, it is more likely this species is avoided by sea otters. There were relatively few sea otters in the Elkhorn Slough in 1986 compared to the previous two years. This, coupled with high bivalve densities, precluded any quantitative comparison of bivalve densities before and after the 1986 sea otter occupation. Qualitative observations made during the course of this study, and quantitative observations from previous studies indicate that, after 3 years, sea otters are not yet significantly affecting bivalve densities in the Elkhorn Slough.

On the stability and spatiotemporal variance distribution of salinity in the upper ocean

Despite recent advances in ocean observing arrays and satellite sensors, there remains great uncertainty in the large-scale spatial variations of upper ocean salinity on the interannual to decadal timescales. Consonant with both broad-scale surface warming and the amplification of the global hydrological cycle, observed global multidecadal salinity changes typically have focussed on the linear response to anthropogenic forcing but not on salinity variations due to changes in the static stability and or variability due to the intrinsic ocean or internal climate processes. Here, we examine the static stability and spatiotemporal variability of upper ocean salinity across a hierarchy of models and reanalyses. In particular, we partition the variance into time bands via application of singular spectral analysis, considering sea surface salinity (SSS), the Brunt Väisälä frequency (N2), and the ocean salinity stratification in terms of the stabilizing effect due to the haline part of N2 over the upper 500m. We identify regions of significant coherent SSS variability, either intrinsic to the ocean or in response to the interannually varying atmosphere. Based on consistency across models (CMIP5 and forced experiments) and reanalyses, we identify the stabilizing role of salinity in the tropics—typically associated with heavy precipitation and barrier layer formation, and the role of salinity in destabilizing upper ocean stratification in the subtropical regions where large-scale density compensation typically occurs.