A trait-based metric sheds new light on the nature of the body size-depth relationship in the deep sea

Summary 1. Variation within species is an often-overlooked aspect of community ecology, despite the fact that the ontogenetic structure of populations influences processes right up to the ecosystem level. Accounting for traits at the individual level is an important advance in the implementation of trait-based approaches in understanding community structure and function. 2. We incorporate individual- and species-level traits into one succinct assemblage structure metric, fractional size, which is calculated as the length of an individual divided by its potential maximum length. We test the implementation of fractional size in demersal fish assemblages along a depth gradient in the deep sea. We use data from an extensive trawl survey at depths of 300–2030 m on the continental slope of the Rockall Trough, Northeast Atlantic, to compare changes in fractional size structure along an environmental gradient to those seen using traditional taxonomic and trait-based approaches. 3. The relationship between fractional size and depth was particularly strong, with the overall pattern being an increase with depth, implying that individuals move deeper as they grow. Body size increased with depth at the intraspecific and assemblage levels. Fractional size, size structure and species composition all varied among assemblages, and this variation could be explained by the depth that the assemblage occupied. 4. The inclusion of individual-level traits and population fractional size structure adds to our understanding at the assemblage level. Fractional size, or where an individual is in its growth trajectory, appears to be an especially important driver of assemblage change with depth. This has implications for understanding fisheries impacts in the deep sea and how these impacts may propagate across depths

Using an integral projection model to assess the effect of temperature on the growth of gilthead seabream Sparus aurata

Accurate information on the growth rates of fish is crucial for fisheries stock assessment and management. Empirical life history parameters (von Bertalanffy growth) are widely fitted to cross-sectional size-at-age data sampled from fish populations. This method often assumes that environmental factors affecting growth remain constant over time. The current study utilized longitudinal life history information contained in otoliths from 412 juveniles and adults of gilthead seabream, Sparus aurata, a commercially important species fished and farmed throughout the Mediterranean. Historical annual growth rates over 11 consecutive years (2002-2012) in the Gulf of Lions (NW Mediterranean) were reconstructed to investigate the effect of temperature variations on the annual growth of this fish. S. aurata growth was modelled linearly as the relationship between otolith size at year t against otolith size at the previous year t-1. The effect of temperature on growth was modelled with linear mixed effects models and a simplified linear model to be implemented in a cohort Integral Projection Model (cIPM). The cIPM was used to project S. aurata growth, year to year, under different temperature scenarios. Our results determined current increasing summer temperatures to have a negative effect on S. aurata annual growth in the Gulf of Lions. They suggest that global warming already has and will further have a significant impact on S. aurata size-at-age, with important implications for age-structured stock assessments and reference points used in fisheries

A unified approach to combinatorial key predistribution schemes for sensor networks

There have been numerous recent proposals for key predistribution schemes for wireless sensor networks based on various types of combinatorial structures such as designs and codes. Many of these schemes have very similar properties and are analysed in a similar manner. We seek to provide a unified framework to study these kinds of schemes. To do so, we define a new, general class of designs, termed “partially balanced t-designs”, that is sufficiently general that it encompasses almost all of the designs that have been proposed for combinatorial key predistribution schemes. However, this new class of designs still has sufficient structure that we are able to derive general formulas for the metrics of the resulting key predistribution schemes. These metrics can be evaluated for a particular scheme simply by substituting appropriate parameters of the underlying combinatorial structure into our general formulas. We also compare various classes of schemes based on different designs, and point out that some existing proposed schemes are in fact identical, even though their descriptions may seem different. We believe that our general framework should facilitate the analysis of proposals for combinatorial key predistribution schemes and their comparison with existing schemes, and also allow researchers to easily evaluate which scheme or schemes present the best combination of performance metrics for a given application scenario

Quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques

To understand changes in ecosystems, the appropriate scale at which to study them must be determined. Large marine ecosystems (LMEs) cover thousands of square kilometres and are a useful classification scheme for ecosystem monitoring and assessment. However, averaging across LMEs may obscure intricate dynamics within. The purpose of this study is to mathematically determine local and regional patterns of ecological change within an LME using empirical orthogonal functions (EOFs). After using EOFs to define regions with distinct patterns of change, a statistical model originating from control theory is applied (Nonlinear AutoRegressive Moving Average with eXogenous input – NARMAX) to assess potential drivers of change within these regions. We have selected spatial data sets (0.5° latitude × 1°longitude) of fish abundance from North Sea fisheries research surveys (spanning 1980–2008) as well as of temperature, oxygen, net primary production and a fishing pressure proxy, to which we apply the EOF and NARMAX methods. Two regions showed significant changes since 1980: the central North Sea displayed a decrease in community size structure which the NARMAX model suggested was linked to changes in fishing; and the Norwegian trench region displayed an increase in community size structure which, as indicated by NARMAX results, was primarily linked to changes in sea-bottom temperature. These regions were compared to an area of no change along the eastern Scottish coast where the model determined the community size structure was most strongly associated to net primary production. This study highlights the multifaceted effects of environmental change and fishing pressures in different regions of the North Sea. Furthermore, by highlighting this spatial heterogeneity in community size structure change, important local spatial dynamics are often overlooked when the North Sea is considered as a broad-scale, homogeneous ecosystem (as normally is the case within the political Marine Strategy Framework Directive)

Supramolecular interactions in clusters of polar and polarizable molecules

We present a model for molecular materials made up of polar and polarizable molecular units. A simple two state model is adopted for each molecular site and only classical intermolecular interactions are accounted for, neglecting any intermolecular overlap. The complex and interesting physics driven by interactions among polar and polarizable molecules becomes fairly transparent in the adopted model. Collective effects are recognized in the large variation of the molecular polarity with supramolecular interactions, and cooperative behavior shows up with the appearance, in attractive lattices, of discontinuous charge crossovers. The mean-field approximation proves fairly accurate in the description of the gs properties of MM, including static linear and non-linear optical susceptibilities, apart from the region in the close proximity of the discontinuous charge crossover. Sizeable deviations from the excitonic description are recognized both in the excitation spectrum and in linear and non-linear optical responses. New and interesting phenomena are recognized near the discontinuous charge crossover for non-centrosymmetric clusters, where the primary photoexcitation event corresponds to a multielectron transfer.Comment: 14 pages, including 11 figure

A jump-growth model for predator-prey dynamics: derivation and application to marine ecosystems

This paper investigates the dynamics of biomass in a marine ecosystem. A stochastic process is defined in which organisms undergo jumps in body size as they catch and eat smaller organisms. Using a systematic expansion of the master equation, we derive a deterministic equation for the macroscopic dynamics, which we call the deterministic jump-growth equation, and a linear Fokker-Planck equation for the stochastic fluctuations. The McKendrick--von Foerster equation, used in previous studies, is shown to be a first-order approximation, appropriate in equilibrium systems where predators are much larger than their prey. The model has a power-law steady state consistent with the approximate constancy of mass density in logarithmic intervals of body mass often observed in marine ecosystems. The behaviours of the stochastic process, the deterministic jump-growth equation and the McKendrick--von Foerster equation are compared using numerical methods. The numerical analysis shows two classes of attractors: steady states and travelling waves.Comment: 27 pages, 4 figures. Final version as published. Only minor change

Current cosmological bounds on neutrino masses and relativistic relics

We combine the most recent observations of large-scale structure (2dF and SDSS galaxy surveys) and cosmic microwave anisotropies (WMAP and ACBAR) to put constraints on flat cosmological models where the number of massive neutrinos and of massless relativistic relics are both left arbitrary. We discuss the impact of each dataset and of various priors on our bounds. For the standard case of three thermalized neutrinos, we find an upper bound on the total neutrino mass sum m_nu < 1.0 (resp. 0.6) eV (at 2sigma), using only CMB and LSS data (resp. including priors from supernovae data and the HST Key Project), a bound that is quite insensitive to the splitting of the total mass between the three species. When the total number of neutrinos or relativistic relics N_eff is left free, the upper bound on sum m_nu (at 2sigma, including all priors) ranges from 1.0 to 1.5 eV depending on the mass splitting. We provide an explanation of the parameter degeneracy that allows larger values of the masses when N_eff increases. Finally, we show that the limit on the total neutrino mass is not significantly modified in the presence of primordial gravitational waves, because current data provide a clear distinction between the corresponding effects.Comment: 13 pages, 6 figure

Dark energy as a mirage

Motivated by the observed cosmic matter distribution, we present the following conjecture: due to the formation of voids and opaque structures, the average matter density on the path of the light from the well-observed objects changes from Omega_M ~ 1 in the homogeneous early universe to Omega_M ~ 0 in the clumpy late universe, so that the average expansion rate increases along our line of sight from EdS expansion Ht ~ 2/3 at high redshifts to free expansion Ht ~ 1 at low redshifts. To calculate the modified observable distance-redshift relations, we introduce a generalized Dyer-Roeder method that allows for two crucial physical properties of the universe: inhomogeneities in the expansion rate and the growth of the nonlinear structures. By treating the transition redshift to the void-dominated era as a free parameter, we find a phenomenological fit to the observations from the CMB anisotropy, the position of the baryon oscillation peak, the magnitude-redshift relations of type Ia supernovae, the local Hubble flow and the nucleosynthesis, resulting in a concordant model of the universe with 90% dark matter, 10% baryons, no dark energy, 15 Gyr as the age of the universe and a natural value for the transition redshift z_0=0.35. Unlike a large local void, the model respects the cosmological principle, further offering an explanation for the late onset of the perceived acceleration as a consequence of the forming nonlinear structures. Additional tests, such as quantitative predictions for angular deviations due to an anisotropic void distribution and a theoretical derivation of the model, can vindicate or falsify the interpretation that light propagation in voids is responsible for the perceived acceleration.Comment: 33 pages, 2 figs; v2: minor clarifications, results unchanged; v3: matches the version published in General Relativity and Gravitatio

A general framework for combining ecosystem models

When making predictions about ecosystems, we often have available a number of different ecosystem models that attempt to represent their dynamics in a detailed mechanistic way. Each of these can be used as a simulator of large-scale experiments and make projections about the fate of ecosystems under different scenarios to support the development of appropriate management strategies. However, structural differences, systematic discrepancies and uncertainties lead to different models giving different predictions. This is further complicated by the fact that the models may not be run with the same functional groups, spatial structure or time scale. Rather than simply trying to select a “best” model, or taking some weighted average, it is important to exploit the strengths of each of the models, while learning from the differences between them. To achieve this, we construct a flexible statistical model of the relationships between a collection of mechanistic models and their biases, allowing for structural and parameter uncertainty and for different ways of representing reality. Using this statistical meta-model, we can combine prior beliefs, model estimates and direct observations using Bayesian methods and make coherent predictions of future outcomes under different scenarios with robust measures of uncertainty. In this study, we take a diverse ensemble of existing North Sea ecosystem models and demonstrate the utility of our framework by applying it to answer the question what would have happened to demersal fish if fishing was to stop