Magnitude and distribution of sea turtle bycatch in the sea scallop (Placopecten magellanicus) dredge fishery in two areas of the northwestern Atlantic Ocean, 2001–2002

In May 2001, the National Marine Fisheries Service (NMFS) opened two areas in the northwestern Atlantic Ocean that had been previously closed to the U.S. sea scallop (Placopecten magellanicus) dredge fishery. Upon reopening these areas, termed the “Hudson Canyon Controlled Access Area” and the “Virginia Beach Controlled Access Area,” NMFS observers found that marine turtles were being caught incidentally in scallop dredges. This study uses the generalized linear model and the generalized additive model fitting techniques to identify environmental factors and gear characteristics that influence bycatch rates, and to predict total bycatch in these two areas during May-December 2001 and 2002 by incorporating environmental factors into the models. Significant factors affecting sea turtle bycatch were season, time-of-day, sea surface temperature, and depth zone. In estimating total bycatch, rates were stratified according to a combination of all these factors except time-of-day which was not available in fishing logbooks. Highest bycatch rates occurred during the summer season, in temperatures greater than 19°C, and in water depths from 49 to 57 m. Total estimated bycatch of sea turtles during May–December in 2001 and 2002 in both areas combined was 169 animals (CV=55.3), of which 164 (97%) animals were caught in the Hudson Canyon area. From these findings, it may be possible to predict hot spots for sea turtle bycatch in future years in the controlled access areas.

Batho-spatial distribution pattern and biomass estimate of the major demersal fishes in Lake Victoria

A generalized bottom trawl exploratory survey was carried out on Lake Victoria to: (i) define the distributional pattern and magnitude of the lakewide demersal stocks, (ii) determine the commercial potential of Haplochromis spp. and (iii) evaluate trawling as a commercial fishing technique for Lake Victoria fisheries. Preliminary results suggest that: (i) bottom trawl catches are more representative of the stocks, (ii) species diversification and fish density decrease with increasing mean depth and (iii) at least 80%of the catchable demersal ichthyomass is Haplochromis. Though bottom trawling is a much more efficient fishing technique for the Lake Victoria fisheries, bio-socio-economic consideration impose that mechanization of the fishery should better proceed in graded steps. Besides demographic and nutritional considerations indicate the necessity for rational management and increased direct human utilization of the fishery resource.

Elemental estimators for the Generalized Extreme Value tail

In a companion paper (McRobie(2013) arxiv:1304.3918), a simple set of `elemental' estimators was presented for the Generalized Pareto tail parameter. Each elemental estimator: involves only three log-spacings; is absolutely unbiased for all values of the tail parameter; is location- and scale-invariant; and is valid for all sample sizes $N$, even as small as $N= 3$. It was suggested that linear combinations of such elementals could then be used to construct efficient unbiased estimators. In this paper, the analogous mathematical approach is taken to the Generalised Extreme Value (GEV) distribution. The resulting elemental estimators, although not absolutely unbiased, are found to have very small bias, and may thus provide a useful basis for the construction of efficient estimators.

Generalized sampling using a compound-eye imaging system for multi-dimensional object acquisition.

In this paper, we propose generalized sampling approaches for measuring a multi-dimensional object using a compact compound-eye imaging system called thin observation module by bound optics (TOMBO). This paper shows the proposed system model, physical examples, and simulations to verify TOMBO imaging using generalized sampling. In the system, an object is modulated and multiplied by a weight distribution with physical coding, and the coded optical signal is integrated on to a detector array. A numerical estimation algorithm employing a sparsity constraint is used for object reconstruction.

Generalized Markov branching processes

A generalized Markov Brnching Process (GMBP) is a Markov branching model where the infinitesimal branching rates are modified with an interaction index. It is proved that there always exists only one GMBP. An associated differential-integral equation is derived. The extinction probalility and the mean and conditional mean extinction times are obtained. Ergodicity and stability of GMBP with resurrection are also considered. Easy checking criteria are established for ordinary and strong ergodicty. The equilibrium distribution is given in an elegant closed form. The probability meaning of our results is clear and thus explained.

Tree diameter distribution modelling: introducing the logitlogistic distribution

Johnson's SB distribution is a four-parameter distribution that is transformed into a normal distribution by a logit transformation. By replacing the normal distribution of Johnson's SB with the logistic distribution, we obtain a new distributional model that approximates SB. It is analytically tractable, and we name it the "logitlogistic" (LL) distribution. A generalized four-parameter Weibull model and the Burr XII model are also introduced for comparison purposes. Using the distribution "shape plane" (with axes skew and kurtosis) we compare the "coverage" properties of the LL, the generalized Weibull, and the Burr XII with Johnson's SB, the beta, and the three-parameter Weibull, the main distributions used in forest modelling. The LL is found to have the largest range of shapes. An empirical case study of the distributional models is conducted on 107 sample plots of Chinese fir. The LL performs best among the four-parameter models.

Effects of environmental conditions on the seasonal distribution of phytoplankton biomass in the North Sea

We study the spatial and seasonal variability of phytoplankton biomass (as phytoplankton color) in relation to the environmental conditions in the North Sea using data from the Continuous Plankton Recorder survey. By using only environmental fields and location as predictor variables we developed a nonparametric model (generalized additive model) to empirically explore how key environmental factors modulate the spatio-temporal patterns of the seasonal cycle of algal biomass as well as how these relate to the ,1988 North Sea regime shift. Solar radiation, as manifest through changes of sea surface temperature (SST), was a key factor not only in the seasonal cycle but also as a driver of the shift. The pronounced increase in SST and in wind speed after the 1980s resulted in an extension of the season favorable for phytoplankton growth. Nutrients appeared to be unimportant as explanatory variables for the observed spatio-temporal pattern, implying that they were not generally limiting factors. Under the new climatic regime the carrying capacity of the whole system has been increased and the southern North Sea, where the environmental changes have been more pronounced, reached a new maximum.

Applying species distribution modelling to identify areas of high conservation value for endangered species: A case study using Margaritifera margaritifera (L.)

The development and implementation of a population supplementation and restoration plan for any endangered species should involve an understanding of the species’ habitat requirements prior to the release of any captive bred individuals. The freshwater pearl mussel, Margaritifera margaritifera, has undergone dramatic declines over the last century and is now globally endangered. In Northern Ireland, the release of captive bred individuals is being used to support wild populations and repatriate the species in areas where it once existed. We employed a combination of maximum entropy modelling (MAXENT) and Generalized Linear Mixed Models (GLMM) to identify ecological parameters necessary to support wild populations using GIS-based landscape scale and ground-truthed habitat scale environmental parameters. The GIS-based landscape scale model suggested that mussel occurrence was associated with altitude and soil characteristics including the carbon, clay, sand, and silt content. Notably, mussels were associated with a relatively narrow band of variance indicating that M. margaritifera has a highly specific landscape niche. The ground-truthed habitat scale model suggested that mussel occurrence was associated with stable consolidated substrates, the extent of bankside trees, presence of indicative macrophyte species and fast flowing water. We propose a three phase conservation strategy for M. margaritifera identifying suitable areas within rivers that (i) have a high conservation value yet needing habitat restoration at a local level, (ii) sites for population supplementation of existing populations and (iii) sites for species reintroduction to rivers where the mussel historically occurred but is now locally extinct. A combined analytical approach including GIS-based landscape scale and ground-truthed habitat scale models provides a robust method by which suitable release sites can be identified for the population supplementation and restoration of an endangered species. Our results will be highly influential in the future management of M. margaritifera in Northern Ireland.

Role of Predalors, Habitat Attributes, and Spatial Autocorrelation on the Distribution of Eggs in the Northern Spectacled Salamander (Salamandrina perspicillata)

We predicted that the probability of egg occurrence of salamander Salamandrina perspicillata depended on stream features and predation by native crayfish Austropotamobius fulcisianus and the introduced trout Salmo trutta. We assessed the presence of S. perspicillata at 54 sites within a natural reserve of southern Tuscany, Italy. Generalized linear models with binomial errors were constructed using egg presence/absence and altitude, stream mean size and slope, electrical conductivity, water pH and temperature, and a predation factor, defined according to the presence/absence of crayfish and trout. Some competing models also included an autocovariate term, which estimated how much the response variable at any one sampling point reflected response values at surrounding points. The resulting models were compared using Akaike's information criterion. Model selection led to a subset of 14 models with Delta AIC(c) <7 (i.e., models ranging from substantial support to considerably less support), and all but one of these included an effect of predation. Models with the autocovariate term had considerably more support than those without the term. According to multimodel inference, the presence of trout and crayfish reduced the probability of egg occurrence from a mean level of 0.90 (SE limits: 0.98-0.55) to 0.12 (SE limits: 0.34-0.04). The presence of crayfish alone had no detectable effects (SE limits: 0.86-0.39). The results suggest that introduced trout have a detrimental effect on the reproductive output of S. perspicillata and confirm the fundamental importance of distinguishing the roles of endogenous and exogenous forces that act on population distribution.

Large-scale spatial patterns in the distribution of Collembola (Hexapoda) species in Antarctic terrestrial ecosystems

We tested whether the distribution of three common springtail species (Gressittacantha terranova, Gomphiocephalus hodgsoni and Friesea grisea) in Victoria Land (Antarctica) could be modelled as a function of latitude, longitude, altitude and distance from the sea.

Victoria Land, Ross Dependency, Antarctica.

Generalized linear models were constructed using species presence/absence data relative to geographical features (latitude, longitude, altitude, distance from sea) across the species' entire ranges. Model results were then integrated with the known phylogeography of each species and hypotheses were generated on the role of climate as a major driver of Antarctic springtail distribution.

Based on model selection using Akaike's information criterion, the species' distributions were: hump-shaped relative to longitude and monotonic with altitude for Gressittacantha terranova; hump-shaped relative to latitude and monotonic with altitude for Gomphiocephalus hodgsoni; and hump-shaped relative to longitude and monotonic with latitude, altitude and distance from the sea for Friesea grisea.

No single distributional pattern was shared by the three species. While distributions were partially a response to climatic spatial clines, the patterns observed strongly suggest that past geological events have influenced the observed distributions. Accordingly, present-day spatial patterns are likely to have arisen from the interaction of historical and environmental drivers. Future studies will need to integrate a range of spatial and temporal scales to further quantify their respective roles.

Generalized Selection Combining for Cognitive Relay Networks over Nakagami-m Fading

We consider transmit antenna selection with receive generalized selection combining (TAS/GSC) for cognitive decodeand-forward (DF) relaying in Nakagami-m fading channels. In an effort to assess the performance, the probability density function and the cumulative distribution function of the endto-end SNR are derived using the moment generating function, from which new exact closed-form expressions for the outage probability and the symbol error rate are derived. We then derive a new closed-form expression for the ergodic capacity. More importantly, by deriving the asymptotic expressions for the outage probability and the symbol error rate, as well as the high SNR approximations of the ergodic capacity, we establish new design insights under the two distinct constraint scenarios: 1) proportional interference power constraint, and 2) fixed interference power constraint. Several pivotal conclusions are reached. For the first scenario, the full diversity order of the
outage probability and the symbol error rate is achieved, and the high SNR slope of the ergodic capacity is 1/2. For the second scenario, the diversity order of the outage probability and the symbol error rate is zero with error floors, and the high SNR slope of the ergodic capacity is zero with capacity ceiling.

Applications of the generalized Langevin equation: Towards a realistic description of the baths

The generalized Langevin equation (GLE) method, as developed previously [L. Stella et al., Phys. Rev. B 89, 134303 (2014)], is used to calculate the dissipative dynamics of systems described at the atomic level. The GLE scheme goes beyond the commonly used bilinear coupling between the central system and the bath, and permits us to have a realistic description of both the dissipative central system and its surrounding bath. We show how to obtain the vibrational properties of a realistic bath and how to convey such properties into an extended Langevin dynamics by the use of the mapping of the bath vibrational properties onto a set of auxiliary variables. Our calculations for a model of a Lennard-Jones solid show that our GLE scheme provides a stable dynamics, with the dissipative/relaxation processes properly described. The total kinetic energy of the central system always thermalizes toward the expected bath temperature, with appropriate fluctuation around the mean value. More importantly, we obtain a velocity distribution for the individual atoms in the central system which follows the expected canonical distribution at the corresponding temperature. This confirms that both our GLE scheme and our mapping procedure onto an extended Langevin dynamics provide the correct thermostat. We also examined the velocity autocorrelation functions and compare our results with more conventional Langevin dynamics.

Temporal distribution of the short-beaked common dolphin (Delphinus delphis) in the south of Madeira Island (Portugal) and relationship with oceanographic variables

Dissertação de mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

Generalized Systematic Risk

We generalize the concept of .systematic risk to a broad class of risk measures potentially accounting for high distribution moments, downside risk, rare disasters, as well as other risk attributes. We offer two different approaches. First is an equilibrium framework generalizing the Capital Asset Pricing Model, two-fund separation, and the security market line. Second is an axiomatic approach resulting in a systematic risk measure as the unique solution to a risk allocation problem. Both approaches lead to similar results extending the traditional beta to capture multiple dimensions of risk. The results lend themselves naturally to empirical investigation.

Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique

This paper presents a new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach. The objective minimizes power losses, balancing load among feeders and subject to constraints: capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages and radial optimal operation of networks. The Generalized Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages; the first one is the Master problem and is formulated as a mixed integer non-linear programming problem. This stage determines the radial topology of the distribution network. The second stage is the Slave problem and is formulated as a non-linear programming problem. This stage is used to determine the feasibility of the Master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in GAMS. The effectiveness of the proposal is demonstrated through two examples extracted from the literature.