The predicting power of models for eutrophication

Restoration of water-bodies from eutrophication has proved to be extremely difficult. Mathematical models have been used extensively to provide guidance for management decisions. The aim of this paper is to elucidate important problems of using models for predicting environmental changes. First, the necessity for a proper uncertainty assessment of the model, upon calibration, has not been widely recognized. Predictions must not be a single time trajectory; they should be a band, expressing system uncertainty and natural variability. Availability of this information may alter the decision to be taken. Second, even with well-calibrated models, there is no guarantee they will give correct projections in situations where the model is used to predict the effects of measures designed to bring the system into an entirely different ”operating point”, as is typically the case in eutrophication abatement. The concept of educated speculation is introduced to partially overcome this difficulty. Lake Veluwe is used as a case to illustrate the point. Third, as questions become more detailed, such as ”what about expected algal composition”, there is a greater probability of running into fundamental problems that are associated with predicting the behaviour of complex non-linear systems. Some of these systems show extreme initial condition sensitivity and even, perhaps, chaotic behaviour, and are therefore fundamentally unpredictable.

Structural dynamic eutrophication models

This article discusses problems of modelling the seasonal succession of algal species in lakes and reservoirs, and the adaptive selection of certain groups of algae in response to changes in the inputs and relative concentrations of nutrients and other environmental variables. A new generation of quantitative models is being developed which attempts to translate some important biological properties of species (survival, variation, inheritance, reproductive rates and population growth) into predictions about the survival of the fittest, where ”fitness” is measured or estimated in thermodynamic terms. The concept of ”exergy” and its calculation is explored to examine maximal exergy as a measure of fitness in ecosystems, and its use for calculating changes in species composition by means of structural dynamic models. These models accomodate short-term changes in parameters that affect the adaptive responses (species selection) of algae.

Proton magnetic resonance studies of ribonucleic acid complexes. I. Complexes of biological bases and oligonucleotides with RNA. II. Template recognition and the degeneracy of the genetic code

Part I. Complexes of Biological Bases and Oligonucleotides with RNA

The physical nature of complexes of several biological bases and oligonucleotides with single-stranded ribonucleic acids have been studied by high resolution proton magnetic resonance spectroscopy. The importance of various forces in the stabilization of these complexes is also discussed.

Previous work has shown that purine forms an intercalated complex with single-stranded nucleic acids. This complex formation led to severe and stereospecific broadening of the purine resonances. From the field dependence of the linewidths, T₁ measurements of the purine protons and nuclear Overhauser enhancement experiments, the mechanism for the line broadening was ascertained to be dipole-dipole interactions between the purine protons and the ribose protons of the nucleic acid.

The interactions of ethidium bromide (EB) with several RNA residues have been studied. EB forms vertically stacked aggregates with itself as well as with uridine, 3'-uridine monophosphate and 5'-uridine monophosphate and forms an intercalated complex with uridylyl (3' → 5') uridine and polyuridylic acid (poly U). The geometry of EB in the intercalated complex has also been determined.

The effect of chain length of oligo-A-nucleotides on their mode of interaction with poly U in D₂0 at neutral pD have also been studied. Below room temperatures, ApA and ApApA form a rigid triple-stranded complex involving a stoichiometry of one adenine to two uracil bases, presumably via specific adenine-uracil base pairing and cooperative base stacking of the adenine bases. While no evidence was obtained for the interaction of ApA with poly U above room temperature, ApApA exhibited complex formation of a 1:1 nature with poly U by forming Watson-Crick base pairs. The thermodynamics of these systems are discussed.

Part II. Template Recognition and the Degeneracy of the Genetic Code

The interaction of ApApG and poly U was studied as a model system for the codon-anticodon interaction of tRNA and mRNA in vivo. ApApG was shown to interact with poly U below ~20°C. The interaction was of a 1:1 nature which exhibited the Hoogsteen bonding scheme. The three bases of ApApG are in an anti conformation and the guanosine base appears to be in the lactim tautomeric form in the complex.

Due to the inadequacies of previous models for the degeneracy of the genetic code in explaining the observed interactions of ApApG with poly U, the "tautomeric doublet" model is proposed as a possible explanation of the degenerate interactions of tRNA with mRNA during protein synthesis in vivo.

Use of biological reference points for the conservation of atlantic salmon (Salmo salar L.)in the River Lune, North West England.

This paper deals with the development and use of biological reference points for salmon conservation on the River Lune, England. The Lune supports recreational and net fisheries with annual catches in the region of 1,000 and 1356 salmon respectively. Using models transported from other river systems, biological reference points exclusive to the Lune were developed; specifically the number of eggs deposited and carrying capacity estimates for age 0+ and 1+ parr. The conservation limit was estimated at 11.9 million eggs and between 1989 and 1998 was exceeded in two years. Comparison of juvenile salmon densities in 1991 and 1997 with estimates of carrying capacity indicated that 0+ and 1+ parr densities were at around 60 % of carrying capacity and may relate to the number of eggs deposited in 1990 and 1996 being approximately 70% of the target value. The paper discusses the management actions taken in order to ensure that the management target of the conservation limit being met four years out of five is delivered. It also discusses the balance between conservation and exploitation and the socio-economic decisions made in order to ensure parity of impacts on the rod and net fisheries. The regulations have been enforced since 1999 and the paper concludes with an assessment of the actions taken to deliver the management targets, over the last five years.

Life-stage recruitment models for Atlantic cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) on Georges Bank

Ichthyoplankton surveys have been used to provide an independent estimate of adult spawning biomass of commercially exploited species and to further our understanding of the recruitment processes in the early life stages. However, predicting recruitment has been difficult because of the complex interaction of physical and biological processes operating at different spatial and temporal scales that can occur at the different life stages. A model of first-year life-stage recruitment was applied to Georges Bank Atlantic cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) stocks over the years 1977–2004 by using environmental and densitydependent relationships. The best lifestage mortality relationships for eggs, larvae, pelagic juveniles, and demersal juveniles were first determined by hindcasting recruitment estimates based on egg and larval abundance and mortality rates derived from two intensive sampling periods, 1977–87 and 1995–99. A wind-driven egg mortality relationship was used to estimate losses due to transport off the bank, and a wind-stress larval mortality relationship was derived from feeding and survival studies. A simple metric for the density-dependent effects of Atlantic cod was used for both Atlantic cod and haddock. These life stage proxies were then applied to the virtual population analysis (VPA) derived annual egg abundances to predict age-1 recruitment. Best models were determined from the correlation of predicted and VPA-derived age-1 abundance. The larval stage was the most quantifiable of any stage from surveys, whereas abundance estimates of the demersal juvenile stage were not available because of undersampling. Attempts to forecast recruitment from spawning stock biomass or egg abundance, however, will always be poor because of variable egg survival.

Modification of the biological intercept model to account for ontogenetic effects in laboratory-reared delta smelt (Hypomesus transpacificus)*

We investigated age, growth, and ontogenetic effects on the proportionality of otolith size to fish size in laboratory-reared delta smelt (Hypomesus transpacificus) from the San Francisco Bay estuary. Delta smelt larvae were reared from hatching in laboratory mesocosms for 100 days. Otolith increments from known-age fish were enumerated to validate that growth increments were deposited daily and to validate the age of fish at first ring formation. Delta smelt were found to lay down daily ring increments; however, the first increment did not form until six days after hatching. The relationship between otolith size and fish size was not biased by age or growth-rate effects but did exhibit an interruption in linear growth owing to an ontogenetic shift at the postflexon stage. To back-calculate the size-at-age of individual fish, we modified the biological intercept (BI) model to account for ontogenetic changes in the otolith-size−fish-size relationship and compared the results to the time-varying growth model, as well as the modified Fry model. We found the modified BI model estimated more accurately the size-at-age from hatching to 100 days after hatching. Before back-calculating size-at-age with existing models, we recommend a critical evaluation of the effects that age, growth, and ontogeny can have on the otolith-size−fish-size relations

Yellowfin Sole, Pleuronectes asper, of the Eastern Bering Sea: Biological Characteristics, History of Exploitation, and Management

Yellowfin sole, Pleuronectes asper, is the second most abundant flatfish in the North Pacific Ocean and is most highly concentrated in the eastern Bering Sea. It has been a target species in the eastern Bering Sea since the mid-1950's, initially by foreign distant-water fisheries but more recently by U.S. fisheries. Annual commercial catches since 1959 have ranged from 42,000 to 554,000 metric tons (t). Yellowfin sole is a relatively small flatfish averaging about 26 cm in length and 200 g in weight in commercial catches. It is distributed from nearshore waters to depths of about 100 m in the eastern Bering Sea in summer, but moves to deeper water in winter to escape sea ice. Yellowfin sole is a benthopelagic feeder. It is a longlived species (>20 years) with a correspondingly low natural mortality rate estimated at 0.12. After being overexploited during the early years of the fishery and suffering a substantial decline in stock abundance, the resource has recovered and is currently in excellent condition. The biomass during the 1980's may have been as high as, if not higher than, that at the beginning of the fishery. Based on results of demersal trawl surveys and two age structured models, the current exploitable biomass has been estimated to range between 1.9 and 2.6 million t. Appropriate harvest strategies were investigated under a range of possible recruitment levels. The recommended harvest level was calculated by multiplying the yield derived from the FOI harvest level (161 g at F = 0.14) hy an average recruitment value resulting in a commercial harvest of 276,900 t, or about 14% of the estimated exploitable biomass.

Nonparametric Bayesian sparse factor models with application to gene expression modeling

A nonparametric Bayesian extension of Factor Analysis (FA) is proposed where observed data $\mathbf{Y}$ is modeled as a linear superposition, $\mathbf{G}$, of a potentially infinite number of hidden factors, $\mathbf{X}$. The Indian Buffet Process (IBP) is used as a prior on $\mathbf{G}$ to incorporate sparsity and to allow the number of latent features to be inferred. The model's utility for modeling gene expression data is investigated using randomly generated data sets based on a known sparse connectivity matrix for E. Coli, and on three biological data sets of increasing complexity.

Comparison of the HSPF and HBV-INCA models: Crossing the Atlantic divide

Observation shows that the watershed-scale models in common use in the United States (US) differ from those used in the European Union (EU). The question arises whether the difference in model use is due to familiarity or necessity. Do conditions in each continent require the use of unique watershed-scale models, or are models sufficiently customizable that independent development of models that serve the same purpose (e.g., continuous/event- based, lumped/distributed, field-Awatershed-scale) is unnecessary? This paper explores this question through the application of two continuous, semi-distributed, watershed-scale models (HSPF and HBV-INCA) to a rural catchment in southern England. The Hydrological Simulation Program-Fortran (HSPF) model is in wide use in the United States. The Integrated Catchments (INCA) model has been used extensively in Europe, and particularly in England. The results of simulation from both models are presented herein. Both models performed adequately according to the criteria set for them. This suggests that there was not a necessity to have alternative, yet similar, models. This partially supports a general conclusion that resources should be devoted towards training in the use of existing models rather than development of new models that serve a similar purpose to existing models. A further comparison of water quality predictions from both models may alter this conclusion.

Global analysis of dynamical decision-making models through local computation around the hidden saddle

Bistable dynamical switches are frequently encountered in mathematical modeling of biological systems because binary decisions are at the core of many cellular processes. Bistable switches present two stable steady-states, each of them corresponding to a distinct decision. In response to a transient signal, the system can flip back and forth between these two stable steady-states, switching between both decisions. Understanding which parameters and states affect this switch between stable states may shed light on the mechanisms underlying the decision-making process. Yet, answering such a question involves analyzing the global dynamical (i.e., transient) behavior of a nonlinear, possibly high dimensional model. In this paper, we show how a local analysis at a particular equilibrium point of bistable systems is highly relevant to understand the global properties of the switching system. The local analysis is performed at the saddle point, an often disregarded equilibrium point of bistable models but which is shown to be a key ruler of the decision-making process. Results are illustrated on three previously published models of biological switches: two models of apoptosis, the programmed cell death and one model of long-term potentiation, a phenomenon underlying synaptic plasticity. © 2012 Trotta et al.

Oscillator models and collective motion

A description of the so called "particles with coupled oscillator dynamics" (PCOD) is presented which is used to model, analyze and synthesize collective motion. An oscillator model with spatial dynamics is presented to help describe how to design steering control laws while it is being used to study biological collectives. Lastly, both engineering and biological analysis were described.

Construction of habitat suitability models (HSMs) for benthic macroinvertebrate and their applications to instream environmental flows: A case study in Xiangxi River of Three Gorges Reservior region, China

Based on a long-term ecological monitoring, the present study chose the most dominant benthic macroinvertebrate (Baetis spp.) as target organisms in Xiangxi River, built the habitat suitability models (HSMs) for water depth, current velocity and substrate, respectively, which is the first aquatic organisms model for habitat suitability in the Chinese Mainland with a long-term consecutive in situ measurement. In order to protect the biointegrity and function of the river ecosystem, the theory system of instream environmental flow should be categorized into three hierarchies, namely minimum required instream flow (hydrological level), minimum instream environmental flow (biospecies level), and optimum instream environmental flow (ecosystem level). These three hierarchies of instream environmental flow models were then constructed with the hydrological and weighted usable area (WUA) method. The results show that the minimum required instream flow of Xiangxi River calculated by the Tennant method (10% of the mean annual flow) was 0.615 m(3) s(-1); the minimum instream environmental flow accounted for 19.22% of the mean annual flow (namely 1.182 m(3) s(-1)), which was the damaged river channel. ow in the dry season; and 42.91% of the mean annual flow (namely 2.639 m(3) s(-1)) should be viewed as the optimum instream environmental flow in order to protect the health of the river ecosystem, maintain the instream biodiversity, and reduce the impact of small hydropower stations nearby the Xiangxi River. We recommend that the hydrological and biological methods can help establish better instream environmental. ow models and design best management practices for use in the small hydropower station project. (C) 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.

View-Based Models of 3D Object Recognition and Class-Specific Invariances

This paper describes the main features of a view-based model of object recognition. The model tries to capture general properties to be expected in a biological architecture for object recognition. The basic module is a regularization network in which each of the hidden units is broadly tuned to a specific view of the object to be recognized.