Phytohormones and plant-herbivore-pathogen interactions: integrating the molecular with the ecological

Current research into indirect phytopathogen–herbivore interactions (i.e., interactions mediated by the host plant) is carried out in two largely independent directions: ecological/mechanistic and molecular. We investigate the origin of these approaches and their strengths and weaknesses. Ecological studies have determined the effect of herbivores and phytopathogens on their host plants and are often correlative: the need for long-term manipulative experiments is pressing. Molecular/cellular studies have concentrated on the role of signaling pathways for systemic induced resistance, mainly involving salicylic acid and jasmonic acid, and more recently the cross-talk between these pathways. This cross-talk demonstrates how interactions between signaling mechanisms and phytohormones could mediate plant–herbivore–pathogen interactions. A bridge between these approaches may be provided by field studies using chemical induction of defense, or investigating whole-organism mechanisms of interactions among the three species. To determine the role of phytohormones in induced resistance in the field, researchers must combine ecological and molecular methods. We discuss how these methods can be integrated and present the concept of “kaleidoscopic defense.” Our recent molecular-level investigations of interactions between the herbivore Gastrophysa viridula and the rust fungus Uromyces rumicis on Rumex obtusifolius, which were well studied at the mechanistic and ecological levels, illustrate the difficulty in combining these different approaches. We suggest that the choice of the right study system (possibly wild relatives of model species) is important, and that molecular studies must consider the environmental conditions under which experiments are performed. The generalization of molecular predictions to ecologically realistic settings will be facilitated by “middle-ground studies” concentrating on the outcomes of the interactions.

Managing threatened species: the ecological toolbox, evolutionary theory and declining-population paradigm

1. The management of threatened species is an important practical way in which conservationists can intervene in the extinction process and reduce the loss of biodiversity. Understanding the causes of population declines (past, present and future) is pivotal to designing effective practical management. This is the declining-population paradigm identified by Caughley. 2. There are three broad classes of ecological tool used by conservationists to guide management decisions for threatened species: statistical models of habitat use, demographic models and behaviour-based models. Each of these is described here, illustrated with a case study and evaluated critically in terms of its practical application. 3. These tools are fundamentally different. Statistical models of habitat use and demographic models both use descriptions of patterns in abundance and demography, in relation to a range of factors, to inform management decisions. In contrast, behaviour-based models describe the evolutionary processes underlying these patterns, and derive such patterns from the strategies employed by individuals when competing for resources under a specific set of environmental conditions. 4. Statistical models of habitat use and demographic models have been used successfully to make management recommendations for declining populations. To do this, assumptions are made about population growth or vital rates that will apply when environmental conditions are restored, based on either past data collected under favourable environmental conditions or estimates of these parameters when the agent of decline is removed. As a result, they can only be used to make reliable quantitative predictions about future environments when a comparable environment has been experienced by the population of interest in the past. 5. Many future changes in the environment driven by management will not have been experienced by a population in the past. Under these circumstances, vital rates and their relationship with population density will change in the future in a way that is not predictable from past patterns. Reliable quantitative predictions about population-level responses then need to be based on an explicit consideration of the evolutionary processes operating at the individual level. 6. Synthesis and applications. It is argued that evolutionary theory underpins Caughley's declining-population paradigm, and that it needs to become much more widely used within mainstream conservation biology. This will help conservationists examine critically the reliability of the tools they have traditionally used to aid management decision-making. It will also give them access to alternative tools, particularly when predictions are required for changes in the environment that have not been experienced by a population in the past.

Demographic models and the management of endangered species: a case study of the critically endangered Seychelles magpie robin

1. Demographic models are assuming an important role in management decisions for endangered species. Elasticity analysis and scope for management analysis are two such applications. Elasticity analysis determines the vital rates that have the greatest impact on population growth. Scope for management analysis examines the effects that feasible management might have on vital rates and population growth. Both methods target management in an attempt to maximize population growth. 2. The Seychelles magpie robin Copsychus sechellarum is a critically endangered island endemic, the population of which underwent significant growth in the early 1990s following the implementation of a recovery programme. We examined how the formal use of elasticity and scope for management analyses might have shaped management in the recovery programme, and assessed their effectiveness by comparison with the actual population growth achieved. 3. The magpie robin population doubled from about 25 birds in 1990 to more than 50 by 1995. A simple two-stage demographic model showed that this growth was driven primarily by a significant increase in the annual survival probability of first-year birds and an increase in the birth rate. Neither the annual survival probability of adults nor the probability of a female breeding at age 1 changed significantly over time. 4. Elasticity analysis showed that the annual survival probability of adults had the greatest impact on population growth. There was some scope to use management to increase survival, but because survival rates were already high (> 0.9) this had a negligible effect on population growth. Scope for management analysis showed that significant population growth could have been achieved by targeting management measures at the birth rate and survival probability of first-year birds, although predicted growth rates were lower than those achieved by the recovery programme when all management measures were in place (i.e. 1992-95). 5. Synthesis and applications. We argue that scope for management analysis can provide a useful basis for management but will inevitably be limited to some extent by a lack of data, as our study shows. This means that identifying perceived ecological problems and designing management to alleviate them must be an important component of endangered species management. The corollary of this is that it will not be possible or wise to consider only management options for which there is a demonstrable ecological benefit. Given these constraints, we see little role for elasticity analysis because, when data are available, a scope for management analysis will always be of greater practical value and, when data are lacking, precautionary management demands that as many perceived ecological problems as possible are tackled.

Effects of resistant starch type III polymorphs on human colon microbiota and short chain fatty acids in human gut models

This study probed the possible effects of type III resistant starch (RS) crystalline polymorphism on RS fermentability by human gut microbiota and the short chain fatty acids production in vitro. Human fecal pH-controlled batch cultures showed RS induces an ecological shift in the colonic microbiota with polymorph B inducing Bifidobacterium spp. and polymorph A inducing Atopobium spp. Interestingly, polymorph B also induced higher butyrate production to levels of 0.79 mM. In addition, human gut simulation demonstrated that polymorph B promotes the growth of bifidobacteria in the proximal part of the colon and double their relative proportion in the microbiota in the distal colon. These findings suggest that RS polymorph B may promote large bowel health. While the findings are limited by study constraints, they do raise the possibility of using different thermal processing to delineate differences in the prebiotic capabilities of RS, especially its butryrogenicity in the human colon.

Solving optimal control problems with state constraints using nonlinear programming and simulation tools

This paper illustrates how nonlinear programming and simulation tools, which are available in packages such as MATLAB and SIMULINK, can easily be used to solve optimal control problems with state- and/or input-dependent inequality constraints. The method presented is illustrated with a model of a single-link manipulator. The method is suitable to be taught to advanced undergraduate and Master's level students in control engineering.

Input constraints handling in an MPC/feedback linearization scheme

The combination of model predictive control based on linear models (MPC) with feedback linearization (FL) has attracted interest for a number of years, giving rise to MPC+FL control schemes. An important advantage of such schemes is that feedback linearizable plants can be controlled with a linear predictive controller with a fixed model. Handling input constraints within such schemes is difficult since simple bound contraints on the input become state dependent because of the nonlinear transformation introduced by feedback linearization. This paper introduces a technique for handling input constraints within a real time MPC/FL scheme, where the plant model employed is a class of dynamic neural networks. The technique is based on a simple affine transformation of the feasible area. A simulated case study is presented to illustrate the use and benefits of the technique.

A new RBF neural network with boundary value constraints

We present a novel topology of the radial basis function (RBF) neural network, referred to as the boundary value constraints (BVC)-RBF, which is able to automatically satisfy a set of BVC. Unlike most existing neural networks whereby the model is identified via learning from observational data only, the proposed BVC-RBF offers a generic framework by taking into account both the deterministic prior knowledge and the stochastic data in an intelligent manner. Like a conventional RBF, the proposed BVC-RBF has a linear-in-the-parameter structure, such that it is advantageous that many of the existing algorithms for linear-in-the-parameters models are directly applicable. The BVC satisfaction properties of the proposed BVC-RBF are discussed. Finally, numerical examples based on the combined D-optimality-based orthogonal least squares algorithm are utilized to illustrate the performance of the proposed BVC-RBF for completeness.

Force distribution in manipulation by a robot hand with equality and inequality constraints

The problem of the appropriate distribution of forces among the fingers of a four-fingered robot hand is addressed. The finger-object interactions are modelled as point frictional contacts, hence the system is indeterminate and an optimal solution is required for controlling forces acting on an object. A fast and efficient method for computing the grasping and manipulation forces is presented, where computation has been based on using the true model of the nonlinear frictional cone of contact. Results are compared with previously employed methods of linearizing the cone constraints and minimizing the internal forces.