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Biological control requires specific tools for the accurate detection and identification of natural enemies, and to detect unusual variations in their density, which may follow changes in agricultural practices. Here we have developed specific molecular markers to detect Lydella thompsoni (Herting) and Pseudoperichaeta nigrolineata (Walker) (Diptera: Tachinidae) within the European corn borer, Ostrinia nubilalis (Hübner) (Lepidoptera: Crambidae). Primers amplifying fragments of the mitochondrial COI gene were designed following alignment of comparable sequences for a range of parasitoid and host species. Each of the primer pairs proved to be species specific to a tachinid species, amplifying DNA fragments of 191 and 91 bp in length for L. thompsoni and P. nigrolineata, respectively. This DNA-based technique allowed molecular evaluation of parasitism in O. nubilalis natural populations. In order to study the geographical distribution of both species in France, O. nubilalis diapausing larvae in maize stalks were collected from 12 locations over the whole country. The molecular evaluation of parasitism was compared with the traditional method of maintaining O. nubilalis populations in controlled conditions before breaking off the diapause. The percentage parasitism found in both species of tachinids was higher — approximately three times — using the molecular method, suggesting an underestimation by the traditional rearing protocol. Tachinid parasitism on O. nubilalis was not significantly different between geographical areas (south, central and north France) for both species. This study shows that molecular methods are very promising for the correct detection and identification of tachinid parasitoids in natural field populations. [ABSTRACT FROM AUTHOR]

The standard model for the dynamics of a fragmented density-dependent population is built from several local logistic models coupled by migrations. First introduced in the 1970s and used in innumerable articles, this standard model applied to a two-patch situation has never been fully analyzed. Here, we complete this analysis and we delineate the conditions under which fragmentation associated with dispersal is either favorable or unfavorable to total population abundance. We pay special attention to the case of asymmetric dispersal, i.e., the situation in which the dispersal rate from patch 1 to patch 2 is not equal to the dispersal rate from patch 2 to patch 1. We show that this asymmetry can have a crucial quantitative influence on the effect of dispersal., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The standard model for the dynamics of a fragmented density-dependent population is built from several local logistic models coupled by migrations. First introduced in the 1970s and used in innumerable articles, this standard model applied to a two-patch situation has never been completely analysed. Here, we complete this analysis and we delineate the conditions under which fragmentation associated to dispersal is either beneficial or detrimental to total population abundance. Therefore, this is a contribution to the SLOSS question. Importantly, we also show that, depending on the underlying mechanism, there is no unique way to generalize the logistic model to a patchy situation. In many cases, the standard model is not the correct generalization. We analyse several alternative models and compare their predictions. Finally, we emphasize the shortcomings of the logistic model when written in the r-K parameterization and we explain why Verhulst's original polynomial expression is to be preferred., (Copyright © 2015. Published by Elsevier Inc.)

Much of the focus in evolutionary biology has been on the adaptive differentiation among organisms. It is equally important to understand the processes that result in similarities of structure among systems. Here, we discuss examples of similarities occurring at different ecological scales, from predator-prey relations (attack rates and handling times) through communities (food-web structures) to ecosystem properties. Selection among systemic configurations or patterns that differ in their intrinsic stability should lead generally to increased representation of relatively stable structures. Such nonadaptive, but selective processes that shape ecological communities offer an enticing mechanism for generating widely observed similarities, and have sparked new interest in stability properties. This nonadaptive systemic selection operates not in opposition to, but in parallel with, adaptive evolution., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Spatial heterogeneity of the environment has long been recognized as a major factor in ecological dynamics. Its role in predator-prey systems has been of particular interest, where it can affect interactions in two qualitatively different ways: by providing (1) refuges for the prey or (2) obstacles that interfere with the movements of both prey and predators. There have been relatively fewer studies of obstacles than refuges, especially studies on their effect on functional responses. By analogy with reaction-diffusion models for chemical systems in heterogeneous environments, we predict that obstacles are likely to reduce the encounter rate between individuals, leading to a lower attack rate (predator-prey encounters) and a lower interference rate (predator-predator encounters). Here, we test these predictions under controlled conditions using collembolans (springtails) as prey and mites as predators in microcosms. The effect of obstacle density on the functional response was investigated at the scales of individual behavior and of the population. As expected, we found that increasing obstacle density reduces the attack rate and predator interference. Our results show that obstacles, like refuges, can reduce the predation rate because obstacles decrease the attack rate. However, while refuges can increase predator dependence, we suggest that obstacles can decrease it by reducing the rate of encounters between predators. Because of their opposite effect on predator dependence, obstacles and refuges could modify in different ways the stability of predator-prey communities.

We constructed a reaction-diffusion model of the development of resistance to transgenic insecticidal Bt crops in pest populations. Kostitzin's demo-genetic model describes local interactions between three competing pest genotypes with alleles conferring resistance or susceptibility to transgenic plants, the spatial spread of insects being modelled by diffusion. This new approach makes it possible to combine a spatial demographic model of population dynamics with classical genetic theory. We used this model to examine the effects of pest dispersal and of the size and shape of the refuge on the efficiency of the "high-dose/refuge" strategy, which was designed to prevent the development of resistance in populations of insect pests, such as the European corn borer, Ostrinia nubilalis Hübner (Lepidoptera, Crambidae). We found that, with realistic combinations of refuge size and pest dispersal, the development of resistance could be considerably delayed. With a small to medium-sized farming area, contiguous refuge plots are more efficient than a larger number of smaller refuge patches. We also show that the formal coupling of classical Fisher-Haldane-Wright population genetics equations with diffusion terms inaccurately describes the development of resistance in a spatially heterogeneous pest population, notably overestimating the speed with which Bt resistance is selected in populations of pests targeted by Bt crops.

The interactions that occur during the ripening of smear cheeses are not well understood. Yeast-yeast interactions and yeast-bacterium interactions were investigated within a microbial community composed of three yeasts and six bacteria found in cheese. The growth dynamics of this community was precisely described during the ripening of a model cheese, and the Lotka-Volterra model was used to evaluate species interactions. Subsequently, the effects on ecosystem functioning of yeast omissions in the microbial community were evaluated. It was found both in the Lotka-Volterra model and in the omission study that negative interactions occurred between yeasts. Yarrowia lipolytica inhibited mycelial expansion of Geotrichum candidum, whereas Y. lipolytica and G. candidum inhibited Debaryomyces hansenii cell viability during the stationary phase. However, the mechanisms involved in these interactions remain unclear. It was also shown that yeast-bacterium interactions played a significant role in the establishment of this multispecies ecosystem on the cheese surface. Yeasts were key species in bacterial development, but their influences on the bacteria differed. It appeared that the growth of Arthrobacter arilaitensis or Hafnia alvei relied less on a specific yeast function because these species dominated the bacterial flora, regardless of which yeasts were present in the ecosystem. For other bacteria, such as Leucobacter sp. or Brevibacterium aurantiacum, growth relied on a specific yeast, i.e., G. candidum. Furthermore, B. aurantiacum, Corynebacterium casei, and Staphylococcus xylosus showed reduced colonization capacities in comparison with the other bacteria in this model cheese. Bacterium-bacterium interactions could not be clearly identified.

Various spatial approaches were developed to study the effect of spatial heterogeneities on population dynamics. We present in this paper a flux-based model to describe an aphid-parasitoid system in a closed and spatially structured environment, i.e. a greenhouse. Derived from previous work and adapted to host-parasitoid interactions, our model represents the level of plant infestation as a continuous variable corresponding to the number of plants bearing a given density of pests at a given time. The variation of this variable is described by a partial differential equation. It is coupled to an ordinary differential equation and a delay-differential equation that describe the parasitized host population and the parasitoid population, respectively. We have applied our approach to the pest Aphis gossypii and to one of its parasitoids, Lysiphlebus testaceipes, in a melon greenhouse. Numerical simulations showed that, regardless of the number and distribution of hosts in the greenhouse, the aphid population is slightly larger if parasitoids display a type III rather than a type II functional response. However, the population dynamics depend on the initial distribution of hosts and the initial density of parasitoids released, which is interesting for biological control strategies. Sensitivity analysis showed that the delay in the parasitoid equation and the growth rate of the pest population are crucial parameters for predicting the dynamics. We demonstrate here that such a flux-based approach generates relevant predictions with a more synthetic formalism than a common plant-by-plant model. We also explain how this approach can be better adapted to test different management strategies and to manage crops of several greenhouses.

A mathematical model of the development of resistance to transgenic Bt-crop in insect-pest populations as applied to the European corn borer has been constructed. The model represents a system of differential equations in special derivatives of the reaction-diffusion type. Local interactions of three competing pest genotypes formed by the allele of Bt-resistance and allele of susceptibility, are described by the same relations as in the Kostitsyn model, and the spread of insects is modelled as diffusion. The model was used to estimate the influence of the pest on the efficiency of the "high dose-refuge" strategy, which is intended for the suppression of development of Bt-resistance in pest populations. It was shown that formal integration of the Fisher-Haldane-Wright model and the diffusion term cannot adequately describe the development of Bt-resistance in a spatially heterogeneous pest population. A further development of the model is discussed.

We explore the phenomenon of animal self-organization due to autotaxis, that is, the movement of individuals induced by their own density gradient. There is natural evidence that clustering occurs as a result of the interplay between random and directed movements of individuals due to mutual attraction and repulsion. Classically, it is assumed that taxis velocity is determined by the density gradient of some stimulus. However, it is known that partial differential equation (PDE) diffusion-advection models that rest on this assumption cannot give a realistic representation of a stationary or moving cohesive group of individuals with a uniform interior density and sharp edges. Pioneering work by Okubo and coworkers suggests that the acceleration of individuals (rather than their velocity directly) is proportional to the population density gradient. A PDE model resting on this finding was constructed and investigated. The model demonstrates the formation of steady heterogeneous structures of the required shape. This feature can be interpreted as dynamic self-organization, like fish shoaling or insect swarming. This model is the first to achieve this result while considering an autonomous population in a simple PDE framework. Analytical and numerical studies show that the link between the acceleration and the density gradient is crucial for the appearance of clusters.

Based on a qualitative analysis of ODE systems, the dynamic properties of alternative predator-prey models with predator-dependent functional response have been compared in order to study the role that predator interference plays in the stabilisation of trophic systems. The models considered for interference have different mathematical expressions and different conceptual foundations. Despite these differences, they give essentially the same qualitative results: when interference is low, increasing it has a positive effect on asymptotic stability and thus on the resilience of the biological system. When it is high, it is the contrary (with logistic prey growth, increasing the interference parameter ensures stability but leads to very small predator densities). Possible consequences on the evolution of the interference level in real ecosystems are discussed.