The Effect of Chemical Information on the Spatial Distribution of Fruit Flies: II Parameterization, Calibration, and Sensitivity

In a companion paper (Lof et al., in Bull. Math. Biol., 2008), we describe a spatio-temporal model for insect behavior. This model includes chemical information for finding resources and conspecifics. As a model species, we used Drosophila melanogaster, because its behavior is documented comparatively well

The Effect of Chemical Information on the Spatial Distribution of Fruit Flies: I Model Results

Animal aggregation is a general phenomenon in ecological systems. Aggregations are generally considered as an evolutionary advantageous state in which members derive the benefits of protection and mate choice, balanced by the costs of limiting resources and competition. In insects, chemical information conveyance plays an important role in finding conspecifics and forming aggregations. In this study, we describe a spatio-temporal simulation model designed to explore and quantify the effects of these infochemicals, i.e., food odors and an aggregation pheromone, on the spatial distribution of a fruit fly (Drosophila melanogaster) population, where the lower and upper limit of local population size are controlled by an Allee effect and competition. We found that during the spatial expansion and strong growth of the population, the use of infochemicals had a positive effect on population size. The positive effects of reduced mortality at low population numbers outweighed the negative effects of increased mortality due to competition. At low resource densities, attraction toward infochemicals also had a positive effect on population size during recolonization of an area after a local population crash, by decreasing the mortality due to the Allee effect. However, when the whole area was colonized and the population was large, the negative effects of competition on population size were larger than the positive effects of the reduction in mortality due to the Allee effect. The use of infochemicals thus has mainly positive effects on population size and population persistence when the population is small and during the colonization of an area

Modelling the effect of gene deployment strategies on durability of plant resistance under selection

Genetic resistance in crop plants is a cornerstone of disease management in agriculture. Such genetic resistance is often rapidly overtaken due to selection in the pathogen population, resulting in an arms race between plant breeders and the pathogen population. Here we ask whether there are strategies that can prolong the useful life of plant resistance genes. In a modelling study we compare three basic strategies: gene pyramiding, sequential use, and simultaneous use, and combinations of these. We furthermore explore the effects of fraction of host area, fraction of resistant host and the threshold fraction of virulence in the pathogen population at which resistance is considered overtaken on the useful life of resistance genes. We found that pyramiding is not always the most durable solution. Model results indicate that the most durable deployment strategy depends on the threshold fraction at which resistance is considered overtaken. This threshold fraction will depend on the economic value of the crop, and whether damage is acceptable. Pyramiding is only the most durable solution if the threshold is low. Otherwise, simultaneous use of single-gene resistant varieties is the most durable solution

Timing in a fluctuating environment: environmental variability and asymmetric fitness curves can lead to adaptively mismatched avian reproduction

Adaptation in dynamic environments depends on the grain, magnitude and predictability of ecological fluctuations experienced within and across generations. Phenotypic plasticity is a well-studied mechanism in this regard, yet the potentially complex effects of stochastic environmental variation on optimal mean trait values are often overlooked. Using an optimality model inspired by timing of reproduction in great tits, we show that temporal variation affects not only optimal reaction norm slope, but also elevation. With increased environmental variation and an asymmetric relationship between fitness and breeding date, optimal timing shifts away from the side of the fitness curve with the steepest decline. In a relatively constant environment, the timing of the birds is matched with the seasonal food peak, but they become adaptively mismatched in environments with temporal variation in temperature whenever the fitness curve is asymmetric. Various processes affecting the survival of offspring and parents influence this asymmetry, which collectively determine the ‘safest’ strategy, i.e. whether females should breed before, on, or after the food peak in a variable environment. As climate change might affect the (co)variance of environmental variables as well as their averages, risk aversion may influence how species should shift their seasonal timing in a warming world

Data from: Modeling winter moth Operophtera brumata egg phenology: nonlinear effects of temperature and developmental stage on developmental rate

Understanding the relationship between an insect's developmental rate and temperature is crucial to forecast insect phenology under climate change. In the winter moth Operophtera brumata timing of egg-hatching has severe fitness consequences on growth and reproduction as egg-hatching has to match bud burst of the host tree. In the winter moth, as in many insect species, egg development is strongly affected by ambient temperatures. Here we use laboratory experiments to show for the first time that the effect of temperature on developmental rate depends on the stage of development of the eggs. Building on this experimental finding, we present a novel physiological model to describe winter moth egg development in response to temperature. Our model, a modification of the existing Sharpe−Schoolfield biophysical model, incorporates the effect of developmental stage on developmental rate. Next we validate this model using a 13-year data-set from winter moth eggs kept under ambient conditions and compared this validation with a degree day model and with the Sharpe−Schoolfield model, which lacks the interaction between temperature and developmental stage on developmental rate. We show that accounting for the interaction between temperature and developmental stage improved the predictive power of the model and contributed to our understanding of annual variation in winter moth egg phenology. As climate change leads to unequal changes in temperatures throughout the year, a description of insect development in response to realistic patterns of temperature rather than an invariable degree-day approach will help us to better predict future responses of insect phenology, and thereby insect fitness, to climate change

Modeling winter moth Operophtera brumata egg phenology : nonlinear effects of temperature and developmental stage on developmental rate

Understanding the relationship between an insect's developmental rate and temperature is crucial to forecast insect phenology under climate change. In the winter moth Operophtera brumata timing of egg-hatching has severe fitness consequences on growth and reproduction as egg-hatching has to match bud burst of the host tree. In the winter moth, as in many insect species, egg development is strongly affected by ambient temperatures. Here we use laboratory experiments to show for the first time that the effect of temperature on developmental rate depends on the stage of development of the eggs. Building on this experimental finding, we present a novel physiological model to describe winter moth egg development in response to temperature. Our model, a modification of the existing Sharpe−Schoolfield biophysical model, incorporates the effect of developmental stage on developmental rate. Next we validate this model using a 13-year data-set from winter moth eggs kept under ambient conditions and compared this validation with a degree day model and with the Sharpe−Schoolfield model, which lacks the interaction between temperature and developmental stage on developmental rate. We show that accounting for the interaction between temperature and developmental stage improved the predictive power of the model and contributed to our understanding of annual variation in winter moth egg phenology. As climate change leads to unequal changes in temperatures throughout the year, a description of insect development in response to realistic patterns of temperature rather than an invariable degree-day approach will help us to better predict future responses of insect phenology, and thereby insect fitness, to climate change.</p

Data from: Modeling winter moth Operophtera brumata egg phenology: nonlinear effects of temperature and developmental stage on developmental rate

Understanding the relationship between an insect's developmental rate and temperature is crucial to forecast insect phenology under climate change. In the winter moth Operophtera brumata timing of egg-hatching has severe fitness consequences on growth and reproduction as egg-hatching has to match bud burst of the host tree. In the winter moth, as in many insect species, egg development is strongly affected by ambient temperatures. Here we use laboratory experiments to show for the first time that the effect of temperature on developmental rate depends on the stage of development of the eggs. Building on this experimental finding, we present a novel physiological model to describe winter moth egg development in response to temperature. Our model, a modification of the existing Sharpe−Schoolfield biophysical model, incorporates the effect of developmental stage on developmental rate. Next we validate this model using a 13-year data-set from winter moth eggs kept under ambient conditions and compared this validation with a degree day model and with the Sharpe−Schoolfield model, which lacks the interaction between temperature and developmental stage on developmental rate. We show that accounting for the interaction between temperature and developmental stage improved the predictive power of the model and contributed to our understanding of annual variation in winter moth egg phenology. As climate change leads to unequal changes in temperatures throughout the year, a description of insect development in response to realistic patterns of temperature rather than an invariable degree-day approach will help us to better predict future responses of insect phenology, and thereby insect fitness, to climate change

The contribution of semi-natural habitats to biological control is dependent on sentinel prey type

It is widely recognized that landscape factors affect the biological control of weed seeds and insect pests in arable crops, but landscape effects have been found to be inconsistent between studies. Here, we compare six different types of sentinels (surrogate prey that was either live insects or seeds) to measure the effects of semi-natural habitats at field to landscape scales on levels of biological control in winter wheat in the UK. Sentinels were located in fields adjacent to three boundary types: grassy margin, hedgerows or woodland to study local scale effects and in landscapes of varying heterogeneity in study areas of 1 km radius. Overall mean levels of predation were higher for most insect prey (60.8%) located on the ground compared to the crop (12.2%) and was lower for seeds (5.8%). Predation of sentinels on the ground was attributed to generalist predators. Semi-natural habitats had both positive and negative effects at field and landscape scales, but the response varied with the sentinel type. Herbaceous linear semi-natural habitats had positive effects at local scales for Calliphora vomitoria and Sitobion avenae sentinels and provides evidence that farmers can introduce linear herbaceous features to benefit biological control. In contrast our distance weighted kernel models identified a positive relationship between woody habitats and the predation of Caliphora vomitoria and Chenopodium album. Natural aphid infestations were lower in landscapes with more semi-natural habitat. Synthesis and applications. Sentinels may be sensitive enough to detect variation in levels of biological control influenced by semi-natural habitats, but this study confirms that landscape effects differ for different types of sentinel prey. This implies that it may not be possible to categorize landscapes as pest suppressive using a single sentinel type. Future studies should therefore consider using multiple sentinels to give a better perspective on predation intensity. The resulting recommendations for farm management include planting woodland adjacent wheat fields infested with seed predators and positioning herbaceous linear habitats adjacent wheat fields infested with Sitobion Avenae, particularly if fields are bordered by woody liner habitats due to their association with decreased Sitobion Avenae predation