Optimal control in individual-based models: implications from aggregated methods.

Use of individual-based models (IBMs) has been expanding in both theoretical and applied ecology. IBMs include details at the level of individuals that may lead to different conclusions from aggregated modeling methods. There has been essentially no guidance available on how to most effectively manage populations when the underlying dynamics are best modeled through IBMs. Using a simple resource-consumer IBM, we investigate whether optimal control theory applied to an aggregated model (AM) can effectively control a harmful species modeled by an IBM or whether interactions between individuals, their spatial distribution, and/or landscape heterogeneities limit the effectiveness of a control derived for the AM. If optimal policies derived from an AM are determined to be generally effective in managing a population modeled with considerably greater complexity, this provides evidence that optimal management strategies may be relatively insensitive to the details of individual behavior and the associated effects on population response. We investigate these issues and find that if there is weak spatial heterogeneity in the resource, the optimal control derived from the AM can be used effectively to control the harmful species in the IBM. The approach is more limited in the case of very strong spatial heterogeneity in the resource. This suggests investigation of a mixture of simplified models in conjunction with detailed simulation models when individual differences affect population processes.

Brazilian free-tailed bats as insect pest regulators in transgenic and conventional cotton crops.

During the past 12000 years agricultural systems have transitioned from natural habitats to conventional agricultural regions and recently to large areas of genetically engineered (GE) croplands. This GE revolution occurred for cotton in a span of slightly more than a decade during which a switch occurred in major cotton production areas from growing 100% conventional cotton to an environment in which 95% transgenics are grown. Ecological interactions between GE targeted insects and other insectivorous insects have been investigated. However, the relationships between ecological functions (such as herbivory and ecosystem transport) and agronomic benefits of avian or mammalian insectivores in the transgenic environment generally remain unclear, although the importance of some agricultural pest management services provided by insectivorous species such as the Brazilian free-tailed bat, Tadarida brasiliensis, have been recognized. We developed a dynamic model to predict regional-scale ecological functions in agricultural food webs by using the indicators of insect pest herbivory measured by cotton boll damage and insect emigration from cotton. In the south-central Texas Winter Garden agricultural region we find that the process of insectivory by bats has a considerable impact on both the ecology and valuation of harvest in Bacillus thuringiensis (Bt) transgenic and nontransgenic cotton crops. Predation on agricultural pests by insectivorous bats may enhance the economic value of agricultural systems by reducing the frequency of required spraying and delaying the ultimate need for new pesticides. In the Winter Garden region, the presence of large numbers of insectivorous bats yields a regional summer dispersion of adult pest insects from Bt cotton that is considerably reduced from the moth emigration when bats are absent in either transgenic or non-transgenic crops. This regional decrease of pest numbers impacts insect herbivory on a transcontinental scale. With a few exceptions, we find that the agronomics of both Bt and conventional cotton production is more profitable when large numbers of insectivorous bats are present.

A general modeling framework for describing spatially structured population dynamics.

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles.

Bats track and exploit changes in insect pest populations.

The role of bats or any generalist predator in suppressing prey populations depends on the predator's ability to track and exploit available prey. Using a qPCR fecal DNA assay, we document significant association between numbers of Brazilian free-tailed bats (Tadarida brasiliensis) consuming corn earworm (CEW) moths (Helicoverpa zea) and seasonal fluctuations in CEW populations. This result is consistent with earlier research linking the bats' diet to patterns of migration, abundance, and crop infestation by important insect pests. Here we confirm opportunistic feeding on one of the world's most destructive insects and support model estimates of the bats' ecosystem services. Regression analysis of CEW consumption versus the moth's abundance at four insect trapping sites further indicates that bats track local abundance of CEW within the regional landscape. Estimates of CEW gene copies in the feces of bats are not associated with seasonal or local patterns of CEW abundance, and results of captive feeding experiments indicate that our qPCR assay does not provide a direct measure of numbers or biomass of prey consumed. Our results support growing evidence for the role of generalist predators, and bats specifically, as agents for biological control and speak to the value of conserving indigenous generalist predators.

Bat population dynamics: multilevel model based on individuals' energetics.

Temperate-zone bats are subject to serious energetic constraints due to their high surface area to volume relations, the cost of temperature regulation, the high metabolic cost of flight, and the seasonality of their resources. We present a novel, multilevel theoretical approach that integrates information on bat biology collected at a lower level of organization, the individual with its physiological characteristics, into a modeling framework at a higher level, the population. Our individual component describes the growth of an individual female bat by modeling the dynamics of the main body compartments (lipids, proteins, and carbohydrates). A structured population model based on extended McKendrick-von Foerster partial differential equations integrates those individual dynamics and provides insight into possible regulatory mechanisms of population size as well as conditions of population survival and extinction. Though parameterized for a specific bat species, all modeling components can be modified to investigate other bats with similar life histories. A better understanding of population dynamics in bats can assist in the development of management techniques and conservation strategies, and to investigate stress effects. Studying population dynamics of bats presents particular challenges, but bats are essential in some areas of concern in conservation and disease ecology that demand immediate investigation.