Optimization Strategies for Captive Breeding

There are many uncertainties that must be evaluated when captive breeding is considered. We have begun examining methods for supporting captive breeding decision-making by combining stochastic models with optimization methods. Captive breeding decisions should be state dependent- i.e., the best decision when there are 20 animals left might be different from one when there are 100 animals left. The method we use to search for state dependent decision that minimize the risk of extinction for a species is called Stochastic Dynamic Programming. We construct stochastic dynamic programming to identify the optimal size of translocations between captivity and the wild. For an initial test we parameterized the model with data on Arabian oryx (Oryx leucoryx). A key result is the importance of captive breeding in minimizing the extinction risk of a species in the wild if we can be sure that the captive population will fare better than the wild population. if the wild population is small the entire wild population is best transferred to a captive breeding facility even if the population in the wild is growing

Optimal resource allocation and prolonged dormancy strategies in herbaceous plants

1. Understanding the fitness consequences of different life histories is critical for explaining their diversity and for predicting effects of changing environmental conditions. However, current theory on plant life histories relies on phenomenological, rather than mechanistic, models of resource production. 2. We combined a well-supported mechanistic model of ontogenetic growth that incorporates differences in the size-dependent scaling of gross resource production and maintenance costs with a dynamic optimization model to predict schedules of reproduction and prolonged dormancy (plants staying below ground for ≥ 1 growing season) that maximize lifetime offspring production. 3. Our model makes three novel predictions: First, maintenance costs strongly influence the conditions under which a monocarpic or polycarpic life history evolves and how resources should be allocated to reproduction by polycarpic plants. Second, in contrast to previous theory, our model allows plants to compensate for low survival conditions by allocating a larger proportion of resources to storage and thereby improving overwinter survival. Incorporating this ecological mechanism in the model is critically important because without it our model never predicts significant investment into storage, which is inconsistent with empirical observations. Third, our model predicts that prolonged dormancy may evolve solely in response to resource allocation tradeoffs. 4. Significance: Our findings reveal that maintenance costs and the effects of resource allocation on survival are primary determinants of the fitness consequences of different life history strategies, yet previous theory on plant life history evolution has largely ignored these factors. Our findings also validate recent arguments that prolonged dormancy may be an optimal response to costs of sprouting. These findings have broad implications for understanding patterns of plant life history variation and predicting plant responses to changing environments

Southern Corn Rootworm (Coleoptera: Chrysomelidae) Adult Emergence and Population Growth Assessment After Selection With Vacuolar ATPase-A double-stranded RNA Over Multiple Generations

The southern corn rootworm, Diabrotica undecimpunctata howardi Barber (Coleoptera: Chrysomelidae), was exposed over multiple generations to vacuolar (v)ATPase-A double-stranded (ds)RNA, first as adults and later, as neonate larvae. During adult selection, high mortality and lower fecundity were observed in the RNAi-selected cages after beetles were exposed to sublethal dsRNA concentrations that varied between LC40 and LC75. During larval selection, a delay in adult emergence and effects on population growth parameters were observed after neonates were exposed to sublethal dsRNA concentrations that varied between LC50 and LC70. Some of the parameters measured for adult emergence such as time to reach maximum linear adult emergence, time elapsed before attaining linear emergence, termination point of the linear emergence, and total days of linear emergence increase, were significantly different between RNAi-selected and control colonies for at least one generation. Significant differences were also observed in population growth parameters such as growth rate, net reproductive rate, doubling time, and generation time. After seven generations of selection, there was no indication that resistance evolved. The sublethal effects caused by exposures of southern corn rootworm to dsRNAs can affect important life history traits and fitness especially through delays in adult emergence and reduction in population growth. Although changes in susceptibility did not occur, the observation of sublethal effects suggests important responses to potential selection pressure. Assuming resistance involves a recessive trait, random mating between susceptible and resistant individuals is an important factor that allows sustainable use of transgenic plants, and delays in adult emergence observed in our studies could potentially compromise this assumption

Composite random search strategies based on non-directional sensory cues

Many foraging animals find food using composite random search strategies, which consist of intensive and extensive search modes. Models of composite search can generate predictions about how optimal foragers should behave in each search mode, and how they should determine when to switch between search modes. Most of these models assume that foragers use resource encounters to decide when to switch between search modes. Empirical observations indicate that a variety of organisms use non-directional sensory cues to identify areas that warrant intensive search. These cues are not precise enough to allow a forager to directly orient itself to a resource, but can be used as a criterion to determine the appropriate search mode. As a potential example, a forager might use olfactory information, which could help it determine if an area is worth searching carefully. We developed a model of composite search based on non-directional sensory cues. With simulations, we compared the search efficiencies of composite foragers that use resource encounters as their mode-switching criterion with those that use non-directional sensory cues. We identified optimal search patterns and mode-switching criteria on a variety of resource distributions, characterized by different levels of resource aggregation and density. On all resource distributions, foraging strategies based on the non-directional sensory criterion were more efficient than those based on the resource encounter criterion. Strategies based on the non-directional sensory criterion were also more robust to changes in resource distribution. Our results suggest that current assumptions about the role of resource encounters in models of optimal composite search should be re-examined. The search strategies predicted by our model can help bridge the gap between random search theory and traditional patch-use foraging theory

Spectral properties of a non-compact operator in ecology

Ecologists have recently used integral projection models (IPMs) to study fish and other animals which continue to grow throughout their lives. Such animals cannot shrink, since they have bony skeletons; a mathematical consequence of this is that the kernel of the integral projection operator T is unbounded, and the operator is not compact. To our knowledge, all theoretical work done on IPMs has assumed the operator is compact, and in particular has a bounded kernel. A priori, it is unclear whether these IPMs have an asymptotic growth rate λ, or a stable-stage distribution ψ. In the case of a compact operator, these quantities are its spectral radius and the associated eigenvector, respectively. Under biologically reasonable assumptions, we prove that the non-compact operators in these IPMs share some important traits with their compact counterparts: the operator T has a unique positive eigenvector ψ corresponding to its spectral radius λ, this λ is strictly greater than the supremum of the modulus of all other spectral values, and for any nonnegative initial population ϕ0, there is a c \u3e 0 such that T nϕ0/λn → c · ψ

Modeling shattercane dynamics in herbicide-tolerant grain sorghum cropping systems

Traditional breeding technology is currently being used to develop grain sorghum [Sorghum bicolor (L.) Moench ssp. bicolor] germplasm that will be tolerant to acetolactate synthase (ALS)-inhibiting herbicides. This technology (InzenTM, DuPontTM) has the potential to improve sorghum production by allowing for the postemergence control of traditionally hard-to-control grasses. However, grain sorghum and shattercane [weedy Sorghum species; Sorghum bicolor (L.) Moench ssp. drummondii (Nees ex Steud.) de Wet ex Davidse] can interbreed and introduced traits such as herbicide tolerance could increase the weediness of the weedy relative. Our objective was to develop a simulation model to assess management options to mitigate risks of ALS-resistance evolution in shattercane populations in US sorghum production areas. Assuming a single major gene confers resistance and gene frequencies change according to the Hardy-Weinberg ratios we constructed a stage-structured (seedbank, plants) matrix model with annual time steps. The model explicitly considered gene flow from Inzen plants to shattercane populations. The management strategies considered in the model were: a) continuous sorghum, b) sorghum followed by (fb) soybeans and c) sorghum fb fallow fb winter wheat, where postemergence ALS-inhibiting herbicides were only used in Inzen years. During sorghum years two options were tested: continuous Inzen and Inzen fb conventional sorghum, for a total of six management strategies. The parameter values used in the model were obtained from our research, the literature, and expert opinion. For each management strategy we ran deterministic and stochastic simulations (with stochastic levels of herbicide efficacy). The time for resistance evolution was predicted to decrease with increased cropping system complexity (more crop diversity than continuous production of Inzen). Evolution of resistance was predicted to occur rapidly if Inzen sorghum is planted continuously because of high selection pressure (ALS-inhibiting herbicide application) and crop-to-weed gene flow. Rotating Inzen with conventional sorghum did not assist with shattercane management. Rotating Inzen with non-sorghum crops where effective herbicide options are available assisted with keeping shattercane density at low levels while postponing resistance evolution to some extent. Crop and herbicide rotation will be key strategies for shattercane management in Inzen sorghum

Temperature fluctuation alters optimal predator community composition for anticipated biological control

Alongside pesticides and specialist predators, natural communities of generalist beetle and spider predators play an important role in suppressing agricultural pests. However, the predation pressure of natural communities can be unpredictable. Overall predation pressure is influenced by a dense network of potential intraguild interactions, which are further shaped by species traits and environmental factors. Understanding how these different influences combine to impact pest control is especially important in the context of changing global temperatures. Recent empirical studies have demonstrated that the foraging behavior of arthropod predators is influenced by an interaction between temperature and predator body size. To explore the consequences of these findings for intraguild interactions and pest control, we expand a previously published model describing interactions between arthropod predators and a pest population. The model assumed that interaction strengths are influenced by body size and habitat preference. In our updated model, we incorporate the effect of temperature on predator foraging activity. We parameterize the model to match empirically observed predator community composition in 10 agricultural fields and use simulations to demonstrate how temperature-dependent behaviors change the expected efficiency of the natural predator community. Then, we use an optimization approach to identify the most efficient composition of natural predators for pest control. We then evaluate whether the most efficient predator compositions would change with increasing average daily temperature and its variability, as is expected under future temperature change. We find that optimal communities often include predators with complementary foraging activity and that in 2 fields, the optimal community changes drastically under future temperatures. We also note that at some temperatures, foraging activity reduces the negative effects of intraguild interference on pest consumption. This work allows us to assess the effect of climate change on the efficiency of natural predator communities to control pest populations and provide guidance for farmers to design pest management strategies tailored to different climate scenarios

Stochastic Variation in Food Availability Influences Weight and Age at Maturity

Variation in mean food availability, and in the variance around the mean, affects the growth rate during development. Previous theoretical work on the influence of environmental quality or growth rates on the phenotypic traits age and size at maturation assumed that there is no variation in growth rate or food availability within a generation. We develop a stochastic dynamic programming (SDP) model of the foraging behavior of aphidophagous syrphids, and use this model to predict when syrphids should pupate (mature) when average food availability changes, or varies stochastically, during development. The optimal strategy takes into account not only the availability of food, but also the timing of its availability. Food availability, when small, influences developmental time, but not weight at pupation. Food availability, when large, influences weight at pupation, but not developmental time. When the food supply is low, the optimal strategy adjusts the size at pupation downwards for stochastic as opposed to deterministic availability of food. The conclusions reinforce the need for lifehistory studies to consider state dependence and short-term variability in growth rates

Towards understanding factors influencing the benefit of diversity in predator communities for prey suppression

It is generally assumed that high biodiversity is key to sustaining critical ecosystem services, including prey suppression by natural predator guilds. Prey suppression is driven by complex interactions between members of predator and prey communities, as well as their shared environment. Because of this, empirical studies have found both positive and negative effects of high predator diversity on prey suppression. However, we lack an understanding of when these different prey suppression outcomes will occur. In this work, we use a mechanistic, trait-based model to unravel how intraguild interactions, species body mass, predator foraging area, and ambient temperature can combine to produce different levels of prey suppression. Surprisingly, we find that prey suppression is only improved by high biodiversity under a limited set of conditions. The most important factor in determining whether diversity improves prey sup- pression is the amount of overlap between predators’ foraging areas. The degree of overlap in foraging areas shapes species interactions, and as the overlap between species increases, we see decreasing benefits from species-rich communities. In contrast, diversity in body mass only improves prey suppression when there is significant variation in temperature