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A Bit of Sex Stabilizes Host–Parasite Dynamics

In mathematical models, very simple communities consisting of three or more species frequently display chaotic dynamics which implies that long‐term predictions of the population trajectories in time are impossible. Communities in the wild tend to be more complex, but evidence for chaotic dynamics from such communities is scarce. We used supercomputing power to test the hypothesis that chaotic dynamics become less frequent in model ecosystems when their complexity increases. We determined the dynamical stability of a universe of mathematical, nonlinear food web models with varying degrees of organizational complexity. We found that the frequency of unpredictable, chaotic dynamics increases with the number of trophic levels in a food web but decreases with the degree of complexity. Our results suggest that natural food webs possess architectural properties that may intrinsically lower the likelihood of chaotic community dynamics.

Crop production in the Midwestern U.S. and Vietnam's Mekong Delta requires sustainable and cost effective weed management strategies because both regions are grappling with increasing weed resistance to herbicides, and concerns over environmental damage from herbicides. Agroecological approaches that employ diverse cropping systems to subject weeds to multiple stress and mortality factors may provide reliable weed management that is cost efficient and less reliant on chemicals. Agroecological weed control is based on sound understanding of weed population dynamics, natural resources, and climate attributes, and thus is practical regardless of the level of technology to which farmers have access. We tested the effectiveness of cropping system diversification on weed control in a field experiment conducted in Boone County, Iowa, USA. We compared weed growth in three cropping systems (2-, 3- and 4-year rotation sequences) managed with two herbicide regimes (low and conventional input levels). For a given rotation system, the low herbicide regime, i.e. reduced herbicide inputs coupled with increased mechanical weed control, used 62% and 94% less herbicide active ingredient (kg a.i. ha-1) on corn and soybean, respectively, compared to the conventional regime. Averaged over herbicide regimes, the 3- and 4-year systems reduced herbicide use 33% and 50%, respectively, compared with the 2-year system. In 2014 and 2015, weed biomass was two-fold greater under the low herbicide regime compared with the conventional regime, and six- to seven-fold greater in the 3-year and 4-year rotations than the 2-year rotation. However, increases in weed biomass did not affect corn or soybean yield. We also assessed whether intensity of soil sampling used in previous research was precise enough for measuring weed seedbank density. A soil sampling intensity of ~ 87 cm2/1732 cm3 (surface area/volume), was acceptable for estimating total weed seed density, and soil material from 36 cores taken within one experimental unit could be combined for single processing. Results of our work indicate that multitactic weed management strategies within diversified cropping systems offer opportunities to reduce reliance on herbicides. Nonetheless, additional research is needed for further improvement of non-chemical weed suppression tactics, and for better understanding of the effects of cropping system diversification on weed population and community dynamics.

Knowledge of the genetic diversity of parasitic weed populations is important in any attempt to develop resistance-breeding strategies for the relevant host crops. Moreover, comparative genetic diversity studies of parasite biotypes in natural habitats and crop fields are important for clarifying the evolutionary path from wild parasitic plants to aggressive parasitic weeds. The genetic diversity of plant populations, analysed by isozymes and SSR, RAPD, ISSR and AFLP markers, is determined by dynamics that deal with the variation in time and space of population composition, size and density. The key elements that determine variation in population dynamics and impact the genetic diversity of parasitic weed populations are the population history, the parasite mating system and dispersal strategy, host preferences and issues imposed by agricultural plant communities, including the existence of host resistances, and farming practices.

Summary 1. Multiple modelling techniques are currently used to describe population dynamics of established invasions, where intraspecific competition is likely to reduce survival, growth and/or fecundity, suppressing population growth rate. To date, it remains unanswered whether these modelling techniques produce similar management recommendations for density‐dependent weed populations and how to model density dependence to better inform management. 2. We constructed demographic models for a short‐lived weed based on data on multiple manipulated densities in a glasshouse and data from the literature using three germination strategies. We compared management recommendations produced by two main modelling techniques for density‐dependent weed populations and examined whether periodic matrix population models constructed from different densities without characterization of density‐dependent processes (implicit models) produce management recommendations similar to that of the same models with density dependence explicitly characterized and simulated (explicit models). The use of a periodic matrix population model enabled us to target simulated management on either vital rates or entire life stages, and to examine the role of a weed’s germination strategy on model outcomes. 3. Management recommendations differed depending on how density dependence was included in demographic models. Explicit models showed that management conducted after the density‐dependent process driving population dynamics best curbed density‐regulated weed populations, with reductions in seed production having a negligible effect regardless of a germination strategy. By contrast, implicit models constructed from multiple densities produced similar management recommendations for sparse and dense populations, with reductions in survival to a flowering stage, juvenile establishment or seed production leading to the greatest predicted declines in weed density. 4. Our results emphasize the importance of model structure when modelling dynamics of density‐dependent weed populations, suggesting that explicit characterization and inclusion of density dependence in population models is often necessary to inform management. As a weed’s germination strategy had a minor effect on model outcomes, our findings about explicit and implicit modelling techniques can be generalized across annual plants with non‐overlapping generations.

Complexity of dynamics is at the core of quantum many-body chaos and exhibits a hierarchical feature: higher-order complexity implies more chaotic dynamics. Conventional ergodicity in thermalization processes is a manifestation of the lowest order complexity, which is represented by the eigenstate thermalization hypothesis (ETH) stating that individual energy eigenstates are thermal. Here, we propose a higher-order generalization of the ETH, named the $ k $-ETH ($ k=1,2,\dots $), to quantify higher-order complexity of quantum many-body dynamics at the level of individual energy eigenstates, where the lowest order ETH (1-ETH) is the conventional ETH. As a non-trivial contribution of the higher-order ETH, we show that the $ k $-ETH with $ k\geq 2 $ implies a universal behavior of the $ k $th Renyi entanglement entropy of individual energy eigenstates. In particular, the Page correction of the entanglement entropy originates from the higher-order ETH, while as is well known, the volume law can be accounted for by the 1-ETH. We numerically verify that the 2-ETH approximately holds for a nonintegrable system, but does not hold in the integrable case. To further investigate the information-theoretic feature behind the $ k $-ETH, we introduce a concept named a partial unitary $ k $-design (PU $ k $-design), which is an approximation of the Haar random unitary up to the $ k $th moment, where partial means that only a limited number of observables are accessible. The $ k $-ETH is a special case of a PU $ k $-design for the ensemble of Hamiltonian dynamics with random-time sampling. In addition, we discuss the relationship between the higher-order ETH and information scrambling quantified by out-of-time-ordered correlators. Our framework provides a unified view on thermalization, entanglement entropy, and unitary $ k $-designs, leading to deeper characterization of higher-order quantum complexity.

Animals and many plants are counted in discrete units. The collection of possible values (state space) of population numbers is thus a nonnegative integer lattice. Despite this fact, many mathematical population models assume a continuum of system states. The complex dynamics, such as chaos, often displayed by such continuous-state models have stimulated much ecological research; yet discrete-state models with bounded population size can display only cyclic behavior. Motivated by data from a population experiment, we compared the predictions of discrete-state and continuous-state population models. Neither the discrete- nor continuous-state models completely account for the data. Rather, the observed dynamics are explained by a stochastic blending of the chaotic dynamics predicted by the continuous-state model and the cyclic dynamics predicted by the discrete-state models. We suggest that such lattice effects could be an important component of natural population fluctuations.

Global herbicide-resistant weed populations continue rising due to selection pressures exerted by herbicides. Despite this, herbicides continue to be farmers’ preferred weed-control method due to cost and efficiency relative to physical or biological methods. However, weeds developing resistance to herbicides not only challenges crop production but also threatens ecosystem services by disrupting biodiversity, reducing soil health, and impacting water quality. Our objective was to develop a simulation model that captures the feedback between weed population dynamics, agricultural management, profitability, and farmer decision-making processes that interact in unique ways to reinforce herbicide resistance in weeds. After calibration to observed data and evaluation by subject matter experts, we tested alternative agronomic, mechanical, or intensive management strategies to evaluate their impact on weed population dynamics. Results indicated that standalone practices enhanced farm profitability in the short term but lead to substantial adverse ecological outcomes in the long term, indicated by elevated herbicide resistance (e.g., harm to non-target species, disrupting natural ecosystem functions). The most management-intensive test yielded the greatest weed control and farm profit, albeit with elevated residual resistant seed bank levels. We discuss these findings in both developed and developing-nation contexts. Future work requires greater connectivity of farm management and genetic-resistance models that currently remain disconnected mechanistically.

The importance of tillage depth in relation to seedling emergence in stale seedbeds

Simulation Analysis of Weed Population Dynamics in Ridge-Tilled fields

Field bindweed (Convolvulus arvensis L.) is a troublesome weed of rainfed areas. Seed bank density, weed population dynamics and crop productivity were studied in wheat crop under different tillage treatments in a field experiment carried out during summer and winter seasons of 2012‒2013 and 2013‒2014. Different combinations of tillage, integrated with glyphosate herbicide were used in the fallow period (summer season). Results showed that tillage systems along with glyphosate in summer season controlled the establishment of seed bank density as observed in conventional tillage treatment. There was a positive and very week correlation between tillage intensity and seed bank density of C. arvensis L. Similarly the weed population dynamics with reference to importance value index of weed was minimum in 1 Disc harrowing + 4 cultivations that was not significantly different from no-till + glyphosate. Tillage intensity integrated with glyphosate showed negligible but negative correlation with the weed population dynamics. In crux, no tillage integrated with glyphosate is recommended for economical reduction of seed bank density and weed population of field bindweed in rainfed wheat areas. © 2016 Friends Science Publishers

The human virome plays an important role for the clinical outcome of lung transplant recipients (LTRs). While pathogenic viruses may cause severe infections, non-pathogenic viruses may serve as potential markers for the level of immunosuppression. However, neither the complexity of the virome in different compartments nor the dynamics of the virus populations posttransplantation are yet understood. Therefore, in this study the virome was analyzed by metagenomic sequencing in simultaneously withdrawn bronchoalveolar lavage (BAL) and plasma samples of 15 LTRs. In seven patients, also follow-up samples were investigated for abundance and dynamics of virus populations posttransplantation. Five eukaryotic and two prokaryotic virus families were identified in BAL, and nine eukaryotic and two prokaryotic families in plasma. Anelloviruses were the most abundant in both compartments, followed by Herpes- and Coronaviruses. Virus abundance was significantly higher in LTRs than in healthy controls (Kruskal-Wallis test, p<0.001). Up to 48 different anellovirus strains were identified within a single LTR. Analyses in the follow-up patients revealed for the first time a highly complex and unique dynamics of individual anellovirus strains in the posttransplantation period. The abundance of anelloviruses in plasma was inversely correlated with that of other eukaryotic viruses (Pearson correlation coefficient r = −0.605; p<0.05). A broad spectrum of virus strains co-exists in BAL and plasma of LTRs. Especially for the anelloviruses, a high degree of co-infections and a highly individual and complex dynamics after transplantation was observed. The biological impact of these findings and their relation to clinical variables remain to be elucidated by future analyses.

Complex dynamics and optimal control of monetary policy in a New Keynesian model with government debt

In conventional farming, farmers usually use tillage equipment to improve the soil structure and to control weeds. But they actually damage the soil structure and contribute to reduced soil fertility in the long term. In conservation agricultural (CA) systems, however, tillage is reduced or totally eliminated. The use of CA is widely increasing in the world due to several advantages, such as conserving the soil and water resources, regenerating the soil’s fertility, protecting the soil from erosion, and reducing labor needs. This system, due to combined effects of the elimination or reduction of tillage, maintaining residues on the soil surface, and employment of diversified crop rotations, has led to wide variations in germination, emergence, and growth of weeds and has caused variations in the density and diversity of weeds under such systems. The increasing reliance on herbicides and usage of herbicide-resistant crops in CA can also lead to changes in weed population dynamics and occurrence of herbicide-resistant weed biotypes. So weeds are overwhelming problems, especially in the early years of the CA adoption, and will require special control strategies. This chapter describes the ecology and population dynamics of weeds under CA systems and effective management practices will also be discussed.

Agriculture and climate change are interwoven with each other in various measures, as climate change is the main culprit of biotic and abiotic stresses, which has adverse impact on crops and weed flora and the effectiveness of weed management strategies. Indeed weed physiology and crop productivity has been greatly influenced by several means of climate variability. Climate change causes a shift in weed population dynamics by altering the physiological pathways with the changing temperature and CO2 conditions. Climate change can affect crop-weed interactions by favouring C4 weeds in increased temperature scenarios requiring adaptation and mitigation strategies. Weeds can also shift their range by invading into new areas and higher latitudes or altitudes due to climatic variability affecting weed diversity, establishment, and management. These factors helps in understanding the crop interactions, weed infestation and herbicide efficacy. This review paper summarizes the challenges that occur due to climate change in weed behaviour requiring more attention on sustainable agricultural production.