Aphid population response to agricultural landscape change: A spatially explicit, individual-based model

Individual based models for the simulation of fish movement near barriers: Current work and future directions

River fragmentation is an increasing issue for water managers and conservationists. Barriers such as dams interfere with freshwater fish migration, leading to drastic population declines. While there are a range of widely implemented mitigation approaches, e.g. fish passes, such measures are often inefficient due to suboptimal operation and design. There is increasing need to be able to assess mitigation options prior to implementation. Individual based models (IBMs) are a promising option. IBMs can simulate the fine-scale movement of individual fish within a population as they attempt to find a fish pass, incorporating movement processes themselves. Moreover, IBMs have high transferability to other sites or conditions (e.g. changing mitigation, change in flow conditions), making them potentially valuable for freshwater fish conservation yet their application to the fine-scale movement of fish past barriers is still novel. Here, we present an overview of existing IBMs for fine-scale freshwater fish movement, with emphasis on study species and the parameters driving movement in the models. In this review, we focus on IBMs suitable for the simulation of fish tracks as they approach or pass a single barrier. The selected IBMs for modelling fine-scale freshwater fish movement largely focus on salmonids and cyprinid species. IBMs have many applications in the context of fish passage, such as testing different mitigation options or understanding processes behind movement. Existing IBMs include movement processes such as attraction and rejection behaviours, as reported in literature. Yet some factors affecting fish movement e.g. biotic interactions are not covered by existing IBMs. As the technology available for fine scale data collection continues to advance, such as increasing data linking fish behaviour to hydraulics, IBMs could become a more common tool in the design and implementation of fish bypass structures.

An update of the Worldwide Integrated Assessment (WIA) on systemic pesticides. Part 4: Alternatives in major cropping systems

We present a synthetic review and expert consultation that assesses the actual risks posed by arthropod pests in four major crops, identifies targets for integrated pest management (IPM) in terms of cultivated land needing pest control and gauges the implementation "readiness" of non-chemical alternatives. Our assessment focuses on the world's primary target pests for neonicotinoid-based management: western corn rootworm (WCR, Diabrotica virgifera virgifera) in maize; wireworms (Agriotes spp.) in maize and winter wheat; bird cherry-oat aphid (Rhopalosiphum padi) in winter wheat; brown planthopper (BPH, Nilaparvata lugens) in rice; cotton aphid (Aphis gossypii) and silver-leaf whitefly (SLW, Bemisia tabaci) in cotton. First, we queried scientific literature databases and consulted experts from different countries in Europe, North America, and Asia about available IPM tools for each crop-pest system. Next, using an online survey, we quantitatively assessed the economic relevance of target pests by compiling country-level records of crop damage, yield impacts, extent of insecticide usage, and "readiness" status of various pest management alternatives (i.e., research, plot-scale validation, grower-uptake). Biological control received considerable scientific attention, while agronomic strategies (e.g., crop rotation), insurance schemes, decision support systems (DSS), and innovative pesticide application modes were listed as key alternatives. Our study identifies opportunities to advance applied research, IPM technology validation, and grower education to halt or drastically reduce our over-reliance on systemic insecticides globally.

Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape

Characterising the spatio-temporal dynamics of pathogens in natura is key to ensuring their efficient prevention and control. However, it is notoriously difficult to estimate dispersal parameters at scales that are relevant to real epidemics. Epidemiological surveys can provide informative data, but parameter estimation can be hampered when the timing of the epidemiological events is uncertain, and in the presence of interactions between disease spread, surveillance, and control. Further complications arise from imperfect detection of disease and from the huge number of data on individual hosts arising from landscape-level surveys. Here, we present a Bayesian framework that overcomes these barriers by integrating over associated uncertainties in a model explicitly combining the processes of disease dispersal, surveillance and control. Using a novel computationally efficient approach to account for patch geometry, we demonstrate that disease dispersal distances can be estimated accurately in a patchy (i.e. fragmented) landscape when disease control is ongoing. Applying this model to data for an aphid-borne virus (Plum pox virus) surveyed for 15 years in 605 orchards, we obtain the first estimate of the distribution of flight distances of infectious aphids at the landscape scale. About 50% of aphid flights terminate beyond 90 m, which implies that most infectious aphids leaving a tree land outside the bounds of a 1-ha orchard. Moreover, long-distance flights are not rare-10% of flights exceed 1 km. By their impact on our quantitative understanding of winged aphid dispersal, these results can inform the design of management strategies for plant viruses, which are mainly aphid-borne.

A computer model of insect traps in a landscape

Attractant-based trap networks are important elements of invasive insect detection, pest control, and basic research programs. We present a landscape-level, spatially explicit model of trap networks, focused on detection, that incorporates variable attractiveness of traps and a movement model for insect dispersion. We describe the model and validate its behavior using field trap data on networks targeting two species, Ceratitis capitata and Anoplophora glabripennis. Our model will assist efforts to optimize trap networks by 1) introducing an accessible and realistic mathematical characterization of the operation of a single trap that lends itself easily to parametrization via field experiments and 2) allowing direct quantification and comparison of sensitivity between trap networks. Results from the two case studies indicate that the relationship between number of traps and their spatial distribution and capture probability under the model is qualitatively dependent on the attractiveness of the traps, a result with important practical consequences.

A spatiotemporal model for predicting grain aphid population dynamics and optimizing insecticide sprays at the scale of continental France

We expose here a detailed spatially explicit model of aphid population dynamics at the scale of a whole country (Metropolitan France). It is based on convection-diffusion-reaction equations, driven by abiotic and biotic factors. The target species is the grain aphid, Sitobion avenae F., considering both its winged and apterous morphs. In this preliminary work, simulations for year 2004 (an outbreak case) produced realistic aphid densities, and showed that both spatial and temporal S. avenae population dynamics can be represented as an irregular wave of population peak densities from southwest to northeast of the country, driven by gradients or differences in temperature, wheat phenology, and wheat surfaces. This wave pattern fits well to our knowledge of S. avenae phenology. The effects of three insecticide spray regimes were simulated in five different sites and showed that insecticide sprays were ineffective in terms of yield increase after wheat flowering. After suitable validation, which will require some further years of observations, the model will be used to forecast aphid densities in real time at any date or growth stage of the crop anywhere in the country. It will be the backbone of a decision support system, forecasting yield losses at the level of a field. The model intends then to complete the punctual forecasting provided by older models by a comprehensive spatial view on a large area and leads to the diminution of insecticide sprayings in wheat crops.

Cereal aphid movement: general principles and simulation modelling

Cereal aphids continue to be an important agricultural pest, with complex lifecycle and dispersal behaviours. Spatially-explicit models that are able to simulate flight initiation, movement direction, distance and timing of arrival of key aphid species can be highly valuable to area-wide pest management programmes. Here I present an overview of how knowledge about cereal aphid flight and migration can be utilized by mechanistic simulation models. This article identifies specific gaps in knowledge for researchers who may wish to further scientific understanding of aphid flight behaviour, whilst at the same time provides a synopsis of the knowledge requirements for a mechanistic approach applicable to the simulation of a wide range of insect species. Although they are one of the most comprehensively studied insect groups in entomology, it is only recently that our understanding of cereal aphid flight and migration has been translated effectively into spatially-explicit simulation models. There are now a multitude of examples available in the literature for modelling methods that address each of the four phases of the aerial transportation process (uplift, transport in the atmosphere, initial distribution, and subsequent movement). I believe it should now be possible to draw together this knowledgebase and the range of modelling methods available to simulate the entire process: integrating mechanistic simulations that estimate the initiation of migration events, with the large scale migration modelling of cereal aphids and their subsequent local movement.

An agent-based simulation of extirpation of Ceratitis capitata applied to invasions in California

We present an agent-based simulation (ABS) of Ceratitis capitata ("Medfly") developed for estimating the time to extirpation of this pest in areas where quarantines and eradication treatments were immediately imposed. We use the ABS, implemented in the program MED-FOES, to study seven different outbreaks that occurred in Southern California from 2008 to 2010. Results are compared with the length of intervention and quarantine imposed by the State, based on a linear developmental model (thermal unit accumulation, or "degree-day"). MED-FOES is a useful tool for invasive species managers as it incorporates more information from the known biology of the Medfly, and includes the important feature of being demographically explicit, providing significant improvements over simple degree-day calculations. While there was general agreement between the length of quarantine by degree-day and the time to extirpation indicated by MED-FOES, the ABS suggests that the margin of safety varies among cases and that in two cases the quarantine may have been excessively long. We also examined changes in the number of individuals over time in MED-FOES and conducted a sensitivity analysis for one of the outbreaks to explore the role of various input parameters on simulation outcomes. While our implementation of the ABS in this work is motivated by C. capitata and takes extirpation as a postulate, the simulation is very flexible and can be used to study a variety of questions on the invasion biology of pest insects and methods proposed to manage or eradicate such species.

Towards victim-oriented crime modelling in a social science e-infrastructure

The National e-Infrastructure for Social Simulation (NeISS) is a multi-disciplinary collaboration between computation and social science within the UK Digital Social Research programme. The project aims to develop new tools and services for social scientists and planners to assist in performing 'what-if' scenario predictions in a variety of policy contexts. A key part of the NeISS remit is to explore real-world scenarios and evaluate real policy applications. Research into the processes and drivers behind crime is an important application area that has major implications for both improving crime-related policy and developing effective crime prevention strategies. This paper will discuss how the current e-infrastructure and available microsimulation tools can be used to improve an existing agent-based burglary simulation (BurgdSIM) by including a more realistic representation of the victims of crime. Results show that the model produces different spatial patterns when individual-level victim data are used and a risk profile of the synthetic victims suggests which types of people have the largest burglary risk.

Landscape composition modulates population genetic structure of Eriosoma lanigerum (Hausmann) on Malus domestica Borkh in central Chile

Landscape genetics have been particularly relevant when assessing the influence of landscape characteristics on the genetic variability and the identification of barriers to gene flow. Linking current practices of area-wide pest management information on pest population genetics and geographical barriers would increase the efficiency of these programs. The woolly apple aphid, Eriosoma lanigerum (Hausmann), an important pest of apple orchards worldwide, was collected on apple trees (Malus domestica Borkh) from different locations in a 400 km north-south transect trough central Chile. In order to determine if there was population structure, diversity and flow were assessed. A total of 215 individuals from these locations were analysed using Inter Simple Sequence Repeat (ISSR) markers. Four ISSR primers generated a total of 114 polymorphic loci. The percentage of molecular variation among locations was 18%. As the algorithm used by structure may be poorly suited for inferring the number of genetic clusters in a data set that has an IBD relationship, the number of genetic clusters in the samples was also analyzed using a Bayesian clustering method implemented in software Baps version 4.14. We inferred the presence of four genetic clusters in the study region. Clustering of individuals followed a pattern explained by some geographical barriers. Using partial Mantel tests, we detected barriers to gene flow other than distance, created by a combination of main rivers and mountains. Although landscape genetics are rarely used in pest management, our results suggest that these tools may be suitable for the design of area-wide pest management programs.

Flight performance of the soybean aphid, Aphis glycines (Hemiptera: Aphididae) under different temperature and humidity regimens

The soybean aphid, Aphis glycines (Matsumura), is native to eastern Asia and has recently invaded North America, where it is currently the most important insect pest of soybeans. The soybean aphid has spread rapidly within North America, presumably through a combination of active and passive (wind-aided) flight. Here, we studied the active flight potential of A. glycines under a range of environmental conditions using an aphid flight mill. Winged (alate) A. glycines were tested on a specially designed 32-channel, computer-monitored flight mill system. Aphids that were 12-24 h old exhibited the strongest flight behavior, with average flight durations of 3.3-4.1 h, which represented flight distances of 4.6-5.1 km. After the age of 72 h, A. glycines flight performance rapidly declined. The optimum temperature range for flight was 16-28 degrees C, whereas optimum relative humidity was 75%. Our findings show that A. glycines posseses a fairly strong active flight aptitude (ability and inclination) and point to the possibility of flight initiation under a broad range of environmental conditions. These results have the potential to aid forecasting and management protocols for A. glycines at the landscape level.

The toad ahead: challenges of modelling the range and spread of an invasive species

An ability to predict the rate at which an organism spreads its range is of growing importance because the process of spread (during invasion by an exotic species) is almost identical to that occurring at the expanding range margins of a native species undergoing range shifts in response to climate change. Thus, the methods used for modelling range spread can also be employed to assess the distributional implications of climate change. Here we review the history of research on the spread of cane toads in Australia and use this case study to broadly examine the benefits and pitfalls of various modelling approaches. We show that the problems of estimating the current range, predicting the future range, and predicting the spread rate are interconnected and inform each other. Generally, we argue that correlative approaches to range-prediction are unsuitable when applied to invasive species and suggest that mechanistic methods are beginning to look promising (despite being more difficult to execute), although robust comparisons of correlative versus mechanistic predictions are lacking. Looking to the future, we argue that mechanistic models of range advance (drawing from both population ecology and environmental variation) are the approaches most likely to yield robust predictions. The complexity of these approaches coupled with the steady rise in computing power means that they have only recently become computationally tractable. Thus, we suggest that the field is only recently in a position to incorporate the complexity necessary to robustly model the rate at which species shift their range.