Spotted Wing Drosophila (SWD), Drosophila suzukii, infestation risk to tomatoes

Spotted Wing Drosophila (SWD), Drosophila suzukii, an invasive fruit fly from Japan, appeared in NY in 2011 and has become of major concern to small fruit growers. Unlike other fruit flies, it lays eggs in intact fruit prior to harvest. Current pesticide control measures target the adult but there is great risk of developing resistance; resistance has already been reported on the West Coast. Known hosts of SWD include soft skinned fruit like raspberries and blueberries. Even though the wild host range of SWD includes nightshades (Solanum spp.) no research had been conducted to evaluate the threat of SWD to tomatoes, Solanum lycopersicum

Cucurbit IPM on Farm Demonstrations

IPM practices in cucurbits were demonstrated at three different farms and on 13 fields (crops included pumpkins, zucchini, cantaloupe, squash, cucumbers, and watermelon). For each field/crop, data on pest levels, pesticide use, insect infestation and damage at harvest were collected. Each field was scouted weekly for striped cucumber beetle, squash bugs and aphids, traps were placed to monitor for squash vine borer, and samples were taken weekly of any possible diseases and brought to Dr. Frank Hay of the Plant Pathology and Plant-­‐Microbe Biology Section for identification. Growers received weekly scouting reports and treatment recommendations. For all three farms the growers reported that having someone scout their cucurbits was extremely helpful and problems were identify much earlier than in previous years

Scalable Probabilistic Similarity Ranking in Uncertain Databases (Technical Report)

This paper introduces a scalable approach for probabilistic top-k similarity ranking on uncertain vector data. Each uncertain object is represented by a set of vector instances that are assumed to be mutually-exclusive. The objective is to rank the uncertain data according to their distance to a reference object. We propose a framework that incrementally computes for each object instance and ranking position, the probability of the object falling at that ranking position. The resulting rank probability distribution can serve as input for several state-of-the-art probabilistic ranking models. Existing approaches compute this probability distribution by applying a dynamic programming approach of quadratic complexity. In this paper we theoretically as well as experimentally show that our framework reduces this to a linear-time complexity while having the same memory requirements, facilitated by incremental accessing of the uncertain vector instances in increasing order of their distance to the reference object. Furthermore, we show how the output of our method can be used to apply probabilistic top-k ranking for the objects, according to different state-of-the-art definitions. We conduct an experimental evaluation on synthetic and real data, which demonstrates the efficiency of our approach

Interdisciplinary system architectures in agile modular development in the product generation development model using the example of a machine tool manufacturer

This paper considers the orientation of product development structures towards interdisciplinary system architectures using the example of a tool machine manufacturer. Due to the change from simple mechanical products to extensively designed systems, whose successful development requires the integration of all disciplines involved, it is analyzed which requirements there are for these interdisciplinary system architectures in today\u27s development environment. In addition, it is validated on the basis of the investigation environment that interdisciplinary system structures are necessary for the development on the different levels of the system view. In doing so, the investigation environment addresses the concept of extracting customer-relevant features (systems) from a physical-tailored modular system (supersystem) in order to develop and test them autonomously, as well as to transfer them to the entire product range in a standardized manner. The elaboration identifies basic requirements for the development of a knowledge base in interdisciplinary system structures and places them into the context of an agile modular kit development

Model-based probabilistic frequent itemset mining

Data uncertainty is inherent in emerging applications such as location-based services, sensor monitoring systems, and data integration. To handle a large amount of imprecise information, uncertain databases have been recently developed. In this paper, we study how to efficiently discover frequent itemsets from large uncertain databases, interpreted under the Possible World Semantics. This is technically challenging, since an uncertain database induces an exponential number of possible worlds. To tackle this problem, we propose a novel methods to capture the itemset mining process as a probability distribution function taking two models into account: the Poisson distribution and the normal distribution. These model-based approaches extract frequent itemsets with a high degree of accuracy and support large databases. We apply our techniques to improve the performance of the algorithms for (1) finding itemsets whose frequentness probabilities are larger than some threshold and (2) mining itemsets with the {Mathematical expression} highest frequentness probabilities. Our approaches support both tuple and attribute uncertainty models, which are commonly used to represent uncertain databases. Extensive evaluation on real and synthetic datasets shows that our methods are highly accurate and four orders of magnitudes faster than previous approaches. In further theoretical and experimental studies, we give an intuition which model-based approach fits best to different types of data sets. © 2012 The Author(s).published_or_final_versio

What are the benefits of interacting with nature?

There is mounting empirical evidence that interacting with nature delivers measurable benefits to people. Reviews of this topic have generally focused on a specific type of benefit, been limited to a single discipline, or covered the benefits delivered from a particular type of interaction. Here we construct novel typologies of the settings, interactions and potential benefits of people-nature experiences, and use these to organise an assessment of the benefits of interacting with nature. We discover that evidence for the benefits of interacting with nature is geographically biased towards high latitudes and Western societies, potentially contributing to a focus on certain types of settings and benefits. Social scientists have been the most active researchers in this field. Contributions from ecologists are few in number, perhaps hindering the identification of key ecological features of the natural environment that deliver human benefits. Although many types of benefits have been studied, benefits to physical health, cognitive performance and psychological well-being have received much more attention than the social or spiritual benefits of interacting with nature, despite the potential for important consequences arising from the latter. The evidence for most benefits is correlational, and although there are several experimental studies, little as yet is known about the mechanisms that are important for delivering these benefits. For example, we do not know which characteristics of natural settings (e.g., biodiversity, level of disturbance, proximity, accessibility) are most important for triggering a beneficial interaction, and how these characteristics vary in importance among cultures, geographic regions and socio-economic groups. These are key directions for future research if we are to design landscapes that promote high quality interactions between people and nature in a rapidly urbanising world

Pest population dynamics are related to a continental overwintering gradient

Overwintering success is an important determinant of arthropod populations that must be considered as climate change continues to influence the spatiotemporal population dynamics of agricultural pests. Using a long-term monitoring database and biologically relevant overwintering zones, we modeled the annual and seasonal population dynamics of a common pest, Helicoverpa zea (Boddie), based on three overwintering suitability zones throughout North America using four decades of soil temperatures: the southern range (able to persist through winter), transitional zone (uncertain overwintering survivorship), and northern limits (unable to survive winter). Our model indicates H. zea population dynamics are hierarchically structured with continental-level effects that are partitioned into three geographic zones. Seasonal populations were initially detected in the southern range, where they experienced multiple large population peaks. All three zones experienced a final peak between late July (southern range) and mid-August to mid-September (transitional zone and northern limits). The southern range expanded by 3% since 1981 and is projected to increase by twofold by 2099 but the areas of other zones are expected to decrease in the future. These changes suggest larger populations may persist at higher latitudes in the future due to reduced low-temperature lethal events during winter. Because H. zea is a highly migratory pest, predicting when populations accumulate in one region can inform synchronous or lagged population development in other regions. We show the value of combining long-term datasets, remotely sensed data, and laboratory findings to inform forecasting of insect pests

Aesthetic and spiritual values of ecosystems: recognising the ontological and axiological plurality of cultural ecosystem 'services'.

This paper explores spiritual and aesthetic cultural values associated with ecosystems. We argue that these values are not best captured by instrumental or consequentialist thinking, and they are grounded in conceptions of nature that differ from the ecosystem services conceptual framework. To support our case, we engage with theories of the aesthetic and the spiritual, sample the discourse of ‘wilderness’, and provide empirical evidence from the recent UK National Ecosystem Assessment Follow-on Phase. We observe that accounts of spiritual and aesthetic value in Western culture are diverse and expressed through different media. We recognise that humans do benefit from their aesthetic and spiritual experiences of nature. However, aesthetic and spiritual understandings of the value of nature lead people to develop moral responsibilities towards nature and these are more significant than aesthetic and spiritual benefits from nature. We conclude that aesthetic and spiritual values challenge economic conceptions of ecosystems and of value (including existence value), and that an analysis of cultural productions and a plural-values approach are needed to evidence them appropriately for decision-making

2016 New York Sweet Corn Pheromone Trap Network (SCPTN)

NYS IPM Type: Project ReportFor 22 years, the Sweet Corn Pheromone Trap Network has been monitoring the flight of three important insect pests of sweet corn, European corn borer, corn earworm, fall armyworm, and more recently, 2010, Western bean cutworm. These insects cause damage to sweet corn ears in their larval stage. These pests are moths in their adult stage and can be monitored using traps baited with pheromone lures specific for each species. Traps are placed near sweet corn fields to monitor moth flights. The weekly trap catch information allows growers, consultants, Cooperative Extension and vegetable processor field staff to track the flights and make informed decisions about when sweet corn fields need to be scouted or treated with an insecticide. This project was funded in part by in-kind contributions from growers and consultants who host and check traps