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Find video protocols related to scientific articles indexed in Pubmed.
Within-plant bottom-up effects mediate non-consumptive impacts of top-down control of soybean aphids.
PLoS ONE
PUBLISHED: 01-13-2013
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There is increasing evidence that top-down controls have strong non-consumptive effects on herbivore populations. However, little is known about how these non-consumptive effects relate to bottom-up influences. Using a series of field trials, we tested how changes in top-down and bottom-up controls at the within-plant scale interact to increase herbivore suppression. In the first experiment, we manipulated access of natural populations of predators (primarily lady beetles) to controlled numbers of A. glycines on upper (i.e. vigorous-growing) versus lower (i.e. slow-growing) soybean nodes and under contrasting plant ages. In a second experiment, we measured aphid dispersion in response to predation. Bottom-up and top-down controls had additive effects on A. glycines population growth. Plant age and within-plant quality had significant bottom-up effects on aphid size and population growth. However, top-down control was the dominant force suppressing aphid population growth, and completely counteracted bottom-up effects at the plant and within-plant scales. The intensity of predation was higher on upper than lower soybean nodes, and resulted in a non-consumptive reduction in aphid population growth because most of the surviving aphids were located on lower plant nodes, where rates of increase were reduced. No effects of predation on aphid dispersal among plants were detected, suggesting an absence of predator avoidance behavior by A. glycines. Our results revealed significant non-consumptive predator impacts on aphids due to the asymmetric intensity of predation at the within-plant scale, suggesting that low numbers of predators are highly effective at suppressing aphid populations.
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Development and validation of node-based sample units for estimating soybean aphid (Hemiptera: Aphididae) densities in field cage experiments.
J. Econ. Entomol.
PUBLISHED: 09-23-2010
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The soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is currently the most important insect threat to soybean, Clycine max (L.) Merr., production in the North Central United States. Field cage studies are a key tool in investigating the potential of natural enemies and host plant resistance to control this pest. However, a major constraint in the use of cage studies is the limited number of treatments and replicates that can be used as aphid densities frequently become so large as to limit the number of experimental units that can be quantified. One way to overcome this limitation is to develop methods that estimate whole-plant aphid densities based on a reduced sampling plan. Here, we extend an existing method, node-sampling, used for estimating aphid populations in open field conditions and apply it to caged populations. We show that parameters calculated under open field conditions are inappropriate to estimate caged populations. In contrast, using four independent data sets of caged populations and a cross-validation technique, we demonstrate that a three-node sampling unit and a weighted formula provide accurate and robust estimates of whole-plant aphid density. This method reduced the number of aphids counted per plant by and average of 60%, with greater reductions at higher aphid densities. We further demonstrate that nearly identical statistical results were obtained when whole-plant or node-sampling estimates were used in the analysis of two case studies. The reduced sample unit method developed here saves time without sacrificing efficiency so that more plants, replications, or studies can be conducted that will lead to improved soybean aphid management.
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Probability of cost-effective management of soybean aphid (Hemiptera: Aphididae) in North America.
J. Econ. Entomol.
PUBLISHED: 11-27-2009
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Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is one of the most damaging pests of soybean, Glycine max (L.) Merrill, in the midwestern United States and Canada. We compared three soybean aphid management techniques in three midwestern states (Iowa, Michigan, and Minnesota) for a 3-yr period (2005-2007). Management techniques included an untreated control, an insecticidal seed treatment, an insecticide fungicide tank-mix applied at flowering (i.e., a prophylactic treatment), and an integrated pest management (IPM) treatment (i.e., an insecticide applied based on a weekly scouting and an economic threshold). In 2005 and 2007, multiple locations experienced aphid population levels that exceeded the economic threshold, resulting in the application of the IPM treatment. Regardless of the timing of the application, all insecticide treatments reduced aphid populations compared with the untreated, and all treatments protected yield as compared with the untreated. Treatment efficacy and cost data were combined to compute the probability of a positive economic return. The IPM treatment had the highest probability of cost effectiveness, compared with the prophylactic tank-mix of fungicide and insecticide. The probability of surpassing the gain threshold was highest in the IPM treatment, regardless of the scouting cost assigned to the treatment (ranging from $0.00 to $19.76/ha). Our study further confirms that a single insecticide application can enhance the profitability of soybean production at risk of a soybean aphid outbreak if used within an IPM based system.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.