A newly updated "Data Logging Temper Tester" should help scientists develop and evaluate improved tactics and chemicals to prevent bee attacks–or lessen their intensity. Newly outfitted with memory and microcontroller chips, the Data Logging Temper Tester is the latest generation of a model originally patented by ARS in 1991. The device logs bees' attempts to sting a black, plastic egg-shaped target about twice the size of a chicken egg. In one experiment, a hive of 40,000 honey bees struck or "pinged" the target more than 700 times in 5 minutes, according to records downloaded from the data logger to a personal computer. By profiling the attack in ten-second intervals, the logger revealed a peak of 80 stings in 10 seconds, or 8 stings per second. Scientists deliberately provoked the colony for this test. Because the target can be suspended at virtually any distance from the hive, the device also reveals how far bees will fly from their home to attack. Of greatest concern are Africanized honey bees in Arizona, California, Nevada, New Mexico and Texas. They sting readily and in great numbers, with little or no provocation.
Carl Hayden Bee Research Center, Tucson, AZ
Hayward G. Spangler, (520) 670-6380, ext. 124, spangler@tucson.ars.ag.gov

ARS scientists in Minnesota are working to make the Snowbelt's early spring weather forecasts more accurate. They've done this by burying heat-measuring plates in the soil below the snow and simultaneously measuring evaporation and heat exchange between the snow surface and the atmosphere. Automated field weather stations add up all of the radiant energy available at the Earth's surface. The scientists then subtract all but one of the ways this energy is used. What they subtract is the energy used to evaporate surface moisture and the energy used to warm air and soil. What remains is the energy used to melt snow. From this, they can predict snowmelt rates over large areas. Available methods for estimating snowmelt rely primarily on computer models, manual snow sampling and automated snow-weighing "pillows" that are more suited to deep snow regions of the mountainous West. The ARS scientists are working with the National Oceanic and Atmospheric Administration to use the new snowmelt estimates to make the computer models more accurate. These models are needed to predict short- and long-term weather and climate, including spring flooding and global climate change. The data are also needed for agricultural models that predict runoff and amounts of chemicals carried offsite in water.
Soil and Water Management Research Unit, St. Paul, MN
John M. Baker, (612) 625-4249, baker@soils.umn.edu

Beef producers can now tap into up-to-date research via a new computer model that helps farmers and ranchers match their herd's feed and genetic resources to best meet market demands. Called DECI, for Decision Evaluator for the Cattle Industry, the user-friendly model explores "what if" management scenarios to help producers avoid costly mistakes or missed opportunities that otherwise might go unrecognized for years. DECI ties several databases together in a way that lets producers use large amounts of research information without being overburdened by it. The model is designed to evolve with the newest research findings. It could eventually help producers determine profits for producing cattle marketed under a premium pricing system based on qualities such as meat leanness rather than carcass weight.
U.S. Meat Animal Research Center, Clay Center, NE
Thomas G. Jenkins, (402) 762-4247, jenkins@email.marc.usda.gov

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