Weather and Society Watch
Cold Advisory for Newborn Livestock: The Stars Aligned
Several years ago, I was informally introduced to the idea of integrating meteorology and social science while on a small commuter plane with three other people during one of my first business trips after moving to Montana. One was a well-known local rancher who just happened to also be the president of the National Cattlemen’s Beef Association. He emphasized to me the enormous importance of weather forecasts to cattle operations and the extent of weather impacts on the industry.
A few years later, I attended the first Weather and Society*Integrated Studies (WAS*IS) workshop in Boulder, Colo., and fortuitous events began transpiring in my professional life and building upon one another until the stars all aligned, and the Cold Advisory for Newborn Livestock (CANL) came to life.
When I attended the WAS*IS workshop, Hurricane Katrina had just occurred, and I think many of us wanted to save the world from weather hazards. It quickly dawned on us that this goal was outside of our sphere of influence, and smaller, more manageable projects were born. My group included Jason Samenow, a climate analyst for the U.S. Environmental Protection Agency (EPA), who was working with Dr. Larry Kalkstein on a team that was developing the Heat Health Guidebook. I quickly learned how important Dr. Kalkstein was in the world of biometeorology after our week in Boulder, listening to discussions mentioning his name.
The WAS*IS project we developed had two components for assessing vulnerability: Heat, which was Jason’s portion of the project and cold, which I worked on. We met again a few months later, and presented our results to our WAS*IS group, but I was still at a loss as to what to do with the information I had gathered and how to apply it.
Several months after I finished the WAS*IS project, our National Weather Service (NWS) office in Glasgow, Mont. was contacted by Dr. Kalkstein. Dr. Kalkstein was interested in expanding his work to look at cold weather impacts and one of his heat/health partners within NWS had suggested our office as a good starting point. Dr. Kalkstein’s work had generally been focused on heat-related mortality, and he was instrumental in the development of heat/health warning systems across the globe. Now that he was hoping to expand into the realm of cold weather, I was starting to see potential connections with my WAS*IS project. We applied for, and received, a grant through the Cooperative Program for Operational Meteorology, Education and Training (COMET) Partnership Program to look at the feasibility of doing a cold-weather warning system in a rural area.
As the project developed, we found that it was very difficult to see any identifiable signal in mortality data for humans during arctic outbreaks. The human population in northeastern Montana (approximately 50,000 people), and across the northern Great Plains, is simply too small to yield statistically significant relationships between mortality in any season and the synoptic-scale weather pattern. We researched the main impacts from cold weather in the region and found that livestock losses had a huge impact in Montana.
Thus, the project focus shifted from looking at the feasibility of developing a cold warning system for humans to that of developing such a system for livestock. It is much easier to identify relationships between livestock mortality and weather because the animals are generally exposed to the environment at all times and because there is a much larger cattle population than human population in the area. There are approximately 2.4 million head of cattle in the state of Montana, but the human population has yet to reach one million (USDA-NASS 2008, U.S. Census Bureau 2007). In 2005, weather-related calf losses resulted in a loss of approximately $6.3 million in Montana alone (USDA-NASS 2006). It turns out that cold greatly affects cattle—and cattle producers—across the country; nationally, approximately 95,000 calves die each year due to cold stress (Azzam et al. 1993), resulting in an estimated $38 million loss to producers (Dietz et al. 2003). It was obvious that mitigating this loss would be in keeping with the NWS’s mission “for the protection of life and property and the enhancement of the national economy.”
With this information, Dr. Kalkstein brought in Dr. Katrina Frank, who has a background in animal science and bioclimatology, to assist with the project. This collaboration was essential to the successful completion of the project because Dr. Frank’s background in livestock production, specifically biothermal responses, gave us an understanding of the biology and production systems of animals that was lacking among the previous team members. As I got to know Katrina better through our monthly conference calls, I encouraged her to apply for the annual summer WAS*IS workshop, both because of her potential contributions to the workshop and to help bring more WAS*IS collaboration into the project. More stars were aligning as she was selected to attend the workshop in 2007 and better understand the connection from research to operations to end users.
For this project to accomplish the goal of developing a warning system for livestock that would be utilized by producers in the area, it was necessary that operational products and their impacts be connected with the needs of the products’ users. It was useless for us, as product developers, to create a product without first consulting the end users to ensure that the proposed product would meet their needs. In order to determine what those needs were, we incorporated some of the methods learned in WAS*IS about qualitative and quantitative survey methods and asked a few of the livestock producers in northeastern Montana what they needed from us. Only once we had gathered information about what product(s) would be useful to the stakeholders could we proceed with development of an operational advisory system.
We received input from ranchers in northeastern Montana who were weather spotters, cooperative weather observers, or known by the NWS to have a significant interest in weather. One rancher even sat down with two of us to discuss our questions in detail. He provided further explanations on cattle, cattle production, and actions taken during inclement weather. He was very pleased that we were undertaking a project that he felt would benefit his ranching operations.
Overall, the producers identified newborn calves as the animals of most concern to them in harsh weather conditions. They are “concerned with calf losses during calving season” (producer with 500 head of cattle, Valley Co., Mont.) because “calves are our saleable product, so no calves, no sales, no income” (producer with 300 head of cattle, Prairie Co., Mont.).
An unintended, but quite fortuitous, result of reaching out to the ranching community was that we were able to strengthen our relationships with cattle producers who were happy to see us showing an interest in their livelihoods and working on a system that would help them. By incorporating the ranchers’ input from the start, we knew that we were working on something that would be economically beneficial to an end user.
We developed a preliminary database of several weather events that resulted in calf losses based on the information provided by the ranchers. We added to the database by reviewing events entered into the NWS Storm Data database that mentioned livestock losses. This brought us a total of eight significant events to review. We then looked further into the climate data during those events, exploring variables such as:
Having these data allowed us to see the range of weather events that had caused losses, or were deemed “significant” by the producers.
Given that our database did not yield enough events that had resulted in calf losses to develop a statistically significant weather/mortality relationship, we had to incorporate the producers’ and Dr. Frank’s knowledge of how calves respond to cold and do a literature review to generate a decision tree for advisory issuance. Through this process, we identified a ‘newborn’ calf as one that was less than 24-hours old because these calves are least able to regulate their body temperature (Sanko et al. 1991).
In keeping with the spirit of WAS*IS to involve the end users as much as possible, Dr. Frank and I organized a user’s workshop the summer before the system was to debut, and she was able to fly to Montana to attend and to meet some of the key users who were providing us feedback. The goal was to show the livestock community what we had developed and to get their feedback on the draft decision tree before it was implemented. We also got feedback on what they expected as a final outcome, how they wanted to access the data, what the final format should look like and how often they needed the information. This workshop was held twice, once during the afternoon and a second time during the morning, to allow as many attendees to come as possible. We were able to tweak the system based on their feedback and develop the documentation needed for NWS to run the system experimentally.
One of the most difficult tasks we encountered was finding a name for the system we had developed. The team eventually decided on Cold Advisory for Newborn Livestock (CANL). Some had suggested the Livestock Advisory, but that was very similar to an outdated product that NWS had issued many years ago. It also implied that a watch, warning or advisory would be issued, and that was not the goal of this system. The intention was to aid producers with a decision support system to prepare for hazardous weather.
The CANL system was run in an experimental mode from February through May 2009 in northeastern Montana. The graphics were displayed on the NWS Glasgow website, where there was a link that allowed people to provide feedback on the system. We received just eight responses through the online feedback, but we did have ranchers who called us and spoke to us in person. One of the first calls was from an elderly man who had dial-up Internet access. He didn’t really understand some of the data and functionality of the web site (e.g., we used “RH” instead of “Relative Humidity”; the initial images were too small, but clicking on them enlarged them), and based on my 30-minute discussion with him we were able to go back and make some great improvements to the webpage. Pre-testing the webpage would have been a good idea, one that we won’t forget in the future!
We advertised the system in a variety of ways including agricultural newsletters, NWS newsletters, on the NWS Glasgow homepage, through the local media, and by mailing information to known livestock producers in northeastern Montana. Getting the word out to the public is ongoing and a very important aspect of continuing the CANL system.
In the fall of 2009, we held another users’ workshop to get feedback after the system had run for a season. Drs. Frank and Kalkstein were able to attend via teleconference. At this workshop, we showed the producers some of the events and forecasts from the previous winter. After reviewing many of the events and non-events, we collected the feedback and modified the decision tree and criteria slightly.
From the onset, we felt that a huge challenge would be expanding the system to other areas of the country. However, during the winter of 2008-2009, the Dakotas and southeastern Montana were hit with many significant winter storms. There were headlines almost daily tallying livestock losses, with economic losses reaching millions of dollars. The NWS offices in Aberdeen, S.D., Billings, Mont., Bismarck, N.D., and Great Falls, Mont., all joined in to be part of the CANL system experimental test period starting January 18, 2010, and running through May 31, 2010.
While in the end, we aren’t saving the world as I had hoped after Hurricane Katrina, we are making a difference to the people who are using the CANL system and those who hopefully will use the system in the near future. A chance discussion with a rancher, an incredible workshop, new collaborations, partnerships, friendships, and a lot of hard work helped align those stars to be bright enough to make a difference in our corner of the world. The elderly rancher who had dial-up ended his call with, “I’ll be using this day and night during calving season. Thank you!”
*Tanja Fransen (Tanja.Fransen@noaa.gov) is the Warning Coordination Meteorologist for the National Weather Service office in Glasgow, Montana. She is also a proud participant in and champion of the Weather and Society * Integrated Studies (WAS*IS) workshop series.
**Dr. Katrina Frank (email@example.com) is currently in Enterprise, Alabama, and working with Dr . Larry Kalkstein on various research projects for the University of Miami’s Synoptic Climatology Laboratory. She is also a strong supporter and participant from the Weather and Society * Integrated Studies Workshop.
This project was inspired by Lynn Cornwell (1951-2008) and set in motion by Julie Adolphson and Dr. Larry Kalkstein through a grant from the COMET Partnership Project, (S07-62730). Those who assisted with the project include, Tom Salem, Corey Bogel, Don Simonsen and Bill Martin (NWS Glasgow) and Scott Sheridan (Kent State).
Azzam, S. M., J. E. Kinder, M. K. Nielsen, L. A. Werth, K. E. Gregory, L. V. Cundiff and R. M. Koch, 1993: Environmental Effects on Neonatal Mortality of Beef Calves. Journal of Animal Science. 71:282-290.
Dietz, R. E., J. B. Hall, W. D. Whittier, F. Elvinger, and D. E. Eversole, 2003: Effects of feeding supplemental fat to beef cows on cold tolerance in newborn calves. Journal of Animal Science. 81:885-894.
Sanko, R. L., M. J. Guthrie, and R. D. Randel, 1991: Response to environmental temperatures in Brahman calves during the first compared to the second day after birth. Journal of Animal Science. 69:4419-4427.
United States Census Bureau. 2007. National and State Population Estimates. [Accessed 18 March, 2008, from http://www.census.gov/popest/states/NST-ann-est.html].
United States Department of Agriculture – National Agricultural Statistics Service. 2008. Montana Data – Cattle & Calves, Cattle Inventory – January 1. [Accessed 18 March, 2008, from http://www.nass.usda.gov/QuickStats/PullData_US.jsp].
United States Department of Agriculture – National Agricultural Statistics Service. 2006. 2005 Montana and United States Cattle Predator Losses. [Accessed 17 March, 2008, from http://www.nass.usda.gov/Statistics_by_State/Montana/Publications/Press_Releases_Livestock/catprdls.htm].