# Presentation: 698498

## Climate Forecast Tools for Livestock Producers

- Norman Breuer and Kenny Broad (UM)
- Carla Roncoli and Todd Crane (UGA)
- Clyde Fraisse and Peter E. Hildebrand (UF)
- Victor Cabrera (NMSU)
- Presented at the NOAA CDWS Tallahassee October 2007

## Outline

- Three Case Studies
- Beef Cattle in NC Florida
- Dairy DSS Process
- Beef Cattle and Forage DSS Process
- Lessons
- Challenges

## Livestock and Forage in Florida

**1.7 million head of cattle and calves**
- Cattle and calves 		  330M $
- Milk and milk products 	  371M $
- Forage and hay 		  516M $
- Total 				  1.22B $

**Notes:**
Are the values in the table dollars?

## Livestock and Forage in Florida

- Frequent drought conditions
- Severe drought in 2006 and 2007 caused pasture and hay shortage
- 2006 hay production was record low for the past 20 years
- Most cattlemen were forced to feed supplements
- Hay farmers experiencing high fertilizer prices
- To cope with drought, ranchers were weaning early or selling off some animals at lower than average weights

## Research Sites

- Beef Cattle

- Dairy

- Cow-calf

- Case Studies

- Map: Google Earth

## Methodology

## SECC Co-Development Framework

## Beef Cattle North Central Florida

- Four Sondeos (multidisciplinary, conversational, rapid team surveys) conducted, 1999-2001
- Linear program developed from secondary data, Sondeo information, and interviews
- Models calibrated using Participatory Linear Programming (PLP)
- DSSAT and Ceres used for summer and winter pasture crop models, respectively, and connected to the model through stocking rate

- Case study 1

## Steps in Participatory DSS Building

- Identify needs through initial contacts with producers
- Create or adapt models
- Develop prototype DSS using secondary data
- Discuss model with stakeholders

- Cabrera, Breuer et al. 2006, submitted

- Case study 2

## Steps in Participatory DSS Building

- Include farmers, consultants, extension agents, government officials, and university faculty in process
- Elicit input on structure and function of systems, coefficients, parameters, and individual modules
- Develop final DSS and return to stakeholders for validation

- Cabrera, Breuer et al. 2006, submitted

- Case study 2

**Notes:**
It would be better to split this into two slides,

## Dairy DS participation in North Florida

- Dairy DS participation in North Florida

- Case study 2

- We conducted:
- 26 separate stakeholder interactions of
-   different types (Sondeos, focus groups,
-   meetings)
- 90 persons of which
- 38 were farmers or farm managers

**Notes:**
Way too much information on this slide.  It is not clear what a stakeholder is.  Aren’t farmers and farm managers also stakeholders?

## Social Learning

- Collective action rather than individual
- Issues and activities of central concern to community members
- Scientists, practitioners, and producers co-develop technologies
- Increased likelihood of adaptation through adoption of climate-based DSS

- Case study 3

## Background

- Declining profits
- Increased cost of energy (pumping)
- Increased transportation cost
- Pressure from increasing land prices
- Variable climate
- Frequent drought or flood

- Case study 3

## Learning Community

- Buck Island Ranch - MacArthur Agro-ecology Research Center
- Ona Range Cattle Research and Education Center
- Private cattle ranchers in the vicinity

- Case study 3

## Learning Community

- Objective
- Develop methods to help cattle ranching remain viable in South Florida with climate-based DSS
- For this: strong climate component needed

- Case study 3

## Cow-Calf Production in SFL:Drought and Flood

- Cow-Calf Production in SFL:Drought and Flood

*An old-timer saying goes “In SFL you are never more than 3 days away from a flood or 3 weeks away from a drought.”*
- Research needed:
- Climate-production relationships
- Climate and ranch economics
- Potential for hay production
- Sod production
- Sale of water retention or release rights to SFWMD

- Case study 3

## Framework for Social Learning Process

- Case study 3

- Adapted from Christensen and Sriskandarajah 2006

## Expected Results of Social Learning

- Development of local capacity
- Increased understanding of relationship between climate and rates of conception in cows and growth rate of calves
- Operational, open access DSS
- Scientific papers
- Sustainability of industry (label of origin)

- Case study 3

## Results

- Beef cattle CFL

- Dairy cattle NFL

- Beef cattle SFL

## Climate-based forecasts could aid ranch management decisions

- Planting and fertilizing rye-grass mixtures only in years when good stocking possibilities exist
- Savings from buying hay ahead of time before a dry, cold winter
- More plentiful stocking during good rainfall winters

- Case study 1

## In dairy, ENSO phases affect nitrogen leaching and biomass production

- N-leaching is 10% higher during El Niño years
- N-leaching is closely correlated with ENSO-related with occurrence of extreme rainfall events
- Potential responses are adjusting crop sequences to increase N-uptake while maintaining biomass necessary for production

- Cabrera, Breuer et al. 2006

- Case study 2

## Lessons

- Participation is a good beginning
- Social learning is a logical progression from past research
- Potential adaptations exist
- Co-development aids adoption
- Value of climate information may be easier to measure community level where adaptations can be well documented

## Challenges and Opportunities

- Cow-calf is different from single crop
- Multiple variables require better statistical methods
- Climate plays an important role
- Users are intensely interested
- A multidisciplinary approach is needed
- Learning communities must be facilitated in order to develop