LIVESTOCK RANCHING, RANGELANDS, AND RESILIENCE: ENSURING ADAPTIVE CAPACITY IN AN INCREASINGLY VARIABLE CLIMATE

We focus on five rangeland regions in the Western US: California annual grasslands, cold deserts, northern mixed prairie, shortgrass steppe, and hot deserts. These broad vegetation types represent considerable diversity in precipitation seasonality and variability, temperature, plant functional type composition, land ownership, and production systems. This diversity provides us with opportunities to test hypotheses about the factors selecting natural and social strategies for coping with variability, and to turn this understanding into effective programs to increase adaptive capacity. Focal sites within each region will anchor our work to long-term monitoring datasets, field expertise, and local extension specialists. Our comparative approach capitalizes on geographic differences in current and future climate conditions; we accompany this regional comparison with attention to within-region variability driven by differences in soils, vegetation, disturbances, and local actors. Objective 1: climate exposure1.1 Assess Current Climate Exposure. To evaluate current climate exposure across the focal rangeland regions, we will use climate records from each focal site to characterize trends in mean climate conditions, and interannual climate variability.1.2 Assess Climate Change Impacts. To evaluate future changes in climate, we will use downscaled climate projections. Because a goal is to relate this exposure to human decision-making, we will consider both a short timescale (20 years, within human memory), and a longer timescale (late 21st C, more typical of climate projections).1.3 Quantify Current and Future Soil Moisture Dynamics. To characterize soil water availability patterns, we will use an ecosystem water balance model (SOILWAT), parameterized with soil properties and vegetation composition data for each site and plot1.4 Using Exposure Results in the Co-Development Process. We will incorporate climate exposure into the co-development process in two ways. For the first workshop with producers and managers, we will develop information about exposure in a focal area over the previous 20 years. These data will inform initial interactions with producers and managers to discover what the innovators and early adopters have already done. For the second workshop, we will develop information about future climate scenarios that describe a gradient in business-as-usual (no change), increased variability representative of the focal region in 20 years, increased variability in the region with greatest exposure, and an extreme end of the 21st C scenario. Objective 2: sensitivity2.1 Determine Sensitivity in Forage Production. Using the soil water modeling results generated under Obj. 1, we will regress forage production on growing season soil water availability. Data on plant production, the response variable, will come from two sources. First, we will use direct, field-based estimates of aboveground net primary production collected at sites in each of our focal regions. Our second data source will be remotely-sensed gross and net primary production data derived from Landsat imagery.2.2 Project Future Forage Sensitivities. The production response functions represent a direct measure of climate sensitivity. To integrate climate sensitivity and exposure, we will project the effect of expected future changes in climate variability on the means and variances of forage production.2.3 Determine Sensitivity in Livestock Production. We will use model-based estimates of livestock production, rather than empirical data sets, driven directly by input data on forage quantity and quality, control for variability in management by focusing on “potential livestock production.”2.4 Model Forage Quality. Our starting point for modeling the response of forage quality to precipitation is the data set of Craine et al. (2017), available on Data Dryad. The data set consists of more than 36,000 observations of forage quality (crude protein and digestible organic matter concentration) spanning a 22 year period and distributed across the western US.2.5 Model Potential Livestock Production. We will use a nutritional balance model (NUTBAL) based on the NRC system for determining nutritional requirements and intake rates and further modified by the Angerer lab.2.6 Using Sensitivity Results in Co-development Process. We will incorporate sensitivity into the co-development process (see section 4.3.2 for more details) in two ways. For the first workshop with producers and managers, we will develop information about production and livestock sensitivity in each focal area over the previous 20 years (e.g., from 4.2.1 and 4.2.3). These data will inform the initial interactions with producers and managers about the range of sensitivities that they can expect in their system. For the second workshop, we will combine the future climate scenarios with future sensitivities to allow exploration of possible futures. We will also assess the last component of sensitivity – that of rancher decision making – as part of the second workshops with individual managers. Objective 3: adaptive capacity3.1 Using Production Response Functions to Assess Forage Vegetation Adaptation. Our first step is to consider the variability in sensitivity functions obtained in the forage modeling objective (see section 4.2.2, above). These patterns will be to assess how sensitivity might changes due to species invasions, woody encroachment, disturbances and some types of grazing managements.3.2 Field Campaign to Characterize Vegetation Strategies. We will identify a suite of 20 sites within each focal region that show differences in forage production sensitivities along the lines described above. At each site, we will broadly characterize dominant functional groups, collect leaf tissue samples to assess water use efficiencies (13C), and soil samples to assess seed dormancy-related mechanisms related to bet-hedging. We will also collect seed of 3-4 of the dominant plant species to confirm the patterns measured in the field in greenhouse assessments.3.3 Scenario Analysis to Understand Livestock Producer Adaptation. A co-development process is an excellent vehicle to facilitate the interactions needed to advance the development and use adaptation strategies in the Western ranching livestock sector. Our co-development process will take place over the course of two cumulative workshops in each of the focal research sites.