Non Technical Summary
Droughts are one of the most devastating natural hazards faced by the United States today. Droughts more severe than those of the 1930s and 1950s are likely to occur with greater frequency in the future. These increases in drought frequency and intensity will be accompanied by more intense storms and record wet periods: witness the recent mega-drought in California, broken by a year of unprecedented rainfall. The challenge is not just coping with drought, but ensuring sustainability in a future of both droughts and deluges.The need to plan and implement adaptation strategies is perhaps nowhere more urgent than in the rangeland sector. Rangeland production systems are globally important and highly vulnerable to current and future climate conditions.Managed grazing covers more than 25% of the global land surface, a larger geographic extent than any other form of land use. In the US, 300 million ha of public and private lands are rangelands. Rangelands provide society with goods (e.g., livestock production/food), services (e.g., wildlife habitat, conservation, water quality), and contribute to the livelihood of millions of humans. However, rangelands are typically located in semi-arid and arid regions characterized by low plant productivity, high precipitation variability, and frequent drought. Rangeland managers often have limited financial and social capital, and in many cases are removed from policy makers and governing institutions.Recently the Sustainable Rangeland Roundtable convened university and agency researchers, public and private land managers and producers, and non-governmental organizations to jointly chart a research agenda of usable science for rangeland sustainability. Out of 142 challenges they identified, "understanding and managing for variability" ranked first. Here, we continue this coproduction process - involving intended end users throughout our research enterprise - to develop a framework to assess the sensitivity of rangeland production systemsto climate variability and identify strategies to improve the adaptive capacity in these systems.Our premise is that strategies to implement climate adaptation will be far more effective if they are tailored to local diversity in exposures, sensitivities and adaptation opportunities faced by ranchers and land managers.Some rangelands may simply experience less climatic variability than others, even in the future. Some rangelands may support forage plants particularly well-adapted to variability, while in others forage production may be sensitive to variability but livestock operations have effective strategies for coping with variability. This project will considerdifferences in vulnerability as key considerations in building adaptation strategies.We use a comparative framework that spans five rangeland regions within the Western US. Our approach combines climate modeling and assessment with forage and livestock production models in a co-development framework to build scenarios and assess feasible, effective adaptation strategies.This iterative process combines research and extension to support a co-development of ideas, capitalizing on diverse adaptation strategies across western rangelands. Our outcome will be a strategic framework that reflects the diversity of exposures, sensitivities and capacity to adapt across the Western US, and will result in a handbook, a white paper and interactive tool co-designed by the science and user communities involved.
Animal Health Component
Research Effort Categories
Goals / Objectives
More frequent drought and intense storms require adaptive management practices that enhance resilience to climate variability and stabilize agroecosystem production. Strategies to implement climate adaptation will be far more effective if they are tailored to local diversity in exposures, sensitivities and adaptation opportunities faced by ranchers and land managers.We have three specific objectives:1) EXPOSURE. Determine climate exposure in different Western US rangeland regions and project their exposure in the future.2) SENSITIVITY. Determine forage and livestock production sensitivities to increased climate variability, considering non-linearity and tipping points.3) ADPATIVE CAPACITY. Evaluate effectiveness of different adaptive strategies given regional exposures and sensitivities. We use a place-based coproduction approach, embedding our extension efforts throughout the project framework, to understand on-going adaptations to recent climate variability by the innovators and early adopters and then to explore how those early adaptations may need modification under future climate scenarios.
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. Thisdiversity 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.