Climate Averages of Soil-climate for Sagebrush Ecosystems
Soil conditions are a key part of functioning ecosystem and affect the distribution and abundance of plants, forage production, and habitat patterns. The distribution of soil conditions, as well as other environmental factors such as precipitation, temperature, geology, topography, and vegetation determine the patterns and dynamics of wildlife habitats and biodiversity across the landscape. We used long-term averages of precipitation and temperature (1981–2010) to define environment conditions that affect the soil. Using climate averages supports understanding of persistent patterns such as distribution of forests, woodlands, shrublands and grasslands. Variability due to inter-annual differences is removed to focus on dominant vegetation patterns, habitat potential, fire frequency, and ecosystem processes. These efforts are intended to help researchers, wildlife and habitat managers, and policymakers, better understand climate patterns ecological implications, including restoration planning, exotic plant invasion risk to invasion, fuels and fire risk, and drought monitoring.
Background
Soil temperature and moisture (soil-climate) affect plant growth and microbial activity and provide important links between patterns in climate, soils, and flora. However, spatial data of soil-climate that represent variation in space and time have been lacking. By improving our ability to estimate and map soil-climate across large landscapes, we can better investigate important ecological relationships including vegetation abundance, diversity, habitat structure, and productivity. Understanding these relationships can improve restoration efforts, habitat management, mitigating risk of invasion by exotic plants and managing fuels.
Methods
We developed a framework that defines monthly estimates of soil-climate properties (moisture and temperature) using a modified version of the Newhall model that relies on spatial climate data and soil properties defined across the western United States. The Newhall model, originally developed by U.S. Department of Agriculture Natural Resources Conservation Service for non-spatial applications, is a daily simulation of vertical movement of water in a soil matrix.
We modified the Newhall model to include spatial data and other data related to climate data, snowmelt, soil properties affecting water holding capacity, multiple methods of estimating evapotranspiration (the dynamics of transferring water from land to the atmosphere by evaporation and transpiration, which results in the loss of water from plants), inclusion of organic material, air-soil temperature offsets, snow insulation, and improvements to the soil moisture and temperature classification system. We calculated an adjusted precipitation to account for snowmelt using daily snow data, raw precipitation data based on climate stations, and a custom equation. This approach allowed us to establish the appropriate timing of water that can infiltrate soils during snowmelt (Figure 1). For this study, we used climate averages (1981–2010) to estimate 1) soil-climate classes, 2) monthly, seasonal, and annual soil moisture estimates, 3) seasonality of soil moisture, and 4) trends in soil moisture. We also used statistical models to establish the connection between soil-climate conditions and the distribution of vegetation, habitat, and ecosystem processes. For more details see our paper on spatial estimates of soil moisture.
Results
Modeling soil-climate in the western United States using climate averages allowed us to produce high resolution (30 meters) spatial data products: monthly, seasonal, and annual soil moisture estimates; seasonality of soil moisture; and seasonal trends in soil moisture. When we examined soil-climate and vegetation patterns, we found that soil moisture was a good predictor of sagebrush cover, annual herbaceous plant cover, bare ground, and fire occurrence.
Research Implications
High spatial resolution (30 meters) data of soil-climate properties is beneficial for understanding ecological site potential, distribution patterns of species and habitats, the resilience of the system after disturbances, the resistance of invasive species and fires, and the response to restoration and other land treatments. These products can help to better understand the relationship between soil-climate and other landscape conditions. For example, typical (average) patterns in moisture availability from spring into summer are important for plant growth and reproduction in many areas and affect the distribution of habitat and effects of disturbance and treatments. Further, soil-climate seasonality estimates can help understand the variability of soil moisture occurring between seasons (Figure 2), which can have important implications for vegetation patterns, wildlife associations, and risk to invasion of exotic plants and fire. Soil moisture estimates can also be used to investigate their relationships with fire occurrences (Figure 3). Here our objective was to assess whether broader temporal and spatial patterns of soil moisture drive frequency and occurrences in fires.
Future research
The study area is being expanded beyond the sagebrush biome to include all the western United States. We are also developing an alternate evapotranspiration model and additional metrics that combine temperature and moisture (for example, growing period, soil degree days, soil moisture of wettest month). We are evaluating relationships of soil-climate and distributions of conifer pinyon-juniper. Finally, we are continuing to work with field and remote sensing data to investigate relations between soil-climate, vegetation and other land cover and habitat patterns.
Funders
U.S. Geological Survey (Ecosystem Mission Area and Wyoming Landscape Conservation Initiative) and North Central Climate Adaptation Science Center
Soil-climate for Managing Sagebrush Ecosystems
Future Scenarios of Soil-climate for Sagebrush Ecosystems
Soil conditions are a key part of functioning ecosystem and affect the distribution and abundance of plants, forage production, and habitat patterns. The distribution of soil conditions, as well as other environmental factors such as precipitation, temperature, geology, topography, and vegetation determine the patterns and dynamics of wildlife habitats and biodiversity across the landscape. We used long-term averages of precipitation and temperature (1981–2010) to define environment conditions that affect the soil. Using climate averages supports understanding of persistent patterns such as distribution of forests, woodlands, shrublands and grasslands. Variability due to inter-annual differences is removed to focus on dominant vegetation patterns, habitat potential, fire frequency, and ecosystem processes. These efforts are intended to help researchers, wildlife and habitat managers, and policymakers, better understand climate patterns ecological implications, including restoration planning, exotic plant invasion risk to invasion, fuels and fire risk, and drought monitoring.
Background
Soil temperature and moisture (soil-climate) affect plant growth and microbial activity and provide important links between patterns in climate, soils, and flora. However, spatial data of soil-climate that represent variation in space and time have been lacking. By improving our ability to estimate and map soil-climate across large landscapes, we can better investigate important ecological relationships including vegetation abundance, diversity, habitat structure, and productivity. Understanding these relationships can improve restoration efforts, habitat management, mitigating risk of invasion by exotic plants and managing fuels.
Methods
We developed a framework that defines monthly estimates of soil-climate properties (moisture and temperature) using a modified version of the Newhall model that relies on spatial climate data and soil properties defined across the western United States. The Newhall model, originally developed by U.S. Department of Agriculture Natural Resources Conservation Service for non-spatial applications, is a daily simulation of vertical movement of water in a soil matrix.
We modified the Newhall model to include spatial data and other data related to climate data, snowmelt, soil properties affecting water holding capacity, multiple methods of estimating evapotranspiration (the dynamics of transferring water from land to the atmosphere by evaporation and transpiration, which results in the loss of water from plants), inclusion of organic material, air-soil temperature offsets, snow insulation, and improvements to the soil moisture and temperature classification system. We calculated an adjusted precipitation to account for snowmelt using daily snow data, raw precipitation data based on climate stations, and a custom equation. This approach allowed us to establish the appropriate timing of water that can infiltrate soils during snowmelt (Figure 1). For this study, we used climate averages (1981–2010) to estimate 1) soil-climate classes, 2) monthly, seasonal, and annual soil moisture estimates, 3) seasonality of soil moisture, and 4) trends in soil moisture. We also used statistical models to establish the connection between soil-climate conditions and the distribution of vegetation, habitat, and ecosystem processes. For more details see our paper on spatial estimates of soil moisture.
Results
Modeling soil-climate in the western United States using climate averages allowed us to produce high resolution (30 meters) spatial data products: monthly, seasonal, and annual soil moisture estimates; seasonality of soil moisture; and seasonal trends in soil moisture. When we examined soil-climate and vegetation patterns, we found that soil moisture was a good predictor of sagebrush cover, annual herbaceous plant cover, bare ground, and fire occurrence.
Research Implications
High spatial resolution (30 meters) data of soil-climate properties is beneficial for understanding ecological site potential, distribution patterns of species and habitats, the resilience of the system after disturbances, the resistance of invasive species and fires, and the response to restoration and other land treatments. These products can help to better understand the relationship between soil-climate and other landscape conditions. For example, typical (average) patterns in moisture availability from spring into summer are important for plant growth and reproduction in many areas and affect the distribution of habitat and effects of disturbance and treatments. Further, soil-climate seasonality estimates can help understand the variability of soil moisture occurring between seasons (Figure 2), which can have important implications for vegetation patterns, wildlife associations, and risk to invasion of exotic plants and fire. Soil moisture estimates can also be used to investigate their relationships with fire occurrences (Figure 3). Here our objective was to assess whether broader temporal and spatial patterns of soil moisture drive frequency and occurrences in fires.
Future research
The study area is being expanded beyond the sagebrush biome to include all the western United States. We are also developing an alternate evapotranspiration model and additional metrics that combine temperature and moisture (for example, growing period, soil degree days, soil moisture of wettest month). We are evaluating relationships of soil-climate and distributions of conifer pinyon-juniper. Finally, we are continuing to work with field and remote sensing data to investigate relations between soil-climate, vegetation and other land cover and habitat patterns.
Funders
U.S. Geological Survey (Ecosystem Mission Area and Wyoming Landscape Conservation Initiative) and North Central Climate Adaptation Science Center