Soil characteristics are associated with gradients of big sagebrush canopy structure after disturbance

Abstract

Reestablishing shrub canopy cover after disturbance in semi‐arid ecosystems, such as sagebrush steppe, is essential to provide wildlife habitat and restore ecosystem functioning. While several studies have explored the effects of landscape and climate factors on the success or failure of sagebrush seeding, the influence of soil properties on gradients of shrub canopy structure in successfully seeded areas remains largely unexplored. In this study, we evaluated associations between soil properties and gradients in sagebrush canopy structure in stands that had successfully reestablished after fire and subsequent seeding treatments. Using a dataset collected across the Great Basin, USA, of sagebrush stands that had burned and reestablished between 1986 and 2013, we tested soil depth and texture, soil surface classification, biological soil crusts plus mean historical precipitation, solar heatload, and fire history as modeling variables to explore gradients in sagebrush canopy structure growth in terms of cover, height, and density. Deeper soils were associated with greater sagebrush canopy structure development in terms of plant density and percent cover, coarser textured soils were associated with greater sagebrush cover and density, and more clayey soils were typically associated with greater height. Biological crust presence was also positively associated with enhanced sagebrush canopy growth, but adding more demographically or morphologically explicit descriptions of biocrust communities did not improve explanatory power. Increasing heatload had a negative effect on sagebrush canopy structure growth, and increased mean annual precipitation was only associated with greater sagebrush height. Given that conservation and restoration of the sagebrush steppe ecosystems has become a priority for land managers, the associations we identify between gradients in post‐fire sagebrush canopy structure growth and field‐identifiable soil characteristics may improve planning of land treatments for sagebrush restoration and the understanding of semi‐arid ecosystem functioning and post‐disturbance dynamics.

Rapid Monitoring of the Abundance and Spread of Exotic Annual Grasses in the Western United States Using Remote Sensing and Machine Learning

“…Topography and potential incident solar radiation modify soil temperature and water availability and influence fuel loads (e.g., exotic annual grass abundance) at landscape and community scales (Brooks et al., 2016; Williamson et al., 2020). Edaphic factors are known to strongly influence the structure and function of vegetation in sagebrush ecosystems, where soil surface and profile characteristics can affect canopy growth and morphology via moisture and nutrient availability (Barnard et al., 2019; Nelson et al., 2014). Post‐fire succession has also been generally linked to soil moisture availability, vegetation communities, physiography, and soil‐surface conditions (Barker et al., 2019; Condon & Pyke, 2018; Germino et al., 2018).…”

Assessing vegetation recovery from energy development using a dynamic reference approach

“…We determined mean elevation of each well pad using a 1/3 arc‐second DEM (U.S. Geological Survey, 2017) with hydrological corrections from Optimized Pit Removal software (Soille, 2004). Soil characteristics may influence growth and survival of sagebrush, including soil texture, soil depth, and salinity, among other factors (Barnard et al, 2019; Germino & Reinhardt, 2014; Renne et al, 2019). We therefore used a recent soil properties dataset (Nauman & Duniway, 2020) to represent several important soil variables.…”

Integrating Ecosystem Resilience and Resistance Into Decision Support Tools for Multi-Scale Population Management of a Sagebrush Indicator Species

“…Second, parameters from studies that explicitly model variation in sagebrush recovery processes as a function of underlying R&R can better inform predictions from statetransition models (e.g., Briske et al, 2008;Stringham et al, 2016;Chambers et al, 2017) and subsequent sage-grouse response. Similar to the studies described above, additional meta-analyses of space for time studies describing sagebrush recovery processes (e.g., Knutson et al, 2014;Barnard et al, 2019) following restoration (Pilliod and Welty, 2013;Pilliod et al, 2017b) in the context of spatially explicit R&R layers at coarse to fine scales (e.g., soil moisture and temperature sub-classes) would be especially useful; as would back-in-time approaches (Shi et al, 2017) that leverage extensive time series of archived satellite data (e.g., Landsat) across expansive extents to classify changes in land cover at relatively high resolution (e.g., percentages of functional plant types with 900 m 2 pixels) (Xian et al, 2015) and then relate back to R&R in a similar fashion. For the latter case, Monroe et al (2020) recently utilized a back-intime approach to quantify factors influencing sagebrush recovery on reclaimed well-pads in Wyoming, and found that dynamic variables such as annual precipitation and temperature modified annual rates of change in cover (e.g., engineering resilience) based on more static state-variables such as soil type and topographic position describing general resilience.…”

“…The aforementioned studies contribute to a proliferation of research that explicitly incorporate general R&R into planning and prioritization at the local-scale within the context (implicitly or explicitly) of sage-grouse habitat requirements and distribution at mid-scales (e.g., Knutson et al, 2014;Pyke et al, 2015;Chambers et al, 2017Chambers et al, , 2019bBarnard et al, 2019). However, few have modeled specifically quantified changes in sage-grouse habitat selection post-restoration as a function of predicted land cover responses to underlying general resilience.…”