Disturbance Response Grouping of Ecological Sites Increases Utility of Ecological Sites and State-and-Transition Models for Landscape Scale Planning in the Great Basin

Plant community responses to historical wildfire in a shrubland–grassland ecotone reveal hybrid disturbance response

“…Ecological sites are partially described as areas that respond similarly to natural disturbances, and responses to fire should therefore be relevant to the development of regional ecological site concepts. Together, our findings suggest that the development of ecological site groups and generalized state-and-transition models (STMs; Bestelmeyer et al 2016 or disturbance response groups (Stringham et al 2016) might be appropriate for this region. 2,3).…”

“…5a, c). Together, our findings suggest that the development of ecological site groups and generalized state-and-transition models (STMs; Bestelmeyer et al 2016 or disturbance response groups (Stringham et al 2016) might be appropriate for this region. Such tools would streamline the communication of key ecosystem dynamics to land managers.…”

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

“…These concepts were made readily operational by classifying existing maps of soil climate that spanned the sagebrush biome into soil temperature and moisture regimes representing a gradient of underlying R&R properties (Maestas et al, 2016;Chambers et al, 2017). At its coarsest scale, soil regimes are aggregated into three categories that index R&R (low, moderate, and high), but use of temperature and moisture subclasses (Chambers et al, 2014(Chambers et al, , 2017(Chambers et al, , 2019aMaestas et al, 2016) along with ecological site potential and collective responses to disturbance (Stringham et al, 2016) can facilitate applications with finer scale and grain (see section: Improving Estimates of Sagebrush Engineering and Spatial Resilience). This spatially explicit tool provided a foundation for triage of sagebrush management efforts across large spatial extents by identifying areas that would likely respond positively to active or passive restoration following disturbance vs. those that likely to respond poorly to restoration and hence prioritized for protection and management actions that enhance resilience (see section: Foundational Tools: Science Framework).…”

“…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.…”

Digital soil mapping for fire prediction and management in rangelands

“…Recommendations associated with fire management may include fire frequencies needed to sustain or alter a given plant community and seed mixes or erosion control strategies to accelerate post-fire recovery. State and transition models can also be used to scale up ecological site information into disturbance response groups that may facilitate post-fire rehabilitation following large fires (Stringham et al 2016). For rangeland landscapes that are at risk of transitioning to communities dominated by non-native, invasive plants, state and transition models provide valuable site-specific predictions regarding changes in and management of vegetation in the face of changing fire regimes.…”