Post-Fire Seed Dispersal of a Wind-Dispersed Shrub Declined with Distance to Seed Source, yet had High Levels of Unexplained Variation

Plant-population recovery across large disturbance areas is often seed-limited. An understanding of seed dispersal patterns is fundamental for determining natural-regeneration potential. However, forecasting seed dispersal rates across heterogeneous landscapes remains a challenge. Our objectives were to determine (i) the landscape patterning of post-disturbance seed dispersal, and underlying sources of variation and the scale at which they operate, and (ii) how the natural seed dispersal patterns relate to a seed augmentation strategy. Vertical seed trapping experiments were replicated across 2 years and five burned and/or managed landscapes in sagebrush steppe. Multi-scale sampling and hierarchical Bayesian models were used to determine the scale of spatial variation in seed dispersal. We then integrated an empirical and mechanistic dispersal kernel for wind-dispersed species to project rates of seed dispersal and compared natural seed arrival to typical post-fire aerial seeding rates. Seeds were captured across the range of tested dispersal distances, up to a maximum distance of 26 m from seed-source plants, although dispersal to the furthest traps was variable. Seed dispersal was better explained by transect heterogeneity than by patch or site heterogeneity (transects were nested within patch within site). The number of seeds captured varied from a modelled mean of ~13 m−2 adjacent to patches of seed-producing plants, to nearly none at 10 m from patches, standardized over a 49-day period. Maximum seed dispersal distances on average were estimated to be 16 m according to a novel modelling approach using a ‘latent’ variable for dispersal distance based on seed trapping heights. Surprisingly, statistical representation of wind did not improve model fit and seed rain was not related to the large variation in total available seed of adjacent patches. The models predicted severe seed limitations were likely on typical burned areas, especially compared to the mean 95–250 seeds per m2 that previous literature suggested were required to generate sagebrush recovery. More broadly, our Bayesian data fusion approach could be applied to other cases that require quantitative estimates of long-distance seed dispersal across heterogeneous landscapes

Interannual Variation in Climate Contributes to Contingency in Post-Fire Restoration Outcomes in Seeded Sagebrush Steppe

Interannual variation, especially weather, is an often-cited reason for restoration “failures”; yet its importance is difficult to experimentally isolate across broad spatiotemporal extents, due to correlations between weather and site characteristics. We examined post-fire treatments within sagebrush-steppe ecosystems to ask: (1) Is weather following seeding efforts a primary reason why restoration outcomes depart from predictions? and (2) Does the management-relevance of weather differ across space and with time since treatment? Our analysis quantified range-wide patterns of sagebrush (Artemisia spp.) recovery, by integrating long-term records of restoration and annual vegetation cover estimates from satellite imagery following thousands of post-fire seeding treatments from 1984 to 2005. Across the Great Basin, sagebrush growth increased in wetter, cooler springs; however, the importance of spring weather varied with sites\u27 long-term climates, suggesting differing ecophysiological limitations across sagebrush\u27s range. Incorporation of spring weather, including from the “planting year,” improved predictions of sagebrush recovery, but these advances were small compared to contributions of time-invariant site characteristics. Given extreme weather conditions threatening this ecosystem, explicit consideration of weather could improve the allocation of management resources, such as by identifying areas requiring repeated treatments; but improved forecasts of shifting mean conditions with climate change may more significantly aid the prediction of sagebrush recovery

Aerodynamic Roughness Length Estimation with Lidar and Imaging Spectroscopy in a Shrub-Dominated Dryland

The aerodynamic roughness length (Z0m) serves an important role in the flux exchange between the land surface and atmosphere. In this study, airborne lidar (ALS), terrestrial lidar (TLS), and imaging spectroscopy data were integrated to develop and test two approaches to estimate Z0m over a shrub dominated dryland study area in south-central Idaho, USA. Sensitivity of the two parameterization methods to estimate Z0m was analyzed. The comparison of eddy covariance-derived Z0m and remote sensing-derived Z0m showed that the accuracy of the estimated Z0m heavily depends on the estimation model and the representation of shrub (e.g., Artemisia tridentata subsp. wyomingensis) height in the models. The geometrical method (RA1994) led to 9 percent (~0.5 cm) and 25% (~1.1 cm) errors at site 1 and site 2, respectively, which performed better than the height variability-based method (MR1994) with bias error of 20 percent and 48 percent at site 1 and site 2, respectively. The RA1994 model resulted in a larger range of Z0m than the MR1994 method. We also found that the mean, median and 75th percentiles of heights (H75) from ALS provides the best Z0 m estimates in the MR1994 model, while the mean, median, and MLD (Median Absolute Deviation from Median Height), as well as AAD (Mean Absolute Deviation from Mean Height) heights from ALS provides the best Z0m estimates in the RA1994 model. In addition, the fractional cover of shrub and grass, distinguished with ALS and imaging spectroscopy data, provided the opportunity to estimate the frontal area index at the pixel-level to assess the influence of grass and shrub on Z0m estimates in the RA1994 method. Results indicate that grass had little effect on Z0m in the RA1994 method. The Z0m estimations were tightly coupled with vegetation height and its local variance for the shrubs. Overall, the results demonstrate that the use of height and fractional cover from remote sensing data are promising for estimating Z0m, and thus refining land surface models at regional scales in semiarid shrublands

Integration of Weed-Suppressive Bacteria with Herbicides to Reduce Exotic Annual Grasses and Wildfire Problems on ITD Right-of-Ways

Invasion by exotic-annual grasses such as cheatgrass is impacting semiarid rangelands and especially transportation corridors, where it causes increased wildfire and many other environmental issues. Methods of reducing exotic annual grasses and restoring native perennials are needed, particularly testing of their intended target or unintended, non-target effects. In a series of experiments arrayed across different site and plant-community conditions on Idaho Transportation Department right-of-ways, the effects of chemical or biological herbicides, site preparation and co-treatments such as raking, and/or seeding were evaluated over 3 years. Strains of the soil bacterium Pseudomonas fluorescens that are supposedly weed-suppressive were generally ineffective, and resulted in relatively weak effects at a small proportion of plots and only at one site, but also resulted in highly undesirable non-target effects at another site. The chemical herbicides imazapic and especially indaziflam (Rejuvra) tended to have more consistent and stronger effects, and indaziflam furthermore provided a longer period of control, although additional years of observation would be required to assess its endurance. Seeding effects were weak, and preparation of seed conclusion, indaziflam appeared to be the most effective tool for reducing cheatgrass, but techniques for increasing perennials after its application are needed