Breaking Dormancy and Increasing Restoration Success of Native Penstemon Species Using Gibberellic Acid Seed Coatings and U-Shaped Furrows.

Many plant species exhibit strong seed dormancy. This attribute benefits the species' long-term survival but can impede restoration when rapid establishment is required. Soaking seeds in gibberellic acid (GA3) can overcome dormancy and increase germination but this treatment may not be effective outside the laboratory. An easier and potentially more effective method to apply this hormone is to coat seeds with a GA3-impregnated polymer. Seed dormancy can also be mitigated by creating a favorable microsite with increased soil moisture. We compared the emergence and establishment of penstemon seeds coated with GA3 to those of uncoated seeds planted in shallow drill rows versus deep, U-shaped furrows. Overall, 6 times more Palmer's penstemon (Penstemon palmeri; p < 0.01) and 21 times more thickleaf penstemon (P. pachyphyllus; p < 0.001) established when coated with GA3, but GA3 coating did not affect the establishment of firecracker penstemon (P. eatonii; p = 1). Establishment was higher from deep furrows than shallow rows (p < 0.001). These results indicate that GA3 seed coating and deep, U-shaped furrows may improve the restoration success of some native forbs by breaking dormancy and providing a favorable microsite. Land managers could use these techniques to restore native forbs in dry, disturbed areas.

Estimates of fine fuel litter biomass in the northern Great Basin reveal increases during short fire-free intervals associated with invasive annual grasses.

Exotic annual grasses invasion across northern Great Basin rangelands has promoted a grass-fire cycle that threatens the sagebrush (Artemisia spp.) steppe ecosystem. In this sense, high accumulation rates and persistence of litter from annual species largely increase the amount and continuity of fine fuels. Here, we highlight the potential use and transferability of remote sensing-derived products to estimate litter biomass on sagebrush rangelands in southeastern Oregon, and link fire regime attributes (fire-free period) with litter biomass spatial patterns at the landscape scale. Every June, from 2018 to 2021, we measured litter biomass in 24 field plots (60 m × 60 m). Two remote sensing-derived datasets were used to predict litter biomass measured in the field plots. The first dataset used was the 30-m annual net primary production (NPP) product partitioned into plant functional traits (annual grass, perennial grass, shrub, and tree) from the Rangeland Analysis Platform (RAP). The second dataset included topographic variables (heat load index -HLI- and site exposure index -SEI-) computed from the USGS 30-m National Elevation Dataset. Through a frequentist model averaging approach (FMA), we determined that the NPP of annual and perennial grasses, as well as HLI and SEI, were important predictors of field-measured litter biomass in 2018, with the model featuring a high overall fit (R2 = 0.61). Model transferability based on extrapolating the FMA predictive relationships from 2018 to the following years provided similar overall fits (R2 ≈ 0.5). The fire-free period had a significant effect on the litter biomass accumulation on rangelands within the study site, with greater litter biomass in areas where the fire-free period was <10 years. Our findings suggest that the proposed remote sensing-derived products could be a key instrument to equip rangeland managers with additional information towards fuel management, fire management, and restoration efforts.

Inducing rapid seed germination of native cool season grasses with solid matrix priming and seed extrusion technology.

There is a need to develop effective techniques for establishing native vegetation in dryland ecosystems. We developed a novel treatment that primes (hydrates) seeds in a matrix of absorbent materials and bio-stimulants and then forms the mixture into pods for planting. In the development process, we determined optimal conditions for priming seeds and then compared seedling emergence from non-treated seeds, non-primed-seed pods, and primed-seed pods. Emergence trials were conducted on soils collected from a hillslope and ridgetop location on the Kaibab Plateau, Arizona, USA. Poa fendleriana and Pseudoroegneria spicata were used as test species. Seeds were primed from -0.5 to -2.5 MPa for up to 12 d. Seeds primed under drier conditions (-1.5 to -2.5 MPa) tended to have quicker germination. Days to 50% emergence for primed-seed pods was between 66.2 to 82.4% faster (5.2 to 14.5 d fewer) than non-treated seeds. Seedling emergence from primed-seed pods for P. fendleriana was 3.8-fold higher than non-treated seeds on the ridgetop soil, but no difference was found on the other soil. Final density of P. spicata primed-seed pods were 2.9 to 3.8-fold higher than non-treated seeds. Overall, primed-seed pods show promise for enhancing germination and seedling emergence, which could aid in native plant establishment.

An object-based image analysis of pinyon and juniper woodlands treated to reduce fuels.

Mechanical and prescribed fire treatments are commonly used to reduce fuel loads and maintain or restore sagebrush steppe rangelands across the Great Basin where pinyon (Pinus) and juniper (Juniperus) trees are encroaching and infilling. Geospatial technologies, particularly remote sensing, could potentially be used in these ecosystems to (1) evaluate the longevity of fuel reduction treatments, (2) provide data for planning and designing future fuel-reduction treatments, and (3) assess the spatial distribution of horizontal fuel structure following fuel-reduction treatments. High-spatial resolution color-infrared imagery (0.06-m pixels) was acquired for pinyon and juniper woodland plots where fuels were reduced by either prescribed fire, tree cutting, or mastication at five sites in Oregon, California, Nevada, and Utah. Imagery was taken with a Vexcel UltraCam X digital camera in June 2009. Within each treatment plot, ground cover was measured as part of the Sagebrush Steppe Treatment Evaluation Project. Trimble eCognition Developer was used to classify land cover classes using object-based image analysis (OBIA) techniques. Differences between cover estimates using OBIA and ground-measurements were not consistently higher or lower for any land cover class and when evaluated for individual sites, were within ±5 % of each other. The overall accuracy and the K hat statistic for classified thematic maps for each treatment were: prescribed burn 85 % and 0.81; cut and fell 82 % and 0.77, and mastication 84 % and 0.80. Although cover assessments from OBIA differed somewhat from ground measurements, they are sufficiently accurate to evaluate treatment success and for supporting a broad range of management concerns.