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

Authors: FERNANDEZ-GUISURAGA, JOSE - University Of Leon; CALVO, LEONOR - University Of Leon; FERNANDES, PAULO - University Of Tras-Os-montes And Alto Douro; HULET, APRIL - Brigham Young University; PERRYMAN, BARRY - University Of Nevada; SCHULTZ, BRAD - University Of Nevada; JENSEN, K. - University Of Idaho; ENTERKINE, JOSH - Boise State University; Boyd, Chad; Davies, Kirk; JOHNSON, DUSTIN - Oregon State University; WOLLSTEIN, KATHERINE - Oregon State University; PRICE, WILLIAM - Oregon State University; ARISPE, SERGIO - Oregon State University

Submitted to: Science of the Total Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/28/2022
Publication Date: 11/30/2022
Citation: Fernandez-Guisuraga, J.M., Calvo, L., Fernandes, P.M., Hulet, A., Perryman, B., Schultz, B., Jensen, K.S., Enterkine, J., Boyd, C.S., Davies, K.W., Johnson, D.D., Wollstein, K., Price, W.J., Arispe, S.A. 2022. Estimates of fine fuel litter biomass in the northern Great Basin reveal increases during short fire-free intervals associated with invasive annual grasses. Science of the Total Environment. 860. Article 160634. https://doi.org/10.1016/j.scitotenv.2022.160634.
DOI: https://doi.org/10.1016/j.scitotenv.2022.160634

Interpretive Summary: Exotic annual grasses invasion has promoted a grass-fire cycle that threatens the sagebrush ecosystem. This is caused by high accumulation rates and persistence of litter from annual species that increases the amount and continuity of fine fuels. We evaluated the potential of remote sensing-derived products to quantitatively estimate litter biomass. We compared remote sensing-derived predictions of litter biomass and to field measured litter biomass. We found that the remote sensing-derived products could be a key instrument to equip rangeland managers with additional information towards fuel management, fire management, and restoration efforts. These results are of interested to fire, fuel, and land managers as well as other scientists.

Technical Abstract: 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.