Cover-Biomass Relationships of an Invasive Annual Grass, Bromus Rubens, in the Mojave Desert
Document Type
Article
Publication Date
12-1-2020
Publication Title
Invasive Plant Science and Management
Volume
13
Issue
4
First page number:
288
Last page number:
292
Abstract
Estimates of plant biomass are helpful for many applications in invasive plant science and management, but measuring biomass can be time-consuming, costly, or impractical if destructive sampling is inappropriate. The objective of this study was to assess feasibility of developing regression equations using a fast, nondestructive measure (cover) to estimate aboveground biomass for red brome (Bromus rubens L.), a widespread nonnative annual grass in the Mojave Desert, USA. At three study sites, including one measured for three consecutive years, B. rubens cover spanned 0.1% to 85% and aboveground biomass 1 to 321 g m−2. In log10-transformed linear regressions, B. rubens cover accounted for 68% to 96% of the variance in B. rubens biomass among sites, with all coefficients of determination significant at P < 0.05. For every doubling of percent cover, biomass was predicted to increase by 78%, 83%, and 144% among the three sites. At the site measured for three consecutive years, which ranged in rainfall from 65% to 159% of the long-term average, regression slopes each year differed from other years. Regression results among sites were insensitive to using cover classes (10 classes encompassing 0% to 100% cover) compared with simulated random distribution of integer cover within classes. Biomass of B. rubens was amenable to estimation in the field using cover, and such estimates may have applications for modeling invasive annual plant fuel loads and ecosystem carbon storage.
Keywords
Allometric equations; Double sampling; Fuel modeling; Red brome; Wildfire
Disciplines
Life Sciences | Plant Sciences
Language
English
Repository Citation
Abella, S. R.
(2020).
Cover-Biomass Relationships of an Invasive Annual Grass, Bromus Rubens, in the Mojave Desert.
Invasive Plant Science and Management, 13(4),
288-292.
http://dx.doi.org/10.1017/inp.2020.33