Allometric Estimates of Aboveground Biomass Using Cover and Height Are Improved by Increasing Specificity of Plant Functional Groups in Eastern Australian Rangelands

Chieppa, Jeff; Power, Sally A.; Tissue, David T.; Nielsen, Uffe N.

doi:10.1016/j.rama.2020.01.009

Cited by 21 publications

(27 citation statements)

References 45 publications

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“…The high goodness-of-fits and low average prediction errors (Table 1 and Table S2) indicate accuracy was as good as conventional in situ allometric approaches reported in the literature (Chieppa et al, 2020;Cunliffe et al, 2020b;Huenneke et al, 2001;Muldavin et al, 2008;Rudgers et al, 2019). Species-level model slopes were generally similar within but different among, PFTs, indicating these relationships appear generally transferrable between species within PFTs (Chieppa et al, 2020;Paul et al, 2016), particularly for the bettersampled types such as graminoids and shrubs, although phenotypic and phenological variation will always limit accuracy (Paul et al, 2016;Poley & McDermid, 2020;Rudgers et al, 2019).…”

Section: Discussionmentioning

confidence: 63%

Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems

Cunliffe

Anderson

Boschetti

et al. 2021

Remote Sens Ecol Conserv

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Section: Discussionmentioning

confidence: 63%

Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems

Cunliffe

Anderson

Boschetti

et al. 2021

Remote Sens Ecol Conserv

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“…This may not occur, however, if other morphological trade-offs accompany the increase in height that keep biomass per plant constant and do not affect cover. In terms of consistency of biomass estimates, including plant height with cover has not necessarily increased coefficients of determination (Chieppa et al 2020). Some authors noted that recording an average height of a group of plants might not improve biomass estimation, such as when height distribution among individuals is bimodal, and that measuring the height of each individual plant could be as time-consuming as simply measuring biomass directly Figure 1.…”

Section: Factors In Cover-biomass Relationshipsmentioning

confidence: 99%

“…As a key measure of ecosystems, plant biomass is needed to model features such as productivity, forage availability, carbon storage, and fuel loads (Chieppa et al 2020). In invasive plant science and management, biomass estimates for nonnative plants can quantify species dominance, how invasions alter ecosystem productivity, and effectiveness of management actions such as reducing hazardous fuels produced by nonnative plants (Casady et al 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Not all species are suited for estimating biomass from cover, however, and consistency of cover-biomass relationships varies among species (e.g., Humphrey 1985;MacDonald et al 2012;Tausch 1989). As a result, assessing which species and growth forms have reliable cover-biomass relationships, developing new biomass equations for species without known relationships, and refining existing equations (e.g., tailoring to site factors or climatic variability) represent an active research area (e.g., Chieppa et al 2020;Ónodi et al 2017;Rudgers et al 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Abella: Cover-biomass estimation (Axmanová et al 2012;Chieppa et al 2020;Muukkonen et al 2006). While being inclusive of assessing these considerations, evaluating in future research whether including height as a covariate improves cover-biomass equations is warranted, because average height of mature B. rubens can vary at least threefold among sites and likely with differences in weather, competition, and genetics (Wu and Jain 1978).…”

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confidence: 99%

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Cover–biomass relationships of an invasive annual grass, Bromus rubens, in the Mojave Desert

Abella

2020

Invasive plant sci. manag.

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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, non-destructive measure (cover) to estimate aboveground biomass for red brome (Bromus rubens L.), a widespread non-native annual grass in the Mojave Desert, USA. At three study sites, including one measured for three consecutive years, B. rubens cover spanned 0.1-85% and aboveground biomass 1-321 g m-2. In log10-transformed linear regressions, B. rubens cover accounted for 68-96% 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 65-159% 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 0-100% 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. Management Implications By altering biomass structure, invasion of non-native grasses has changed fuels and fire behavior in drylands. Modeling fuels and many other features of non-native plants requires estimates of biomass, which can be time consuming or infeasible to measure directly. As an alternative, this study developed regression equations to estimate biomass from the rapid, non-destructive measure of plant cover for red brome (Bromus rubens L.), a pervasive, non-native annual grass in the Mojave Desert, USA. For every doubling of B. rubens cover, predicted B. rubens biomass increased by 78-144% among sites. In applying the equations to estimate fire-risk thresholds of hazardous fuels using cover, a provisional threshold of 100 g m-2 of B. rubens biomass required for fire spread was exceeded at 19, 25, and 45% B. rubens cover among sites. The equations, and suggested refinements in future work, may be helpful for rapidly estimating fuel loads and assessing effectiveness of invasive plant management, including levels required to keep fuels below wildfire spread risk thresholds. Accompanying the equations, a photographic guide showing cover classes and their associated biomass is provided.

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Allometric relationships and trade‐offs in 11 common Mediterranean‐climate grasses

Gao,

Koven,

Kueppers

2024

Ecological Applications

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Biomass allocation in plants is the foundation for understanding dynamics in ecosystem carbon balance, species competition, and plant–environment interactions. However, existing work on plant allometry has mainly focused on trees, with fewer studies having developed allometric equations for grasses. Grasses with different life histories can vary in their carbon investment by prioritizing the growth of specific organs to survive, outcompete co‐occurring plants, and ensure population persistence. Further, because grasses are important fuels for wildfire, the lack of grass allocation data adds uncertainty to process‐based models that relate plant physiology to wildfire dynamics. To fill this gap, we conducted a greenhouse experiment with 11 common California grasses varying in photosynthetic pathway and growth form. We measured plant sizes and harvested above‐ and belowground biomass throughout the life cycle of annual species, while for the establishment stage of perennial grasses to quantify allometric relationships for leaf, stem, and root biomass, as well as plant height and canopy area. We used basal diameter as a reference measure of plant size. Overall, basal diameter is the best predictor for leaf and stem biomass, height, and canopy area. Including height as another predictor can improve model accuracy in predicting leaf and stem biomass and canopy area. Fine root biomass is a function of leaf biomass alone. Species vary in their allometric relationships, with most variation occurring for plant height, canopy area, and stem biomass. We further explored potential trade‐offs in biomass allocation across species between leaf and fine root, leaf and stem, and allocation to reproduction. Consistent with our expectation, we found that fast‐growing plants allocated a greater fraction to reproduction. Additionally, plant height and specific leaf area negatively influenced the leaf‐to‐stem ratio. However, contrary to our hypothesis, there were no differences in root‐to‐leaf ratio between perennial and annual or C4 and C3 plants. Our study provides species‐specific and functional‐type‐specific allometry equations for both above‐ and belowground organs of 11 common California grass species, enabling nondestructive biomass assessment in California grasslands. These allometric relationships and trade‐offs in carbon allocation across species can improve ecosystem model predictions of grassland species interactions and environmental responses through differences in morphology.

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Allometric Estimates of Aboveground Biomass Using Cover and Height Are Improved by Increasing Specificity of Plant Functional Groups in Eastern Australian Rangelands

Cited by 21 publications

References 45 publications

Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems

Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems

Cover–biomass relationships of an invasive annual grass, Bromus rubens, in the Mojave Desert

Allometric relationships and trade‐offs in 11 common Mediterranean‐climate grasses

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