Improving estimation of woody aboveground biomass in drylands by accounting for disturbances and spatial heterogeneity
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| Title: | Main Title: Improving estimation of woody aboveground biomass in drylands by accounting for disturbances and spatial heterogeneity |
| Descriptions: | Abstract: Existing methodologies for estimating woody aboveground biomass and carbon stored therein have been developed for forests but are not tailored to the vast dryland ecosystems where vegetation is heterogenous and highly disturbed. Still, those methods are widely applied with questionable results and possible problematic implications, not only for biomass quantification but also for disturbance ecology, biodiversity research, and ecosystem service assessments.
We hereby propose a new methodology especially designed to encompass small, disturbed, and irregular woody growth while keeping sampling effort within reasonable limits. Meaningful demographic growth classes are deployed which enable a stratified sampling design and structure a practicable workflow for integration of different allometric models. To account for the high natural and anthropogenic disturbance levels typically shaping dryland vegetation, our method incorporates a detailed damage assessment by harnessing the ecological archive contained in trees. This allows for quantification of biomass losses to certain disturbance agents, uncovers interactive effects between disturbance agents, and enables assessing the impact of disturbance regime shifts. Extrapolation of biomass losses to stand or landscape level also greatly improves the usual reference state comparison approach.
Here, we review the problems of conventional methodologies being applied to drylands, develop and present the improved method proposed by us, and perform a formal method comparison between the two.
Results indicate that the conventional allometric method is systematically underestimating biomass and carbon storage in disturbed dryland ecosystems. The bias is highest where general biomass density is lowest and disturbance impacts are severest. Damage assessment demonstrates a dependency between main disturbance agents (elephants and fire) while generally biomass is decreased by increasing elephant densities.
The method proposed by us is more time consuming than a conventional allometric approach, yet it can cover sufficient areas within reasonable timespans. Consequent higher data accuracy with concomitant applicability to a wider range of research questions are worth the effort. The proposed method can easily be attuned to other ecosystems or research questions, and elements of it may be adapted to fit alternative sampling schemes. Other: This article is a preprint and has not been certified by peer review. The finally published paper can be accessed at: https://doi.org/10.1016/j.ecolind.2021.108466 |
| Identifier: | 10.5880/TRR228DB.5 (DOI) |
| Related Resource: | Is Previous Version Of Text 10.1016/j.ecolind.2021.108466 (DOI) |
Responsible Party
| Creators: | Liana Kindermann (Author), Magnus Dobler (Author), Daniela Niedeggen (Author), Anja Linstädter (Author) |
| Funding Reference: | Deutsche Forschungsgemeinschaft (DFG): CRC/TRR 228: Future Rural Africa: Future-making and social-ecological transformation |
| Publisher: | CRC/TRR228 Database (TRR228DB) |
| Publication Year: | 2020 |
Topic
| Subjects: | Keywords: Biomass, Carbon, Carbon Storage Dynamics, Conservation Areas, Ecology, Ecosystem, National Park, Vegetation, Vegetation Structure, Wildlife |
| Geogr. Information Topic: | Biota |
File Details
| Filename: | Kindermann_etal_MethodPaper_PREPRINT.pdf |
| Data Type: | Text - Text |
| File Size: | 1.6 MB |
| Date: | Available: 07.12.2020 |
| Mime Type: | application/pdf |
| Language: | English |
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| Download Permission: | Free |
| Licence: | None |
Geographic
Metadata Details
| Metadata Creator: | Liana Kindermann |
| Metadata Created: | 07.12.2020 |
| Metadata Last Updated: | 04.01.2022 |
| Subproject: | A1 |
| Funding Phase: | 1 |
| Metadata Language: | English |
| Metadata Version: | V50 |
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| Page Visits: | 1342 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 38 |
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