Cite this dataset as
Fleiss, S. (2020). R code to reproduce analyses of aboveground carbon stocks and associated plant diversity in fragmented and continuous forest sites in Sabah, Malaysian Borneo, 2017. NERC Environmental Information Data Centre. (Model). https://doi.org/10.5285/9ff5cdca-b504-4994-8b07-5912ee6aff47
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This model code is available under the terms of the Open Government Licence
R code to reproduce analyses of aboveground carbon stocks and associated plant diversity in fragmented and continuous forest sites in Sabah, Malaysian Borneo, 2017
The R code "analyses_and_figures.R" runs analyses and makes figures of aboveground carbon stocks and associated plant diversity for these sites, as presented in Fleiss et al. (2020)
This R code was created in order to investigate the following: (1) to establish the value of conservation set-asides for increasing oil palm plantation aboveground carbon stocks; (2) to establish whether set-asides with high aboveground carbon stocks can have co-benefits for plant diversity; (3) to compare the carbon stocks and vegetation structure of conservation set-asides with that of continuous forest, including assessing tree regeneration potential by examining variation in seedling density; (4) to examine potential drivers of variation in aboveground carbon stocks of conservation set-asides (topography, degree of fragmentation, and soil parameters); (5) to scale-up the estimates of the aboveground carbon stocks of conservation set-asides, in order to predict average carbon stocks of oil palm plantations with and without set-asides, and for varying coverage of set-asides across the plantation.
Format
Comma-separated values (CSV)
Spatial information
- Study area
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Temporal information
- Temporal extent
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2017-07-21 to 2017-10-28
Provenance & quality
At each site, vegetation was surveyed in 2-3 circular plots spaced 100 m apart along a transect (the smallest fragmented sites had only 2 plots and all other sites had 3). In each plot, living trees and palms, saplings, seedlings, deadwood, and lianas on trees were surveyed in a nested plot design. All living trees, saplings and seedlings were identified to genus, and to species where possible. Field data were collected in collaboration with experienced local botanists. In addition, eight soil parameters were measured from topsoil samples in each plot. Metrics relating to the degree of forest fragmentation in the surrounding landscape were calculated for each plot, using drone (UAV) imagery from an oil palm company. Note that additional measurements (e.g. ground vegetation) are available in the full dataset, which were not included in these analyses (see https://doi.org/10.5285/c67b06b7-c3f6-49a3-baf2-9fc3a72cb98a ).
Related
Related datasets
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Citations
Correspondence/contact details
Author
Other contacts
- Rights holder
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University of York
- Custodian
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NERC EDS Environmental Information Data Centreinfo@eidc.ac.uk
- Publisher
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NERC Environmental Information Data Centreinfo@eidc.ac.uk
Additional metadata
- Topic categories
- biota
environment
farming
planningCadastre - Keywords
- agricultural ecology , Agricultural landscapes , agriculture , Agriculture , biodiversity , Biodiversity , Borneo , Carbon storage , Climate and climate change , climate change mitigation , Conservation set-aside , Ecosystem services , environmental impact of agriculture , Flora , flora (biology) , Forest fragmentation , Land use , Oil palm , Planta , Plant biodiversity , Roundtable on Sustainable Palm Oil , Soil , Sustainable agriculture , tropical forest , Tropical rainforest
- Last updated
- 05 March 2024 08:47
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By accessing or using this dataset, you agree to the terms of the relevant licence agreement(s). You will ensure that this dataset is cited in any publication that describes research in which the data have been used.
This model code is available under the terms of the Open Government Licence
CITE AS: Fleiss, S. (2020). R code to reproduce analyses of aboveground carbon stocks and associated plant diversity in fragmented and continuous forest sites in Sabah, Malaysian Borneo, 2017. NERC Environmental Information Data Centre. https://doi.org/10.5285/9ff5cdca-b504-4994-8b07-5912ee6aff47