LandCover6k goals and methods


Overarching goal

Provide the climate modeling community with information on past land use consisting of:

1. Pollen-based estimates of land-cover change in quantitative terms, i.e. m2/m2 for plant functional types and three land-cover types, i.e. summer-green and evergreen trees and open land.

2. Archaeology/history based information on major land-use types and associated quantifiable variables relevant to global processes such as:

- Burning, use of landscape-scale fire
- Tillage, cropping intensity, m2/m2
- Grazing, intensity, m2/m2 livestock
- Wood harvest, m2/m2
- Irrigation, m2/m2
- Presence of specific crops/domesticates


Methods

We use:

- The ERV model (Parsons and Prentice 1981; Prentice and Parsons 1983) to infer relative pollen productivity (RPP) from modern pollen-vegetation datasets; RPP is a necessary parameter to apply the REVEALS model (see below)

- The REVEALS model (Sugita 2007) to estimate plant cover in % of a 1°x 1° grid cell using Holocene pollen records (LC)

- For comparison, additional pollen-based methods, existing and in development, e.g. modern analogue technique (MAT) and biomization (Davis et al. 2015), pseudobiomization (Fyfe et al. 2010), and STEPPS (Dawson et al. 2016; Williams et al. 2018)

- A global land-use categorization (product of LandCover6k’s first phase (Morrison et al. 2018) to map land-use from archaeological and historical data, and expert-based quantitative estimates of variables related to the land-use categories (LU)

- Methods are developed to implement the REVEALS LC and Archaelogy/History LU in ALCCs (Klein Goldewijk et al; Kaplan et al., in prep).


Work packages

NOTE: for more details, contact the coordinators of LandCover6k or the work package’s coordinators (in brackets, below)

a) Pollen-based REVEALS LC
M.-J. Gaillard

- WP-LC1: N America, Canada, Alaska (ECR Andria Dawson, ECR Mathias Trachsel, ECR Michelle Chaput)
- WP-LC2: Latin and Central America (Sonia Fontana, Thomas Giesecke)
- WP-LC3: Europe (ECR Esther Githumbi, ECR Jessie Woodbridge, Florence Mazier, Ralph Fyfe)
- WP-LU4: Middle East/Eastern Mediterranean/Central Asia (ECR Esther Githumbi, Sandy Harrison, Ulrike Herzschuh)
- WP-LC5: Africa (ECR Esther Githumbi, Rob Marchant, Anne-Marie Lézine)
- WP-LC6: India (ECR Navya Reghu, ECR Parminder Ranhotra, Kryshnamurthi Anupama)
- WP-LC7: China (ECR Furong Li, ECR Xianyong Cao, Qinghai Xu, Zhuo Zheng)
- WP-LC8: Japan (Shinya Sugita, Hikaru Takahara)
- WP-LC9: Australia/Oceania (ECR Michela Mariani, Simon Heberle)

A first priority sub-product will be the Monsoon region (WP-LC4-5-6).

b) Archaeology/history-based LU
Kathy Morrison, Nicki Whitehouse, Marco Madella

- WP-LU1: N America and Central America (Thomas Foster; Andrew Sluyter)
- WP-LU2: Latin America (Umberto Lombardo)
- WP-LU3: Europe (ECR Ferran Antolin, ECR Jan Kolář, Mark Groenhuijzen, Marc Vander Linden, Elena Marinova)
- WP-LU4: Middle East/Eastern Mediterranean/Central Asia (Laura Popova)
- WP-LU5: Africa (ECR Andrea Kay, ECR Colin Courtney Mustaphi, ECR Oliver Boles, Anneli Ekblom, Mats Widgren)
- WP-LU6: S & SE Asia (Andrew Bauer)
- WP-LU7: N & E Asia (ECR Zhao Wanyi, S Xiuqi Fang, S. Alice Yao)
- WP-LU8: Japan (ECR Enrico Crema)
- WP-LU9: Australia/Oceania (ECR Kristyn Hara)

c) ALCC modeling (WP HYDE-KK): Implementation of a) and b) in HYDE and KK
Kees Klein Goldewijk (HYDE) and Jed O Kaplan (KK)

- WP-HYDE-KK1: Revised HYDE and KK for Europe (development of method and test)
- WP-HYDE-KK2: N Hemisphere
- WP-HYDE-KK3: S Hemisphere

d) WP-Clim: co-design of climate modeling experiments with PMIP and CMIP
ECR Kamolphat Atsawawaranunt, Sandy Harrison

 

References

Davis BAS, Collins PM & Kaplan JO (2015) The age and post-glacial development of the modern European vegetation: a plant functional approach based on pollen data. Vegetation History and Archaeobotany 2, 303–317, https://doi.org/10.1007/s00334-014-0476-9.

Dawson A et al. (2016) Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data. Quat Sci Rev 137, 156-175 https://doi.org/10.1016/j.quascirev.2016.01.012

Fyfe RM, Roberts CN & Woodbridge J (2010) A pollen-based pseudo-biomisation approach to anthropogenic land cover change. The Holocene 20(7), 1165-1171. https://doi.org/10.1177/0959683610369509

Morrison K et al. (2018) Global-scale comparisons of human land use: developing shared terminology for land-use practices for global change. Past Global Changes Magazine 26(1), 8-9. https://doi.org/10.22498/pages.26.1.8

Parsons RW & Prentice IC (1981) Statistical approaches to R-values and the pollen— vegetation relationship. Review of Palaeobotany and Palynology, 32(2): 127-152.

Prentice IC & Parsons RW (1983) Maximum Likelihood Linear Calibration of Pollen Spectra in Terms of Forest Composition. Biometrics, 39(4): 1051-1057.

Williams JW et al. (2018) The Neotoma Paleoecology Database, a multiproxy, international, community-curated data resource. Quat Res 89, 156-177. https://doi.org/10.1017/qua.2017.105