scholarly journals Mapping past human land use using archaeological data: A new classification for global land use synthesis and data harmonization

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0246662 ◽  
Author(s):  
Kathleen D. Morrison ◽  
Emily Hammer ◽  
Oliver Boles ◽  
Marco Madella ◽  
Nicola Whitehouse ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Classification Scheme ◽  
Earth System ◽  
Land Use Systems ◽  
System Models ◽  
The Past ◽  
The Earth ◽  
Earth System Models ◽  
Past Land Use

In the 12,000 years preceding the Industrial Revolution, human activities led to significant changes in land cover, plant and animal distributions, surface hydrology, and biochemical cycles. Earth system models suggest that this anthropogenic land cover change influenced regional and global climate. However, the representation of past land use in earth system models is currently oversimplified. As a result, there are large uncertainties in the current understanding of the past and current state of the earth system. In order to improve representation of the variety and scale of impacts that past land use had on the earth system, a global effort is underway to aggregate and synthesize archaeological and historical evidence of land use systems. Here we present a simple, hierarchical classification of land use systems designed to be used with archaeological and historical data at a global scale and a schema of codes that identify land use practices common to a range of systems, both implemented in a geospatial database. The classification scheme and database resulted from an extensive process of consultation with researchers worldwide. Our scheme is designed to deliver consistent, empirically robust data for the improvement of land use models, while simultaneously allowing for a comparative, detailed mapping of land use relevant to the needs of historical scholars. To illustrate the benefits of the classification scheme and methods for mapping historical land use, we apply it to Mesopotamia and Arabia at 6 kya (c. 4000 BCE). The scheme will be used to describe land use by the Past Global Changes (PAGES) LandCover6k working group, an international project comprised of archaeologists, historians, geographers, paleoecologists, and modelers. Beyond this, the scheme has a wide utility for creating a common language between research and policy communities, linking archaeologists with climate modelers, biodiversity conservation workers and initiatives.

scholarly journals Plant functional type mapping for earth system models

2011 ◽  
Vol 4 (3) ◽  
pp. 2081-2121 ◽  
Author(s):  
B. Poulter ◽  
P. Ciais ◽  
E. Hodson ◽  
H. Lischke ◽  
F. Maignan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Climate Variability ◽  
Forest Cover ◽  
Plant Functional Type ◽  
Earth System ◽  
Functional Type ◽  
System Models ◽  
Satellite Sensors ◽  
Earth System Models

Abstract. The sensitivity of global carbon and water cycling to climate variability is coupled directly to land cover and the distribution of vegetation. To investigate biogeochemistry-climate interactions, earth system models require a representation of vegetation distributions that are either prescribed from remote sensing data or simulated via biogeography models. However, the abstraction of earth system state variables in models means that data products derived from remote sensing need to be post-processed for model-data assimilation. Dynamic global vegetation models (DGVM) rely on the concept of plant functional types (PFT) to group shared traits of thousands of plant species into just several classes. Available databases of observed PFT distributions must be relevant to existing satellite sensors and their derived products, and to the present day distribution of managed lands. Here, we develop four PFT datasets based on land-cover information from three satellite sensors (EOS-MODIS 1 km and 0.5 km, SPOT4-VEGETATION 1 km, and ENVISAT-MERIS 0.3 km spatial resolution) that are merged with spatially-consistent Köppen-Geiger climate zones. Using a beta (β) diversity metric to assess reclassification similarity, we find that the greatest uncertainty in PFT classifications occur most frequently between cropland and grassland categories, and in dryland systems between shrubland, grassland and forest categories because of differences in the minimum threshold required for forest cover. The biogeography-biogeochemistry DGVM, LPJmL, is used in diagnostic mode with the four PFT datasets prescribed to quantify the effect of land-cover uncertainty on climatic sensitivity of gross primary productivity (GPP) and transpiration fluxes. Our results show that land-cover uncertainty has large effects in arid regions, contributing up to 30 % (20 %) uncertainty in the sensitivity of GPP (transpiration) to precipitation. The availability of plant functional type datasets that are consistent with current satellite products and adapted for earth system models is an important component for reducing the uncertainty of terrestrial biogeochemistry to climate variability.

scholarly journals Use of various remote sensing land cover products for PFT mapping over Siberia

2013 ◽  
Vol 6 (1) ◽  
pp. 255-296
Author(s):  
C. Ottlé ◽  
J. Lescure ◽  
F. Maignan ◽  
B. Poulter ◽  
T. Wang ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Land Surface ◽  
Land Cover Classification ◽  
Classification Systems ◽  
Tree Cover ◽  
Surface Model ◽  
Earth System ◽  
System Models ◽  
Earth System Models

Abstract. High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover datasets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing earth system models. Earth system models also require specific land cover classification systems based on plant functional types, rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover datasets against one another and with auxiliary data to identify key uncertainties that contribute to variability in Plant Functional Type (PFT) classifications that would introduce errors in earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, continuous vegetation fields (MODIS-VCF) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover dataset, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFTs maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT dataset, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground-truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to better represent the water and carbon cycles in northern latitudes. Updated land cover datasets are critical for improving and maintaining the relevance of earth system models for assessing climate and human impacts on biogeochemistry and biophysics. The new PFT map at 5 km scale is available for download from the PANGAEA website, at: doi:10.1594/PANGAEA.810709.

scholarly journals Next generation framework for aquatic modeling of the Earth System

2009 ◽  
Vol 2 (1) ◽  
pp. 279-307 ◽  
Author(s):  
B. M. Fekete ◽  
W. M. Wollheim ◽  
D. Wisser ◽  
C. J. Vörösmarty
Keyword(s):  
Model Development ◽  
Learning Curves ◽  
Earth System ◽  
Next Generation ◽  
Model Calculations ◽  
System Models ◽  
The Earth ◽  
Wide Range ◽  
Spatial Domains ◽  
Earth System Models

Abstract. Earth System model development is becoming an increasingly complex task. As scientists attempt to represent the physical and bio-geochemical processes and various feedback mechanisms in unprecedented detail, the models themselves are becoming increasingly complex. At the same time, the complexity of the surrounding IT infrastructure is growing as well. Earth System models must manage a vast amount of data in heterogeneous computing environments. Numerous development efforts are on the way to ease that burden and offer model development platforms that reduce IT challenges and allow scientists to focus on their science. While these new modeling frameworks (e.g. FMS, ESMF, CCA, OpenMI) do provide solutions to many IT challenges (performing input/output, managing space and time, establishing model coupling, etc.), they are still considerably complex and often have steep learning curves. The Next generation Framework for Aquatic Modeling of the Earth System (NextFrAMES, a revised version of FrAMES) have numerous similarities to those developed by other teams, but represents a novel model development paradigm. NextFrAMES is built around a modeling XML that lets modelers to express the overall model structure and provides an API for dynamically linked plugins to represent the processes. The model XML is executed by the NextFrAMES run-time engine that parses the model definition, loads the module plugins, performs the model I/O and executes the model calculations. NextFrAMES has a minimalistic view representing spatial domains and treats every domain (regardless of its layout such as grid, network tree, individual points, polygons, etc.) as vector of objects. NextFrAMES performs computations on multiple domains and interactions between different spatial domains are carried out through couplers. NextFrAMES allows processes to operate at different frequencies by providing rudimentary aggregation and disaggregation facilities. NextFrAMES was designed primarily for hydrological modeling purposes, but many of its functionality should be applicable for a wide range of land surface models. In its present capabilities NextFrAMES is probably inadequate to implement fully coupled Earth System models, but future versions with the guidance from Earth System developers might someday eliminate its limitations. Our intent with NextFrAMES is to initiate a dialog about new ways of expressing models that is less tied to the actual implementation and allow scientist to develop models at a more abstract level.

An Overview of Parameterezations of Heat Transfer over Moss-Covered Surfaces in the Earth System Models

2020 ◽  
Vol 56 (2) ◽  
pp. 101-111
Author(s):  
V. M. Stepanenko ◽  
I. A. Repina ◽  
V. E. Fedosov ◽  
S. S. Zilitinkevich ◽  
V. N. Lykossov
Keyword(s):  
Heat Transfer ◽  
Earth System ◽  
System Models ◽  
The Earth ◽  
Earth System Models

Goal and products of PAGES LandCover6k 2018-2020: Past Global Land Cover and Land Use for Climate Modelling

2020 ◽  
Author(s):  
Marie-Jose Gaillard ◽  
Andria Dawson ◽  
Ralph Fyfe ◽  
Esther Githumbi ◽  
Emily Hammer ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Carbon Cycle ◽  
Climate Model ◽  
Climate Modelling ◽  
Model Simulations ◽  
Lulc Changes ◽  
The Past ◽  
Per Capita ◽  
Past Land Use

<p>The question of whether prehistoric human impacts on land cover (i.e. anthropogenic land cover change due to land use, LULC) were sufficiently large to have a major impact on regional cli-mates is still a matter of debate. Climate model simulations have shown that LULC datasets can have large regional impacts on climate in recent and prehistoric time<sup> (1)</sup>. But there are major differences between the available LULC scenarios/datasets such as HYDE (History Database of the Global En-vironment) and Kaplan’s KK10 <sup>(2)</sup>, and diagnoses of inferred carbon-cycle impacts show that none of the scenarios are realistic <sup>(3)</sup>. The only way to provide a useful assessment of the potential for LULC changes to affect climate in the past, is to provide more realistic LULC data based on palaeovegetation and archaeological evidence to improve the LULC datasets used in climate modelling<sup>(4)</sup>. We use the REVEALS model to reconstruct LC from pollen data at a regional scale, and archaeological data to map LU types and distribution, and estimate per capita LU. The archaeology-based LU maps and per-capita LU estimates are used to improve LULC datasets. Pollen-based REVEALS LC estimates are then used to evaluate/validate the new, improved LULC datasets. These new datasets will be used to implement past land use in palaeoclimate and carbon cycle model simulations. Such simulations are necessary to assess the impact of LULC changes in the past and understand the effect of ecosys-tem management on future climate. We present results from five years of PAGES LandCover6k activities. </p><p>(1) Strandberg G, Kjellström E, Poska A, Wagner S, Gaillard M-J et al. (2014) Regional climate model sim-ulations for Europe at 6 and 0.2 k BP: sensitivity to changes in anthropogenic deforestation. Clim. Past 10, 661–680.<br>(2) Gaillard M-J, Sugita S, Mazier F et al (2010) Holocene land-cover reconstructions for studies on land cover-climate feedbacks. Clim. Past 6, 483-499.<br>(3) Stocker B, Yud Z, Massae C, Joos F (2017) Holocene peatland and ice-core data constraints on the tim-ing and magnitude of CO2 emissions from past land use. www.pnas.org/cgi/doi/10.1073/ pnas.1613889114.<br>(4) Harrison S P, Gaillard M-J, Stocker B D, Vander Linden M, Klein Goldewijk K, Boles O, Braconnot P, Dawson A, Fluet-Chouinard E, Kaplan J O, Kastner T, Pausata F S R, Robinson E, Whitehouse N J, Madella M, and Morrison K D (2019) Development and testing of scenarios for implementing Holocene LULC in Earth Sys-tem Model Experiments, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-125, in review, 2019.</p><p><sup> </sup></p><p> </p><p> </p>

Future fires in the Coupled Model Intercomparison Project (CMIP) phase 6

2020 ◽  
Author(s):  
Gitta Lasslop ◽  
Stijn Hantson ◽  
Victor Brovkin ◽  
Fang Li ◽  
David Lawrence ◽  
...  
Keyword(s):  
Land Use ◽  
Fire Regime ◽  
Coupled Model ◽  
Fire Regimes ◽  
Atmospheric Composition ◽  
Cloud Formation ◽  
Burned Area ◽  
Earth System ◽  
System Models ◽  
Earth System Models

<p>Fires are an important component in Earth system models (ESMs), they impact vegetation carbon storage, vegetation distribution, atmospheric composition and cloud formation. The representation of fires in ESMs contributing to CMIP phase 5 was still very simplified. Several Earth system models updated their representation of fires in the meantime. Using the latest simulations of CMIP6 we investigate how fire regimes change in the future for different scenarios and how land use, climate and atmospheric CO<sub>2</sub> concentration contribute to the fire regimes changes. We quantify changes in fire danger, burned area and carbon emissions on an annual and seasonal basis. Factorial model simulations allow to quantify the influence of land use, climate and atmospheric CO<sub>2</sub> on fire regimes.</p><p>We complement the information on fire regime change supplied by ESMs that include a fire module with a statistical modelling approach for burned area. This will use information from simulated changes in climate, vegetation and socioeconomic changes (population density and land use) provided for a set of different future scenarios. This allows the integration of information provided by global satellite products on burned area with the process-based simulations of climate and vegetation changes and information from socioeconomic scenarios.</p><p> </p>

scholarly journals Research priorities in land use and land-cover change for the Earth system and integrated assessment modelling

2010 ◽  
Vol 30 (13) ◽  
pp. 2118-2128 ◽  
Author(s):  
Kathy Hibbard ◽  
Anthony Janetos ◽  
Detlef P. van Vuuren ◽  
Julia Pongratz ◽  
Steven K. Rose ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Integrated Assessment ◽  
Research Priorities ◽  
Earth System ◽  
Integrated Assessment Modelling ◽  
The Earth

scholarly journals A global assessment of gross and net land change dynamics for current conditions and future scenarios

2018 ◽  
Vol 9 (2) ◽  
pp. 441-458 ◽  
Author(s):  
Richard Fuchs ◽  
Reinhard Prestele ◽  
Peter H. Verburg
Keyword(s):  
Land Use ◽  
Shifting Cultivation ◽  
Large Scale ◽  
Earth System ◽  
Grid Cells ◽  
Land Change ◽  
System Models ◽  
Change Dynamics ◽  
Earth System Models ◽  
Land Changes

Abstract. The consideration of gross land changes, meaning all area gains and losses within a pixel or administrative unit (e.g. country), plays an essential role in the estimation of total land changes. Gross land changes affect the magnitude of total land changes, which feeds back to the attribution of biogeochemical and biophysical processes related to climate change in Earth system models. Global empirical studies on gross land changes are currently lacking. Whilst the relevance of gross changes for global change has been indicated in the literature, it is not accounted for in future land change scenarios. In this study, we extract gross and net land change dynamics from large-scale and high-resolution (30–100 m) remote sensing products to create a new global gross and net change dataset. Subsequently, we developed an approach to integrate our empirically derived gross and net changes with the results of future simulation models by accounting for the gross and net change addressed by the land use model and the gross and net change that is below the resolution of modelling. Based on our empirical data, we found that gross land change within 0.5∘ grid cells was substantially larger than net changes in all parts of the world. As 0.5∘ grid cells are a standard resolution of Earth system models, this leads to an underestimation of the amount of change. This finding contradicts earlier studies, which assumed gross land changes to appear in shifting cultivation areas only. Applied in a future scenario, the consideration of gross land changes led to approximately 50 % more land changes globally compared to a net land change representation. Gross land changes were most important in heterogeneous land systems with multiple land uses (e.g. shifting cultivation, smallholder farming, and agro-forestry systems). Moreover, the importance of gross changes decreased over time due to further polarization and intensification of land use. Our results serve as an empirical database for land change dynamics that can be applied in Earth system models and integrated assessment models.

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