Abstract
Abstract. Land-use and land-cover change (LULCC) represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs). The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC). Fully coupled models of climate, land use and biogeochemical cycles to explore land use–climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs) to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use–climate interaction studies: (I) provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II) accounting for sub-grid processes and bidirectional changes (gross changes) across spatial scales, and (III) the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest concentrating on the development of integrated modeling frameworks that may provide further understanding of possible land–climate–society feedbacks.
Highlights
We discuss, based on literature review and illustrative analysis of empirical and modeled Land-use and land-cover change (LULCC) data, three major challenges of this current LULCC representation and their implications for land use– climate interaction studies: (I) provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II) accounting for sub-grid processes and bidirectional changes across spatial scales, and (III) the allocation strategy of independent land-use data at the grid cell level in terrestrial biosphere models (TBMs)
We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs
LULCC is being increasingly included in terrestrial biosphere models (TBMs), including dynamic global vegetation models (DGVMs) and land surface models (LSMs) (Fisher et al, 2014), to quantify historical and future climate impacts both in terms of biophysical and biogeochemical variables (Le Quéré et al, 2015; Luyssaert et al, 2014; Mahmood et al, 2014)
Summary
The short history of implementing landuse change in TBMs (∼ 10 years; Canadell et al, 2007), along with the need to include external data (e.g., maps of global cropland or pasture distribution) to represent land-use change, has led to several issues that complicate the quantification of land-use change impacts on climate and biogeochemical cycles using TBMs. For example, carbon fluxes related to land-use change that increase the atmospheric concentration of greenhouse gases are the largest source of uncertainty in the global carbon budget (Ballantyne et al, 2015; Le Quéré et al, 2015). The current land-use representation requires improvement to narrow down the uncertainty range in reported results of land use–climate studies and eventually increase the confidence level of climate change assessments.
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