Geosci. Model Dev., 11, 1343–1375, 2018 https://doi.org/10.5194/gmd-11-1343-2018 © Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License. LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description Sibyll Schaphoff1, Werner von Bloh1, Anja Rammig2, Kirsten Thonicke1, Hester Biemans3, Matthias Forkel4, Dieter Gerten1,5, Jens Heinke1, Jonas Jägermeyr1, Jürgen Knauer6, Fanny Langerwisch1, Wolfgang Lucht1,5, Christoph Müller1, Susanne Rolinski1, and Katharina Waha1,7 1Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, 14412 Potsdam, Germany 2Technical University of Munich, School of Life Sciences Weihenstephan, 85354 Freising, Germany 3Alterra, Wageningen University & Research, P.O. Box 47, 6700 AA Wageningen, the Netherlands 4TU Wien, Climate and Environmental Remote Sensing Group, Department of Geodesy and Geoinformation, Gusshausstraße 25–29, 1040 Vienna, Austria 5Humboldt Universität zu Berlin, Department of Geography, Unter den Linden 6, 10099 Berlin, Germany 6Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany 7CSIRO Agriculture & Food, 306 Carmody Rd, St Lucia QLD 4067, Australia Correspondence: Sibyll Schaphoff ([email protected]) Received: 21 June 2017 – Discussion started: 27 July 2017 Revised: 26 February 2018 – Accepted: 5 March 2018 – Published: 12 April 2018 Abstract. This paper provides a comprehensive description companion paper. By making the model source code freely of the newest version of the Dynamic Global Vegetation available at https://gitlab.pik-potsdam.de/lpjml/LPJmL, we Model with managed Land, LPJmL4. This model simulates hope to stimulate the application and further development of – internally consistently – the growth and productivity of LPJmL4 across scientific communities in support of major both natural and agricultural vegetation as coherently linked activities such as the IPCC and SDG process. through their water, carbon, and energy fluxes. These fea- tures render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial bio- sphere as increasingly shaped by human activities such as cli- 1 Introduction mate change and land use change. Here we describe the core model structure, including recently developed modules now The terrestrial biosphere, a highly dynamic key component unified in LPJmL4. Thereby, we also review LPJmL model of the Earth system, is undergoing significant and widespread developments and evaluations in the field of permafrost, hu- transformations induced by human activities such as climate man and ecological water demand, and improved representa- and land use change. Humans have by now transformed tion of crop types. We summarize and discuss LPJmL model about 40 % of the terrestrial ice-free land surface into land applications dealing with the impacts of historical and future used for agriculture and urban settlements (Ellis et al., 2010), environmental change on the terrestrial biosphere at regional thus pushing the planetary dynamics beyond the boundaries and global scale and provide a comprehensive overview of that have been characteristic for the past ca. 12 000 years LPJmL publications since the first model description in 2007. (Rockström et al., 2009). These interventions put at risk im- To demonstrate the main features of the LPJmL4 model, portant functions of the biosphere such as the provisioning of we display reference simulation results for key processes floral and faunal biodiversity (Vörösmarty et al., 2010), the such as the current global distribution of natural and man- terrestrial carbon sink (Le Quéré et al., 2015), and the provi- aged ecosystems, their productivities, and associated water sioning of accessible fresh water (Vörösmarty et al., 2010). fluxes. A thorough evaluation of the model is provided in a Understanding and modelling the current and potential fu- ture dynamics of the Earth system thus renders it necessary Published by Copernicus Publications on behalf of the European Geosciences Union. 1344 S. Schaphoff et al.: LPJmL4 – Part 1: Model description to consider human activities as an integral part, while rep- originates from a former version of the model described by resenting the major dynamics of the biosphere in a spatio- Sitch et al.(2003) and simulates the growth and geographi- temporally explicit and process-based manner, accounting cal distribution of natural plant functional types (PFTs), crop for the feedbacks between vegetation, global carbon and wa- functional types (CFTs), and the associated biogeochemical ter cycling, and the atmosphere. This would also allow for processes (mainly carbon cycling). Recent developments fo- the numerical evaluation of potential implementation path- cused on an improved energy balance model able to estimate ways for the United Nations Sustainable Development Goals permafrost dynamics based on a vertical soil carbon distribu- (SDGs; https://sustainabledevelopment.un.org) and their im- tion scheme and a new soil hydrological scheme (Schaphoff pacts on the terrestrial environment, complementing the im- et al., 2013). Also, a new process-based fire module (SPIT- portant role that dynamic biosphere models have played in FIRE) was implemented that allows for detailed simulation the United Nations scientific assessment reports on climate of fire ignition, spread, and effects to estimate fire impacts change published by the United Nations Intergovernmental and emissions (Thonicke et al., 2010). An updated phenol- Panel on Climate Change (IPCC, 2014). By combining core ogy scheme was developed, which now takes phenology lim- features of global biogeographical and biogeochemical mod- itations arising from low temperatures, limited light, and els developed in the 1990s, dynamic global vegetation mod- drought into account (Forkel et al., 2014). Further model els (DGVMs) emerged as the main tool to simulate the pro- developments encompass the parallelization of the model cesses underlying the dynamics of natural vegetation types to efficiently simulate river routing (Von Bloh et al., 2010) (growth, mortality, resource competition, and disturbances and the implementation of an irrigation scheme (Rost et al., such as wildfires) and the associated carbon and water fluxes 2008), recently updated with a mechanistic representation of (Cramer et al., 2001; Prentice et al., 2007; Sitch et al., 2008; the three major irrigation systems (Jägermeyr et al., 2015). Friend et al., 2014). In light of strengthening human inter- Biemans et al.(2011) implemented reservoir operations and ferences, DGVMs were further developed to integrate ad- irrigation extraction and evaluated the impact on river dis- ditional processes that are relevant to the original research charge. Other developments focused on a newly formulated quest of studying biogeography and biogeochemical cycles implementation of different cropping systems in sub-Saharan under climate change (Canadell et al., 2007). This includes Africa (Waha et al., 2013), Mediterranean agricultural plant the incorporation of human land use and the simulation of types (Fader et al., 2015) and bioenergy crops such as sugar- agricultural production systems (Bondeau et al., 2007; Lin- cane (Lapola et al., 2009), fast-growing grasses, and bioen- deskog et al., 2013), nutrient limitation (Zaehle et al., 2010; ergy trees (Beringer et al., 2011). With these implementa- Smith et al., 2014), hydrological modules, and river-routing tions, the potential of bioenergy production under future land schemes (Gerten et al., 2004; Rost et al., 2008). Knowledge use, population, and climate development could be exten- derived from models that are designed to cover aspects of sively investigated (Haberl et al., 2011; Popp et al., 2011; the Earth system other than terrestrial vegetation and the car- Humpenöder et al., 2014). All developments, the core model bon cycle, such as models of the global water balance, could structure, and recently developed modules of DGVM LPJmL evidentially improve the DGVMs’ ability to also evaluate version 4.0 (in the following referred to as LPJmL4) will be model performance for processes (e.g. river discharge) that described in Sect.2 in more detail. We show that the model in are closely connected to simulated vegetation and carbon cy- its present form allows for a consistent and joint quantifica- cle dynamics (Bondeau et al., 2007; Smith et al., 2014). The tion of climate and land use change impacts on the terrestrial development towards more comprehensive models of Earth’s biosphere, the water cycle, the carbon cycle, and on agricul- land surface offers new possibilities for cross-disciplinary re- tural production (a systematic evaluation can be found in Part search. DGVMs as land components of Earth system mod- II of this paper). To give an overview of recent developments els still show large uncertainties about the terrestrial carbon and applications of LPJmL4, we present the following. (C) balance under future climate change (Friedlingstein et al., 2013). This uncertainty partly results from differences in the 1. A comprehensive description of the full model with all simulation of soil and vegetation C residence times (Carval- contributing developments since its original publication hais et al., 2014; Friend et al., 2014). The time that C resides by Sitch et al.(2003) and Bondeau et al.(2007). We in an ecosystem is thereby strongly affected by simulated aim at consistently uniting all developments, includ- processes of vegetation