The LPJmL model is a process-based dynamic vegetation model that simulates plant responses to climate and climate change. It has been developed from the LPJ model to include additional modules like grassland dynamics, agricultural trees, and nitrogen cycling. The LPJmL model has high spatial and temporal resolution and is widely used to model vegetation/carbon dynamics, agro-ecosystems, grasslands, and the impacts of climate change on the biogeochemical cycles. Future plans for the model include refining management modules, adding more crops, understanding CO2 fertilization uncertainties, and improving grassland/livestock representations.
3. Introduction
• The LPJmL model has been developed from LPJ, a Dynamic
Global Vegetation Model (DGVM)
• Grassland dynamics, grassland productivity, and the impact on
the biogeochemical cycles
• Process‐based dynamic vegetation model, originates from
EPIC and BIOME models
• Simulates plant responses to climate and climate change
• High spatial and temporal resolution Photosynthesis Soil
water
8. Introduction-Codes
• licensed under the GNU AFFERO GENERAL PUBLIC LICENSE Version 3
• All source code, configuration and parameter files are subject to copyright
(C) by the Potsdam Institute for Climate Impact Research
• The source code is distributed via the git repository at
https://github.com/PIKLPJmL/LPJmL.
9. Application fields-1
• Modelling Mediterranean agro-ecosystems by including agricultural
trees in the LPJmL model
• Modeling vegetation and carbon dynamics of managed grasslands at
the global scale with LPJmL 3.6
• Evaluation of ecosystem dynamics, plant geography and terrestrial
carbon cycling in the LPJ Dynamic Vegetation Model
• Implementing the nitrogen cycle into the dynamic global vegetation,
hydrology, and crop growth model LPJmL (version 5.0)
• https://www.pikpotsdam.de/en/institute/departments/activities/biosph
ere-water-modelling/lpjml/key-publications
11. Under development and future plans
• Refine management modules (irrigation, rainwater harvesting
and vapor shift techniques, multiple cropping)
• Add more crops (potato, cotton, date palm, citrus, …)
• Continue development of bioenergy plants
• Understand uncertainty in CO2 fertilization effect (coupled
effects from increased temperatures and CO2)
• Improve grassland management and representation of
livestock
• Revise simulated impacts of extreme temperature and
precipitation
The response of land ecosystems to future climate change is among the largest unknowns in the global climate-carbon cycle feedback, Moreover, The dynamics of the terrestrial biosphere and the associated terrestrial carbon cycle are of central importance for Earth system science. Climate–carbon cycle feedbacks have become integral parts of Earth system models (ESMs) for climate change projections. However, the terrestrial carbon cycle dynamic are not only driven by climate and carbon dioxide (CO2) fertilization (Schimel et al., 2015; Norby et al., 2005), but also by land use change (Müller et al., 2006, 2016; Arneth et al., 2017; Le Quéré et al., 2016) and vegetation dynamics (Müller et al., 2016, and references therein). And these are countered by LPJml which will be studied in next couple of slides.
Hello ladies and gentlemen ,myself suraj shah, from CRE,UCAS, without further delay lets move to next slide which is Outlines
I have three topics to discuss today..
At first I will spend most of time for introduction part where I will cover history, codes availability, features
Then at second ,application fields where I will mention fields and research implied on the different fields
And at last phase of my presentation will be focused on Under development and future plans of LPJml model
so lets move to introduction part…
Lund-Potsdam-Jena managed Land which was designed to simulate the global terrestrial carbon cycle and the response of carbon and vegetation patterns under climate change ,
It also, simulate vegetation composition and distribution as well as stocks and land-atmosphere exchange flows of carbon and water, for both natural and agricultural ecosystems.
Using a combination of plant physiological relations, generalized empirically established functions and plant trait parameters, it simulates processes such as photosynthesis, plant growth, maintenance and regeneration losses, fire disturbance, soil moisture, runoff, evapotranspiration, irrigation and vegetation structure.
LPJmL is currently the only DGVM that has dynamic land use fully incorporated at the global scale and also simulates the production of woody and herbaceous short-rotation bioenergy plantations and the terrestrial hydrology
High spatial and temporal resolution Photosynthesis Soil water
1.The original LPJ code ("LPJ version 1"), published in 2003, was written in Fortran and was published in 2003 (Sitch et al., Global Change Biology, 2003).
2.Since 2000, a separate version of LPJ ("LPJ version 2") has emerged that mainly comprises a species and stand-based simulation tool that is more detailed (and much slower) than LPJ but shares many of its core routines
3. As of 2005, a consolidated and completely re-written modular version of LPJ ("LPJ version 3") has been created at PIK in the programming language C. Recent advances in LPJmL include river routing and agricultural irrigation
4. After a long process of bringing together multiple model extensions that were developed in parallel, LPJmL version 4.0 was published in a comprehensive full model description (Schaphoff et al. 2018a), accompanied by a thorough and multi-featured model evaluation (Schaphoff et al. 2018b)
5. LPJmL version 5.0 with nitrogen Shortly after the release of LPJmL version 4.0, the implementation of the terrestrial nitrogen dynamics in LPJmL were completed.
Although we discussed some unique features and capabilities of LPJml model ,lets put eye on data, monthly and daily input data are spatially explicit time series (typically ~60,000 global 0.5x0.5° grid cells) of climate, human land use, soil properties, and river flow directions. Grid cells may contain mosaics of one or several types of natural or agricultural vegetation.
Similarly,Outputs are generated as daily, monthly or annual spatially explicit time series for individual plants, carbon and water pools and fluxes, individual land-use types or the entire mosaic present in each grid cell.
Again ,if we talk about features, there are 9 pft ,12 reperesentive crops ,management modules and so on… uhh after long introduction , lets explore code availability of LPJml and its license. And copyright which is on next slide..
1. licensed under the GNU AFFERO GENERAL PUBLIC LICENSE Version 3
2. The registration is free of costs.
3. New model development can be submitted to the LPJmL git repository in separate repository branches and pull requests can be issued and languages used to built LPJml is shown in the slide..
After hard work in writing code, it is obvious it should produce good application, so LPJml model have been applied in various fields and research like
Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0)
Implementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0)
Improving the LPJmL4-SPITFIRE vegetation–fire model for South America using satellite data
The importance of management information and soil moisture representation for simulating tillage effects on N2O emissions in LPJmL5.0
Moreover , it has been applied in Bioenergy development, Nitrogen cycle and LPJml FIT for Europe and so on.
Since 4 version are already applied and version 5 is in development and tries to cover more crops, revise simulated impacts of extreme temperature and precipitation.