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SPACES Project ARS AfricaE – Adaptive Resilience of Southern African ecosystems Falge, E. 1 , Brümmer, C. 1 , Mukwashi, K. 1 , Schmullius, C. 2 , Hüttich, C. 2 , Odipo, V. 2 , Scholes, R.J. 3,6 , Mudau, A. 3 , Midgley, G. 4 , Hickler, T. 5,6 , Scheiter, S. 6 , Martens, C. 6 , Twine, W. 7 , Iiyambo, T. 1,7 , Bradshaw, K. 8 , Lück, W. 9 , Lenfers, U. 10 , Thiel-Clemen, T. 10 , du Toit, J. 11 , Mukelabai, M. 12 , and Kutsch, W. 13 EGU Vienna 2015– Abstract Nr. EGU2015-4869 Background & Objectives Contact: Eva Falge Thünen-Institute of Climate-Smart Agriculture Bundesallee 50, 38116 Braunschweig, Germany [email protected] Acknowledgements: This project is funded by the BMBF under contract number 01 LL 1303 A. 1 Thünen Institute of Climate-Smart Agriculture (TI-AK), Braunschweig, Germany 2 Friedrich-Schiller-University Jena (FSU), Jena, Germany 3 Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa 4 Stellenbosch University, South Africa 5 Johann Wolfgang Goethe University Frankfurt (UFRA), Frankfurt, Germany 6 Biodiversity and Climate Research Centre (BiK-F), Frankfurt, Germany 7 University of the Witwatersrand (WITS), Johannesburg, South Africa 8 Rhodes University, Grahamstown, South Africa 9 Forest Sense, Pretoria, South Africa 10 Hamburg University of Applied Sciences (HAW), Hamburg, Germany 11 Grootfontein Agricultural Development Institute (GADI), Middelburg, South Africa 12 Zambian Meteorological Department, Lusaka, Zambia 13 Integrated Carbon Observation System (ICOS), Headoffice, Helsinki, Finland create a network of research clusters (with natural and altered vegetation) along an aridity gradient most arid: Greater Karoo, South Africa intermediate: Kruger National Park, South Africa humid: Kataba Forest Reserve, Zambia WP1 WP2 WP4 WP5 WP3 C 2 1 ARS AfricaE fluxtower ZA-GRO1 Coordinates: -31.4253, 25.0294 ARS AfricaE fluxtower ZA-GRO2 Coordinates: -31.4209, 25.01780 Over- grazed until 5 years ago, under recovery Planned treatment: 1st year continuing of recovery From 2nd year on heavy grazing. Gently- grazed plot. Closest to Karoo vegetation as possible. Planned treatment: Continuous monitoring Karoo reference and satellite sites, experimental plots of Grootfontein Agricultural Research Station Zambia reference and satellite sites Kataba Forest Reserve, Mongu Fluxnet Site Code: ZM-Mkt Data Period: 2001-2007; 2015-2017 Coordinates: -15.43833, 23.25333 Cassava (manioc) field to be established Malopeni (KNP) Fluxnet Site Code: ZA-Map Data Period: 2007-2017 Coordinates: -23.83254, 31.21436 Skukuza (KNP) Fluxnet Site Code: ZA-KRU Data Period: 2001-2017 Coordinates: -25.0197, 31.4969 Agincourt/Bushbuckridge to be established Phalaborwa (Sclerocarya birrea) to be established by SAEON Kruger National Park reference sites, experimental plots of CSIR Kruger National Park satellite sites Nowadays, many semi-arid ecosystems are affected by at least two different kinds of disturbances: land use (change) and climate change. Based on this, it can be hypothesized that even very resilient ecosystems may not return to their initial state after disturbance, but will rather adapt to a new steady-state. We name this phenomenon “Adaptive Resilience of Ecosystems” and use it as base for the research concept of ARS AfricaE. This project wants to go beyond older approaches that only describe structural changes in savannas and their drivers. It employs functional aspects, such as the investigation of biogeochemical cycles, but also targets a deeper understanding of the functional consequences of ecosystem changes caused by multiple disturbances, and defines “degradation” as a sustained loss in the broad set of ecosystem services, i.e. a decrease in natural capital. WP1 WP2 WP3 WP5 WP4 C link biogeochemical functions with ecosystem structure, diversity of species and eco-physiological properties describe ecosystem disturbance (and recovery) in terms of ecosystem function such as carbon balance components and water use efficiency WP1 WP2 WP4 WP5 WP3 C Ecosystem Structure and Plant Ecophysiology (Skukuza, Mongu, Grootfontein, Malopeni): diurnal and seasonal gas exchange and shoot water potential; stem flux, diurnal fluctuation in stem width leaf characteristics of selected representative species (SLA; Leaf N; D13C, WUE) temperature response of leaf/stem respiration (LiCor 6400 / Walz GFS3000) semi-automated soil respiration measurements during site visits, for bare soil and trenched sites under selected species canopy structure and phenology in footprint of flux towers (LAI2000; Decagon ceptometer and physical measurements, detailed mapping in conjunction with TLS1000 radar; phenological cameras) Dynamic Vegetation Modelling (aDGVM2): Simulations for flux tower sites and benchmark with available flux data Up-scaling at km scale Up-scaling at regional scale Biome shifts under future conditions Higgins & Scheiter 2012 (Nature) build an individual-based model to predict ecosystem dynamics under (post) disturbance managements WP1 WP2 WP4 WP5 WP3 C MARS Layer System aDGVM2 CSIRO CABLE Topography Surface water Elevation Soil type Fire dynamics Land-use Remote sensing photos, Bare soil, sunny, covered The Board: Environmental Influences The Modeling The Tokens: Agents Tree A Tree B MARS (Multi Agent Research and Simulation): highly scalable, distributable and usable framework of loosely coupled components multi-disciplinary simulation scenarios at very large scales simulation of > 50 M self-organized agents in reasonable time scenario oriented easy to use especially for non-programmers adaptable to various domains of research Applications: ecology (Togo Rain Forest, Predator-Prey interaction, Animal movement, …) epidemiology (spreading of infectious diseases) evacuation (individual movement of pedestrians) New Application: prototype model for Skukuza combine the models with long-term landscape dynamic information derived from remote sensing and aerial photography WP1 WP2 WP4 WP5 WP3 C Spectral domain spatial domain Aerial photos Periodically / recent & historic life form, cover, height High-Res. Satellite Imagery phenology/ land type Inter-annual vegetation physiognomy SAR-optical observations Time series Intra-annual phenology Space-Time Cube: for each flux tower location with an extent of 5 x 5 km² Unmanned aerial vehicle Set up of a long-term satellite and aerial photo data archive multi-sensor synergy analyses to derive vegetation structural parameters using SAR and optical data analyses of historical data to compare recent and historic vegetation states land cover (trends) for all sites using Landsat-type imagery broad scale biophysical parameters from global archives to support regional scale ecological modelling tasks Satellite Data (since 1963) Corona; Landsat; RapidEye; MODIS; JERS-1; TerraSAR-X/TanDEM-X/COSMO SkyMed; ERS/ASAR/Sentinel; SIR-C/30m SRTM Ground Truth Measurements develop sustainable management strategies for disturbed ecosystems, land use change and adaptations for conservation areas WP1 WP2 WP4 WP5 WP3 C Zambia: Areas of different livelihoods in Namushekende and Kataba. Livelihoods in the blue area are independent from charcoal, in the red area highly depending on charcoal. The green area seems to be intermediate. Socio-economic surveys in Agincourt/Bushbuckridge (South Africa, SUCSES, 2010-2014) and near Mongu (Zambia, 2015-17): quantify livelihoods in local communities assess local resource governance structures quantify disturbance/resource extraction rates, including the importance of livelihood shocks provide measures of ecosystem services that are provided by the natural ecosystems investigate scenarios, including impacts of different land-cover change trajectories on local livelihoods advance calculation of emissions from land use and land use change Flux Tower To achieve this goal, the project combines five work packages under a central coordination: WP1: Ecosystem Metabolism and Trace Gas Exchange - WP2: Ecosystem Structure, Plant Ecophysiology and Dynamic Vegetation Modelling - WP3: Data Integration and Agent Based Modelling - WP4: Remote Sensing and Upscaling - WP5: Socio-economic Studies
