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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
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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.
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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
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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
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MA
RS
Laye
r Sy
stem
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
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Spectral domain
sp
atia
l d
om
ain
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
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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