Modelling biodiversity indicators using the CCE background database CCE workshop Rome 2014 Gert Jan Reinds, Luc Bonten, Janet Mol, Wieger Wamelink, Max.

Slides:



Advertisements
Similar presentations
Atmospheric Deposition to Complex Terrain: Scaling Up to the Landscape K.C. Weathers, G.M. Lovett, S.E. Lindberg S.M. Simkin, D.N. Lewis, K. Schwarz Institute.
Advertisements

History of Critical Loads meetings – how have we gotten to this point? Andrzej Bytnerowicz 1, Rich Fisher 2 and Al Riebau 3 USDA Forest Service 1 Pacific.
ICP Forests EB.AIR/WG.1/2011/ Report „Effects of air pollution on forests“ Two studies Forest soil condition Bruno De Vos et al. (FSCC at INBO, Belgium)
24 th CCE workshop& 30 th TF M&M, Rome, 7-10 April Call for Data results Jaap Slootweg & Max Posch.
Quantifying the threat from ozone pollution to food security ICP Vegetation – EMEP collaboration Gina Mills, David Simpson, Harry Harmens et al. > Brief.
VSD+ training session, Indianapolis 2014 VSD+ PROPS Gert Jan Reinds.
Jean-Paul Hettelingh, Coordination Centre for Effects (CCE), Workshop to promote the ratification of the protocol on heavy metals across.
The ForSAFE-VEG model system Reporting on new progress with the ForSAFE-VEG model on vegetation modelling. The result of calibrating a vegetation parameterization.
In the Coronado National Forest Onamia Pope August 23, 2000.
Evolution of Biodiversity
Call for Data for Nitrogen and Sulphur Critical Load Functions (N & S CLFs) Coordination Centre for Effects (CCE) of the ICP Modelling & Mapping.
Chapter 16 Chi Squared Tests.
RegIS2: Regional Climate Change Impact & Response Studies RegIS2: Regional Climate Change Impact & Response Studies
Expected Change of the Key Agrometeorological Parameters in Central Europe by 2050 Trnka M. 1,3, Štěpánek P. 2, Dubrovský M. 3, Semerádová D. 1,3, Eitzinger.
ICP Forests Common and Specific Workplan Items Outline according to CWIs Ex-post application Acidification/eutrophication under under different deposition.
Current use of spatial reference grids in European Environment Agency
Applications of Bayesian sensitivity and uncertainty analysis to the statistical analysis of computer simulators for carbon dynamics Marc Kennedy Clive.
Basic concepts in ordination
Modelling N driven biodiversity changes in Austrian forest and grassland habitats Thomas Dirnböck & Ika Djukic 1.
LBG/LB 1 Working Group on Effects, ICPM&M-Coordination Center for Effects, J.-P.Hettelingh, Gothenburg, October 2004 New developments on air pollution.
Measuring Diversity.
Coordination Centre for Effects Jean-Paul Hettelingh, EC4MACS kick off meeting, IIASA, 6-7 March 2007 EC4MACS Task 3: Ecosystem Impact Assessment by the.
Coordination Centre for Effects, TFIAM Meeting, Bilthoven, 8-10 June 2009 (Further) (Possible) ICP M&M Contribution to Integrated Assessment Maximilian.
Conception for lands of high natural value – international agreements.
Biodiversity metrics – a way forward Ed Rowe. Let’s GROW Goal Reality Options Way forward.
SIMULATION OF GROUND VEGETATION DIVERSITY IN BOREAL FORESTS Larisa Khanina 1, Maxim Bobrovsky 2, Alexander Komarov 2, Alex Mikhajlov 2 1 Institute of Mathematical.
VSD+ PROPS Luc Bonten, Janet Mol, Wieger Wamelink, Gert Jan Reinds, Jan-Cees Voogd.
ICP Integrated Monitoring of Air Pollution Effects on Ecosystems - ICP IM Activities & Priorities Lars Lundin Swedish University of Agricultural.
17 May 2007RSS Kent Local Group1 Quantifying uncertainty in the UK carbon flux Tony O’Hagan CTCD, Sheffield.
NACLIM annual meeting - 15/10/ NACLIM Annual Meeting 2014 (Berlin) WP4.2 - Extraction of city morphology indicators for urban climate modeling: a.
Extent and Mask Extent of original data Extent of analysis area Mask – areas of interest Remember all rasters are rectangles.
Invest Nutrient Retention model Yonas Ghile.
A critical evaluation of country-dependent impact factors for acidification in Europe summary of a scientific paper submitted for review -Do Not Quote.
Arjen van Hinsberg, Janet Mol Dynamic modelling of impacts in Natura 2000 habitats the Dutch response to the call for data.
1 Trends in soil solution chemistry in temperate forests under on-going recovery from acidification and climate change in Flanders, Belgium Arne Verstraeten.
Coordination Centre for Effects, Workshop to Promote the Ratification of the Protocols, St. Petersburg, October 2009 Critical Loads and their exceedances;
JEG DM: common work items Targets & ex post analysis Robustness Links with biodiversity Trends in selected modeled/measured parameters.
Biodiversity. Average Size Measure all trees in a transect or quadrat. Produce a size-frequency histogram to show the size distribution. Can also calculate.
Introduction to Models Lecture 8 February 22, 2005.
WGE September 20111Brit Lisa Skjelkvåle Trends in precipitation chemistry, surface water chemistry and aquatic biota in acidified areas in Europe.
Scope for further emission reductions: The range between Current Legislation and Maximum Technically Feasible Reductions M. Amann, I. Bertok, R. Cabala,
ICP Modelling and Mapping, 30th Task Force 24th CCE Workshop Roma, 7 – 10 april 2014.
Why use landscape models?  Models allow us to generate and test hypotheses on systems Collect data, construct model based on assumptions, observe behavior.
JEG DM: progress in DM dynamic models became a commonly used tool, several ICPs and national focal points use DM DM provide timescale to expected changes.
What if? prospects based on Corilis Alex Oulton, Manuel Winograd Ronan Uhel & Jean-Louis Weber LAND QUICK SCAN INTERFACE: Challenges and needs Internal.
On Indices … … to characterise (the state of) plant diversity … using output of Vegie models M. Posch, L Bonten, J Slootweg, GJ Reinds, …
ECLAIRE: Effects of climate change on air pollution impacts and response strategies for European ecosystems.
Monitoring and Estimating Species Richness Paul F. Doherty, Jr. Fishery and Wildlife Biology Department Colorado State University Fort Collins, CO.
Modelling with CORILIS Change in land cover patterns, landscape ecological potential & “temperatures” on N2000, river basins and UMZ Wire frame and examples.
Module 4 – Biodiversity By Ms Cullen. Terminology Try and define the following terms used when studying the environment.
Bioscience – Aarhus University Modelling the joint abundance of more plant species - pin-point cover data Christian Damgaard Department of Bioscience Aarhus.
3.1.1 Biodiversity. Biodiversity  A measure of the biological richness of an area taking into account the number of species, community complexity and.
Joint meeting on the harmonization of land-cover information for applications under the Convention on LRTAP presentation of work by CCE (J.Slootweg) and.
ICP Integrated Monitoring of Air Pollution Effects on Ecosystems -
Biodiversity Variety of life
Biodiversity Variety of life
Global Terrestrial Observing System
ICP waters; use of data from EMEP …and some results Brit Lisa Skjelkvåle and Heleen de Wit Norwegian Institute for Water Research.
Butterflies and nitrogen: The Netherlands experience
WGE Extended Bureau Meeting LRTAP Convention, Geneva, 20 March 2017
Results: ICP M&M call for data Jean-Paul Hettelingh, Max Posch, Jaap Slootweg, Anne-Christine Le Gall 3rd Joint session of the Working Group.
Species Diversity Comparison North and South Slopes
Measuring Biodiversity
Recent and planned activities ICP Integrated Monitoring Dynamic vegetation modelling study at selected ICP IM sites First communication Maria Holmberg.
Training session A common biodiversity index, without excluding country specific indices Presentations by: Ed Row summarized, contextualized and wrapped.
of lead, cadmium and mercury German Federal Environment Agency
Model assessment of heavy metal pollution from global to local scales
Conception for lands of high natural value – international agreements
Conception for lands of high natural value – international agreements
progress in activities and results of call for data
Presentation transcript:

Modelling biodiversity indicators using the CCE background database CCE workshop Rome 2014 Gert Jan Reinds, Luc Bonten, Janet Mol, Wieger Wamelink, Max Posch (CCE)

Introduction  Introduction  Methods ● Selection of sites ● Vegetation modelling  Results  Conclusions

Introduction  To support the ongoing development on soil-vegetation modelling we applied VSD+-PROPS to sites in Europe  We tested modelling concepts and robustness  We discuss how one could proceed  Its still somewhat preliminary...

Modelling VSD+ Methyd GrowUp MakeDep PROPS Climate & Hydrology Reduction Functions Uptake of N and Bc C and N inputs to soil pH, NO3 Climate & hydrology

Methods: selecting sites

Selecting sites The 2014 call for data states:  (1) … selects (at least) two sites within every (level-3) EUNIS class present in the country for which the chosen soil-vegetation model can calibrated  (2) … selects the endpoint pertinent to the site and a corresponding biodiversity indicator;  (3) …runs the model with the background and the GP depositions to 2100 (provided by the CCE);  (4) …reports the indicator values and other variables computed for 2100 to the CCE

Selecting sites from the EU background data base 1. Select the dominant vegetation type for decidious forest, conifers forest and grassland/heathland 2. Find two EMEP cells in each country were this vegetation type occurs, one with a low and one with a high deposition 3. Find in these EMEP cells the units for VSD+ with the proper vegetation type (broadleaves, conifers, natural vegetation). 4. Compute SMB critical loads for these sites 5. Select from those VSD+ sites a sensitive site (with a CL(N),CL(S) closest to the 5 th percentile CL of the country)

VSD+ application  Spatial data bases on soils, land cover...  Outputs from MetHyd (climate and hydrology and reduction functions for N mi and N de ) and GrowUp (uptake and litterfall)  Soil chemistry data: transfer functions using soil type and soil texture and parent material class (as in VSD)  Mineralisation constants and C/N ratios of the C-pools from calibration of VSD+ (on sites and chronosequences)  Drivers: deposition of N, S and BC from EMEP models, climate change according to A1b scenario or constant climate.  Initial C-pool, initial C/N ratio and exchange constants from calibration

VSD+ calibration  We calibrated initial Cpool,initial C/N ratio and exchange constants.  We estimated ‘observed’ C/N, Cpool and Bsat as a function of soil type, texture, vegetation type and country based on existing European data bases (like ICP- F level I with 6000 sites)  We used standard Bayesian calibration

Methods: biotic modelling

Vegetation modelling with PROPS  For each site we created a species list based on the vegetation type (as in VSD+Studio)  We run PROPS for each sites and compute the various diversity indices (Shannon, Simpson, Bray-Curtis, Habitat quality)

Results

Climate change

Abiotic conditions;pH

Abiotic conditions; N

Results; Bray Curtis

Results; habitat quality

I would have liked to show even more but

Conclusions  Selecting sites for each vegetation type seems to be a useful approach as each site can be calibrated  But: Check how representative the sites are and how sensitive the outcome to the selections made  Bray Curtis index may provide useful information but principally should be based on abundance not probability  Habitat quality indicator is based on probability; now we used wanted (?) species only, unwanted should be added (?)  Some more in-depth analysis of results is needed

Future work  So far the model has been applied on 128 sites. Next steps would be to apply it for all ‘important habitat types’ per country.  We could select sites for VSD+PROPS using stratified random sampling (e.g. 10 (?) sites per habitat type per country) and check if this would be sufficient for a good regional representation by checking results against those of a ‘true’ regional application of VSD+-PROPS for 1-2 not-too-large countries This could then yield ‘response functions’

End

Results; Simpson Index

Influence of climate change on abiotic conditions....