Biophysical measurement Indicator: Soil carbon

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Integrated Assessment
Authors Contributors Prof A.N. Other

• Biophysical measurement / Indicator Soil carbon

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Overview

• Brief summary of CS extent and type of data
• Overview of Integrated Assessment
• Project structure
• Linking biophysical measurement to ecosystem
  service
• Attribution and forecasting
• Data database
• hypothesis testing
• statistical development
• Interactions and trade-offs between services
• Up-scaling to catchment modelling and mapping
• Evaluation of approaches
• Questions

3
Countryside Survey sampling strategy

• Sample size
• (km squares)
• 1978 256
• 1984 384
• 1990 508
• 569
• 2007 591

stratified random sample
Based on OS data, climate, soils and geology
classified to give 32 land classes originally,
currently 45
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Work Package1 Habitats and Features- spatial
mapping
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WP1 Habitats and Features- Vegetation plots
Margin plots (lt15)
Linear plots Hedges (10,2) Streams (3,2) Roads
(3,2) Boundaries (5) Arable (5)
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WP2 Land Cover Map 2007
2000
2007
1990
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WP3 Freshwater Module

• CS2000
• 425 small stream sites
• Macroinvertebrate community
• River Habitat Survey
• Physical environmental data
• Indicative hydrochemistry

• For CS2007,
• 373 stream sites
• Same as CS2000
• Macrophyte community
• Ponds (260 sites)
• Macrophyte community
• Physical environmental data
• Indicative hydrochemistry

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WP4 Soils
Previously sampled in 1978 and 1998, increased
sample size in 2007 Measurements made Soil
organic matter content Soil pH Bulk
density Microbial community composition Microarthr
opod community Phosphorus Total N
content Mineralisable N Heavy metals
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WP6 Integrated Assessment
How will ecological impacts of different
pressures translate into effects on ecosystem
services?
- report on current state in potential
of natural resources to provide key ecosystem
services using CS data- main report and
WP6 - assessment of effect of anthropogenic
pressures on the provision of ecosystem
services- WP6 - Attribution - Forecasting
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Project structure and work flow
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Linking Biophysical measurement to Ecosystem
service

• (Ecosystem servicethe benefits people obtain
  from ecosystems)

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Linking CS metrics to ecosystem services

• 1a yes CS will be able to say something
• 1b yes CS can say something, but what can be
  said will be limited
• 2 CS can contribute to but requires further
  data/collaboration
• 3 CS can't help/there are better data sources
  than CS

Haines-Young, R. and M. Potschin (2007)
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An Ecosystem Service cascade - The logic
underlying the ecosystem services paradigm (after
Haines-Young et al., 2006)
Reference Haines-Young, R. Potschin, M. and D.
Cheshire (2006) Defining and identifying
Environmental Limits for Sustainable Development.
A Scoping Study. Final Overview Report to Defra,
44 pp, Project Code NR0102.
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Scoping Ecosystem services at 1km square
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Attribution and Forecasting
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CS Geodatabase
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Data requirements, sources issues

• Climate
• Atmospheric deposition- N,S, CO2, Ozone
• Management- June Census, SPS, IACS,
  Agri-environment, Fertiliser, pesticides etc.
• Net Primary Productivity
• Water quality- EA, N,P, RHS, discharge
• Topography and Landcover- Nextmap, LCM, SSSI, SPA
  etc.
• Geology Soils
• Hydrology- Flooding, River network
• Socio-economic- popn. density, Farm typology
• Issues confidentiality, spatial and temporal
  resolution

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Biophysical measurements from CS

• Biodiversity
• Soil carbon
• Soil contaminant levels and Nutrient status
• Water quality

NPP Pollination Pests
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Hypothesis development and testing some examples

• Biodiversity
• There is a positive relationship between
  biodiversity and other ecosystem services.
• The response of biodiversity to driving
  variables depends upon starting productivity,
  disturbance and degree of connection to the local
  species pool.
• Soil Carbon
• When Land Use changes to agriculture soil carbon
  will decrease
• Water Quality
• There is a negative relationship between
  intensity of land use and water quality.
• Landuse change has a more significant impact on
  water quality than Climate change.

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Statistical Development

• Development of path analysis tools for signal
  attribution
• Quantify causal/correlative chains
• Partition variation
• Take account of nested structure of CS data
• Bayesian analysis using WinBUGS offers a very
  flexible way of addressing these problems

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Conceptual attribution model
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Interactions and Trade-offs between services
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Interactions and Trade-offs between services

• Relationships between services simple
  correlations between variables (Naidoo 2008)
• Matrix of services within habitat by square
  based on real CS data
• Summarise by landclass
• Scaling up- Land Cover Map, other land
  classifications, contextual environmental and
  socio-economic information
• Temporal vs spatial relationships
• Overlay demand map
• Application of scenarios

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Up-scaling to catchment modelling and mapping

• Example Ribble and Loweswater catchments

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Evaluation of approaches

• Future outputs
• Report in 2010
• Scientific papers
• Methodological developments

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Questions

• Are you happy with the links weve made between
  measurement and service?
• Have we chosen the correct measurements for
  further attribution work?
• Can you suggest other drivers or external
  datasets that we could use?
• Can you suggest additional hypotheses for
  testing?