中国生态系统研究网络

Long-term ecosystem research & monitoring:

from local to global

Terry PARR [email protected]

UK

Centre for Ecology and Hydrology Natural Environment Research Council

Development of the UK Environmental Change Network and its role in addressing current and future

environmental issues

Countryside Council for Wales

EHS

The UK The UK

Environmental Change Environmental Change

Network (ECN) Network (ECN)

The UK’s long-term ecosystem monitoring and research (LTER) network.

1992-

www.ecn.ac.uk

Summary

ƒ

Brief overview of ECN

z

Integrated approaches to environmental monitoring and research

• Multi-scale approaches within the UK

• Networking LTER: site- national-continental-global integration

ƒ

Analysis: ECN in relation to

z

Biodiversity and climate change

z

Data resources

ƒ

Knowledge transfer and outreach

z Uses in research, policy and education

landscapes are highly

modified by human activities

•Long-term ecosystem research to understand, predict and manage changes

• Inter-disciplinary

•

• Multiple stakeholders

• Need to predict and manage environmental change impacts

The UK:

Many people, much urbanisation, intensive agriculture,

continuing economic growth

Public, policy and media concerns

UK Observation and Research Hierarchy for ecosystem research

Wide-scale survey

e.g. biological records, countryside survey Designated sites

e.g. condition monitoring Long-term

ecosystem research

sites

Remote Sensing - Land cover/habitat Biodiversity observatories

Birds, butterflies etc.

Intensive/

process based

Extensive survey

Land Cover Map Countryside Survey

UK Phenology Network

Butterfly Monitoring Scheme Biological Records Centre

Land Cover Map 1990, 2000, 2007

Comprehensive UK coverage Vector data set containing 6.6 million land parcels (segments) 0.5 ha minimum mappable unit Widespread Broad Habitats

Landsat

Atmosphere & climate

change Agriculture

Health & hazards Impact assessment

Ecology & conservation Marine & coastal

Water & catchments

Education & publicity Statistics, information Urban studies

Telecommunications Landscape planning

Uses of Land Cover Map data

Classified generalised MM (LCM2007) Satellite image & generalised MM LCM2000 & generalised MM

Changing methods

1990 2000 2007

Countryside Survey

Sample-based field surveys of the UK Vegetation, habitats,

soils, freshwater Land Cover Map

Census of land cover using remotely-sensed

satellite data

Countryside Survey

ITE Land Classification

Resource assessment and management in the UK

Informatics and Knowledge Transfer

Countryside Survey:

field survey sampling strategy

www.cs2000.org.uk

32 environmental strata

Sample size (km squares) 1978 256 1984 384 1990 508 1998 569 2007 629

Based on OS data, climate, soils and geology classified

to give 32 land classes

stratified random sample

GB covered by 629 1km squares

Broad Habitat types and landscape

features mapped in each 1km sample square

Components of the field survey

Sampling of

•

vegetation (approx 18,000 plots)

• freshwater biota

• soils

Policy - Hedgerow Protection

HEDGEROW PROTECTION LEGISLATION

Hedges ₁₉₉₀ ¹⁹⁸⁴

1998

0 100 200 300 400 500 600 700

'000 km

14 16 18 20 22

78 90 98

Year of survey

Mean species richness

Infertile grassland Upland wooded Upland grassland

Changes in Habitat quality

• Evidence that the condition of habitats declined since 1990

Smart et al. (2006) Biodiversity loss and biotic homogenisation. Proc R Soc

•

GB vegetation is becoming more homogenous

1990 (17 species)

1998 (7 species)

State of the Environment

UK Sustainable Development Indicators

CS Research Agenda…

ƒ What has changed?

..SIGNAL DETECTION

ƒ What caused the change?

..SIGNAL ATTRIBUTION

ƒ Do the changes matter?

..UNDERSTANDING CONSEQUENCES FOR ECOSYSTEM SERVICES

ƒ Forecasting and managing change?

..UNDERSTANDING PROCESSES

14 16 18 20 22

78 90 98

Year of survey

Mean species richness

Infertile grassland Upland wooded Upland grassland

Changes in Habitat quality

• Evidence that the condition of habitats declined since 1990

Smart et al. (2006) Biodiversity loss and biotic homogenisation. Proc R Soc

•

GB vegetation is becoming more homogenous

1990 (17 species)

1998 (7 species)

Key questions - soils

(and measurements)

ƒ

Is soil carbon changing and what are the drivers

z LOI, organic C

ƒ

Is recovery from acidification continuing?

z pH

ƒ

Is eutrophication continuing?

z %N and available-N

ƒ

What are the links between changes in below-ground biodiversity and changes in C and N?

z Invertebrate diversity, C, N

ƒ

Are their good indicators of soil quality and health?

z Olsen P, available N, LOI, invertebrate diversity, metals

Black et al., 2003. J. Env. Manag.

Changing states - soils

±

Differences in LOI (1978 - 2000) -12 -9 -6 -3 0 3 6 9

NB:

Suggest Soil carbon is

increasing in some areas.

Differs from Bellamy 2005 Nature paper

National map of change in soil organic matter

content

Soil Invertebrate Diversity (Shannon-Weiner Index H')

Mean Mean盨 E Mean? .96*SE

crops/weeds tall grass/herbs fertile grass infertile grass lowland wood upland wood moorland/grass heath/bog Vegetation Aggregate Class (CVS) 0.3

0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2

H'

First ever national survey of invertebrate diversity

Soil Invertebrate Diversity (Shannon-Weiner Index H')

Mean Mean盨 E Mean? .96*SE

crops/weeds tall grass/herbs fertile grass infertile grass lowland wood upland wood moorland/grass heath/bog Vegetation Aggregate Class (CVS) 0.3

0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2

H'

First ever national survey of invertebrate diversity

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50

3.5

<pH

<=4 .5

4.5<pH<=5.5 5.5

<pH

<=6 .5

6.5

<pH<=7.5 7.5<pH<=8

.5

mean change in pH (+ 1 s.e.)

pH interval [soil pH(1978+1998/8)/2]

Countryside Survey 2000 Mean change in soil pH from 1978 to 1998/9

767 soil samples (0 - 15 cm depth) from fixed locations across GB

Clear evidence of recovery from acidification

Black, Frogbrook et al., In Prep

1998

New Methods for Looking at Change CS2007 and Molecular Ecology

z

first country-level survey of microbial diversity in terrestrial ecosystems

z

establish baseline measurements for future surveys

z

UK wide genomic archive of our microbial biodiversity

Use of molecular techniques e.g. high density “microarray

technologies” to assess multiple taxa and

relationships to ‘soil quality’

CS Research Agenda…(2)

ƒ What caused the change?

..SIGNAL ATTRIBUTION

z

Land use change – agriculture & forestry

z

Atmospheric pollution

z

Non-native species

z

urbanisation

z

Climate change

Total N deposition Kg Ha yr-1

Species number

Acid grassland Calcareous grassland

Heathland 4.9

8.0 11.3

14.4 17.4

20.4 23.4

26.5 29.7

34.3

40.0 1

4 7 10 13 16 19 22 25 28 31 34 37 40

Maskell et al (in prep)

Are nitrogen inputs from the atmosphere a major driver of GB vegetation change?

2003 Smart et al Locating eutrophication effects in vegetation Global Change Biol 9 1763 2004 Smart & Scott. Bias in use of Ellenberg N. J Veg Sci 15 843

2004 Smart et al Detecting signal of atmospheric deposition of N on vegetation change Water, Air and Soil Pollution 4 269

Are non-native species a problem?

Non-native species often have a big local impact …

…. but are not yet a big problem in the wider countryside.

Maskell et al (2006) Non-native plants in common habitats. J Ecol

Himalyan balsam only present in 30 plots in 1998 Japanese knotweed is not

significant in CS

CS Research Agenda…(3)

ƒ Do the changes matter?

..UNDERSTANDING CONSEQUENCES FOR ECOSYSTEM SERVICES

Water Agriculture

Forestry Soils / carbon stores landscape and wildlife

tourism

0 2 4 6 8 10

Butterfly larval foodplants

Lowland farmland bird foodplants

1990 1998

Loss of Biodiversity

Declines in arable weeds

Declines in butterfly and bird foodplants

Smart et al (2000) Changes in abundance in food plants for birds and butterflies J Appl Ecol 37 398

-25 -20 -15 -10 -5 0 5 10 15

Bee forage plants Other plant species

Mean % change in CS plots (± SE)

Decline of bumblebee forage plants 1978-1998

Carvell et al. (2006) Biol. Conservation

Loss of Pollinators

Sustainable Land Management Research and Advice

ƒ Prescriptions for sustainable rural land management under agricultural reform

ƒ Catchment management

ƒ Capacity for renewable energy

production

ƒ CS provides info for:

z

Carbon inventory

z

Wood energy

z

Novel biofuels

z

Wind turbines

z

Critical loads

z

Natural stock at risk

Potential turbine density

0 2 4 6 8 Turbines per

square

U K E N E R G Y R E S E A R C H C E N T R E

CS & Energy Issues

Environmental capacity to provide energy

CS Research Agenda…(4)

ƒ Forecasting and managing change?

..UNDERSTANDING PROCESSES

Integrated assessment framework

Human well-being

• Material needs

• Health

• Good social relations

• Security

• Freedom of choice

Ecosystem services

•Provisioning

• Regulating

• Cultural

• Supporting

Drivers of change

•Land cover and land use

• Climate change

• Technology use

• Inputs (fertilisers, etc ..)

• Natural drivers

Responses

• Economic

• Socio-political

• Scientific and technological

• Cultural

Human well-being

• Material needs

• Health

• Good social relations

• Security

• Freedom of choice

Human well-being

• Material needs

• Health

• Good social relations

• Security

• Freedom of choice

Ecosystem services

•Provisioning

• Regulating

• Cultural

• Supporting

Ecosystem services

•Provisioning

• Regulating

• Cultural

• Supporting

Drivers of change

•Land cover and land use

• Climate change

• Technology use

• Inputs (fertilisers, etc ..)

• Natural drivers

Drivers of change

•Land cover and land use

• Climate change

• Technology use

• Inputs (fertilisers, etc ..)

• Natural drivers

Responses

• Economic

• Socio-political

• Scientific and technological

• Cultural

Responses

• Economic

• Socio-political

• Scientific and technological

• Cultural

Millennium Ecosystem Assessment (2003):

How will ecological impacts of different pressures translate into effects on ecosystem services?

Vegetation

Soils Freshwaters

Habitats

Features

CS & Natural Resource Management

N deposition

PRESSURES (Scenarios)

e.g.

STATE (from CS) e.g. effects on:

How will ecological impacts of different pressures translate into effects on ecosystem services?

Models and spatial data

Biodiversity Carbon Hydrology &

water quality Landscape

Land use &

productivity IMPACT:

Effects on Ecosystem Services and

Natural resources

Countryside Survey 2007 - Informatics

.. data brought together to deliver robust

information - quickly.

CS 2007 - Conclusion

STRENGTHS

ƒ Large-scale, long-term policy relevant survey

z cross-sectoral policy development

z links field and remote sensing data

ƒ Science outputs and potential

z major trends and pressures in the countryside

z implications for key ecosystem services

WEAKNESSES Expensive

Causes of change at ecosystem level - e.g climate change

-Forecasting

-e.g future climate change impacts

UK Observation and Research Hierarchy for ecosystem research

Wide-scale survey

e.g. biological records, countryside survey Designated sites

e.g. condition monitoring Long-term

ecosystem research

sites

Remote Sensing - Land cover/habitat Biodiversity observatories

Birds, butterflies etc.

Intensive/

process based

Extensive survey

UK Environmental Change Network

UK Environmental Change Network

Rationale and Mission Objectives

1992-

• Collect high-quality long-term data from a UK network of integrated monitoring sites.

• Disseminate data, information and research products for a range of uses in science, policy and the public.

• Analyse data to detect and interpret environmental

change.

The UK Environmental Change Network

Monitoring and research to detect and interpret environmental change

CENTRAL DATABASE www.ecn.ac.uk

ISSUES Climate change Atmospheric pollution

Land-use change Water resources

Biodiversity Soil quality 54 SITES

54 SITES 54 SITES

260 MEASUREMENTS driver and response variables

since 1993:standard protocols

260 MEASUREMENTS driver and response variables

since 1993:standard protocols

External use:

Direct Web-to-database access for users in science,

society and education 14 sponsoring and

9 research organisations

Internal Use:

Analysis & Modelling for:

-indicators -trend detection

- forecasting Quality Assurance:

•Control

•Validation

•Assessment

+

long-term experiments and process studies

Disturbed Sites < --- >Near Pristine Sites

42 ECN Freshwater Sites 12 ECN Terrestrial Sites

ECN: Standard Protocols for Environmental Monitoring

• Meteorology

• Atmospheric Chemistry

• Surface water flow & chemistry

• Soil solution chemistry

• Precipitation chemistry

• Soil surveys

•Vegetation surveys

•Vertebrates (birds, rabbits, deer, bats, frogs)

•Invertebrates

(butterflies, moths, ground predators, spittle bugs, crane flies)

•Site Management

• Surface water chemistry

• River discharge

• Continuous pH, temperature, conductivity & turbidity

• Temperature and dissolved oxygen profiles for lakes

• Chlorophyll a

• Invertebrates

• Macrophytes

• Zooplankton

• Phytoplankton

• Diatoms

Terrestrial Protocols Freshwater Protocols

Integrated measurements of

pressures, states and ecosystem services

Linking the cause and effects

of environmental change

Detecting and attributing change

The value of ECN/LTER Sites

Environmental Change Network Environmental Change Network

at at Moor House

Moor House – – Upper Teesdale Upper Teesdale

Climate warming

Climate warming - - “ “ Snow Days Snow Days ” ”

ECN Moor House ECN Moor House

0 20 40 60 80 100

1993-1994 1994-1995 1995-1996 1996-1997 1997-1998 1998-1999 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005

Snow Days per Winter

ECN Data

Climate effects Climate effects

Frog Spawning at Moor House Frog Spawning at Moor House

23-Feb 04-Mar 14-Mar 24-Mar 03-Apr 13-Apr 23-Apr 03-May 13-May

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Foot and Mouth

ECN Data

Climate Effects?

Climate Effects? - - Butterflies Butterflies

ECN Data from Ian Findlay, Butterfly Photos www.butterfly-guide.co.uk

1975 1980 1985 1990 1995 2000 2005

1977

Green-veined White Large White Painted Lady

Peacock Red Admiral Small Heath Small Tortoiseshell

Small White

1983

Common Blue

1993

Orange Tip 1994

Comma

2000

Small Skipper

2002

Dark Green Frit.

2002

Meadow Brown2003

Small Copper 2004

Ringlet

Grazing Grazing

Rabbit Density at Moor House Rabbit Density at Moor House

0 5000 10000 15000 20000 25000 30000 35000

1997 1998 1999 2000 2001 2002 2003 2004 2005

Number of Droppings

Autumn Summer Spring

ECN Data

Experiments Experiments

Grazing Removal Plots, 1954 to 2001 Grazing Removal Plots, 1954 to 2001

Burning Plots, Established 1954 Burning Plots, Established 1954

0 2 4 6 8 10 12 14

Grazed & Unburnt Grazed & Burnt Ungrazed & Unburnt

Depth (cm)

Block D Block C Block B Block A

Garnett, Ineson & Stevenson (2000) The Holocene, 10, 729 - 736

Carbon Dynamics and Moor Burning Carbon Dynamics and Moor Burning

Carbon Accumulation

Organisations Working at Moor House in 2005

CEH Edinburgh

Durham University

(Biology, Geog & Earth Sci) CEH Lancaster

Lancaster University (Env Sci & Biology) Glasgow University

York University Leeds University

Reading University Portsmouth University

University of Wales

Manchester University

Moor House Upper Teesdale

CEH Wallingford

Main Research Areas Since 1996 Peatland carbon dynamics

Effects of land management Stream sediment dynamics Biogeochemisty

Peat erosion

Peatland hydrology Pollution deposition Upland meteorology

Autecology (eg Red Grouse, Northern Eggar) Population dynamics (eg stream inverts)

Impacts of altitude (eg spittle bugs)

ECN Moor House:

Multi-functional multi-partner research platform

0 10 20 30 40 50

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

mg per litre

10 cm in Peat 50 cm in Peat

Error Bars: +/- 1 Standard Error

Dissolved Organic Carbon in Peat at Moor House Dissolved Organic Carbon in Peat at Moor House

ECN Data

Carbon stored in peatland

Carbon from weathering of underlying strata

Gaseous CH₄ Rainfall

Net gaseous CO₂exchange

DOC DIC POC

-1 0 0 -5 0 0 5 0 1 0 0 1 5 0

1 9 9 3 1 9 9 4 1 9 9 5 1 9 9 6 1 9 9 7 1 9 9 8 1 9 9 9 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 Y e a r

Net carbon flux (tonnes C/km

Net s ink

Net s ourc e

Av erage = 11 .4 Mg C/km²/yr

University of Durham

Ecosystem Services - Climate Change Mitigation

Are UK upland peats a sink or source of carbon?

ECN Data – e.g. dissolved organic carbon

Used to construct carbon budgets and models

Indicate peats may be changing from

C-sink to source

Sustainable Uplands

ƒ What is the future of carbon storage in the uplands?

ƒ What management strategies can we use to enhance carbon storage?

ƒ Using models developed and calibrated at Moor House and applying them to Peak District National Park

University of Durham Current

With burning

Detecting and attributing change

The value of UK Networks

Long-term changes in lake

ecosystems: trends, causes &

consequences

Lake Ecosystem Group

Centre for Ecology & Hydrology Lancaster Environment Centre

E-mail: [email protected]

Long-term data on lakes in Cumbria

Over 300 lake-years of data: at least fortnightly (previously weekly or fortnightly) from:

From 1945- Windermere North Basin, Windermere South Basin

Esthwaite Water Blelham Tarn From 1969- Grasmere

From 1990- Derwent Water, Bassenthwaite Lake

Examples of data

South Basin of Windermere

0 10 20 30 40 50

1945 1949 1953 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005

Date

[PO4-P]/ mg m-3

Measurements include:

Profiles of water temperature & O₂ Light penetration

Nutrient chemistry

Phytoplankton species & abundance Zooplankton

Fish populations 10.00

12.00 14.00 16.00 18.00

1960 1970 1980 1990 2000 2010 Year

Temperature (o C)

Summer temperature at 10 m

0.046 ^oC/yr ***

Perch spawning time

16 17 18 19 20 21 22 23

1940 1960 1980 2000

Year

Week

Concentration of PO₄-P

Regional patterns- the North Atlantic Oscillation & winter weather

ƒ

+ve NAOI produces relatively wet, mild, windy winters

ƒ

-ve NAOI produces relatively dry, cold, calm winters

Positive NAO

H L

Positive NAO Positive NAO

H

L

Differential sensitivity

-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8

Surface temperature

Winter nitrate Winter phosphate Overwinter chlorophyll a

Asterionella day of maximum

Correlation with NAOI (r)

North Basin Windermere South Basin Windermere Esthwaite Water

Blelham Tarn

Temperature NO3-N PO4-P Chl a Day of

Asterionella bloom

Correlation with NAO

Changes in timing of events

Esthwaite Water, Cumbria

y = -0.65x + 1381.55 R² = 0.26

0 30 60 90 120 150 180

1940 1960 1980 2000

Year

Day of Asterionella maximum

Asterionella

formosa

North Basin W indermere

y = -0.40x + 953.23 R² = 0.24

y = -0.16x + 450.65 R² = 0.10

y = -0.31x + 760.20 R² = 0.43

100 120 140 160 180 200

1920 1940 1960 1980 2000 2020 Year

Day of year

Daphnia max

Phytoplankton chlorophyll Perch spawning

Match-mismatch?

Cf. Walther et al. 2002 day yr^-1 Plant flowering/leaf break 0.14 – 0.31 Butterfly emergence 0.28 – 0.32 Bird migration 0.13 – 0.14 Bird breeding 0.19 – 0.48

General circulation models (GCM)

Regional circulation models (RCM)

Emission scenarios

Weather scenarios Nutrient inflow

PROTECH

Current work & future prospects ^:

II – Forecasting lake responses to perturbation

0 2 4 6 8 10 12 14

1 51 101 151 201 251 301 351

Day of year

Chlorophylla (mg m-3 ) Asterionella Dinobryon

Anabaena Microcystis Cryptom onas Tabellaria Rhodom onas Melosira

Conclusions

Long-term data are invaluable in documenting how lakes have responded to perturbation in the past and forecasting how they may respond in the future

Weather patterns (Gulf stream, NAO) will influence lakes regionally

Not all lakes will be equally sensitive to given aspects of climate change

Lakes are complex ecosystems that respond to changes in the catchment and atmosphere

Modelling in conjunction with long-term data, is a powerful

method of attribution and of forecasting responses to future

conditions

Are we losing biodiversity? Why? And so what?

LTER sites measure biodiversity, pressures and

ecosystem services.

Spawning

y = -0.9862x + 2044.4 R² = 0.1272

0 20 40 60 80 100 120 140

1992 1994 1996 1998 2000 2002 2004 2006

Year

day of spawning

Alice Holt Drayt on Glensaugh 1 Glensaugh 2 Hillsborough 1 Hillsborough 2 Moor House/ Upper Teesdale 1 Moor House/ Upper Teesdale 2 Moor House/ Upper Teesdale 3 Moor House/ Upper Teesdale 4 Moor House/ Upper Teesdale 5 Moor House/ Upper Teesdale 6 Moor House/ Upper Teesdale 7 Nort h Wyke Rot hamst ed Wyt ham Y Wyddf a/ Snowdon 1 Y Wyddf a/ Snowdon 2 All Linear (All)

Congregation

y = -2.4541x + 4978 R² = 0.3156

0 20 40 60 80 100 120 140

1992 1994 1996 1998 2000 2002 2004 2006

Year

day of spawning

Alice Holt Drayt on Glensaugh 1 Glensaugh 2 Hillsborough 1 Hillsborough 2 Moor House/ Upper Teesdale 1 Moor House/ Upper Teesdale 2 Moor House/ Upper Teesdale 3 Moor House/ Upper Teesdale 4 Moor House/ Upper Teesdale 5 Moor House/ Upper Teesdale 6 Moor House/ Upper Teesdale 7 Nort h Wyke Rot hamst ed Wyt ham Y Wyddf a/ Snowdon 1 Y Wyddf a/ Snowdon 2 All Linear (All)

Hatching

y = -0.1839x + 465.66 R² = 0.004 0

20 40 60 80 100 120 140 160

1992 1994 1996 1998 2000 2002 2004 2006

Year

day of spawning

Alice Holt Drayt on Glensaugh 1 Glensaugh 2 Hillsborough 1 Hillsborough 2 Moor House/ Upper Teesdale 1 Moor House/ Upper Teesdale 2 Moor House/ Upper Teesdale 3 Moor House/ Upper Teesdale 4 Moor House/ Upper Teesdale 5 Moor House/ Upper Teesdale 6 Moor House/ Upper Teesdale 7 Nort h Wyke Rot hamst ed Wyt ham Y Wyddf a/ Snowdon 1 Y Wyddf a/ Snowdon 2 All Linear (All)

Leaving

y = 2.128x - 4058.9 R² = 0.26

140 150 160 170 180 190 200 210 220 230 240

1992 1994 1996 1998 2000 2002 2004 2006

Year

day of spawning

Alice Holt Drayt on Glensaugh 1 Glensaugh 2 Hillsborough 1 Hillsborough 2 Moor House/ Upper Teesdale 1 Moor House/ Upper Teesdale 2 Moor House/ Upper Teesdale 3 Moor House/ Upper Teesdale 4 Moor House/ Upper Teesdale 5 Moor House/ Upper Teesdale 6 Moor House/ Upper Teesdale 7 Nort h Wyke Rot hamst ed Wyt ham Y Wyddf a/ Snowdon 1 Y Wyddf a/ Snowdon 2 All Linear (All)

FROGS – CLIMATE EFFECTS ON LIFE HISTORY

Trends in breeding dates. Overall extension of breeding season

Towards indicators of Climate Change Impacts

Effects of 1995 drought on insects in the UK (Data from 10 ECN sites)

ƒ can identify species of particular functional types that are likely to respond to climate change

ƒ E.g southern species with high mobility

BUTTERFLIES MOTHS BEETLES

0 20 40 60

Butterflies Moths Beetles

Number of species in drought year

Increasing Decreasing

Number of species in drought year

Increasing Decreasing

Morecroft et al (2003)

6.1

6.1 6.2 6.6

6.5 6.3

5.1 5.1 5.2

?

6.2

Ground Beetles

An Index of Southern-ness based on species’

distributions

Roy Anderson DARD(NI)

Changing Distributions – increases in “Southern” species

R² = 0.3919

6 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8

1992 1994 1996 1998 2000 2002

Carabid beetles–

Key part of food chain,

Cai r ngor ms

y = 32821e^-0.4153x R² = 0.7231

10 100 1000 10000 100000

0 2 4 6 8 10 12 14

A l i ce Hol t

y = 1593.2e^{0.05 25 x} R² = 0.1482

100 1000 10000

0 2 4 6 8 10 12 14

Cai r ngor ms

y = 32821e^{-0.41 53 x} R² = 0. 7231

10 100 1000 10000 100000

0 2 4 6 8 10 12 14

Dr ayt on

y = 890. 53e^{0.11 41 x} R² = 0. 3912

100 1000 10000

0 2 4 6 8 10 12 14

Gl ensaugh

y = 2288e^{-0.1 45 2x} R² = 0. 4635

100 1000 10000

0 2 4 6 8 10 12 14

Hi l l s bor ough

y = 4371. 1e^{-0.1 28 8x} R² = 0. 5761

100 1000 10000

0 2 4 6 8 10 12 14

M oor House

y = 63. 225e^{-0.2 06 8x} R² = 0. 7502

1 10 100

0 2 4 6 8 10 12 14

P or t on

y = 92. 644e^{0.2 133 x} R² = 0. 5373

1 10 100 1000 10000

0 2 4 6 8 10 12 14

Nor t h Wyk e

y = 1726. 6e^-0.1008x R² = 0. 1547

100 1000 10000

0 2 4 6 8 10 12 14

Rot hamst ed

y = 2294. 1e^{0.1 07 6x} R² = 0. 3159

1000 10000

0 2 4 6 8 10 12 14

Snowdon

y = 29782e^{-0.2 46 2x} R² = 0. 807

100 1000 10000 100000

0 2 4 6 8 10 12 14

Wyt ham

y = 620e^{0.065 7x} R² = 0. 3025

100 1000 10000

0 2 4 6 8 10 12 14

Sour hope

y = 2289. 4e^{-0.15 x} R² = 0. 5993

100 1000 10000

0 2 4 6 8 10 12 14

Glensaugh

Sourhope

Porton Wytham

North Wyke

Drayton Y Wyddfa

(Snowdon)

Rothamsted Hillsborough Moor House - Upper

Teesdale

Alice Holt Cairngorms

Glensaugh

Sourhope

Porton Wytham

North Wyke

Drayton Y Wyddfa

(Snowdon)

Rothamsted Hillsborough Moor House - Upper

Teesdale

Alice Holt Cairngorms

Glensaugh

Sourhope

Porton Wytham

North Wyke

Drayton Y Wyddfa

(Snowdon)

Rothamsted Hillsborough Moor House - Upper

Teesdale

Alice Holt Cairngorms

Carabids – Trends 1994-2003

“Indicator C1: a climate change impact indicator based on changes in the abundance of climate

sensitive species in ECN sites”

2002

Climate Impact Indicators

“A Biodiversity Strategy for England”

Biodiversity and climate change UK & European Policy Context

1. Will climate change prevent us meeting our legal obligation to protect wildlife in designated sites?

2. How many sites and what measurements would we need to “prove” climate change and air pollution impacts on

nature conservation sites?

MSOffic

幻灯片 66

MSOffice12 ate

, 2006-5-23

Targeted Monitoring Network – Design

Compare sites in:

High v low climate change areas High v low atmospheric pollution

40-90 sites needed

Measurements

• Climate

• Air pollution

• Wet deposition - pH, nitrate, ammonium, sulphate

• Ammonia concentration - diffusion tubes

• Total nitrogen deposition

• Soil chemistry and physical description

• Vegetation composition

• Butterflies

• Birds

• Satellite remote sensing of phenology

• Site management

Cost – c. $10,000 /site/year

LTER: Demonstration & Research Sites

Sites for science, training and education

Understanding the processes of environmental change and their

impacts on biodiversity and ecosystem services

Knowledge Management &

Communication in ECN

Educational Outreach

The “Climate Change Explorer”

working with artists and schools to inform people about climate change

ƒ

Phase II – funded by Department of Environment to raise awareness of

climate change amongst young people

www.

ec n.a c.uk

Ac ces s to Ra w D ata and Da ta P rodu cts

Open Access to Data

Summary Data - trends

e.g. Water Quality Dissolved organic carbon

Applications – Research

Surveillance

- Data Grid

Services

-

Data Grid Technology

uniform access to heterogeneous distributed databases

meta information; security; semantic mediation

Data &

Information Resources

Application

Layer Data discovery, exploration, analysis, visualisation

Science

Policy Public

Understanding

Users

ECN & UK databases

European databases

ALTER-Net

(EU Framework VI)

US Networks

Global Networks

Joining up data for ecosystem and climate impact research

from data to knowledge for environmental management and policy.

Detecting and attributing change

International Networks

LTER Sites

National Networks

European Networks

www.lter-europe.ceh.ac.uk

• inform national action plans

-how and why is biodiversity changing?

- forests, inland waters

- site management recommendations

• Assessment of policies - in protected areas - wider countryside, - cross-sectoral issues

local

LTER-Europe – established June 2007 Chair Michael Mirtl: UBA, Austria

European Networking for Biodiversity and

Ecosystem Research: capacity building

Knowledge from European LTER sites

Examples:

Glensaugh

Sourhope

Porton Wytham

North Wyke

Drayton Y Wyddfa (Snowdon)

Rothamsted Hillsborough Moor House - Upper

Teesdale

Alice Holt Cairngorms

Glensaugh

Sourhope

Porton Wytham

North Wyke

Drayton Y Wyddfa (Snowdon)

Rothamsted Hillsborough Moor House - Upper

Teesdale

Alice Holt Cairngorms

Glensaugh

Sourhope

Porton Wytham

North Wyke

Drayton Y Wyddfa (Snowdon)

Rothamsted Hillsborough Moor House - Upper

Teesdale

Alice Holt Cairngorms

DECREASE DECREASE

INCREASE INCREASE

Italy:

climate change impacts on

mountain plants Romania:

Valuation of ecosystem services in protected wetlands

UK:

trends vary across the country

Long-term

ecosystem research across Europe

Responses:

management and policy response

options e.g. habitats directive, water

framework directive

Adding the human dimension

Decisions affecting biodiversity must take into account the social, cultural and political context

A network of sites in which social scientists and ecologists work together:

•Deliberative events

•Public attitudes

•Conflict resolution

•Policy

Lower Danube, Romania

The DPSIR Indicator and Research Framework

PRESSURES for Change e.g. climate,

land management nutrient enrichment

STATE of biodiversity

socio-economic

DRIVERS of biodiversity loss (e.g. energy use,

transport, land use)

The Human RESPONSE Policy, ecosystem

management

Drivers:Pressure:State:Impact:Response (DPSIR)

IMPACT on ecosystem goods &

services

DPSIR DPSIR

LTER Sites

National Networks

Regional Networks

Global ILTER

www.ilternet.edu

local

global

Global Networking of Ecosystem research sites