Coordination Team (CT) Biosphere

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Coordination Team (CT) Biosphere Mark Frenzel, Cornelia Baessler, Mathias Scholz & Stefan Klotz TERENO-Workshop Potsdam 24.-25. January 2012 Helmholtz Centre for Environmental Research - UFZ Dept. Community Ecology

Transcript of Coordination Team (CT) Biosphere

Page 1: Coordination Team (CT) Biosphere

Coordination Team (CT)

Biosphere

Mark Frenzel, Cornelia Baessler, Mathias Scholz & Stefan Klotz

TERENO-Workshop Potsdam 24.-25. January 2012

Helmholtz Centre for Environmental Research - UFZ

Dept. Community Ecology

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Harz/Central German Lowland Observatory

Magdeburg

Halle

Leipzig

Bode

Saale

Unstrut

Elbe

Core sites with (historical) data held by UFZ

Core sites established in 2009

Floodplain sites Agricultural sites

Agricultural sites

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Page 3 Frenzel, Baeßler, Klotz: CT Biospere

Global change

climate

land use

biodiversity

Evolutionary processes

Species interactions

Ecosystem functioning

net primary production

matter cycling

stability …

Issues of CT Biosphere

Approaches:

1. Monitoring and observation

2. Experimentation on different

scales

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SWOT-Analysis

Strengths: characteristics of business / project team

Weaknesses (or Limitations): characteristics placing the team at a disadvantage relative to others

Opportunities: external chances to improve performance

Threats: external elements that could cause trouble for business / project

Source: Wikipedia

Page 4 Frenzel, Baessler, Klotz: CT Biosphere

Origin Helpful Harmful

Internal

(attribute of

organization)

Strengths

Weaknesses

External

(attribute of

environment)

Opportunities

Threats

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Strengths (helpful, internal)

Hypothesis-driven

Page 5 Frenzel, Baessler, Klotz: CT Biosphere

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CT Biosphere Hypotheses

Climate and land use change influence…

1. … local adaptation => depends on genetic variation

2. … population genetics of plants => microevolutionary processes

3. … areal shifts of species => changes in existing communities

4. … ecological communities => consequences for ecosystem

functions and services (productivity, erosion control, pollination)

5. …the adaptability of selected ecosystems in the long-term

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S C

A L

E

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Strengths (helpful, internal)

Hypothesis-driven

Bioindication: organism-based integrative indication (reaction or

accumulation) of diverse (anthropogenic) impacts on / characteristics of

ecosystems

Page 7 Frenzel, Baessler, Klotz: CT Biosphere

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Bioindication: community similarity

Responses of community similarity in seven different communities to

land-use intensity (pesticide index)

landscape structure (splitting index of herbaceous vegetation)

Page 8 Frenzel, Baessler, Klotz: CT Biosphere

Dormann et al. (Global Ecol Biogeogr; 2007)

Page 9: Coordination Team (CT) Biosphere

Bioindication: community similarity

Response of bird and bee community similarity to landscape configuration

Page 9 Frenzel, Baessler, Klotz: CT Biosphere

Dormann et al. (Global Ecol Biogeogr; 2007)

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Strengths (helpful, internal)

Hypothesis-driven

Bioindication: organism-based integrative indication (reaction or accumulation) of diverse (anthropogenic) impacts on / characteristics of ecosystems

Indispensible Important indicator groups (what happens to the biotic part of ecosystems?)

Vascular plants => Primary producers (overall biodiversity indicators)

Bees & Hoverflies => Important pollinators (ecosystem service agents) (TMD – Tagfalter Monitoring)

Butterflies => Indicators for habitat quality, pollinators

Birds => Highly mobile, sensitive to landscape context, integrative on landscape scale

Page 10 Frenzel, Baessler, Klotz: CT Biosphere

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Weaknesses (harmful, internal)

Small team (UFZ staff only): biodiversity related research within TERENO main focus at UFZ

Harz/Central German Lowland Observatory (6 sites à 4x4km, 6 floodplain sites)

SoilCan sites (4 + replications)

Selected species groups (organism groups, frequency)

Low frequency data (e.g. bird surveys each third year)

Labor-intensive observations (traps, field surveys)

Not device-based (no automated measurements possible)

Extra budget for external assistance (specialists for specific groups)

Integration with abiotic measurements can still be improved

Page 11 Frenzel, Baessler, Klotz: CT Biosphere

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Opportunities (helpful, external)

Well-embedded in European initiatives (biotic and abiotic issues as well):

NETWORKS

LTER-Europe (Long-Term Ecosystem Research and Monitoring): Expert Panel Standardization & Technology

LTER-D (German network)

PROJECTS: WP‘s related to standardization of parameters and methods based on ecological integrity concept

• EnvEurope (Life+; 2010-13): Environmental quality and pressures assessment across Europe: the LTER network as an integrated and shared system for ecosystem monitoring

• Expeer (FP7; 2010-14): Experimentation in Ecosystem Research

• DBU Nature heritage sites: Monitoring concept

Page 12 Frenzel, Baessler, Klotz: CT Biosphere

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Threats (harmful, external)

Biodiversity measurements: Basic measurements comparable in

international context, but others (e.g. ECN – Environmental Change

Network UK) have resources to do more

All our efforts may be (suddenly ) overridden by unexpected climate

change effects (see worst scenarios of CO2 increase of the past have

already become true…)

Page 13 Frenzel, Baessler, Klotz: CT Biosphere

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Proposals for improvement

Within TERENO

Enhancing interdisciplinary links

Joint workshops

Tuning of measurement campaigns (see SoilCan)

… and of course some more

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Relationships between plant functional types and

ecosystem properties/ecosystem services

Topography

Land use Environmental parameters

(e.g. Soil properties)

Ecosystem properties

Biomass production

Water balance

Soil condition (e.g. carbon content)

Flowering onset mean & div.

Plant species diversity

Ecosystem services

Agronomic value

Cultural value

Pollination value

Soil carbon stock

Water quality

Plant functional traits (CWM, FD)

Biomass

C / N concentration

Biological traits (e.g. Flowering onset, Pollen vector)

Ecological traits (e.g. Ellenberg Indicator values)

Direct effects

Trait effects = Indirect effects

Trait response

(nach Lavorel et al. 2011)

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Relationships between plant functional types and

ecosystem properties/ecosystem services

TERENO Observatory Schäfertal

Magdeburg

Halle

Leipzig

Bode

Saale

Unstrut

Elbe

Floodplain sites Agricultural sites

Agricultural sites

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Relationships between plant functional types and

ecosystem properties/ecosystem services

TERENO Observatory Schäfertal

Magdeburg

Halle

Leipzig

Bode

Saale

Unstrut

Elbe

Floodplain sites Agricultural sites

Agricultural sites

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Relationships between plant functional types and

ecosystem properties/ecosystem services

TERENO Observatory Schäfertal

Magdeburg

Halle

Leipzig

Bode

Saale

Unstrut

Elbe

Floodplain sites Agricultural sites

Agricultural sites

Permanent plots

• Historical data: landscape

structure, land use & vegetation

data (1970, 2003, 2010)

• Collection of species frequency

data at permanent plots since

2010 – biennial (annually)

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Relationships between plant functional types and

ecosystem properties/ecosystem services

TERENO Observatory Schäfertal

Magdeburg

Halle

Leipzig

Bode

Saale

Unstrut

Elbe

Floodplain sites Agricultural sites

Agricultural sites

Permanent plots

• Historical data: landscape

structure, land use & vegetation

data (1970, 2003, 2010)

• Collection of species frequency

data at permanent plots since

2010 – biennial (annually)

Analyses of multidimensional functional diversity indices (FD) and

community weighted mean trait values (CWM) using plant functional traits

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Relationships between plant functional types and

ecosystem properties/ecosystem services

• Analysis of functional diversity

indices using different

biological and ecological trait

values, taking the frequency of

each species into account

Changes in functional diversity

across time

Period

1970 2003 2010

Fu

ncti

on

al

Ric

hn

ess

a

b

c

Multidimensional functional diversity (FD)

(ANOVA, Tukey HSD with Bonferroni correction)

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Relationships between plant functional types and

ecosystem properties/ecosystem services

• Significant shifts of

Community-weighted

traits across time

Period Period Period

1970 2003 2010 1970 2003 2010 1970 2003 2010

Fo

od

Qu

ality

Tem

pera

ture

Hu

mu

s

So

il M

ois

ture

N

utr

ien

ts

Community Weighted Mean trait values (CWM)

(ANOVA, Tukey HSD with Bonferroni correction)

a

b c

a

b c a b c

a

b

c

a

b c

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1970 2003 2010

Te

mp

era

ture

a

b

c

Land-use

Intensity

Soil conditions

Water balance

Species composition

(traits)

Soil erosion

Water quality

Species – Gene pool

Pollination

PRESSURE

• landscape

structure

• fertilizer

application

Ecosystem

function

Biodiversity

Ecosystem

services

Social,

Environmental

and

Economic

value

Policy

(EU, national)

(Baessler 2008)

N

Environmental

parameter +

Page 23: Coordination Team (CT) Biosphere

Vielen Dank!

Thank you very much!

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Landscape structure (Core site Friedeburg)

FB 2000

FB 1969

FB 1953

GH 1960

GH 1976

GH 2000

WAN 1955

WAN 1978

WAN 2000

0 1000 2000 3000 4000 Meters

Dry grasslands

Meadows Wetlands

Woodlands

Arable Fields Built-up Areas

Water Traffic Network

N

FB 2000

FB 1969

FB 1953

GH 1960

GH 1976

GH 2000

WAN 1955

WAN 1978

WAN 2000

0 1000 2000 3000 4000 Meters

Dry grasslands

Meadows Wetlands

Woodlands

Arable Fields Built-up Areas

Water Traffic Network

N

Period Nitrogen

(N; kg/ha)

Phosphorus

(P2O5; kg/ha)

1950s 35 31

1970s 124 61

2000 178 32

Period Shannon

Diversity

Share semi-

natural habitats

PROX whole

landscape (*10³)

Mean size

arable fields (ha)

1950s 0.97 36.1 1.6 1.6

1970s 0.85 29.8 3.4 8.1

2000 0.77 25.8 4.8 10.5

Baessler & Klotz 2006

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Vegetation analyses: arable weeds species richness (3 core sites)

Baessler 2008

arable weeds

Proximity whole landscapes

2000 4000 6000 8000 10000

sp

ecie

s n

um

be

r

15

20

25

30

35

40

45

50

55

woodland species

Proximity meadows

0 1000 2000 3000 4000 5000

sp

ecie

s n

um

be

r

0

1

2

3

4

5

arable weeds

Habitat diversity (SHDI)

0.4 0.5 0.6 0.7 0.8 0.9 1.0

sp

ecie

s n

um

be

r

15

20

25

30

35

40

45

50

55

arable weeds

nitrogen application (kg*ha-1

)

20 40 60 80 100 120 140 160 180 200

sp

ecie

s n

um

be

r

15

20

25

30

35

40

45

50

55

all study sites

WAN

FB

GH

a) b)

c) d)

arable weeds

share of semi-natural habitats (%)

15 20 25 30 35 40

sp

ecie

s n

um

be

r

15

20

25

30

35

40

45

50

55

e)

arable weeds

Proximity whole landscapes

2000 4000 6000 8000 10000

sp

ecie

s n

um

be

r

15

20

25

30

35

40

45

50

55

woodland species

Proximity meadows

0 1000 2000 3000 4000 5000

sp

ecie

s n

um

be

r

0

1

2

3

4

5

arable weeds

Habitat diversity (SHDI)

0.4 0.5 0.6 0.7 0.8 0.9 1.0

sp

ecie

s n

um

be

r

15

20

25

30

35

40

45

50

55

arable weeds

nitrogen application (kg*ha-1

)

20 40 60 80 100 120 140 160 180 200

sp

ecie

s n

um

be

r

15

20

25

30

35

40

45

50

55

all study sites

WAN

FB

GH

a) b)

c) d)

arable weeds

share of semi-natural habitats (%)

15 20 25 30 35 40

sp

ecie

s n

um

be

r

15

20

25

30

35

40

45

50

55

e)

F = 27.8*

F = 11.7*

sp

ec

ies

ric

hn

es

s

sp

ec

ies

ric

hn

es

s

wetlands

MPS meadows

0.6 0.8 1.0 1.2 1.4 1.6

30

35

40

45

50

woodlands

livestock density (ha-1

)

0.2 0.4 0.6 0.8 1.0 1.2

25

50

75

100

125

150

175

200

c) d)

e)

all semi-natural habitats

MPS meadows

0.6 0.8 1.0 1.2 1.4 1.6

sp

ec

ies

nu

mb

er

160

180

200

220

240

260

280

300

all semi-natural habitats

Proximity meadows

0 1000 2000 3000 4000 5000

sp

ec

ies

nu

mb

er

160

180

200

220

240

260

280

300

all semi-natural habitats

phosphorus application (ha-1

)

25 30 35 40 45 50 55 60 65

sp

ec

ies

nu

mb

er

160

180

200

220

240

260

280

300

a) b)

f)

wetlands

phosphorus application (ha-1

)

25 30 35 40 45 50 55 60 65

30

35

40

45

50

FB

WAN

GH

all study sites

Dates of relevés: 50ties, 70ties, 2000

• High habitat diversity => high

species richness

• High nitrogen application => low

species richness

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Land-use

Intensity

Soil conditions

Water balance

Species composition

(traits)

Soil erosion

Water quality

Species – Gene pool

Pollination

PRESSURE

landscape

structure

fertilizer

applications

ecosystem

function

Biodiversity

ecosystem

services

Social,

Environmental

and

Economic

value

Policy

(EU, national)

Baessler 2008

FB 2000

FB 1969

FB 1953

GH 1960

GH 1976

GH 2000

WAN 1955

WAN 1978

WAN 2000

0 1000 2000 3000 4000 Meters

Dry grasslands

Meadows Wetlands

Woodlands

Arable Fields Built-up Areas

Water Traffic Network

N

FB 2000

FB 1969

FB 1953

GH 1960

GH 1976

GH 2000

WAN 1955

WAN 1978

WAN 2000

0 1000 2000 3000 4000 Meters

Dry grasslands

Meadows Wetlands

Woodlands

Arable Fields Built-up Areas

Water Traffic Network

N

N

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Concepts I: DPSIR

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Ecological

integrity

Provision

of ecosystem

services

Human

well-being

Land use Drivers of

human action Response

Decision process

STATE IMPACT

of Ecosystems Decline (or improvement)

RESPONSE

Improve or mitigate

DRIVER

Need for…

PRESSURE

Human influence…

Page 28: Coordination Team (CT) Biosphere

Connection Ecol. Integrity - Ecosystem Services

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Ecosystem structures

- biotic diversity

- abiotic heterogeneity

Ecosystem processes

- energy balance

- water balance

- matter balance

Regulating services

- climate regulation

- water purification

. . .

Provision services

- food

- fuels

. . .

Cultural services

- inspiration

- genetic ressources

. . .

Social well-being

- health

- social security

- education

- nutrition

- accommodation

- leisure

. . .

Economy

- employment

- spending power

- infrastructure

- progress

. . .

STATE ESS HUMAN WELFARE

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ECOLOGICAL INTEGRITY

Ec

os

ys

tem

Str

uctu

res

Biotic Diversity / Processes and

Interactions

flora diversity

fauna diversity

habitat structure

additional variables

Abiotic Heterogeneity

soil heterogeneity

water heterogeneity

air heterogeneity

habitat heterogeneity

additional variables

Ec

os

ys

tem

Pro

ce

ss

Energy Budget

input exergy capture

storage exergy storage

output entropy production

additional state variables meteorology

efficiency measures metabolic efficiency

Matter Budget

input matter input

storage matter storage

output matter loss

additional state variables element concentrations

efficiency measures nutrient cycling

Water Budget

input water input

storage water storage

output water output

additional state variables element concentrations

efficiency measures biotic water flow

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