MichielRutgers - Niedersachsen · in the Dutch Soil Monitoring Network MichielRutgers. 2 Biological Indicators of Soil Quality ... –aggregate formation Stability of soil ecosystem

1 06 December 2011

Biological Indicators of Soil Quality (BISQ) in the Dutch Soil Monitoring Network

Michiel Rutgers

2 Biological Indicators of Soil Quality (BISQ) inthe Dutch Soil Monitoring Network | 06 December 2011

Content

1. Indicators and measurements

2. Data, theory and models

3. Ecosystem services, from theory to practise

Biological Indicators of Soil Quality (BISQ) inthe Dutch Soil Monitoring Network | 06 December 2011

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4


5

Concern about loss of biodiversity

Agreement at the Earth Summit in Rio (1992)

� Convention on Biological Diversity (CBD):

●conservation and sustainable use

●biodiversity; and goods and services through biodiversity

The Netherlands: 70% agricultural area (small nature areas)

� Strategic Action Plan (SPA, 1994):

● focus on soil organisms and processes (life support functions)

●monitoring in a network � 1997


6

Life support functions in Dutch soil (1997)

● Decomposition of organic material

– Fragmentation

– Transformation of organic substrate

● Cycling of nutrients (N, C, P, S, K, Fe, H2O)

● Availability of nutrients for plants

● Formation of soil structure

– bioturbation

– aggregate formation

● Stability of soil ecosystemand food web


7

1997 Biological indicator of Soil Quality (BiSQ)

BB

QQSSii

1) Bacteria (several endpoints)

2) Fungi (biomass)

3) Nematodes (community composition)

4) Enchytraeids (idem)

5) Earthworms (idem)

6) Mites and springtails (idem)

7) Processes

8) Organic matter

9) More chemical and physical parameters

10) Vegetation, crops

11) Land management

-

Schouten et al. 1997. RIVM report 712910005 Schouten et al. 2004. Nem Mon Persp 2:469-482Rutgers et al. 2009. Eur J Soil Sci 60:820


8

Organisms interact in food webs

Hunt et al. 1987 Biol Fert Soils 3:57-68De Ruiter et al. 1995. Science 269:1257-1260


9

Sampling sites BISQ / DSMNDairy farm sand organic

Dairy farm sand extensive

Dairy farm sand intensive

Dairy farm sand intensive+

Dairy farm river clay intensive

Dairy farm marine clay organic

Dairy farm marine clay intensive

Dairy farm peat organic

Dairy farm peat intensive

Dairy farm loess organic

Dairy farm loess intensive

Arable farm sand organic

Arable farm sand intensive

Arable farm marine clay organic

Arable farm marine clay intensive

Horticulture sand

Bulb-growing sand

Semi-natural grassland sand

Heathland sand

Forest sand

Dutch Soil Quality Network (DSQN)20 categories:

● land use X soil type

● stratified grid; farm level

● represents ~75% surface area Netherlands

Categories:

conventional farms, organic farms (dairy orarable), nature, parks

Major soil types:

sand, peat, loess,marine clay, river clay


10

Field sampling


11

Field sampling

320 cores


12

Field sampling 2 x 6 columns


13

Field sampling

6 cubes (20x20x20 cm)


14

Data

diversity

(operational diversity units)

amount(biomass or number)

0

5

10

15

20

25

30

35

40

HoSa Ar Sa DaSa SgSa Ar Mc DaMc DaRc

l a nd us e a nd s o i l t y pe

0

2

4

6

8

10

12

14

16



0

0.5

1

1.5

2

2.5

3


l a nd us e a nd s oi l t y pe

0

5

10

15

20

25

30


l a nd u s e a nd s o i l t y pe

0

10

20

30

40

50

60

70

80



bac

teri

alD

NA

mic

ro-a

rth

rop

od

sea

rth

wo

rms

po

two

rms

nem

ato

des

(DN

A b

and

s)

(t

axa)

(

fish

eral

fa)

(ta

xa)

(

taxa

)

HoSa ArSa DaSa SgSa ArMc DaMc DaRc

land use and soil type

0

10 00

20 00

30 00

40 00

50 00

60 00

HoSa ArSa DaSa SgSa Ar Mc DaMc DaRc

lan d use an d soil t ype

0

10000

20000

30000

40000

50000

60000

70000

80000

90000


l a nd u s e a nd s oi l t y pe

0

100

200

300

400

500

600


l a nd use a nd s oi l t y pe

0

20000

40000

60000

80000

100000



0

100

200

300

400

500

600





bac

teri

alb

iom

ass

mic

ro-a

rth

rop

od

sea

rth

wo

rms

potw

orm

sne

mat

od

es(m

g C

/ g D

W)

(

n /

m2)

(n /

m2)

(n /

m2)

(n

/ 10

0g fw

)

diversity(operational diversity units)

amount(biomass or number)

0

5

10

15

20

25

30

35

40



0

2

4

6

8

10

12

14

16



0

0.5

1

1.5

2

2.5

3



0

5

10

15

20

25

30



0

10

20

30

40

50

60

70

80



0

5

10

15

20

25

30

35

40



0

2

4

6

8

10

12

14

16



0

0.5

1

1.5

2

2.5

3



0

5

10

15

20

25

30



0

10

20

30

40

50

60

70

80



bac

teri

alD

NA

mic

ro-a

rth

rop

od

sea

rth

wo

rms

po

two

rms

nem

ato

des

(DN

A b

and

s)

(t

axa)

(

fish

eral

fa)

(ta

xa)

(

taxa

)



0

10 00

20 00

30 00

40 00

50 00

60 00



0

10000

20000

30000

40000

50000

60000

70000

80000

90000



0

100

200

300

400

500

600



0

20000

40000

60000

80000

100000



0

100

200

300

400

500

600



0

10 00

20 00

30 00

40 00

50 00

60 00



0

10000

20000

30000

40000

50000

60000

70000

80000

90000



0

100

200

300

400

500

600



0

20000

40000

60000

80000

100000



0

100

200

300

400

500

600





bac

teri

alb

iom

ass

mic

ro-a

rth

rop

od

sea

rth

wo

rms

potw

orm

sne

mat

od

es(m

g C

/ g D

W)

(

n /

m2)

(n /

m2)

(n /

m2)

(n

/ 10

0g fw

)

● Many (106-107)

● >100 pub’s

● Variable but realistic


15

ODE - melkveehouderij op klei (1999-2003)

regenwormen

0

2

4

6

8

10

12

0 5 10 15 20

organische stof (% DM)

OT

U (a

anta

l tax

a)

microarthropoden

0

10

20

30

40

50

60

0 5 10 15 20


OT

U (a

anta

l tax

a)

bacterie-functies

0.00

0.20

0.40

0.60

0.80

1.00

0 5 10 15 20


OT

U (h

ellin

g B

iolo

g)

bacterie-DNA

20

30

40

50

60

70

80

0 5 10 15 20


OT

U (D

NA

-ban

den

)

nematoden

10

20

30

40

50

0 5 10 15 20


OT

U (a

anta

l tax

a)

potwormen

0

5

10

15

20

0 5 10 15 20


OTU

(aan

tal t

axa)

regenwormen

0

2

4

6

8

10

12

0 5 10 15 20


OT

U (a

anta

l tax

a)

microarthropoden

0

10

20

30

40

50

60

0 5 10 15 20


OT

U (a

anta

l tax

a)

bacterie-functies

0.00

0.20

0.40

0.60

0.80

1.00

0 5 10 15 20


OT

U (h

ellin

g B

iolo

g)

bacterie-DNA

20

30

40

50

60

70

80

0 5 10 15 20


OT

U (D

NA

-ban

den

)

nematoden

10

20

30

40

50

0 5 10 15 20


OT

U (a

anta

l tax

a)

potwormen

0

5

10

15

20

0 5 10 15 20


OTU

(aan

tal t

axa)

nematoden

0

2000

4000

6000

8000

10000

12000

0 5 10 15 20


biom

assa

(aan

talle

n)

regenwormen

0

300

600

900

0 5 10 15 20


biom

assa

(aan

talle

n)

potwormen

0

30000

60000

90000

0 5 10 15 20


biom

assa

(aan

talle

n)

micro-arthropoden

0

10000

20000

30000

40000

50000

0 5 10 15 20


bio

mas

sa (a

anta

llen

)

bacterien (microscoop)

0

300

600

900

1200

1500

0 5 10 15 20


bio

mas

sa (u

g C

/g D

W)

bacterien (biochemisch)

1

10

100

1000

10000

0 5 10 15 20


bio

mas

sa (u

g D

W/5

0% o

mze

ttin

g)

nematoden

0

2000

4000

6000

8000

10000

12000

0 5 10 15 20


biom

assa

(aan

talle

n)

regenwormen

0

300

600

900

0 5 10 15 20


biom

assa

(aan

talle

n)

potwormen

0

30000

60000

90000

0 5 10 15 20


biom

assa

(aan

talle

n)

micro-arthropoden

0

10000

20000

30000

40000

50000

0 5 10 15 20


bio

mas

sa (a

anta

llen

)

bacterien (microscoop)

0

300

600

900

1200

1500

0 5 10 15 20


bio

mas

sa (u

g C

/g D

W)

bacterien (biochemisch)

1

10

100

1000

10000

0 5 10 15 20


bio

mas

sa (u

g D

W/5

0% o

mze

ttin

g)

0 10 20 0 10 20 0 10 20 0 10 20 0 10 20 0 10 20

0 10 20 0 10 20 0 10 20 0 10 20 0 10 20 0 10 20

Biomass – dairy farming on clay (1999-2003)

ODU – dairy farming on clay (1999-2003) nematodes (taxa) earthworms (fisher-alfa) potworms (taxa) micro-arthropods (taxa) bac teria (DNA bands) bacteria (ODU Biolog)

nematodes (n/100g) earthworms (n/m2) potworms (n/m2) micro-arthropods (n/m2) bact eria (µg C/g DW) bacteria (Biolog)

� Organic matter content (% dw)

� Organic matter content (% dw)

Rutgers et al. 2010. RIVM report 607370002


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Bacterial pathway Detrital pathway

24 25 26

27 28 29

30

3 4 5 6

7 8 10

11 12

13 14

15 16

19 20 21 2297bis 23

17 18

1 2

SOIL RESOURCES

SOIL SYSTEMMulder. 2006. Naturwissenschaften 93:467-479

But we can easily merge this huge amount of informa tion in a Cartesian plane

Theory


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mites

collembolans

nematodesenchytraeids

MICROFAUNA MESOFAUNA

R 2 = 0.622

1

2

3

4

5

6

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5

Average body mass (log10 micrograms)

Nu

mer

ical

ab

un

dan

ce (

log

10 in

div

idu

als)

Better Organic Matter

SAME FOOD WEB AS IN THE PREVIOUS SLIDE

Scaling

EF

FE

CT


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exploitation

restoration

management

inte

nsit

y of

str

ess

environmentalchange

DISTURBANCE

REFERENCE

ALLOMETRIC RESPONSE

ASSESSMENT

Such a “Distance to Target” enables the measure of any deviation from the chosen reference

org

anis

m a

bun

dan

ce

organism mass

affected target

b

exploitation

restoration

management

inte

nsit

y of

str

ess

environmentalchange

DISTURBANCE

REFERENCE

ALLOMETRIC RESPONSE

ASSESSMENT


org

anis

m a

bun

dan

ce

organism mass

affected target

b

exploitation

restoration

management

inte

nsit

y of

str

ess

environmentalchange

DISTURBANCE

REFERENCE

ALLOMETRIC RESPONSE

ASSESSMENT


org

anis

m a

bun

dan

ce

organism mass

affected target

b

org

anis

m a

bun

dan

ce

organism mass

affected target

b

Mulder et al. 2011. Oikos 120:529-536Data and assessment


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Ecosystem services (ES)

The benefits fromecosystems

These include products like clean drinking water and processes such as the decomposition of toxic waste.

Main categories Millennium

Ecosystem Assessment 2005

● Provisioning

● Regulating

● Cultural

● (Supporting)


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Soil organisms provide ecosystem services

Supporting services Nutrient cycling Primary production Soil formation

SANDY SOILS (PODZOL)

Fungi (1), Lumbricidae (2), Protozoa (3), Enchytraeidae (4),

Bacteria (5), Collembola (6)

Fungi (1), Nematoda (2), Lumbricidae (3), Protozoa (4), Bacteria (5), Enchytraeidae (6),

Collembola (7), Acarina (8)

Lumbricidae (1), Enchytraeidae (2), Fungi (3), Bacteria (4)

CLAYS (CAMBISOL AND FLUVISOL)

Enchytraeidae (1), Collembola (2), Fungi (3), Protozoa (4),

Lumbricidae (5), Bacteria (6), Nematoda (7), Acarina (8)

Nematoda (1), Enchytraeidae (2), Fungi (3), Protozoa (4), Bacteria (5), Collembola (6), Lumbricidae

(7), Acarina (8)

Enchytraeidae (1), Collembola (2), Bacteria (3), Fungi (4),

Lumbricidae (5)

Literature and expert judgement, e.g.; Mulder et al. 2011. Adv Ecol Res 44:277-357Luck et al. 2009. Bioscience 59:223-235


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Pilot Hoeksche Waard

2

3 4

11

1


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Equations ecosystem services (ES)

soil quality = Σ γ(i) • ESsoil(i)

ESsoil = f (biotics, abiotics, other)

(weight factors γ(i) were determined in a multi-stakeholder process)


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soil structure 72%

water retention 79%

climate functions 116%

nutrient retention 69%

disease and pest control 93%

resistance resilience 89%

adaptation 73%

turn over OM 76 %

natural attenuation 109%

biodiversity 84%

soil structure 72%

water retention 79%





adaptation 73%

turn over OM 76 %


biodiversity 84%

soil structure 72%

water retention 79%





adaptation 73%

turn over OM 76 %


biodiversity 84%

10 ecosystem services at 4 arable farms

Rutgers et al. 2011. Sci Tot Environ (in press)

average A B C D

1. production related functions

a. nutrient retention and release 0.69 0.64 0.65 0.72 0.70

b. soil structure formation 0.72 0.74 0.80 0.65 0.66

c. disease and pest control 0.87 1.23 1.05 0.69 0.76

2. resilience and resistance

a. resistance and resilience 0.89 0.93 0.97 0.81 0.74

b. adaptation, land use change 0.73 0.77 0.79 0.64 0.62

3. Environmental functions

a. fragmentation mineralization OM 0.76 0.66 0.71 0.73 0.82

b. natural attenuation 1.09 1.10 1.05 0.98 1.25

c. water retention 0.79 0.78 0.88 0.69 0.77

d. climatic functions (humidity, gasses,..) 1.16 1.03 1.16 1.10 1.21

4. biodiversity

a. habitat function of the soil 0.84 0.89 0.90 0.76 0.69


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Conclusions and outlook

● Pragmatic choices enable quick and practical quantification of soil quality through the performance of ES:

– validation of quantification schemes is still requested

– always do a comprehensive check with all stakeholders for ‘forgotten’ ES

– use weight factors to prioritize ES for applications in DSS

● Ecosystem theory is required for quantification of ES; not enough is known, but progress is accelerating …..

● Maps can be used in the stakeholder process and for awareness raising


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Thanks RIVM:

Christian MulderTon SchoutenTon BreureDick de ZwartHarm van WijnenJaap BogteHenri den HollanderLeo Posthuma

partners:

Jaap BloemGerard Jagers op AkkerhuisRon de GoedeNick van EekerenHarm KeidelWim DimmersTamas SalankiAn VosGerard Korthals


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End

Documents

MichielRutgers - Niedersachsen · in the Dutch Soil Monitoring Network MichielRutgers. 2 Biological Indicators of Soil Quality ... –aggregate formation Stability of soil ecosystem