Biological Indicators of Soil Quality (BISQ) in the Dutch Soil Monitoring Network Michiel Rutgers 1 6 December 211
Content 1. Indicators and measurements 2. Data, theory and models 3. Ecosystem services, from theory to practise 2
3
4
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: 7% agricultural area (small nature areas) Strategic Action Plan (SPA, 1994): focus on soil organisms and processes (life support functions) monitoring in a network 1997 5
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 ecosystem and food web 6
1997 Biological indicator of Soil Quality (BiSQ) 1) Bacteria (several endpoints) 2) Fungi (biomass) 3) Nematodes (community composition) 4) Enchytraeids (idem) B S 5) Earthworms (idem) 6) Mites and springtails (idem) 7) Processes 8) Organic matter i Q - 9) More chemical and physical parameters 1) Vegetation, crops 11) Land management 7 Schouten et al. 1997. RIVM report 712915 Schouten et al. 24. Nem Mon Persp 2:469-482 Rutgers et al. 29. Eur J Soil Sci 6:82
Organisms interact in food webs Hunt et al. 1987 Biol Fert Soils 3:57-68 De Ruiter et al. 1995. Science 269:1257-126 8
Sampling sites BISQ / DSMN Dairy farm sand organic Dairy farm sand extensive Dutch Soil Quality Network (DSQN) 2 categories: land use X soil type stratified grid; farm level represents ~75% surface area Netherlands Categories: conventional farms, organic farms (dairy or arable), nature, parks 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 Major soil types: sand, peat, loess, marine clay, river clay 9
Field sampling 1
Field sampling 32 cores 11
Field sampling 2 x 6 columns 12
Field sampling 6 cubes (2x2x2 cm) 13
diversity (operational diversity units) amount (biomass or number) 4 6 35 5 Data Many (1 6-1 7 ) >1 pub s Variable but realistic 14 bacterial DNA micro-arthropods earthworms potworms nematodes (DNA bands) (taxa) (fisher alfa) (taxa) (taxa) 3 25 2 15 1 5 16 14 12 1 8 6 4 2 3 2.5 2 1.5 1.5 3 25 2 15 1 5 8 7 6 5 4 3 2 1 HoSa Ar Sa DaSa SgSa Ar Mc DaMc DaRc l a n d us e a n d s o i l t y p e HoSa Ar Sa DaSa SgSa Ar Mc DaMc DaRc l a nd u s e a nd s o i l t y pe HoSa Ar Sa DaSa SgSa Ar Mc DaMc DaRc l a nd us e a nd s oi l t y pe HoSa Ar Sa DaSa SgSa ArMc DaMc DaRc l a nd u s e a nd s o i l t y pe HoSa ArSa DaSa SgSa ArMc DaMc DaRc HoSa ArSa DaSa SgSa ArMc DaMc DaRc l a nd us e a nd s oi l t y pe l a nd us e a n d s oi l t y pe land use and soil type bacterial biomass micro-arthropods earthworms potworms nematodes (mg C/ g DW) (n / m2) (n / m2) (n / m2) (n / 1g fw) 4 3 2 1 9 HoSa ArSa DaSa SgSa Ar Mc DaMc DaRc 8 7 lan d use an d soil t ype 6 5 4 3 2 1 6 HoSa ArSa DaSa SgSa Ar Mc DaMc DaRc 5 l a nd u s e a nd s oi l t y p e 4 3 2 1 1 HoSa Ar Sa DaSa SgSa Ar Mc DaMc DaRc 8 l a nd use a nd s oi l t y pe 6 4 2 HoSa Ar Sa DaSa SgSa Ar Mc DaMc DaRc 6 5 l and use and soi l type 4 3 2 1 land use and soil type
ODU dairy farming on clay (1999-23) Rutgers et al. 21. RIVM report 67372 bacterie-functies nematodes nematoden (taxa) earthworms regenwormen (fisher-alfa) potworms potwormen (taxa) micro-arthropods microarthropoden (taxa) bacteria bacterie-dna (DNA bands) bacteria (ODU Biolog) 5 12 2 6 8. OTU (aantal taxa) 4 3 2 OTU (aantal taxa) 1 8 6 1 3 5 ODE - melkveehouderij op klei (1999-23) 4 2 OTU (aantal taxa) 15 5 OTU (aantal taxa) 5 4 2 1 OTU (DNA-banden) 7 6 4 3 OTU (helling Biolog).2.4.6.8 1 5 1 15 2 organische stof (% DM) 5 1 15 2 organische stof (% DM) 5 1 15 2 organische stof (% DM) 5 1 15 2 organische stof (% DM) 2 5 1 15 2 organische stof (% DM) 5 1 15 2 1. 1 2 1 2 1 2 1 2 1 2 1 2 Organic matter content (% dw) Biomass dairy farming on clay (1999-23) organische stof (% DM) bacterien (biochemisch) nematodes nematoden(n/1g) earthworms regenwormen (n/m2) potworms potwormen (n/m2) micro-arthropods micro-arthropoden (n/m2) bacteria bacterien (microscoop) (µg C/g DW) bacteria (Biolog) 12 9 9 5 15 1 biomassa (aantallen) 1 8 6 4 2 biomassa (aantallen) 6 3 biomassa (aantallen) 6 3 biomassa (aantallen) 4 3 2 1 biomassa (ug C/g DW) 12 9 6 3 biomassa (ug DW/5% omzetting) 1 1 1 5 1 15 2 5 1 15 2 5 1 15 2 5 1 15 2 5 1 15 2 15 organische 1 stof (% DM) 2 organische 1 stof (% DM) 2 organische 1 stof (% DM) 2 organische 1 stof (% DM) 2 organische 1 organische stof (% DM) stof (% DM) 2 1 2 Organic matter content (% dw) 5 1 15 2 1
Theory Mulder. 26. Naturwissenschaften 93:467-479 Bacterial pathway SOIL SYSTEM 3 Detrital pathway 27 28 29 24 25 26 7bis 7 8 9 1 13 14 19 2 21 22 23 3 4 5 6 11 12 15 16 17 18 1 2 SOIL RESOURCES But we can easily merge this huge amount of information in a Cartesian plane 16
Numerical abundance (log 1 individuals) 6 5 4 3 2 1 MICROFAUNA Scaling nematodes MESOFAUNA enchytraeids collembolans mites R 2 =.622-2 -1.5-1 -.5.5 1 1.5 2 2.5 Average body mass (log 1 micrograms) Better Organic Matter EFFECT 17 SAME FOOD WEB AS IN THE PREVIOUS SLIDE
Data and assessment Mulder et al. 211. Oikos 12:529-536 REFERENCE DISTURBANCE environmental change intensity of stress exploitation management restoration organism abundance b ALLOMETRIC RESPONSE affected target organism mass Such a Distance to Target enables the measure of any deviation from the chosen reference ASSESSMENT 18
Ecosystem services (ES) The benefits from ecosystems These include products like clean drinking water and processes such as the decomposition of toxic waste. Main categories Millennium Ecosystem Assessment 25 Provisioning Regulating Cultural (Supporting) 19
Soil organisms provide ecosystem services Literature and expert judgement, e.g.; Mulder et al. 211. Adv Ecol Res 44:277-357 Luck et al. 29. Bioscience 59:223-235 Supporting services SANDY SOILS (PODZOL) CLAYS (CAMBISOL AND FLUVISOL) Nutrient cycling Primary production Soil formation 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) 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) 2
Pilot Hoeksche Waard 3 4 1 2 1 1 21
Equations ecosystem services (ES) soil quality = Σ γ (i) ES soil(i) (weight factors γ (i) were determined in a multi-stakeholder process) ES soil = f (biotics, abiotics, other) 22
1 ecosystem services at 4 arable farms average A B C D 1. production related functions a. nutrient retention and release.69.64.65.72.7 b. soil structure formation.72.74.8.65.66 c. disease and pest control.87 1.23 1.5.69.76 2. resilience and resistance a. resistance and resilience.89.93.97.81.74 b. adaptation, land use change.73.77.79.64.62 3. Environmental functions a. fragmentation mineralization OM.76.66.71.73.82 b. natural attenuation 1.9 1.1 1.5.98 1.25 c. water retention.79.78.88.69.77 d. climatic functions (humidity, gasses,..) 1.16 1.3 1.16 1.1 1.21 4. biodiversity a. habitat function of the soil.84.89.9.76.69 disease and pest control 93% resistance resilience 89% soil structure 72% adaptation 73% nutrient retention 69% turn over OM 76 % natural attenuation 19% water retention 79% biodiversity 84% climate functions 116% Rutgers et al. 211. Sci Tot Environ (in press) 23
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 24
Thanks RIVM: Christian Mulder Ton Schouten Ton Breure Dick de Zwart Harm van Wijnen Jaap Bogte Henri den Hollander Leo Posthuma partners: Jaap Bloem Gerard Jagers op Akkerhuis Ron de Goede Nick van Eekeren Harm Keidel Wim Dimmers Tamas Salanki An Vos Gerard Korthals 25
End 26