why a cost action on soil fauna and som dynamics? current ... · “why a cost action on soil fauna...

Earth System Science and Environmental Management (ESSEM) Domain

“Why a COST Action on soil fauna and

SOM dynamics?

Current status and future challenges”

Pyrenean Institute of Ecology (IPE-CSIC) Spain

COST is supported by the EU Framework Programme Horizon 2020

Coimbra, 4-7 October 2016

Juan J. Jiménez

1st Training School

COST Action ES1406

www.keysom.eu

With contributions from Juliane Filser, Patrick lavelle, Sébastien Barot and many others

http://www.keysom.eu/

Earth System Science and Environmental Management (ESSEM) Domain

COST Action ES1406

“Soil fauna: key to soil organic matter dynamics and

modelling (KEYSOM)”

1 Pyrenean Institute of Ecology (IPE-CSIC) Spain


Juan J. Jiménez1 (Chair) Juliane Filser2 (Vice chair)

…and MC members

2 Center for Environmental Research and

Sustainable Technology

www.keysom.eu

http://www.keysom.eu/

Participating countries list (as per September 2016)

ESSEM COST Action ES1406

Common experimentation

and testing

Including Italy and Finland

23 Countries

Country Date

Austria 15/12/2014

Belgium 17/04/2015

Bulgaria 06/08/2015

Croatia 20/02/2015

Czech Republic 14/01/2015

Denmark 15/07/2015

Estonia 09/02/2015

France 26/01/2015

Germany 05/12/2014

Greece 08/05/2015

Ireland 10/12/2014

Italy 06/06/2016

Lithuania 22/12/2014

Netherlands 05/02/2015

Norway 29/01/2015

Poland 12/12/2014

Portugal 03/02/2015

Romania 15/01/2015

Serbia 21/10/2015

Slovenia 08/04/2016

Spain 24/11/2014

Switzerland 18/05/2015

United Kingdom 14/10/2015

http://www.cost.eu/about_cost/cost_countries?countrycode=AT

http://www.cost.eu/about_cost/cost_countries?countrycode=BE

http://www.cost.eu/about_cost/cost_countries?countrycode=BG

http://www.cost.eu/about_cost/cost_countries?countrycode=HR

http://www.cost.eu/about_cost/cost_countries?countrycode=CZ



http://www.cost.eu/about_cost/cost_countries?countrycode=DK

http://www.cost.eu/about_cost/cost_countries?countrycode=EE

http://www.cost.eu/about_cost/cost_countries?countrycode=FR

http://www.cost.eu/about_cost/cost_countries?countrycode=DE

http://www.cost.eu/about_cost/cost_countries?countrycode=EL

http://www.cost.eu/about_cost/cost_countries?countrycode=IE

http://www.cost.eu/about_cost/cost_countries?countrycode=IT

http://www.cost.eu/about_cost/cost_countries?countrycode=LT

http://www.cost.eu/about_cost/cost_countries?countrycode=NL

http://www.cost.eu/about_cost/cost_countries?countrycode=NO

http://www.cost.eu/about_cost/cost_countries?countrycode=PL

http://www.cost.eu/about_cost/cost_countries?countrycode=PT

http://www.cost.eu/about_cost/cost_countries?countrycode=RO

http://www.cost.eu/about_cost/cost_countries?countrycode=RS

http://www.cost.eu/about_cost/cost_countries?countrycode=SI

http://www.cost.eu/about_cost/cost_countries?countrycode=ES

http://www.cost.eu/about_cost/cost_countries?countrycode=CH

http://www.cost.eu/about_cost/cost_countries?countrycode=UK



OBJECTIVES AND BENEFITS

To implement the role of soil fauna into existing SOM models for land use and

natural resource management.

A set of recommended agricultural practices for reducing depletion of SOM and

beneficial soil fauna will be promoted.

Benefits:

(1) network of experts in biogeosciences, soil ecology, SOM turnover, microbiology,

nutrient dynamics (N, P cycles), and modelling across Europe

(2) knowledge gaps analysis and conceptual framework development for guiding future

research;

(3) training to the next generation of researchers;

(4) European perspective emphasis within global research network, and

(5) Supportive decision-making policies at local, regional and international levels.


Working groups and tasks

WG 4 (Prof. Paulo Sousa) Dissemination of results from analyses, knowledge management and material for training and stakeholder purposes;

Gender balance achieved

WG1 (Prof. Juliane Filser) Data sharing and information, state-of-the-art and gap analysis of SOM – soil fauna interactions;

WG2 (Dr. Sébastien Barot) Review existing global SOM models and analysis of their potentials and limitations for inclusion of soil fauna effects;

WG 3 (Dr. Davorka Hackenberg) Assembling data from the different sites (studies) in a meta-database for further extensive analyses;


• Great paper on models

• But role of soil fauna in the process totally overlooked, once again!

• Soil ecology researchers reacted to this (ICSZ Coimbra 2012)


????

Juliane Filser

“The Architect Forgot the Engineers ICSZ„

Coimbra, August 2012

Existing Models on SOM Turnover

PF

C

HS

SOM

Turnover

Molecular structure

Physical

heterogeneity

Humic

substances

Fire-

derived C

Soil depth

Roots

Permafrost

Main elements

State-of-the-art (Schmidt et al. 2011)

Soil fauna totally

ignored!


Soil micro-

organisms

Let us reconcile… • In the end of the article, the authors state:

Join forces and connect research communities “(…) There are those studying litter decomposition, with a focus on the biotic breakdown of plant inputs (…)„

So, what can WE do about it?

Interestingly, none of the 46 papers citing this

article (by August 8, 2012) focused on soil fauna!


Juliane Filser

“The Architect Forgot the Engineers ICSZ„

Coimbra, August 2012

Rationale (I)


• Soil ecologists: two rather different ways to explain processes: “food-web vs. self-organization”.

• Soil animals (biodiversity and species traits) play a crucial role in SOM turnover (although not sufficiently acknowledged).

• Without them, models seem to be less predictive*;

• Interdisciplinary approaches needed to better understand and model SOM (in agreement with Schmidt et al. paper)

• Limited communication (linkages) between biogeochemistry, microbiology and soil ecology;

• Lack of [awareness of] data on soil animals (both field and lab experiments),

* We argue that explicit consideration of soil animals is essential to make realistic modelling predictions and detect expected non-linear responses to Global Change

Rationale (II)


Various forms & age

CO2

Litter

Soil

Organic carbon

Shoots

Roots

Soil biota

Exudates

Respiration

Photosynthesis

C-in C-out

leaching

C- sequestration

C in C out >

erosion

De Deyn (2013)

- Biological transformation of SOM

- Stabilization of SOM in organo-mineral complexes (Δ turnover rates)

- Biogeochemical SOM models oversimplify soil community (or reduced to microbial component)

- Soil fauna role in SOM dynamics (soil ecologists) mainly based in food-webs; Who eats who, who feeds upon who?

- The situation becomes perpetual.

Understanding and modelling SOM dynamics is essential for managing soil fertility, agricultural productivity and soil ecosystem services like nutrient cycling and C sequestration.

Contribution of soil fauna to 8 aspects considered


Molecular structure

HS Humic substances

Role of faunal casts and excreta in dynamics/turnover of humic substances and biogenic elements;

C Fire-derived C Fate and re-distribution;

Roots Effects of animal burrows, root herbivores, rhizosphere grazers;

Physical

heterogeneity

Casts, mounds and burrows produced by soil ecosystem engineers (including soil fauna and roots) affecting vertical and horizontal organic matter patterns in soil;

Soil depth Distribution of old and young C through fauna (accessibility vs. recalcitrance of SOM to microbial attack and C sequestration);

PF Permafrost Short- and long-term invasion effects by soil fauna (e.g. enchytraeids and earthworms);

Soil micro-organisms Gut passage, modification of environmental conditions, and distribution of microbial propagules (promotion of coexistence of different microbial species)

Juliane Filser, Gerlinde De Deyn, Jack H. Faber, Lijbert Brussaard, Diana H. Wall, Alexei V. Uvarov, Matty P. Berg, Patrick Lavelle, Michel Loreau, Alexei V. Tiunov, Jan

Frouz, Pascal Querner, Herman Eijsackers, Juan J. Jiménez. SOIL (accepted).


(…)

State of the art

Juliane Filser, Gerlinde De Deyn, Jack H. Faber, Lijbert Brussaard, Diana H. Wall, Alexei V.

Uvarov, Matty P. Berg, Patrick Lavelle, Michel Loreau, Alexei V. Tiunov, Jan Frouz, Pascal

Querner, Herman Eijsackers, Juan J. Jiménez. SOIL (OA journal, accepted).


A few challenges ……

Literature Review and Gap Analysis • How animal groups should be represented • Geographical differences, site-specific effects • Data

– Laboratory vs. field (e.g. Lubbers et al. 2013) – Scale

• How to cope with – different methods, foci? – the huge complexity?

• How much detail is needed?

Impact of one lab species on GHG release



Challenges (cont’d)

I. Biodiversity in soils II. Soil fauna – SOM Interactions III. Spatial and temporal patterns

(Bardgett and van der Putten, 2014)

Life in the soil


We still do not know how many soil invertebrate species exist worldwide, and there is

almost no soil where we are able to identify or even quantify all the resident invertebrate

species

www.prairieecosystems.pbworks.

com

Main taxonomic groups of soil organisms on body size basis

(Decaëns, Lavelle & Jiménez 2008, after Swift et al. 1979)

1024

m m

1 2 4 8 16 32 64 128 256 512 1024 1 2 4 8 16 32 64 128 256 512

mm

Bacteria

Fungi

Nematoda

Protozoa

Acari

Collembola

Diplura

Symphyla

Enchytraeidae

Isoptera / Formicoidea

Diptera

Isopoda

Myriapoda

Arachnida

Coleoptera

Mollusca

Oligochaeta

Vertebrata

Microflora / microfauna Mesofauna Macro - and megafauna

100 m m 2 mm 20 mm

Body size

Life in the soil


MACROFAUNA (> 2mm): 17 KEY taxa

Taxa Biomass (%)

Density (%)

Oligochaeta opisthopora1 74.43 9.85

Coleoptera (larvae and adults)2

6.89 3.32

Isoptera3 6.30 49.15

Myriapoda (Diplopoda4 and Chilopoda5)

5.23 3.27

Formicidae6 2.65 29.28

Gasteropoda7 1.30 0.49

Aranaea8 1.00 1.17

Blattoidea9 0.64 0.19

Orthoptera10 0.38 0.08

Dermaptera11 0.27 0.51

Isopoda12 0.26 0.96

Hemiptera13 0.22 0.13

Lepidoptera (larvas)14 0.21 0.20

Diptera (larvas y adultos)15

0.17 0.39

Residues (Insects16 and non-insects17)

1.26 1.00

IBOY-Macrofauna report, 2000 http://www.bondy.ird.fr/lest/iboy/workshop-report.pdf)

>95%


(Decaëns et al. 2008)

Lavelle et al., unpubl.

Life in the soil


Models on soil fauna and SOM interactions?


direct pathway to plants indirect pathway to plants

Trophic based below- and aboveground interactions

root feeding fauna

mycorrhiza

pathogens

belowground

aboveground

(Wardle et al. 2004; Osler and Sommerkorn 2007)

food web

- Significant effects on nutrient pools and fluxes - Integration of biogeochemical and soil food web

models - Protists and bacteria-feeding nematodes important

for N mineralization - Enchytraeids and fungal-feeding micro-arthropods

important for DOM production


Focus: Element fluxes

Non-trophic interactions: Soil ecosystem engineering

Ecosystem engineers (sensu Jones et al. 1994)

© P. Lavelle

© J.J. Jiménez

(Decaëns et al. 2008)


Focus: Habitat structure / physical conditions

OM

Aggregates

Which conceptual model to be proposed?

De Ruiter et al. (1994)

NOT a single one, accepted by all of us CAN WE PROPOSE A SIMPLE AND OPERATIONAL MODEL

FOODWEBS SELF-ORGANIZED SOIL

Short sighted Allows precise modeling Ignores soil (structure)

Long sighted No modeling done so far

Lavelle et al., 2006

M i cr o o r ga n i sm s

M i cr o f o o dw e b

F u n cti o n a l do m a i n

S o i l pr o f i l e

B i o ge n i c str u ctu r e s

M e so - a ggr e ga te s

M i cr o bi a l a ggr e ga te s

M o sa i c o f f u n cti o n a l do m a i n s

4

5

3

1

S o i l ca te n a

L a n dsca pe

2

A theoretical attempt by Sanders et al. (2014)

A huge quantity of empirical data

The impact of soil fauna on the dynamics of dead organic

matter has been studied for ages

Many many mechanisms are involved (comminution, bioturbation, …. )

Several spatial scales are involved (processes may vary)

Several temporal scales are involved

Yes but …

Many organisms are involved

Many compartments of organic matter are involved

Challenges on modelling SOM – soil fauna

(Barot et al., in prep.)


Diffuse reflectance (Stenberg et al. 2010)

NIR spectral readings

A. rosea

1 day-old

L. friendi

1 day-old

P. pyrenaicus

1 day-old

Spectral data of recently deposited casts for 3 earthworm species (reference library data)

PLS-DA model

RMSECV*: 0.437

*Root mean square error of cross validation = prediction ability calculated by the model based on the NIR spectral data of the reference library (accuracy and robustness)

(Jiménez et al., in prep.)

Role of soil engineers in C models?

Example with earthworms

Litter fragmentation and

distribution within

the soil profile

SOM

Digestion of a fraction

of the ingested SOM Stimulation

of some

micro-organisms

CO2 CO2

Digestion of a fraction

of the ingested

micro-organisms

Protection of SOM

within soil aggregates ?

Positive

effect

on plant

growth

Feedbacks on

organic matter

inputs



Towards a generic model

The model must incorporate the most important processes

controlled by soil fauna

The model relatively simple to allow mathematical analyses

The model to be used for any group of soil fauna or combination

of soil fauna groups (guilds, functional groups)

Litter fragmentation

Bioturbation

Consumption of SOM and stimulation of microorganisms

Protection of SOM in casts / pellets



Towards a generic model

Litter fragmentation

(Barot et al. in prep.)

Ab

ove

gro

un

d

Be

low

gro

un

d


Preliminary results

111

f btot

f f b S

S Rm m

Total stock of C without fauna

Total stock of C with fauna achieving all functions

1

1 1

1 1

1

1

1

1

1

1

en

f an b ep an f f

tot

ep an f f an b en oc

an b ep a

ep ep an an

yc

yc

e

ep an

ep e

n

n fp an a f

S en

e

n

n oc

m E E E

a aS R

E E m E

f f

f f

f

E m w

E E E

a wam E

E m

b

b c

m

b

wc

f

mc

Simple model (Barot et al. in prep.)


(Deckym et al. in prep.)

A basic submodel for soil biodiversity into existing ecosystem and soil models + implement example soil model (ie adaptable to most ecosystems) of soil C and N (i.e. C storage and fertility (N availability) as main outputs).

Engineers: influence beyond foodweb, others more through foodweb


Next steps

Mathematical analysis of the results

E.g.

Derivatives relatively to biomasses of soil fauna

Mathematical conditions for soil fauna to increase the total

C stock

Parameterization, probably using “mean standard parameters”

Inclusion of new mechanisms

Feedbacks between soil fauna dynamics and SOM dynamics

Explicit inclusion of microorganisms (bacteria and fungi)

Possibility of concentration of organic matter within casts / pellets

(Barot et al. in prep.)

• Soil fauna is impacted by global change which will impact

organic matter dynamics

Challenges (III)


(Decaëns et al. 2009; Jiménez et al. 2012)

Number of inds. found in each variable (range)

C0-5

0-25 25-50 >50 N

Glo 9 819 18 846

Aym 0 630 18 648

And 18 288 0 306

Epi 0 477 477 954

Anr 0 9 0 9

Ocn 36 2313 54 2403

Mrt 9 972 45 1026

C5-10

0-15 15-30 30-45 >45 >60

0 819 27 0 0

0 585 18 45 0

9 297 0 0 0

477 477 0 0 0

0 9 0 0 0

36 2331 18 18 0

9 963 45 9 0

BD

0.7-1.0 1.0-1.2 1.2-1.4 >1.4

0 225 549 72

0 315 333 0

0 45 216 45

513 27 414 0

0 9 0 0

18 513 1827 45

9 225 783 9

PR2.5

0-1 1-3 3-5 5-7 >7

315 18 9 261 243

495 0 18 108 27

72 72 18 90 54

180 9 36 720 9

9 0 0 0 0

936 153 81 783 450

594 36 9 288 99

Trophic (nutrients) Space (physical)

Spp

./

asse

mb

lage

s

How species and assemblages relate with soil abiotic

factors at multiple scales?

And how do they affect their surrounding environment?

Use of trophic and space resources

(Jiménez et al. 2014)

Spatial distribution of resources (fine and coarse roots)

(m sample-1) (g dry wt sample-1)

Cross-correlogram for roots and soil nutrient- and physical-related variables:

FiRL with SOC and P

CoRL with N, SOC and P

FiRW with SOC and P and litter

CoRW with SOC, P

FiRL with Aggregates, Cond and Moisture

CoRL with Aggregates and Cond

FiRW with Aggregates and BD

CoRW with Aggregates


Glossodrilus

Aymara Andiodrilus

Andiorrhinus

Ocnerodrilidae Martiodrilus

Litter

N0-5

N5-10

P0-5

P5-10

C0-5

C5-10

C:N 0-5

C:N5-10

FiRL

CoRL

FiRW

CoRW

PR5-20

0.053-

0.125

0.125-0.25 0.25-0.5

0.5-1

1-2

2-5

5-10

>10Agg

Bulk

Density

Soil compaction

Cond

Hum(%)

-0.43

0.36 -0.36 0.3

F I (64.1%)

F II (1

7.7

%)

p<0.0001

MedAgg

SmallAgg

LargeAgg

VLargeAgg

VSmallAgg Root Length

Root Biomass

Montecarlo rand.

Co-Inertia analysis


Correlogram with the factorial coordinates of axis 1 (square) and

axis 2 (triangle) extracted in the CoIA M

ora

n's

I

2 7 11 16 20 25 30 34 39 43 48 52

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

Lag distance (m)

Axis 2

Axis 1

Ew effect

Nutrient resources

Species 1


En

do

gei

cs

ass

emb

lage

Eart

hw

orm

com

mu

nit

y

Intersampling

distance = 10 m

Ep

igeic +

an

ecic

assem

bla

ge

An

dio

dri

lus,

Aym

ara

an

d n

ew

gen

us

1 a

ssem

bla

ge

Martio

drilu

s,

Glo

ssodrilu

sa

nd

new

gen

us 2

assem

bla

ge


Variation partitioning in a spatial context

10 20 30 40 50 60

0.0

02

0.0

06

0

.01

0

0.0

14

Distance (m)

Sem

ivar

ian

ce

PCNM1

PCNM3

PCNM5

PCNM8

PCNM12

PCNM33

PCNM51

Principal Component of Neighbouring Matrices (Dray et al. 2006) and

Variation partitioning (Borcard et al. 1992; Peres-Neto et al. 2006)

Multi-scale spatial relationships


SOM – soil fauna interaction

must also be integrated into a

holistic view of ecosystem

functioning



Thanks for your attention!

Enjoy this training school!

http://www.cost.eu/COST_Actions/essem/Actions/ES1406


© F. Fillat

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why a cost action on soil fauna and som dynamics? current ... · “why a cost action on soil fauna...

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