Coupling spatial variations in earthworm density and soil structure, a modelling approach

1. Coupling spatial variations in earthworm density and soil structure, a modelling approach Sébastien BarotJean-Pierre RossiPatrick Lavelle UMR 137Laboratoire d’Écologie des Sols TropicauxIRD

2. Soil fauna tends to have heterogeneous spatial distributions A Earthworms Large patches with higher densities B (A) Density of the earthworm Chuniodrilus zielae and (B) Millsonia anomala (juvenile) in the savanna of Lamto (Rossi & Lavelle, 1998)

3. What are the causes of soil fauna distribution? Preexisting soil heterogeneity?  Heterogeneous distribution of plant litter and roots  Heterogeneity of soil structure (granulometry, soil aggregate size) Heterogeneity in chemical properties  Content in organic matter and mineral nutrients

4. Yet, data analyses show that  Soil heterogeneity is correlated with soil fauna distribution But the greatest part of the heterogeneity in soil fauna density is not explained by soil heterogeneity (Decaëns 2001, Whalen 2003)  Can the own dynamics of soil fauna lead to complex spatial patterns? Mobility? Mortality? Spatially dependent factors of auto-regulations? This hypothesis was tested using a spatially explicit simulation model

5. Description of the model 1: the biology  In the savannas of Lamto (Côte d’Ivoire), the earthworm Millsonia anomala compacts the soil by only ingesting small aggregates and by producing large size casts (Ø>5 mm ) (Blanchard 1997) Large aggregates are broken into smaller ones by weathering, roots, and earthworms of theeudrilidea family, which are able to dig into large aggregates, and produce small casts (5 mm>Ø) Experiments suggest that mortality increases when soil structure becomes too unfavorable: not enough small aggregates Hypothesis of auto-regulation by the availability of small aggregates

6. Description of the model parameters  A cellular automaton (50 X 50 cells), each cell (1 m2) defined by M. anomala density (nT), and the percentage of soil mass in small aggregates (sp1)  Annual rate of production of coarse aggregates by an earthworm (C), rate of destruction of these aggregates for a mean eudrilidea density (D)  Fecundity (b), minimum mortality (dmin),sensitivity of mortality to % of thin aggregates (ed)  Dispersal follows a normal law

7. Analysis of the model  All parameters but the mobility and the sensitivity of mortality to soil aggregationcan be assessed using field studies  Comparison with observed patterns Variance and mean of the density Spatial distribution Spatial autocorrelation Semivariance Distance

8. First results 1: fecundity = 2, only mortality depends on soil structure, mortalitythen dispersal

9. a C0+C Semivariance C0 Distance First results 2: fecundity = 2, only mortality depends on soil structure, mortality then dispersal Spherical model

10. How do we get some spatial structure?  Increased fecundity  Dispersal before mortality Dependence of mortality and fecundity on soil aggregation is sufficient to get long range spatial structures Dependence of dispersal on soil aggregation is not sufficient  Very complex spatial patterns arise for certain combinations of parameters values

11. An example: fecundity = 4, only mortality depends on soil structure, dispersal then mortality 50 m Semivariance 0 15 30 0 15 30 Distance (m)

12. Discussion 1 : interpretation of the results The own dynamics of earthworms can lead to long range spatial structures This arises when sensitivity of fecundity or mortality to soil aggregation is high, and when mobility is very low This suggests that it is really the case In these cases the simulated mean and standard deviations of the density are compatible with values observed in the field

13. Discussion 2 : limitations and further analyses  No size structure, no temporal variation in parameters although they probably depend on climatic variations  The dynamic of decompacting earthworms is not taken into account Soil organic matter is not taken into accountLink earthworm demographic parameters to ecosystem properties such as the mineralization rate Experimental work  To measure the sensitivity of parameters to soil aggregation  To measure mobility