A null-model analysis of the spatio-temporal distribution of earthworm species assemblages in Colombian grasslands
Summary (5 min read)
- The study of the spatial pattern of soil biota and the factors by which they are governed is a key research area in understanding the structure and function of soil biodiversity and their relationships with above-ground processes (Ettema & Wardle 2002, Ettema et al. 2000).
- To date however, soil communities have been minimally considered in spatial ecology when compared with aboveground biota (Ettema & Wardle 2002).
- Earthworm spatial patterns are however likely to contribute to existing heterogeneity in soil resources 1 Corresponding author.
416 THIBAUD DECAËNS, JUAN JOSÉ JIMÉNEZ AND JEAN-PIERRE ROSSI
- Species responses to the heterogeneity in plant cover and soil properties (Margerie et al. 2001, Phillipson et al. 1976, Poier & Richter 1992), intrinsic population processes such as reproduction rates and limited dispersal (Barot et al.
- Classic examples of the latter include limitation of similarity in body size or in multi-trait morphology (Hutchinson 1959, MacArthur & Levins 1967, Weiher & Keddy 1995, Weiher et al. 1998).
- Recently, null model analysis has emerged as an efficient tool to identify nonrandom community patterns (Gotelli 2001, Gotelli & Graves 1996).
- A data set was compiled from two studies carried out at the CIAT-CORPOICA Carimagua Research Station, in the phytogeographic unit of the well-drained isohyperthermic savannas of eastern Colombia (4◦37′N, 71◦19′W, 175 m asl).
- Study plots were located in an upland area with a well-drained silty clay Oxisol (Tropeptic Haplustox Isohyperthermic; USDA classification), characterized by its acidity (pH[H2O] = 4.5), a high Al saturation (>80%) and low values of exchangeable cations.
- All the study plots were located in the same area of the Research Station, with no more than 100 m between each other.
- Nees, Panicum sp., Trachypogon sp. and Imperata brasiliensis Trin. Pasture 1 was a 1 ha and 18-y-old plot of Urochloa decumbens R.D. Webster and Pueraria phaseoloides Benth.
- In each plot, samples were taken on a regular grid of evenly spaced points.
- As the characteristics of samples varied significantly among plots, the authors used non-parametric regression (using Ecosim software, Acquired Intelligence Inc. & KeseyBear, http://garyentsminger.com/ecosim.htm) to verify that differences in observed patterns were not a byproduct of different sampling procedures.
- Two 20 × 20 × 20-cm soil cores were sampled 1 m distance from the monolith; the soil was then washed and sieved to collect small species that were not efficiently collected by hand sorting (Jiménez et al. 2006b).
- It was used for each plot to identify the species assemblages that characterized similar patches at different dates, to which the authors refer herein as the ‘patch-level assemblages’.
- The maps of the coordinates of the sampling points on the first compromise axis thus described the spatio-temporal distribution of these patchlevel assemblages.
Size distribution analysis
- The authors tested if identified assemblages presented patterns that limit biometric similarity between co-existing species for the three morphometric traits that were used in the niche overlap analysis.
- For each trait, the authors calculated: (1) the minimum segment length (MSL), which is the smallest size difference found in all available pairs of species; (2) the variance in segment length that measures the overall tendency for the trait values to be evenly spaced.
- Observed values were calculated for all assemblages that comprised more than two species, and were compared with those obtained for 10 000 random assemblages.
- In a competitively structured community or assemblage, MSL and VarSL should be higher and lower than EBC, respectively (Gotelli & Ellison 2002).
- Calculations and tests were done with the ‘Size Overlap’ module of Ecosim.
- For each index (Pianka’s and Czechanowski Oik, MSL, VarSL), the authors calculated the standardised effect size (SES): SE S = (Iobs − Isi m) Ssi m where Isim is the mean index of the simulated assemblages, Ssim is the standard deviation, and Iobs is the observed index (Gotelli & Graves 1996).
- For each type of assemblage (patch-level or plot-level) and each index, the authors further calculated the average values of the observed and simulated indices, and the average corresponding SES.
- Each test involved 10 000 iterations in which the data were reshuffled among the categories to determine how much variation was expected among the means.
- The null hypothesis was that the observed variation among the means of the groups was no greater than EBC.
- Calculations were performed using the ‘Anova’ module of Ecosim.
Earthworm assemblage composition
- A total of six species, all still undescribed and all native from the study region, was identified in the six sampled plots (Jiménez 1999).
- Apart from Andiorrhinus sp., which occurred only in Pasture 1 and Savanna 1, all species were present in all the plots (Tables 1 and 2).
- Detailed studies of species assemblage composition in the different study plots have been published previously in Decaëns & Jiménez (2002) and Jiménez et al. (1998b).
- The highest densities were recorded for Glossodrilus sp. and, in the pastures, Ocnerodrilidae sp.
420 THIBAUD DECAËNS, JUAN JOSÉ JIMÉNEZ AND JEAN-PIERRE ROSSI
- Plot, the highest contributions to biomass were recorded for Glossodrilus sp., Andiodrilus sp. or Martiodrilus sp., the latter being dominant in the three pastures.
- The percentages of the total inertia explained by the first axes of the PTA’s interstructure and compromise analyses are presented in Table 1.
- Values were always lower than 50%, indicating relatively little inertia in the data.
- Interstructure analyses described the patterns of population distribution that were stable across time.
- In each sampled plot, earthworm assemblages thus presented non-random and statistically significant spatio-temporal structure consisting in a juxtaposition of patches characterized by dominant ‘patch-level assemblages’.
Niche overlap patterns
- Both the Pianka and Czechanowski indices provided very similar results and the authors thus decided to present only those obtained with the former.
- Temporal niche overlap was significantly higher than EBC for the majority of patch- and plot-level assemblages (Table 3) and average observed overlaps were unusually high (P = 0.050 and P = 0.002, respectively).
- Average SES was significantly higher than 0 at both scales, but was significantly lower in patch- as compared with plot-level assemblages (Table 3).
422 THIBAUD DECAËNS, JUAN JOSÉ JIMÉNEZ AND JEAN-PIERRE ROSSI
- At both patch- and plot-levels, vertical niche overlap was almost always significantly higher than EBC, average observed Pianka’s.
- Average SES was not significantly different between patch- and plot-level assemblages.
- Biometric niche overlap was lower than EBC in a majority of patch assemblages, but the observed and EBC values were not significantly different, and the SES was not significantly lower than 0 (Table 3).
- Patterns were mainly random for plot-level assemblages and no significant difference was found when comparing average SES calculated for patch- and plot-level assemblages.
Size distribution patterns
- Patch-level assemblages showed a consistent trend toward over and even spacing of body length (Table 4).
- Conversely, plot-level assemblages were characterized by random body length ratio patterns and, when compared with patch-level assemblages, lower average value of the SES calculated for MSL.
- The VarSL was lower than EBC in the majority of patch and plot assemblages (with two individually significant values for patch-level assemblages), showed an unusually small average (P = 0.011 for both patchand plot-level assemblages), and a SES significantly lower than 0.
- Body weight tended to be over spaced in both patchand plot-level assemblages (Table 4): although average observed values were not significantly higher than simulated ones, the corresponding SESs were significantly higher than 0.
- In patchlevel assemblages MSL was higher than EBC in six of seven cases (with significant individual tests in one of them), average MSL was significantly higher than EBC (P = 0.050) and SES was significantly higher than 0.
- The spatial organization of earthworm assemblages in alternating patches characterized by specific species Earthworm assemblages in Colombian grasslands 423 assemblages has been found in both tropical and temperate soils (Margerie et al.
- This indicates a high residual variability from the analysis, which may result from different sources including species vagility (Decaëns & Rossi 2001), sampling error (Jiménez et al. 2006b) and/or small-scale variability (below the minimum inter-sample distance) in species distribution (Rossi & Nuutinen 2004).
- The reason why patch-level assemblages differed so much in composition among plots of the same habitat type is an interesting question that will require additional information to be elucidated.
- The relationship between species biometric features and life history strategies, and in particular resource uses, is also central in most eco-morphological classifications that are classically recognized in earthworm studies (Bouché 1977, Lavelle 1997).
424 THIBAUD DECAËNS, JUAN JOSÉ JIMÉNEZ AND JEAN-PIERRE ROSSI
- Competition may however generate different patterns according to the spatial scale considered.
- The authors found that body weight was significantly overdispersed and constant among species at both the plot and patch scales, while body length shows a similar pattern at the patch scale only.
- Alternatively, species body length was reported to reflect the size of the ingested soil particles, although no general pathway for this relationship has been pointed to date (Blanchart et al. 1997, Lothe authors & Butt 2003).
- Dalby et al. (1998) found that competition among species may result from direct cocoon consumption.
- Spatial and temporal niche partitioning in grassland ants.
- Patterns of diversity and habitat relationships in terrestrial mollusc communities of the Pukeamaru Ecological District, northeastern New Zealand.
- Self-organization in a simple consumer-resource system, the example of earthworms.
BLANCHART, E., LAVELLE, P., BRAUDEAU, E., LE BISSONNAIS, Y.
- The feeding ecology of earthworms – a review.
- Ecological and community-wide character displacement: the next generation.
HERNÁNDEZ, P., FERNÁNDEZ, R., NOVO, M., TRIGO, D. & DÍAZ-COSÍN,
- Relating niche and spatial overlap at the community level.
- Doctoral Thesis, Universidad Complutense de Madrid, Madrid.
- Vertical distribution of earthworms in grassland soils of the Colombian Llanos.
JIMÉNEZ, J. J., BROWN, G. G., DECAËNS, T., FEIJOO, A. & LAVELLE, P.
- Differences in the timing of diapause and patterns of aestivation in tropical earthworms.
- Two goals for predictive community ecology, also known as Assembly and response rules.
- Three mode principal component analysis: “analyse triadique complète”.
- Diversity of soil fauna and ecosystem function.
LAVELLE, P., DECAËNS, T., AUBERT, M., BAROT, S., BLOUIN, M.,
- Influence of food particle size on inter- and intra-specific interactions of Allolobophora chlorotica and Lumbricus terrestris.
- The limiting similarity, convergence, and divergence of coexisting species.
MARCHINKO, K. B., NISHIZAKI, M. T. & BURNS, K. C.
- Community-wide character displacement in barnacles: a new perspective for past observations.
- Spatial distribution of earthworm species assemblages in a chalky slope of the Seine Valley (Normandy, France).
- Comptes Rendus de l’Académie des Sciences de Paris.
PHILLIPSON, J., ABEL, A., STEEL, J. & WOODELL, S. R. J. 1976.
- Earthworms and the factors governing their distribution in an English beechwood.
- Intraguild predation and competition among desert scorpions.
- The spatiotemporal pattern of a tropical earthworm species assemblage and its relationship with soil structure.
THIOULOUSE, J., CHESSEL, D., DOLÉDEC, S. & OLIVIER, J. M. 1997.
- A multivariate analysis and graphical display software, also known as ADE-4.
- Assembly rules, null models, and trait dispersions: new questions from old patterns.
- Community assembly rules, morphological dispersion, and the coexistence of plant species.
- Linking spatio-temporal dynamics of earthworm populations to nutrient cycling in temperate agricultural and forest ecosystems.
- Evidence for competition from field observations, using a patch model, also known as Limitation to species coexistence.
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Cites background from "A null-model analysis of the spatio..."
...The negative correlations that occur between the spatial distributions of soil ecosystem engineers of different species producing separate cast types have been often interpreted as a result of competition (Jimenez et al., 2001; Decaëns et al., 2009; Jimenez et al., 2012)....
"A null-model analysis of the spatio..." refers background in this paper
...Additionally, earthworms are ecosystem engineers (sensu Jones et al. 1994) able to physically modify their environment, thus altering resource availability for other species....
"A null-model analysis of the spatio..." refers background in this paper
...…to observe two types of non-random patterns: (1) within-patch niche overlap should be lower than EBC and lower than plot-scale overlap (MacArthur & Levins 1967, Weiher & Keddy 1995); (2) morphometric distance (size ratio) between species co-existing in a given patch should be higher and more…...
...Classic examples of the latter include limitation of similarity in body size or in multi-trait morphology (Hutchinson 1959, MacArthur & Levins 1967, Weiher & Keddy 1995, Weiher et al. 1998)....