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Soil arthropods indicate the range of plant facilitation on the soil of Mediterranean drylands

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Abstract

Drylands are ecosystems, where lack of rains imposes harsh conditions for the survival of organisms. These ecosystems are also susceptible to degradation and desertification. Their conservation depends on the understanding of the ecological functioning of vegetation and soil. In drylands, the vegetation is spatially structured as a mosaic of patches (vegetation) and interpatches (bare soil). This structure is a consequence of plant-plant interactions (facilitation and competition). Empirical data and modeling approaches reinforce the role of ecological facilitation for the maintenance of all organisms in drylands. However, the true range of facilitation is still poorly known. Here, we explored data of meso- and microarthropods living in soil, as bioindicators, to infer the range of facilitation provided by plants to soil. As dependent variables, we regard data of abundances and species richness collected in random patches (independent samples) and bare soil places. Data from patch size and distances between bare soil and patches were arranged in a single chute. Thus, one may consider a one-dimensional coordinate system, where zero is the border; negative coordinates are distances between bare soil and the border, while positive coordinates represent patch sizes. Discrete portions of this system are taken to calculate averages and variances of abundance and species richness. With these statistics, we investigate how soil communities vary across the patch border. Techniques of data transformation and signal analysis allowed us to reduce the data noise, reveal a continuous mean behavior, and fit a logistic function. Our findings indicate that soil communities change suddenly from simple patterns to numerous and diverse communities in bare soil regions. This abrupt change of fauna quantities, around 0.35 and 0.5 m outside the patch border, means that the facilitation of vegetation on soil goes beyond the patch border. However, the abundance and richness of soil communities in bare soil are small in comparison to overall quantities of soil arthropods. Consequently, variations in quantities of arthropods on bare soil do not necessarily reflect the main role of these soil arthropods for soil functions, which mainly occurs under the patches. Also, we found a minimum patch size (radius ≈ 0.5 m) able to maintain high diverse communities in soil. Accordingly, our results reveal information that can be interpreted in terms of soil amelioration, and, therefore, it indicates the range of plant facilitation, and the minimum patch size able to produce soil amelioration. These findings provide objective values that can be employed to update the general understanding of the ecological dynamics of drylands,as well as to better plan restoration and conservation actions.

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Notes

  1. New data entries were necessary because the registers explored in Meloni et al. (2020b) contained only few samples of large patches (radius R > 1.0 m), which could limit our analyses. Hence, the data set was complemented with 10 additional samples, all of them representing large patches from the same region.

  2. The distribution of A and ρ inside patches are assumed to be negligible.

  3. We tested if samples showing zeros could change our results. Although both results (with vs without zeros) are very similar, an important problem arises if zeros are maintained. Because we employ moving averages, some values assume values between 0 and 1, and our analyses consider data in the logarithmic scale. Consequently, the inclusion of zeros produce a set that (a) overestimates differences for small values of abundance and richness, and (b) produces negative values. Both aspects hamper the modeling and the interpretation. We have tried to avoid (a) and (b) by adding a constant c ≫ 1 to each register, as \(N=\log (A+c)\) and \(S=\log (\rho +c)\). Despite this procedure enabled us to carry out our analysis, the additional mathematical steps also hampered the interpretation of results to the broad audience. Bearing all aspects in mind, we opted for removing the zeros.

  4. Because this approach is not widely known, we advise interested readers to find out more in the specialized literature. We indicate the Refs. Stanley (1971) and Papon et al. (2007), and Hillert (2007) as good starting points.

  5. The employment of moving average prevents the calculation of true confidence intervals from the statistics.

  6. Exceptions may occurs, e.g., when aggressive species (invasive or native) is very abundant due to a degraded condition that favors its fitness.

  7. The log transformation makes also multiplicative terms become aditive, as \(\log (a\times b\times c\times ...) = \log (a)+\log (b)+\log (c)+\log (...)\).

Abbreviations

A :

abundance; \(N = \ln (A)\)

ρ :

species richness; \(S = \ln (\rho )\)

R :

patch radius (m)

\(\bar {D}\):\(\bar {D}\) :

average distance between interpatch middle region and its four-nearest patches (m)

x :

continuous 1-d representation of R and \(\bar {D}\) (m)

Δx :

regular discrete intervals of x

\(\bar {\mu }_{N}\) and \(\bar {\mu }_{S}\) :

average values of N and S in a given interval Δx

\({\sigma ^{2}_{N}}\) and \({\sigma ^{2}_{S}}\) :

variance of N and S in a given interval Δx

Φ(x):

generic representation of \(\bar {\mu }_{A}(x)=\exp [\bar {\mu }_{N}(x)]\) or \(\bar {\mu }_{\rho }(x)=\exp [\bar {\mu }_{S}(x)]\)

\(f_{1\rightarrow 3}(x)\) and \(g_{1\rightarrow 3}(x)\) :

logistic functions fitted for data

\(f^{\prime }_{1\rightarrow 3}(x)\) and \(g^{\prime }_{1\rightarrow 3}(x)\) :

second-order derivative of \(f_{1\rightarrow 3}(x)\) and \(g_{1\rightarrow 3}(x)\)

x ∗ :

inflection point of \(f_{1\rightarrow 3}(x)\) or \(g_{1\rightarrow 3}(x)\)

\(x_{a}^{*}\) and \(x_{b}^{*}\) :

regions of interest of \(f_{1\rightarrow 3}(x)\) and \(g_{1\rightarrow 3}(x)\)

x (o) :

inflection point for \(\exp [f_{1\rightarrow 3}(x)]\) and \(\exp [ g_{1\rightarrow 3}(x)]\)

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Acknowledgments

F.M. and A.S. Martinez thank to São Paulo Research Foundation (FAPESP, grant 2013/06196-4) and to Coordination of Superior Level Staff Improvement —Brazil (CAPES), Finance Code 001. Thank to the team of Instituto Nacional de Ciência e Tecnologia de Sistemas Complexos (INCT-SC), Brazil, and to the team of the Dep. of Physics, FFCLRP, University of São Paulo for the administrative support. Special thanks to Susana Bautista and to Department of Ecology, University of Alicante, Spain, for providing hosting and facilities during the early stages of the research; and to Pablo Pacheco for his comments.

Funding

This research was funded by FAPESP 13/06196-4 and CAPES 88887.363718/2019-00, Finance Code 001.” https://bv.fapesp.br/pt/pesquisador/668540/ and CNPq 309851/2018-1.

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Authors and Affiliations

  1. Department of Physics, FFCLRP, University of São Paulo, Av Bandeirantes - 3900, Ribeirão Preto, Brazil

    Fernando Meloni & Alexandre Souto Martinez

  2. Instituto Nacional de Ciência e Tecnologia de Sistemas Complexos (INCT-SC), Dr. Xavier Sigaud - 150, Rio de Janeiro, Brazil

    Fernando Meloni & Alexandre Souto Martinez

Authors
  1. Fernando Meloni
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  2. Alexandre Souto Martinez
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Correspondence to Fernando Meloni.

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Appendix: Figure 6

Appendix: Figure 6

Figure 6 depicts results obtained after the inclusion of data obtained by the employment of moving averages to the raw data.

Fig. 6
figure 6

Abundances (A) and species density (ρ) plotted against x as raw data, after the inclusion of pseudo-samples produced by moving averages. Continuous red lines are logistic functions and represent the average behavior of data

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Meloni, F., Martinez, A.S. Soil arthropods indicate the range of plant facilitation on the soil of Mediterranean drylands. Theor Ecol 14, 303–319 (2021). https://doi.org/10.1007/s12080-020-00498-z

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