European Journal of Soil Biology 117 (2023) 103514

Contents lists available at ScienceDirect

European Journal of Soil Biology

journal homepage: www.elsevier.com/locate/ejsobi

Original article

Edaphic and epigeic macrofauna responses to land use change in Brazil

Beatriz S. Vanolli a, *, Arthur P.A. Pereira b, André L.C. Franco c, Maurício R. Cherubin a
a
“Luiz de Queiroz” College of Agriculture, University of São Paulo, ESALQ/USP, 13418-900, Piracicaba, SP, Brazil
b
Federal University of Ceará, 60020-181, Fortaleza, CE, Brazil
c
Indiana University Bloomington, 47405, Bloomington, United States

A R T I C L E I N F O A B S T R A C T

Handling Editor: B. Griffiths The expansion of sugarcane (Saccharum spp.) over extensive pasture areas has been one of the primary land-use
change (LUC) scenarios in central-southern Brazil. However, LUC could negatively affect soil fauna along with
Keywords: the multiple functions and services associated with these organisms. Numerous groups of macroinvertebrates
Sugarcane inhabiting the soil surface (i.e., epigeic) or the soil profile (i.e., edaphic) are fundamental for litter fragmentation,
Soil management
soil structuring and stabilization, water infiltration, biogeochemical cycling. In this study, both the edaphic and
Soil health
epigeic macrofauna communities were surveyed simultaneously to assess responses induced by the expansion of
Soil functions
Biodiversity sugarcane cultivation over extensive pastures and to investigate whether the magnitude of such responses to LUC
TSBF differs according to the community niche (i.e., soil profile versus surface). We hypothesized that LUC to a semi-
perennial crop such as sugarcane would increase the density and diversity of the edaphic macrofauna, while the
epigeic community would be negatively affected by LUC due to drastic changes in surface litter. The studied
areas were two sites varying in soil texture (i.e., clay versus sandy soils) each including the following land uses: i)
native vegetation, ii) extensive pasture, iii) newly planted sugarcane crop (sugarcane); and iv) established
sugarcane (sugarcane ratoon). To evaluate edaphic macrofauna the TSBF methodology was adopted, while pitfall
traps were installed at the same sampling points to collected epigeic macrofauna. The evaluated community
attributes were density, Shannon diversity index, evenness index, richness of soil macrofauna taxa, as well as the
chemical and physical attributes of the soil. Linear mixed effects analysis showed that LUC affected the relative
abundance of edaphic (Land use p = 0.1191 r2marginal = 0.28, r2conditional = 0.33) and epigeic (Land use p = 0.0176;
r2marginal = 0.22, r2conditional = 0.32) macroinvertebrates. Both groups showed the greatest density of organisms
under native vegetation. Coleoptera and earthworms were associated with pasture areas, especially in clayey soil.
Response ratios of LUC effects on macrofauna showed stronger responses of the epigeic compared to edaphic
macrofauna, indicating a greater sensitivity of surface-dwelling organisms and their functions to disturbances
such as those caused by LUC. In general, the density and diversity of macrofauna exhibited a positive correlation
with soil organic matter, microbial carbon and nitrogen, macroporosity, and total porosity, and a negative
correlation with soil density (p < 0.05). Also, the conversion of pasture to sugarcane cultivation (planting) causes
significant macrofauna losses, particularly, in the clay soil. The cultivation of ratoon sugarcane led to a reduction
of the density, taxonomic richness, diversity, and evenness of macrofauna. Given the importance of epigeic
macroinvertebrates for litter fragmentation and decomposition, these results may indicate a rapid loss of key soil
functions related to decomposition and carbon and nutrient cycling following LUC.

1. Introduction Soil fauna is composed of invertebrates that inhabit or spend part or

their entire life cycle in the soil [8] and are essential to soil structure and
Soil is a major reservoir of the planet’s biodiversity [1] and con­ decomposition of organic materials [9]. An important group is macro­
tributes to several essential ecosystem functions [2]. Loss of biodiversity fauna, which are invertebrates with a diameter greater than 2 mm (e.g.,
can directly influence disease control, the quality of food produced, air Oligochaeta, Coleoptera, Hymenoptera, Araneae, Hemiptera, Isopoda,
and water quality [3,4] and, importantly, the biogeochemical cycling of Geophilomorpha, and other taxa) inhabiting the soil surface (i.e.,
soil carbon and nutrients [5–7]. epigeic fauna) or the soil profile (i.e., edaphic fauna) [10,11]. The

* Corresponding author.
E-mail address: beatrizvanolli@usp.br (B.S. Vanolli).

https://doi.org/10.1016/j.ejsobi.2023.103514
Received 13 April 2023; Received in revised form 3 June 2023; Accepted 5 June 2023
Available online 15 June 2023
1164-5563/© 2023 Published by Elsevier Masson SAS.
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

edaphic macrofauna is responsible for the initial fragmentation of the macrofauna communities; and (iv) that the physical and chemical
organic material, favoring microbial colonization and consequently the properties of the soil are related to macrofauna density/diversity,
cycling of carbon and nutrients, and bioturbation that regulates physical mainly the presence of macropores and macronutrients.
aspects of the soil, including the increase in soil porosity, water infil­
tration and distribution into the profile [5]. The epigeic macrofauna has 2. Material and methods
been characterized as effective bioindicators of soil health [8,12,13], as
they are very sensitive to soil use and management [14–16]. 2.1. Description of study sites
Farming practices and cropping systems, such as monoculture sug­
arcane cultivation, can affect the density and diversity of macrofauna The study areas are located in strategic and representative locations
[17–19]. Nevertheless, sugarcane is one of main crops cultivated in in central-south Brazil, the main sugarcane-production, located in the
Brazil, contributing to socio-economic development of the country and municipalities of i) Manduri, Sorocaba mesoregion, central-south of São
playing a strategic role for bioenergy production [20]. Brazil is the Paulo state (Lat.: 23◦ 00’S; Long.: 49◦ 19’W) with an average altitude of
world’s leading sugarcane producer, with approximately 8.3 million 709 m, and ii) Brotas, Piracicaba mesoregion, central São Paulo state
hectares planted and a production of 598.34 million tons in the (Lat.: 22◦ 17’S; Long.: 48◦ 07’W) with average age altitude of 677 m
2022/2023 harvest [21]. The country is the second largest producer of (Fig. 1). The climate of the Manduri region is classified as Cfa (Köppen
ethanol in the world (26.60 billion liters of ethanol in the 2022/2023 and Geiger classification) with an average rainfall of 1249 mm
harvest) [21] and the largest fleet of flex-fuel vehicles (~43.2 million) throughout the year and an average annual temperature of 19.8 ◦ C. The
[22]. An estimated 151 million hectares of Brazilian territory are pasture climate classification for Brotas is Cwa (Köppen and Geiger classifica­
areas used by the livestock sector [23]. Much of this pasture area is in tion) with an average annual rainfall of 1337 mm, mainly concentrated
some stage of degradation (~60%), in which the national average pro­ from October to March, and the average annual temperature is 20.0 ◦ C
ductivity reaches 22–34% of the potential productivity [24]. The [35]. In these locations, the rainy season is in the spring and summer
intensification of cultivated pastures would free up enough available (October–March), while the dry season is in the autumn and winter
areas to expand crops, including sugarcane [25], which would not (April–September). Soil texture is characterized throughout the text as
require the opening of new areas [26] and presumably minimize envi­ “clayey” (Manduri) and as “sandy” (Brotas). The sandy soil is classified
ronmental impacts on the soil [26–29]. as Arenosol [36] or Quartzipsamments [37] and the clayey Ferralsol
Responses of the edaphic and epigeic macrofauna to sugarcane [36] or Oxisol [37] (Table 1). A detailed chemical characterization of
expansion have been evaluated separately, with mostly negative effects the soil is provided in Tables 2 and 3.
on density, taxa richness, and other community attributes [18,30].
Epigean communities, which are invertebrates that live on the surface,
2.2. Sequence of land-use change
may be more sensitive to land use modifications than invertebrates that
live in the soil profile. These organisms are directly exposed to changes
A synchronous approach (space-for-time substitution approach) was
in the physical environment caused by land use modifications [31].
adopted with chronosequence of land-use types: i) Native Vegetation
Biotic and abiotic changes can affect the microclimate for macrofauna,
their food sources, and the quality of their habitat, ultimately affecting
their survival and reproduction [32].
Land-use changes (LUC) to semi-perennial crops such as sugarcane
may reduce surface vegetation cover, and then cause a decline in the
density and diversity of epigeal macrofauna, while the density and di­
versity of edaphic macrofauna may increase or remain relatively un­
changed. This is due to the fact that epigeal macrofauna depend on the
surface vegetation cover for food and shelter, while edaphic macrofauna
can survive in deeper soil layers [33]. Soil macrofauna decomposes the
recalcitrant straw, physically breaking it up and creating small pieces
that can be broken down by microorganisms through hydrolytic en­
zymes [34]. These organisms are essential for the effective decomposi­
tion of sugarcane straw deposited in the soil, because it is a highly
recalcitrant material, having a highly active faunal community in the
soil improves the mineralization rate of this crop [19]. Epigean macro­
fauna is, therefore more exposed to the effects of land use changes, such
as soil erosion and habitat loss, than edaphic macrofauna.
Here, we present a complete macrofauna assessment where edaphic
and epigeic communities were simultaneously surveyed across chro­
nosequences of LUC in the main sugarcane producing region of Brazil.
The goal was (i) to investigate LUC effects on soil macrofauna, especially
the effect of sugarcane cultivation on the density and diversity of soil
macrofauna compared to extensive pasture and native vegetation, and
(ii) whether the magnitude of macrofauna responses to LUC differs ac­
cording to the community’s niche (above and belowground) and (iii)
whether there are possible relationships between macrofauna density
and diversity with soil physical and chemical parameters. The hypoth­
eses were raised that (i) LUC to a semi-perennial crop such as sugarcane
would increase the density and diversity of the edaphic macrofauna,
while the epigeic community would be negatively affected by LUC due
to drastic changes in surface litter; (ii) epigeic communities would
exhibit greater negative responses than truly edaphic communities; (iii) Fig. 1. Location of study sites in Brazil, Manduri/SP (clayey soil) and Brotas/SP
sugarcane replanting would provide conditions for the recovery of (sandy soil).

2
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

Table 1 2.3. Sampling

Soil particle size distribution (g kg− 1) in sandy and clayey soil in São Paulo state,
Brazil. Soil macrofauna was collected at the end of the rainy season (be­
Location identification Clayey tween March and April 2019). In each land use (area of approximately
Geographical Manduri-SP (Lat.: 23◦ 00’ S; Long.: 49◦ 19’ O)
2.25 ha), four sampling points were defined, spaced 50 m apart in each
coordinates study area (i.e., Clayey and Sandy). Thus, the number of sampling points
totaled 16 per area (i.e., 4 land use types × 4 sampling points). Samples
Soil classification Ferralsol (WRB, 2015), Oxisol (USDA, 2014)
for edaphic macrofauna were collected in the layers 0–10, 10–20, and
1
Soil particle size distribution (g kg− ) 20–30 cm. Using the “Tropical Soil Biology and Fertility” (TSBF)
Depth (cm) NV PA SCp SCr
0–20 Clay 592 472 620 577
methodology [38], monoliths (25 cm long × 25 cm wide × 10 cm deep)
Silt 306 265 286 316 were collected at each sampling point at depths mentioned above.
Sand 102 263 94 107 Extracted invertebrates with a body diameter greater than 2 mm were
20–40 Clay 614 503 650 580 maintained in ethanol (70%) and subsequently identified at the Class,
Silt 296 247 292 310
Subclass, Order, and/or Family levels with the aid of a stereoscopic
Sand 90 250 58 110
microscope (40×).
Location identification Sandy
The collection of epigeic macrofauna was done through the instal­
Geographical Brotas-SP (Lat.: 22◦ 17’S; Long.: 48◦ 07’O)
coordinates
lation of pitfall traps [39,40] in March 2020. In each area, a total of 20
Soil classification Arenosol (WRB, 2015), Quartzipsamments (USDA, pitfall traps were installed (i.e., 4 land use types × 5 sampling points) 30
2014) m apart from each other. The captured organisms were preserved in
Soil particle size distribution (g kg− 1
) ethanol (70%) and formalin (2%) solution. The traps remained in the
Depth (cm) NV PA SCp SCr field for ten days. Macroinvertebrates were sorted and identified at the
0–20 Clay 50 49 75 75 Class, Subclass, Order, and/or Family levels with the aid of a stereo­
Silt 11 20 10 1
scopic microscope (40×).
Sand 939 930 915 924
20–40 Clay 75 100 124 151
The microbial biomass carbon (MBC) and nitrogen (MBN) were
Silt 17 19 17 3 determined by the chloroform-fumigation-extraction method proposed
Sand 908 881 860 847 by Refs. [41,42] MBC contents were obtained from the difference be­
*NV = native vegetation; PA = pasture; SCp = sugarcane plant; SCr = sugarcane tween the organic carbon extracted from fumigated and non-fumigated
ratoon. soil samples using a correction factor (kEC) of 0.33 [41].
Cavalcanti were quantified by the analytical methods described in
(NV) – Atlantic Forest fragment (natural ecosystem reference); ii) Ref. [43] active (pHCaCl2 0.01 mol L− 1) and potential acidity (H + Al)
extensive Pasture (PA) – managed in continuous grazing without in­ by SMP solution, available calcium (Ca2+) and magnesium (Mg2+) by
vestment in fertilization or liming and the forage plant was brachiaria; ion exchange resin/atomic absorption, potassium (K+) by ion exchange
iii) planted Sugarcane (SCp) – area recently converted to sugarcane resin/atomic emission, phosphorus (P) by ion exchange resin/­
(October 2018) from extensive pasture, using conventional tillage; and colorimetry, sulfur (S-sulfate) by calcium phosphate/turbidimetry, base
iv) Sugarcane ratoon (SCr) – areas cultivated with sugarcane in second saturation (V%) and potential cation-exchange capacity (CECpH7), and
ratoon (sandy) and third ratoon (clayey), cultivated conventionally with organic matter (OM), determined by colorimetry with sulfuric acid [43].
mechanized harvesting without straw removal (Fig. 2). The four land For physical indicators, undisturbed samples were collected using
uses were in adjacent areas (side by side), to minimize the effects of volumetric rings of ~100 cm3 at depths of 0–10, 10–20, and 20–30 cm,
climatic, topographic, and edaphic variations. The history of land use and the gravimetric moisture and soil bulk density (BD) were deter­
and brief description of the management operations conducted at the mined. To determine the density, the ratio between the dry soil mass and
studied sites can be found in Table 4. the ring volume was calculated. The volumetric water content (θ) was
calculated by the relationship between BD and gravimetric moisture.

Table 2
Attributes of soil acidity, cation-exchange capacity, and organic matter for the 0–10, 10–20, and 20–30 cm layers under native forest, pasture, planted sugarcane, and
sugarcane ratoon in the studied locations.
Attributes Sandy Clayey

Native Vegetation Pasture Planted Sugarcane Sugarcane ratoon Native Vegetation Pasture Planted Sugarcane Sugarcane ratoon

0–10 cm
pH 4.07 (±0.09) 4.85 (±0.19) 5.27 (±0.35) 5.05 (±0.12) 3.77 (±0.20) 4.25 (±0.05) 4.35 (±0.19) 4.97 (±0.17)
H + Al 130.33 (±8.08) 40.25 (±5.56) 38.33 (±6.35) 41.5 (±6.55) 60.00 (±6.92) 33.25 (±1.50) 41.66 (±9.23) 20.50 (±1.91)
V% 9.25 (±2.21) 46.66 (±4.50) 51.33 (±9.45) 58.75 (±7.08) 7.75 (±1.70) 18.75 (±1.25) 24.00 (±7.81) 39.00 (±3.00)
CEC 144.43 (±6.71) 69.65 (±6.69) 100.70 (±17.15) 100.75 (±9.14) 59.95 (±10.76) 40.80 (±1.78) 47.30 (±7.35) 37.50 (±4.92)
OM 47.33 (±6.11) 35.00 (±3.91) 31.00 (±7.00) 36.25 (±2.62) 22.25 (±6.02) 20.00 (±1.82) 19.00 (±1.82) 13.00 (±1.63)
10–20 cm
pH 3.95 (±0.05) 4.87 (±0.26) 4.82 (±0.28) 4.77 (±0.25) 3.87 (±0.15) 4.15 (±0.05) 4.62 (±0.37) 4.77 (±0.32)
H + Al 131.50 (±7.00) 41.00 (±6.55) 35.33 (±2.30) 56.00 (±6.92) 45.33 (±2.88) 34.00 (±0) 28.25 (±6.94) 21.00 (±4.69)
V% 5.75 (±0.90) 43.33 (±5.13) 44.00 (±6.92) 30.66 (±6.65) 4.25 (±2.36) 12.50 (±2.88) 39.25 (±11.89) 36.25 (±11.89)
CEC 139.67 (±7.48) 60.80 (±5.74) 64.16 (±13.53) 76.72 (±7.87) 52.17 (±9.92) 38.95 (±1.29) 41.30 (±8.46) 32.70 (±1.51)
OM 31.75 (±3.86) 26.50 (±2.64) 28.00 (±6.97) 28.00 (±2.16) 16.00 (±2.16) 14.00 (±1.41) 14.00 (±3.46) 9.00 (±0.81)
20–30 cm
pH 3.92 (±0.09) 4.72 (±0.44) 4.55 (±0.52) 4.32 (±0.63) 3.95 (±0.05) 4.17 (±0.09) 4.55 (±0.46) 4.67 (±0.28)
H + Al 131.50 (±7.00) 46.00 (±10.39) 41.00 (±14.79) 80.33 (±17.03) 40.50 (±6.75) 35.00 (±2.00) 27.33 (±9.23) 22.00 (±4.32)
V% 4.00 (±1.41) 32.66 (±12.05) 29.66 (±15.69) 15.00 (±5.56) 3.50 (±2.51) 12.50 (±3.78) 29.00 (±16.46) 32.00 (±8.12)
CEC 136.75 (±6.32) 56.45 (±6.82) 57.16 (±7.31) 93.56 (±14.11) 41.97 (±5.96) 40.07 (±2.25) 41.22 (±7.78) 32.05 (±2.54)
OM 29.75 (±2.21) 23.25 (±2.62) 23.75 (±3.50) 24.25 (±0.95) 10.75 (±1.25) 12.5 (±1.00) 14.25 (±3.30) 7.5 (±1.00)
1
*Units: pHCaCl2 0.01 mol L− (pH); potential acidity (H + Al) (mmolc dm− 3); V (%): CEC saturation by bases; CEC (mmolc dm− 3): cation exchange capacity; OM (g
dm− 3) colorimetric.

3
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

Table 3
Soil macronutrient content for the 0–10, 10–20, and 20–30 cm layers under native forest, pasture, planted sugarcane, and sugarcane ratoon in the studied locations.
Attributes* Sandy Clayey

Native Vegetation Pasture Planted Sugarcane Sugarcane ratoon Native Vegetation Pasture Planted Sugarcane Sugarcane ratoon

0–10 cm
P 14.33 (±3.78) 4.5 (±0.57) 7.66 (±1.52) 11.33 (±3.21) 3.00 (±0.95) 3.00 (±3.55) 3.00 (±6.95) 7.75 (±4.50)
S 7.50 (±0.70) 5.00 (±0.70) 9.33 (±2.51) 15.00 (±1.41) 5.3 (±0.57) 7.00 (±1.20) 7.50 (±0.70) 8.00 (±1.41)
K 1.87 (±0.68) 0.90 (±0.10) 1.70 (±0.69) 1.50 (±1.27) <0.90 (±0)** <0.90 (±0) <0.90 (±0) <0.90 (±0)
Ca 4.75 (±2.06) 18.66 (±7.72) 39.66 (±17.03) 43.25 (±5.73) 2.50 (±0.57) 3.50 (±5.77) 5.75 (±2.21) 12.00 (±5.35)
Mg 5.50 (±1.94) 14.00 (±1.00) 24.66 (±8.50) 16.66 (±1.15) 1.00 (±0) 3.00 (±0) 2.25 (±0.95) 4.25 (±1.50)
10–20 cm
P 11.00 (±0.81) 3.00 (±0) 5.00 (±0.70) 7.33 (±4.04) 3.00 (±3.09) 3.00 (±0.57) 3.00 (±6.07) 3.00 (±0)
S 6.00 (±2.12) <5.00 (±0) 6.00 (±0.563) 30.66 (±6.50) 6.00 (±1.22) <5.00 (±0) 5.33 (±0.57) <5.00 (±0)
K 1.67 (±0.28) <0.90 (±0) 1.20 (±0) <0.90 (±0) <0.90 (±0) <0.90 (±0) <0.90 (±0) <0.90 (±0)
Ca 3.00 (±0) 15.66 (±0.57) 11.66 (±2.08) 16.50 (±3.10) <1.00 (±0) 3.25 (±0.95) 9.66 (±4.72) 7.25 (±2.06)
Mg 3.50 (±1.00) 8.75 (±2.87) 10.50 (±3.78) 9.25 (±2.36) 1.00 (±0.56) 1.25 (±0.50) 6.33 (±3.21) 3.75 (±1.50)
20–30 cm
P 6.75 (±2.06) <3.00 (±0) 5.00 (±3.53) 3.00 (±1.41) 3.00 (±0) 3.00 (±1.00) 3.00 (±4.71) 3.00 (±0)
S <5.00 (±0) 5.00 (±0) 8.00 (±4.24) 33.33 (±17.21) 5.00 (±0.53) 5.00 (±0.58) 5.00 (±0.12) 5.00 (±0.23)
K 1.25 (±0.23) <0.90 (±0) <0.90 (±0) <0.90 (±0) <0.90 (±0) <0.90 (±0) <0.90 (±0) <0.90 (±0)
Ca 1.00 (±0) 9.0 (±4.39) 7.25 (±4.42) 7.00 (±1.73) <1.00 (±0) 3.25 (±1.25) 5.25 (±3.20) 6.25 (±1.50)
Mg 2.75 (±0.95) 5.50 (±2.08) 6.00 (±3.55) 7.50 (±9.37) 1.00 (±0.25) 1.25 (±0.50) 4.00 (±1.73) 3.00 (±0.81)

*Units: Phosphorus (P) (mg dm− 3); sulfur (S) (mg dm− 3); potassium (K) (mmolc dm− 3); calcium (Ca) (mmolc dm− 3). and magnesium (Mg) (mmolc dm− 3). **(<) less
than the limit of quantification.

Fig. 2. Experimental areas with different land use to evaluate the ecosystem services of clayey soil: (a) Native vegetation area; (b) Extensive pasture area; (c) Planted
sugarcane area; (d) Ratoon sugarcane area. Sandy: (a) Native vegetation area; (b) Extensive pasture area; (c) Planted sugarcane area; (d) Sugarcane ratoon area.

The macro- (MaP), meso- (MeP), and microporosity (MiP) were calcu­ fauna, we determined the total density of organisms (individuals m− 2)
lated according to the pore distribution as a function of the radius of and taxonomic richness (number of macrofauna groups), with which it
each pore, with macropores >50 μm, mesopores between 50 and 15 μm, was calculated the Shannon’s diversity index (H′ ) and Pielou’s Evenness
and micropores <15 μm according to Cavalcanti et al. [44]. Hence, the index (J′ ). The Shannon index and Pielou index are used to assess
following relationships were calculated. biodiversity of macrofauna communities because they consider both the
number of different species and the relative density of each species in the
TP = [1 – (BD/PD)]; MaP = TP – θ30hPa; MeP = θ30hPa – θ100hPa; MiP =
sample. This provides a more complete picture of the overall diversity
θ100hPa and evenness of the community.
where TP and PD are total porosity and particle density, respectively, Shannon’s index was calculated using Eq. (1).
θ30 h Pa and θ100 h Pa are the volumetric water content at tensions of ∑
s

30 and 10, respectively. (1)

′
H =− (pi log2 pi)
i=1

2.4. Data analysis where: H′ = Shannon’s diversity index. Σ = Total number of taxa found
at the site. pi = Relative density (proportion) of species “i” in the sample.
After identification and quantification of the edaphic and epigeic

4
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

Table 4 layer depth were used as fixed effects in the models. As a random effect,
Historical information on land use and brief description of the management the location was used to explain the interdependence that results from
operations conducted at the sites studied. having multiple measurements per location. Slopes describing the
Location Use Description relationship between community attributes and land use were used to
Sandy NV Secondary vegetation and seasonal semideciduous forest
interpret possible differences in the sensitivity of edaphic and epigeic
Soil composed of Trichillia clausenii, Euterpe edulis, and Aspidosperma fauna to LUC. For each model, both the r2marginal (proportion of variance
polyneuron as dominant species. explained by the moderating variables) and the r2conditional (that of the
PA The conversion of VN to PA occurred in 1975. PA was entire model, including the random effect) were calculated [45]. The p
cultivated with brachiaria (Brachiaria decumbens) cv. Basilik,
values were obtained by evaluating the likelihood ratio of the complete
without application of mineral fertilizer and with an animal
stocking rate of ~7 animal units (AU) (7 AU ha− 1) until 2018. model with the effect in question against the model without the effect.
B. decumbens was replaced by Brachiaria brizanta cv. Marandu All analyzes were conducted using R software, version 3.2.2 (R. Core,
in 2018. During this conversion, 2 Mg ha− 1 of lime, and 200, 2013), and nlme packages [46], piecewiseSEM [47] vegan [48] and
135, and 115 kg ha-1 of nitrogen, Phosphorus, and potassium, ggplot2 [49].
respectively, were applied to the soil surface. For weed control,
1.5 L ha− 1 of 2.4-D (a.i.) was applied. The stocking rate
Principal component analysis was conducted to find possible re­
remained the same as in the previous period with continuous lationships between macrofauna density and diversity and the physical
grazing throughout the year. and chemical parameters of the soil. In addition, Pearson’s linear cor­
SCp The conversion from PA to SCp occurred in 2018. The relation analysis was performed between macrofauna data (i.e., density,
conversion was done through conventional tillage with plowing
Shannon’s diversity, main macroinvertebrate groups) and soil chemical
and harrowing. To the soil surface, 2 t ha− 1 of lime was applied
and 60, 150, and 120 kg ha− 1 of nitrogen, phosphorus, and and physical attributes (i.e., soil pH, macronutrients, cation-exchange
potassium, respectively, were applied to the planting lines. The capacity (CEC), microbial biomass carbon (MBC), microbial biomass
cultivar planted was IAC SP 97–4039. nitrogen (MBN), bulk density and soil porosity).
SCr The conversion of PA to SCr occurred in 2002. In the
following years, the harvest was done mechanically without
burning and without straw removal. The sugarcane was
3. Results
replanted every 5 years with plowing and harrowing. The last
replanting was in 2017 where the cultivar IAC SP 97–4039. 3.1. Soil macrofauna sampled by TSBF method
After the 2018 harvest, 155, 41, and 86 kg ha− 1 of nitrogen,
phosphorus, and potassium were applied, respectively.
The total density of edaphic macrofauna found corresponded to 1556
Description of SCr. During mechanized harvesting, the straw is
evenly distributed in the area. Then the windrowing operation individuals, of which 1336 (86%) were found in clayey soil and 220
is carried out in which the straw is removed from the rows and (14%) in sandy soils. The macrofauna was summed up in a frequency of
added between the rows, resulting in the deposition of straw in Araneae (2%), Chilopoda (3%), Coleoptera (26%), Diplopoda (6%),
the same place over the years. Diptera (1%), Formicidae (4%), Hemiptera (4%), Isoptera (4%) and
Clayey NV Same description as in sandy soil.
Soil PA The conversion from VN to PA occurred in 1970. The pasture
Oligochaeta (51%). However, in the sandy soil, the macrofauna identi­
was composed of Brachiaria decumbens without the addition of fied was restricted to Araneae (2%), Coleoptera (76%), Hemiptera
mineral fertilizer. Grazing was continuous with a stocking rate (18%), and Oligochaeta (4%). The frequency of each group identified in
of 1.2 AU ha− 1. the clayey soil was Araneae (1%), Chilopoda (4%), Coleoptera (18%),
SCp The conversion from PA to SCp took place in 2018. The
Diplopoda (7%), Diptera (1%), Formicidae (4%), Hemiptera (1%), Iso­
conversion was done through conventional tillage with plowing
and harrowing. At that time, 2 t ha− 1 of lime were applied to the ptera (5%) and Oligochaeta (59%) (Table 5).
soil surface, and 50, 150, and 50 kg ha− 1 of nitrogen, Land-use change and soil depth affected the density of edaphic
phosphorus, and potassium, respectively, were applied to the macrofauna (Land use p = 0.0432; Depth p < 0.0001; r2marginal = 0.27,
planting rows. r2conditional = 0.32), with no interaction between the two explanatory
SCr The conversion from PA to SCr took place in 2016. In 2017
and 2018, mechanical harvesting was done without burning
variables (p = 0.8082) (Fig. 3a). The total density (log + 1) of macro­
and without removal of straw. After each harvest, 90 and 80 kg fauna was lower in PA (− 1.56 ± 0.98, p = 0.1164), SCp (− 1.08 ± 0.98,
ha− 1 of nitrogen and potassium were applied, respectively. p = 0.275), and significantly lower in SCr (− 2.94 ± 0.98, p = 0.003) in
relation about was lower in the 10–20 cm (− 2.65 ± 0.97; p = 0.0087)
and 20–30 cm (− 3.00 ± 0.98; p = 0.98; 0031) compared to the 0–10 cm
The Pielou index measures the evenness of the community, which is
surface layer (Fig. 3).
important in determining the health and stability of biotic communities.
The effects of LUC on taxa richness of edaphic macroinvertebrates
The evenness index ranges from 0 to 1, defined by the pattern of even­
were dependent on soil depth (Land use*Depth p < 0.0552; r2marginal =
ness of individuals between species or groups, i.e., how much the pro­
0.29, r2conditional = 0.34) (Fig. 3b). Compared to NV, taxa richness
portions of species are equally distributed in the community, calculated
decreased in PA (− 1.87 ± 0.53, p = 0.0007), SCp (− 1.37 ± 0.53, p =
by Eq. (2).
0.0111), and SCr (− 1.87 ± 0.53, p = 0.0007). In all cases, these re­
H
′
ductions were stronger at the surface compared to deeper soil layers
(2)
′
E =
ln (S) 10–20 cm (− 2.25 ± 0.51; p = 0.000) and 20–30 cm (− 2.00 ± 0.51; p =
0.0002) (Fig. 3b).
where E’ = Pielou index; H’ = Shannon index; S = the number of species Despite LUC effects on both density and taxa richness of edaphic
or groups; ln = logarithm to the natural base. macrofauna, there were no significant changes on diversity and even­
Overall, the Shannon and Pielou indexes are more versatile and can ness (Shannon p = 0.0789, Pielou p = 0.3121). Along of soil profile,
provide a more nuanced understanding of biodiversity in macrofauna deeper soil layers presented the lowest Shannon (depth p = 0.0294;
communities. r2marginal = 0.21, r2conditional = 0.26) and Pielou values (depth p = 0.0001;
Data normality was tested using Shapiro-Wilk’s test (p > 0.05). The r2marginal = 0.28, r2conditional = 0.33) (Table 6). The PA area had a high
density of data was re-transformed into logs (x + 1) to meet the relative density of edaphic organisms about areas (Fig. 3a) but had a
assumption of normal distribution of the data. Linear mixed effect lower diversity index (− 0.62 ± 0.18 p = 0.0013) than the NV area
models were used to analyze the relationship between edaphic and (Table 6), confirming the dominance of specific groups (e.g., Oli­
epigeic macrofauna variables (density, richness of groups, Shannon gochaeta and Coleoptera). On average 70% of the edaphic organisms
index, and Pielou (evenness) index) and land uses. Land use and soil found in each land use occurred in the top 0–10 cm layer of the soil
profile (mainly the groups Araneae, Chilopoda, Diplopoda, Dermaptera,

5
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

Table 5
Density (individuals m− 2) and standard deviation of edaphic macrofauna groups in the 0–30 cm layer in different land uses, N = 4.
Taxon Common Taxonomic Clayey Sandy
Name Level
Native Extensive Planted Sugarcane Native Extensive Planted Sugarcane
Vegetation Pasture Sugarcane Ratoon Vegetation Pasture Sugarcane Ratoon

Araneae Spiders Order 16 ± 9 – 4±2 – 4±2 – – –

Chilopoda Centipedes Class 48 ± 28 4±2 – – – – – –
Coleoptera Beetles Order 56 ± 14 108 ± 49 12 ± 4 60 ± 17 104 ± 36 32 ± 12 24 ± 11 8±5
Diplopoda Millipedes Class 80 ± 46 4±2 – 4±2 – – – –
Diptera Flies Order 12 ± 7 – – 4±2 – – – –
Formicidae Ants Family 16 ± 9 12 ± 7 12 ± 4 16 ± 6 – – – –
Hemiptera True Bugs Order – 12 ± 7 4±2 – – – 40 ± 12 –
Isoptera Termites Suborder – 4±2 – 60 ± 28 – – – –
Oligochaeta Earthworms Subclass 32 ± 10 564 ± 315 168 ± 97 24 ± 8 4±2 – – 4±2
Total 260 708 200 168 112 32 64 12
Richness 7 7 5 6 3 1 2 2
(number of
taxa)

Fig. 3. Total density (a) and taxa richness (b) of edaphic macrofauna as a function of land use in clayey and sandy soils, and (c) the composite mean of all sites (n
= 4).

Formicidae, Isoptera, Oligochaeta), along the soil profile Coleoptera and (belonging the Blattodea, Lepidoptera, Mantodea, and Neuroptera or­
Oligochaeta groups were found in lower density, Hemiptera was found ders) were grouped as “Others”, because their frequency was equal to 1
in greater density in the 10–20 cm layer. A greater predominance of individual (Table 7). The total number of macroinvertebrates found was
Formicidae, Coleoptera, and Orthoptera was found in the pasture of the 332 individuals. The clayey soil accounted for 44% of the total number
sandy soil. In the clayey soil, there was a predominance of Oligochaeta of individuals and the sandy soil for 56%. All groups studied were found
in the PA and SCp. In the clayey soil, one sampling point stood out from for both locations.
the others with a great density of earthworms, making this group the The density of epigeic macrofauna was affected by LUC (land use p =
most abundant in the pasture area. The reduction of organisms with 0.0021; r2marginal = 0.28, r2conditional = 0.39) (Fig. 5). Lower absolute
increasing soil depth was evident in all land uses (Fig. 4). density values were found in the SCp (− 21.7 ± 8.88, p = 0.0201) and
SCr (− 1.233 ± 9.78, p = 0.2261) areas compared to NV. PA showed no
significant effects on the density compared to NV (10.10 ± 8.88, p =
3.2. Soil macrofauna sampled by pitfall traps 0.2637). Taxa richness was also altered with the LUC (land use p =
0.0012; r2marginal = 0.30, r2conditional = 0.40) (Fig. 5) and exhibited a
The groups that predominated in the epigeic macrofauna were Ara­ similar pattern a for density, with lower values in the SCr area (− 1.80 ±
neae (3%); Coleoptera (36%); Dermaptera (10%); Diptera (2%); For­ 0.62, p = 0.0067) than the NV. For the other uses, there were no sig­
micidae (31%); Hemiptera (1%); Hymenoptera (2%); Isoptera (1%) and nificant reductions (p > 0.10).
Orthoptera (13%). In addition to these groups, 2% of the individuals

6
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

Table 6
Shannon diversity and Pielou equability indices of edaphic macrofauna as a function of land use in two locations (Clayey and Sandy).
Clayey Sandy

NV PA SCp SCr NV PA SCp SCr

0–10 cm
Shannon 1.29 ± 0.10 0.19 ± 0.18 0.33 ± 0.66 0.49 ± 0.63 0.14 ± 0.28 – 0.22 ± 0.43 –
Evenness 0.59 ± 0.04 0.09 ± 0.08 0.15 ± 0.30 0.22 ± 0.28 0.08 ± 0.15 – 0.12 ± 0.24 –
10–20 cm
Shannon – 0.32 ± 0.39 – 0.39 ± 0.45 – – – –
Evenness – 0.15 ± 0.17 – 0.18 ± 0.20 – – – –
20–30 cm
Shannon 0.30 ± 0.34 0.43 ± 0.52 – – 0.17 ± 0.34 – – –
Evenness 0.14 ± 0.15 0.20 ± 0.23 – – 0.10 ± 0.19 – – –
Evenness index
Land Use p = 0.0709 Land Use p = 0.3121
Depth p = 0.0294 Depth p = 0.0001
r2marginal 0.21 r2marginal 0.28
r2conditional 0.26 r2condicional 0.33

Shannon’s diversity and Pielou’s evenness indexes changed as a Macrofauna density and organism diversity displayed a positive
function of LUC (diversity of organisms: land use p = 0.0152; r2marginal = correlation with SOM, CEC, MBC, MBN, MaP, and TP, and a negative
0.21, r2conditional = 0.33; evenness index of organisms: land use p = correlation for physical attributes such as BD and MeP (p < 0.05)
0.0168; r2marginal = 0.20, r2conditional = 0.32). The diversity and evenness of (Table 9). These results confirmed the second hypothesis that soil
organisms reduced in SCr compared to the NV, which did not occur for physical and chemical properties (mainly the presence of macropores
the other land uses (Shannon diversity − 0.34 ± 0.14 p = 0.0184, Pielou and macronutrients) are related to macrofauna density/diversity. The
evenness − 0.13 ± 0.05 p = 0.0208) (Table 8). Oligochaeta group had a positive correlation with Ca2+ and Mg2+, and
biological attributes such as SOM, MBC, and MBN (p < 0.05). The
3.3. Differential sensitivity of edaphic and epigeic macrofauna to LUC density of ants (Formicidae) was related to K+ and Mg2+ (p < 0.05). The
Diplopoda, Chilopoda, and Araneae groups exhibited correlations with
The epigeic macrofauna presented a greater magnitude of response K+, and H + Al was related to the presence of these taxa (p < 0.05). Bulk
to LUC than the edaphic macrofauna confirming our first hypothesis, in density had a negative correlation with all identified organisms, espe­
which epigeic communities would exhibit greater negative responses cially Formicidae, Diplopoda, Chilopoda, and Araneae (p < 0.05). The
than truly edaphic communities (Fig. 6). This magnitude of response was presence of organisms conditioned the soil porosity, and the micropores
increased with the intensification of land use, i.e. sugarcane areas were correlated with the presence of individuals from the Formicidae
showed more negative responses for epigeic macrofauna (and more family (Table 9).
intensely in the SCr) compared to other land uses. Sugarcane soils were generally associated with higher pH and higher
Ca2+ and Mg2+ contents. Native vegetation soils were grouped close to
3.4. Relationship between macrofauna and chemical, physical, and the variables H+Al, MaP, and CEC. In clayey soil, density, diversity, and
microbiological attributes groups of earthworms and ants correlated with the highest levels of
MBC, MBN, and SOM (Fig. 1S). Chilopoda and Araneae were more
Principal component analysis showed that the two axes explained associated with NV areas. The invertebrate community were more
51.8% of the variance for clayey soil and 46.8% of the variance for sandy clustered in NV than PA, SCp and SCr, which presented overlapping
soil (Fig. 7). Sugarcane soils were generally associated with higher pH points, mainly in clayey soil and regardless of depth (Fig. 1S). In sandy
and higher Ca2+ and Mg2+ contents. Native vegetation soils were soil, the density and diversity of organisms had a positive correlation to
grouped close to the variables H+Al, MaP, and CEC. In clayey soil, macroporosity and SOM (Fig. 2S). The macroinvertebrate composition
density, diversity, and groups of earthworms and ants correlated with in the deeper layers of sandy soil for layers in SCr was not correlated
the highest levels of MBC, MBN, and soil organic matter (SOM) (Fig. 7). with the other uses, being very different from the PA, SCp, and NV
Chilopoda and Araneae were more associated with NV areas. The (Fig. 2S).
invertebrate community was more clustered in NV than PA, SCp and In summary, the NV contained greater richness and diversity of or­
SCr, which presented overlapping points, mainly in clayey soil and ganisms compared to other land use types. The conversion from NV to
regardless of depth (Fig. 7). PA did not change the density of macrofauna but resulted in a reduced
In the surface (0–10 cm) layer of clayey soil, the macroinvertebrate richness and diversity, leading to the dominance of the Coleoptera and
community found in SCr was different from the community found in Formicidae groups. The conversion from PA to SCp cultivation caused
SCp, PA, and NV. On the other hand, the macrofauna composition found significant losses to the soil macrofauna, mostly on clayey soil. The SCr
in the r SCp and PA overlapped, showing similarities. In the surface layer cultivation led to SCr the reduction of density, taxonomic richness, di­
of the soil (0–10 cm) the presence of earthworms was associated with PA versity, and evenness of macrofauna.
and SC land uses, whereas predators such as Chilopoda and Araneae
were associated with NV (Fig. 1S). In the deeper layers (10–20 and 4. Discussion
20–30 cm) these differences were not observed, since the composition of
macrofauna found in PA, SC, and SCr overlapped, distancing themselves In contrast to what we predicted in our first hypothesis, the con­
only from the NV. Soil chemical attributes correlated mainly with SCr version of pastures to sugarcane reduced both the edaphic and epigeic
area at the three depths in clayey soil (Fig. 1S). In the surface layer communities. Despite being a semi-perennial crop with less intense
(0–10 cm) of sandy soil, the macrofauna community of the PA, SCp, and management compared to annual crops, our results suggest that there
SCr was close, distancing themselves from the NV. The presence of are enough soil physical disturbances induced by soil tillage in sugar­
earthworms was correlated to the SCr area. In the soil layers (10–20 and cane cropping to affect the biota. The disturbance generated by soil
20–30 cm), the macrofauna present in SCr did not correlate with the preparation can harm organisms, especially those that live on the soil
other groups (Fig. 2S). surface. In simplified environments, as is the case of monoculture, the

7
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

Fig. 4. Vertical distribution of density by a group of edaphic and epigeic macrofauna.

plant residues may have lower nutritional value compared to those of cycle, which are well-known causes of negative effect on soil in­
more complex environments, which in turn reduces macrofauna groups vertebrates and the services they provide [52,53].
[50]. In these monoculture areas, groups such as ants which are capable The low soil moisture and inputs of organic material in the sandy soil
of colonizing low-resource locations often dominate the faunal com­ explains the lower presence of organisms compared to clay soils. In
munities [51]. In addition, pesticides are used during the sugarcane sandy soil, the native vegetation had a predominance of the Coleoptera

8
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

Table 7
Density (individuals per trap) and standard deviation of epigeic macrofauna groups, N = 5.
Taxon Common Taxonomic Clayey Sandy
Name Level
Native Extensive Planted Sugarcane Native Extensive Planted Sugarcane
Vegetation Pasture Sugarcane Ratoon Vegetation Pasture Sugarcane Ratoon

Araneae Spiders Order 1.6 ± 1.1 2.2 ± 2.1 1.6 ± 1.5 1.4 ± 1.3 1.4 ± 0.5 2.2 ± 1.7 0.6 ± 0.8 0.3 ± 0.5
Coleoptera Beetles Order 0.6 ± 0.8 18.0 ± 11.4 9.6 ± 6.9 11.2 ± 13.7 34.6 ± 16.9 25.0 ± 6.3 6.6 ± 2.3 12.8 ± 12.4
Dermaptera Earwigs Order 4.0 ± 3.3 5.2 ± 2.1 1.2 ± 0.8 2.8 ± 2.7 15.8 ± 9.8 1.2 ± 1.3 0.2 ± 0.4 2.3 ± 1.7
Diptera Flies Order 0.6 ± 1.3 0.6 ± 1.3 0.2 ± 0.4 0.2 ± 0.4 0.4 ± 0.5 1.8 ± 1.6 0.8 ± 0.8 0.8 ± 0.9
Formicidae Ants Family 15.0 ± 8.3 23.6 ± 9.2 8.8 ± 7.4 13.4 ± 11.0 17.2 ± 7.4 18.2 ± 8.7 5.0 ± 3.6 1.8 ± 2.3
Hemiptera True Bugs Order 0.2 ± 0.4 – 0.6 ± 0.8 – 0.2 ± 0.4 0.8 ± 0.8 1.6 ± 3.0 –
Hymenoptera Wasps Order 0.4 ± 0.5 – 3.8 ± 8.4 – – 0.2 ± 0.4 – 1.3 ± 1.5
Isoptera Termites Suborder 0.4 ± 0.8 0.2 ± 0.4 1.2 ± 2.1 – – – – –
Orthoptera Locusts Order 3.6 ± 4.0 2.4 ± 1.9 3.0 ± 2.8 8.0 ± 6.1 – 16.0 ± 13.5 9.8 ± 6.4 0.8 ± 0.9
Others 0.4 ± 0.2 0.6 ± 0.1 – – 2.4 ± 0.8 3.0 ± 1.5 0.4 ± 0.2 –
Total 26.8 52.8 30 37 72 68.4 25 19.75
Richness (number of taxon) 10 8 9 6 7 9 8 7

“Others”: Individuals with frequency lower than 1 – orders Blattodea, Lepidoptera, Mantodea and Neuroptera.

Fig. 5. Absolute density of epigeic macrofauna as a function of land use at two clayey (a) and sandy (b) sites, and (c) the composite mean of all sites. The absolute
richness of organisms as a function of land use at two clayey (d) and sandy (e) sites, and (f) the composite mean of all sites (n = 4).

Table 8
Shannon diversity and Pielou index (equability) of epigeic macrofauna as a function of land use at two locations (Clayey and Sandy).
Clayey Sandy

NV PA SC SCr NV PA SC SCr

Shannon 1.26 ± 0.18 1.24 ± 0.18 1.27 ± 0.25 1.23 ± 0.05 1.19 ± 0.20 1.37 ± 0.14 1.28 ± 0.36 0.77 ± 0.49
Pielou 0.49 ± 0.07 0.48 ± 0.07 0.49 ± 0.10 0.48 ± 0.02 0.44 ± 0.07 0.51 ± 0.06 0.47 ± 0.13 0.28 ± 0.18

Shannon Pielou

Land use p = 0.0184 Land use p = 0.0208

r2marginal 0.21 r2marginal 0.20
r2conditional 0.32 r2conditional 0.30

9
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

localized accumulation of organic matter from cattle manure [57,58].

The high density of Oligochaeta in pasture areas was also confirmed by
Ref. [18]. The presence of earthworms provides positive benefits to the
soil, as these invertebrates build biogenic structures through biopores,
participating in the structural stability of tropical soils [59–61]. Over the
years, extensive pasture areas become an environment with less human
disturbance than recently converted sugarcane areas, supporting a
greater density of invertebrates. Previous studies confirm that macro­
fauna community size in tropical soils tends to increase with time after
the conversion of native vegetation to pasture [18,62,63].
As predicted in our second hypothesis, our results revealed stronger
responses of epigeic compared to edaphic macrofauna to LUC. It in­
dicates that litter- and surface-dwelling invertebrate communities are
more vulnerable to disturbance from land use and management than
truly edaphic ones and suggests that the key role of epigeic fauna on
litter decomposition may be impaired shortly following LUC. This
response may be particularly visible in intensive monocultures such as
sugarcane, where the food sources and ecological niches on the soil
surface are highly reduced [29,30,64]. Therefore, organisms that
inhabit the soil surface such as spiders, millipedes, snails, slugs, and
Fig. 6. Slope describing the relationships between macrofauna abundance and
insects are more exposed to disturbances in habitat and food. Greater
LUC from native vegetation to pasture (PA), sugarcane (SC), and sugarcane
negative responses were found of the edaphic fauna in areas cultivated
ratoon (SCr).
for longer periods (i.e., SCr) supporting the idea that time since LUC and
land use intensity are determining factors for the magnitude of edaphic
and Araneae groups (Fig. 4). Spiders are edaphic generalist predators,
fauna responses. In contrast to our third hypothesis, ratoon sugarcane
and with soil management or LUC and habitat modification prey
cultivation negatively impacted macrofauna density, taxonomic rich­
availability is reduced [54]. On the other hand, coleoptera is less sen­
ness, diversity, and evenness (Fig. 3; Tables 5 and 6). With the reduction
sitive to soil management [55]. The predominant presence of these
of the density and diversity of organisms in the ratoon sugarcane, the
groups corroborates other studies, in which Coleoptera, Formicidae and
Coleoptera and Formicidae groups became dominant, especially the
Araneae were the most common groups found, where the presence of
epigeic fauna, as occurred in the pasture area (Fig. 4). These groups are
spiders was associated with tree cover in the landscape and pasture [14,
among the most diverse arthropods in a terrestrial environment, and
18,30].
some species are more adapted to simplified environments [56,60].
The Formicidae family was present in all land uses (Fig. 4), which is
Groups such as ants, termites, and earthworms play a fundamental
common, as ants have broad species adaptability and diverse feeding
role in structuring and stabilizing soils. They participate in the aggre­
habits [51]. A more detailed analysis of these ubiquitous invertebrates
gation and increase soil macroporosity, which explains the significant
showed contrasting LUC effects across ant species [30]. Some species
correlation among these variables observed in Table 9, affecting infil­
show greater adaptability in more simplified habitats, such as pasture,
tration and water distribution in the profile, in addition to creating
due to their low ecological requirements [56]. In the pasture, high
habitats for organisms, including microorganisms and plants [5,8,33,
abundances of earthworms were found, which can be explained by
65]. The cultivation of sugarcane was linked to lower levels of organic

Fig. 7. Principal Component Analysis englobing the density, diversity, evenness, and main macrofauna groups with chemical, physical, and biological attributes in
clayey (a) and sandy (b) soil in the 0–30 cm layer.

10
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

matter, as well as lower levels of density and diversity (Table 2).

*Units: pH: pHCaCl2 0.01 mol L− 1; OM organic matter (g dm− 3); P: Phosphorus (mg dm− 3); S: sulfur (mg dm− 3); K: potassium (mmolc dm− 3); Ca: calcium (mmolc dm− 3) and Mg: magnesium (mmolc dm− 3); H + Al:
potential acidity (mmolc dm− 3); SB: Sum of bases; CEC: cation exchange capacity (mmolc dm− 3); V(%): CEC saturation by bases; MBC: Microbial biomass carbon; MBN: Microbial biomass nitrogen Ds: Soil density; MaP:
0.217
0.364

0.196
0.314
0.218
0.288
Intensive sugarcane cultivation can have negative effects on physical

0.126
0.145
TP
and biological attributes, such as increased soil compaction, structural
degradation, and less storage of soil organic carbon, which are closely

0.269

0.210
0.176

0.130
0.004

0.156
0.117
0.077
correlated with a lower density and diversity of soil macrofauna [28].

MiP
The vast majority of edaphic macrofauna were concentrated in the
surface layer of the soil (0–10 cm) (Fig. 3), which also occurred in other
¡0.195
¡0.204
studies [16,18]. The soil organic matter gradually reduced with

− 0.152
− 0.051
− 0.184
− 0.123
− 0.111
− 0.077
MeP

increasing depth in all uses, regardless of soil type (Table 2). Soil organic
matter has a positive correlation with the density and diversity of or­
ganisms (Table 9). Franco et al. [7] also found relationships between a
0.236
0.293

0.215
0.156
0.303
0.224
0.327
0.141
MaP

reduced density of organisms and reduced soil organic carbon stocks,

and the dependence on soil depth for carbon stock. The density of
edaphic macrofauna is concentrated in the superficial soil layers, which
¡0.215
¡0.382

¡0.211
¡0.349
¡0.295
¡0.331
− 0.119
− 0.117

can be explained by higher food availability and oxygen diffusion.

Ds

The content of soil organic matter was related to the vertical distri­
bution of edaphic macrofauna, in which a greater density and diversity
0.445
0.404
0.341

0.426
0.543
0.402
0.515
0.061

of organisms occurred on the surface (0–10 cm). The diversity and

MBN

contrast of edaphic macrofauna in clayey and sandy soils were evident

(Fig. 3). Overall, it is likely that the higher diversity of edaphic macro­
0.471
0.537
0.357

0.392
0.586
0.440
0.533
0.087

fauna in clayey soils compared to sandy soils is due to a combination of

MBC

factors, including higher water-holding capacity, higher nutrient avail­

Pearson correlation between abundance, diversity and major macrofauna groups, chemical, physical and biological attributes for the 0–30 layer.

ability, and more stable soil structure. The clayey soil presented
− 0.059

− 0.044

− 0.147
− 0.143
− 0.146

approximately 50% more organic matter than the sandy soil (Table 2), a
0.184

0.212
V (%)

0.107

fact that may be linked to the lower density of edaphic macrofauna in

the sandy soil.
Macrofauna density and diversity presented positive correlations
0.199
0.380

0.246
0.376
0.324
0.333
0.104
0.074
CEC

with biological attributes, such as microbial biomass carbon and nitro­

gen (Table 9). The positive correlations between macrofauna density
− 0.011
− 0.038
− 0.014

and diversity and biological attributes suggest that an increase in the

Soil macroporosity; MeP: Soil mesoporosity; MiP: Soil microposity; TP: Total porosity. Values in bold represent p < 0.05.
0.324

0.308

0.228
0.114

0.028

number and variety of macrofauna can have a beneficial effect on the

SB

functioning of an ecosystem [66]. With increased nutrient availability in

the soil, soil macrofauna diversity is expected to increase as a reflection
− 0.041
H + Al

0.332

0.386
0.346
0.344
0.048

0.062
0.142

of more energy, nutrient sources and habitat [67]. Arthropods, in

addition to being linked to the functionalities of microorganisms, also
influence the distribution of microbial communities in the soil using the
0.371

0.364

0.258
0.135

0.022

0.026
0.003
0.041

transport of these microorganisms over the arthropod’s body or by the

Mg

formation of microhabitats in the soil [8].

Soil porosity, particularly macropores, was related to the density and
− 0.046
− 0.070
− 0.058
0.284

0.268

diversity of all identified organisms (Table 9). It corroborates results of

0.093

0.025
0.199
Ca

Demetrio et al. [65], who found that larger macrofauna populations

were associated with better soil structural quality. The movement of
0.197

0.239
0.362
0.223
0.324

these macroinvertebrates helps to form galleries and biopores, which

0.156

0.088
0.065

favors the passage of air and water infiltration. In a study focused on the
K

physical and hydraulic properties of the soil in these same experimental

− 0.022

− 0.041
− 0.047

areas, da Luz et al. [68] found lower macroporosity in the 10–20 cm

0.220
0.009

0.085
0.153
0.031

layer in the ratoon sugarcane area, where g the lowest density of mac­
S

rofauna was found. However, in both soil types, the total porosity was
not altered due to land conversion from PA to sugarcane. The pedo­
− 0.032
0.076
0.113

0.100
0.062
0.139
0.067
0.088

turbation caused by these organisms aids in the entry of organic matter

P

into the subsurface, increasing mineral nutrients and the area for root
ion exchange of plants and mixing organic matter in the upper layers of
0.394
0.387
0.280

0.339
0.399
0.311
0.348
0.125

the soil. Specific organisms such as earthworms can alter soil structure
OM

and modify microbial communities, as well as make organo-mineral

associations in their gut through soil ingestion, resulting in organic
− 0.042

− 0.070

− 0.139
− 0.134
− 0.141
0.138

0.171

0.078

carbon mineralization [69]. Thus, soil fertility may be favored by

pH

biodiversity [8,70] as observed in the correlations of total density or

specific groups with soil macronutrients (Table 9). However, the inverse
Shannon’s diversity index

may be true, where more fertile soil becomes the best environment for
these macroinvertebrates to live in. Epigeic macrofauna responded more
strongly to land-use change than edaphic macrofauna, proving to be
more sensitive to soil management. The impact is amplified in more
Oligochaeta

intensified systems, such as sugarcane cultivation.

Abundance

Formicidae
Coleoptera

Diplopoda
Chilopoda
Aranae
Table 9

11
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

5. Conclusion [10] E. Barrios, Soil biota, ecosystem services and land productivity, Ecol. Econ. 64
(2007) 269–285, https://doi.org/10.1016/J.ECOLECON.2007.03.004.
[11] P. Lavelle, E. Barros, E. Blanchart, G. Brown, T. Desjardins, L. Mariani, J.-P. Rossi,
This study showed that the expansion of sugarcane over pasture SOM management in the tropics: why feeding the soil macrofauna? Manag. Org.
areas harms the edaphic and epigeic macrofauna over the years. The Matter Trop. Soils Scope Limitations. 61 (2001) 53–61, https://doi.org/10.1007/
epigeic macrofauna indicated a greater sensitivity to disturbances such 978-94-017-2172-1_6.
[12] L. Nazareth Silva, A. Alves do Amaral, Amostragem da mesofauna e macrofauna de
as those caused by land use change compared to edaphic macrofauna. solo com armadilha de queda, Rev. Verde Agroecol. Desenvolv. Sustent. 8 (2013)
The abundance and diversity of macrofauna exhibited a positive corre­ 15. ISSN-e 1981-8203, Vol. 8, No. 5, 2013 (Ejemplar Dedic. a EDIÇÃO Espec. htt
lation with soil organic matter, microbial biomass carbon and nitrogen, ps://dialnet.unirioja.es/servlet/articulo?codigo=7404592&info=resumen&idiom
a=ENG (accessed June 2, 2023)
macroporosity, total porosity, and a negative correlation with soil den­ [13] V.O. Coelho, A.R. Neto, A.C.B.M. Anhê, S.S. de Lima, D.M. da S. Vieira, A. Loss, J.L.
sity. These findings reinforce the need for management strategies that R. Torres, Soil macrofauna as bioindicator of soil quality in different management
prioritize the maintenance of the soil fauna. Future studies should systems, Res. Soc. Dev. 10 (2021), e54210616118, https://doi.org/10.33448/RSD-
V10I6.16118.
attempt to consider management strategies that promote soil biodiver­ [14] D. Lemessa, P.A. Hambäck, K. Hylander, The effect of local and landscape level
sity, such as straw maintenance, as well as the transition from the con­ land-use composition on predatory arthropods in a tropical agricultural landscape,
ventional tillage system to minimum or no tillage, traffic control and the Landsc. Ecol. 30 (2015) 167–180, https://doi.org/10.1007/S10980-014-0115-Y/
FIGURES/3.
introduction of cover crops in the replanting of sugarcane fields. [15] R. Marichal, M. Grimaldi, M.A. Feijoo, J. Oszwald, C. Praxedes, D.H. Ruiz Cobo,
M. del Pilar Hurtado, T. Desjardins, M.L. da Silva Junior, L.G. da Silva Costa, I.
S. Miranda, M.N. Delgado Oliveira, G.G. Brown, S. Tsélouiko, M.B. Martins,
Declaration of competing interest T. Decaëns, E. Velasquez, P. Lavelle, Soil macroinvertebrate communities and
ecosystem services in deforested landscapes of Amazonia, Appl. Soil Ecol. 83
(2014) 177–185, https://doi.org/10.1016/J.APSOIL.2014.05.006.
The authors declare that they have no known competing financial [16] W.L.F. de Vasconcelos, D. de M. Rodrigues, R.O.C. Silva, S.S. Alfaia, Diversity and
interests or personal relationships that could have appeared to influence abundance of soil macrofauna in three land use systems in Eastern Amazonia, Rev.
the work reported in this paper. Bras. Cienc. Do Solo. 44 (2020) 1–16, https://doi.org/10.36783/
18069657RBCS20190136.
[17] R.R. de L. Abreu, S.S. de Lima, N.C. De Rodrigues Oliveira, L.F.C. Leite, Fauna
Data availability edáfica sob diferentes níveis de palhada em cultivo de cana-de-açúcar, Pesqui,
Agropecuária Trop. 44 (2014) 409–416, https://doi.org/10.1590/S1983-
40632014000400002.
Data will be made available on request. [18] A.L.C. Franco, M.L.C. Bartz, M.R. Cherubin, D. Baretta, C.E.P. Cerri, B.J. Feigl, D.
H. Wall, C.A. Davies, C.C. Cerri, Loss of soil (macro)fauna due to the expansion of
Brazilian sugarcane acreage, Sci. Total Environ. (2016) 563–564, https://doi.org/
Acknowledgment
10.1016/J.SCITOTENV.2016.04.116, 160–168.
[19] L.M.S. Menandro, L.O. de Moraes, C.D. Borges, M.R. Cherubin, G.A. Castioni, J.L.
This research was financed in part by the Coordination for the N. Carvalho, Soil macrofauna responses to sugarcane straw removal for bioenergy
Improvement of Higher Education Personnel – Brazil (CAPES) – Finance production, Bioenergy Res 12 (2019) 944–957, https://doi.org/10.1007/S12155-
019-10053-2/FIGURES/5.
Code 001 and by São Paulo Research Foundation (Process #2018/ [20] J. Goldemberg, F.F.C. Mello, C.E.P. Cerri, C.A. Davies, C.C. Cerri, Meeting the
09845-7 and #2019/16764-6). Maurício R. Cherubin thanks National global demand for biofuels in 2021 through sustainable land use change policy,
Council for Scientific and Technological Development recognition by Energy Pol. 69 (2014) 14–18, https://doi.org/10.1016/J.ENPOL.2014.02.008.
[21] de Abastecimento Conab - Companhia Nacional, de Cana-de-Açúcar Safra
the Research Productivity Fellowship (311787/2021-5). Brasileira. https://www.conab.gov.br/info-agro/safras/cana, 2023 accessed June
2, 2023).
[22] Sindipeças e Abipeças, Relatório da Frota Circulante 2022. https://www.sindipeca
Appendix A. Supplementary data
s.org.br/sindinews/Economia/2022/RelatorioFrotaCirculante_2022.pdf, 2022
(accessed June 2, 2023).
Supplementary data to this article can be found online at https://doi. [23] Projeto MapBiomas, Coleção 7 da Série Anual de Mapas de Uso e Cobertura da
org/10.1016/j.ejsobi.2023.103514. Terra do Brasil. https://storage.googleapis.com/mapbiomas-public/brasil/collec
tion-7/lclu/coverage/brasil_coverage_2021.tif, 2023 (accessed June 2, 2023).
[24] M.B. Dias-Filho, Degradação de pastagens: processos, causas e estratégias de
References recuperação, 2011.
[25] M.M.C. Bustamante, C.A. Nobre, R. Smeraldi, A.P.D. Aguiar, L.G. Barioni, L.
G. Ferreira, K. Longo, P. May, A.S. Pinto, J.P.H.B. Ometto, Estimating greenhouse
[1] T. Decaëns, J.J. Jiménez, C. Gioia, G.J. Measey, P. Lavelle, The values of soil
gas emissions from cattle raising in Brazil, Clim. Change 115 (2012) 559–577,
animals for conservation biology, Eur. J. Soil Biol. 42 (2006) S23–S38, https://doi.
https://doi.org/10.1007/S10584-012-0443-3/TABLES/8.
org/10.1016/j.ejsobi.2006.07.001.
[26] B.B.N. Strassburg, A.E. Latawiec, L.G. Barioni, C.A. Nobre, V.P. da Silva, J.
[2] R.D. Bardgett, W.H. Van Der Putten, Belowground biodiversity and ecosystem
F. Valentim, M. Vianna, E.D. Assad, When enough should be enough: improving
functioning, Nature 515 (2014) 505–511, https://doi.org/10.1038/nature13855,
the use of current agricultural lands could meet production demands and spare
2014 5157528.
natural habitats in Brazil, Global Environ. Change 28 (2014) 84–97, https://doi.
[3] E.M. Bach, K.S. Ramirez, T.D. Fraser, D.H. Wall, Soil biodiversity integrates
org/10.1016/J.GLOENVCHA.2014.06.001.
solutions for a sustainable future, Sustain. Times 12 (2020) 2662, https://doi.org/
[27] M. Adami, B.F.T. Rudorff, R.M. Freitas, D.A. Aguiar, L.M. Sugawara, M.P. Mello,
10.3390/SU12072662.
Remote sensing time series to evaluate direct land use change of recent expanded
[4] E.H. Duran-Bautista, Y.K. Angel-Sanchez, M.F. Bermúdez, J.C. Suárez, Agroforestry
sugarcane crop in Brazil, Sustain. Times 4 (2012) 574–585, https://doi.org/
systems generate changes in soil macrofauna and soil physical quality relationship
10.3390/SU4040574.
in the northwestern Colombian Amazon, Agrofor. Syst. 97 (2023) 927–938,
[28] M.R. Cherubin, D.L. Karlen, C.E.P. Cerri, A.L.C. Franco, C.A. Tormena, C.A. Davies,
https://doi.org/10.1007/S10457-023-00838-Y/FIGURES/5.
C.C. Cerri, Soil quality indexing strategies for evaluating sugarcane expansion in
[5] P. Lavelle, T. Decaëns, M. Aubert, S. Barot, M. Blouin, F. Bureau, P. Margerie,
Brazil, PLoS One 11 (2016), e0150860, https://doi.org/10.1371/JOURNAL.
P. Mora, J.P. Rossi, Soil invertebrates and ecosystem services, Eur. J. Soil Biol. 42
PONE.0150860.
(2006) S3–S15, https://doi.org/10.1016/J.EJSOBI.2006.10.002.
[29] D.M.S. Oliveira, M.R. Cherubin, A.L.C. Franco, A.S. Santos, J.G. Gelain, N.M.
[6] M. Delgado-Baquerizo, A.M. Oliverio, T.E. Brewer, A. Benavent-González, D.
S. Dias, T.R. Diniz, A.N. Almeida, B.J. Feigl, C.A. Davies, K. Paustian, D.L. Karlen,
J. Eldridge, R.D. Bardgett, F.T. Maestre, B.K. Singh, N. Fierer, A global atlas of the
P. Smith, C.C. Cerri, C.E.P. Cerri, Is the expansion of sugarcane over pasturelands a
dominant bacteria found in soil, Science 359 (2018) 320–325, https://doi.org/
sustainable strategy for Brazil’s bioenergy industry? Renew. Sustain. Energy Rev.
10.1126/SCIENCE.AAP9516/SUPPL_FILE/AAP9516_TABLE_S1_V2.XLSX.
102 (2019) 346–355, https://doi.org/10.1016/J.RSER.2018.12.012.
[7] A.L.C. Franco, M.R. Cherubin, C.E.P. Cerri, J. Six, D.H. Wall, C.C. Cerri, Linking soil
[30] B.S. Vanolli, L.P. Canisares, A.L.C. Franco, J.H.C. Delabie, C.E.P. Cerri, M.
engineers, structural stability, and organic matter allocation to unravel soil carbon
R. Cherubin, Epigeic fauna (with emphasis on ant community) response to land-use
responses to land-use change, Soil Biol. Biochem. 150 (2020), 107998, https://doi.
change for sugarcane expansion in Brazil, Acta Oecol. 110 (2021), 103702, https://
org/10.1016/J.SOILBIO.2020.107998.
doi.org/10.1016/J.ACTAO.2021.103702.
[8] D. Baretta, J. Santos, J.C. Segat, E.V. Geremia, Fauna edáfica e qualidade do solo,
[31] J. Landgraf, D. Tetzlaff, S. Wu, J. Freymüller, C. Soulsby, Using stable water
Tópicos Em Ciência Do Solo, 2011, pp. 119–170. https://www.researchgate.net/pu
isotopes to understand ecohydrological partitioning under contrasting land uses in
blication/267333227 (accessed June 2, 2023).
a drought-sensitive rural, lowland catchment, Hydrol. Process. 36 (2022), e14779,
[9] A. Lehmann, W. Zheng, M.C. Rillig, Soil biota contributions to soil aggregation,
https://doi.org/10.1002/HYP.14779.
Nat. Ecol. Evol. 112 (2017) 1828–1835, https://doi.org/10.1038/s41559-017-
0344-y, 1 (2017).

12
B.S. Vanolli et al. European Journal of Soil Biology 117 (2023) 103514

[32] M.M.C. Bustamante, F.J.S. Calaça, V.T. Pompermaier, M.R.S.S. da Silva, R. Silveira, [53] C. Pelosi, S. Barot, Y. Capowiez, M. Hedde, F. Vandenbulcke, Pesticides and
Effects of Land Use Changes on Soil Biodiversity Conservation, 2023, pp. 125–143, earthworms. A review, Agron. Sustain. Dev. 34 (2014) 199–228, https://doi.org/
https://doi.org/10.1007/978-3-031-29853-0_7. 10.1007/S13593-013-0151-Z/FIGURES/4.
[33] T.W. Culliney, Role of arthropods in maintaining soil fertility, Agriculture 3 (2013) [54] C.I. Argañaraz, G.D. Rubio, M. Rubio, F. Castellarini, Ground-dwelling spiders in
629–659, https://doi.org/10.3390/AGRICULTURE3040629. agroecosystems of the Dry Chaco: a rapid assessment of community shifts in
[34] S. Soliveres, F. Van Der Plas, P. Manning, D. Prati, M.M. Gossner, S.C. Renner, response to land use changes, Biodiversity (2020), https://doi.org/10.1080/
F. Alt, H. Arndt, V. Baumgartner, J. Binkenstein, K. Birkhofer, S. Blaser, 14888386.2020.1831605/SUPPL_FILE/TBID_A_1831605_SM0941.DOCX.
N. Blüthgen, S. Boch, S. Böhm, C. Börschig, F. Buscot, T. Diekötter, J. Heinze, [55] S.G. Zulu, N.M. Motsa, N.J. Sithole, L.S. Magwaza, K. Ncama, Soil macrofauna
N. Hölzel, K. Jung, V.H. Klaus, T. Kleinebecker, S. Klemmer, J. Krauss, M. Lange, E. abundance and taxonomic richness under long-term No-till conservation
K. Morris, J. Müller, Y. Oelmann, J. Overmann, E. Pašalić, M.C. Rillig, H. agriculture in a semi-arid environment of South Africa, Agronomy 12 (2022) 722,
M. Schaefer, M. Schloter, B. Schmitt, I. Schöning, M. Schrumpf, J. Sikorski, S. https://doi.org/10.3390/AGRONOMY12030722.
A. Socher, E.F. Solly, I. Sonnemann, E. Sorkau, J. Steckel, I. Steffan-Dewenter, [56] J.H.C. Delabie, R. Céréghino, S. Groc, A. Dejean, M. Gibernau, B. Corbara,
B. Stempfhuber, M. Tschapka, M. Türke, P.C. Venter, C.N. Weiner, W.W. Weisser, A. Dejean, Ants as biological indicators of Wayana Amerindian land use in French
M. Werner, C. Westphal, W. Wilcke, V. Wolters, T. Wubet, S. Wurst, M. Fischer, Guiana, C. R. Biol. 332 (2009) 673–684, https://doi.org/10.1016/J.
E. Allan, Biodiversity at multiple trophic levels is needed for ecosystem CRVI.2009.01.006.
multifunctionality, Nature 536 (2016) 456–459, https://doi.org/10.1038/ [57] N.L. Schon, A.D. Mackay, R.A. Gray, M.B. Dodd, C. van Koten, Quantifying dung
NATURE19092. carbon incorporation by earthworms in pasture soils, Eur. J. Soil Sci. 66 (2015)
[35] C.A. Alvares, J.L. Stape, P.C. Sentelhas, J.L. De Moraes Gonçalves, G. Sparovek, 348–358, https://doi.org/10.1111/EJSS.12217.
Köppen’s climate classification map for Brazil, Meteorol. Z. 22 (2013) 711–728, [58] M.P. Rodríguez, A. Domínguez, M.M. Ferroni, L.G. Wall, J.C. Bedano, The
https://doi.org/10.1127/0941-2948/2013/0507. diversification and intensification of crop rotations under No-till promote
[36] K. Sawada, Y. Inagaki, K. Toyota, T. Kosaki, S. Funakawa, World Reference Base for earthworm abundance and biomass, Agronomy 10 (2020) 919, https://doi.org/
Soil Resources, International soil classification system for naming soils and creating 10.3390/AGRONOMY10070919.
legends for soil maps, (No Title) 83 (2014) 27–33, https://doi.org/10.1016/J. [59] H. Nadolny, A. Santos, W. Demetrio, T. Ferreira, L. dos S. Maia, A.C. Conrado,
EJSOBI.2017.10.002, 2014. M. Bartz, M. Garrastazu, E. da Silva, P. Lavelle, D. Baretta, A. Pasini, F. Vezzani, J.
[37] USDA-Natural Resources Conservation Service, Keys to Soil Taxonomy, twelfth ed., P. Sousa, L. Cunha, J. Mathieu, J. Römbke, G. Brown, Recommendations for
2014. Washington, DC. assessing earthworm populations in Brazilian ecosystems, Pesqui. Agropecuária
[38] J.M. Anderson, J.S.I. Ingram, Tropical soil biology and fertility: a handbook of Bras. 55 (2020), e01006, https://doi.org/10.1590/S1678-3921.PAB2020.
methods, J. Ecol. 78 (1990) 547, https://doi.org/10.2307/2261129. V55.01006.
[39] A.R. Moldenke, Arthropods, methods soil anal. Part 2 Microbiol, Biochem. Prop. [60] N. Bottinelli, P. Jouquet, Y. Capowiez, P. Podwojewski, M. Grimaldi, X. Peng, Why
(2018) 517–542, https://doi.org/10.2136/SSSABOOKSER5.2.C24. is the influence of soil macrofauna on soil structure only considered by soil
[40] Z.I. Antoniolli, P.C. Conceição, V. Böck, O. Port, D.M. da Silva, R.F. da Silva, ecologists? Soil Tillage Res. 146 (2015) 118–124, https://doi.org/10.1016/J.
Método alternativo para estudar a fauna do solo, Ciência Florest. 16 (2006) STILL.2014.01.007.
407–417, https://doi.org/10.5902/198050981922. [61] L. Brussaard, P.C. de Ruiter, G.G. Brown, Soil biodiversity for agricultural
[41] G.P. Sparling, A.W. West, A direct extraction method to estimate soil microbial C: sustainability, Agric. Ecosyst. Environ. 121 (2007) 233–244, https://doi.org/
calibration in situ using microbial respiration and 14C labelled cells, Soil Biol. 10.1016/J.AGEE.2006.12.013.
Biochem. 20 (1988) 337–343, https://doi.org/10.1016/0038-0717(88)90014-4. [62] P. Lavelle, N. Rodríguez, O. Arguello, J. Bernal, C. Botero, P. Chaparro, Y. Gómez,
[42] E.D. Vance, P.C. Brookes, D.S. Jenkinson, An extraction method for measuring soil A. Gutiérrez, M. del P. Hurtado, S. Loaiza, S.X. Pullido, E. Rodríguez, C. Sanabria,
microbial biomass C, Soil Biol. Biochem. 19 (1987) 703–707, https://doi.org/ E. Velásquez, S.J. Fonte, Soil ecosystem services and land use in the rapidly
10.1016/0038-0717(87)90052-6. changing Orinoco River Basin of Colombia, Agric. Ecosyst. Environ. 185 (2014)
[43] B. van, J.C. de Raij, Andrade, H. Cantarella, J.A. Quaggio, Análise química para 106–117, https://doi.org/10.1016/J.AGEE.2013.12.020.
avaliação da fertilidade de solos tropicais, Instituto Agronômico, Campinas, 2001. [63] E. Vazquez, N. Teutscherova, B. Lojka, J. Arango, M. Pulleman, Pasture
www.iac.br (accessed June 3, 2023). diversification affects soil macrofauna and soil biophysical properties in tropical
[44] R.Q. Cavalcanti, M.M. Rolim, R.P. de Lima, U.E. Tavares, E.M.R. Pedrosa, M. (silvo)pastoral systems, Agric. Ecosyst. Environ. 302 (2020), 107083, https://doi.
R. Cherubin, Soil physical changes induced by sugarcane cultivation in the Atlantic org/10.1016/J.AGEE.2020.107083.
Forest biome, northeastern Brazil, Geoderma 370 (2020), 114353, https://doi.org/ [64] S. Filoso, J.B. Do Carmo, S.F. Mardegan, S.R.M. Lins, T.F. Gomes, L.A. Martinelli,
10.1016/J.GEODERMA.2020.114353. Reassessing the environmental impacts of sugarcane ethanol production in Brazil
[45] S. Nakagawa, H. Schielzeth, A general and simple method for obtaining R2 from to help meet sustainability goals, Renew. Sustain. Energy Rev. 52 (2015)
generalized linear mixed-effects models, Methods Ecol. Evol. 4 (2013) 133–142, 1847–1856, https://doi.org/10.1016/J.RSER.2015.08.012.
https://doi.org/10.1111/J.2041-210X.2012.00261.X. [65] W. Demetrio, K.M.V. Cavalieri-Polizeli, R.M.L. Guimarães, S. de A. Ferreira, L.
[46] J. Pinheiro, D. Bates, S. DebRoy, D. Sarkar, Linear and nonlinear mixed effects M. Parron, G.G. Brown, W. Demetrio, K.M.V. Cavalieri-Polizeli, R.M.L. Guimarães,
models, R Packag. Version. 3, 1–117, http://www.academia.edu/download/3490 S. de A. Ferreira, L.M. Parron, G.G. Brown, Macrofauna communities and their
9952/5-Modelos_lineales_mixtos_en_R.pdf, 2009 (accessed June 2, 2023). relationship with soil structural quality in different land use systems, Soil Res. 60
[47] J.S. Lefcheck, piecewiseSEM: Piecewise structural equation modelling in r for (2022) 648–660, https://doi.org/10.1071/SR21157.
ecology, evolution, and systematics, Methods Ecol. Evol. 7 (2016) 573–579, [66] Y. Peng, M. Holmstrup, I.K. Schmidt, A. De Schrijver, S. Schelfhout, P. Heděnec,
https://doi.org/10.1111/2041-210X.12512. H. Zheng, L.R. Bachega, K. Yue, L. Vesterdal, Litter quality, mycorrhizal
[48] J. Oksanen, F. Blanchet, R. Kindt, Vegan: community ecology package, in: association, and soil properties regulate effects of tree species on the soil fauna
R Package: 2.3, World Agroforestry, 2016. https://apps.worldagroforestry.org/p community, Geoderma 407 (2022), 115570, https://doi.org/10.1016/J.
ublication/vegan-community-ecology-package-r-package-23 (accessed June 2, GEODERMA.2021.115570.
2023). [67] O.P. Olayemi, J.P. Schneekloth, M.D. Wallenstein, P. Trivedi, F.J. Calderón,
[49] H. Wickham, Ggplot: using the grammar of graphics with R, New York, NY, USA. J. Corwin, S.J. Fonte, Soil macrofauna and microbial communities respond in
https://scholar.google.com/scholar?hl=pt-BR&as_sdt=0%2C5&q=wickham+ similar ways to management drivers in an irrigated maize system of Colorado
2009+ggplot&oq=Wickham%2C+2009+, 2009 (accessed June 3, 2023). (USA), Appl. Soil Ecol. 178 (2022), 104562, https://doi.org/10.1016/J.
[50] D. Baretta, M.L.C. Bartz, I. Fachini, R. Anselmi, T. Zortéa, C.R.D.M. Baretta, Soil APSOIL.2022.104562.
fauna and its relation with environmental variables in soil management systems, [68] F.B. da Luz, M.L. Carvalho, D.A. de Borba, B.E. Schiebelbein, R.P. de Lima, M.
Rev. Cienc. Agron. 45 (2014) 871–879, https://doi.org/10.1590/S1806- R. Cherubin, Linking soil water changes to soil physical quality in sugarcane
66902014000500002. expansion areas in Brazil, Water 12 (2020) 3156, https://doi.org/10.3390/
[51] D.M.S. Esquivel, E. Wajnberg, L.C. de Menezes e Souza, D. Acosta-Avalos, M. W12113156.
B. Pinho, A.Y. Harada, Magnetic material diversity in Brazilian ants: displacement [69] J. Barthod, M.F. Dignac, G. Le Mer, N. Bottinelli, F. Watteau, I. Kögel-Knabner,
behaviour and environmental adaptability, Eur. Biophys. J. 48 (2019) 161–171, C. Rumpel, How do earthworms affect organic matter decomposition in the
https://doi.org/10.1007/S00249-018-1343-X/FIGURES/4. presence of clay-sized minerals? Soil Biol. Biochem. 143 (2020), 107730 https://
[52] C.J.S. Fox, The effects of five herbicides on the numbers of certain invertebrate doi.org/10.1016/J.SOILBIO.2020.107730.
animals in grassland soil, 44, 2011, pp. 405–409, https://doi.org/10.4141/ [70] R. Lal, Effects of macrofauna on soil properties in tropical ecosystems, Agric.
CJPS64-080. Ecosyst. Environ. 24 (1988) 101–116, https://doi.org/10.1016/0167-8809(88)
90059-X.

13