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\begin{document}

\title{Influence of different tree species on autotrophic and heterotrophic
soil respiration in a mined area under reclamation}



\author[1]{Fernanda Valente}%
\author[1]{Marllon Castro}%
\author[1]{Lucas Gomes}%
\author[1]{Julio Cesar Neves}%
\author[1]{IVO Silva}%
\author[1]{Teógenes de Oliveira}%
\affil[1]{Federal University of Viçosa}%


\vspace{-1em}



  
  \date{June 18, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Planting trees is one of the most effective activities in recovering
soil organic carbon (SOC) stocks of degraded areas, but we still lack
information on how different tree species can influence soil
respiration, one of the main sources of dioxide carbon (CO2) to the
atmosphere. This study aimed to explore the influence of different
forest species on the autotrophic and heterotrophic components of the
total soil respiration in a bauxite mining area under reclamation. We
analysed the soil CO2 efflux under five treatments: i) monoculture of
clonal Eucalyptus; ii) monoculture of Anadenanthera peregrina (L.); iii)
a mixed plantation of 16 native forest species (Nat); iv) a mined area
without vegetation cover; and v) a natural forest cover. This design
allowed exploring the soil CO2 dynamics in a gradient of recovery, from
a degraded area to natural vegetation. Additionally, we measured soil
temperature, moisture and soil characteristics. Soil CO2 efflux
increased with increasing forest species cover in the rainy months.
There was no significant change in CO2 efflux among the tree species.
Heterotrophic soil respiration contributed to 64\% of total soil CO2
efflux and was associated with litter decomposition. Amongst the abiotic
variables, increases in soil moisture had the most influence on CO2
efflux. Therefore, these results help to understand the factors that
underpin the loss of SOC and can orient management practices to improve
soil organic matter and restore soil quality in degraded areas.%
\end{abstract}%



\sloppy


\textbf{Influence of different tree species on autotrophic and
heterotrophic soil respiration in a mined area under reclamation}

F.D.A.Valente\textsuperscript{*}, M.F.Castro, L.C. Gomes, J.C.L.Neves,
I.R. Silva, T.S. Oliveira

Departamento de Solos, Universidade Federal de Vi\selectlanguage{ngerman}çosa, Viçosa MG
36570-900, Brasil.

\emph{fdalmeidavalente@gmail.com; marllon.castro22007@gmail.com;
lucascarvalhogomes15@hotmail.com; julio\_n2003@yahoo.com.br;
ivosilva@ufv.br; teo@ufv.br}

*Correspondence:

Fernanda Valente,\emph{fdalmeidavalente@gmail.com}

Department of Soil, Universidade Federal de Viçosa, Viçosa MG 36570-900,
Brasil.

\textbf{Abstract}

Planting trees is one of the most effective activities in recovering
soil organic carbon (SOC) stocks of degraded areas, but we still lack
information on how different tree species can influence soil
respiration, one of the main sources of dioxide carbon
(CO\textsubscript{2}) to the atmosphere. This study aimed to explore the
influence of different forest species on the autotrophic and
heterotrophic components of the total soil respiration in a bauxite
mining area under reclamation. We analysed the soil
CO\textsubscript{2}efflux under five treatments: i) monoculture of
clonal Eucalyptus; ii) monoculture of \emph{Anadenanthera peregrina}
(L.); iii) a mixed plantation of 16 native forest species (Nat); iv) a
mined area without vegetation cover; and v) a natural forest cover. This
design allowed exploring the soil CO\textsubscript{2} dynamics in a
gradient of recovery, from a degraded area to natural vegetation.
Additionally, we measured soil temperature, moisture and soil
characteristics. Soil CO\textsubscript{2} efflux increased with
increasing forest species cover in the rainy months. There was no
significant change in CO\textsubscript{2} efflux among the tree species.
Heterotrophic soil respiration contributed to 64\% of total soil
CO\textsubscript{2} efflux and was associated with litter decomposition.
Amongst the abiotic variables, increases in soil moisture had the most
influence on CO\textsubscript{2} efflux. Therefore, these results help
to understand the factors that underpin the loss of SOC and can orient
management practices to improve soil organic matter and restore soil
quality in degraded areas.

\textbf{Keywords:} Land reclamation; bauxite, CO\textsubscript{2} flux,
soil organic matter, Atlantic rainforest

\textbf{Introduction}

Soil respiration is one of the main sources of terrestrial dioxide
carbon (CO\textsubscript{2}), which increase in the atmosphere has been
associated with global warming (Köchy \emph{et al} ., 2015; Shrestha \&
Lal, 2006). Soil is the largest C reservoir in terrestrial ecosystems,
containing about twice as much C as the atmosphere (Kuzyakov \& Cheng,
2001) and three times as much as the vegetation (Granier \emph{et al} .,
2000). Soil respiration is a combination of root respiration, root
associated microbes and mycorrhizal association (autotrophic
respiration) and the respiration of microorganisms during the
decomposition process of both soil organic matter and litter
(heterotrophic respiration) (Fontaine \emph{et al.} , 2003;
Hanson\emph{et al} ., 2000; Millard \emph{et al} ., 2010; Bujalský
\emph{et al.} , 2014). However, the magnitude of the temporal variations
and the biotic and abiotic factors that influence the efflux of
CO\textsubscript{2} from the Reclamaid Mine Degraded Land (RMDL) in
process of recovery are still not well understood. Understanding the
factors that underline soil CO\textsubscript{2} flux can orient
management practices to improve soil organic matter (SOM) and restore
soil quality in degraded areas. Mining activities promote drastic
changes in the landscape, where the total removal of vegetation cover
and topsoil results in intense soil disturbances, which can lead to a
decrease of SOM due to the increase in CO\textsubscript{2} efflux
(Lorenz \& Lal, 2007; Shrestha \& Lal, 2006). The recovery process for
these soils aims to restore the organic matter content with the
restitution of vegetation cover that can provide carbon assimilation
through photosynthesis (Shrestha \& Lal, 2006). The carbon stored in the
shoots and roots is important in reactivating nutrient cycling,
increasing soil carbon stocks.

Soil CO\textsubscript{2} efflux is a sensitive indicator of soil
metabolic activity and an important tool to investigate the SOM dynamics
(Kuzyakov \& Cheng, 2001; Haney et al. 2008). Increase SOM and nutrient
cycling are major objectives to recovery soil in degraded areas and the
analysis of soil CO\textsubscript{2} efflux can give important insights
about the rehabilitation process (Subke \& Bahm, 2010). The rates of
soil CO\textsubscript{2} efflux in mining areas under recovery are
associated with the soil organic carbon contents, nutrient availability
and environmental variables (Ahirwal et al., 2017, Ahirwal \& Maite,
2018). Mukhopadhyay \&Maite (2014) compared a mined area in recovery
with grassland and natural forest and found that the highest values of
soil CO\textsubscript{2} in the grassland were associated with the
higher levels of organic matter, microbiological activity and root
biomass. Temperature is an important driver of soil
CO\textsubscript{2}efflux, and Bujalský \emph{et al.} (2014) found that
soil respiration was associated with temperature and higher contents of
organic carbon and root biomass comparing recovered mined area and
natural regeneration. Although few studies report the influence of tree
species on soil respiration (Yohannes et al., 2010), there is a lack of
studies that explore the influence of tree species on the components of
soil respiration in mined areas under reclamation.

The study of CO\textsubscript{2} efflux under field conditions can
generate important information about changes in land use and management,
however, there is a large gap in such studies for forest ecosystems in
tropical regions (Wei \emph{et al.} , 2010), especially in mining areas
in the process of recovery. The main hypothesis of this study was that
soil respiration in recovering mined areas is not influenced by the
composition and density of the tree species used, but they present a
strong relation with soil moisture and temperature. Therefore, this
study aimed to determine (i) the CO\textsubscript{2} efflux during the
dry and rainy months in an area of bauxite mining revegetated with
different forest species, (ii) the contribution of heterotrophic and
autotrophic respiration to total soil respiration, and (iii) the
influence of biotic and abiotic variables on soil
CO\textsubscript{2}efflux.

\textbf{Material and Methods}

\emph{Study area and experimental design}

The study was carried on a bauxite mined area at 780 m altitude in São
Sebastião da Vargem Alegre (21°1'58'' S and 42°35'8'' W), Minas Gerais
state, Brazil. The climate predominant is Cwa (Köppen), with hot and
rainy summers and a well-defined dry season. The annual precipitation is
1,287 mm and temperature average of 20.3ºC (INMET, 2016). The domain
soils are Oxisols, which is depth weathered and present low nutrients
availability (Santos et al., 2013; Soil Survey Staff, 2014). Before
started the mining, the soil surface layer (0.00-0.20 m) was removed and
stored next to the area for one year. During the topographic
reconfiguration of the mined area, the soil stored was used to cover the
areas followed by a decompaction process using a subsoiler at a depth of
0.60 m.

The experiment was installed in March 2011 using a randomized block
design with split plots and three replicates. The plots (40 × 18 m)
comprised the following forest cover:\emph{Anadenanthera peregrina} (L.)
Speg (Ap); clonal \emph{Eucalyptus}(a hybrid from a cross between
\emph{Eucalyptus urophylla} and\emph{Eucalyptus grandis} - clone
AEC144\textsuperscript{®}) (Euc) and a mixed plantation (Nat) consisting
of 16 native forest species from the region. In addition, we installed
plots in a native forest at the second stage of regeneration (Woodland)
and in an post-mined area kept without vegetation (Ncov).

Table 1 -- Trees species and phenological groups of the mixed plantation
treatment.\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
Species & Phenological group\tabularnewline
\midrule
\endhead
\emph{Anadenanthera peregrina} & Pioneer\tabularnewline
\emph{Ficus insipida} Willd & Pioneer\tabularnewline
\emph{Inga edulis} Mart. & Pioneer\tabularnewline
\emph{Piptadenia gonoacantha} (Mart.) JF Macbr. & Pioneer\tabularnewline
\emph{Enterolobium contortisiliquum} (Vell.) Morong. &
Pioneer\tabularnewline
\emph{Ceiba speciosa} (A. St.-Hil.) Ravenna & Pioneer\tabularnewline
\emph{Sapindus saponaria} L. & Pioneer\tabularnewline
\emph{Pera glabrata} (Schott) Poepp. Ex Baill & Pioneer\tabularnewline
\emph{Trichilia} sp - & Non pioneer\tabularnewline
\emph{Cupania oblongifolia} Mart. - & Non pioneer\tabularnewline
\emph{Apuleia leiocarpa} (Vogel) JF Macbr & Non pioneer\tabularnewline
\emph{Handroanthus chrysotrichus} (Mart. Ex A. DC.) Mattos & Non
pioneer\tabularnewline
\emph{Hymenaea courbaril} var. \emph{stilbocarpa} (Hayne) YT Lee and
Langenh & Non pioneer\tabularnewline
\emph{Lecythis sp} & Non pioneer\tabularnewline
\emph{Paubrasilia echinata} Lam. & Non pioneer\tabularnewline
\emph{Annona squamosa} L & Non pioneer\tabularnewline
\bottomrule
\end{longtable}

These native species were planted in Quincunx (4 pioneers, with one
climax in the center) at a spacing of 2.0 \selectlanguage{ngerman}× 1.5 m, using seedlings
produced from seeds collected in fragments of Atlantic Forest
(Woodland). For Euc and Ap, the adopted spacing was 3 × 2 m.

\emph{Evaluation of soil CO\textsubscript{2} efflux}

To evaluate the soil CO\textsubscript{2} efflux we installed
chloro-polyvinyl chambers (0.20 m x 0.30 m) in triplicate 42 months
after planting the Eu, Ap and Nat, as well as in the Woodland and NCov.
We installed chambers beneath and outside the litter collectors,
allowing to evaluate the soil CO\textsubscript{2} efflux with and
without the input of litter from the aerial part of Euc, Ap and Nat. We
collected the CO\textsubscript{2} using syringes in the periods of 0,
10, 20 and 40 minutes after closing the chambers. We collected soil
CO\textsubscript{2} every two months between September 2014 and July
2015 and we analysed it in a cavity resonance spectrometer (CRDS -
cavity ring-down spectroscopy, G2131-i, Picarro, Sunnyvale, CA). During
the soil CO\textsubscript{2} efflux measurements, we also assessed soil
temperature with a digital thermometer inserted at a depth of 5 cm, and
soil moisture by the gravimetric method. The CO\textsubscript{2} efflux
was calculated using the equation:

\begin{equation}
Flux=\frac{(Q}{T)}\times M\times\frac{(PV}{TR)}\times\frac{1}{A}\nonumber \\
 \end{equation}

where Flux: CO\textsubscript{2} (mg
m\textsuperscript{-2}h\textsuperscript{-1}); \selectlanguage{greek}Δ\selectlanguage{english}Q/\selectlanguage{greek}Δ\selectlanguage{english}T: the angular
coefficient of the adjusted straight line (ppm/s) obtained by
readjustment of the gas concentrations during the time (T) of
collection; M: the molar mass of CO\textsubscript{2} (g
mol\textsuperscript{-1}); P: internal pressure of the chamber, assumed
to be 1 atmosphere (atm); V: volume of the chamber (L); R: universal gas
constant (0.08205 L atm K\textsuperscript{-1}mol\textsuperscript{-1});
T: soil temperature (K); A: base area of the chamber (m\selectlanguage{ngerman}²).

\emph{Soil CO\textsubscript{2} efflux partitioning}

Aiming to identify the contribution of autotrophic (AR) and
heterotrophic respiration (HR) to the total soil respiration (TR), we
used the partitioning method that was carried in areas with Euc, Ap and
Nat. We also analysed the relative contribution of soil microbiota
respiration under the influence of litter (HR\textsubscript{litter}) and
SOM (HR\textsubscript{SOM}).

\begin{equation}
TR=AR+HR\nonumber \\
 \end{equation}\begin{equation}
AR=\text{TR}_{\text{nolitter}}-\text{TR}_{\text{Ncover}}\nonumber \\
 \end{equation}\begin{equation}
HR=TR-AR\nonumber \\
 \end{equation}\begin{equation}
\text{HR}_{\text{litter}}=\text{TR}_{\text{whithlitter}}-\text{TR}_{\text{nolitter}}\nonumber \\
 \end{equation}\begin{equation}
\text{HR}_{\text{SOM}}=\text{HR}_{\text{total}}-\text{HR}_{\text{litter}}\nonumber \\
 \end{equation}\begin{equation}
HR=\text{HR}_{\text{litter}}-\text{HR}_{\text{SOM}}\nonumber \\
 \end{equation}

Where, TR\textsubscript{nolitter} and TR\textsubscript{withlitter}:
total soil CO\textsubscript{2} efflux in the treatment with the absence
and presence of litter, respectively; TR\textsubscript{Ncover}: total
soil respiration in the minded area without cover

\emph{Soil analysis and root density}

Aiming to identify other variables that may influence the soil
CO\textsubscript{2} efflux, we determined the main soil soil properties
and roots density. Soil samples from the 0-10 layer of each plot, ground
in a mortar and passed through a 60-mesh sieve (0.250 mm), were used to
determine total organic carbon (TC) and total nitrogen (TN). Total
organic carbon was quantified by wet oxidation (YEOMANS; BREMNER, 1988)
and TN was determined by the Kjeldahl method, modified by Tedesco
(1985). In addition, we analysed the soil bulk density (Ds), by the
volumetric ring method; soil particle density (Dp) by the volumetric
balloon method and total porosity (Pr). The microbial biomass carbon
(CMB) and nitrogen (NMB) of the soil were determined in the 0-10 cm
layer only. Samples (\textless{}2 mm) were placed in lidded plastic
flasks, incubated for 10 days at 25\selectlanguage{ngerman}°C, with moisture corresponding to
80\% of the moisture equivalent, in order to re-establish the microbial
community. After incubation, the CMB and NMB content were determined by
irradiation-extraction (ISLAM; WEIL, 1998).

To deternine the roots density, we collected blocks of soil with
dimensions of 20 x 20 x 20 cm in triplicate in all plots. After
collection, the roots were manually separated from the soil, washed and
divided into two classes, with a diameter smaller or larger than 2 mm.
After determining the wet weight, the roots were placed in plastic pots
with 25\% alcohol and stored in a refrigerator for later evaluation. An
Epson XL 10000 scanner, equipped with an additional light unit (TPU),
together the WinRHIZO Pro 2009 software, was used to determine the
following morphological characteristics: the biomass of roots smaller
than 2 mm (BioRSm2), length of roots smaller than 2 mm (LengRSm2),
specific root length (SRL), sectional area of roots smaller than 2 mm
(SARSm2), mean root diameter and volume of roots smaller than 2 mm
(VRSm2). Following these evaluations, the roots were placed in paper
bags and dried in an oven at 60°C to obtain the dry weight. All results
of soil properties and roots area presented in the Appendix 1.

\emph{Statistical analysis}

The data for soil CO\textsubscript{2} efflux were submitted to analysis
of variance (ANOVA) and the mean values compared by Tukey's (10\%). The
influence of biotic and abiotic variables on the
CO\textsubscript{2}efflux was evaluated using multivariate regression
analysis.

\textbf{Results}

\emph{Variations in soil moisture and temperature}

The soil presented the highest moisture content during November 2014,
March and May 2015 for most of the types of cover, while the highest
soil temperatures occurred in September 2014, and January and March 2015
(Fig. 1). Woodland showed the highest soil moisture and NCov the highest
soil temperature for the studied period.

\subsection*{\texorpdfstring{\emph{3.2. Soil
CO\textsubscript{2}efflux}}{3.2. Soil CO2efflux}}

{\label{soil-co2-efflux}}

The five treatments showed significant differences in
CO\textsubscript{2} efflux (p \textless{}0.1) (Fig. 2), with NCov
presenting the lowest soil CO\textsubscript{2} values. Woodland had the
highest values for CO\textsubscript{2} efflux during January and March
2015, while the soil CO\textsubscript{2} efflux in Euc, Ap and Nat did
not vary during the study period. Euc and Nat had a similar soil
CO\textsubscript{2} efflux pattern, with a tendency for higher
CO\textsubscript{2} efflux during November, March and May. The increase
of CO\textsubscript{2} efflux in Euc, Ap and Nat showed high percentage
values compared to Woodland for all measurements, except in May 2015,
when the soil CO\textsubscript{2} efflux presented the lowest
percentages (\textless{} 33\%) (Fig. 2a). In November, the three forest
covers showed the same soil CO\textsubscript{2} efflux compared to the
Woodland.

\subsection*{\texorpdfstring{\emph{Temporal variation in
CO\textsubscript{2}
efflux}}{Temporal variation in CO2 efflux}}

{\label{temporal-variation-in-co2-efflux}}

The highest CO\textsubscript{2} effluxes were recorded in the months of
higher soil moisture (Fig. 3), i.e. November 2014, March and May 2015,
with Woodland presenting the highest and NCov the lowest values.
Although Euc showed a tendency with higher soil
CO\textsubscript{2}efflux during the months of higher soil moisture when
compared to Ap and Nat, there were no significant differences between
the three types of cover (p\textgreater{}0,1). In the driest months
(September 2014, January and July 2015) Woodland, Euc, Ap and Nat showed
no differences for CO\textsubscript{2} efflux, differing only from NCov.

All covers types showed similar soil moisture in the drier months
(September 2014, January and July 2015), except Woodland, which had
higher soil moisture (Fig. 4). In the rainy months (November 2014, March
and May 2015), the lowest soil moisture was found for Euc and the
highest for Woodland. Soil temperature was similar for Euc, Ap and Nat
in the months of lowest soil moisture, while the lowest and the highest
soil temperature were measured for Woodland and NCov respectively. In
the rainy season, the highest soil temperature was recorded for NCov.

\subsection*{\texorpdfstring{\emph{Soil CO\textsubscript{2} efflux
partitioning}}{Soil CO2 efflux partitioning}}

{\label{soil-co2-efflux-partitioning}}

The contributions of AR and HR to soil TR were statically significant
over the months (p \textless{}0.1), with HR presenting the highest
values (Fig. 5), These differences can be seen in November 2014, and
March and May of 2015, when HR contributed more to TR than AR. In
September 2014, and January and July 2015, there was no difference
between the contributions of AR and HR to soil TR. AR and HR did not
differ in the areas of Euc, Ap or Nat.

Grouping the values for AR and HR during the months of highest and
lowest soil moisture, (i.e. in the months of the highest and lowest
precipitation) for the moments before gas collection it was seen that
during the drier months there was no difference between the
contributions of AR and HR to TR, with HR accounting for around 55\% of
TR. However, during the wettest months, HR contributed more to TR
(71\%). The forest plantations did not differ during the dry months
concerning AR and HR, and during the rainy months, differences were only
seen between Ap and Nat for AR (Fig. 6).

\subsection*{\texorpdfstring{\emph{Contribution of litter to
heterotrophic soil
respiration}}{Contribution of litter to heterotrophic soil respiration}}

{\label{contribution-of-litter-to-heterotrophic-soil-respiration}}

The litter contributed significantly more than the SOM to HR for the
cover's types (p \textless{}0.1; Fig. 7). The greatest contribution to
HR by the litter was recorded in November 2014 for the three types of
forest cover. The contribution of litter to HR does not differ between
Euc, Ap and Nat, except for November 2015, when the HR was higher in Euc
than Nat.

\emph{Principal component analysis}

The multivariate model with two principal components (PCA) explained
70.7\% of the variation of the data set: PC1 (60.3\%) and PC2 (10.1\%)
(Fig. 8). The variables TC, CMB and LC together contributed 43.4\%, TN
and NMB 25.9\%, and DRsm and DRgr 19.7\%. From the PCA analysis, we
identified three groups, with NCov and Woodland at the two extremes of
the scatter plot and the other forest types are allocated between in the
middle. In general, soil CO\textsubscript{2} efflux (TR) was positively
correlated with soil moisture (Ms), total TC, TN and CMB.

\textbf{Discussion}

\emph{4.1. Effect of plant cover on soil CO\textsubscript{2} efflux}

Plant cover can highly influence soil CO\textsubscript{2} efflux (Raich
\& Tufekciogul, 2000) and removal of native forests and land use changes
during mining activities accelerate the TC losses by increasing
CO\textsubscript{2} efflux (Lorenz \& Lal, 2007; Polglase \emph{et al}
., 2000; ). Planting trees is one of the most effective activities in
recovering TC stocks of degraded areas (Moghiseh \emph{et al.,} 2013).
The present study identified that CO\textsubscript{2} efflux tends to
increase with the planting of forest cover. Higher diversity in plant
species, together with favorable climate conditions, may result in
abundance and diversity of soil microbiological community (Lange\emph{et
al} ., 2015). Higher microbial activity may affect the decomposition of
tree's residues and SOM, and consequently, the production of soil
CO\textsubscript{2}.

Planting different types of forest cover led to an increase in
CO\textsubscript{2} efflux due to the benefits of increasing SOM. Forest
species favor soil microbiological activity by contributing organic
material from the shoots and roots that contribute to nutrient cycling,
speeding up the ecosystem recovery (Shrestha \& Lal, 2006), and which
may reflect in the increase in soil CO\textsubscript{2} efflux. While
the treatment with no plant covers presented the lower values of
CO\textsubscript{2} efflux, the Woodland showed higher values (Fig. 2).
Soils of mining areas pose a limitation on plant growth, but our results
show that planting forest species is the right way to achieve similar
soil CO\textsubscript{2} efflux compared with the unmined Woodland.

The forest types Euc, Ap and Nat showed higher values for
CO\textsubscript{2} efflux compared to NCov. Different forest covers can
influence the soil chemical and biological properties by the input and
composition of organic material from the trees (litter and roots),
resulting in an increase of TC and soil biological activity. Different
tree species contribute with organic material of different
characteristics (Craine \& Gelderman, 2011; Martin \emph{et al} .,
2009), which may also affect the soil microbiological activity
(Barreto\emph{et al} ., 2008) and the increase of TC. Therefore,
differences in root biomass, soil organic matter content, and the
spatial arrangement of the trees may contribute to soil
CO\textsubscript{2} efflux variations (Katayama \emph{et al} ., 2009;
Gomes \emph{et al} ., 2016).

Optimum soil moisture and temperature conditions combined with higher
values for TC, TN, LC, C-MB, N-MB and root density (Table 1), may
explain the greater values for CO\textsubscript{2} efflux in Woodland
(Figure 3). With favourable conditions of temperature and moisture, soil
microorganisms act more intensely and produce more CO\textsubscript{2}.
In addition, the higher root density in Woodland is associated with the
higher soil CO\textsubscript{2} efflux for the same climate conditions.
Tree roots are responsible for a large flow of C and nutrients in soil,
with respiration accounting for a third or more of the total soil
CO\textsubscript{2} efflux in tropical forests (Högberg \& Read, 2006).
In addition, the amount and quality of available C and photosynthetic
activity also influence soil CO\textsubscript{2} concentrations and
consequently the efflux (Kuzyakov \& Cheng, 2001). Therefore, increasing
the diversity of forest species, promotes in time the development of
soil microorganisms and roots, resulting in higher rates of
CO\textsubscript{2} efflux.

\subsection*{\texorpdfstring{\emph{4.2. Autotrophic and heterotrophic
respiration}}{4.2. Autotrophic and heterotrophic respiration}}

{\label{autotrophic-and-heterotrophic-respiration}}

The contribution of soil heterotrophic respiration to total respiration
in the forest species was on average 55\% during the driest period, and
72\% during the wettest period (Figure 3). The relative contributions of
heterotrophic and autotrophic respiration are specific
context-dependent, since are influenced by local soil temperature and
moisture conditions (Liu \emph{et al.} , 2009; Hanson \emph{et al} .,
2000), and by intrinsic plant factors, such as the photoassimilates
allocation to roots (Epron \emph{et al} ., 2011; Högberg \& Read, 2006).
The Ap forest cover showed the highest values for the relative
contribution of HR (77.4\%) during the rainy season. This result may be
related to the high decomposition rate of the leaflets from this type of
forest cover compared to the others (Gama-Rodrigues \emph{et al.} ,
1997) (Figure 4). Wei \emph{et al} . (2010) analysed a global data of
forest ecosystems and also found increases in HR in rainy seasons. Soil
microbiota is sensitive to soil moisture and may explain the higher HR
contribution of HR to total soil respiration during the rainy season
(Carbone \emph{et al} ., 2011). Variations in AR are more dependent on
plant photosynthetic activity (Gomes \emph{et al} ., 2016), responding
slowly to variations in soil temperature and soil moisture when compared
to HR (Bond-Lamberty \emph{et al} ., 2004; Högberg \emph{et al} ., 2008,
2009).

The specific partitioning of heterotrophic respiration showed that the
soil CO\textsubscript{2} produced originates mainly from the
mineralization of plant residues (Figure 7). Plant residues are
relatively easier to be degraded by microorganisms compared to the SOM,
which is protected by clay-mineral associations and has been passed by
biological degradation. In areas in an initial process of recovery, the
microorganisms have a preference to use the most recent added forms of C
(Novara \emph{et al} ., 2014).

\subsection*{\texorpdfstring{\emph{4.3. Influence of biotic and abiotic
factors on
CO\textsubscript{2}flux}}{4.3. Influence of biotic and abiotic factors on CO2flux}}

{\label{influence-of-biotic-and-abiotic-factors-on-co2-flux}}

The principal component analysis shows that the planted forests are
placed between NCov and Woodland, and follow the same pattern of soil
CO\textsubscript{2} efflux (Figure 2). This indicates that the planted
forests are improving the soil properties comparing with the treatment
with no ground cover and are on the way to the soil quality presented in
the native forest.

Soil CO\textsubscript{2} efflux is a complex process and is influenced
by biotic and abiotic factors. Soil temperature and moisture are the
main abiotic factors that influence these processes (Fenn \emph{et al.}
, 2010; Wu \emph{et al} ., 2010), affecting directly the biotic factors,
such as microorganisms activity and plant cover. An increase in soil
temperature leads to an increase in microorganisms activity
(Atkin\emph{et al.} , 2000) and root respiration (Schindlbacher \emph{et
al} ., 2011), leading to increases in soil CO\textsubscript{2} efflux.
Plant cover with tree species creates a microclimate beneath the canopy
that reduces variations in soil temperature, and therefore their
influence on soil CO\textsubscript{2} efflux (Gomes \emph{et al} .,
2016). However, in the present study, soil temperature did not vary much
during the measurements (Figure 1) and a significative response was not
found (Figures 9 and 10). Soil moisture is a very important factor in
the maintenance and development of microbial activity (Liu \emph{et al}
., 2009). Our results demonstrated that soil moisture was the most
important variable and associated positively with soil
CO\textsubscript{2} efflux. While low values of soil moisture at the end
of the dry season leading to low values of soil
CO\textsubscript{2}efflux (Figure 2), the increase of precipitation in
the rainy season promoted the increase of soil CO2 efflux values. These
fluctuations of soil CO2 efflux are directly linked with microbial
activity during the dry and rainy seasons.

\subsection*{Conclusions}

{\label{conclusions}}

In this study, we found that afforestation increases total
CO\textsubscript{2} efflux in RMDL compared to those with no vegetation
cover.

In afforested RMDL, heterotrophic respiration contributes more to total
soil respiration and litter decomposition is responsible for the highest
CO\textsubscript{2} efflux.

The variation in moisture is the main factor responsible for the soil
CO\textsubscript{2} efflux changes in the types of forest cover studied.

The plantations of Euc, Ap and Nat forest cover were efficient in
recovering the mined soils, with similar CO\textsubscript{2} efflux
values found under the Atlantic Forest remnant.

\textbf{Acknowledgments}

The authors would like to thank the Coordenação de Aperfeiçoamento de
Pessoal de Nível Superior (CAPES) (Grand/awards number: PROEX 1840/2016)
and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
(Grand/awards number: 306950/2013-8) for providing scholarships for the
authors and financial support. The authors are also grateful to
Companhia Brasileira de Alumínio (CBA)/Votorantim Metais -- Unidade
Miraí (Grand/awards number: 184015/50130266478) for the concession of
the experimental area and its employees for help in the experiment
maintenance.

\textbf{Declaration of Competing Interest}

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to
influence the work reported in this paper.

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Appendix 1. Physical, chemical and biological properties of the soil in
an area of bauxite mining in process of recovery with eucalyptus (Euc),
angico (Ang) and a mixed plantation of native species (Nat), native
forest in the second stage of regeneration (Woodland), and a post-mined
area with no ground cover (NCov). Mean values are followed by the
standard deviation (n = 6).\selectlanguage{english}
\begin{longtable}[]{@{}llllllllllll@{}}
\toprule
Ground cover & Soil layer (cm) & TC & TN & LC & CMB & NMB & Ds & Dp & Pr
& DRsm & DRgr\tabularnewline
& & & & & & & & & & \textless{} 2mm & \textgreater{} 2mm\tabularnewline
& & dag kg\textsuperscript{-1} & dag kg\textsuperscript{-1} & g
kg\textsuperscript{-1} & \selectlanguage{greek}µ\selectlanguage{english}g g-\selectlanguage{ngerman}¹ & \selectlanguage{greek}µ\selectlanguage{english}g g-\selectlanguage{ngerman}¹ & g cm\textsuperscript{-3} & g
cm\textsuperscript{-3} & m\textsuperscript{3} m\textsuperscript{-3} & g
m\textsuperscript{-3} & g m\textsuperscript{-3}\tabularnewline
NCov & 0-10 & 1.44\selectlanguage{ngerman}±0.05 & 0.11\selectlanguage{ngerman}±0.00 & 1.16\selectlanguage{ngerman}±0.17 & 62.16\selectlanguage{ngerman}±1.75 &
18.20\selectlanguage{ngerman}±3.17 & 1.13\selectlanguage{ngerman}±0.19 & 2.73\selectlanguage{ngerman}±0.03 & 0.59\selectlanguage{ngerman}±0.07 & - & -\tabularnewline
Euc & 0-10 & 2.37\selectlanguage{ngerman}±0.32 & 0.17\selectlanguage{ngerman}±0.04 & 1.75\selectlanguage{ngerman}±0.64 & 174.69\selectlanguage{ngerman}±46.63 &
25.84\selectlanguage{ngerman}±14.18 & 1.32\selectlanguage{ngerman}±0.14 & 2.70\selectlanguage{ngerman}±0.09 & 0.51\selectlanguage{ngerman}±0.04 & 266.68\selectlanguage{ngerman}±89.2 &
253.6\selectlanguage{ngerman}±107.1\tabularnewline
Ang & 0-10 & 2.45\selectlanguage{ngerman}±0.61 & 0.18\selectlanguage{ngerman}±0.05 & 2.08\selectlanguage{ngerman}±0.56 & 153.33\selectlanguage{ngerman}±59.62 &
28.58\selectlanguage{ngerman}±8.81 & 1.26\selectlanguage{ngerman}±0.10 & 2.68\selectlanguage{ngerman}±0.05 & 0.53\selectlanguage{ngerman}±0.03 & 437.46\selectlanguage{ngerman}±11.2 &
236.2\selectlanguage{ngerman}±49.7\tabularnewline
Nat & 0-10 & 2.10\selectlanguage{ngerman}±0.31 & 0.14\selectlanguage{ngerman}±0.02 & 1.82\selectlanguage{ngerman}±0.24 & 157.98\selectlanguage{ngerman}±55.08 &
23.70\selectlanguage{ngerman}±12.32 & 1.21\selectlanguage{ngerman}±0.10 & 2.70\selectlanguage{ngerman}±0.04 & 0.55\selectlanguage{ngerman}±0.04 & 939.36\selectlanguage{ngerman}±275.1 &
741.9\selectlanguage{ngerman}±248.\tabularnewline
Woodland & 0-10 & 5.03\selectlanguage{ngerman}±0.51 & 0.36\selectlanguage{ngerman}±0.04 & 4.54\selectlanguage{ngerman}±0.20 & 705.77\selectlanguage{ngerman}±28.26 &
68.65\selectlanguage{ngerman}±6.82 & 0.97\selectlanguage{ngerman}±0.09 & 2.54\selectlanguage{ngerman}±0.03 & 0.62\selectlanguage{ngerman}±0.04 & 2061.41\selectlanguage{ngerman}±739.4 &
1543.7\selectlanguage{ngerman}±375.6\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{ngerman}

\selectlanguage{english}
\FloatBarrier
\end{document}

