How do we monitor degraded areas recovery projects?

doi:10.21203/rs.3.rs-1962050/v2

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How do we monitor degraded areas recovery projects?

https://doi.org/10.21203/rs.3.rs-1962050/v2

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Areas undergoing forest restoration need to be monitored to achieve ecosystem services. This work was carried out to evaluate the establishment of the riparian forest area in the restoration process, after 18 years of intervention, through temporal analysis of the landscape, biotic and soil indicators. Moreover, a temporal analysis of the landscape, biomass and Gross Primary Production (GPP) was carried out, via geoprocessing, at five-intervals within the period from 2002 to 2020, as well as biotic indicators (seed rain, seed bank, seedlings), and edaphic indicators from 2019 to 2020. The seed rain presented 1,197 propagules, belonging to 27 different species. The soil seed bank showed higher density in the rainy season (21.3 seeds/m²), 25 seeds, seven species, and only one botanical family recorded. In the seedling bank, 1,193 seedlings were reported, belonging to 28 botanical families, in which 57% of the individuals are arboreal-shrubby of the forest. Edaphic conditions improved compared to the initial project implementation. In 2010 using the temporal analysis of the landscape, the planting area was 100% covered with dense vegetation. For biomass and the GPP is a linear increment over time. The successional stage of the area is advanced, with a significant representation of secondary and climax species. The monitoring favored understanding the dynamics of the restoration environment and conservation.

Regeneration

active and passive recovery

restoration

environmental restoration.

Brazil has high water potential worldwide, covering 12 hydrographic regions in its territory, with about 12% of the world's freshwater (ANA, 2020; de Mello et al., 2020). The São Francisco River Basin (SFRB) stands out for the volume of water that supplies the semi-arid region of the country.

The SFRB is submitted to several environmental damages and is disorderly exploitation. In large part, the damage occurs due to anthropical changes promoted by land use. The changes, in general have caused a significant reduction in forest resources which play a fundamental role in the regulation and function of ecological and hydrological processes, resulting in socio-environmental problems (Prokopová et al., 2019). The most significant impacts, whether environmental, hydrological, or socio-environmental, resulted in higher intensity in the hydrographic sub-region known as the low course of the river, the Low São Francisco (do Vasco, 2019; Farias et al., 2019; Holanda et al., 2021).

The intense modification of the natural landscapes in this region accelerates erosive processes (Guimarães et al., 2010; Li et al., 2019). It is dangerous, primarily due to the increasing fragmentation and suppression of riparian areas, which play essential roles in regulating water quality and quantity (Santos Júnior et al., 2017; Yirigui et al., 2019), which involves the capacity of the watershed.

Riparian forests in Brazil are protected by Law number 12651, and are classified as Permanent Preservation Areas (PPA), which must be protected, and any degradation must be recovered (Brasil, 2012). In Sergipe, a state located in the Lower São Francisco (LSF) region, most of the riparian forests are in an advanced disturbance or degradation, which suggests the need for restoration to switch the dynamics and interactions of local ecosystems (Almeida, 2016; Moreno-Mateos et al., 2020).

Therefore, forest restoration was carried out in the municipality of Santana do São Francisco in Sergipe, in 2003. This action aimed to mitigate anthropic consequences and enable the resumption of ecological processes, consequently maintaining native vegetation. Species of natural occurrence in the region were used for artificial restoration.

In 2016, 13 years after the forest species (13) were implemented, it was identified the presence of 165 species in the area, including shrubs, trees, and herbaceous individuals. Nevertheless, during this period, no surveys were carried out using the biological indicators of natural regeneration. Consequently, there was a gap in the dynamics of local ecological succession. In this environment, there is a necessity to develop evaluations and continuous monitoring. Natural regeneration mechanisms were accessed, such as seed rain, soil attributes and seed banks. It is also indicated to evaluate the climate and the soil, both in physical and fertility, and temporal landscape scenarios to observe the shifts over time. The analysis of these processes and environment components can make possible to understand the temporal dynamics in the area and if the restoration was well conducted.

The geospatial tools can be applied as an efficient strategy to monitor and permit interpretations and draw up conservation plans to develop more efficient environmental management of land use and occupation (Wu et al., 2019; Hurskainen et al., 2019; Sousa; Davis, 2020). Such actions are allies in long-term reforestation projects in degraded areas. However, the results must be associated with the use of biological indicators. They permit inferences to the vertical and horizontal structure evolution of the forest, directing strategies to obtain the successional events of the restoration.

One of the leading biological indicators is natural regeneration. Its evaluation is based on quantitative and qualitative methodologies. It is necessary to use biological indicators to monitor the changes in the environments, mainly due edaphic transformations as physical, chemical, and hydrological, through river flow and water quality. However, hydrological assessments do not always respond to actions on environmental microscales.

Seed rain is the primary indicator of local successional dynamics, and it is possible to verify the presence of species propagules in the surrounding vegetation and other sites by dispersion. This occurrence favors the enrichment of local floristic diversity (Sccoti et al., 2016; Fróes et al., 2020). The formation of soil seed banks occurs with viable or non-viable propagules (Fabricante et al., 2016; Moravcová et al., 2022). On the other hand, the seedling bank is formed by young and viable, recently germinated seeds sometimes that cannot be stored for long periods due to the high metabolic activity. They are dispersed mainly on the forest floor (Silva et al., 2018).

Soil-plant relationship and nutrient availability depend on chemical and physical attributes as abiotic indicators. The soil is conditioned to express the water retention, presence, mobility of contaminants, cation exchange capacity (CEC), buffer capacity, pH, among other variables (Caldeira et al., 2013; Shen et al., 2020; He et al., 2021).

Assessments made with biological indicators support the management of forest recovery projects. In this way, it is possible to identify conflicts and enable decision-making about interventions to guarantee the conservation of natural resources, self-renewal, sustainability, and maintenance of the biological diversity (Almeida, 2016).

Therefore, this work was carried out to monitor the efficiency of artificial and passive restoration using soil, seed, and seedling data on a restored riparian forest floor, after 18 years of implantation. The restoration was established with seedling planting and direct seeding of 13 forest species of natural occurrence in the region.

Area of study

A farm of study is in Santana do São Francisco, Village called Saúde (10°15’32” S and 36°38’23” W) (Fig. 1). The municipality is in the extreme northeast region of the state of Sergipe. The region has the lowest Human Development Index (HDI) in Sergipe. The region is near the North of the state of Alagoas and to the South, East, and West of Neópolis, SE (Fig. 1).

The farm is in the permanent preservation area (PPA) of the São Francisco River. The area was established in 2003 in 2.5 ha. Thirteen forest species of natural occurrence in the region was used with different planting densities (3x3 and 3x1.5m). The seedlings were produced in the forest garden in São Cristóvão municipality and in a sustainable use protected area, the Ibura National Forest (NF; 144 ha; 10°50'26" S, 37°08'30" W; Datum WGS84). The species' choice was based on their potential local occurrence and ecological function in the environment (Table 1).

Table 1

Species selected for riparian restoration in 2003, Santana do São Francisco - Sergipe.
Family	Species	Ecological Group
Anacardiaceae	Schinus terebinthifolia Raddi	Pioneer
Anacardiaceae	Tapirira guianensis Aubl.	Pioneer
Fabaceae	Cassia grandis L. f	Climax
	Enterolobium contortisiliquum Vell. Morong.	Climax
	Erythrina velutina Willd.	Pioneer
	Hymenaea courbaril L.	Climax
	Libidibia férrea var. leiostachya (Mart. ExTul.) L. P. Queiroz	Climax
	Mimosa caesalpiniifolia Benth.*	Pioneer
	Poincianella pyramidalis (Tul.) L. P. Queiroz	Pioneer
Lamiaceae	Vitex rufescens A. Juss.	Climax
Meliaceae	Cedrela fissilis Vell.	Climax
Rubiaceae	Genipa americana L.	Climax
Sapindaceae	Cupania impressinervia Acev. - Rodr.	Climax
* Species planted after the reforestation project.

Natural Regeneration

The natural regeneration process started in 2019, after 16 years of project implementation. To accurately measure the stage of the area the species composition of seed rain, soil seed bank, and the seedling bank were evaluated.

Seed Rain

In the area, 15 wooden collectors (1m x 1m) were disposed to investigate the composition and quantify the seed rain. The collectors have a shade screen (1 mm), 10 cm deep, fixed at 50 cm above the ground surface.

The evaluations were carried out every quarter between August 2019 and February 2020, where all the material deposited on the collectors was packed in labeled plastic bags for later identification and quantification. All propagules were manually separated from the inert material using stereomicroscopic when necessary. According to the Angiosperm Phylogeny Group IV classification system, seeds were counted and identified at family, genus, and species levels (APG, 2016).

Soil Seed Bank

Samples were collected in two year-round seasons, the end of the rainy season (August) and the dry season (November to March).

The collections were established randomly using 12 plots of 1m². The seed banks were sampled with a metallic frame (25 cm x 25 cm), introduced into the soil at 0–5 cm layer. Soil seed bank samples were placed in plastic bags for subsequent identification.

Seedling Bank

The seedling bank evaluations were simultaneously obtained in the same year of the seedling bank evaluation (2019 and 2020). Two collections were carried out, 1 for each season, dry (February) and rainy (November). The samples were systematically collected in the plots with a frame of polyvinyl chloride (PVC) (1 m²). In each plot, the regenerants were measured for height and diameter with a centimeter bar and a digital caliper.

The seedlings were classified into classes (I, II, and III) according to the methodology proposed by Scolforo (2004). Class I with 0 ≤ height (H) < 0.30 m, class II 0.30 m ≤ H < 1.50 m, and class III 1.50 m ≤ H < 3.0 m.

Natural Regeneration

According to the Angiosperm Phylogeny Group IV classification, seeds and seedlings were identified for family, genus, and species (APG IV, 2016). According to the recommendations of Martins (2007), the values of frequency (absolute and relative), density (absolute and relative), dominance (absolute and relative), importance value (V), and Pielou's Equability Index (J') (Pielou, 1975) and Shannon's (IDS) (Shannon; Weaver, 1949) were estimate for all regenerants.

Density, frequency, abundance, dominance, and species importance values were estimated using the Fitopac 2.1 program (Shepherd, 2010).

Physical And Chemical Attributes Of Soil

The soil attributes were accomplished in 2003 and after 18 years of restoration, using the same initial methodology. Soil samples were collected in May 2021 at 0–20 cm with the aid of a Dutch auger. Five zig-zag subsamples were collected within each plot, totaling 60 subsamples. The subsamples were homogenized to compose only a sample of the entire area.

Soil fertility parameters were evaluated. Estimated values of base sum (BS), effective and potential CEC, base saturation (V%), sodium saturation (SS), aluminum saturation (Al3+), and granulometric analysis: sand, silt, and clay, followed the methodology of the Manual of Chemical Analysis of Soils, Plants, and Fertilizers (Teixeira et al., 2017). The results were compared to those obtained in 2003.

Data analysis

Landsat 7 ETM (L7) and 8 OLI (L8) satellite images were assessed in Google Earth Engine (GEE) platform, the database provided by the United States Geological Survey (USGS). Surface Reflectance (SR) was used to map land use and temporal classification. The image of pixels were composed of median SR values for each year. The filter to remove pixels with clouds was applied using the mass cloud function and removed from the Fmask algorithm that uses the Q60 band as a reference, a bitmask band with cloud mask information.

Land Use And Occupation

In the Code Editor of the GEE, a code in JavaScript was implemented with the Random Forest classification algorithm. Initially, five spectral targets were observed inside the area (Table 2).

Table 2

Land occupation classes are selected through satellite image (Landsat 7 – ETM) and their definitions, according to visual characteristics, based on the Land Use Technical Manual (IBGE, 2013).
Spectral Targets (Class)	Definition
Water	Presence of water bodies (lakes, ponds, rivers, spring areas).
Dense vegetation	Areas with the presence of natural forest/shrubby vegetation with characteristic plant physiognomy of the Caatinga, exclusively Brazilian vegetation and typical of Tropical Dry Forests and Atlantic Forest, the typical vegetation of humid Tropical Forests.
Exposed soil	Bare land surface space, with a total absence of vegetation.
Altered areas	Anthropogenic areas with the absence of closed forest arboreal vegetation or with the presence of activities aimed at agriculture with a predominance of annual or permanent crops.
Built areas	Non-agricultural anthropic areas with a predominance of typically residential, industrial and other areas.

Afterward, geometries collections (feature collections) were created to set the classification algorithm, performed at 50 random sampling points. For each land use and occupation class, 10 points were collected directly from the false color InfraRed composition (bands 4, 3, and 2 for L7 and 5, 4, and 3 for L8). The commands for classification and validation of the mappings were inserted in the confusion matrix to evaluate the global accuracy (Eq. 1) and Kappa index (Eq. 2) (Table 3). After calculated for each year, the mean values of these variables were excluded.

Global Accuracy =\(\left(\frac{\sum _{i=1}^{K}{X}_{ii}}{N}\right).100\) (1)

\(\widehat{K}\)=\(\frac{N\sum _{i=1}^{K}{X}_{ii} - \sum _{i=1}^{k}({x}_{i+} . {x}_{+i})}{{N}^{2}- \sum _{i=1}^{k}({x}_{i+} . {x}_{+i})}\) (2)

\(\widehat{K}\) : estimated index value Kappa.

k: number of rows in the confusion matrix.

\({X}_{ii}\) : number of observations in row i and column i.

\(\sum _{i=1}^{K}{X}_{ii}\) : sum of the matrix elements on its main diagonal.

\({X}_{i+}\) : total sum of observations for rows.

\({X}_{+i}\) : total sum of observations for columns.

total number of observations.

Table 3

Supervised classification accuracy from Kappa's index (coefficient) (Landis; Koch, 1977).
Kappa Index (K)	Quality
0.2	Bad
0.2 < 0.4	Reasonable
0.4 < 0.6	Good
0.6 < 0.8	Very good
≥ 0.8	Excelent

The images (.tiff) were exported to Google Drive and transferred to ArcGis 10.3 - ArcMap Extension. Two shapefiles were created (.shp), one for the entire farm and the other for the recovery planting area. It was possible to isolate and extract the areas of interest and estimate the size (m²) of the different spectral targets, now called land cover classes. This procedure was done to understand the increment in vegetation. The Boundary clean tool (ArcToolbox) helped to clean irregular edges, smoothing the boundaries between classes. Subsequently, land cover classification maps were generated for the four studied periods.

The area of the different land cover classes and an increment graph was elaborated over time to observe the performance of forest suppression or vegetation gain in the study area.

Biomass And Gpp

Gross Primary Productivity data (GPP - MOD17A2H) and biomass from the Net Primary Production (NPP - MOD17A3HGF) of the MODIS sensor were used for 2002, 2006, 2010, 2015, and 2020. The product provides ready-made GPP data and NPP every eight days in terrestrial ecosystems globally (Running et al., 2015, 2019). Data were available on the platform by USGS, and the values from the Code Editor of the GEE platform.

Seed rain

For seed rain, an average of 398 seeds was identified (15 collectors) per year and 25 seeds/m² for the evaluated periods. A significant number of seeds was observed in November, with 992 seeds in the area (0.36 ha), about 62 seeds/m² (Table 4). Seed rain contributes to the horizontal component of the area. Thus, the presence of 26 species were observed, with a total of 1,198 propagules collected in August, November, and February (Table 4).

Table 4

Species in the seed rain at Farm, Santana do São Francisco, Sergipe.
Family	Species	Habit	Ecological Group	Number of Seeds
Family	Species	Habit		Ago	Nov	Fev
Anacardiaceae	Mangifera indica L.	arboreous	Exotic	-	-	1
Anacardiaceae	Schinus terebinthifolia Raddi.	arboreous	Pioneer	19	23	-
Bignoneaceae	Tabebuia aurea (Silva Manso) Benth. & Hook. F. ex S. moore	arboreous	Pioneer	-	3	-
Fabaceae	Anadenanthera colubrina (Vell.) Brenan	arboreous	Initial Secondary	-	-	41
	Cassia grandis L. f	arboreous	Initial Secondary	-	-	9
	Erythrina velutina Willd.	arboreous	Pioneer	15	-	-
	Inga vera Willd.	arboreous	Initial Secondary	1	-	-
	Libidibia ferrea var. Leiostachya (Benth.) L. P. Queiroz	arboreous	Climax	26	13	-
	Lonchocarpus sericeus (Poir.) Kunthex DC	arboreous	Initial Secondary	-	746	24
	Fabaceae sp.1	-	-	-	-	2
	Fabaceae sp.2	-	-	-	3	-
Euphorbiaceae	Euphorbiaceae sp.	-	-	-	2	-
Lamiaceae	Vitex rufescens A. Juss	arboreous	Climax	10	4	-
Myrtaceae	Psidium guianense SW.	arboreous	Initial secondary	-	78	-
Rhamnaceae	Ziziphus joazeiro Mart.	arboreous	Late secondary	2	1	-
Rubiaceae	Genipa americana L.	arboreous	Climax	45	-	-
Not identified	sp. 1			-	24	-
	sp. 2			-	3	-
	sp. 3			1	1	-
	sp. 4			1	-	-
	sp. 5			-	90	-
	sp. 6			-	1	-
	sp. 7			2	2	-
	sp. 8			-	-	2
	sp. 9			-	-	3
Total seeds*				122	992	82
Estimated seeds per m²				8	66	5
Estimate of seeds in the sample area **				28,467	289,333	19,333
* Sampled area = 15 m² (collector area 1m² x 15 collectors); ** planted area: ≅3500 m²

Fourteen species were identified (Fig. 2), three at the family level, and the remaining without identification due to the lack of information. The unidentified propagules represent only 11% of individuals.

The density in seed rain was 25 seeds/m². These values differ from those found in other works in the Atlantic Forest. In a deciduous forest remnant of 560 ha, a density of 1,350 seeds/m² was reported (Sccoti, 2011).

Eight botanical families were observed in the collected samples, emphasizing the Fabaceae family with remarkable diversity in species (08) and Anacardiaceae (02). The other families presented only one species each (Table 4). The highest number of seeds produced was for Lonchocarpus sericeus (Poir.) Kunthex DC. The occurrence of the Craibeira (Tabebuia aurea (Silva Manso) Benth. & Hook. F. ex S. Moore) in the area was probably due the process of introduction via dispersion since it was not initially used in the area.

There were species of different groups: pioneers, early secondary, late secondary, and climax. The initial and climax secondary species stand out, with 890 and 107 individuals, respectively.

All identified species are arboreal. This attribute, associated with the low presence of pioneers, permits to infer the current situation of the implanted forest. Considering that these species have already fulfilled their ecological role of providing better conditions for secondary species to develop, as shading; the absence of pioneers and the significant presence of secondary and climax species as conclusion the area is in the advanced stages of the succession.

Due to the small number of pioneer species propagules in the seed rain in the project's initial phase, the species probably began a physiological decline due to the shading provided by the climax species. In this course, these species fulfilled their ecological function in the area. Also, pioneer species have restricted seed dispersal when subjected to adversity due to genetic and dispersal factors (Lowe et al., 2018).

During the development of the monitoring, anthropic interferences were observed, such as broken and remotion of collectors.

Seed Bank

Among the three regeneration strategies used, the seed bank had the lowest number of species (Table 5). Cassia grandis L. f., Erythrina velutina Willd., Libidibia ferrea var. leiostachya (Benth.) L. P. Queiroz and Lonchocarpus sericeus (Poir.) Kunthex DC was identified in the Fabaceae family. Three species were not identified (Table 5).

Table 5

Species in seed bank of the rainy and dry seasons in area in Santana do São Francisco, Sergipe.
Family	Species	habit	Ecological Goup	Quantity of seeds per season
Family	Species	habit	Ecological Goup	Rainny	Dry
Fabaceae	Cassia grandis L. f	arboreous	Climax	-	3
	Erythrina velutina Willd.	arboreous	Pioneer	1	1
	Libidibia ferrea var. Leiostachya (Benth.) L. P. Queiroz	arboreous	Climax	15	-
	Lonchocarpus sericeus (Poir.) Kunthex DC	arboreous	Initial Secondary	-	1
Indefined	Sp. 1			-	1
	Sp. 2			-	1
	Sp. 3			-	2
16	9
21	12
74,550	42,000
Sampled area = 0.75 m² (collector area 0.0625 m² x 12 plots); *Planted area: ≅ 3,500 m².

Differences were observed in the number of individuals (Fig. 3-B) and species. The density in the rainy season was 21 seeds/m², 64% of total seeds sampled in both periods, and there was a reduction to 12 seeds/m² in the dry season. Four species are arboreal; among them, two were climaxes, one initial secondary and one pioneer. Leiostachya and Cassia grandis showed higher values r of individuals, density, and frequency (Fig. 3-A).

In this method, the soil seed bank proved self-renewing the area and presents essential species in this process. It is worth mentioning that the recovered area is relatively new, and the species found in the seed bank reflect the presence of adults used during the beginning of the restoration. It is still possible to observe that the composition reflects the fulfillment of the ecological role of the pioneer species, like E. velutina.

Therefore, a lower presence of pioneer species is due the replacement succession by the climax and late secondary species, which have been the majority. The species primarily were on the seedling bank, where they developed under the canopy of the pioneer plants until they reached the highest strata of the forest (Miranda, 2009; Almeida, 2016).

Seedling Bank

In the seedling bank, 170 individuals were identified (106 of rainy seasons and 64 of dry seasons), which correspond to 28 botanical families (Table 6).

Table 6

Species in the seedling bank in restored area in Santana do São Francisco, Sergipe.
Family	Species	Habit	Ecological Goup	Quantity
Family	Species	Habit	Ecological Goup	Rainny	Dry
Acanthaceae	Ruellia bahiensis (Nees) Morong.	herb	Pioneer	12	7
Anacardiaceae	Mangifera indica L.	arboreous	Exotic	-	1
Apocynaceae	Matelea ganglinosa (Vell.) Rapini	climbing habit	Pioneer	1	-
Asteraceae	Bidens pilosa L.	herb	Pioneer	1	-
Boraginaceae	Varronia curassavica Jacq.	shrub	Initial Secondary	1	3
Cannabaceae	Celtis iguanaea (Jacq.) Sarg.	shrub	Pioneer	3	5
Capparaceae	Cynophalla flexuosa (L.) J. Presl	shrub	Initial Secondary	3	6
Chrysobalanaceae	Licania tomentosa (Benth.) Fritsch	arboreous	Not Classified	-	3
Cyperaceae	Cyperus distans L.	herb	Pioneer	4	-
Cyperaceae	Cyperus laxus Lam.	herb	Pioneer	1	-
Cyperaceae	Rhynchospora nervosa (Vahl) Boeckeler	herb	Pioneer	2	-
Euphorbiaceae	Caperonia palustris (L.) A.St.-Hil.	herb	Not Classified	1	-
	Croton blanchetianus Baill.	arboreous	Pioneer	-	2
	Croton heliotropiifolius Kunth	shrub	Pioneer	2	-
	Chamaecrista ramosa (Vogel) H.S.Irwin & Barneby		Pioneer	1	-
Fabaceae	Crotalaria retusa L.	herb	Pioneer	1	-
	Crotalaria stipularia Desv.	herb	Pioneer	2	-
	Bauhinia cheilantha (Bong.) Steud.	shrub	Pioneer	1	-
	Inga vera Willd.	arboreous	Initial Secondary	3	1
	Machaerium hirtum (Vell.) Stellfeld	arboreous	Initial Secondary	3	2
	Senegalia tenuifolia (L.) Britton & Rose	shrub	Climax	5	-
	Senna splendida (Vogel) H.S.Irwin & Barneby	shrub	Not Classified	3	-
	Stylosanthes scabra Vogel	herb	Pioneer	1	-
Lamiaceae	Aegiphila verticillata Vell.	shrub	Not Classified	-	1
Lamiaceae	Vitex rufescens A. Juss	arboreous	Climax	-	9
Loganiaceae	Spigelia anthelmia L.	herb	Pioneer	1	-
Lygodiaceae	Lygodium venustum Sw.	herb	Not Classified	3	-
Malvaceae	Pavonia communis A.St.-Hil.	herb	Not Classified	6	-
Menispermaceae	Cissampelos glaberrima A.St.-Hil.	climbing habit	Not Classified	1	1
Myrtaceae	Campomanesia aromatica (Aubl.) Griseb.	arboreous	Climax	1	1
	Campomanesia dichotoma (O.Berg) Mattos	arboreous	Not Classified	-	2
	Eugenia ligustrina (Sw.) Willd.	arboreous	Not Classified	1	-
	Psidium guajava L.	arboreous	Late Secondary	1	-
	Psidium guineense Sw.	arboreous	Climax	1	-
Orchidaceae	Oeceoclades maculata (Lindl.) Lindl.	herb	Pioneer	3	-
Poaceae	Leersia hexandra Sw.	herb	Not Classified	9	-
Poaceae	Urochloa fusca (Sw.) B.F.Hansen & Wunderlin	herb	Pioneer	1	-
Polygonaceae	Coccoloba ramosissima Wedd.	shrub	Pioneer	-	1
Rhamnaceae	Ziziphus joazeiro Mart.	arboreous	Late Secondary	5	8
Rubiaceae	Borreria verticillata (L.) G.Mey	herb	Pioneer	5	-
	Genipa americana L.	arboreous	Climax	4	1
	Guettarda angelica Mart. ex Müll.Arg.	shrub	Pioneer	1	-
	Tocoyena formosa (Cham. & Schltdl.) K.Schum	shrub	Pioneer	-	3
Rutaceae	Ertela trifolia (L.) Kuntz	herb	Initial Secondary	-	1
Salicaceae	Casearia lasiophylla Eichler	shrub	Pioneer	2	-
Sapindaceae	Allophylus quercifolius (Mart.) Radlk.	shrub	Not Classified	-	1
Sapindaceae	Paullinia pinnata L.	climbing habit	Initial Secondary	2	3
Urticaceae	Urtica dioica L.	herb	Not Classified	1	-
Verbenaceae	Lantana camara L.	shrub	Initial Secondary	5	2
Violaceae	Pombalia oppositifolia (L.) Paula-Souza	herb	Not Classified	2	-
Total seedlings sampled *				106	64
Estimate of seeds per m² Estimation of seeds in the planted area **				9	5
				30.917	18.677
Sampled area = 12m² (collector area 1m² x 12 plots); *Planted area: ≅ 3500 m²

Euphorbiaceae and Fabaceae stood out with six species each, followed by Myrtaceae (05) and Rubiaceae (04).

These families represented 42% of the specimens in the area. The Fabaceae has been increasingly reported due to the increase in its use in areas of natural regeneration (Fernandes et al., 2018; Silva, 2019). Such species have a high ecological impact and favor the choice of individuals in recovery projects. Its ability to develop root nodules as a symbiosis with atmospheric nitrogen-fixing bacteria and mycorrhizal fungi promotes nitrogen fixation in the soil, accelerating plant establishment and growth (Nogueira, 2012; Rodrigues et al., 2016).

Forest's tree-shrub are represented by 28 families (57%), and many individuals were on the floor. Herbs represented 19 families, and 64 seedlings were identified.

There was a high species diversity during the rainy season; 106 specimens, with an average density of ≅ 9/m², in contrast to 5 seedlings/m², during the dry period. These results differ from those reported in other areas in Sergipe, where the regenerants had a lower average density of 1.86 seedlings/m² and 3.77 seedlings/m² for the rainy and dry seasons, respectively (Silva, 2019).

For the rainy season, dominance (absolute and relative) and importance (IVI) was seen for Cynophalla flexuosa (L.) J.Presl, Genipa americana L., Inga vera Willd, Senna splendida (Vogel) H.S.Irwin & Barneby, Ziziphus joazeiro Mart., Eugenia ligustrina (Sw.) Willd. (Annex 1). For the same index in the dry period, the species that stood out were Mangifera indica L., Paullinia pinnata L., Z. joazeiro, Vitex rufescens A. Juss, Varronia curassavica Jacq., Ruellia bahiensis (Nees) Morong (Appendix 2).

In the seedling bank, the species G. americana stood out for density and relative frequency with the highest rates in the rainy season.

Shannon's (IDS) and Pielou's (P) diversity index differed between seasons. The IDS and P for the rainy season were 3.34 and 3.25, higher than in the dry season, where IDS = 2.13 and P = 2.04. Thus, the rainy season presents higher diversity of specimens.

Despite the farm limits being protected with a fence to avoid human and animal interference, such actions interfere with the local dynamics. The main human interferences were collection of fruits, woody suppression even of the collectors for domestic purposes, and the occurrence of criminal forest fires. These activities trigger impacts on the farm's forest restoration process. The gain in terms of the horizontal and vertical structure of the area is evident. Recompositing of environments and features of an area of forest inclines us to assess whether the benefits went beyond the visual. For this purpose, a chemical analysis of the soil was conducted to verify if the recovery action changes the soil condition.

Soil Attributes

Soil attributes differed, as seen in Fig. 4. The pH increased (from 5.10 to 5.85), showing a reduction in acidity. In degraded areas, the reduction in soil acidity led to benefits such as a decrease in the mobilization of toxic elements such as aluminum, arsenic (Guimarães et al., 2017) and magnesium (Teran et al., 2020). pH between 5.8 to 6.2 is an optimal range promoting availability of essential nutrients for the plant. In addition, pH above 5.5 indicates that aluminum is in its precipitated form, completely insolubilized, and without damaging the roots (Sobral et al., 2015).

Soil chemical properties differed between 2003 and 2021. There were improvements in soil fertility over time, indicating a positive effect on soil attributes. No adverse effects of regeneration on the chemical and physical attributes of the soil were observed after 18 years of project implementation.

In areas of bauxite soil chemical attributes permitted significant contributions to forest restoration with increased soil quality and decreased elements such as aluminum (Xue, 2019).

The value of organic matter was not measured in the initial phase, but in 2021 its content was classified as medium (1.58%). Organic matter is the primary source of soil nutrients (Liu et al., 2016) and is directly affected by plant species diversity, composition, and distribution (Anwar et al., 2019). Soil chemical characteristics are influenced by the quality of the decomposed material from the litter produced by individuals in each area (Oliveira et al., 2019).

The values of exchangeable bases (sodium, potassium, calcium + magnesium), SB, effective and potential CTC, PST, and V% increased after 19 years. Thus, the area in this study overcomes the changes suffered and is re-established, favoring excellent vegetation development. It can be seen by the increase in exchangeable bases (Sobral et al., 2015). Reducing soil acidification reduces the leaching of exchangeable cations (Lu et al., 2014), and higher values for exchangeable bases such as calcium and magnesium can be identified (Yan et al., 2020). It indicates that the studied area presents higher availability of nutrients for the plants after re-establishing the forest restoration.

The effective CTC went from medium to high levels over the years and the potential CTC, increased, remains in the medium range (Sobral et al., 2015). Evaluations of organic matter, CEC, and pH are essential to understand the availability of storage capacity of cations, the concentration of ions, and the presence of toxic substances in the soil. The CTC in the soil makes it possible to know its capacity to retain cations and facilitate the absorption of nutrients by plants (Coelho et al., 2011). High CTC indicate balanced fertility (Silva et al., 2015), and low values indicate that the soil has little capacity to retain cations in exchangeable form (Ronquim, 2010).

When using soil chemical variables as abiotic indicators in a transition region between the Atlantic Forest and Caatinga, researchers observed that they are efficient in indicating changes in soil attributes over the ecological succession process (Novak et al., 2017).

The potential acidity (Hydrogen + Aluminum) decreased, a fact that should be seen as positive since this parameter is linked to the increase in pH (Sobral et al., 2015), and its reduction over the years indicates that the species present in the area have better growth conditions when compared to the beginning of the implantation (Ferreira et al., 2012). In tropical riparian forests, the soil's chemical attributes and the intensity of the decomposition process of organic matter are correlated with the vegetation's structure, therefore the composition and forest diversity (Soares et al., 2020).

There was a restructuring of the soil physical condition, where the clay and silt increased, and the sand content decreased. Nitrogen-fixing species can increase clay and silt content and reduce sand content (Li et al., 2022) making soil particles more uniform (Zhang et al., 2019a). The results expressed for granulometry prove that the restoration reduced the sand content and increased the acceptable particle content.

The Landscape Scenarios

The results in Fig. 5 demonstrate that the landscape was changed over 18 years. The areas that were altered in 2002 were restored and 100% stabilized.

Within the area, only the classes of dense vegetation and altered areas were identified, with the other classes described in the methodology. The average Kappa index (0.84) indicates the efficiency as excellent.

During the restoration of the first four years (2002–2006), an increase of 97.81% in vegetation was observed. In 2010, the area reached 100% of its coverage with dense vegetation, maintained until 2020 (Fig. 6). In Fig. 6, the area and adjacent were enriched by vegetation. Therefore, the reforestation applied in 2003 favored forest connectivity. The process of artificial or active restoration increases the diversity of forest species dynamically when compared to the natural method, without intervention, granting improvements in structural and ecological terms (Jayawardhane; Gunaratne, 2020). The insertion of forest species from vegetative propagules (seedlings and seeds) can reestablish functions such as gene flow and dispersion over time and favor ecosystem services (Cordeiro et al., 2019).

We evaluated the production of plant biomass and organic carbon (GPP) through estimates of the MODIS (Fig. 7). We observed that the flows of both variables showed a positive linear tendency (Fig. 7-B and C).

A decrease between 2002 and 2006 was observed to produce biomass and GPP. The reduction may be due to the high mortality of the species initially planted at the beginning. The gross primary production of organic carbon (GPP) continued to grow, while for biomass, there was another decrease between 2010 and 2015.

The reduction in biomass reflects the ecological succession process in the area where the pioneer species (short life cycle) begin to die, giving opportunity for secondary and climax species, which present slow growth. In areas under succession, a reduction number of pioneer species and their subsequent decline is expected (Chai; Wang, 2016).

GPP represents the ability to transform carbon dioxide into organic carbon through photosynthesis and depends on factors such as evapotranspiration (Zhao; Running, 2010; Collalti; Prentice, 2019). Biomass was estimated from the relationship of NPP and GPP, where the NPP/GPP ratio should be applied to measure total carbon at the ecosystem scale (Landsberg et al., 2020).

The Farm is in an area of riparian forest, defined as an APP. The APP was categorized in a disturbance stage (Torres et al., 2021). Therefore, interventions are an emergence. The lack of restoration actions in this region has shown severe consequences, where the degradation of forests contributed to the increase of suspended sediments in water bodies and alteration in the process of deposition of river sediments (Dompieri et al., 2020; Torres et al., 2021), as the absence of riparian vegetation that accentuates the marginal erosive processes (Holanda et al., 2021). The geospatial tools, such as satellite images to study the earth's surface, can detect changes in land use and cover over different temporal scales and make it possible to identify exploratory activities (Philogene; Ni-Meister, 2021).

A temporal analysis of land use and cover in Brazilian Biomes was constructed from Landsat archives for the last three decades (1985–2017), and the results showed that the country lost about 71 million hectares of natural vegetation (Souza et al., 2020). These tools are an essential data source for relevant environmental studies (Hansen et al., 2013). In addition, it facilitates the monitoring of the passive conservation and can be applied preventively and proactively to avoid environmental damages.

Monitoring environments in the restoration process should be included as one of the project's stages, as it can prevent situations that jeopardize co-benefits and how ecosystem services return to the local community (Hayward et al., 2021). It is possible to verify the connection among forest fragments and consequently maintenance of diversity. The remote sensing data for environmental monitoring consists of estimated results.

The biomass produced by an area undergoing restoration also influences the improvement of the soil's physical structure since it is the primary source of organic matter that promotes soil stability (Flores et al., 2008). The diversity of species benefits a more outstanding and varied litter and root biomass. It acts indirectly on soil properties, as it generates an increase in carbon inputs and activity of the micro and macro fauna of the soil that, consequently, promotes increased water holding capacity (Zhang et al., 2019b).

Reforestation with native species is one of the efficient ways to restore soil fertility, as this type of vegetation improves the soil's organic matter content, available nutrients, cation exchange capacity, increases biological activities, and improves physical soil conditions (Zhang et al., 2019b; Celentano et al., 2016). In regions with soils compacted, after 25 years of restoration with different forest species, it was observed that the chemical properties of the soil had full recovery (Jourgholami et al., 2019).

In riparian forests, soil fertility is related to the preservation of ecosystems, as its levels are influenced by the condition and composition of the local vegetation. The degradation alters soil fertility and triggers problems in the spontaneous development of plants (Celentano et al., 2016). Consequently, negatively influence the process of ecological succession and the resilience of the habitat. Soil analyses are of paramount importance to indicate the nutritional conditions of plants, allowing intervention through forest management to guarantee the continuity and functionality of ecosystems, especially in riparian forest areas, because of their ecological and social relevance.

Six years after the implementation of the restoration project, it was observed that the survival of the species planted in the initial phase was higher than 54%, and there was no difference (P ≤ 0.05) in growth and survival. At 12 years old, in this same area was an enrichment of 165 species, 134 genera, and 51 botanical families. Herbaceous species were predominant, with 74 species (44.8%), followed by 42 trees (25.5%), 33 shrubs (20%), and 16 vines (9.7%). The species presented a height from 3.26 and 8.05 m.

Active restoration, it is a method used in the project implementation in 2003, is seen as a silvicultural technique capable to improve the ecological succession and granting short and lon-term benefits to degraded environments, mainly concerning soil stability (Chaves, 2007; Ferreira et al., 2011).

In the Farm studied, an advanced stage of succession is observed, representing secondary and climax species.

The area's natural regeneration mechanisms shows that the species included in the forest restoration project in 2003 established and are spread propagules for their enrichment.

One fact is area's connectivity and the presence of dispersers that contributed to the increase in biodiversity.

Soil chemical and physical attributes improved, demonstrating that forest restoration went beyond the establishment of plant species and can be used in different regions of the different countries. Thus, the monitoring is essential to make decisions to reach the restoration goal and the environmental services.

Geoprocessing is a fast and effective technique for monitoring environments undergoing restoration and could be an ally using seed and seedling bank information.

This work successfully presents the methods to monitor de restoration of forest species in a degraded area through ecological indicators such as temporal landscape scenarios and biotic and edaphic indicators. The strategies adopted in the initial restoration stage are efficient for reestablishing of the local forest scenario. Therefore, to monitor environments under restoration report the success of the project, and management could be applied to correct the actions and methods, in time.

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.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Funding

The authors thank the Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES - Financial Code 001), the Banco do Nordeste do Brasil (BNB/ETENE/FUNDECI), and the Brazilian National Research Council (CNPq-Brasília/Brazil).

Author Contributions

Maria Fernanda Oliveira Torres: Conceptualization, methodology, research data validation. Fernanda Cristina Aguiar Mendonça and Renan Costa Santos: Data collection, field prospection. Robério Anastácio Ferreira and Renata Silva-Mann: Supervision, guided the research, revised the text and contributed to the writing of the manuscript.

Almeida DS (2016) Recuperação ambiental da Mata Atlântica. 3. ed. Ilhéus, BA: Editus. 200 p.
ANA (Agência Nacional de Águas) (2020) Disponível em: https://www.ana.gov.br/. Acesso em:15
Andrade FHN, de Almeida CDGC, de Almeida BG, Filho A, Mantovanelli JAC, Araújo Filho JC (2020) Atributos físico-hídricos do solo via funções de pedotransferência em solos dos Tabuleiros Costeiros de Pernambuco. Irriga 25(1):69–86
Apg II(2003) Angiosperm phylogeny group
Anwar S, Khan SM, Ahmad Z, Ullah Z, Iqbal M (2019) Floristic composition and ecological gradient analyses of the Liakot Forests in the Kalam region of District Swat, Pakistan. J Forestry Res 30(4):1407–1416
Brasil (2012) Lei nº 12.651, de 25 de maio de 2012. Dispõe sobre a proteção da vegetação nativa e dá outras providências. Diário Oficial da União
Caldeira MVW, da Silva RD, Kunz SH, Zorzanelli JPF, Castro KC, de Oliveira Godinho T (2013) Biomassa e nutrientes da serapilheira em diferentes coberturas florestais. Comunicata Sci 4(2):111–119
Celentano D, Rousseau GX, Engel VL, Zelarayán M, Oliveira EC, Araujo ACM, de Moura EG (2017) Degradation of riparian forest affects soil properties and ecosystem services provision in eastern Amazon of Brazil. Land Degrad Dev 28(2):482–493
Chai Z, Wang D (2016) Environmental influences on the successful regeneration of pine-oak mixed forests in the Qinling Mountains, China. Scand J For Res 31(4):368–381
Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D, Yamakura T (2005) Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145(1):87–99
Coelho EF, Or D, de SOUSA VF(2011) Aspectos básicos em fertirrigação.
Collalti A, Prentice IC (2019) Is NPP proportional to GPP? Waring’s hypothesis 20 years on. Tree Physiol 39(8):1473–1483
Cordeiro EM, Macrini CM, Sujii PS, Schwarcz KD, Pinheiro JB, Rodrigues RR, Zucchi MI (2019) Diversity, genetic structure, and population genomics of the tropical tree Centrolobium tomentosum in remnant and restored Atlantic forests. Conserv Genet 20(5):1073–1085
de Mello K, Taniwaki RH, de Paula FR, Valente RA, Randhir TO, Macedo DR, Hughes RM (2020) Multiscale land use impacts on water quality: Assessment, planning, and future perspectives in Brazil. J Environ Manage 270:110879
do Vasco AN, Netto ADOA, da Silva MG (2019) The influence of dams on ecohydrological conditions in the São Francisco River Basin, Brazil. Ecohydrol Hydrobiol 19(4):556–565
Dompieri MHG (2020) Análise do uso e ocupação das terras no baixo São Francisco, a partir de técnicas estatísticas multivariadas. Revista Econômica do Nordeste 51(3):25–50
Fabricante JR, Araújo KC, Castro RA, Cotarelli VM(2016) Banco de sementes do solo de sítios de Caatinga sob influência do Projeto de Integração do Rio São Francisco.Scientia Plena, 12(4)
Farias VGL, Lima GP, de Holanda Leite MJ, Cavalcante ATG, da Silva ACM, de Almeida Moura AC, Cavalcante RM (2019) Socio-environmental impacts caused by hydroelectric dams in northeastern Brazil. Brazilian J Dev 5(11):22846–22853
Andrade GKO, Ferreira RA, Fernandes MM, Silva TR, Souza IBA, Magalhães JS (2018) Regeneração natural em área de reflorestamento misto com espécies nativas no estado de Sergipe. Amazonian J 60(5):24–36
Ferreira EPDB, Fageriae NK, Didonet AD (2012) Chemical properties of an Oxisol under organic management as influenced by application of sugarcane bagasse ash. Revista Ciência Agronômica 43:228–236
Ferreira RA, Netto A, Santos ADO, Santos TIS, Matos ELD (2011) Nascentes da sub-bacia hidrográfica do rio Poxim, estado de Sergipe: da degradação à restauração. Revista Árvore 35:265–277
Flores CA, Reinert DJ, Reichert JM, Albuquerque JA, Pauletto EA (2008) Recuperação da qualidade estrutural, pelo sistema plantio direto, de um Argissolo Vermelho. Ciência Rural 38:2164–2172
Quinhones Fróes C, Ferreira da Costa P, Lopes Fernandes SS, Vieira da Silva AP, de Jesus M, R., & Valdivina Pereira Z(2020) Chuva de sementes como indicador ambiental de áreas em processo de restauração ecológica do Mato Grosso do Sul.Ciência Florestal(01039954),30(4)
Dias L, Cordeiro A, Guimarães LDO, Freire A, Assis I(2017) Espécies arbóreas potenciais para a revegetação de rejeito salino contaminado com arsênio. Ciência Florestal, v. 27, n. 3, p. 871–881, 2017
Guimarães MFR, Holanda FSR, da Rocha IP, de Araujo Filho RN, Vieira TRS (2010) Indicadores ambientais para o estudo da erosão marginal no Rio São Francisco, vol 11. Caminhos da Geografia, Uberlândia, pp 84–92. 34
Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova SA, Tyukavina A, Townshend J (2013) High-resolution global maps of 21st-century forest cover change. Science 342(6160):850–853
Hayward RM, Banin LF, Burslem DF, Chapman DS, Philipson CD, Cutler ME, Dent DH (2021) Three decades of post-logging tree community recovery in naturally regenerating and actively restored dipterocarp forest in Borneo. For Ecol Manag 488:119036
He M, Xiong X, Wang L, Hou D, Bolan NS, Ok YS, Tsang DC (2021) A critical review on performance indicators for evaluating soil biota and soil health of biochar-amended soils. J Hazard Mater 414:125378
Holanda FSR, Santos MHD, Jesus JBD, Santos WDM, Sena EOA, Chagas TX, … Santos LDV(2021) Sediment input from the São Francisco River bank, Northeast Brazil, under low discharge period. Investigaciones geográficas, (105)
Holanda FSR, Santos MHD, Jesus JBD, Santos WDM, Sena EOA, Chagas TX, … & Santos LDV(2021) Sediment input from the São Francisco River bank, Northeast Brazil, under low discharge period. Investigaciones geográficas, (105)
IBGE - Instituto Brasileiro de Geografia e Estatística. Manual Técnico de Uso da Terra. 3ª edição. Rio de Janeiro: IBGE, 2013. Disponível em: https://biblioteca.ibge.gov.br/visualizacao/livros/liv81615.pdf. Acesso em: 12/03/2021
Jayawardhane J, Gunaratne AMTA (2020) Restoration success evaluation of a thinned and enriched pine plantation in Sri Lanka. J Trop For Sci 32(4):402–413
Jayawardhane J, Gunaratne AMTA (2020) Restoration success evaluation of a thinned and enriched pine plantation in Sri Lanka. J Trop For Sci 32(4):402–413
Landis JR, Koch GG (1977) An application of hierarchical kappa-type statistics in the assessment of majority agreement among multiple observers. Biometrics, pp 363–374
Landsberg JJ, Waring RH, Williams M (2020) The assessment of NPP/GPP ratio. Tree Physiol 40(6):695–699
Landsberg JJ, Waring RH, Williams M (2020) The assessment of NPP/GPP ratio. Tree Physiol 40(6):695–699
Liu H, Xiong Z, Jiang X, Liu G, Liu W (2016) Heavy metal concentrations in riparian soils along the Han River, China: the importance of soil properties, topography and upland land use. Ecol Eng 97:545–552
Liu P, Liu X, Dai Y, Feng Y, Zhang Q, Chu G (2020) Influence of Vegetation Restoration on Soil Hydraulic Properties in South China. Forests 11(10):1111
Lowe AJ, Breed MF, Caron H, Colpaert N, Dick C, Finegan B, Cavers S (2018) Standardized genetic diversity-life history correlates for improved genetic resource management of Neotropical trees. Divers Distrib 24(6):730–741
Lu X, Mao Q, Gilliam FS, Luo Y, Mo J (2014) Nitrogen deposition contributes to soil acidification in tropical ecosystems. Glob Change Biol 20(12):3790–3801
Martins SV (2007) Recuperação de matas ciliares. Aprenda Fácil Editora
Miranda JC(2009) Sucessão ecológica: conceitos, modelos e perspectivas.SaBios-Revista de Saúde e Biologia, 4(1)
Moravcová L, Carta A, Pyšek P, Skálová H, Gioria M (2022) Long-term seed burial reveals differences in the seed-banking strategies of naturalized and invasive alien herbs. Sci Rep 12(1):1–10
Moreno-Mateos D, Alberdi A, Morriën E, van der Putten WH, Rodríguez-Uña A, Montoya D (2020) The long-term restoration of ecosystem complexity. Nat Ecol Evol 4(5):676–685
Nogueira N, Oliveira O, Martins C, Bernardes C(2012) Utilização de leguminosas para recuperação de áreas degradadas.Enciclopédia Biosfera, 8(14)
Novak E, Carvalho LA, Santiago EF, Portilho IIR (2017) Chemical and microbiological attributes under different soil cover. Cerne 23:19–30
Oliveira RA, Marques R, Marques MC (2019) Plant diversity and local environmental conditions indirectly affect litter decomposition in a tropical forest. Appl Soil Ecol 134:45–53
Philogene S, Ni-Meister W (2021) Relationship between Fire Events and Land Use Changes in the State of São Paulo, Brazil. Remote Sens 13(15):2853
Philogene S, Ni-Meister W (2021) Relationship between Fire Events and Land Use Changes in the State of São Paulo, Brazil. Remote Sens 13(15):2853
Prokopová M, Salvati L, Egidi G, Cudlín O, Včeláková R, Plch R, Cudlín P (2019) Envisioning present and future land-use change under varying ecological regimes and their influence on landscape stability. Sustainability 11(17):4654
Rodrigues KDM, Correia MEF, Resende ASD, Camilo FDL, Campelo EFC, Franco AA, Dechen SCF (2016) Fauna do solo ao longo do processo de sucessão ecológica em voçoroca revegetada no município de Pinheiral-RJ. Ciência Florestal 26:355–364
Ronquim CC(2010) Conceitos de fertilidade do solo e manejo adequado para as regiões tropicais
Running S, Mu Q, Zhao M (2015) MOD17A2H MODIS/terra gross primary productivity 8-day L4 global 500m SIN grid V006. NASA EOSDIS Land Processes DAAC
Running S, Zhao M (2019) MOD17A3HGF MODIS/Terra Net Primary Production Gap-Filled Yearly L4 Global 500 m SIN Grid V006. NASA EOSDIS Land Processes DAAC
Júnior EMS, Ferrari SF, Beltrão-Mendes R, Bitencurti DP, de Carvalho TM (2017) Mapeamento e caracterização dos fragmentos florestais na bacia hidrográfica do baixo rio São Francisco, Sergipe. Revista Geográfica Acadêmica 11(1):104–128
Sccoti MSV, Araujo MM, Tonetto TDS, Longhi SJ (2016) Dinâmica da chuva de sementes em remanescente de floresta estacional subtropical. Ciência Florestal 26:1179–1188
Sccoti MSV, Araujo MM, Tonetto TDS, Longhi SJ (2016) Dinâmica da chuva de sementes em remanescente de floresta estacional subtropical. Ciência Florestal 26:1179–1188
Scolforo JRS (2004) Inventário Florestal, 440 edn. Universidade Federal de Lavras, Lavras
Shannon CE, Weaver W (1949) The mathematical theory of communication. Univ. of Illinois Press, Urbana. The mathematical theory of communication. Univ. of Illinois Press, Urbana
Shen Y, Yu Y, Lucas-Borja ME, Chen F, Chen Q, Tang Y (2020) Change of soil K, N and P following forest restoration in rock outcrop rich karst area. CATENA 186:104395
Shepherd GJ (2010) Fitopac 2.1. 2.85. Manual do Usuário. Depto de Biologia Vegetal, Univ. Estadual de Campinas, Campinas, SP
Silva JM, de Quadros Tronco KM, Almeida ALC (2015) Influência da recuperação de matas ciliares ao igarapé D´ Alincourt sobre propriedades do solo. Revista Brasileira de Ciências da Amazônia/Brazilian Journal of Science of the Amazon 4(1):29–40
Silva JPGD, Marangon LC, Feliciano ALP, Ferreira RLC (2018) Chuva de sementes e estabelecimento de plântulas em floresta tropical na região nordeste do Brasil. Ciência Florestal 28:1478–1490
Soares JAH, de Souza ALT, de Abreu Pestana LF, Tanaka MO (2020) Combined effects of soil fertility and vegetation structure on early decomposition of organic matter in a tropical riparian zone. Ecol Eng 152:105899
Sobral LF, Barreto MDV, Silva D, Anjos AJ,D(2015) J. L. Guia prático para interpretação de resultados de análises de solos.
Sousa D, Davis FW (2020) Scalable mapping and monitoring of Mediterranean-climate oak landscapes with temporal mixture models. Remote Sens Environ 247:111937
Souza Jr CM, Shimbo Z, Rosa J, Parente MR, Alencar LLA, Rudorff A, Azevedo BF, T (2020) Reconstructing three decades of land use and land cover changes in Brazilian biomes with landsat archive and earth engine. Remote Sens 12(17):2735
Teixeira PC, Donagemma GK, Fontana A, Teixeira WG(2017)Manual de métodos de análise de solo
Teran FJC, de Oliveira Santos G, Júnior WT, de Freitas ECB, Soares JA (2020) Avaliação da recuperação de áreas degradadas por exploração de cascalho laterítico por meio da incorporação de lodo de esgoto. Estudo de caso no Distrito Federal. Brazilian J Dev 6(1):3243–3255
Torres MFO, Moura MM, Ferreira RA, Silva-Mann R, de Almeida AQ, Nascimento MIC (2021) Spatial framework vulnerability in riparian area in Sergipe: The case of the lower course of the São Francisco River, vol 24. Society and Environment, Remote Sensing Applications, p 100628
Wu J, Lu J (2021) Spatial scale effects of landscape metrics on stream water quality and their seasonal changes. Water Res 191:116811
Wu Q, Lane CR, Li X, Zhao K, Zhou Y, Clinton N, Lang MW (2019) Integrating LiDAR data and multi-temporal aerial imagery to map wetland inundation dynamics using Google Earth Engine. Remote Sens Environ 228:1–13
Xue SG (2019) Soil formation in bauxite residue: The most promising way to large-scale and ecological disposal. J Cent South Univ 26(2):265–267
Yan P, Wu L, Wang D, Fu J, Shen C, Li X, Wenyan H (2020) Soil acidification in Chinese tea plantations. Sci Total Environ 715:136963
Yirigui Y, Lee SW, Nejadhashemi AP, Herman MR, Lee JW (2019) Relationships between riparian forest fragmentation and biological indicators of streams. Sustainability 11(10):2870
Zhang B, Xu Q, Gao D, Jiang C, Liu F, Jiang J, Ma Y (2019) Higher soil capacity of intercepting heavy rainfall in mixed stands than in pure stands in riparian forests. Sci Total Environ 658:1514–1522
Zhang X, Zhao W, Wang L, Liu Y, Liu Y, Feng Q (2019) Relationship between soil water content and soil particle size on typical slopes of the Loess Plateau during a drought year. Sci Total Environ 648:943–954
Zhao M, Running SW(2010) Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. science, 329(5994), 940–943

No competing interests reported.

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How do we monitor degraded areas recovery projects?

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Abstract

Figures

Introduction

Material And Methods

Area of study

Natural Regeneration

Seed Rain

Soil Seed Bank

Seedling Bank

Natural Regeneration

Physical And Chemical Attributes Of Soil

Data analysis

Land Use And Occupation

Biomass And Gpp

Results And Discussion

Seed rain

Seed Bank

Seedling Bank

Soil Attributes

The Landscape Scenarios

Conclusions

Declarations

References

Additional Declarations

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