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Article

Impact of Land Use Change on Tree Diversity and Aboveground Carbon Storage in the Mayombe Tropical Forest of the Democratic Republic of Congo

by
Opelele Omeno Michel
1,2,3,
Ying Yu
1,2,
Wenyi Fan
1,2,*,
Tolerant Lubalega
4,5,
Chen Chen
1,2 and
Claude Kachaka Sudi Kaiko
3
1
School of Forestry, Northeast Forestry University, Harbin 150040, China
2
Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, School of Forestry, Northeast Forestry University, Harbin 150040, China
3
Department of Natural Resources Management, Faculty of Agricultural Sciences, University of Kinshasa, Kinshasa 01302, Democratic Republic of the Congo
4
Institut National Pour l’Étude et la Recherche Agronomiques (INERA/Luki), Antenne de Gestion et Conservation des Ressources Naturelles, Luki 03106, Democratic Republic of the Congo
5
Département de Phytotechnie, Faculté des Sciences Agronomiques, Université de Kikwit, Kikwit 02201, Democratic Republic of the Congo
*
Author to whom correspondence should be addressed.
Land 2022, 11(6), 787; https://doi.org/10.3390/land11060787
Submission received: 13 April 2022 / Revised: 13 May 2022 / Accepted: 23 May 2022 / Published: 26 May 2022
(This article belongs to the Section Land, Biodiversity, and Human Wellbeing)
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Versions Notes

Abstract

:
The Mayombe tropical forest has experienced dramatic changes over several decades due to human activities. However, the impact of these changes on tree biodiversity and ecosystem services has not been studied yet. Such a study could advance the current knowledge on tree biodiversity and carbon storage within the Mayombe forest, which is presently under high anthropogenic pressures. This information could benefit decision-makers to design and implement strategies for biodiversity conservation and sustainable natural resource utilization. As such, biodiversity surveys were conducted within the forest under different land utilization regimes. To evaluate the effect of human utilization on tree biodiversity and ecosystem services (carbon storage), land was classified into three categories based on the intensity of human utilization: low utilization, moderate utilization, and high utilization. Additionally, the study evaluated the recovery potential of the disturbed forest under both moderate and high utilization, after abandonment for 10 and 20 years. Tree diameter and height were measured for all trees whose diameter at breast height was greater than or equal to 10 cm. Our findings revealed that forest land with both high and moderate utilization regimes, and having no regulation, resulted in the decline of tree species richness, tree species diversity, and carbon storage. The magnitude of decrease was greater in high utilization compared to moderate utilization regimes. On the other hand, high values of biodiversity indices and carbon storage were observed in the low utilization regime. This study also demonstrated that fallow land that had been left undisturbed for more than 10 years, but had experienced both high and moderate utilization regimes, could reasonably recover carbon storage, and an acceptable level of tree species biodiversity can be achieved. However, there remains a significant difference when compared with the original level in the low utilization regime, suggesting that the Mayombe forest takes longer to recover. Based on the findings on tree biodiversity and carbon storage over the recovery trajectory, this study improves the understanding of the degraded forest restoration process within the Mayombe forest. It is therefore necessary to formulate new strategies to regulate forest land utilization within the Mayombe forest. This will ensure sustainability and availability of all ecosystem services this forest provides to a human population that strongly depends on it for their survival.

1. Introduction

Forests play a vital role in the preservation of biodiversity and climate regulation [1,2,3,4]. During the last century, forest ecosystems have, however, experienced dramatic changes all around the world [5,6,7,8,9,10,11,12,13,14]. These changes have been reported to induce the decrease in biodiversity [9,15,16,17] and ecosystem services including carbon storage [9,17,18,19,20,21,22,23]. Consequently, the Convention on Biological Diversity was created in 1992 in order to reduce the biodiversity loss. In 2005, the Millennium Ecosystem Assessment (MA) pointed out the necessity for biodiversity conservation, as it is key in the maintenance of human life [24]. Indeed, it has been widely reported that biodiversity supports ecosystem functioning and that the provisioning of ecosystem services is indispensable for human well-being [24,25]. In addition, biodiversity and ecosystem services can be utilized to eradicate poverty, to meet one of the foundations of the Strategic Plan for Biodiversity of the Convention on Biological Diversity (CBD) [26]. Thus, different projects have been initiated to reduce biodiversity loss and the decrease in the provision of the ecosystem services [27]. However, only a few studies have attempted to address these issues in relation to the impact of land use change on biodiversity and ecosystem services [28,29].
According to Lambin et al. [30] and Butchart et al. [15], the intensification of land use changes due to human activities, such as agriculture and wood harvesting, is the major driver of global change in forests all around the world. Biodiversity loss can be observed at different scales due to forest fragmentation and the forest habitat loss, induced by land use changes [31,32]. The decline in biodiversity induces major changes in the supply of ecosystem services [24]. Therefore, it is necessary to better comprehend how the supply of ecosystem services is linked to the biodiversity trends. Numerous studies have reported that the relationship between biodiversity and ecosystem services has been poorly studied [28,33,34]. However, understanding this relationship is very crucial for designing and implementing strategies for biodiversity conservation and natural resource utilization. Many experts have reported the need for the conservation of forest biodiversity and ecosystem services [29,35], to ensure sustainable benefits for human populations [35,36].
The Mayombe tropical forest belongs to a landscape that USAID-Central African Regional Program for the Environment (CARPE) considers as a conservation priority area [35]. This forest is part of the Transfrontier Conservation Areas (TFCAs) of the Southern Africa Development Community (SADEC) region [37]. However, the Mayombe forest has been experiencing major changes due to the high dependence of local communities on forest resources to sustain their livelihoods [38]. Most of these changes are mainly driven by agriculture [39,40], wood extraction to supply energy and construction materials [41], the collection of non-timber forest products, and expansion of villages [41]. Recently, more attention has been given to the Mayombe forest with respect to land use changes, and the focus is on the restoration of biomass storage and biodiversity in the degraded forest ecosystem [38]. Moreover, there have been several initiatives towards this forest, which are aimed at ensuring sustainable land management and implementation of projects related to the Reduction of Emissions from Deforestation and Degradation (REDD+) [38]. However, the impact of land utilization on carbon storage and forest tree biodiversity in the Mayombe forest is unknown, which calls for further studies. Sedano et al. [42] reported the easiness in detecting forest losses induced by agriculture by means of remote sensing technology and their related effects on tree biodiversity and biomass storage. However, it is difficult to detect disturbances induced by the selective harvesting of forest products for livelihood purposes, and their related effects.
The present study aims to fill this knowledge gap by examining the impact of differing intensities of forest utilization on tree biodiversity and carbon storage within the Mayombe tropical forest. Additionally, the study investigates the potential of recovery of the disturbed forest after abandonment. In order to achieve this, the following research questions were posed to guide the study: (1) how does the differing of forest utilization impact forest biodiversity and ecosystem services (carbon storage); and (2) what is the recovery potential of a disturbed forest after abandonment in the Mayombe tropical forest? Following, we hypothesized that the current human utilization of forest land induces major change in forest biodiversity and ecosystem services (carbon storage) within the Mayombe forest ecosystems, of which the magnitude will compromise the long-term sustainability of Mayombe biodiversity. The Mayombe tropical forest needs effective land management strategies to support the sustainability of natural resources that are subject to high human pressures. Thus, the findings of this study could provide new understanding to support biodiversity conservation initiatives such as the REDD+ program. Advancing the knowledge about carbon storage and forest tree biodiversity under different utilization regimes and recovery stages is very essential in developing a clear understanding of forest restoration processes and in implementing management strategies of forest ecosystems under different forest disturbance regimes [43].

2. Materials and Methods

2.1. Study Area

The present study was carried out in the Mayombe tropical forest located in the southern part of the Democratic Republic of Congo (DRC) (Figure 1). This region contains some forest remnants due to the overexploitation of natural resources [44]. The region is characterized by an annual average rainfall of 1095.66 mm, with the annual average temperature of 24.65 °C [45] (Figure 2). According to the Köppen classification, the Mayombe tropical forest is located within a humid tropical climate Aw5 [46]. The soils are generally ferrallitic and acidic [47] and are characterized by a low content of cations. The Mayombe forest is prone to anthropogenic pressure, mainly due to local population activities, such as slash-and-burn agriculture, wood harvesting for energy supply, bush fires, fuelwood, illegal logging, etc. This compromises the sustainability of natural resources in the Reserve.
Land 11 00787 g001 550
Figure 1. The study area: (a) The map of Mayombe forest in the Democratic Republic of Congo, (b) enlarged map Mayombe forest.
Figure 1. The study area: (a) The map of Mayombe forest in the Democratic Republic of Congo, (b) enlarged map Mayombe forest.
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Land 11 00787 g002 550
Figure 2. Annual temperature (a) and precipitation (b) variations, from the year 1901 to 2019 [48].
Figure 2. Annual temperature (a) and precipitation (b) variations, from the year 1901 to 2019 [48].
Land 11 00787 g002

2.2. Research Design and Methods

The present research used stratified purposive sampling to select the sampling sites [49]. The selection of sampling sites based on this approach requires the knowledge of the sites and their elements [50]. Sampling plots were established in the forest based on the land use types. The different land use types were categorized into three groups based on the intensities of human utilization in each group. The intensity of human utilization in each plot was measured by counting the number of stumps. The minimum and the maximum number of stumps were 2 and 28, respectively. Here, three classes were created, of which the first class comprised 2 stumps (minimum number of stumps) and 6 stumps (maximum number of stumps), and the mean stump number was 3.3 ± 1.3. The second class comprised 10 stumps (minimum number of stumps) and 18 stumps (maximum number of stumps), and the mean stump number of 14.9 ± 2.2. The third class comprised 21 stumps (minimum number of stumps) and 28 stumps (maximum number of stumps), and the mean stump number was 24.9 ± 2.0. Based on the intensity of human utilization, the first class was categorized as low utilized land since it had not experienced major human or natural activities. Utilization in this class mainly involved gathering of non-timber forest products, even though some trees had been harvested for artisanal logging. Given the low intensity of human utilization in this class, it was considered as undisturbed forest. The second class comprised of land where people were involved in the tree harvesting for artisanal logging and the gathering of non-timber forest products. This land was included in the moderate utilization category. The third class was the high utilization category, in which people practiced all activities including artisanal logging, charcoal production, and the harvesting of non-timber forest products. This class comprised of all types of utilizations. The biodiversity surveys were also conducted in fallow land in order to evaluate the potential of this forest to recover after moderate and high utilization. The fallow duration selected for this study was 10 to 20 years. In each category (moderate utilization and high utilization), the fallow land comprised areas that had been abandoned after being subjected to the aforementioned different activities. To ensure that sampling in different fallow lands was conducted in similar environmental conditions, information about the duration of each land use category was required, in addition to some other criteria such as the land use history, the absence of human disturbances, the absence of post-abandonment removal of some trees, biophysical conditions, and historical factors. These factors have been reported to impact forest composition and structure [51].

2.3. Plot Establishment and Field Measurements

Ninety sampling plots were established in the forest, within which the biodiversity survey was conducted. The age of fallow lands was determined before establishing the plots at a given location within the age categories. Informal interviews were used to obtain information about the historical use and ages of different land use categories. These interviews were conducted with local farmers, artisanal loggers, and charcoal producers. The interview process followed the approach suggested by Patton [52]. Therefore, we interviewed 20 respondents based on our previous discussion with local authorities, local farmers, artisanal loggers, and charcoal producers. The determination of the age of fallow land was based on the knowledge and experiences of local communities on the historical use of the land. Thus, a wide range of questions was asked to local communities in order to categorize the ages. As a result, all fallow lands were grouped into two age classes: 10 year and 20 year classes for the moderate and high land utilization, respectively. Plots measuring 30 m × 30 m were established within all land utilization types, and for those that were subject to various fallow ages [53,54]. The small plots were used in this study because of the high tree density, which makes sampling time consuming, more expensive, and more laborious [55]. As such, the selection of plot sizes was limited to the study objectives, time constraints, and resource availability [53]. Meanwhile, the geographic coordinates of each plot center were recorded using GPS (global positioning system) receivers. The diameter at breast height (DBH, 1.3 meters above ground) for each tree within each sampling plot was measured using a diameter tape [56,57,58]. The tree height of each tree was also measured. The species name for each tree with DBH greater than 10 cm was identified with the help of botanists.

2.4. Data Analysis

2.4.1. Tree Species Biodiversity and Floristic Indices

To measure the tree biodiversity, the present study used the iNEXT package implemented in the R software version 3.6.1 [59] to compute the effective species numbers, known as Hill numbers or actual diversities [60,61,62] (of order 0, 1, and 2). This was performed for all the categories of land use in order to evaluate the effect of land use change on tree biodiversity. The Hill numbers contained three components. The first component is related to the species richness and was presented by the order number of 0 (q = 0). The second component is related to the exponential of Shannon’s diversity and was presented by the order number of 1 (q = 1). The third component is related to the inverse of Simpson’s diversity and was presented by the order number of 2 (q = 2). Both Shannon and Simpson indices were used to quantify the tree biodiversity within the sites under study. Numerous studies have used the Shannon index for quantitative evaluation of biodiversity [63,64,65]. The Shannon index measures rarity and commonness of species within a sampled community. It represents the null value when only one species is present in a population with no uncertainty about what species each individual can be in a population. This study also used the Simpson index, as its utility has been demonstrated in studies related to the quantification of vegetation biodiversity [63]. The following formulas explain the computation of the integrated species richness and species abundances (Hill numbers are effective numbers of species) for quantifying tree species diversity:
q D   =   ∑ i   =   1 s p i q 1 1   −   q   =   ∑ i   =   1 s p i 0   =   s
q D   =   lim n → 1 q D exp − ∑ n   =   1 s p i log p i   =   exp H ′
q D   =   1 ∑ i   =   1 s p i 2   =   1 / D
S indicates species number in the sample, Pi represents the proportion of species relative abundance (n/N), i.e., the abundance of each species (n) in the sample divided by the total abundance of all species in the sample (N) [53,66], H′ indicates Shannon diversity index, and D represents Simpson diversity index, and q denotes the order number.

2.4.2. Quantifying Aboveground Carbon Storage

Allometric models were used to compute the aboveground biomass of individual trees using diameter and tree height. This study computed the aboveground biomass using both tree diameter and height, despite the possibility of the diameter to explain more than 95% of the variations in aboveground forest carbon stocks [67,68]. Meanwhile, several allometric models have been developed for the tropical forest. However, based on the reviewed literature, no allometric model for estimating aboveground biomass is locally available for the Mayombe tropical forest. Therefore, the allometric equation of Fayolle et al. [69] was adapted to convert field data to AGB for each tree. The predicted aboveground forest biomass for all the trees within each plot was summed up to represent the plot biomass. We then estimated the aboveground biomass at the scale of each land use category. Finally, the factor 0.5 was multiplied with the computed biomass to obtain the carbon stock for each plot, since 50% of biomass is carbon [23,70,71].

2.4.3. Statistical Analysis

Statistical tests were based on the variance of carbon storage between different land use practices. The one-way ANOVA and the post hoc test Tukey’s HSD implemented in R software version 3.6.1 [72] were performed, as they provide satisfactory results. The level of significance of the results was 0.05. To compare the mean of carbon storage at each age of fallow, the present study used the independent-samples t-test. The independent-samples t-test is used to compare the mean score, on some continuous variables, for two different groups [73].

3. Results

3.1. Tree Floristic Composition Based Land Management Regimes

In total, 3470 tree stems (2101 in low utilization class and 1369 in both moderate and high utilization classes) grouped into 92 tree species and 27 families were sampled in all the sites regardless of the type of land use. The first three families with the highest number of species were the Fabaceae family with 15 species, Annonaceae family with 12 species, and Anacardiaceae family with 11 species. These three families represented around 38% of the total number of stems recorded (Figure 3). The highest number of families (24) was recorded in the low utilization class. On the other hand, the high utilization class recorded the lowest number of families (11). All the other sites recorded 18 families, apart from the moderate utilization class that recorded 20 families at 20 years of abandonment. However, only seven families, Meliaceae, Moraceae, Euphorbiaceae, Fabaceae, Cecropiacea, Bignoniaceae, and Anacardiaceae, were present in all land utilization regimes.

3.2. Vegetation Structure

The structure of the forest stand varied with the land utilization regimes, with the low utilization regime showing a typical reverse J-shaped curve [74], which contained the highest number of stems in the first class. However, the highest number of stems in the first class of the high and moderate utilization regimes were induced by the high regeneration of trees of a similar age (5–10 years) induced by increased availability of light after opening of the forest canopy. A small number of stems were observed in the high diameter class of the high utilization regime (Figure 4).

3.3. Tree Species Richness and Diversity Based on Land Utilization Regimes

As shown in Table 1, the present study revealed a difference in effective species numbers among different land management regimes. For instance, the highest effective species number (92 tree species), Shannon index (82.48), and Simpson index (75.14) were observed in the low utilization class. The moderate utilization class recorded the highest effective species number (59 tree species), Shannon index (50.97), and Simpson index (45.32), compared to the high utilization class. The confidence interval plots of species richness, Shannon diversity index, and Simpson diversity index (Figure 5) of different land management regimes did not overlap. This shows significant differences in species richness, Shannon diversity index and Simpson diversity index between land management regimes.

3.4. Tree Species Richness and Diversity under Different Fallow Ages

The variation in biodiversity indices was observed between different fallow ages of both high and moderate utilization classes (Table 2). Upon comparing tree diversity and species richness based on the age of fallow, the highest values were recorded in the moderate utilization class. For the moderate utilization class with the fallow age of 10 years, the species richness, Shannon index, and Simpson diversity index were 63, 53.57, and 46.62, respectively. These values were greater than their corresponding values for the high utilization class with the fallow age of 10 years. For the moderate utilization class with the fallow age of 20 years, the species richness, Shannon index, and Simpson diversity index were 67, 56.67, and 48.89, respectively. These values were greater than their corresponding values for the high utilization class with the fallow age of 20 years.
However, in terms of tree species richness (computed using the Shannon index and Simpson index), there was a significant difference between the high utilization class and its related fallow age classes of 10 and 20 years, since there was no overlap of the confidence interval plots (Figure 6) for tree species richness for both indices. This was not the case for the moderate utilization class, which showed no significant difference in terms of tree species richness, Shannon index, and Simpson index between different fallow ages (Figure 7). A comparison of different tree biodiversity indices between fallow lands under different land management regimes revealed a significant difference between fallow land of high utilization and moderate utilization classes of the same age (Figure 8 and Figure 9).

3.5. Aboveground Carbon Storage

As shown in Table 3 and Figure 10, this study demonstrates that carbon storage for the high utilization class was 14.16 ± 4.09 Mg C ha−1, 23.96 ± 5.19, and 42.16 ± 8.49 Mg C ha−1, at 0 year, 10 years, and 20 years of abandonment, respectively. As for the moderate utilization class, the aboveground carbon storage was 56.04 ± 13.96 Mg C ha−1 at 0 years of abandonment, 65.21 ± 15.67 at 10 years of abandonment, and 83.20 ± 15.09 Mg C ha−1 at 20 years of abandonment. The comparison of aboveground carbon storage between the high utilization class and the moderate utilization class revealed a significant difference at 0 years of abandonment; there was a higher storage of aboveground carbon for the moderate utilization class when compared to the high utilization class (t = −15.77, p < 0.001). At 10 years after abandonment, the moderate utilization class had statistically significant higher carbon storage (65.21 ± 15.67 Mg C ha−1) than the high utilization class (23.96 ± 5.19 Mg C ha−1) (t = −13.69, p < 0.001). Statistically significant differences in carbon storage were also observed at 20 years after abandonment, with the moderate utilization class storing a higher amount of aboveground carbon (83.20 ± 15.09 Mg C ha−1) than the high utilization class (42.16 ± 8.49 Mg C ha−1) (t = −12.98, p > 0.05). A one-way ANOVA analyses showed statistically significant differences (F = 293.27, p < 0.001, Tukey’s HSD: p < 0.001) in aboveground carbon storage between the low utilization class and both moderate and high utilization classes. Carbon storage was higher in the low utilization class (124.35 ± 14.88 Mg C ha−1).

4. Discussion

4.1. Tree Biodiversity, Vegetation Structure, and Ecosystem Functioning

The present study inventoried 92 tree species and 27 families in all the sites regardless of the type of land use regimes. However, there was a significant variation in forest biodiversity measures (effective species number, Shannon index, and Simpson index) within different land utilization regimes, with high values being observed in the low utilization regime compared to both moderate and high utilization regimes. This indicated that all measures of biodiversity (effective species number, Shannon index, and Simpson index) decreased with the increase in human disturbances in the forest land. Similar responses to disturbances such the decline of biodiversity have been observed elsewhere [75,76,77]. Several studies have also reported that environmental factors such as rainfall, altitude, soils, and underlying geology can induce change in tree species composition [78,79]. However, in our study area, where environmental factors such as soil types, altitude, rainfall, and geology are relatively uniform, the variation in tree species composition is more likely to be induced by the current land use changes. Species such as Entandrophragma utile, Prioria balsamifera, Terminalia superba, and Prioria oxyphylla are overharvested within the high utilization land, since they are more preferred by local communities for sawing purposes. Lack of regeneration of these species within this land category was also observed, which may have been caused by several factors including practices of burning lands. Indeed, previous studies have reported the lack of species regeneration due to the frequent practices of burning in regenerating areas [80]. In addition, species such as Musanga cecropioides, Elaeis guineensis, Trema orientalis, and Oncoba welwitschii were dominant in high utilization lands. This could be explained by the fact that these species are fast growing and dominate in early-stage succession [81].
This study has also demonstrated a higher biodiversity in different age classes of the moderate utilization regime compared to their corresponding fallow age class in the high utilization regime. Our results were consistent with those of previous studies that reported the decline in biodiversity due to agriculture and charcoal production [82,83]. This study also revealed that, after 15 years of abandonment of lands that were subject to agriculture, logging, and charcoal production, the tree species biodiversity was still different and lower than that of the undisturbed forests. During the process of the natural vegetation restoration after disturbances related to agriculture, previous studies have reported that 40 years and 55 years of re-growth was insufficient for the species composition at re-growth sites to equal that of undisturbed forests [84,85]. Similarly, Jacobs et al. [86] suggested that it requires centuries of re-growth for the disturbed vegetation to recover the species composition as that of undisturbed forests. Similar observations were made in the Mayombe forest that was subject to agriculture and other human activities that led to the removal of trees, and its biodiversity did not recover after 20 years of abandonment. The biodiversity level was still different than that of the mature forest. However, given that tree species in the Mayombe forest are used by local communities for various purposes [39,87], the decline in tree species composition may impact the sustainability of rural livelihoods. Similarly, Chapin et al. [88] and Figueiredo and Pereira [89] reported that the decline of tree species composition due to these changes may eventually reduce the resilience and resistance of ecosystems to environmental changes.
With regard to forest stand structure, the observed reverse J-shaped curve in the low utilization regime indicates a steady and expanding population that is characterized by the highest number of trees in the smaller classes [90]. This indicates a continuous recruitment in a sustainable system [91]. Similar structure has been reported in previous studies [78,92,93]. However, the forest stand structure was significantly affected by the overexploitation of trees [94]. Indeed, the study observed a higher number of trees in the first class within both moderate and high utilization regimes. This was due to high regeneration of stems induced by the overexploitation of the tree forest within these two categories of lands, denoting an unsustainable forest utilization. In areas where tree forests are overharvested, increase in recruitment due to the increase in light is expected [95]. Meanwhile, the overharvesting of trees for various purposes has induced the lack of large trees within these two land utilization categories. Thus, more restrictions on harvesting young trees are necessary to ensure sustainable forest management within these land utilization regimes.

4.2. Carbon Storage and Changes in the Recovery Trajectory

The present study has demonstrated the effect of land management regimes on the carbon storage in the Mayombe forest. The studied sites comprised the low utilization, moderate utilization, and high utilization forest classes. To evaluate the potential of recovery of forest ecosystems after disturbances, two classes of fallow land (10 and 20 years) were considered for both moderate and high utilization. There was significant variation in the carbon stocks at different sites, with high values of carbon storage being recorded in low utilization, followed by moderate and high utilization classes, respectively. This suggests that the increase in land utilization intensities induced the decline of carbon storage within our study area. However, after 10 and 20 years of abandonment, the moderate utilization forest class provided higher carbon storage than high utilization, at both periods of abandonment. The high rate of regeneration in the forests under the moderate utilization regime can be explained by the high development of trees from the stumps. Previous studies have demonstrated the ability of tree species to regenerate from coppices [96,97,98]. Additionally, seedlings that grow under big trees may benefit from good environmental conditions after trees are cut down during charcoal production, and therefore rapidly increase the carbon stocks. However, the low regeneration in agricultural fallow lands may be attributed to the fact that slash and burning land management practices may lead to the death of plants, reducing the regeneration from stumps [99,100]. However, based on the age classes, older fallow land classes stored a higher amount of carbon compared to young fallow lands, regardless of the management regimes. These findings were consistent with previous studies conducted in the Miombo forests, where the carbon stocks were high in old fallow lands [9,17]. However, the present study provided a lower carbon amount in both moderate and high utilization under fallow, compared to undisturbed forests. Considering the variation in the carbon stocks in the recovery trajectory of both management regimes, this study provides empirical evidence of the capability of the Mayombe forest to sequester aboveground carbon.

4.3. Mayombe Forest’s Recovery Process and Carbon-Based Payment of Ecosystem Services

The findings revealed that the Mayombe forest stores a significant amount of carbon, which could contribute to the regulation of climate change. Thus, these forests are eligible to benefit from the financial support related to C-based payment of ecosystem services, which could promote their conservation. As shown in this study, the Mayombe forest has the potential to recover after human disturbances. This provides clear evidence that fallow lands under both high and moderate utilization can be managed under the REDD+ initiative to facilitate the recovery process of carbon storage, biodiversity, and other ecosystem services. This provides a double advantage to local communities through the derived income from both the sale of carbon credits and other forest products, which could entice them to the preservation of fallow lands. However, in the past, the restoration process of natural degraded forests (as observed in the Mayombe forest after clear felling for agriculture and harvesting trees for both charcoal production and timber production) was not considered in the Kyoto protocol, since this convention considered only afforestation and reforestation. In 2009, during the Copenhagen Accord and subsequent meetings, opportunities for forest restoration based on the improvement of land utilization strategies to increase carbon storage, preserve biodiversity, and improve livelihoods were adopted. This suggests that the REDD+ initiative in the Mayombe forest should integrate the process of natural recovery of degraded forests instead of only focusing on ways of mitigating deforestation. Within the Mayombe forest, this can be achieved by adopting an approach that promotes forest restoration at the scale of small farmers and charcoal producers where forest patches are allocated to various utilizations. This suggests the integration of forest trees on farmland that can provide more benefits to the farmers [101]. These practices, referred to as agroforestry, have been reported to improve agricultural yields and are therefore important in achieving sustainable food production [102] and conserving agrobiodiversity [103]. Consequently, this will provide more benefits to local communities, and improve their livelihoods through the products that they will derive from a degraded forest after its recovery.

5. Conclusions

The Mayombe tropical forest continues to experience dramatic degradation and a high rate of deforestation due to human activities. The lack of land utilization regulations results in the decline of biodiversity and supply of ecosystem services. As such, it is necessary to implement sustainable land management strategies that integrate ecological and social concerns. The findings of the present research revealed that lands under both high and moderate utilization regimes, which are experiencing a high level of disturbances, had significantly low species richness, diversity, carbon storage, and a loss of large trees compared to areas under the low utilization regime. This study further demonstrated that after 20 years of fallow, for lands under both moderate and high utilization regimes, the forest was not able to recover its original biodiversity and carbon storage. This suggests that the recovery process needs more time. However, trends in the recovery of biodiversity and ecosystem services are more acceptable in moderate utilization when compared to high utilization. Indeed, the overexploitation of forest trees in high utilization regimes induces significant damages to biodiversity and ecosystem services. Thus, a monitoring system for land utilization for both high and moderate utilizations is urgently required. This monitoring system should aim at evaluating the level of land utilization and its related impacts on forest ecosystems. Additionally, land management strategies should initiate a system of utilization that avoids complete tree felling activities for all forest land utilization regimes. This study revealed that the Mayombe tropical forest constitutes a great carbon storage forest, for which decision-makers and local communities could benefit with the funding related to carbon-based payments of ecosystem services. Based on the detailed information related to the change in tree species biodiversity and carbon storage over the recovery trajectory, this study improves the understanding of the process of restoration of degraded forest land within the Mayombe forest. Thus, for the purpose of sustainable management of the Mayombe forest, it is necessary to strengthen the capacity in governance of forest resources to support the regulation and the sustainability of forest resource utilization. This could result in the long-term maintenance of forest biodiversity and the supply of ecosystem services to local communities.

Author Contributions

Conceptualization, method development, and writing: O.O.M., W.F., Y.Y., C.K.S.K.; visualization and data processing: O.O.M. and C.C.; investigation, supervision, writing, and resources: O.O.M. and T.L. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by The Fundamental Research Funds for the Central Universities (2572019CP12).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 3. Proportion of tree stem based on different families.
Figure 3. Proportion of tree stem based on different families.
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Figure 4. The structure of the stand based on DBH classes over different land utilization regimes: (1) DBH < 10 cm; (2) DBH 11–20 cm; (3) DBH 21–30 cm; (4) DBH 31–40 cm; (5) DBH ≥ 40 cm.
Figure 4. The structure of the stand based on DBH classes over different land utilization regimes: (1) DBH < 10 cm; (2) DBH 11–20 cm; (3) DBH 21–30 cm; (4) DBH 31–40 cm; (5) DBH ≥ 40 cm.
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Figure 5. Comparison of tree species biodiversity between different land utilization regimes based on Hill numbers for different orders (0, 1, and 2). The solid and dotted line represent rarefaction and the extrapolation curve, respectively. The shaded area indicates the confidence interval at 95%, based on bootstrap method with 200 replications.
Figure 5. Comparison of tree species biodiversity between different land utilization regimes based on Hill numbers for different orders (0, 1, and 2). The solid and dotted line represent rarefaction and the extrapolation curve, respectively. The shaded area indicates the confidence interval at 95%, based on bootstrap method with 200 replications.
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Figure 6. Comparison of tree species biodiversity between different sites under high utilization management regimes based on Hill numbers for different orders (0, 1, and 2). The solid and dotted lines represent the rarefaction and extrapolation curves, respectively. The shaded area indicates the confidence interval at 95%, based on bootstrap method with 200 replications.
Figure 6. Comparison of tree species biodiversity between different sites under high utilization management regimes based on Hill numbers for different orders (0, 1, and 2). The solid and dotted lines represent the rarefaction and extrapolation curves, respectively. The shaded area indicates the confidence interval at 95%, based on bootstrap method with 200 replications.
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Figure 7. Comparison of tree species biodiversity between different sites under moderate utilization management regime based on Hill numbers for different orders (0, 1, and 2). The solid and dotted line represent the rarefaction and extrapolation curves, respectively. The shaded area indicates the confidence interval at 95%, based on bootstrap method with 200 replications.
Figure 7. Comparison of tree species biodiversity between different sites under moderate utilization management regime based on Hill numbers for different orders (0, 1, and 2). The solid and dotted line represent the rarefaction and extrapolation curves, respectively. The shaded area indicates the confidence interval at 95%, based on bootstrap method with 200 replications.
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Land 11 00787 g008 550
Figure 8. Comparison of tree species biodiversity between high and moderate utilization regimes after 10 years of abandonment based on Hill numbers for different orders (0, 1, and 2). The solid and dotted lines represent the rarefaction and extrapolation curves, respectively. The shaded area indicates the confidence interval at 95%, based on bootstrap method with 200 replications.
Figure 8. Comparison of tree species biodiversity between high and moderate utilization regimes after 10 years of abandonment based on Hill numbers for different orders (0, 1, and 2). The solid and dotted lines represent the rarefaction and extrapolation curves, respectively. The shaded area indicates the confidence interval at 95%, based on bootstrap method with 200 replications.
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Land 11 00787 g009 550
Figure 9. Comparison of tree species biodiversity between high and moderate utilization regimes after 20 years of abandonment based on Hill numbers for different orders (0, 1, and 2). The solid and dotted lines represent the rarefaction and extrapolation curves, respectively. The shaded area indicates the confidence interval at 95%, based on bootstrap method with 200 replications.
Figure 9. Comparison of tree species biodiversity between high and moderate utilization regimes after 20 years of abandonment based on Hill numbers for different orders (0, 1, and 2). The solid and dotted lines represent the rarefaction and extrapolation curves, respectively. The shaded area indicates the confidence interval at 95%, based on bootstrap method with 200 replications.
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Land 11 00787 g010 550
Figure 10. The effect of fallow time on carbon storage recovery. 1: Low utilization, 2: moderate utilization at 10 years of abandonment, 3: moderate utilization at 20 years of abandonment, 4: high utilization at 10 years of abandonment, 5: high utilization at 20 years of abandonment. The black box and the red line represent the mean carbon value and the standard error, respectively.
Figure 10. The effect of fallow time on carbon storage recovery. 1: Low utilization, 2: moderate utilization at 10 years of abandonment, 3: moderate utilization at 20 years of abandonment, 4: high utilization at 10 years of abandonment, 5: high utilization at 20 years of abandonment. The black box and the red line represent the mean carbon value and the standard error, respectively.
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Table
Table 1. Estimation of species biodiversity of land under different management regimes.
Table 1. Estimation of species biodiversity of land under different management regimes.
Biodiversity Measure
Species RichnessShannon DiversitySimpson Diversity
SitesObservedEstimatedS.eObservedEstimatedS.eObservedEstimatedS.e
Low utilization92.0092.000.1782.4884.300.8775.1477.891.52
Moderate utilization59.0066.495.2850.9763.573.2145.3261.975.2
High utilization20.0020.250.6116.7319.321.5014.4817.872.04
Table
Table 2. Species biodiversity measure between sites under different fallow regimes.
Table 2. Species biodiversity measure between sites under different fallow regimes.
Biodiversity Measure
Species RichnessShannon DiversitySimpson Diversity
SitesObservedEstimatedS.eObservedEstimatedS.eObservedEstimatedS.e
High 10 years4751.633.7532.9137.822.3525.2328.682.36
High 20 years5557.032.1841.6746.351.8333.8338.272.50
Moderate 10 years6363.260.6053.5760.822.2046.6256.593.51
Moderate 20 years6767.501.0356.6762.042.0248.8955.883.09
Table
Table 3. Comparisons of aboveground carbon storage between sites at different age classes of abandoned fallows.
Table 3. Comparisons of aboveground carbon storage between sites at different age classes of abandoned fallows.
Plot AgeMean Aboveground Storaget-Valuep-Value
High Utilization ClassModerate Utilization Class
10 years23.96 ± 5.1965.21 ± 15.67−13.69 <0.001
20 years42.16 ± 8.4983.20 ± 15.09−12.98 <0.001
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Michel, O.O.; Yu, Y.; Fan, W.; Lubalega, T.; Chen, C.; Sudi Kaiko, C.K. Impact of Land Use Change on Tree Diversity and Aboveground Carbon Storage in the Mayombe Tropical Forest of the Democratic Republic of Congo. Land 2022, 11, 787. https://doi.org/10.3390/land11060787

AMA Style

Michel OO, Yu Y, Fan W, Lubalega T, Chen C, Sudi Kaiko CK. Impact of Land Use Change on Tree Diversity and Aboveground Carbon Storage in the Mayombe Tropical Forest of the Democratic Republic of Congo. Land. 2022; 11(6):787. https://doi.org/10.3390/land11060787

Chicago/Turabian Style

Michel, Opelele Omeno, Ying Yu, Wenyi Fan, Tolerant Lubalega, Chen Chen, and Claude Kachaka Sudi Kaiko. 2022. "Impact of Land Use Change on Tree Diversity and Aboveground Carbon Storage in the Mayombe Tropical Forest of the Democratic Republic of Congo" Land 11, no. 6: 787. https://doi.org/10.3390/land11060787

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