Long-Term Vegetation Change in Central Africa: The Need for an Integrated Management Framework for Forests and Savannas

peer reviewedTropical forests and savannas are the main biomes in sub-Saharan Africa, covering most of the continent. Collectively they offer important habitat for biodiversity and provide multiple ecosystem services. Considering their global importance and the multiple sustainability challenges they face in the era of the Anthropocene, this chapter undertakes a comprehensive analysis of the past, present, and future vegetation patterns in central African forests and savannas. Past changes in climate, vegetation, land use, and human activity have affected the distribution of forests and savannas across central Africa. Currently, forests form a continuous block across the wet and moist areas of central Africa, and are characterized by high tree cover (>90% tree cover). Savannas and woodlands have lower tree cover (<40% tree cover), are found in drier sites in the north and south of the region, and are maintained by frequent fires. Recent tree cover loss (2000–2015) has been more important for forests than for savannas, which, however, reportedly experienced woody encroachment. Future cropland expansion is expected to have a strong impact on savannas, while the extent of climatic impacts depends on the actual scenario. We finally identify some of the policy implications for restoring ecosystems, expanding protected areas, and designing sustainable ecosystem management approaches in the region

New data on the recent history of the littoral forests of southern Cameroon: an insight into the role of historical human disturbances on the current forest composition

Background and aims–Prior to European colonisation of Central Africa, human populations were dispersed through the forests, where they practiced slash-and-burn cultivation. From the 19th century they were progressively concentrated in villages along roads, leaving large areas of forest derelict. In south-western Cameroon, and elsewhere in Central Africa, forest canopy is dominated by long-lived lightdemanding tree species, suggesting a possible role of human disturbance. The aim of this study was to bring new insights into the possible effect of historical human disturbances in terms of timing and spatial extent on the current forest composition. Location–Wet evergreen littoral forest in south-western Cameroon. Methods and key results–A combined vegetation sampling and archaeobotanical survey were conducted. Potsherds, oil-palm endocarps, and charcoal were found throughout the study area, suggesting generalised human occupation and anthropogenic fire. Human occupancy occurred in two periods: between 2200 and 1500 BP, and, more recently, beginning three centuries ago. High frequency of fire and the presence of Elaeis guineensis both dated recently (between 260 and 145 BP) suggest slash-and-burn shifting cultivation practices. These human-induced disturbances may coincide with the age of the current emergent lightdemanding species, the age of which can be estimated around 200 years, or with the phases of drying climate recorded in the Central African forest in the early 18th century. Conclusions–These results support the idea that historical human disturbances are one of the major factors that shaped the current forest composition in Central Africa.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Soil charcoal to assess the impacts of past human disturbances on tropical forests

The canopy of many central African forests is dominated by light-demanding tree species that do not regenerate well under themselves. The prevalence of these species might result from ancient slash-and-burn agricultural activities that created large openings, while a decline of these activities since the colonial period could explain their deficit of regeneration. To verify this hypothesis, we compared soil charcoal abundance, used as a proxy for past slash-and-burn agriculture, and tree species composition assessed on 208 rainforest 0.2 ha plots located in three areas from Southern Cameroon. Species were classified in regeneration guilds (pioneer, non-pioneer light-demanding, shade-bearer) and characterized by their woodspecific gravity, assumed to reflect light requirement. We tested the correlation between soil charcoal abundance and: (i) the relative abundance of each guild, (ii) each species and family abundance and (iii) mean wood-specific gravity. Charcoal was found in 83% of the plots, indicating frequent past forest fires. Radiocarbon dating revealed two periods of fires: ‘‘recent’’ charcoal were on average 300 years old (up to 860 BP, n = 16) and occurred in the uppermost 20 cm soil layer, while ‘‘ancient’’ charcoal were on average 1900 years old (range: 1500 to 2800 BP, n = 43, excluding one sample dated 9400 BP), and found in all soil layers. While we expected a positive correlation between the relative abundance of light demanding species and charcoal abundance in the upper soil layer, overall there was no evidence that the current heterogeneity in tree species composition can be explained by charcoal abundance in any soil layer. The absence of signal supporting our hypothesis might result from (i) a relatively uniform impact of past slash-and-burn activities, (ii) pedoturbation processes bringing ancient charcoal to the upper soil layer, blurring the signal of centuries-old Human disturbances, or (iii) the prevalence of other environmental factors on species composition

Data from: The influence of spatially structured soil properties on tree community assemblages at a landscape scale in the tropical forests of southern Cameroon

Species distribution within plant communities results from both the influence of deterministic processes, related to environmental conditions, and neutral processes related to dispersal limitation and stochastic events, the relative importance of each factor depending on the observation scale. Assessing the relative contribution of environment necessitates controlling for spatial dependences among data points. Recent methods, combining multiple regression and Moran's eigenvectors maps (MEM), have been proved successful in disentangling the influence of pure spatial processes related to dispersal limitation, pure environmental variables (not spatially structured) and spatially structured environmental properties. However, the latter influence is usually not testable when using advanced spatial models like MEM. To overcome this issue, we propose an original approach, based on torus-translations and Moran spectral randomizations, to test the fraction of species abundance variation that is jointly explained by space and seven soil variables, using three environmental and tree species abundance data sets (consisting of 120, 52 and 34 plots of 0·2 ha each, located along 101-, 66- and 35-km-long transect-like inventories, respectively) collected in tropical moist forests in southern Cameroon. The overall abundance of species represented by ≥30 individuals, and 27% of these species taken individually, were significantly explained by fine-scale (<5 km) and/or broad-scale (5–100 km) spatially structured variations in soil nutrient concentrations (essentially the concentration of available Mn, Mg and Ca) along the 120-plots area. The number of significant tests considerably decreased when investigating the two smaller data sets, which mostly resulted from low statistical power rather than weaker floristic and/or edaphic variation captured among plots. Synthesis. Our results provide evidence that tree species turnovers are partly controlled by spatially structured concentrations in soil nutrients at scales ranging from few hundreds of metres to c. 100 km, a poorly documented subject in Central African forests. We also highlight the usefulness of our testing procedure to correctly interpret the space-soil fraction of variation partitioning analyses (which always accounted here for the most important part of the soil contribution), as this fraction was sometimes relatively high (R2 values up to c. 0·3) but nearly or not significant

Autocorrelogram of CAI values for each study area: mean Moran's <i>I</i> computed for 12 to 14 distance intervals.

<p>On the left side (<1 m), the abscissa for the two first symbols represent the vertical distance between soil layers from a same pit, the left and right symbols distinguishing adjacent layers from non-adjacent layers, respectively. On the right side (>10 m), the abscissa corresponds to horizontal distance between soil volumes from different pits located in a same plot (first symbol between 10 m and 100 m), different plots of a same site (between 100 m and 5000 m) or different sites (>5000 m). Full symbols indicate significantly positive or negative Moran's <i>I</i> value (<i>P</i><0.05).</p

Geographical location of the three study areas.

<p>Each site is represented by a rectangle. Sites in Areas 1 and 2 are linearly disposed along a virtual transect represented by a dashed line.</p

Age-depth relationship for 60 charcoal fragments sampled in the three areas investigated.

<p>Charcoals collected in a same soil pit are connected by a dashed line.</p

Pearson correlations between CAI in two soil layers (0–20 cm and 20–100 cm) and variables related to species functional traits.

<p>P/NPLD/SB  =  relative abundance of Pioneers/Non-Pioneer Light-Demanders/Shade-Bearers.</p>a<p>Wood-specific gravity (g/cm³).</p>b<p><i>r</i>-Pearson correlation between row variable and CAI in the (i) 0–20 cm (upper line) and (ii) the 20–100 cm (bottom line; values in italics) soil layers. “*”indicates significant test with the classic correlation test: *<i>p</i>< = 0.05 **<i>p</i><0.01 ***<i>p</i><0.001. All the tests based on toroidal translations were non-significant.</p><p>Pearson correlations between CAI in two soil layers (0–20 cm and 20–100 cm) and variables related to species functional traits.</p

Abundance and diversity data for each study area.

<p>RG  =  regeneration guild. P  =  Pioneers. NPLD  =  Non-Pioneer Light-Demanders. SB  =  Shade-bearers. ENS(2) or ENS(100)  =  effective number of species expected for a random sample of 2 or 100 individuals. Ind.  =  individuals. Sp.  =  species. WSG  =  wood-specific gravity (g/cm³). GS  =  <i>Greenwayodendron suaveolens</i> (Annonaceae). BW  =  <i>Blighia welwitschii</i> (Sapindaceae).</p>a<p>Percentage calculated over the total number of stems in the study area.</p>b<p>Percentage calculated over the total number of species in the study area.</p>c<p>Percentage calculated over the number of individuals assigned to a RG.</p><p>Abundance and diversity data for each study area.</p

Mean charcoal abundance index (CAI) and functional trait variables per site, and Kruskal-Wallis tests for among sites differences within each study area (using values computed at the plot level).

<p>Sites 1 to 6, 7 to 9, and 10 to 12 correspond to Areas 1, 2 and 3, respectively.</p>a<p>Charcoal abundance index (0–20 cm and 20–100 cm).</p>b<p>Wood-specific gravity (g/cm³).</p>c<p><i>P</i>-value of a Kruskal-Wallis test among sites: *<i>p</i>-value <0.05, **<i>p</i>-value <0.01, *** <i>p</i>-value <0.001. P/NPLD/SB  =  Pioneers/Non-Pioneer Light-Demanders/Shade-Bearers. a  =  relative abundance. b  =  relative basal area.</p><p>Mean charcoal abundance index (CAI) and functional trait variables per site, and Kruskal-Wallis tests for among sites differences within each study area (using values computed at the plot level).</p