• Energy Research

Aim Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns. Location Tropical rain forest, West Africa and Atlantic Central Africa. Methods Alpha diversity estimates were compiled for trees with diameter at breast height = 10 cm in 573 inventory plots. Linear regression (ordinary least squares, OLS) and random forest (RF) statistical techniques were used to project alpha diversity estimates at unsampled locations using climate data and remote sensing data [Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI), Quick Scatterometer (QSCAT), tree cover, elevation]. The prediction reliabilities of OLS and RF models were evaluated using a novel approach and compared to that of a kriging model based on geographic location alone. Results The predictive power of the kriging model was comparable to that of OLS and RF models based on climatic and remote sensing data. The three models provided congruent predictions of alpha diversity in well-sampled areas but not in poorly inventoried locations. The reliability of the predictions of all three models declined markedly with distance from points with inventory data, becoming very low at distances > 50 km. According to inventory data, Atlantic Central African forests display a higher mean alpha diversity than do West African forests. Main conclusions The lower tree alpha diversity in West Africa than in Atlantic Central Africa may reflect a richer regional species pool in the latter. Our results emphasize and illustrate the need to test model predictions in a spatially explicit manner. Good OLS or RF model predictions from inventory data at short distance largely result from the strong spatial autocorrelation displayed by both the alpha diversity and the predictive variables rather than necessarily from causal relationships. Our results suggest that alpha diversity is driven by history rather than by the contemporary environment. Given the low predictive power of models, we call for a major effort to broaden the geographical extent and intensity of forest assessments to expand our knowledge of African rain forest diversity.

Tropical agroforestry systems support the wellbeing of many smallholder farmers. These systems provide smallholders with crops for consumption and income through their ecological interactions between their tree, soil, and crop components. These interactions, however, could be vulnerable to changes in climate conditions; yet a reliable understanding of how this could happen is not well documented. The aim of this study is to understand how tree-soil-crop interactions and crop yield are affected by changes in climate conditions, which has implications for recognising how these systems could be affected by climate change. We used a space-for-time climate analogue approach, in conjunction with structural equation modelling, to empirically examine how warmer and drier climate conditions affects tree-soil-crop interactions and banana yield in Mt. Kilimanjaro's homegarden agroforest. Overall, the change in climate conditions negatively affected ecological interactions in the homegardens by destabilizing soil nutrient cycles. Banana yield, however, was mainly directly influenced by the climate. Banana yields could initially benefit from the warmer climate before later declining under water stress. Our findings imply that under increasingly warmer and drier climate conditions, homegarden agroforestry may not be a robust long-term farming practice which can protect smallholder's wellbeing unless effective irrigation measures are implemented.

Tropical species with narrow elevational ranges may be thermally specialized and vulnerable to global warming. Local studies of distributions along elevational gradients reveal small-scale patterns but do not allow generalizations among geographic regions or taxa. We critically assessed data from 249 studies of species elevational distributions in the American, African, and Asia-Pacific tropics. Of these, 150 had sufficient data quality, sampling intensity, elevational range, and freedom from serious habitat disturbance to permit robust across-study comparisons. We found four main patterns: (1) species classified as elevational specialists (upper- or lower-zone specialists) are relatively more frequent in the American than Asia-Pacific tropics, with African tropics being intermediate; (2) elevational specialists are rare on islands, especially oceanic and smaller continental islands, largely due to a paucity of upper-zone specialists; (3) a relatively high proportion of plants and ectothermic vertebrates (amphibians and reptiles) are upper-zone specialists; and (4) relatively few endothermic vertebrates (birds and mammals) are upper-zone specialists. Understanding these broad-scale trends will help identify taxa and geographic regions vulnerable to global warming and highlight future research priorities.

We report above-ground biomass (AGB), basal area, stem density and wood mass density estimates from 260 sample plots (mean size: 1.2 ha) in intact closed-canopy tropical forests across 12 African countries. Mean AGB is 395.7 Mg dry mass ha −1 (95% CI: 14.3), substantially higher than Amazonian values, with the Congo Basin and contiguous forest region attaining AGB values (429 Mg ha −1 ) similar to those of Bornean forests, and significantly greater than East or West African forests. AGB therefore appears generally higher in palaeo- compared with neotropical forests. However, mean stem density is low (426 ± 11 stems ha −1 greater than or equal to 100 mm diameter) compared with both Amazonian and Bornean forests (cf. approx. 600) and is the signature structural feature of African tropical forests. While spatial autocorrelation complicates analyses, AGB shows a positive relationship with rainfall in the driest nine months of the year, and an opposite association with the wettest three months of the year; a negative relationship with temperature; positive relationship with clay-rich soils; and negative relationships with C : N ratio (suggesting a positive soil phosphorus–AGB relationship), and soil fertility computed as the sum of base cations. The results indicate that AGB is mediated by both climate and soils, and suggest that the AGB of African closed-canopy tropical forests may be particularly sensitive to future precipitation and temperature changes.