Search Results (622)

Since 2014, the Paleoanthropology Group of the National Museum of Natural Sciences (CSIC), in collaboration with Equatoguinean researchers, has been conducting archeo-paleontological fieldwork in Equatorial Guinea, continuing a longstanding Spanish naturalist tradition in this region of West Central Africa. These multidisciplinary investigations, framed within an archeo-paleo-anthropological approach, aim primarily to identify early human occupation in the Central African rainforests. To date, robust evidence of Pleistocene human presence has been documented, particularly through lithic assemblages. Although the scarcity and fragmentation of well-dated sites in Central Africa complicate chronological placement, technological traits observed in the lithic industries recorded in Equatorial Guinea show clear affinities with the African Middle Stone Age (MSA). Complementary taphonomic analyses of faunal remains have been undertaken to better understand bone preservation and fossilization processes under tropical rainforest conditions, thereby contributing to the interpretation of archeological contexts. In parallel, ongoing primatological research within the project—focused on extant primates in their natural habitats—seeks to provide ethological models relevant to the study of hominin locomotor evolution. Notably, the project has led to the ecogeographic characterization of the Engong chimpanzee group in Monte Alén National Park, one of the country’s most pristine protected areas. Full article

Cancer disparities in low- and middle-income countries (LMICs) arise from multifaceted interactions between environmental exposures, infectious agents, and systemic inequities, such as limited access to care. The exposome, a framework encompassing the totality of non-genetic exposures throughout life, offers a powerful lens for understanding these disparities. In LMICs, populations are disproportionately affected by air and water pollution, occupational hazards, and oncogenic infections, including human papillomavirus (HPV), hepatitis B virus (HBV), Helicobacter pylori (H. pylori), human immunodeficiency virus (HIV), and neglected tropical diseases, such as schistosomiasis. These infectious agents contribute to increased cancer susceptibility and poor outcomes, particularly in immunocompromised individuals. Moreover, climate change, food insecurity, and barriers to healthcare access exacerbate these risks. This review adopts a population-level exposome approach to explore how environmental and infectious exposures intersect with genetic, epigenetic, and immune mechanisms to influence cancer incidence and progression in LMICs. We highlight the critical pathways linking chronic exposure and inflammation to tumor development and evaluate strategies such as HPV and HBV vaccination, antiretroviral therapy, and environmental regulation. Special attention is given to tools such as exposome-wide association studies (ExWASs), which offer promise for exposure surveillance, early detection, and public health policy. By integrating exposomic insights into national health systems, especially in regions such as sub-Saharan Africa (SSA) and South Asia, LMICs can advance equitable cancer prevention and control strategies. A holistic, exposome-informed strategy is essential for reducing global cancer disparities and improving outcomes in vulnerable populations. Full article

The agronomic effectiveness of biofertilizers is influenced by strain origin, genetic identity, crop genotype, soil type, and environmental conditions. For best results, both the plant and rhizobia strain must be adapted to the common harsh soil conditions in the tropics. While plant varieties have changed over the years, complementary research on new strains effectiveness under varying soil fertility conditions has lagged in southern Africa. Seven field experiments were established in the main soybean-producing areas of Zimbabwe in the north, central, and north–east regions to evaluate agronomic benefits of new rhizobia strains against the current exotic commercial strain (MAR1491). One site was irrigated (site 3), and the other six sites were rainfed (sites 1, 2, 4, 5, 6, and 7). While trends in inoculation response varied from site to site due to site conditions, inoculation with the strains NAZ15, NAZ25, and NAK128 consistently yielded high grain yields, which were similar to the current commercial strain MAR1491 and to application of mineral fertilizer (51.75 and 100 kg N ha⁻¹). Grain yield levels were generally below 2 t ha⁻¹ for sites 2, 3, and 5 and above 2 t ha⁻¹ for sites 1, 4, and 6, while for the irrigated site 3, they ranged upwards of 3 t ha⁻¹. When irrigated, all strains except NAK9 performed similarly in terms of grain yields and aboveground N uptake. Further testing on the inclusion of the indigenous strains NAZ15, NAZ25, and NAK128 in multi-strain commercial inoculant production targeting application in regions and soils where they excel beyond the current exotic strain MAR1491 is recommended. Full article

In a warming climate, rising temperature are expected to influence atmospheric humidity. This study examined the spatio-temporal dynamics of temperature (TEMP) and relative humidity (RH) across Equatorial Africa from 1980 to 2020. The analysis used RH data from European Centre of Medium-range Weather Forecasts Reanalysis v.5 (ERA5) reanalysis, TEMP and precipitation (PRE) from Climate Research Unit (CRU), and soil moisture (SM) and evapotranspiration (ET) from the Global Land Evaporation Amsterdam Model (GLEAM). In addition, four teleconnection indices were considered: El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO). This study used the Mann–Kendall test and Sen’s slope estimator to analyze trends, alongside multiple linear regression to investigate the relationships between TEMP, RH, and key climatic variables—namely evapotranspiration (ET), soil moisture (SM), and precipitation (PRE)—as well as large-scale teleconnection indices (e.g., IOD, ENSO, PDO, and NAO) on annual and seasonal scales. The key findings are as follows: (1) mean annual TEMP exceeding 30 °C and RH less than 30% were concentrated in arid regions of the Sahelian–Sudano belt in West Africa (WAF), Central Africa (CAF) and North East Africa (NEAF). Semi-arid regions in the Sahelian–Guinean belt recorded moderate TEMP (25–30 °C) and RH (30–60%), while the Guinean coastal belt and Congo Basin experienced cooler, more humid conditions (TEMP < 20 °C, RH (60–90%). (2) Trend analysis using Mann–Kendal and Sen slope estimator analysis revealed spatial heterogeneity, with increasing TEMP and deceasing RH trends varying by region and season. (3) The warming rate was higher in arid and semi-arid areas, with seasonal rates exceeding annual averages (0.18 °C decade⁻¹). Winter (0.27 °C decade⁻¹) and spring (0.20 °C decade⁻¹) exhibited the strongest warming, followed by autumn (0.18 °C decade⁻¹) and summer (0.10 °C decade⁻¹). (4) RH trends showed stronger seasonal decline compared to annual changes, with reduction ranging from 5 to 10% per decade in certain seasons, and about 2% per decade annually. (5) Pearson correlation analysis demonstrated a strong negative relationship between TEMP and RH with a correlation coefficient of r = − 0.60. (6) Significant associations were also observed between TEMP/RH and both climatic variables (ET, SM, PRE) and large scale-teleconnection indices (ENSO, IOD, PDO, NAO), indicating that surface conditions may reflect a combination of local response and remote climate influences. However, further analysis is needed to distinguish the extent to which local variability is independently driven versus being a response to large-scale forcing. Overall, this research highlights the physical mechanism linking TEMP and RH trends and their climatic drivers, offering insights into how these changes may impact different ecological and socio-economic sectors. Full article

After decades of calls for more sustainable land use systems, there is still a lack of consensus on an appropriate way forward, especially for tropical and subtropical agroecosystems. Land Maxing utilises appropriate, community-based interventions to fortify and maximise the multiple, long-term benefits and interest flows from investments that rebuild all six essential capitals of sustainable development (natural, social, human, physical, financial and political/corporate will) for resource-poor smallholder communities in tropical and subtropical countries. Land Maxing adds domestication of overlooked indigenous food tree species, and the commercialization of their marketable products, to existing land restoration efforts while empowering local communities, enhancing food sovereignty, and boosting the local economy and overall production. These agroecological and socio-economic interventions sustainably restore and intensify subsistence agriculture replacing conventional negative trade-offs with fortifying ‘trade-ons’. Land Maxing is therefore productive, regenerative, remunerative and transformative for farming communities in the tropics and sub-tropics. Through the development of resilience at all levels, Land Maxing uniquely addresses the big global issues of environmental degradation, hunger, malnutrition, poverty and social injustice, while mitigating climate change and restoring wildlife habitats. This buffers subsistence farming from population growth and poor international governance. The Tropical Agricultural Association International is currently planning a programme to up-scale and out-scale Land Maxing in Africa. Full article

For tropical forests characterized by tall and densely packed trees, even long-wavelength SAR signals may fail to achieve full penetration, posing a significant challenge for retrieving sub-canopy terrain using polarimetric interferometric SAR (InSAR)(PolInSAR) techniques. This paper proposes a single-baseline PolInSAR-based correction method for sub-canopy terrain estimation based on a one-dimensional lookup table (LUT) that links forest height to unpenetrated depth. The approach begins by applying an optimal normal matrix approximation to constrain the complex coherence measurements. Subsequently, the difference between the PolInSAR Digital Terrain Model (DTM) derived from the Random Volume over Ground (RVoG) model and the LiDAR DTM is defined as the unpenetrated depth. A nonlinear iterative optimization algorithm is then employed to estimate forest height, from which a fundamental mapping between forest height and unpenetrated depth is established. This mapping can be used to correct the bias in sub-canopy terrain estimation based on the PolInSAR RVoG model, even with only a small amount of sparse LiDAR DTM data. To validate the effectiveness of the method, experiments were conducted using fully polarimetric P-band airborne SAR data acquired by the European Space Agency (ESA) during the AfriSAR campaign over the Mabounie region in Gabon, Africa, in 2016. The experimental results demonstrate that the proposed method effectively mitigates terrain estimation errors caused by insufficient signal penetration or the limitation of single-interferometric geometry. Further analysis reveals that the availability of sufficient and precise forest height data significantly improves sub-canopy terrain accuracy. Compared with LiDAR-derived DTM, the proposed method achieves an average root mean square error (RMSE) of 5.90 m, representing an accuracy improvement of approximately 38.3% over traditional RVoG-derived InSAR DTM retrieval. These findings further confirm that there exist unpenetrated phenomena in single-baseline low-frequency PolInSAR-derived DTMs of tropical forested areas. Nevertheless, when sparse LiDAR topographic data is available, the integration of fully PolInSAR data with LUT-based compensation enables improved sub-canopy terrain retrieval. This provides a promising technical pathway with single-baseline configuration for spaceborne missions, such as ESA’s BIOMASS mission, to estimate sub-canopy terrain in tropical-rainforest regions. Full article

Urban settings in West Africa are increasingly experiencing extreme weather events, such as heat waves, floods, and windstorms. Climate phenomena exacerbated by global climate change are not unique to this region but reflect a broader trend of worldwide environmental changes. However, how local communities in tropical cities in the global south adapt to these extreme events is not fully understood. Understanding local adaptation strategies is crucial in enhancing our ability to develop context-specific policies that address climate vulnerabilities. This study aimed to analyse the adaptation and mitigation strategies employed by the urban residents of Abuja and Ouagadougou in response to recurrent floods, heat waves, and windstorms. To investigate adaptation and mitigation strategies for climate change in urban areas, this study collected quantitative data from a sample of 840 households in Abuja and 840 households in Ouagadougou. The results revealed that the participants of each city used different strategies to adapt to and mitigate heat waves, floods, and windstorms. However, the level of adoption of these measures differed among the respondents. The findings revealed a low level of adoption of climate change mitigation measures. Context-specific policies must prioritise strengthening local adaptation strategies, addressing socioeconomic disparities, and fostering urban design solutions tailored to each city’s unique environmental and infrastructural challenges. Full article

Land-based bioenergy systems are increasingly promoted for their potential to support climate change mitigation and energy security. Building on previous productivity and efficiency analyses, this study applies the MiscanFor and SalixFor models to evaluate land use energy intensity (LUEI) for Miscanthus (Miscanthus × giganteus) and willow (Salix spp.) under baseline (1961–1990) and future climate scenarios, and Business-as-Usual (B1) and Fossil Intensive (A1FI) scenarios, projected to 2060. The study also assesses the impact of biomass transport on energy use efficiency (EUE) and quantifies soil organic carbon (SOC) sequestration by Miscanthus. Under current conditions, Miscanthus exhibits a higher global mean LUEI (321 ± 179 GJ ha⁻¹) than willow (164 ± 115.6 GJ ha⁻¹) across all regions (p < 0.0001), with energy yield hotspots in tropical and subtropical regions such as South America, Sub-Saharan Africa, and Southeast Asia. Colder regions, such as Europe and Canada, show limited energy potential. By 2060, LUEI is projected to decline by 9–15% for Miscanthus and 8–13% for willow, with B1 improving energy returns in temperate zones and A1FI reducing them in the tropics. Global EUE for Miscanthus declines significantly (p < 0.0001) by 21%, from 15.73 ± 7.1 to 12.37 ± 5.2 as biomass transport distance increases from 50 km to 500 km. Mean SOC sequestration is estimated at 1.20 ± 1.46 t C ha⁻¹, with tropical hotspots reaching up to 4.57 t C ha⁻¹ and some cooler regions exhibiting net losses (–7.93 t C ha⁻¹). Climate change significantly reduces SOC gains compared to baseline (p < 0.0001), although differences between B1 and A1FI are not statistically significant. These findings highlight the importance of region-specific, climate-resilient biomass systems to optimize energy returns and carbon benefits under future climate conditions. Full article

Natural wetlands are critical water quality regulators, especially in developing tropical countries. The Lubigi wetland is a large urban wetland in Kampala, the largest city in Uganda in Africa. We studied whether stormwater discharge and wastewater effluent from a nearby stormwater channel and a sewage treatment plant in the western part of the city were cleaned as they flowed through the wetland. Despite the significant pollution, the wetland removed ammonium-nitrogen, orthophosphate, and particulate nutrients during both seasons, achieving removal rates ranging from 50 to 60% for orthophosphate but only 20–40% for ammonium-nitrogen. Overall, seasonal differences in loads and retention rates of nutrient and organic matter inputs were minimal. Interestingly, the wetland mostly released nitrate and nitrite during water passage through the wetland, most likely due to the mineralization of organic nitrogen and agricultural run-off during rainy events in the wet season. However, the limited capacity of the sewage treatment plant and untreated stormwater discharge from the Nsooba main channel reduced the wetland’s ability to clean water. The insufficient carrying capacity of the treatment plant and the release of untreated sewage into the wetland significantly impact the self-purification capacity of the Lubigi wetland. Thus, the concept of Nature-Based Solutions is ineffective if the wetland systems are overloaded. Full article

Sorghum (Sorghum bicolor, (L.) Moench.), is one of the most important cereals in semi-arid and subtropical regions of Africa. However, in these regions, sorghum cultivation is often faced with several constraints. In Mali, terminal or post-flowering drought, caused by the early cessation of rains towards the end of the rainy season, is one of the most common constraints. Sorghum is generally adapted to harsh conditions. However, drought combined to heat reduce its yield and production in tropical and subtropical regions. To identify parents of sorghum hybrids tolerant to post-flowering drought for commercial hybrids development and deployment, a total of 200 genotypes, including male and female parents of the hybrids, were evaluated in 2022 by lysimeters under two water regimes, well-irrigated and water-stressed, at ICRISAT in Niger. Agronomic traits such as phenological stages, physiological traits including transpiration efficiency, and morphological traits such as green leaf number were recorded. Genotype × environment (G × E) interaction was significant for harvest index (HI), green leaf number (GLN), and transpiration efficiency (TE), indicating different responses of genotypes under varying water conditions. Transpiration efficiency (TE) was significantly and positively correlated with total biomass (BT), harvest index (HI), and grain weight (GW) under both stress conditions. Genotypes ICSV216094, ICSB293, ICSV1049, ICSV1460016, and ICSV216074 performed better under optimal and stress conditions. The Principal Component Analysis (PCA) results led to the identification of three groups of genotypes. The Groups 1 and 3 are characterized by their yield stability and better performance under stress and optimal conditions. These two groups could be used by breeding programs to develop high yield and drought tolerant hybrids. Full article

While the role of expanding agriculture in deforestation and the loss of other natural ecosystems is well known, the specific drivers in the context of small- and large-scale agriculture remain poorly understood. In this study, we employed satellite data and a deep learning algorithm to map the agricultural landscape of Central Africa (Cameroon, Central Africa Republic, Congo, Democratic Republic of Congo, Equatorial Guinea, and Gabon) into large- (including for plantations and intensively cultivated areas) and small-scale tree crops and non-tree crop cover. This permits the assessment of forest loss between the years 2000 and 2022 as a result of small- and large-scale agriculture. Thematic [user’s] accuracy ranged between 91.2 ± 2.5 percent (large-scale oil palm) and 17.8 ± 3.9 percent (large-scale non-tree crops). Small-scale tree crops achieved relatively low accuracy (63.5 ± 5.9 percent), highlighting the difficulties of reliably mapping crop types at a regional scale. In general, we observed that small-scale agriculture is fifteen times the size of large-scale agriculture, as area estimates of small-scale non-tree crops and small-scale tree crops ranged between 164,823 ± 4224 km² and 293,249 ± 12,695 km², respectively. Large-scale non-tree crops and large-scale tree crops ranged between 20,153 ± 1195 km² and 7436 ± 280 km², respectively. Small-scale cropping activities represent 12 percent of the total land cover and have led to dramatic encroachment into tropical moist forests in the past two decades in all six countries. We summarized key recommendations to help the forest conservation effort of existing policy frameworks. Full article

While the methods for monitoring deforestation are relatively well established, there is still no compromise on those for forest degradation. We propose here a systematic review on studies about forest degradation in the Congo Basin. Our analysis focused on seven key anthropogenic causes of forest degradation. Shifting agriculture emerged as the most significant driver, accounting for 61% ± 28.58% (mean ± SD) of canopy opening, 73.16% ± 16.88% aboveground carbon loss, and 30.37% ± 30.67% of tree species diversity loss over a 5–60-year period. Our analysis reveals a significant disconnect. Only 29% of the reviewed studies address this driver, while over 64% focus primarily on the consequences of industrial timber harvesting. Despite its comparatively minor contribution to degradation, with effects range from only 8.98% ± 13.63% of canopy opening, 14.79% ± 22.21 aboveground carbon loss, and 4.27 ± 21.07 tree species diversity loss over 1–20 years. Indeed, most of the methods focus on detecting changes in canopy structure associated with forest logging over a short period (0–5 years). These illustrate the need for a shift in focus in scientific research towards innovative methods, which can be developed over time, to monitor the various impacts of all causes of forest degradation. Full article

Leishmaniasis are infectious diseases caused by several parasitic species of Leishmania, mainly transmitted by the bite of infected phlebotomine sandflies. Humans, dogs, rodents, and other domestic and wild animals can act as reservoir hosts for the different Leishmania species. It is a neglected tropical disease that is endemic in Asia, the Middle East, North and East Africa, the Mediterranean region, and South and Central America. Clinical manifestations and disease severity depend on the species of the infecting parasites and the immunity status of the host. Leishmania represses the protective host immune response by manipulating the macrophage function, subverting cytokine expression to favor its survival and dissemination. A balance between pro-inflammatory and regulatory cells is necessary to bring a positive outcome. Accurate diagnosis and effective treatment represent the cornerstone in the control of this disease, although these are difficult in an environment of precariousness and poverty. Some recent studies highlighted the progressing work on diagnosis and treatments, such as the development of new benzimidazole-triazole derivatives for blocking the parasite growth, feline leishmaniasis with a comparison of immune responses in cats and dogs, and a transglutaminase that has been purified from L. infantum. The results of these studies could open new avenues in combating leishmaniasis. Full article

Sterculia foetida L., commonly known as the Java olive, is a tropical tree species native to regions of East Africa, tropical Asia, and northern Australia. This study employs species distribution modeling (SDM) to predict the potential geographic distribution of S. foetida under current and future climate scenarios. Using 1425 occurrence data and 19 environmental variables, we applied an ensemble modelling approach of three algorithms: Boosting Regression Trees (BRT), Generalized Linear Model (GLM), and Random Forests (RF), to generate distribution maps. Our models showed high accuracy (mean AUC = 0.98) to indicate that S. foetida has a broad ecological niche, with high suitability in tropical and subtropical regions of north Australia (New Guinea and Papua), Southeast Asia (India, Thailand, Myanmar, Taiwan, Philippines, Malaysia, Sri Lanka), Oman and Yemen in the southwest of Asia, Central Africa (Guinea, Ghana, Nigeria, Congo, Kenya and Tanzania), the Greater and Lesser Antilles, Mesoamerica, and the north of South America (Colombia, Panama, Venezuela, Ecuador and Brazil). Indeed, the probability of occurrence of S. foetida positively correlates with the Maximum temperature of warmest month (bio5), Mean temperature of wettest quarter (bio8) and Precipitation of wettest month (bio13). The model results showed a suitability area of 4,744,653 km², representing 37.86% of the total study area, classified into Low (14.12%), Moderate (8.71%), and High suitability (15.02%). Furthermore, the study found that habitat suitability for S. foetida showed similar trends under both near future climate scenarios (SSP1-2.6 and SSP5-8.5 for 2041–2060), with a slight loss in potential distribution (0.24% and 0.25%, respectively) and moderate gains (1.98% and 2.12%). In the far future (2061–2080), the low scenario (SSP1-2.6) indicated a 0.29% loss and a 2.52% gain, while the high scenario (SSP5-8.5) showed a more dramatic increase in both loss (0.6%) and gain areas (3.79%). These findings are crucial for conservation planning and management, particularly in regions where S. foetida is considered invasive and could become problematic. The study underscores the importance of incorporating climate change projections in SDM to better understand species invasiveness dynamics and inform biodiversity conservation strategies. Full article

Schistosomiasis, a neglected tropical disease caused by parasitic worms of the genus Schistosoma and transmitted through freshwater snails, affects over 200 million people worldwide. Climate change, through rising temperatures, altered rainfall patterns, and extreme weather events, is influencing the distribution and transmission dynamics of schistosomiasis. This scoping review examines the impact of climate change on schistosomiasis transmission and its implications for disease control. This review aims to synthesize current knowledge on the influence of climate variables (temperature, rainfall, water bodies) on snail populations, transmission dynamics, and the shifting geographic range of schistosomiasis. It also explores the potential effects of climate adaptation policies on disease control. The review follows the Arksey and O’Malley framework and PRISMA-ScR guidelines, including studies published from 2000 to 2024. Eligible studies were selected based on empirical data on climate change, schistosomiasis transmission, and snail dynamics. A two-stage study selection process was followed: title/abstract screening and full-text review. Data were extracted on environmental factors, snail population dynamics, transmission patterns, and climate adaptation strategies. Climate change is expected to increase schistosomiasis transmission in endemic regions like Sub-Saharan Africa, Southeast Asia, and South America, while some areas, such as parts of West Africa, may see reduced risk. Emerging hotspots were identified in regions not currently endemic. Climate adaptation policies, such as improved water management and early warning systems, were found effective in reducing transmission. Integrating climate adaptation strategies into schistosomiasis control programs is critical to mitigating the disease’s spread, particularly in emerging hotspots and shifting endemic areas. Full article