164 research outputs found
Soil structural degradation and nutrient limitations across land use categories and climatic zones in Southern Africa
Although soil degradation is a major threat to food security and carbon sequestration, our knowledge of the spatial extent of the problem and its drivers is very limited in Southern Africa. Therefore, this study aimed to quantify the risk of soil structural degradation and determine the variation in soil stoichiometry and nutrient limitations with land use categories (LUCs) and climatic zones. Using data on soil clay, silt, organic carbon (SOC), total nitrogen (N), available phosphorus (P), and sulfur (S) concentrations collected from 4,468 plots on 29 sites across Angola, Botswana, Malawi, Mozambique, Zambia and Zimbabwe, this study presents novel insights into the variations in soil structural degradation and nutrient limitations. The analysis revealed strikingly consistent stoichiometric coupling of total N, P, and S concentrations with SOC across LUCs. The only exception was on crop land where available P was decoupled from SOC. Across sample plots, the probability (φ) of severe soil structural degradation was 0.52. The probability of SOC concentrations falling below the critical value of 1.5% was 0.49. The probabilities of soil total N, available P, and S concentrations falling below their critical values were 0.95, 0.70, and 0.83, respectively. N limitation occurred with greater probability in woodland (φ = .99) and forestland (φ = .97) than in cropland (φ = .92) and grassland (φ = .90) soils. It is concluded that soil structural degradation, low SOC concentrations, and N and S limitations are widespread across Southern Africa. Therefore, significant changes in policies and practices in land management are needed to reverse the rate of soil structural degradation and increase soil carbon storage
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Seed germination and in vitro regeneration of the African medicinal and pesticidal plant, Bobgunnia madagascariensis
Propagation of the medicinal and pesticidal tree, Bobgunnia madagascarensis is difficult due to poor and erratic germination of its seeds and slow growth of its seedlings. This study involved two separate experiments. The first evaluated the effect of pre-sowing treatments and growing medium on ex vitro seed germination and early seedling development. The second experiment involved in vitro germination, shoot initiation and rooting of shoots. Pre-sowing seed treatments involved soaking seeds in cold and hot water for 12 and 24 h and soaking in different concentrations (0, 100, 200, 400 and 800 mg/l) of gibberellic acid for 24 h. Soaking of seeds in cold or hot water for up to 24 h did not achieve more than 45% germination, while seeds treated with gibberellic acid achieved 76%) when seeds were sown in a growing medium without compost compared with a medium with compost (<43%). All shoot-tips isolated from the in vitro germinated seedlings on B5 media without plant growth regulators continued to grow as a single shoot, while shoot-tips cultured on B5 supplemented with 0.1 mg/l of naphthaleneacetic acid (NAA) and thidiazuron (TDZ) produced two shoots each after four weeks. It was concluded that B. madagascariensis seeds had very low ex vitro germination percentages. Although, in vitro cultures improved seed germination, axillary shoot multiplication and rooting were not satisfactory. Therefore, further studies are needed to develop an optimal in vitro multiplication protocol for B. madagascariensis
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Farmers’ ethno-ecological knowledge of vegetable pests and pesticidal plant use in Malawi and Zambia
While pests are a major constraint in vegetable production in many parts of Southern Africa, little is known about farmers’ knowledge and management practices. A survey was conducted among 168 and 91 vegetable farmers in Northern Malawi and Eastern Zambia, respectively, to evaluate their knowledge, attitudes and traditional management practices in tomato and crucifers (brassica). All respondents in Malawi and Zambia reported pest damage on tomato and crucifers, and 75% had used synthetic pesticides. The use of pesticidal plants, cultural practices and resistant varieties constituted a smaller portion of the pest control options in both crucifers and tomato. Over 70% of the respondents were aware of pesticidal plants, and more female (75%) than male (55%) respondents reported using them. While over 20 different plant species were mentioned by respondents, Tephrosia vogelii accounted for 61 and 53% of the pesticidal species known to respondents in Malawi and Zambia, respectively. Farmers with small landholdings were more inclined to use pesticidal plants than those with medium and large landholding highlighting the importance of this management alternative for poor farmers. Most respondents were willing to cultivate pesticidal plants, which indicate that farmers understand the potential value of these plants in pest management
Spatial Variation in Tree Density and Estimated Aboveground Carbon Stocks in Southern Africa
Variability in woody plant species, vegetation assemblages and anthropogenic activities derails the efforts to have common approaches for estimating biomass and carbon stocks in Africa. In order to suggest management options, it is important to understand the vegetation dynamics and the major drivers governing the observed conditions. This study uses data from 29 sentinel landscapes (4640 plots) across the southern Africa. We used T-Square distance method to sample trees. Allometric models were used to estimate aboveground tree biomass from which aboveground biomass carbon stock (AGBCS) was derived for each site. Results show average tree density of 502 trees·ha−1 with semi-arid areas having the highest (682 trees·ha−1) and arid regions the lowest (393 trees·ha−1). The overall AGBCS was 56.4 Mg·ha−1. However, significant site to site variability existed across the region. Over 60 fold differences were noted between the lowest AGBCS (2.2 Mg·ha−1) in the Musungwa plains of Zambia and the highest (138.1 Mg·ha−1) in the scrublands of Kenilworth in Zimbabwe. Semi-arid and humid sites had higher carbon stocks than sites in sub-humid and arid regions. Anthropogenic activities also influenced the observed carbon stocks. Repeated measurements would reveal future trends in tree cover and carbon stocks across different systems
Modelling of correlated soil animals count data
Ecological studies naturally result in correlated data. Ignoring these correlations can result in
biased estimation of ecological effects jeopardizing the integrity of the scientific inference.
Mixed effects models are likely to appeal to ecologists for handling correlated data (e.g.
Sileshi, 2008), however careful consideration must be given to the interpretation of the
parameter estimates from generalized linear mixed effects models with non-identity link
functions. The objective of this study was to compare the generalized estimating equations
(GEE) under different correlation structures and suggest appropriate models to describe the
relationship between soil animal counts and covariates. The GEE with independence,
exchangeable and AR1 correlation structures were compared using count data set of ants from
soils under the agroforestry systems in eastern Zambia. The GEE model with AR1 correlation
structure gave a better description of the data than did the independence and exchangeable
correlation structures.http://www.sastat.org.za/journal.htmam201
Aboveground and belowground tree biomass and carbon stocks in the miombo woodlands of the Copperbelt in Zambia
Please read abstract in the article.The National Science and Technology Council (NSTC), African Forest Forum (AFF) and the University of Pretoria.https://www.tandfonline.com/loi/tcmt202022-06-14hj2022Plant Production and Soil Scienc
Cassava response to the integrated use of manure and NPK fertilizer in Zambia
Open Access JournalCassava is Africa's second most important food source in terms of calories consumed per capita. However, farmers use little or no fertilizer on cassava and scant information is available regarding the cassava yield response to mineral and organic fertilizer inputs in Zambia. This study was undertaken to determine the response of cassava to the integrated use of organic and inorganic nutrient sources in two contrasting agroecological zones of Zambia; Mansa located in Zone III and Kabangwe located in Zone II. The treatments consisted of a factorial combination of four NPK rates (unfertilized control, 50N-11P-41.5K, 100N-22P-83K, and 150N-33P-124.5K kg/ha) with four rates of chicken manure (0, 1.4, 2.8, and 4.2 t/ha). The treatments were laid out in a randomized complete block design with three replications. Cassava height, stem girth, canopy diameter, leaf area index, and chlorophyll index were monitored over time and roots were harvested at 12 months after planting (MAP). Growth parameters and yield varied significantly (p < 0.01) both with NPK, manure application, and their interaction effects at 12 MAP. The combined application of 4.2 t/ha of chicken manure and 100N-22P-83 K kg/ha of mineral fertilizer resulted in the highest yields of 35.2 t/ha at Kabangwe. But, the highest average yield of 34.4 t/ha was recorded with the application of 2.8 t/ha manure and 100N-22P-83 K kg/ha mineral fertilizer at Mansa. This increased treatment yield by 24 and 29% over the sole NPK fertilizer application at Mansa and Kabangwe sites, respectively. Harvest index (HI) was higher when 2.8 t/ha chicken manure was applied in combination with 50N-11P-41.5K kg/ha at Kabangwe. But, the highest HI at Mansa site was achieved with the combination of 2.8 t/ha manure and 100N-22P-83 K kg/ha. This combination also resulted in the highest agronomic efficiency of N, P and K at both sites. It is concluded that cassava productivity and nutrient use efficiency can be improved through the integrated use of NPK and manure in Zambia
Accurate crop yield predictions from modelling tree-crop interactions in gliricidia-maize agroforestry
Agroforestry systems, containing mixtures of trees and crops, are often promoted because the net effect of interactions between woody and herbaceous components is thought to be positive if evaluated over the long term. From a modelling perspective, agroforestry has received much less attention than monocultures. However, for the potential of agroforestry to impact food security in Africa to be fully evaluated, models are required that accurately predict crop yields in the presence of trees. The positive effects of the fertiliser tree gliricidia (Gliricidia sepium) on maize (Zea mays) are well documented and use of this tree-crop combination to increase crop production is expanding in several African countries. Simulation of gliricidia-maize interactions can complement field trials by predicting crop response across a broader range of contexts than can be achieved by experimentation alone. We tested a model developed within the APSIM framework. APSIM models are widely used for one dimensional (1D), process-based simulation of crops such as maize and wheat in monoculture. The Next Generation version of APSIM was used here to test a 2D agroforestry model where maize growth and yield varied spatially in response to interactions with gliricidia. The simulations were done using data for gliricidia-maize interactions over two years (short-term) in Kenya and 11 years (long-term) in Malawi, with differing proportions of trees and crops and contrasting management. Predictions were compared with observations for maize grain yield, and soil water content. Simulations in Kenya were in agreement with observed yields reflecting lower observed maize germination in rows close to gliricidia. Soil water content was also adequately simulated, except for a tendency for slower simulated drying of the soil profile each season. Simulated maize yields in Malawi were also in agreement with observations. Trends in soil carbon over a decade were similar to those measured, but could not be statistically evaluated. These results show that the agroforestry model in APSIM Next Generation adequately represented tree-crop interactions in these two contrasting agro-ecological conditions and agroforestry practices. Further testing of the model is warranted to explore tree-crop interactions under a wider range of environmental conditions
Yield gap analysis of field crops: Methods and case studies
The challenges of global agriculture have been analysed exhaustively and the need has been established for sustainable improvement in agricultural production aimed at food security in a context of increasing pressure on natural resources. Whereas the importance of R&D investment in agriculture is increasingly recognised, better allocation of limited funding is essential to improve food production. In this context, the common and often large gap between actual and attainable yield is a critical target. Realistic solutions are required to close yield gaps in both small and large scale cropping systems worldwide; to make progress in this direction, we need (1) definitions and techniques to measure and model yield at different levels (actual, attainable, potential) and different scales in space (field, farm, region, global) and time (short, long term); (2) identification of the causes of gaps between yield levels; (3) management options to reduce the gaps where feasible and (4) policies to favour adoption of gap-closing technologies. The aim of this publication is to review the methods for yield gap analysis, and to use case studies to illustrate different approaches, hence addressing the first of these four requirements. Theoretical, potential, water-limited, and actual yield are defined. Yield gap is the difference between two levels of yield in this series. Depending on the objectives of the study, different yield gaps are relevant. The exploitable yield gap accounts for both the unlikely alignment of all factors required for achievement of potential or water limited yield and the economic, management and environmental constraints that preclude, for example, the use of fertiliser rates that maximise yield, when growers’ aim is often a compromise between maximising profit and minimising risk at the whole-farm scale, rather than maximising yield of individual crops. The gap between potential and water limited yield is an indication of yield gap that can be removed with irrigation. Spatial and temporal scales for the determination of yield gaps are discussed. Spatially, yield gaps have been quantified at levels of field, region, national or mega-environment and globally. Remote sensing techniques describes the spatial variability of crop yield, even up to individual plots. Time scales can be defined in order to either remove or capture the dynamic components of the environment (soil, climate, biotic components of ecosystems) and technology. Criteria to define scales in both space and time need to be made explicit, and should be consistent with the objectives of the analysis. Satellite measurements can complement in situ measurements. The accuracy of estimating yield gaps is determined by the weakest link, which in many cases is good quality, sub-national scale data on actual yields that farmers achieve. In addition, calculation and interpretation of yield gaps requires reliable weather data, additional agronomic information and transparent assumptions. The main types of methods used in yield benchmarking and gap analysis are outlined using selected case studies. The diversity of benchmarking methods outlined in this publication reflects the diversity of spatial and temporal scales, the questions asked, and the resources available to answer them. We grouped methods in four broad approaches.
Approach 1 compares actual yield with the best yield achieved in comparable environmental conditions, e.g. between neighbours with similar topography and soils. Comparisons of this type are spatially constrained by definition, and are an approximation to the gap between actual and attainable yield. With minimum input and greatest simplicity, this allows for limited but useful benchmarks; yield gaps can be primarily attributed to differences in management. This approach can be biased, however, where best management practices are not feasible; modelled yields provide more relevant benchmarks in these cases.
Approach 2 is a variation of approach 1, i.e. it is based on comparisons of actual yield, but instead of a single yield benchmark, yield is expressed as a function of one or few environmental drivers in simple models. In common with Approach 1, these methods do not necessarily capture best management practices. The French and Schultz model is the archetype in this approach; this method plots actual yield against seasonal water use, fits a boundary function representing the best yield for a given water use, and calculates yield gaps as the departure between actual yields and the boundary function. A boundary model fitted to the data provides a scaled benchmark, thus partially accounting for seasonal conditions. Boundary functions can be estimated with different statistical methods but it is recommended that the shape and parameters of boundary functions are also assessed on the basis of their biophysical meaning. Variants of this approach use nitrogen uptake or soil properties instead of water.
Approach 3 is based on modelling which may range from simple climatic indices to models of intermediate (e.g. AquaCrop) or high complexity (e.g. CERES-type models). More complex models are valuable agronomically because they capture some genetic features of the specific cultivar, and the critical interaction between water and nitrogen. On the other hand, more complex models have requirements of parameters and inputs that are not always available. “Best practice” approaches to model yield in gap analysis are outlined. Importantly, models to estimate potential yield require parameters that capture the physiology of unstressed crops.
Approach 4 benchmarking involves a range of approaches combining actual data, remote sensing, GIS and models of varying complexity. This approach is important for benchmarking at and above the regional scale. At these large scales, particular attention needs to be paid to weather data used in modelling yield because significant bias can accrue from inappropriate data sources. Studies that have used gridded weather databases to simulate potential and water-limited yields for a grid are rarely validated against simulated yields based on actual weather station data from locations within the same grid. This should be standard practice, particularly where global scale yield gaps are used for policy decisions or investment in R&D. Alternatively, point-based simulations of potential and water-limited yields, complemented with an appropriate up-scaling method, may be more appropriate for large scale yield gap analysis. Remote sensing applied to yield gap analysis has improved over the last years, mainly through pixel-based biomass production models. Site-specific yield validation, disaggregated in biomass radiation-use-efficiency and harvest index, remains necessary and need to be carried out every 5 to 10 years
Molecular epidemiology of tuberculosis in the Somali region, eastern Ethiopia
Background: Tuberculosis (TB) is one of the leading causes of morbidity and mortality in low-income countries like Ethiopia. However, because of the limited laboratory infrastructure there is a shortage of comprehensive data on the genotypes of clinical isolates of Mycobacterium tuberculosis (M. tuberculosis) complex (MTBC) in peripheral regions of Ethiopia. The objective of this study was to characterize MTBC isolates in the Somali region of eastern Ethiopia. Methods: A cross-sectional study was conducted in three health institutions between October 2018 and December 2019 in the capital of Somali region. A total of 323 MTBC isolates (249 from pulmonary TB and 74 from extrapulmonary TB) were analyzed using regions of difference 9 (RD 9)-based polymerase chain reaction (PCR) and spoligotyping. Results: Of the 323 MTBC isolates, 99.7% (95% CI: 99.1-100%) were M. tuberculosis while the remaining one isolate was M. bovis based on RD 9-based PCR. Spoligotyping identified 71 spoligotype patterns; 61 shared types and 10 orphans. A majority of the isolates were grouped in shared types while the remaining grouped in orphans. The M. tuberculosis lineages identified in this study were lineage 1, 2, 3, 4, and 7 with the percentages of 7.4, 2.2, 28.2, 60.4, and 0.6%, respectively. Most (87.9%) of the isolates were classified in clustered spoligotypes while the remaining 12.1% isolates were singletons. The predominant clustered spoligotypes identified were SIT 149, SIT 21, SIT 26, SIT 53, and SIT 52, each consisting of 17.6, 13.3, 8.4, 7.4, and 5%, respectively. Lineage 3 and lineage 4, as well as the age group (15-24), were associated significantly with clustering. Conclusion: The MTBC isolated from TB patients in Somali region were highly diverse, with considerable spoligotype clustering which suggests active TB transmission. In addition, the Beijing spoligotype was isolated in relatively higher frequency than the frequencies of its isolation from the other regions of Ethiopia warranting the attention of the TB Control Program of the Somali region
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