The Efficiency of Small-Scale Agriculture in Limpopo Province of South Africa

The aim of this study is to evaluate the efficiency of the small scale farmers for the production year 2006/2007 in Limpopo province using policy analysis matrix. A total of twelve production systems were selected. Result shows that all were profitable under market condition with existing policies and all except Dry land maize had comparative advantage suggesting efficiency in the systems. Ranking the systems in term of PRC and DRC, irrigated vegetables like Potatoes, cabbages and tomatoes had higher profitability and comparative advantages than field crops like both dry and irrigated maize, Peanut and Beans. Despite competiveness in all and comparative advantage in most systems, these was not due to policy intervention as incentive indicators, e.g. SRP, shows that all production systems are being taxed indicating little motivation from policies for small scale farmers to production.Farm Management,

Modelling phosphorus in Lake Simcoe and its subcatchments: scenario analysis to assess alternative management strategies

In Lake Simcoe (Ontario, Canada), anthropogenic phosphorus (P) loads have contributed to increased algal growth, low hypolimnetic dissolved oxygen concentrations, and impaired fish reproduction. Management targets to control eutrophication require an ambitious programme to reduce P loads to the lake. Remediation strategies rely upon an improved understanding of P sources and assessment of the effectiveness of different control options. Here we present an application of the integrated catchment model for phosphorus (INCA-P) to examine P sources across the Lake Simcoe watershed and simulate in-lake P concentrations. This is the first application of INCA-P to a complex watershed of this nature and the first to include a lake component. We evaluated a set of management actions to simulate anticipated effects of P reduction strategies on in-lake total phosphorus (TP) concentrations. The INCA-P scenarios show the difficulty of achieving large-scale reductions from the watershed, given the low rates of P export; however, the study shows that a multifaceted strategy, including fertilizer reduction, addition of buffer strips, more stringent controls on sewage treatment plant effluent, and reduced deposition of P to the lake surface, could achieve a 25% reduction in lake-water TP concentrations and produce TP close to the target of 0.01 mg L−1

Phosphorus dynamics across intensively monitored subcatchments in the Beaver River

We report results from a spatially intensive monitoring and modelling study to assess phosphorus (P) dynamics in the Beaver River, a tributary of Lake Simcoe, Ontario. We established multiple monitoring stations (9 flow and 24 water quality stations) from headwaters to near the outflow that were operated for 2 field seasons, complementing longer term data from a flow monitoring site and water chemistry monitoring site. We applied the Branched-INCA-P model, which allows fully distributed simulations supported by highly distributed monitoring data. Using spatially distributed data helped better understand variable P and sediment dynamics across the catchment and identify key model uncertainties and uncertainties related to catchment P management. Measured and modelled total P concentrations often exceeded provisional water quality thresholds in many areas of the catchment and highlight the value of studying water quality across multiple subcatchments rather than at a single site. Total P export coefficients differed widely among subcatchments, ranging from 2.1–21.4 kg km-2 y-1 over a single year. Export coefficients were most strongly (negatively) related to the proportion of wetland cover in subcatchments. The INCA-P model captured spatial variation in P concentrations relatively well, but short-term temporal variability in the observed data was not well simulated across sites, in part due to unmodelled hydrological phenomena including beaver activity and unknown drivers of P peaks that were not associated with hydrological events

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Breast cancer management pathways during the COVID-19 pandemic: outcomes from the UK ‘Alert Level 4’ phase of the B-MaP-C study

Abstract: Background: The B-MaP-C study aimed to determine alterations to breast cancer (BC) management during the peak transmission period of the UK COVID-19 pandemic and the potential impact of these treatment decisions. Methods: This was a national cohort study of patients with early BC undergoing multidisciplinary team (MDT)-guided treatment recommendations during the pandemic, designated ‘standard’ or ‘COVID-altered’, in the preoperative, operative and post-operative setting. Findings: Of 3776 patients (from 64 UK units) in the study, 2246 (59%) had ‘COVID-altered’ management. ‘Bridging’ endocrine therapy was used (n = 951) where theatre capacity was reduced. There was increasing access to COVID-19 low-risk theatres during the study period (59%). In line with national guidance, immediate breast reconstruction was avoided (n = 299). Where adjuvant chemotherapy was omitted (n = 81), the median benefit was only 3% (IQR 2–9%) using ‘NHS Predict’. There was the rapid adoption of new evidence-based hypofractionated radiotherapy (n = 781, from 46 units). Only 14 patients (1%) tested positive for SARS-CoV-2 during their treatment journey. Conclusions: The majority of ‘COVID-altered’ management decisions were largely in line with pre-COVID evidence-based guidelines, implying that breast cancer survival outcomes are unlikely to be negatively impacted by the pandemic. However, in this study, the potential impact of delays to BC presentation or diagnosis remains unknown

The Efficiency of Small-Scale Agriculture in Limpopo Province of South Africa

The aim of this study is to evaluate the efficiency of the small scale farmers for the production year 2006/2007 in Limpopo province using policy analysis matrix. A total of twelve production systems were selected. Result shows that all were profitable under market condition with existing policies and all except Dry land maize had comparative advantage suggesting efficiency in the systems. Ranking the systems in term of PRC and DRC, irrigated vegetables like Potatoes, cabbages and tomatoes had higher profitability and comparative advantages than field crops like both dry and irrigated maize, Peanut and Beans. Despite competiveness in all and comparative advantage in most systems, these was not due to policy intervention as incentive indicators, e.g. SRP, shows that all production systems are being taxed indicating little motivation from policies for small scale farmers to production

Cross-scale ensemble projections of dissolved organic carbon dynamics in boreal forest streams

Climate is an important driver of dissolved organic carbon (DOC) dynamics in boreal catchments characterized by networks of streams within forest-wetland landscape mosaics. In this paper, we assess how climate change may affect stream DOC concentrations ([DOC]) and export from boreal forest streams with a multi-model ensemble approach. First, we apply an ensemble of regional climate models (RCMs) to project soil temperatures and stream-flows. These data are then used to drive two biogeochemical models of surface water DOC: (1) The Integrated Catchment model for Carbon (INCA-C), a detailed process-based model of DOC operating at the catchment scale, and (2) The Riparian Integration Model (RIM), a simple dynamic hillslope scale model of stream [DOC]. All RCMs project a consistent increase in temperature and precipitation as well as a shift in spring runoff peaks from May to April. However, they present a considerable range of possible future runoff conditions with an ensemble median increase of 31 % between current and future (2061–2090) conditions. Both biogeochemical models perform well in describing the dynamics of present-day stream [DOC] and fluxes, but disagree in their future projections. Here, we assess possible futures in three boreal catchments representative of forest, mire and mixed landscape elements. INCA-C projects a wider range of stream [DOC] due to its temperature sensitivity, whereas RIM gives consistently larger inter-annual variation and a wider range of exports due to its sensitivity to hydrological variations. The uncertainties associated with modeling complex processes that control future DOC dynamics in boreal and temperate catchments are still the main limitation to our understanding of DOC mechanisms under changing climate conditions. Novel, currently overlooked or unknown drivers may appear that will present new challenges to modelling DOC in the future

Cross-scale ensemble projections of dissolved organic carbon dynamics in boreal forest streams

Climate is an important driver of dissolved organic carbon (DOC) dynamics in boreal catchments characterized by networks of streams within forest-wetland landscape mosaics. In this paper, we assess how climate change may affect stream DOC concentrations ([DOC]) and export from boreal forest streams with a multi-model ensemble approach. First, we apply an ensemble of regional climate models (RCMs) to project soil temperatures and stream-flows. These data are then used to drive two biogeochemical models of surface water DOC: (1) The Integrated Catchment model for Carbon (INCA-C), a detailed process-based model of DOC operating at the catchment scale, and (2) The Riparian Integration Model (RIM), a simple dynamic hillslope scale model of stream [DOC]. All RCMs project a consistent increase in temperature and precipitation as well as a shift in spring runoff peaks from May to April. However, they present a considerable range of possible future runoff conditions with an ensemble median increase of 31 % between current and future (2061–2090) conditions. Both biogeochemical models perform well in describing the dynamics of present-day stream [DOC] and fluxes, but disagree in their future projections. Here, we assess possible futures in three boreal catchments representative of forest, mire and mixed landscape elements. INCA-C projects a wider range of stream [DOC] due to its temperature sensitivity, whereas RIM gives consistently larger inter-annual variation and a wider range of exports due to its sensitivity to hydrological variations. The uncertainties associated with modeling complex processes that control future DOC dynamics in boreal and temperate catchments are still the main limitation to our understanding of DOC mechanisms under changing climate conditions. Novel, currently overlooked or unknown drivers may appear that will present new challenges to modelling DOC in the future

Effect of Climate Change on Soil Temperature in Swedish Boreal Forests

Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions