Effect of Cricket Frass Fertilizer on growth and pod production of green beans (Phaseolus vulgaris L.).

Cricket Frass Fertilizer (CFF) was tested for its efficiency and potential as a fertilizer on the growth of green beans (Phaseolus vulgaris L.) in central Madagascar from April 2020 to October 2020. We grew green beans experimentally for 93 days with seven different fertilizer treatments: NPK 200 kg/ha (0.47 g of N/plant), GUANOMAD (guano from bat) 300 kg/ha (0.26 g of N/ plant), CFF 100 kg/ha (0.12 g of N/plant), CFF 200 kg/ha (0.24 g of N/plant), CFF 300 kg/ha (0.38 g of N/plant), CFF 400 kg/ha (0.52 g of N/plant), and no fertilizer (0 g of N/plant). Three plant traits were measured: survival proportion, vegetative biomass, and pod biomass. The survival proportion of plants treated with the highest dose of CFF (400 kg/ha, 88.1%), NPK (79.8%), and GUANOMAD (81.2%) were similar, but plants treated with the former yielded significantly higher vegetative (35.5 g/plant) and pod biomass (11 g/plant). These results suggest that fertilizing green beans with CFF at a 400 kg/ha dose is sufficient for plant survival and growth, and improves pod production. In Madagascar where soil quality is poor, dependence on imported chemical fertilizers (NPK) and other organic fertilizer (GUANOMAD) can be reduced. Cricket Frass Fertilizer can be used as an alternative sustainable fertilizer for beans.

Sociodemographic Variables Can Guide Prioritized Testing Strategies for Epidemic Control in Resource-Limited Contexts.

BACKGROUND: Targeted surveillance allows public health authorities to implement testing and isolation strategies when diagnostic resources are limited, and can be implemented via the consideration of social network topologies. However, it remains unclear how to implement such surveillance and control when network data are unavailable. METHODS: We evaluated the ability of sociodemographic proxies of degree centrality to guide prioritized testing of infected individuals compared to known degree centrality. Proxies were estimated via readily available sociodemographic variables (age, gender, marital status, educational attainment, household size). We simulated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics via a susceptible-exposed-infected-recovered individual-based model on 2 contact networks from rural Madagascar to test applicability of these findings to low-resource contexts. RESULTS: Targeted testing using sociodemographic proxies performed similarly to targeted testing using known degree centralities. At low testing capacity, using proxies reduced infection burden by 22%-33% while using 20% fewer tests, compared to random testing. By comparison, using known degree centrality reduced the infection burden by 31%-44% while using 26%-29% fewer tests. CONCLUSIONS: We demonstrate that incorporating social network information into epidemic control strategies is an effective countermeasure to low testing capacity and can be implemented via sociodemographic proxies when social network data are unavailable.

Regeneration strategies and forest resilience to changing fire regimes: Insights from a Goldilocks model.

Disturbances are ubiquitous in ecological systems, and species have evolved a range of strategies to resist or rebound following disturbance. Understanding how the presence and complementarity of regeneration traits will affect community responses to disturbance is increasingly urgent as disturbance regimes shift beyond their historical ranges of variability. We define "disturbance niche" as a species' fitness across a range of disturbance sizes and frequencies that can reflect the fundamental or realized niche, that is, whether the species occurs alone or with other species. We developed a model of intermediate complexity (i.e., a Goldilocks model) to infer the disturbance niche. We parameterized the model for subalpine forests in Yellowstone National Park (USA) adapted to infrequent stand-replacing fires and included the three major tree-regeneration strategies: (1) obligate seeders that rely on ex situ seeding into burned areas (non-serotinous lodgepole pine, Pinus contorta var. latifola), (2) obligate seeders that depend on in situ seedbanks (serotinous lodgepole pine, Pinus contorta var. latifola), and (3) species that can resprout from surviving roots following fire (quaking aspen, Populus tremuloides). Our results showed which regeneration strategies increase or decrease in prevalence as fire rotation declines. Non-serotinous pines were extirpated when fire rotation was below 50 years in a monoculture and 100 years in a mixed forest; serotinous pines were extirpated when fire rotation was below 20 years; and aspen was extirpated when fire rotation fell below 6 years. The fundamental and realized disturbance niches pinpointed the key mechanisms limiting regeneration for each strategy, namely, increasing fire size for non-serotinous pine (ex situ seeders), decreasing fire frequency for serotinous pine (in situ seeders), and interspecific competition for aspen (resprouters). In a mixed forest, the three regeneration strategies were complementary and each dominated at different combinations of fire size and frequency. Consequently, diversity of regeneration strategies enhanced forest resilience to declining fire rotations. Despite its simplicity, our Goldilocks model produced realistic dynamics and could be readily adapted to other disturbance-prone ecosystems to explore the generality of these results. The disturbance niche is a key concept for anticipating community resilience to changing disturbance regimes.

Prioritizing COVID-19 vaccination efforts and dose allocation within Madagascar.

BACKGROUND: While mass COVID-19 vaccination programs are underway in high-income countries, limited availability of doses has resulted in few vaccines administered in low and middle income countries (LMICs). The COVID-19 Vaccines Global Access (COVAX) is a WHO-led initiative to promote vaccine access equity to LMICs and is providing many of the doses available in these settings. However, initial doses are limited and countries, such as Madagascar, need to develop prioritization schemes to maximize the benefits of vaccination with very limited supplies. There is some consensus that dose deployment should initially target health care workers, and those who are more vulnerable including older individuals. However, questions of geographic deployment remain, in particular associated with limits around vaccine access and delivery capacity in underserved communities, for example in rural areas that may also include substantial proportions of the population. METHODS: To address these questions, we developed a mathematical model of SARS-CoV-2 transmission dynamics and simulated various vaccination allocation strategies for Madagascar. Simulated strategies were based on a number of possible geographical prioritization schemes, testing sensitivity to initial susceptibility in the population, and evaluating the potential of tests for previous infection. RESULTS: Using cumulative deaths due to COVID-19 as the main outcome of interest, our results indicate that distributing the number of vaccine doses according to the number of elderly living in the region or according to the population size results in a greater reduction of mortality compared to distributing doses based on the reported number of cases and deaths. The benefits of vaccination strategies are diminished if the burden (and thus accumulated immunity) has been greatest in the most populous regions, but the overall strategy ranking remains comparable. If rapid tests for prior immunity may be swiftly and effectively delivered, there is potential for considerable gain in mortality averted, but considering delivery limitations modulates this. CONCLUSION: At a subnational scale, our results support the strategy adopted by the COVAX initiative at a global scale.

Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar.

For emerging epidemics such as the COVID-19 pandemic, quantifying travel is a key component of developing accurate predictive models of disease spread to inform public health planning. However, in many LMICs, traditional data sets on travel such as commuting surveys as well as non-traditional sources such as mobile phone data are lacking, or, where available, have only rarely been leveraged by the public health community. Evaluating the accuracy of available data to measure transmission-relevant travel may be further hampered by limited reporting of suspected and laboratory confirmed infections. Here, we leverage case data collected as part of a COVID-19 dashboard collated via daily reports from the Malagasy authorities on reported cases of SARS-CoV-2 across the 22 regions of Madagascar. We compare the order of the timing of when cases were reported with predictions from a SARS-CoV-2 metapopulation model of Madagascar informed using various measures of connectivity including a gravity model based on different measures of distance, Internal Migration Flow data, and mobile phone data. Overall, the models based on mobile phone connectivity and the gravity-based on Euclidean distance best predicted the observed spread. The ranks of the regions most remote from the capital were more difficult to predict but interestingly, regions where the mobile phone connectivity model was more accurate differed from those where the gravity model was most accurate. This suggests that there may be additional features of mobility or connectivity that were consistently underestimated using all approaches but are epidemiologically relevant. This work highlights the importance of data availability and strengthening collaboration among different institutions with access to critical data - models are only as good as the data that they use, so building towards effective data-sharing pipelines is essential.

Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar.

For emerging epidemics such as the COVID-19 pandemic, quantifying travel is a key component of developing accurate predictive models of disease spread to inform public health planning. However, in many LMICs, traditional data sets on travel such as commuting surveys as well as non-traditional sources such as mobile phone data are lacking, or, where available, have only rarely been leveraged by the public health community. Evaluating the accuracy of available data to measure transmission-relevant travel may be further hampered by limited reporting of suspected and laboratory confirmed infections. Here, we leverage case data collected as part of a COVID-19 dashboard collated via daily reports from the Malagasy authorities on reported cases of SARS-CoV-2 across the 22 regions of Madagascar. We compare the order of the timing of when cases were reported with predictions from a SARS-CoV-2 metapopulation model of Madagascar informed using various measures of connectivity including a gravity model based on different measures of distance, Internal Migration Flow data, and mobile phone data. Overall, the models based on mobile phone connectivity and the gravity-based on Euclidean distance best predicted the observed spread. The ranks of the regions most remote from the capital were more difficult to predict but interestingly, regions where the mobile phone connectivity model was more accurate differed from those where the gravity model was most accurate. This suggests that there may be additional features of mobility or connectivity that were consistently underestimated using all approaches, but are epidemiologically relevant. This work highlights the importance of data availability and strengthening collaboration among different institutions with access to critical data - models are only as good as the data that they use, so building towards effective data-sharing pipelines is essential.

Variation in SARS-CoV-2 outbreaks across sub-Saharan Africa.

A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (for example, warmer environments1, younger populations2-4) have yet to be framed within a comprehensive analysis. We synthesized factors hypothesized to drive the pace and burden of this pandemic in SSA during the period from 25 February to 20 December 2020, encompassing demographic, comorbidity, climatic, healthcare capacity, intervention efforts and human mobility dimensions. Large diversity in the probable drivers indicates a need for caution in interpreting analyses that aggregate data across low- and middle-income settings. Our simulation shows that climatic variation between SSA population centers has little effect on early outbreak trajectories; however, heterogeneity in connectivity, although rarely considered, is likely an important contributor to variance in the pace of viral spread across SSA. Our synthesis points to the potential benefits of context-specific adaptation of surveillance systems during the ongoing pandemic. In particular, characterizing patterns of severity over age will be a priority in settings with high comorbidity burdens and poor access to care. Understanding the spatial extent of outbreaks warrants emphasis in settings where low connectivity could drive prolonged, asynchronous outbreaks resulting in extended stress to health systems.

Transient top-down and bottom-up effects of resources pulsed to multiple trophic levels.

Pulsed fluxes of organisms across ecosystem boundaries can exert top-down and bottom-up effects in recipient food webs, through both direct effects on the subsidized trophic levels and indirect effects on other components of the system. While previous theoretical and empirical studies demonstrate the influence of allochthonous subsidies on bottom-up and top-down processes, understanding how these forces act in conjunction is still limited, particularly when an allochthonous resource can simultaneously subsidize multiple trophic levels. Using the Lake Mývatn region in Iceland as an example system of allochthony and its potential effects on multiple trophic levels, we analyzed a mathematical model to evaluate how pulsed subsidies of aquatic insects affect the dynamics of a soil-plant-arthropod food web. We found that the relative balance of top-down and bottom-up effects on a given food web compartment was determined by trophic position, subsidy magnitude, and top predators' ability to exploit the subsidy. For intermediate trophic levels (e.g., detritivores and herbivores), we found that the subsidy could either alleviate or intensify top-down pressure from the predator. For some parameter combinations, alleviation and intensification occurred sequentially during and after the resource pulse. The total effect of the subsidy on detritivores and herbivores, including top-down and bottom-up processes, was determined by the rate at which predator consumption saturated with increasing size of the allochthonous subsidy, with greater saturation leading to increased bottom-up effects. Our findings illustrate how resource pulses to multiple trophic levels can influence food web dynamics by changing the relative strength of bottom-up and top-down effects, with bottom-up predominating top-down effects in most scenarios in this subarctic system.

Monitoring for outbreak-associated excess mortality in an African city: Detection limits in Antananarivo, Madagascar.

OBJECTIVES: Quantitative estimates of the impact of infectious disease outbreaks are required to develop measured policy responses. In many low- and middle-income countries, inadequate surveillance and incompleteness of death registration are important barriers. DESIGN: Here, we characterize how large an impact on mortality would have to be for being detectable using the uniquely detailed mortality notification data from the city of Antananarivo, Madagascar, with application to a recent measles outbreak. RESULTS: The weekly mortality rate of children during the 2018-2019 measles outbreak was 161% above the expected value at its peak, and the signal can be detected earlier in children than in the general population. This approach to detect anomalies from expected baseline mortality allows us to delineate the prevalence of COVID-19 at which excess mortality would be detectable with the existing death notification system in Antananarivo. CONCLUSIONS: Given current age-specific estimates of the COVID-19 fatality ratio and the age structure of the population in Antananarivo, we estimate that as few as 11 deaths per week in the 60-70 years age group (corresponding to an infection rate of approximately 1%) would detectably exceed the baseline. Data from 2020 will undergo necessary processing and quality control in the coming months. Our results provide a baseline for interpreting this information.

High variation expected in the pace and burden of SARS-CoV-2 outbreaks across sub-Saharan Africa.

A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (e.g., warmer environments1, younger populations2-4) have yet to be framed within a comprehensive analysis accounting for factors that may offset the effects of climate and demography. Here, we synthesize factors hypothesized to shape the pace of this pandemic and its burden as it moves across SSA, encompassing demographic, comorbidity, climatic, healthcare and intervention capacity, and human mobility dimensions of risk. We find large scale diversity in probable drivers, such that outcomes are likely to be highly variable among SSA countries. While simulation shows that extensive climatic variation among SSA population centers has little effect on early outbreak trajectories, heterogeneity in connectivity is likely to play a large role in shaping the pace of viral spread. The prolonged, asynchronous outbreaks expected in weakly connected settings may result in extended stress to health systems. In addition, the observed variability in comorbidities and access to care will likely modulate the severity of infection: We show that even small shifts in the infection fatality ratio towards younger ages, which are likely in high risk settings, can eliminate the protective effect of younger populations. We highlight countries with elevated risk of 'slow pace', high burden outbreaks. Empirical data on the spatial extent of outbreaks within SSA countries, their patterns in severity over age, and the relationship between epidemic pace and health system disruptions are urgently needed to guide efforts to mitigate the high burden scenarios explored here.

The potential role of intrinsic processes in generating abrupt and quasi-synchronous tree declines during the Holocene.

Multiple abrupt and sometimes near-synchronous declines in tree populations have been detected in the temperate forests of eastern North America and Europe during the Holocene. Traditional approaches to understanding these declines focus on searching for climatic or other broad-scale extrinsic drivers. These approaches include multi-proxy studies that match reconstructed changes in tree abundance to reconstructed changes in precipitation or temperature. Although these correlative approaches are informative, they neglect the potential role of intrinsic processes, such as competition and dispersal, in shaping tree community dynamics. We developed a simple process-based community model that includes competition among tree species, density-dependent survival, and dispersal to investigate how these processes might generate abrupt changes in tree abundances even when extrinsic climatic factors do not themselves change abruptly. Specifically, a self-reinforcing (i.e., positive) feedback between abundance and survival can produce abrupt changes in tree abundance in the absence of long-term climatic changes. Furthermore, spatially correlated, short-term environmental variation and seed dispersal can increase the synchrony of abrupt changes. Using the well-studied, late-Holocene crash of Tsuga canadensis (eastern hemlock) populations as an empirical case study, we find that our model generates abrupt and quasi-synchronized crashes qualitatively similar to the observed hemlock patterns. Other tree taxa vary in the frequency and clustering of abrupt change and the proportion of increases and decreases. This complexity argues for caution in interpreting abrupt changes in species abundances as indicative of abrupt climatic changes. Nonetheless, some taxa show patterns that the model cannot produce: observed abrupt declines in hemlock abundance are more synchronized than abrupt increases, whereas the degree of synchronization is the same for abrupt decreases and increases in the model. Our results show that intrinsic processes can be significant contributing factors in abrupt tree population changes and highlight the diagnostic value of analyzing entire time series rather than single events when testing hypotheses about abrupt changes. Thus, intrinsic processes should be considered along with extrinsic drivers when seeking to explain rapid changes in community composition.

Responses of generalist and specialist species to fragmented landscapes.

Empirical studies have shown that, unlike species with specialized resource requirements, generalist species may benefit from habitat destruction. We use a family of models to probe the causes of the contrasting responses of these two types of species to habitat destruction. Our approach allows a number of mechanisms to be switched on and off, thereby making it possible to study their marginal and joint effects. Unlike many previous models, we do not assume any intrinsic competitive asymmetry between the species, and we assume pre-emptive rather than displacement competition. Under these assumptions, in the mean-field model the prevalences of all species decrease monotonically with decreasing habitat availability, independently of the degree of specialization. However, in the stochastic and spatial individual-based simulations of the same model, the specialists dominate in landscapes of high quality, whereas generalists thrive in landscapes of intermediate quality; no species persist in very poor landscapes. The same pattern also occurs in a non-spatial stochastic model but not in a deterministic spatial model, showing that demographic stochasticity plays a key role in shaping the outcome of competitive interactions.

Abrupt Change in Ecological Systems: Inference and Diagnosis.

Abrupt ecological changes are, by definition, those that occur over short periods of time relative to typical rates of change for a given ecosystem. The potential for such changes is growing due to anthropogenic pressures, which challenges the resilience of societies and ecosystems. Abrupt ecological changes are difficult to diagnose because they can arise from a variety of circumstances, including rapid changes in external drivers (e.g., climate, or resource extraction), nonlinear responses to gradual changes in drivers, and interactions among multiple drivers and disturbances. We synthesize strategies for identifying causes of abrupt ecological change and highlight instances where abrupt changes are likely. Diagnosing abrupt changes and inferring causation are increasingly important as society seek to adapt to rapid, multifaceted environmental changes.

Spatial and temporal dynamics of malaria in Madagascar.

BACKGROUND: Malaria is one of the primary health concerns in Madagascar. Based on the duration and intensity of transmission, Madagascar is divided into five epidemiological strata that range from low to mesoendemic transmission. In this study, the spatial and temporal dynamics of malaria within each epidemiological zone were studied. METHODS: The number of reported cases of uncomplicated malaria from 112 health districts between 2010 and 2014 were compiled and analysed. First, a Standardized Incidence Ratio was calculated to detect districts with anomalous incidence compared to the stratum-level incidence. Building on this, spatial and temporal malaria clusters were identified throughout the country and their variability across zones and over time was analysed. RESULTS: The incidence of malaria increased from 2010 to 2014 within each stratum. A basic analysis showed that districts with more than 50 cases per 1000 inhabitants are mainly located in two strata: East and West. Lower incidence values were found in the Highlands and Fringe zones. The standardization method revealed that the number of districts with a higher than expected numbers of cases increased through time and expanded into the Highlands and Fringe zones. The cluster analysis showed that for the endemic coastal region, clusters of districts migrated southward and the incidence of malaria was the highest between January and July with some variation within strata. CONCLUSION: This study identified critical districts with low incidence that shifted to high incidence and district that were consistent clusters across each year. The current study provided a detailed description of changes in malaria epidemiology and can aid the national malaria programme to reduce and prevent the expansion of the disease by targeting the appropriate areas.

Large-Scale Habitat Corridors for Biodiversity Conservation: A Forest Corridor in Madagascar.

In biodiversity conservation, habitat corridors are assumed to increase landscape-level connectivity and to enhance the viability of otherwise isolated populations. While the role of corridors is supported by empirical evidence, studies have typically been conducted at small spatial scales. Here, we assess the quality and the functionality of a large 95-km long forest corridor connecting two large national parks (416 and 311 km2) in the southeastern escarpment of Madagascar. We analyze the occurrence of 300 species in 5 taxonomic groups in the parks and in the corridor, and combine high-resolution forest cover data with a simulation model to examine various scenarios of corridor destruction. At present, the corridor contains essentially the same communities as the national parks, reflecting its breadth which on average matches that of the parks. In the simulation model, we consider three types of dispersers: passive dispersers, which settle randomly around the source population; active dispersers, which settle only in favorable habitat; and gap-avoiding active dispersers, which avoid dispersing across non-habitat. Our results suggest that long-distance passive dispersers are most sensitive to ongoing degradation of the corridor, because increasing numbers of propagules are lost outside the forest habitat. For a wide range of dispersal parameters, the national parks are large enough to sustain stable populations until the corridor becomes severely broken, which will happen around 2065 if the current rate of forest loss continues. A significant decrease in gene flow along the corridor is expected after 2040, and this will exacerbate the adverse consequences of isolation. Our results demonstrate that simulation studies assessing the role of habitat corridors should pay close attention to the mode of dispersal and the effects of regional stochasticity.