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Background: The West African country of Burkina Faso (BFA) is an example for the enduring importance of traditional plant use today. A large proportion of its 17 million inhabitants lives in rural communities and strongly depends on local plant products for their livelihood. However, literature on traditional plant use is still scarce and a comprehensive analysis for the country is still missing.
Methods: In this study we combine the information of a recently published plant checklist with information from ethnobotanical literature for a comprehensive, national scale analysis of plant use in Burkina Faso. We quantify the application of plant species in 10 different use categories, evaluate plant use on a plant family level and use the relative importance index to rank all species in the country according to their usefulness. We focus on traditional medicine and quantify the use of plants as remedy against 22 classes of health disorders, evaluate plant use in traditional medicine on the level of plant families and rank all species used in traditional medicine according to their respective usefulness.
Results: A total of 1033 species (50%) in Burkina Faso had a documented use. Traditional medicine, human nutrition and animal fodder were the most important use categories. The 12 most common plant families in BFA differed considerably in their usefulness and application. Fabaceae, Poaceae and Malvaceae were the plant families with the most used species. In this study Khaya senegalensis, Adansonia digitata and Diospyros mespiliformis were ranked the top useful plants in BFA. Infections/Infestations, digestive system disorders and genitourinary disorders are the health problems most commonly addressed with medicinal plants. Fabaceae, Poaceae, Asteraceae, Apocynaceae, Malvaceae and Rubiaceae were the most important plant families in traditional medicine. Tamarindus indica, Vitellaria paradoxa and Adansonia digitata were ranked the most important medicinal plants.
Conclusions: The national-scale analysis revealed systematic patterns of traditional plant use throughout BFA. These results are of interest for applied research, as a detailed knowledge of traditional plant use can a) help to communicate conservation needs and b) facilitate future research on drug screening.
One of the major problems in evolutionary biology is to elucidate the relationships between historical events and the tempo and mode of lineage divergence. The development of relaxed molecular clock models and the increasing availability of DNA sequences resulted in more accurate estimations of taxa divergence times. However, finding the link between competing historical events and divergence is still challenging. Here we investigate assigning constrained-age priors to nodes of interest in a time-calibrated phylogeny as a means of hypothesis comparison. These priors are equivalent to historic scenarios for lineage origin. The hypothesis that best explains the data can be selected by comparing the likelihood values of the competing hypotheses, modelled with different priors. A simulation approach was taken to evaluate the performance of the prior-based method and to compare it with an unconstrained approach. We explored the effect of DNA sequence length and the temporal placement and span of competing hypotheses (i.e. historic scenarios) on selection of the correct hypothesis and the strength of the inference. Competing hypotheses were compared applying a posterior simulation analogue of the Akaike Information Criterion and Bayes factors (obtained after calculation of the marginal likelihood with three estimators: Harmonic Mean, Stepping Stone and Path Sampling). We illustrate the potential application of the prior-based method on an empirical data set to compare competing geological hypotheses explaining the biogeographic patterns in Pleurodeles newts. The correct hypothesis was selected on average 89% times. The best performance was observed with DNA sequence length of 3500-10000 bp. The prior-based method is most reliable when the hypotheses compared are not temporally too close. The strongest inferences were obtained when using the Stepping Stone and Path Sampling estimators. The prior-based approach proved effective in discriminating between competing hypotheses when used on empirical data. The unconstrained analyses performed well but it probably requires additional computational effort. Researchers applying this approach should rely only on inferences with moderate to strong support. The prior-based approach could be applied on biogeographical and phylogeographical studies where robust methods for historical inferences are still lacking.
Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use the dynamic vegetation model LPJ-GUESS to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one exemplary "business-as-usual" climate scenario). Single factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C–N interactions, compared to the C-only version of the model, as documented in previous studies. Under a RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics until present. However, during the 21st century nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contradicts earlier model results that showed an 8 to 37% decrease in carbon uptake, questioning the often stated assumption that projections of future terrestrial C dynamics from C-only models are too optimistic.
Network graphs have become a popular tool to represent complex systems composed of many interacting subunits; especially in neuroscience, network graphs are increasingly used to represent and analyze functional interactions between multiple neural sources. Interactions are often reconstructed using pairwise bivariate analyses, overlooking the multivariate nature of interactions: it is neglected that investigating the effect of one source on a target necessitates to take all other sources as potential nuisance variables into account; also combinations of sources may act jointly on a given target. Bivariate analyses produce networks that may contain spurious interactions, which reduce the interpretability of the network and its graph metrics. A truly multivariate reconstruction, however, is computationally intractable because of the combinatorial explosion in the number of potential interactions. Thus, we have to resort to approximative methods to handle the intractability of multivariate interaction reconstruction, and thereby enable the use of networks in neuroscience. Here, we suggest such an approximative approach in the form of an algorithm that extends fast bivariate interaction reconstruction by identifying potentially spurious interactions post-hoc: the algorithm uses interaction delays reconstructed for directed bivariate interactions to tag potentially spurious edges on the basis of their timing signatures in the context of the surrounding network. Such tagged interactions may then be pruned, which produces a statistically conservative network approximation that is guaranteed to contain non-spurious interactions only. We describe the algorithm and present a reference implementation in MATLAB to test the algorithm’s performance on simulated networks as well as networks derived from magnetoencephalographic data. We discuss the algorithm in relation to other approximative multivariate methods and highlight suitable application scenarios. Our approach is a tractable and data-efficient way of reconstructing approximative networks of multivariate interactions. It is preferable if available data are limited or if fully multivariate approaches are computationally infeasible.
All giraffe (Giraffa) were previously assigned to a single species (G. camelopardalis) and nine subspecies. However, multi‐locus analyses of all subspecies have shown that there are four genetically distinct clades and suggest four giraffe species. This conclusion might not be fully accepted due to limited data and lack of explicit gene flow analyses. Here, we present an extended study based on 21 independent nuclear loci from 137 individuals. Explicit gene flow analyses identify less than one migrant per generation, including between the closely related northern and reticulated giraffe. Thus, gene flow analyses and population genetics of the extended dataset confirm four genetically distinct giraffe clades and support four independent giraffe species. The new findings support a revision of the IUCN classification of giraffe taxonomy. Three of the four species are threatened with extinction, and mostly occurring in politically unstable regions, and as such, require the highest conservation support possible.
Background: The invasive temperate mosquito Aedes japonicus japonicus is a potential vector for various infectious diseases and therefore a target of vector control measures. Even though established in Germany, it is unclear whether the species has already reached its full distribution potential. The possible range of the species, its annual population dynamics, the success of vector control measures and future expansions due to climate change still remain poorly understood. While numerous studies on occurrence have been conducted, they used mainly presence data from relatively few locations. In contrast, we used experimental life history data to model the dynamics of a continuous stage-structured population to infer potential seasonal densities and ask whether stable populations are likely to establish over a period of more than one year. In addition, we used climate change models to infer future ranges. Finally, we evaluated the effectiveness of various stage-specific vector control measures.
Results: Aedes j. japonicus has already established stable populations in the southwest and west of Germany. Our models predict a spread of Ae. j. japonicus beyond the currently observed range, but likely not much further eastwards under current climatic conditions. Climate change models, however, will expand this range substantially and higher annual densities can be expected. Applying vector control measures to oviposition, survival of eggs, larvae or adults showed that application of adulticides for 30 days between late spring and early autumn, while ambient temperatures are above 9 °C, can reduce population density by 75%. Continuous application of larvicide showed similar results in population reduction. Most importantly, we showed that with the consequent application of a mixed strategy, it should be possible to significantly reduce or even extinguish existing populations with reasonable effort.
Conclusion: Our study provides valuable insights into the mechanisms concerning the establishment of stable populations in invasive species. In order to minimise the hazard to public health, we recommend vector control measures to be applied in ‘high risk areas’ which are predicted to allow establishment of stable populations to establish.
Strong seasonal variability of hygric and thermal soil conditions are a defining environmental feature in Northern Australia. However, how such changes affect the soil–atmosphere exchange of nitrous oxide (N2O), nitric oxide (NO) and dinitrogen (N2) is still 5 not well explored. By incubating intact soil cores from four sites (3 savanna, 1 pasture) under controlled soil temperatures (ST) and soil moisture (SM) we investigated the release of the trace gas fluxes of N2O, NO and carbon dioxide (CO2). Furthermore, the release of N2 due to denitrification was measured using the helium gas flow soil core technique. Under dry pre-incubation conditions NO and N2O emission were very low (< 7.0± 5.0 μgNO-Nm−2 h−1; < 0.0± 1.4 μgN2O-Nm−2 h−1) or in case of N2O, even a net soil uptake was observed. Substantial NO (max: 306.5 μgNm−2 h−1) and relatively small N2O pulse emissions (max: 5.8±5.0 μgNm−2 h−1) were recorded following soil wetting, but these pulses were short-lived, lasting only up to 3 days. The total atmospheric loss of nitrogen was dominated by N2 emissions (82.4–99.3% of total N lost), although NO emissions contributed almost 43.2% at 50% SM and 30 °C ST. N2O emissions were systematically higher for 3 of 12 sample locations, which indicates substantial spatial variability at site level, but on average soils acted as weak N2O sources or even sinks. Emissions were controlled by SM and ST for N2O and CO2, ST and pH for NO, and SM and pH for N2.
Strong seasonal variability of hygric and thermal soil conditions are a defining environmental feature in northern Australia. However, how such changes affect the soil–atmosphere exchange of nitrous oxide (N2O), nitric oxide (NO) and dinitrogen (N2) is still not well explored. By incubating intact soil cores from four sites (three savanna, one pasture) under controlled soil temperatures (ST) and soil moisture (SM) we investigated the release of the trace gas fluxes of N2O, NO and carbon dioxide (CO2). Furthermore, the release of N2 due to denitrification was measured using the helium gas flow soil core technique. Under dry pre-incubation conditions NO and N2O emissions were very low (<7.0 ± 5.0 μg NO-N m−2 h−1; <0.0 ± 1.4 μg N2O-N m−2 h−1) or in the case of N2O, even a net soil uptake was observed. Substantial NO (max: 306.5 μg N m−2 h−1) and relatively small N2O pulse emissions (max: 5.8 ± 5.0 μg N m−2 h−1) were recorded following soil wetting, but these pulses were short lived, lasting only up to 3 days. The total atmospheric loss of nitrogen was generally dominated by N2 emissions (82.4–99.3% of total N lost), although NO emissions contributed almost 43.2% to the total atmospheric nitrogen loss at 50% SM and 30 °C ST incubation settings (the contribution of N2 at these soil conditions was only 53.2%). N2O emissions were systematically higher for 3 of 12 sample locations, which indicates substantial spatial variability at site level, but on average soils acted as weak N2O sources or even sinks. By using a conservative upscale approach we estimate total annual emissions from savanna soils to average 0.12 kg N ha−1 yr−1 (N2O), 0.68 kg N ha−1 yr−1 (NO) and 6.65 kg N ha−1 yr−1 (N2). The analysis of long-term SM and ST records makes it clear that extreme soil saturation that can lead to high N2O and N2 emissions only occurs a few days per year and thus has little impact on the annual total. The potential contribution of nitrogen released due to pulse events compared to the total annual emissions was found to be of importance for NO emissions (contribution to total: 5–22%), but not for N2O emissions. Our results indicate that the total gaseous release of nitrogen from these soils is low and clearly dominated by loss in the form of inert nitrogen. Effects of seasonally varying soil temperature and moisture were detected, but were found to be low due to the small amounts of available nitrogen in the soils (total nitrogen <0.1%).
Nowadays a number of endemic mosquito species are known to possess vector abilities for various diseases, as e.g. the sibling species Culex pipiens and Culex torrentium. Due to their morphological similarity, ecology, distribution and vector abilities, knowledge about these species' population structure is essential. Culicidae from 25 different sampling sites were collected from March till October 2012. All analyses were performed with aligned cox1 sequences with a total length of 658 bp. Population structure as well as distribution patterns of both species were analysed using molecular methods and different statistical tests like distance based redundancy analysis (dbDRA), analysis of molecular variances (AMOVA) or McDonald & Kreitman test and Tajima's D. Within both species, we could show a genetic variability among the cox1 fragment. The construction of haplotype networks revealed one dominating haplotype for Cx. pipiens, widely distributed within Germany and a more homogeneous pattern for Cx. torrentium. The low genetic differences within Cx. pipiens could be a result of an infection with Wolbachia which can induce a sweep through populations by passively taking the also maternally inherited mtDNA through the population, thereby reducing the mitochondrial diversity as an outcome of reproductive incompatibility. Pairwise population genetic differentiation (FST) ranged significantly from moderate to very great between populations of Cx. pipiens and Cx. torrentium. Analyses of molecular variances revealed for both species that the main genetic variability exists within the populations (Cx. pipiens [88.38%]; Cx. torrentium [66.54%]). Based on a distance based redundancy analysis geographical origin explained a small but significant part of the species' genetic variation. Overall, the results confirm that Cx. pipiens and Cx. torrentium underlie different factors regarding their mitochondrial differentiation, which could be a result of endosymbiosis, dispersal between nearly located populations or human introduction.