Brood indicators are an early warning signal of honey bee colony loss-a simulation-based study

Honey bees (Apis mellifera) are exposed to multiple stressors such as pesticides, lack of forage, and diseases. It is therefore a long-standing aim to develop robust and meaningful indicators of bee vitality to assist beekeepers While established indicators often focus on expected colony winter mortality based on adult bee abundance and honey reserves at the beginning of the winter, it would be useful to have indicators that allow detection of stress effects earlier in the year to allow for adaptive management. We used the established honey bee simulation model BEEHAVE to explore the potential of different indicators such as population size, number of capped brood cells, flight activity, abundance of Varroa mites, honey stores and a brood-bee ratio. We implemented two types of stressors in our simulations: 1) parasite pressure, i.e. sub-optimal Varroa treatment by the beekeeper (hereafter referred as Biotic stress) and 2) temporal forage gaps in spring and autumn (hereafter referred as Environmental stress). Neither stressor type could be detected by bee abundance or honey reserves at the end of the first year. However, all response variables used in this study did reveal early warning signals during the course of the year. The most reliable and useful measures seem to be related to brood and the abundance of Varroa mites at the end of the year. However, while in the model we have full access to time series of variables from stressed and unstressed colonies, knowledge of these variables in the field is challenging. We discuss how our findings can nevertheless be used to develop practical early warning indicators. As a next step in the interactive development of such indicators we suggest empirical studies on the importance of the number of capped brood cells at certain times of the year on bee population vitality.

Simulation of Varroa mite control in honey bee colonies without synthetic acaricides: Demonstration of Good Beekeeping Practice for Germany in the BEEHAVE model

The BEEHAVE model simulates the population dynamics and foraging activity of a single honey bee colony (Apis mellifera) in great detail. Although it still makes numerous simplifying assumptions, it appears to capture a wide range of empirical observations. It could, therefore, in principle, also be used as a tool in beekeeper education, as it allows the implementation and comparison of different management options. Here, we focus on treatments aimed at controlling the mite Varroa destructor. However, since BEEHAVE was developed in the UK, mite treatment includes the use of a synthetic acaricide, which is not part of Good Beekeeping Practice in Germany. A practice that consists of drone brood removal from April to June, treatment with formic acid in August/September, and treatment with oxalic acid in November/December. We implemented these measures, focusing on the timing, frequency, and spacing between drone brood removals. The effect of drone brood removal and acid treatment, individually or in combination, on a mite-infested colony was examined. We quantify the efficacy of Varroa mite control as the reduction of mites in treated bee colonies compared to untreated bee colonies. We found that drone brood removal was very effective, reducing mites by 90% at the end of the first simulation year after the introduction of mites. This value was significantly higher than the 50-67% reduction expected by bee experts and confirmed by empirical studies. However, literature reports varying percent reductions in mite numbers from 10 to 85% after drone brood removal. The discrepancy between model results, empirical data, and expert estimates indicate that these three sources should be reviewed and refined, as all are based on simplifying assumptions. These results and the adaptation of BEEHAVE to the Good Beekeeping Practice are a decisive step forward for the future use of BEEHAVE in beekeeper education in Germany and anywhere where organic acids and drone brood removal are utilized.

Chronic and Acute Effects of Imidacloprid on a Simulated BEEHAVE Honeybee Colony

Honeybees (Apis mellifera) are important pollinators for wild plants as well as for crops, but honeybee performance is threatened by several stressors including varroa mites, gaps in foraging supply, and pesticides. The consequences of bee colony longtime exposure to multiple stressors are not well understood. The vast number of possible stressor combinations and necessary study duration require research comprising field, laboratory, and simulation experiments. We simulated long-term exposure of a honeybee colony to the insecticide imidacloprid and to varroa mites carrying the deformed wing virus in landscapes with different temporal gaps in resource availability as single stressors and in combinations. Furthermore, we put a strong emphasis on chronic lethal, acute sublethal, and acute lethal effects of imidacloprid on honeybees. We have chosen conservative published values to parameterize our model (e.g., highest reported imidacloprid contamination). As expected, combinations of stressors had a stronger negative effect on bee performance than each single stressor alone, and effect sizes were larger after 3 years of exposure than after the first year. Imidacloprid-caused reduction in bee performance was almost exclusively due to chronic lethal effects because the thresholds for acute effects were rarely met in simulations. In addition, honeybee colony extinctions were observed by the last day of the first year but more pronounced on the last days of the second and third simulation year. In conclusion, our study highlights the need for more long-term studies on chronic lethal effects of pesticides on honeybees. Environ Toxicol Chem 2022;41:2318-2327. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Accelerated forest fragmentation leads to critical increase in tropical forest edge area

Large areas of tropical forests have been lost through deforestation, resulting in fragmented forest landscapes. However, the dynamics of forest fragmentation are still unknown, especially the critical forest edge areas, which are sources of carbon emissions due to increased tree mortality. We analyzed the changes in forest fragmentation for the entire tropics using high-resolution forest cover maps. We found that forest edge area increased from 27 to 31% of the total forest area in just 10 years, with the largest increase in Africa. The number of forest fragments increased by 20 million with consequences for connectivity of tropical landscapes. Simulations suggest that ongoing deforestation will further accelerate forest fragmentation. By 2100, 50% of tropical forest area will be at the forest edge, causing additional carbon emissions of up to 500 million MT carbon per year. Thus, efforts to limit fragmentation in the world’s tropical forests are important for climate change mitigation.

Informal risk-sharing between smallholders may be threatened by formal insurance: Lessons from a stylized agent-based model

Microinsurance is promoted as a valuable instrument for low-income households to buffer financial losses due to health or climate-related risks. However, apart from direct positive effects, such formal insurance schemes can have unintended side effects when insured households lower their contribution to traditional informal arrangements where risk is shared through private monetary support. Using a stylized agent-based model, we assess impacts of microinsurance on the resilience of those smallholders in a social network who cannot afford this financial instrument. We explicitly include the decision behavior regarding informal transfers. We find that the introduction of formal insurance can have negative side effects even if insured households are willing to contribute to informal risk arrangements. However, when many households are simultaneously affected by a shock, e.g. by droughts or floods, formal insurance is a valuable addition to informal risk-sharing. By explicitly taking into account long-term effects of short-term transfer decisions, our study allows to complement existing empirical research. The model results underline that new insurance programs have to be developed in close alignment with established risk-coping instruments. Only then can they be effective without weakening functioning aspects of informal risk management, which could lead to increased poverty.

Rarity of monodominance in hyperdiverse Amazonian forests

Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such “monodominant” forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors.

Global patterns of tropical forest fragmentation

Remote sensing enables the quantification of tropical deforestation with high spatial resolution. This in-depth mapping has led to substantial advances in the analysis of continent-wide fragmentation of tropical forests. Here we identified approximately 130 million forest fragments in three continents that show surprisingly similar power-law size and perimeter distributions as well as fractal dimensions. Power-law distributions have been observed in many natural phenomena such as wildfires, landslides and earthquakes. The principles of percolation theory provide one explanation for the observed patterns, and suggest that forest fragmentation is close to the critical point of percolation; simulation modelling also supports this hypothesis. The observed patterns emerge not only from random deforestation, which can be described by percolation theory, but also from a wide range of deforestation and forest-recovery regimes. Our models predict that additional forest loss will result in a large increase in the total number of forest fragments-at maximum by a factor of 33 over 50 years-as well as a decrease in their size, and that these consequences could be partly mitigated by reforestation and forest protection.

High resolution analysis of tropical forest fragmentation and its impact on the global carbon cycle

Deforestation in the tropics is not only responsible for direct carbon emissions but also extends the forest edge wherein trees suffer increased mortality. Here we combine high-resolution (30 m) satellite maps of forest cover with estimates of the edge effect and show that 19% of the remaining area of tropical forests lies within 100 m of a forest edge. The tropics house around 50 million forest fragments and the length of the world's tropical forest edges sums to nearly 50 million km. Edge effects in tropical forests have caused an additional 10.3 Gt (2.1–14.4 Gt) of carbon emissions, which translates into 0.34 Gt per year and represents 31% of the currently estimated annual carbon releases due to tropical deforestation. Fragmentation substantially augments carbon emissions from tropical forests and must be taken into account when analysing the role of vegetation in the global carbon cycle.

Vast quantities of carbon stored in tropical forests are threatened by deforestation. Here, using high resolution satellite data, Brinck et al. examine how edge effects influence carbon emissions and they find an additional 10.3 Gt of carbon are released by deforestation when including fragmentation effects.

Monodominance in tropical forests: modelling reveals emerging clusters and phase transitions

Tropical forests are highly diverse ecosystems, but within such forests there can be large patches dominated by a single tree species. The myriad presumed mechanisms that lead to the emergence of such monodominant areas is currently the subject of intensive research. We used the most generic of these mechanisms, large seed mass and low dispersal ability of the monodominant species, in a spatially explicit model. The model represents seven identical species with long-distance dispersal of small seeds, competing with one potentially monodominant species with short-distance dispersal of large seeds. Monodominant patches emerged and persisted only for a narrow range of species traits; these results have the characteristic features of phase transitions. Additional mechanisms may explain monodominance in different ecological contexts, but our results suggest that percolation-like phenomena and phase transitions might be pervasive in this type of system.

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine: Brussels, Belgium. 15-18 March 2016

[This corrects the article DOI: 10.1186/s13054-016-1208-6.].

A critical evaluation of ecological indices for the comparative analysis of microbial communities based on molecular datasets

In times of global change and intensified resource exploitation, advanced knowledge of ecophysiological processes in natural and engineered systems driven by complex microbial communities is crucial for both safeguarding environmental processes and optimising rational control of biotechnological processes. To gain such knowledge, high-throughput molecular techniques are routinely employed to investigate microbial community composition and dynamics within a wide range of natural or engineered environments. However, for molecular dataset analyses no consensus about a generally applicable alpha diversity concept and no appropriate benchmarking of corresponding statistical indices exist yet. To overcome this, we listed criteria for the appropriateness of an index for such analyses and systematically scrutinised commonly employed ecological indices describing diversity, evenness and richness based on artificial and real molecular datasets. We identified appropriate indices warranting interstudy comparability and intuitive interpretability. The unified diversity concept based on 'effective numbers of types' provides the mathematical framework for describing community composition. Additionally, the Bray-Curtis dissimilarity as a beta-diversity index was found to reflect compositional changes. The employed statistical procedure is presented comprising commented R-scripts and example datasets for user-friendly trial application.

Simulating the effects of different spatio-temporal fire regimes on plant metapopulation persistence in a Mediterranean-type region

Spatio-temporal fire regimes are likely to shift with changes in land use and climate. Such a shift in the disturbance regime has been proposed from recent reconstructions of the regional fire history in the Mediterranean-type woodlands and shrublands of Western Australia which suggest that fire was much more frequent before 1930 (local fire intervals of 3–5 years) than it is today (local fire intervals of 8–15 years).

To investigate the potential biodiversity consequences of such changes in fire regime for fire-killed woody species, we developed a spatial model for the serotinous shrub Banksia hookeriana that grows on sand dunes of the Eneabba Plain, Western Australia. We sought to identify the envelope of fire regimes under which the spatially separated populations in this species are able to persist, and whether this encompasses the fire regimes proposed by recent fire-history reconstructions.

We tested two fire frequency-size distribution scenarios: (1) a scenario where fire size depends on the spatial patch configuration; and (2) a scenario depending also on available fuel (time since last fire), which reduces fire size at short inter-fire intervals.

In scenario 1, metapopulation persistence was only likely for mean ignition intervals at the landscape scale of 6 years. In scenario 2, persistence was likely for the whole range of fire interval distributions at the landscape scale suggested by the empirical data. However, persistence was almost impossible if the mean return fire interval at the local scale (i.e. for individual dunes) is < 8 years.

Synthesis and applications. We have demonstrated that this plant metapopulation can potentially persist over a wide range of temporal fire regimes at the landscape scale, so long as there are buffering mechanisms at work (e.g. feedback between fire spread and vegetation age) which reduces the probability of large fires at short intervals. Our findings demonstrate that at least some parts of the landscape must burn substantially less frequently on average than suggested by the empirical fire reconstructions for the early and pre-European period if populations of fire-killed woody species such as B. hookeriana are to be conserved.

Prediction of mortality in febrile medical patients: How useful are systemic inflammatory response syndrome and sepsis criteria?

STUDY OBJECTIVES

The aim was to evaluate demographic, clinical, and laboratory variables in febrile patients, with or without a microbiologically confirmed infection, for prediction of death, in comparison to the systemic inflammatory response syndrome (SIRS) and its criteria, such as abnormal temperature, tachycardia, tachypnea, and abnormal WBC count, and to sepsis, that includes SIRS and an infection.

DESIGN

A prospective cohort study.

SETTING

Department of internal medicine at a university hospital.

PATIENTS

In 300 consecutive, hospitalized medical patients with new onset of fever, demographic, clinical, and laboratory variables were obtained during the 2 days after inclusion, while microbiological results for a follow-up period of 7 days were collected. Patients were followed up for survival or death, up to a maximum of 28 days after inclusion.

MEASUREMENTS AND RESULTS

Of all patients, 95% had SIRS, 44% had sepsis with a microbiologically confirmed infection, and 9% died. A model with a set of variables all significantly (p<0.01) contributing to the prediction of mortality was derived. The set included the presence of hospital-acquired fever, the peak respiratory rate, the nadir score on the Glasgow coma scale, and the nadir albumin plasma level within the first 2 days after inclusion. This set of variables predicted mortality for febrile patients with microbiologically confirmed infection even better. The predictive values for mortality of SIRS and sepsis were less than that of our set of variables.

CONCLUSIONS

In comparison to SIRS and sepsis, the new set of variables predicted mortality better for all patients with fever and also for those with microbiologically confirmed infection only. This type of effort may help in refining definitions of SIRS and sepsis, based on prognostically important demographic, clinical, and laboratory variables that are easily obtainable at the bedside.

Simultaneous determination of creatine compounds and adenine nucleotides in myocardial tissue by high-performance liquid chromatography

A rapid high-performance liquid chromatography method was developed for the determination of creatine phosphate, creatine, adenine nucleotides, and related compounds in myocardial tissue. Analysis was performed by reversed-phase chromatography on a C18 column containing 3-microns particles, employing gradient elution and uv detection at 210 nm. Separation was achieved in less than 5 min. Total analysis time, including equilibration of the column after return of the gradient to starting conditions, was 8 min. The high reproducibility and short analysis time make this method suitable for the routine analysis of large series of samples.

Antigenic heterogeneity of human brain tumors defined by monoclonal antibodies

The antigenic profiles of human gliomas and in vitro established cell lines were investigated using the monoclonal antibodies (MABs) MUC 8-22 and MUC 2-63. The reactivity with tissue samples and cytospin preparations obtained from 45 brain tumors was estimated by the indirect immunoperoxidase technique. In addition, computer-assisted cytofluorometry was used to quantify the intensity and distribution of antibody-binding. Various degrees of antibody-binding among and within gliomas and glioma-derived cell lines were observed. The data show that a variable percentage of cells are not labeled with the employed MABs. The spectrum of reactivity of the selected antibodies was independent of the histological grading of gliomas. However, there were significant differences in various stages of subcultivation of glioma lines. In most cases, the heterogeneity of antigen expression decreased during successive in vitro propagation of glioma cells. The extent of variation in staining intensity values differed within cell populations and reflected the antigenic heterogeneity of human brain tumors. The findings presented here suggest that the use of MABs which recognize glioma-associated antigens facilitates the objective analysis of brain tumors and is of potential value for immunohistochemical application in surgical neuropathology.