Following the liberalization of the coffee sector, governance and power balance in the international coffee trade has changed, with associated impacts on livelihoods in producing countries, most of which are middle- and low-income countries. Drawing on trade data for the period 1995–2018, we examine the dynamics and evolution of the international green coffee market to shed light on the re-distribution of value in the coffee supply chain. Data analysis shows that, over the studied period, the green coffee trade has increased considerably while the number of countries with a relevant role in trade has decreased, so that large exporting countries cover a higher share of trade, to the detriment of small exporting countries. We analyzed various properties of the global coffee trade network to provide insight on the relative contribution of countries not only in terms of their export value but also in terms of other selected features. The green coffee trade has gone from being distributed in many traditionally coffee-producing countries to concentrating mainly on the major coffee producers, as well as in some non-producing countries. These changes in the structure of the international green coffee market have led to greater inequality between producing and importing countries.

Cystic fibrosis (CF) lung microbiota composition has recently been redefined by the application of next-generation sequencing (NGS) tools, identifying, among others, previously undescribed anaerobic and uncultivable bacteria. In the present study, we monitored the fluctuations of this ecosystem in 15 CF patients during a 1-year follow-up period, describing for the first time, as far as we know, the presence of predator bacteria in the CF lung microbiome. In addition, a new computational model was developed to ascertain the hypothetical ecological repercussions of a prey-predator interaction in CF lung microbial communities. Fifteen adult CF patients, stratified according to their pulmonary function into mild ( n = 5), moderate ( n = 9), and severe ( n = 1) disease, were recruited at the CF unit of the Ramón y Cajal University Hospital (Madrid, Spain). Each patient contributed three or four induced sputum samples during a 1-year follow-up period. Lung microbiota composition was determined by both cultivation and NGS techniques and was compared with the patients’ clinical variables. Results revealed a particular microbiota composition for each patient that was maintained during the study period, although some fluctuations were detected without any clinical correlation. For the first time, Bdellovibrio and Vampirovibrio predator bacteria were shown in CF lung microbiota and reduced-genome bacterial parasites of the phylum Parcubacteria were also consistently detected. The newly designed computational model allows us to hypothesize that inoculation of predators into the pulmonary microbiome might contribute to the control of chronic colonization by CF pathogens in early colonization stages. IMPORTANCE The application of NGS to sequential samples of CF patients demonstrated the complexity of the organisms present in the lung (156 species) and the constancy of basic individual colonization patterns, although some differences between samples from the same patient were observed, probably related to sampling bias. Bdellovibrio and Vampirovibrio predator bacteria were found for the first time by NGS as part of the CF lung microbiota, although their ecological significance needs to be clarified. The newly designed computational model allows us to hypothesize that inoculation of predators into the lung microbiome can eradicate CF pathogens in early stages of the process. Our data strongly suggest that lower respiratory microbiome fluctuations are not necessarily related to the patient’s clinical status.

Mutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r-K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r-K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities.