Ecological intensification, or the improvement of crop yield through enhancement of biodiversity, may be a sustainable pathway toward greater food supplies. Such sustainable increases may be especially important for the 2 billion people reliant on small farms, many of which are undernourished, yet we know little about the efficacy of this approach. Using a coordinated protocol across regions and crops, we quantify to what degree enhancing pollinator density and richness can improve yields on 344 fields from 33 pollinator-dependent crop systems in small and large farms from Africa, Asia, and Latin America. For fields less than 2 hectares, we found that yield gaps could be closed by a median of 24% through higher flower-visitor density. For larger fields, such benefits only occurred at high flower-visitor richness. Worldwide, our study demonstrates that ecological intensification can create synchronous biodiversity and yield outcomes.

Food production is challenged by changes in climate and land use and expanding human population growth. Proper pollination can increase the production and quality of fruit, nut, oil, and fiber crops. We reviewed crop dependence on pollinators and estimated the economic value of pollination per year for each crop in Brazil. We analyzed 141 crops and found that 85 depend on pollinators. Almost one-third of these crops have an essential or great dependence on pollinators. The economic contribution of pollinators totals ∼30% (∼US$12 billion) of the total annual agricultural income of the dependent crops (totalizing almost US$45 billion). However, half of these figures includes soybean crop (US$5.7 billion of pollinators' contribution and US$22 billion of annual income). Soybean was considered as having a modest dependence on pollinators, but this remains controversial because pollinator dependence might vary among different varieties cultivated in Brazil. Moreover, we have no information about pollinator dependence regarding some important crops, showing the urgent need for basic research into reproductive biology and pollination ecology.

Biotic interactions have been considered as an important feature in species distribution modeling, but little is known about the effect of including different types of interactions or performing different strategies of integrating biotic interactions in species distribution modelling. This study compares different methods for including interspecific interactions in species distribution models for bees, their cleptoparasites, and the plants they pollinate. Hostparasite interactions among bumble bees (genus Bombus: generalist pollinators and brood parasites) and specialist plant-pollinator interactions between Centris bees and Krameria flowers were used as case studies. We used 7 different modelling algorithms available in the BIOMOD R package. Adding biotic information to present day predictions of potential occurrence significantly improved the cross-validated area under the receiver operating characteristic curve (AUC), a measure often applied to estimate model accuracy. Different species and types of interaction showed different AUC results in line with data quality, level of biological linkage and interdependence of each interaction. Furthermore, the species that presented the best improvement of AUC was projected under future climate scenarios. The results showed marked differences when using abiotic data only, and when including biotic interactions of various types. The results show that choosing the correct biotic information, based on biological and ecological knowledge, is critical to improve the accuracy of species distribution models, and also to forecast distribution change.

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Supergeneralists, defined as species that interact with multiple groups of species in ecological networks, can act as important connectors of otherwise disconnected species subsets. In Brazil, there are two supergeneralist bees: the honeybee Apis mellifera, a non-native species, and Trigona spinipes, a native stingless bee. We compared the role of both species and the effect of geographic and local factors on networks by addressing three questions: 1) Do both species have similar abundance and interaction patterns (degree and strength) in plant-bee networks? 2) Are both species equally influential to the network structure (nestedness, connectance, and plant and bee niche overlap)? 3) How are these species affected by geographic (altitude, temperature, precipitation) and local (natural vs. disturbed habitat) factors? We analyzed 21 plant-bee weighted interaction networks, encompassing most of the main biomes in Brazil. We found no significant difference between both species in abundance, in the number of plant species with which each bee species interacts (degree), and in the sum of their dependencies (strength). Structural equation models revealed the effect of A. mellifera and T. spinipes, respectively, on the interaction network pattern (nestedness) and in the similarity in bee’s interactive partners (bee niche overlap). It is most likely that the recent invasion of A. mellifera resulted in its rapid settlement inside the core of species that retain the largest number of interactions, resulting in a strong influence on nestedness. However, the long-term interaction between native T. spinipes and other bees most likely has a more direct effect on their interactive behavior. Moreover, temperature negatively affected A. mellifera bees, whereas disturbed habitats positively affected T. spinipes. Conversely, precipitation showed no effect. Being positively (T. spinipes) or indifferently (A. mellifera) affected by disturbed habitats makes these species prone to pollinate plant species in these areas, which are potentially poor in pollinators.

Escherichia coli is an important microorganism in the gastrointestinal tract of warm-blooded animals. Commensal populations of E. coli consist of stable genetic isolates, which means that each individual has only one phylogenetic group (phylogroup). We evaluated the frequency of human commensal E. coli phylogroups from 116 people and observed that the majority of isolates belonged to group A. We also evaluated the frequency of phylogroups in wastewater samples and found a strong positive correlation between the phylogroup distribution in wastewater and human hosts. In order to find out if some factors, such as geographical location, and climate could influence the worldwide phylogroup distribution, we performed a meta-analysis of 39 different studies and 24 countries, including different climates, living areas, and feeding habits. Unexpectedly, our results showed no substructuring patterns of phylogroups; indicating there was no correlation between phylogroup distribution and geographic location, climate, living area, feeding habits, or date of collection.

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