Defining a land boundary for sustainable livestock consumption

The need for more sustainable production and consumption of animal source food (ASF) is central to the achievement of the sustainable development goals: within this context, wise use of land is a core challenge and concern. A key question in feeding the future world is: how much ASF should we eat? We demonstrate that livestock raised under the circular economy concept could provide a significant, nonnegligible part (9–23 g/per capita) of our daily protein needs (~50–60 g/per capita). This livestock then would not consume human‐edible biomass, such as grains, but mainly convert leftovers from arable land and grass resources into valuable food, implying that production of livestock feed is largely decoupled from arable land. The availability of these biomass streams for livestock then determines the boundaries for livestock production and consumption. Under this concept, the competition for land for feed or food would be minimized and compared to no ASF, including some ASF in the human diet could free up about one quarter of global arable land. Our results also demonstrate that restricted growth in consumption of ASF in Africa and Asia would be feasible under these boundary conditions, while reductions in the rest of the world would be necessary to meet land use sustainability criteria. Managing this expansion and contraction of future consumption of ASF is essential for achieving sustainable nutrition security.     

Landscape configuration drives persistent spatial patterns of occupant distributions

Variation in the density of organisms among habitat patches is often attributed to variation in inherent patch properties. For example, higher quality patches might have higher densities because they attract more colonists or confer better post-colonization survival. However, variation in occupant density can also be driven by landscape configuration if neighboring patches draw potential colonists away from the focal habitat (a phenomenon we call propagule redirection). Here, we develop and analyze a stochastic model to quantify the role of landscape configuration and propagule redirection on occupant density patterns. We model a system with a dispersive larval stage and a sedentary adult stage. The model includes sensing and decision-making in the colonization stage and density-dependent mortality (a proxy for patch quality) in the post-colonization stage. We demonstrate that spatial variation in colonization is retained when the supply of colonists is not too high, post-colonization density-dependent survival is not too strong, and colonization events are not too frequent. Using a reef fish system, we show that the spatial variation produced by propagule redirection is comparable to spatial variation expected when patch quality varies. Thus, variation in density arising from the spatial patterning of otherwise identical habitat can play an important role in shaping long-term spatial patterns of organisms occupying patchy habitats. Propagule redirection is a potentially powerful mechanism by which landscape configuration can drive variation in occupant densities, and may therefore offer new insights into how populations may shift as landscapes change in response to natural and anthropogenic forces.     

Three-dimensional simulation of obstacle-mediated chemotaxis

Amoeboid cells exhibit a highly dynamic motion that can be directed by external chemical signals, through the process of chemotaxis. Here, we propose a three-dimensional model for chemotactic motion of amoeboid cells. We account for the interactions between the extracellular substances, the membrane-bound proteins, and the cytosolic components involved in the signaling pathway that originates cell motility. We show two- and three-dimensional simulations of cell migration on planar substrates, flat surfaces with obstacles, and fibrous networks. The results show that our model reproduces the main features of chemotactic amoeboid motion. Our simulations unveil a complicated interplay between the geometry of the cell’s environment and the chemoattractant dynamics that tightly regulates cell motion. The model opens new opportunities to simulate the interactions between extra- and intra-cellular compounds mediated by the matrix geometry.     

Nutritional quality modulates trait variability

Background

Trait based functional and community ecology is en vogue. Most studies, however, ignore phenotypical diversity by characterizing entire species considering only trait means rather than their variability. Phenotypical variability may arise from genotypical differences or from ecological factors (e.g., nutritionally imbalanced diet), and these causes can usually not be separated in natural populations. We used a single genotype from a parthenogenetic model system (the oribatid mite Archegozetes longisetosus Aoki) to exclude genotypical differences. We investigated patterns of dietary (10 different food treatments) induced trait variation by measuring the response of nine different traits (relating to life history, morphology or exocrine gland chemistry).

Results

Nutritional quality (approximated by carbon-to-nitrogen ratios) influenced all trait means and their variation. Some traits were more prone to variation than others. Furthermore, the “threshold elemental ratio”- rule of element stoichiometry applied to phenotypic trait variation. Imbalanced food (i.e. food not able to fully meet the nutritional demands of an animal) led to lower trait mean values, but also to a higher variation of traits.

Conclusion

Imbalanced food led not only to lower trait value averages, but also to higher trait variability. There was a negative relationship between both parameters, indicating a direct link of both, average trait levels and trait variation to nutritional quality. Hence, variation of trait means may be a predictor for general food quality, and further indicate trade-offs in specific traits an animal must deal with while feeding on imbalanced diets.

     

Profiling microbial strains in urban environments using metagenomic sequencing data

Background

The microbial communities populating human and natural environments have been extensively characterized with shotgun metagenomics, which provides an in-depth representation of the microbial diversity within a sample. Microbes thriving in urban environments may be crucially important for human health, but have received less attention than those of other environments. Ongoing efforts started to target urban microbiomes at a large scale, but the most recent computational methods to profile these metagenomes have never been applied in this context. It is thus currently unclear whether such methods, that have proven successful at distinguishing even closely related strains in human microbiomes, are also effective in urban settings for tasks such as cultivation-free pathogen detection and microbial surveillance. Here, we aimed at a) testing the currently available metagenomic profiling tools on urban metagenomics; b) characterizing the organisms in urban environment at the resolution of single strain and c) discussing the biological insights that can be inferred from such methods.

Results

We applied three complementary methods on the 1614 metagenomes of the CAMDA 2017 challenge. With MetaMLST we identified 121 known sequence-types from 15 species of clinical relevance. For instance, we identified several Acinetobacter strains that were close to the nosocomial opportunistic pathogen A. nosocomialis. With StrainPhlAn, a generalized version of the MetaMLST approach, we inferred the phylogenetic structure of Pseudomonas stutzeri strains and suggested that the strain-level heterogeneity in environmental samples is higher than in the human microbiome. Finally, we also probed the functional potential of the different strains with PanPhlAn. We further showed that SNV-based and pangenome-based profiling provide complementary information that can be combined to investigate the evolutionary trajectories of microbes and to identify specific genetic determinants of virulence and antibiotic resistances within closely related strains.

Conclusion

We show that strain-level methods developed primarily for the analysis of human microbiomes can be effective for city-associated microbiomes. In fact, (opportunistic) pathogens can be tracked and monitored across many hundreds of urban metagenomes. However, while more effort is needed to profile strains of currently uncharacterized species, this work poses the basis for high-resolution analyses of microbiomes sampled in city and mass transportation environments.

Reviewers

This article was reviewed by Alexandra Bettina Graf, Daniel Huson and Trevor Cickovski.