Biodiversity, functional redundancy and system stability: subtle connections

Contextualizing the ecology of plant-plant interactions and constructive networks

Botanical concepts have traditionally viewed the environment as a static box containing plants. In this box, plants compete with one another and act as passive resource consumers subjected to the environment in a top-down manner. This entails that plants have only negative effects on other plants and have no influence on the environment. By contrast, there is increasing evidence that plants have positive, bottom-up engineering effects and diversity effects on other plants and on the environment. Here, to overcome the limitations of top-down environmental control, antagonistic-only and pairwise interactions, I propose the concept of constructive networks. Constructive networks unify niche construction and network theory recognizing that (i) plants have manifold ecological functions and impacts on their neighbours, and (ii) the environment shapes and is shaped by diverse organisms, primarily plants. Constructive networks integrate both plant-environment and plant-plant interactions in a relational context. They address how plants influence the environment and support or inhibit other plant species by physically, biochemically and ecologically shaping environmental conditions. Constructive networks acknowledge the fact that diverse plants change and create novel environmental conditions and co-produce, share and transform resources, thereby influencing biological communities and the environment in constructive ways. Different interaction types are considered simultaneously in constructive networks. Yet, the main limitation to understanding constructive networks is the identification of plant links. This barrier may be overcome by applying complexity theory and statistical mechanics to comparative data and experimental field botany. Considering multiple interaction types and feedback between plants and the environment may improve our understanding of mechanisms responsible for biodiversity maintenance and help us to better anticipate the response of plant systems to global change.

Revealing proteome-level functional redundancy in the human gut microbiome using ultra-deep metaproteomics

Functional redundancy is a key ecosystem property representing the fact that different taxa contribute to an ecosystem in similar ways through the expression of redundant functions. The redundancy of potential functions (or genome-level functional redundancy [Formula: see text]) of human microbiomes has been recently quantified using metagenomics data. Yet, the redundancy of expressed functions in the human microbiome has never been quantitatively explored. Here, we present an approach to quantify the proteome-level functional redundancy [Formula: see text] in the human gut microbiome using metaproteomics. Ultra-deep metaproteomics reveals high proteome-level functional redundancy and high nestedness in the human gut proteomic content networks (i.e., the bipartite graphs connecting taxa to functions). We find that the nested topology of proteomic content networks and relatively small functional distances between proteomes of certain pairs of taxa together contribute to high [Formula: see text] in the human gut microbiome. As a metric comprehensively incorporating the factors of presence/absence of each function, protein abundances of each function and biomass of each taxon, [Formula: see text] outcompetes diversity indices in detecting significant microbiome responses to environmental factors, including individuality, biogeography, xenobiotics, and disease. We show that gut inflammation and exposure to specific xenobiotics can significantly diminish the [Formula: see text] with no significant change in taxonomic diversity.

Analysis of trophic networks: an optimisation approach

We introduce a methodology to study the possible matter flows of an ecosystem defined by observational biomass data and realistic biological constraints. The flows belong to a polyhedron in a multi dimensional space that may make statistical exploration difficult in practice; instead, we propose to solve a convex optimization problem. Seven criteria based on ecological network indices have been selected to be used as convex goal functions. Numerical results show that the method is fast and can be used for large systems. Minimum flow solutions are analyzed using flow decomposition in paths and circuits. Their consistency is also tested by introducing a system of differential equations for the biomasses and examining the stability of the biomass fixed point. The method is illustrated and explained throughout the text on an ecosystem toy model. It is also applied to realistic food models.

Provision of refugia and seeding with native bivalves can enhance biodiversity on vertical seawalls

Recent studies have suggested that increasing habitat complexity of artificial seawalls by modifying surface heterogeneity could enhance exploitable habitat and therefore species richness and abundance. We tested the effects of adding complex tiles (with crevices/ledges) of different heterogeneity (i.e., flat tiles resembling the seawall vs. tiles with crevices of 2.5 cm or 5.0 cm depth) and seeding with native rock oysters, Saccostrea cuccullata (unseeded vs. seeded) on species richness and abundances of intertidal marine organisms on two vertical seawalls in Hong Kong. Tiles were affixed to the mid-intertidal zone of the seawalls for 12 months. The results showed that the tiles with crevices had greater species richness and cover of sessile epifauna than flat tiles. Seeding tiles with S. cuccullata also facilitated natural recruitment of the same species. Our results support the hypothesis that using eco-engineering to increase habitat complexity can enhance the biodiversity of intertidal marine organisms on seawalls.

Does evolution design robust food webs?

Theoretical works that use a dynamical approach to study the ability of ecological communities to resist perturbations are largely based on randomly generated ecosystem structures. By contrast, we ask here whether the evolutionary history of food webs matters for their robustness. Using a community evolution model, we first generate trophic networks by varying the level of energy supply (richness) of the environment in which species adapt and diversify. After placing our simulation outputs in perspective with present-day food webs empirical data, we highlight the complex, structuring role of this environmental condition during the evolutionary setting up of trophic networks. We then assess the robustness of food webs by studying their short-term ecological responses to swift changes in their customary environmental richness. We reveal that the past conditions have a crucial effect on the robustness of current food webs. Moreover, directly focusing on connectance of evolved food webs, it turns out that the most connected ones appear to be the least robust to sharp depletion in the environmental energy supply. Finally, we appraise the 'adaptation' of food webs themselves: generally poor, except in relation to a diversity of flux property.

Information Across the Ecological Hierarchy

The ecosystem is a theatre upon which is presented, in various degrees and at differing scales, a drama of constraint and information vs. disorganization and entropy. Concerning biology, most think immediately of genomic information. It strongly constrains the form and behavior of individual species, but its influence upon community structure is indeterminate. At the community level, information acts as a formal cause behind regular patterns of development. Community structure is an amalgam of information and entropy, and the Gibbs–Boltzmann formula departs from the thermodynamic sense of entropy. It measures only the extreme that entropy might reach if the elements of the system were completely independent. A closer analogy to physical entropy in systems with interactions is the conditional entropy—the amount by which the Shannon measure is reduced after the information in the constraints among elements has been subtracted. Finally, at the whole ecosystem level, in communities that inhabit mostly fixed physical environments (e.g., landscapes or seabeds), the distributions of plants and animals appear to be independent both of causal mechanisms and trophic controls, and assume instead forms that maximize the overall entropy of dispersal.