An inexpensive photosynthetic irradiance sensor for ecological field studies

The design and characteristics of inexpensive and simply constructed equal-energy response photosynthetic irradiance sensors is described for use particularly where several cells are required in comparative ecological studies either above or below water. The dimensions of the sensors can be changed proportionally to suit different applications or components. The response of the sensor to irradiance at varying angles corresponds very closely to that required by the cosine law. The sensor is comparatively insensitive to other environmental variables in field use and gave a stable output; the long term drift was proportional to electrical output but in continuous use, drift is regular and could reach -0.08 year^-1 of the total. The spectral range and cosine response is discussed in comparison to other more expensive (x 5–10) commercially available, sensors and to local standards.     

Response of three lotic assemblages to riparian and catchment‐scale land use: implications for designing catchment monitoring programmes

1. Although many studies have focussed on the effects of catchment land use on lotic systems, the importance of broad (catchment) and fine (segment/reach) scale effects on stream assemblages remain poorly understood. 2. Nine biological metrics for macrophytes (498 sites), benthic macroinvertebrates (491) and fish (478) of lowland and mountain streams in four ecoregions of France and Germany were related to catchment and riparian buffer land use using partial Redundancy Analysis and Boosted Regression Trees (BRTs). 3. Lotic fauna was better correlated (mean max., r = 0.450) than flora (r = 0.277) to both scales of land use: the strongest correlations were noted for mountain streams. BRTs revealed strong non‐linear relationships between mountain assemblage metrics and land use. Correlations increased with increasing buffer lengths, suggesting the importance of near‐stream land use on biotic assemblages. 4. Several metrics changed markedly between 10–20% (mountain ecoregions) and 40–45% (lowland) of arable land use, irrespective of the buffer size. At mountain sites with >10% catchment arable land use, metric values differed between sites with <30% and sites with >30% forest in the near‐stream riparian area. 5. These findings support the role of riparian land use in catchment management; however, differences between mountain and lowland ecoregions support the need for ecoregion‐specific management.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Structure-based protein design with deep learning

Since the first revelation of proteins functioning as macromolecular machines through their three dimensional structures, researchers have been intrigued by the marvelous ways the biochemical processes are carried out by proteins. The aspiration to understand protein structures has fueled extensive efforts across different scientific disciplines. In recent years, it has been demonstrated that proteins with new functionality or shapes can be designed via structure-based modeling methods, and the design strategies have combined all available information — but largely piece-by-piece — from sequence derived statistics to the detailed atomic-level modeling of chemical interactions. Despite the significant progress, incorporating data-derived approaches through the use of deep learning methods can be a game changer. In this review, we summarize current progress, compare the arc of developing the deep learning approaches with the conventional methods, and describe the motivation and concepts behind current strategies that may lead to potential future opportunities.     

Growth-induced mass flows in fungal networks

Cord-forming fungi form extensive networks that continuously adapt to maintain an efficient transport system. As osmotically driven water uptake is often distal from the tips, and aqueous fluids are incompressible, we propose that growth induces mass flows across the mycelium, whether or not there are intrahyphal concentration gradients. We imaged the temporal evolution of networks formed by Phanerochaete velutina, and at each stage calculated the unique set of currents that account for the observed changes in cord volume, while minimizing the work required to overcome viscous drag. Predicted speeds were in reasonable agreement with experimental data, and the pressure gradients needed to produce these flows are small. Furthermore, cords that were predicted to carry fast-moving or large currents were significantly more likely to increase in size than cords with slow-moving or small currents. The incompressibility of the fluids within fungi means there is a rapid global response to local fluid movements. Hence velocity of fluid flow is a local signal that conveys quasi-global information about the role of a cord within the mycelium. We suggest that fluid incompressibility and the coupling of growth and mass flow are critical physical features that enable the development of efficient, adaptive biological transport networks.     

The role of epiphytism in architecture and evolutionary constraint within mycorrhizal networks of tropical orchids

Characterizing the architecture of bipartite networks is increasingly used as a framework to study biotic interactions within their ecological context and to assess the extent to which evolutionary constraint shape them. Orchid mycorrhizal symbioses are particularly interesting as they are viewed as more beneficial for plants than for fungi, a situation expected to result in an asymmetry of biological constraint. This study addressed the architecture and phylogenetic constraint in these associations in tropical context. We identified a bipartite network including 73 orchid species and 95 taxonomic units of mycorrhizal fungi across the natural habitats of Reunion Island. Unlike some recent evidence for nestedness in mycorrhizal symbioses, we found a highly modular architecture that largely reflected an ecological barrier between epiphytic and terrestrial subnetworks. By testing for phylogenetic signal, the overall signal was stronger for both partners in the epiphytic subnetwork. Moreover, in the subnetwork of epiphytic angraecoid orchids, the signal in orchid phylogeny was stronger than the signal in fungal phylogeny. Epiphytic associations are therefore more conservative and may co‐evolve more than terrestrial ones. We suggest that such tighter phylogenetic specialization may have been driven by stressful life conditions in the epiphytic niches. In addition to paralleling recent insights into mycorrhizal networks, this study furthermore provides support for epiphytism as a major factor affecting ecological assemblage and evolutionary constraint in tropical mycorrhizal symbioses.     

Local grassland restoration affects insect communities

1. It is hypothesised that ecological restoration in grasslands can induce an alternative stable state shift in vegetation. The change in vegetation influences insect community assemblages and allows for greater functional redundancy in pollination and refuge for native insect species. 2. Insect community assemblages at eight coastal California grassland sites were evaluated. Half of these sites had undergone restoration through active revegetation of native grassland flora and half were non‐restored. Insects were collected from Lupinus bicolor (Fabaceae) within 2 × 2‐m² plots in spring 2017. Lupinus bicolor is a common native species that is used in California restoration projects, and home and state landscaping projects. 3. Ordination demonstrated that insect community assemblages were different between restored and non‐restored sites. These differences were seen in insect functional groups as well as taxa‐specific differences and were found to be driven by environmental characteristics such as non‐native forb cover. 4. Functional redundancy of herbivores decreased at restored sites, while pollinators became more redundant compared with non‐restored sites. The assemblages of the common species found at restoration sites contained more native insects than those found at non‐restored sites, including species such as Bombus vosnesenskii. 5. Local grassland restoration has the potential to induce an alternative stable state change and affect insect community assemblages. Additionally, it was found that grassland restoration can be a potential conservation tool to provide refugia for bumblebees (Bombus), but additional studies are required to fully understand its broader applicability.     

Distinguishing Drift and Selection Empirically: “The Great Snail Debate” of the 1950s

Biologists and philosophers have been extremely pessimistic about the possibility of demonstrating random drift in nature, particularly when it comes to distinguishing random drift from natural selection. However, examination of a historical case – Maxime Lamotte’s study of natural populations of the land snail, Cepaea nemoralis in the 1950s – shows that while some pessimism is warranted, it has been overstated. Indeed, by describing a unique signature for drift and showing that this signature obtained in the populations under study, Lamotte was able to make a good case for a significant role for␣drift. It may be difficult to disentangle the causes of drift and selection acting in a population, but it is not (always) impossible.