Biology subjects

Duran-Nebreda, S.

Publications and source records attributed to Duran-Nebreda, S..

4 recordsLinked to original sources

bioRxiv2022

Composition, structure and robustness of Lichen guilds

Symbiosis is a major engine of evolutionary innovation underlying the many extant complex organisms. Lichens are a paradigmatic example that offers a unique perspective on the role of symbiosis in ecological success and evolutionary diversification. Lichen studies have produced a wealth of information regarding the importance of symbiosis in many different species, but they frequently focus on a few species, limiting our understanding of large-scale phenomena such as guilds. Guilds are groupings of lichens that assist each others proliferation and are intimately linked by a shared set of photobionts, constituting an extensive network of relationships. To characterize the network of lichen symbionts, we used a large data set (n = 206 publications) of natural photobiont-mycobiont associations. The entire lichen network was found to be modular, but this organization does not replicate taxonomic information in the data set, prompting a reconsideration of lichen guild structure and composition. The characteristic scale of effective information reveals that the major lichen guilds are better represented as clusters with several substructures rather than as monolithic communities. Heterogeneous guild structure fosters robustness, with keystone species functioning as bridges between guilds and whose extinction would endanger global stability.

ecology↗

bioRxiv2020

Accurate And Versatile 3D Segmentation Of Plant Tissues At Cellular Resolution

Quantitative analysis of plant and animal morphogenesis requires accurate segmentation of individual cells in volumetric images of growing organs. In the last years, deep learning has provided robust automated algorithms that approach human performance, with applications to bio-image analysis now starting to emerge. Here, we present PlantSeg, a pipeline for volumetric segmentation of plant tissues into cells. PlantSeg employs a convolutional neural network to predict cell boundaries and graph partitioning to segment cells based on the neural network predictions. PlantSeg was trained on fixed and live plant organs imaged with confocal and light sheet microscopes. PlantSeg delivers accurate results and generalizes well across different tissues, scales, and acquisition settings. We present results of PlantSeg applications in diverse developmental contexts. PlantSeg is free and open-source, with both a command line and a user-friendly graphical interface.

plant biology↗

bioRxiv2017

The Paradox Of Constant Oceanic Plastic Debris: Evidence For Evolved Microbial Biodegradation?

Although the presence of vast amounts of plastic in the open ocean has generated great concern due to its potential ecological consequences, recent studies reveal that its measured abundance is much smaller than expected. Regional and global studies indicate that the difference between expected and actual estimates is enormous, suggesting that a large part of the plastic has been degraded by either physical and biotic processes. A paradoxical observation is the lack of a trend in plastic accumulation found in the North Atlantic Subtropical Gyre, despite the rapid increase in plastic production and disposal. In this paper we show, using mathematical and computer models, that this observation could be explained by the nonlinear coupling between plastic (as a resource) and an evolved set of organisms (the consumers) capable of degrading it. The result is derived using two different resource-consumer mathematical approaches as well as a spatially-dependent plastic-microbial model incorporating a minimal hydrodynamical coupling with a two-dimensional fluid. The potential consequences of the evolution of marine plastic garbage and its removal are outlined.

ecology↗

bioRxiv2016

Population dynamics of synthetic Terraformation motifs

Ecosystems are complex systems, currently experiencing several threats associated with global warming, intensive exploitation, and human-driven habitat degradation. Such threats are pushing ecosystems to the brink of collapse. Because of a general presence of multiple stable states, including states involving population extinction, and due to intrinsic nonlinearities associated with feedback loops, collapse can occur in a catastrophic manner. Such catastrophic shifts have been suggested to pervade many of the future transitions affecting ecosystems at many different scales. Many studies have tried to delineate potential warning signals predicting such ongoing shifts but little is known about how such transitions might be effectively prevented. It has been recently suggested that a potential path to prevent or modify the outcome of these transitions would involve designing synthetic organisms and synthetic ecological interactions that could push these endangered systems out of the critical boundaries. Four classes of such ecological engineering designs or Terraformation motifs have been defined in a qualitative way. Here we develop the simplest mathematical models associated with these motifs, defining the expected stability conditions and domains where the motifs shall properly work.

synthetic biology↗