Ecosystem size and complexity are extrinsic drivers of food chain length in branching networks

Understanding the drivers of food chain length in natural communities has intrigued ecologists since the publication of ‘food cycles’ by Elton in the early 20th century. Proposed drivers of food chain length have included extrinsic controls such as productivity, disturbance regime, and ecosystem size, as well as intrinsic factors including food web motifs. However, current theories have largely assumed simple, two-dimensional habitat architectures, and may not be adequate to predict food chain length in ecosystems which have a complex, branching structure. Here, we develop a spatially explicit theoretical model which provides an integrated framework for predicting food chain length in branching networks. We show food chain length responds independently to both ecosystem size and complexity, and that these responses are contingent upon other extrinsic and intrinsic controls. Our results show that accounting for ecosystem complexity is an important driver of food chain length and may reconcile inconsistent results from empirical studies of food chain length in river ecosystems.

A Nature-inspired Hierarchical Branching Structure Pressure Sensor for Medical Wearables

Both ecosystems and biological systems in nature have evolved with unique hierarchical branching networks to maximize the efficiency and range of material transmission and adaptability to their external environment. Here we emulate this hierarchical branching (HB) network using a multilayer superposition approach and apply it in the design of flexible pressure sensors for medical wearables. Based on the HB structure, simulation results demonstrate that the deformation of microstructures is efficiently scheduled. Experiments show that the sensitivity of the HB sensor exhibits almost 34- and 55-fold improvements over the medium-pressure and high-pressure ranges, respectively, compared with that of a pressure sensor with a traditional monolayer structure. Successful monitoring of the diverse stimuli from humans demonstrates the considerable potential of the HB sensor in medical wearables. Additionally, the small and thin nature of the sensor enables it to quantify medical diagnostic processes, such as intelligent traditional Chinese medicine pulse diagnosis.

Design and Construction of Three-Dimensional Physiologically-Based Vascular Branching Networks for Respiratory Assist Devices

Microfluidic lab-on-a-chip devices are changing the way that in vitro diagnostics and drug development are conducted, based on the increased precision, miniaturization and efficiency of these systems relative to prior...

Branching principles of animal and plant networks identified by combining extensive data, machine learning and modelling

Branching in vascular networks and in overall organismic form is one of the most common and ancient features of multicellular plants, fungi and animals. By combining machine-learning techniques with new theory that relates vascular form to metabolic function, we enable novel classification of diverse branching networks—mouse lung, human head and torso, angiosperm and gymnosperm plants. We find that ratios of limb radii—which dictate essential biologic functions related to resource transport and supply—are best at distinguishing branching networks. We also show how variation in vascular and branching geometry persists despite observing a convergent relationship across organisms for how metabolic rate depends on body mass.