Methods for broad-scale plant phenology assessments using citizen scientists’ photographs

© 2020 Barve et al. Applications in Plant Sciences is published by Wiley Periodicals, Inc. on behalf of the Botanical Society of America Premise: Citizen science platforms for sharing photographed digital vouchers, such as iNaturalist, are a promising source of phenology data, but methods and best practices for use have not been developed. Here we introduce methods using Yucca flowering phenology as a case study, because drivers of Yucca phenology are not well understood despite the need to synchronize flowering with obligate pollinators. There is also evidence of recent anomalous winter flowering events, but with unknown spatiotemporal extents. Methods: We collaboratively developed a rigorous, consensus-based approach for annotating and sharing whole plant and flower presence data from iNaturalist and applied it to Yucca records. We compared spatiotemporal flowering coverage from our annotations with other broad-scale monitoring networks (e.g., the National Phenology Network) in order to determine the unique value of photograph-based citizen science resources. Results: Annotations from iNaturalist were uniquely able to delineate extents of unusual flowering events in Yucca. These events, which occurred in two different regions of the Desert Southwest, did not appear to disrupt the typical-period flowering. Discussion: Our work demonstrates that best practice approaches to scoring iNaturalist records provide fine-scale delimitation of phenological events. This approach can be applied to other plant groups to better understand how phenology responds to changing climate

Machine learning using digitized herbarium specimens to advance phenological research

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens—preserved plant material curated in natural history collections—but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth

A Hybrid Redox-Supercapacitor System with Anionic Catholyte and Cationic Anolyte

A significant challenge for energy storage technologies is to realize battery-level energy density and capacitor-level durability and power density in one device. By introducing an electrolyte composed of an anionic catholyte and a cationic anolyte into a symmetric carbon-based supercapacitor configuration, a hybrid electrochemical battery-supercapacitor system using soluble redox species delivers significantly improved energy density from 20 to 42 W•h/kg (based on the electrode mass) and stable capacities for > 10⁴ cycles. The ionic species formed in the electrolyte are studied by UV-Vis, Raman and mass spectroscopy to probe the energy storage mechanism. The strategy is general and may provide a route to critically-needed fast-charging devices with both high energy density and power.Keywords: Electrochemical capacitors, Energy storag

The role of GDNF family ligand signalling in the differentiation of sympathetic and dorsal root ganglion neurons

The diversity of neurons in sympathetic ganglia and dorsal root ganglia (DRG) provides intriguing systems for the analysis of neuronal differentiation. Cell surface receptors for the GDNF family ligands (GFLs) glial cell-line-derived neurotrophic factor (GDNF), neurturin and artemin, are expressed in subpopulations of these neurons prompting the question regarding their involvement in neuronal subtype specification. Mutational analysis in mice has demonstrated the requirement for GFL signalling during embryonic development of cholinergic sympathetic neurons as shown by the loss of expression from the cholinergic gene locus in ganglia from mice deficient for ret, the signal transducing subunit of the GFL receptor complex. Analysis in mutant animals and transgenic mice overexpressing GFLs demonstrates an effect on sensitivity to thermal and mechanical stimuli in DRG neurons correlating at least partially with the altered expression of transient receptor potential ion channels and acid-sensitive cation channels. Persistence of targeted cells in mutant ganglia suggests that the alterations are caused by differentiation effects and not by cell loss. Because of the massive effect of GFLs on neurite outgrowth, it remains to be determined whether GFL signalling acts directly on neuronal specification or indirectly via altered target innervation and access to other growth factors. The data show that GFL signalling is required for the specification of subpopulations of sensory and autonomic neurons. In order to comprehend this process fully, the role of individual GFLs, the transduction of the GFL signals, and the interplay of GFL signalling with other regulatory pathways need to be deciphered

Phenotypic Switching of Nonpeptidergic Cutaneous Sensory Neurons following Peripheral Nerve Injury

In adult mammals, the phenotype of half of all pain-sensing (nociceptive) sensory neurons is tonically modulated by growth factors in the glial cell line-derived neurotrophic factor (GDNF) family that includes GDNF, artemin (ARTN) and neurturin (NRTN). Each family member binds a distinct GFRα family co-receptor, such that GDNF, NRTN and ARTN bind GFRα1, -α2, and -α3, respectively. Previous studies revealed transcriptional regulation of all three receptors in following axotomy, possibly in response to changes in growth factor availability. Here, we examined changes in the expression of GFRα1-3 in response to injury in vivo and in vitro. We found that after dissociation of adult sensory ganglia, up to 27% of neurons die within 4 days (d) in culture and this can be prevented by nerve growth factor (NGF), GDNF and ARTN, but not NRTN. Moreover, up-regulation of ATF3 (a marker of neuronal injury) in vitro could be prevented by NGF and ARTN, but not by GDNF or NRTN. The lack of NRTN efficacy was correlated with rapid and near-complete loss of GFRα2 immunoreactivity. By retrogradely-labeling cutaneous afferents in vivo prior to nerve cut, we demonstrated that GFRα2-positive neurons switch phenotype following injury and begin to express GFRα3 as well as the capsaicin receptor, transient receptor potential vanilloid 1(TRPV1), an important transducer of noxious stimuli. This switch was correlated with down-regulation of Runt-related transcription factor 1 (Runx1), a transcription factor that controls expression of GFRα2 and TRPV1 during development. These studies show that NRTN-responsive neurons are unique with respect to their plasticity and response to injury, and suggest that Runx1 plays an ongoing modulatory role in the adult

Modeling and Analysis of the Molecular Basis of Pain in Sensory Neurons

Intracellular calcium dynamics are critical to cellular functions like pain transmission. Extracellular ATP plays an important role in modulating intracellular calcium levels by interacting with the P2 family of surface receptors. In this study, we developed a mechanistic mathematical model of ATP-induced P2 mediated calcium signaling in archetype sensory neurons. The model architecture, which described 90 species connected by 162 interactions, was formulated by aggregating disparate molecular modules from literature. Unlike previous models, only mass action kinetics were used to describe the rate of molecular interactions. Thus, the majority of the 252 unknown model parameters were either association, dissociation or catalytic rate constants. Model parameters were estimated from nine independent data sets taken from multiple laboratories. The training data consisted of both dynamic and steady-state measurements. However, because of the complexity of the calcium network, we were unable to estimate unique model parameters. Instead, we estimated a family or ensemble of probable parameter sets using a multi-objective thermal ensemble method. Each member of the ensemble met an error criterion and was located along or near the optimal trade-off surface between the individual training data sets. The model quantitatively reproduced experimental measurements from dorsal root ganglion neurons as a function of extracellular ATP forcing. Hypothesized architecture linking phosphoinositide regulation with P2X receptor activity explained the inhibition of P2X-mediated current flow by activated metabotropic P2Y receptors. Sensitivity analysis using individual and the whole system outputs suggested which molecular subsystems were most important following P2 activation. Taken together, modeling and analysis of ATP-induced P2 mediated calcium signaling generated qualitative insight into the critical interactions controlling ATP induced calcium dynamics. Understanding these critical interactions may prove useful for the design of the next generation of molecular pain management strategies