Learning resilience: Household and institutional responses to multiple livelihood threats in the context of Hurricanes Iota and Eta in northern Nicaragua

Despite converging agendas identifying the importance of farm and livelihood diversification as a key strategy to help reduce disaster risk, conserve biodiversity, reduce climate emissions, improve food security, and build resilience in agriculture and food systems (Kremen and Merenlender 2018; Hufnagel et al., 2020), contentious debates continue about how to accelerate broader food system transformations, who should lead them, and where they are going (e.g., the 2021 UN Food Summit). The influential 2016 report of the International Panel of Experts on Sustainable Food Systems, which analyzed obstacles and opportunities for moving from either traditional subsistence agriculture or industrialized monoculture towards diversified agroecological farming (IPES-Food 2016), helped shift the policy agenda toward an alternative approach to food systems transformation (Gliessman & Ferguson, 2020). However, several assumptions about farmers’ initial starting conditions oversimplified how smallholder farmers begin potential transitions. In practice, many smallholders are neither purely subsistence producers nor entirely specialized commodity farmers; instead they combine subsistence and commercial agriculture to try to make a living, feed themselves, shape their cultures, and achieve their self-defined goals (Burnett & Murphy, 2014). Despite recent studies addressing several of these issues (Kerr et al., 2019), research gaps remain, including the absence of broad-based empirical evidence on which diversification strategies are most likely to contribute to farmers’ dietary diversity, food sovereignty, food security, women’s empowerment, and resilience, and under what circumstances; how smallholders learn about these practices and why they adopt or avoid them; and how cooperatives or other institutions promote (or may retard) them. We seek to fill these gaps using a mixed-methods, place-based study

Crystalline Silicate Emission in the Protostellar Binary Serpens--SVS20

We present spatially resolved mid-infrared spectroscopy of the class I/flat-spectrum protostellar binary system SVS20 in the Serpens cloud core. The spectra were obtained with the mid-infrared instrument T-ReCS on Gemini-South. SVS20-South, the more luminous of the two sources, exhibits a mid-infrared emission spectrum peaking near 11.3 \micron, while SVS20-North exhibits a shallow amorphous silicate absorption spectrum with a peak optical depth of $\tau \sim 0.3$. After removal of the the line-of-sight extinction by the molecular common envelope, the ``protostar-only'' spectra are found to be dominated by strong amorphous olivine emission peaking near 10 \micron. We also find evidence for emission from crystalline forsterite and enstatite associated with both SVS20-S and SVS20-N. The presence of crystalline silicate in such a young binary system indicates that the grain processing found in more evolved HAeBe and T Tauri pre-main sequence stars likely begins at a relatively young evolutionary stage, while mass accretion is still ongoing.Comment: Accepted for publication by The Astrophysical Journa

Using dust, gas and stellar mass selected samples to probe dust sources and sinks in low metallicity galaxies

We combine samples of nearby galaxies with Herschel photometry selected on their dust, metal, H I and stellar mass content, and compare these to chemical evolution models in order to discriminate between different dust sources. In a companion paper, we used an H I-selected sample of nearby galaxies to reveal a subsample of very gas-rich (gas fraction >80 per cent) sources with dust masses significantly below predictions from simple chemical evolution models, and well below Md/M* and Md/Mgas scaling relations seen in dust and stellar-selected samples of local galaxies. We use a chemical evolution model to explain these dust-poor, but gas-rich, sources as well as the observed star formation rates (SFRs) and dust-to-gas ratios. We find that (i) a delayed star formation history is required to model the observed SFRs; (ii) inflows and outflows are required to model the observed metallicities at low gas fractions; (iii) a reduced contribution of dust from supernovae (SNe) is needed to explain the dust-poor sources with high gas fractions. These dust-poor, low stellar mass galaxies require a typical core-collapse SN to produce 0.01-0.16 M⊙ of dust. To match the observed dust masses at lower gas fractions, significant grain growth is required to counteract the reduced contribution from dust in SNe and dust destruction from SN shocks. These findings are statistically robust, though due to intrinsic scatter it is not always possible to find one single model that successfully describes all the data. We also show that the dust-to-metal ratio decreases towards lower metallicity

Spatio-temporal expression patterns of Arabidopsis thaliana and Medicago truncatula defensin-like genes

Plant genomes contain several hundred defensin-like (DEFL) genes that encode short cysteine-rich proteins resembling defensins, which are well known antimicrobial polypeptides. Little is known about the expression patterns or functions of many DEFLs because most were discovered recently and hence are not well represented on standard microarrays. We designed a custom Affymetrix chip consisting of probe sets for 317 and 684 DEFLs from Arabidopsis thaliana and Medicago truncatula, respectively for cataloging DEFL expression in a variety of plant organs at different developmental stages and during symbiotic and pathogenic associations. The microarray analysis provided evidence for the transcription of 71% and 90% of the DEFLs identified in Arabidopsis and Medicago, respectively, including many of the recently annotated DEFL genes that previously lacked expression information. Both model plants contain a subset of DEFLs specifically expressed in seeds or fruits. A few DEFLs, including some plant defensins, were significantly up-regulated in Arabidopsis leaves inoculated with Alternaria brassicicola or Pseudomonas syringae pathogens. Among these, some were dependent on jasmonic acid signaling or were associated with specific types of immune responses. There were notable differences in DEFL gene expression patterns between Arabidopsis and Medicago, as the majority of Arabidopsis DEFLs were expressed in inflorescences, while only a few exhibited root-enhanced expression. By contrast, Medicago DEFLs were most prominently expressed in nitrogen-fixing root nodules. Thus, our data document salient differences in DEFL temporal and spatial expression between Arabidopsis and Medicago, suggesting distinct signaling routes and distinct roles for these proteins in the two plant species

Automated Device to Enable Passive Pronation and Supination Activities of the Hand for Experimental Testing with Cadaveric Specimens: A Collaboration Between The University of New Mexico and New Mexico Institute of Mining and Technology

In cadaveric research, reproducing physiological conditions under which the specimens would be loaded in vivo is essential to achieve clinical applicability. This is a collaborative study bringing together engineers from The University of New Mexico and New Mexico Institute of Mining and Technology. We describe development of an automated device to enable passive pronation and supination of the hand (rotation achieved through direct manipulation) for use in cadaveric experimental testing of the hand, wrist, forearm, or elbow. We present a brief motivation for development of this device, design details, an overview of one possible application, and ways to use this device for active pronation and supination activities (rotation achieved through tendon loading). We aim to provide the necessary information for reproduction of this device by other institutions for similar testing purposes

Advances in field-based high-throughput photosynthetic phenotyping

Gas exchange techniques revolutionized plant research and advanced understanding, including associated fluxes and efficiencies, of photosynthesis, photorespiration, and respiration of plants from cellular to ecosystem scales. These techniques remain the gold standard for inferring photosynthetic rates and underlying physiology/biochemistry, although their utility for high-throughput phenotyping (HTP) of photosynthesis is limited both by the number of gas exchange systems available and the number of personnel available to operate the equipment. Remote sensing techniques have long been used to assess ecosystem productivity at coarse spatial and temporal resolutions, and advances in sensor technology coupled with advanced statistical techniques are expanding remote sensing tools to finer spatial scales and increasing the number and complexity of phenotypes that can be extracted. In this review, we outline the photosynthetic phenotypes of interest to the plant science community and describe the advances in high-throughput techniques to characterize photosynthesis at spatial scales useful to infer treatment or genotypic variation in field-based experiments or breeding trials. We will accomplish this objective by presenting six lessons learned thus far through the development and application of proximal/remote sensing-based measurements and the accompanying statistical analyses. We will conclude by outlining what we perceive as the current limitations, bottlenecks, and opportunities facing HTP of photosynthesis