A convergent spectroscopy-based approach for Vcmax across leaf age and growth environments.

Abstract OOS 2-2

Hydraulic architecture explains species moisture dependency but not mortality rates across a tropical rainfall gradient

Intensified droughts are affecting tropical forests across the globe. However, the underlying mechanisms of tree drought response and mortality are poorly understood. Hydraulic traits and especially hydraulic safety margins (HSMs), that is, the extent to which plants buffer themselves from thresholds of water stress, provide insights into species-specific drought vulnerability. We investigated hydraulic traits during an intense drought triggered by the 2015–2016 El Niño on 27 canopy tree species across three tropical forest sites with differing precipitation. We capitalized on the drought event as a time when plant water status might approach or exceed thresholds of water stress. We investigated the degree to which these traits varied across the rainfall gradient, as well as relationships among hydraulic traits and species-specific optimal moisture and mortality rates. There were no differences among sites for any measured trait. There was strong coordination among traits, with a network analysis revealing two major groups of coordinated traits. In one group, there were water potentials, turgor loss point, sapwood capacitance and density, HSMs, and mortality rate. In the second group, there was leaf mass per area, leaf dry matter content, hydraulic architecture (leaf area to sapwood area ratio), and species-specific optimal moisture. These results demonstrated that while species with greater safety from turgor loss had lower mortality rates, hydraulic architecture was the only trait that explained species’ moisture dependency. Species with a greater leaf area to sapwood area ratio were associated with drier sites and reduced their transpirational demand during the dry season via deciduousness

One Stomatal Model to Rule Them All?:Toward Improved Representation of Carbon and Water Exchange in Global Models

Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land-surface model (LSM) simulations during drought. However, systematic evaluations of both optimality-based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimization approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviors differ in response to abiotic changes. We also evaluate the models against leaf-level observations of gas-exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361–3,286 mm yr−1. We find that models differ in how easily parameterized they are, due to: (a) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (b) low influence parameters, (c) sensitivities to environmental drivers. In both the idealized experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapor pressure deficit. For example, stomatal closure rates at high vapor pressure deficit range between −45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf-gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses

A Pilot Study with a Novel Setup for Collaborative Play of the Humanoid Robot KASPAR with children with autism

This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.This article describes a pilot study in which a novel experimental setup, involving an autonomous humanoid robot, KASPAR, participating in a collaborative, dyadic video game, was implemented and tested with children with autism, all of whom had impairments in playing socially and communicating with others. The children alternated between playing the collaborative video game with a neurotypical adult and playing the same game with the humanoid robot, being exposed to each condition twice. The equipment and experimental setup were designed to observe whether the children would engage in more collaborative behaviours while playing the video game and interacting with the adult than performing the same activities with the humanoid robot. The article describes the development of the experimental setup and its first evaluation in a small-scale exploratory pilot study. The purpose of the study was to gain experience with the operational limits of the robot as well as the dyadic video game, to determine what changes should be made to the systems, and to gain experience with analyzing the data from this study in order to conduct a more extensive evaluation in the future. Based on our observations of the childrens’ experiences in playing the cooperative game, we determined that while the children enjoyed both playing the game and interacting with the robot, the game should be made simpler to play as well as more explicitly collaborative in its mechanics. Also, the robot should be more explicit in its speech as well as more structured in its interactions. Results show that the children found the activity to be more entertaining, appeared more engaged in playing, and displayed better collaborative behaviours with their partners (For the purposes of this article, ‘partner’ refers to the human/robotic agent which interacts with the children with autism. We are not using the term’s other meanings that refer to specific relationships or emotional involvement between two individuals.) in the second sessions of playing with human adults than during their first sessions. One way of explaining these findings is that the children’s intermediary play session with the humanoid robot impacted their subsequent play session with the human adult. However, another longer and more thorough study would have to be conducted in order to better re-interpret these findings. Furthermore, although the children with autism were more interested in and entertained by the robotic partner, the children showed more examples of collaborative play and cooperation while playing with the human adult.Peer reviewe

High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean (Glycine max) nested association mapping population

Photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500-2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R2 from 0.56 to 0.96 and root mean square error approximately \u3c10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis

Overlapping regional security institutions in South America: The case of OAS and UNASUR

The Union of South American Nations (UNASUR) has positioned itself as a regional security organization aimed at reducing the influence of the Organization of American States (OAS) in South America. At the same time, the OAS paradoxically serves as a model for UNASUR because of its operational capacity and its legitimacy as a regional organization. This article analyzes the seemingly contradictory tendencies of replication and dissociation that UNASUR exhibits towards the OAS in terms of security conceptions and practices. In the first part of the paper, we will draw on recent debates on international regime complexity to develop a framework to study institutional overlap. The second part analyzes to what extent and in which respects UNASUR, and particularly its Defense Council, overlaps with the OAS in terms of security conceptions and practices, while the third part examines the causes of the emergence of a “competitor” for the OAS in South America

Aboriginal Children and Their Caregivers Living with Low Income: Outcomes from a Two-Generation Preschool Program

The development of preschool children of Aboriginal heritage is jeopardized by the inter-generational transmission of risk that has created, and continues to create, social disadvantage. Early intervention programs are intended to mitigate the impact of social disadvantage. Yet, evidence of the effectiveness of these programs for children of Aboriginal heritage is limited. The purpose of this study was to examine the effects of a two-generation, multi-cultural preschool program on 45 children of Aboriginal heritage and their caregivers. We used a single-group, pretest (program intake)/posttest (program exit) design with follow-up when the children were 7 years old. We used an observational measure of child receptive language (Peabody Picture Vocabulary Test–III) and caregiver-reported measures of child development (Nipissing District Developmental Screen), risk for child maltreatment (Adult-Adolescent Parenting Inventory; AAPI), parenting stress (Parenting Stress Index; PSI), self-esteem (Rosenberg Self-Esteem scale; RSE), and life skills (Community Life Skills scale; CLS). Using paired t-tests we found statistically significant increases in child receptive language scores between intake and exit, and repeated-measures ANOVA showed that these improvements were maintained up to age 7 years. For caregivers, Pearson’s correlations demonstrated that risk for child maltreatment, parenting stress, self-esteem, and life skills were stable over time. Results of this study suggest that children of Aboriginal heritage can benefit from participation in a two-generation, multi-cultural preschool program. Their caregivers may have received greater benefit if issues of intergenerational transmission of the negative influences of residential schools were addressed as part of programming

Integrating plant physiology into simulation of fire behavior and effects

Wildfires are a global crisis, but current fire models fail to capture vegetation response to changing climate. With drought and elevated temperature increasing the importance of vegetation dynamics to fire behavior, and the advent of next generation models capable of capturing increasingly complex physical processes, we provide a renewed focus on representation of woody vegetation in fire models. Currently, the most advanced representations of fire behavior and biophysical fire effects are found in distinct classes of fine-scale models and do not capture variation in live fuel (i.e. living plant) properties. We demonstrate that plant water and carbon dynamics, which influence combustion and heat transfer into the plant and often dictate plant survival, provide the mechanistic linkage between fire behavior and effects. Our conceptual framework linking remotely sensed estimates of plant water and carbon to fine-scale models of fire behavior and effects could be a critical first step toward improving the fidelity of the coarse scale models that are now relied upon for global fire forecasting. This process-based approach will be essential to capturing the influence of physiological responses to drought and warming on live fuel conditions, strengthening the science needed to guide fire managers in an uncertain future