Sensitive Traits Research Articles

A Novel Image-Based Screening Method to Study Water-Deficit Response and Recovery of Barley Populations Using Canopy Dynamics Phenotyping and Simple Metabolite Profiling.

Plant phenotyping platforms offer automated, fast scoring of traits that simplify the selection of varieties that are more competitive under stress conditions. However, indoor phenotyping methods are frequently based on the analysis of plant growth in individual pots. We present a reproducible indoor phenotyping method for screening young barley populations under water stress conditions and after subsequent rewatering. The method is based on a simple read-out of data using RGB imaging, projected canopy height, as a useful feature for indirectly following the kinetics of growth and water loss in a population of barley. A total of 47 variables including 15 traits and 32 biochemical metabolites measured (morphometric parameters, chlorophyll fluorescence imaging, quantification of stress-related metabolites; amino acids and polyamines, and enzymatic activities) were used to validate the method. The study allowed the identification of metabolites related to water stress response and recovery. Specifically, we found that cadaverine (Cad), 1,3-aminopropane (DAP), tryptamine (Tryp), and tyramine (Tyra) were the major contributors to the water stress response, whereas Cad, DAP, and Tyra, but not Tryp, remained at higher levels in the stressed plants even after rewatering. In this work, we designed, optimized and validated a non-invasive image-based method for automated screening of potential water stress tolerance genotypes in barley populations. We demonstrated the applicability of the method using transgenic barley lines with different sensitivity to drought stress showing that combining canopy height and the metabolite profile we can discriminate tolerant from sensitive genotypes. We showed that the projected canopy height a sensitive trait that truly reflects other invasively studied morphological, physiological, and metabolic traits and that our presented methodological setup can be easily applicable for large-scale screenings in low-cost systems equipped with a simple RGB camera. We believe that our approach will contribute to accelerate the study and understanding of the plant water stress response and recovery capacity in crops, such as barley.

A binary unrelated-question RRT model accounting for untruthful responding

Estimating the prevalence of a sensitive trait in a population is not a simple task due to the general tendency among survey respondents to answer sensitive questions in a way that is socially desirable. Use of randomized response techniques (RRT) is one of several approaches for reducing the impact of this tendency. However, despite the additional privacy provided by RRT models, some respondents may still provide an untruthful response. We consider the impact of untruthful responding on binary unrelated-question RRT models and observe that even if only a small number of respondents lie, a significant bias may be introduced to the model. We propose a binary unrelated-question model that accounts for those respondents who may respond untruthfully. This adds an extra layer of precaution to the estimation of the sensitive trait and decreases the importance of presurvey respondent training. Our results are validated using a simulation study.

Searching for urban pollution signature and sensitive macroinvertebrate traits and ecological preferences in a river in the Eastern Cape of South Africa

Abstract Urbanisation of riverine landscapes is a major threat to river ecosystems because of the ecological consequences of the so called urban stream syndrome. Taxonomically, certain macroinvertebrate metrics such as the diversity of species of Ephemeroptera, Plecoptera and Trichoptera (EPT) are known to be sensitive to urban pollution, whereas chironomids and oligochaetes are relatively tolerant. Trait correlates of such taxonomic metrics are yet to be established even though traits are less constrained by geographical differences. Using the Swartkops as a case study of a river receiving urban pollution, the pattern of trait distribution in relation to a gradient of urban pollution was examined, and urban pollution signature and sensitive traits identified. Macroinvertebrates and physico-chemical analysis were undertaken over a period of three years between August 2009 and September 2012 at one control site and three impacted downstream sites. Seven traits resolved into 32 trait attributes including body size, respiration, body shape, mobility, biotope preference, preferred food, and feeding habits were fuzzy coded and analysed using RLQ and fourth-corner analyses. Of the 32 trait and ecological attributes, four, including large body size (>20 to 40 mm), animal materials as preferred food, predation and a preference for vegetation biotope, which were associated with the impacted sites, and were also significantly positively correlated with at least one physico-chemical indicator of increasing urban pollution were deemed signature traits. Three traits, swimming, fine particulate organic matter and grazing, associated with the control site, which showed significant negative correlations with at least one physico-chemical indicator of increasing urban pollution were identified as sensitive traits. The results indicate that urban pollution differentially influenced macroinvertebrate traits, with the identification of pollution signature and sensitive traits seen as an important step towards the development of trait-based indices for riverine monitoring of urban pollution effects.

Chlorophyll α Fluorescence Parameters as an Indicator to Identify Drought Susceptibility in Common Bush Bean

The common bean is susceptible to drought conditions and the evaluation of plant responses to low water availability can be difficult. The quantification of chlorophyll fluorescence as a sensitive trait to environmental stresses is an important alternative in the characterization of drought-susceptible genotypes. The objective of this study was to evaluate mainly the use of chlorophyll α fluorescence (maximum efficiency of PSII (Fv/Fm), photochemical quenching (qP), non-photochemical quenching (NPQ)) and rapid light-response curves (RLCs) (initial slope of the curve (α), minimum saturation irradiance (Ik) and maximum relative electron transport rate (ETRmax)) parameters as tools for the identification of susceptible or tolerant bush bean cultivars to water deficit stress conditions in two different phenological stages. Using a randomized block design in a factorial arrangement, five bush bean cultivars (Cerinza, Bachue, NUA35, Bacata and Bianca) were evaluated under water deficit conditions by the suspension of irrigation for 15 days from 40 to 55 Days after Emergence (DAE) (vegetative stage) or 50 to 65 DAE (reproductive stage). The results showed that Fv/Fm and NPQ recorded the highest variation due to water deficit conditions, especially in the vegetative stage. The greatest reductions in Fv/Fm (0.67) and NPQ (0.71) were evidenced in cultivar NUA35 compared to its control plants (0.78 and 1.07, respectively). The parameters obtained from RLCs showed that cultivar Bacata registered the lowest α (0.17) and Ik (838.19 μmol∙m−2∙s−1) values compared to its control plants (α 0.23; Ik 769.99 μmol∙m−2∙s−1). Differences were only obtained in ETRmax in the reproductive stage (50–65 DAE) in which cultivar NUA35 reached values of 158.5 in stressed plants compared to control plants (251.22). In conclusion, the parameters derived from RLCs such as α and Ik can be used as tools to identify drought susceptibility in the vegetative stage, whereas ETRmax can be used in the reproductive stage. In addition, PSII photochemistry (Fv/Fm and NPQ) can also help to understand the agronomic responses of common bush bean cultivars to drought conditions.

Habitat amount drives the functional diversity and nestedness of anuran communities in an Atlantic Forest fragmented landscape

AbstractNatural environments disturbed by human activities can suffer from species extinctions, but some can still harbor high taxonomic diversity. However, disturbances may have impacts beyond the species level, if the species lost represent unique functions in the ecosystem. In this study, we evaluated to what extent the amount of habitat can determine the functional diversity and nestedness of amphibian communities in an Atlantic Forest fragmented landscape in Brazil, and if there is a threshold of habitat amount beyond which there is severe loss of functional diversity. As species responses may depend on their habitat type, we performed the analyses for three different sets of species: all species, forest‐dependent species, and generalist species. We also evaluated the relative importance of turnover and nestedness components to total functional dissimilarity among sites. Habitat amount affected functional diversity of frogs, especially for forest‐dependent species where a linear reduction was detected. The functional dissimilarity among sites was mostly explained by the nestedness component. The reduction of functional diversity was mediated by an ordered loss of traits, leading to a functionally nested metacommunity. These sensitive traits were closely related to habits and reproductive modes that depend on rivers and streams. The maintenance of functional diversity of frogs in fragmented landscapes must rely on the conservation of both terrestrial and aquatic environments, as some species and their traits can disappear from remnants of native vegetation lacking some specific habitats (e.g. streams).Abstract in Portuguese is available with online material.

Contrasting responses of steppe Stipa ssp. to warming and precipitation variability.

Climate change, characterized by warming and precipitation variability, restricted the growth of plants in arid and semiarid areas, and various functional traits are impacted differently. Comparing responses of functional traits to warming and precipitation variability and determining critical water threshold of dominate steppe grasses from Inner Mongolia facilitates the identification and monitoring of water stress effects. A combination of warming (ambient temperature, +1.5°C and +2.0°C) and varying precipitation (−30%, −15%, ambient, +15%, and +30%) manipulation experiments were performed on four Stipa species (S. baicalensis, S. bungeana, S. grandis, and S. breviflora) from Inner Mongolia steppe. The results showed that the functional traits of the four grasses differed in their responses to precipitation, but they shared common sensitive traits (root/shoot ratio, R/S, and specific leaf area; SLA) under ambient temperature condition. Warming increased the response of the four grasses to changing precipitation, and these differences in functional traits resulted in changes to their total biomass, with leaf area, SLA, and R/S making the largest contributions. Critical water thresholds of the four grasses were identified, and warming led to their higher optimum precipitation requirements. The four steppe grasses were able to adapt better to mild drought (summer precipitation decreased by 12%–28%) when warming 1.5°C rather than 2.0°C. These results indicated that if the Paris Agreement to limit global warming to 1.5°C will be accomplished, this will increase the probability for sustained viability of the Stipa steppes in the next 50–100 years.

A Laterally Transferred Viral Gene Modifies Aphid Wing Plasticity

Organisms often respond to changing environments by altering development of particular traits. These plastic traits exhibit genetic variation; i.e., genotypes respond differently to the same environmental cues. Theoretical studies have demonstrated the importance of this variation, which is targeted by natural selection, in adapting plastic responses to maximize fitness [1, 2]. However, little is known about the underlying genetic mechanisms. We identify two laterally transferred genes that contribute to variation in a classic example of phenotypic plasticity: the peaaphid's ability to produce winged offspring in response to crowding. We discovered that aphid genotypes vary extensively for this trait and that aphid genes of viral origin are upregulated in response to crowding solely in highly inducible genotypes. We knocked down expression of these genes to demonstrate their functional role in wing plasticity. Through phylogenetic analysis, we found that these genes likely originated from a virus that infects rosy apple aphids and causes their hosts to produce winged offspring [3]. The function of these genes has therefore been retained following transfer to pea aphids. Our results uncover a novel role for co-opted viral genes, demonstrating that they are used to modulate ecologically relevant, plastic phenotypes. Our findings also address a critical question about the evolution of environmentally sensitive traits: whether the genes that control the expression of plastic traits also underlie variation in plasticity. The genes we identify originated from outside aphids themselves, and thus, our work shows that genes formerly unrelated to plasticity can fine-tune the strength of plastic responses to the environment.

List Experiments with Measurement Error

Measurement error threatens the validity of survey research, especially when studying sensitive questions. Although list experiments can help discourage deliberate misreporting, they may also suffer from nonstrategic measurement error due to flawed implementation and respondents’ inattention. Such error runs against the assumptions of the standard maximum likelihood regression (MLreg) estimator for list experiments and can result in misleading inferences, especially when the underlying sensitive trait is rare. We address this problem by providing new tools for diagnosing and mitigating measurement error in list experiments. First, we demonstrate that the nonlinear least squares regression (NLSreg) estimator proposed in Imai (2011) is robust to nonstrategic measurement error. Second, we offer a general model misspecification test to gauge the divergence of theMLregandNLSregestimates. Third, we show how to model measurement error directly, proposing new estimators that preserve the statistical efficiency ofMLregwhile improving robustness. Last, we revisit empirical studies shown to exhibit nonstrategic measurement error, and demonstrate that our tools readily diagnose and mitigate the bias. We conclude this article with a number of practical recommendations for applied researchers. The proposed methods are implemented through an open-source software package.

An Efficient Survey Technique for Estimating the Proportion and Sensitivity Attributes in a Dichotomous Finite Population

In this paper, a simple survey technique is applied to estimate the population proportion π of a sensitive trait, in addition to T, the probability that a respondent truthfully states that he or she bears a sensitive character when questioned directly and examined its properties. It has been found that the suggested model is efficient. Numerical illustrations are presented to support the theoretical results.

Maternal nesting behaviour in city dragons: a species with temperature-dependent sex determination

Abstract Urban environments present some of the greatest challenges to species survival. This is particularly true for species that exhibit thermally sensitive traits, such as temperature-dependent sex determination (TSD). This is because urban environments not only present species with entirely novel ecosystems, but species will also experience increased temperatures. These temperature increases may result not only in offspring mortality, but also skewed population sex ratios. To persist in cities, urban dwellers with TSD will therefore need to adjust the temperature of the nesting environment, either through phenotypic plasticity or rapid evolution through natural selection. Here, we investigate the nesting ecology of a long-lived, urban dwelling reptile, the eastern water dragon (Intellagama lesueurii), to understand how a TSD species may respond to urban environments. Based on data collected from 72 nests over 2 nesting seasons, we show that city dragons not only dug significantly deeper nests than previously observed across their natural riparian habitat, but also nested in novel substrates. Furthermore, we observed a behaviour not previously described in this species, where mothers travel outside of their core home range to nest. This excursion behaviour potentially represents a greater maternal investment and is linked to the selection of specific microhabitats.

Comparative physiological and leaf proteomic analyses revealed the tolerant and sensitive traits to drought stress in two wheat parental lines and their F6 progenies

Comparative physiological and proteomic analyses of two wheat cultivars Arg (resistant to drought), Arta (sensitive to drought) and four F6 lines (B1, B2, W1, W2) derived from their crossbreed lead us to discriminate the Arg, B1 and B2 lines to be resistant toward strong leaf water deficit. Proteins belonging to carbon metabolism, photosynthesis and detoxification/defense showed the major change. Tolerant Arg showed the accumulation of stress-responsive proteins under drought stress higher than in sensitive Arta. The high level of Cu/Zn superoxide dismutase, and two chloroplastic encoded enzymes indicate that their accumulation might improve stress resistance. Morphological and physiological traits of B1 and B2 confirmed that these lines are tolerant to drought stress. Proline and MDA contents are higher and lower, respectively, in these two lines than in other ones. This act synergistically with the modulation of primary metabolisms and protection against dehydration and oxidative damage resulting in the improvements of survival of the seedlings, greater vegetative vigor and productive capacity that also exceeds that of the tolerant Arg parental line. For all these evidences, the B1 and B2 progenies could be selected as the best lines in the future cultivation trials for wheat breeding under moderate and severe drought conditions.

Are Ponto-Caspian species able to cross salinity barriers? A case study of the gammarid Pontogammarus maeoticus.

Recently, Ponto‐Caspian species (i.e., area of Azov, Black, and Caspian Seas) have invaded brackish and freshwater habitats of the North and Baltic Seas and the Laurentian Great Lakes in much higher numbers than expected based on shipping frequency and environmental conditions among these regions. Therefore, it has been suggested that Ponto‐Caspian species may have inherent advantages over other species in colonizing new habitats, or that they are of freshwater origin. Artificial selection offers the possibility to investigate phenotypic plasticity, shifts in environmental tolerance, and heritability of environmentally sensitive traits; therefore, in this study, we conducted artificial selection experiments on Ponto‐Caspian amphipod Pontogammarus maeoticus collected from 10 PSU to evaluate adaptation capacity of this species to different salinities, and to shed additional light on a possible freshwater origin of Ponto‐Caspian invaders. Our results indicated that selection to lower salinity than that of the population's ambient salinity is possible within few generations due to a likely existence of standing polymorphic variation for selection to act on. In contrast, selection to higher salinity was unsuccessful because the phenotypic variation was mainly caused by environmental variance and therefore might depend on new mutations. Consequently, the results of our study suggest that the tested species might be of freshwater origin and lacks necessary genetic background for adaptation to fully marine conditions. Further selection studies using more species and populations, as well as molecular techniques, should be conducted to elucidate if other Ponto‐Caspian invaders are of freshwater origin as well.

New Stratified Bayesian Estimators Using Warner’s Randomized Response Technique Through Mixed Priors

In this paper, we propose new stratified Bayesian estimators of population proportion of a sensitive trait by adopting a mixture of alternative beta distributions as quantification of prior information in a stratified random sampling situation. Data were collected through Warner’s randomized response technique. To study the performance of the newly developed stratified estimators, mean squared error and absolute bias were used as performance criteria. The proposed estimators were compared with the existing one. We observed that the proposed estimators are more sensitive to responses than the existing one at various sample sizes respectively.

Germination Stage Water Scarcity in Bread and Einkorn Wheat

Germination (GR, %) and power (GP, %) rates, coleoptile (CL, cm), shoot lenght (SL, cm), and root (RL, cm) length, shoot/root length ratio (SRLR), root fresh weight (RFW, mg) and dry (RDW, mg) weight, and root fresh/dry root ratio (RFDWR) of 12 bread and 10 einkorn wheat genotypes were investigated under 7 drought stress levels. SL and SRLR in the study were the most sensitive traits and followed by CL and RL. The mean performance of all traits was worsened starting at various stress levels. The highest percent reduction was in SL (100.00%), SRLR (100.00%), and RL (99.07%), and the lowest one was in GP (55.9%). The common applied drought tolerance indices grouped the entries as tolerant, moderate, and susceptible. Einkorn populations from higher rainfall Blacksea region responded worse under drought stress than bread wheat cultivars, which were improved for drier or relatively drier Central Anatolia, Sub-Marmara, and Thrace regions.

Why the ‘Computer says no’: illustrating big data’s discrimination risk through complex systems science

The GDPR poses special requirements for the processing of sensitive data, but it is not clear whether these requirements are sufficient to prevent the risk associated with this processing because this risk is not clearly defined. Furthermore, the GDPR’s clauses on the processing of—and profiling based on—sensitive data do not sufficiently account for the fact that individual data subjects are parts of complex systems, whose emergent properties betray sensitive traits from non-sensitive data. The algorithms used to process big data are largely opaque to both controllers and data subjects: if the output of an algorithm has discriminatory effects coinciding with sensitive traits because the algorithm accidentally discerns an emergent property, this may remain unnoticed. At the moment, there are no remedies that can prevent the discovery of sensitive traits from non-sensitive data. Managing the risks resulting from processing data that can reveal sensitive traits requires a strategy combining precautionary measures, public discourse, and enforcement until the risks are more completely understood. Insights from complex systems science are likely to be useful in better understanding these risks.

A meta-analysis of birth-origin effects on reproduction in diverse captive environments

Successfully establishing captive breeding programs is a priority across diverse industries to address food security, demand for ethical laboratory research animals, and prevent extinction. Differences in reproductive success due to birth origin may threaten the long-term sustainability of captive breeding. Our meta-analysis examining 115 effect sizes from 44 species of invertebrates, fish, birds, and mammals shows that, overall, captive-born animals have a 42% decreased odds of reproductive success in captivity compared to their wild-born counterparts. The largest effects are seen in commercial aquaculture, relative to conservation or laboratory settings, and offspring survival and offspring quality were the most sensitive traits. Although a somewhat weaker trend, reproductive success in conservation and laboratory research breeding programs is also in a negative direction for captive-born animals. Our study provides the foundation for future investigation of non-genetic and genetic drivers of change in captivity, and reveals areas for the urgent improvement of captive breeding.

Sensitive Survey Questions with Auxiliary Information

Scholars increasingly rely on indirect questioning techniques to reduce social desirability bias and item nonresponse for sensitive survey questions. The major drawback of these approaches, however, is their inefficiency relative to direct questioning. We show how to improve the statistical analysis of the list experiment, randomized response technique, and endorsement experiment by exploiting auxiliary information on the sensitive trait. We apply the proposed methodology to survey experiments conducted among voters in a controversial antiabortion referendum held during the 2011 Mississippi General Election. By incorporating the official county-level election results, we obtain precinct- and individual-level estimates that are more accurate than standard indirect questioning estimates and occasionally even more efficient than direct questioning. Our simulation studies shed light on the conditions under which our approach can improve the efficiency and robustness of estimates based on indirect questioning techniques. Open-source software is available for implementing the proposed methodology.

What Drives Reticence? Reporting Bias from Monopolies and Distrustful Firm Managers

This article examines the determinants of underreporting (reticence) on randomized response questions. A simple model is created to describe the interview process and draw some conclusion as to why people might misreport their true status despite given the assurance of institutional and statistical confidentiality. By looking at the relationship between firm-specific reticence and other firm-specific and industry-location-specific variables, it is found that (mis)trust (proxied by the proportion of contracts arranged before delivery) is a significant predictor of reticence. Underreporting does not seem to be significantly related to a misunderstanding of the procedure, education, profit levels or guilt. This seems to suggest that firms which are more cautious in their business dealings are also more cautious with the randomized response (RR) technique. In such cases, weighted estimates of the prevalence of sensitive traits might be derived without the use of the RR technique but through the use of variables relating to the nature of firm-level contracts. Moreover, more accurate data on sensitive topics can be extracted from large homogeneous populations. JEL: C81, C83, D81

Field responses of potato to increased temperature during tuber bulking: Projection for climate change scenarios, at high-yield environments of Southern Chile

Potato is considered a key crop for food security, mainly in developing countries. Increased temperature in future climate scenarios could be a significant constraint for potato productivity in tropical regions, while favorable for temperate regions. Global warming in the range of moderately high temperatures (15–32°C) is projected for temperate areas of southern Chile, which is a high potential environment for potato. The present study assessed the impact of moderately high temperatures on yield and physiological traits, during tuber bulking (TB) of two native Chilean varieties and three commercial varieties. Experiments were carried out under field conditions during two growing seasons. Three thermal regimes were applied: (i) ambient temperature (T0), and increased temperature (2.3–5.3°C) for 20days (ii) from the beginning to middle of TB (T1) and (iii) from the middle of TB until the beginning of leaf yellowing (T2). Effect of temperature on yield and physiological performance of genotypes were dependent on the timing of heat treatments. T1 increased tuber yield by 11–59%, but T2 did not modify tuber yield. Yield sensitivity was highly dependent on genotype. Harvest index was the most sensitive trait to increase temperature at T1, decreasing in the range of temperatures evaluated without reduction for tuber yield. Increased tuber yield at T1 was associated with higher intercepted radiation between flowering and 50% of leaf brownship, explained in part by elongation of this period and stomatal conductance of leaves.

Uncovering a Blind Spot in Sensitive Question Research: False Positives Undermine the Crosswise-Model RRT

Validly measuring sensitive issues such as norm violations or stigmatizing traits through self-reports in surveys is often problematic. Special techniques for sensitive questions like the Randomized Response Technique (RRT) and, among its variants, the recent crosswise model should generate more honest answers by providing full response privacy. Different types of validation studies have examined whether these techniques actually improve data validity, with varying results. Yet, most of these studies did not consider the possibility of false positives, i.e., that respondents are misclassified as having a sensitive trait even though they actually do not. Assuming that respondents only falsely deny but never falsely admit possessing a sensitive trait, higher prevalence estimates have typically been interpreted as more valid estimates. If false positives occur, however, conclusions drawn under this assumption might be misleading. We present a comparative validation design that is able to detect false positives without the need for an individual-level validation criterion — which is often unavailable. Results show that the most widely used crosswise-model implementation produced false positives to a nonignorable extent. This defect was not revealed by several previous validation studies that did not consider false positives — apparently a blind spot in past sensitive question research.