Growth-defense trade-offs shape population genetic composition in an iconic forest tree species.

All organisms experience fundamental conflicts between divergent metabolic processes. In plants, a pivotal conflict occurs between allocation to growth, which accelerates resource acquisition, and to defense, which protects existing tissue against herbivory. Trade-offs between growth and defense traits are not universally observed, and a central prediction of plant evolutionary ecology is that context-dependence of these trade-offs contributes to the maintenance of intraspecific variation in defense [Züst and Agrawal, Annu. Rev. Plant Biol., 68, 513-534 (2017)]. This prediction has rarely been tested, however, and the evolutionary consequences of growth-defense trade-offs in different environments are poorly understood, especially in long-lived species [Cipollini et al., Annual Plant Reviews (Wiley, 2014), pp. 263-307]. Here we show that intraspecific trait trade-offs, even when fixed across divergent environments, interact with competition to drive natural selection of tree genotypes corresponding to their growth-defense phenotypes. Our results show that a functional trait trade-off, when coupled with environmental variation, causes real-time divergence in the genetic architecture of tree populations in an experimental setting. Specifically, competitive selection for faster growth resulted in dominance by fast-growing tree genotypes that were poorly defended against natural enemies. This outcome is a signature example of eco-evolutionary dynamics: Competitive interactions affected microevolutionary trajectories on a timescale relevant to subsequent ecological interactions [Brunner et al., Funct. Ecol. 33, 7-12 (2019)]. Eco-evolutionary drivers of tree growth and defense are thus critical to stand-level trait variation, which structures communities and ecosystems over expansive spatiotemporal scales.

Predicting Kidney Transplant Evaluation Non-attendance.

Non-attendance to kidney transplant evaluation (KTE) appointments is a barrier to optimal care for those with kidney failure. We examined the medical and socio-cultural factors that predict KTE non-attendance to identify opportunities for integrated medical teams to intervene. Patients scheduled for KTE between May, 2015 and June, 2018 completed an interview before their initial KTE appointment. The interview assessed various social determinants of health, including demographic (e.g., income), medical (e.g. co-morbidities), transplant knowledge, cultural (e.g., medical mistrust), and psychosocial (e.g., social support) factors. We used multiple logistic regression analysis to determine the strongest predictor of KTE non-attendance. Our sample (N = 1119) was 37% female, 76% non-Hispanic White, median age 59.4 years (IQR 49.2-67.5). Of note, 142 (13%) never attended an initial KTE clinic appointment. Being on dialysis predicted higher odds of KTE non-attendance (OR 1.76; p = .02; 64% of KTE attendees on dialysis vs. 77% of non-attendees on dialysis). Transplant and nephrology teams should consider working collaboratively with dialysis units to better coordinate care, (e.g., resources to attend appointment or outreach to emphasize the importance of transplant) adjusting the KTE referral and evaluation process to address access issues (e.g., using tele-health) and encouraging partnership with clinical psychologists to promote quality of life for those on dialysis.

Genotypic variation rather than ploidy level determines functional trait expression in a foundation tree species in the presence and absence of environmental stress.

BACKGROUND AND AIMS: At the population level, genetic diversity is a key determinant of a tree species' capacity to cope with stress. However, little is known about the relative importance of the different components of genetic diversity for tree stress responses. We compared how two sources of genetic diversity, genotype and cytotype (i.e. differences in ploidy levels), influence growth, phytochemical and physiological traits of Populus tremuloides in the presence and absence of environmental stress. METHODS: In a series of field studies, we first assessed variation in traits across diploid and triploid aspen genotypes from Utah and Wisconsin under non-stressed conditions. In two follow-up experiments, we exposed diploid and triploid aspen genotypes from Wisconsin to individual and interactive drought stress and defoliation treatments and quantified trait variations under stress. KEY RESULTS: We found that (1) tree growth and associated traits did not differ significantly between ploidy levels under non-stressed conditions. Instead, variation in tree growth and most other traits was driven by genotypic and population differences. (2) Genotypic differences were critical for explaining variation of most functional traits and their responses to stress. (3) Ploidy level played a subtle role in shaping traits and trait stress responses, as its influence was typically obscured by genotypic differences. (4) As an exception to the third conclusion, we showed that triploid trees expressed 17 % higher foliar defence (tremulacin) levels, 11 % higher photosynthesis levels and 23 % higher rubisco activity under well-watered conditions. Moreover, triploid trees displayed greater drought resilience than diploids as they produced 35 % more new tissue than diploids when recovering from drought stress. CONCLUSION: Although ploidy level can strongly influence the ecology of tree species, those effects may be relatively small in contrast to the effects of genotypic variation in highly diverse species.

Leaf spectroscopy reveals divergent inter- and intra-species foliar trait covariation and trait-environment relationships across NEON domains.

Concurrent measurement of multiple foliar traits to assess the full range of trade-offs among and within taxa and across broad environmental gradients is limited. Leaf spectroscopy can quantify a wide range of foliar functional traits, enabling assessment of interrelationships among traits and with the environment. We analyzed leaf trait measurements from 32 sites along the wide eco-climatic gradient encompassed by the US National Ecological Observatory Network (NEON). We explored the relationships among 14 foliar traits of 1103 individuals across and within species, and with environmental factors. Across all species pooled, the relationships between leaf economic traits (leaf mass per area, nitrogen) and traits indicative of defense and stress tolerance (phenolics, nonstructural carbohydrates) were weak, but became strong within certain species. Elevation, mean annual temperature and precipitation weakly predicted trait variation across species, although some traits exhibited species-specific significant relationships with environmental factors. Foliar functional traits vary idiosyncratically and species express diverse combinations of leaf traits to achieve fitness. Leaf spectroscopy offers an effective approach to quantify intra-species trait variation and covariation, and potentially could be used to improve the characterization of vegetation in Earth system models.

Trait plasticity and trade-offs shape intra-specific variation in competitive response in a foundation tree species.

The ability to tolerate neighboring plants (i.e. degree of competitive response) is a key determinant of plant success in high-competition environments. Plant genotypes adjust their functional trait expression under high levels of competition, which may help explain intra-specific variation in competitive response. However, the relationships between traits and competitive response are not well understood, especially in trees. In this study, we investigated among-genotype associations between tree trait plasticity and competitive response. We manipulated competition intensity in experimental stands of trembling aspen (Populus tremuloides) to address the covariance between competition-induced changes in functional trait expression and aspects of competitive ability at the genotype level. Genotypic variation in the direction and magnitude of functional trait responses, especially those of crown foliar mass, phytochemistry, and leaf physiology, was associated with genotypic variation in competitive response. Traits exhibited distinct plastic responses to competition, with varying degrees of genotypic variation and covariance with other trait responses. The combination of genotypic diversity and covariance among functional traits led to tree responses to competition that were coordinated among traits yet variable among genotypes. Such relationships between tree traits and competitive success have the potential to shape stand-level trait distributions over space and time.

Integrative data analysis of self-efficacy in 4 clinical trials for alcohol use disorder.

BACKGROUND: Self-efficacy has been proposed as a key predictor of alcohol treatment outcomes and a potential mechanism of success in achieving abstinence or drinking reductions following alcohol treatment. Integrative data analysis, where data from multiple studies are combined for analyses, can be used to synthesize analyses across multiple alcohol treatment trials by creating a commensurate measure and controlling for differential item functioning (DIF) to determine whether alcohol treatments improve self-efficacy. METHOD: The current study used moderated nonlinear factor analysis (MNLFA) to examine the effect of treatment on self-efficacy across four different treatment studies (N = 3720; 72.5% male, 68.4% non-Hispanic white). Self-efficacy was measured using the Alcohol Abstinence Self-Efficacy Scale (AASE) in the COMBINE Study (n = 1383) and Project MATCH (n = 1726), and the Drug Taking Confidence Questionnaire (DTCQ) in two studies of Telephone Continuing Care (TEL Study 1: n = 303; TEL Study 2: n = 212). DIF was examined across time, study, treatment condition, marital status, age, and sex. RESULTS: We identified 12 items from the AASE and DTCQ to create a commensurate measure of self-efficacy using MNLFA. All active treatments, including cognitive-behavioral treatment, a combined behavioral intervention, medication management, motivation enhancement treatment, telephone continuing care, twelve-step facilitation, and relapse prevention, were associated with significant increases in self-efficacy from baseline to posttreatment that were maintained for up to a year. Importantly, treatment as usual in community settings, which consisted of weekly group therapy that included addiction counseling and twelve-step recovery support, was not associated with significant increases in self-efficacy. CONCLUSIONS: Alcohol self-efficacy increases following treatment and numerous evidence-based treatments are associated with significant increases in self-efficacy, which are maintained over time. Community treatment that focuses solely on addiction counseling and twelve-step support may not promote increases in self-efficacy.

Physical therapists should play a greater role in managing patients with opioid use and opioid misuse.

The U.S. opioid crisis necessitates that health care providers of all types work collaboratively to manage patients taking prescription opioid medications and manage those who may be misusing prescription opioids. Musculoskeletal conditions are the most common diagnoses associated with an opioid prescription. Physical therapists commonly manage patients with musculoskeletal conditions and chronic pain. Some patients who attend physical therapy for pain management take prescription opioid medications for pain and some of these patients may be misusing prescription opioids. Physical therapists who manage patients with musculoskeletal conditions are well-positioned to help address the opioid crisis. Historically, physical therapists have not been adequately engaged in efforts to manage persons with co-occurring musculoskeletal pain and opioid misuse or OUD. The American Physical Therapy Association (APTA) has emphasized physical therapy over the use of prescription opioids for the management of painful conditions. The APTA, however, does not highlight the important role that physical therapists could play in monitoring opioid use among patients receiving treatment for pain, nor the role that physical therapists should play in screening for opioid misuse. Such screening could facilitate referral of patients suspected misuse to an appropriate provider for formal assessment and treatment. This commentary presents simulated musculoskeletal patient presentations depicting 2 common opioid use states; chronic opioid use and opioid misuse. The cases highlight and interactions that physical therapists could have with these patients and actions that the physical therapist could take when working inter-disciplinarily. Recommendations are provided that aim to increase physical therapists' knowledge and skills related to managing patients taking prescription opioid medications for pain.

Latent Class Mediation: A Comparison of Six Approaches.

Latent class mediation modeling is designed to estimate the mediation effect when both the mediator and the outcome are latent class variables. We suggest using an adjusted one-step approach in which the latent class models for the mediator and the outcome are estimated first to decide on the number of classes, then the latent class models and the mediation model are jointly estimated. We present both an empirical demonstration and a simulation study to compare the performance of this one-step approach to a standard three-step approach with modal assignment (modal) and four different modern three-step approaches. Results from the study indicate that unadjusted modal, which ignores the classification errors of the latent class models, produced biased mediation effects. On the other hand, the adjusted one-step approach and the modern three-step approaches performed well with respect to bias for estimating mediation effects, regardless of measurement quality (i.e., model entropy) and latent class size. Among the three-step approaches we investigated, the maximum likelihood method with modal assignment and the BCH correction with robust standard error estimators are good alternatives to the adjusted one-step approach, given their unbiased standard error estimations.

Foliar functional traits from imaging spectroscopy across biomes in eastern North America.

Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. Model validation accuracy varied among traits (normalized root mean squared error, 9.1-19.4%; coefficient of determination, 0.28-0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28-81% provided high confidence for multiple traits concurrently. Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental-scale functional diversity.

To compete or defend: linking functional trait variation with life-history tradeoffs in a foundation tree species.

Although chemical deterrents to herbivory often exact costs in terms of plant growth, the manner in which those costs arise, and their physiological relationship to other functional traits, remain unclear. In the absence of appreciable herbivory, we examined interrelationships among chemical defense levels and other foliar functional traits (e.g., light-saturated photosynthesis, specific leaf area, nitrogen concentration) as co-determinants of tree growth and, by extension, competitive ability in high-density populations comprising 16 genotypes of Populus tremuloides. Across genotypes, concentrations of chemical defenses were not significantly related to other leaf functional traits, but levels of the salicinoid phenolic glycosides (SPGs) salicin, salicortin and tremulacin were each negatively correlated with relative mass growth (RMG) of aboveground woody tissue (P ≤ 0.001). RMG, in turn, underpinned 77% of the genotypic variation in relative height growth (our index of competitive ability). RMG was also positively related to light-saturated photosynthesis (P ≤ 0.001), which, together with the three SPGs, explained 86% of genotypic RMG variation (P ≤ 0.001). Moreover, results of a carbon balance simulation indicated that costs of resource allocation to SPGs, reaching nearly a third of annual crown photosynthesis, were likely mediated by substantial metabolic turnover, particularly for salicin. The lack of discernible links between foliar defense allocation and other (measured) functional traits, and the illustrated potential of metabolic turnover to reconcile influences of SPG allocation on RMG, shed additional light on fundamental physiological mechanisms underlying evolutionary tradeoffs between chemical defense investment and competitive ability in a foundation tree species.

Global photosynthetic capacity is optimized to the environment.

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (Vcmax ), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co-optimization of carboxylation and water costs for photosynthesis, suggests that optimal Vcmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field-measured Vcmax dataset for C3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first-order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.

From the Arctic to the tropics: multibiome prediction of leaf mass per area using leaf reflectance.

Leaf mass per area (LMA) is a key plant trait, reflecting tradeoffs between leaf photosynthetic function, longevity, and structural investment. Capturing spatial and temporal variability in LMA has been a long-standing goal of ecological research and is an essential component for advancing Earth system models. Despite the substantial variation in LMA within and across Earth's biomes, an efficient, globally generalizable approach to predict LMA is still lacking. We explored the capacity to predict LMA from leaf spectra across much of the global LMA trait space, with values ranging from 17 to 393 g m-2 . Our dataset contained leaves from a wide range of biomes from the high Arctic to the tropics, included broad- and needleleaf species, and upper- and lower-canopy (i.e. sun and shade) growth environments. Here we demonstrate the capacity to rapidly estimate LMA using only spectral measurements across a wide range of species, leaf age and canopy position from diverse biomes. Our model captures LMA variability with high accuracy and low error (R2  = 0.89; root mean square error (RMSE) = 15.45 g m-2 ). Our finding highlights the fact that the leaf economics spectrum is mirrored by the leaf optical spectrum, paving the way for this technology to predict the diversity of LMA in ecosystems across global biomes.

Acclimation and adaptation components of the temperature dependence of plant photosynthesis at the global scale.

The temperature response of photosynthesis is one of the key factors determining predicted responses to warming in global vegetation models (GVMs). The response may vary geographically, owing to genetic adaptation to climate, and temporally, as a result of acclimation to changes in ambient temperature. Our goal was to develop a robust quantitative global model representing acclimation and adaptation of photosynthetic temperature responses. We quantified and modelled key mechanisms responsible for photosynthetic temperature acclimation and adaptation using a global dataset of photosynthetic CO2 response curves, including data from 141 C3 species from tropical rainforest to Arctic tundra. We separated temperature acclimation and adaptation processes by considering seasonal and common-garden datasets, respectively. The observed global variation in the temperature optimum of photosynthesis was primarily explained by biochemical limitations to photosynthesis, rather than stomatal conductance or respiration. We found acclimation to growth temperature to be a stronger driver of this variation than adaptation to temperature at climate of origin. We developed a summary model to represent photosynthetic temperature responses and showed that it predicted the observed global variation in optimal temperatures with high accuracy. This novel algorithm should enable improved prediction of the function of global ecosystems in a warming climate.

Consumption outcomes in clinical trials of alcohol use disorder treatment: Consideration of standard drink misestimation.

Background. The Food and Drug Administration recently added a new clinical endpoint for evaluating the efficacy of alcohol use disorder (AUD) treatment that is more inclusive of treatment goals besides abstinence: no heavy drinking days (NHDD). However, numerous critiques have been noted for such binary models of treatment outcome. Further, there is mounting evidence that participants inaccurately estimate the quantities of alcohol they consume during drinking episodes (i.e., drink size misestimation), which may be particularly problematic when using a binary criterion (NHDD) compared to a similar, continuous alternative outcome variable: percent heavy drinking days (PHDD). Yet, the impact of drinking misestimation on binary (e.g., NHDD) versus continuous outcome variables (e.g., PHDD) has not been studied. Objectives. Using simulation methods, the present study examined the potential impact of drink size misestimation on NHDD and PHDD. Methods. Data simulations were based on previously published findings of the amount of error in how much alcohol is actually poured when estimating standard drinks. We started with self-reported daily drinking data from COMBINE study participants with complete data (N = 888; 68.1% male), then simulated inaccuracy in those estimations based on literature on standard drink size misestimation. Results. Clinical trial effect sizes were consistently lower for NHDD than for PHDD. Drink size misestimation further lowered effect sizes for NHDD and PHDD. Conclusions. Drink size misestimation may lead to inaccurate conclusions about drinking outcomes and the comparative effectiveness of AUD treatments, including inflated type-II error rates, particularly when treatment "success" is defined by binary outcomes such as NHDD.

Using imaging spectroscopy to detect variation in terrestrial ecosystem productivity across a water-stressed landscape.

A central challenge to understanding how climate anomalies, such as drought and heatwaves, impact the terrestrial carbon cycle, is quantification and scaling of spatial and temporal variation in ecosystem gross primary productivity (GPP). Existing empirical and model-based satellite broadband spectra-based products have been shown to miss critical variation in GPP. Here, we evaluate the potential of high spectral resolution (10 nm) shortwave (400-2,500 nm) imagery to better detect spatial and temporal variations in GPP across a range of ecosystems, including forests, grassland-savannas, wetlands, and shrublands in a water-stressed region. Estimates of GPP from eddy covariance observations were compared against airborne hyperspectral imagery, collected across California during the 2013-2014 HyspIRI airborne preparatory campaign. Observations from 19 flux towers across 23 flight campaigns (102 total image-flux tower pairs) showed GPP to be strongly correlated to a suite of spectral wavelengths and band ratios associated with foliar physiology and chemistry. A partial least squares regression (PLSR) modeling approach was then used to predict GPP with higher validation accuracy (adjusted R2  = 0.71) and low bias (0.04) compared to existing broadband approaches (e.g., adjusted R2  = 0.68 and bias = -5.71 with the Sims et al. model). Significant wavelengths contributing to the PLSR include those previously shown to coincide with Rubisco (wavelengths 1,680, 1,740, and 2,290 nm) and Vcmax (wavelengths 1,680, 1,722, 1,732, 1,760, and 2,300 nm). These results provide strong evidence that advances in satellite spectral resolution offer significant promise for improved satellite-based monitoring of GPP variability across a diverse range of terrestrial ecosystems.

Multi-level selection, social signaling, and the evolution of human suffering gestures: The example of pain behaviors.

Pain suffering has been naturally selected to be experienced and expressed within a wider social system. The communication of pain improves group coordination and decision-making about engaging in resource dependent and potentially risky endeavors. Recent findings warrant the development of a cohesive framework for understanding the reciprocal nature of pain expression and individual and group-level outcomes that can generate novel predictions on the heuristical expression of human suffering in naturalistic and clinical settings.

Task specificity and the impact on both the individual and group during the formation of groups.

We agree with aspects of Baumeister et al.'s view that shared identities are necessary during initial stages of group formation. In contrast to their analysis, however, we provide evidence that the value of self-differentiation depends more on the task itself than on the stage of group development and challenge the authors to focus on the functions of the group.

Trends in seedling growth and carbon-use efficiency vary among broadleaf tree species along a latitudinal transect in eastern North America.

Factors constraining the geographic ranges of broadleaf tree species in eastern North America were examined in common gardens along a ~1500 km latitudinal transect travers in grange boundaries of four target species: trembling aspen (Populus tremuloides) and paper birch (Betula papyrifera) to the north vs. eastern cottonwood (Populus deltoides) and sweet gum (Liquidambar styraciflua) to the south. In 2006 and 2007, carbon-use efficiency (CUE), the proportion of assimilated carbon retained in biomass, was estimated for seedlings of the four species as the quotient of relative growth rate (RGR) and photosynthesis per unit tree mass (Atree ). In aspen and birch, CUE and RGR declined significantly with increasing growth temperature, which spanned 9 °C across gardens and years. The 37% (relative) CUE decrease from coolest to warmest garden correlated with increases in leaf nighttime respiration (Rleaf ) and the ratio of Rleaf to leaf photosynthesis (R%A ). For cottonwood and sweet gum, however, similar increases in Rleaf and R%A accompanied modest CUE declines, implying that processes other than Rleaf were responsible for species differences in CUE's temperature response. Our findings illustrate marked taxonomic variation, at least among young trees, in the thermal sensitivity of CUE, and point to potentially negative consequences of climate warming for the carbon balance, competitive ability, and persistence of two foundation species in northern temperate and boreal forests.

Prenatal substance use and mental health comorbidities predict continued use.

OBJECTIVE: Prenatal substance use is common and can affect maternal and infant health. In addition, prenatal substance use is associated with mental health comorbidities (depression, anxiety, and posttraumatic stress disorder). Unremitting prenatal substance use disorders and mental health comorbidities are associated with poor health outcomes for mothers and exposed infants. The purpose of this study was to examine how any substance use, type of substance use (polysubstance use vs. single substance use), and combinations of mental health comorbidities predict continued use during pregnancy (i.e., use in the 30 days prior to delivery). METHOD: Health records of patients enrolled in a comprehensive prenatal program for women with substance use disorders were retrospectively analyzed (N = 281). Urine drug screen records were used to determine substance use, and diagnostic codes were used to identify mental health comorbidities. RESULTS: Thirty-seven percent of the sample (n = 105/281) tested positive for substances at admission and 42% (n = 119/281) demonstrated continued use. 30% of the sample (n = 85/281) had depression, anxiety, and posttraumatic stress disorder, 27% (n = 76/281) had two of the three mental health comorbidities, 26% (n = 73/281) had one of the three comorbidities, and 17% (n = 47/281) did not have a mental health comorbidity. Any substance use at admission or having all three mental health conditions were associated with continued use. CONCLUSIONS: Substance use at admission and number of mental health conditions were independent predictors of continued use, although substance use was the stronger predictor. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Challenges of perioperative pain control in opioid use disorder patients following intramedullary nail fixation.

BACKGROUND: Outcomes of patients with opioid use disorder undergoing elective procedures have been well studied, but research is lacking in the orthopaedic trauma population. AIM: The aim was to compare perioperative pain and morphine equivalents required by patients with versus without opioid use disorder following intramedullary nail fixation of femoral or tibial fractures. METHODS: We conducted a retrospective review of all patients with isolated femoral or tibial diaphyseal fractures treated with intramedullary nail fixation. Outcomes were compared between patients with diagnosed opioid use disorder and controls without, including daily morphine equivalents and patient-reported pain scores. RESULTS: Patients with opioid use disorder (n = 42) required greater morphine equivalents and reported higher pain than controls (n = 42) at all time points but did not differ in change of morphine equivalents over the perioperative period. CONCLUSION: This highlights the challenge of perioperative pain control in this population and need for improved specific pain management protocols.