Subsequent Time Periods Research Articles

Lion-tailed macaques show a stable direction and reinforcement of hand preference in simple reaching tasks over several years

Research on hand preference in non-human primates provides information about the evolutionary origin of population-level bias of human handedness. Human hand preference has been shown to remain stable throughout an individual's lifespan. However, the stability of hand preference and its change with age in non-human primates remains questionable. We recorded hand use in lion-tailed macaques (Macaca silenus) during simple reaching tasks in three time periods over six years. We tested the effect of age and body posture on the direction and strength of hand preference in 23 observed individuals. In a subsample of 13 individuals followed for two or three subsequent time periods, we assessed the stability of hand preference across study periods. The direction of hand preference was highly stable; we detected no individuals changing from a left- to right-, or right- to left- preference and repeated quantitative measures of hand preference were correlated among subsequent study periods. Hand preference was, however, reinforced in older individuals and an individual's hand preference was stronger in postures with both hands free for foraging. Stable hand preference at an individual level, and its reinforcement over an individual's lifetime, is emerging as a robust finding across the primate order.

Factor-augmented Bayesian treatment effects models for panel outcomes

A new, flexible model for inference of the effect of a binary treatment on a continuous outcome observed over subsequent time periods is proposed. The model allows to separate the associations due to endogeneity under treatment selection and additional longitudinal association of the outcomes, thus yielding unbiased estimates of dynamic treatment effects if both sources of association are present. The performance of the proposed method is investigated on simulated data and employed to re-analyze data on the longitudinal effects of a long maternity leave on mothers’ earnings after their return to the labour market.

Illegal Drug Use, Depressive Symptoms, and General Health: Exploring Co-occurrence across 11 Years in a National Sample

ABSTRACT The co-occurrence of illegal drug use, symptoms of depression, and a lower perception of general health among adolescents continues to be of substantive interest for researchers and the general public alike. Research on this topic, however, remains relatively stagnant, focusing on narrow developmental periods and each association independently, with limited consideration for the existence of a nexus between the three constructs as individuals age. Considering these limitations, the current study examines the longitudinal progression, from adolescence to early adulthood, of illegal drug use, symptoms of depression, and a lower perception of general health. The National Longitudinal Survey of Youth 1997 (NLSY97; N = 8,984), measures over an eleven-year data collection period, and between-and within-individual analytical strategies were used to evaluate the nexus between the constructs. The findings suggested that illegal drug use, depressive symptoms, and general health at previous time periods directly and indirectly predicted illegal drug use, depressive symptoms, and general health at subsequent time periods. Moreover, the within-individual change in illegal drug use was associated with the change in depressive symptoms, and the change in depressive symptoms was associated with the change in general health. Practitioners should consider this co-occurrence when treating symptoms related to illegal drug use, symptoms of depression, and physical health.

Nephropathogenic Infectious Bronchitis Virus Mediates Kidney Injury in Chickens via the TLR7/NF-κB Signaling Axis.

Nephropathogenic infectious bronchitis virus (NIBV) is one of the most important viral pathogens in the world poultry industry. Here, we used RT–qPCR, WB and immunofluorescence to explore the interaction between NIBV and the host innate immune system of the kidney. Multiple virions were found in the kidney tissues of the disease group under electron microscopy, and pathological changes such as structural damage of renal tubules and bleeding were observed by HE staining. In addition, we found that the mRNA levels of TLR7, TRAF6, and IKKβ were upregulated after NIBV infection. IRF7 mRNA levels decreased significantly at 5 dpi and increased significantly at 11 to 18 dpi. The NF-κB P65 mRNA level increased significantly at 5 to 18 dpi and decreased at 28 dpi. However, NIBV infection-induced NF-κB P65 protein levels were downregulated at multiple time points. Moreover, we demonstrated that the cytokine (IFN-γ, IL-8, and IL-6) mRNA and protein expression levels were increased significantly at multiple time points after NIBV infection. Furthermore, immunofluorescence analysis showed that NF-κB P65 and IFN-γ were mainly located in the nuclear or perinuclear region. The positive signal intensity of NF-κB P65 was significantly lower than that of the normal group at 1 to 5 dpi, and there was no significant change in the subsequent time period. The positive signal intensity of IFN-γ decreased significantly at 5 dpi, and increased significantly at 11 to 28 dpi. In conclusion, we found that NIBV promoted cytokine release through the TLR7/NF-κB signaling axis, thus causing kidney injury.

Learning in Sequential Bilevel Linear Programming

We consider a framework for sequential bilevel linear programming in which a leader and a follower interact over multiple time periods. In each period, the follower observes the actions taken by the leader and reacts optimally, according to the follower’s own objective function, which is initially unknown to the leader. By observing various forms of information feedback from the follower’s actions, the leader is able to refine the leader’s knowledge about the follower’s objective function and, hence, adjust the leader’s actions at subsequent time periods, which ought to help in maximizing the leader’s cumulative benefit. We show that greedy and robust policies adapted from previous work in the max-min (symmetric) setting might fail to recover the optimal full-information solution to the problem (i.e., a solution implemented by an oracle with complete prior knowledge of the follower’s objective function) in the asymmetric case. In contrast, we present a family of greedy and best-case policies that are able to recover the full-information optimal solution and also provide real-time certificates of optimality. In addition, we show that the proposed policies can be computed by solving a series of linear mixed-integer programs. We test policy performance through exhaustive numerical experiments in the context of asymmetric shortest path interdiction, considering various forms of feedback and several benchmark policies.

Technique for optimizing the adaptive control of the output of an enterprise based on a dynamical economic and mathematical model

The article is devoted to the application of dynamic economic and mathematical models for managing the production of an enterprise based on the use of the feedback principle. Formation of a discrete controllable dynamical system is given, which describes the process of production output by a manufacturing enterprise in the presence of a predictable demand function for products. The phase vector of a dynamical system describes the main parameters of production, and the control action vector (control vector) describes the intensity of the use of technological methods of production that are available to the subject of control. It is assumed that in each period of time the subject of control knows the vector function that describes the volume of demand for the company's products in subsequent periods of time, and the given geometric restrictions on the implementation of the phase vector, control vector and demand vector are also known. As the target function of the problem, the value of the discrepancy between the volumes of output by the enterprise relative to the given predicted value of the demand function in the subsequent control period is considered. Using the generated dynamical system, the paper proposes an economic-mathematical model of the studied problem of optimizing the adaptive control of the enterprise's output, which includes a class of admissible strategies for adaptive control and the formulation of the problem. The paper proposes a method for solving the formulated problem of optimizing the adaptive control of the output of an enterprise, which is implemented as a finite sequence of one-step algebraic operations on vectors of a finite-dimensional vector space, a finite set of solutions to problems of linear and convex mathematical programming. The results obtained can be used in the development of intelligent decision support systems for the actual tasks of managing the production of products at industrial enterprises.

Impact of COVID-19 type events on the economy and climate under the stochastic DICE model

The classical DICE model is a widely accepted integrated assessment model for the joint modeling of economic and climate systems, where all model state variables evolve over time deterministically. We reformulate and solve the DICE model as an optimal control dynamic programming problem with six state variables (related to the carbon concentration, temperature, and economic capital) evolving over time deterministically and affected by two controls (carbon emission mitigation rate and consumption). We then extend the model by adding a discrete stochastic shock variable to model the economy in the stressed and normal regimes as a jump process caused by events, such as the COVID-19 pandemic. These shocks reduce the world gross output leading to a reduction in both the world net output and carbon emission. The extended model is solved under several scenarios as an optimal stochastic control problem, assuming that the shock events occur randomly on average once every 100 years and last for 5 years. The results show that, if the world gross output recovers in full after each event, the impact of the COVID-19 events on the temperature and carbon concentration will be immaterial even in the case of a conservative 10% drop in the annual gross output over a 5-year period. The impact becomes noticeable, although still extremely small (long-term temperature drops by 0.1^circ mathrm {C}), in a presence of persistent shocks of a 5% output drop propagating to the subsequent time periods through the recursively reduced productivity. If the deterministic DICE model policy is applied in a presence of stochastic shocks (i.e., when this policy is suboptimal), then the drop in temperature is larger (approximately 0.25^circ mathrm {C}), that is, the lower economic activities owing to shocks imply that more ambitious mitigation targets are now feasible at lower costs.

Associations between author-level metrics in subsequent time periods

Understanding the dynamics of authors is relevant to predict and quantify performance in science. While the relationship between recent and future citation counts is well-known, many relationships between scholarly metrics at the author-level remain unknown. In this context, we performed an analysis of author-level metrics extracted from subsequent periods, focusing on visibility, productivity and interdisciplinarity. First, we investigated how metrics controlled by the authors (such as references diversity and productivity) affect their visibility and citation diversity. We also explore the relation between authors' interdisciplinarity and citation counts. The analysis in a subset of Physics papers revealed that there is no strong correlation between authors' productivity and future visibility for most of the authors. A higher fraction of strong positive correlations though was found for those with a lower number of publications. We also found that reference diversity computed at the author-level may impact positively authors' future visibility. The analysis of metrics impacting future interdisciplinarity suggests that productivity may play a role only for low productivity authors. We also found a surprisingly strong positive correlation between references diversity and interdisciplinarity, suggesting that an increase in diverse citing behavior may be related to a future increase in authors interdisciplinarity. Finally, interdisciplinarity and visibility were found to be moderated positively associated: significant positive correlations were observed for 30% of authors with lower productivity.

Analyzing disparities in COVID-19 testing trends according to risk for COVID-19 severity across New York City

BackgroundGiven the interplay between race and comorbidities on COVID-19 morbidity and mortality, it is vital that testing be performed in areas of greatest need, where more severe cases are expected. The goal of this analysis is to evaluate COVID-19 testing data in NYC relative to risk factors for COVID-19 disease severity and demographic characteristics of NYC neighborhoods.MethodsCOVID-19 testing and the racial/ethnic composition of NYC Zip Code Tabulation Areas (ZCTA) were obtained from the NYC Coronavirus data repository and the American Community Survey, respectively. The prevalence of neighborhood-level risk factors for COVID-19 severity according to the Centers for Disease Control and Prevention criteria for risk of severe illness and complications from COVID-19 were used to create a ZCTA-level risk index. Poisson regressions were performed to study the ratio of total tests relative to the total ZCTA population and the proportion of positive tests relative to the total tests performed over time.ResultsFrom March 2nd-April 6th, the total tests/population (%) was positively associated with the proportion of white residents (IRRadj: 1.0003, 95% CI: 1.0003–1.0004) and the COVID risk index (IRRadj: 1.038, 95% CI: 1.029–1.046). The risk index (IRRadj: 1.017, 95% CI: 0.939–1.101) was not associated with total tests performed from April 6th-May 12th, and inversely associated from May 12th-July 6th (IRRadj: 0.862, 95% CI: 0.814–0.913). From March 2nd-April 6th the COVID risk index was not statistically associated (IRRadj: 1.010, 95% CI: 0.987–1.034) with positive tests/total tests. From April 6th-May 12th, the COVID risk index was positively associated (IRRadj: 1.031, 95% CI: 1.002–1.060), while from May 12th-July 6th, the risk index was inversely associated (IRRadj: 1.135, 95% CI: 1.042–1.237) with positivity.ConclusionsTesting in NYC has suffered from the lack of availability in high-risk populations, and was initially limited as a diagnostic tool for those with severe symptoms, which were mostly concentrated in areas where vulnerable residents live. Subsequent time periods of testing were not targeted in areas according to COVID-19 disease risk, as these areas still experience more positive tests.

Do Firms Learn from Pre‐announcement Experience? Evidence from Optimistic Pre‐announcements and Market Responses

In this study, we examine whether firms learn from pre‐announcement experience by focusing on optimistic pre‐announcements and market responses. Optimistic pre‐announcements are pre‐announced Earnings Per Share (EPS) higher than or equal to actual EPS. Based on organizational learning theory, we hypothesize that firms experiencing negative market responses to positive pre‐announcements (pre‐announced EPS higher than or equal to analysts' consensus) are less likely to make another pre‐announcement during subsequent time periods. Our findings support this hypothesis. For firms making another pre‐announcement, we find that the experience of a negative market response to a positive pre‐announcement is negatively related to making an optimistic pre‐announcement. Taken together, our findings suggest that firms learn from the previous experience of pre‐announcements and the corresponding market responses.

Optimization of the Electrical Demand of an Existing Building with Storage Management through Machine Learning Techniques

Accurate prediction from electricity demand models is helpful in controlling and optimizing building energy performance. The application of machine learning techniques to adjust the electrical consumption of buildings has been a growing trend in recent years. Battery management systems through the machine learning models allow a control of the supply, adapting the building demand to the possible changes that take place during the day, increasing the users’ comfort, and ensuring greenhouse gas emission reduction and an economic benefit. Thus, an intelligent system that defines whether the storage system should be charged according to the electrical needs of that moment and the prediction of the subsequent periods of time is defined. Favoring consumption in the building in periods when energy prices are cheaper or the renewable origin is preferable. The aim of this study was to obtain a building electrical energy demand model in order to be combined with storage devices with the purpose of reducing electricity expenses. Specifically, multilayer perceptron neural network models were applied, and the battery usage optimization is obtained through mathematical modelling. This approach was applied to a public office building located in Bangkok, Thailand.

Long-Term Natural Gas Consumption Forecasting Based on Analog Method and Fuzzy Decision Tree

Classic forecasting methods of natural gas consumption extrapolate trends from the past to subsequent periods of time. The paper presents a different approach that uses analogues to create long-term forecasts of the annual natural gas consumption. The energy intensity (energy consumption per dollar of Gross Domestic Product—GDP) and gas share in energy mix in some countries, usually more developed, are the starting point for forecasts of other countries in the later period. The novelty of the approach arises in the use of cluster analysis to create similar groups of countries and periods based on two indicators: energy intensity of GDP and share of natural gas consumption in the energy mix, and then the use of fuzzy decision trees for classifying countries in different years into clusters based on several other economic indicators. The final long-term forecasts are obtained with the use of fuzzy decision trees by combining the forecasts for different fuzzy sets made by the method of relative chain increments. The forecast accuracy of our method is higher than that of other benchmark methods. The proposed method may be an excellent tool for forecasting long-term territorial natural gas consumption for any administrative unit.

Do factors affecting time from symptom onset to diagnosis or treatment of ovarian cancer also affect survival?

<h3>Objectives:</h3> Little is known about whether factors affecting time from symptom onset to diagnosis or treatment of ovarian cancer also affect overall survival (OS) or cancer-specific survival (CSS). In this study, we aim to identify variables associated with improved time to diagnosis, treatment, and survival of ovarian cancer. <h3>Methods:</h3> A population-based study of the Surveillance, Epidemiology, and End Results (SEER)-Medicare database was conducted on patients ≥66 years old from 1992-2015 with a diagnosis of stage II-IV primary epithelial ovarian cancer. Regression models evaluated time from first coded symptom in a claim to diagnosis and treatment, OS, and CSS by age, race, comorbidity score, marital status, region, poverty level, year of diagnosis, urban/rural location, number of physician visit types in the 30 days prior to diagnosis, and emergency room presentation. <h3>Results:</h3> We identified 18693 women for analysis. Faster time to diagnosis was associated with BlackBlack race (p=.001) and both faster time to diagnosis and treatment were associated with unmarried status (diagnosis p<.001, treatment p<.001) and mostly rural (p=.011, p=.003) or all rural (p<.001, p=.003) location. Conversely, both slower time to diagnosis and treatment were associated with older age (p<.001, p<.001), higher comorbidity score (p<.001, p<.001), non-Northeast region (p<.001, p=.001), >4 physician visit types (p<.001, p<.001), emergency department presentation (p<.001, p<.001), and diagnosis after 1992-1999 (p<.001, p<.001). Five-year OS and CSS were 22.4% and 39.5%, respectively. Despite being associated with faster time to diagnosis and/or treatment, there were lower 5-year OS and CSS associated with unmarried status (OS p<.001, CSS p<.001), all rural location (p<.001, p<.001), and BlackBlack race (p<.001, p=.025). Lower 5-year OS and CSS were also associated with older age (p<.001, p<.001), higher comorbidity score (p<.001, p<.001), emergency presentation (p<.001, p<.001), and higher poverty level (p=.018, p=.048). Despite being associated with slower time to diagnosis and treatment, higher 5-year CSS was associated with >4 physician visit types (p=.002) and both higher 5-year OS and CSS were associated with diagnosis after 1992-1999 (p<.001, p<.001). Compared to 1992-1999, the hazard ratios of 5-year cancer-specific death after 5 years decreased for each subsequent time period (2000-2005 HR=.90; 2006-2010 HR=.82; 2011-2015 HR=.72). <h3>Conclusions:</h3> In our SEER-based database study, variables associated with faster time to diagnosis and treatment of ovarian cancer often correlated with worse OS and CSS. We hypothesize that the discordance between time from diagnosis to treatment and survival seen based on clinical and demographic variables may be due to unmeasured social determinants of health or deviations from guideline-concordant care. Future research to understand this discordance is warranted.

Early Inflammatory Cytokine Expression in Cerebrospinal Fluid of Patients with Spontaneous Intraventricular Hemorrhage.

We investigated cerebrospinal fluid (CSF) expression of inflammatory cytokines and their relationship with spontaneous intracerebral and intraventricular hemorrhage (ICH, IVH) and perihematomal edema (PHE) volumes in patients with acute IVH. Twenty-eight adults with IVH requiring external ventricular drainage for obstructive hydrocephalus had cerebrospinal fluid (CSF) collected for up to 10 days and had levels of interleukin-1α (IL-1α), IL-1β, IL-6, IL-8, IL-10, tumor necrosis factor-α (TNFα), and C-C motif chemokine ligand CCL2 measured using enzyme-linked immunosorbent assay. Median [IQR] ICH and IVH volumes at baseline (T0) were 19.8 [5.8–48.8] and 14.3 [5.3–38] mL respectively. Mean levels of IL-1β, IL-6, IL-10, TNF-α, and CCL2 peaked early compared to day 9–10 (p < 0.05) and decreased across subsequent time periods. Levels of IL-1β, IL-6, IL-8, IL-10, and CCL2 had positive correlations with IVH volume at days 3–8 whereas positive correlations with ICH volume occurred earlier at day 1–2. Significant correlations were found with PHE volume for IL-6, IL-10 and CCL2 at day 1–2 and with relative PHE at days 7–8 or 9–10 for IL-1β, IL-6, IL-8, and IL-10. Time trends of CSF cytokines support experimental data suggesting association of cerebral inflammatory responses with ICH/IVH severity. Pro-inflammatory markers are potential targets for injury reduction.

Variations by race/ethnicity and time in Covid-19 testing among Veterans Health Administration users with COVID-19 symptoms or exposure

Racial/ethnic disparities in coronavirus disease 2019 (COVID-19) hospitalization and mortality have emerged in the United States, but less is known about whether similar differences exist in testing, and how this changed as COVID-19 knowledge and policies evolved. We examined racial/ethnic variations in COVID-19 testing over time among veterans who sought care for COVID-19 symptoms or exposure. In the national population of all Veterans who sought Veterans Health Administration (VHA) care for COVID-19 symptoms or exposure (n = 913,806), we conducted multivariate logistic regressions to explore race/ethnicity-by-time period differences in testing from 3/1/2020–11/25/2020, and calculated predicted probabilities by race/ethnicity and time period.Early in the pandemic (3/1/2020–4/6/2020) when testing was limited and there was less awareness of racial/ethnic disparities, non-Hispanic Black, Hispanic, and other non-White racial/ethnic minority Veterans who sought care from VHA for COVID-19 symptoms or exposure were more likely than non-Hispanic White Veterans to receive a COVID-19 test (p < 0.05). In subsequent time periods (4/7/2020–11/25/2020), testing was similar among all racial/ethnic groups.Among Veterans with COVID-19 symptoms or exposure, non-Hispanic Black and Hispanic patients were just as likely, and in some cases, more likely, to receive a COVID-19 test versus non-Hispanic White patients. The United States faced testing shortages at the start of the third wave of the pandemic; additional shortages are likely to emerge as the pandemic continues to peak and ebb. It is important to ensure that racial/ethnic minorities and others at greater risk for infection continue to have access to COVID-19 testing with each of these peaks.

Jewish Mysticism: From Ancient Times through Today

Jewish Mysticism: From Ancient Times through Today

Revisiting Zuckerman's (1999) categorical imperative: An application of epistemic maps for replication

AbstractResearch SummaryWe revisit Zuckerman's (1999) “The Categorical Imperative: Securities Analysts and the Illegitimacy Discount,” which theorizes that when organizations are recognized as legitimate players in a category, they perform better. A replication exercise fails to reproduce two of three sets of results. Assisted by data shared by the original author, we find evidence that the inconsistency is due to a coding error in the original and differences between analyst data sets. We illustrate the use of epistemic maps and evaluate the theory's predictive power across a broad set of plausible empirical assumptions and also for a subsequent time period. The results are not robust. We conclude that these data provide little evidence to support strategic recommendations. Challenges and remedies for replication are discussed.Managerial SummaryThis paper replicates a 1999 study “The Categorical Imperative: Securities Analysts and the Illegitimacy Discount” (Zuckerman, 1999). A key implication of the 1999 study is that firms should actively seek to be covered by analysts who specialize in their industries, and that a failure to be covered by analysts who are industry specialists will lead to lower capital market valuations. Our replication exercise indicates that there is insufficient evidence to recommend actively managing coverage along this dimension.

Fishing specialization and the inland trade of the Chilean jack mackerel or jurel, Trachurus murphyi, in far southern Peru

Beginning by at least the Andean Middle Horizon (AD 600–1000), sites located more than 60 km inland from the Pacific coast in far southern Peru contain the remains of jack mackerel (Trachurus murphyi). The coastal region near the modern Peruvian city of Ilo was the habitat where people procured fish and transported them to sites in the Moquegua Valley. Abundant neurocranial fragments indicate that coastal occupants shipped whole fish, not processed body portions, to inland destinations. I previously interpreted the remains of jack mackerel as imported fishes indicating high status deposits, particularly at imperial administrative outposts associated with the Wari Empire. The recent identification of jack mackerel at highly provisional, agricultural sites inhabited by non-elite residents suggests that these fishes were everyday, rather than elite, fare. The analysis indicates that the pre-Hispanic inhabitants discontinued trade in marine fishes after the collapse of the politically integrated empires in the region, but people reestablished fish trade in subsequent time periods. I examine the probable capture methods and possible culinary reasons as to why the Chilean jack mackerel is common at some inland sites in far southern Peru.

Reciprocal relationship between workplace incivility and deviant silence—The moderating role of moral attentiveness

AbstractIn the present study, we examine the reciprocal relationship between employees' perceptions of workplace incivility and their deviant silence. We also explore the moderating role of moral attentiveness on the relationship between workplace incivility and deviant silence. Utilizing three‐waves of longitudinal data from 297 full‐time employees working in different industrial sectors in the United States, we find support for the reciprocal model as the best fit to the data, thus validating relationships over time between our study variables. Taken together, our results suggest that workplace incivility at T1/T2 significantly predicted deviant silence at T2/T3. The results also reveal that deviant silence at T1/T2 significantly predicted workplace incivility at T2/T3. Importantly, we found that reflective but not perceptual moral attentiveness significantly reduced the negative influence of workplace incivility on deviant silence in subsequent time periods.

Twenty years of drought\u2010mediated change in snag populations in mixed\u2010conifer and ponderosa pine forests in Northern Arizona

BackgroundSnags (standing dead trees) are important biological legacies in forest systems, providing numerous resources as well as a record of recent tree mortality. From 1997 to 2017, we monitored snag populations in drought-influenced mixed-conifer and ponderosa pine (Pinus ponderosa) forests in northern Arizona.ResultsSnag density increased significantly in both forest types. This increase was driven largely by a pulse in snag recruitment that occurred between 2002 and 2007, following an extreme drought year in 2002, with snag recruitment returning to pre-pulse levels in subsequent time periods. Some later years during the study also were warmer and/or drier than average, but these years were not as extreme as 2002 and did not trigger the same level of snag recruitment. Snag recruitment was not equal across tree species and size classes, resulting in significant changes in species composition and size-class distributions of snag populations in both forest types. Because trees were far more abundant than snags in these forests, the effect of this mortality pulse on tree populations was far smaller than its effect on snag populations. Snag loss rates increased over time during the study, even though many snags were newly recruited. This may reflect the increasing prevalence of white fir snags and/or snags in the smaller size classes, which generally decay faster than snags of other species or larger snags. Thus, although total numbers of snags increased, many of the newly recruited snags may not persist long enough to be valuable as nesting substrates for native wildlife.ConclusionsIncreases in snag abundance appeared to be due to a short-term tree mortality “event” rather than a longer-term pattern of elevated tree mortality. This mortality event followed a dry and extremely warm year (2002) embedded within a longer-term megadrought. Climate models suggest that years like 2002 may occur with increasing frequency in the southwestern U.S. Such years may result in additional mortality pulses, which in turn may strongly affect trajectories in abundance, structure, and composition of snag populations. Relative effects on tree populations likely will be smaller, but, over time, also could be significant.