Untreated Units Research Articles

Restoration treatments enhance tree growth and alter climatic constraints during extreme drought.

The frequency and severity of drought events are predicted to increase due to anthropogenic climate change, with cascading effects across forested ecosystems. Management activities such as forest thinning and prescribed burning, which are often intended to mitigate fire hazard and restore ecosystem processes, may also help promote tree resistance to drought. However, it is unclear whether these treatments remain effective during the most severe drought conditions or whether their impacts differ across environmental gradients. We used tree-ring data from a system of replicated, long-term (>20 years) experiments in the southwestern United States to evaluate the effects of forest restoration treatments (i.e., evidence-based thinning and burning) on annual growth rates (i.e., basal area increment; BAI) of ponderosa pine (Pinus ponderosa), a broadly distributed and heavily managed species in western North America. The study sites were established at the onset of the most extreme drought event in at least 1200 years and span much of the climatic niche of Rocky Mountain ponderosa pine. Across sites, tree-level BAI increased due to treatment, where trees in treated units grew 133.1% faster than trees in paired, untreated units. Likewise, trees in treated units grew an average of 85.6% faster than their pre-treatment baseline levels (1985 to ca. 2000), despite warm, dry conditions in the post-treatment period (ca. 2000-2018). Variation in the local competitive environment promoted variation in BAI, and larger trees were the fastest-growing individuals, irrespective of treatment. Tree thinning and prescribed fire altered the climatic constraints on growth, decreasing the effects of belowground moisture availability and increasing the effects of atmospheric evaporative demand over multi-year timescales. Our results illustrate that restoration treatments can enhance tree-level growth across sites spanning ponderosa pine's climatic niche, even during recent, extreme drought events. However, shifting climatic constraints, combined with predicted increases in evaporative demand in the southwestern United States, suggest that the beneficial effects of such treatments on tree growth may wane over the upcoming decades.

Effectiveness of pre-fire forest management on post-fire forest conditions in southeastern Arizona

BackgroundWestern forests in the United States are facing multiple threats that have the potential to permanently alter forest composition and structure. In particular, wildfire can either have beneficial or adverse effects on overall forest health and resilience. Monitoring and assessing the effectiveness of existing forest treatment plans for meeting forest management goals is becoming more critical to increase the capacity for managers to prepare for and accommodate uncertainty associated with changing disturbance regimes. We used a combination of fine-scale vegetation and microclimate surveys on 57 plots, active remotely sensed data (light detection and ranging: LiDAR), and high-resolution satellite imagery to evaluate the effectiveness of an existing management strategy to increase disturbance resistance and resilience of an isolated mixed-conifer forest following a recent large-scale wildfire in southeastern Arizona, USA. We specifically assessed the effectiveness of forest overstory live tree thinning treatments (silviculture) as well as understory fuel reduction treatments (fuel) for influencing post-fire abiotic and biotic conditions, reducing direct post-fire tree mortality, and increasing resilience as compared to untreated forest stands.ResultsWe found that forest silviculture and fuel reduction treatments implemented prior to a large wildfire had mixed results on post-fire fine-scale vegetation composition and structure, microclimate conditions, tree mortality, and tree resilience. Fine-scale vegetation characteristics within silviculture- and fuel-treated forest units displayed higher herbaceous diversity and decreased density of new tree snags as compared to untreated units post-fire. Relevant to seedling emergence, we found that variance in spring soil moisture content was lower overall in treated units; however, units that received overstory thinning (silviculture) treatments were also associated with higher average summer high soil temperatures as compared to untreated units. Additionally, direct tree mortality and rate of recovery of trees post-fire differed between two treatment types (silviculture and fuel reduction) when compared to untreated units and among contrasting levels of burn severity. Post-fire tree mortality and tree resilience did not differ between control and silviculture units; however, these characteristics did differ between control and fuel units. Unlike control units, probability of tree mortality changed little between burn severity categories in fuel treatments (53.4% of mortality occurring in unburned/low vs. 46.7% in moderate/high severity) and resilience increased an average of 2.04% for trees from unburned/low to moderate/high-severity burn categories.ConclusionsOur methodology could be applied to any forested system experiencing increasing intensity and frequency of wildfire. Our results indicate that post-fire forest conditions and resilience are influenced by forest management strategies, particularly fuel reduction treatments. To accommodate uncertainty associated with changing disturbance regimes and climate change, implementing post-fire and post-treatment assessments and monitoring as presented in this study will be essential for developing attainable goals and for maintaining desired forest conditions.

Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets: a synthetic-control approach

Abstract In cities, the creation of public transport infrastructure such as light rails can cause changes on a very detailed spatial scale, with different stories unfolding next to each other within the same urban neighbourhood. We study the direct effect of a light rail line built in Florence (Italy) on the retail density of the street where it was built and its spillover effect on other streets in the treated street’s neighbourhood. To this aim, we investigate the use of the synthetic control group (SCG) methods in panel comparative case studies where interference between the treated and the untreated units is plausible, an issue still little researched in the SCG methodological literature. We frame our discussion in the potential outcomes approach. Under a partial interference assumption, we formally define relevant direct and spillover causal effects.

Local Gaussian Process Extrapolation for BART Models with Applications to Causal Inference

Bayesian additive regression trees (BART) is a semi-parametric regression model offering state-of-the-art performance on out-of-sample prediction. Despite this success, standard implementations of BART typically suffer from inaccurate prediction and overly narrow prediction intervals at points outside the range of the training data. This article proposes a novel extrapolation strategy that grafts Gaussian processes to the leaf nodes in BART for predicting points outside the range of the observed data. The new method is compared to standard BART implementations and recent frequentist resampling-based methods for predictive inference. We apply the new approach to a challenging problem from causal inference, wherein for some regions of predictor space, only treated or untreated units are observed (but not both). In simulation studies, the new approach boasts superior performance compared to popular alternatives, such as Jackknife+. Supplementary materials for this article are available online.

A non-parametric assessment of the effects of the Euro on GVC trade

This work makes a fresh contribution to the long-standing debate on the trade effects of the euro. Its novelty lies in the joint use of trade in value added and non-parametric techniques. Specifically: i) we measure bilateral trade in value added to proxy backward and forward global value chain (GVC) linkages within the eurozone; ii) we compare these outcomes for treated and untreated units by disentangling long-term and short-term effects of the euro, taking advantage of panel data and combining matching and difference-in-difference approaches. Results show no robust evidence of a positive post-assessment of the euro effect on intra-eurozone GVC trade. These findings are robust to a set of sensitivity tests such as looking both at the intensity and composition of trade in value added flows and extending the sample to various control groups and datasets. We believe that our findings contribute to the long-standing debate on the euro by complementing the previous empirical evidence and providing an overall coherent and informative picture for policymaking.

Synthetic Control with Time Varying Coefficients A State Space Approach with Bayesian Shrinkage

Synthetic control methods are a popular tool for measuring the effects of policy interventions on a single treated unit. In practice, researchers create a counterfactual using a linear combination of untreated units that closely mimic the treated unit. Oftentimes, creating a synthetic control is not possible due to untreated units’ dynamic characteristics such as integrated processes or a time varying relationship. These are cases in which viewing the counterfactual estimation problem as a cross-sectional one fails. In this article, I investigate a new approach to estimate the synthetic control counterfactual incorporating time varying parameters to handle such situations. This is done using a state space framework and Bayesian shrinkage. The dynamics allow for a closer pretreatment fit leading to a more accurate counterfactual estimate. Monte Carlo simulations are performed showcasing the usefulness of the proposed model in a synthetic control setting. I then compare the proposed model to existing approaches in a classic synthetic control case study.

Mine closures and local diversification: Job diversity for coal-mining areas in a post-coal economy

This paper tries to shed light in the research that relates mining activities and regional diversification by studying how a group of local economies heavily specialized in mining diversified its economy after the ending of public subsidies that supported coal extraction. The case of study are the mining municipalities located in the center of Asturias (an autonomous region in Northern Spain), which constituted one the most important coal basins in the country. Although the extraction of coal was one of the main driving forces of the economic activity of the region, the mine pits were located in just a few municipalities across the territory. The economy of this area experienced the most severe effects produced by this policy, which started to be implemented in the early nineties and that gradually led to the cease of coal extraction in 2018. According to recent literature (see Fitjar and Timmermans, 2019), this shift in the public mining policy should have produced a greater diversification in the local economies previously specialized in mining activities, but a proper measurement of this effect can be problematic. Traditional methods, as difference-in-differences, are precluded due to the small number of spatial units directly affected by the treatment. This paper applies the estimation strategy proposed in Abadie and Gardeazabal (2003) of the Synthetic Control Method (SCM) to overcome this problem. The application of the SCM generates a weighted average of the untreated units (non-mining municipalities) that closely matches the treated unit over the pre-treatment period. Outcomes for this synthetic control are then projected into the post-treatment period using the weights identified from the pre-treatment comparison. This projection is used as the counterfactual for the treated unit. This methodology will be exploited together with rich historical data on local employment classified by industry, available for all the municipalities of the region for the period 1978-2018. The level of diversification on each area is quantified by calculating a Herfindahl-Hirschman Index (HHI), being this indicator the variable of interest. Taking the initial years of the 1990 decade as the break-point (when the policies of public support to coal extraction started to end), the application of this technique shows how this sped-up the diversification of the mining area, producing significant differences on the HHI with the counterfactual synthetic unit and indicating that the level of concentration of the economic activity is significantly lower than it would be if the mining activity had prolonged over time.

Assessment of dengue virus inactivation in random donor platelets using amotosalen and ultraviolet A illumination.

OBJECTIVES:The study objective was evaluation of amotosalen and ultraviolet A (UVA) illumination-based inactivation of dengue virus (DENV) in blood platelets.MATERIALS AND METHODS:Whole blood was collected from healthy donors and platelet concentrates were prepared at a tertiary care hospital in Gurugram, India. Platelet units collected from five blood group matched individuals were pooled and spiked with DENV. The spiked platelet units were subjected to amotosalen treatment followed by UVA illumination, to evaluate the efficiency of this method for viral inactivation. The treated platelet units were evaluated for the presence of infectious DENV. Amotosalen levels were quantified in the treated samples using high-performance liquid chromatography.RESULTS:The presence of replicating DENV was not observed in spiked platelet units treated with amotosalen and UVA illumination, whereas untreated units contained actively replicating DENV. Amotosalen levels were found to be in the permissible range after photochemical inactivation.CONCLUSIONS:Amotosalen/UVA pathogen inactivation treatment showed efficient inactivation of DENV in platelet components. Therefore, it seems to be a promising method for mitigating the risk of dengue transmission through transfusion of potentially contaminated platelet components in dengue-endemic countries such as India.

Prescribed fire limits wildfire severity without altering ecological importance for birds

BackgroundFire suppression and anthropogenic land use have increased severity of wildfire in western U.S. dry conifer forests. Managers use fuels reduction methods (e.g., prescribed fire) to limit high-severity wildfire and restore ecological function to these fire-adapted forests. Many avian species that evolved in these forests, however, are adapted to conditions created by high-severity wildfire. To fully understand the ecological implications of fuels reduction treatments, we need to understand direct treatment effects and how treatments modulate subsequent wildfire effects on natural communities. We studied bird population and community patterns over nine years at six study units, including unburned (2002–2003), after prescribed fire (2004–2007), and after wildfire (2008–2010). We used a before-after, control-impact (BACI) approach to analyze shifts in species occupancy and richness in treated units following prescribed fire and again in relation to burn severity following wildfire.ResultsWe found examples of both positive and negative effects of wildfire and prescribed fire on bird species occupancy depending on and largely consistent with their life history traits; several woodpecker species, secondary cavity-nesting species, aerial insectivores, and understory species exhibited positive effects, whereas open cup canopy-nesting species and foliage- or bark-gleaning insectivores exhibited negative effects. Wildfire affected more species more consistently through time than did prescribed fire. Wildfire burned units initially treated with prescribed fire less severely than untreated units, but the slopes of wildfire effects on species occupancy were similar regardless of prior prescribed fire treatment.ConclusionsOur results suggest managers can employ prescribed fire to reduce wildfire severity without necessarily altering the ecological importance of wildfire to birds (i.e., the identity of species exhibiting negative versus positive responses). Additional study of the ecological implications of various fuels reduction practices, representing a range of intensities and fire regimes, would further inform forest management that includes biodiversity objectives.

A Penalized Synthetic Control Estimator for Disaggregated Data

Synthetic control methods are commonly applied in empirical research to estimate the effects of treatments or interventions on aggregate outcomes. A synthetic control estimator compares the outcome of a treated unit to the outcome of a weighted average of untreated units that best resembles the characteristics of the treated unit before the intervention. When disaggregated data are available, constructing separate synthetic controls for each treated unit may help avoid interpolation biases. However, the problem of finding a synthetic control that best reproduces the characteristics of a treated unit may not have a unique solution. Multiplicity of solutions is a particularly daunting challenge when the data includes many treated and untreated units. To address this challenge, we propose a synthetic control estimator that penalizes the pairwise discrepancies between the characteristics of the treated units and the characteristics of the units that contribute to their synthetic controls. The penalization parameter trades off pairwise matching discrepancies with respect to the characteristics of each unit in the synthetic control against matching discrepancies with respect to the characteristics of the synthetic control unit as a whole. We study the properties of this estimator and propose data-driven choices of the penalization parameter.

Containing costs in the Italian local healthcare market.

We aim to investigate the cost containment effects of the creation in 2005 of agencies specifically responsible for all technical and administrative services within the regional healthcare system of the Tuscany region of Italy. We seek to contribute to the existing literature on the centralization and decentralization of purchases and technical services by assessing the amount of savings produced by these agencies at the intermediate level between local authorities and hospitals and the regional administration. We use the balances of all Italian local health authorities and hospital trusts combined with the synthetic control procedure to create from a donor pool of untreated units a weighted average of observations resembling the exposed units before and after the policy change in 2005. The magnitude of the effect is significant as the creation of these agencies is estimated to have reduced expenditures on auxiliary goods and contracted services by 6% in the period from 2006-2014. Moreover, we find that the cost reduction is not associated with a decrease in the provision of healthcare services and procedures to the general population or in the quality or efficiency of the regional healthcare system itself.

Evaluating natural experiments in ecology: using synthetic controls in assessments of remotely sensed land treatments.

Many important ecological phenomena occur on large spatial scales and/or are unplanned and thus do not easily fit within analytical frameworks that rely on randomization, replication, and interspersed a priori controls for statistical comparison. Analyses of such large-scale, natural experiments are common in the health and econometrics literature, where techniques have been developed to derive insight from large, noisy observational data sets. Here, we apply a technique from this literature, synthetic control, to assess landscape change with remote sensing data. The basic data requirements for synthetic control include (1) a discrete set of treated and untreated units, (2) a known date of treatment intervention, and (3) time series response data that include both pre- and post-treatment outcomes for all units. Synthetic control generates a response metric for treated units relative to a no-action alternative based on prior relationships between treated and unexposed groups. Using simulations and a case study involving a large-scale brush-clearing management event, we show how synthetic control can intuitively infer treatment effect sizes from satellite data, even in the presence of confounding noise from climate anomalies, long-term vegetation dynamics, or sensor errors. We find that accuracy depends on the number and quality of potential control units, highlighting the importance of selecting appropriate control populations. Although we consider the synthetic control approach in the context of natural experiments with remote sensing data, we expect the methodology to have wider utility in ecology, particularly for systems with large, complex, and poorly replicated experimental units.

Synthetic Control with Time Varying Coefficients: A State Space Approach with Bayesian Shrinkage

Synthetic control methods are a popular tool for measuring the effects of policy interventions on a single treated unit. In practice, researchers create a counterfactual using a linear combination of untreated units that closely mimic the treated unit. Often times, creating a synthetic control is not possible due to untreated units' dynamic characteristics such as integrated processes or a time varying relationship. These are cases in which viewing the counterfactual estimation problem as a cross sectional one fails. In this paper, I propose a new approach to estimate the synthetic control counterfactual by incorporating time varying parameters. This is done using a state space framework and Bayesian shrinkage. The dynamics allow for a closer pre-treatment fit leading to a more accurate counterfactual estimate. Monte Carlo simulations are performed to investigate the usefulness of the proposed model in a synthetic control setting. I then compare the proposed model to two existing approaches in classic synthetic control case studies. Results suggest the proposed model produces lower mean squared forecast error when dynamic relationships are present and better coverage compared to the existing model. In addition, the model performs similar to existing approaches when no dynamics are present.

Forest restoration treatments in a ponderosa pine forest enhance physiological activity and growth under climatic stress.

As the climate warms, drought will increasingly occur under elevated temperatures, placing forest ecosystems at growing risk of extensive dieback and mortality. In some cases, increases in tree density following early 20th-century fire suppression may exacerbate this risk. Treatments designed to restore historical stand structure and enhance resistance to high-severity fire might also alleviate drought stress by reducing competition, but the duration of these effects and the underlying mechanisms remain poorly understood. To elucidate these mechanisms, we evaluate tree growth, mortality, and tree-ring stable-carbon isotope responses to stand-density reduction treatments with and without prescribed fire in a ponderosa pine forest of western Montana. Moderate and heavier cutting experiments (basal area reductions of 35% and 56%, respectively) were initiated in 1992, followed by prescribed burning in a subset of the thinned units. All treatments led to a growth release that persisted to the time of resampling. The treatments had little effect on climate-growth relationships, but they markedly altered seasonal carbon isotope signals and their relationship to climate. In burned and unburned treatments, carbon isotope discrimination (Δ13 C) increased in the earlywood (EW) and decreased in the latewood (LW) relative to the control. The sensitivity of LW Δ13 C to late-summer climate also increased in all treatments, but not in the control. Such increased sensitivity indicates that the reduction in competition enabled trees to continue to fix carbon for new stem growth, even when the climate became sufficiently stressful to stop new assimilation in slower-growing trees in untreated units. These findings would have been masked had we not separated EW and LW. The importance of faster growth and enhanced carbon assimilation under late-summer climatic stress became evident in the second decade post-treatment, when mountain pine beetle activity increased locally, and tree mortality rates in the controls of both experiments increased to more than twice those in their respective treatments. These findings highlight that, when thinning is used to restore historical forest structure or increase resistance to high-severity fire, there will likely be additional benefits of enhanced growth and physiological activity under climatic stress, and the effects may persist for more than two decades.

The effect of reduced unemployment duration on the unemployment rate: a Synthetic Control Approach

This paper examines the impact of the fourth partial revision of the law of unemployment insurance (AVIG) on unemployment dynamics in Switzerland at a cantonal level. The authors apply the Synthetic Control Method (SCM), a matching method for comparative case studies. A counterfactual analysis of the cases studied is performed by combining a control group of several untreated units, which provides a better comparison to the treatment group than a single unit. The control unit is designed as a weighted average of the available cantons in the donor pool, taking into account the similarities between the chosen controls and the treated unit. Once policy changes are controlled, the results suggest a significant effect on the unemployment rate at a cantonal level: the reform had a discernible impact on lowering the unemployment rate in the Italian- and French-speaking cantons in Switzerland.

1216. A Novel Antimicrobial Surface Coating Demonstrates Persistent Reduction of both Microbial Burden and Healthcare-Associated Infections at Two High-acuity Hospitals

BackgroundHealthcare-Associated Infections (HAIs) pose substantial risks to patients and hospitals. Surface disinfection practices in hospitals have limited efficacy because surfaces are frequently and easily re-contaminated. A need for innovative technologies to address these challenges exists. One such innovation is a novel antimicrobial surface coating with potential to persistently reduce environmental bacterial load. Here, we use a multicenter, nonrandomized, controlled, pre-post study design to assess the impact of an antimicrobial surface coating on environmental bioburden and HAIs at two high acuity hospitals.MethodsAn antimicrobial surface coating was applied via electrostatic spray to patient rooms and common areas in three selected units at each hospital. Quantitative surface cultures were sent to an independent microbiology laboratory pre- and 11-weeks post-application to identify total bacterial colony-forming units (CFU). HAI outcomes from treatment and contemporaneous control units were assessed using National Healthcare Safety Network protocols for multidrug-resistant organism bloodstream infections (MDRO-BSI) and Clostridium difficile infections (CDI). We used Poisson regression models to compare HAI rates for treated and untreated units for 12-months before and after application of surface coating.ResultsBoth hospitals showed statistically significant decreases in total bacterial CFU following application of the antimicrobial surface coating (64% and 75% decreases in Hospitals A and B, respectively, P < 0.0001). Across both hospitals, there was a 36% decline in pooled HAIs (hospital-onset MDRO-BSI + CDI) following application of surface coating in treated units (IRR = 0.64, 95% CI = 0.44–0.91), and no decline in HAIs over the same period in nontreated units (IRR = 1.20, 95% CI = 0.92–1.55).ConclusionSignificant and persistent reductions in both microbial burden and associated HAIs occurred in units where surfaces were treated with antimicrobial surface coating, suggesting the potential for improved patient outcomes and reduced healthcare costs. Optimal implementation methods and long-term impact should be assessed with further study of this novel environmental control intervention.Disclosures All authors: No reported disclosures.

Inference on finite-population treatment effects under limited overlap

Summary This paper studies inference on finite-population average and local average treatment effects under limited overlap, meaning that some strata have a small proportion of treated or untreated units. We model limited overlap in an asymptotic framework, sending the propensity score to zero (or one) with the sample size. We derive the asymptotic distribution of analogue estimators of the treatment effects under two common randomization schemes: conditionally independent and stratified block randomization. Under either scheme, the limit distribution is the same and conventional standard error formulas remain asymptotically valid, but the rate of convergence is slower the faster the propensity score degenerates. The practical import of these results is two-fold. When overlap is limited, standard methods can perform poorly in smaller samples, as asymptotic approximations are inadequate owing to the slower rate of convergence. However, in larger samples, standard methods can work quite well even when the propensity score is small.

Inference on Finite Population Treatment Effects Under Limited Overlap

This paper studies inference on finite population average and local average treatment effects under limited overlap, meaning some strata have a small proportion of treated or untreated units. We model limited overlap in an asymptotic framework sending the propensity score to zero (or one) with the sample size. We derive the asymptotic distribution of analog estimators of the treatment effects under two common randomization schemes: conditionally independent and stratified block randomization. Under either scheme, the limit distribution is the same and conventional standard error formulas remain asymptotically valid, but the rate of convergence is slower the faster the propensity score degenerates. The practical import of these results is twofold. When overlap is limited, standard methods can perform poorly in smaller samples, as asymptotic approximations are inadequate due to the slower rate of convergence. However, in larger samples, standard methods can work quite well even when the propensity score is small.

Haemostatic responsiveness and release of biological response modifiers following cryopreservation of platelets treated with amotosalen and ultraviolet A light.

Due to the risk of replication of contaminating pathogens, platelets have a limited storage time of 5 days, which can be prolonged to 7 days by the use of pathogen inactivation technologies. Cryopreservation (CP) may be an alternative to permit longer storage periods and increased availability. However, the preparation of platelets can result in secretion of biological response modifiers (BRM), which can cause adverse transfusion reactions in the recipient. We investigated the impact of CP on platelet function and release of BRM in untreated (conventional) and pathogen-inactivated (PI) platelet concentrates. Twelve buffy coat-derived platelet units were treated with amotosalen and ultraviolet A light to inactivate pathogens. Twelve untreated units were used as controls. The 24 units were cryopreserved and in vitro variables were analysed before and after CP. The in vitro variables investigated included platelet surface receptors and activation markers by flow cytometry, and coagulation time by viscoelastography. A panel of BRM, including cytokines, was investigated. CP of both conventional and PI platelets resulted in a significant increase of BRM with similar increases of most of the BRM after CP of conventional and PI platelet concentrates. The increase in some of the BRM correlated significantly with shortened coagulation time, increased P-selectin expression, reduced mitochondrial transmembrane potential, and reduced capacity to respond to stimulation with ADP and collagen. Cryopreservation of both conventional and PI platelets results in secretion of BRM. The increase in some of the BRM correlated with changes in platelet function variables and suggests that BRM release is affected, in part, in a similar way by CP as are changes in platelet function variables. PI with amotosalen and ultraviolet A light in combination with CP did not affect the release of immunomodulatory factors more than CP alone did.

Forest structure and climate mediate drought-induced tree mortality in forests of the Sierra Nevada, USA.

Extreme drought stress and associated bark beetle population growth contributed to an extensive tree mortality event in California, USA, resulting in more than 129million trees dying between 2012 and 2016. Although drought is an important driver of this mortality event, past and ongoing fire suppression and the consequent densification of forests may have contributed. In some areas, land management agencies have worked to reduce stand density through mechanical treatments and prescribed fire to restore forests to less dense, more open conditions that are presumably more resilient to disturbance and changing climate. Here, we evaluate if stand structural conditions associated with treated (e.g., thinned and prescribed burned) forests in the Sierra Nevada of California conferred more resistance to the bark beetle epidemic and drought event of 2012-2016. We found that, compared to untreated units, treated units had lower stand densities, larger average tree diameters, and greater dominance of pines (Pinus), the historically dominant trees. For all tree species studied, mortality was substantially greater in climatically drier areas (i.e., lower elevations and latitudes). Both pine species studied (ponderosa pine [Pinus ponderosa] and sugar pine [Pinus lambertiana]) had greater mortality in areas where their diameters were larger, suggesting a size preference for their insect mortality agents. For ponderosa pine, the tree species experiencing greatest mortality, individual-tree mortality probability (for a given tree diameter) was significantly lower in treated stands. Ponderosa pine mortality was also positively related to density of medium- to large-sized conspecific trees, especially in areas with lower precipitation, suggesting that abundance of nearby host trees for insect mortality agents was an important determinant of pine mortality. Mortality of incense cedar (Calocedrus decurrens) and white fir (Abies concolor) was positively associated with basal area, suggesting sensitivity to competition during drought, but overall mortality was lower, likely because the most prevalent and effective mortality agents (the bark beetles Dendroctonus brevicomis and D.ponderosae) are associated specifically with pine species within our study region. Our findings suggest that forest thinning treatments are effective in reducing drought-related tree mortality in forests, and they underscore the important interaction between water and forest density in mediating bark beetle-caused mortality.